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

1338851（陶）。RCN的目标是开发一个合作研究平台，以克服工程，软件和社会/经济科学中阻碍可持续建筑技术广泛应用的瓶颈为中心。该网络的活动将侧重于定义一个创新的新的跨学科领域，“可持续的人类建筑生态系统（SHBE）”，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，用于建筑能耗和居住者舒适度的数据验证。开发的合作战略和标准化数据平台将大大减少预测人类适应建筑生态系统的能源效率和可持续性的不确定性，这也将解决一些基本问题，如“可持续建筑投资在个人、企业或城市规划层面对人们有什么好处？“新的SHBE-RCN的活动包括：为一个信息技术支持的、数据联网的研究平台共同制定一个基于共识的机制，以便分享建立生态系统要素的不同模式的连接方法;创建联网机制，以招募更多的参与者或更新工作组;为确定的分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，具有国内和国际合作经验，并能获得各种可持续建筑项目的数据：Yong Tao，Derrick D？北德克萨斯大学的Souza和Ruthanne Thompson，北卡罗来纳州夏洛特大学的William Tolone和Mirsad Hadzikadic，佛罗里达州立大学的大卫Cartes和Richard Feiock，佛罗里达国际大学的Yimin Zhu和托马斯Spiegelhalter，德克萨斯A M大学的Wei Yan，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旨在促进对人类建设生态系统关键要素之间复杂相互作用的新理解，并致力于建立一套新的预测模型整合理论，以探索以下假设：将居住者行为与从大型现场数据集验证的建筑环境性能相结合，可以显著降低人类适应能源效率的预测模型的不确定性和生态系统建设的可持续性。它将把来自不同领域的研究人员聚集在一起，否则他们将无法在一起建立网络，形成工作组，专注于理解互操作性。（或输入和输出）的预测模型从不同的学科在五个专题框架：I-建筑物的物理系统和环境建模; 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;以及V-模型集成和验证。所有五个主题都相互关联，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。这个网络？的研究议程将使研究人员致力于解决影响人们，他们的社区和他们的生活的未来。为量化可持续建筑生态系统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、政治和金融决策者为人类和自然环境开发最平衡的可持续解决方案。网络管理团队还将实施一项机制，通过讲习班和实验室访问招聘研究生助理和网络参与者，促进多样性。这将通过与佛罗里达国际大学工程和计算多样性中心（一个西班牙裔服务机构（HSI））以及参与机构的类似举措合作来实现。网络参与者还将有助于一个独特的跨学科学习计划的发展，基于结果驱动，多样化和个性化的学习机制的概念。

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.