• Korean Journal of Breeding Science
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• v.43 no.4
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• pp.273-281
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• 2011

Fusarium head blight (FHB), also known as scab, caused mainly by Fusarium graminearum is a devastating disease of wheat in regions that are warm and humid during flowering. In addition to significant yield and quality losses, the mycotoxin deoxynivalenol produced by the pathogen in infected wheat kernels is a serious problem for food and feed safety. Twenty- three Korean cultivars and "Sumai 3", which is a FHB-resistant Chinese cultivar were tested for Type I, Type II resistances of FHB. Three cultivars were identified as resistant in Type I assessment, and two cultivars were resistant in Type II assessment. Genetic variation and relationship among the cultivars were evaluated on the basis of 11 Simple Sequence Repeat (SSR) and 29 Sequence Tagged Site (STS) markers that were linked to FHB resistance Quantitative Trait Loci (QTL) on chromosome 3BS. One SSR and 7 STS markers detected polymorphisms. Especially, using a STS marker (XSTS3B-57), 32.4% of the variation for Type II FHB resistance could be explained. Genetic relationship among Korean wheat cultivars was generally consistent with their released year. These markers on chromosome 3BS have the potential for accelerating the development of Korean wheat cultivars with improved Fusarium head blight resistance through the use of marker-assisted selection.

• Structural Engineering and Mechanics
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• v.71 no.1
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• pp.45-56
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• 2019

A modified mechanical model of pre-pressed spring self-centering energy dissipation (PS-SCED) brace is proposed, and the hysteresis band is distinguished by the indication of relevant state variables. The MDOF frame system equipped with the braces is formulated in an incremental form of linear acceleration method. A multi-objective genetic algorithm (GA) based brace parameter optimization method is developed to obtain an optimal solution from the primary design scheme. Parameter sensitivities derived by the direct differentiation method are used to modify the change rate of parameters in the GA operator. A case study is conducted on a steel braced frame to illustrate the effect of brace parameters on node displacements, and validate the feasibility of the modified mechanical model. The optimization results and computational process information are compared among three cases of different strategies of parameter change as well. The accuracy is also verified by the calculation results of finite element model. This work can help the applications of PS-SCED brace optimization related to parameter sensitivity, and fulfill the systematic design procedure of PS-SCED brace-structure system with completed and prospective consequences.

• Journal of Ocean Engineering and Technology
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• v.34 no.6
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• pp.481-488
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• 2020

Composite materialsuch as glass-fiber reinforced plastic and carbon-fiber reinforced plastic (CFRP) shows anisotropic property and have been widely used for structural members and outfitings of ships. The structural safety of composite structures has been generally evaluated via finite element analysis. This paper presents a technique for updating the finite element model of anisotropic beams or plates via natural frequencies. The finite element model updates involved a compensation process of anisotropic material properties, such as the elastic and shear moduli of orthotropic structural members. The technique adopted was based on a discrete genetic algorithm, which is an optimization technique. The cost function was adopted to assess the optimization problem, which consisted of the calculated and referenced low-order natural frequencies for the target structure. The optimization process was implemented with MATLAB, which includes the finite element updates and the corresponding natural frequency calculations with MSC/NASTRAN. Material properties of a virtual cantilevered orthotropic beam were estimated to verify the presented method and the results obtained were compared with the reference values. Furthermore, the technique was applied to a cantilevered CFRP beam to successfully estimate the unknown material properties.

• Journal of Hydrogen and New Energy
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• v.32 no.4
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• pp.212-218
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• 2021

In this study, we conducted a design optimization of the Type 4 composite pressure vessels to enhance the pressure-resistant performance of the vessels while keeping the thickness of the composite layer. The design variables for the optimization were the stacking angles of the helical layers of the vessels to improve the performance. Since the carbon fibers are expensive material, it is desirable to reduce the use of the carbon fibers by applying an optimal design of the composite pressure vessel. The structural analysis and optimization process for the design of Type 4 composite pressure vessels were carried out using a commercial finite element analysis software, Abaqus and a plug-in for automated simulation, Isight, respectively. The optimization results confirmed the performance and safety of the optimized Type 4 composite pressure vessels was enhanced by 12.84% compared to the initial design.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.28 no.12
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• pp.1914-1922
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• 2004

This paper provides a comprehensive study of optimum design of a helicopter tailrotor driveshaft made of the flexible matrix composites (FMCs). Since the driveshaft transmits power while subjected to large bending deformation due to aerodynamic loadings, the FMCs can be ideal for enhancing the drivetrain performance by absorbing the lateral deformation without shaft segmentation. However, the increased lateral flexibility and high internal damping of the FMCs may induce whirling instability at supercritical operating conditions. Thus, the purpose of optimization in this paper is to find a set of tailored FMC parameters that compromise between the lateral flexibility and the whirling stability while satisfying several criteria such as torsional buckling safety and the maximum shaft temperature at steadystate conditions. At first, the drivetrain was modeled based on the finite element method and the classical laminate theory with complex modulus approach. Then, an objective function was defined as a combination of an allowable bending deformation and external damping and a genetic algorithm was applied to search for an optimum set with respect to ply angles and stack sequences. Results show that an optimum laminate consists of two groups of layers: (i) one has ply angles well below 45$^{\circ}$ and the other far above 45$^{\circ}$ and (ii) the number of layers with low ply angles is much bigger than that with high ply angles. It is also found that a thick FMC shaft is desirable for both lateral flexibility and whirling stability. The genetic algorithm was effective in converging to several local optimums, whose laminates exhibit similar patterns as mentioned above.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.37 no.6
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• pp.949-963
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• 2017

