Collaborative Research: Fusing Massive Disparate Data and Fast Surrogate Models for Probabilistic Quantification of Uncertain Hazards

协作研究:融合海量不同数据和快速替代模型以对不确定危害进行概率量化

基本信息

  • 批准号:
    2053414
  • 负责人:
  • 金额:
    $ 5万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
    Standard Grant
  • 财政年份:
    2021
  • 资助国家:
    美国
  • 起止时间:
    2021-07-01 至 2024-06-30
  • 项目状态:
    已结题

项目摘要

Mitigating the impact of natural hazards, such as volcanic eruptions, earthquakes, or infectious diseases, rests on our ability to accurately quantify hazard risks in advance of their occurrence. This project will tackle this challenge and develop a new computationally feasible framework to integrate disparate field observations and computer simulations. The new framework will deliver substantial upgrades in computational efficiency for natural hazard quantification. One testbed will be the 2018 eruption of the Kilauea Volcano in Hawaii, which injured 23 people and destroyed more than 700 dwellings. For this event, extensive field observations from disparate sources, such as radar satellites, global navigation satellite system receivers, borehole tiltmeters, and seismometers, as well as large-scale computer simulations, will be used to analyze methods for volcanic hazard quantification. The methods developed in the project will be implemented in open-source software available to a wide community of scientists and engineers. The project is complemented by training for both graduate and undergraduate students. The first major roadblock for precisely quantifying uncertain natural hazards is the computational scalability of computer simulations, as they often require the numerical solution of partial differential equations on massive spatio-temporal domains with multi-dimensional input. This challenge will be overcome by developing Gaussian process (GP) emulators as a computationally feasible surrogate model to approximate outcomes of computer experiments. This approach is appealing because it not only includes parallel predictions with linear computational order with respect to the number of coordinates, but it also leverages the correlation between coordinates to enable fast predictive sampling. The second computational challenge is in fusing disparate data from multiple sources to calibrate physical models. The project will address this challenge by quantifying uncertainty in data processing and estimating the discrepancy between the physical model and reality to allow for data integration. While this project focuses on applications in natural hazard quantification, the new GP emulator, computational tools for model calibration, and data integration methods will more generally extend the applicability of data science and machine learning algorithms.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.
减轻火山喷发、地震或传染病等自然灾害的影响,取决于我们在灾害风险发生前准确量化风险的能力。该项目将解决这一挑战,并开发一种新的计算上可行的框架,以整合不同的现场观测和计算机模拟。新的框架将大幅提升自然灾害量化的计算效率。其中一个试验田将是2018年夏威夷基拉韦厄火山喷发,那次喷发造成23人受伤,700多所房屋被毁。在这次活动中,将使用来自不同来源的广泛的现场观测,如雷达卫星、全球导航卫星系统接收器、钻孔倾斜仪和地震仪,以及大规模的计算机模拟,来分析火山危险量化的方法。该项目中开发的方法将在开放源码软件中实施,可供广大科学家和工程师使用。该项目还包括对研究生和本科生的培训。精确量化不确定的自然灾害的第一个主要障碍是计算机模拟的计算可扩展性,因为它们通常需要在具有多维输入的海量时空区域上数值求解偏微分方程组。这一挑战将通过开发高斯过程(GP)仿真器作为计算上可行的替代模型来克服,以近似计算机实验的结果。这种方法很有吸引力,因为它不仅包括相对于坐标数量具有线性计算顺序的并行预测,而且它还利用坐标之间的相关性来实现快速预测采样。第二个计算挑战是融合来自多个来源的不同数据,以校准物理模型。该项目将通过量化数据处理中的不确定性和估计物理模型与现实之间的差异来解决这一挑战,以便进行数据整合。虽然这个项目专注于自然灾害量化方面的应用,但新的GP仿真器、用于模型校准的计算工具和数据集成方法将更广泛地扩展数据科学和机器学习算法的适用性。该奖项反映了NSF的法定使命,并通过使用基金会的智力优势和更广泛的影响审查标准进行评估,被认为值得支持。

