Timeless Digital Twins for the Energy Health Nexus

数字孪生是自下而上的，要么是建筑层面的，要么是逐建筑的库存模型，捕捉建筑的异质特征。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，目前的数字孪生是有时间限制的“快照”模型，它代表了特定时间点的建筑物或库存，到目前为止还无法反映建筑物的演变和变化。在这个项目中，我们将为选定的建筑物创建一个永恒的数字孪生库存模型，不仅全面代表每座建筑物，而且还使用众包能源、建筑和室内空气质量数据不断保持最新状态，并通过模型校准进行验证。通过结合这些独特的特征，这种能源和详细的室内空气质量数据的新颖整合提供了一个逐步变化，使能够确定改善能源和环境绩效的最佳策略，并更有效地评估当前和未来方案措施的影响。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，以整合室内空气质量和非住宅建筑从早期建筑设计到运营阶段的能源预测。该项目旨在培养学生成为以下领域的专家：建筑性能模拟、能源和室内环境质量评估、研究伦理、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.