• Title/Summary/Keyword: Multi-level Optimization

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Optimal sensor placement under uncertainties using a nondirective movement glowworm swarm optimization algorithm

  • Zhou, Guang-Dong;Yi, Ting-Hua;Zhang, Huan;Li, Hong-Nan
    • Smart Structures and Systems
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    • v.16 no.2
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    • pp.243-262
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    • 2015
  • Optimal sensor placement (OSP) is a critical issue in construction and implementation of a sophisticated structural health monitoring (SHM) system. The uncertainties in the identified structural parameters based on the measured data may dramatically reduce the reliability of the condition evaluation results. In this paper, the information entropy, which provides an uncertainty metric for the identified structural parameters, is adopted as the performance measure for a sensor configuration, and the OSP problem is formulated as the multi-objective optimization problem of extracting the Pareto optimal sensor configurations that simultaneously minimize the appropriately defined information entropy indices. The nondirective movement glowworm swarm optimization (NMGSO) algorithm (based on the basic glowworm swarm optimization (GSO) algorithm) is proposed for identifying the effective Pareto optimal sensor configurations. The one-dimensional binary coding system is introduced to code the glowworms instead of the real vector coding method. The Hamming distance is employed to describe the divergence of different glowworms. The luciferin level of the glowworm is defined as a function of the rank value (RV) and the crowding distance (CD), which are deduced by non-dominated sorting. In addition, nondirective movement is developed to relocate the glowworms. A numerical simulation of a long-span suspension bridge is performed to demonstrate the effectiveness of the NMGSO algorithm. The results indicate that the NMGSO algorithm is capable of capturing the Pareto optimal sensor configurations with high accuracy and efficiency.

Muti-Objective Design Optimization of Self-Compacting Concrete using CCD Experimental Design and Weighted Multiple Objectives Considering Cost-Effectiveness (비용효율을 고려한 자기 충전형 콘크리트의 CCD 실험설계법 및 가중 다목적성 기반 다목적설계최적화(MODO))

  • Do, Jeongyun
    • Journal of the Korea institute for structural maintenance and inspection
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    • v.24 no.3
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    • pp.26-38
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    • 2020
  • Mixture design of self-compacting concrete is a typical multi-criteria decision making problem and conventional mixture designs are based on the low level engineering method like trials and errors through iteration method to satisfy the various requirements. This study concerns with performing the straightforward multiobjective design optimization of economic SCC mixture considering relative importances of the various requirements and cost-effectives of SCC. Total five requirements of 28day compressive strength, filling ability, segregation stability, material cost and mass were taken into consideration to prepare the objective function to be formulated in form of the weighted-multiobjective mixture design optimization problem. Economic SCC mixture computational design can be given in a rational way which considering material costs and the relative importances of the requiremets and from the result of this study it is expected that the development of SCC mixtue computational design and the consequent univeral concrete material design optimization methodology can be advanced.

Optimal Design for Flexible Passive Biped Walker Based on Chaotic Particle Swarm Optimization

  • Wu, Yao;Yao, Daojin;Xiao, Xiaohui
    • Journal of Electrical Engineering and Technology
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    • v.13 no.6
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    • pp.2493-2503
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    • 2018
  • Passive dynamic walking exhibits humanoid and energy efficient gaits. However, optimal design of passive walker at multi-variable level is not well studied yet. This paper presents a Chaotic Particle Swarm Optimization (CPSO) algorithm and applies it to the optimal design of flexible passive walker. Hip torsional stiffness and damping were incorporated into flexible biped walker, to imitate passive elastic mechanisms utilized in human locomotion. Hybrid dynamics were developed to model passive walking, and period-one gait was gained. The parameters global searching scopes were gained after investigating the influences of structural parameters on passive gait. CPSO were utilized to optimize the flexible passive walker. To improve the performance of PSO, multi-scroll Jerk chaotic system was used to generate pseudorandom sequences, and chaotic disturbance would be triggered if the swarm is trapped into local optimum. The effectiveness of CPSO is verified by comparisons with standard PSO and two typical chaotic PSO methods. Numerical simulations show that better fitness value of optimal design could be gained by CPSO presented. The proposed CPSO would be useful to design biped robot prototype.

