Seung-Yong Ok

System reliability analysis using dominant failure modes identified by selective searching technique

The failure of a redundant structural system is often described by innumerable system failure modes such as combinations or sequences of local failures. An efficient approach is proposed to identify dominant failure modes in the space of random variables, and then perform system reliability analysis to compute the system failure probability. To identify dominant failure modes in the decreasing order of their contributions to the system failure probability, a new simulation-based selective searching technique is developed using a genetic algorithm. The system failure probability is computed by a multi-scale matrix-based system reliability (MSR) method. Lower-scale MSR analyses evaluate the probabilities of the identified failure modes and their statistical dependence. A higher-scale MSR analysis evaluates the system failure probability based on the results of the lower-scale analyses. Three illustrative examples demonstrate the efficiency and accuracy of the approach through comparison with existing methods and Monte Carlo simulations. The results show that the proposed method skillfully identifies the dominant failure modes, including those neglected by existing approaches. The multi-scale MSR method accurately evaluates the system failure probability with statistical dependence fully considered. The decoupling between the failure mode identification and the system reliability evaluation allows for effective applications to larger structural systems.

Robust multi-objective maintenance planning of deteriorating bridges against uncertainty in performance model

This study proposes a new robust multi-objective maintenance planning approach of the deteriorating bridges against uncertainty in performance degradation model. The main focus is to guarantee the performance requirements of the bridge by the scheduled maintenance interventions even in the presence of uncertainty in time-dependent performance degradation model. The uncertainties are modeled as the perturbation of the system parameters. These are simulated by a sampling method, and incorporated into the GA-based multi-objective optimization framework which produces a set of optimal preventive maintenance scenarios. In order to focus the searching on the most preferable region, the performance models of the bridge components are all integrated into single overall performance measure by using the preference-based objective-space reduction method. Numerical example of a typical prestressed concrete girder bridge is provided to demonstrate the new robust maintenance scheduling approach. For comparison purpose, non-robust multi-objective maintenance planning without considering uncertainty of the bridge performance is also provided. It is verified that the proposed approach can produce successfully-performing maintenance scenarios under the perturbation of bridge condition grades while maintaining well-balanced maintenance strategy both in terms of bridge performance and maintenance cost.

Robust Performance of Fuzzy Supervisory Control for Seismically Excited Cable-Stayed Bridge

This paper investigates the robust performance of fuzzy supervisory control (FSC) technique for seismically excited cable-stayed bridge. The FSC technique utilizes fuzzy logic-based decision-making process to incorporate a set of pre-designed static control gains into a time-varying optimal control gain. To demonstrate the excellent robustness of the FSC technique on response control of earthquake-excited cable-stayed bridge, a conventional linear quadratic Gaussian (LQG) controller with single static gain and two fuzzy supervisory controllers are designed for the benchmark cable-stayed bridge, and their robust performances are examined under uncertainty in bridge model and against failures in actuators and sensors. Under the presence of uncertainty in the bridge model, the FSC system successfully reduces the seismic responses of the bridge without significant increase in the total amount of power and stroke required by the control system, while the LQG system exhibits a substantial increase in the seismic responses. Under conditions of sensor or actuator failures, the FSC system guarantees a more enhanced robust performance than the LQG system as well.

System Reliability Analysis of Rack Storage Facilities

This study proposes a system reliability analysis of rack storage facilities subjected to forklift colliding events. The proposed system reliability analysis consists of two steps: the first step is to identify dominant failure modes that most contribute to the failure of the whole rack facilities, and the second step is to evaluate the system failure probability. In the first step, dominant failure modes are identified by using a simulation-based selective searching technique where the contribution of a failure mode to the system failure is roughly estimated based on the distance from the origin in the space of the random variables. In the second step, the multi-scale system reliability method is used to compute the system reliability where the first-order reliability method (FORM) is initially used to evaluate the component failure probability (failure probability of one member), and then the probabilities of the identified failure modes and their statistical dependence are evaluated, which is called as the lower-scale reliability analysis. Since the system failure probability is comprised of the probabilities of the failure modes, a higher-scale reliability analysis is performed again based on the results of the lower-scale analyses, and the system failure probability is finally evaluated. The illustrative example demonstrates the results of the system reliability analysis of the rack storage facilities subjected to forklift impact loadings. The numerical efficiency and accuracy of the approach are compared with the Monte Carlo simulations. The results show that the proposed two-step approach is able to provide accurate reliability assessment as well as significant saving of computational time. The results of the identified failure modes additionally let us know the most-critical members and their failure sequence under the complicated configuration of the member connections.

Multiobjective Optimization Approach for Robust Bridge Damage Identification against Sensor Noise

One of the important goals of structural health monitoring is to identify structural damage using measured responses. However, such damage identification is sensitive to noises in the response measurements. Even a small change in the measurement may result in a significantly biased damage assessment. The goal of this paper is to expand the multiobjective optimization approach developed for robust damage identification in order to facilitate its applications to more realistic bridge damage identification problems. Specifically, a benchmark problem on highway bridges, developed under the auspices of International Association for Bridge Maintenance and Safety (IABMAS), is investigated. Various issues regarding sensor noises, multiple measurements, and loading scenarios are addressed to improve the robustness of bridge damage identification. A major finding from this study is that the stochastic process of Pareto optimal solutions obtained in a single run not only captures the actual damage locations successfully but also provides useful information such as damage-detected ratio on the potential candidates for damage to be inspected on site. Moreover, it is shown through the success, failure, and partial detection rates that the robustness of the proposed approach can be improved by using appropriate excitation scenarios and multiple sets of measurement data.

Efficient Vibration Control Approach of Two Identical Adjacent Structures

Abstract : This study proposes a new control approach for efficient vibration suppression of two identical adjacent structures. The conventional control approach of two adjacent structures is to interconnect the two structures with passive, semi-active or active control devices. However, when the two adjacent structures are identical to each other, their dynamical behaviors such as frequency and damping properties are also the same. In this case, the interconnected control devices cannot exhibit the dissipative control forces on the both structures as expected since the relative displacements and velocities of the devices become close to zero. In other words, the interconnection method does not work for the twin structures as enough as expected. In order to solve this problem, we propose several new control approaches to effectively and efficiently reduce the identically-fluctuating responses of the adjacent structures with minimum control efforts. In order to demonstrate the proposed control systems, the proposed several control systems are optimally designed and their control performances are compared with that of the conventional optimal control system where each TMD(tuned mass damper) is installed in each structure for independent control purpose. The simulated results show that one of the proposed control systems(System 04) is able to guarantee enhanced control performance compared with the conventional system.

FORM-based Structural Reliability Analysis of Dynamical Active Control System

Abstract : This study describes structural reliability analysis of actively-controlled structure for which random vibration analysis is incorporated into the first-order reliability method (FORM) framework. The existing approaches perform the reliability analysis based on the RMS response, whereas the proposed study uses the peak response for the reliability analysis. Therefore, the proposed approach provides us a meaningful performance measure of the active control system, i.e., realistic failure probability. In addition, it can deal with the uncertainties in the system parameters as well as the excitations in single-loop reliability analysis, whereas the conventional random vibration analysis requires double-loop reliability analysis; one is for the system parameters and the other is for stochastic excitations. The effectiveness of the proposed approach is demonstrated through a numerical example where the proposed approach shows fast and accurate reliability (or inversely failure probability) assessment results of the dynamical active control system against random seismic excitations in the presence of parametric uncertainties of the dynamical structural system.