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  • 1.
    Aslanidou, Ioanna
    et al.
    Mälardalens högskola, Akademin för ekonomi, samhälle och teknik, Framtidens energi.
    Zaccaria, Valentina
    Mälardalens högskola, Akademin för ekonomi, samhälle och teknik, Framtidens energi.
    Pontika, E.
    Aristotle University of Thessaloniki, Thessaloniki, Greece.
    Zimmerman, Nathan
    Mälardalens högskola, Akademin för ekonomi, samhälle och teknik, Framtidens energi.
    Kalfas, A. I.
    Aristotle University of Thessaloniki, Thessaloniki, Greece.
    Kyprianidis, Konstantinos
    Mälardalens högskola, Akademin för ekonomi, samhälle och teknik, Framtidens energi.
    Teaching gas turbine technology to undergraduate students in Sweden2018Ingår i: Proceedings of the ASME Turbo Expo, American Society of Mechanical Engineers (ASME) , 2018, Vol. 6Konferensbidrag (Refereegranskat)
    Abstract [en]

    This paper addresses the teaching of gas turbine technology in a third-year undergraduate course in Sweden and the challenges encountered. The improvements noted in the reaction of the students and the achievement of the learning outcomes is discussed. The course, aimed at students with a broad academic education on energy, is focused on gas turbines, covering topics from cycle studies and performance calculations to detailed design of turbomachinery components. It also includes economic aspects during the operation of heat and power generation systems and addresses combined cycles as well as hybrid energy systems with fuel cells. The course structure comprises lectures from academics and industrial experts, study visits, and a comprehensive assignment. With the inclusion of all of these aspects in the course, the students find it rewarding despite the significant challenges encountered. An important contribution to the education of the students is giving them the chance, stimulation, and support to complete an assignment on gas turbine design. Particular attention is given on striking a balance between helping them find the solution to the design problem and encouraging them to think on their own. Feedback received from the students highlighted some of the challenges and has given directions for improvements in the structure of the course, particularly with regards to the course assignment. This year, an application developed for a mobile phone in the Aristotle University of Thessaloniki for the calculation of engine performance will be introduced in the course. The app will have a supporting role during discussions and presentations in the classroom and help the students better understand gas turbine operation. This is also expected to reduce the workload of the students for the assignment and spike their interest.

  • 2.
    Aslanidou, Ioanna
    et al.
    Mälardalens högskola, Akademin för ekonomi, samhälle och teknik, Framtidens energi.
    Zaccaria, Valentina
    Mälardalens högskola, Akademin för ekonomi, samhälle och teknik, Framtidens energi.
    Rahman, Moksadur
    Mälardalens högskola, Akademin för ekonomi, samhälle och teknik, Framtidens energi.
    Oostveen, Mark
    Micro Turbine Technology bv, Eindhoven, Netherlands.
    Olsson, Tomas
    Mälardalens högskola, Akademin för innovation, design och teknik, Inbyggda system. RISE SICS, Västerås, Sweden.
    Kyprianidis, Konstantinos
    Mälardalens högskola, Akademin för ekonomi, samhälle och teknik, Framtidens energi.
    Towards an Integrated Approach for Micro Gas Turbine Fleet Monitoring, Control and Diagnostics2018Konferensbidrag (Refereegranskat)
    Abstract [en]

    Real-time engine condition monitoring and fault diagnostics results in reduced operating and maintenance costs and increased component and engine life. Prediction of faults can change the maintenance model of a system from a fixed maintenance interval to a condition based maintenance interval, further decreasing the total cost of ownership of a system. Technologies developed for engine health monitoring and advanced diagnostic capabilities are generally developed for larger gas turbines, and generally focus on a single system; no solutions are publicly available for engine fleets. This paper presents a concept for fleet monitoring finely tuned to the specific needs of micro gas turbines. The proposed framework includes a physics-based model and a data-driven model with machine learning capabilities for predicting system behaviour, combined with a diagnostic tool for anomaly detection and classification. The integrated system will develop advanced diagnostics and condition monitoring for gas turbines with a power output under 100 kW.

