• Computers and Concrete
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• 제12권4호
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• pp.377-392
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• 2013

This paper investigates prediction models estimating the hydration properties of concrete, such as the compressive strength, the splitting tensile strength, the elastic modulus,and the autogenous shrinkage. A prediction model is suggested on the basis of an equation that is formulated to predict the compressive strength. Based on the assumption that the apparent activation energy is a characteristic property of concrete, a prediction model for the compressive strength is applied to hydration-related properties. The hydration properties predicted by the model are compared with experimental results, and it is concluded that the prediction model properly estimates the splitting tensile strength, elastic modulus, and autogenous shrinkage as well as the compressive strength of concrete.

• Structural Monitoring and Maintenance
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• 제10권2호
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• pp.175-190
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• 2023

This article aims to quantitatively predict the snowmelt in extreme cold regions, considering a combination of grayscale and neural models. The traditional non-equidistant GM(1,1) prediction model is optimized by adjusting the time-distance weight matrix, optimizing the background value of the differential equation and optimizing the initial value of the model, and using the BP neural network for the first. The adjusted ice forecast model has an accuracy of 0.984 and posterior variance and the average forecast error value is 1.46%. Compared with the GM(1,1) and BP network models, the accuracy of the prediction results has been significantly improved, and the quantitative prediction of the ice sheet is more accurate. The monitoring and maintenance of the structure by quantitative prediction model by gray models was clearly demonstrated in the model.

• 한국식품과학회지
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• 제20권2호
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• pp.280-286
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• 1988

이상과 같이, 기존 data의 정확도에 대한 고찰과 본 연구에서 소개한 단순한 해석적 방법에 의한 식품의 동결 시간예측 model로서, 실제 측정한 시료별 실험치와 기존 model을 비교 검토하였다. 기 발표된 lean beef등 109개의 data중, Hung & Thompson의 data는 Nagaoka 및 Pham의 model에, Cleland & Earle의 data는 Hung $ Thompson의 model에 매우 접근함을 볼 수 있으며, 시료별로 살펴볼 때, tylose등 5품목의 시료는 Nagaoka 및 Pham의 model에 잘 적용됨을 알 수 있다. 그러나 본 실험에서 사용한 pine mushroom등 4품목은 Cleland & Earle, Hung & Tompson 및 Pham의 model에 잘 부합되며, 제안된 model의 간편성과 정확도에 있어서도 단지 3가지의 실험적 매개변수와 7가지의 물성치 만으로 실험치와 비교한 결과, 공학적 최소오차 범위인 ${\pm}10%$ 이내로 나타났다.

• 설비공학논문집
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• 제28권12호
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• pp.467-476
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• 2016

As the energy saving issues become one of the important global agenda, the building simulation method is generally used to predict the inside energy usage to establish the power-saving strategies. To foretell an accurate energy usage of a building, proper and typical weather data are needed. For this reason, typical weather data are fundamental in building energy simulations and among the meteorological factors, the solar irradiation is the most important element. Therefore, preparing solar irradiation is a basic factor. However, there are few places where the horizontal solar radiation in domestic weather stations can be measured, so the prediction of the solar radiation is needed to arrive at typical weather data. In this paper, four solar radiation prediction models were analyzed in terms of their applicability for domestic weather conditions. A total of 12 regions were analyzed to compare the differences of solar irradiation between measurements and the prediction results. The applicability of the solar irradiation prediction model for a certain region was determined by the comparisons. The results were that the Zhang and Huang model showed the highest accuracy (Rad 0.87~0.80) in most of the analyzed regions. The Kasten model which utilizes a simple regression equation exhibited the second-highest accuracy. The Angstrom-Prescott model is easily used, also by employing a plain regression equation Lastly, the Winslow model which is known for predicting global horizontal solar irradiation at any climate regions uses a daily integration equation and showed a low accuracy regarding the domestic climate conditions in Korea.

• Journal of Biosystems Engineering
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• 제15권1호
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• pp.44-51
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• 1990

Four models in current use for cereal grain drying, equilibrium model, Morey model, partial differential equation model and simplified partial differential equation model, were modified to be suitable for natural air drying of barley. The predicted by the four models and experimental results were compared. Three models except equilibrium model predicted moisture comtent and grain temperature very well. But equilibrium model overpredicted moisture content and grain temperature of bottom layer. The degree of prediction of the four models for relative humidities of exhaust air didn't differ much from one another and equally the four models predicted relative humidity statisfatorily. Morey model took much shorter computing time than any other models. Therefore, considering the degree of prediction and computing time Morey model was the most suitable for natural air drying of barley.

• Geomechanics and Engineering
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• 제29권5호
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• pp.523-533
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• 2022

Several prediction model of penetration rate (PR) of tunnel boring machines (TBMs) have been focused on applying to design stage. In construction stage, however, the expected PR and its trends are changed during tunneling owing to TBM excavation skills and the gap between the investigated and actual geological conditions. Monitoring the PR during tunneling is crucial to rescheduling the excavation plan in real-time. This study proposes a sequential prediction method applicable in the construction stage. Geological and TBM operating data are collected from Gunpo cable tunnel in Korea, and preprocessed through normalization and augmentation. The results show that the sequential prediction for 1 ring unit prediction distance (UPD) is R²≥0.79; whereas, a one-step prediction is R²≤0.30. In modeling algorithm, a gradient boosted regression tree (GBRT) outperformed a least square-based linear regression in sequential prediction method. For practical use, a simple equation between the R² and UPD is proposed. When UPD increases R² decreases exponentially; In particular, UPD at R²=0.60 is calculated as 28 rings using the equation. Such a time interval will provide enough time for decision-making. Evidently, the UPD can be adjusted depending on other project and the R² value targeted by an operator. Therefore, a calculation process for the equation between the R² and UPD is addressed.

