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  • 251.
    Rong, X.
    et al.
    CSCEC Green Construction Engineering Research Center, Chengdu, 610041, China.
    Long, W.
    CSCEC Green Construction Engineering Research Center, Chengdu, 610041, China.
    Jia, J.
    CSCEC Green Construction Engineering Research Center, Chengdu, 610041, China.
    Liu, L.
    CSCEC Green Construction Engineering Research Center, Chengdu, 610041, China.
    Si, P.
    CSCEC Green Construction Engineering Research Center, Chengdu, 610041, China.
    Shi, L.
    CSCEC Green Construction Engineering Research Center, Chengdu, 610041, China.
    Yan, Jinyue
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center.
    Liu, B.
    CSCEC Green Construction Engineering Research Center, Chengdu, 610041, China.
    Zhao, M.
    Guangdong New Energy Technology Development Co. Ltd., Guangdong, 511356, China.
    Experimental study on a multi-evaporator mutual defrosting system for air source heat pumps2023In: Applied Energy, ISSN 0306-2619, E-ISSN 1872-9118, Vol. 332, article id 120528Article in journal (Refereed)
    Abstract [en]

    Air source heat pumps (ASHPs) are prone to frost when heating in a low-temperature and high-humidity environment, which deteriorates the heating performance of the unit. In this study, a new multi-evaporator mutual defrosting (MEMD) system was proposed to overcome the disadvantages of traditional defrosting methods: intermittent heating and inefficient defrosting. To validate the performance of the proposed defrosting technology, comparative tests were conducted in various outdoor environmental conditions. The experimental results showed that the MEMD system could continuously heat water during the defrosting period. In five experimental conditions, the MEMD system exhibited a lower water temperature drop range (2.1–2.8 °C) than that of a traditional reverse-cycle defrosting (RCD) system (6.0–7.3 °C). Due to the effective utilization of heat production during the heating period, the effective heat power (qe) of the unit increased by 0.7–1.4 kW, and the heat loss coefficient (HLC) of frosting and defrosting increased by an average of 6 % in the five experimental conditions, effectively reducing the heating capacity loss of the unit caused by defrosting. While defrosting, the MEMD system was able to utilize the remaining evaporators to absorb heat from the air and then deliver it to the defrosting evaporator. The equivalent defrosting energy efficiency (COPd) of the MEMD system was 17.5 % greater than that of the RCD system on average. During the heating and defrosting cycle, the energy saved when defrosting could increase the cycle coefficient of performance (CCOP) of heating by 3.7 %. 

  • 252.
    Rong, Z.
    et al.
    Sun Yat-Sen University, Guangzhou, China.
    Ding, J.
    Sun Yat-Sen University, Guangzhou, China.
    Lu, J.
    Sun Yat-Sen University, Guangzhou, China.
    Wang, W.
    Sun Yat-Sen University, Guangzhou, China.
    Yan, Jinyue
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center. Royal Institute of Technology, Stockholm, Sweden.
    Experimental and theoretical investigation of an innovative composite nanofluid for solar energy photothermal conversion and storage2022In: Journal of Energy Storage, ISSN 2352-152X, E-ISSN 2352-1538, Vol. 52, article id 104800Article in journal (Refereed)
    Abstract [en]

    Molten salts play a key role in the heat transfer and thermal energy storage processes of concentrated solar power plants. A novel composite material was prepared in this work by adding micron-sized magnesium particles into Li2CO3-Na2CO3-K2CO3 molten salt, the heat transfer and thermal energy storage properties of the composites were studied experimentally. A stable composite nanofluid can be obtained, and a thermal conductivity of 0.728 W/(m·K) at 973 K with an enhancement of 31% is achieved for the Mg/molten carbonate nanofluid. And the strengthening mechanism of thermal conductivity was revealed by using ab-initio molecular dynamics method. It is found that the main bonding interactions exist between Mg and O atoms at the surface of Mg particles. A compressed ion layer with a more compact and ordered ionic structure is formed around Mg particles, and the Brownian motions of Mg particles lead to the micro-convections of carbonate ions around them. These factors are helpful to the enhancement of thermal conduction with the improved probability and frequency of ion collisions. This work can provide a guidance for further studies and applications on metal/molten salt composites with enhanced heat transfer and thermal energy storage capacity. 

  • 253.
    Sadeghi, Mohammad
    et al.
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center.
    Arman, Ali
    Sharif Univ Branch, Vacuum Technol Res Grp, ACECR, Tehran, Iran..
    Talu, Stefan
    Tech Univ Cluj Napoca, Directorate Res Dev & Innovat Management DMCDI, Constantin Daicoviciu St 15, Cluj Napoca 400020, Cluj County, Romania..
    Korpi, Alireza Grayeli
    Nucl Sci & Technol Res Inst, Phys & Accelerators Res Sch, Tehran, Iran..
    Shakoury, Reza
    Imam Khomeini Int Univ, Fac Sci, Dept Phys, Qazvin, Iran..
    Zelati, Amir
    Birjand Univ Technol, Dept Basic Sci, Birjand, Iran..
    da Fonseca Filho, Henrique Duarte
    Univ Fed Amazonas, Dept Phys, Lab Nanomat Synth & Nanoscopy, BR-69067005 Manaus, Amazonas, Brazil..
    Influence of ion implantation on corrosion resistance of the nickel over steelIn: Materials Science and Technology, ISSN 0267-0836, E-ISSN 1743-2847Article in journal (Refereed)
    Abstract [en]

    Nitrogen ions were implanted at different energies of 15, 30, 45 and 60 keV and with the flux of 10(17) N(+)cm(-2) inside the nickel layers that have been deposited on the 304 stainless steel using the electron gun method at room temperature. XRD patterns showed different crystalline phases of nickel nitride for the implanted samples. The surface morphology was extracted by MountainsMap software's using statistical data from AFM analysis. In addition, a potentiodynamic polarisation test was performed in a 3.5% NaCl solution to study the corrosion behaviour. These studies revealed that corrosion was directly related to the deposition parameters, mainly the implantation energy, modifying the surface so that the highest corrosion resistance was obtained for the sample implanted with 60 keV.

  • 254.
    Sadeghi, Mohammad
    et al.
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center.
    Zelati, Amir
    Birjand Univ Technol, Dept Basic Sci, Birjand, Iran..
    Rezaee, Sahar
    Islamic Azad Univ, Dept Phys, Kermanshah, Iran..
    Luna, Carlos
    Univ Autonoma Nuevo Leon UANL, Nuevo Leon, Mexico..
    Matos, Robert Saraiva
    Univ Fed Sergipe, Sao Cristovao, Brazil..
    Pires, Marcelo Amanajas
    Fed Univ Ceara UFC, Ceara, Brazil..
    Ferreira, Nilson S.
    Univ Fed Sergipe, Sao Cristovao, Brazil..
    da Fonseca Filho, Henrique Duarte
    Fed Univ Amazonas UFAM, Manaus, Amazonas, Brazil..
    Ahmadpourian, Azin
    Islamic Azad Univ, Kermanshah, Iran..
    Talu, Stefan
    Tech Univ Cluj Napoca, Romania..
    Evaluating the Topological Surface Properties of Cu/Cr Thin Films Using 3D Atomic Force Microscopy Topographical Maps2022In: Coatings, ISSN 2079-6412, Vol. 12, no 9, article id 1364Article in journal (Refereed)
    Abstract [en]

    In the present work, Cu/Cr thin films were deposited on substrates of a different nature (Si, Glass, Bk7, and ITO) through a thermal evaporation deposition method. Non-contact atomic force microscopy (AFM) was used to obtain 3D AFM topographical maps of the surface for the Cu/Cr samples. Various analyses were carried out to obtain crucial parameters for the characterization of the surface features. In particular, Minkowski functionals (including the normalized Minkowski volume, the Minkowski boundary, and the Minkowski connectivity) and studies of the spatial microtexture by fractal and multifractal analyses were carried out. Different roughness parameters (including arithmetical mean height, root mean square height, skewness, kurtosis, fractal dimension, Hurst coefficient, topographical entropy, and fractal lacunarity) were quantified in these analyses for the comparison of the surface morphology of the different samples. All the samples displayed non-Gaussian randomly rough surfaces, indicating the presence of multifractal features.

  • 255.
    Sadeghian, Parastoo
    et al.
    KTH Royal Inst Technol, Dept Civil & Architectural Engn, Brinellvagen 23, SE-10044 Stockholm, Sweden..
    Rahnama, Samira
    Aalborg Univ, Dept Built Environm, Copenhagen, Denmark..
    Afshari, Alireza
    Aalborg Univ, Dept Built Environm, Copenhagen, Denmark..
    Sadrizadeh, Sasan
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center. KTH Royal Inst Technol, Dept Civil & Architectural Engn, Brinellvagen 23, SE-10044 Stockholm, Sweden..
    The role of design parameters on the performance of diffuse ceiling ventilation systems - thermal comfort analyses for indoor environmentIn: Advances in Building Energy Research, ISSN 1751-2549, E-ISSN 1756-2201Article in journal (Refereed)
    Abstract [en]

    Thermal comfort conditions profoundly affect the occupants' health and productivity. A diffuse ceiling ventilation system is an air distribution system in which the air is supplied to the occupied zone with relatively a low velocity through the perforated panels installed in the ceiling. The current study evaluated the impact of diffuse ceiling design parameters, i.e. diffuse panel configurations and heat load distributions, on the thermal comfort condition of the occupants. In this regard, the computational fluid dynamics technique was used to evaluate thermal comfort conditions in a waiting room, meeting room and office. The central and dispersal configuration of active diffuse panels was considered. The PMV-PPD model was applied to evaluate the overall occupants' comfort, while the draft rate was considered to assess local thermal comfort. The model validation was performed by comparing the collected laboratory measurement data. Overall, the results indicated that the central active diffuse panel configuration had a better thermal comfort than the dispersed one. The evaluation of dispersed configuration in realist scenarios, including office and waiting room, had the highest dissatisfaction, with a PPD value of 9%. Local thermal comfort assessment revealed that dispersed configuration had the highest draft rate of 14% in the office.

  • 256.
    Sadrizadeh, Sasan
    et al.
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center. Department of Civil and Architectural Engineering, KTH Royal Institute of Technology, Stockholm, Sweden.
    Yao, R.
    Joint International Research Laboratory of Green Buildings and Built Environments, School of the Civil Engineering, Chongqing University, China.
    Yuan, F.
    Awbi, H.
    Joint International Research Laboratory of Green Buildings and Built Environments, School of the Civil Engineering, Chongqing University, China.
    Bahnfleth, W.
    Department of Architectural Engineering, The Pennsylvania State University, University Park, PA, United States.
    Bi, Y.
    Department of Energy and Process Engineering, Norwegian University of Science and Technology, Norway.
    Cao, G.
    Department of Energy and Process Engineering, Norwegian University of Science and Technology, Norway.
    Croitoru, C.
    Technical University of Civil Engineering Bucharest, CAMBI Research Centre, Romania.
    de Dear, R.
    School of Architecture, Design, and Planning, The University of Sydney, NSW, Australia.
    Haghighat, F.
    Department of Building, Civil and Environmental Engineering, Concordia University, Montreal, Canada.
    Kumar, P.
    Department of Civil and Environmental Engineering, University of Surrey, United Kingdom.
    Malayeri, M.
    Department of Building, Civil and Environmental Engineering, Concordia University, Montreal, Canada.
    Nasiri, F.
    Department of Building, Civil and Environmental Engineering, Concordia University, Montreal, Canada.
    Ruud, M.
    Department of Energy and Process Engineering, Norwegian University of Science and Technology, Norway.
    Sadeghian, Parastoo
    Department of Civil and Architectural Engineering, KTH Royal Institute of Technology, Stockholm, Sweden.
    Wargocki, P.
    Department of Civil Engineering, Technical University of Denmark, Kongens Lyngby, Denmark.
    Xiong, J.
    School of Architecture, Design, and Planning, The University of Sydney, NSW, Australia.
    Yu, W.
    Joint International Research Laboratory of Green Buildings and Built Environments, School of the Civil Engineering, Chongqing University, China.
    Li, B.
    Joint International Research Laboratory of Green Buildings and Built Environments, School of the Civil Engineering, Chongqing University, China.
    Indoor air quality and health in schools: A critical review for developing the roadmap for the future school environment2022In: Journal of Building Engineering, E-ISSN 2352-7102, Vol. 57, article id 104908Article in journal (Refereed)
    Abstract [en]

    Several research studies have ranked indoor pollution among the top environmental risks to public health in recent years. Good indoor air quality is an essential component of a healthy indoor environment and significantly affects human health and well-being. Poor air quality in such environments may cause respiratory disease for millions of pupils around the globe and, in the current pandemic-dominated era, require ever more urgent actions to tackle the burden of its impacts. The poor indoor quality in such environments could result from poor management, operation, maintenance, and cleaning. Pupils are a different segment of the population from adults in many ways, and they are more exposed to the poor indoor environment: They breathe in more air per unit weight and are more sensitive to heat/cold and moisture. Thus, their vulnerability is higher than adults, and poor conditions may affect proper development. However, a healthy learning environment can reduce the absence rate, improves test scores, and enhances pupil/teacher learning/teaching productivity. In this article, we analyzed recent literature on indoor air quality and health in schools, with the primary focus on ventilation, thermal comfort, productivity, and exposure risk. This study conducts a comprehensive review to summarizes the existing knowledge to highlight the latest research and solutions and proposes a roadmap for the future school environment. In conclusion, we summarize the critical limitations of the existing studies, reveal insights for future research directions, and propose a roadmap for further improvements in school air quality. More parameters and specific data should be obtained from in-site measurements to get a more in-depth understanding at contaminant characteristics. Meanwhile, site-specific strategies for different school locations, such as proximity to transportation routes and industrial areas, should be developed to suit the characteristics of schools in different regions. The socio-economic consequences of health and performance effects on children in classrooms should be considered. There is a great need for more comprehensive studies with larger sample sizes to study on environmental health exposure, student performance, and indoor satisfaction. More complex mitigation measures should be evaluated by considering energy efficiency, IAQ and health effects.

