REuse of Structural sTeel in cOnstRuction (RESTOR)
Lead Research Organisation:
University of Birmingham
Department Name: Civil Engineering
Abstract
Steel buildings form the vast majority of multi-storey and industrial buildings in the UK. More than 85% of the structural steel in existing buildings is recycled at the end of their service life whereas less than 15% is reused. However, steel recycling is energy-demanding and contributes to the UK iron and steel industry being the largest industrial sector in terms of both energy demands and greenhouse gas emissions. Thus, there is a genuine need for cutting-edge technical innovations embedded in the circular economy that maximizes sustainable, efficient and low-energy reuse, rather than energy-demanding recycling, of structural steel.
RESTOR is the first project of its kind to apply sophisticated non-destructive testing (NDT), machine learning optimization, and building information modelling to reuse structural steel in construction. At the end of the first lifespan of used steel members (e.g., beams, columns, braces), RESTOR will allow their material properties to be determined based on NDT measurements. RESTOR will optimize the repurposing of used steel members and validate their structural performance during their second lifespan. It will develop a new, validated and optimized state-of-the-art generative design tool that will create automated and optimized building configurations made of used steel members. The outputs of RESTOR will therefore enable sustainable delivery of the infrastructure projects planned as part of the post-COVID-19 economic recovery strategy.
RESTOR is the first project of its kind to apply sophisticated non-destructive testing (NDT), machine learning optimization, and building information modelling to reuse structural steel in construction. At the end of the first lifespan of used steel members (e.g., beams, columns, braces), RESTOR will allow their material properties to be determined based on NDT measurements. RESTOR will optimize the repurposing of used steel members and validate their structural performance during their second lifespan. It will develop a new, validated and optimized state-of-the-art generative design tool that will create automated and optimized building configurations made of used steel members. The outputs of RESTOR will therefore enable sustainable delivery of the infrastructure projects planned as part of the post-COVID-19 economic recovery strategy.
Organisations
- University of Birmingham (Lead Research Organisation)
- Nolan Associates (Project Partner)
- Tata Steel (UK) (Project Partner)
- ISG Construction Limited (Project Partner)
- HCL Technologies UK Limited (Project Partner)
- Chetwoods Associates Services Ltd (Project Partner)
- Atkins Group Limited (Project Partner)
- PTC Inc. (Project Partner)
- Trimble, Inc. (International) (Project Partner)
- Steel Construction Institute (Project Partner)
Publications

Kookalani S
(2023)
Reinventing Steel with AI: Towards a Sustainable Future in Construction

Kookalani S
(2024)
Exploring Deep Generative Models in Building Design


Kookalani S
(2024)
Trajectory of building and structural design automation from generative design towards the integration of deep generative models and optimization: A review
in Journal of Building Engineering
Description | Preliminary results from experiments and computer simulations show that by combining on-site non-destructive testing, existing data, and machine learning-based optimisation, steel members from old structures can be successfully reused to build new ones. |
Exploitation Route | the generative web design (that is being developed) can be used by steel industry, manufacturers, designers, policy makers, and government bodies to develop, plan and design strategies about building new structures from old steel members thereby reducing the impacts of CO2 emissions due to use of new steel members or recycling old ones. |
Sectors | Aerospace Defence and Marine Communities and Social Services/Policy Construction Digital/Communication/Information Technologies (including Software) Education Energy Environment Financial Services and Management Consultancy Healthcare Government Democracy and Justice Manufacturing including Industrial Biotechology Retail Transport |
URL | https://www.restorproject.co.uk/ |
Description | The project has raised awareness among relevant industries and project partners about its significance and the potential of a digital generative tool for reusing steel members in the construction of new structures. |
First Year Of Impact | 2024 |
Sector | Construction,Education,Manufacturing, including Industrial Biotechology |
Impact Types | Policy & public services |
Description | Invited talk - The Impact of AI on the Steel Construction Sector |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | National |
Primary Audience | Professional Practitioners |
Results and Impact | About 50 practitioners from the construction industry as well as members of the British Constructional Steelwork Association attended a talk on the impact of AI on the steel construction sector. The talk sparked questions and discussion afterwards, and fueled interest in the project. |
Year(s) Of Engagement Activity | 2023 |
Description | Keynote presentation: University of Birmingham's Digital Twin |
Form Of Engagement Activity | Participation in an activity, workshop or similar |
Part Of Official Scheme? | No |
Geographic Reach | National |
Primary Audience | Professional Practitioners |
Results and Impact | In this presentation, Professor Asaad Faramarzi highlighted some of the work that has gone into development of University of Birmingham's Digital Twin (DT). Asaad described the start of the DT work, from the partnership with Siemens, to external consultancy involvement and the Smart Campus project. The campus has over 30k occupancy sensors, 10k environmental sensors, 1000s of water and energy meters and more, such as space and building models, energy and water consumption, timetabling etc. An early version of the conceptual architecture has already been developed, bringing together the data, plus WiFi data into a dashboard to visualise the data into as close to real-time as possible. The DT aim is to reduce energy and costs, as well as support sustainability, improve heating & cooling, improve use of space and a host of other benefits. The project could potentially be expanded to the city as part of a smart city initiative. "Datasets when connected become greater than the sum of their parts!" he noted. Additionally, Professor Faramarzi highlighted some of the research that has are aligned with the works done so far. |
Year(s) Of Engagement Activity | 2024 |
URL | https://www.dafni.ac.uk/annual-conference-2024/ |
Description | Presentation to the British Constructional Steelwork Association |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | National |
Primary Audience | Professional Practitioners |
Results and Impact | A comprehensive summary of RESTOR project was provided, with particular emphasis on work packages 1 and 2 (WP1 and WP2). The intended purpose of the presentation was to inform the tests planned as part of these WPs with industrial input in such a way that the test results will be impactful. The audience consisted of 40 practitioners actively involved in steel reuse initiatives. RESTOR team received valuable feedback from the attendees, which fed directly into refining the experimental programme to encompass real-life damage scenarios commonly observed in reclaimed steel members. |
Year(s) Of Engagement Activity | 2023 |