• Title/Summary/Keyword: Genetic loading

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Ship Loading Plan for Tandem Crane in Container Terminals (탠덤 크레인을 고려한 컨테이너터미널 선적 계획)

  • Kwon, Sun-Cheol;Shin, Jae-Young;Kim, Sang-Jin
    • Proceedings of the Korean Institute of Navigation and Port Research Conference
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    • 2009.06a
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    • pp.167-168
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    • 2009
  • As the rapid increase of the container trade, most of the container terminals strive to improve the container handling productivity. Therefore, they consider to find efficient operating strategies and to introduce new container handling facilities. In terms of equipment, there are a variety of types of quay cranes. Single-lift crane operates only one container regardless of size and twin-lift crane operates two 20' containers or one 40' container simultaneously. Tandem crane, recently introduced, can operate four 20' containers or two 40' containers simultaneously. In this paper, we propose the mathematical model and the solution procedure of the ship loading scheduling problem for the tandem crane.

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Material distribution optimization of 2D heterogeneous cylinder under thermo-mechanical loading

  • Asgari, Masoud
    • Structural Engineering and Mechanics
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    • v.53 no.4
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    • pp.703-723
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    • 2015
  • In this paper optimization of volume fraction distribution in a thick hollow cylinder with finite length made of two-dimensional functionally graded material (2D-FGM) and subjected to steady state thermal and mechanical loadings is considered. The finite element method with graded material properties within each element (graded finite elements) is used to model the structure. Volume fractions of constituent materials on a finite number of design points are taken as design variables and the volume fractions at any arbitrary point in the cylinder are obtained via cubic spline interpolation functions. The objective function selected as having the normalized effective stress equal to one at all points that leads to a uniform stress distribution in the structure. Genetic Algorithm jointed with interior penalty-function method for implementing constraints is effectively employed to find the global solution of the optimization problem. Obtained results indicates that by using the uniform distribution of normalized effective stress as objective function, considerably more efficient usage of materials can be achieved compared with the power law volume fraction distribution. Also considering uniform distribution of safety factor as design criteria instead of minimizing peak effective stress affects remarkably the optimum volume fractions.

Maximizing the Overall Satisfaction Degree of all Participants in the Market Using Real Code-based Genetic Algorithm by Optimally Locating and Sizing the Thyristor-Controlled Series Capacitor

  • Nabavi, Seyed M.H.;Hajforoosh, Somayeh;Hajforoosh, Sajad;Karimi, Ali;Khafafi, Kamran
    • Journal of Electrical Engineering and Technology
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    • v.6 no.4
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    • pp.493-504
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    • 2011
  • The present paper presents a genetic algorithm (GA) to maximize social welfare and perform congestion management by optimally placing and sizing one Thyristor-Controlled Series Capacitor (TCSC) device in a double-sided auction market. Simulation results, with line flow constraints before and after the compensation, are compared through the Sequential Quadratic Programming SQP method, and are used to analyze the effect of TCSC on the congestion levels of modified IEEE 14-bus and 30-bus test systems. Quadratic, smooth and nonsmooth (with sine components due to valve point loading effect) generator cost curves, and quadratic smooth consumer benefit functions are considered. The main aims of the present study are the inclusion of customer benefit in the social welfare maximization and congestion management objective function, the consideration of nonsmooth generator characteristics, and the optimal locating and sizing of the TCSC using real code-based GA to guarantee fast convergence to the best solution.

Effects of infill walls on RC buildings under time history loading using genetic programming and neuro-fuzzy

