• Journal of Electrical Engineering and Technology
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• v.13 no.2
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• pp.704-710
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• 2018

For the optimal design of electromagnetic device involving uncertainties in design variables, this paper proposes a new reliability-based optimal design algorithm for multiple constraints problems. Through optimizing the nominal objective function and maximizing the minimum reliability, a set of global optimal reliable solutions representing different reliability levels are obtained by the multi-objective particle swarm optimization algorithm. Applying the sensitivity-assisted Monte Carlo simulation method, the numerical efficiency of optimization procedure is guaranteed. The proposed reliability-based algorithm supplying multi-reliable solutions is investigated through applications to analytic examples and the optimal design of two electromagnetic problems.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 1993.04a
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• pp.135-140
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• 1993

The optimum weight design of structure is to determine the combination of structural members which minimize the weight of structures and satisfy design conditions as well. Since most of loads and design variables considered in structural design have uncertain natures, the reliability-based optimization techniques need to be developed. The aim of this study is to estabilish the general algorithm for the minimum weight design of transmission tower structure system with reliability constraints. The sequential linear programming method is used to solve non-linear minimization problems, which converts original non-linear programming problems to sequential linear programming problems. The optimal solutions are produced for various reliability levels such as reliability levels inherent in current standard transmission tower cross-section and optimal transmission tower cross-section obtained with constraints of current design criteria as well as selected target reliability index. The optimal transmission towers satisfying reliability constraints sustain consistent reliability levels on all members. Consequently, more balanced optimum designs are accomplished with less structural weight than traditional designs dealing with deterministic design criteria.

• Journal of Magnetics
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• v.19 no.3
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• pp.266-272
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• 2014

In this paper, we suggest reliability as a metric to evaluate the robustness of a design for the optimal design of electromagnetic devices, with respect to constraints under the uncertainties in design variables. For fast numerical efficiency, we applied the sensitivity-assisted Monte Carlo simulation (S-MCS) method to perform reliability calculation. Furthermore, we incorporated the S-MCS with single-objective and multi-objective particle swarm optimization algorithms to achieve reliability-based optimal designs, undertaking probabilistic constraint and multi-objective optimization approaches, respectively. We validated the performance of the developed optimization algorithms through application to the optimal design of a superconducting magnetic energy storage system.

• Journal of the Korea Institute of Military Science and Technology
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• v.15 no.1
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• pp.93-100
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• 2012

In this paper, the deterministic optimal design for the tail plane made of composite materials is conducted under the deterministic loading condition and compared with that of the metallic materials. Next, the reliability analysis with five random variables such as loading and material properties of unidirectional prepreg is conducted to examine the probability of failure for the deterministic optimal design results. The MATLAB programing is used for reliability analysis combined with FEA S/W(COMSOL) for structural analysis. The laminated composite is assumed to the equivalent orthotropic material using classical laminated plate theory. The response surface methodology and importance sampling technique are adopted to reduce computational cost with satisfying the accuracy in reliability analysis. As a result, structural weight of composite materials is lighter than that of metals in deterministic optimal design. However, the probability of failure for the deterministic optimal design of the tail plane structures is too high to be neglected. The sensitivity of each variable is also estimated using probabilistic sensitivity analysis to figure out which variables are sensitive to failure. The computational cost is considerably reduced when response surface methodology and importance sampling technique are used. The study of the computationally inexpensive method for reliability-based design optimization will be necessary in further work.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.12
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• pp.3071-3095
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• 2013

Configuring optimization of wireless sensor networks, which can improve the network performance such as utilization efficiency and network lifetime with minimal energy, has received considerable attention in recent years. In this paper, a cross layer optimal approach is proposed for multi-source linear network and grid network under Rayleigh block-fading channels, which not only achieves an optimal utility but also guarantees the end-to-end reliability. Specifically, in this paper, we first strictly present the optimization method for optimal nodal number $N^*$, nodal placement $d^*$ and nodal transmission structure $p^*$ under constraints of minimum total energy consumption and minimum unit data transmitting energy consumption. Then, based on the facts that nodal energy consumption is higher for those nodes near the sink and those nodes far from the sink may have remaining energy, a cross layer optimal design is proposed to achieve balanced network energy consumption. The design adopts lower reliability requirement and shorter transmission distance for nodes near the sink, and adopts higher reliability requirement and farther transmission distance for nodes far from the sink, the solvability conditions is given as well. In the end, both the theoretical analysis and experimental results for performance evaluation show that the optimal design indeed can improve the network lifetime by 20-50%, network utility by 20% and guarantee desire level of reliability.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2002.05a
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• pp.672-676
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• 2002

