• Title/Summary/Keyword: Multi parameter

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The Study on Fatigue Life Prediction under Biaxial Variable Load (이축 변동하중하에서의 피로수명 예측기법에 관한 연구)

  • 오세종;이현우;전제춘
    • Proceedings of the Korean Society of Precision Engineering Conference
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    • 1993.10a
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    • pp.666-671
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    • 1993
  • Fatigue life prediction under multi-axial variable load were performed for Aluminium 7075-T651 alloy using SAE Notched specimen & Torque tube shaft component specimen. When variable multiaxial load is applied to material, maximum damaged plane(critical plane) change. To clarify the situation, experiment is performed on two different changing load path. For multiaxial fatigue life prediction, miner rule is expanded to critical plane theory. Shear based parameter and Elliptical parameter give better correlation. This suggests that miner rule can be applicable on multi-axial variable load.

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Application of multi-objective genetic algorithm for waste load allocation in a river basin (오염부하량 할당에 있어서 다목적 유전알고리즘의 적용 방법에 관한 연구)

  • Cho, Jae-Heon
    • Journal of Environmental Impact Assessment
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    • v.22 no.6
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    • pp.713-724
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    • 2013
  • In terms of waste load allocation, inequality of waste load discharge must be considered as well as economic aspects such as minimization of waste load abatement. The inequality of waste load discharge between areas was calculated with Gini coefficient and was included as one of the objective functions of the multi-objective waste load allocation. In the past, multi-objective functions were usually weighted and then transformed into a single objective optimization problem. Recently, however, due to the difficulties of applying weighting factors, multi-objective genetic algorithms (GA) that require only one execution for optimization is being developed. This study analyzes multi-objective waste load allocation using NSGA-II-aJG that applies Pareto-dominance theory and it's adaptation of jumping gene. A sensitivity analysis was conducted for the parameters that have significant influence on the solution of multi-objective GA such as population size, crossover probability, mutation probability, length of chromosome, jumping gene probability. Among the five aforementioned parameters, mutation probability turned out to be the most sensitive parameter towards the objective function of minimization of waste load abatement. Spacing and maximum spread are indexes that show the distribution and range of optimum solution, and these two values were the optimum or near optimal values for the selected parameter values to minimize waste load abatement.

Empirical Performance Evaluation of Communication Libraries for Multi-GPU based Distributed Deep Learning in a Container Environment

  • Choi, HyeonSeong;Kim, Youngrang;Lee, Jaehwan;Kim, Yoonhee
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.15 no.3
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    • pp.911-931
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    • 2021
  • Recently, most cloud services use Docker container environment to provide their services. However, there are no researches to evaluate the performance of communication libraries for multi-GPU based distributed deep learning in a Docker container environment. In this paper, we propose an efficient communication architecture for multi-GPU based deep learning in a Docker container environment by evaluating the performances of various communication libraries. We compare the performances of the parameter server architecture and the All-reduce architecture, which are typical distributed deep learning architectures. Further, we analyze the performances of two separate multi-GPU resource allocation policies - allocating a single GPU to each Docker container and allocating multiple GPUs to each Docker container. We also experiment with the scalability of collective communication by increasing the number of GPUs from one to four. Through experiments, we compare OpenMPI and MPICH, which are representative open source MPI libraries, and NCCL, which is NVIDIA's collective communication library for the multi-GPU setting. In the parameter server architecture, we show that using CUDA-aware OpenMPI with multi-GPU per Docker container environment reduces communication latency by up to 75%. Also, we show that using NCCL in All-reduce architecture reduces communication latency by up to 93% compared to other libraries.

FATIGUE DAMAGE PARAMETER OF SPOT WELDED JOINTS UNDER PROPORTIONAL LOADING

  • KANG H. T.
    • International Journal of Automotive Technology
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    • v.6 no.3
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    • pp.285-291
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    • 2005
  • In this paper, the author proposes a fatigue damage parameter of spot welded joints under proportional loading. The proposed fatigue damage parameter is developed based on von Mises' equivalent stress and local structural stress at the edge of spot weld nugget. The structural stress at the edges of the weld nugget in each sheet is calculated using the forces and moments that are determined by finite element analysis. A structural equivalent stress is then calculated by von Mises' equivalent stress equation. The structural equivalent stresses are correlated to experimental fatigue life of the spot welded joints. The proposed parameter is evaluated with fatigue test data of spot welds subjected to multi axial and tensile-shear loads. Sheppard's parameter and Rupp and co-workers' parameter are also evaluated with the same test data to compare with the author's parameter. This proposed parameter presents a better correlation with experimental fatigue data than those of Sheppard's and Rupp and co-workers' parameter. The proposed parameter should be very effective for durability calculations during the early design phase since coarsely meshed finite element models can be employed.

A Study on Calculation of Capacitance Parameter for Interconnection Line in Multilayer Dielectric Media (다층 유전체 매질에서의 Interconnection Line에 대한 Capacitance Parameter 계산에 관한 연구)

  • 김한구;곽계달
    • Journal of the Korean Institute of Telematics and Electronics
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    • v.26 no.8
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    • pp.1187-1196
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    • 1989
  • In this paper, a method for computing the capacitance parameter for a multi-interconnection line in a multilayered dielectric region is presented. The number of interconnection lines and the number of dielectric layers are arbitrary, and the interconnection lines are finite cross section or infinite cross section. The surface of lines and dielectric interface are divided into subsection. The surface charge density of each subsection is a constant step-pulse function for each subsection. After the solution of surface charge density is effected by the method of moments, capacitance parameter is calculated.

