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: 1338851
• 负责人: Yong Tao
• 金额: $ 65.28万
• 依托单位: University of North Texas
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2013
• 资助国家: 美国
• 起止时间: 2013-09-01 至 2016-12-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1338851&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（陶）。该RCN的目的是开发一个协作研究平台，该平台以克服工程，软件和社会/经济科学领域的瓶颈，这阻碍了更广泛的可持续建筑技术应用。网络活动将着重于定义一个创新的，新的跨学科领域，即“可持续的人类建设生态系统（SHBE）”，该领域将人类行为科学，社会和经济科学与建筑设计，工程和计量学的科学与建筑能源消费和居住者舒适度的数据验证相结合。开发的协作策略和标准化数据平台将导致预测人类适应能源效率和建筑生态系统的可持续性的不确定性大大减少，这也将解决诸如“在个人，企业或城市计划水平上对人们对人的可持续建筑投资对人的可持续性投资的好处？”？新的SHBE-RCN的活动包括：为IT支持IT的数据网络研究平台共同开发基于共识的机制，允许共享来自构建生态系统元素的不同模型的连接方法；创建网络机制来招募其他参与者或更新工作组；为确定的亚地区开发新的研究方向；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。 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,佛罗里达国际大学的Yimin Zhu和Thomas Spiegelhalter，得克萨斯A＆M大学的Wei Yan，Carnegie Mellon大学的Kee Poh Lam和威斯康星大学 - 麦迪逊分校的Carol Menassa。 SHBE RCN旨在促进对人类建设生态系统的关键要素之间复杂互动的新理解，并致力于建立预测模型的一组新理论，以探索以下假设：将乘员行为整合到从大型现场数据中验证的建立环境性能验证的建立不可测能的能力效果的大型现场数据验证，以实现人类的不确定性和不确定性的效果。 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）和业务生态系统建模；以及V模型集成和验证。所有五个主题都以这样的方式链接，没有任何主题就不会产生有意义的结果，而没有其他主题的重大输入。该网络的研究议程将使研究人员能够致力于影响人们，社区和生活的未来的解决方案。为有意义的研究合作提供了一个可行的平台，以量化可持续建筑生态系统，将使新理论和方法的发展可以帮助城市规划者以及政治和财务决策者为人类和自然环境开发最平衡的可持续解决方案。网络管理团队还将通过研讨会和实验室访问招募研究生助理和网络参与者来实施一种促进多样性的机制。这将通过与佛罗里达国际大学，西班牙裔服务机构（HSI）以及参与机构的类似举措的工程和计算多样性中心合作来实现。网络参与者还将基于结果驱动，多样化和个性化的学习机制的概念，为独特的跨学科学习计划的制定做出贡献。