Hazards SEES Type 1: Predicting Landslide Runout and Granular Flow Hazard: Enhanced-g Centrifuge Experiments, Contact Dynamics Model Development and Theoretical Study

灾害 SEES 类型 1：预测滑坡跳动和颗粒流灾害：增强型离心机实验、接触动力学模型开发和理论研究

• 批准号: 1331499
• 负责人: Colin Stark
• 金额: $ 29.97万
• 依托单位: Columbia University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2013
• 资助国家: 美国
• 起止时间: 2013-09-01 至 2015-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1331499&HistoricalAwards=false
• 关键词: Hazards; SEES; Type; Predicting; Landslide

The broad goal of this project is to address the unpredictability of landslides and debris flows and to boost societal resilience and sustainability in the face of growing landslide hazard and risk across the world. Landslides and debris flows are frequent agents of natural disaster and they pose a particular challenge because their timing, location, size and impact on infrastructure and people are notoriously hard to predict. Such unpredictability undermines society's ability to make accurate risk assessments, to frame safe design principles or to enforce sound engineering codes. This project is being tackled by an interdisciplinary team of computer scientists, engineers and geoscientists working together on laboratory experiments and numerical simulations. The research is framed around enhanced-g experiments conducted on a state-of-the-art geotechnical centrifuge.These experiments are designed to measure the forces driving and resisting landslide motion across a range of simulated scales, to guide development of numerical algorithms to simulate such motion, and to help in the framing of continuum models that can be applied simply to real world problems. The experimental results are to be disseminated as part of a new community initiative for establishing best practices for the sharing of laboratory data. Cutting-edge, open-source, 3d contact dynamics code, tailored to handling eroding granular flows and their impact on the environment, provides a valuable new cross-cutting resource. The project fosters new international collaboration with overseas engineers and geoscientists engaged in both experimental studies and in field assessments of granular flow hazards following recent typhoon and earthquake disasters. Mentoring is provided for two early career researchers and a graduate student in a project of unusual disciplinary breadth.

该项目的广泛目标是解决陆上滑坡和碎屑流的不可预测性，并在面对全球增长的滑坡危险和风险的情况下，提高社会的韧性和可持续性。滑坡和碎屑流是自然灾害的常见代理商，它们构成了一个特殊的挑战，因为它们的时间，位置，规模和对基础设施的影响，人们很难预测人们。 这种不可预测的能力破坏了社会进行准确的风险评估，构架安全设计原则或执行声音工程代码的能力。该项目由计算机科学家，工程师和地球科学家共同进行实验室实验和数值模拟的跨学科团队解决。这项研究是围绕在最先进的岩土工程离心机进行的增强G实验进行了构建的。这些实验旨在测量驾驶和抵抗一系列模拟尺度上的压力滑坡运动的力量，以指导数值算法的开发，以模拟这种运动，并帮助您简单地解决这个问题，以实现现实世界中的问题。实验结果将作为一项新的社区计划的一部分进行传播，以建立共享实验室数据的最佳实践。尖端的，开源的3D接触动力学代码是为处理侵蚀颗粒流及其对环境的影响而定制的，提供了宝贵的新横切资源。该项目促进了与海外工程师和地质学家的新国际合作，并在最近的台风和地震灾难后从事实验研究和现场评估。为两名早期职业研究人员和一名研究生提供了一个不寻常的纪律广度的研究生指导。