Reevaluating the Experimental Foundation for the Rheology of Crust-Forming Minerals

重新评估结壳矿物流变学的实验基础

• 批准号: 2208393
• 负责人: Jun Korenaga
• 金额: $ 14.1万
• 依托单位: Yale 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: 2023-01-01 至 2024-12-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2208393&HistoricalAwards=false
• 关键词: Reevaluating; Experimental; Foundation; Rheology; Crust

The Earth's crust is constantly deforming in response to applied forces, and at depths where temperatures and pressures are high (typically about ten miles or more below the surface), rocks slowly flow (or "creep") rather than breaking as they do at shallower depths. The mathematical relationship describing this creep is called a "flow law", and it depends on the flow laws of the rock's component minerals. Many experiments have been done to define mineral flow laws, but they all have one drawback: the experiments have to be completed within months rather than millions of years, so samples must be deformed ten billion times faster than in the Earth. To get around this problem, the equations derived from laboratory experiments have to be as precise as possible. Korenaga will address this issue by applying sophisticated statistical methods to obtain new mineral flow laws from experimental deformation data that has been produced over the years by other scientists. He will recruit a group of undergraduate students to do this analysis for a wide range of minerals, which will give them valuable research and data science experience. Using these new flow laws, geophysicists will be able to more confidently apply their numerical models to understanding plate tectonics and how slow deformation deep in the Earth leads to earthquakes.Incorporating realistic rock mechanics via ductile flow laws has become increasingly common in geophysical modeling, as seen in recent studies on the dynamics of continental lithosphere. However, considerable extrapolation is involved when using experimentally-derived rheology in numerical modeling. Strain rates attained in laboratories are usually on the order of 10-5 s-1, which is ten orders of magnitude faster than geological strain rates (10-15 s-1). When estimating a flow law from rock deformation data, therefore, it becomes essential to conduct a rigorous statistical analysis, by considering all experimental uncertainties, so that a flow law can be trusted for extrapolation over ten orders of magnitude. This project plans to conduct a series of reanalysis of published deformation data for crust-forming minerals, capitalizing on the Markov Chain Monte Carlo (MCMC) inversion method that has been developed over the last decade to investigate the rheology of olivine The project is based on the two-fold potential of the MCMC-based reanalysis of published deformation data. First, a short-term project using MCMC inversion has a definite appeal for physics undergraduates who already have familiarity with the technique, and a reanalysis project can serve as their entry point for earth sciences. The use of MCMC in data analysis is now part of standard data science, so this practical aspect also helps to attract undergraduates with solid quantitative skills. Second, producing a series of reanalysis results, through multiple summer intern projects, will build a collection of case studies for the deformation of different minerals and rocks. The aim of building a collection of case studies is to provide a “critical mass” so that the community of crustal dynamics, including numerical modelers, rock mechanicists, and field geologists and geophysicists, will recognize the importance of the rigorous analysis of rock deformation data.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.

地壳在外力作用下不断变形，在温度和压力较高的深度（通常在地表以下10英里或更深），岩石缓慢流动（或“蠕变”），而不是像在较浅的深度那样破裂。描述这种蠕变的数学关系称为“流动定律”，它取决于岩石成分矿物的流动定律。人们已经做了许多实验来定义矿物流动定律，但它们都有一个缺点：实验必须在几个月内完成，而不是数百万年，因此样品必须以比地球快100亿倍的速度变形。为了解决这个问题，从实验室实验中得出的方程必须尽可能精确。Korenaga将通过应用复杂的统计方法来解决这个问题，从其他科学家多年来产生的实验变形数据中获得新的矿物流动规律。他将招募一群本科生对各种矿物进行分析，这将为他们提供宝贵的研究和数据科学经验。利用这些新的流动定律，地球物理学家将能够更自信地应用他们的数值模型来理解板块构造以及地球深处的缓慢变形如何导致地震。通过韧性流动定律来描述现实的岩石力学在地球物理建模中越来越普遍，正如最近对大陆岩石圈动力学的研究所见。然而，相当多的外推涉及时，使用实验推导的流变学数值模拟。在实验室中获得的应变速率通常在10-5 s-1的数量级上，这比地质应变速率（10-15 s-1）快十个数量级。因此，当从岩石变形数据估计流动定律时，必须进行严格的统计分析，考虑所有实验的不确定性，以便流动定律可以被信任地外推超过十个数量级。该项目计划对已发表的地壳形成矿物变形数据进行一系列再分析，利用过去十年来开发的马尔可夫链蒙特卡罗（MCMC）反演方法来研究橄榄石的流变学。该项目基于对已发表变形数据进行MCMC再分析的双重潜力。首先，使用MCMC反演的短期项目对已经熟悉该技术的物理本科生具有一定的吸引力，而再分析项目可以作为他们进入地球科学的切入点。 在数据分析中使用MCMC现在是标准数据科学的一部分，因此这一实用方面也有助于吸引具有扎实定量技能的本科生。第二，通过多个暑期实习项目产生一系列再分析结果，将建立一系列不同矿物和岩石变形的案例研究。建立一个案例研究集的目的是提供一个“临界质量”，以便地壳动力学界，包括数值模拟师、岩石力学家、野外地质学家和岩石力学家，该奖项反映了NSF的法定使命，并被认为是值得通过使用基金会的智力价值和更广泛的影响进行评估的支持审查标准。