mdh.sePublikationer
Ändra sökning
Avgränsa sökresultatet
1 - 20 av 20
RefereraExporteraLänk till träfflistan
Permanent länk
Referera
Referensformat
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Annat format
Fler format
Språk
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Annat språk
Fler språk
Utmatningsformat
  • html
  • text
  • asciidoc
  • rtf
Träffar per sida
  • 5
  • 10
  • 20
  • 50
  • 100
  • 250
Sortering
  • Standard (Relevans)
  • Författare A-Ö
  • Författare Ö-A
  • Titel A-Ö
  • Titel Ö-A
  • Publikationstyp A-Ö
  • Publikationstyp Ö-A
  • Äldst först
  • Nyast först
  • Skapad (Äldst först)
  • Skapad (Nyast först)
  • Senast uppdaterad (Äldst först)
  • Senast uppdaterad (Nyast först)
  • Disputationsdatum (tidigaste först)
  • Disputationsdatum (senaste först)
  • Standard (Relevans)
  • Författare A-Ö
  • Författare Ö-A
  • Titel A-Ö
  • Titel Ö-A
  • Publikationstyp A-Ö
  • Publikationstyp Ö-A
  • Äldst först
  • Nyast först
  • Skapad (Äldst först)
  • Skapad (Nyast först)
  • Senast uppdaterad (Äldst först)
  • Senast uppdaterad (Nyast först)
  • Disputationsdatum (tidigaste först)
  • Disputationsdatum (senaste först)
Markera
Maxantalet träffar du kan exportera från sökgränssnittet är 250. Vid större uttag använd dig av utsökningar.
  • 1.
    Ahmed, Mobyen Uddin
    et al.
    Mälardalens högskola, Akademin för innovation, design och teknik, Inbyggda system.
    Andersson, Peter
    Mälardalens högskola, Akademin för innovation, design och teknik, Inbyggda system.
    Andersson, Tim
    Mälardalens högskola, Akademin för innovation, design och teknik, Inbyggda system.
    Tomas Aparicio, Elena
    Mälardalens högskola, Akademin för ekonomi, samhälle och teknik, Framtidens energi. Malardalen Univ, Future Energy Ctr, Sch Business Soc & Engn, SE-72123 Vasteras, Sweden.;Malarenergi AB, Sjohagsvagen 3, S-72103 Vasteras, Sweden..
    Baaz, Hampus
    Mälardalens högskola, Akademin för innovation, design och teknik, Inbyggda system.
    Barua, Shaibal
    Mälardalens högskola, Akademin för innovation, design och teknik, Inbyggda system.
    Bergström, Albert
    Mälardalens högskola, Akademin för innovation, design och teknik, Inbyggda system.
    Bengtsson, Daniel
    Mälardalens högskola, Akademin för innovation, design och teknik, Inbyggda system.
    Orisio, Daniele
    State Inst Higher Educ Guglielmo Marconi, Dalmine, Italy..
    Skvaril, Jan
    Mälardalens högskola, Akademin för ekonomi, samhälle och teknik, Framtidens energi.
    Zambrano, Jesus
    Mälardalens högskola, Akademin för ekonomi, samhälle och teknik, Framtidens energi.
    A Machine Learning Approach for Biomass Characterization2019Ingår i: INNOVATIVE SOLUTIONS FOR ENERGY TRANSITIONS / [ed] Yan, J Yang, HX Li, H Chen, X, ELSEVIER SCIENCE BV , 2019, s. 1279-1287Konferensbidrag (Refereegranskat)
    Abstract [en]

    The aim of this work is to apply and evaluate different chemometric approaches employing several machine learning techniques in order to characterize the moisture content in biomass from data obtained by Near Infrared (NIR) spectroscopy. The approaches include three main parts: a) data pre-processing, b) wavelength selection and c) development of a regression model enabling moisture content measurement. Standard Normal Variate (SNV), Multiplicative Scatter Correction and Savitzky-Golay first (SGi) and second (SG2) derivatives and its combinations were applied for data pre-processing. Genetic algorithm (GA) and iterative PLS (iPLS) were used for wavelength selection. Artificial Neural Network (ANN), Gaussian Process Regression (GPR), Support Vector Regression (SVR) and traditional Partial Least Squares (PLS) regression, were employed as machine learning regression methods. Results shows that SNV combined with SG1 first derivative performs the best in data pre-processing. The GA is the most effective methods for variable selection and GPR achieved a high accuracy in regression modeling while having low demands on computation time. Overall, the machine learning techniques demonstrate a great potential to be used in future NIR spectroscopy applications.

