Exergo-ecological evaluation of heat exchanger
Thermodynamic optimization of thermal devices requires information about the influence of operational and structural parameters on its behaviour. The interconnections among parameters can be estimated by tools such as CFD, experimental statistic of the deviceetc. Despite precise and compreh...
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VINCA Institute of Nuclear Sciences
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doaj-3a2b0a1f162142d5af0a99ee9c00f7692021-01-02T01:09:58ZengVINCA Institute of Nuclear SciencesThermal Science0354-98362014-01-0118385386210.2298/TSCI1403853S0354-98361403853SExergo-ecological evaluation of heat exchangerStanek Wojciech0Czarnowska Lucyna1Szczygiel Ireneusz2Rojczyk Marek3Institute of Thermal Technology, Silesian University of Technology, Gliwice, PolandInstitute of Thermal Technology, Silesian University of Technology, Gliwice, PolandInstitute of Thermal Technology, Silesian University of Technology, Gliwice, PolandInstitute of Thermal Technology, Silesian University of Technology, Gliwice, PolandThermodynamic optimization of thermal devices requires information about the influence of operational and structural parameters on its behaviour. The interconnections among parameters can be estimated by tools such as CFD, experimental statistic of the deviceetc. Despite precise and comprehensive results obtained by CFD, the time of computations is relatively long. This disadvantage often cannot be accepted in case of optimization as well as online control of thermal devices. As opposed to CFD the neural network or regression is characterized by short computational time, but does not take into account any physical phenomena occurring in the considered process. The CFD model of heat exchanger was built using commercial package Fluent/Ansys. The empirical model of heat exchanger has been assessed by regression and neural networks based on the set of pseudo-measurements generated by the exact CFD model. In the paper, the usage of the developed empirical model of heat exchanger for the minimisation of TEC is presented. The optimisationconcerns operational parameters of heat exchanger. The TEC expresses the cumulative exergy consumption of non-renewable resources. The minimization of the TEC is based on the objective function formulated by Szargut. However, the authors extended the classical TEC by the introduction of the exergy bonus theory proposed by Valero. The TEC objective function fulfils the rules of life cycle analysis because it contains the investment expenditures (measured by the cumulative exergy consumption of non-renewable natural resources), the operation of devices and the final effects of decommissioning the installation.http://www.doiserbia.nb.rs/img/doi/0354-9836/2014/0354-98361403853S.pdfthermo-ecological costheat exchangerCFD modellingoptimizationneural networks |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Stanek Wojciech Czarnowska Lucyna Szczygiel Ireneusz Rojczyk Marek |
spellingShingle |
Stanek Wojciech Czarnowska Lucyna Szczygiel Ireneusz Rojczyk Marek Exergo-ecological evaluation of heat exchanger Thermal Science thermo-ecological cost heat exchanger CFD modelling optimization neural networks |
author_facet |
Stanek Wojciech Czarnowska Lucyna Szczygiel Ireneusz Rojczyk Marek |
author_sort |
Stanek Wojciech |
title |
Exergo-ecological evaluation of heat exchanger |
title_short |
Exergo-ecological evaluation of heat exchanger |
title_full |
Exergo-ecological evaluation of heat exchanger |
title_fullStr |
Exergo-ecological evaluation of heat exchanger |
title_full_unstemmed |
Exergo-ecological evaluation of heat exchanger |
title_sort |
exergo-ecological evaluation of heat exchanger |
publisher |
VINCA Institute of Nuclear Sciences |
series |
Thermal Science |
issn |
0354-9836 |
publishDate |
2014-01-01 |
description |
Thermodynamic optimization of thermal devices requires information about the
influence of operational and structural parameters on its behaviour. The
interconnections among parameters can be estimated by tools such as CFD,
experimental statistic of the deviceetc. Despite precise and comprehensive
results obtained by CFD, the time of computations is relatively long. This
disadvantage often cannot be accepted in case of optimization as well as
online control of thermal devices. As opposed to CFD the neural network or
regression is characterized by short computational time, but does not take
into account any physical phenomena occurring in the considered process. The
CFD model of heat exchanger was built using commercial package Fluent/Ansys.
The empirical model of heat exchanger has been assessed by regression and
neural networks based on the set of pseudo-measurements generated by the
exact CFD model. In the paper, the usage of the developed empirical model of
heat exchanger for the minimisation of TEC is presented. The
optimisationconcerns operational parameters of heat exchanger. The TEC
expresses the cumulative exergy consumption of non-renewable resources. The
minimization of the TEC is based on the objective function formulated by
Szargut. However, the authors extended the classical TEC by the introduction
of the exergy bonus theory proposed by Valero. The TEC objective function
fulfils the rules of life cycle analysis because it contains the investment
expenditures (measured by the cumulative exergy consumption of non-renewable
natural resources), the operation of devices and the final effects of
decommissioning the installation. |
topic |
thermo-ecological cost heat exchanger CFD modelling optimization neural networks |
url |
http://www.doiserbia.nb.rs/img/doi/0354-9836/2014/0354-98361403853S.pdf |
work_keys_str_mv |
AT stanekwojciech exergoecologicalevaluationofheatexchanger AT czarnowskalucyna exergoecologicalevaluationofheatexchanger AT szczygielireneusz exergoecologicalevaluationofheatexchanger AT rojczykmarek exergoecologicalevaluationofheatexchanger |
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