Author ORCID Identifier
Semester
Summer
Date of Graduation
2024
Document Type
Dissertation
Degree Type
PhD
College
Statler College of Engineering and Mineral Resources
Department
Mechanical and Aerospace Engineering
Committee Chair
Nithi T. Sivaneri, Ph.D.
Committee Co-Chair
Osama M. Mukdadi, Ph.D.
Committee Member
Christopher D. Griffin, Ph.D.
Committee Member
Marcello R. Napolitano, Ph.D.
Committee Member
Adam M. Halasz, Ph.D.
Abstract
Knowledge of excitation loads that structures experience during their service life is pivotal in different engineering fields, not only from a structural design optimization point of view but also as prevention of possible damages to the structures themselves. However, in case of dynamic events such as tornadoes, structures subjected to impulsive load due to their vicinity of explosions, the excitation load cannot be directly determined through direct measurements. In these scenarios, the inverse problem is used, and it is called load identification. This type of problem tries to determine the excitation load knowing the system response through a series of sensors placed on the structure. Most of the time, the number of sensors and their locations are randomly selected causing errors in the load estimation. The proposed mathematical method provides the appropriate number of sensors and their optimal locations. It combines the Craig-Brampton condensation method with the normal-mode method and D-optimal design technique. This method is employed and verified on simple structural members such as beams and plates and then it is applied on more complex structures such as a wind-turbine tower, wind-turbine blade, and an aircraft wing, which lead to more complexity in the procedures. Finite element models of these simple and complex structures are made in the general-purpose software ABAQUS. Then, a free-vibration analysis is carried out on each structure and the natural frequencies and mode shapes are extracted. Different load shapes are applied on the structures at different frequencies and noise conditions. The dynamic load is reconstructed by measuring the transient response of the structure at the optimum sensor locations. The results reveal that the proposed method can reconstruct a dynamic load with a high level of accuracy. Furthermore, the implementation of different parameters, such as noise effects, does not cause amplified errors in the final load estimation making the proposed method more robust.
Recommended Citation
Pecora, Iole, "Dynamic Load Identification using Optimal Sensor Placement and Dynamic Condensation Methods" (2024). Graduate Theses, Dissertations, and Problem Reports. 12591.
https://researchrepository.wvu.edu/etd/12591