• Smart Structures and Systems
• /
• v.21 no.2
• /
• pp.235-248
• /
• 2018

An efficient method utilizing the multi-stage improved differential evolution algorithm (MSIDEA) as an optimization solver is presented here to detect the multiple-damage of structural systems. Natural frequency changes of a structure are considered as a criterion for damage occurrence. The structural damage detection problem is first transmuted into a standard optimization problem dealing with continuous variables, and then the MSIDEA is utilized to solve the optimization problem for finding the site and severity of structural damage. In order to assess the performance of the proposed method for damage identification, an experimental study and two numerical examples with considering measurement noise are considered. All the results demonstrate the effectiveness of the proposed method for accurately determining the site and severity of multiple-damage. Also, the performance of the MSIDEA for damage detection compared to the standard differential evolution algorithm (DEA) is confirmed by test examples.

• International Journal of Fluid Machinery and Systems
• /
• v.9 no.1
• /
• pp.95-106
• /
• 2016

A method of optimization design for the blade profile of a centrifugal impeller by controlling velocity distribution is presented, and a plenum fan is successfully designed. This method is based on the inner flow calculation inside the centrifugal impeller, and is related to the distribution of relative velocity. The results show that after optimization, the boundary layer separation on the suction surface has been inhibited and the stability of plenum fan is improved. The flow at the impeller outlet is also studied, and the jet-wake pattern at the impeller outlet is improved obviously by optimization. The calculation result shows that the static pressure and static pressure efficiency can be increased by 15.4% and 21.4% respectively.

• Journal of Electrical Engineering and Technology
• /
• v.9 no.4
• /
• pp.1315-1323
• /
• 2014

Although the power density in Double Stator Switched Reluctance Motor (DSSRM) has been improved, the torque ripple is still very high. So, it is important to reduce the torque ripple for specific applications such as Electric Vehicles (EVs). In This paper, an effective rotor shaping optimization technique for torque ripple reduction of DSSRM is presented. This method leads to the lower torque pulsation without significant reduction in the average torque. The method is based on shape optimization of the rotor using Finite Element Method and Taguchi's optimization method for rotor reshaping for redistribution of the flux so that the phase inductance profile has smoother variation as the rotor poles move into alignment with excited stator poles. To check on new design robustness, mechanical analysis was used to evaluate structural conformity against local electromagnetic forces which cause vibration and deformation. The results show that this shape optimization technique has profound effect on the torque ripple reduction.

• Proceedings of the KIEE Conference
• /
• summer
• /
• pp.944-946
• /
• 2004

In this paper, a new technique for electromagnetic topology optimization is proposed. The proposed technique is based on the large-step Markov chain (LSMC) method with novel local optimization algorithm. Because the proposed algorithm keeps a good convergence characteristic of LSMC, fast convergence is assured. The proposed LSMC is verified by an application to an inverse reconstruction problem.

• Journal of Information Processing Systems
• /
• v.16 no.1
• /
• pp.210-223
• /
• 2020

Since constrained optimization algorithms are easy to fall into local optimum and their ability of searching are weak, an improved symbiotic organisms search algorithm with mixed strategy based on adaptive ε constrained (ε_SOSMS) is proposed in this paper. Firstly, an adaptive ε constrained method is presented to balance the relationship between the constrained violation degrees and fitness. Secondly, the evolutionary strategies of symbiotic organisms search algorithm are improved as follows. Selecting different best individuals according to the proportion of feasible individuals and infeasible individuals to make evolutionary strategy more suitable for solving constrained optimization problems, and the individual comparison criteria is replaced with population selection strategy, which can better enhance the diversity of population. Finally, numerical experiments on 13 benchmark functions show that not only is ε_SOSMS able to converge to the global optimal solution, but also it has better robustness.

• Journal of Electrical Engineering and Technology
• /
• v.9 no.2
• /
• pp.471-477
• /
• 2014

The novel permanent magnetic actuator (PMA) and its optimal design method were proposed in this paper. The proposed PMA is referred to as the separated permanent magnetic actuator (SPMA) and significantly superior in terms of its cost and performance level over a conventional PMA. The proposed optimal design method uses the evolutionary strategy algorithm (ESA), the kriging meta-model (KMM), and the multi-step optimization. The KMM can compensate the slow convergence of the ESA. The proposed multi-step optimization process, which separates the independent variables, can decrease time and increase the reliability for the optimal design result. Briefly, the optimization time and the poor reliability of the optimum are mitigated by the proposed optimization method.

• Nuclear Engineering and Technology
• /
• v.48 no.6
• /
• pp.1315-1320
• /
• 2016

The present study aims to predict the heat transfer characteristics around a square cylinder with different corner radii using multivariate adaptive regression splines (MARS). Further, the MARS-generated objective function is optimized by particle swarm optimization. The data for the prediction are taken from the recently published article by the present authors [P. Dey, A. Sarkar, A.K. Das, Development of GEP and ANN model to predict the unsteady forced convection over a cylinder, Neural Comput. Appl. (2015) 1-13]. Further, the MARS model is compared with artificial neural network and gene expression programming. It has been found that the MARS model is very efficient in predicting the heat transfer characteristics. It has also been found that MARS is more efficient than artificial neural network and gene expression programming in predicting the forced convection data, and also particle swarm optimization can efficiently optimize the heat transfer rate.

• Journal of Mechanical Science and Technology
• /
• v.20 no.6
• /
• pp.731-737
• /
• 2006

Interactive Fuzzy Physical Programming (IFPP) developed in this paper is a new efficient multi-objective optimization method, which retains the advantages of physical programming while considering the fuzziness of the designer's preferences. The fuzzy preference function is introduced based on the model of linear physical programming, which is used to guide the search for improved solutions by interactive decision analysis. The example of multi-objective optimization design of the spindle of internal grinder demonstrates that the improved preference conforms to the subjective desires of the designer.

• Proceedings of the Korean Society of Precision Engineering Conference
• /
• 2005.10a
• /
• pp.464-469
• /
• 2005

Optimum sensitivity analysis (OSA) is the process to find the sensitivity of optimum solution with respect to the parameter in the optimization problem. The prevalent OSA methods calculate the optimum sensitivity as a post-processing. In this research, a simple technique is proposed to obtain optimum sensitivity as a result of the original optimization problem, provided that the optimum sensitivity of objective function is required. The parameters are considered as additional design variables in the original optimization problem. And then, it is endowed with equality constraints to penalize the additional variables. When the optimization problem is solved, the optimum sensitivity of objective function is simultaneously obtained as Lagrange multiplier. Several mathematical and engineering examples are solved to show the applicability and efficiency of the method compared to other OSA ones.

• Structural Engineering and Mechanics
• /
• v.55 no.6
• /
• pp.1157-1176
• /
• 2015

This study presents optimizing structural topology patterns using regularization of Heaviside function. The present method needs not filtering process to typical SIMP method. Using the penalty formulation of the SIMP approach, a topology optimization problem is formulated in co-operation, i.e., couple-signals, with design variable values of discrete elements and a regularized Heaviside step function. The regularization of discontinuous material distributions is a key scheme in order to improve the numerical problems of material topology optimization with 0 (void)-1 (solid) solutions. The weak forms of an equilibrium equation are expressed using a coupled regularized Heaviside function to evaluate sensitivity analysis. Numerical results show that the incorporation of the regularized Heaviside function and the SIMP leads to convergent solutions. This method is tested using several examples of a linear elastostatic structure. It demonstrates that improved optimal solutions can be obtained without the additional use of sensitivity filtering to improve the discontinuous 0-1 solutions, which have generally been used in material topology optimization problems.