  • 257.
    Sahoo, Smruti
    et al.
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center.
    Kavvalos, Mavroudis
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center.
    Diamantidou, Eirini
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center.
    Kyprianidis, Konstantinos
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center.
    System-level assessment of a partially distributed hybrid electric propulsion system2022In: Proceedings of the ASME Turbo Expo, American Society of Mechanical Engineers (ASME) , 2022, Vol. 1, article id V001T01A018Conference paper (Refereed)
    Abstract [en]

    Hybrid electric propulsion system based aircraft designs are paving the path towards a future greener aviation sector and thus, have been the major focus of the aeronautical community. The fuel efficiency improvements of such propulsion system configurations are realized at the aircraft level. In order to assess such benefits, a radical shift in the sub-system modeling requirements and an integrated conceptual aircraft design environment is necessary. This work highlights performance model development work pertaining to different hybrid electric propulsion system components and development of a design platform which facilitates tighter integration of different novel propulsion system disciplines at aircraft level. Furthermore, a serial/parallel partially distributed hybrid electric propulsion system is chosen as the candidate configuration to assess the potential benefits and associated trade-offs by conducting multidisciplinary design space exploration studies. It is established that the distributed hybrid electric configurations pose the potential for aircraft structural weight reduction benefits. The study further illustrates the impacts from onboard charging during the low thrust requirement segments, quantitatively. It is highlighted that the amount of off-take power extraction for onboard charging of the battery is limited due to engine operability and higher specific fuel consumption issues. Though provisioning of onboard charging lowers the potential for block fuel savings, improvement in battery specific energy can make it more promising, which is also dependent on the hybridization power level. It is established that distributed propulsion system configurations particularly benefit from a high aspect ratio wing structure, which manifests for high hybridization power levels. A high voltage level transmission system with more efficient electrical components, enhances opportunities for achieving block fuel saving benefits.

  • 258.
    Sahoo, Smruti
    et al.
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center.
    Kavvalos, Mavroudis
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center.
    Diamantidou, Eirini
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center.
    Kyprianidis, Konstantinos
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center.
    System-Level Assessment of a Partially Distributed Hybrid Electric Propulsion System2023In: Journal of engineering for gas turbines and power, ISSN 0742-4795, E-ISSN 1528-8919, Vol. 145, no 2, article id 021030Article in journal (Refereed)
    Abstract [en]

    Hybrid electric propulsion system-based aircraft designs are paving the path toward a future greener aviation sector and thus, have been the major focus of the aeronautical community. The fuel efficiency improvement associated to such propulsion system configurations are realized at the aircraft level. In order to assess such benefits, a radical shift in the subsystem modeling requirements and of a conceptual-level aircraft design environment are necessary. This work highlights performance model development work pertaining to different hybrid electric propulsion system components and the development of a design platform that facilitates tighter integration of different novel propulsion system disciplines at the aircraft level. Furthermore, a serial/parallel partially distributed hybrid electric propulsion system is chosen as the candidate configuration to assess the potential benefits and associated tradeoffs by conducting multidisciplinary design space exploration studies. It is established that the distributed hybrid electric configurations pose the potential for aircraft structural weight reduction benefits. The study further illustrates the impacts of onboard charging during the low thrust requirement segments, quantitatively. The provision of onboard charging lowers the potential for block fuel savings, and improvement in battery specific energy can make it more promising, which is also dependent on the hybridization power level. It is established that distributed propulsion system configurations particularly benefit from a high aspect ratio wing structure, which manifests in high hybridization power levels. A high voltage level transmission system with more efficient electrical components enhances opportunities for achieving block fuel saving benefits.

  • 259.
    Saif-ul-Allah, M. W.
    et al.
    Process and Energy Systems Engineering Center-PRESTIGE, Department of Chemical Engineering, COMSATS University Islamabad, Lahore Campus, Lahore, Pakistan.
    Qyyum, M. A.
    Department of Petroleum and Chemical Engineering, Sultan Qaboos University, Muscat, Oman.
    Ul-Haq, N.
    Department of Chemical Engineering, COMSATS University Islamabad, Lahore Campus, Lahore, Pakistan.
    Salman, Chaudhary Awais
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center.
    Ahmed, F.
    Process and Energy Systems Engineering Center-PRESTIGE, Department of Chemical Engineering, COMSATS University Islamabad, Lahore Campus, Lahore, Pakistan.
    Gated Recurrent Unit Coupled with Projection to Model Plane Imputation for the PM2.5 Prediction for Guangzhou City, China2022In: Frontiers in Environmental Science, E-ISSN 2296-665X, Vol. 9, article id 816616Article in journal (Refereed)
    Abstract [en]

    Air pollution is generating serious health issues as well as threats to our natural ecosystem. Accurate prediction of PM2.5 can help taking preventive measures for reducing air pollution. The periodic pattern of PM2.5 can be modeled with recurrent neural networks to predict air quality. To the best of the author’s knowledge, very limited work has been conducted on the coupling of missing value imputation methods with gated recurrent unit (GRU) for the prediction of PM2.5 concentration of Guangzhou City, China. This paper proposes the combination of project to model plane (PMP) with GRU for the superior prediction performance of PM2.5 concentration of Guangzhou City, China. Initially, outperforming the missing value imputation method PMP is proposed for air quality data under consideration by making a comparison study on various methods such as KDR, TSR, IA, NIPALS, DA, and PMP. Secondly, it presents GRU in combination with PMP to show its superiority on other machine learning techniques such as LSSVM and two other RNN variants, LSTM and Bi-LSTM. For this study, data for Guangzhou City were collected from China’s governmental air quality website. Data contained daily values of PM2.5, PM10, O3, SOx, NOx, and CO. This study has employed RMSE, MAPE, and MEDAE as model prediction performance criteria. Comparison of prediction performance criteria on the test data showed GRU in combination with PMP has outperformed the LSSVM and other RNN variants LSTM and Bi-LSTM for Guangzhou City, China. In comparison with prediction performance of LSSVM, GRU improved the prediction performance on test data by 40.9% RMSE, 48.5% MAPE, and 50.4% MEDAE. 

  • 260.
    Saif-Ul-Allah, Muhammad Waqas
    et al.
    COMSATS Univ Islamabad, Proc & Energy Syst Engn Ctr, Dept Chem Engn, PRESTIGE, Lahore, Pakistan..
    Khan, Javed
    COMSATS Univ Islamabad, Proc & Energy Syst Engn Ctr, Dept Chem Engn, PRESTIGE, Lahore, Pakistan..
    Ahmed, Faisal
    COMSATS Univ Islamabad, Proc & Energy Syst Engn Ctr, Dept Chem Engn, PRESTIGE, Lahore, Pakistan..
    Salman, Chaudhary Awais
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center.
    Gillani, Zeeshan
    COMSATS Univ Islamabad, Dept Comp Sci, Lahore, Pakistan..
    Hussain, Arif
    COMSATS Univ Islamabad, Proc & Energy Syst Engn Ctr, Dept Chem Engn, PRESTIGE, Lahore, Pakistan..
    Yasin, Muhammad
    COMSATS Univ Islamabad, Dept Chem Engn, Lahore, Pakistan..
    Ul-Haq, Noaman
    COMSATS Univ Islamabad, Dept Chem Engn, Lahore, Pakistan..
    Khan, Asad Ullah
    COMSATS Univ Islamabad, Dept Chem Engn, Lahore, Pakistan.;Natl Univ Sci & Technol, Dept Chem Engn, SCME, Islamabad, Pakistan..
    Bazmi, Aqeel Ahmed
    COMSATS Univ Islamabad, Proc & Energy Syst Engn Ctr, Dept Chem Engn, PRESTIGE, Lahore, Pakistan..
    Ahmad, Zubair
    Yeungnam Univ, Sch Chem Engn, Gyongsan, South Korea..
    Hasan, Mudassir
    King Khalid Univ, Coll Engn, Dept Chem Engn, Abha, Saudi Arabia..
    Computationally Inexpensive 1D-CNN for the Prediction of Noisy Data of NOx Emissions From 500 MW Coal-Fired Power Plant2022In: Frontiers in Energy Research, E-ISSN 2296-598X, Vol. 10, article id 945769Article in journal (Refereed)
    Abstract [en]

    Coal-fired power plants have been used to meet the energy requirements in countries where coal reserves are abundant and are the key source of NOx emissions. Owing to the serious environmental and health concerns associated with NOx emissions, much work has been carried out to reduce NOx emissions. Sophisticated artificial intelligence (AI) techniques have been employed during the past few decades, such as least-squares support vector machine (LSSVM), artificial neural networks (ANN), long short-term memory (LSTM), and gated recurrent unit (GRU), to develop the NOx prediction model. Several studies have investigated deep neural networks (DNN) models for accurate NOx emission prediction. However, there is a need to investigate a DNN-based NOx prediction model that is accurate and computationally inexpensive. Recently, a new AI technique, convolutional neural network (CNN), has been introduced and proven superior for image class prediction accuracy. According to the best of the author's knowledge, not much work has been done on the utilization of CNN on NOx emissions from coal-fired power plants. Therefore, this study investigated the prediction performance and computational time of one-dimensional CNN (1D-CNN) on NOx emissions data from a 500 MW coal-fired power plant. The variations of hyperparameters of LSTM, GRU, and 1D-CNN were investigated, and the performance metrics such as RMSE and computational time were recorded to obtain optimal hyperparameters. The obtained optimal values of hyperparameters of LSTM, GRU, and 1D-CNN were then employed for models' development, and consequently, the models were tested on test data. The 1D-CNN NOx emission model improved the training efficiency in terms of RMSE by 70.6% and 60.1% compared to LSTM and GRU, respectively. Furthermore, the testing efficiency for 1D-CNN improved by 10.2% and 15.7% compared to LSTM and GRU, respectively. Moreover, 1D-CNN (26 s) reduced the training time by 83.8% and 50% compared to LSTM (160 s) and GRU (52 s), respectively. Results reveal that 1D-CNN is more accurate, more stable, and computationally inexpensive compared to LSTM and GRU on NOx emission data from the 500 MW power plant.

