CAREER: Accelerating Real-time Hybrid Physical-Numerical Simulations in Natural Hazards Engineering with a Graphics Processing Unit (GPU)-driven Paradigm

该奖项全部或部分根据2021年美国救援计划法案（公法117-2）资助。该教师早期职业发展（CAREER）奖将通过为使用图形处理单元（GPU）的高保真模拟奠定算法基础，促进对自然灾害对建筑环境造成的风险的基本理解。复杂结构系统的高分辨率仿真需要以独特的方式解决详细的模型。例如，高层建筑在功能上如此重要，以至于它们“太大而不能倒”，因为中等程度的损坏可能难以修复，高层建筑功能的丧失严重影响事后恢复。然而，土-结构相互作用（SSI）的影响，在地震过程中的高层建筑反应至关重要，往往被忽视，由于计算成本和物理测试的限制。为了实现更真实和更快的模拟，这项研究将推导，演示和促进利用GPU的大规模并行性的高级数值方法，即，实时计算机芯片最初是为图形渲染而开发的，以克服结构模拟中的计算瓶颈，特别是高层建筑的实时混合仿真（RTHS）。与此同时，这项研究的多学科组成部分将与更大的教育承诺相结合，以开发，传播和不断反思包容性教学法，以提高学生在计算中的持久性和乐趣，培养学生所需的技能越来越技术驱动的劳动力。该奖项将有助于国家科学基金会（NSF）在国家地震减灾计划（NEHRP）中的作用。使用RTHS将物理实验与真实的数值模型结合起来，对复杂结构进行高分辨率模拟在以前是非常困难的。精细的高保真模型可以提高分辨率和准确度，但也会增加运行时间，从而抑制RTHS的可行性。图形处理器将首次用于加速RTHS，以实现对土木结构的更高保真度的“实时”模拟。土木结构的地震响应对全GPU加速提出了独特的挑战，包括异构单元公式、不同程度的非线性以及对直接求解器隐式积分方案的依赖。为了应对这些挑战，本研究将重新制定方法来组装和解决GPU上的运动方程：（i）大规模并行算法，（ii）半离散时间积分方案，以及（iii）事件驱动的GPU适应RTHS架构。这项研究将最终在一个分层的测试程序，以模拟现实的高层建筑的反应，包括SSI。该项目将在结构工程和科学计算的交叉点建立多学科研究和指导。相互合作将用于综合三个NSF支持的自然灾害工程研究基础设施（NHERI）设施的专业知识，包括加州大学伯克利分校的计算建模和仿真中心，利哈伊大学的实验设施，以及德克萨斯大学奥斯汀分校的DesignSafe网络基础设施。项目数据将在NHERI数据库（https：//www.example.com）中存档并公开提供。该奖项反映了NSF的法定使命，并被认为值得通过使用基金会的知识价值和更广泛的影响审查标准进行评估来支持。www.DesignSafe-ci.org

This award is funded in whole or in part under the American Rescue Plan Act of 2021 (Public Law 117-2).This Faculty Early Career Development (CAREER) award will advance fundamental understanding of the risks posed by natural hazards to the built environment by laying the algorithmic foundation for high-fidelity simulations using graphics processing units (GPUs). High-resolution simulation of complex structural systems requires that detailed models be solved in unique ways. For example, tall buildings are so functionally important that they are “too big to fail,” as moderate damage can be difficult to repair and tall building loss of function severely affects post-event recovery. Yet, the influence of soil-structure interaction (SSI), critically important to tall building response during an earthquake, is often neglected due to computational cost and physical testing constraints. To enable more realistic and faster simulations, this research will derive, demonstrate, and facilitate advanced numerical methods that harness the massive parallelism of GPUs, i.e., real-time computer chips originally developed for graphics rendering, to overcome computational bottlenecks in structural simulations, specifically in the real-time hybrid simulation (RTHS) of tall buildings. In parallel, the multi-disciplinary components of this research will be integrated with a larger educational commitment to develop, disseminate, and continuously reflect on an inclusive teaching pedagogy to enhance student persistence and joy in computation, training students with the skills needed for an increasingly technology-driven workforce. This award will contribute to the National Science Foundation (NSF) role in the National Earthquake Hazards Reduction Program (NEHRP). High-resolution simulations of complex structures using RTHS, which couples physical experiments with numerical models in real time, has previously been exceptionally difficult. Refined, high-fidelity models result in greater resolution and accuracy but also suffer increased run time, inhibiting the feasibility of RTHS. Graphics processors will, for the first time, be used to accelerate RTHS to enable higher-fidelity "on-the-fly" simulation of civil structures. The seismic response of civil structures poses unique challenges for full GPU acceleration, including heterogeneous element formulations, varying degrees of nonlinearities, and reliance on implicit integration schemes with direct solvers. To address these challenges, this research will re-formulate approaches to assembling and solving the equations of motion on GPUs with: (i) massively parallel algorithms, (ii) semi-discrete time integration schemes, and (iii) an event-driven GPU-adapted RTHS architecture. This research will culminate in a tiered testing program to simulate realistic tall building response, including SSI. This project will establish multi-disciplinary research and mentorship at the intersection of structural engineering and scientific computing. Mutual collaborations will be used to synthesize expertise across three NSF-supported Natural Hazards Engineering Research Infrastructure (NHERI) facilities, including the Computational Modeling and Simulation Center at the University of California, Berkeley, the experimental facility at Lehigh University, and the DesignSafe cyberinfrastructure at the University of Texas at Austin. Project data will be archived and made publicly available in the NHERI Data Depot (https://www.DesignSafe-ci.org).This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.