Date of Award
Master of Science
Anoop K. Dhingra
Ilya Avdeev, Wilkistar Otieno
Inverse Calculations, Matrix Operations, Model Reduction, Moving Load Identification, Numerical Methods, Structural Engineering
A structure in service can be subjected to static, dynamic or moving loads. Several situations in practice involve estimation of moving loads which induce vibrations in the structure on which they are applied. An accurate estimation of these loads will ensure product quality and reliability of the final design, and mitigate the cost of structural health monitoring systems. The moving nature of dynamic loads increases the computational difficulty of the problem. One of the types of Inverse Problems involves estimation of the applied load from measured structural response such as strain or accelerations.
Measuring response at a limited number of locations causes unavailability of the full structural response, which can lead to inaccurate results. The unavailability of full structural response is mainly due to three reasons - (i) financial constraints limiting the number of sensors that can be used, (ii) inaccessibility of loading locations to place sensors, and (iii) sensor influence on structural response. The load recovered from limited structural response data will be prone to errors. Ill-conditioning of the inverse problem can be eliminated by choosing optimum sensor locations on the structure, which leads to precise load estimates. No studies could be found which consider optimum sensor placement while recovering dynamic moving loads acting on a structure.
In this thesis, the recovery of the dynamic moving loads through measurement of structural response at a finite number of optimally selected locations is investigated. Optimum sensor locations are identified using the D-optimal design algorithm. Separate algorithms are developed for dynamic moving load recovery using strain measurements and acceleration measurements. The developed algorithms are successfully implemented using ANSYS APDL and MATLAB programming environment. Compared to conventional algorithms for estimating moving loads, the developed methods make the dynamic moving load recovery procedure accurate and relatively easy to implement.
Augustine, Paul, "Dynamic Moving Load Identification Using Optimal Sensor Placement and Model Reduction" (2015). Theses and Dissertations. 971.