{"title":"利用具有高斯过程趋势的克里金法高效模拟三维条件随机场","authors":"","doi":"10.1016/j.compgeo.2024.106862","DOIUrl":null,"url":null,"abstract":"<div><div>Previous investigations have shown that for the modeling the soil spatial variability, the Gaussian process regression (GPR) provides a more plausible trend model than the linear combination of basis functions. However, the effectiveness of the conditional random (CRF) simulation based on the GPR trend model (denoted by the t-GPR kriging) has not been investigated. This study first addresses the high computational cost issue of the t-GPR kriging for realisic 3D problems by deriving the Kronecker-product algorithms. Then, this study further investigates the effectiveness of the t-GPR kriging in CRF simulation using real case studies. It is shown that with the Kronecker-product derivations, the computational time can be dramatically reduced such that the t-GPR kriging can conduct CRF simulation for full-scale 3D problems.</div></div>","PeriodicalId":55217,"journal":{"name":"Computers and Geotechnics","volume":null,"pages":null},"PeriodicalIF":5.3000,"publicationDate":"2024-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Efficient simulation of 3D conditional random field using kriging with Gaussian-process trend\",\"authors\":\"\",\"doi\":\"10.1016/j.compgeo.2024.106862\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>Previous investigations have shown that for the modeling the soil spatial variability, the Gaussian process regression (GPR) provides a more plausible trend model than the linear combination of basis functions. However, the effectiveness of the conditional random (CRF) simulation based on the GPR trend model (denoted by the t-GPR kriging) has not been investigated. This study first addresses the high computational cost issue of the t-GPR kriging for realisic 3D problems by deriving the Kronecker-product algorithms. Then, this study further investigates the effectiveness of the t-GPR kriging in CRF simulation using real case studies. It is shown that with the Kronecker-product derivations, the computational time can be dramatically reduced such that the t-GPR kriging can conduct CRF simulation for full-scale 3D problems.</div></div>\",\"PeriodicalId\":55217,\"journal\":{\"name\":\"Computers and Geotechnics\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":5.3000,\"publicationDate\":\"2024-10-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Computers and Geotechnics\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0266352X24008012\",\"RegionNum\":1,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Computers and Geotechnics","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0266352X24008012","RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS","Score":null,"Total":0}
Efficient simulation of 3D conditional random field using kriging with Gaussian-process trend
Previous investigations have shown that for the modeling the soil spatial variability, the Gaussian process regression (GPR) provides a more plausible trend model than the linear combination of basis functions. However, the effectiveness of the conditional random (CRF) simulation based on the GPR trend model (denoted by the t-GPR kriging) has not been investigated. This study first addresses the high computational cost issue of the t-GPR kriging for realisic 3D problems by deriving the Kronecker-product algorithms. Then, this study further investigates the effectiveness of the t-GPR kriging in CRF simulation using real case studies. It is shown that with the Kronecker-product derivations, the computational time can be dramatically reduced such that the t-GPR kriging can conduct CRF simulation for full-scale 3D problems.
期刊介绍:
The use of computers is firmly established in geotechnical engineering and continues to grow rapidly in both engineering practice and academe. The development of advanced numerical techniques and constitutive modeling, in conjunction with rapid developments in computer hardware, enables problems to be tackled that were unthinkable even a few years ago. Computers and Geotechnics provides an up-to-date reference for engineers and researchers engaged in computer aided analysis and research in geotechnical engineering. The journal is intended for an expeditious dissemination of advanced computer applications across a broad range of geotechnical topics. Contributions on advances in numerical algorithms, computer implementation of new constitutive models and probabilistic methods are especially encouraged.