Collaborative Research: High-velocity and long-displacement stick-slips: Experimental analogs of earthquake rupture and the seismic cycle

合作研究：高速和长位移粘滑运动：地震破裂和地震周期的实验模拟

• 批准号: 2240417
• 负责人: Nicola Tisato
• 金额: $ 44.03万
• 依托单位: University of Texas at Austin
• 依托单位国家: 美国
• 项目类别: Continuing 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=2240417&HistoricalAwards=false
• 关键词: Collaborative; Research; velocity; long; displacement

An earthquake develops when rocks deep in the Earth suddenly break, or when sudden offset or 'slip' occurs along a pre-existing fault. Geoscientists lack detailed knowledge of rock failure and fault slip behavior, and this is one reason that efforts to forecast damaging earthquakes have not been entirely successful. Earthquake fault slip begins below the Earth's surface where it cannot be directly observed, so scientists perform laboratory experiments to simulate miniature earthquakes in blocks of rock under controlled conditions. Tisato and their team will develop new laboratory techniques to generate small earthquakes in the lab, and will take detailed measurements of quantities like fault slip speed, rock temperature, vibrations, and fault strength in an effort to better understand their mechanics. Tisato's experiments are unique in that they can simulate long sequences of earthquakes and can see how these earthquakes interact with each other. Knowledge gained from these experiments can be applied to real-world faults using mathematical equations, and may enable scientists to identify phenomena that could signal an upcoming large earthquake.Currently, experimental systems of earthquake processes belong to two general types: (A) Rotary shear apparatuses that produce large displacements under controlled slip-velocity but cannot simulate the spontaneous nucleation, propagation, and seismic recurrence of natural earthquakes, and (B) Stick-slip systems that simulate the spontaneous nature of earthquakes but are limited to small displacements. This proposal will integrate the capabilities of these two experimental types into one system that can simulate the key earthquake features of spontaneous nucleation and rupture propagation, along with millimetric to metric slip displacements. The preliminary results of this unique method already produced a gamut of typical features of natural seismogenic faults, including high-intensity events due to fast rupture propagation and high slip velocity, large slip displacements, foreshocks, and slow-slip events. The planned use of transparent materials and high-speed cameras will allow the observation of the processes happening on the laboratory fault while monitoring acoustic emissions as earthquake analogs. Experiments will also be performed on rock samples, and the analyzed results will be applied to validate natural earthquake models. The intrinsic nature of the method is well-tailored for statistical and machine-learning algorithms that could be used to create earthquake forecasting models. The project will also focus on outreach by creating educational materials and providing laboratory experiment experiences for undergraduate and high-school students.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.

当地球在地球深处突然破裂，或者突然偏移或“滑动”沿着先前存在的断层发生时，地震就会发展。地球科学家缺乏对岩石故障和断层滑移行为的详细知识，这是预测破坏地震的努力并没有完全成功的原因之一。地震断层滑动从无法直接观察到地球表面以下，因此科学家进行了实验室实验，以模拟受控条件下岩石块中的微型地震。 Tisato及其团队将开发新的实验室技术，以在实验室中产生小地震，并将详细测量诸如故障滑移速度，岩石温度，振动和故障强度等数量，以更好地了解其机制。 Tisato的实验是独一无二的，因为它们可以模拟长序列地震，并可以看到这些地震如何相互作用。从这些实验中获得的知识可以使用数学方程式应用于现实世界中的故障，并可以使科学家能够识别出可能向即将发生的大地震发出的现象。目前，地震过程的实验系统属于两种一般类型：（a）旋转剪切。在受控的滑移下产生较大位移但无法模拟自然地震的自发成核，传播和地震复发的设备，以及（b）模拟地震自发性质但仅限于小型位移的粘性滑滑系统。该建议将将这两种实验类型的能力整合到一个系统中，该系统可以模拟自发成核和破裂传播的关键地震特征，以及毫米到度量滑移位移。这种独特方法的初步结果已经产生了一系列自然地震源性断层的典型特征，包括由于快速破裂的传播和高滑动速度，大型破裂，大型滑移位移，前锁和慢速滑滑事件而引起的高强度事件。计划使用透明材料和高速相机将允许观察实验室断层上发生的过程，同时监测声音排放作为地震类似物。实验还将在岩石样品上进行，分析结果将用于验证天然地震模型。该方法的内在性质是针对可用于创建地震预测模型的统计和机器学习算法的详尽量。该项目还将通过创建教育材料并为本科和高中生提供实验室实验经验来关注外展。该奖项反映了NSF的法定任务，并被认为是值得通过基金会的知识分子和更广泛影响的评估评估标准的评估来支持的。