  • 2.
    Ahmed, Mobyen Uddin
    et al.
    Mälardalens högskola, Akademin för innovation, design och teknik, Inbyggda system.
    Andersson, Peter
    Mälardalens högskola, Akademin för innovation, design och teknik, Inbyggda system.
    Andersson, Tim
    Mälardalens högskola, Akademin för innovation, design och teknik, Inbyggda system.
    Tomas Aparicio, Elena
    Mälardalens högskola, Akademin för ekonomi, samhälle och teknik, Framtidens energi. Mälarenergi AB, Sweden.
    Baaz, Hampus
    Mälardalens högskola, Akademin för innovation, design och teknik, Inbyggda system.
    Barua, Shaibal
    Mälardalens högskola, Akademin för innovation, design och teknik, Inbyggda system. RISE SICS, Sweden.
    Bergström, Albert
    Mälardalens högskola, Akademin för innovation, design och teknik, Inbyggda system.
    Bengtsson, Daniel
    Mälardalens högskola, Akademin för innovation, design och teknik, Inbyggda system.
    Skvaril, Jan
    Mälardalens högskola, Akademin för ekonomi, samhälle och teknik, Framtidens energi.
    Zambrano, Jesus
    Mälardalens högskola, Akademin för ekonomi, samhälle och teknik, Framtidens energi.
    Real-time Biomass Characterization in Energy Conversion Processes using Near Infrared Spectroscopy: A Machine Learning Approach2019Ingår i: “Innovative Solutions for Energy Transitions” / [ed] Elsevier, 2019, Vol. 158, s. 1279-1287Konferensbidrag (Refereegranskat)
    Abstract [en]

    The aim of this work is to apply and evaluate different chemometric approaches employing several machine learning techniques in order to characterize the moisture content in biomass from data obtained by Near Infrared (NIR) spectroscopy. The approaches include three main parts: a) data pre-processing, b) wavelength selection and c) development of a regression model enabling moisture content measurement. Standard Normal Variate (SNV), Multiplicative Scatter Correction and Savitzky-Golay first (SG1) and second (SG2) derivatives and its combinations were applied for data pre-processing. Genetic algorithm (GA) and iterative PLS (iPLS) were used for wavelength selection. Artificial Neural Network (ANN), Gaussian Process Regression (GPR), Support Vector Regression (SVR) and traditional Partial Least Squares (PLS) regression, were employed as machine learning regression methods. Results shows that SNV combined with SG1 first derivative performs the best in data pre-processing. The GA is the most effective methods for variable selection and GPR achieved a high accuracy in regression modeling while having low demands on computation time. Overall, the machine learning techniques demonstrate a great potential to be used in future NIR spectroscopy applications.

  • 3.
    Avelin, Anders
    et al.
    Mälardalens högskola, Akademin för ekonomi, samhälle och teknik, Framtidens energi.
    Skvaril, Jan
    Mälardalens högskola, Akademin för ekonomi, samhälle och teknik, Framtidens energi.
    Aulin, Robert
    Swedish University of Agricultural Sciences, Sweden.
    Odlare, Monica
    Mälardalens högskola, Akademin för ekonomi, samhälle och teknik, Framtidens energi.
    Dahlquist, Erik
    Mälardalens högskola, Akademin för ekonomi, samhälle och teknik, Framtidens energi.
    Forest biomass for bioenergy production – comparison of different forest species2014Ingår i: / [ed] J. Yan, 2014Konferensbidrag (Refereegranskat)
    Abstract [en]

    Forest biomass is a renewable and sustainable source of energy that can be used for producing electricity, heat, and biofuels. The production of biomass for energy is considered to be an important step in developing sustainable communities and managing greenhouse gas emissions effectively. Biomass properties vary and are commonly associated with plant species. Hence, efficient methods to predict biofuel characteristics will greatly affect the utilization and management of feedstock production. In this paper attempt was made to correlate various chemical characteristics with NIR spectra. Wood chips from various plant species was analyzed for lignin content, heating value, ash content and NIR and the results were evaluated with correlation, PCA and PCR. Initial evaluation showed promising results where chemical components in the wood correlate to NIR spectra. A selection of results will be presented in this paper. Further analysis as well as results from PCA and PCR models will be presented in the full paper version.

    Ladda ner fulltext (pdf)
    fulltext
  • 4.
    Kyprianidis, Konstantinos
    et al.
    Mälardalens högskola, Akademin för ekonomi, samhälle och teknik, Framtidens energi.
    Skvaril, JanMälardalens högskola, Akademin för ekonomi, samhälle och teknik, Framtidens energi.
    Developments in Combustion Technology2016Samlingsverk (redaktörskap) (Refereegranskat)
    Abstract [en]

