• Title/Summary/Keyword: Parameters Optimization

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MgFe$_2$/GeO$_2$ AR Coating on o-type(100) Cz Silicon Solar Cells

  • Lim, D.G.;Lee, I.;Lee, U.J.;Yi, J.
    • Transactions on Electrical and Electronic Materials
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    • v.1 no.4
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    • pp.11-15
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    • 2000
  • This paper presents a process optimization of antireflection (AR) coating on crystalline Si solar cells. Theoretical and experimental investigations were performed on a double-layer AR(DLAR) coating of MgFe$_2$/GeO$_2$. We investigated GeO$_2$ films as an AR layer because they have a proper refractive index of 2.46 and demonstrate the same lattice constant as Si substrate. RF sputter grown GeO$_2$ film showed deposition temperature strong dependence. The GeO$_2$ at 400$\^{C}$ exhibited a strong (111) preferred orientation and the lowest surface roughness of 6.87 $\AA$. Refractive index of MgFe$_2$film was measured as 1.386 for the most of growth temperature. An optimized DLAR coating showed a reflectance as low as 2.04% in the wavelengths ranged from 0.4 ㎛ to 1.1 ㎛. Solar cells with a structure of MgFe$_2$/GeO$_2$/Ag/N$\^$+//p-type Si/P$\^$+//Al were investigated with the without DLAR coatings. We achieved the efficiency of solar cells greater than 15% with 3.12% improvement with DLAR coatings. Further details about MgFe$_2$,GeO$_2$ films, and cell fabrication parameters are presented in this paper.

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3D Human Shape Estimation from a Silhouette Image by using Statistical Human Shape Spaces (통계적 신체 외형 데이터베이스를 활용한 실루엣으로부터의 3차원 인체 외형 예측)

  • Dasol Ahn;Sang Il Park
    • Journal of the Korea Computer Graphics Society
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    • v.29 no.1
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    • pp.13-22
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    • 2023
  • In this paper, we present a method for estimating full 3D shapes from given 2D silhouette images of human bodies. Because the silhouette only consists of the partial information on the true shape, it is an ill-posed problem. To address the problem, we use the statistical human shape space obtained from the existing large 3D human shape database. The method consists of three steps. First, we extract the boundary pixels and their appropriate normal vectors from the input silhouette images. Then, we initialize the correspondences of each pixel to the vertex of the statistically-deformable 3D human model. Finally, we numerically optimize the parameters of the statistical model to fit best to the given silhouettes. The viability and the robustness of the method is demonstrated with various experiments.

Analysis of Laser-protection Performance of Asymmetric-phase-mask Wavefront-coding Imaging Systems

  • Yangliang, Li;Qing, Ye;Lei, Wang;Hao, Zhang;Yunlong, Wu;Xian'an, Dou;Xiaoquan, Sun
    • Current Optics and Photonics
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    • v.7 no.1
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    • pp.1-14
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    • 2023
  • Wavefront-coding imaging can achieve high-quality imaging along with a wide range of defocus. In this paper, the anti-laser detection and damage performance of wavefront-coding imaging systems using different asymmetric phase masks are studied, through modeling and simulation. Based on FresnelKirchhoff diffraction theory, the laser-propagation model of the wavefront-coding imaging system is established. The model uses defocus distance rather than wave aberration to characterize the degree of defocus of an imaging system. Then, based on a given defocus range, an optimization method based on Fisher information is used to determine the optimal phase-mask parameters. Finally, the anti-laser detection and damage performance of asymmetric phase masks at different defocus distances and propagation distances are simulated and analyzed. When studying the influence of defocus distance, compared to conventional imaging, the maximum single-pixel receiving power and echo-detection receiving power of asymmetric phase masks are reduced by about one and two orders of magnitude respectively. When exploring the influence of propagation distance, the maximum single-pixel receiving power of asymmetric phase masks decreases by about one order of magnitude and remains stable, and the echodetection receiving power gradually decreases with increasing propagation distance, until it approaches zero.

Study on three-dimensional numerical simulation of shell and tube heat exchanger of the surface ship under marine conditions