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Design of a Controller using Algorithm in the Robust Controller (강인제어기 알고리즘을 이용한 제어기 설계)

  • Hwang, Yu-Sub
    • Journal of the Korean Society of Industry Convergence
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    • v.7 no.2
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    • pp.215-220
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    • 2004
  • In this paper, some algorithms for robust stabilization of linerar time - invariant single - input - multi output (SIMO) systems subject to parameter perturbatations are presented. At first, the determination algorithm of the largest stable hypersphere in the parameter space of a given characteristic polynomial with its coefficient perturbations near some stable nominal values is presented. These algorithms iteratively enlarge the stability hypersph ere in plant parameter space and can be used to design a controller to stabilize a plant subject to givien range of parameter ecxursions.

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Time-varying physical parameter identification of shear type structures based on discrete wavelet transform

  • Wang, Chao;Ren, Wei-Xin;Wang, Zuo-Cai;Zhu, Hong-Ping
    • Smart Structures and Systems
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    • v.14 no.5
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    • pp.831-845
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    • 2014
  • This paper proposed a discrete wavelet transform based method for time-varying physical parameter identification of shear type structures. The time-varying physical parameters are dispersed and expanded at multi-scale as profile and detail signal using discrete wavelet basis. To reduce the number of unknown quantity, the wavelet coefficients that reflect the detail signal are ignored by setting as zero value. Consequently, the time-varying parameter can be approximately estimated only using the scale coefficients that reflect the profile signal, and the identification task is transformed to an equivalent time-invariant scale coefficient estimation. The time-invariant scale coefficients can be simply estimated using regular least-squares methods, and then the original time-varying physical parameters can be reconstructed by using the identified time-invariant scale coefficients. To reduce the influence of the ill-posed problem of equation resolving caused by noise, the Tikhonov regularization method instead of regular least-squares method is used in the paper to estimate the scale coefficients. A two-story shear type frame structure with time-varying stiffness and damping are simulated to validate the effectiveness and accuracy of the proposed method. It is demonstrated that the identified time-varying stiffness is with a good accuracy, while the identified damping is sensitive to noise.

A study on the accuracy of multi-task learning structure artificial neural network applicable to multi-quality prediction in injection molding process (사출성형공정에서 다수 품질 예측에 적용가능한 다중 작업 학습 구조 인공신경망의 정확성에 대한 연구)

  • Lee, Jun-Han;Kim, Jong-Sun
    • Design & Manufacturing
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    • v.16 no.3
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    • pp.1-8
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    • 2022
  • In this study, an artificial neural network(ANN) was constructed to establish the relationship between process condition prameters and the qualities of the injection-molded product in the injection molding process. Six process parmeters were set as input parameter for ANN: melt temperature, mold temperature, injection speed, packing pressure, packing time, and cooling time. As output parameters, the mass, nominal diameter, and height of the injection-molded product were set. Two learning structures were applied to the ANN. The single-task learning, in which all output parameters are learned in correlation with each other, and the multi-task learning structure in which each output parameters is individually learned according to the characteristics, were constructed. As a result of constructing an artificial neural network with two learning structures and evaluating the prediction performance, it was confirmed that the predicted value of the ANN to which the multi-task learning structure was applied had a low RMSE compared with the single-task learning structure. In addition, when comparing the quality specifications of injection molded products with the prediction values of the ANN, it was confirmed that the ANN of the multi-task learning structure satisfies the quality specifications for all of the mass, diameter, and height.

Blind Parameter Estimation Schemes for Uniform Linear Array MIMO Radars Using Distributed Multiple Electronic Sensors (분산 다중 전자전 센서를 이용한 등 간격 선형 배치 MIMO 레이다 파라미터의 암맹 추정 기법)

  • Kim, Dong-Hyun;Lee, Jae-Hoon;Song, Jong-In;Chung, Wonzoo
    • The Journal of Korean Institute of Electromagnetic Engineering and Science
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    • v.28 no.8
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    • pp.619-627
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    • 2017
  • MIMO(Multi-Input Multi-Output) radar is an emerging radar technology for its numerous advantages. However, in the electric warfare viewpoint, MIMO radar is a new developed radar technology for that existing parameter estimation cannot applied and a new radar parameter estimation based on the characteristics of MIMO radar is desired. In this paper, we propose a blind estimation scheme for the number of orthogonal waveforms of a uniform linear array(ULA) MIMO radar using minimum two electronic sensors.

Study on Multi Parameter Measurement and Analysis of Distribution High Voltage Cable Connection Part (배전용 특고압 케이블 접속재의 다변수 측정 분석 연구)

  • Song, Ki-Hong;Bae, Young-Chul;Kim, Yi-Gon
    • The Journal of the Korea institute of electronic communication sciences
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    • v.16 no.1
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    • pp.53-60
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    • 2021
  • High voltage CV cables have been widely installed underground due to their convenience and urban aesthetics. However, cable accidents have occurred frequently owing to poor construction and natural degradations. This paper proposes the method to measure the multi parameter measurement for optimum diagnostics of high voltage cable connection parts and verifies its technical usefulness. This measurement is intended to diagnose degradations of cable connection parts by using simultaneous vibration and thermography as well as partial discharge(PD). The experiment in a shielded laboratory was carried out to verify the usefulness of the multi parameter measurement. The experiment defined the degradation of the cable connection part as 12 types, and produced each degradation sample. As a result of experiment, it was possible to check the correlation of vibration signals with regard to progress in some defects. In the case of thermography, the coherence with regard to the progress of some defects was found. We figure that the proposed method would be useful also in the noise environment.