    Over the past few decades, exciting developments have taken place in the field of combustion technology. The present edited volume intends to cover recent developments and provide a broad perspective of the key challenges that characterize the field. The target audience for this book includes engineers involved in combustion system design, operational planning and maintenance. Manufacturers and combustion technology researchers will also benefit from the timely and accurate information provided in this work. The volume is organized into five main sections comprising 15 chapters overall: - Coal and Biofuel Combustion - Waste Combustion - Combustion and Biofuels in Reciprocating Engines - Chemical Looping and Catalysis - Fundamental and Emerging Topics in Combustion Technology

  • 5.
    Kyprianidis, Konstantinos
    et al.
    Mälardalens högskola, Akademin för ekonomi, samhälle och teknik, Framtidens energi.
    Skvaril, JanMälardalens högskola, Akademin för ekonomi, samhälle och teknik, Framtidens energi.
    Developments in Near-Infrared Spectroscopy2017Samlingsverk (redaktörskap) (Refereegranskat)
    Abstract [en]

    Over the past few decades, exciting developments have taken place in the field of near-infrared spectroscopy (NIRS). This has been enabled by the advent of robust Fourier transform interferometers and diode array solutions, coupled with complex chemometric methods that can easily be executed using modern microprocessors. The present edited volume intends to cover recent developments in NIRS and provide a broad perspective of some of the challenges that characterize the field. The volume comprises six chapters overall and covers several sectors. The target audience for this book includes engineers, practitioners, and researchers involved in NIRS system design and utilization in different applications. We believe that they will greatly benefit from the timely and accurate information provided in this work.

  • 6.
    Mirmoshtaghi, Guilnaz
    et al.
    Mälardalens högskola, Akademin för ekonomi, samhälle och teknik, Framtidens energi.
    Skvaril, Jan
    Mälardalens högskola, Akademin för ekonomi, samhälle och teknik, Framtidens energi.
    Campana, Pietro Elia
    Mälardalens högskola, Akademin för ekonomi, samhälle och teknik, Framtidens energi.
    Li, Hailong
    Mälardalens högskola, Akademin för ekonomi, samhälle och teknik, Framtidens energi.
    Thorin, Eva
    Mälardalens högskola, Akademin för ekonomi, samhälle och teknik, Framtidens energi.
    Dahlquist, Erik
    Mälardalens högskola, Akademin för ekonomi, samhälle och teknik, Framtidens energi.
    The influence of different parameters on biomass gasification in circulating fluidized bed gasifiers2016Ingår i: Energy Conversion and Management, ISSN 0196-8904, E-ISSN 1879-2227, Vol. 126, s. 110-123Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    The mechanism of biomass gasification has been studied for decades. However, for circulating fluidized bed (CFB) gasifiers, the impacts of different parameters on the gas quality and gasifiers performance have still not been fully investigated. In this paper, different CFB gasifiers have been analyzed by multivariate analysis statistical tools to identify the hidden interrelation between operating parameters and product gas quality, the most influencing input parameters and the optimum points for operation. The results show that equivalence ratio (ER), bed material, temperature, particle size and carbon content of the biomass are the input parameters influencing the output of the gasifier the most. Investigating among the input parameters with opposite impact on product gas quality, cases with optimal gas quality can result in high tar yield and low carbon conversion while low tar yield and high carbon conversion can result in product gas with low quality. However using Olivine as the bed material and setting ER value around 0.3, steam to biomass ratio to 0.7 and using biomass with 3 mm particle size and 9 wt% moisture content can result in optimal product gas with low tar yield.

  • 7.
    Mirmoshtaghi, Guilnaz
    et al.
    Mälardalens högskola, Akademin för ekonomi, samhälle och teknik, Framtidens energi. Mälardalen Högskola.
    Skvaril, Jan
    Mälardalens högskola, Akademin för ekonomi, samhälle och teknik, Framtidens energi.
    Li, Hailong
    Thorin, Eva
    Mälardalens högskola, Akademin för ekonomi, samhälle och teknik, Framtidens energi.
    Dahlquist, Erik
    Mälardalens högskola, Akademin för ekonomi, samhälle och teknik, Framtidens energi.
    INVESTIGATION OF EFFECTIVE PARAMETERS ON BIOMASS GASIFICATION IN CIRCULATING FLUIDIZED BED GASIFIERS2015Konferensbidrag (Refereegranskat)
    Ladda ner fulltext (pdf)
    fulltext
  • 8.
    Mirmoshtaghi, Guilnaz
    et al.
    Mälardalens högskola, Akademin för ekonomi, samhälle och teknik, Framtidens energi.
    Skvaril, Jan
    Mälardalens högskola, Akademin för ekonomi, samhälle och teknik, Framtidens energi.
    Li, Hailong
    Mälardalens högskola, Akademin för ekonomi, samhälle och teknik, Framtidens energi.
    Thorin, Eva
    Mälardalens högskola, Akademin för ekonomi, samhälle och teknik, Framtidens energi.
    Dahlquist, Erik
    Mälardalens högskola, Akademin för ekonomi, samhälle och teknik, Framtidens energi.
    Investigation of Most Effective Parameters on Biomass Gasufication in Circulating Fluidized bed Gasifiers2015Ingår i: Forest and Plant Bioproducts Division 2015 - Core Programming Area at the 2015 AIChE Annual Meeting, 2015, s. 189-200Konferensbidrag (Refereegranskat)
  • 9.
    Skvaril, Jan
    Mälardalens högskola, Akademin för ekonomi, samhälle och teknik, Framtidens energi.
    Near-Infrared Spectroscopy and Extractive Probe Sampling for Biomass and Combustion Characterization2017Doktorsavhandling, sammanläggning (Övrigt vetenskapligt)
    Abstract [en]