  • 3.
    Campana, Pietro Elia
    et al.
    Mälardalens högskola, Akademin för ekonomi, samhälle och teknik, Framtidens energi.
    Li, Hailong
    Mälardalens högskola, Akademin för ekonomi, samhälle och teknik, Framtidens energi.
    Zaccaria, Valentina
    Mälardalens högskola, Akademin för ekonomi, samhälle och teknik, Framtidens energi.
    Zhang, Yang
    Stridh, Bengt
    Mälardalens högskola, Akademin för ekonomi, samhälle och teknik, Framtidens energi.
    Yan, Jinyue
    Mälardalens högskola, Akademin för ekonomi, samhälle och teknik, Framtidens energi.
    Flexibility Services Provided by Building Thermal Inertia2018Konferensbidrag (Refereegranskat)
  • 4.
    Cuneo, A.
    et al.
    Thermochemical Power Group, Università di Genova, Italy.
    Zaccaria, Valentina
    Mälardalens högskola, Akademin för ekonomi, samhälle och teknik, Framtidens energi.
    Tucker, D.
    U.S. DOE National Energy Technology Laboratory, Morgantown, United States.
    Sorce, A.
    Thermochemical Power Group, Università di Genova, Italy.
    Gas turbine size optimization in a hybrid system considering SOFC degradation2018Ingår i: Applied Energy, ISSN 0306-2619, E-ISSN 1872-9118, Vol. 230, s. 855-864Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    The coupling of a pressurized solid oxide fuel cell (SOFC) and a gas turbine has been proven to result in extremely high efficiency and reduced emissions. The presence of the gas turbine can improve system durability compared to a standalone SOFC, because the turbomachinery can supply additional power as the fuel cell degrades to meet the power request. Since performance degradation is an obstacles to SOFC systems commercialization, the optimization of the hybrid system to mitigate SOFC degradation effects is of great interest. In this work, an optimization approach was used to innovatively study the effect of gas turbine size on system durability for a 400 kW fuel cell stack. A larger turbine allowed a bigger reduction in SOFC power before replacing the stack, but increased the initial capital investment and decreased the initial turbine efficiency. Thus, the power ratio between SOFC and gas turbine significantly influenced system economic results.

  • 5.
    Rahman, Moksadur
    et al.
    Mälardalens högskola, Akademin för ekonomi, samhälle och teknik, Framtidens energi.
    Zaccaria, Valentina
    Mälardalens högskola, Akademin för ekonomi, samhälle och teknik, Framtidens energi.
    Xin, Zhao
    Mälardalens högskola, Akademin för ekonomi, samhälle och teknik, Framtidens energi.
    Kyprianidis, Konstantinos
    Mälardalens högskola, Akademin för ekonomi, samhälle och teknik, Framtidens energi.
    Diagnostics-Oriented Modelling of Micro Gas Turbines for Fleet Monitoring and Maintenance Optimization2018Ingår i: Processes, ISSN 2227-9717, Vol. 6, nr 11Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    The market for the small-scale micro gas turbine is expected to grow rapidly in the coming years. Especially, utilization of commercial off-the-shelf components is rapidly reducing the cost of ownership and maintenance, which is paving the way for vast adoption of such units. However, to meet the high-reliability requirements of power generators, there is an acute need of a real-time monitoring system that will be able to detect faults and performance degradation, and thus allow preventive maintenance of these units to decrease downtime. In this paper, a micro gas turbine based combined heat and power system is modelled and used for development of physics-based diagnostic approaches. Different diagnostic schemes for performance monitoring of micro gas turbines are investigated.

  • 6.
    Rossi, I.
    et al.
    University of Genoa, Genova, Italy.
    Zaccaria, Valentina
    Mälardalens högskola, Akademin för ekonomi, samhälle och teknik, Framtidens energi.
    Traverso, A.
    University of Genoa, Genova, Italy.
    Advanced Control for Clusters of SOFC/Gas Turbine Hybrid Systems2018Ingår i: Journal of engineering for gas turbines and power, ISSN 0742-4795, E-ISSN 1528-8919, Vol. 140, nr 5, artikel-id 051703Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    The use of model predictive control (MPC) in advanced power systems can be advantageous in controlling highly coupled variables and optimizing system operations. Solid oxide fuel cell/gas turbine (SOFC/GT) hybrids are an example where advanced control techniques can be effectively applied. For example, to manage load distribution among several identical generation units characterized by different temperature distributions due to different degradation paths of the fuel cell stacks. When implementing an MPC, a critical aspect is the trade-off between model accuracy and simplicity, the latter related to a fast computational time. In this work, a hybrid physical and numerical approach was used to reduce the number of states necessary to describe such complex target system. The reduced number of states in the model and the simple framework allow real-time performance and potential extension to a wide range of power plants for industrial application, at the expense of accuracy losses, discussed in the paper. 

