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Research and development of field theory-based three-dimensional risk assessment. Part II: Regional overall risk

For three-dimensional (3D) risk assessments, the scalar fields of risk can be clarified so that the risk value at any point in 3D space can be obtained. Notably, the 3D risk function can be used to calculate the surface integral to reveal the overall risk level in a certain area. As a result, a nove...

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Autores principales: Yan, Fang, Dong, Longjun, Wang, Bing, Hu, Tao, Ge, Ji
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9918764/
https://www.ncbi.nlm.nih.gov/pubmed/36785815
http://dx.doi.org/10.1016/j.heliyon.2023.e13194
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author Yan, Fang
Dong, Longjun
Wang, Bing
Hu, Tao
Ge, Ji
author_facet Yan, Fang
Dong, Longjun
Wang, Bing
Hu, Tao
Ge, Ji
author_sort Yan, Fang
collection PubMed
description For three-dimensional (3D) risk assessments, the scalar fields of risk can be clarified so that the risk value at any point in 3D space can be obtained. Notably, the 3D risk function can be used to calculate the surface integral to reveal the overall risk level in a certain area. As a result, a novel field theory-based 3D risk assessment method called the regional overall risk assessment (RORA) is proposed in this study. The regional overall risk (ROR) is introduced to describe the overall risk level of the assessed area. The corresponding definition and algorithm of the ROR are determined. The selection rule of the surfaces, which are used to create the surface integrals and compute the ROR, is also provided and discussed. To demonstrate the effectiveness of the RORA, the 3D risk caused by biomass gasification stations is utilized to conduct a case study. For the assessed area (Huangtukan Village and Yanjia Village), values of ROR are 29.5787 and 39.3858, respectively. The results represent accurate overall risk levels of the assessed areas and can provide effective guidance for risk prevention in the assessed areas, including land-use planning and safety planning. Moreover, the validity and availability of the proposed RORA is verified by a sensitivity analysis. The prospects and limitations of the RORA are also analyzed and discussed in this work.
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spelling pubmed-99187642023-02-12 Research and development of field theory-based three-dimensional risk assessment. Part II: Regional overall risk Yan, Fang Dong, Longjun Wang, Bing Hu, Tao Ge, Ji Heliyon Research Article For three-dimensional (3D) risk assessments, the scalar fields of risk can be clarified so that the risk value at any point in 3D space can be obtained. Notably, the 3D risk function can be used to calculate the surface integral to reveal the overall risk level in a certain area. As a result, a novel field theory-based 3D risk assessment method called the regional overall risk assessment (RORA) is proposed in this study. The regional overall risk (ROR) is introduced to describe the overall risk level of the assessed area. The corresponding definition and algorithm of the ROR are determined. The selection rule of the surfaces, which are used to create the surface integrals and compute the ROR, is also provided and discussed. To demonstrate the effectiveness of the RORA, the 3D risk caused by biomass gasification stations is utilized to conduct a case study. For the assessed area (Huangtukan Village and Yanjia Village), values of ROR are 29.5787 and 39.3858, respectively. The results represent accurate overall risk levels of the assessed areas and can provide effective guidance for risk prevention in the assessed areas, including land-use planning and safety planning. Moreover, the validity and availability of the proposed RORA is verified by a sensitivity analysis. The prospects and limitations of the RORA are also analyzed and discussed in this work. Elsevier 2023-01-26 /pmc/articles/PMC9918764/ /pubmed/36785815 http://dx.doi.org/10.1016/j.heliyon.2023.e13194 Text en © 2023 The Authors. Published by Elsevier Ltd. https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Research Article
Yan, Fang
Dong, Longjun
Wang, Bing
Hu, Tao
Ge, Ji
Research and development of field theory-based three-dimensional risk assessment. Part II: Regional overall risk
title Research and development of field theory-based three-dimensional risk assessment. Part II: Regional overall risk
title_full Research and development of field theory-based three-dimensional risk assessment. Part II: Regional overall risk
title_fullStr Research and development of field theory-based three-dimensional risk assessment. Part II: Regional overall risk
title_full_unstemmed Research and development of field theory-based three-dimensional risk assessment. Part II: Regional overall risk
title_short Research and development of field theory-based three-dimensional risk assessment. Part II: Regional overall risk
title_sort research and development of field theory-based three-dimensional risk assessment. part ii: regional overall risk
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9918764/
https://www.ncbi.nlm.nih.gov/pubmed/36785815
http://dx.doi.org/10.1016/j.heliyon.2023.e13194
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