A Variational Principle Based Study of Random Front Speeds

基于变分原理的随机前沿速度研究

基本信息

  • 批准号:
    0506766
  • 负责人:
  • 金额:
    $ 10.5万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
    Standard Grant
  • 财政年份:
    2005
  • 资助国家:
    美国
  • 起止时间:
    2005-07-01 至 2005-10-31
  • 项目状态:
    已结题

项目摘要

Abstract: DMS-0506766, J Xin, University of TexasTitle: A Variational Principle Based Study of Random Front Speeds The project pursues analysis and computation of reaction-diffusionfront speeds in random media based on their variational principles.Direct computation of the speed ensemble can be both expensiveand less accurate. Because front speeds are part of the large time(large scale) behavior of solutions to stochastic reaction-diffusion equations, one needs a large domain size, sufficient resolution of front structures, and many realizations of random samples. The variational principles are establishedby exploiting the analytical and probabilistic properties of solutions. Significant dimensional reductions are achieved so that onlyassociated linear problems need to be solved to find principaleigenvalues or Lyapunov exponents. Besides being a useful tool for analysis of speed statistics, the variational principles also help to generate fast and efficient computational algorithms. The project willexplore this approach to study front speeds in various space/time random media, the speed asymptotic laws and the dependence on statistics of random media.The project is motivated by flame fronts in the environment (forest or building fires) and internal combustion engines of vehicles, where fluid (air or liquid) motion could alter the speed of burning processsignificantly. The fluid motion often contains uncertainties andcan be best described as random media. Scientific understandingand efficient computing of front speeds can help to control thespread of flames, and minimize the waste gases from the combustion enginesto benefit the environment. The methods being developed in the project will contribute to both the understanding and computingof random fronts, a subject largely in its infancy.
摘要:DMS-0506766,J Xin,德克萨斯大学标题:基于变分原理的随机波阵面速度研究该项目基于变分原理对随机介质中的反应扩散波阵面速度进行分析和计算,直接计算速度系综既昂贵又不准确。由于前沿速度是随机反应扩散方程解的大时间(大尺度)行为的一部分,因此需要较大的区域大小、足够的前沿结构分辨率和许多随机样本的实现。变分原理是利用解的解析和概率性质建立的。实现了显著的降维,因此只需解决相关的线性问题即可找到主特征值或Lyapunov指数。变分原理除了是速度统计分析的有用工具外,还有助于生成快速高效的计算算法。该项目将探索这种方法来研究各种空间/时间随机介质中的前沿速度、速度渐近规律和随机介质的统计相关性。该项目的动机是环境(森林或建筑火灾)和车辆内燃机中的火焰前沿,其中流体(空气或液体)运动可以显著改变燃烧过程的速度。流体运动通常包含不确定性,可以最好地描述为随机介质。对发动机前缘速度的科学认识和有效计算,有助于控制火焰的蔓延,最大限度地减少内燃机废气对环境的影响。该项目正在开发的方法将有助于理解和计算随机前沿,这是一个在很大程度上处于初级阶段的学科。

项目成果

期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)

数据更新时间:{{ journalArticles.updateTime }}

{{ item.title }}
{{ item.translation_title }}
  • DOI:
    {{ item.doi }}
  • 发表时间:
    {{ item.publish_year }}
  • 期刊:
  • 影响因子:
    {{ item.factor }}
  • 作者:
    {{ item.authors }}
  • 通讯作者:
    {{ item.author }}

数据更新时间:{{ journalArticles.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ monograph.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ sciAawards.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ conferencePapers.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ patent.updateTime }}