  • 7.
    Stenfelt, Mikael
    et al.
    Mälardalens högskola, Akademin för ekonomi, samhälle och teknik, Framtidens energi.
    Zaccaria, Valentina
    Mälardalens högskola, Akademin för ekonomi, samhälle och teknik, Framtidens energi.
    Kyprianidis, Konstantinos
    Mälardalens högskola, Akademin för ekonomi, samhälle och teknik, Framtidens energi.
    AUTOMATIC GAS TURBINE MATCHING SCHEME ADAPTATION FOR ROBUST GPA DIAGNOSTICS2019Ingår i: Proceedings of the ASME Turbo ExpoVolume 6, 2019, 2019, Vol. 6Konferensbidrag (Refereegranskat)
    Abstract [en]

    When performing gas turbine diagnostics using Gas Path Analysis (GPA), a convenient way of extracting the degradations is by feeding the measured data from a gas turbine to a well-tuned gas turbine performance code, which in turn calculates the deltas on the chosen health parameters matching the measured inputs. For this, a set of measured parameters must be matched with suitable health parameters, such as deltas on compressor and turbine efficiency and flow capacity.

    In aero engines, the number of sensors are in general limited due to cost and weight constraints and only the necessary sensors for safe engine operation are available. Some important sensors may have redundancy in case of a sensor loss but it is far from certain that this applies to all sensors available.

    If a sensor malfunctions by giving false or no values, the functions using the sensor will be negatively affected in some way causing them to either synthesize a fictive measurement, changing operating scheme, going into a degraded operating mode or shutting down parts or the whole process. If an onboard diagnostic algorithm fails due to sensor faults it will lead to a decrease in flight safety, thus there is a need for a robust system.

    This paper presents a strategy for automatic modifications of the gas turbine diagnostic matching scheme when sensors malfunction to ensure a robust function. When a sensor fault is detected and classified as malfunctioning, the gas turbine matching scheme is modified according to predefined rules. If possible, a redundant measurement replaces the faulty measurement. If not, the matching scheme will be modified by determining if any health parameters cannot be derived by the functional set of measurements and remove the least valuable health parameter while maintaining a working matching scheme for the remaining health parameters.

  • 8.
    Zaccaria, Valentina
    et al.
    U.S. Department of Energy, US.
    Branum, Zachary
    Arizona State University, USA.
    Tucker, David
    U.S. Department of Energy, US.
    Fuel Cell Temperature Control with a Pre-Combustor in SOFC Gas Turbine Hybrids during Load Changes2017Ingår i: Journal of electrochemical energy conversion and storage, ISSN 2381-6872, Vol. 14, s. 031006-031014Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    The use of high temperature fuel cells, such as Solid Oxide Fuel Cells (SOFCs), for power generation is considered a very efficient and clean solution to conservation of energy resources. When the SOFC is coupled with a gas turbine, the global system efficiency can go beyond 70% on natural gas LHV. However, durability of the ceramic material and system operability can be significantly penalized by thermal stresses due to temperature fluctuations and non-even temperature distributions. Thermal management of the cell during load following is therefore essential.The purpose of this work was to develop and test a pre-combustor model for real-time applications in hardware-based simulations, and to implement a control strategy to keep constant cathode inlet temperature during different operative conditions. The real-time model of the pre-combustor was incorporated into the existing SOFC model and tested in a hybrid system facility, where a physical gas turbine and hardware components were coupled with a cyber-physical fuel cell for flexible, accurate, and cost-reduced simulations.The control of the fuel flow to the pre-combustor was proven to be effective in maintaining a constant cathode inlet temperature during a step change in fuel cell load. With a 20 A load variation, the maximum temperature deviation from the nominal value was below 0.3% (3K). Temperature gradients along the cell were maintained below 10 K/cm. An efficiency analysis was performed in order to evaluate the impact of the pre-combustor on the overall system efficiency.

