• Title/Summary/Keyword: Prediction density

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Prediction of steel corrosion in magnesium cement concrete based on two dimensional Copula function

  • Feng, Qiong;Qiao, Hongxia;Wang, Penghui;Gong, Wei
    • Computers and Concrete
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    • v.21 no.2
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    • pp.181-187
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    • 2018
  • In order to solve the life prediction problem of damaged coating steel bar in magnesium cement concrete, this study tries to establish the marginal distribution function by using the corrosion current density as a single degradation factor. Representing the degree of steel corrosion, the corrosion current density were tested in electrochemical workstation. Then based on the Copula function, the joint distribution function of the damaged coating was established. Therefore, it is indicated that the corrosion current density of the bare steel and coated steel bar can be used as the boundary element to establish the marginal distribution function. By using the Frank-Copula function of Copula Archimedean function family, the joint distribution function of the damaged coating steel bar was successfully established. Finally, the life of the damaged coating steel bar has been lost in 7320d. As a new method for the corrosion of steel bar under the multi-dimensional factors, the two-dimensional Copula function has certain practical significance by putting forward some new ideas.

Nonuniformity of Conditioning Density According to CMP Conditioning System Design Variables Using Artificial Neural Network (인공신경망을 활용한 CMP 컨디셔닝 시스템 설계 변수에 따른 컨디셔닝 밀도의 불균일도 분석)

  • Park, Byeonghun;Lee, Hyunseop
    • Tribology and Lubricants
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    • v.38 no.4
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    • pp.152-161
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    • 2022
  • Chemical mechanical planarization (CMP) is a technology that planarizes the surfaces of semiconductor devices using chemical reaction and mechanical material removal, and it is an essential process in manufacturing highly integrated semiconductors. In the CMP process, a conditioning process using a diamond conditioner is applied to remove by-products generated during processing and ensure the surface roughness of the CMP pad. In previous studies, prediction of pad wear by CMP conditioning has depended on numerical analysis studies based on mathematical simulation. In this study, using an artificial neural network, the ratio of conditioner coverage to the distance between centers in the conditioning system is input, and the average conditioning density, standard deviation, nonuniformity (NU), and conditioning density distribution are trained as targets. The result of training seems to predict the target data well, although the average conditioning density, standard deviation, and NU in the contact area of wafer and pad and all areas of the pad have some errors. In addition, in the case of NU, the prediction calculated from the training results of the average conditioning density and standard deviation can reduce the error of training compared with the results predicted through training. The results of training on the conditioning density profile generally follow the target data well, confirming that the shape of the conditioning density profile can be predicted.

Low Cycle Fatigue Life Assessment of Alloy 617 Weldments at 900℃ by Coffin-Manson and Strain Energy Density-Based Models

  • Rando, Tungga Dewa;Kim, Seon-Jin
    • Journal of Power System Engineering
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    • v.21 no.1
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    • pp.43-49
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    • 2017
  • This work aims to investigate on the low cycle fatigue life assessment, which is adopted on the strain-life relationship, or better known as the Coffin-Manson relationship, and also the strain energy density-based model. The low cycle fatigue test results of Alloy 617 weldments under $900^{\circ}C$ have been statistically estimated through the Coffin-Manson relationship according to the provided strain profile. In addition, the strain energy density-based model is proposed to represent the energy dissipated per cycle as fatigue damage parameter. Based on the results, Alloy 617 weldments followed the Coffin-Manson relationship and strain energy density-based model well, and they were compatible with the experimental data. The predicted lives based on these two proposed models were examined with the experimental data to select a proper life prediction parameter.

Study on the Relationship between the Forest Canopy Closure and Hyperspectral Signatures

  • Lin, Chinsu;Chang, Chein-I
    • Proceedings of the KSRS Conference
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    • 2003.11a
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    • pp.72-74
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    • 2003
  • Forest canopy density is an ideal representative of the forest habitat situations. It can directly or indirectly depict the canopy structure and gap size in the forestland, thus could be applied to assessment of wildlife’s diversit y. Since population survey of vegetation and wildlife diversities is a key issue for sustainable forest ecosystem management, many research efforts have been focused on forest canopy density using multispectral data in the last two decades. Unfortunately, prediction of canopy density using large scaling remote sensing data remains a challenging issue. Due to recent advances in hyperspectral image sensors hyperspectral imagery is now available for environmental monitoring. In this paper, we conduct experiments to monitor complicated environments of forestland that can be captured by using hyperspectral imagery and further be analyzed to test a prediction model of forest canopy density. The results show that 95% of canopy density could be well described by using 2 difference vegetation indices (DVIs), which are difference of blue and green reflectances rband_100-rband_150 and difference of 2 short wave infrared reflectancse rband_406-rband_410 With the wavelengths of band no. 100, 150, 406, and 410 specified by 462.39 nm, 534.40 nm, 918.22 nm and 924.41 nm respectively.

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Prediction Intervals for Proportional Hazard Rate Models Based on Progressively Type II Censored Samples

  • Asgharzadeh, A.;Valiollahi, R.
    • Communications for Statistical Applications and Methods
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    • v.17 no.1
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    • pp.99-106
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    • 2010
  • In this paper, we present two methods for obtaining prediction intervals for the times to failure of units censored in multiple stages in a progressively censored sample from proportional hazard rate models. A numerical example and a Monte Carlo simulation study are presented to illustrate the prediction methods.