Jack Xin其他文献

A structure-preserving scheme for computing effective diffusivity and anomalous diffusion phenomena of random flows
计算随机流的有效扩散率和反常扩散现象的结构保持方案
  • DOI:
    10.48550/arxiv.2405.19003
  • 发表时间:
    2024
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Tan Zhang;Zhongjian Wang;Jack Xin;Zhiwen Zhang
  • 通讯作者:
    Zhiwen Zhang
Finite Element Computation of KPP Front Speeds in Cellular and Cat#39;s Eye Flows
Cellular 和 Cat 中 KPP 前沿速度的有限元计算
Learning Sparse Neural Networks via \ell _0 and T \ell _1 by a Relaxed Variable Splitting Method with Application to Multi-scale Curve Classification
通过松弛变量分裂方法通过 ell _0 和 T ell _1 学习稀疏神经网络并应用于多尺度曲线分类
Design projects motivated and informed by the needs of severely disabled autistic children
设计项目以严重残疾自闭症儿童的需求为动力和信息
Three $$l_1$$ Based Nonconvex Methods in Constructing Sparse Mean Reverting Portfolios
  • DOI:
    10.1007/s10915-017-0578-5
  • 发表时间:
    2017-10-20
  • 期刊:
  • 影响因子:
    3.300
  • 作者:
    Xiaolong Long;Knut Solna;Jack Xin
  • 通讯作者:
    Jack Xin

Jack Xin的其他文献

{{ item.title }}
{{ item.translation_title }}
  • DOI:
    {{ item.doi }}
  • 发表时间:
    {{ item.publish_year }}
  • 期刊:
  • 影响因子:
    {{ item.factor }}
  • 作者:
    {{ item.authors }}
  • 通讯作者:
    {{ item.author }}

{{ truncateString('Jack Xin', 18)}}的其他基金

Deep Particle Algorithms and Advection-Reaction-Diffusion Transport Problems
深层粒子算法与平流反应扩散传输问题
  • 批准号:
    2309520
  • 财政年份:
    2023
  • 资助金额:
    $ 10.5万
  • 项目类别:
    Standard Grant
Collaborative Research: ATD: Fast Algorithms and Novel Continuous-depth Graph Neural Networks for Threat Detection
合作研究:ATD:用于威胁检测的快速算法和新颖的连续深度图神经网络
  • 批准号:
    2219904
  • 财政年份:
    2023
  • 资助金额:
    $ 10.5万
  • 项目类别:
    Standard Grant
Computational and Mathematical Studies of Compression and Distillation Methods for Deep Neural Networks and Applications
深度神经网络压缩和蒸馏方法的计算和数学研究及应用
  • 批准号:
    2151235
  • 财政年份:
    2022
  • 资助金额:
    $ 10.5万
  • 项目类别:
    Continuing Grant
FRG: Collaborative Research: Robust, Efficient, and Private Deep Learning Algorithms
FRG:协作研究:稳健、高效、私密的深度学习算法
  • 批准号:
    1952644
  • 财政年份:
    2020
  • 资助金额:
    $ 10.5万
  • 项目类别:
    Standard Grant
Computational and Mathematical Studies of Complexity Reduction Methods for Deep Neural Networks and Applications
深度神经网络复杂度降低方法的计算和数学研究及应用
  • 批准号:
    1854434
  • 财政年份:
    2019
  • 资助金额:
    $ 10.5万
  • 项目类别:
    Standard Grant
Collaborative Research: ATD: Robust, Accurate and Efficient Graph-Structured RNN for Spatio-Temporal Forecasting and Anomaly Detection
合作研究:ATD:用于时空预测和异常检测的鲁棒、准确和高效的图结构 RNN
  • 批准号:
    1924548
  • 财政年份:
    2019
  • 资助金额:
    $ 10.5万
  • 项目类别:
    Standard Grant
BIGDATA: Collaborative Research: F: Foundations of Nonconvex Problems in BigData Science and Engineering: Models, Algorithms, and Analysis
BIGDATA:协作研究:F:大数据科学与工程中非凸问题的基础:模型、算法和分析
  • 批准号:
    1632935
  • 财政年份:
    2016
  • 资助金额:
    $ 10.5万
  • 项目类别:
    Standard Grant
Theory and Algorithms of Transformed L1 Minimization with Applications in Data Science
变换 L1 最小化的理论和算法及其在数据科学中的应用
  • 批准号:
    1522383
  • 财政年份:
    2015
  • 资助金额:
    $ 10.5万
  • 项目类别:
    Standard Grant
Reaction-Diffusion Front Speeds in Chaotic and Stochastic Flows
混沌和随机流中的反应扩散前沿速度
  • 批准号:
    1211179
  • 财政年份:
    2012
  • 资助金额:
    $ 10.5万
  • 项目类别:
    Continuing Grant
ATD: Blind and Template Assisted Source Separation Algorithms with Applications to Spectroscopic Data
ATD:盲和模板辅助源分离算法及其在光谱数据中的应用
  • 批准号:
    1222507
  • 财政年份:
    2012
  • 资助金额:
    $ 10.5万
  • 项目类别:
    Continuing Grant

