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: 1200196
• 负责人: Kallol Sett
• 金额: $ 22.21万
• 依托单位: University of Akron
• 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 2014-02-28
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1200196&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.

现有的地震地面运动预测方法及其相关的不确定性主要依赖于拟合记录的运动（通常在表面）与已知的地震和场地特征。 然而，这样获得的概率地面运动的岩土工程问题，如自由场概率现场响应分析或概率土-结构相互作用分析的应用，双重计数的不确定性和非线性的土壤介质。 这个项目的目标是开发一种新的、基于物理学的方法和一种伴随的计算工具来获得完整的概率描述通过（1）表征和量化未来地震事件期间场地处基岩运动的不确定性，（右手侧（RHS）不确定性），（2）表征和量化特定场地土壤性质中的不确定性（左手侧（LHS）不确定性），以及（3）通过不确定土壤传播不确定基岩运动。 获得这种场地特定地震动时程的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：可以采取什么措施来减少这种不确定性？在回答这个问题时，RHS（震源和路径）和LHS（土壤性质）不确定性参数对地震运动总体不确定性的相对贡献的评估过程也将得到证明。 这将有助于项目所有者调动资源，以加深对不确定性最重要因素的了解（来源？网站？路径？），减少知识的不确定性，并随后减少整体地面运动的不确定性。 此外，拟议的理论能力的发展，系统地传播不同来源的不确定性，通过力学的控制方程将大大有利于经验建模社区在开发衰减模型，特别是在有有限的或没有数据的地区（例如，美国东部）。 即使对于美国西部，它也将帮助经验建模者更好地约束他们的模型。此外，所提出的技术也将提供洞察力，了解地面运动的空间变化及其相关的不确定性（协方差结构），这是在研究界的新的兴趣，特别是由于其对生命线结构的抗震性能的影响。本计画将联合收割机结合最新的随机微积分与力学原理，发展一个以有限元素为基础的随机计算架构，以在随机非线性非均匀介质中传播随机波。据我们所知，这是第一次尝试模拟波通过非线性（弹塑性）非均匀介质中的随机空间，同时考虑LHS和RHS的不确定性。 由于材料特性和外力的不确定性存在于所有工程领域，因此该项目的影响将远远超出岩土工程领域。 为了确保这一项目的未来发展，高中科学和数学教师将通过暑期讲习班参与（通过可再生能源技术补充），以便他们能够将自己的经验传授给高中课堂。这里的目的是强调数学和物理在建模物理现象，如地震和植物的早期种子之间的未来工程师寻求在这一领域的职业生涯的重要性。