Reliability Optimization Design Research Articles

Reliability design optimization of composite structures based on PSO together with FEA

The present work aims to develop a method for reliability-based optimum design of composite structures. A procedure combining particle swarm optimization (PSO) and finite element analysis (FEA) has been proposed. Numerical examples for the reliability design optimization (RDO) of a laminate and a composite cylindrical shell are worked out to demonstrate the effectiveness of the method. Then a design for composite pressure vessels is studied. The advantages and necessity of RDO over the conventional equi-strength design are addressed. Examples show that the proposed method has good stability and is efficient in dealing with the probabilistic optimal design of composite structures. It may serve as an effective tool to optimize other complicated structures with uncertainties.

Fuzzy Reliability Optimization Design of Tunnel Bottom Drum

Fuzzy Reliability Optimization Design of Tunnel Bottom Drum

Stability Analysis and Convergence Control of Iterative Algorithms for Reliability Analysis and Design Optimization

Iterative algorithms are widely applied in reliability analysis and design optimization. Nevertheless, phenomena of failed convergence, such as periodic oscillation, bifurcation, and chaos, are oftentimes observed in iterative procedures of solving some nonlinear problems. In the present paper, the essential causes of numerical instabilities including periodic oscillation and chaos of iterative solutions are revealed by the eigenvalue-based stability analysis of iterative schemes. To understand and control these instabilities, the stability transformation method (STM), which is capable of tackling numerical instabilities of iterative algorithms in reliability analysis and design optimization, is proposed. Finally, several benchmark examples of convergence control of PMA (performance measure approach) for probabilistic analysis and the SORA (sequential optimization and reliability assessment) for reliability-based design optimization (RBDO) are presented. The observations from the benchmark examples indicate that the STM is a promising approach to achieve convergence control for iterative algorithms in reliability analysis and design optimization.

Structural Reliability Sensitivities under Nonstationary Random Vibrations

Response sensitivity evaluation is an important element in reliability evaluation and design optimization of structural systems. It has been widely studied under static and dynamic forcing conditions with deterministic input data. In this paper, structural response and reliability sensitivities are determined by means of the time domain covariance analysis in both classically and nonclassically damped linear structural systems. A time integration scheme is proposed for covariance sensitivity. A modulated, filtered, white noise input process is adopted to model the stochastic nonstationary loads. The method allows for the evaluation of sensitivity statistics of different quantities of dynamic response with respect to structural parameters. Finally, numerical examples are presented regarding a multistorey shear frame building.

Feasibility and Optimal Reliable Design of Renewable Hybrid Energy System for Rural Electrification in Iran

A hybrid hydro/wind/photovoltaic base on hydrogen storage system is designed to supply power demand. The aim of the optimization problem is minimization of net present cost of the hybrid system to reliable supply of the demand. The system is investigated in the north west of Iran (Meshkinshahr) and the local data is applied. About 12 villages (corresponding to 680 people) are found in the upper Blue Qarahsou river gorge and far remote areas, which makes the task of their electrification via grid system very difficult. The hydro potentials are analyzed with the help of GIS data of Iran. Meteorological data from renewable energy organization (SUNA) of Iran and other sources, such as NASA, is used for the estimation of solar and wind energy potentials. In this paper, hydro/PV/wind/ fuel cell hybrid system is compared with above system without hydro unit. An advanced variation of genetic algorithm (GA) is proposed to solve the optimization problem. The developed algorithm is compared with HOMER software and the results show that GA accuracy is better than HOMER software. Result reveals the effects of components outages on the reliability and cost of the proposed hybrid system. Thus, they are directly dependent on component’s reliabilities, i.e. Outages result need for a larger generating system for supplying the load with the acceptable reliability. Different system types and their component sizes are identified having a cost of energy less than 0.3 $/KWh.

Evidence Theory and Differential Evolution for Uncertainty Quantification of Structures

Due to lack of knowledge or incomplete, inaccurate, unclear information in the modeling, simulation, measurement and reliability assessment and design optimization, there are limitations in using only one framework (probability theory) to quantify the uncertainty in a system because of the impreciseness of data or knowledge. In this paper, evidence theory is proposed as an alternative to the classical probability theory to handle the imprecise data situation. In order to alleviate the computational difficulties in the evidence theory based uncertainty quantification (UQ) analysis, a differential evolution based interval optimization for computing bounds method is developed. A typical truss structure with the aleatory and epistemic uncertainties is investigated to demonstrate accuracy and efficiency of the proposed method.

Reliability Design and Wear Extent Determination of a Cam Mechanism

The application of the cam mechanism is an important field in agricultural machinery since it can realize complex mechanical movement. The wear extent and action reliability of the cam affect the performance and accuracy of the mechanism. The paper combined reliability optimal design and tribology to build a fuzzy optimization model, with minimum of the cam base circle radius and minimum of the maximum contact stress as the objective functions. Compared with conventional optimization, the cam weight was reduced by 11.7%, the stress was increased by 1.96%, and the reliability increased 0.71%. Contrast tests were designed to determine the wear extent before and after optimization. The results prove the feasibility of optimization.

