Automation in decision making and design of retrofitting

Abstract

Civil engineering deals with a variety of tasks. Out of these constructions is the most widely known. Construction of a structure is aimed at two major requirements: Safety and Serviceability. As time progresses constructed structures need aids to maintain them. It may be because the structure loses its initial targeted or the change in requirement. The process of increasing strength, ductility, and stiffness of a structure are called retrofitting. There are two types of retrofitting, global and local retrofitting. The process of retrofitting deals with steps like designing, analysis and decision making. The conventional linear analysis is found to be less accurate; hence the nonlinear pushover analysis is gaining popularity. The design and analysis are generally done by the Finite Element Modelling and Analysis software. This makes the designing of retrofitting a complicated and tedious process. An experienced human intellect is needed. But as the field of automation is flourishing with all leaps and bounds, the field of civil engineering is no exception. The self-intelligent method can help in not only designing retrofit but also in decision making. Self-learning algorithms developed through supervised machine learning (regression model and decision tree) can assist the designing and decision-making process in the field of retrofitting. This can not only reduce the complicacy of the process but will also boost the accuracy and speed. This manner the Artificial Intelligence will Automate the Decision Making and Design of Retrofitting.