项目成果

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Paul Segall其他文献

Look up for magma insights
查找岩浆方面的见解
  • DOI:
    10.1038/ngeo2064
  • 发表时间:
    2014-01-12
  • 期刊:
  • 影响因子:
    16.100
  • 作者:
    Paul Segall;Kyle Anderson
  • 通讯作者:
    Kyle Anderson
Duration of Transient Deformation in Northeast Japan as Observed by Geodetic Data from 1890 to 2010
1890年至2010年大地测量数据观测到的日本东北部瞬态变形持续时间
  • DOI:
  • 发表时间:
    2020
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Angela Meneses-Gutierrez;Paul Segall;and Takeshi Sagiya
  • 通讯作者:
    and Takeshi Sagiya
Modeling dike trajectories in a biaxial stress field with coupled magma flow, fracture, and elasticity
在耦合岩浆流、断裂和弹性的双轴应力场中模拟岩脉轨迹
  • DOI:
    10.1007/s00445-024-01734-8
  • 发表时间:
    2024
  • 期刊:
  • 影响因子:
    3.5
  • 作者:
    L. Blackstone;Benjamin E. Grossman‐Ponemon;E. Heimisson;Adrian J. Lew;Paul Segall
  • 通讯作者:
    Paul Segall
Earthquakes: slow down for safety
地震:为安全减速
  • DOI:
    10.1038/383021a0
  • 发表时间:
    1996-09-05
  • 期刊:
  • 影响因子:
    48.500
  • 作者:
    Paul Segall
  • 通讯作者:
    Paul Segall
Horizontal deformation in NE Japan from triangulation, trilateration, and GPS from 1890 to 2010
1890 年至 2010 年根据三角测量、三边测量和 GPS 得出的日本东北部水平形变
  • DOI:
  • 发表时间:
    2020
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Angela Meneses-Gutierrez;Paul Segall;and Takeshi Sagiya
  • 通讯作者:
    and Takeshi Sagiya

Paul Segall的其他文献

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{{ truncateString('Paul Segall', 18)}}的其他基金

Understanding Dike Propagation Through Comparison of High-fidelity Coupled Fracture and Fluid Flow Models and Field Observations
通过比较高保真耦合裂缝和流体流动模型以及现场观测来了解堤坝的扩展
  • 批准号:
    2333837
  • 财政年份:
    2024
  • 资助金额:
    $ 5万
  • 项目类别:
    Continuing Grant
Insights into Episodic Caldera Collapse and Magmatic Systems from the 2018 Eruption of Kilauea Volcano
从 2018 年基拉韦厄火山喷发洞察火山口火山口崩塌和岩浆系统
  • 批准号:
    2040425
  • 财政年份:
    2021
  • 资助金额:
    $ 5万
  • 项目类别:
    Continuing Grant
Constraints on absolute magma chamber volume from geodetic measurements: Trapdoor faulting in the Galapagos
大地测量对绝对岩浆房体积的限制:加拉帕戈斯群岛的活板门断层
  • 批准号:
    1829763
  • 财政年份:
    2018
  • 资助金额:
    $ 5万
  • 项目类别:
    Standard Grant
Collaborative Research: Probing the frictional behavior of the Tohoku megathrust using GPS, seismicity, and physics-based models
合作研究:利用 GPS、地震活动和基于物理的模型探索东北巨型逆冲断层的摩擦行为
  • 批准号:
    1620496
  • 财政年份:
    2016
  • 资助金额:
    $ 5万
  • 项目类别:
    Continuing Grant
Physics-Based Volcano Geodesy with Application to Effusive Eruptions at Mount St Helens
基于物理的火山大地测量及其在圣海伦斯火山喷发中的应用
  • 批准号:
    1358607
  • 财政年份:
    2014
  • 资助金额:
    $ 5万
  • 项目类别:
    Continuing Grant
Collaborative Research: Geodetic Constraints on Moment Deficit and Physics-based Earthquake Cycle Models in the Source Region of the M 9 Tohoku, Japan Earthquake
合作研究:日本东北9级地震震源区矩差的大地测量约束和基于物理的地震周期模型
  • 批准号:
    1141931
  • 财政年份:
    2012
  • 资助金额:
    $ 5万
  • 项目类别:
    Continuing Grant
Dilatant Stabilization as a Mechanism for Slow Slip Events
膨胀稳定作为慢滑移事件的机制
  • 批准号:
    0838267
  • 财政年份:
    2009
  • 资助金额:
    $ 5万
  • 项目类别:
    Standard Grant
Modeling recent behavior of Mt. St. Helens: extrusion dynamics, deformation, and seismicity
对圣海伦斯山的近期行为进行建模:挤压动力学、变形和地震活动
  • 批准号:
    0910708
  • 财政年份:
    2009
  • 资助金额:
    $ 5万
  • 项目类别:
    Standard Grant
Deformation and Seismicity Accompanying Effusive Silicic Eruptions
伴随硅质喷发的变形和地震活动
  • 批准号:
    0710844
  • 财政年份:
    2007
  • 资助金额:
    $ 5万
  • 项目类别:
    Standard Grant
Collaborative Research: Utilizing GPS Measurements of Postseismic Deformation to Infer Spatial Distribution of Frictional Properties on Faults
合作研究:利用震后变形的 GPS 测量来推断断层摩擦特性的空间分布
  • 批准号:
    0635633
  • 财政年份:
    2007
  • 资助金额:
    $ 5万
  • 项目类别:
    Standard Grant

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