Improving Building Energy Efficiency through Measurement of Building Physics Properties Using Dynamic Heating Tests

© 2019 the author. Licensee MDPI, Basel, Switzerland.Buildings contribute to nearly 30% of global carbon dioxide emissions, making a significant impact on climate change. Despite advanced design methods, such as those based on dynamic simulation tools, a significant discrepancy exists between designed and actual performance. This so-called performance gap occurs as a result of many factors, including the discrepancies between theoretical properties of building materials and properties of the same materials in buildings in use, reflected in the physics properties of the entire building. There are several different ways in which building physics properties and the underlying properties of materials can be established: a co-heating test, which measures the overall heat loss coefficient of the building; a dynamic heating test, which, in addition to the overall heat loss coefficient, also measures the effective thermal capacitance and the time constant of the building; and a simulation of the dynamic heating test with a calibrated simulation model, which establishes the same three properties in a non-disruptive way in comparison with the actual physical tests. This article introduces a method of measuring building physics properties through actual and simulated dynamic heating tests. It gives insights into the properties of building materials in use and it documents significant discrepancies between theoretical and measured properties. It introduces a quality assurance method for building construction and retrofit projects, and it explains the application of results on energy efficiency improvements in building design and control. It calls for re-examination of material properties data and for increased safety margins in order to make significant improvements in building energy efficiency.Peer reviewedFinal Published versio

Design Implications of Model-Generated Urban Data

Published by the Architectural Research Centers Consortium under the terms of the Attribution-NonCommercial-ShareAlike 4.0 International license.The staggering complexity of urban environment and long timescales in the causal mechanisms prevent designers to fully understand the implications of their design interventions. In order to investigate these causal mechanisms and provide measurable trends, a model that partially replicates urban complexity has been developed. Using a cellular automata approach to model land use types and markets for products, services, labour and property, the model has enabled numerical experiments to be carried out. The results revealed causal mechanisms and performance metrics obtained in a much shorter timescale than the real-life processes, pointing to a number of design implications for urban environments.Peer reviewedFinal Published versio

Lessons learnt from design, off-site construction and performance analysis of deep energy retrofit of residential buildings

The article introduces the process of deep energy retrofit carried out on a residential building in the UK, using a ‘TCosy’ approach in which the existing building is completely surrounded by a new thermal envelope. It reports on the entire process, from establishing the characteristics of the existing building, carrying out design simulations, documenting the off- site manufacture and on-site installation, and carrying out instrumental monitoring, occupant studies and performance evaluation. Multi-objective optimisation is used throughout the process, for establishing the characteristics of the building before the retrofit, conducting the design simulations, and evaluating the success of the completed retrofit. Building physics parameters before and after retrofit are evaluated in an innovative way through simulation of dynamic heating tests with calibrated models, and the method can be used as quality control measure in future retrofit programmes. New insights are provided into retrofit economics in the context of occupants’ health and wellbeing improvements. The wide scope of the lessons learnt can be instrumental in the creation of continuing professional development programmes, university courses, and public education that raises awareness and demand. These lessons can also be valuable for development of new funding schemes that address the outstanding challenges and the need for updating technical reference material, informing policy and building regulations.Peer reviewedFinal Published versio

A Simulation Method for Measuring Building Physics Properties

© International Building performance Simulation Association, 2020.Designing building energy performance with confidence requires accurate information on the properties of building materials and on assemblies of these materials.However, thermal properties of the building in use are rarely compared to manufacturers’ specifications. The approach reported in this paper determines building thermal properties using simulations of dynamic heating tests. It replaces the need for physical tests with the actual buildings, by conducting these tests with calibrated simulation models using data from energy performance monitoring of that building during its normal operation. The resultant method represents a tool for establishing physics properties of buildings in use before and after retrofit, and facilitates quality control of retrofit projects.The results pinpoint major discrepancies between theoretical and actual thermal properties before and after the retrofit, giving practical guidance for safety margins in relation to technical specifications of building material properties and re-evaluation of corresponding technical specifications.Final Published versio