    Biomass is characterized by highly variable properties. It can be converted to more valuable energy forms and products through a variety of conversion processes. This thesis focuses on addressing several important issues related to combustion and pulping.

    Experimental investigations were carried out on a biomass-fired industrial fluidized-bed boiler. The observed combustion asymmetry was explained by an imbalance in the fuel feed. Increased levels of carbon monoxide were detected close to boiler walls which contribute significantly to the risk of wall corrosion.

    Moreover, extensive literature analysis showed that near-infrared spectroscopy (NIRS) has a great potential to provide property information for heterogeneous feedstocks or products, and to directly monitor processes producing/processing biofuels in real-time. The developed NIRS-based models were able to predict characteristics such as heating value, ash content and glass content. A study focusing on the influence of different spectra acquisition parameters on lignin quantification was carried out. Spectral data acquired on moving woodchips were found to increase the representativeness of the spectral measurements leading to improvements in model performance.

    The present thesis demonstrates the potential of developing NIRS-based soft-sensors for characterization of biomass properties. The on-line installation of such sensors in an industrial setting can enable feed-forward process control, diagnostics and optimization.

    Ladda ner fulltext (pdf)
    fulltext
  • 10.
    Skvaril, Jan
    et al.
    Mälardalens högskola, Akademin för ekonomi, samhälle och teknik, Framtidens energi.
    Avelin, Anders
    Mälardalens högskola, Akademin för ekonomi, samhälle och teknik, Framtidens energi.
    Sandberg, Jan
    Mälardalens högskola, Akademin för ekonomi, samhälle och teknik, Framtidens energi.
    Dahlquist, Erik
    Mälardalens högskola, Akademin för ekonomi, samhälle och teknik, Framtidens energi.
    The experimental study of full-scale biomass-fired bubbling fluidized bed boiler2014Ingår i: Energy Procedia, ISSN 1876-6102, E-ISSN 1876-6102, Vol. 61, s. 643-647Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    This paper presents experimental data concerning combustion characteristics of full-scale biomass-fired bubbling fluidized bed (BFB) steam boiler with a thermal output of 31 MW. The purpose of the experimental measurements is to show how the values of selected combustion parameters vary in reality depending on measurement position. Experimentation involves specifically a determination of combustion gas temperature and concentration of gas species i.e. O2, CO2, CO and NOX at different positions in the furnace and the flue gas trains. Character of results from the furnace indicates the intermediate stage of thermochemical reactions. Increased levels of CO close to the wall have been found, this may be indicating reducing atmosphere and thereby increased corrosion risk. Results from flue gas trains demonstrate that behavior there is related to the fluid dynamics and heat transfer, the temperature is too low for further combustion reactions. Results show great variations among measured values of all measurands depending on a distance along the line from the wall to the center of the boiler. The measurements from permanently installed fixed sensors are not giving value representing average conditions, but overall profiles can be correlated to online measurements from fixed sensors.

    Ladda ner fulltext (pdf)
    fulltext
  • 11.
    Skvaril, Jan
    et al.
    Mälardalens högskola, Akademin för ekonomi, samhälle och teknik, Framtidens energi.
    Kyprianidis, Konstantinos
    Mälardalens högskola, Akademin för ekonomi, samhälle och teknik, Framtidens energi.
    Avelin, Anders
    Mälardalens högskola, Akademin för ekonomi, samhälle och teknik, Framtidens energi.
    Odlare, Monica
    Mälardalens högskola, Akademin för ekonomi, samhälle och teknik, Framtidens energi.
    Dahlquist, Erik
    Mälardalens högskola, Akademin för ekonomi, samhälle och teknik, Framtidens energi.
    Application of Near Infrared Spectroscopy for Rapid Characterization of Feedstock Material in Pulp and Paper Industry2015Ingår i: Book of abstracts, 2015Konferensbidrag (Refereegranskat)
    Abstract [en]

