Next Generation Highrise

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Decarbonisation is one of the pressing challenges in the built environment as the unprecedented growth of cities, particularly in Asia will continue to have a massive environmental impact. Demographic changes put additional pressure on how we plan buildings for uncertain futures. Planners, construction industries, governmental agencies and stakeholders require new approaches to design and respective material choices to minimise the embodied carbon. Data and tools are fragmented and hardly allow for a holistic integration of knowledge in one platform as the digitalisation in the building industries is still at its infancy. One of the areas that is difficult to measure is the embodied carbon of a building in its planning process, indicated as Global Warming Potential (GWP in kg CO2-eq per kg of material). Most available Carbon Calculators depend on detailed data such as Building Integration Management (BIM) models that are usually only available in later design stages. 

Our research at SUTD has developed methods, mathematical models and mock-up computational tools that allow designers to make informed design decisions and assess the environmental performance in early design and assessment stages. We have also established a framework for flexible building designs: habitation patterns are continuously changing and unforeseen situations such as the 2020 pandemic demand the ability for quick adaptations. 

The research has been focussing on three integrative aspects for the development of such tool: 

1. 1.An intuitive feedback on environmental performance in early design stages.
2. 2.The assessment of flexibility in regard to the impact of alterations on the service life-time of buildings. 
3. 3.The integration of available Life Cycle Inventory (LCI) data into predictive modelling to generate a range of probable outcomes indicated as Global Warming Potential (GWP, usually measured in kg of CO2 eq per kg of material).

The research has been constrained to residential typologies and specifically to hybrid concrete-timber construction systems in order to establish an applicable methodology and the respective mock-up tools. 

Firstly, the mock-up tool for simplified Life Cycle Assessment (LCA, measured in Global Warming Potential GWP) demonstrates how designers can get an intuitively legible and visual feedback to systematically compare the environmental performance of alternative design iterations at initial design stages. To enable such a systematic comparison of design variants the workflow follows an 'Open Building' approach and segments designs into permanent support and adaptable infill systems.  Here, it goes further and differentiates into various degrees of flexibility in each of the main systems: concrete construction systems would normally be used as permanent support structures such as cores (containing circulation, infrastructure, and service functions), whereas partly load bearing components made from timber could be adapted and changed over long periods of time, and hence they would have a basic degree of flexibility. The infill systems are also further distinguished into conventional partitioning systems (such as drywalls that already have a higher degree of flexibility, but to the cost of their destruction) and modular systems that can be altered in various combinations. A Shoebox approach was adopted for the visual representation of a building concept in a simplified and intuitively legible interface. In the Shoebox representation, a series of dynamically alterable modules represent alternative load-bearing systems and variable material fractions. These are linked to a simplified parametric building model to extract data for the comparison of GWP results (fig. 1). 

Fig. 1 – Shoebox approach: the cube on the left represents one spatial unit within a building. The radar charts on the right displays the estimated embodied carbon outputs for different design variants, and for different construction systems.

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Secondly, it focussed on the flexibility of buildings so that they can respond to demands for functional changes and make use of a systematic differentiation between permanent support- and adaptable infill components. As mentioned, both systems are further categorised into kits of parts with variant degrees of flexibility. Predictive mathematical models are used to translate cycles of changing demands during service life-time into varying configurations within the infill system. The degree of flexibility is used to specify the potential service lifetime extension of buildings, helping decision-makers to decrease the overall environmental impact of a building (fig. 2). 

Fig. 2 – An embedded graph syntax detects the probability of walls to be changed over time.

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Thirdly, the research outlined the concept for a predictive mathematical model to overcome current challenges in the available LCI data:

1. 1.This data is mostly specific to particular markets and regions only;
2. 2.Varying Life Cycle Assessment (LCA) methods are applied, which makes it difficult or even impossible to compare;
3. 3.There are huge gaps in the data in those global regions that undergo the fastest growth in urbanisation. 

The methodology of this workflow suggests the collection of data from existing buildings with simplified input data (reduction to the essential parameters), integration of the information into Bayesian Neural Network models (capable of machine learning by updating its predictions with the availability of more current data) and predicting a range of possible outcomes to help a user make more informed decisions (fig. 3). 

Fig. 3 – The bar on the left represents a simplified list of possible construction systems, the user can adjust the dimensions on the building scale in the center and on the unit scale on the right. An additional choice to determine material ratios at (bottom) enables users to asses more adaptable and more environmentally friendly alternatives on the element scale.

Whereas the mock-up tool is design-based and requires minimal information on floor plans (such as in concept development stages), this data-driven tool requires no prior knowledge of the design and is thus applicable in even earlier phases (such as a project framing and programming phase).

Background Research 

This research has been funded by the SUTD-MIT International Design Centre since August 2018. The developed methodology and workflow was initially specifically catered to projects in South East Asia, a region of massive urban expansion with increasing Greenhouse Gas (GHG) emissions. Since this is taking place in close proximity to one of the world’s largest forested areas with vast resources of wood, a renewable and sustainable material. The research was exploring the potentials and constraints of hybrid concrete-timber construction systems in residential typologies. Currently, the available concrete technologies are on a very advanced level whereas timber is  rarely applied in construction despite recent technological innovations and attempts for a reintroduction. After it has been replaced by concrete and steel as the predominant materials for the construction of cities in the past century, we are here assessing the potential impacts of partly supplementing concrete structures with timber. This has an immediate impact on the embodied carbon and indirectly offers the possibility of keeping the more lightweight timber elements adaptable during a building’s lifetime.

Fig. 4 – Next Generation High Rise: methodology for an early stage design Life Cycle Assessment (LCA) of different construction systems (top left) with an integration of occupational patterns due to demographic changes over a buildings’ operational life time (centre right).

The team was awarded the Arup Global Research Challenge 2019 and will continue working on the mock-up tool, focusing on the integration of structural data and the determination of material quantities. The research was among five selected out of 75 participants in an open international call for research proposals by Arup.