  • 261.
    Salilew, W. M.
    et al.
    Mechanical Engineering Department, Universiti Teknologi PETRONAS, Bandar Seri Iskandar 32610, Malaysia.
    Gilani, S. I.
    Mechanical Engineering Department, Universiti Teknologi PETRONAS, Bandar Seri Iskandar 32610, Malaysia.
    Alemu Lemma, Tamiru
    Mälardalen University, School of Business, Society and Engineering.
    Fentaye, Amare Desalegn
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center.
    Kyprianidis, Konstantinos
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center.
    Simultaneous Fault Diagnostics for Three-Shaft Industrial Gas Turbine2023In: Machines, E-ISSN 2075-1702, Vol. 11, no 8, article id 832Article in journal (Refereed)
    Abstract [en]

    The study focused on the development of -gas turbine full- and part-load operation diagnostics. The gas turbine performance model was developed using commercial software and validated using the engine manufacturer data. Upon the validation, fouling, erosion, and variable inlet guide vane drift were simulated to generate faulty data for the diagnostics development. Because the data from the model was noise-free, sensor noise was added to each of the diagnostic set parameters to reflect the actual scenario of the field operation. The data was normalized. In total, 13 single, and 61 double, classes, including 1 clean class, were prepared and used as input. The number of observations for single faults diagnostics were 1092, which was 84 for each class, and 20,496 for double faults diagnostics, which was 336 for each class. Twenty-eight machine learning techniques were investigated to select the one which outperformed the others, and further investigations were conducted with it. The diagnostics results show that the neural network group exhibited better diagnostic accuracy at both full- and part-load operations. The test results and its comparison with literature results demonstrated that the proposed method has a satisfactory and reliable accuracy in diagnosing the considered fault scenarios. The results are discussed, following the plots.

  • 262.
    Salilew, W. M.
    et al.
    Mechanical Engineering Department, Universiti Teknologi PETRONAS, Perak, Bandar Seri Iskandar, 32610, Malaysia.
    Gilani, S. I.
    Mechanical Engineering Department, Universiti Teknologi PETRONAS, Perak, Bandar Seri Iskandar, 32610, Malaysia.
    Lemma, T. A.
    Mechanical Engineering Department, Universiti Teknologi PETRONAS, Perak, Bandar Seri Iskandar, 32610, Malaysia.
    Fentaye, Amare Desalegn
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center.
    Kyprianidis, Konstantinos
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center.
    Synergistic Effect of Physical Faults and Variable Inlet Guide Vane Drift on Gas Turbine Engine2023In: Machines, E-ISSN 2075-1702, Vol. 11, no 8, article id 789Article in journal (Refereed)
    Abstract [en]

    This study presents a comprehensive analysis of the impact of variable inlet guide vanes and physical faults on the performance of a three-shaft gas turbine engine operating at full load. By utilizing the input data provided by the engine manufacturer, the performance models for both the design point and off-design scenarios have been developed. To ensure the accuracy of our models, validation was conducted using the manufacturer’s data. Once the models were successfully validated, various degradation conditions, such as variable inlet guide vane drift, fouling, and erosion, were simulated. Three scenarios that cause gas turbine degradation have been considered and simulated: First, how would the variable inlet guide vane drift affect the gas turbine performance? Second, how would the combined effect of fouling and variable inlet guide vane drift cause the degradation of the engine performance? Third, how would the combined effect of erosion and variable inlet guide vane drift cause the degradation of the engine performance? The results revealed that up-VIGV drift, which is combined fouling and erosion, shows a small deviation because of offsetting the isentropic efficiency drop caused by fouling and erosion. It is clearly observed that fouling affects more upstream components, whereas erosion affects more downstream components. Furthermore, the deviation of performance and output parameters due to the combined faults has been discussed.

  • 263.
    Salilew, Waleligne Molla
    et al.
    Univ Teknol PETRONAS, Dept Mech Engn, Bandar Seri Iskandar 32610, Perak, Malaysia..
    Abdul Karim, Zainal Ambri
    Univ Teknol PETRONAS, Ctr Automot Res & Elect Mobil CAREM, Seri Iskandar 32610, Perak, Malaysia..
    Lemma, Tamiru Alemu
    Univ Teknol PETRONAS, Dept Mech Engn, Bandar Seri Iskandar 32610, Perak, Malaysia..
    Fentaye, Amare Desalegn
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center.
    Kyprianidis, Konstantinos
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center.
    Predicting the Performance Deterioration of a Three-Shaft Industrial Gas Turbine2022In: Entropy, E-ISSN 1099-4300, Vol. 24, no 8, article id 1052Article in journal (Refereed)
    Abstract [en]

    The gas turbine was one of the most important technological developments of the early 20th century, and it has had a significant impact on our lives. Although some researchers have worked on predicting the performance of three-shaft gas turbines, the effects of the deteriorated components on other primary components and of the physical faults on the component measurement parameters when considering the variable inlet guide valve scheduling and secondary air system for three-shaft gas turbine engines have remained unexplored. In this paper, design point and off-design performance models for a three-shaft gas turbine were developed and validated using the GasTurb 13 commercial software. Since the input data were limited, some engineering judgment and optimization processes were applied. Later, the developed models were validated using the engine manufacturer's data. Right after the validation, using the component health parameters, the physical faults were implanted into the non-linear steady-state model to investigate the performance of the gas turbine during deterioration conditions. The effects of common faults, namely fouling and erosion in primary components of the case study engine, were simulated during full-load operation. The fault simulation results demonstrated that as the severity of the fault increases, the component performance parameters and measurement parameters deviated linearly from the clean state. Furthermore, the sensitivity of the measurement parameters to the fault location and type were discussed, and as a result they can be used to determine the location and kind of fault during the development of a diagnosis model.

  • 264.
    Salilew, Waleligne Molla
    et al.
    Mechanical Engineering Department, Seri Iskandar 32610, Universiti Teknologi PETRONAS, Malaysia.
    Abdul Karim, Zainal Ambri
    Mechanical Engineering Department, Seri Iskandar 32610, Universiti Teknologi PETRONAS, Malaysia.
    Lemma, Tamiru Alemu
    Mechanical Engineering Department, Seri Iskandar 32610, Universiti Teknologi PETRONAS, Malaysia.
    Fentaye, Amare Desalegn
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center.
    Kyprianidis, Konstantinos
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center.
    Three Shaft Industrial Gas Turbine Transient Performance Analysis2023In: Sensors, E-ISSN 1424-8220, Vol. 23, no 4Article in journal (Refereed)
    Abstract [en]

    The power demand from gas turbines in electrical grids is becoming more dynamic due to the rising demand for power generation from renewable energy sources. Therefore, including the transient data in the fault diagnostic process is important when the steady-state data are limited and if some component faults are more observable in the transient condition than in the steady-state condition. This study analyses the transient behaviour of a three-shaft industrial gas turbine engine in clean and degraded conditions with consideration of the secondary air system and variable inlet guide vane effects. Different gas path faults are simulated to demonstrate how magnified the transient measurement deviations are compared with the steady-state measurement deviations. The results show that some of the key measurement deviations are considerably higher in the transient mode than in the steady state. This confirms the importance of considering transient measurements for early fault detection and more accurate diagnostic solutions.

  • 265.
    Salilew, Waleligne Molla
    et al.
    Univ Teknol Petronas, Mech Engn Dept, Bandar Seri Iskandar 32610, Perak, Malaysia..
    Karim, Zainal Ambri Abdul
    Univ Teknol Petronas, Ctr Automot Res & Elect Mobil CAREM, Bandar Seri Iskandar 32610, Perak, Malaysia..
    Lemma, Tamiru Alemu
    Univ Teknol Petronas, Mech Engn Dept, Bandar Seri Iskandar 32610, Perak, Malaysia..
    Fentaye, Amare Desalegn
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center.
    Kyprianidis, Konstantinos
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center.
    The Effect of Physical Faults on a Three-Shaft Gas Turbine Performance at Full- and Part-Load Operation2022In: Sensors, E-ISSN 1424-8220, Vol. 22, no 19, article id 7150Article in journal (Refereed)
    Abstract [en]

    A gas path analysis approach of dynamic modelling was used to examine the gas turbine performance. This study presents an investigation of the effect of physical faults on the performance of a three-shaft gas turbine at full-load and part-load operation. A nonlinear steady state performance model was developed and validated. The datasheet from the engine manufacturer was used to gather the input and validation data. Some engineering judgement and optimization were used. Following validation of the engine performance model with the engine manufacturer data using physical fault and component health parameter relationships, physical faults were implanted into the performance model to evaluate the performance characteristics of the gas turbine at degradation state at full- and part-load operation. The impact of erosion and fouling on the gas turbine output parameters, component measurement parameters, and the impact of degraded components on another primary component of the engine have been investigated. The simulation results show that the deviation in the output parameters and component isentropic efficiency due to compressor fouling and erosion is linear with the load variation, but it is almost nonlinear for the downstream components. The results are discussed following the plots.

  • 266.
    Scheiff, Valentin
    et al.
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center.
    Aslanidou, Ioanna
    Mälardalen University, School of Innovation, Design and Engineering, Innovation and Product Realisation.
    Kyprianidis, Konstantinos
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center.
    Bel Fdhila, Rebei
    Hitachi Energy Research, Västerås, Sweden.
    Experimental Study Of Nucleate Boiling Dynamics In A Rectangular Mini-Channel Set-Up2023In: 8th Thermal and Fluids Engineering Conference (TFEC); March, 2023 Partially Online Virtual and at University of Maryland, MD Conference, Begell House, 2023, p. 1199-1208Conference paper (Refereed)
    Abstract [en]

    Nowadays thermal management becomes a challenge as it implies high power density with high lossesconverted to large heat release. For low power levels, natural or forced single-phase convection could besufficient. For a much higher heat release nucleate boiling can be the alternative solution since it can dissipate the heat more efficiently, thanks to the latent heat effect present during the phase change. Its performance depends on many parameters that enable potential control and make system integration often very complex. The transition towards nucleate boiling, called Onset of Nucleate Boiling requires better estimation, and the mechanism still lacks understanding, especially in mini-channels. This study aims to characterize nucleate boiling in a rectangular mini-channel experimental set-up, built at Mälardalenuniversity, to better characterize the onset of nucleate boiling and the fully developed bubbly flow. The experiment allows full control of single-phase and two-phase regimes by varying the thermo-hydraulic and heat transfer conditions. With the use of a high-speed camera, bubble dynamics and their principal characteristics such as size, shape, propagation, and nucleation site location are determined with a digital image analysis technique developed within this work. The image processing has proved to be successful even on noisy images due to shadows or background changes. The reconstruction of segmented bubbles enabled flexible and automated bubble and path detection with a statistical approach, especially at the Onset of Nucleate Boiling. Local Reynolds numbers are then estimated to determine the drag coefficient in the flow during bubble growth, or their coalescence.

  • 267.
    Sedaghat, M. H.
    et al.
    Department of Mechanical Engineering, Technical and Vocational University (TVU), Tehran, Iran.
    Sadrizadeh, Sasan
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center. Department of Civil and Architectural Engineering, KTH Royal Institute of Technology, Stockholm, Sweden.
    Abouali, O.
    Department of Civil and Architectural Engineering, KTH Royal Institute of Technology, Stockholm, Sweden.
    Three-dimensional simulation of mucociliary clearance under the ciliary abnormalities2023In: Journal of Non-Newtonian Fluid Mechanics, ISSN 0377-0257, E-ISSN 1873-2631, Vol. 316, article id 105029Article in journal (Refereed)
    Abstract [en]

    In this study three-dimensional computational model of a segment of bronchial airway surface liquid has been investigated to study the effect of various cilia abnormalities on mucociliary clearance (MCC), which was reported in common respiratory diseases. Numerical simulations have been devoted to studying a two-layer fluid model of the airway surface liquid (ASL) consisting of a Newtonian lower periciliary liquid (PCL) layer and a nonlinear viscoelastic upper mucus layer. The time-dependent governing and constitutive equations have been discretized and solved by a finite difference projection method on a staggered grid. The immersed boundary method has also been employed to study the effect of cilia propulsive effect on ASL. Numerical results have been devoted to investigating the influence of various cilia abnormalities, such as phase difference between cilia, cilia beat pattern, cilia beat frequency, cilia lattice geometry, missing cilia regions, and cilia density on MCC. The mucus was modeled as a nonlinear viscoelastic fluid in 3D geometry. Numerical results show that some cilia abnormalities such as cilia density, cilia beat pattern, and cilia beat frequency have a dominant effect on MCC and some abnormalities such as missing cilia regions and phase differences between cilia have a moderate influence on that. Results also show the negligible impact of cilia lattice geometry on mucus flow.

