RCN-SEES: Predictive Modeling Network for Sustainable Human-Building Ecosystems (SHBE)

RCN-SEES：可持续人类建筑生态系统预测模型网络 (SHBE)

• 批准号: 1952395
• 负责人: Yong Tao
• 金额: $ 1.48万
• 依托单位: Cleveland State University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-08-19 至 2022-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1952395&HistoricalAwards=false
• 关键词: RCN; SEES; Predictive; Modeling; Network

1338851 (Tao). The objective of this RCN is to develop a collaborative research platform centered on overcoming bottlenecks in engineering, software and social/economic sciences that impede wider application of sustainable building technology. The network activities will focus on defining an innovative, new interdisciplinary area, "Sustainable Human-Building Ecosystem (SHBE)," that integrates human behavioral science, social and economic sciences in tandem with sciences of building design, engineering, and metrology for data validation of building energy consumption and occupant comforts. The developed collaboration strategies and standardized data platform will lead to significant reductions of the uncertainty in predicting human adaptation to energy efficiency and sustainability of building ecosystems, which will also address fundamental questions such as "what are the benefits of sustainable building investment to people at a personal, business, or urban planning level?" The activities of the new SHBE-RCN include: collectively develop a consensus-based mechanism for an IT-enabled, data-networked research platform that allows sharing the connectivity methods from different models of building ecosystem elements; create the networking mechanism to recruit additional participants or update the working groups; develop the new research directions for identified subareas; evaluate the success of the SHBE network; and develop an innovative learning program for graduate students of diverse backgrounds. The steering committee members are from engineering, architecture, computer science, construction, environmental science, business and social science with national and international collaboration experience and access to data from various sustainable building projects: Yong Tao, Derrick D?Souza, and Ruthanne Thompson of the University of North Texas, William Tolone and Mirsad Hadzikadic of the University of North Carolina at Charlotte, David Cartes and Richard Feiock of Florida State University, Yimin Zhu and Thomas Spiegelhalter, of Florida International University, Wei Yan of Texas A&M University, Kee Poh Lam of Carnegie Mellon University, and Carol Menassa of the University of Wisconsin-Madison. The SHBE RCN aims to foster a new understanding of the complex interactions among the key elements of human-building ecosystems and to work towards a set of new theories for integration of predictive models to explore the following hypothesis: Integrating occupant behaviors with built environment performances validated from large field data sets can lead to significant reductions of the uncertainty in predictive models for human adaptation to energy efficiency and sustainability of building ecosystems. It will bring together researchers from different fields, who otherwise would not be able to network together, to form working groups focusing on understanding the interoperability (or inputs and outputs) of predictive models from different disciplines within the five thematic frameworks: I-Building physical system and environment modeling; II-Human behavior modeling; III-Social/policy impact modeling; IV-Dynamic life cycle assessment (LCA) and business ecosystem modeling; and V-Model integration and validation. All five themes are linked in such a way that no single theme will produce meaningful outcomes without the significant input from other themes. This network?s research agenda will allow researchers to work towards solutions impacting people, their communities, and future of their lives. Providing a viable platform for meaningful research collaboration in quantifying the sustainable building ecosystem will enable the development of new theories and methods that could help city planners and political and financial decision makers to develop the most balanced sustainable solutions for both human and natural environment. The network management team will also implement a mechanism to promote diversity by recruiting graduate assistants and network participants through workshops and lab visits. This will be achieved by working with the Center for Diversity in Engineering and Computing at Florida International University, a Hispanic Serving Institution (HSI), and similar initiatives in the participating institutions. The network participants will also contribute to the development of a unique interdisciplinary learning program, based on the concept of an outcome-driven, diverse, and individualized learning mechanism.

1338851（涛）。该 RCN 的目标是开发一个协作研究平台，重点克服工程、软件和社会/经济科学领域阻碍可持续建筑技术更广泛应用的瓶颈。该网络活动将侧重于定义一个创新的、新的跨学科领域，“可持续人类建筑生态系统（SHBE）”，它将人类行为科学、社会和经济科学与建筑设计、工程和计量科学相结合以进行数据验证建筑能耗和居住舒适度。制定的合作战略和标准化数据平台将大大减少预测人类对建筑生态系统的能源效率和可持续性的适应的不确定性，这也将解决诸如“可持续建筑投资对人们有什么好处”等基本问题。个人、商业还是城市规划层面？”新的 SHBE-RCN 的活动包括： 共同开发基于共识的机制，建立一个 IT 支持的数据网络研究平台，允许共享不同构建生态系统要素模型的连接方法；创建网络机制以招募更多参与者或更新工作组；为已确定的子领域制定新的研究方向；评估 SHBE 网络的成功；并为不同背景的研究生制定创新的学习计划。指导委员会成员来自工程、建筑、计算机科学、建筑、环境科学、商业和社会科学领域，拥有国内和国际合作经验，并能够获取各种可持续建筑项目的数据：陶永、Derrick D?Souza 和 Ruthanne Thompson北德克萨斯大学、北卡罗来纳大学夏洛特分校的 William Tolone 和 Mirsad Hadzikadic、佛罗里达州立大学的 David Cartes 和 Richard Feiock、佛罗里达国际大学的 Yimin Zhu 和 Thomas Spiegelhalter、德克萨斯州的 Wei Yan A&M 大学、卡内基梅隆大学的 Kee Poh Lam 和威斯康星大学麦迪逊分校的 Carol Menassa。 SHBE RCN 旨在促进对人类建筑生态系统关键要素之间复杂相互作用的新理解，并致力于建立一套集成预测模型的新理论，以探索以下假设：将居住者行为与经过验证的建筑环境性能相结合来自大型现场数据集的分析可以显着减少人类适应建筑生态系统的能源效率和可持续性的预测模型的不确定性。它将汇集来自不同领域的研究人员，否则他们将无法联系在一起，组建工作组，重点了解五个主题框架内不同学科的预测模型的互操作性（或输入和输出）：系统和环境建模； II-人类行为建模； III-社会/政策影响建模； IV-动态生命周期评估（LCA）和商业生态系统建模； V 模型集成和验证。所有五个主题都以这样一种方式联系在一起，如果没有其他主题的重要投入，任何一个主题都不会产生有意义的结果。该网络的研究议程将使研究人员能够致力于寻求影响人们、他们的社区和他们生活的未来的解决方案。为量化可持续建筑生态系统方面的有意义的研究合作提供一个可行的平台，将有助于开发新的理论和方法，帮助城市规划者以及政治和金融决策者为人类和自然环境制定最平衡的可持续解决方案。网络管理团队还将实施一种促进多样性的机制，通过研讨会和实验室参观来招募研究生助理和网络参与者。这将通过与佛罗里达国际大学工程和计算多样性中心、西班牙裔服务机构 (HSI) 合作以及参与机构的类似举措来实现。网络参与者还将基于结果驱动、多样化和个性化学习机制的概念，为独特的跨学科学习计划的开发做出贡献。