Nader M. Okasha

Novel Approach for Multicriteria Optimization of Life-Cycle Preventive and Essential Maintenance of Deteriorating Structures

In this paper, the performance of structures is modeled using lifetime functions. Specifically, the unavailability and redundancy are used as performance indicators, based on which optimum maintenance strategies are sought. Models that reflect the separate or combined effects of essential and preventive maintenance on the unavailability are presented. A novel optimization approach is proposed in which the problem is formulated to provide optimum maintenance strategies with either or both essential and preventive maintenance actions. Genetic algorithms are used to solve this problem. In this paper, multiple essential maintenance types and multiple preventive maintenance types are considered, and regular or irregular preventive maintenance time-intervals are considered. Furthermore, essential maintenance is treated as performance-based, i.e., essential maintenance is only applied when a performance threshold is reached, and an algorithm is proposed for conducting the optimization under uncertainty. Although applicable to any type of structure, the proposed approach is illustrated on a highway bridge example.

Time-variant redundancy of structural systems

Structural redundancy is expected to change over time due to time-variant loading and damage under uncertainties. The objective of this paper is to investigate the time-variant redundancy of structural systems. Analyses of structural reliability and redundancy affected by deterioration in structural resistance and increase in applied loads are conducted by using numerical examples. It is shown that the structural system redundancy is influenced by several factors, such as the material type, the resistance correlation structure and deterioration rate and the rate of increase in applied loads. The results show the importance of including the time factor in the quantification of redundancy. Such results are useful for identifying the best measures to take in order to maintain a satisfactory level of redundancy throughout the life of structural systems and to incorporate the time-variant redundancy in a lifetime-oriented multi-objective optimisation framework of risk-based management of structural systems.

Redundancy of structural systems with and without maintenance: An approach based on lifetime functions

The lifetime reliability of existing structures may be quantified by lifetime functions. Redundancy is an additional type of structural performance indicator that is defined as a measure of warning available prior to system collapse. Lifetime functions provide a basis on which lifetime redundancy can be evaluated and its quantification can be formulated. The objective of this paper is to present a novel approach for the evaluation of the lifetime redundancy of structural systems. Measures of lifetime redundancy based on lifetime functions are investigated. The effects of maintenance on lifetime functions and redundancy are also presented. Furthermore, the lifetime redundancy is incorporated in a maintenance optimization algorithm. This optimization algorithm is illustrated on an existing highway bridge.

Reliability analysis and damage detection in high-speed naval craft based on structural health monitoring data

Current and future trends in naval craft design are leaning toward the development of high-speed and high-performance vessels. Lack of information on wave-induced loads for these vessels presents a challenge in ensuring their safety that is best tackled with monitoring operational loads and detecting damage via structural health monitoring (SHM) systems. These monitoring systems, however, require efficient statistical and probabilistic procedures that are able to effectively treat the uncertainties inherent in the massive volumes of collected data and provide interpretable information regarding the reliability and condition of the craft structure. In this article, an approach for using SHM data in the reliability analysis and damage detection in high-speed naval craft (HSNC) under uncertainty is presented. This statistical damage detection technique makes use of vector autoregressive modeling for detection and localization of damage in the ship structure. The methodology is illustrated on an HSNC, HSV-2. Data obtained from seakeeping trials of HSV-2 were treated as the SHM data mentioned above.

Integration of structural health monitoring in a system performance based life-cycle bridge management framework

In this paper, an approach for integrating the information obtained from structural health monitoring in a life-cycle bridge management framework is proposed. The framework is developed on the basis of life-cycle system performance concepts that are also presented in this paper. The performance of the bridge is quantified by incorporating prior knowledge and information obtained from structural health monitoring using Bayesian updating concepts. This performance is predicted in the future using extreme value statistics. Advanced modelling tools and techniques are used for the lifetime reliability computations, including incremental nonlinear finite element analyses, quadratic response surface modelling using design of experiments concepts, and Latin hypercube sampling, among other techniques. The methodology is illustrated on an existing bridge in the state of Wisconsin.

Advanced Modeling for Efficient Computation of Life-Cycle Performance Prediction and Service-Life Estimation of Bridges

The rapid progress in computational hardware and software has brought about advanced capabilities enabling more accurate modeling of structures and better understanding of their lifetime behavior. Unfortunately, research in life-cycle performance prediction and service-life estimation of bridges has not fully caught up with the impressive advances in today’s technology, and has not taken enough advantage of the power offered by these advances. In this paper, a computational methodology for the life-cycle prediction and service-life estimation of bridges using advanced modeling tools and techniques is presented. The methodology employs incremental nonlinear finite element analyses, quadratic response surface modeling using design of experiments concepts, and Latin hypercube sampling, among other techniques. The methodology is illustrated on an existing bridge in the state of Wisconsin.

Automated finite element updating using strain data for the lifetime reliability assessment of bridges

The importance of improving the understanding of the performance of structures over their lifetime under uncertainty with information obtained from structural health monitoring (SHM) has been widely recognized. However, frameworks that efficiently integrate monitoring data into the life-cycle management of structures are yet to be developed. The objective of this paper is to propose and illustrate an approach for updating the lifetime reliability of aging bridges using monitored strain data obtained from crawl tests. It is proposed to use automated finite element model updating techniques as a tool for updating the resistance parameters of the structure. In this paper, the results from crawl tests are used to update the finite element model and, in turn, update the lifetime reliability. The original and updated lifetime reliabilities are computed using advanced computational tools. The approach is illustrated on an existing bridge.

Proposed Algorithms for an Efficient System Reliability-Based Design Optimization of Truss Structures

AbstractThe design optimization considering the system reliability of a structural system is a computationally challenging task. This is especially the case in an indeterminate structure that has many possible modes or paths to complete failure. Accomplishing this task efficiently requires using enhanced and powerful techniques for the structural analysis, the reliability analysis, and the optimization solution. In a simulation-based reliability analysis, the actual value of the performance functions is irrelevant to the calculated probability of failure. The actual value of the performance function is merely calculated to determine whether the system failed or not. In this paper, nonlinear analysis algorithms for truss structures are proposed. These algorithms are used for determining whether the structural system failure occurs during the simulation-based system reliability analysis in a computationally efficient manner. Using these algorithms, a simulation-based system reliability design optimization o...

Redundancy of Structural Systems based on Survivor Functions

Efficient management of transportation infrastructure requires the ability to accurately predict its lifetime performance. The uncertainties associated with deteriorating structures require the use of probabilistic methods to properly asses their lifetime performance. Existing and used lifetime performance indicators thus far are mostly safety based, such as the reliability index and the probability of failure or survival. The lifetime performance of existing structures may also be characterized by survivor functions. These functions allow the consideration of the effect of aging on the decrease of the probability of survival of a structure. Redundancy is an additional structural performance indicator that measures the adequacy of warning available prior to system collapse. Probabilistic measures of redundancy are usually formulated in terms of the reliability index or probabilities of failure or damage occurrence. Survivor functions provide an alternative basis on which lifetime redundancy can be evaluated and its measures can be formulated. The objective of this paper is to present a novel approach for the evaluation of the lifetime redundancy of structural systems. Measures of lifetime redundancy based on survivor functions will be investigated. The lifetime redundancy of various structural systems will be explored, including series, parallel, and series-parallel systems.