Realistic Visualization of Car Configurator Based On Unreal Engine 4(UE4)

  • Zhong, Yiming;Yun, Tae Soo;Lee, Byung Chun
    • International Journal of Internet, Broadcasting and Communication
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    • v.14 no.1
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    • pp.105-115
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    • 2022
  • The platform for displaying cars has been changing with the times. From the popularity of paper media to the rise of computer graphics, the improvement of technology has brought more space and possibilities to the automotive industry. Yiming Zhong proposed the workflow of car configurator through Unreal Engine 4 to implement the basic functions of configuration in 2021, according to Yiming Zhong's final presentation, there is still room to improve the realism of graphics and functionality of the car configurator. Therefore, in this paper we propose to upgrade the car shaders and lighting environments according to the real-world physics and add multi-scenes switching function to car configurator. However the multi-scenes switching function also brings a large amount of data, which leads to the problem of display lag. At the end of the paper, we use the level of details(LOD) process to reduce the amount of data for real-time computing in Unreal Engine 4 and the increase of frames per second(FPS) values verifies the feasibility of our optimization solution.

Study on the Structure Optimization and the Operation Scheme Design of a Double-Tube Once-Through Steam Generator

  • Wei, Xinyu;Wu, Shifa;Wang, Pengfei;Zhao, Fuyu
    • Nuclear Engineering and Technology
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    • v.48 no.4
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    • pp.1022-1035
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    • 2016
  • A double-tube once-through steam generator (DOTSG) consisting of an outer straight tube and an inner helical tube is studied in this work. First, the structure of the DOTSG is optimized by considering two different objective functions. The tube length and the total pressure drop are considered as the first and second objective functions, respectively. Because the DOTSG is divided into the subcooled, boiling, and superheated sections according to the different secondary fluid states, the pitches in the three sections are defined as the optimization variables. A multi-objective optimization model is established and solved by particle swarm optimization. The optimization pitch is small in the subcooled region and superheated region, and large in the boiling region. Considering the availability of the optimum structure at power levels below 100% full power, we propose a new operating scheme that can fix the boundaries between the three heat-transfer sections. The operation scheme is proposed on the basis of data for full power, and the operation parameters are calculated at low power level. The primary inlet and outlet temperatures, as well as flow rate and secondary outlet temperature are changed according to the operation procedure.

Optimum multi-objective modified step-stress accelerated life test plan for the Burr type-XII distribution

  • Srivastava, P.W.;Mittal, N.
    • International Journal of Reliability and Applications
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    • v.15 no.1
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    • pp.23-50
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    • 2014
  • This paper deals with formulation of optimum multi-objective modified step-stress accelerated life test (ALT) plan for Burr type-XII distribution under type-I censoring. Since it is impractical to estimate only one objective parameter after conducting costly ALT tests; also, it is not desirable to assume instantaneous changes in stress levels because of limited capacity of test equipments and the presence of undesirable failure modes, therefore, an optimum multi-objective modified step-stress ALT plan has been designed. The optimal test plan consists in determining the optimum low stress level and optimal time at which stress starts linearly increasing from low stress by minimizing the weighted sum of the asymptotic variances of the maximum likelihood estimator of quantile lifetimes at design constant stress. The method developed has been illustrated using an example. Sensitivity analysis has been carried out. Comparative study has also been done to highlight the merits of the proposed model.