  • 268.
    Shabani, Masoume
    et al.
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center.
    Dahlquist, Erik
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center.
    Wallin, Fredrik
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center.
    Yan, Jinyue
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center. School of Chemical Science & Engineering , KTH - Royal Institute of Technology, SE - 10044 Stockholm, Sweden .
    Comparison of the optimal design of PV-battery and PV-PHS off-grid energy systems-a case study in Sweden2019In: Volume 5: Innovative Solutions for Energy Transitions, Mälardalen University, 2019, Vol. 5, article id 1214Conference paper (Refereed)
    Abstract [en]

    This study deals with the investigating of the potential of employing two energy storage technologies., i.e. battery storage and pumped hydro storage (PHS), for PV powered supply system on a small island in Sweden. The optimal design of two hybrid PV-Battery and PV-PHS systems are compared and analyzed. Genetic Algorithm (NSGA-II) is employed as the optimization algorithm. Investment cost and loss of power supply probability are considered as objective functions. Number of PV modules and battery capacity are considered as design variables for PV-Battery system and a wide range of design variables including number of PV modules, turbine capacity, pump capacity, volume, installation height and depth to diameter ratio of reservoir, pipes diameters constitute for PV-PHS system. As a result, a hybrid pareto front is proposed for case study, that means, regarding objective functions, designer can decide that which of two systems are more suitable for current case study. The results show that pareto fronts of two hybrid systems intersect each other at a point. In this case, PV-PHS led to the lower pareto front for LPSPs up to about 6.94% and for LPSPs higher than 6.94%, pareto front of PV-PHS system lies above that of PVBattery system. This implies that under LPSPs range of 0- 6.94%, the PV-PHS system resulted in the lower initial cost, therefore, it is better option for the current case study. In contrast, for LPSPs higher than 6.94%, for the same LPSP, PV-Battery system led to the lower investment cost in comparison with PV-PHS, so it can be chosen as a better option regarding designer’s priorities. Also, results show that the proposed strategy can reach a design with the full satisfaction of fluctuating demand and system constraints. In this case, for the yearly average demand of 16.3 kW, the investment cost is obtained to be 2.1M$ and 1.87 M$ for the PV-battery and PV-PHS, respectively. The paper compares in detail the optimal designs and operations obtained for the two hybrid PV-Battery and PV-PHS systems.

  • 269.
    Shabani, Masoume
    et al.
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center.
    Shabani, Mohadeseh
    Wallin, Fredrik
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center.
    Dahlquist, Erik
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center.
    Yan, Jinyue
    The Hong Kong Polytechnic University.
    Smart and Optimization-Based Operation Scheduling Strategies for Maximizing Battery Profitability and Longevity in Grid-Connected ApplicationManuscript (preprint) (Other (popular science, discussion, etc.))
  • 270.
    Shabani, Masoume
    et al.
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center.
    Wallin, Fredrik
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center.
    Dahlquist, Erik
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center.
    Yan, Jinyue
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center. Department of Building Environment and Energy Engineering, Hong Kong Polytechnic University, Hong Kong.
    Smart and optimization-based operation scheduling strategies for maximizing battery profitability and longevity in grid-connected application2024In: Energy Conversion and Management: X, ISSN 2590-1745, Vol. 21, article id 100519Article in journal (Refereed)
    Abstract [en]

    Lithium-ion battery storage has emerged as a promising solution for various energy systems. However, complex degradation behavior, relatively short lifetime, high capital, and operational costs, and electricity market volatility are critical factors that challenge its practical viability. Thus, to ensure sustained profitability of Lithium-ion batteries in real-life applications, a smart and optimal management strategy considering key influencing factors is imperative for achieving efficient battery utilization. This study proposes two day-ahead battery-behavior-aware operation scheduling strategies to maximize profitability and longevity in residential grid-connected applications with dynamic electricity pricing. Each scenario employs unique approaches to make optimal decisions for optimal battery utilization. The first scenario optimizes short-term profitability by prioritizing revenue gains under three charge/discharge rates (high, moderate, low), considering daily charge and discharge timings as decision variables. Conversely, the second scenario proposes a smart strategy capable of making intelligent decisions on a wide range of variables to simultaneously maximize revenue and minimize degradation costs, ensuring short-term and long-term profitability. Decision variables include the cycle frequency for each specific day, timings as well as durations for charging and discharging per cycle. To ensure effective long-term assessment, both scenarios accurately estimate battery performance, calendric and cyclic capacity degradations, remaining-useful-lifetime, and internal states under real operational conditions until battery reaches its end-of-life criteria. The scenarios are assessed economically using various indicators. Furthermore, the impact of battery price and size on optimization outcomes are examined. The key findings indicate that, among the first set of scenarios, the strategy with low charge/discharge rate extends the battery lifetime most efficiently, estimated at 14.8 years. However, it proved to be the least profitable, resulting in negative profit of −3€/kWh/yr. On the other hand, strategies with high and moderate charge/discharge rates resulted in positive profit of 8.3 €/kWh/year and 9.2 €/kWh/year, despite having shorter battery lifetimes, estimated at 10.1 years and 13.6 years, respectively. Furthermore, from a payback perspective, the strategy with fast charge/discharge capability led to 1.5 years shorter payback period than that of the moderate rate strategy. The findings highlight that the first set of scenarios limits the strategy's flexibility in achieving both sustainability and profitability. In contrast, the second scenario achieves impressive profit (18 €/kWh/yr), shortest payback period (7.5 year), a commendable lifespan (12.5 years), contrasting revenue-focused scenarios, emphasizing the importance of striking optimal balance between revenue gain and degradation costs for charging/discharging actions, ensuring sustained profitability. The findings offer valuable insights for decision-makers, enabling informed strategic choices and effective solutions.

  • 271.
    Shabani, Masoume
    et al.
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center.
    Wallin, Fredrik
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center.
    Dahlquist, Erik
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center.
    Yan, Jinyue
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center.
    Techno-economic assessment of battery storage integrated into a grid-connected and solar-powered residential building under different battery ageing models2022In: Applied Energy, ISSN 0306-2619, E-ISSN 1872-9118, Vol. 318, article id 119166Article in journal (Refereed)
    Abstract [en]

    Battery storage in solar residential applications has the potential to improve system flexibility under high renewable energy penetration. A better understanding of the dynamic operational conditions of batteries is of high importance for the technical and economic feasibility of the associated system. This study evaluates key parameters for the proper battery management design, control, and optimization of a battery system integrated into a grid-connected, solar-powered building. Three different battery modelling scenarios are proposed in terms of battery ageing and lifetimes, internal states, and control strategies. Each proposed scenario consists of a set of specific methods for the estimation of battery voltage-current characteristics, capacity degradation, remaining lifetime, states of charge, states of health, and states of power. A criteria-based operational strategy linked to a nondominated sorting genetic algorithm (NSGA_II) is constructed for the simulation and multiobjective optimization of the system. The self-sufficiency ratio and life-cycle cost of a battery are considered the technical and economic goals, which are influenced by the capacity degradation and achievable lifetime of the battery. Moreover, the annual battery degradation cost and self-consumption ratio are calculated over the project lifetime. The comparison between the techno-economic optimization results obtained under three battery modelling scenarios indicate that a more realistic design and a superior techno-economic assessment are obtained under Model 3, which is able to simulate battery degradation considering all ageing influence parameters under real operational conditions. In comparison with Model 3, Model 1 which neglects the battery degradation, techno-economically leads an overly optimistic result and also Model 2, which was based on linear capacity degradation regardless of the observed dynamic operational conditions, leads an excessively pessimistic result, implying that applying several simplifying assumptions for a battery operation simulation in a real-life application greatly affects the resulting battery state of charge, state of power, and state of health estimations, leading to an improper battery management system and consequently to the misestimation of techno-economic objective functions. The results prove that the real design and techno-economic assessment of a battery in a solar-powered application highly depend on battery operations in which the seasonal photovoltaic (PV) power production affects the rates of calendric and cyclic battery degradation. 

  • 272.
    Shabani, Masoume
    et al.
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center.
    Wallin, Fredrik
    School of Chemical Science & Engineering, KTH-Royal Institute of Technology, Stockholm, Sweden.
    Dahlquist, Erik
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center.
    Yan, Jinyue
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center.
    Techno-economic evaluation of a battery system integrated into a residential grid-connected PV system considering battery degradation2021In: Energy Proceedings, Scanditale AB , 2021, Vol. 15Conference paper (Other academic)
    Abstract [en]

    Stationary battery storages become a promising solution for improving flexibility of renewable energy system to balance the fluctuating of power production and demand. However, each application has a specific operational strategy, consequently a specific dynamic operational profile which leads to a different estimated battery lifetime due to the degradation of battery capacity over its operation in the application. An accurate knowledge about battery lifetime, and battery state of health at different operational conditions is important to ensure a feasible techno-economic assessment. This paper deals with the techno-economic evaluation of a battery system integrated into a residential grid-connected PV system considering two battery models with and without battery degradation. The battery life cycle cost, the self-sufficiency ratio and battery lifetime are analyzed for techno-economic assessment of a residential grid-connected hybrid PV-battery system. The results show that the simulation without battery degradation gives 31.43% lower life cycle cost and 7.4% higher self-sufficiency ratio, compared to the modeling with battery degradation. This proves the importance of battery aging model for assessing a battery integrated into a renewable PV system.

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  • 273.
    Shabani, Masoume
    et al.
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center.
    Wallin, Fredrik
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center.
    Dahlquist, Erik
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center.
    Yan, Jinyue
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center. Department of Building Environment and Energy Engineering, Hong Kong Polytechnic University, Hong Kong.
    The impact of battery operating management strategies on life cycle cost assessment in real power market for a grid-connected residential battery application2023In: Energy, ISSN 0360-5442, E-ISSN 1873-6785, Vol. 270, article id 126829Article in journal (Refereed)
    Abstract [en]

    The relatively short lifetime of batteries is one of the crucial factors that affects its economic viability in current electricity markets. Thus, to make batteries a more viable technology in real power market from life cycle cost assessment perspective, full understanding of battery ageing parameters and which operating control strategies cause slower degradation rate is essential and still an open problem. This study deals with the 32 different battery operating control strategies to evaluate their importance on cyclic and calendric degradation, lifetime, and life cycle cost assessment of a battery system in a grid-connected residential application. In other words, it is evaluated that at which operating control strategy the system simulation results in a more beneficial system from techno-economic perspective. A battery modelling scenario is proposed to accurately estimate battery performance, degradation, and lifetime under real operational condition given different operating control strategies. An operational strategy, which benefits from the dynamic real-time electricity price scheme, is conducted to simulate the system operation. The key results show that selecting a proper state-of-charge control strategy positively affects the battery lifetime and consequently its net-present-value, in which the best strategy led to 30% improvement in net-present-value compared to the worst strategy.

  • 274.
    Shi, J.
    et al.
    Tianjin Key Laboratory of Refrigeration Technology, Tianjin University of Commerce, Tianjin, 300134, China.
    Li, X.
    Tianjin Key Laboratory of Refrigeration Technology, Tianjin University of Commerce, Tianjin, 300134, China.
    Wang, Y.
    Tianjin Key Laboratory of Refrigeration Technology, Tianjin University of Commerce, Tianjin, 300134, China.
    Wang, Z.
    Tianjin Key Laboratory of Refrigeration Technology, Tianjin University of Commerce, Tianjin, 300134, China.
    Liu, S.
    Tianjin Key Laboratory of Refrigeration Technology, Tianjin University of Commerce, Tianjin, 300134, China.
    Li, Hailong
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center. Tianjin Key Laboratory of Refrigeration Technology, Tianjin University of Commerce, Tianjin, 300134, China.
    Capacity Fading Characteristics of Lithium Iron Phosphate Batteries Under Different Precooling Conditions2023In: Lecture Notes in Electrical Engineering, vol. 1016, Springer Science and Business Media Deutschland GmbH , 2023, p. 1-9Conference paper (Refereed)
    Abstract [en]

    The capacity fading of lithium iron phosphate batteries is related to its internal temperature and the growth of solid electrolyte (SEI). It is an effective way by controlling its internal temperature to mitigate capacity fading. This paper discusses the impact of pre-cooling and resting time on capacity fading and the growth of SEI. Results showed that the battery capacity increased and the thickness of SEI decreased if the pre-cooling was employed. Compared to 25 °C of ambient temperature, the thickness of SEI under 5 °C of pre-cooling temperature decreased by 404 nm, 386 nm, and 502 nm for 2C, 3C, and 5C discharge rate, respectively. The internal temperature of battery could be better cooled and therefore capacity increased with the increase of resting time. At 15 °C of pre-cooling temperature, the capacity increased by 3.8% if the resting time increased from 600 s to 2400 s. Therefore, the pre-cooling method could effectively mitigate capacity fading. The conclusion obtained in this paper could provide guidance for battery thermal management. 

