Assessment of multi-objective optimization for nondestructive evaluation of damage in structural components

A self-evolving parameterization approach for nondestructive evaluation (NDE) of damage in structural components is presented and numerically evaluated. Focused herein on problems relating to characterizing an unknown quantity of localized changes in properties, the adaptive approach utilizes the substantial solution diversity that is uniquely provided by multi-objective optimization to iteratively build up the parameterization and accurately characterize all localized property changes with the minimum dimensional parameterization. Through simulated test problems based on the characterization of damage within plates, the NDE approach with self-evolving parameterization is shown to provide an accurate and efficient process for the solution of inverse characterization problems.

The major focus in earthquake analysis is typically on the excitation caused by two in-plane horizontal components. However, the direction of vertical ground motion (VGM) is a critical aspect of an earthquake’s inherent nature that has received less attention in recent research. Accordingly’, the present study investigates the effects of VGM direction on the responses of a multi-span continuous concrete bridge pier seismically isolated with a friction pendulum system (FPS). The friction-based isolator is chosen because vertical force influences the coefficient of friction through variations in the normal force. To precisely assess the impact of vertical ground motion, a coefficient is proposed based on the ratio of the peak ground acceleration (PGA) of the vertical component in the upward and downward directions. The incremental dynamic analysis approach for the vertical component of an earthquake (IDA-V) is introduced and applied using a set of ground motion records. These records are categorized by their predominant vertical acceleration direction to emphasize the vertical impacts of inertia forces on the overall bridge responses. Fragility curves for substructure components are then developed. The results indicate that when the predominant direction of VGM is upward, it can cause compression-based damage in structural components, such as column compression failure and increased displacement of the friction pendulum systems (FPS). Conversely, when the predominant direction of VGM is downward, it can lead to tension-based damage, including tensile forces along the columns and a higher probability of isolator uplift. In general, incorporating the effects of VGM in the analysis increases the probability of failure across all structural components and damage states. Additionally, accounting for the upward or downward direction of VGM results in distinct types of damage.

Sensitivity analysis to precursor emissions of multi-objective air quality control policies

The determination of the optimal feed profiles for a reactive crystallizer is an important dynamic optimization problem, as the feed profiles offer a significant control over the quality of the product crystals. Crystallization processes typically have multiple performance objectives and optimization using different objective functions leads to significantly different optimal operating conditions. Therefore, a multiobjective approach is more appropriate for optimization of these processes. The potential for multiobjective optimization approach is demonstrated for semibatch reactive crystallization processes. The multiobjective approach usually gives rise to a set of optimal solutions, largely known as Pareto‐optimal solutions. The Pareto‐optimal solutions can help the designer visualize the trade‐offs between different objectives, and select an appropriate operating condition for the process. A well known multiobjective evolutionary algorithm, the elitist nondominated sorting genetic algorithm, has been adapted to illustrate the potential for the multiobjective optimization approach. © 2007 American Institute of Chemical Engineers AIChE J, 2007

This paper presents an experimental verification of a method of evaluating local damage in steel beam-column connections using modal vibratory characteristics under ambient vibrations. First, a unique testing method is proposed to provide a vibration-test environment which enables measurements of modal vibration characteristics of steel beamcolumn connection as damage proceeds. In the testing method, a specimen of structural component is installed in a resonance frame that supports large fictitious mass and the resonance frequency of the entire system is set as the natural frequency of a mid-rise steel building. The specimen is damaged quasi-statically, and resonance vibration tests are conducted with a modal shaker. The proposed method enables evaluation of realistic damage in structural components without constructing a large specimen of an entire structural system. The transition of the neutral axis and the reduction of the root mean square (RMS) of dynamic strain response are tracked in order to quantify damage in floor slabs and steel beams, respectively. Two specimens of steel beam-column connection with or without floor slab were tested to investigate sensitivity of the damage-related features to loss of floor composite action and fractures in steel beams. In the end, by updating numerical models of the specimens using the identified damage-related features, seismic capacities of damaged specimens were estimated.

