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description Publicationkeyboard_double_arrow_right Article , Journal 2020 China (People's Republic of), Hong Kong, China (People's Republic of)Publisher:Elsevier BV Dominic C. Y. Foo; Haoshui Yu; Bingjian Zhang; Jingzheng Ren; Qinglin Chen; Chang He; Qiping Zhu; Qiping Zhu;handle: 10397/104148
Abstract Incorporation of closed wet cooling tower (CWCT) in the existing circulating water system has been recognized as a viable path to reduce water use in process industry. This paper introduces a specifically tailored framework based on model reductions for multiscale optimization of CWCT-based cooling water system considering environmental variations. An optimal design of experiment is performed for accurate approximation of the multivariate probability distributions by generating a finite set of samples over the entire input space. The probability distributions are propagated via multi-sample CFD simulations for constructing the physics-based and data-driven reduced models of CWCTs. Based on the developed reduced models, a multiscale optimization model is proposed for performing integrated design and management of CWCTs and cooling water system. It employs sampling-based stochastic programming and the heterogeneous integration of reduced models of CWCTs and other shortcut models. Finally, the performance of the proposed approach is illustrated through its comparison with a deterministic approach.
Hong Kong Polytechni... arrow_drop_down Hong Kong Polytechnic University: PolyU Institutional Repository (PolyU IR)Article . 2024License: CC BY NC NDFull-Text: http://hdl.handle.net/10397/104148Data sources: Bielefeld Academic Search Engine (BASE)Chemical Engineering ScienceArticle . 2020 . Peer-reviewedLicense: Elsevier TDMData sources: Crossrefadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1016/j.ces.2020.115773&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess RoutesGreen 22 citations 22 popularity Top 10% influence Top 10% impulse Top 10% Powered by BIP!
more_vert Hong Kong Polytechni... arrow_drop_down Hong Kong Polytechnic University: PolyU Institutional Repository (PolyU IR)Article . 2024License: CC BY NC NDFull-Text: http://hdl.handle.net/10397/104148Data sources: Bielefeld Academic Search Engine (BASE)Chemical Engineering ScienceArticle . 2020 . Peer-reviewedLicense: Elsevier TDMData sources: Crossrefadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1016/j.ces.2020.115773&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eu
description Publicationkeyboard_double_arrow_right Article , Journal 2020 China (People's Republic of), Hong Kong, China (People's Republic of)Publisher:Elsevier BV Dominic C. Y. Foo; Haoshui Yu; Bingjian Zhang; Jingzheng Ren; Qinglin Chen; Chang He; Qiping Zhu; Qiping Zhu;handle: 10397/104148
Abstract Incorporation of closed wet cooling tower (CWCT) in the existing circulating water system has been recognized as a viable path to reduce water use in process industry. This paper introduces a specifically tailored framework based on model reductions for multiscale optimization of CWCT-based cooling water system considering environmental variations. An optimal design of experiment is performed for accurate approximation of the multivariate probability distributions by generating a finite set of samples over the entire input space. The probability distributions are propagated via multi-sample CFD simulations for constructing the physics-based and data-driven reduced models of CWCTs. Based on the developed reduced models, a multiscale optimization model is proposed for performing integrated design and management of CWCTs and cooling water system. It employs sampling-based stochastic programming and the heterogeneous integration of reduced models of CWCTs and other shortcut models. Finally, the performance of the proposed approach is illustrated through its comparison with a deterministic approach.
Hong Kong Polytechni... arrow_drop_down Hong Kong Polytechnic University: PolyU Institutional Repository (PolyU IR)Article . 2024License: CC BY NC NDFull-Text: http://hdl.handle.net/10397/104148Data sources: Bielefeld Academic Search Engine (BASE)Chemical Engineering ScienceArticle . 2020 . Peer-reviewedLicense: Elsevier TDMData sources: Crossrefadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1016/j.ces.2020.115773&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess RoutesGreen 22 citations 22 popularity Top 10% influence Top 10% impulse Top 10% Powered by BIP!
more_vert Hong Kong Polytechni... arrow_drop_down Hong Kong Polytechnic University: PolyU Institutional Repository (PolyU IR)Article . 2024License: CC BY NC NDFull-Text: http://hdl.handle.net/10397/104148Data sources: Bielefeld Academic Search Engine (BASE)Chemical Engineering ScienceArticle . 2020 . Peer-reviewedLicense: Elsevier TDMData sources: Crossrefadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1016/j.ces.2020.115773&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eu