  • 275.
    Shi, Xiaodan
    et al.
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center. Univ Tokyo, Ctr Spatial Informat Sci, Kashiwa, Chiba 2778568, Japan..
    Zhang, Haoran
    Peking Univ, Sch Urban Planning & Design, Shenzhen 518055, Guangdong, Peoples R China..
    Yuan, Wei
    Univ Tokyo, Ctr Spatial Informat Sci, Kashiwa, Chiba 2778568, Japan..
    Shibasaki, Ryosuke
    Univ Tokyo, Ctr Spatial Informat Sci, Kashiwa, Chiba 2778568, Japan..
    MetaTraj: Meta-Learning for Cross-Scene Cross-Object Trajectory Prediction2023In: IEEE transactions on intelligent transportation systems (Print), ISSN 1524-9050, E-ISSN 1558-0016Article in journal (Refereed)
    Abstract [en]

    Long-term pedestrian trajectory prediction in crowds is highly valuable for safety driving and social robot navigation. The recent research of trajectory prediction usually focuses on solving the problems of modeling social interactions, physical constraints and multi-modality of futures without considering the generalization of prediction models to other scenes and objects, which is critical for real-world applications. In this paper, we propose a general framework that makes trajectory prediction models able to transfer well across unseen scenes and objects by quickly learning the prior information of trajectories. The trajectory sequences are closely related to the circumstance setting (e.g. exits, roads, buildings, entries etc.) and the objects (e.g. pedestrians, bicycles, vehicles etc.). We argue that those trajectory information varying across scenes and objects makes a trained prediction model not perform well over unseen target data. To address it, we introduce MetaTraj that contains carefully designed sub-tasks and meta-tasks to learn prior information of trajectories related to scenes and objects, which then contributes to accurate long-term future prediction. Both sub-tasks and meta-tasks are generated from trajectory sequences effortlessly and can be easily integrated into many prediction models. Extensive experiments over several trajectory prediction benchmarks demonstrate that MetaTraj can be applied to multiple prediction models and enables them generalize well to unseen scenes and objects.

  • 276.
    Shinde, Amar Mohan
    et al.
    Manipal Acad Higher Educ, Manipal Inst Technol, Dept Civil Engn, Manipal 576104, Karnataka, India..
    Dikshit, Anil Kumar
    Indian Inst Technol, Dept Environm Sci & Engn, Mumbai, Maharashtra, India..
    Odlare, Monica
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center.
    Thorin, Eva
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center.
    Schwede, Sebastian
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center.
    Life cycle assessment of bio-methane and biogas-based electricity production from organic waste for utilization as a vehicle fuel2021In: Clean Technologies and Environmental Policy, ISSN 1618-954X, E-ISSN 1618-9558, Vol. 23, no 6, p. 1715-1725Article in journal (Refereed)
    Abstract [en]

    The concerns about climate change, energy security and price fluctuation of fossil fuels are driving the growing interest in the development and utilization of renewable energy as a transportation fuel. In this aspect, the utilization of organic household waste for the production of biogas avoids the environmental impact of landfills. The further upgrading and utilization of biogas as a vehicle fuel avoids the environmental impact of fossil fuels. This paper presents the life cycle assessment of two utilization pathways of biogas produced from co-digestion of organic household waste, grease trap removal sludge and ley crops grown by local farmers. Specifically, this study assessed and compared the environmental impact of the production and utilization of bio-methane and biogas-based electricity as a vehicle fuel for public transport buses in Vasteras, Sweden. The system boundary for biogas production covered seven main steps: cultivation, harvesting and transport of ley crops, collection and transport of waste, pre-treatment and co-digestion of the substrate. The system boundary for bio-methane was further extended to account for the upgrading process and tailpipe emissions from combustion of bio-methane in the buses. In the case of biogas-based electricity, the system boundary was further extended to account for the combustion of biogas in the CHP unit and further utilization of electricity in the electric bus. The evaluation of the production routes showed that the methane losses and high energy consumption for both biogas production and upgrading process dominated the environmental impact of bio-methane production. However, the emissions from the CHP unit were solely responsible for the environmental impact of biogas-based electricity production. The functional unit identified for this study is 1 vehicle km travelled (VKT) of the bio-methane fuelled bus and electric bus. The global warming potential of the electric buses was 0.11 kg CO2-eq/VKT compared to 0.26 kg CO2-eq/VKT for the bio-methane buses. The electric buses could also reduce about half of the acidification and eutrophication impacts associated with the bio-methane fuelled buses. The lower fuel efficiency and high tailpipe emissions decreased the environmental advantages of the bio-methane buses. Eventually, this study ensures the biogas utilization which is environmentally sound and compares favourably with the alternative options. [GRAPHICS] .

  • 277.
    Shirazi, Peimaneh
    et al.
    Ontario Tech Univ, Dept Mech & Mfg Engn, Oshawa, ON, Canada..
    Behzadi, Amirmohammad
    KTH Royal Inst Technol, Dept Civil & Architectural Engn, Stockholm, Sweden..
    Ahmadi, Pouria
    Univ Pittsburgh Bradford, Engn Technol & Energy Programs, Div Phys & Computat Sci, Bradford, PA 16701 USA..
    Sadrizadeh, Sasan
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center. KTH Royal Inst Technol, Dept Civil & Architectural Engn, Stockholm, Sweden.
    Comparison of control strategies for efficient thermal energy storage to decarbonize residential buildings in cold climates: A focus on solar and biomass sources2024In: Renewable energy, ISSN 0960-1481, E-ISSN 1879-0682, Vol. 220, article id 119681Article in journal (Refereed)
    Abstract [en]

    This work presents novel energy production/storage/usage systems to reduce energy use and environmental effects, in order to address concerns about excessive heating demand/emissions in buildings. This focus is the design, control, and comparison of a biomass-fired model with a novel heater type and a solar-driven system integrated with photovoltaic thermal (PVT) panels and a heat pump. The heater has an external boiler and shell and tube heat exchanger, providing enhanced control over the combustion process and increased efficiency. Another feature of the present work is establishing a rule-based automation framework to manage the energy storage/flow among the components/grid/building. This smart integration reduces the size of the components, eliminates the need for a battery, and allows the system to interact in both directions with the electricity grid. The practicality of both systems is assessed and compared via a code developed in TRNSYS-MATLAB, considering the specific conditions of Toronto, Canada, characterized by high heat demand in winter. According to the results, the proposed solar-based system has an acceptable energy cost (78.9 USD per MWh of heating and electricity) attributable to the developed controllers applied to thermal energy storage. The results show that the PVT-based system integrated with a heat pump is environmentally superior, with a reduction in CO2 emission of 7.2 tonnes over a year. However, the biomass-fired system is an excellent option from the aspect of efficiency, with a relatively high energy efficiency of 69 %. Also, it is observed that the night set-back of the supply temperature can reduce the annual primary energy use and emission up to 60.3 MWh and 21.1 t, respectively. While the system relies more on the heat pump in cold months, the solar energy system supplies the entire demand in summer, demonstrating the significance of PVT and heat pump integration to increase energy reliability throughout the year.

  • 278.
    Siddachary, Ullas
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center.
    MICRO-CLIMATE CHARACTERIZATION OF COMFORT MATERIALS: A CLIMATE ANALYSIS OF HIGH RESILIENCE FOAM IN MICRO-CLIMATE CONDITIONS2022Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    Currently, it is widely recognised that the operational energy consumption of most building types currently outweighs their embodied energy by some margin. However, as we make dramatic increases in energy efficiency the embodied energy of the materials and components that we use will become proportionally larger and may account for a substantial proportion of the energy associated with buildings in the future. The main factor that might contribute to comfort/discomfort perception is the thermal equilibrium caused by the interaction between a person and the interaction of an object.This is easy to demonstrate as an assumption, mainly in situations where almost the whole body is in contact with the object. The main purpose of this work is to determine important parameters that differentiate different materials and develop new way of working with comfort materials (in particular, soft materials like High Resilience foam and High-Density foam) and characterize them based on their response to temperature and humidity. A literature study is performed to gain more knowledge about current state of foam technology and experimental methods are used to obtain analytical data.To characterize the materials, climate chamber is used to evaluate the materials to determine their properties. From the experiment, the key parameters were determined to be Temperature, Humidity, Vapour pressure and Heat Index. These parameters have a significant impact on the comfortability of the material and hence can be used to determine a soft material’s properties and their reaction to certain environments. The most important characteristics such as temperature, humidity, partial water vapour pressure show that HS materials which 400-450mm of PCR coating have much better sweat diffusion which can be attributed to chemical composition of the material and thermal capacity. The most difficult part micro-climate analysis is to accurately represent what is ‘comfortable’, as comfort is subjective but by using these methods of experiments and analysing methods, the characteristics of the materials can be determined, and a conclusion can be drawn. One of the most difficult things in microclimate testing or testing as such is the repetition of equal processes because it requires experience with the device and the complex process to gain comparable data. There are many variables that were not included in this study due to time constraints but can certainly add to the accuracy of the results. The study was conducted only on two materials over a certain period which can be extended for further accuracy.

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  • 279.
    Sielemann, M.
    et al.
    Modelon, München, Germany.
    Coïc, C.
    Modelon, München, Germany.
    Hübel, M.
    Modelon, Hamburg, Germany.
    Zhao, X.
    Chalmers University of Technology, Gothenburg, Sweden.
    Kyprianidis, Konstantinos
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center.
    Introduction to multi-point design strategies for aero engines2020In: Proceedings of the ASME Turbo Expo, American Society of Mechanical Engineers (ASME) , 2020Conference paper (Refereed)
    Abstract [en]

    Classic gas turbine design relies on the definition of a design point, and the subsequent assessment of the design on a range of off-design conditions. On the design point, both component sizing (e.g., in terms of physical dimensions or in terms of map scaling parameters) and a solution to the off-design governing equations are established. With this approach, it is however difficult to capture the contradicting requirements on the full operating envelope. Thus, practical design efforts rely on various multi-point design approaches. This paper introduces a simplified notation of such multi-point approaches via synthesis matching tables. It then summarizes two academic state-of-the-art multi-point design schemes using such tables in a comprehensible fashion. The target audience are students and engineers familiar with the basics of classic cycle design and analysis looking for a practical introduction to such multi-point design approaches. Application examples are given in terms of a simple turbojet and a typical geared turbofan as modeled in state-of-the-art academic cycle design and analysis efforts. The results of the classic design point approach are compared to those of multi-point approaches. Copyright © 2020 ASME

  • 280.
    Sielemann, Michael
    et al.
    Modelon Deutschland GmbH, Bavaria, Munich, 80992, Germany.
    Kavvalos, Mavroudis
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center.
    Selvan, Nitish
    Modelon Engineering Pvt. Ltd., Tamilnadu, Tiruchirappalli, 620017, India.
    Claesson, Jim
    Modelon AB, Skåne, Lund, 22370, Sweden.
    Kyprianidis, Konstantinos
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center.
    Select trade-offs in parallel hybrid turboprop cycle design2022In: Proceedings of the ASME Turbo Expo, American Society of Mechanical Engineers (ASME) , 2022, Vol. 1, article id V001T01A014Conference paper (Refereed)
    Abstract [en]

    Parallel hybrid turboprop engines propose a means to reduce fuel consumption of regional aircraft due to lower flight velocities. They feature an electric drive, typically on the free power turbine, and require a design trade-off between the gas turbine and electric power sub-system characteristics. Degrees of freedom include the nozzle expansion, the propeller power loading, the gear ratio, and the selection of shaft speeds. The latter for instance requires a trade-off between propeller and free power turbine efficiency. For a parallel hybrid, the electric machine efficiency becomes a third factor to consider. The objective of this paper is to expose some key aspects of these trade-offs in terms of efficiency and weight. The paper applies sophisticated methodology in both the gas turbine and electrical power domains. For the gas turbine, multi-point design is used. Here, an extension of established synthesis matching schemes is used, which covers the design and operation rules also for the electric components of the hybrid. For the electrical machine, fully analytical sizing is used, which also captures the impact of cooling. For all main gas turbine components and the electric machine, the geometry is estimated based on the sizing methodology, and used as input for the weight estimation. Results are presented for parallel hybrid electric 2.5-spool geared turboprop architectures fulfilling requirements of a notional 19 passenger regional aircraft. Uninstalled fuel consumption can be lower for the hybrid than the conventional baseline, and the key relations to typical cycle parameters such as overall pressure ratio and shaft speed selection are exposed. Overall, the benefit of hybridization is low however with the concept of operations inspired by hybrid turbofans. This is related to differences in contradicting cycle design requirements.