    Pulp digesters can be continuous or batch reactors with significant residence time which are fed with woodchips and cooking chemicals. They deliver the pulp-fibers that are used in the production of paper, as well as black liquor that is combusted in the chemical recovery boiler. The possibility to measure what is happening inside the digester is limited. The most important quality properties of the feedstock material is content of lignin, which is being dissolved during the process, and related material reactivity. Pulp quality after the process is measured by Kappa number which is a measure of residual lignin in the pulp. One of the biggest challenges in pulp production process is the great variability in feedstock material properties. If the process is not adjusted by well-timed and appropriate operational control measures i.e. control of inlet and outlet flows and setting of the cooking recipe, it will result in the large variations in Kappa number, lower fiber quality or excess use of environmentally harmful cooking chemicals. This becomes particularly important during the swing between softwood and hardwood as part of meeting the final paper product quality requirements. Therefore, a rapid method that is capable of continuous feedstock material characterization is required.Near infrared (NIR) spectroscopy can be used for non-destructive characterization of the feedstock material. In this study, both Fourier transform and grating NIR spectrophotometers were used for NIR absorbance spectra acquisition. Each spectrum was recorded in the range between 700 and 2500 nm. During the calibration of spectra of various wood species with known lignin content, wood samples were placed on a tray so that the tray may move horizontally in a reciprocating manner underneath the sensor while maintaining the constant distance between the sensor and sample. This was done in order to simulate the movement of a real conveyor belt as used for transporting feedstock to the digester. In the on-line application the NIR meter is situated above the conveyor belt that wood up to the digester.Spectral data were pretreated with different methods such as normalization, scatter correction, smoothing, first and second derivative (Savitzky-Golay algorithm), selection of different spectral ranges and its combinations. Mathematical models to estimate lignin content were constructed using Partial Least Square Regression (PLS-R) and Principle component regression (PCR) statistical methods. Response data for model build-up were determined in the chemical laboratory according to standardized procedures including test repetitions. Different combinations of NIR instrument used, pre-treatment methods and statistical methods were evaluated in order to find the model with the best prediction performance.Results are promising and demonstrate that it is possible to characterize the lignin content and reactivity of the feedstock material by NIR spectrophotometers with reasonable prediction model performance. Improved prediction can be obtained if only selected spectral ranges are included as an input for statistical modelling; similarly using derivatives is better than using the raw spectrum. In the next step, developed statistical models for rapid lignin content prediction will be used as a feed-forward input for dynamic process control.

    Ladda ner (pdf)
    attachment
  • 12.
    Skvaril, Jan
    et al.
    Mälardalens högskola, Akademin för ekonomi, samhälle och teknik, Framtidens energi.
    Kyprianidis, Konstantinos
    Mälardalens högskola, Akademin för ekonomi, samhälle och teknik, Framtidens energi.
    Avelin, Anders
    Mälardalens högskola, Akademin för ekonomi, samhälle och teknik, Framtidens energi.
    Odlare, Monica
    Mälardalens högskola, Akademin för ekonomi, samhälle och teknik, Framtidens energi.
    Dahlquist, Erik
    Mälardalens högskola, Akademin för ekonomi, samhälle och teknik, Framtidens energi.
    Effect of wood chip moving velocity on NIR spectra acquisition and model calibration for lignin quantificationManuskript (preprint) (Övrigt vetenskapligt)
  • 13.
    Skvaril, Jan
    et al.
    Mälardalens högskola, Akademin för ekonomi, samhälle och teknik, Framtidens energi.
    Kyprianidis, Konstantinos
    Mälardalens högskola, Akademin för ekonomi, samhälle och teknik, Framtidens energi.
    Avelin, Anders
    Mälardalens högskola, Akademin för ekonomi, samhälle och teknik, Framtidens energi.
    Odlare, Monica
    Mälardalens högskola, Akademin för ekonomi, samhälle och teknik, Framtidens energi.
    Dahlquist, Erik
    Mälardalens högskola, Akademin för ekonomi, samhälle och teknik, Framtidens energi.
    Fast Determination of Fuel Properties in Solid Biofuel Mixtures by Near Infrared Spectroscopy2017Ingår i: Energy Procedia, ISSN 1876-6102, E-ISSN 1876-6102, Vol. 105, s. 1309-1317Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    This paper focuses on the characterization of highly variable biofuel properties such as moisture content, ash content and higher heating value by near-infrared (NIR) spectroscopy. Experiments were performed on different biofuel sample mixtures consisting of stem wood chips, forest residue chips, bark, sawdust, and peat. NIR scans were performed using a Fourier transform NIR instrument, and reference values were obtained according to standardized laboratory methods. Spectral data were pre-processed by Multiplicative scatter correction correcting light scattering and change in a path length for each sample. Multivariate calibration was carried out employing Partial least squares regression while absorbance values from full NIR spectral range (12,000–4000 cm-1), and reference values were used as inputs. It was demonstrated that different solid biofuel properties can be measured by means of NIR spectroscopy. The accuracy of the models is satisfactory for industrial implementation towards improved process control. 

