Document Type : Review Article

Authors

1 Master of Structural Engineering, Shahid Bahonar University, Kerman

2 CEO, Faraz Tarh-e-Hegmatane Consulting Engineers Co.

3 Technical Deputy of Three Municipality Region Hamedan

Abstract

In today's modern world, traces of artificial intelligence can be found in almost any field. In recent years, with the introduction of algorithms and machines, the fields of building engineering and construction project management have also experienced new challenges, from optimizing processes and improving product design to automating tasks and parametric design. Artificial intelligence in structural engineering involves the use of advanced algorithms and machine learning techniques to simplify and improve various aspects of the design and analysis process. Also, artificial intelligence software related to construction is a group of technological tools and solutions that use artificial intelligence to optimize various functions of this industry. On the other hand, one of the relatively new topics that artificial intelligence can enter into is the investigation of various types of damage, including progressive damage in the design and construction of structures. In this article, an attempt has been made to define artificial intelligence and machine learning, to explain the various functions of this technology, and practical algorithms, plus introduce useful and pioneering software in civil engineering, where artificial intelligence is the main origin. Also, the basic influencing parameters in the study of progressive collapse, such as critical path identification and extreme load patterns, have been investigated. According to the functions stated in this research, the importance of using artificial intelligence in theoretical studies and future applied projects is clearly known. Especially vital projects such as Spatial Structures or buildings with a special seismic bearing system such as Staggered Truss Systems and structures with high ductility requirements that need special analysis, design, and monitoring.

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