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山体滑坡和泥石流的不可预测性，并在世界各地面临日益严重的山体滑坡灾害和风险的情况下提高社会复原力和可持续性。山体滑坡和泥石流是自然灾害的常见因素，它们构成了一个特殊的挑战，因为它们的时间，地点，规模以及对基础设施和人民的影响众所周知难以预测。 这种不可预测性破坏了社会进行准确风险评估、制定安全设计原则或执行合理工程规范的能力。该项目由计算机科学家、工程师和地球科学家组成的跨学科团队共同进行实验室实验和数值模拟。这项研究是围绕增强-g实验进行了国家的最先进的土工离心机。这些实验的目的是测量驱动力和抵抗力的滑坡运动在一系列模拟尺度，以指导数值算法的发展，以模拟这种运动，并帮助在框架的连续体模型，可以简单地应用到真实的世界问题。实验结果将作为建立实验室数据共享最佳做法的新社区倡议的一部分予以传播。尖端的，开源的，3d接触动力学代码，为处理侵蚀颗粒流及其对环境的影响而量身定制，提供了一个有价值的新的交叉资源。该项目促进与从事实验研究和最近台风和地震灾害后颗粒流危害实地评估的海外工程师和地球科学家开展新的国际合作。指导是提供了两个早期的职业研究人员和一个研究生在一个不寻常的学科广度的项目。