Project Details
Description
RECONSTRUCT will develop low-carbon alternatives to Ordinary Portland Cement (OPC) and using them together with recycled and bio-based materials to produce in-situ components, precast components and sandwich panels designed to be removable, repairable and reusable.
The whole lifecycle of construction materials will be digitized allowing the tracking and sharing of material info and together with the extensive use of digital tools to support the design, construction and deconstruction phases will allow impact and waste minimization. These innovations will be applied to both onsite and prefabricated construction approaches while AI-based solutions will be used to establish stable regional supply chains of waste materials.
The whole lifecycle of construction materials will be digitized allowing the tracking and sharing of material info and together with the extensive use of digital tools to support the design, construction and deconstruction phases will allow impact and waste minimization. These innovations will be applied to both onsite and prefabricated construction approaches while AI-based solutions will be used to establish stable regional supply chains of waste materials.
Key findings
RECONSTRUCT will demonstrate its approach through the construction of two real-scale demonstrators and set up regional Circular Construction Clusters incorporating all the local value chain. By doing so, RECONSTRUCT aims to achieve a step-change in material consumption and carbon footprint by reducing waste generated during construction by 90%, developing materials with up to 0% virgin content, reducing the carbon footprint of buildings by 50% and increasing recycling to 90%.
| Acronym | RECONSTRUCT |
|---|---|
| Status | Active |
| Effective start/end date | 1/06/23 → 31/05/27 |
Collaborative partners
- Teesside University (lead)
Funding
- Innovate UK
Fingerprint
Explore the research topics touched on by this project. These labels are generated based on the underlying awards/grants. Together they form a unique fingerprint.
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BIM-integrated semantic framework for construction waste quantification and optimisation
Sivashanmugam, S., Rodriguez Trejo, S. & Rahimian, F., 15 Dec 2024, In: Automation in Construction. 168, Part B, 26 p., 105842.Research output: Contribution to journal › Article › peer-review
Open AccessFile118 Downloads (Pure) -
Enhancing information standards for automated construction waste quantification and classification
Sivashanmugam, S., Rodriguez, S., Pour Rahimian, F., Elghaish, F. & Dawood, N., 1 Aug 2023, In: Automation in Construction. 152, 104898.Research output: Contribution to journal › Review article › peer-review
Open Access