  • Kose, M. Metin;Kayadelen, Cafer
    • Structural Engineering and Mechanics
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    • v.47 no.3
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    • pp.401-419
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    • 2013
  • In this study, the efficiency of adaptive neuro-fuzzy inference system (ANFIS) and genetic expression programming (GEP) in predicting the effects of infill walls on base reactions and roof drift of reinforced concrete frames were investigated. Current standards generally consider weight and fundamental period of structures in predicting base reactions and roof drift of structures by neglecting numbers of floors, bays, shear walls and infilled bays. Number of stories, number of bays in x and y directions, ratio of shear wall areas to the floor area, ratio of bays with infilled walls to total number bays and existence of open story were selected as parameters in GEP and ANFIS modeling. GEP and ANFIS have been widely used as alternative approaches to model complex systems. The effects of these parameters on base reactions and roof drift of RC frames were studied using 3D finite element method on 216 building models. Results obtained from 3D FEM models were used to in training and testing ANFIS and GEP models. In ANFIS and GEP models, number of floors, number of bays, ratio of shear walls and ratio of infilled bays were selected as input parameters, and base reactions and roof drifts were selected as output parameters. Results showed that the ANFIS and GEP models are capable of accurately predicting the base reactions and roof drifts of RC frames used in the training and testing phase of the study. The GEP model results better prediction compared to ANFIS model.

Optimal design of floating substructures for spar-type wind turbine systems

  • Choi, Ejae;Han, Changwan;Kim, Hanjong;Park, Seonghun
    • Wind and Structures
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    • v.18 no.3
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    • pp.253-265
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    • 2014
  • The platform and floating structure of spar type offshore wind turbine systems should be designed in order for the 6-DOF motions to be minimized, considering diverse loading environments such as the ocean wave, wind, and current conditions. The objective of this study is to optimally design the platform and substructure of a 3MW spar type wind turbine system with the maximum postural stability in 6-DOF motions as well as the minimum material cost. Therefore, design variables of the platform and substructure were first determined and then optimized by a hydrodynamic analysis. For the hydrodynamic analysis, the body weight of the system was considered, and the ocean wave conditions were quantified to the wave forces using the Morison's equation. Moreover, the minimal number of computation analysis models was generated by the Design of Experiments (DOE), and the design variables of the platform and substructure were finally optimized by using a genetic algorithm with a neural network approximation.

Multi-floor Layout Model for Topsides of Floating Offshore Plant using the Optimization Technique (최적화 기법을 이용한 부유식 해양 플랜트 상부 구조의 다층 배치 모델)

  • Jeong, Se-Yong;Roh, Myung-Il;Shin, Hyunkyoung
    • Journal of the Society of Naval Architects of Korea
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    • v.52 no.1
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    • pp.77-87
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    • 2015
  • For a floating offshore plant such as FPSO(Floating, Production, Storage, and Off-loading unit), various equipment should be installed in the restricted space, as compared with an onshore plant. The requirement for an optimal layout method of the plant has been increased in these days. Thus, a layout method of the floating offshore plant was proposed in this study. For this, an optimization problem for layout design was mathematically formulated, and then an optimization algorithm based on the genetic algorithm was implemented with C++ language in order to solve it. Finally, the proposed method was applied to an example of FPSO topsides. As a result, it was shown that the proposed method can be applied to layout design of the floating offshore plant such as FPSO.

An Association Study of the Brain-Derived Neurotrophic Factor Val66Met Gene Polymorphism and Schizophrenia (Brain-Derived Neurotrophic Factor Val66Met 다형성과 정신분열병의 관련 연구)

  • Lee, Hwa-Young;Kim, Dae-Jin;Kim, Yong-Ku
    • Korean Journal of Biological Psychiatry
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    • v.13 no.4
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    • pp.267-272
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    • 2006
  • Objectives : Schizophrenia is a clinically heterogenous disease with a strong genetic component. Many studies have suggested that brain-derived neurotrophic factor(BDNF) is involved in the pathophysiology of schizophrenia. This study was performed to determine whether there is an association between BDNF Val66Met polymorphism and schizophrenia. Methods : To identify any genetic predisposition to schizophrenia, we investigated the BDNF Val66Met polymorphism in 106 patients with schizophrenia and 147 normal controls with PCR-RFLP method. Statistical analyses were used to test the association between and BDNF Val66Met genotype and Schizophrenia. Results : No association was found between BDNF Val66Met polymorphism and schizophrenia. No significant differences were found comparing the BDNF genotype distributions according to the age of onset, the number of admission and familial loading in schizophrenia. Conclusion : This result indicates that BDNF Val66Met polymorphism is not associated with schizophrenia. However, further studies with a large number of subjects are needed to confirm whether the BDNF gene is related to schizophrenia.