Modelling Computational Fluid Dynamics with Swarm Behaviour

© 2018 The Author(s).The paper looks at replacing the current top-down approach to modelling, predominantly used in dynamic simulation tools, with a nature inspired bottom-up approach based on principles of swarming. Computational fluid dynamics (CFD) is chosen for this research, as one of the most time-consuming processes under the traditional simulation approach. Generally based on Navier-Stokes simultaneous differential equations, CFD requires considerable user preparation time and considerable CPU execution time. The main reason is that the top-down equations represent the system as a whole and generate a large solution space, requiring a solver to find a solution. However, air and building materials do not have cognitive capabilities to solve systems of equations in order to ‘know’ how to transfer heat. Instead, heat transfer occurs through proximity interaction between molecules, leading to self-organised behaviour that is much faster than the behaviour modelled by the top-down systems of equations. The paper investigates how the bottom-up approach using the principles of swarming could improve the speed and interactivity of CFD simulation.Final Published versio

Radical overhaul of construction industry needed if UK to have any chance of net zero by 2050 – new research

Final Published versio

Experiments with Self-Organised Simulation of Movement of Infectious Aerosols in Buildings

© 2020 The Author(s). This is an open access article distributed under the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly citedThe ultimate aim of sustainability in buildings gained an additional new dimension as the start of the year 2020 saw a rapid worldwide spread of the infectious disease caused by a coronavirus named COVID-19. There is evidence that, in addition to person to person contact, the disease transmission occurs through airborne droplets/aerosols generated by breathing, speaking, coughing or sneezing. For that reason, building heating, ventilating and air conditioning systems can play an important role, as they may both contribute as well as reduce the transmission risk. However, there is insufficient understanding of the movement of infectious aerosols in buildings. This article introduces a method of bottom-up emergent modelling of the movement of infectious aerosols in internal space using a physics engine, and reports on simple simulation experiments. The results show that the smallest droplets that are large enough to contain the virus can be suspended in the air for an extended period of time; that turbulent air flow can contribute to the infectious aerosols remaining in the room; and that unidirectional air flow can contribute to purging the room of the infectious aerosols. The model introduced in this article is a starting point for further development and for increasing our understanding of the movement of infectious aerosols in buildings, and thus for increased sustainability of building design.Peer reviewe

Reducing simulation performance gap in hemp-lime buildings using fourier filtering

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).Abstract: Mainstream dynamic simulation tools used by designers do not have a built-in capability to accurately simulate the effect of hemp-lime on building temperature and relative humidity. Due to the specific structure of hemp-lime, heat travels via a maze of solid branches whilst the capillary tubes absorb and release moisture. The resultant heat and moisture transfer cannot be fully represented in mainstream simulation tools, causing a significant performance gap between the simulation and the actual performance. The author has developed an analysis method, based on a numerical procedure for digital signal filtering using Fourier series. The paper develops and experimentally validates transfer functions that enhance simulation results and enable accurate representation of behaviour of buildings built from hemp-lime material using the results of a post-occupancy research project. As a performance gap between design simulation and actual buildings occurs in relation to all buildings, this method has a wider scope of application in reducing the performance gap.Peer reviewedFinal Published versio

Cellular Automata Simulation of Three-dimensional Building Heat Loss

© International Building performance Simulation Association, 2020.Conventional design development and simulation methods provide a top-down approach towards exploration of design solutions. This research identifies this limitation and presents a bottom-up approach framework inspired by nature. Natural interaction processes operate based on component to component interaction. This research re-creates such natural interactions using principles of cellular automata and complexity. Developed simulation models represent the various components of the building fabric and re-create complex natural processes such as heat-loss. The result is an emergent pattern in response to the heat-loss process. This pattern can be utilised as a starting point by designers for design exploration. The contribution of this research is that, through this bottom-up approach it visualises the complex interaction processes of heat-loss and empowers built-environment professionals with a stronger understanding of the building behaviour

Reducing Simulation Performance Gap from Hempcrete Buildings Using Multi Objective Optimization

© International Building performance Simulation Association, 2020.Hempcrete is increasingly used as a construction material, as it provides stable temperature and relative humidity conditions in buildings. In addition to low energy operations, buildings built from hempcrete possess negative embodied CO2, absorbed into the hemp plant material. Hempcrete is hard to represent in design simulations because standard dynamic simulation tools do not have a built-in capability to simulate its effect accurately, due to the specific material structure and combined heat and moisture transfer, causing a considerable performance gap. This paper investigates appropriate specification of key parameters to be used in simulation of hempcrete, to reduce simulation performance gap from hempcrete buildings, using multi objective optimisation, to facilitate hempcrete simulation