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Process Optimization Formulated in GDP/MINLP Using Hybrid Genetic Algorithm (혼합 유전 알고리즘을 이용한 GDP/MINLP로 표현된 공정 최적화)

  • 송상옥;장영중;김구회;윤인섭
    • Journal of Institute of Control, Robotics and Systems
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    • v.9 no.2
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    • pp.168-175
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    • 2003
  • A new algorithm based on Genetic Algorithms is proposed f3r solving process optimization problems formulated in MINLP, GDP and hybrid MINLP/GDP. This work is focused especially on the design of the Genetic Algorithm suitable to handle disjunctive programming with the same level of MINLP handling capability. Hybridization with the Simulated Annealing is experimented and many heuristics are adopted. Real and binary coded Genetic Algorithm initiates the global search in the entire search space and at every stage Simulated Annealing makes the candidates to climb up the local hills. Multi-Niche Crowding method is adopted as the multimodal function optimization technique. and the adaptation of probabilistic parameters and dynamic penalty systems are also implemented. New strategies to take the logical variables and constraints into consideration are proposed, as well. Various test problems selected from many fields of process systems engineering are tried and satisfactory results are obtained.

Reconfigurable Selective Harmonic Elimination Technique for Wide Range Operations in Asymmetric Cascaded Multilevel Inverter

  • Kavitha, R;Rani, Thottungal
    • Journal of Power Electronics
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    • v.18 no.4
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    • pp.1037-1050
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    • 2018
  • This paper presents a novel reconfigurable selective harmonic elimination technique to control harmonics over a wide range of Modulation Indexes (MI) in Multi-Level Inverter (MLI). In the proposed method, the region of the MI is divided into various sectors and expressions are formulated with different switching patterns for each of the sectors. A memetic BBO-MAS (Biogeography Based Optimization - Mesh Adaptive direct Search) optimization algorithm is proposed for solving the Selective Harmonic Elimination - Pulse Width Modulation (SHE-PWM) technique. An experimental prototype is developed using a Field Programmable Gate Array (FPGA) and their FFT spectrums are analyzed over a wide range of MI using a fluke power logger. Simulation and experimental results have validated the performance of the proposed optimization algorithms and the reconfigurable SHE-PWM technique. Further, the sensitivity of the harmonics has been analyzed considering non-integer variations in the magnitude of the input DC sources.

Optimization for Thermal spray Process by Taguchi Method (다구찌 기법을 이용한 용사코팅의 공정 최적화)

  • Kim, K.T.;Kim, Y.S.
    • Journal of Power System Engineering
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    • v.16 no.2
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    • pp.54-59
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    • 2012
  • In the present study, process optimization for thermal-sprayed Ni-based alloy coating has been performed using Taguchi method and analysis of variance(ANOVA). Ni-based alloy coatings were fabricated by flame spray process on steel substrate, and the hardness test and wear test were performed. Experiments were designed as per Taguchi's L9 orthogonal array and tests were conducted with different Oxygen gas flow, Acetylene gas flow, Powder feed rate and Spray distance. Multi response signal to noise ratio (MRSN) was calculated for the response variables and the optimum combination level of factors was obtained simultaneously using Taguchi's parametric design.

Multi-stage approach for structural damage identification using particle swarm optimization

  • Tang, H.;Zhang, W.;Xie, L.;Xue, S.
    • Smart Structures and Systems
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    • v.11 no.1
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    • pp.69-86
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    • 2013
  • An efficient methodology using static test data and changes in natural frequencies is proposed to identify the damages in structural systems. The methodology consists of two main stages. In the first stage, the Damage Signal Match (DSM) technique is employed to quickly identify the most potentially damaged elements so as to reduce the number of the solution space (solution parameters). In the second stage, a particle swarm optimization (PSO) approach is presented to accurately determine the actual damage extents using the first stage results. One numerical case study by using a planar truss and one experimental case study by using a full-scale steel truss structure are used to verify the proposed hybrid method. The identification results show that the proposed methodology can identify the location and severity of damage with a reasonable level of accuracy, even when practical considerations limit the number of measurements to only a few for a complex structure.