• Earthquakes and Structures
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• v.8 no.1
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• pp.101-132
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• 2015

This research formulates a closed-form equation to predict a glass panel cracking failure drift for several curtain wall and storefront systems. An evaluation of the ASCE 7-10 equation for Dclear, which is the drift corresponding to glass-to-frame contact, shows that the kinematic modeling assumed for formulation of the equation is sound. The equation proposed in this paper builds on the ASCE equation and offers a revision of that equation to predict drift corresponding to cracking failure by considering glazing characteristics such as glass type, glass panel configuration, and system type. The formulation of the proposed equation and corresponding analyses with the ASCE equation is based on compiled experimental data of twenty-two different glass systems configurations tested over the past decade. A final comparative analysis between the ASCE equation and the proposed equation shows that the latter can predict the drift corresponding to glass cracking failure more accurately.

• Journal of the Korean Society of Industry Convergence
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• v.24 no.5
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• pp.573-579
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• 2021

In this study, flow analysis was performed on three types of strainers for ships with different flow rates to predict the pressure drop of the strainer due to the filter of strainer. In the case of flow analysis, the flow analysis was performed by applying the porous media method by applying the resistance value derived by Ergun's equation to the filter position. As a result of the analysis, it was found that when the dimensions of the strainer body were small, the influence of the flow rate on the pressure drop was large. In addition, the amount of pressure drop and the flow rate are almost linearly proportional, and an analysis formula that can predict the amount of pressure drop was derived. In order to predict the amount of pressure drop of the strainer when blockage exist in the strainer filter, the analysis was performed by introducing the resistance ratio to derive the prediction equation. Using this equation, it is thought that it will be possible to predict the performance of the strainer due to blockage in the future strainer design and field application.

• Bulletin of the Korean Chemical Society
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• v.25 no.8
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• pp.1165-1170
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• 2004

The applicability of the combined nearly ideal binary solvent/Redlich-Kister (CNIBS/R-K) equation for correlation of various solvatochromic parameters (SP) with composition is shown employing 84 experimental data sets for aqueous and organic binary solvent systems at temperatures ranging 15 to $75^{\circ}C$. The model provides a simple computational model to correlate/predict different SP values in various binary solvent systems. In proposed equations, $MPD_s$ (mean percentage deviations) are between 0.0500% and 6.9591% in mixtures of dimethyl sulfoxide with 2-methylpropan-2-ol and benzene with 2-methylpropan-2-ol, respectively. Correlation of the calculated and experimental values of various SP give an equation with an overall mean percentage deviation (OMPD) of 1.1900, $R^2$ = 0.99692, s.e = 0.01223 and F = 341925.51. Approximately 70% of the calculated SP values have IPD (individual percentage deviation) lower than one and it is possible to predict unmeasured SP values by using only eight experimental data.

• Steel and Composite Structures
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• v.35 no.3
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• pp.415-437
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• 2020

Circular concrete filled steel tube (CFST) columns have an advantage over all other sections when they are used in compression members. This paper proposes a new approach for deriving a new empirical equation to predict the axial compressive capacity of circular CFST columns using the Artificial Neural Network (ANN). The developed ANN model uses 5 input parameters that include the diameter of circular steel tube, the length of the column, the thickness of steel tube, the steel yield strength and the compressive strength of concrete. The only output parameter is the axial compressive capacity. Training and testing the developed ANN model was carried out using 219 available sets of data collected from the experimental results in the literature. An empirical equation is then proposed as an important result of this study, which is practically used to predict the axial compressive capacity of a circular CFST column. To evaluate the performance of the developed ANN model and the proposed equation, the predicted results are compared with those of the empirical equations stated in the current design codes and other models. It is shown that the proposed equation can predict the axial compressive capacity of circular CFST columns more accurately than other methods. This is confirmed by the high accuracy of a large number of existing test results. Finally, the parametric study result is analyzed for the proposed ANN equation to consider the effect of the input parameters on axial compressive strength.

• Asian-Australasian Journal of Animal Sciences
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• v.33 no.12
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• pp.2039-2049
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• 2020

Objective: This study was conducted to provide models to accurately predict nitrogen (N) and phosphorus (P) excretion of dairy cows on smallholder farms in Indonesia based on readily available farm data. Methods: The generic model in this study is based on the principles of the Lucas equation, describing the relation between dry matter intake (DMI) and faecal N excretion to predict the quantity of faecal N (Q_FN). Excretion of urinary N and faecal P were calculated based on National Research Council recommendations for dairy cows. A farm survey was conducted to collect input parameters for the models. The data set was used to calibrate the model to predict Q_FN for the specific case. The model was validated by comparing the predicted quantity of faecal N with the actual quantity of faecal N (Q_FNACT) based on measurements, and the calibrated model was compared to the Lucas equation. The models were used to predict N and P excretion of all 144 dairy cows in the data set. Results: Our estimate of true N digestibility equalled the standard value of 92% in the original Lucas equation, whereas our estimate of metabolic faecal N was -0.60 g/100 g DMI, with the standard value being -0.61 g/100 g DMI. Results of the model validation showed that the R² was 0.63, the MAE was 15 g/animal/d (17% from Q_FNACT), and the RMSE was 20 g/animal/d (22% from Q_FNACT). We predicted that the total N excretion of dairy cows in Indonesia was on average 197 g/animal/d, whereas P excretion was on average 56 g/animal/d. Conclusion: The proposed models can be used with reasonable accuracy to predict N and P excretion of dairy cattle on smallholder farms in Indonesia, which can contribute to improving manure management and reduce environmental issues related to nutrient losses.

