Data-driven design for sustainability

Enabling better LCA insights for architecture through Computational Design and BIM 

• 12 months Research Assistant position at Liège University, under the supervision of Prof. Aurélie de Boissieu and co-supervision of Prof. Sigrid Reiter.
• Partnership with Grimshaw under the supervision of Andy Watts (Director of Design Technology)

Research project

In architectural design, Life Cycle Assessment (LCA) enables better understanding of the environmental impacts of projects[1, 2]. Through evaluation of all environmental costs (energy, carbon etc.) of projects from construction to demolition or recycling, LCA enables holistic and strong understanding of our built environment. Unfortunately, LCA remains a tedious and onerous study to perform and often intervenes late in the design process. Running Life Cycle Assessments late and infrequently means that its insights are available to designers only when the main design decisions have already been taken, leaving little room for improvement to our built environment [3–5].

To support better LCA practices in architecture and thus the design of a better environment, digital practices offer very interesting opportunities. Digital practices in architectural design are fast changing, especially through Computational Design (CD) and Building Information Modeling (BIM). CD practices leverage the power of computation as well as computational thinking to empower architectural design [6, 7]. BIM, on the other hand, focuses on enabling better collaboration processes between the project stakeholders during the whole project life cycle through improved data management and data-oriented practices [8, 9].

The uses of BIM to enable better LCA processes is currently widely explored in research (see figure 1) [3, 4] as well as in practice, supported by a growing number of tools[1] and Life Cycle Inventory (LCI) data bases. But while LCA starts to leverage BIM processes to enable easier access to the building quantity take off, these practices remain niche, developed in silos on specific projects, and still support poorly early stage design decision [3, 4, 10].

Figure 01 : Publications on LCA, BIM and computational Design in Scopus

In this research, we focus on data-driven strategies in architecture practice aiming at supporting LCA performances in design focused environments. Computational Design and BIM will be interrogated together in order to explore better LCA processes and performances in architecture, including in early design stages. The research aims at supporting better decision making processes, in which early data-driven LCA insights are enabled before main architectural decisions are made. Potentialities of Data-Driven practices [11–13], leveraging both CD and BIM will be interrogated to enable iterative LCA processes across multiple projects at an office level.

This research is developed in partnership with Grimshaw, an international architecture studio with an ambitious sustainability agenda[1] and strong Design Technologies practices, in both BIM and CD.

The research position proposed here is an opportunity to develop a PhD project at the University of Liège. The position is based in Liège and includes frequent travel in London. The main language of the research is English.

During these 12 months, the researcher will work especially on:

• Establishing a thorough literature review on LCA in Architectural Design with a focus on Computational Design and BIM,
• Collecting exploratory data at Grimshaw through interviews and participatory observations,
• Writing a detailed PhD project as well as first results and/or developments.

The work will be documented in reports and papers. Support and guidance will be provided to the researcher by Prof. Aurélie de Boissieu all along the work.

How to apply

Applications (CV and motivation letters) are to be sent at prof. Aurélie de Boissieu for July 10th 2022 at the latest.

References

1. Nematchoua MK, Teller J, Reiter S (2019) Statistical life cycle assessment of residential buildings in a temperate climate of northern part of Europe. J Clean Prod 229:621–631. https://doi.org/10.1016/j.jclepro.2019.04.370
2. ISO (2006) ISO 14040:2006, Environmental management — Life cycle assessment: Principles and framework
3. Safari K, AzariJafari H (2021) Challenges and opportunities for integrating BIM and LCA: Methodological choices and framework development. Sustain Cities Soc 67:102728. https://doi.org/10.1016/j.scs.2021.102728
4. Obrecht TP, Röck M, Hoxha E, Passer A (2020) BIM and LCA integration: A systematic literature review. Sustain 12:. https://doi.org/10.3390/su12145534
5. Jusselme P (2020) Data-driven method for low-carbon building design at early stages. EPFL
6. Menges A, Ahlquist S (2011) Computational Design Thinking, AD readers. Wiley
7. de Boissieu A (2013) Modélisation paramétrique en conception architecturale : Caractérisation des opérations cognitives de conception pour une pédagogie. Universite Paris-Est
8. Eastman C, Teicholz P, Sacks R, Liston K (2011) BIM Handbook : A Guide to Building Information Modeling for Owners, Managers, Designers, Engineers and Contractors, 2nd Editio. John Wiley & Sons, Hoboken
9. ISO (2018) EN ISO 19650-1:2018 Information management using building information modelling Part 1: Concepts and principles, bsi
10. Cays J (2017) Life-Cycle Assessment, Reducing environmental Impact risk with workflow data you can trust. In: Garber R (ed) Digital Workflows and the Expanded Territory of the Architect, AD. Wiley
11. Anderson C (2015) Creating a data-driven organization. O’Reilly
12. Deutsch R (2016) Data-Driven Design and Construction: 25 Strategies for Capturing, Analyzing and Applying Building Data. Wiley, Hoboken
13. Bernstein PG (2018) Architecture, design, data : practice competency in the era of computation. Birkhauser Architecture

[1] Such as OneClic LCA (https://www.oneclicklca.com/), Umberto (https://www.ifu.com/en/umberto/lca-software/), Tally (https://choosetally.com/), GaBi (http://www.gabi-software.com/)