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Climatic responsive heating and cooling for indoor thermal environments

  • Full or part time
    Dr R Yao
  • Application Deadline
    Applications accepted all year round
  • Self-Funded PhD Students Only
    Self-Funded PhD Students Only

Project Description

Climate change and regional climates significantly impact on energy consumption of heating and cooling for achieving thermal comfort. Building energy consumption accounts for large proportion in cities. The estimation of building stock energy consumption in the city level is important for the policy-makers in terms of energy conservation strategies. The PhD research will focus on developing robust, simplified, predictive models of heating and cooling energy with responding to the climate characteristics and end-users thermal comfort needs. Computer simulations and regression methods will applied in the research. The research will include inter-linked aspects of 1) classification of climates characteristic and climate change scenarios; 2) classification of end-users’ needs ( occupancy patterns, thermal comfort requirements); and 3) building stock information of a case study city. Energy modelling and dynamic simulations will be performed. Based on the high-resolution hourly dynamic simulation results and an uncertainty analysis, a simplified /reduced-order model (ROM) for building stock energy consumption is expected to be developed using rigorous modelling techniques. Finally, factor analysis will be performed using the developed reduced-order model to analysis the impact of climates, user patterns, and engineering technologies and cost effectiveness of heating/cooling energy in cities.

Funding Notes

First-class or 2.1 (Hons) degree, or Masters degree (or equivalent) in an appropriate subject such as building physics, thermal and mechanical engineering. Applicants will be judged on their academic experience, their understanding of the proposed research topic and their references

How good is research at University of Reading in Architecture, Built Environment and Planning?

FTE Category A staff submitted: 34.90

Research output data provided by the Research Excellence Framework (REF)

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