• Proceedings of the Korean Geotechical Society Conference
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• 2008.03a
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• pp.644-655
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• 2008

Conventional hyperbolic model does not satisfactorily predict the overall stress-strain behaviors of various geomaterials. Tatsuoka and Shibuya(1992) suggest the generalized hyperbolic equation(GHE) considering strain dependency and calculated performance is in good agreement with precise triaxial compression test results of stress-strain relations over wide range of strains before peak stress condition in some cases, but GHE model also does not satisfactorily predict stress-strain relations as strain goes on state of peak stress in most cases. For improve a weak point of the GHE, in this study, modified form of generalized hyperbolic equation (MGHE model) is proposed which can predict highly nonlinear stress-strain behavior for various geomaterials from small strain to peak stress condition.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.20 no.10
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• pp.9-18
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• 2021

The cutting force in a cutting simulation is determined by the cutting conditions, such as cutting speed, feed rate, and depth of cut. The cutting force changes, depending on the material and cutting conditions, and is affected by the heat generated during cutting. The physical properties for predicting the cutting force use constitutive equations as functions of the hardening term, rate-hardening term, and thermal-softening term. To accurately predict the thermal properties, it is necessary to accurately predict the thermal-softening coefficient. In this study, the thermal-softening coefficient was determined, and the cutting force was predicted, using the response-surface method with the cutting conditions and the thermal-softening coefficient as factors.

• Journal of Animal Science and Technology
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• v.66 no.2
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• pp.374-386
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• 2024

To predict the apparent total tract digestibility (ATTD) of crude protein (CP) in dogs we developed an in vitro system using an in vitro digestion method and a statistical analysis. The experimental diets used chicken meat powder as the protein source, with CP levels of 20% (22.01%, analyzed CP value as dry-based), 30% (31.35%, analyzed CP value as dry-based), and 40% (41.34%, analyzed CP value as dry-based). To simulate in vivo digestive processes a static in vitro digestion was performed in two steps; stomach and small intestine. To analyze ATTD the total fecal samples were collected in eight neutered beagle dogs during the experimental period. CP digestibility was calculated by measuring CP levels in dog food, in vitro undigested fraction, and dog feces. In result, CP digestibility at both in vivo and in vitro was increased with increasing dietary CP levels. To estimate in vivo digestibility the co-relation of in vivo ATTD and in vitro digestibility was investigated statistically and a regression equation was developed to predict the CP ATTD (% = 2.5405 × in vitro CP digestibility (%) + + 151.8). The regression equation was evaluated its feasibility by using a commercial diet. The predicted CP digestibility which was calculated by the regression equation showed high index of similarity (100.16%) with that of in vivo in dogs. With that, it would be a feasible non-animal method to predict in vivo CP digestibility by using in vitro digestion method and the proposed linear regression equation in adult dogs.

• Journal of Biosystems Engineering
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• v.18 no.3
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• pp.220-229
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• 1993

A dimensional analysis was carried out to investigate if model agricultural radial tire can predict the tractive performance of prototype tires. Experimental data was analyzed to prove the results of dimensional analysis. The results was summerized as follows ; 1. When the model and prototype tires are tested under the same soil conditions, inflation pressure, slip and dynamic load, traction coefficient ratio between two tires depend on the geometry of two tires. 2. According to the regression analysis of the experimental data, traction equation parameters of the prototype tires can be predicted from the that of model tire 3. Predicted traction coefficient of prototype tire, calculated from the traction equation paramters, showed good correlation with that of experimental results. Thus it was possible to predict net and gross traction of prototype tire from the model traction equation parameters.

• Transactions of the Korean Society of Mechanical Engineers
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• v.19 no.2
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• pp.580-590
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• 1995

To design and develop a turbocharged engine, ti needs that many study must be preceded about the characteristics of engine performance. Especially, a basic data about deciding target power is urgently needed for which is practically useful for engine design. The power output of turbo-charged engine is dominated by engine speed, displacement, compression ratio, air fuel ratio and charge pressure ratio. Therefore, the independent effect of these factors on power output was clarified from experiment, and the experimental equation to predict the power was founded from there results. The predicted power output from the experimental equation was well coincided with power measured through experiment.