Artificial intelligence (AI) has burst onto the scene with transformative force, also within civil engineering, a discipline in which it is expanding the limits of what is possible. Traditionally, load management in the design, construction and maintenance of infrastructure was based on mathematical models and the experience of professionals. However, AI brings a new dimension by processing massive volumes of data and identifying patterns imperceptible to the human eye.
For example, AI tools enable engineers to anticipate in real time the behaviour of a structure under different situations and, in this way, prevent failures long before they materialise. The maximum optimisation of designs is another of its contributions, as these tools are capable of exploring countless possible structural configurations and recommending those that withstand loads with a minimum of materials and maximum efficiency. Consequently, they help to reduce construction costs. Meanwhile, the durability of structures is extended and their safety increased by improving their resistance to extreme loads.
Despite this promising outlook, the full adoption of AI in civil engineering is not without challenges. The quality and quantity of data available to train models remains a critical obstacle. Furthermore, the intrinsic complexity of accurately modelling highly variable physical phenomena is a challenge in itself. To this are added considerations regarding the costs and resources required to support these technologies, as well as growing concerns about the security and privacy of the data collected.
By Raúl Soriano, Senior Modeller in the Architecture Department at Amusement Logic