Reliability Optimization Design Based on the Blind Number Theory

The concept and operation rules of the blind number based on Unascertained Theory are introduced. This case study demonstrates the advantage of unascertained theory described in reliability optimization, and a stress-strength reliability optimization design model is built up at same time. In addition, the corresponding practical optimization calculating program is given. Test on the validity and practicability of this model is also verified by comparing the result of reliability gained from this model with that obtained from the traditional reliability-design method.

Study on Reliability-Based Optimal Design of Multi-Stage Planetary Gear Train in Wind Power Yaw Reducer

Based on reliability optimization design theory and sub step optimization method, the mathematical models of transmission ratio distribution and gears’ parameters are established, respectively. In the model, the normal module, pressure angle, the teeth width, teeth number and modification coefficient of the gears are taken as design variables, while the volumes of the yaw reducer and single stage transmission are taken as the objective functions. Then the complex optimal problems are solved using two heuristic optimization algorithms. Compared to the original design, the volume of the yaw reducer decreased by about 3.5% under the premise of maintaining the strength requirements and ensuring high reliability, which supplies an effective approach to further developing the reliability optimization design of multi-stage planetary gear systems.

Optimal reliable design and operation of water distribution systems through decomposition

Reliability in general, and in water distribution systems in particular, is a measure of probabilistic performance. A system is said to be reliable if it functions properly for a given time interval and within boundary conditions. Although water distribution system reliability has attracted considerable research attention over the last three decades, there is still no consensus on what reliability measures or evaluation methodologies should be used for the design/operation of water distribution systems. No system is perfectly reliable. In every system undesirable events—failures—can cause a decline or interruption in system performance. Failures are of a stochastic nature and are the result of unpredictable events that occur in the system itself and/or in its environs. A least cost design problem with normal design loadings will result in the cheapest system, but this system will have minimum residual capacity. However, if an increased loading (i.e., higher than the normal design) is implemented, the system's capacity will be increased, thus improving its residual capacity. Finding this “virtual increased loading,” which results in a minimum cost residual system capacity that sustains a required reliability level, is the essence of the proposed methodology, which follows decomposition. The methodology is demonstrated on two example applications of increasing complexity. The main limitation of the suggested method for further extensions to real sized water distribution systems is the computational effort associated with the computation of the “inner” problem. Exploring the required computational burden divided between the “outer” and “inner” problems is a major challenge for future elaborations of this approach.

SO-MI: A surrogate model algorithm for computationally expensive nonlinear mixed-integer black-box global optimization problems

This paper introduces a surrogate model based algorithm for computationally expensive mixed-integer black-box global optimization problems with both binary and non-binary integer variables that may have computationally expensive constraints. The goal is to find accurate solutions with relatively few function evaluations. A radial basis function surrogate model (response surface) is used to select candidates for integer and continuous decision variable points at which the computationally expensive objective and constraint functions are to be evaluated. In every iteration multiple new points are selected based on different methods, and the function evaluations are done in parallel. The algorithm converges to the global optimum almost surely. The performance of this new algorithm, SO-MI, is compared to a branch and bound algorithm for nonlinear problems, a genetic algorithm, and the NOMAD (Nonsmooth Optimization by Mesh Adaptive Direct Search) algorithm for mixed-integer problems on 16 test problems from the literature (constrained, unconstrained, unimodal and multimodal problems), as well as on two application problems arising from structural optimization, and three application problems from optimal reliability design. The numerical experiments show that SO-MI reaches significantly better results than the other algorithms when the number of function evaluations is very restricted (200–300 evaluations).

Reliability Optimum Design of Spring in the Tools Storage

According to the spring’s failures in the tools storage and mechnical tools locking, the thesis will discuss the reliability optimization design for spring. With the known probability characteristics of basic random parameters, the random perturbation method, the reliability theory and optimal design technology are used to give the spring reliability design problems in locking knife spring in the tools storage and mechanical tools of machining center, to put forward the practical and effective reliability-based optimization design method, which can shorten the design cycle, save the testing cost, improve the design level and the reliability of parts. DOI: http://dx.doi.org/10.11591/telkomnika.v10i5.1276

Reliability Optimization Design for Mechanical Components

The traditional reliability model of mechanical components can not well reflect the effect of strength degradation on reliability。In the paper, A new method is applied to develop a dynamic reliability model of mechanical components considering the strength deterioration with time passing。The calculated result s by a real example show that could not only calculate the failure probability of the response, but also could make the process of optimization of the response under the conditions of meeting reliability restraint.