  • 281.
    Soibam, Jerol
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center.
    Data-Driven Techniques for Fluid Mechanics and Heat Transfer2022Licentiate thesis, comprehensive summary (Other academic)
    Abstract [en]

    One of the main challenges in fluid mechanics and heat transfer is the need for detailed studies andfast computational speed to monitor and optimise a system. These fluid/heat flows comprise time-dependent velocity, multi-scale, pressure, and energy fluctuations. Although there has been major advancements in computational power and technology, modelling detailed physical problems is currently falling short. The fluid mechanics and heat transfer domains are rapidly advancing, driven by unprecedented volumes of data from experiments, field measurements, and large-scale simulations at multiple spatio temporal scales. Such an increase in the volume of data unlocks the possibility of using techniques like machine learning. These machine learning algorithms offer a wealth of techniques to extract information from data that can be translated into knowledge about the underlying physics. Moreover, machine learning algorithms can augment domain knowledge and automate tasks related to flow control and optimisation. A significant milestone in the area of machine learning is the rise of deep learning, which is a powerful tool which can handle large data sets describing complex nonlinear dynamics that are commonly encountered in heat transfer and fluidflows.

    Therefore, this thesis aims to investigate data obtained from numerical simulations with deep learning techniques to reproduce the underlying physics present in data and considerably speed up the process. In this study, subcooled boiling transfer data has been used to train the deep neural network model then the trained model is validated using a validation dataset. The performance of the model is further evaluated using a set of interpolation and extrapolation datasets for different operating conditions outside the training and validation data. Furthermore, to highlight the robustness and reliability of the deep learning model, uncertainty quantification techniques such as Monte Carlo dropout and Deep Ensemble are implemented.

    This study demonstrates how a data-driven model can be used for subcooled boiling heat transfer and highlights why uncertainty quantification is important for such a model. The analysis and discussion in this thesis serve as the basis for further extending the potential use of data-driven methods for system optimisation, control and monitoring, diagnostic, and industrial applications. 

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  • 282.
    Soibam, Jerol
    et al.
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center.
    Aslanidou, Ioanna
    Mälardalen University, School of Innovation, Design and Engineering, Innovation and Product Realisation.
    Kyprianidis, Konstantinos
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center.
    Bel Fdhila, Rebei
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center. Hitachi Energy Research, Västerås, Sweden..
    Inverse flow prediction using ensemble PINNs and uncertainty quantification2024In: International Journal of Heat and Mass Transfer, ISSN 0017-9310, E-ISSN 1879-2189, Vol. 226Article in journal (Refereed)
    Abstract [en]

    The thermal boundary conditions in a numerical simulation for heat transfer are often imprecise. This leads to poorly defined boundary conditions for the energy equation. The lack of accurate thermal boundary conditions in real-world applications makes it impossible to effectively solve the problem, regardless of the advancement of conventional numerical methods. 

    This study utilises a physics-informed neural network to tackle ill-posed problems for unknown thermal boundaries with limited sensor data. The network approximates velocity and temperature fields while complying with the Navier-Stokes and energy equations, thereby revealing unknown thermal boundaries and reconstructing the flow field around a square cylinder. The method relies on optimal sensor placement determined by the QR pivoting technique, which ensures the effective capture of the dynamics, leading to enhanced model accuracy. In an effort to increase the robustness and generalisability, an ensemble physics-informed neural network is implemented. This approach mitigates the risks of overfitting and underfitting while providing a measure of model confidence. As a result, the ensemble model can identify regions of reliable prediction and potential inaccuracies. Therefore, broadening its applicability in tackling complex heat transfer problems with unknown boundary conditions.

  • 283.
    Soibam, Jerol
    et al.
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center.
    Aslanidou, Ioanna
    Mälardalen University, School of Innovation, Design and Engineering, Innovation and Product Realisation.
    Kyprianidis, Konstantinos
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center.
    Bel Fdhila, Rebei
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center. Hitachi Energy Research, Västerås, Sweden.
    Inverse Flow Prediction Using Pinns In An Enclosure Containing Heat Sources2023In: Proc. Thermal Fluids Eng. Summer Conf., Begell House Inc. , 2023, p. 429-438Conference paper (Refereed)
    Abstract [en]

    While simulating heat transfer problems using a numerical method, the thermal boundary conditions are never known precisely, which leads to ill-posed boundary conditions for the energy equation. The lack of knowledge of accurate thermal boundary conditions in a practical application makes it impossible to solve this problem no matter how sophisticated the conventional numerical method is. Hence, the current work addresses this ill-posed problem using physics informed neural network by assuming that the thermal boundary near the source is unknown and only a few measurements of temperature are known in the domain. Physics-informed neural network is employed to represent the velocity and temperature fields, while simultaneously enforcing the Navier-Stokes and energy equations at random points in the domain. This work serves as an inverse problem since the goal here is to reproduce the global flow field and temperature profile in the domain with few measurement data points. Furthermore, the work focuses on using transfer learning for different parameters such as the position and size of the source term inside the enclosure domain. These parameters are of particular interest while designing a thermal system and being able to predict the flow and thermal behaviour instantly will allow for better design of the system. For this study, the sensors' data are extracted from numerical simulation results. The placement of the sensors in the domain plays a vital role in accuracy hence, sensors were optimized using the residual of the energy equation. The results obtained from this work demonstrate that the proposed method is in good agreement with the underlying physics represented by the numerical results.

  • 284.
    Soibam, Jerol
    et al.
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center.
    Scheiff, Valentin
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center.
    Aslanidou, Ioanna
    Mälardalen University, School of Innovation, Design and Engineering, Innovation and Product Realisation.
    Kyprianidis, Konstantinos
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center.
    Bel Fdhila, Rebei
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center. Hitachi Energy Res, Vasteras, Sweden .
    Application of deep learning for segmentation of bubble dynamics in subcooled boiling2023In: International Journal of Multiphase Flow, ISSN 0301-9322, E-ISSN 1879-3533, Vol. 169, article id 104589Article in journal (Refereed)
    Abstract [en]

    The present work focuses on designing a robust deep-learning model to track bubble dynamics in a vertical rectangular mini-channel. The rectangular mini-channel is heated from one side with a constant heat flux, resulting in the creation of bubbles. Images of the bubbles are recorded using a high-speed camera, which serve as the input data for the deep learning model. The raw image data acquired from the high-speed camera is inherently noisy due to the presence of shadows, reflections, background noise, and chaotic bubbles. The objective is to extract the mask of the bubble given all these challenging factors. Transfer learning is adopted to eliminate the need for a large dataset to train the deep learning model and also to reduce computational costs. The trained model is then validated against the validation datasets, demonstrating an accuracy of 98% while detecting the bubbles. The model is then evaluated on different experimental conditions, such as lighting, background, and blurry images with noise. The model demonstrates high robustness to different conditions and is able to detect the edges of the bubbles and classify them accurately. Moreover, the model achieves an average intersection over union of 85%, indicating a high level of accuracy in predicting the masks of the bubbles. The method enables accurate recognition and tracking of individual bubble dynamics, capturing their coalescence, oscillation, and collisions to estimate local parameters by proving the bubble masks. This allows for a comprehensive understanding of their spatial-temporal behaviour, including the estimation of local Reynolds numbers.

  • 285.
    Song, J.
    et al.
    School of Mechanical Engineering, Guizhou University, Guiyang Guizhou, 550025, China.
    Zhang, F.
    School of Mechanical Engineering, Guizhou University, Guiyang Guizhou, 550025, China.
    Qi, L.
    School of Mechanical Engineering, Guizhou University, Guiyang Guizhou, 550025, China.
    Cao, H.
    chool of Mechanical Engineering, Southwest Jiaotong University, Chengdu, 610031, China.
    Wang, Y.
    School of Mechanical Engineering, Guizhou University, Guiyang Guizhou, 550025, China.
    Zhang, Z.
    chool of Mechanical Engineering, Southwest Jiaotong University, Chengdu, 610031, China.
    Yan, Jinyue
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center. Department of Building Environment and Energy Engineering, The Hong Kong Polytechnic University, Hongkong, China .
    Parameter optimization analysis of rotary electromagnetic vibration energy harvester for performance enhancement under free vibration2023In: iScience, E-ISSN 2589-0042, Vol. 26, no 10, article id 107989Article in journal (Refereed)
    Abstract [en]

    In this paper, three new important aspects of rotary electromagnetic vibration energy harvesting technology (RE-VEH) are concerned and investigated: (i) vibro-electric coupling mechanism of the RE-VEH system is studied through theoretical modeling; (ii) quantitative analysis of system parameters based on numerical simulation method is carried out for the optimal design of RE-VEH; and (iii) dynamic power output performance of the RE-VEH system in free vibration is discussed. The parameter adjusting methods of the RE-VEH system in free vibration mode are obtained through theoretical analysis and numerical simulation. The experimental results show that the power output performance of RE-VEH in free vibration mode matches the numerical simulation results. The simulation and experimental results show that the maximum voltage output and power output of the RE-VEH with different structure parameters under free vibration can be up to the level of 100∼101 V/watt. The above results indicate that RE-VEH in a free vibration environment has significant energy output performance. 

  • 286.
    Stenfelt, Mikael
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center.
    On model based aero engine diagnostics2023Licentiate thesis, comprehensive summary (Other academic)
    Abstract [en]

    Maintenance and diagnostics play a vital role in the aviation sector. This is especially true for the engines, being one of the most vital components. Lack of maintenance, or poor knowledge of the current health status of the engines, may lead to unforeseen disruptions and possibly catastrophic effects. To keep track of the health status, and thereby supporting maintenance planning, model based diagnostics is a key factor. 

    In the work going into this thesis, various aspects of model based gas turbine diagnostics, focused on aero engines, are covered. First, the importance of knowing what health parameters may be derived from a set of measurements is addressed. The selected combination is herein denoted as a matching scheme. A framework is proposed where the most suitable matching scheme is selected for a numerically robust diagnostic system. If a sensor malfunction is detected, the system automatically adapts.

    The second subject is a system for detecting a burn-through of an afterburner inner liner. This kind of burn-through event has a very small impact on available on-board measurements, making it difficult to detect numerically. A method is proposed performing back-to-back testing after each engine start. The method has shown potential to detect major burn-through events under the preconditions, regarding data collection time and frequency. Increasing these will allow for more accurate estimations.

    The third subject covers the importance of knowing the airplane installation effects. These are generally the intake pressure recovery, bleed and shaft power extraction. Just like inaccurate measurements affect diagnostic results, so does erroneous installation effects. A method for estimating said effects in the presence of gradual degradation has been proposed by using neural networks. By retraining the networks throughout the degradation process, the estimation errors is reduced, ensuring relevant estimations even at severe degradations.

    Finally, an issue related to the general lack of on-board measurements for diagnostics is addressed. Due to lack of measurements, the diagnostic model tend to be underdetermined. A least square solver working without a priori information has been implemented and evaluated. Results from the solver is very much dependent on available instrumentation. In well instrumented components, such as the compressors, good diagnostic accuracy was achieved while the turbine health estimations suffer from smeared out results due to poor instrumentation.