In this paper, a reliability-based design optimization method, which enables the determination of optimum design that incorporate confidence range for structures, is studied. Response surface method and Monte Carlo simulation are utilized to determine limit state function. The proposed method is applied to the I-type steel structure for reliability based optimal design.

• Journal of Electrical Engineering and Technology
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• v.8 no.2
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• pp.331-338
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• 2013

A new reliability calculation method is proposed based on design sensitivity analysis by the finite element method for nonlinear performance constraints in the optimal design of electromagnetic devices. In the proposed method, the reliability of a given design is calculated by using the Monte Carlo simulation (MCS) method after approximating a constraint function to a linear one in the confidence interval with the help of its sensitivity information. The validity and numerical efficiency of the proposed sensitivity-assisted MCS method are investigated by comparing its numerical results with those obtained by using the conventional MCS method and the first-order reliability method for analytic functions and the TEAM Workshop Problem 22.

• Structural Engineering and Mechanics
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• v.85 no.3
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• pp.369-379
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• 2023

Reliability-Based Design Optimization (RBDO) is an appropriate framework for obtaining optimal designs by taking uncertainties into account. Large-scale problems with implicit limit state functions and problems with discrete design variables are two significant challenges to traditional RBDO methods. To overcome these challenges, this paper proposes a hybrid method to perform RBDO of structures that links Firefly Algorithm (FA) as an optimization tool to advanced (finite element) reliability methods. Furthermore, the Genetic Algorithm (GA) and the FA are compared based on the design cost (objective function) they achieve. In the proposed method, Weighted Simulation Method (WSM) is utilized to assess reliability constraints in the RBDO problems with explicit limit state functions. WSM is selected to reduce computational costs. To performing RBDO of structures with finite element modeling and implicit limit state functions, a First-Order Reliability Method (FORM) based on the Direct Differentiation Method (DDM) is utilized. Four numerical examples are considered to assess the effectiveness of the proposed method. The findings illustrate that the proposed RBDO method is applicable and efficient for RBDO problems with discrete and continuous design variables and finite element modeling.

• International Journal of Concrete Structures and Materials
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• v.3 no.2
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• pp.103-110
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• 2009

Concrete carbonation is a cause of problems in concrete structures, so it needs to be estimated. And concrete cover is designed to protect structures from this damaging. Usually the cover thickness is considered based on the limit states design codes in which the important target is the reliability safety index. However, it is not clear that whether the safety index determined is optimal or not with respect to the cost. The codes are mainly proceeded quantitatively (i.e. making a safe structure) while the economic aspects are only considered qualitatively. So the reliability-based design considering life cycle cost (LCC) is called for, and here the focus is on the advanced analysis solution to optimize the reliability safety regarding LCC.

• International Journal of Automotive Technology
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• v.8 no.1
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• pp.93-102
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• 2007

The frontal crash optimization of an engine room member using the response surface method was studied. The engine room member is composed of the front side member and the sub-frame. The thicknesses of the panels on the front side member and the sub-frame were selected as the design variables. The purpose of the optimization was to reduce the weight of the structure, under the constraint that the objective quantity of crash energy is absorbed. The response surface method was used to approximate the crash behavior in mathematical form for optimization procedure. To research the effect of the regression method, two different methodologies were used in constructing the response surface model, the least square method and the moving least square method. The optimum with the two methods was verified by the simulation result. The precision of the surrogate model affected the optimal design. The moving least square method showed better approximation than the least square method. In addition to the deterministic optimization, the reliability-based design optimization using the response surface method was executed to examine the effect of uncertainties in design variables. The requirement for reliability made the optimal structure be heavier than the result of the deterministic optimization. Compared with the deterministic optimum, the optimal design using the reliability-based design optimization showed higher crash energy absorption and little probability of failure in achieving the objective.