Regenerative design processes are those in which design aims and targets go beyond currently established sustainable and environmentally friendly paradigms. Regenerative design solutions should positively contribute to the ecosystems in which they are inserted, thereby regenerating the environmental qualities of site and context to its original condition and beyond [1-4], an ambition that requires a substantial amount of evidence from concept generation to concept validation. Thus, designers nowadays make extensive use of digital tools not only to explore
Observations comprised: (i) attending sessions in which each participant presented their current work, (ii) recording design development sessions using 360° portable digital cameras and dictaphones, and (iii) video recording and observing training school tutorial sessions related to regenerative design, integrated design, human well-being, parametric design and life cycle assessment, attended by one representative member of each group. Preliminary results are extracted from the discussions that took place in tutorial sessions of regenerative and integrated design. Some of the discussion highlights are listed below and are followed by a set of provoking questions to stimulate further thinking.
CAUSALITY VERSUS PRODUCING EVIDENCE
The first discussion highlight was the causality dilemma of using evidence to make decisions versus producing evidence from decisions. Concept developers reported waiting for data analysts to generate evidence so they could propose/make decisions, and at the same time, data analysts reported waiting for concept developers to generate ideas so they could test them. Particular cases in which this occurred involved concepts that needed evidence and/or testing of wind patterns, energy use and water collection and storage.
Figure 25
The experiment was conducted using as reference the Barrio of La Luz in Malaga, built around 1960, the teams had to propose retrofit solutions to achieve regenerative targets.
Discussions around this dilemma constantly revolved around the type of evidence to be produced and the best ways to display such evidence, pushing analysts also to propose changes and develop concepts further. This observation yields two critical questions for the design process: What kind of evidence do concept developers need to be able to make decisions? How can data analysts produce tests that are less focused on diagnosing problems and are inspirational to expand the search in the design solution space?
Narrowing the search in the design solution space while attempting to solve in depth a particular environmental design problem or while proposing a particular regenerative design solution led to another interesting question: Is it better to go for a punctual intervention or to adopt a systemic approach? An example of a more systemic approach was rethinking the mobility system to increase the area for green spaces and attempt to regenerate the water ecosystem. The danger of a systemic approach is the level of cooperation it requires different stakeholders at multiple scales.
Figure 26
The involved teams used a full set of algorithms in Grasshopper and ladybug Tools. Here is an example of one of the simulations operated by the teams where Computational Fluid Dynamics (CFD) was used to account for the Urban Heat Island modelling.
For instance, one cannot expect a reduction in the use of cars to increase areas dedicated to green spaces without a reliable and frequent public transport network. On the other extreme, it was clear that a punctual intervention, almost in the form of a ‘gadget’, was used as a powerful reinforcement of a design statement, for instance when a major piece of built infrastructure was proposed to induce specific wind patterns and provide solar shading.
As opting for punctual interventions can easily lead to a spiral set of ‘side effects’ to be resolved, a compromise is usually found in re-framing the original problem to focus on searching for a few multipurpose solutions. Multipurpose solutions require high levels of concerted action. From a human perspective, this means concept developers need to have a basic understanding of all disciplines involved in the project to be able to explain what they wish to achieve to analysts. At the same time, analysts need to have a good understanding of this very early stage of the design process to be able to provide appropriate evidence for decisions to be made. Moreover, they also need to understand the different specialisms involved in the design process so that their solutions do not conflict with other types of building performance. In this context, digital tools can be seen as a risk to the achievement of multipurpose solutions because they are heavily specialised in terms of performance assessment. This yields useful questions for design teams: What is the right balance between the use of digital tools and non-digital expert knowledge within the design process? What are the different types of knowledge that need to be in place to enable the emergence of multipurpose solutions?
