A Novel Digital Twin Framework for Structural Health Monitoring

Structures can be subjected to cyclic loading and corrosive environment while they are in operation and undesired consequences can occur which can cause human life losses, economical losses, or environmental pollution. To minimize such risks, it is important to continuously monitor the health of structures by using sensors located at different parts of structures by establishing their “digital twin”, so that necessary actions can be taken before catastrophic consequences occur. There are various structural health monitoring approaches available for this purpose. In this seminar, a new methodology, known as inverse Finite Element Method (iFEM), will be presented. iFEM has various advantages for being fast and robust which makes it suitable for real-time monitoring. Moreover, it is not necessary to measure loading acting on the structure which may not be an easy task under operational conditions. iFEM has been utilised for different structure types which will be demonstrated as part of this seminar. In addition, the importance of the location and number of sensors will be highlighted.
While iFEM is a useful technique for detecting damage in a structure, it is also important to predict how damages can evolve in the future. Prediction of fracture and failure is a challenging research area. There are various methods available for this purpose including well-known finite element (FE) method. FE method is a powerful technique for deformation and stress analysis of structures. However, it has various disadvantages in predicting failure due to its mathematical structure. In order to overcome this problem, a new computational technique peridynamics was introduced. Peridynamics is a meshless approach and it is very suitable for predicting crack initiation and propagation in structures subjected to different types of loading and environmental conditions. In this seminar, various applications of peridynamics will be demonstrated.