Researchers at a US university claim to have created a powerful computer model capable of radically reducing carbon emissions and materials used in construction projects – potentially using a laptop
A team at the Massachusetts Institute of Technology (MIT) have developed a computational framework that could significantly reduce the amount of material used in buildings and bridges.
The technique, described in a new paper published in the journal Automation in Construction, builds on an existing design method called topology optimisation – a computer-based approach that calculates the most efficient distribution of material within a given structure.
While topology optimisation has existed for decades, its practical application in the construction industry has remained limited. The MIT team says it has now developed a framework that makes the method genuinely viable for civil and structural engineers working on real projects.
The research was led by Josephine Carstensen, MIT’s Gilbert W. Winslow Career Development professor in civil engineering, alongside PhD student and first author Zane Schemmer.
The gap between theory and construction
Topology optimisation is capable of reducing material use by as much as 90% in certain applications, the author’s claim. That’s a saving that researchers say could represent a multi-gigaton reduction in building-related carbon emissions.
Global production of construction materials accounted for more than seven per cent of total carbon emissions in 2022, according to figures cited in the paper.
Despite its potential, the method has largely been confined to academic research and specialist manufacturing processes such as 3D printing, where complex geometries can be produced with relative ease.
In construction, the intricate, web-like structures that topology optimisation tends to generate have been considered too difficult and too costly to build using conventional methods.
“In the literature, there’s sometimes been a disconnect between the carbon savings you can achieve on a computer and the realistic carbon savings you can achieve for built structures – especially when it comes to design technologies like topology optimisation,” said Carstensen.
“The problem lies in the lack of constructability of designs. These designs have been perceived as too difficult to make with conventional methods, so they are never even attempted. That’s what is exciting about our approach: we can add constraints so that you will never be in a situation where the design that comes out is too hard to make.”
Schemmer added: “A big question Josephine and I were asking is why isn’t industry using it? What are the obstacles that prevent industry from designing things more efficiently, and how can we fill the gaps between research and real life?”
How the framework works
The MIT framework allows engineers to apply practical constraints to algorithmically generated structures, limiting their complexity to levels that are achievable on site and within budget.
Users can specify the maximum number of components that meet at any single joint, the minimum angle permitted between connected elements, and the smallest allowable part size. Each of these parameters directly influences how the model generates its final design.
Underpinning the system is a class of mathematical tools known as mixed integer algorithms, which enable the model to make binary decisions – for instance, whether a given component should be made from timber or steel, rather than producing an ambiguous blend of the two.
“You can’t have a part that’s 72% timber and 28% steel,” said Schemmer. “Instead, it says, ‘This truss or cable is going to be made out of this,’ and then based on that decision, how do we make sure all of these connections meet their strength standards?”
The framework also accounts for the structural behaviour of different materials. Steel struts, for example, can resist compressive loads, while steel cables cannot. The model incorporates these distinctions and applies them when determining how loads should be distributed across a structure.
Connection detailing – long a weakness of earlier topology optimisation approaches – has also been improved to reflect the real-world constraints of timber and steel construction, which each carry distinct rules governing how members join.
The researchers tested their approach by designing truss structures for buildings and bridges using steel only, timber only, and combinations of the two materials. They also used the Lockport “Upside-Down Bridge” near Buffalo, New York, as a case study, applying individual constraints to the bridge’s truss design to examine how each parameter affected the outcome.
“A big aspect of sustainability going forward will be not only using less material, but also implementing materials efficiently based on considerations like where you are in the world, your access to materials, and each of their associated carbon costs,” said Schemmer.
The wood-steel hybrid designs illustrated the potential of the combined approach. “We saw how the system knew that you could design a bridge of pure steel, but that might not be best from a carbon standpoint,” said Schemmer. “Or you could design a bridge out of purely timber, but that might not be the strongest. But these materials can work together, so you use timber for the carbon savings and steel where you need extra strength, and there’s a balance you can find in these structures.”
Viability for industry
The researchers acknowledge that their method is more computationally demanding than simpler topology optimisation approaches. However, they note that the experiments were conducted on a standard MacBook Pro, and they believe the framework is within reach of most civil engineering practices.
“It’s computationally a little tougher to solve, but there’s a lot of tools coming out nowadays that make these problems a lot more feasible,” said Schemmer. “This approach has been avoided by industry in the past, but now we think it’s a practical way to solve problems dealing with variable constraints.”
For firms with greater computing resources, the team says the framework could be scaled to accommodate a wider range of materials and larger, more complex structures than those examined in the paper.
Next steps for the research team include the physical construction of scaled-down structures designed by the model, which will allow them to validate its predictions against real-world performance. They also intend to refine the constraint system further to make the tool more seamlessly integrated into existing engineering workflows.
Carstensen said the broader ambition is to close the long-standing gap between what optimisation software can theoretically achieve and what the construction industry can practically deliver.
Schemmer said: “As a structural engineer by training, I was never taught how to design for low-carbon. To tackle a problem as big as climate change, addressing the built environment is a great place to start.”
Image credit: Ranimiro Lotufo Neto/Shutterstock
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