Collaborative Research: Frameworks: Quakeworx - An extensible software framework for earthquake simulations

协作研究：框架：Quakeworx - 用于地震模拟的可扩展软件框架

• 批准号: 2311206
• 负责人: Yehuda Ben-Zion
• 金额: $ 57万
• 依托单位: University of Southern California
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-09-01 至 2028-08-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2311206&HistoricalAwards=false
• 关键词: Collaborative; Research; Frameworks; Quakeworx; extensible

Physics-based forecasts of seismic hazard from future earthquakes are important for developing plans for land use, building codes, transportation and communication infrastructure, power and water systems, and many other aspects that are integral to society. The Quakeworx framework is a new multi-disciplinary collaboration to enable a wide community of users to access state-of-the-art physics-based models of rupture forecasts, further improve existing tools, and validate model results. Quakeworx also helps advance the science of rupture forecasts, obtain new insights on earthquake physics, improve seismic hazard estimates, and create new opportunities for STEM education and engagement. Quakeworx enables rapid immersion of students, post-docs, and early career scientists with state-of-the-art simulation and analysis tools that aid in modernizing education and training in earthquake physics, computational modeling, software engineering, and related fields. The project contributes to the national interest by supporting a more resilient society with improved capabilities for forecasting earthquakes and assessing seismic hazard, which are foundational for mitigation of seismic risk, contributing to STEM workforce development, and facilitating translation of results to the society at large.A core element of Quakeworx is a new science gateway, which provides access to state-of-the-art methods that combine novel physics-based modeling frameworks with standardized pipelines for simulations, data-based assimilation to inform and validate models on-demand, and machine-learning pattern recognition on big datasets. The project enables simulations of coupled evolution of earthquakes and faults producing diverse outputs (seismicity, ground motion, fault network configuration, strain rates, topography), and facilitates the development, validation, application, and reproducibility of improved rupture forecasts for research and education. Quakeworx curates and seeds many leading tools and data products that leverage existing community data models describing fault and rock properties as simulation input. Additionally, the gateway enables the research and education community to contribute, curate and share tools for simulations, data analysis and visualization, data products and knowledge base. The project provides a foundation that eliminates barriers due to lack of expertise and lack of access to compute resources, and it delivers an innovative service-oriented and easy-to-use cyberinfrastructure to a large user community.This award by the NSF Office of Advanced Cyberinfrastructure is jointly supported by the Division of Research, Innovation, Synergies, and Education (RISE), the Division of Earth Sciences (EAR), and the Geophysics Program within the NSF Directorate for Geosciences.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.

基于物理的未来地震地震危害预测对于制定土地使用、建筑规范、交通和通信基础设施、电力和供水系统以及社会不可或缺的许多其他方面的计划非常重要。 Quakeworx 框架是一个新的多学科协作框架，使广泛的用户社区能够访问最先进的基于物理的破裂预测模型，进一步改进现有工具并验证模型结果。 Quakeworx 还有助于推进破裂预测科学，获得有关地震物理学的新见解，改进地震灾害估计，并为 STEM 教育和参与创造新的机会。 Quakeworx 使学生、博士后和早期职业科学家能够快速沉浸在最先进的模拟和分析工具中，这些工具有助于实现地震物理、计算建模、软件工程和相关领域的现代化教育和培训。该项目通过提高地震预测和地震灾害评估能力来支持建设更具复原力的社会，从而为国家利益做出贡献，这是减轻地震风险的基础，有助于 STEM 劳动力发展，并促进将成果转化为整个社会。 Quakeworx 的核心元素是一个新的科学网关，它提供了对最先进方法的访问，这些方法将新颖的基于物理的建模框架与用于模拟、基于数据的同化的标准化管道相结合，以按需通知和验证模型，以及大数据集上的机器学习模式识别。该项目能够模拟地震和断层的耦合演化，产生不同的输出（地震活动、地面运动、断层网络配置、应变率、地形），并促进研究和教育改进破裂预测的开发、验证、应用和再现。 Quakeworx 策划并培育了许多领先的工具和数据产品，这些工具和数据产品利用现有的社区数据模型来描述断层和岩石特性作为模拟输入。此外，该网关使研究和教育界能够贡献、策划和共享用于模拟、数据分析和可视化、数据产品和知识库的工具。该项目提供了一个基础，消除了由于缺乏专业知识和无法访问计算资源而造成的障碍，并为大型用户社区提供了一个创新的、面向服务且易于使用的网络基础设施。该奖项由 NSF 高级办公室授予网络基础设施由 NSF 地球科学理事会的研究、创新、协同和教育部 (RISE)、地球科学部 (EAR) 和地球物理学项目联合支持。该奖项反映了 NSF 的法定使命，并通过使用基金会的智力价值和更广泛的影响审查标准进行评估，被认为值得支持。