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

1338851(道)。这个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更广泛应用的瓶颈。网络活动将侧重于定义一个创新的跨学科领域--可持续人类建筑生态系统(SHBE)，它将人类行为科学、社会科学和经济学与建筑设计、工程和计量学相结合，用于验证建筑能耗和居住舒适度的数据。开发的协作战略和标准化数据平台将显著减少预测人类适应建筑生态系统的能效和可持续性的不确定性，这还将解决基本问题，如“可持续建筑投资对个人、企业或城市规划层面的人有什么好处？”新的SHBE-RCN的活动包括：为一个以IT为基础的、数据联网的研究平台共同开发一个基于共识的机制，允许分享不同生态系统元素构建模式的连接方法；创建网络机制以招募更多参与者或更新工作组；为已确定的分领域制定新的研究方向；评估SHBE网络的成功；以及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，具有国内和国际合作经验，并能够获得各种可持续建筑项目的数据：北得克萨斯大学的陶勇、德里克·D？索萨和露莎娜·汤普森，北卡罗来纳大学夏洛特分校的威廉·托龙和米尔萨德·哈齐卡迪，佛罗里达州立大学的大卫·卡特斯和理查德·费洛克，佛罗里达国际大学的朱一民和托马斯·斯皮格哈尔特，德克萨斯A&AMM大学的韦艳，卡内基梅隆大学的Kee Poh Lam，以及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，并致力于建立一套新的预测模型集成理论，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，可以显著减少人类适应建筑生态系统能源效率和可持续性的预测模型的不确定性。它将把原本无法建立网络的不同领域的研究人员聚集在一起，组成工作组，重点了解来自不同学科的预测模型在五个专题框架内的互操作性(或输入和输出)：一-建筑物理系统和环境建模；二-人类行为建模；三-社会/政策影响建模；四-动态生命周期评估和商业生态系统建模；以及V-模型的整合和验证。所有五个主题都是相互关联的，没有其他主题的重大投入，任何一个主题都不会产生有意义的成果。这个网络？S的研究议程将允许研究人员努力寻找影响人们、他们的社区和他们未来生活的解决方案。在量化可持续建筑生态系统方面为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，帮助城市规划者和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。网络管理小组还将实施一种机制，通过讲习班和实验室访问招聘研究生助理和网络参与者，以促进多样性。这将通过与佛罗里达国际大学工程和计算多样性中心、一个拉美裔服务机构(HSI)以及参与机构的类似倡议来实现。网络参与者还将基于以结果为导向的、多样化和个性化的学习机制的概念，为制定独特的跨学科学习计划做出贡献。

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.