The Experts below are selected from a list of 94944 Experts worldwide ranked by ideXlab platform
Julien Ramousse - One of the best experts on this subject based on the ideXlab platform.
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optimization of thermoelectric heat pumps by Operating Condition management and heat exchanger design
Energy Conversion and Management, 2012Co-Authors: Benjamin David, Julien RamousseAbstract:Abstract This paper introduces an optimization method for improving thermoelectric heat pump performance by Operating Condition management of the thermoelectric modules (TEMs) and design optimization of the heat exchangers linked to the TEMs. The device studied, corresponding to an original configuration of the thermoelectric heat pump, comprises two commercial thermoelectric modules and two mini-channel heat sinks through which water flows, in contact with both sides of the TEMs. The objective function is the maximization of the device’s coefficient of performance (COP), including the electrical and mechanical consumption of the thermoelectric modules and the circulating auxiliaries. First, the optimization variables are the number and the diameter of mini-channels, and the mass flows for both heat sinks (hot and cold sides). The results show that similar results are obtained by minimization of the entropy generation in the device. Finally, the hot thermal power demand is included in the optimization variables for complete optimization of the device. The results of full optimization converge with those obtained with the previous partial optimization.
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Optimization of thermoelectric heat pumps by Operating Condition management and heat exchanger design
Energy Conversion and Management, 2012Co-Authors: Benjamin David, Julien Ramousse, Lingai LuoAbstract:This paper introduces an optimization method for improving thermoelectric heat pump performance by Operating Condition management of the thermoelectric modules (TEMs) and design optimization of the heat exchangers linked to the TEMs. The device studied, corresponding to an original configuration of the thermoelectric heat pump, comprises two commercial thermoelectric modules and two mini-channel heat sinks through which water flows, in contact with both sides of the TEMs. The objective function is the maximization of the device's coefficient of performance (COP), including the electrical and mechanical consumption of the thermoelectric modules and the circulating auxiliaries. First, the optimization variables are the number and the diameter of mini-channels, and the mass flows for both heat sinks (hot and cold sides). The results show that similar results are obtained by minimization of the entropy generation in the device. Finally, the hot thermal power demand is included in the optimization variables for complete optimization of the device. The results of full optimization converge with those obtained with the previous partial optimization. © 2012 Elsevier Ltd. All rights reserved.
Benjamin David - One of the best experts on this subject based on the ideXlab platform.
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optimization of thermoelectric heat pumps by Operating Condition management and heat exchanger design
Energy Conversion and Management, 2012Co-Authors: Benjamin David, Julien RamousseAbstract:Abstract This paper introduces an optimization method for improving thermoelectric heat pump performance by Operating Condition management of the thermoelectric modules (TEMs) and design optimization of the heat exchangers linked to the TEMs. The device studied, corresponding to an original configuration of the thermoelectric heat pump, comprises two commercial thermoelectric modules and two mini-channel heat sinks through which water flows, in contact with both sides of the TEMs. The objective function is the maximization of the device’s coefficient of performance (COP), including the electrical and mechanical consumption of the thermoelectric modules and the circulating auxiliaries. First, the optimization variables are the number and the diameter of mini-channels, and the mass flows for both heat sinks (hot and cold sides). The results show that similar results are obtained by minimization of the entropy generation in the device. Finally, the hot thermal power demand is included in the optimization variables for complete optimization of the device. The results of full optimization converge with those obtained with the previous partial optimization.
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Optimization of thermoelectric heat pumps by Operating Condition management and heat exchanger design
Energy Conversion and Management, 2012Co-Authors: Benjamin David, Julien Ramousse, Lingai LuoAbstract:This paper introduces an optimization method for improving thermoelectric heat pump performance by Operating Condition management of the thermoelectric modules (TEMs) and design optimization of the heat exchangers linked to the TEMs. The device studied, corresponding to an original configuration of the thermoelectric heat pump, comprises two commercial thermoelectric modules and two mini-channel heat sinks through which water flows, in contact with both sides of the TEMs. The objective function is the maximization of the device's coefficient of performance (COP), including the electrical and mechanical consumption of the thermoelectric modules and the circulating auxiliaries. First, the optimization variables are the number and the diameter of mini-channels, and the mass flows for both heat sinks (hot and cold sides). The results show that similar results are obtained by minimization of the entropy generation in the device. Finally, the hot thermal power demand is included in the optimization variables for complete optimization of the device. The results of full optimization converge with those obtained with the previous partial optimization. © 2012 Elsevier Ltd. All rights reserved.
Lingai Luo - One of the best experts on this subject based on the ideXlab platform.