相似海外基金

Study for reformation of the hearsay exceptions based on the best evidence principle
基于最佳证据原则的传闻证据例外改革研究
  • 批准号:
    23K01149
  • 财政年份:
    2023
  • 资助金额:
    $ 10.5万
  • 项目类别:
    Grant-in-Aid for Scientific Research (C)
Simulation studies of the interaction between turbulent and neoclassical transport in three-dimensional magnetic plasma based on the global first principle model
基于全局第一性原理模型的三维磁等离子体中湍流与新古典输运相互作用的模拟研究
  • 批准号:
    23K03364
  • 财政年份:
    2023
  • 资助金额:
    $ 10.5万
  • 项目类别:
    Grant-in-Aid for Scientific Research (C)
Development of high-speed random access vision principle based on mirror array
基于镜面阵列的高速随机存取视觉原理研制
  • 批准号:
    23K18473
  • 财政年份:
    2023
  • 资助金额:
    $ 10.5万
  • 项目类别:
    Grant-in-Aid for Challenging Research (Exploratory)
Theory and Practice of Deep Learning Based on Fisher Information Matrix and MDL Principle
基于Fisher信息矩阵和MDL原理的深度学习理论与实践
  • 批准号:
    23H05492
  • 财政年份:
    2023
  • 资助金额:
    $ 10.5万
  • 项目类别:
    Grant-in-Aid for Scientific Research (S)
Establishment of a new quantitative evaluation method for detecting concrete defects by automatic scanning based on the principle of radiation scattering attenuation.
基于辐射散射衰减原理建立自动扫描检测混凝土缺陷定量评价新方法。
  • 批准号:
    23H01556
  • 财政年份:
    2023
  • 资助金额:
    $ 10.5万
  • 项目类别:
    Grant-in-Aid for Scientific Research (B)
Seeking universal principle for nonequilibrium thermodynamics based on differential geometry
基于微分几何寻求非平衡热力学普遍原理
  • 批准号:
    22H01141
  • 财政年份:
    2022
  • 资助金额:
    $ 10.5万
  • 项目类别:
    Grant-in-Aid for Scientific Research (B)
Developments of walking robot based on passive walking and walking assist device based on principle of the robot
基于被动行走的行走机器人及基于机器人原理的行走辅助装置的研制
  • 批准号:
    22K04015
  • 财政年份:
    2022
  • 资助金额:
    $ 10.5万
  • 项目类别:
    Grant-in-Aid for Scientific Research (C)
A refinement of the principle of typicality based on the analysis of Wigner's friend in quantum mechanics
基于维格纳量子力学朋友的分析对典型性原理的细化
  • 批准号:
    22K03409
  • 财政年份:
    2022
  • 资助金额:
    $ 10.5万
  • 项目类别:
    Grant-in-Aid for Scientific Research (C)
Rapid carbon-heteroatom bond formation based on elucidation of the principle of gold nanoparticle-acid-base cooperation
基于金纳米粒子-酸碱合作原理的快速碳-杂原子键形成
  • 批准号:
    21H01719
  • 财政年份:
    2021
  • 资助金额:
    $ 10.5万
  • 项目类别:
    Grant-in-Aid for Scientific Research (B)
Material evaluation technology that is opened up by spectroscopy principle based on the direct acquisition of optical response function
基于直接获取光学响应函数的光谱学原理开辟的材料评价技术
  • 批准号:
    21H05014
  • 财政年份:
    2021
  • 资助金额:
    $ 10.5万
  • 项目类别:
    Grant-in-Aid for Scientific Research (S)
{{ showInfoDetail.title }}

作者:{{ showInfoDetail.author }}

知道了