Earticle

This study shows a variance regularization method in order to obtain the stable optimal solutions, when a numerical method accelerating design variables is used for material topology optimization algorithm. Since a moved and regularized Heaviside function used in the accelerated method is composed of nonlinear concave and convex functions in a given design domain between 0 and 1, design variables below 0.5 can move fast toward the value of 0 and those over 0.5 are rapidly located to the value of 1. However optimal solutions may be not stable due to singularity of element stiffness, while the accelerated design variables are too closed to value 0. In particular this instability may occur to the accelerated method-based material topology optimization algorithms much repeating the moved and regularized Heaviside function. In order to resolve the problem, in this study, a variance regularization is formulated within a linear governing equation for structural analyses of optimization procedures. Numerical examples for topologically optimally modeling a linear elastostatic MBB-beam verify that the accelerated method of design variables take numerical stability of topological optimal solutions by being associated with the variance regularization method.

This paper considers a condition-based maintenance (i.e. CBM) model for the hydro generating unit in the deregulated power system. As the generating loss varies according to the time-varying inflows, the economic dependence among the critical component of the generating unit is dynamic. To reduce the maintenance cost effectively, we propose an inflow-dependent control-limit policy instead of the constant control-limit policy for CBM optimization. An example for the hydro generating unit is presented to verify the effectiveness of the proposed policy.

This paper considers a condition-based maintenance (i.e. CBM) model for the hydro generating unit in the deregulated power system. As the downtime cost of the generating unit varies according to the time-varying electricity price, the economic dependence among the critical component of the generating unit is dynamic. In this paper, the proposed Dynamic-Economic-Dependence and proportional hazards model based CBM policy considers the dynamic economic dependence among components as well as the reliability and the monitoring information of different critical components. An example for the hydro generating unit is presented to verify the effectiveness of the proposed condition based maintenance policy.

This paper presents a novel approach for dynamic economic dispatch in a MicroGrid by using the improved ant colony optimization (ACO). In order to satisfy the power balance and load demand, the mathematical model of economic dispatch is given to support the MicroGrid in both grid-connected and islanded mode. By means of ACO, the dynamic economic dispatch solution is proposed in combination with sequential quadratic programming (SQP), and the essential procedure is introduced. Simulation results demonstrate the feasibility and benefits of the proposed scheme.

Lactic acid is an important chemical that can be used to synthesize biodegradable polymers, such as polylactic acid (PLA) and its copolymers. Precipitation was employed to recover lactic acid from a calcium lactate solution using sulfuric acid. In this study, we optimized process parameters of precipitation to obtain a high yield and purity of lactic acid from a calcium lactate solution. Also, we observed the influence of the main process parameters on precipitate formation during the course of precipitation using a video microscope. The optimal calcium lactate/sulfuric acid molar ratio and pH were 1/1 and 6.8, respectively. Also, the effect of mixing method on the efficiency of precipitation and the formation of precipitate were evaluated. When the sample was mixed continuously after adding sulfuric acid, lactic acid was obtained in high yield. By mixing the sample, we were able to significantly reduce the precipitation time, the length of which has been a problem inherent in the conventional precipitation process. The yield of recovered lactic acid was 92% with a purity of 71%.

In this paper, we consider a convex optimization problem with a convex integrable objective function and a geometric constraint set. We characterize the solution set of the problem when we know its one solution.

The majority of real-world problems encountered by engineers involve simultaneous optimization of competing objectives. In this case instead of single optima, there is a set of alternative trade-offs, generally known as Pareto-optimal solutions. The use of evolutionary algorithms Pareto GA, which was first introduced by Goldberg in 1989, has now become a sort of standard in solving Multiobjective Optimization Problems (MOPs). Though this approach was further developed leading to numerous applications, these applications are based on Pareto ranking and employ the use of the fitness sharing function to maintain diversity. Another scheme for solving MOPs has been presented by J. Nash to solve MOPs originated from Game Theory and Economics. Sefrioui introduced the Nash Genetic Algorithm in 1998. This approach combines genetic algorithms with Nash's idea. Another central achievement of Game Theory is the introduction of an Evolutionary Stable Strategy, introduced by Maynard Smith in 1982. In this paper, we will try to find ESS as a solution of MOPs using our game model based co-evolutionary algorithm. First, we will investigate the validity of our co-evolutionary approach to solve MOPs. That is, we will demonstrate how the evolutionary game can be embodied using co-evolutionary algorithms and also confirm whether it can reach the optimal equilibrium point of a MOP. Second, we will evaluate the effectiveness of our approach, comparing it with other methods through rigorous experiments on several MOPs.

