Timeless Digital Twins for the Energy Health Nexus

数字双胞胎是自下而上的，要么是楼层，要么是逐栋建筑的库存模型，捕捉到建筑的异质特征。因此，他们可以更好地评估哪些具体措施可能比其他措施更好。然而，目前的数字双胞胎是受时间限制的“快照”模型，代表了某一时间点的建筑或库存，到目前为止还不能反映建筑是如何演变和变化的。在这个项目中，我们将为选定的建筑创建一个永恒的数字双库存模型，该模型不仅全面代表每栋建筑，而且使用通过模型校准验证的众源能源、建筑和室内空气质量数据来持续保持最新。通过结合这些独特的特点，这种新颖的能源和详细的室内空气质量数据的集成提供了一个步骤，使人们能够识别改善能源和环境性能的最佳策略，并更有效地评估措施对当前和未来场景的影响。该项目的目的是创建工程设计流程，并建立建筑性能模拟方法，用于从早期建筑设计到运行阶段集成非住宅建筑的室内空气质量和能源预测。在专业方面，这个项目的目的是培养学生成为以下主题的专家：建筑性能模拟、能源和室内环境质量评估、研究伦理学、EDI、学术写作。

Digital twins are bottom up, either building level or building-by-building stock models capturing the heterogenous characteristics of buildings. They can therefore better assess where specific measures might be better than others. However current digital twins are time-constrained 'snapshot' models, which represent the building or a stock at a certain point in time and until now unable to reflect how buildings evolve and change. In this project we will create a timeless digital twin stock model of selected buildings that not only comprehensively represents each building but is also continually kept up-to date using crowd-sourced energy, building and indoor air quality data which is verified via model calibration. By combining these unique characteristics, this novel integration of energy and detailed indoor air quality data provides a step-change in enabling the identification of the best strategies for improving both energy and environmental performance and more effectively assessing the impact of measures for both current and future scenarios.The aim of this project is to create engineering design processes and establish building performance simulation methods for integration of indoor air quality and energy predictions of non-domestic buildings from early architectural design to operational stages. Professionally the aim of this studentship to train a student to become experts on the following topics: Building performance simulation, Energy and indoor environmental quality evaluation, Research Ethics, EDI, Academic Writing.