ITR/AP: A COMPUTATIONAL INFRASTRUCTURE FOR RELIABLE COMPUTER SIMULATIONS

ITR/AP：可靠计算机模拟的计算基础设施

• 批准号: 0205181
• 负责人: J. Tinsley Oden
• 金额: $ 55万
• 依托单位: University of Texas at Austin
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2002
• 资助国家: 美国
• 起止时间: 2002-09-15 至 2005-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0205181&HistoricalAwards=false
• 关键词: ITR; AP; COMPUTATIONAL; INFRASTRUCTURE; RELIABLE

EIA-0205181 J. Tinsley Oden University of Texas, Austin ITR/AP: A COMPILATION INFRASTRUCTURE FOR RELIABLE COMPUTER SIMULATIONSThe research of this project will develop mathematical and computational processes for validation analogous to those used for verification and evaluate these processes by actual and computational experiments. At the core of the proposed integrated framework for verification and validation lies the concept of hierarchical modeling. Hierarchical modeling is a systematic coarsening of mathematical models from a base model which is known a priori to contain all of the information, which can be extracted from a given experiment to within quantifiable bounds. The goal is to determine, by introducing approximations into the base model, the computationally simplest model which contains the information content of the experiment. This process requires an ability to evaluate the error introduced by each approximation to the base model, a capability for capturing the semantic content of both models and experiments, a capability for comparing the information content of the experiments and simulations and a capability for implementing a family of computational systems implementing the sequence of models so that the conceptual process can be realized and evaluated.

EIA-0205181 J. Tinsley Oden德克萨斯大学，奥斯汀ITR/AP：可靠计算机仿真的编译基础设施本项目的研究将开发用于验证的数学和计算过程，类似于用于验证的过程，并通过实际和计算实验评估这些过程。 在所提出的综合框架验证和确认的核心是分层建模的概念。 分层建模是从一个基础模型中系统地粗化数学模型，该基础模型先验地已知包含所有信息，这些信息可以从给定的实验中提取到可量化的范围内。 我们的目标是确定，通过引入近似的基础模型，计算最简单的模型，其中包含的信息内容的实验。 这个过程需要一个能力，以评估由每个近似的基础模型，捕获模型和实验的语义内容的能力，比较实验和模拟的信息内容的能力和一个能力，用于实现一系列的计算系统，实现模型的序列，使概念过程可以实现和评估引入的错误。