Boundedness for the set of all the $\epsilon$-approximate solutions for convex optimization problems are considered. We give necessary and sufficient conditions for the sets of all the $\epsilon$-approximate solutions of a convex optimization problem involving finitely many convex functions and a convex semidefinite problem involving a linear matrix inequality to be bounded. Furthermore, we give examples illustrating our results for the boundedness.

In this paper, we propose a design method for GBSB (generalized brain-state-in-a-box) based associative memories. Based on the theoretical investigation about the properties of GBSB, we parameterize the solution space utilizing the limited number of parameters sufficient to represent the solution space and appropriate to be searched. Next we formulate the problem of finding a GBSB that can store the given pattern as stable states in the form of constrained optimization problems. Finally, we transform the constrained optimization problem into a SDP(semidefinite program), which can be solved by recently developed interior point methods. The applicability of the proposed method is illustrated via design examples.

In this paper we study the problem of three-dimensional layout optimization on the simplified rotating vessel of satellite. The layout optimization model with behavioral constraints is established and some effective and convenient conditions of performance optimization are presented. Moreover, we prove that the performance objective function is locally Lipschitz continuous and the results on the relations between the local optimal solution and the global optimal solution are derived.

In this paper, a procedure is developed for identifying a number of representative solutions manageable for decision-making in a multiobjective optimization problem concerning the test intervals of the components of a safety system of a nuclear power plant. Pareto Front solutions are identified by a genetic algorithm and then clustered by subtractive clustering into "families". On the basis of the decision maker's preferences, each family is then synthetically represented by a "head of the family" solution. This is done by introducing a scoring system that ranks the solutions with respect to the different objectives: a fuzzy preference assignment is employed to this purpose. Level Diagrams are then used to represent, analyze and interpret the Pareto Fronts reduced to the head-of-the-family solutions.

In this paper, we introduce a hybrid iterative method for finding a common element of the set of solutions of a mixed equilibrium problem, the set of common mixed points of finitely many nonexpansive mappings and the set of solutions of the variational inequality for an inverse strongly monotone mapping in a Hilbert space. We show that the iterative sequences converge strongly to a common element of the three sets. The results extended and improved the corresponding results of L.-C.Ceng and J.-C.Yao.

Urokinase is an enzyme with fibrinolytic activity (plasminogen activator) isolated from fresh urine of healthy men. Viral safety is an important prerequisite for clinical preparation of the protein from urine. In order to increase the viral safety of a high purity urokinase in regard to non-enveloped viruses, a virus removal process using a novel polyvinylidene fluoride membrane filter (Viresolve NFP) has been optimized. Urokinase was able to pass through the filter with recoveries of 95% in the production scale process. No substantial changes were observed in physical and biochemical characteristics of the filtered urokinase in comparison with those of the enzyme before filtration. A 47-mm disk membrane filter was used to simulate the process performance of the production scale cartridges and tested if it could remove several experimental model viruses for human pathogenic viruses, including porcine parvovirus (PPV), human hepatitis A virus (HAV), murine encephalomyocarditis virus (EMCV), bovine viral diarrhoea virus (BVDV), and bovine herpes virus (BHV). Non-enveloped viruses (PPV, HAV, and EMCV) as well as enveloped viruses (BVDV and BHV) were completely removed during filtration. The log reduction factors achieved were $\geq$4.86 for PPV, $\geq$4.60 for HAV, $\geq$6.87 for EMCV, $\geq$4.60 for BVDV, and $\geq$5.44 for BHV. These results indicate that the virus filtration process successfully improved the viral safety of the final products.

Since many infinite horizon problems have infinite sequence of data to be considered, in general, it is impossible to express the optimal strategies finitely or to calculate them in finite time. This paper considers undiscounted nonhomogeneous deterministic infinite horizon problems. For those problems, we take a basic step to solve this class of infinite horizon problems optimally by giving a sufficient condition for a finite solution.

본 논문은 정밀 유도무기에 장착되어 목표물 명중 확률을 좌우하고, 비용적인 측면에서 유도무기의 가장 큰 부분을 차지하는 적외선 영상탐색기에 대한 성능 대비 개발비용 최적화에 대한 연구이다. 탐색기 개발 비용의 주요항목인 해상도와 그에 따른 탐지성능에 영향을 미치는 인자들을 분석함으로써, 설계 단계에서 해상도 별 탐지성능과 개발 비용과의 상관관계를 분석하는 연구를 수행하였다. 다양한 신호 대 클러터 비 조건에서 해상도 별 표적탐지 확률을 설계 시 중요인자로 정의하고, 개발비용 선정의 기준이 되는 해상도 별 탐지성능 분석을 수행하였으며, 탐지성능 확보를 위한 최적의 해상도와 그에 따른 투입비용에 대한 관계를 도출하였다. 다양한 클러터 환경에 따른 사례연구를 통하여 제안한 분석 방식이 탐지성능 만족을 위하여 요구되는 개발비용 예측에 효과적임을 검증하였으며, 유도무기 운용 환경에서 성능대비 최적화된 개발비용을 설계단계에서 미리 도출할 수 있는 연구 자료로 활용하고자 한다.