This study present an efficient way of operating drainage pump station as part of nonstructural measures for reducing urban flood damage. The water level in the drainage pump station was forecast using Neuro-Fuzzy and then operation rule of the drainage pump station was determined applying the genetic algorithm method based on the predicted inner water level. In order to reflect the topographical characteristics of the drainage area when constructing the Neuro-Fuzzy model, the model considering spatial parameters was developed. Also, the model was applied a penalty type of genetic algorithm so as to prevent repeated stops and operations while lowering my highest water level. The applicability of the development model for the five drainage pump stations in the Mapo drainage area was verified. It is considered to be able to effectively manage urban drainage facilities in the development of these operating rules.

• International Journal of Highway Engineering
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• v.13 no.2
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• pp.175-185
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• 2011

Geometric information is a key element for evaluating traffic safety and road maintenance. This study developed an algorithm to identify horizontal alignment using global positioning system(GPS) and inertial navigation system(INS) data. Roll and heading information extracted from GPS/INS were utilized to classify horizontal alignment into tangent, circular curve, and transition curve. The proposed algorithm consists of two components including smoothing for eliminating outlier and a heuristic classification algorithm. A genetic algorithm(GA) was adopted to calibrate parameters associated with the algorithm. Both freeway and rural highway data were used to evaluate the performance of the proposed algorithm. Promising results, which 90.48% and 88.24% of classification accuracy were obtainable for freeway and rural highway respectively, demonstrated the technical feasibility of the algorithm for the implementation.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.31 no.1 s.256
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• pp.26-35
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• 2007

The vehicle of urban transit is a complex system that consists of various electric, electronic, and mechanical equipments, and the maintenance cost of this complex and large-scale system generally occupies sixty percent of the LCC (Life Cycle Cost). For reasonable establishing of maintenance strategies, safety security and cost limitation must be considered at the same time. The concept of system reliability has been introduced and optimized as the key of reasonable maintenance strategies. For optimization, three preceding studies were accomplished; standardizing a maintenance classification, constructing RBD (Reliability Block Diagram) of VVVF (Variable Voltage Variable Frequency) urban transit, and developing a web based reliability evaluation system. Historical maintenance data in terms of reliability index can be derived from the web based reliability evaluation system. In this paper, we propose applying inverse problem analysis method and hybrid neuro-genetic algorithm to system reliability optimization for using historical maintenance data in database of web based system. Feed-forward multi-layer neural networks trained by back propagation are used to find out the relationship between several component reliability (input) and system reliability (output) of structural system. The inverse problem can be formulated by using neural network. One of the neural network training algorithms, the back propagation algorithm, can attain stable and quick convergence during training process. Genetic algorithm is used to find the minimum square error.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.48 no.8
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• pp.621-629
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• 2020

LRU layout is a complex problem that requires consideration of various criteria such as airworthiness, performance, maintainability and environmental requirements. As aircraft functions become more complex, the necessary equipment is increasing, and unmanned aerial vehicles are equipped with more equipment as a substitute for pilots. Due to the complexity of the problem, the increase in the number of equipment, and the limited development period, the placement of equipment is largely dependent on the engineer's insight and experience. For optimization, quantitative criteria are required for evaluation, but criteria such as safety, performance, and maintainability are difficult to quantitatively compare or have limitations. In this study, we consider the installation and maintenance of the equipment, simplify the deployment model to the traveling salesman problem, Optimization was performed using a genetic algorithm to minimize the weight of the connecting cable between the equipment. When the optimization results were compared with the global calculations, the same results were obtained with less time required, and the improvement was compared with the heuristic.

• Journal of the Korea Convergence Society
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• v.11 no.5
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• pp.175-182
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• 2020

The calculation of the optimal trajectory of the stepped top-down robot was made using a genetic algorithm and a computational torque controller. First, the total energy efficiency was minimized using the Red-Cold Generic Algorithm (RCGA) consisting of reproductive, cross, and mutation. The reproducibility condition related to the position assembly of the start and end of the stride and the joints, angles, and angular velocities are linear constraints. Next, the unequal constraint accompanies the condition for preventing the collision of the swing leg at the corner with the outer surface of the stairs, the condition of the knee joint for preventing kinematic peculiarity, and the condition of no moment in safety in the traveling direction. Finally, the angular trajectory of each joint is defined by fourth-order polynomial whose coefficient is to approximate chromosomes. This is to approximate walking. In this study, the energy efficiency of the optimal trajectory was analyzed by computer simulation through a biped robot with seven degrees of freedom composed of seven links.