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Optimization of thermoelectric heat pumps by Operating Condition management and heat exchanger design
Energy Conversion and Management, 2012Co-Authors: Benjamin David, Julien Ramousse, Lingai LuoAbstract:This paper introduces an optimization method for improving thermoelectric heat pump performance by Operating Condition management of the thermoelectric modules (TEMs) and design optimization of the heat exchangers linked to the TEMs. The device studied, corresponding to an original configuration of the thermoelectric heat pump, comprises two commercial thermoelectric modules and two mini-channel heat sinks through which water flows, in contact with both sides of the TEMs. The objective function is the maximization of the device's coefficient of performance (COP), including the electrical and mechanical consumption of the thermoelectric modules and the circulating auxiliaries. First, the optimization variables are the number and the diameter of mini-channels, and the mass flows for both heat sinks (hot and cold sides). The results show that similar results are obtained by minimization of the entropy generation in the device. Finally, the hot thermal power demand is included in the optimization variables for complete optimization of the device. The results of full optimization converge with those obtained with the previous partial optimization. © 2012 Elsevier Ltd. All rights reserved.
Chao Shang - One of the best experts on this subject based on the ideXlab platform.
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Monitoring of Operating Condition and Process Dynamics with Slow Feature Analysis
Dynamic Modeling of Complex Industrial Processes: Data-driven Methods and Application Research, 2018Co-Authors: Chao ShangAbstract:Latent variable (LV) models have been widely used in multivariate statistical process monitoring. However, whatever deviation from nominal Operating Condition is detected, an alarm is triggered based on classical monitoring methods. Consequently, they cannot distinguish real faults incurring dynamics anomalies from normal deviations in Operating Conditions. In this chapter, a new process monitoring strategy based on slow feature analysis (SFA) is proposed for the concurrent monitoring of Operating point deviations and process dynamics anomalies. Slow features as LVs are developed to describe slowly varying dynamics, yielding improved physical interpretation. In addition to classical statistics for monitoring deviation from design Conditions, two novel indices are proposed to detect anomalies in process dynamics through the slowness of LVs. The proposed approach can distinguish whether normal changes in Operating Conditions or real faults occur. Two case studies show the validity of the SFA-based process monitoring approach.
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concurrent monitoring of Operating Condition deviations and process dynamics anomalies with slow feature analysis
Aiche Journal, 2015Co-Authors: Chao Shang, Fan Yang, Xiaolin Huang, Johan A K Suykens, Dexian HuangAbstract:Latent variable (LV) models have been widely used in multivariate statistical process monitoring. However, whatever deviation from nominal Operating Condition is detected, an alarm is triggered based on classical monitoring methods. Therefore, they fail to distinguish real faults incurring dynamics anomalies from normal deviations in Operating Conditions. A new process monitoring strategy based on slow feature analysis (SFA) is proposed for the concurrent monitoring of Operating point deviations and process dynamics anomalies. Slow features as LVs are developed to describe slowly varying dynamics, yielding improved physical interpretation. In addition to classical statistics for monitoring deviation from design Conditions, two novel indices are proposed to detect anomalies in process dynamics through the slowness of LVs. The proposed approach can distinguish whether the changes in Operating Conditions are normal or real faults occur. Two case studies show the validity of the SFA-based process monitoring approach. © 2015 American Institute of Chemical Engineers AIChE J, 61: 3666–3682, 2015
Dexian Huang - One of the best experts on this subject based on the ideXlab platform.
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concurrent monitoring of Operating Condition deviations and process dynamics anomalies with slow feature analysis
Aiche Journal, 2015Co-Authors: Chao Shang, Fan Yang, Xiaolin Huang, Johan A K Suykens, Dexian HuangAbstract:Latent variable (LV) models have been widely used in multivariate statistical process monitoring. However, whatever deviation from nominal Operating Condition is detected, an alarm is triggered based on classical monitoring methods. Therefore, they fail to distinguish real faults incurring dynamics anomalies from normal deviations in Operating Conditions. A new process monitoring strategy based on slow feature analysis (SFA) is proposed for the concurrent monitoring of Operating point deviations and process dynamics anomalies. Slow features as LVs are developed to describe slowly varying dynamics, yielding improved physical interpretation. In addition to classical statistics for monitoring deviation from design Conditions, two novel indices are proposed to detect anomalies in process dynamics through the slowness of LVs. The proposed approach can distinguish whether the changes in Operating Conditions are normal or real faults occur. Two case studies show the validity of the SFA-based process monitoring approach. © 2015 American Institute of Chemical Engineers AIChE J, 61: 3666–3682, 2015
