Thanks to computer simulations and modelling techniques – as well as data-driven analyses – design teams can now create sustainable, energy-efficient and comfortable buildings for their occupants.

Words Yogesh Gooljar IMAGES PJC + Partners

Computational Design: revolutionising the way we work

Computational design and data-driven analyses have transformed the way architects, engineers and construction professionals approach building design. Fluid shapes, automation and robotics have changed the construction scene for the better – or for worse. Building designers are no longer satisfied with creating designs: they want data. Computational design can give them both of these and more.

Fluid shapes, automation and robotics have changed the construction scene for the better – or for worse.
An analysis of the potential for natural ventilation from location-based climate data.
An assessment of the annual solar radiation for Cape Town provides insight into climate-responsive architecture.

The evolution of computational design

The roots of computational design and building performance modelling can be traced back to the early days of computer-aided design (CAD) in the 1960s. In the following decades, computer technology evolved, and new tools emerged that allowed architects and engineers to create digital models of their designs. One of the earliest examples of building performance modelling was the use of energy modelling software in the 1980s to predict a building’s energy consumption.

Building designers are no longer satisfied with creating designs: they want data.

In the 1990s, computational fluid dynamics (CFD) allowed designers to simulate airflows and thermal conditions within buildings, giving a more accurate representation of the building’s performance. With the advent of parametric and generative design in the 2000s, designers could now create complex geometries and optimise their designs for specific environmental conditions.

Solar radiation analysis on a building facade to test shading strategies.

Direct vs computational modelling

Conventional modelling in software such as SketchUp, 3ds Max and Revit is known as direct modelling. No algorithms or parameters for design iteration are involved.

To work with computational modelling, add-ons and plugins are necessary to enhance the functionality of the software. For example, Revit offers Dynamo and Rhino.Inside.Revit as computational features.

An example of visual programming in Grasshopper for computational design.

Better environmental performance

Computational design tools have now merged with numerous building performance-analysis and simulation tools, enabling designers to analyse their design based on environmental performance indicators.

Computational design is being used to create sustainable, energy-efficient and comfortable buildings and spaces.

Solar radiation and energy analyses are common analyses necessary for an energy-efficient design. Designers can now run simulations and analyses during the design development stage with the aid of visual programming, and iterate design options based on the results.

Various types of simulations are used in environmental performance modelling. The most common include:
Energy modelling, used to predict a building’s energy consumption and identify opportunities to improve energy-efficiency. Examples of energy modelling software include EnergyPlus, DesignBuilder, IESVE and eQuest.
Solar radiation modelling, used to assess the impact of solar radiation on the building envelope for shading purposes, ground surface for landscaping and outdoor comfort, and even to calculate renewable energy potential.
Computational fluid dynamics (CFD) simulations, which analyse airflows, temperature distribution and indoor air quality. CFD software examples include OpenFOAM, ANSYS Fluent, and Autodesk CFD.
Daylight modelling, used to analyse natural lighting conditions within a building. Software examples include Radiance, Velux Daylight Visualizer and ClimateStudio.
Lighting modelling, which includes analyses of artificial lighting levels and artificial lighting energy use, among other performance outputs. Software examples include Relux and DIALux.
Acoustic modelling, used to analyse sound transmission within a building. Examples of acoustic modelling software include Odeon, INSUL and CadnaA.

Daylight availability simulation inside a lecture theatre, used to test fenestration responses.
External lighting simulations are used to assess light pollution impact into the night sky.

Luminance contrast is analysed as a performance indicator for glare within an atrium.

Applications arising from computational design

Computational design is being used in innovative ways to create sustainable, energy-efficient and comfortable buildings and spaces. As the popularity of computational design grows, more subsets are derived, and more definitions arise as the industry tries to understand this complex niche.

Rather than getting lost within the definitions of these terms, ask the question: “How can computational design make our design process more efficient with better results for the building owner and the building users?”

Analysing outdoor comfort in public spaces using the Universal Thermal Climate Index (UTCI) metric.

There may be no limit as to how computational design can be applied. It allows designers to create complex geometries that can be optimised for specific environmental conditions. Another example is the use of performance data during early urban design and planning stages. These tools have enabled designers to create buildings and spaces that are both beautiful and functional, with high performance and efficiency.

Bringing meaning to ideas

Data-driven processes and procedures are changing the way we look at sustainable design and building operations. Efficient workflows can be utilised to include building performance in early stages of design, from concept to detailed design development, thus allowing for meaningful data-driven decisions on any project.

Emerging trends

Computational design has become a critical tool for architects engineers, and construction professionals in creating sustainable and energy-efficient buildings. These are some of the emerging trends in using computational design for environmental performance:

• Building information modelling (BIM) is a digital representation of a building’s physical and functional characteristics. BIM allows for the integration of different building systems, such as heating, ventilation and air conditioning (HVAC) and lighting, and enables designers to optimise building performance.
• Digital twins are virtual replicas of physical buildings that allow designers to monitor and optimise building performance in real-time. Digital twins use sensors and data analytics to simulate building conditions and identify opportunities for optimisation.
• Augmented reality (AR) is being used in building design and construction to provide real-time visualisation of building systems and components. AR allows designers and construction professionals to identify potential issues and optimise building performance in real-time.
• Machine learning can be used to optimise building systems, such as HVAC and lighting, based on real-time data. Machine learning algorithms can also be used to predict building energy consumption and identify opportunities to improve energy efficiency.

What’s in it for you?

Computational design and building performance modelling have made design and construction teams more efficient and effective in several ways.

Design better solutions

The computational design tools allow for iterative design, enabling designers to explore multiple design options and optimise building performance quickly. Hundreds or even thousands of design options can be available within minutes, whereas it would have likely taken days with manual design development and drafting. Performing analyses during design ideation, we can be part of the architectural process and allow architects to make informed decisions.

Hundreds or even thousands of design options can be available within minutes.

Automate repetitive tasks

In direct modelling, a simple task of updating dimensions can become tedious. In computational design tools, the algorithms play a huge role in facilitating the process, where all elements can be updated instantaneously in real time, and the impact on environmental performance can be seen almost immediately.

Mitigate design risks

Informed decision-making during the iterative design process enables us to improve design quality. The power of computation can bring forth higher quality than is achievable within human capabilities. The analysis doesn’t just cover building performance: using immersive reality and AI, we can even create multiple scenarios to test a design.

Reduce project costs

All of these outcomes can ultimately reduce project costs, yet still produce a high-quality building design. Automating repetitive tasks saves time so that there are fewer professionals involved, or more projects can be taken up within the same time frame. Mitigating design risks for better design solutions reduces the chance of reworks and potential design hazards during construction.

Using computational design and data-driven analyses for environmental performance and beyond in this industry has, and can still, revolutionise the way architects, engineers and construction professionals approach building and urban design. These tools allow for better collaboration, iterative design and cost reduction, creating a more sustainable built environment for future generations.

Yogesh Gooljar

Director and partner at PJC+Partners, Yogesh Gooljar combined a background in engineering with his interest in the building sector’s environmental performance, and now practises as a sustainability engineer and independent commissioning authority.

He has more than 15 years’ experience covering a wide range of projects in the residential, retail, educational and commercial sectors for both existing and new building developments on the African continent and Indian Ocean Islands.

As a Green Star Accredited Professional, Yogesh is involved in a wide range of projects pursuing green building certifications across multiple typologies for new build, existing building performance and net-zero ratings. He is passionate about data-driven, performance-based, human-centric design in the built environment, and believes that our goals for a cleaner and more resilient building industry should be backed by technology.