Faculty Advisor or Committee Member

Yeesock Kim, Advisor

Faculty Advisor or Committee Member

Leonard D. Albano, Committee Member

Faculty Advisor or Committee Member

Jo Woon Chong, Committee Member

Identifier

etd-041214-153536

Abstract

In recent years, response analysis of complex structures under impact loads has attracted a great deal of attention. For example, a collision or an accident that produces impact loads that exceed the design load can cause severe damage on the structural components. Although the AASHTO specification is used for impact-resistant bridge design, it has many limitations. The AASHTO specification does not incorporate complex and uncertain factors. Thus, a well-designed structure that can survive a collision under specific conditions in one region may be severely damaged if it were impacted by a different vessel, or if it were located elsewhere with different in-situ conditions. With these limitations in mind, we propose different solutions that use smart control technology to mitigate impact hazard on structures. However, it is challenging to develop an accurate mathematical model of the integrated structure-smart control systems. The reason is due to the complicated nonlinear behavior of the integrated nonlinear systems and uncertainties of high impact forces. In this context, novel algorithms are developed for identification, control and monitoring of nonlinear responses of smart structures under high impact forces. To evaluate the proposed approaches, a smart aluminum and two smart reinforced concrete beam structures were designed, manufactured, and tested in the High Impact Engineering Laboratory of Civil and Environmental Engineering at WPI. High-speed impact force and structural responses such as strain, deflection and acceleration were measured in the experimental tests. It has been demonstrated from the analytical and experimental study that: 1) the proposed system identification model predicts nonlinear behavior of smart structures under a variety of high impact forces, 2) the developed structural health monitoring algorithm is effective in identifying damage in time-varying nonlinear dynamic systems under ambient excitations, and 3) the proposed controller is effective in mitigating high impact responses of the smart structures.

Publisher

Worcester Polytechnic Institute

Degree Name

PhD

Department

Civil & Environmental Engineering

Project Type

Dissertation

Date Accepted

2014-04-12

Award

Sigma Xi Graduate Research Award for Outstanding Doctoral Dissertation (2015)

Accessibility

Unrestricted

Subjects

high impact load, magnetorheological (MR) damper, discrete wavelet transform, fuzzy logic control, structural health monitoring, nonlinear system identification, adaptive neuro-fuzzy inference system (ANFIS)

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