Estimation of lightweight aggregate concrete characteristics using a novel stacking ensemble approach

  • Kaloop, Mosbeh R.;Bardhan, Abidhan;Hu, Jong Wan;Abd-Elrahman, Mohamed
    • Advances in nano research
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    • v.13 no.5
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    • pp.499-512
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    • 2022
  • This study investigates the efficiency of ensemble machine learning for predicting the lightweight-aggregate concrete (LWC) characteristics. A stacking ensemble (STEN) approach was proposed to estimate the dry density (DD) and 28 days compressive strength (Fc-28) of LWC using two meta-models called random forest regressor (RFR) and extra tree regressor (ETR), and two novel ensemble models called STEN-RFR and STEN-ETR, were constructed. Four standalone machine learning models including artificial neural network, gradient boosting regression, K neighbor regression, and support vector regression were used to compare the performance of the proposed models. For this purpose, a sum of 140 LWC mixtures with 21 influencing parameters for producing LWC with a density less than 1000 kg/m3, were used. Based on the experimental results with multiple performance criteria, it can be concluded that the proposed STEN-ETR model can be used to estimate the DD and Fc-28 of LWC. Moreover, the STEN-ETR approach was found to be a significant technique in prediction DD and Fc-28 of LWC with minimal prediction error. In the validation phase, the accuracy of the proposed STEN-ETR model in predicting DD and Fc-28 was found to be 96.79% and 81.50%, respectively. In addition, the significance of cement, water-cement ratio, silica fume, and aggregate with expanded glass variables is efficient in modeling DD and Fc-28 of LWC.

Study on the Power Performance on WindPRO Prediction in the Southeast Region of Jeju Island (제주 남동부 지역을 대상으로 한 WindPRO의 발전량 예측에 관한 연구)

  • Hyun, Seunggun;Kim, Keonhoon;Huh, Jongchul
    • 한국신재생에너지학회:학술대회논문집
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    • 2010.06a
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    • pp.184.1-184.1
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    • 2010
  • In order to research the way to evaluate wind resource without actual Met Mast data, this paper has been carried out on the southeastern region of Jeju island, Korea. Although wind turbine has been an economical alternative energy resource, misjudging the prediction of lifetime or payback period occurs because of the inaccurate assessment of wind resource and the location of wind turbine. Using WindPRO(Ver. 2.7), a software for wind farm design developed by EMD from Denmark, wind resources for the southeastern region of Jeju island was analyzed, and the performance of WindPRO prediction was evaluated in detail. Met Mast data in Su-san 5.5Km far from Samdal wind farm, AWS in Sung-san 4.5km far from Samdal wind farm, and Korea Wind Map data had been collected for this work.

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Influence of Exchange-Correlation Functional in the Calculations of Vertical Excitation Energies of Halogenated Copper Phthalocyanines using Time-Dependent Density Functional Theory (TD-DFT)

  • Lee, Sang Uck
    • Bulletin of the Korean Chemical Society
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    • v.34 no.8
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    • pp.2276-2280
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    • 2013
  • The accurate prediction of vertical excitation energies is very important for the development of new materials in the dye and pigment industry. A time-dependent density functional theory (TD-DFT) approach coupled with 22 different exchange-correlation functionals was used for the prediction of vertical excitation energies in the halogenated copper phthalocyanine molecules in order to find the most appropriate functional and to determine the accuracy of the prediction of the absorption wavelength and observed spectral shifts. Among the tested functional, B3LYP functional provides much more accurate vertical excitation energies and UV-vis spectra. Our results clearly provide a benchmark calibration of the TD-DFT method for phthalocyanine based dyes and pigments used in industry.

Prediction Model on Electrical Conductivity of High Density Metallic Plasma (고밀도 금속 플라즈마 전기전도도 예측모델)

  • Kyoungjin Kim
    • Journal of the Korean Society of Propulsion Engineers
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    • v.26 no.6
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    • pp.1-9
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    • 2022
  • This study introduces the calculation model of ionization composition and electrical conductivity for metallic plasma for practical application to modeling and simulation of modern electrical detonators. The present model includes the correction for non-ideality of dense plasma conditions which are expected in electrical explosion of bridge in detonators. The computational results for copper plasma show favorable agreement with experimental data for a wide range of plasma temperature and high density conditions and the model is proper for detonator modeling with good prediction accuracy.

Fatigue Strength Assessment of Spot-Welded Lap Joint Using Strain Energy Density Factor

  • Sohn, Ilseon;Bae, Dongho
    • Journal of Mechanical Science and Technology
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    • v.15 no.1
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    • pp.44-51
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    • 2001
  • One of the recent issues in design of the spot-welded structure such as the automobile body is to develop an economical prediction method of the fatigue design criterion without additional fatigue test. In this paper, as one of basic investigation for developing such methods, fracture mechanical approach was investigated. First, the Model I, Mode II and Mode III, stress intensity factors were analyzed. Second, strain energy density factor (S) synthetically including them was calculated. And finally, in order to decide the systematic fatigue design criterion by using this strain energy density factor, fatigue data of the ΔP-N(sub)f obtained on the various in-plane bending type spot-welded lap joints were systematically re-arranged in the ΔS-N(sub)f relation. And its utility and reliability were verified by the theory of Weibull probability distribution function. The reliability of the proposed fatigue life prediction value at 10(sup)7 cycles by the strain energy density factor was estimated by 85%. Therefore, it is possible to decide the fatigue design criterion of spot-welded lap joint instead of the ΔP-N(sub)f relation.

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