Collaborative Research: Stochastic Nonlinear Dynamic Simulation for Prediction of Seismic Ground Motion

合作研究：用于预测地震地面运动的随机非线性动态模拟

• 批准号: 1200702
• 负责人: Boris Jeremic
• 金额: $ 34.15万
• 依托单位: University of California-Davis
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2012
• 资助国家: 美国
• 起止时间: 2012-07-01 至 2016-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1200702&HistoricalAwards=false
• 关键词: Collaborative; Research; Stochastic; Nonlinear; Dynamic

Existing approaches for prediction of seismic ground motion and its associated uncertainties mostly rely on fitting to a recorded motion (usually at the surface) with known earthquake and site characteristics. However, application of such obtained probabilistic ground motion to geotechnical engineering problems, such as free-field probabilistic site response analysis or probabilistic soil-structure interaction analysis, double counts the uncertainties and non-linearities of the soil medium. The goal of this project is to develop a new, physics-based methodology and an attendant computational tool to obtain a complete probabilistic description (probability density function) of site-specific ground motion time-history for a future seismic event by (1) characterizing and quantifying uncertainties in bed-rock motion at a site during future seismic event (right hand side (RHS) uncertainty), (2) characterizing and quantifying uncertainties in site-specific soil properties (left hand side (LHS) uncertainty), and (3) propagating the uncertain bed-rock motion through the uncertain soil. The ability to obtain such probabilistic description of site-specific ground motion time history will not only help in accurately assessing performance of any civil infrastructure object, but also help in critical decision-making process by the project owners, policy makers, and insurance agencies. For example, if the predicted ground motion is too uncertain, then the project owner may ask the following question: what step can be taken to reduce that uncertainty? In answering that question, a process for evaluating the relative contributions of RHS (source and path) and LHS (soil properties) uncertain parameters to overall uncertainty in seismic motions will be demonstrated as well. This will assist the project owners in mobilizing resources for increase understanding of the most significant contributor of uncertainty (source? site? path?), reduce the knowledge uncertainty, and subsequently reduce the overall ground motion uncertainty. In addition, the proposed development of theoretical capability to systematically propagate different sources of uncertainties through the governing equation of mechanics will greatly benefit the empirical modeling community in developing attenuation models especially for the regions where there are limited or no data (for example, eastern United States). Even for western United States, it will help the empirical modelers in better constraining their models. Further, the proposed technique will also provide insight in understanding spatial variation of ground motion and its associated uncertainties (covariance structure), which are under renewed interest in the research community, especially due to their effects on seismic performances of lifeline structures. This project will combine the state-of-the-art stochastic calculus with the principles of mechanics in developing a finite element based stochastic computational framework to propagate random waves through random non--linear heterogeneous media. It, to best of our knowledge, is the first attempt to simulate wave propagation through nonlinear (elastic--plastic) heterogeneous medium in the stochastic space considering both LHS and RHS uncertainties. Since uncertainties in material properties and external forces are present in all fields of engineering, the impact of this project will be much wider than just in the area of geotechnical engineering. In order to ensure future of developments from this project, high school science and mathematics teachers will be involved (via RET supplement) through summer workshops so that they can transmit their experiences to high school classrooms. The objective here is to emphasize the importance of mathematics and physics in modeling physical phenomena such as earthquake and plant an early seed among the future engineers to seek a career in this field.

现有的预测地震地面运动及其相关不确定性的方法大多依赖于与已知地震和场地特征的记录运动(通常在地表)进行拟合。然而，将所获得的概率地震动应用于岩土工程问题，如自由场概率场地反应分析或概率土-结构相互作用分析，将重复考虑土介质的不确定性和非线性。该项目的目标是开发一种新的基于物理的方法和随之而来的计算工具，通过(1)表征和量化未来地震事件期间场地基岩运动的不确定性(右侧(RHS)不确定性)，(2)表征和量化场地特定土壤性质的不确定性(左侧(LHS)不确定性)，以及(3)通过不确定的土壤传播不确定的基岩运动，从而获得未来地震事件的场地特定地面运动时程的完整概率描述(概率密度函数)。获得场地特定地震动时程的这种概率描述的能力不仅有助于准确评估任何民用基础设施对象的性能，而且有助于项目业主、政策制定者和保险机构的关键决策过程。例如，如果预测的地面运动太不确定，那么项目业主可能会问以下问题：可以采取什么步骤来减少这种不确定性？在回答这个问题时，还将演示一个评估RHS(震源和路径)和LHS(土性)不确定参数对地震运动总体不确定性的相对贡献的过程。这将有助于项目所有者调动资源，以增加对不确定性的最重要因素的了解(来源？地点？路径？)，减少知识不确定性，从而降低整体地震动不确定性。此外，拟议的通过力学控制方程系统地传播不同不确定性来源的理论能力的发展将极大地有利于经验模型界开发衰减模型，特别是对于数据有限或没有数据的地区(例如，美国东部)。即使对美国西部来说，这也将有助于经验建模者更好地约束他们的模型。此外，该技术还将有助于理解地面运动及其相关不确定性(协方差结构)的空间变化，这是研究界重新关注的问题，特别是由于它们对生命线结构抗震性能的影响。该项目将把最先进的随机微积分与力学原理相结合，开发一个基于有限元的随机计算框架，以在随机的非线性非均匀介质中传播随机波。据我们所知，这是首次尝试在同时考虑LHS和RHS不确定性的随机空间中模拟波在非线性(弹塑性)非均匀介质中的传播。由于材料特性和外力的不确定性存在于所有工程领域，该项目的影响将远远超出仅限于岩土工程领域。为了确保该项目未来的发展，高中科学和数学教师将通过暑期讲习班参与(通过RET补充)，以便他们能够将他们的经验传播到高中课堂。这里的目标是强调数学和物理在模拟地震等物理现象方面的重要性，并在未来的工程师中播下在这一领域寻求职业生涯的早期种子。