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Optimum design of steel frame structures considering construction cost and seismic damage

  • Kaveh, A.;Fahimi-Farzam, M.;Kalateh-Ahani, M.
    • Smart Structures and Systems
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    • v.16 no.1
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    • pp.1-26
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    • 2015
  • Minimizing construction cost and reducing seismic damage are two conflicting objectives in the design of any new structure. In the present work, we try to develop a framework in order to solve the optimum performance-based design problem considering the construction cost and the seismic damage of steel moment-frame structures. The Park-Ang damage index is selected as the seismic damage measure because it is one of the most realistic measures of structural damage. The non-dominated sorting genetic algorithm (NSGA-II) is employed as the optimization algorithm to search the Pareto optimal solutions. To improve the time efficiency of the proposed framework, three simplifying strategies are adopted: first, simplified nonlinear modeling investigating minimum level of structural modeling sophistication; second, fitness approximation decreasing the number of fitness function evaluations; third, wavelet decomposition of earthquake record decreasing the number of acceleration points involved in time-history loading. The constraints of the optimization problem are considered in accordance with Federal Emergency Management Agency's (FEMA) recommended seismic design specifications. The results from numerical application of the proposed framework demonstrate the efficiency of the framework in solving the present multi-objective optimization problem.

Life-cycle cost optimization of steel moment-frame structures: performance-based seismic design approach

  • Kaveh, A.;Kalateh-Ahani, M.;Fahimi-Farzam, M.
    • Earthquakes and Structures
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    • v.7 no.3
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    • pp.271-294
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    • 2014
  • In recent years, along with the advances made in performance-based design optimization, the need for fast calculation of response parameters in dynamic analysis procedures has become an important issue. The main problem in this field is the extremely high computational demand of time-history analyses which may convert the solution algorithm to illogical ones. Two simplifying strategies have shown to be very effective in tackling this problem; first, simplified nonlinear modeling investigating minimum level of structural modeling sophistication, second, wavelet analysis of earthquake records decreasing the number of acceleration points involved in time-history loading. In this paper, we try to develop an efficient framework, using both strategies, to solve the performance-based multi-objective optimal design problem considering the initial cost and the seismic damage cost of steel moment-frame structures. The non-dominated sorting genetic algorithm (NSGA-II) is employed as the optimization algorithm to search the Pareto optimal solutions. The constraints of the optimization problem are considered in accordance with Federal Emergency Management Agency (FEMA) recommended design specifications. The results from numerical application of the proposed framework demonstrate the capabilities of the framework in solving the present multi-objective optimization problem.

Integrated Whole-Cell Biocatalysis for Trehalose Production from Maltose Using Permeabilized Pseudomonas monteilii Cells and Bioremoval of Byproduct

  • Trakarnpaiboon, Srisakul;Champreda, Verawat
    • Journal of Microbiology and Biotechnology
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    • v.32 no.8
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    • pp.1054-1063
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    • 2022
  • Trehalose is a non-conventional sugar with potent applications in the food, healthcare and biopharma industries. In this study, trehalose was synthesized from maltose using whole-cell Pseudomonas monteilii TBRC 1196 producing trehalose synthase (TreS) as the biocatalyst. The reaction condition was optimized using 1% Triton X-100 permeabilized cells. According to our central composite design (CCD) experiment, the optimal process was achieved at 35℃ and pH 8.0 for 24 h, resulting in the maximum trehalose yield of 51.60 g/g after 12 h using an initial cell loading of 94 g/l. Scale-up production in a lab-scale bioreactor led to the final trehalose concentration of 51.91 g/l with a yield of 51.60 g/g and productivity of 4.37 g/l/h together with 8.24 g/l glucose as a byproduct. A one-pot process integrating trehalose production and byproduct bioremoval showed 53.35% trehalose yield from 107.4 g/l after 15 h by permeabilized P. moteilii cells. The residual maltose and glucose were subsequently removed by Saccharomyces cerevisiae TBRC 12153, resulting in trehalose recovery of 99.23% with 24.85 g/l ethanol obtained as a co-product. The present work provides an integrated alternative process for trehalose production from maltose syrup in bio-industry.