Matthew Gordon

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Gordon

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Matthew

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0000-0003-2426-7845

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Publications 1 - 7 of 7

Automating building element detection for deconstruction planning and material reuse: A case study
Gordon, Matthew; Batallé, Anna; De Wolf, Catherine; et al. (2023)
Automation in Construction
To address the need for a shift from a linear to a circular economy in the built environment, this paper develops a semi-automated assistive process for planning building material deconstruction for reuse using sensing and scanning, Scan-to-BIM, and computer vision techniques. These methods are applied and tested in a real-world case study in Geneva, Switzerland, with a focus on reconstruction and recovery analysis for floor beam systems. First, accessible sensing and scanning tools, such as mobile photography and smartphone-based consumer-grade Lidar devices, are used to capture imagery and other data from an active demolition site. Then, photogrammetry and point cloud data analysis are performed to construct a 3D BIM model of relevant areas. The structural relationships between reconstructed BIM elements are evaluated to score the feasibility for recovery of each element. This study illustrates what is feasible and where further development is necessary for automating building material reuse planning at scale to increase the uptake of circular economy practices in the construction sector.
Calculating embodied carbon for reused structural components with laser scanning
Byers, Brandon; Gordon, Matthew; Iuorio, Ornella; et al. (2023)
Life-Cycle of Structures and Infrastructure Systems
The global warming potential (GWP) of reused building elements can be evaluated based on two variables: structural material quantity (SMQ) and embodied carbon coefficient (ECC). The volume of the SMQ can often be unknown, however, and it is not clear how to best estimate the ECC of a reused element. This paper illustrates a method for extracting the volume of reused metal structural elements to calculate their GWP in buildings that lack documentation. The authors use laser scanning and voxelization to extract the volume and a method based on the Swiss Society of Engineers and Architects (SIA) 2032 norms for calculating the GWP of reused materials. The reality capture method is accurate enough to approximate structural material volume, although it requires exposed structures. The results are important for building managers to understand the relative environmental impact savings from reused versus new building elements.
Optimisation goals for efficient construction from reused materials towards a circular built environment
Gordon, Matthew; De Wolf, Catherine (2024)
Developments in the Built Environment
Building materials that are reused in a circular economy context are often non-standard because previous usage has altered their original properties. Material matching algorithms aid design and construction by matching components in stock with those needed in a design. The efficiency of these matches is assessed based on factors such as waste, logistics, and structural applicability. In this paper, we evaluate the efficacy and practicality for design evolution of construction-relevant optimisation goals. We evaluate goals based on their construction-time and design time results, using a software pipeline optimising both the mapping and design. One design was also constructed based on the optimised matching, to assess additional considerations when working component-specific designs. Based on difficulties and inefficiencies observed during fabrication, we propose two alternate matching strategies and compare their effects on the chosen factors. The study reveals that component allocation systems frequently overlook the need for both contingency planning and redundancy in the construction process. Additionally, inaccuracies in inventory tracking can significantly compromise the feasibility of the planned design. The stability of these design assistive techniques strongly affects their ability to be applied in large-volume projects. This implies the need for a new set of objective factors to be incorporated into existing methods of design optimisation.
Reality capture and site-scanning techniques for material reuse planning
Xiong, Zhijia; Gordon, Matthew; Byers, Brandon; et al. (2022)
Proceedings of IASS Annual Symposia ~ Proceedings of the IASS/APCS 2022 Beijing Symposium: Sustainable Heritage Challenges and Strategies in the Preservation and Conservation of 20th Century Historic Concrete Shells
The reuse of building materials requires both broad-ranging and detailed information on available building stocks in order to effectively plan for connecting available materials with their eventual reuse in new buildings. Critical information includes component counts, dimensions, and on-site locations. Currently, this information is usually gathered using manual measurements, though contemporary digitization and scanning technology can be used to efficiently gather dimensional and geometric data about pre-demolition sites. The primary digital technologies to automate this data gathering, being photogrammetry and terrestrial Light Detection and Ranging (LIDAR), have historically shown significant gaps in efficiency and accuracy, while their hardware and software systems are rapidly advancing in capabilities. In this study, contemporary implementations of these methods are compared for their efficiency, interior coverage, and raw accuracy across two case studies with significant geometric differences. These results inform decision-making regarding the appropriate integration of these technologies in industry and identify technologies that require more development for effective use.
Predicting recoverable material stock in buildings: using machine learning with demolition audit data as a case study
Kobylinska, Natalia; Raghu, Deepika; Gordon, Matthew; et al. (2023)
Computing in Construction ~ Proceedings of the 2023 European Conference on Computing in Construction and the 40th International CIB W78 Conference
Early specification of materials in buildings before their demolition could foster reuse in the construction industry. Studies have already shown the usefulness of machine learning in demolition waste estimation; however, application to real-world datasets is still limited. This study tests the feasibility of predicting recoverable material stock in the local context of the city of Zurich. The results show promise for the overall approach, although training models by using a small and heterogeneous dataset poses challenges. Therefore, we conceptualized an improved demolition data collection, processing, and dissemination. The resulting framework could help researchers and authorities in urban material stock estimation.
D5 digital circular workflow: five digital steps towards matchmaking for material reuse in construction
De Wolf, Catherine; Byers, Brandon S.; Raghu, Deepika; et al. (2024)
npj Materials Sustainability
The intersection of digital transformation and circular construction practices presents significant potential to mitigate environmental impacts through optimised material reuse. We propose a five-step (D5) digital circular workflow that integrates these digital innovations towards reuse, validated through real-world case studies. We assessed a variety of digital tools for enhancing the reuse of construction materials, including digital product passports, material classification assisted by artificial intelligence (AI), reality capture, computational design, design inspired by generative AI, digital fabrication techniques, extended reality, and blockchain technology. Using action research through a multiple case study approach, we disassembled several buildings that were set for demolition and subsequently designed and executed construction projects using the salvaged materials. Our findings indicate that digital transformation for detection, disassembly, distribution, design, and finally deployment significantly support the application of circular economy principles. We demonstrate the potential of the proposed workflow for industry implementation and scalability.
Design for and from disassembly with timber elements: strategies based on two case studies from Switzerland
Grüter, Cäsar; Gordon, Matthew; Muster, Marcel; et al. (2023)
Frontiers in Built Environment
When a timber building gets disassembled and its elements either are burned or biodegrade, the carbon stored in the timber structure gets released to the atmosphere as CO2. Reusing timber elements prevents this process from happening and thus delays the global warming caused by greenhouse gas emissions. Even if there is a long historic tradition of timber reuse in Switzerland, currently a low fraction of a timber building’s elements is being reused after its disassembly. In this study, strategies that could facilitate circular use of timber elements are analyzed. The focus lies on the design process, which is investigated from two perspectives: strategies at the start-of-life of buildings to enable new timber element cycles to emerge (design for disassembly, or DforD), and strategies at the end-of-life of buildings to keep existing timber elements cycles closed (design from disassembly, or DfromD). Two case studies of recently completed multi-story timber-hybrid buildings in Switzerland were analyzed from both perspectives. Regarding DforD, a scoring system was developed that assesses single elements according to their disassembly and reuse potential. Regarding DfromD, a building design optimization tool was created that takes dimensional design tolerances of a building as an input and proposes a procurement-optimized and structurally safe arrangement of reused elements, which are taken from an inventory that is based on the two case studies. It was found that connections between reinforced concrete and timber parts play a crucial role in terms of DforD and that building layouts with DfromD elements may vary widely according to the chosen optimization variable. In conclusion, both applications have the potential to scale up the competitiveness of reused elements.

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