Recent advances in multiscale CFD modelling of cooling processes and systems for the agrifood industry
Spoilage of agrifood produce is a major issue in the industry. Cooling is an effective technique for extending the shelf life of fresh agrifood produce to minimize spoilage. Due to the practical inability of directly solving the wide spatial and temporal scales in large industrial agrifood cooling s...
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| Published in: | Critical reviews in food science and nutrition Vol. 61; no. 15; pp. 2455 - 2470 |
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| Main Authors: | , , |
| Format: | Journal Article |
| Language: | English |
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United States
Taylor & Francis
22.08.2021
Taylor & Francis Ltd |
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| ISSN: | 1040-8398, 1549-7852, 1549-7852 |
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| Abstract | Spoilage of agrifood produce is a major issue in the industry. Cooling is an effective technique for extending the shelf life of fresh agrifood produce to minimize spoilage. Due to the practical inability of directly solving the wide spatial and temporal scales in large industrial agrifood cooling systems, the porous medium approach is mostly used. However, improvements of current porous medium models and modeling across much wider scales are needed to better understand the multiscale cooling process and system problems. Recently, as a result of increased computational capacity, multiscale computational fluid dynamics (CFD) modeling approaches have been developed to tackle some of these challenges. The associated problems and applications of CFD in the design and process optimization of cooling processes and systems at different scales are considered. CFD solution and scale bridging techniques relevant for handling multiscale cooling processes and systems problems are discussed. Innovative applications of various CFD modeling techniques at different scales in cooling processes and systems are reviewed. CFD modeling techniques can be used to handle multiscale cooling process and system problems. Lattice Boltzmann method (LBM) is a potentially viable discrete modeling technique for complimentary usages alongside current continuum techniques in future multiscale CFD modeling. The multiscale CFD modeling paradigm can overcome the computational resource limitations associated with the direct modeling approach and enhance model extension across wider spatial and temporal scales. Information from multiscale CFD could be used to improve the accuracy of current porous medium models, and thus the design of more efficient cooling systems. |
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| AbstractList | Spoilage of agrifood produce is a major issue in the industry. Cooling is an effective technique for extending the shelf life of fresh agrifood produce to minimize spoilage. Due to the practical inability of directly solving the wide spatial and temporal scales in large industrial agrifood cooling systems, the porous medium approach is mostly used. However, improvements of current porous medium models and modeling across much wider scales are needed to better understand the multiscale cooling process and system problems. Recently, as a result of increased computational capacity, multiscale computational fluid dynamics (CFD) modeling approaches have been developed to tackle some of these challenges. The associated problems and applications of CFD in the design and process optimization of cooling processes and systems at different scales are considered. CFD solution and scale bridging techniques relevant for handling multiscale cooling processes and systems problems are discussed. Innovative applications of various CFD modeling techniques at different scales in cooling processes and systems are reviewed. CFD modeling techniques can be used to handle multiscale cooling process and system problems. Lattice Boltzmann method (LBM) is a potentially viable discrete modeling technique for complimentary usages alongside current continuum techniques in future multiscale CFD modeling. The multiscale CFD modeling paradigm can overcome the computational resource limitations associated with the direct modeling approach and enhance model extension across wider spatial and temporal scales. Information from multiscale CFD could be used to improve the accuracy of current porous medium models, and thus the design of more efficient cooling systems. Spoilage of agrifood produce is a major issue in the industry. Cooling is an effective technique for extending the shelf life of fresh agrifood produce to minimize spoilage. Due to the practical inability of directly solving the wide spatial and temporal scales in large industrial agrifood cooling systems, the porous medium approach is mostly used. However, improvements of current porous medium models and