  • 9.
    Zaccaria, Valentina
    et al.
    Mälardalens högskola, Akademin för ekonomi, samhälle och teknik, Framtidens energi.
    Cuneo, Alessandra
    University of Genoa, Italy.
    Sorce, Alessandro
    University of Genoa, Italy.
    Influence of multiple degrading components on fuel cell gas turbine hybrid systems lifetime2018Ingår i: Proceedings of GPPS Forum 18 Global Power and Propulsion Society Zurich, 10th-12th January 2018, 2018Konferensbidrag (Refereegranskat)
    Abstract [en]

    Energy system reliability and operational cost depend highly on the performance degradation experienced by system components. In complex systems, degradation of each single component affects matching and interactions of different system parts. Gas turbine fuel cell hybrid systems combine two different technologies to produce power with an extremely high conversion efficiency. Severe performance decay over time currently limits high temperature fuel cells lifetime; although at a different rate, gas turbine engines also experience gradual deterioration phenomena such as erosion, corrosion, and creep. This work aims at evaluating, for the first time, the complex performance interaction between degrading components in a hybrid system. The effect of deterioration in gas turbine pressure ratio and efficiency on fuel cell performance was analyzed, and at the same time, the impact of the degrading fuel cell thermal output on turbine blade aging was modeled to estimate a remaining useful lifetime.

  • 10.
    Zaccaria, Valentina
    et al.
    Mälardalens högskola, Akademin för ekonomi, samhälle och teknik, Framtidens energi.
    Dik, Andreas
    Mälardalens högskola, Akademin för ekonomi, samhälle och teknik, Framtidens energi.
    Bitén, Nikolas
    Mälardalens högskola, Akademin för ekonomi, samhälle och teknik, Framtidens energi.
    Aslanidou, Ioanna
    Mälardalens högskola, Akademin för ekonomi, samhälle och teknik, Framtidens energi.
    Kyprianidis, Konstantinos
    Mälardalens högskola, Akademin för ekonomi, samhälle och teknik, Framtidens energi.
    Conceptual Design of a 3-Shaft Turbofan Engine with Reduced Fuel Consumption for 20252017Ingår i: Energy Procedia / [ed] Elsevier, 2017Konferensbidrag (Refereegranskat)
    Abstract [en]

    In the past decade, aircraft fuel burn has been continually decreased, mainly by improving thermal and propulsion efficiencies with consequent decrement in specific fuel consumption. In view of future emission specifications, the requirements for SFC in the forthcoming years are expected to become more stringent. In this paper, a preliminary design of a turbofan engine for entry in service in 2025 was performed. The design of a baseline 2010 EIS engine was improved according to 2025 specifications. A thermodynamic analysis was carried out to select optimal jet velocity ratio, pressure ratio, and temperatures with the goal of minimizing specific fuel consumption. A gas path layout was generated and an aerodynamic analysis was performed to optimize the engine stage by stage design. The optimization resulted in a 3-shaft turbofan jet engine with a 21% increase in fan diameter, a 2.2% increment in engine length, and a fuel burn improvement of 11% compared to the baseline engine, mainly due to an increment in propulsive efficiency. A sensitivity analysis was also conducted to highlight what the focus of technology development should be.

  • 11.
    Zaccaria, Valentina
    et al.
    Mälardalens högskola, Akademin för ekonomi, samhälle och teknik.
    Ferrari, Mario
    University of Genoa, Italy.
    Kyprianidis, Konstantinos
    Mälardalens högskola, Akademin för ekonomi, samhälle och teknik, Framtidens energi.
    Adaptive Control of Micro Gas Turbine for Engine Degradation Compensation2019Ingår i: Journal of engineering for gas turbines and power, ISSN 0742-4795, E-ISSN 1528-8919, Vol. 3Artikel i tidskrift (Refereegranskat)
  • 12.
    Zaccaria, Valentina
    et al.
    Mälardalens högskola, Akademin för ekonomi, samhälle och teknik, Framtidens energi.
    Rahman, Moksadur
    Mälardalens högskola, Akademin för ekonomi, samhälle och teknik, Framtidens energi.
    Aslanidou, Ioanna
    Mälardalens högskola, Akademin för ekonomi, samhälle och teknik, Framtidens energi.
    Kyprianidis, Konstantinos
    Mälardalens högskola, Akademin för ekonomi, samhälle och teknik, Framtidens energi.
    A review of information fusion methodsfor gas turbine diagnostics2019Ingår i: Sustainability, ISSN 2071-1050, E-ISSN 2071-1050, Vol. 11, nr 22, artikel-id 6202Artikel, forskningsöversikt (Refereegranskat)
    Abstract [en]

