An Integrated Multi-Scale Stochastic Framework for Dynamic Analysis and Control of Transport Phenomena in Building Systems

用于建筑系统中传输现象动态分析和控制的集成多尺度随机框架

• 批准号: 0556352
• 负责人: Prashant Mehta
• 金额: --
• 依托单位: University of Illinois at Urbana-Champaign
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2006
• 资助国家: 美国
• 起止时间: 2006-09-01 至 2010-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0556352&HistoricalAwards=false
• 关键词: Integrated; Multi; Scale; Stochastic; Framework

AbstractThis project proposes a Dynamical Systems based integrated framework for analysis, detection, and control of transport processes in diverse Building systems applications. The premise of this proposal is that the complexity of transport models is a key technical barrier that prevents effective integrated building system solutions. CFD-based Monte-Carlo simulations for assessing performance is not efficient and complex models are ill-suited for detection, control or design. The objective of the proposal is to develop and demonstrate computationally a mathematical framework that enables a) dynamic analysis, b) study of fundamental limitations in performance, c) sensor architecture definition, and d) detection and control design for complex transport problems in building systems. The innovation of this proposal lies in the re-casting of the transport models as Markov chains on graphs. Markov chains are constructed using efficient set-oriented methods to propagate uncertainty in a multi-scale fashion. This idea incorporates a multi-scale complexity reduction approach to diverse problems in building systems and hence provides for an integrated modeling framework. The approach further has the potential (that will be rigorously explored) to exploit recent advances in both Dynamical Systems and Control Theory.

本项目提出了一个基于动态系统的集成框架，用于分析、检测和控制不同建筑系统应用中的运输过程。 该提案的前提是，运输模式的复杂性是阻碍有效的综合建筑系统解决方案的关键技术障碍。用于评估性能的基于CFD的蒙特-卡罗模拟不是有效的，并且复杂的模型不适合于检测、控制或设计。该提案的目的是开发和演示计算的数学框架，使a）动态分析，B）性能的基本限制的研究，c）传感器架构的定义，和d）检测和控制设计复杂的运输问题，在建筑系统。该方案的创新之处在于将运输模型重新转换为图上的马尔可夫链。马尔可夫链是使用有效的面向集合的方法来构建的，以多尺度的方式传播不确定性。 这个想法结合了一个多尺度的复杂性降低方法，在建筑系统中的各种问题，因此提供了一个集成的建模框架。 该方法还具有利用动力系统和控制理论的最新进展的潜力（将被严格探索）。