• Nuclear Engineering and Technology
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• v.56 no.8
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• pp.3425-3434
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• 2024

The main features of the loading pattern optimization (LPO) problem, such as high-dimensionality, multi-modality, and non-linearity, make it difficult to achieve a truly optimal configuration. In recent years, metaheuristic methods have been successfully used to solve this problem. In this research, a discrete golden eagle optimization (DGEO) algorithm has been developed to solve the LPO problem in the first cycle of VVER-1000 reactor core. To evaluate the proposed algorithm, a linear multi-purpose fitness function has been used to improve the safety parameters of the reactor core by obtaining a flatter power distribution during the first cycle, and also to enhance the economic parameters by increasing the cycle length and reducing the cost of fuel recycling. For this purpose, a FORTRAN program has been written to map the DGEO algorithm for the LPO problem using the PMAX and PARCS core calculation code to compute the fitness function in each iteration. To speed up the calculations, parallel computing has been applied in the written program. The results demonstrated that the loading pattern, which is suggested by the DGEO algorithm, enhances all the safety and economic parameters in the fitness function. Thus, the DGEO algorithm is highly reliable for the LPO problems in the VVER 1000 reactor core.

• International conference on construction engineering and project management
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• 2024.07a
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• pp.558-565
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• 2024

This paper presents the development of an optimization framework for road slope design. Recognizing the limitations of current manual stability analysis methods, which are time-consuming, are error-prone, and suffer from data mismatches, this study proposes a systematic approach to improve efficiency, reduce costs, and ensure the safety of infrastructure projects. The framework addresses the subjectivity inherent in engineers' decision-making process by formalizing decision variables, constraints, and objective functions to minimize costs while ensuring safety and environmental considerations. The necessity of this framework is embodied by the review of existing literature, which reveals a trend toward specialization within sub-disciplines of road design; however, a gap remains in addressing the complexities of road slope design through an integrated optimization approach. A genetic algorithm (GA) is employed as a fundamental optimization tool due to its well-established mechanisms of selection, crossover, and mutation, which are suitable for evolving road slope designs toward optimal solutions. An automated batch analysis process supports the GA, demonstrating the potential of the proposed framework. Although the framework focuses on the design optimization of single cross-section road slopes, the implications extend to broader applications in civil engineering practices. Future research directions include refining the GA, expanding the decision variables, and empirically validating the framework in real-world scenarios. Ultimately, this research lays the groundwork for more comprehensive optimization models that could consider multiple cross-sections and contribute to safer and more cost-effective road slope designs.

• 한국전산유체공학회:학술대회논문집
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• 2006.05a
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• pp.393-394
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• 2006

• Journal of computational fluids engineering
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• v.11 no.2 s.33
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• pp.19-24
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• 2006

A research to evaluate the efficiency of design optimization was carried out for aerodynamic design optimization problem in distributed computing environment. The aerodynamic analyses which take most of computational work during design optimization were divided into several jobs and allocated to associated PC clients through network. This is not a parallel process based on domain decomposition in a single analysis rather than a simultaneous distributed-analyses using network-distributed computers. GBOM(gradient-based optimization method), SAO(Sequential Approximate Optimization) and RSM(Response Surface Method) were implemented to perform design optimization of transonic airfoils and evaluate their efficiencies. dimensional minimization followed by direction search involved in the GBOM was found an obstacle against improving efficiency of the design process in the present distributed computing system. The SAO was found fairly suitable for the distributed computing environment even it has a handicap of local search. The RSM is apparently the most efficient algorithm in the present distributed computing environment, but additional trial and error works needed to enhance the reliability of the approximation model deteriorate its efficiency from the practical point of view.