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  • 287.
    Stenfelt, Mikael
    et al.
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center. SAAB Aeronut, S-58254 Linkoping, Sweden..
    Kyprianidis, Konstantinos
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center.
    Estimation and Mitigation of Unknown Airplane Installation Effects on GPA Diagnostics2022In: Machines, E-ISSN 2075-1702, Vol. 10, no 1, article id 36Article in journal (Refereed)
    Abstract [en]

    In gas turbines used for airplane propulsion, the number of sensors are kept at a minimum for accurate control and safe operation. Additionally, when data are communicated between the airplane main computer and the various subsystems, different systems may have different constraints and requirements regarding what data transmit. Early in the design process, these parameters are relatively easy to change, compared to a mature product. If the gas turbine diagnostic system is not considered early in the design process, it may lead to diagnostic functions having to operate with reduced amount of data. In this paper, a scenario where the diagnostic function cannot obtain airplane installation effects is considered. The installation effects in question is air intake pressure loss (pressure recovery), bleed flow and shaft power extraction. A framework is presented where the unknown installation effects are estimated based on available data through surrogate models, which is incorporated into the diagnostic framework. The method has been evaluated for a low-bypass turbofan with two different sensor suites. It has also been evaluated for two different diagnostic schemes, both determined and underdetermined. Results show that, compared to assuming a best-guess constant-bleed and shaft power, the proposed method reduce the RMS in health parameter estimation from 26% up to 80% for the selected health parameters. At the same time, the proposed method show the same degradation pattern as if the installation effects were known.

  • 288.
    Sun, H.
    et al.
    Key Laboratory of Ocean Energy Utilization and Energy Conservation of Ministry of Education, Dalian University of Technology, Dalian, 116024, China.
    Chen, B.
    Key Laboratory of Ocean Energy Utilization and Energy Conservation of Ministry of Education, Dalian University of Technology, Dalian, 116024, China.
    Li, K.
    Key Laboratory of Ocean Energy Utilization and Energy Conservation of Ministry of Education, Dalian University of Technology, Dalian, 116024, China.
    Song, Y.
    Key Laboratory of Ocean Energy Utilization and Energy Conservation of Ministry of Education, Dalian University of Technology, Dalian, 116024, China.
    Yang, M.
    Key Laboratory of Ocean Energy Utilization and Energy Conservation of Ministry of Education, Dalian University of Technology, Dalian, 116024, China.
    Jiang, L.
    Key Laboratory of Ocean Energy Utilization and Energy Conservation of Ministry of Education, Dalian University of Technology, Dalian, 116024, China.
    Yan, Jinyue
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center.
    Methane hydrate re-formation and blockage mechanism in a pore-level water-gas flow process2023In: Energy, ISSN 0360-5442, E-ISSN 1873-6785, Vol. 263, article id 125851Article in journal (Refereed)
    Abstract [en]

    Hydrate re-formation increases blockage risk and further reduces gas production efficiency. Considering the huge water production and gas migration, it is essential to determine the key parameters that control hydrate re-formation and blockage in the two-phase flow process. However, little research reveals the mechanism of hydrate re-formation in the water-dominated two-phase flow system. In this study, two-phase flow in hydrate sediment is simulated by controlling the water-gas flow rate, and the effect of effective sectional velocity on hydrate re-formation characteristics is analyzed. The experimental results showed that temperature and pressure followed a three-stage change trend in the water-dominated two-phase flow process: including hydrate re-formation induction stage I, mass hydrate re-formation and agglomeration stage II, and pore gas consumption stage III. Moreover, a lower effective sectional velocity of water (WESV) would reduce the gas concentration gradient between water and hydrate to enhance the hydrate re-formation process. Meanwhile, the gas phase impeded the mass transfer on the water-hydrate interface and acted as the nucleation site to promote hydrate re-formation. Furthermore, it was noticed that the relationship between the onset time of flow blockage and WESV was linearly positive, however, the amount of hydrate re-formation reduced with increasing WESV. 

  • 289.
    Sun, Y.
    et al.
    Tianjin University of Commerce, China.
    Dong, Beibei
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center. Tianjin University of Commerce, China.
    Wang, L.
    SINTEF Energy Research, Sluppen, Trondheim, 7Norway.
    Thorin, Eva
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center.
    Li, Hailong
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center.
    Capturing CO2 from Wood Fast Pyrolysis2021In: Energy Proceedings, Scanditale AB , 2021, Vol. 23Conference paper (Refereed)
    Abstract [en]

    To achieve the climate goal set by the Paris Agreement, negative emission technologies (NETs) will play an important role. Bioenergy with carbon capture and storage (BECCS) is one of the most promising of NETs. This work aims to find a suitable technology for capturing CO2 from fast pyrolysis, which include Monoethanolamine based chemical absorption (MEACC), temperature swing absorption (TSA) and calcium looping (CCL) are considered. By using validated models, the CO2 capture rate, CO2 purity and energy penalty are employed as key performance indicators to compare the performance of those technologies. It has been found that CCL has the highest CO2 purity, MEA-CC, TSA and CCL have similar CO2 capture rates and TSA has the lowest energy penalty. Results provide insights and suggestions about the selection of CO2 capture technology for pyrolysis.

  • 290.
    Sun, Y.
    et al.
    Joint Laboratory for Advanced Energy Storage and Application, School of Mechanical Engineering, Beijing Institute of Technology, No. 5 South Zhongguancun Street, Haidian District, Beijing, 100081, China.
    Xiong, R.
    Joint Laboratory for Advanced Energy Storage and Application, School of Mechanical Engineering, Beijing Institute of Technology, No. 5 South Zhongguancun Street, Haidian District, Beijing, 100081, China.
    Wang, C.
    Joint Laboratory for Advanced Energy Storage and Application, School of Mechanical Engineering, Beijing Institute of Technology, No. 5 South Zhongguancun Street, Haidian District, Beijing, 100081, China.
    Tian, J.
    Joint Laboratory for Advanced Energy Storage and Application, School of Mechanical Engineering, Beijing Institute of Technology, No. 5 South Zhongguancun Street, Haidian District, Beijing, 100081, China.
    Li, Hailong
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center.
    Deep neural network based battery impedance spectrum prediction using only impedance at characteristic frequencies2023In: Journal of Power Sources, ISSN 0378-7753, E-ISSN 1873-2755, Vol. 580, article id 233414Article in journal (Refereed)
    Abstract [en]

    Electrochemical impedance spectroscopy can be used for characterizing and monitoring the state of batteries. However, the difficulty in the onboard acquisition limits its wide applications. This work proposes a new method to obtain the impedance spectrum by using convolutional neural network, which uses the impedance measured at several characteristic frequencies as input. The characteristic frequencies are determined according to the time constants corresponding to the characteristic peaks and valleys of contact polarization and solid electrolyte interphase growth processes from the distribution of relaxation time. The proposed method is validated based on the dataset which contains the impedance spectra of eight batteries over the whole life cycle. The predictions coincide with the ground truth, with a maximum root mean square error of 0.93 mΩ. The developed method can also be quickly adapted to acquire the impedance spectrum of other batteries with different chemistries and be used for predictions of various battery states based on the transfer learning approach. 

  • 291.
    Sun, Yingying
    et al.
    Tianjin Univ Commerce, Tianjin, Peoples R China..
    Dong, Beibei
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center. Tianjin Univ Commerce, Tianjin, Peoples R China..
    Wang, Liang
    SINTEF Energy Res, Trondheim, Norway..
    Li, Hailong
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center.
    Thorin, Eva
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center.
    Technology selection for capturing CO2 from wood pyrolysis2022In: Energy Conversion and Management, ISSN 0196-8904, E-ISSN 1879-2227, Vol. 266, article id 115835Article in journal (Refereed)
    Abstract [en]

    Emerging negative emission technologies (NETs) are considered as effective measures to reduce carbon dioxide emissions to achieve the climate goal set by the Paris Agreement, and bioenergy with carbon capture and storage (BECCS) is one of the most important NETs. Integrating CO2 capture with biomass pyrolysis (PyrCC) is attracting increasing interest, because biomass pyrolysis has been widely used to produce biooil to replace fossil fuel for decarbonizing the transport sector. In order to provide guidance to the selection of CO2 capture technologies, this paper evaluated the technical and economic performances of PyrCC when different CO2 capture technologies are integrated, including monoethanolamine-based chemical absorption (MEA-CA), temperature swing absorption (TSA), calcium looping (CaL), and chemical looping combustion (CLC). Generally speaking, CLC can realize the highest capture amount of CO2 with the lowest energy penalty. Meanwhile, CLC and CaL show the lowest levelized cost of CO2 (LCOC), which are around 56$/tCO(2); and on the contrary MEA-CA shows the highest one of 83 $/tCO(2). In addition, the key process parameter of pyrolysis, reaction time, has clear effects on the performance of CO2 capture as the longer reaction time leads to an increased amount of captured CO2 and reduced energy penalty. As a result, when the reaction time increases, the LCOCs of all assessed technologies decrease. Moreover, the net present value and the payback time are also estimated for different technologies. At the carbon price of 70.1$/tCO(2), MEA-CA and CLC show the longest and shortest payback time that are 5.9 years and 3.2 years respectively.

  • 292.
    Sylwan, Ida
    et al.
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center.
    Bergna, Davide
    Univ Oulu, Res Unit Sustainable Chem, POB 8000, FI-90014 Oulu, Finland..
    Runtti, Hanna
    Univ Oulu, Res Unit Sustainable Chem, POB 8000, FI-90014 Oulu, Finland..
    Westholm, Lena Johansson
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center.
    Thorin, Eva
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center.
    Primary and digested sludge-derived char as a Cd sorbent: feasibility of local utilisation2023In: Water Science and Technology, ISSN 0273-1223, E-ISSN 1996-9732, Vol. 11, p. 2917-2930Article in journal (Refereed)
    Abstract [en]

    Cadmium (Cd) is a highly toxic metal, occurring in municipal wastewater and stormwater as well as in wastewater from various industries. Char derived from the pyrolysis of municipal sewage sludge has the potential to be a low-cost sorption media for the removal of Cd. However, the balance between possible local char production and demand has not been assessed previously. In this study, the Cd sorption capacities of chars derived from primary (PSC) and secondary sludge (DSC), as well as the feasibility of char production for Cd sorbent purposes, and the pyrolysis energy balance were evaluated. Results showed that the sorption capacity of PSC (9.1 mg/g; 800 degrees C, 70 min) was superior to that of DSC (6.0 mg/g; 800 degrees C, 70 min), and increased with a higher pyrolysis temperature. Pyrolysis of primary sludge had a more favourable energy balance compared with the pyrolysis of digested sludge, however, when accounting for loss of biogas production the energy balance of primary sludge pyrolysis was negative. Assessment of the regional demand (V & auml;ster & aring;s, Sweden) indicated that PSC or DSC may cover the local Cd sorbent demand. However, it was estimated that large char volumes would be required, thus making the use of DSC/PSC less feasible.

  • 293.
    Sylwan, Ida
    et al.
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center.
    Thorin, Eva
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center.
    Potential of sludge-derived char as a metal sorbent during primary settling of municipal wastewater2023In: Environmental Technology & Innovation, ISSN 2352-1864, Vol. 32, article id 103258Article in journal (Refereed)
    Abstract [en]

    Reuse of nutrients and water from municipal wastewater is attracting increasing attention. However, pollutants such as toxic metals should be minimised. This study investigated the potential for reducing metal concentrations in wastewater effluent and secondary sludge by introducing sludge-derived char (SDC) as a sorbent in primary settling. Batch experiments, performed in aqueous metal solution and wastewater, showed that Cu and Ni removal was significantly reduced in wastewater containing dissolved organic matter (68% and 40%, respectively), compared to metal solution (>99% and 99%, respectively). Modelling of primary settling indicated Cd and Cu removal enhancement with SDC addition (from 39%–79% and 30%–43%, respectively). Smaller effects were observed for Pb, Cr, and Zn. An increased risk of Ni concentration in primary settler effluent was identified (−53% removal). These results demonstrate the challenges of implementing SDC as a sorbent for real wastewater.