modeling across much wider scales are needed to better understand the multiscale cooling process and system problems. Recently, as a result of increased computational capacity, multiscale computational fluid dynamics (CFD) modeling approaches have been developed to tackle some of these challenges. The associated problems and applications of CFD in the design and process optimization of cooling processes and systems at different scales are considered. CFD solution and scale bridging techniques relevant for handling multiscale cooling processes and systems problems are discussed. Innovative applications of various CFD modeling techniques at different scales in cooling processes and systems are reviewed. CFD modeling techniques can be used to handle multiscale cooling process and system problems. Lattice Boltzmann method (LBM) is a potentially viable discrete modeling technique for complimentary usages alongside current continuum techniques in future multiscale CFD modeling. The multiscale CFD modeling paradigm can overcome the computational resource limitations associated with the direct modeling approach and enhance model extension across wider spatial and temporal scales. Information from multiscale CFD could be used to improve the accuracy of current porous medium models, and thus the design of more efficient cooling systems.Spoilage of agrifood produce is a major issue in the industry. Cooling is an effective technique for extending the shelf life of fresh agrifood produce to minimize spoilage. Due to the practical inability of directly solving the wide spatial and temporal scales in large industrial agrifood cooling systems, the porous medium approach is mostly used. However, improvements of current porous medium models and modeling across much wider scales are needed to better understand the multiscale cooling process and system problems. Recently, as a result of increased computational capacity, multiscale computational fluid dynamics (CFD) modeling approaches have been developed to tackle some of these challenges. The associated problems and applications of CFD in the design and process optimization of cooling processes and systems at different scales are considered. CFD solution and scale bridging techniques relevant for handling multiscale cooling processes and systems problems are discussed. Innovative applications of various CFD modeling techniques at different scales in cooling processes and systems are reviewed. CFD modeling techniques can be used to handle multiscale cooling process and system problems. Lattice Boltzmann method (LBM) is a potentially viable discrete modeling technique for complimentary usages alongside current continuum techniques in future multiscale CFD modeling. The multiscale CFD modeling paradigm can overcome the computational resource limitations associated with the direct modeling approach and enhance model extension across wider spatial and temporal scales. Information from multiscale CFD could be used to improve the accuracy of current porous medium models, and thus the design of more efficient cooling systems. |
| Author | Ajani, Clement Kehinde Zhu, Zhiwei Sun, Da-Wen |
| Author_xml | – sequence: 1 givenname: Clement Kehinde surname: Ajani fullname: Ajani, Clement Kehinde organization: Engineering and Technological Research Centre of Guangdong Province on Intelligent Sensing and Process Control of Cold Chain Foods, Guangdong Province Engineering Laboratory for Intelligent Cold Chain Logistics Equipment for Agricultural Products, Guangzhou Higher Education Mega Centre – sequence: 2 givenname: Zhiwei surname: Zhu fullname: Zhu, Zhiwei organization: Engineering and Technological Research Centre of Guangdong Province on Intelligent Sensing and Process Control of Cold Chain Foods, Guangdong Province Engineering Laboratory for Intelligent Cold Chain Logistics Equipment for Agricultural Products, Guangzhou Higher Education Mega Centre – sequence: 3 givenname: Da-Wen surname: Sun fullname: Sun, Da-Wen organization: Food Refrigeration and Computerized Food Technology (FRCFT), Agriculture and Food Science Centre, University College Dublin, National University of Ireland |
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| Cites_doi | 10.1016/j.agrformet.2019.107773 10.1016/j.scienta.2016.06.011 10.1016/j.jfoodeng.2017.02.011 10.1016/j.jfoodeng.2020.110112 10.1007/s11947-016-1733-y 10.1016/j.ijheatmasstransfer.2015.04.003 10.1016/bs.host.2018.06.002 10.1016/j.jfoodeng.2013.05.007 10.1111/jfpp.12556 10.1016/j.jfoodeng.2008.08.027 10.1016/j.egypro.2017.07.284 10.1016/j.lwt.2020.109066 10.1016/j.tifs.2018.02.019 10.1016/j.ijheatmasstransfer.2019.118624 10.1016/j.ijheatmasstransfer.2015.04.004 10.1080/10408398.2018.1482528 10.1016/j.jcp.2012.08.029 10.1016/j.biosystemseng.2010.02.004 10.1016/j.foodchem.2017.07.011 10.1016/j.lwt.2018.12.079 10.1016/j.biosystemseng.2018.02.003 10.1016/j.apm.2014.07.001 10.1016/j.tifs.2012.08.001 10.1016/j.ijheatmasstransfer.2017.04.015 