Statistical Representation of Large Buildings for Quantita- tive Performance Assessment

用于定量性能评估的大型建筑的统计表示

• 批准号: 8420540
• 负责人: Francis T. Ventre
• 金额: $ 19.88万
• 依托单位: Virginia Polytechnic Institute and State University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 1985
• 资助国家: 美国
• 起止时间: 1985-09-01 至 1989-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=8420540&HistoricalAwards=false
• 关键词: Statistical; Representation; Large; Buildings; Quantita

This project will develop and field-validate analytically tractable methods for statistically representing large buildings, enabling more rigorous assessments of their spatially distributed performance attributes. Measurements for each of four single performance attributes will be made at selected points within the building to generate a time series of attribute performance at a sample point. Aggregating the sample point values into an estimated distribution over the entire building is the principal objective, achieved through theoretical research needed to develop a "Multi-characteristic Spatially Distributed Sampling Method" (MSDSM), and through data from several large buildings and the integration of the traditional single characteristic methods into the multi-characteristic sampling procedures. Data gathering and management in the first half will focus on a precise definition of the kind and quality of data needed to initially calibrate the statistical models under development.

该项目将开发和现场验证分析听话 用于统计表示大型建筑物的方法， 严格评估其空间分布性能 美德.先知-愿 四个单一性能的测量 属性将在建筑物内的选定点进行， 生成样本点处的属性性能的时间序列。 将样本点值聚合到估计分布中， 整个建筑是主要目标，通过 理论研究需要发展一个“多特征 空间分布抽样方法”（MSDSM），并通过来自 几栋大型建筑与传统单体的融合 多特征抽样 程序. 上半年的数据收集和管理将集中在 关于所需数据的种类和质量的精确定义， 初步校准正在开发的统计模型。