  • Yi Liao;Qi Cai;Shaopeng He;Mingjun Wang;Hongguang Xiao;Zili Gong;Cong Wang;Zhen Jia;Tangtao Feng;Suizheng Qiu
    • Nuclear Engineering and Technology
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    • v.55 no.4
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    • pp.1233-1243
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    • 2023
  • Shell-and-tube heat exchanger (STHX) is widely used by virtue of its simple structure and high reliability, especially in a space-constrained surface ship. For the STHX of the surface ship, roll, pitch and other motion of the ship will affect the heat transfer performance, resistance characteristics and structural strength of the heat exchanger. Therefore, it is urgent to carry out numerical simulation research on three-dimensional thermal hydraulic characteristics of surface ship STHX under the marine conditions. In this paper, the numerical simulation of marine shell and tube heat exchanger of surface ship was carried out using the porous media model. Firstly, the mathematical physical model and numerical method are validated based on the experimental data of a marine engine cooling water shell and tube heat exchanger. The simulation results are in good agreement with the experimental results. The prediction errors of pressure drop and heat transfer are less than 10% and 1% respectively. The effect of marine conditions on the heat transfer characteristics of the heat exchanger is investigated by introducing the additional force model of marine condition to evaluate the effect of different motion parameters on the heat transfer performance of the heat exchanger. This study could provide a reference for the optimization of marine heat exchanger design.

Soft computing based mathematical models for improved prediction of rock brittleness index

  • Abiodun I. Lawal;Minju Kim;Sangki Kwon
    • Geomechanics and Engineering
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    • v.33 no.3
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    • pp.279-289
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    • 2023
  • Brittleness index (BI) is an important property of rocks because it is a good index to predict rockburst. Due to its importance, several empirical and soft computing (SC) models have been proposed in the literature based on the punch penetration test (PPT) results. These models are very important as there is no clear-cut experimental means for measuring BI asides the PPT which is very costly and time consuming to perform. This study used a novel Multivariate Adaptive regression spline (MARS), M5P, and white-box ANN to predict the BI of rocks using the available data in the literature for an improved BI prediction. The rock density, uniaxial compressive strength (σc) and tensile strength (σt) were used as the input parameters into the models while the BI was the targeted output. The models were implemented in the MATLAB software. The results of the proposed models were compared with those from existing multilinear regression, linear and nonlinear particle swarm optimization (PSO) and genetic algorithm (GA) based models using similar datasets. The coefficient of determination (R2), adjusted R2 (Adj R2), root-mean squared error (RMSE) and mean absolute percentage error (MAPE) were the indices used for the comparison. The outcomes of the comparison revealed that the proposed ANN and MARS models performed better than the other models with R2 and Adj R2 values above 0.9 and least error values while the M5P gave similar performance to those of the existing models. Weight partitioning method was also used to examine the percentage contribution of model predictors to the predicted BI and tensile strength was found to have the highest influence on the predicted BI.

Prediction of skewness and kurtosis of pressure coefficients on a low-rise building by deep learning

  • Youqin Huang;Guanheng Ou;Jiyang Fu;Huifan Wu
    • Wind and Structures
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    • v.36 no.6
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    • pp.393-404
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    • 2023
  • Skewness and kurtosis are important higher-order statistics for simulating non-Gaussian wind pressure series on low-rise buildings, but their predictions are less studied in comparison with those of the low order statistics as mean and rms. The distribution gradients of skewness and kurtosis on roofs are evidently higher than those of mean and rms, which increases their prediction difficulty. The conventional artificial neural networks (ANNs) used for predicting mean and rms show unsatisfactory accuracy in predicting skewness and kurtosis owing to the limited capacity of shallow learning of ANNs. In this work, the deep neural networks (DNNs) model with the ability of deep learning is introduced to predict the skewness and kurtosis on a low-rise building. For obtaining the optimal generalization of the DNNs model, the hyper parameters are automatically determined by Bayesian Optimization (BO). Moreover, for providing a benchmark for future studies on predicting higher order statistics, the data sets for training and testing the DNNs model are extracted from the internationally open NIST-UWO database, and the prediction errors of all taps are comprehensively quantified by various error metrices. The results show that the prediction accuracy in this study is apparently better than that in the literature, since the correlation coefficient between the predicted and experimental results is 0.99 and 0.75 in this paper and the literature respectively. In the untrained cornering wind direction, the distributions of skewness and kurtosis are well captured by DNNs on the whole building including the roof corner with strong non-normality, and the correlation coefficients between the predicted and experimental results are 0.99 and 0.95 for skewness and kurtosis respectively.

An Adaptive Tuned Heave Plate (ATHP) for suppressing heave motion of floating platforms