  • 294.
    Sylwan, Ida
    et al.
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center.
    Thorin, Eva
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center.
    Sludge-derived char - potential as a heavy metal sorbent during primary settling of municipal wastewater2022Conference paper (Other academic)
  • 295.
    Söderkvist Vermelin, Wilhelm
    et al.
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center. RISE Research Institutes of Sweden, Västra Götaland, Mölndal, 431 53, Sweden.
    Lövberg, A.
    RISE Research Institutes of Sweden, Västra Götaland, Mölndal, 431 53, Sweden.
    Kyprianidis, K.
    Self-supervised learning for efficient remaining useful life prediction2022In: Proceedings of the Annual Conference of the Prognostics and Health Management Society, PHM, vol 14, nr 1, Prognostics and Health Management Society , 2022, no 1Conference paper (Refereed)
    Abstract [en]

    Canonical deep learning-based remaining useful life prediction relies on supervised learning methods, which in turn requires large data sets of run-to-failure data to ensure model performance. In a considerable class of cases, run-to-failure data is difficult to collect in practice as it may be expensive and unsafe to operate assets until failure. As such, there is a need to leverage data that are not run-to-failure but may still contain some measurable, and thus learnable, degradation signal. In this paper, we propose utilizing self-supervised learning as a pretraining step to learn representations of data which will enable efficient training on the downstream task of remaining useful life prediction. The self-supervised learning task chosen is time series sequence ordering, a task that involves constructing tuples each consisting of n sequences sampled from the time series and reordered with some probability p. Subsequently, a classifier is trained on the resulting binary classification task; distinguishing between correctly ordered and shuffled tuples. The classifier’s weights are then transferred to the remaining useful life prediction model and fine-tuned using run-to-failure data. To conduct our experiments, we use a data set of simulated run-to-failure turbofan jet engines. We show that the proposed self-supervised learning scheme can retain performance when training on a fraction of the full data set. In addition, we show indications that self-supervised learning as a pretraining step can enhance the performance of the model even when training on the full run-to-failure data set. 

  • 296.
    Taha, Mohammed
    et al.
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center.
    Lundvall, Nick
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center.
    Kyprianidis, Konstantinos
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center.
    Salman, Awais
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center.
    Vouros, Stavros
    Mälardalen University, School of Innovation, Design and Engineering, Innovation and Product Realisation.
    Zaccaria, Valentina
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center.
    Techno-economic evaluation of hydrogen production for airport hubs2024In: Energy Proceedings, Scanditale AB , 2024, Vol. 45Conference paper (Refereed)
    Abstract [en]

    Hydrogen is considered one of the most promising alternative fuels for aviation, which can be used to power aircraft and airport ground services. Onsite hydrogen production from renewables can be suitable for small- size airports, while the larger size airports can be supplied through transportation either from dedicated green hydrogen production plants or other sources of hydrogen. This paper presents a study of two hydrogen supply scenarios, one taking the small airport of Stockholm Skavsta as a case study for in-house hydrogen production. The second is evaluating offshore green hydrogen supply to the large size airport of Arlanda. The in-house hydrogen production evaluates 18 scenarios covering all possible scenarios for alkaline, PEM, and solid oxide electrolysis as production means and compressed, cryo- compressed, and liquid gas as storage, with power supply from grid and grid plus in-house solar system. The optimum production and storage facility size is determined in association with the levelized cost and carbon emissions for each scenario. For the large-size airport, the study evaluates the hydrogen supply from offshore production facilities transported as compressed, cryo-compressed, or liquid gas via offshore pipeline and onshore pipeline, Offshore pipeline and truck, Ship and onshore pipeline, or Ship and truck. The results showed the levelized cost to be between 2.93-2.44 Euro/kg H2 in the case of in-house production. Compressed hydrogen offshore and onshore pipeline is the least cost for Arlanda airport hydrogen supply. This paper demonstrates a direction for aviation sector decarbonization and establishes a pathway for airports' in-house hydrogen production and outsourced hydrogen supply.

  • 297.
    Teng, Siyu
    et al.
    Hong Kong Baptist University, Kowloon, China.
    Chen, Long
    State Key Laboratory of Management and Control for Complex Systems, Institute of Automation, Chinese Academy of Sciences, Beijing, China.
    Ai, Yunfeng
    University of Chinese Academy of Sciences, Beijing, China.
    Zhou, Yuanye
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center.
    Xuanyuan, Zhe
    BNU-HKBU United International College, Zhuhai, China.
    Hu, Xuemin
    School of Computer Science and Information Engineering, Hubei University, Wuhan, China.
    Hierarchical Interpretable Imitation Learning for End-to-End Autonomous Driving2023In: IEEE Transactions on Intelligent Vehicles, ISSN 2379-8858, E-ISSN 2379-8904, Vol. 8, no 1, p. 673-683Article in journal (Refereed)
    Abstract [en]

    End-to-end autonomous driving provides a simple and efficient framework for autonomous driving systems, which can directly obtain control commands from raw perception data. However, it fails to address stability and interpretability problems in complex urban scenarios. In this paper, we construct a two-stage end-to-end autonomous driving model for complex urban scenarios, named HIIL (Hierarchical Interpretable Imitation Learning), which integrates interpretable BEV mask and steering angle to solve the problems shown above. In Stage One, we propose a pretrained Bird's Eye View (BEV) model which leverages a BEV mask to present an interpretation of the surrounding environment. In Stage Two, we construct an Interpretable Imitation Learning (IIL) model that fuses BEV latent feature from Stage One with an additional steering angle from Pure-Pursuit (PP) algorithm. In the HIIL model, visual information is converted to semantic images by the semantic segmentation network, and the semantic images are encoded to extract the BEV latent feature, which are decoded to predict BEV masks and fed to the IIL as perception data. In this way, the BEV latent feature bridges the BEV and IIL models. Visual information can be supplemented by the calculated steering angle for PP algorithm, speed vector, and location information, thus it could have better performance in complex and terrible scenarios. Our HIIL model meets an urgent requirement for interpretability and robustness of autonomous driving. We validate the proposed model in the CARLA simulator with extensive experiments which show remarkable interpretability, generalization, and robustness capability in unknown scenarios for navigation tasks.

  • 298.
    Tian, Yu
    et al.
    Beijing Inst Technol, Sch Mech Engn, Beijing 100081, Peoples R China..
    Lin, Cheng
    Beijing Inst Technol, Sch Mech Engn, Beijing 100081, Peoples R China..
    Li, Hailong
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center.
    Du, Jiuyu
    Tsinghua Univ, State Key Lab Automot Safety & Energy, Beijing, Peoples R China..
    Xiong, Rui
    Beijing Inst Technol, Sch Mech Engn, Beijing 100081, Peoples R China..
    Deep neural network-driven in-situ detection and quantification of lithium plating on anodes in commercial lithium-ion batteries2022In: ECOMAT, ISSN 2567-3173, article id e12280Article in journal (Refereed)
    Abstract [en]

    Lithium plating seriously threatens the life of lithium-ion batteries at low temperatures charging conditions, but the onboard detection and quantification of lithium plating are severely hampered by the limited available signals and volatile operating conditions in real scenarios. Herein, we propose a detection method to predict the occurrence and quantification of lithium plating under uncertain conditions by only using constant-current curves during charging based on deep learning. A deep neural network (DNN) is developed to extract data-driven features induced by lithium plating from the charge curves, avoiding the challenge of manual feature selection. Only using the most common voltage and current signals as inputs, the network exhibits superior adaptability and accuracy. The detection accuracy of the proposed method is 98.64%, while the quantity of the lithium plating can be accurately predicted with a root-mean-square error <4.1712 mg. Moreover, the generalization ability of the proposed method is verified by its reliable detection accuracy under conditions that are not used in the training dataset. The detection accuracy is 92.39% for brand new charging conditions and 95.53% for brand new aging states. This method shortens the detection time that currently takes more than several hours (the widely used differential curve analysis) to milliseconds and eliminates the need for a rigorous testing environment, showing great potential for onboard application in future battery management systems.

  • 299.
    Tonda, R.
    et al.
    University of Muhammadiyah Malang, Indonesia.
    Zalizar, L.
    University of Muhammadiyah Malang, Indonesia.
    Widodo, W.
    Setyobudi, R. H.
    University of Muhammadiyah Malang, Indonesia.
    Hermawan, D.
    University of Muhammadiyah Malang, Indonesia.
    Damat, D.
    University of Muhammadiyah Malang, Indonesia.
    Purbajanti, E. D.
    University of Diponegoro, Semarang, Indonesia.
    Prasetyo, H.
    University of Brawijaya, Malang, East Java, Indonesia .
    Ekawati, I.
    University of Wiraraja, Sumenep, East Java, Indonesia.
    Jani, Yahya
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center.
    Burlakovs, J.
    Institute of the Polish Academy of Sciences, Kraków, Poland.
    Wahono, S. K.
    Research Center for Food Technology and Processing - National Research and Innovation Agency Republic of Indonesia, Special Region of Yogyakarta, Indonesia.
    Anam, C.
    Universitas Islam Darul Ulum, Lamongan, Indonesia.
    Pakarti, T. A.
    Mayantara School, Malang, East Java, Indonesia.
    Susanti, M. S.
    Aura Statistics Consultant, Malang, East Java, Indonesia.
    Mahnunin, R.
    PT. Zakiyah Jaya Mandiri, Lumajang, East Java, Indonesia.
    Sutanto, A.
    University of Muhammadiyah Malang, Malang, East Java, Indonesia.
    Sari, D. K.
    PT. Zakiyah Jaya Mandiri, Lumajang, East Java, Indonesia.
    Hilda, H.
    CV. Harapan Jaya Abadi, Malang, East Java, Indonesia.
    Fauzi, A.
    University of Muhammadiyah Malang, Malang, East Java, Indonesia.
    Wirawan, W.
    University of Tribhuwana Tunggadewi, Malang, East Java, Indonesia.
    Sebayang, N. S.
    University of Muhammadiyah Palembang, Palembang, South Sumatera, Indonesia.
    Hadinoto, H.
    University of Lancang Kuning, Pekanbaru, Riau, Indonesia.
    Suhesti, E.
    University of Lancang Kuning, Pekanbaru, Riau 28266, Indonesia.
    Amri, U.
    University of Muhammadiyah Makassar, Makassar, South Sulawesi, Indonesia.
    Busa, Y.
    University of Muhammadiyah Enrekang, Enrekang, South Sulawesi Indonesia.
    Potential Utilization of Dried Rice Leftover of Household Organic Waste for Poultry Functional Feed2022In: Jordan Journal of Biological Sciences, ISSN 1995-6673, Vol. 15, no 5, p. 879-886Article in journal (Refereed)
    Abstract [en]

    Indonesia produced 30 × 106 t of waste in 2021; 40 % was organic and 276 × 103 t leftover rice. Meanwhile, broiler chicken farmers have been struggling with high feed costs to continue their production. Processing leftover rice into "aking-rice" is environmentally friendly, and it also provides alternative feed for chickens. "Aking-rice" is a type of resistant starch because it has undergone a gelatinization process that works as a synthesis of short-chain fatty acids that positively improve the function of the digestive tract because it increases the villi in the small intestine. This study analyzed the potential of “akingrice” in broiler chicken productivity. The experimental method was a completely randomized design with three treatments, five replications and 12 chickens in each unit. The treatments are T0 (100 % basal feed), T1 (80 % basal feed + 20 % “akingrice” spread on top of the basal feed), and T2 (80 % basal feed + 20 % "aking-rice" mix). Statistical analysis used ANOVA, and continued with LSD with observed variables, i.e. Feed Intake (FI), Average Daily Gain (ADG), Feed Conversion Ratio (FCR), and Performance Index (PI). The results showed that the highest FI values were T0 (99.02), T1 (97.45), and T2 (96.58). The highest ADG was T1 (40.40) then T0 (37.07) and the lowest was T2 (36.40). T1 has the lowest FCR (2.42) compared to T0 (2.68), T2 (2.66). The lowest FCR is T1 (2.42), then T2 (2.66) and the highest is T0 (2.68). The third variable was not significantly different, but the PI results showed a significant difference with the highest PI value T1 (433.84), while T0 (374.81) and T2 (372.67) were not different. Economic analysis also shows that the highest cost T0 (118 475) is significantly different from T1 (110 541) and T2 (109 558). The highest profit is shown by T1 (2 102) then T2 (1 063) and T0 (507). In conclusion, the use of "aking-rice" can increase the performance index with a higher ADG value and a lower FCR so that the costs are smaller and the profit is greater.

  • 300.
    Toorajipour, Reza
    et al.
    Mälardalen University, School of Innovation, Design and Engineering, Innovation and Product Realisation.
    Chirumalla, Koteshwar
    Mälardalen University, School of Innovation, Design and Engineering, Innovation and Product Realisation.
    Johansson, Glenn
    Lund University, Sweden.
    Dahlquist, Erik
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center.
    Wallin, Fredrik
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center.
    Implementing circular business models for electric vehicle battery second life: Challenges and enablers from an ecosystem perspective2023Manuscript (preprint) (Other academic)
345678 251 - 300 of 395
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