    The correct and early detection of incipient faults or severe degradation phenomena in gas turbine systems is essential for safe and cost-effective operations. A multitude of monitoring and diagnostic systems were developed and tested in the last few decades. The current computational capability of modern digital systems was exploited for both accurate physics-based methods and artificial intelligence or machine learning methods. However, progress is rather limited and none of the methods explored so far seem to be superior to others. One solution to enhance diagnostic systems exploiting the advantages of various techniques is to fuse the information coming from different tools, for example, through statistical methods. Information fusion techniques such as Bayesian networks, fuzzy logic, or probabilistic neural networks can be used to implement a decision support system. This paper presents a comprehensive review of information and decision fusion methods applied to gas turbine diagnostics and the use of probabilistic reasoning to enhance diagnostic accuracy. The different solutions presented in the literature are compared, and major challenges for practical implementation on an industrial gas turbine are discussed. Detecting and isolating faults in a system is a complex problem with many uncertainties, including the integrity of available information. The capability of different information fusion techniques to deal with uncertainty are also compared and discussed. Based on the lessons learned, new perspectives for diagnostics and a decision support system are proposed. 

  • 13.
    Zaccaria, Valentina
    et al.
    Mälardalens högskola, Akademin för ekonomi, samhälle och teknik, Framtidens energi.
    Stenfelt, Mikael
    Mälardalens högskola, Akademin för ekonomi, samhälle och teknik, Framtidens energi.
    Aslanidou, Ioanna
    Mälardalens högskola, Akademin för ekonomi, samhälle och teknik, Framtidens energi.
    Kyprianidis, Konstantinos
    Mälardalens högskola, Akademin för ekonomi, samhälle och teknik, Framtidens energi.
    Fleet monitoring and diagnostics framework based on digital twin of aero-engines2018Ingår i: Proceedings of the ASME Turbo Expo, American Society of Mechanical Engineers (ASME) , 2018, Vol. 6Konferensbidrag (Refereegranskat)
    Abstract [en]

    Monitoring aircraft performance in a fleet is fundamental to ensure optimal operation and promptly detect anomalies that can increase fuel consumption or compromise flight safety. Accurate failure detection and life prediction methods also result in reduced maintenance costs. The major challenges in fleet monitoring are the great amount of collected data that need to be processed and the variability between engines of the fleet, which requires adaptive models. In this paper, a framework for monitoring, diagnostics, and health management of a fleet of aircrafts is proposed. The framework consists of a multi-level approach: starting from thresholds exceedance monitoring, problematic engines are isolated, on which a fault detection system is then applied. Different methods for fault isolation, identification, and quantification are presented and compared, and the related challenges and opportunities are discussed. This conceptual strategy is tested on fleet data generated through a performance model of a turbofan engine, considering engine-to-engine and flight-to-flight variations and uncertainties in sensor measurements. Limitations of physics-based methods and machine learning techniques are investigated and the needs for fleet diagnostics are highlighted. 

  • 14.
    Zaccaria, Valentina
    et al.
    Mälardalens högskola, Akademin för ekonomi, samhälle och teknik, Framtidens energi.
    Stenfelt, Mikael
    Mälardalens högskola, Akademin för ekonomi, samhälle och teknik, Framtidens energi.
    Sjunnesson, Anna
    Siemens Industrial Turbomachinery AB, Sweden.
    Andreas, Hansson
    Siemens Industrial Turbomachinery AB, Sweden.
    Kyprianidis, Konstantinos
    Mälardalens högskola, Akademin för ekonomi, samhälle och teknik, Framtidens energi.
    A MODEL-BASED SOLUTION FOR GAS TURBINE DIAGNOSTICS: SIMULATIONS AND EXPERIMENTAL VERIFICATION2019Ingår i: Proceedings of the ASME Turbo ExpoVolume 6, 2019, 2019, artikel-id GT2019-90858Konferensbidrag (Refereegranskat)
    Abstract [en]