  • 14.
    Skvaril, Jan
    et al.
    Mälardalens högskola, Akademin för ekonomi, samhälle och teknik, Framtidens energi.
    Kyprianidis, Konstantinos
    Mälardalens högskola, Akademin för ekonomi, samhälle och teknik, Framtidens energi.
    Avelin, Anders
    Mälardalens högskola, Akademin för ekonomi, samhälle och teknik, Framtidens energi.
    Odlare, Monica
    Mälardalens högskola, Akademin för ekonomi, samhälle och teknik, Framtidens energi.
    Dahlquist, Erik
    Mälardalens högskola, Akademin för ekonomi, samhälle och teknik, Framtidens energi.
    Fast Determination of Lignin Content in Feedstock Material for Pulping Process Monitoring and Optimization2015Ingår i: ICAVS 8 - Abstracts poster, 2015, s. 556-557Konferensbidrag (Refereegranskat)
    Abstract [en]

    Pulping process is delivering pulp fibers which are further used in the production of paper. The reactor is fed with feedstock material in the form of wood chips. Moreover, cooking chemicals are brought at several points into the reactor. Previous studies have shown that the knowledge of the feedstock material properties which are highly variable is limited. One of the most important parameters is the lignin content, which has to be dissolved, this requires a significant residence time. The residual lignin in the resulting pulp after the process is measured in the form of Kappa number. Inappropriate application of cooking chemicals could lead to large variations in the Kappa number, low fiber quality and other issues. Therefore continuous characterization of the feedstock material is required. One of the available methods for nondestructive characterization of feedstock material is NIR spectroscopy. Presented study is conducted in order to assess the possibility of determining lignin content using NIR method. The spectroscopy workflow consist of four major steps i.e. sample preparation, spectral data acquisition, data pre-processing and multivariate calibration. We used test samples from 13 different tree species, which were tested in the form of wood chips, pulverized wood and mixture of both. Acquired spectral data were pre-processed mainly by second derivative and standard normal variate transformation. PLS regression with full cross validation was used for the development of a calibration model based on selected wavelengths. Acquisition of reference variable has been done according to standardized procedures and it represents the total amount of lignin in the sample.

    The results of lignin characterization in feedstock material by NIR are very promising. The resulting PLS regressionmodel includes 2-factors and uses 16 predicting variables, resulting in R2 = 0,975, RMSE = 0,885 wt%. In the next step, presented work will be improved by applying large amount of samples, independent validation data set and by simulation of conveyor belt movements. The objective of this research is to test the NIR method at a real pulp digester, in order to improve monitoring andoptimization of the process. Furthermore, continuous characterization of the feedstock materials is intended to be used for the improvement of the control process. The measured lignin content will be compared to the content calculated within the pulp digester physical model and the Kappa number. This will be used for improving the digester physical model accuracy and as an input to advanced model based control, where the correlation will be made not only to lignin content but also with the feedstock material reactivity.

    Ladda ner (pdf)
    attachment
  • 15.
    Skvaril, Jan
    et al.
    Mälardalens högskola, Akademin för ekonomi, samhälle och teknik, Framtidens energi.
    Kyprianidis, Konstantinos
    Mälardalens högskola, Akademin för ekonomi, samhälle och teknik, Framtidens energi.
    Avelin, Anders
    Mälardalens högskola, Akademin för ekonomi, samhälle och teknik, Framtidens energi.
    Odlare, Monica
    Mälardalens högskola, Akademin för ekonomi, samhälle och teknik, Framtidens energi.
    Dahlquist, Erik
    Mälardalens högskola, Akademin för ekonomi, samhälle och teknik, Framtidens energi.
    Multivariate analysis models for wood properties combined with Open Modelica model for process performance monitoring2015Ingår i: IFAC Proceedings Volumes (IFAC-PapersOnline), 2015, Vol. 48:1, s. 898-899Konferensbidrag (Övrig (populärvetenskap, debatt, mm))
    Abstract [en]

    To perform advanced model based control it is important to know what is fed into a system such as a waste or biomass fired boiler or a pulp digester. In this paper, we present correlations between the lignin content of different types of wood chips and their Near-infrared (NIR) spectra. The Principal Component Regression (PCR) method is used for deriving the correlation, as well as selecting certain wave lengths. Analysis is made including different parts of the spectra in the wave length range 700 – 2500 nm. The model is then used as input to an Open Modelica pulp digester model to tune the reactivity constant of the dissolution of lignin. The lignin content of wood-chips is determined on-line through the NIR measurement at the feed to the digester. Simulations are carried out to determine the content of residual lignin on fibers at the exit (continuous digester) or at the end of a cook (batch digester). By comparing the deviation between predicted values and actual measured values the reactivity constant of the lignin is determined. The regression can be made to the NIR spectrum aside of the lignin content as such. The original content of lignin together with reactivity may then be used for optimized on-line control of the digester. It can also be used for diagnostic purposes with regard to process issues like hang-ups or channeling, as well as possible sensor faults and data reconciliation.

