In November of 2023, an earthquake measuring 6.9 on the Richter scale hit Nepal and North India, resulting in 157 deaths and significant damage to buildings and infrastructure. Many people were crushed to death by collapsing buildings and structures. According to one IIT Kanpur study, over 75% of deaths during an earthquake are due to falling buildings. Engineers and researchers are constantly exploring ways to make buildings more resilient, especially during natural calamities.
Against this backdrop, a group of researchers from the Indian Institute of Technology (IIT) Madras is tackling this question by studying the connections between beams, the horizontal parts of a building that bear loads, and columns, the vertical supports. Since joints are the weakest points, not just in the human body but also in structures, understanding these connecting points can help improve building techniques.
Their research uses a computer modelling technique called the microplane model, which is part of a larger family of computer models called Gradient Damage Plasticity (GDP) models. GDP models, like the microplane model, simulate concrete behaviour under various loading conditions by combining concepts of plasticity and damage mechanics.
They used the Microplane model to address a particularly tough question: What happens to concrete and steel when a building starts to fail under strong forces, and how can we predict that failure more accurately? The team aims to improve the design of earthquake-resistant structures by combining expertise in civil engineering, materials science, and computational modelling.
For the study, the researchers examined beam-column junctions in steel-concrete composite frames. Composite frames use both steel and concrete, where the steel can bend and stretch, while concrete is excellent at handling compression and rigidity. Concrete alone is strong in compression but relatively brittle when stretched. Steel is strong in tension but can offer some ductility or bending before snapping. Where the beams and columns meet, engineers often add steel plates, bolts, and embedded steel bars in concrete to help keep everything intact.
When concrete cracks, it does not instantly go from fully strong to “failed.” It gradually loses stiffness and strength. Older computer models that use purely elastic or rigid attributes often struggle here. They didn’t represent the actual softening curve that happens in concrete in the real world. Gradient Damage Plasticity includes unique damage parameters that keep track of cracks and stiffness deterioration. The Gradient part of the model spreads out the damage instead of letting it concentrate in a single spot, which can cause unsteady simulation results. The Plasticity part represents permanent changes in shape or deformation. Using both these factors leads to an improved prediction of the joint behaviour.
The team gathered data from experiments to understand how these joints behave, especially beyond their point of maximum strength. They applied two different types of loads to the connecting point: monotonic loads, where a single sustained load is applied, or cyclic loads, where a strain is applied cyclically. The group compared the forces they recorded in the lab with the forces suggested by the computer model. They paid special attention to what happens after the concrete begins to crack and lose strength, a phase known as strain softening.
Understanding post-peak behaviour is crucial for earthquake-resistant design. Peak refers to the point where strain softening has started, and the concrete has begun to crack. Because Gradient Damage Plasticity can also replicate the softening and hardening behaviour, it offers insight into how cracks appear, grow, and sometimes even close up again under reversing loads, which is vital for real-world seismic conditions modelling. They found that their Gradient Damage Plasticity approach did a better job of capturing these cracks and shifts in strength than some older modelling methods.
Another improvement over older models by GDP models is the mesh objectivity. A mesh is a virtual net used to break a computer-based model into many small parts for simulation. Older methods were highly mesh-sensitive, meaning results could vary if you changed the size of these tiny segments. With GDP, the researchers found a more stable outcome that wasn’t so dependent on the mesh size, making the simulations more reliable.
The research emphasises that during an earthquake, it’s often the little details, like how a beam connects to a column, that matter most. By painstakingly modelling every crack and strain in concrete, the Gradient Damage Plasticity approach offers engineers a more precise tool for designing safer buildings. Even though it comes with added complexity and the need for thorough testing, the benefits may very well save lives when the ground starts to shake.