Numerical Modeling of Structures Using Advanced Software and the Role of Artificial Intelligence in Improving Accuracy and Speed of Analyses

Technological advances over the past decade, especially in artificial intelligence (AI) and machine learning, have significantly impacted the field of structural engineering. These modern technologies have introduced new methods to analyze and predict the behavior of structures more accurately and efficiently. While traditional numerical software such as ABAQUS and ANSYS provide detailed and precise structural analysis, they often require high computational power, complex configurations, and rely on simplifications that can reduce their overall efficiency. AI algorithms, particularly deep learning and reinforcement learning techniques, offer innovative ways to simulate nonlinear structural behavior, which is difficult to capture with classical methods alone. This paper investigates how combining classical numerical methods with modern AI technologies can result in more accurate, faster, and cost-effective structural analyses. Moreover, the important role of AI in structural health monitoring (SHM) is examined, focusing on its potential to detect damage early and reduce the risks associated with structural failures. By comparing AI-based models with traditional approaches, the study provides insights into the future of structural modeling and engineering. The integration of AI in this field is expected to enhance the safety, reliability, and sustainability of engineering projects worldwide.

کلیدواژه ها:

Numerical Modeling ، Artificial Intelligence ، Machine Learning ، Nonlinear Behavior ، Structural Health Monitoring ، Structural Analysis.