  • 16.
    Skvaril, Jan
    et al.
    Mälardalens högskola, Akademin för ekonomi, samhälle och teknik, Framtidens energi.
    Kyprianidis, Konstantinos
    Mälardalens högskola, Akademin för ekonomi, samhälle och teknik, Framtidens energi.
    Avelin, Anders
    Mälardalens högskola, Akademin för ekonomi, samhälle och teknik, Framtidens energi.
    Odlare, Monica
    Mälardalens högskola, Akademin för ekonomi, samhälle och teknik, Framtidens energi.
    Dahlquist, Erik
    Mälardalens högskola, Akademin för ekonomi, samhälle och teknik, Framtidens energi.
    Rapid Determination of Selected Compounds in Waste-based Fuel by Near Infrared Spectroscopy2015Ingår i: Book of abstracts, 2015Konferensbidrag (Refereegranskat)
    Abstract [en]

    Composition of the waste-based fuel intended for incineration has substantial effect on combustion process performance and formation of environmentally harmful emissions. Fuel composition vary significantly depending on the material source, waste sorting and recycling procedures and other waste pretreatment methods. In general, it typically contains paper, plastics, wood, textile, other organic material and further undesired substances including glass and metals. The knowledge of actual composition of the material fed into the boiler is limited to the direct or indirect continuous moisture content measurements and periodic fuel sampling providing elementary composition. This information is not sufficient for process control and performance optimization, particularly when considering strongly heterogeneous fuel feed. Therefore a rapid and reliable technique for fuel characterization is needed.The work presented here is focused to the quantitative determination of selected plastic materials and glass content. Incomplete combustion of different plastics may lead to the formation of carbon monoxide, hydrogen-cyanides, acid compounds and aromatic hydrocarbons etc. If the waste contains chlorine then highly chlorinated polycyclic compounds such as dioxins and furans may be formed. Plastics often contain flame retardants which can also contribute to production of harmful emissions. On the other hand, the highly corrosive deposits of alkali chlorides and other compounds may be formed on the heat exchangers, this lowers the heat transfer and boiler efficiency and decrease life-time of the equipment. Moreover, increased content of glass in the fuel supports the formation of agglomerates in the fuel bed, defluidization of the bed or ash removal problems which result in malfunction or failure of the combustion equipment.Near infrared (NIR) spectroscopy can be used for non-destructive quantitative determination of plastics and glass in waste-based fuel. Experimental work was performed on two types of spectrophotometers i.e. grating and Fourier transform instruments. Samples of known content of glass and different plastics were placed on a moving tray that reciprocated horizontally back and forth underneath the NIR sensor. This was done in order to replicate online application where the NIR spectrophotometer is places above the conveyor belt that transport the fuel to the boiler.Spectra were recorded in the range between 700 and 2500 nm. Acquired spectral data were pretreated with different methods such as normalization, scatter correction, smoothing, first and second derivative (Savitzky-Golay algorithm), selection of different spectral ranges and its combinations. Mathematical models to estimate content of glass and different plastics were constructed using Partial Least Square Regression (PLS-R) and Principle component regression (PCR) statistical methods. Different combinations of spectrophotometer type, pre-treatment methods and statistical methods were evaluated in order to find the model with the best prediction performance.Results prove the potential of the method to quantitatively determine the content of different types of plastics as well as glass with reasonable prediction accuracy. The ultimate goal of this research is to test the method at a real industrial boiler in order to improve process monitoring and control.

    Ladda ner (pdf)
    attachment
  • 17.
    Skvaril, Jan
    et al.
    Mälardalens högskola, Akademin för ekonomi, samhälle och teknik, Framtidens energi.
    Kyprianidis, Konstantinos
    Mälardalens högskola, Akademin för ekonomi, samhälle och teknik, Framtidens energi.
    Avelin, Anders
    Mälardalens högskola, Akademin för ekonomi, samhälle och teknik, Framtidens energi.
    Odlare, Monica
    Mälardalens högskola, Akademin för ekonomi, samhälle och teknik, Framtidens energi.
    Dahlquist, Erik
    Mälardalens högskola, Akademin för ekonomi, samhälle och teknik, Framtidens energi.
    Utilization of Near Infrared (NIR) Spectrometry for Detection of Glass in the Waste-based Fuel2015Ingår i: Energy Procedia, ISSN 1876-6102, E-ISSN 1876-6102, Vol. 75, s. 734-741Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    This paper presents the results of experimental measurements and multivariate statistical modeling concerning detection of soda-lime glass using near infrared (NIR) spectrometry technique. The purpose is to test if the glass is quantitatively detectable in a waste-based material and to assess what method of spectral data pretreatment is the most suitable in order to develop prediction models. The experiments were performed on six test samples containing a specific amount of glass distributed in background material. Pretreatment methods such as normalization and first and second derivatives were applied on the acquired absorbance spectral data. Principal component analysis (PCA) was employed in order to describe the relationship between pretreated data and the amount of glass in the test samples. Subsequently, principal component regression (PCR) was utilized for the development of prediction models. The results from the models show strong correlation between the pretreated data and the glass content. The most promising results were obtained from the model based on 1st derivative pretreatment when only absorbance spectral data from selected wavelengths are included. 