    Prompt detection of incipient faults and accurate monitoring of engine deterioration are key aspects for ensuring safe operations and planning a timely maintenance. Modern computing capabilities allow for more and more complex tools for engine monitoring and diagnostics. Nevertheless, an underlying physics-based approach is often preferable, because not only the “what” but also the “why” can be identified, providing an effective decision support tool to the service engineer. In this work, a physics-based adaptive model is used to evaluate performance deltas and correct the data to reference conditions (gas turbine load and ambient conditions), while a data-driven correlation algorithm identifies the most likely matches within a fault signatures database. Possible faults are ordered from the highest correlation in the decision support system and the most likely fault can be selected based on the number of occurrences and the associated correlation. Gradual engine degradation can also be monitored by displaying performance deltas trends during time. The diagnostics tool was tested on a validated performance model of a single-shaft industrial gas turbine and subsequently on experimental data. This paper presents the diagnostics system structure, the model adaptation scheme, and the results obtained from simulated and real fault data. Accurate fault isolation and severity identification were achieved in all cases, demonstrating the tool capability for decision support system.

  • 15.
    Zaccaria, Valentina
    et al.
    University of Genova, Italy.
    Traverso, Alberto
    University of Genova, Italy.
    Tucker, David
    U.S. Department of Energy, US.
    Advanced gas turbine hybrid power systems to improve SOFC economic viability2017Ingår i: Journal of the Global Power and Propulsion Society, ISSN 2515-3080, Vol. 1, s. 28-40Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Coupling a solid oxide fuel cell (SOFC) with a gas turbineprovides a substantial increment in system efficiency comparedto the separate technologies, which can potentiallyintroduce economic benefits and favor an early market penetrationof fuel cells. Currently, the economic viability of suchsystems is limited by fuel cell short lifetime due to a progressiveperformance degradation that leads to cell failure.Mitigating these phenomena would have a significant impacton system economic feasibility. In this study, the lifetime of astandalone, atmospheric SOFC system was compared to apressurized SOFC gas turbine hybrid and an economic analysiswas performed. In both cases, the power production wasrequired to be constant over time, with significantly differentresults for the two systems in terms of fuel cell operating life,system efficiency, and economic return. In the hybrid system,an extended fuel cell lifetime is achieved while maintaininghigh system efficiency and improving economic performance.In this work, the optimal power density was determined forthe standalone fuel cell in order to have the best economicperformance. Nevertheless, the hybrid system showed bettereconomic performance, and it was less affected by the stackcost.

  • 16.
    Zaccaria, Valentina
    et al.
    U.S. Department of Energy, United States.
    Tucker, David
    U.S. Department of Energy, United States.
    Traverso, Alberto
    University of Genoa, Italy.
    Transfer function development for SOFC/GT hybrid systems control using cold air bypass2016Ingår i: Applied Energy, ISSN 0306-2619, E-ISSN 1872-9118, Vol. 165, s. 695-706Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Fuel cell gas turbine hybrids present significant challenges in terms of system control because of the couplingof different time-scale phenomena. Hence, the importance of studying the integrated systemdynamics is critical. With the aim of safe operability and efficiency optimization, the cold air bypass valvewas considered an important actuator since it affects several key parameters and can be very effective incontrolling compressor surge. Two different tests were conducted using a cyber-physical approach. TheHybrid Performance (HyPer) facility couples gas turbine equipment with a cyber physical solid oxide fuelcell in which the hardware is driven by a numerical fuel cell model operating in real time. The tests wereperformed moving the cold air valve from the nominal position of 40% with a step of 15% up and down,while the system was in open loop, i.e. no control on turbine speed or inlet temperature. The effect of thevalve change on the system was analyzed and transfer functions were developed for several importantvariables such as cathode mass flow, total pressure drop and surge margin. Transfer functions can showthe response time of different system variables, and are used to characterize the dynamic response of theintegrated system. Opening the valve resulted in an immediate positive impact on pressure drop andsurge margin. A valve change also significantly affected fuel cell temperature, demonstrating that the coldair bypass can be used for thermal management of the cell.

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