An Image Infra-Red(IIR) seeker is widely used for precision guided munitions to provide intelligent and precise target detection in terms of high kill probability. However, there have been issues in determining the performance versus cost trade-offs due to high cost of seeker comparing to other units of the munitions. In this paper, performance/cost evaluations have been carried out to find the most cost-effective solution for developing the IIR seekers. The relationships between the critical parameters and cost are investigated to determine the optimal point which represents the low cost with high performance. It is expected that the presented approach will be able to be used for guidelines to select the appropriate IIR seeker for the given operating conditions and can be useful to estimate the cost effectiveness of the precision guided munitions at early design stage.

본 연구는 SiC 용액 성장에서 Cr 40 %가 첨가된 Si melt 내부의 용액과 탄소흐름의 변화를 수치적으로 분석하여 장시간 성장과 고품질의 SiC 단결정을 얻기 위한 최적공정 조건의 설계를 목적으로 진행하였다. 수치 시뮬레이션으로는 crystal growth simulator ($CGSim^{TM}$, STR Group Ltd.)가 사용되었다. 결과적으로, 성장온도, 종자정축과 도가니축의 회전속도 및 성장 시 종자정의 위치에 따라 melt내부의 용액 흐름과 탄소흐름의 속도 및 방향이 변화함으로써 더 균일한 온도구배를 형성하여 안정적인 성장이 이루어지는 조건을 확인하였다. 그러므로, 성장조건들을 조절함으로써 시뮬레이션 상에서 실험조건의 최적화가 가능하였고 향후 실제 실험에서도 많은 도움이 될 것으로 예상된다.

In this study, numerical simulation was performed to focus on optimized process condition for obtaining a long-term growth and high quality SiC crystal. It could be optimized by considering the change of fluid and a carbon flow in the Si melt added with 40 % Cr. The Crystal Growth Simulator ($CGSim^{TM}$, STR Group Ltd.) was used as a numerical simulation. It was confirmed that many parameters such as temperature, rotation speed of seed crystal and crucible, and seed position during the crystal growth step had a strong influence on the speed and direction of solution flow for uniform temperature gradient and stable crystal growth. The optimized process condition for the solution growth of SiC crystal was successfully exhibited by adjusting various process parameters in the numerical simulation, which would be helpful for real crystal growth.

Reliability has been considered as an important design measure in various industrial systems. We discuss a reliability optimization problem with component choices (ROP-CC) subject to a budget constraint. This problem has been known as a NP-hard problem in the reliability design fields. Several researchers have been working to find the optimal solution through different heuristic methods. In this paper, we describe our development of simulated annealing (SA) and tabu search (TS) algorithms and a reoptimization procedure of the two algorithms for solving the problem. Experimental results for some examples are shown to evaluate the performance of these methods. We compare the results with the solutions of a previous study which used ant system (AS) and the global optimal solution of each example obtained through an optimization package, CPLEX 9.1. The computational results indicate that the developed algorithms outperform the previous results.

This study aims to optimize the DL-EPR test solution for duplex stainless steel S31083 using the Taguchi design. The test solution parameters applied to the Taguchi design are H₂SO₄, NaCl, KSCN concentration, and temperature. In the experimental design, an orthogonal array of 4 levels 4 factor L₁₆(4⁴) was used. Output values for the orthogonal array were used for resolution (degree of sensitization) and selective etch (I_a) values. The optimal test solution conditions were selected by comparing the normalized S/N ratio for the two reaction properties. As a result, the H₂SO₄ and NaCl were identified as the main factors influencing the sensitivity measurement, but the delta statistics showed that the KSCN concentration and temperature had relatively low influence. The optimal condition was identified as 1.5 M H₂SO₄+0.03 M KSCN+1.5M NaCl at 30 ℃. The degree of sensitization presented a tendency to depend on the heat treatment temperature and time in the optimal test solution. This investigation confirmed the possibility of optimizing the experiment solution for the DL-EPR test of stainless steel using the Taguchi technique.