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: 2244614
• 负责人: Vanshan Wright
• 金额: $ 48.03万
• 依托单位: University of California-San Diego Scripps Inst of Oceanography
• 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=2244614&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.

山体滑坡、海底滑坡、地裂缝和液化是近地表沉积物突然消失时发生的地质灾害，这些地质灾害可能导致人员伤亡和基础设施破坏，但科学界尚未找到预测这些事件的方法。这项工作的目的是确定激发振动模式 (DoM) 密度的测量是否能在实验室环境中成功提供故障前兆信号，从而为该技术提供前进的道路。研究人员将首先在海滩沙子中进行测试，然后可能在更复杂的近地表环境中进行测试，包括其他团队已经收集和发布的数据。 STEM 学生跨越学科界限，采用专家开发的强调协作和指导的最佳实践，我们脚下的地面会随着时间的推移而发生变化，有时会缓慢地蠕动，有时会像流体一样流动，有时会导致山体滑坡、海底滑坡、地裂缝，以及随着全球变暖、海平面上升和极端天气事件加剧，这些地质灾害的发生频率和破坏能力不断增加。目前最先进的技术缺乏可靠的方法来预测这些事件，这主要是由于缺乏预测方法。该提案开创了将土壤尺度信息纳入失效模型的可靠方法，激发振动模式（DoM）的密度是一种统计物理量，可提供公认的失效前兆信号（低频范围扩大和增加）。这项工作旨在回答以下问题：“DoM 测量如何补充和对应于批量地球物理测量？”以及“DoM 是否提供了对不断发展的变化的洞察力。”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识别和监测与斜坡稳定性相关的危险的新方法；该奖项反映了 NSF 的法定使命，并通过使用基金会的智力价值和更广泛的影响审查标准进行评估，被认为值得支持。