COMPUTER SIMULATION AND HAND CALCULATIONS One of the groups presented an interesting combination of repertoire recall with hand calculations and some carefully crafted computer simulations. This balanced combination shed light on the fact that the conceptual design stage is always populated by some uncertainties that have a significant impact on the generation of evidence. If a large number of assumptions is necessary either to support specific decisions or to assess them, simulations might be seen as unnecessary or even misleading. In this sense, the overfamiliarity of the data analyst with specific simulation tools might be dangerous if it does not lead to the questioning of uncertainties, whereas the questioning of uncertainties can lead to the complete rejection of simulation tools, either in favour of hand calculations and/or in recalling past solutions from the practitioner’s repertoire.
Either through simulations or not, the need to produce evidence to support or test regenerative design decisions was seen as fundamental in all design teams. This paper raised a set of considerations concerning the production of evidence and the way it is currently integrated throughout the design process. It has shown that there are potentially two different types of evidence to be considered: Evidence to enable concept developers to make decisions, and inspirational evidence to expand the search in the design solution space. It demystified the idea that evidence necessarily needs to come from digital simulations but that it does require expertise to be produced because it includes not only using simulation tools but also judging when they are effectively necessary. This paper proposes that specialisation can add to the design solution if all parties involved are reasonably knowledgeable of the different types of performance involved and are aware of the inherent uncertainties in the early design stages.
The paper concludes that further thinking is needed concerning how different types of expert knowledge can effectively be used to produce the necessary evidence required in the regenerative design.
REFERENCES
[1] G. Sonetti, M. Brown, E. Naboni., About the triggering of UN sustainable development goals and regenerative sustainability in higher education. Sustainability 11 (2019) 1-17.
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[2] G. Sonetti, E. Naboni., M. Brown, Exploring the potentials of ICT tools for human-centric regenerative design. Sustainability 10 (2017) 1-14. doi: 10.3390/su10041217
[3] International Living Future Institute, Living Building Challenge 3.1: A visionary path to a regenerative future (2017) 82pp.
[4] M. Brown, Futurestorative: Working towards new sustainability; RIBA Publishing, London UK (2016)
[5] M. S. Roudsari, M. Pak, Ladybug: A parametric environmental plugin for Grasshopper to help designers create an environmentally-conscious design. Proceedings of BS2013: 13th Conference of International Building Performance Simulation Association, Chambery, France (2013).
[6] M. S. Roudsari, Seeing the process: Ladybug + Honeybee, dynamic building simulation solutions for integrated iterative design. In: D. Willis, W. W. Braham, K. Muramoto, D. A. (eds.) Barber Energy Accounts: Architectural representations of energy, climate and the future.
Routledge, (2016) 112-116.
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Part I of The Tool(s) vs. The Toolkit [1] laid a foundation of five principles for designing and selecting for software to act as a part of an integrated toolkit instead of a single, isolated tool. It also presented a case for why an integrated toolkit is necessary for the building industry to reach the full potential of environmental modelling in its design workflows. Perhaps most notable among the arguments raised in Part I is that monolithic, isolated tools often hinder the learning process of the modeller and can prevent him or her from reaching a deeper understanding of the underlying components and assumptions of a computer simulation. Much like any technology, computer modelling can be misused, and when a modeller does not adequately understand the premises of a model they have built, they can end up making the wrong decision in a design process, ultimately detracting value rather than adding it. Modularized, connected, and open toolkits help defend against this situation by:
- enabling a learning process that can happen component-by- component,
- allowing for ease of cross-validation through connections to other tools, and
- supporting the mixing/matching of tools within the kit, thereby empowering modellers to answer new questions and test new creative solutions.
Accordingly, the original five principles of the toolkit published in part I constitute a doctrine found useful while developing the Ladybug Tools Legacy Plugins and to which they attribute much of the project’s success. ‘Ladybug Tools’ collectively describe an open source project that was started in 2013 to support environmental design and education. Since its founding, a community of over 50,000 designers, engineers and building scientists has grown around it, adding code contributions and participating in the discussions of an online forum that receives an average of 3.5k pageviews per day. Of all the available environmental design software packages, Ladybug Tools is among the most comprehensive, connecting 3D CAD interfaces to a host of validated simulation engines, allowing designers to simulate daylight, building energy use, thermal comfort and several other environmental design parameters.