The aim of this project is to investigate how light gauge steel modular construction can be used to provide affordable, low energy, comfortable homes.
The project uses a mixed methods approach, focusing primarily on building monitoring and building dynamic thermal simulations, but also using qualitative data from observation and participant questionnaires.
Two existing modular buildings have been chosen for case studies, they are both student halls of residences, one based in Loughborough and the other in London.
These buildings are currently being monitored and modelled to determine both real and predicted energy and thermal performance. The results will be compared and the reason for any gap between prediction and reality investigated. The aim is to use the data collected to calibrate the model and reduce the gap.
The calibrated model will then be used to investigate design options to reduce the energy demand, and ensure thermal comfort, in modular domestic buildings
Thermal comfort, internal temperatures and overheating is particularly important because steel modular construction is often thermally lightweight, which means there is a significant risk of overheating, both now, and increasingly into the future if the climate continues to warm.
A truly viable design solution must not only meet the carbon targets, but must also create a safe and comfortable environment for its occupants throughout the life of the building.
Challenges in Building Monitoring
To date, my biggest challenge has been to monitor real modular buildings, so much is required to create a plan and then to realise it.
I use the term monitoring, to describe the continuous measurement of a range of parameters over time. I am using a variety of sensors which communicate wirelessly with a controller unit, which I can access remotely over the internet.
This setup allows me, at any time throughout the study, to observe current and historic conditions, to download and analyse data, and to make improvements and resolve any issues as soon as they are realised.
Achieving an installation that works has been very challenging for numerous reasons, but largely because of the complications around monitoring electricity use.
Why Monitor and Measure?
I wanted to investigate the real performance in modular buildings because of the existence of a ‘performance gap’ when models are used alone.
Determining the energy demand or internal environment of any building using physics is complicated due to the large number of dynamic, interacting systems that affect energy and environment. The attempt to do so through building models is challenging, and it has been shown that models can often under-predict energy use for buildings, and may not adequately consider thermal comfort and overheating.
The reasons for the ‘performance gap’ are multivariate, and may differ from building to building, from model to model, and from investigator to investigator.
Causes of a performance gap include, but are not limited to:
Through monitoring and measuring, I am obtaining an understanding and data about the real operation and performance of the modular buildings in my studies. This allows me to use field data as inputs into a model; the aim is to reduce the gap between prediction and reality, and thus create a calibrated model. Calibration of the model provides increased confidence in the model’s predictions; which can then be used to investigate design changes for the purpose of improving energy and thermal performance.
Monitoring and measuring buildings, does not only give quantitative data to input into the model; it also provides qualitative data about countless factors, which can give insight into design improvements.
The qualitative data comes from a variety of sources including:
Which Parameters to Monitor and Measure?
There are so many parameters that are important to energy demand, sustainability, and internal environment, and it is impossible to monitor them all in one project. Therefore it was necessary to determine which parameters were the most important for my project aim.
The following parameters were selected for monitoring in two case study buildings over a number of months:
The following parameters were selected for one-off measurements:
These parameters have been selected because they provide a good insight into: