FNR - Attenuating the Environmental Impact of our Buildings through Semantic-based Dynamic Life cycle Assessment (SemanticLCA)

Lead Research Organisation: Cardiff University
Department Name: Sch of Engineering

Abstract

Our vision is that humans can attenuate and control positively the impact of their buildings on the environment and mitigate the effects of climate change. This can be achieved by a new generation of life cycle assessment methods and tools that are model-based, continuously learn from real-time data, while informing effective operation and management strategies of buildings and districts.

In that respect, current LCA methods present important limitations and gaps, including:

(a) Lack of reasoning and decision support capabilities, such as exploring "what if" scenarios for the evaluation of alternative design options and devising adapted strategies, thus promoting active control of buildings and districts.
(b) Lack of alignment with domain models, e.g. BIM (Building Information Modelling), GIS (Geographical Information Systems), and LCA data structures.
(c) Lack of support of temporal information. There is a need to factor in temporal information in the life cycle inventory (LCI) and Impact Assessment (LCIA) phases to address maintenance, operation, deconstruction, disposal and recycling stages.

The proposed research addresses the challenge of leveraging digital built environment resources by using semantic web technologies to deliver life cycle assessment solutions to our built assets. Our hypothesis is that: life cycle assessment underpinned by semantics and informed by dynamic data paves the way to more accurate life cycle impact assessment while supporting life cycle decision making and active control of buildings and districts.

In a nutshell, the aim of SemanticLCA is the development of a (near) real-time semantic capability that exploits a wide range of digital data sources and leverages artificial intelligence to assess the whole-life cycle environmental impacts of built assets. The following research questions are posited:

RQ1: Can the use of semantics, including BIM (IFC) and GIS (CityGML), to integrate and contextualise existing life cycle inventory databases, provide a sound basis to streamline the life cycle assessment process of buildings and districts?
RQ2: Can access to dynamic data, managed in a BIM and GIS friendly time series database, provide more accurate accounts of environmental impacts during the construction and operation stages?
RQ3: Can the resulting SemanticLCA environment assist in decision making by non-experts by exploring a wide range of options and scenarios with the least environmental impact, while also advising on corrective plans?

Our work programme involves three Work-Packages (WP), each addressing one of our posited research questions, and a fourth cross-cutting WP addressing demonstration and validation activities.

The evaluation will be carried out in two demonstration sites: Cardiff (UK) and Belval (Luxembourg). The Cardiff demonstration will be carried out in the Queen's building (School of Engineering) and scaled up to the 130 buildings owned and managed by Cardiff university, majority of which are located in the city centre. The LIST demonstration will be carried out in the Maison de l'Innovation in Belval and scaled up to the entire district of Belval (managed by Fonds Belval). Given the complexity of LCA at district level, validation will utilise a simulation based approach with a subset of use cases demonstrated and validated in real operation conditions. The validation work will leverage ongoing developments of city platforms for Cardiff and Belval, as illustrated on the CUSP website: www.cuspplatform.com.

SemanticLCA is supported by 10 partners and an experienced team of investigators from Cardiff University and LIST bringing together complementary expertise in: a) AI applications in the built environment, b) semantic contextualisation of multi-scale built environment data, c) intelligent cloud/edge computing, d) Life cycle assessment methods and tools, e) Building Information Modelling for asset modelling and energy efficiency.

Planned Impact

SemanticLCA will deliver a new value proposition in the life cycle assessment of buildings and districts, that factors in multi-aspects real-time data, to continuously inform decision making, including the implementation of corrective measures that attenuate the environmental impacts of our built environment. This will pave the way to significant societal, environmental, and economic impacts. We will be among the first to manage in real-time the life cycle impact of buildings using real-time data grounded in semantic models, including BIM (Building Information Modelling) and GIS (Geographical Information Systems). We provide scientific excellence with environmental and societal impact because environmental impacts and their consequences on humans are factored into our approach.

Knowledge impact: We will organise a series of Workshops for members of industry, academia and policy-makers, using case studies in Cardiff and Belval (Luxembourg) to demonstrate how SemanticLCA works. Our data, information and knowledge on the concept of dynamic life cycle assessment will be useful not only in evaluating the environmental impact of buildings already in use but also to inform practice by (a) revisiting and improving aspects of existing codes and guidelines, (b) informing the briefing process driven by a user-centred approach, (c) regulating the handover / commissioning stage, (d) devising operational strategies to continuously monitor and pro-actively adapt the indoor environment, energy consuming devices, and energy systems in place, to minimise impacts on the environment, and (e) establishing a learning culture that continuously informs practice. Additionally, we will disseminate our findings via our dedicated portal (www.sematicLCA.net) that will be maintained by Cardiff University beyond the project, thus forming a real legacy.

Societal impact: SemanticLCA will provide a unique rich and multi-aspects data source for buildings and districts, hosted within our platform (www.semanticLCA.net) to support policy making around the environmental impacts of our built environment in the UK, Luxembourg and globally. Resulting data will also underpin the future use of active control systems in buildings and districts, and our engagement with policy makers will allow such systems to be realised in retrofitted and new buildings. As such, we will exploit our partners' (including BRE) network of contacts to gain access to, and engage with, policy makers. We will take our findings on a UK and Europe wide roadshow to highlight the potential of SemanticLCA.

Economic impact: Our project partners will be the primary adopters and beneficiaries of SemanticLCA, and we will facilitate regular meetings and webinars to encourage uptake. The second tranche of adopters will be a broader cross-section of the construction industry, encouraged by our academic network of contacts (via Digital Built Britain and related initiatives, including in Luxembourg and wider Europe facilitated by support from the ECTP - European Construction Technology Platform) as well as our ambitious dissemination programme through our planned workshops, public exhibition and conference. We will also target facility managers and SMEs involved in sensors and sensing, all of whom stand to benefit from this transformation.

People impact: Our team, which will include all investigators, Post Doctoral Research Assistants (PDRAs), and a PhD student (fully funded by Cardiff university), will grow organically into a powerful grouping through outstanding people development. Academics involved in SemanticLCA will become part of an entirely new, pioneering, inter-disciplinary research field at the intersection of Semantics (including BIM) and Artificial Intelligence. We will feed our research into new taught programmes, and run annual summer schools for students showing interest in our approach. We will run the SemanticLCA Research Society to engage research colleagues around the globe.

Publications

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