Emulation of Stochastic Computer Models with an Application to Building Design

Lead Research Organisation: UNIVERSITY OF EXETER
Department Name: Engineering Computer Science and Maths

Abstract

Climate change over the next few decades will affect the way we design buildings. In particular improved insulation and rising temperatures could mean that overheating becomes a serious problem, in both domestic and public buildings (particularly in hospitals). In this PhD we will study the effect of climate change on the thermal properties of buildings. We will use mathematical models of buildings driven by stochastic weather files. These allow us to model the variability in weather. Running the full numerical model of a building is computationally expensive so we build an emulator for this model. An emulator is a fast statistical approximation to the full expensive numerical code. Because we are using stochastic weather fields to drive the model we will need to derive new stochastic emulators that preserve the uncertainty coming from the weather files. Once we have built the emulator we will explore the effect of different future climates and building designs on thermal performance (and overheating). We will investigate the possibility of optimal design for the thermal performance of buildings which will last for the next 50-100 years.

Publications

10 25 50

Studentship Projects

Project Reference Relationship Related To Start End Student Name
EP/N509656/1 01/10/2016 30/09/2021
1917423 Studentship EP/N509656/1 01/10/2017 08/09/2021 Evan Baker
 
Description Emulators are statistical surrogate models used to act in lieu of full, computationally expensive, computer models. During this PhD, new methodology for building emulators was developed, wherein the outputs from a deterministic (i.e. non-noisy) computer model can be linked to the outputs from a stochastic (noisy) computer model. Additionally, a framework for optimising the insulatory properties of a building was developed and showcased (using a complex energy usage model called EnergyPlus, coupled with emulators).
Two journal articles were published as a result of this work.

Additionally, a collaborative project with the American institution SAMSI resulted in a publication explaining how one can build and use emulators for stochastic computer models.
Exploitation Route Academically, the publications directly obtained from the PhD could be taken further. Linking deterministic and stochastic models together to obtain improved results is an interesting avenue for future research, both methodologically and implementing in practice. The review done with aid from SAMSI is a valuable tool for new researchers and practioners who have access to a stochastic computer model and need assistance in performing analysis.

Additionally, the framework developed in the second publication could see use in industry, and seems off-the-shelf capable.
Sectors Energy,Other

 
Description Collaboration with SAMSI 
Organisation Statistical and Applied Mathematical Sciences Institute
Country United States 
Sector Academic/University 
PI Contribution Together, with other academics that attended a SAMSI programme, we wrote and published a review paper
Collaborator Contribution Collaborators helped write and provide content for the review paper
Impact Review paper on statistical emulation for stochastic computer models was written and published: https://projecteuclid.org/journals/statistical-science/volume-37/issue-1/Analyzing-Stochastic-Computer-Models-A-Review-with-Opportunities/10.1214/21-STS822.short. In a way, this is cross disciplinary, including statistics, mathematical modelling, oceanography, ecology, epidimieology, and more.
Start Year 2019