• 한국해양공학회지
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• 제15권2호
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• pp.6-10
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• 2001

Water waves propagate over irregular bottom bathymetry are transformed by refraction, diffraction, shoaling, reflection etc. Principal factor of wave transform is bottom bathymetry, but in case of current field, current is another important factor which effect wave transformation. The governing equation of this study is develope as wave-current equation type to investigate the effect of wave-current interaction. It starts from Berkhoff's(1972) mild slope equation and is transformed to time-dependent hyperbolic type equation by using variational principal. Finally the governing equation is shown as a parabolic type equation by splitting method. This wave-current model was applied to the kwangan beach which is located at Pusan. The numerical simulation results of this model show the characteristics of wave transformation and flow pattern around the Kwangan beach fairly well.

• 한국소성가공학회:학술대회논문집
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• 한국소성가공학회 2006년도 제5회 박판성형 SYMPOSIUM
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• pp.55-60
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• 2006

Draw-bead is applied to control the material flow in a stamping process and improve the product quality by controlling the draw-bead restraining force (DBRF). Actual die design depends mostly on the trial-and-error method without calculating the optimum DBRF. Die design with the predicted value of DBRF can be utilized at the tryout stage effectively reducing the cost of the product development. For the prediction of DBRF, a simulation-based prediction model of the circular draw-bead is developed using the Box-Behnken design with selected shape parameters such as the bead height, the shoulder radius and the sheet thickness. The value of DBRF obtained from each design case by analysis is approximated by a second order regression equation. This equation can be utilized to the calculation of the restraining force and the determination of the draw-bead shape as a prediction model. For the evaluation of the prediction model, the optimum design of DBRF in sheet metal forming is carried out using response surface methodology. The suitable type of the draw-bead is suggested based on the optimum values of DBRF. The prediction model of the circular draw-bead proposes the design method of the draw-bead shape. The present procedure provides a guideline in the tool design stage for sheet metal forming to reduce the cost of the product development.

• 대한기계학회논문집B
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• 제20권1호
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• pp.304-320
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• 1996

A multiple production .epsilon. equation model was developed in the low Reynolds number $\kappa$-$\varepsilon$ model with the aids of DNS data. We derived the model theoretically and avoided the use of empirical correlations as much as possible in order for the model to have generality in the prediction of complex turbulent flow. Unavoidable model constants were, however, optimized with the aids of DNS data. All the production and dissipation models in the $\varepsilon$ equation were modified with damping functions to satisfy the wall limiting behavior. A new $f_{\mu}$ function, turbulent diffusion and pressure diffusion model for the k and .epsilon. equations were also proposed to satisfy the wall limiting behavior. By, computational investigation on the plane channel flows, we found that the multiple production model for .epsilon. equation could improve the near wall turbulence behavior compared with the standard production model without the complicated empirical modification. Satisfication of the wall limiting conditions for each turbulence model term was found to be most important for the accurate prediction of near wall turbulence behaviors.

• Asian-Australasian Journal of Animal Sciences
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• 제29권9호
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• pp.1215-1221
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• 2016

The prediction of carcass composition in Hanwoo steers is very important for value-based marketing, and the improvement of prediction accuracy and precision can be achieved through the analyses of independent variables using a prediction equation with a sufficient dataset. The present study was conducted to develop a prediction equation for Hanwoo carcass composition for which data was collected from 7,907 Hanwoo steers raised at a private farm in Gangwon Province, South Korea, and slaughtered in the period between January 2009 and September 2014. Carcass traits such as carcass weight (CWT), back fat thickness (BFT), eye-muscle area (EMA), and marbling score (MAR) were used as independent variables for the development of a prediction equation for carcass composition, such as retail cut weight and percentage (RC, and %RC, respectively), trimmed fat weight and percentage (FAT, and %FAT, respectively), and separated bone weight and percentage (BONE, and %BONE), and its feasibility for practical use was evaluated using the estimated retail yield percentage (ELP) currently used in Korea. The equations were functions of all the variables, and the significance was estimated via stepwise regression analyses. Further, the model equations were verified by means of the residual standard deviation and the coefficient of determination ($R^2$) between the predicted and observed values. As the results of stepwise analyses, CWT was the most important single variable in the equation for RC and FAT, and BFT was the most important variable for the equation of %RC and %FAT. The precision and accuracy of three variable equation consisting CWT, BFT, and EMA were very similar to those of four variable equation that included all for independent variables (CWT, BFT, EMA, and MAR) in RC and FAT, while the three variable equations provided a more accurate prediction for %RC. Consequently, the three-variable equation might be more appropriate for practical use than the four-variable equation based on its easy and cost-effective measurement. However, a relatively high average difference for the ELP in absolute value implies a revision of the official equation may be required, although the current official equation for predicting RC with three variables is still valid.