The field of structural design has witnessed the rapid evolution of technology over the past decade, especially with the emerging use of artificial intelligence (AI) to optimise and automate the design process. One of the most promising and impactful applications of AI is the design of steel reinforcement, which is a vital component of any concrete structure.
Steel reinforcement provides strength, ductility and durability to concrete structures. However, designing steel reinforcement is a complex and tedious task, as it involves considering various factors such as load, stress, strain, deflection, cracking, corrosion, fire resistance and constructability. Traditionally, this task is done manually by engineers using codes, standards and empirical formulas. This can lead to errors, inefficiencies and inconsistencies in the design.
AI can help overcome these challenges by providing new tools and methods that can enhance the quality, efficiency and creativity of the design process.
Modelling systems
AI can help create accurate and realistic models of structures using data from sensors, images, drawings and simulations. These models can capture the geometry, material properties, boundary conditions and loading scenarios of the structures. AI can also help update and refine these models based on feedback from testing and monitoring.
Analysis and optimisation
AI can help analyse the behaviour and performance of structures under different forces and conditions using numerical methods, such as finite element analysis (FEA). AI can also help optimise the design of structures by finding the best combination of parameters that minimise cost, weight, material usage and environmental impact while maximising safety, functionality and aesthetics.
Prediction and decision-making
AI can help predict the future outcomes and risks of structures using statistical methods, such as machine learning (ML) and deep learning (DL). These methods can learn from historical data and patterns to make predictions about unknown or uncertain situations. AI can also help make informed decisions about the design of structures by providing recommendations, suggestions and alternatives based on the analysis and optimization results.
Generative Design
One of the most exciting applications of AI in structural design is the use of generative design. Generative design is a process that uses AI to generate multiple design options that meet certain criteria or objectives. The designer can then explore, evaluate and select the best option for the project. Generative design can enable faster, cheaper and more innovative solutions for structural design.
One example of generative design for steel reinforcement is the use of topology optimization. Topology optimization is a method that uses FEA to find the optimal distribution of material in a given domain or space. The method can reduce the amount of material used while maintaining or improving the structural performance. Topology optimization can help design steel reinforcement that is efficient, lightweight and aesthetically pleasing.
AI is revolutionising the way we design structures in the construction industry, unleashing new potential for quality, efficiency and creativity. Architects and civil engineers can harness AI as a powerful partner to elevate their profession and their projects. With AI, they can craft stunning structures that serve their society and their environment safely and efficiently for years to come.
