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CAREER: Impact of a coupled energy-carbon-water system on environmentally sustainable building designs under climate variability and automation - a diagnostic-prognostic approach

职业：气候变化和自动化下能源-碳-水耦合系统对环境可持续建筑设计的影响——一种诊断预测方法

基本信息

批准号：
2048093
负责人：
Manish Kumar Dixit
金额：
$ 50.98万
依托单位：
Texas A&M University
依托单位国家：
美国
项目类别：
Continuing Grant
财政年份：
2021
资助国家：
美国
起止时间：
2021-03-01 至 2026-02-28
项目状态：
未结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=2048093&HistoricalAwards=false
关键词：
CAREER Impact coupled energy carbon

项目摘要

Buildings consume over 40% of the global energy supply in their construction and operation as embodied (EE) and operational energy (OE), causing over 39% of total global carbon emissions and consuming an enormous amount of freshwater. To reduce the environmental burden of buildings in design and construction decisions, this project seeks to understand the interdependencies of EE and OE components, their relationship to water use and carbon emission, and the current and future impacts of the energy-carbon-water (ECW) nexus. Three research objectives will be pursued: (1) quantify EE-OE interdependencies by measuring an EE factor that represents the EE expense of saving one unit of OE; (2) examine energy-focused design decisions from an ECW perspective; and (3) investigate how fast-changing energy mix and use may influence future EE-OE interdependencies. The key educational goal is to enhance science education of environmentally sustainable buildings by embedding energy modeling and innovative Virtual Reality (VR)-based learning activities into existing curricula and research training. The educational objectives are: (1) stimulate a diagnostic-prognostic-based sustainable built environment education at the university level; (2) enhance the science education of environmental sustainability at the high school level; and (3) extend tools and resources to architects, engineers, and home builders for broader societal benefits. The research plan offers knowledge and resources to be used by students, who, in turn, create data models to help accomplish the research goal.This study combines building information and energy models from engineering with earth science and economic models to close three knowledge gaps. First, the interdependencies of EE and OE components are not fully understood. This research aim to answer: (1) how do different EE and OE components function and influence each other? and (2) which design measures or EE/OE components may be the main driver of environmental change? Second, it is unclear how design decisions based on EE and OE would differ if energy-related carbon emission and water use are considered. This project will explore how the interplay of a complex ECW system may influence design decisions and which system may be the most impactful. Third, the forces of climate change and automation are shifting building energy use towards electricity. How such a shift may influence future ECW interactions is unclear. This study will explore how the forces of climate variability and automation may alter future states of energy use and environmental change and how such changes may affect the complex ECW system in the future. Through a more diagnostic- prognostic modeling of a building’s environmental impacts, this study seeks to close these gaps and create resources to help architects, engineers, and policy makers make scientifically-informed decisions.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

建筑物在其建造和运营中消耗了全球40%以上的能源供应，其中包括嵌入式能源（EE）和运营能源（OE），占全球碳排放总量的39%以上，并消耗大量淡水。为了减少建筑物在设计和施工决策中的环境负担，本项目旨在了解EE和OE组件的相互依赖性，它们与用水和碳排放的关系，以及能源-碳-水（ECW）关系的当前和未来影响。将追求三个研究目标：（1）量化EE-OE的相互依赖性，通过测量代表节约一个OE单位的EE费用的EE因素;（2）从ECW的角度研究以能源为中心的设计决策;（3）调查快速变化的能源组合和使用如何影响未来的EE-OE相互依赖性。主要的教育目标是通过将能源建模和创新的基于虚拟现实（VR）的学习活动嵌入到现有的课程和研究培训中，加强环境可持续建筑的科学教育。教育目标是：（1）在大学层面促进基于诊断预测的可持续建筑环境教育;（2）在高中层面加强环境可持续性的科学教育;（3）将工具和资源扩展到建筑师，工程师和房屋建筑商，以获得更广泛的社会效益。该研究计划提供了知识和资源，供学生使用，谁，反过来，创建数据模型，以帮助实现研究目标。这项研究结合了建设信息和能源模型，从工程与地球科学和经济模型，以弥补三个知识差距。首先，EE和OE组件的相互依赖性没有得到充分理解。本研究旨在回答：（1）不同的EE和OE组件如何相互作用和影响？以及（2）哪些设计措施或EE/OE组件可能是环境变化的主要驱动力？其次，如果考虑与能源有关的碳排放和用水，基于能效和运行经验的设计决策将有何不同，这一点尚不清楚。该项目将探讨复杂ECW系统的相互作用如何影响设计决策，以及哪个系统可能最有效。第三，气候变化和自动化的力量正在将建筑能源的使用转向电力。这种转变如何影响未来的ECW互动尚不清楚。这项研究将探讨气候变化和自动化的力量如何改变未来的能源使用和环境变化的状态，以及这些变化如何影响未来复杂的ECW系统。通过对建筑物环境影响的诊断-预测模型，这项研究旨在缩小这些差距，并创造资源，帮助建筑师，工程师和政策制定者做出科学明智的决策。该奖项反映了NSF的法定使命，并被认为值得通过使用基金会的智力价值和更广泛的影响审查标准进行评估来支持。