  • Ruisheng Ma;Kaiming Bi;Haoran Zuo
    • Smart Structures and Systems
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    • v.31 no.3
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    • pp.283-299
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    • 2023
  • Structural stability of floating platforms has long since been a crucial issue in the field of marine engineering. Excessive motions would not only deteriorate the operating conditions but also seriously impact the safety, service life, and production efficiency. In recent decades, several control devices have been proposed to reduce unwanted motions, and an attractive one is the tuned heave plate (THP). However, the THP system may reduce or even lose its effectiveness when it is mistuned due to the shift of dominant wave frequency. In the present study, a novel adaptive tuned heave plate (ATHP) is proposed based on inerter by adjusting its inertance, which allows to overcome the limitation of the conventional THP and realize adaptations to the dominant wave frequencies in real time. Specifically, the analytical model of a representative semisubmersible platform (SSP) equipped with an ATHP is created, and the equations of motion are formulated accordingly. Two optimization strategies (i.e., J1 and J2 optimizations) are developed to determine the optimum design parameters of ATHP. The control effectiveness of the optimized ATHP is then examined in the frequency domain by comparing to those without control and controlled by the conventional THP. Moreover, parametric analyses are systematically performed to evaluate the influences of the pre-specified frequency ratio, damping ratio, heave plate sizes, peak periods and wave heights on the performance of ATHP. Furthermore, a Simulink model is also developed to examine the control performance of ATHP in the time domain. It is demonstrated that the proposed ATHP could adaptively adjust the optimum inertance-to-mass ratio by tracking the dominant wave frequencies in real time, and the proposed system shows better control performance than the conventional THP.

Estimation of Shear Strength of RC Shear Connection for the Steel-Concrete Composite Girder (강합성 거더용 철근콘크리트 전단연결체의 전단강도 평가)

  • Shin, Hyun Seop;You, Young Jun;Jeong, Youn Ju;Eom, In Su
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.30 no.3A
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    • pp.229-239
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    • 2010
  • For the purpose of improvement of the load carrying capacity and constructibility of the conventional steel-concrete composite girder through a effective appliance of the construction materials and optimization of the girder section, a new type section of composite girder and RC shear connection were proposed. In this study shear strength of the RC shear connection is estimated, and the characteristics of shear load-slip behaviour is analyzed. Push-out tests on shear specimens and FEM analysis with various design parameters are carried out, and results are analyzed. The results of test and FEM analysis showed that shear strength of RC shear connection is underestimated by the design provisions of the current design code. By regression analysis a empirical equation for the estimation of shear strength of RC shear connection is proposed.

Analytical study on cable shape and its lateral and vertical sags for earth-anchored suspension bridges with spatial cables

  • Gen-min Tian;Wen-ming Zhang;Jia-qi Chang;Zhao Liu
    • Structural Engineering and Mechanics
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    • v.87 no.3
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    • pp.255-272
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    • 2023
  • Spatial cable systems can provide more transverse stiffness and torsional stiffness without sacrificing the vertical bearing capacity compared with conventional vertical cable systems, which is quite lucrative for long-span earth-anchored suspension bridges' development. Higher economy highlights the importance of refined form-finding analysis. Meanwhile, the internal connection between the lateral and vertical sags has not yet been specified. Given this, an analytic algorithm of form-finding for the earth-anchored suspension bridge with spatial cables is proposed in this paper. Through the geometric compatibility condition and mechanical equilibrium condition, the expressions for cable segment, the recurrence relationship between catenary parameters and control equations of spatial cable are established. Additionally, the nonlinear general reduced gradient method is introduced into fast and high-precision numerical analysis. Furthermore, the analytic expression of the lateral and vertical sags is deduced and discussed. This is very significant for the space design above the bridge deck and the optimization of the sag-to-span ratio in the preliminary design stage of the bridge. Finally, the proposed method is verified with the aid of two examples, one being an operational self-anchored suspension bridge (with spatial cables and a 260 m main span), and the other being an earth-anchored suspension bridge under design (with spatial cables and a 500 m main span). The necessity of an iterative calculation for hanger tensions on earth-anchored suspension bridges is confirmed. It is further concluded that the main cable and their connected hangers are in very close inclined planes.

Battery thermal runaway cell detection using DBSCAN and statistical validation algorithms (DBSCAN과 통계적 검증 알고리즘을 사용한 배터리 열폭주 셀 탐지)

  • Jingeun Kim;Yourim Yoon
    • The Journal of the Convergence on Culture Technology
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    • v.9 no.5
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    • pp.569-582
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    • 2023
  • Lead-acid Battery is the oldest rechargeable battery system and has maintained its position in the rechargeable battery field. The battery causes thermal runaway for various reasons, which can lead to major accidents. Therefore, preventing thermal runaway is a key part of the battery management system. Recently, research is underway to categorize thermal runaway battery cells into machine learning. In this paper, we present a thermal runaway hazard cell detection and verification algorithm using DBSCAN and statistical method. An experiment was conducted to classify thermal runaway hazard cells using only the resistance values as measured by the Battery Management System (BMS). The results demonstrated the efficacy of the proposed algorithms in accurately classifying thermal runaway cells. Furthermore, the proposed algorithm was able to classify thermal runaway cells between thermal runaway hazard cells and cells containing noise. Additionally, the thermal runaway hazard cells were early detected through the optimization of DBSCAN parameters using a grid search approach.