Comparison study between probabilistic and possibilistic methods for problems under a lack of correlated input statistical information

In most industrial applications, only limited statistical information is available to describe the input uncertainty model due to expensive experimental testing costs. It would be unreliable to use the estimated input uncertainty model obtained from insufficient data for the design optimization. Furthermore, when input variables are correlated, we would obtain non-optimum design if we assume that they are independent. In this paper, two methods for problems with a lack of input statistical information--possibility-based design optimization (PBDO) and reliability-based design optimization (RBDO) with confidence level on the input model--are compared using mathematical examples and an Abrams M1A1 tank roadarm example. The comparison study shows that PBDO could provide an unreliable optimum design when the number of samples is very small. In addition, PBDO provides an optimum design that is too conservative when the number of samples is relatively large. Furthermore, the obtained PBDO designs do not converge to the optimum design obtained using the true input distribution as the number of samples increases. On the other hand, RBDO with confidence level on the input model provides a conservative and reliable optimum design in a stable manner. The obtained RBDO designs converge to the optimum design obtained using the true input distribution as the number of samples increases.

TSV Stress-Aware Full-Chip Mechanical Reliability Analysis and Optimization for 3-D IC

In this paper, we propose an efficient and accurate full-chip thermomechanical stress and reliability analysis tool and design optimization methodology to alleviate mechanical reliability issues in 3-D integrated circuits (ICs). First, we analyze detailed thermomechanical stress induced by through-silicon vias in conjunction with various associated structures such as landing pad and dielectric liner. Then, we explore and validate the linear superposition principle of stress tensors and demonstrate the accuracy of this method against detailed finite element analysis simulations. Next, we apply this linear superposition method to full-chip stress simulation and a reliability metric named the von Mises yield criterion. Finally, we propose a design optimization methodology to mitigate the mechanical reliability problems in 3-D ICs. Our numerical experimental results demonstrate the effectiveness of the proposed methodology.

Reliability Optimization Design of Spacecraft Valve Spring

Firstly, methodology of valve spring’s static strength and fatigue strength reliability analysis is built up, and detailed computational formulas to derive distributions of the stress and strength are described. Secondly, to make full use of the material characteristic and consider reliability of the mechanism part, taking the spring’s mass as the objective function and based on spring’s traditional and reliability constraints, mathematic model of reliability optimization design of valve spring is established using mechanical reliability design method and mechanical optimization design method. At last, the proposed method is applied to a practical spring design example by integrating optimization tools with the optimization model. The comparison of reliability optimization design results and traditional optimization design results shows that the reliability optimization method is practical and reliable; its design results can satisfy all design requirements with smaller mass.

Finite Element Analysis of the Static/Dynamic Behavior of Wind Turbine Gearbox

Gearbox is a key part and is more easily over loaded and it has a high failure rate in MW-class wind turbine. It is necessary to analyze, predict and optimize its static/dynamical behavior. It presents the performance of one type wind turbine gearbox and the static analysis results of the housing, spline and gear pairs of the wind turbine gearbox are obtained using finite element method. The natural frequency and modal shape of the gearbox are analyzed. The modification data of the flank shape for each class tooth alignment and tooth profiles are obtained from the analysis. The related data on the strength and stiffness of all the parts in wind turbine gearbox are provided. It lays a foundation for the reliability assessment and optimization design of wind turbine gearbox.

Applied Research on Optimum Design of Planetary Reducer

Reliability optimum design of the mechanical system is studied thoroughly based on the existing research results. Taking the 2K-H planetary reducer of PCP system as the physical mode, the main target of optimization is module, breadth of tooth and number of teeth. The objective function for obtaining a smaller gearbox volume is set up and the requirement of reliability is taken into account. The optimum solution is obtained by the complex method. The result is in conformity with the requirement and it indicates that the synthesis effect is satisfied. The reduction of volume is beneficial to improve PCP system performance.

Reliability design optimization for aerospace product an integrated approach

The need for continuous improvement in engineering designs of aerospace and automotive products exist in order to optimize cost, weight, volume etc. Due to the inherent uncertainties such as external loading, material properties and manufacturing quality, the prototypes of manufactured product may not satisfy all the requirements. Deterministic approaches cannot take into account all the variabilities that characterize design input properties leading to oversized or undersized structure. The present paper deals with response surface methodology where the performance functions are generated using design of experiments. These simplified linear performance functions are used for design optimization. Further, an outline of the methodology is discussed that could serve as a guideline to develop a more efficient and optimized design process. Here, the product optimization is carried out in stages starting from deterministic optimization, followed by reliability based design optimization using reliability index approach and performance measure approach to meet target reliability requirements.

Reliability Optimization Design of Mechanical Parts Based on Global Optimization

Generally, action of constraints exists in reliability optimization design of mechanical parts. Usually, general optimum methods are adopted in reliability optimization design, so the local solution is obtained. Aimed at this situation, a global optimum method was introduced by Lingo13.0 software. The result shows the model is practical and effective and its solution is global solution better than the result with general optimum method. As the method is simple, it is worthy to spread in optimum design