Mohammad Nikooei, Clarence Edward Choi, Jiaqi Zhang
{"title":"多尺度数据驱动的致密颗粒流瞬态沉积物理学建模","authors":"Mohammad Nikooei, Clarence Edward Choi, Jiaqi Zhang","doi":"10.1016/j.compgeo.2024.106825","DOIUrl":null,"url":null,"abstract":"<div><div>Geophysical flows involving granular masses exhibit complex dynamics with transient mass and momentum changes due to deposition. Geophysical flows are typically simulated using depth-averaged (DA) models, which rely on empirical closures for deposition. However, these models typically overlook the detailed grain-scale physics involved in deposition, treating the flow as an equivalent fluid at the macro-scale. This study introduces a multiscale framework to integrate grain-scale deposition physics into macro-scale DA models without relying on empirical closures. The framework utilizes a surrogate model, trained on discrete element modeling (DEM) datasets, to capture changes in effective flow depth. This surrogate model is integrated with a DA model to create a multiscale approach, improving the deposition physics within an efficient computational framework. The effectiveness of the proposed multiscale framework is assessed by studying how a granular mass, initially in motion, settles when the slope angle is suddenly reduced to zero. Predictions from the multiscale model of effective flow depth (i.e., not including deposited material) and DA velocity are compared with DEM results. It is demonstrated that the proposed framework has potential to streamline upscaling simulations and facilitate field-scale hazard assessments in the future.</div></div>","PeriodicalId":55217,"journal":{"name":"Computers and Geotechnics","volume":null,"pages":null},"PeriodicalIF":5.3000,"publicationDate":"2024-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Multiscale data-driven modeling of transient deposition physics of dense granular flows\",\"authors\":\"Mohammad Nikooei, Clarence Edward Choi, Jiaqi Zhang\",\"doi\":\"10.1016/j.compgeo.2024.106825\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>Geophysical flows involving granular masses exhibit complex dynamics with transient mass and momentum changes due to deposition. Geophysical flows are typically simulated using depth-averaged (DA) models, which rely on empirical closures for deposition. However, these models typically overlook the detailed grain-scale physics involved in deposition, treating the flow as an equivalent fluid at the macro-scale. This study introduces a multiscale framework to integrate grain-scale deposition physics into macro-scale DA models without relying on empirical closures. The framework utilizes a surrogate model, trained on discrete element modeling (DEM) datasets, to capture changes in effective flow depth. This surrogate model is integrated with a DA model to create a multiscale approach, improving the deposition physics within an efficient computational framework. The effectiveness of the proposed multiscale framework is assessed by studying how a granular mass, initially in motion, settles when the slope angle is suddenly reduced to zero. Predictions from the multiscale model of effective flow depth (i.e., not including deposited material) and DA velocity are compared with DEM results. It is demonstrated that the proposed framework has potential to streamline upscaling simulations and facilitate field-scale hazard assessments in the future.</div></div>\",\"PeriodicalId\":55217,\"journal\":{\"name\":\"Computers and Geotechnics\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":5.3000,\"publicationDate\":\"2024-10-10\",\"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/S0266352X2400764X\",\"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/S0266352X2400764X","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}
引用次数: 0
摘要
涉及粒状物质的地球物理流表现出复杂的动力学特征,由于沉积作用而产生瞬时质量和动量变化。地球物理流动通常使用深度平均(DA)模型进行模拟,这些模型依赖于沉积的经验闭合。然而,这些模型通常忽略了沉积过程中涉及的详细晶粒尺度物理现象,而将流动视为宏观尺度上的等效流体。本研究引入了一个多尺度框架,在不依赖经验闭合的情况下,将颗粒尺度沉积物理学整合到宏观尺度 DA 模型中。该框架利用在离散元建模(DEM)数据集上训练的代用模型来捕捉有效流深的变化。该代用模型与大尺度模型相结合,创建了一种多尺度方法,在一个高效的计算框架内改进了沉积物理学。通过研究最初处于运动状态的颗粒质量在坡度角突然减小为零时如何沉降,对所提出的多尺度框架的有效性进行了评估。多尺度模型对有效流深(即不包括沉积物)和DA速度的预测结果与DEM结果进行了比较。结果表明,所提出的框架具有简化升级模拟的潜力,并有助于未来进行实地规模的灾害评估。
Multiscale data-driven modeling of transient deposition physics of dense granular flows
Geophysical flows involving granular masses exhibit complex dynamics with transient mass and momentum changes due to deposition. Geophysical flows are typically simulated using depth-averaged (DA) models, which rely on empirical closures for deposition. However, these models typically overlook the detailed grain-scale physics involved in deposition, treating the flow as an equivalent fluid at the macro-scale. This study introduces a multiscale framework to integrate grain-scale deposition physics into macro-scale DA models without relying on empirical closures. The framework utilizes a surrogate model, trained on discrete element modeling (DEM) datasets, to capture changes in effective flow depth. This surrogate model is integrated with a DA model to create a multiscale approach, improving the deposition physics within an efficient computational framework. The effectiveness of the proposed multiscale framework is assessed by studying how a granular mass, initially in motion, settles when the slope angle is suddenly reduced to zero. Predictions from the multiscale model of effective flow depth (i.e., not including deposited material) and DA velocity are compared with DEM results. It is demonstrated that the proposed framework has potential to streamline upscaling simulations and facilitate field-scale hazard assessments in the future.
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.