• International Journal of Naval Architecture and Ocean Engineering
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• v.7 no.1
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• pp.142-156
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• 2015

A new method for ship Inner Shell optimization, which is called Parametric Inner Shell Optimization Method (PISOM), is presented in this paper in order to improve both hull performance and design efficiency of transport ship. The foundation of PISOM is the parametric Inner Shell Plate (ISP) model, which is a fully-associative model driven by dimensions. A method to create parametric ISP model is proposed, including geometric primitives, geometric constraints, geometric constraint solving etc. The standard optimization procedure of ship ISP optimization based on parametric ISP model is put forward, and an efficient optimization approach for typical transport ship is developed based on this procedure. This approach takes the section area of ISP and the other dominant parameters as variables, while all the design requirements such as propeller immersion, fore bottom wave slap, bridge visibility, longitudinal strength etc, are made constraints. The optimization objective is maximum volume of cargo oil tanker/cargo hold, and the genetic algorithm is used to solve this optimization model. This method is applied to the optimization of a product oil tanker and a bulk carrier, and it is proved to be effective, highly efficient, and engineering practical.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2000.04b
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• pp.187-194
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• 2000

Weight reduction for an automobile body is being sought for the fuel efficiency and the energy conservation. One way of the efforts is adopting Ultra Light Steel Auto Body (ULSAB) concept. The ULSAB concept can be used for the light weight of an automobile door with the tailor welded blank (TWB). A design process is defined for the TWB. The inner panel of door is designed by the TWB and optimization. The design starts from an existing component. At first, the hinge and inner reinforcements are removed. In the conceptual design stage, topology optimization is conducted to find the distribution of variable thicknesses. The number of parts and the welding lines are determined from the topology design. In the detailed design process, size optimization is carried out to find thickness while stiffness constraints are satisfied. The final parting lines are determined by shape optimization.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.14 no.5
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• pp.499-505
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• 2003

In the design of mobile wireless communication system, base station location is one of the most important parameters. Designing base station location, the cost must be minimized by combining various, complex parameters. We can solve this problem by combining optimization algorithm, such as Simulated Annealing, Tabu Search, Genetic Algorithm, Random Walk Algorithm that have been used extensively fur global optimization. This paper shows the 4 kinds of algorithm to be applied to the optimization of base station location for communication system and then compares, analyzes the results and shows optimization process of algorithm.

• Magazine of the Korean Society of Agricultural Engineers
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• v.37 no.E
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• pp.31-39
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• 1995

Weight minimization for the steel bridge girders using an approximation based optimization technique is presented. To accomplish this, an optimization oriented finite element program is used to achieve continuous weight reduction until the optimum is reached. To reduce computational cost, approximation techniques are adopted during the optimization process. Constraint deletion as well as intermediate design variables and responses are also used for higher qualitv of approximations and for a better convergence rate. Both the reliability and the effectiveness of the underlying optimization method are reviewed.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 1996.10a
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• pp.296-303
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• 1996

This paper proposes a method for shape optimization of trusses. The potential savings offered by shape optimization will certainly be more significant than those resulting from fixed-geometry optimization. On the other hand, difficulties associated with topology and geometry optimization are still in existence. Even with a known topology, the geometry optimization problem is still a difficult task. An evolutionary procedure to be adopted and improved in this work, however, offers a means to achieve optimization in topology and geometry together. A plane truss structure is modelled within a specified domain and made to include a great number of nodes and members. Then the structure is analyzed and those members with stresses below a certain level are progressively eliminated from the structural system In this manner the structure evolves into a truss with a better topology and geometry by removing less important parts. Through the worked examples, we can see that the method presented in this Paper shows much promise.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2000.11a
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• pp.369-372
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• 2000

ESO(Evolutionary Structural Optimization) method is known that elements involved low stress value are removed from the previous model or that elements are added around elements involved high stress level on it and then the optimized model is obtained with required weight. Rejection ratio/addition ratio and evolutionary ratio are predefined and elements having lower/higher stress than reference stress, which average Mises stress on edge elements times rejection ratio, are deleted/added. In this study, when the plate having a cutout is subjected various in-plane load, a cutout shape is optimized using ESO method. ANSYS is used to analyse a finite element model and optimization procedure is made by APDL (ANSYS Parametric Design Language). ESO method is useful in rather than a complex structure optimization as well as a cutout shape optimization.