Comparison on seismic resilience of hybrid, isolation, and damping control reinforced concrete frame-shear wall buildings

A multi-objective evolutionary approach for the electric vehicle charging stations problem

Coordinated multi-stage and multi-objective optimization approach for ship collision avoidance decision-making

The increasing in the demand for Wireless Sensor Networks (WSNs) has intensified studies which are dedicated to obtain more energy-efficient solutions, since the energy storage limitation is critical in those systems. Additionally, there are other aspects which usually must be ensured in order to get an acceptable performance of WSNs, such as area coverage and network connectivity. This paper proposes a procedure for enhancing the performance of WSNs: a multiobjective hybrid optimization algorithm is employed for solving the Dynamic Coverage and Connectivity Problem (DCCP) in flat WSNs subjected to node failures. This method combines a multiobjective global on-demand algorithm (MGoDA), which improves the current DCCP solution using a Genetic Algorithm, with a local on line algorithm (LoA), which is intended to restore the network coverage soon after any failure. The proposed approach is compared with an Integer Linear Programming (ILP)-based approach and a similar mono-objective approach with regard to coverage, network lifetime and required running time for achieving the optimal solution provided by each method. Results achieved for a test instance show that the hybrid approach presented can improve the performance of the WSN obtaining good solutions with a considerably smaller computational time than ILP. The multiobjective approach still provides a feasible method for extending WSNs lifetime with slight decreasing in the network mean coverage.

Recent earthquake events evidenced that damage of structural components in a lifeline network may cause prolonged disruption of lifeline services, which eventually results in significant socio‐economic losses in the affected area. Despite recent advances in network reliability analysis, the complexity of the problem and various uncertainties still make it a challenging task to evaluate the post‐hazard performance and connectivity of lifeline networks efficiently and accurately. In order to overcome such challenges and take advantage of merits of multi‐scale analysis, this paper develops a multi‐scale system reliability analysis method by integrating a network decomposition approach with the matrix‐based system reliability (MSR) method. In addition to facilitating system reliability analysis of large‐size networks, the multi‐scale approach enables optimizing the level of computational effort on subsystems; identifying the relative importance of components and subsystems at multiple scales; and providing a collaborative risk management framework. The MSR method is uniformly applied for system reliability analyses at both the lower‐scale (for link failure) and the higher‐scale (for system connectivity) to obtain the probability of general system events, various conditional probabilities, component importance measures, statistical correlation between subsystem failures and parameter sensitivities. The proposed multi‐scale analysis method is demonstrated by its application to a gas distribution network in Shelby County of Tennessee. A parametric study is performed to determine the number of segments during the lower‐scale MSR analysis of each pipeline based on the strength of the spatial correlation of seismic intensity. It is shown that the spatial correlation should be considered at both scales for accurate reliability evaluation. The proposed multi‐scale analysis approach provides an effective framework of risk assessment and decision support for lifeline networks under earthquake hazards. Copyright © 2009 John Wiley & Sons, Ltd.

Optimal release time determination is a typical application of software reliability models. In this decision process, reliability and cost are the two important dimensions that are generally considered. Most existing research formulates this decision process as single-objective optimization problems. Although these formulations can greatly reduce the complexity, they can hardly reflect the nature of the decision process, which is essentially a multi-objective optimization problem. More specifically, maximizing reliability and minimizing cost should be achieved simultaneously. Due to this consideration, in this paper, software release time determination is investigated by various multi-objective optimization approaches, including the trade-off analysis, multi-attribute utility theory, and physical programming approach. Numerical examples are provided for illustrative purpose. The applicability and limitations of different multi-objective optimization approaches are also discussed, which can help management to make a more reasonable decision in practice.

Pareto based multi-objective optimization of turbulent heat transfer flow in helically corrugated tubes

A multi-objective approach to the application of real-world production scheduling

The multi-objective optimization approach has a large influence in the industrial production scheduling. The goal of such optimization is to find a production schedule that satisfies different, usually contradictory, production and business constraints. In the paper, memetic versions of three multi-objective algorithms with different approaches to problem solving are implemented. The customized reproduction operators and local search procedures are also used. These memetic algorithms are applied to real order-lists from a production company. It is shown that the multi-objective approaches are able to find high-quality solutions, also when quick respond is required to adapt to dynamic business conditions. According to the results it is concluded that for the two tested real-world problems the IBEA confirmed its superiority over the NSGA-II and SPEA2.

For operational optimization of the iron ore beneficiation process which is a multi-stage process, the objective of each unit process (i.e. the operational indices) should be coordinated to fulfill the targets of global production indices. The relationship between the operational indices and the production indices is complex and it is difficult to be described using exact mechanism model, therefore the existing approaches cannot be used. To solve this problem, a multiobjective operational optimization approach for iron ore beneficiation process is proposed, which includes a multiobjective optimization module, a prediction based evaluation module and a dynamic regulation module. The proposed approach can generate the initial operational indices and then adjust it using the prediction information of production indices. The experiment based on the actual production data is carried out and results show the effectiveness of the proposed approach.