Collaborative Research: RUI: Density of Modes: A New Way to Forecast Sediment Failure

合作研究：RUI：模式密度：预测沉积物破坏的新方法

• 批准号: 2244615
• 负责人: Karen Daniels
• 金额: $ 21.9万
• 依托单位: North Carolina State University
• 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: 2023-03-01 至 2026-02-28
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2244615&HistoricalAwards=false
• 关键词: Collaborative; Research; RUI; Density; Modes

Landslides, submarine slides, ground fissures, and liquefaction are geohazards that occur when near-surface sediments suddenly fail. These geohazards can cause loss of human life and destroy infrastructure. Unfortunately, the scientific community has yet to devise a way to forecast these events. This work aims to determine whether measurements of the density of excited vibrational modes (DoM), a technique that has successfully provided a precursor signal to failure in the laboratory context, provide a route forward. To date, this technique has yet to be tested in natural samples. The researchers will develop the technique first in beach sands, then possibly in more complex near-surface environments, including for data already being collected and published by other groups. Professors on the team will lead a diverse group of STEM students across disciplinary boundaries, using best practices developed by experts that emphasize collaborations and mentorship. The ground beneath our feet shifts over time, sometimes slowly creeping, sometimes flowing like a fluid, and sometimes suddenly failing. These shifts cause landslides, submarine slides, ground fissures, and liquefaction. These geohazards' frequency and destructive capabilities have increased as global warming worsens, sea levels rise, and extreme weather events intensify. The current state-of-the-art lacks a reliable way to forecast these events, largely due to a lack of reliable methods for incorporating soil-scale information into failure models. This proposal hypothesizes that measurements of the density of excited vibrational modes (DoM), a statistical physics quantity that provides well-established failure precursors signals (broadening and increase in excess of low-frequency modes) within lab-reconstituted and numerically simulated granular materials, provides a route forward. The work seeks to answer the following questions: “How do DoM measurements complement and correspond to bulk geophysical measurements?” and “Does the DoM provide insight into the evolving state of naturally-deposited sediments?” These efforts would represent the first application of the DoM technique in the natural sediments; if successful, the translation of the technique to Earth settings would provide a new way to identify and monitor slope stability-related hazards within the near surface.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.

滑坡、海底滑坡、地裂缝和液化是近地表沉积物突然破裂时发生的地质灾害。这些地质灾害可能造成人员伤亡和基础设施破坏。不幸的是，科学界还没有想出一种方法来预测这些事件。这项工作的目的是确定是否激发振动模式（DoM），一种技术，成功地提供了一个前兆信号，在实验室环境中失败的密度测量，提供了一条前进的道路。迄今为止，这项技术尚未在自然样品中进行测试。研究人员将首先在海滩沙子中开发这项技术，然后可能在更复杂的近地表环境中开发，包括其他小组已经收集和发布的数据。团队中的教授将领导一个跨学科界限的STEM学生多元化小组，使用专家开发的强调合作和指导的最佳实践。我们脚下的土地随着时间的推移而变化，有时缓慢爬行，有时像流体一样流动，有时突然失败。这些变化导致山体滑坡、海底滑坡、地裂缝和液化。随着全球变暖、海平面上升和极端天气事件的加剧，这些地质灾害的发生频率和破坏力都在增加。目前的最先进的缺乏一个可靠的方法来预测这些事件，主要是由于缺乏可靠的方法，将土壤尺度的信息到故障模型。该提案假设，激发振动模式（DoM）的密度的测量，一个统计物理量，提供了完善的故障前兆信号（扩大和增加超过低频模式）在实验室重构和数值模拟的颗粒材料，提供了一条前进的道路。这项工作旨在回答以下问题：“如何做DoM测量补充和对应于散装地球物理测量？”和“DoM是否提供了对自然沉积沉积物演变状态的洞察？” 这些努力将代表DoM技术在天然沉积物中的首次应用;如果成功，将该技术转化为地球环境将提供一种新的方法来识别和监测近地表内与边坡稳定性相关的危害。该奖项反映了NSF的法定使命，并被认为值得通过使用基金会的知识价值和更广泛的影响审查标准进行评估来支持。