10.3390/en12173272 10.1016/j.jfoodeng.2017.01.026 10.1016/j.ijrefrig.2018.02.012 10.1016/j.camwa.2018.08.018 10.1016/j.compag.2012.05.009 10.1016/j.compag.2013.05.008 10.1201/9781420009217 10.1016/j.ijrefrig.2006.03.019 10.1016/j.apenergy.2016.01.101 10.18280/ijht.340426 10.1080/10408398.2017.1345854 10.1016/j.compag.2017.02.015 10.1016/j.ijrefrig.2016.06.013 10.1016/j.jbiotec.2015.11.008 10.1016/j.jfoodeng.2009.03.004 10.1017/S0022112005008153 10.1016/j.jcp.2006.07.034 10.1016/j.applthermaleng.2014.11.012 10.1007/s10494-016-9751-4 10.1016/j.tifs.2017.11.017 10.13140/RG.2.2.35857.33129/2 10.1093/oso/9780198503989.001.0001 10.1016/j.jfoodeng.2008.03.026 10.1016/j.tifs.2015.04.008 10.1533/9780857098894.2.336 10.1007/s11947-018-2086-5 10.1007/s11947-012-0883-9 10.1155/2013/928309 10.1016/j.enconman.2005.10.007 10.1007/s11431-017-9100-2 10.1016/S0260-8774(00)00082-0 10.1111/j.1469-8137.2008.02732.x 10.3182/20110828-6-IT-1002.02886 10.1016/j.ijheatmasstransfer.2013.05.075 10.1080/23311835.2017.1327502 10.1016/j.tifs.2006.05.004 10.1016/j.ijthermalsci.2017.12.017 10.1080/10408398.2010.518256 10.1016/j.jfoodeng.2012.08.019 10.1515/ijfe-2012-0015 10.1016/j.jfoodeng.2012.09.003 10.1007/s11947-012-0913-7 10.1080/10408398.2018.1490696 10.1016/j.applthermaleng.2018.12.054 10.1016/j.foodchem.2017.12.050 10.1007/s11947-018-2163-9 10.1016/j.postharvbio.2016.05.008 10.1016/j.agrformet.2012.04.010 10.1016/j.jfoodeng.2014.06.041 10.1007/s11242-019-01282-2 10.1016/j.jfoodeng.2004.11.010 10.1080/10408398.2018.1496900 10.1016/j.postharvbio.2016.10.005 10.1016/j.jfoodeng.2017.02.010 10.5539/mas.v6n1p102 10.1016/j.ijheatmasstransfer.2014.09.051 10.1016/j.tifs.2019.09.010 10.1016/j.ijrefrig.2005.12.010 10.1016/j.applthermaleng.2017.11.049 10.1016/j.postharvbio.2016.11.019 10.33552/GJES.2018.01.000503 10.1016/j.ijrefrig.2006.01.013 10.1016/j.tifs.2019.11.009 10.1016/j.ijheatmasstransfer.2009.09.029 10.1016/j.applthermaleng.2016.12.063 10.1137/09077059X 10.1111/1541-4337.12380 10.1016/j.cja.2014.12.007 10.1007/s12393-010-9027-z 10.1093/aob/mct313 10.1016/j.ultsonch.2020.105162 |
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| References_xml | – ident: CIT0051 doi: 10.1016/j.agrformet.2019.107773 – ident: CIT0058 doi: 10.1016/j.scienta.2016.06.011 – ident: CIT0036 doi: 10.1016/j.jfoodeng.2017.02.011 – ident: CIT1050 doi: 10.1016/j.jfoodeng.2020.110112 – ident: CIT0010 doi: 10.1007/s11947-016-1733-y – ident: CIT0086 doi: 10.1016/j.ijheatmasstransfer.2015.04.003 – ident: CIT0034 doi: 10.1016/bs.host.2018.06.002 – ident: CIT0003 doi: 10.1016/j.jfoodeng.2013.05.007 – volume: 40 start-page: 1 year: 2016 ident: CIT0040 publication-title: Journal of Food Process Engineering doi: 10.1111/jfpp.12556 – start-page: 121 volume-title: Computational fluid dynamics in food processing year: 2019 ident: CIT0062 – start-page: 149 volume-title: Computational fluid dynamics in food processing year: 2019 ident: CIT0052 – ident: CIT0026 doi: 10.1016/j.jfoodeng.2008.08.027 – ident: CIT0078 doi: 10.1016/j.egypro.2017.07.284 – ident: CIT1049 doi: 10.1016/j.lwt.2020.109066 – ident: CIT1045 doi: 10.1016/j.tifs.2018.02.019 – ident: CIT0016 doi: 10.1016/j.ijheatmasstransfer.2019.118624 – ident: CIT0085 doi: 10.1016/j.ijheatmasstransfer.2015.04.004 – ident: CIT1055 doi: 10.1080/10408398.2018.1482528 – ident: CIT0046 doi: 10.1016/j.jcp.2012.08.029 – ident: CIT0087 doi: 10.1016/j.biosystemseng.2010.02.004 – ident: CIT1043 doi: 10.1016/j.foodchem.2017.07.011 – ident: CIT1053 doi: 10.1016/j.lwt.2018.12.079 – ident: CIT0084 doi: 10.1016/j.biosystemseng.2018.02.003 – ident: CIT0007 doi: 10.1016/j.apm.2014.07.001 – ident: CIT0055 doi: 10.1016/j.tifs.2012.08.001 – ident: CIT0041 doi: 10.1016/j.ijheatmasstransfer.2017.04.015 – ident: CIT0030 doi: 10.3390/en12173272 – ident: CIT0005 doi: 10.1016/j.jfoodeng.2017.01.026 – ident: CIT0042 doi: 10.1016/j.ijrefrig.2018.02.012 – ident: CIT0033 doi: 10.1016/j.camwa.2018.08.018 – start-page: 87 volume-title: Computational fluid dynamics in food processing year: 2019 ident: CIT0064 – ident: CIT0002 doi: 10.1016/j.compag.2012.05.009 – ident: CIT0022 doi: 10.1016/j.compag.2013.05.008 – 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| Snippet | Spoilage of agrifood produce is a major issue in the industry. Cooling is an effective technique for extending the shelf life of fresh agrifood produce to... |
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| SubjectTerms | Agribusiness Agricultural production Computational fluid dynamics Computer applications Cooling Cooling process Cooling systems Design optimization Fluid dynamics fluid mechanics food industry food science Hydrodynamics LBM Mathematical models multiscale CFD modeling nutrition Porous media porous medium modeling Shelf life Spoilage turbulence |
| Title | Recent advances in multiscale CFD modelling of cooling processes and systems for the agrifood industry |
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