A spatiotemporal data-driven homogenization approach for hierarchical modeling of multiphase frozen soil in permafrost

时空数据驱动的多年冻土多相冻土分层建模方法

• 批准号: RGPIN-2019-06471
• 负责人: Na, SeonHong
• 金额: $ 1.89万
• 依托单位: McMaster University
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2022
• 资助国家: 加拿大
• 起止时间: 2022-01-01 至 2023-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=749398
• 关键词: spatiotemporal; data; driven; homogenization; approach

Global issues related to extreme climate change and demanding energy resources have created new engineering problems. Those issues are associated with sustainable development and resilient infrastructure in our society, such as heavy rainfall-induced slope stability, sinkhole due to groundwater level change, hydraulic fracturing for unconventional energy recovery, geothermal energy facility, nuclear waste disposal, etc. Within the Canadian context, the melting of frozen soil is a critical issue in permafrost. The main reason is global warming that accelerates the thawing and subsequently the cyclic freezing, which in turn results in damaging buildings and infrastructures. In other words, frozen soils in permafrost are subjected to coupled loading conditions in terms of thermal, hydraulic, and mechanical aspects. As a mixture of air-water-ice-solid, furthermore, the multiphase frozen soil possesses multiscale characteristics that show size-dependent responses. Therefore, the thawing and freezing soil in permafrost requires our fundamental knowledge and advanced technologies to understand, analyze, and predict its complicated behavior. In the short term, the proposed research program is designed to develop a unified computational framework that transcends the multiscale behavior of multiphase frozen soils based on a hierarchical modeling approach. Focus Area I concentrates on deriving theoretical formulations to characterize the coupled thermo-hydro-mechanical processes under freeze-thaw actions for the pore-scale level. Focus Area II involves developing a data-driven constitutive model aiming at specimen-size level by leveraging machine learning to improve multiscale computational cost and flexibility. The pore-scale simulations from Focus Area I will be used to generate a database for training the data-driven model. Focus Area III involves constructing a unified framework for field-scale simulations by developing a multiscale bridging algorithm. The domain mapping technique to accommodate the spatiotemporal information of frozen soil will be further developed to be combined into the framework. This process will integrate the achievements from Focus Areas I and II and field/experimental data - a hybridized modeling method. In the long-term, the unified computational framework will be further advanced to interactively update monitoring information or additional site investigation in permafrost. This hybridized computational framework will provide an innovative methodology in analyzing conventional engineering problems, validating designs, and making predictions for resilient infrastructures, intelligent energy systems, and challenging environmental issues in Canada. The ultimate goal and strategic plan of the applicant's research will further provide cutting-edge knowledge and advanced technical skill set not only to train High Qualified Personnel (HQP), but to support industry, government, and academia in Canada and across the world.

与极端气候变化和能源需求相关的全球问题产生了新的工程问题。这些问题与可持续发展和弹性基础设施在我们的社会，如重碎石引起的边坡稳定性，天坑由于地下水位变化，水力压裂的非常规能源回收，地热能设施，核废料处理等在加拿大的背景下，冻土融化是一个关键问题，在永久冻土。主要原因是全球变暖加速了解冻和随后的循环冻结，这反过来又导致建筑物和基础设施的破坏。换句话说，多年冻土中的冻土受到热，水力和机械方面的耦合载荷条件。此外，作为空气-水-冰-固体的混合物，多相冻土具有多尺度特性，表现出与尺寸相关的响应。因此，冻土融冻问题需要我们的基础知识和先进技术来认识、分析和预测其复杂的行为。在短期内，拟议的研究计划的目的是开发一个统一的计算框架，超越多相冻土的多尺度行为的基础上的分层建模方法。重点领域一集中在推导理论公式，以表征耦合热-水-力学过程下的冻融作用的孔隙尺度水平。重点领域II涉及开发一个数据驱动的本构模型，旨在通过利用机器学习来提高多尺度计算成本和灵活性。来自焦点区域I的孔隙尺度模拟将用于生成用于训练数据驱动模型的数据库。重点领域三涉及通过开发多尺度桥接算法构建场尺度模拟的统一框架。将进一步发展适应冻土时空信息的领域映射技术，将其结合到框架中。这一过程将综合重点领域一和二的成果以及实地/实验数据-一种混合建模方法。从长远来看，统一的计算框架将进一步发展，以交互式更新监测信息或额外的现场调查在冻土。这种混合计算框架将提供一种创新的方法，用于分析传统的工程问题，验证设计，并预测加拿大的弹性基础设施，智能能源系统和具有挑战性的环境问题。申请人研究的最终目标和战略计划将进一步提供尖端知识和先进的技术技能，不仅用于培养高素质人才（HQP），而且用于支持加拿大和世界各地的工业，政府和学术界。