  • 18.
    Skvaril, Jan
    et al.
    Mälardalens högskola, Akademin för ekonomi, samhälle och teknik, Framtidens energi.
    Kyprianidis, Konstantinos
    Mälardalens högskola, Akademin för ekonomi, samhälle och teknik, Framtidens energi.
    Avelin, Anders
    Mälardalens högskola, Akademin för ekonomi, samhälle och teknik, Framtidens energi.
    Sandberg, Jan
    Mälardalens högskola, Akademin för ekonomi, samhälle och teknik, Framtidens energi.
    Erik, Dahlquist
    Mälardalens högskola, Akademin för ekonomi, samhälle och teknik, Framtidens energi.
    Experimental investigation of part load operation of a full-scale biomass-fired fluidized bed boilerManuskript (preprint) (Övrigt vetenskapligt)
  • 19.
    Skvaril, Jan
    et al.
    Mälardalens högskola, Akademin för ekonomi, samhälle och teknik, Framtidens energi.
    Kyprianidis, Konstantinos
    Mälardalens högskola, Akademin för ekonomi, samhälle och teknik, Framtidens energi.
    Dahlquist, Erik
    Mälardalens högskola, Akademin för ekonomi, samhälle och teknik, Framtidens energi.
    Applications of near-infrared spectroscopy (NIRS) in biomass energy conversion processes: A review2017Ingår i: Applied spectroscopy reviews (Softcover ed.), ISSN 0570-4928, E-ISSN 1520-569X, Vol. 52, nr 8, s. 675-728Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Biomass used in energy conversion processes is typically characterized by high variability, making its utilization challenging. Therefore, there is a need for a fast and non-destructive method to determine feedstock/product properties and directly monitor process reactors. The near-infrared spectroscopy (NIRS) technique together with advanced data analysis methods offers a possible solution. This review focuses on the introduction of the NIRS method and its recent applications to physical, thermochemical, biochemical and physiochemical biomass conversion processes represented mainly by pelleting, combustion, gasification, pyrolysis, as well as biogas, bioethanol, and biodiesel production. NIRS has been proven to be a reliable and inexpensive method with a great potential for use in process optimization, advanced control, or product quality assurance.

  • 20.
    Winn, Olivia
    et al.
    Mälardalens högskola.
    Sivaram, Kiran Thekkemadathil
    Mälardalens högskola.
    Aslanidou, Ioanna
    Mälardalens högskola, Akademin för ekonomi, samhälle och teknik, Framtidens energi.
    Skvaril, Jan
    Mälardalens högskola, Akademin för ekonomi, samhälle och teknik, Framtidens energi.
    Kyprianidis, Konstantinos
    Mälardalens högskola, Akademin för ekonomi, samhälle och teknik, Framtidens energi.
    Near-infrared spectral measurements and multivariate analysis for predicting glass contamination of refuse-derived fuel2017Ingår i: Energy Procedia, ISSN 1876-6102, E-ISSN 1876-6102, Vol. 142, s. 943-949Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    This paper investigates how glass contamination in refuse-derived fuel can be quantitatively detected using near-infrared spectroscopy. Near-infrared spectral data of glass in four different background materials were collected, each material chosen to represent a main component in municipal solid waste; actual refuse-derived fuel was not tested. The resulting spectra were pre- processed and used to develop multi-variate predictive models using partial least squares regression. It was shown that predictive models for coloured glass content are reasonably accurate, while models for mixed glass or clear glass content are not; the validated model for coloured glass content had a coefficient of determination of 0.83 between the predicted and reference data, and a root- mean-square error of validation of 0.64. The methods investigated in this paper show potential in predicting coloured glass content in different types of background material, but a different approach would be needed for predicting mixed type glass contamination in refuse-derived fuel. 

1 - 20 av 20
RefereraExporteraLänk till träfflistan
Permanent länk
Referera
Referensformat
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Annat format
Fler format
Språk
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Annat språk
Fler språk
Utmatningsformat
  • html
  • text
  • asciidoc
  • rtf