SEES Fellows: Building Informatics: Utilizing Data-Driven Methodologies to Enable Energy Efficiency and Sustainability Planning of Urban Building Systems

SEES 研究员：建筑信息学：利用数据驱动的方法实现城市建筑系统的能源效率和可持续性规划

• 批准号: 1461549
• 负责人: Rishee Jain
• 金额: $ 52.82万
• 依托单位: Stanford University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-09-01 至 2019-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1461549&HistoricalAwards=false
• 关键词: SEES; Fellows; Building; Informatics; Utilizing

The project is supported under the NSF Science, Engineering and Education for Sustainability Fellows (SEES Fellows) program, with the goal of helping to enable discoveries needed to inform actions that lead to environmental, energy and societal sustainability while creating the necessary workforce to address these challenges. Sustainability science is an emerging field that addresses the challenges of meeting human needs without harm to the environment, and without sacrificing the ability of future generations to meet their needs. A strong scientific workforce requires individuals educated and trained in interdisciplinary research and thinking, especially in the area of sustainability science. With the SEES Fellowship support, this project will enable a promising early career researcher to establish himself in an independent research career related to sustainability. This project addresses the fact that buildings are responsible for over 40% of all energy consumption and GHG emissions in the US. The impact of building systems is even more pronounced in dense urban areas like New York City (NYC) where over 75% of GHG emissions come from energy used in buildings. Any transition towards a sustainable NYC will require addressing this energy and pollution intensive built environment. This research proposal aims to integrate data-driven methodologies from information science, social science, network science and urban planning with engineering to increase the energy efficiency and sustainability of urban building systems. Specifically, this project will identify district level energy efficiency opportunities for urban buildings systems, characterize the interdependencies between the built, natural and human environments and model the impact of energy policy instruments to enhance the sustainability and resilience of NYC and Mumbai, India. As a part of this project, the PI will build upon his expertise in civil engineering and building systems by incorporating data science, social science and urban planning into his exploration of energy and sustainability challenges facing urban building systems.

该项目得到了NSF科学，工程和教育可持续发展研究员（SEES研究员）计划的支持，其目标是帮助实现所需的发现，为导致环境，能源和社会可持续性的行动提供信息，同时创造必要的劳动力来应对这些挑战。可持续发展科学是一个新兴的领域，它解决了在不损害环境的情况下满足人类需求的挑战，并且不牺牲后代满足其需求的能力。一个强大的科学队伍需要在跨学科研究和思维方面受过教育和培训的个人，特别是在可持续发展科学领域。在SEES奖学金的支持下，该项目将使一位有前途的早期职业研究人员能够在与可持续发展相关的独立研究生涯中站稳脚跟。该项目解决了建筑物占美国所有能源消耗和温室气体排放量40%以上的事实。建筑系统的影响在像纽约市（NYC）这样的密集城市地区更加明显，超过75%的温室气体排放来自建筑物使用的能源。任何向可持续纽约市的过渡都需要解决这种能源和污染密集的建筑环境。该研究计划旨在将信息科学，社会科学，网络科学和城市规划的数据驱动方法与工程相结合，以提高城市建筑系统的能源效率和可持续性。具体而言，该项目将确定城市建筑系统的地区级能源效率机会，描述建筑、自然和人类环境之间的相互依存关系，并模拟能源政策工具的影响，以提高纽约市和印度孟买的可持续性和复原力。作为该项目的一部分，PI将利用他在土木工程和建筑系统方面的专业知识，将数据科学，社会科学和城市规划纳入他对城市建筑系统面临的能源和可持续性挑战的探索中。