• Computers and Concrete
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• v.24 no.4
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• pp.295-302
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• 2019

Evolutionary algorithms based on conventional statistical methods such as regression and classification have been widely used in data mining applications. This work involves application of gene expression programming (GEP) for predicting compressive strength of fly ash geopolymer concrete, which is gaining increasing interest as an environmentally friendly alternative of Portland cement concrete. Based on 56 test results from the existing literature, a model was obtained relating the compressive strength of fly ash geopolymer concrete with the significantly influencing mix design parameters. The predictions of the model in training and validation were evaluated. The coefficient of determination ($R^2$), mean (${\mu}$) and standard deviation (${\sigma}$) were 0.89, 1.0 and 0.12 respectively, for the training set, and 0.89, 0.99 and 0.13 respectively, for the validation set. The error of prediction by the model was also evaluated and found to be very low. This indicates that the predictions of GEP model are in close agreement with the experimental results suggesting this as a promising method for compressive strength prediction of fly ash geopolymer concrete.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.4
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• pp.1232-1245
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• 2021

In this study, prediction of product sales as they relate to changes in temperature is proposed. This model uses long short-term memory (LSTM), which has shown excellent performance for time series predictions. For verification of the proposed sales prediction model, the sales of short pants, flip-flop sandals, and winter outerwear are predicted based on changes in temperature and time series sales data for clothing products collected from 2015 to 2019 (a total of 1,865 days). The sales predictions using the proposed model show increases in the sale of shorts and flip-flops as the temperature rises (a pattern similar to actual sales), while the sale of winter outerwear increases as the temperature decreases.

• Geomechanics and Engineering
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• v.8 no.4
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• pp.559-594
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• 2015

A nonlinear creep function incorporated into the elastic visco-plastic model may describe the long-term soil deformation more accurately. However, by applying the conventional procedure, there are challenges to determine the model parameters due to limitation of suitable data points. This paper presents a numerical solution to obtain several parameters simultaneously for a nonlinear elastic visco-plastic (EVP) model using the available consolidation data. The finite difference scheme using the Crank-Nicolson procedure is applied to solve a set of coupled partial differential equations of the time dependent strain and pore water pressure dissipation. The model parameters are determined by applying the algorithm of trust-region reflective optimisation in conjunction with the finite difference solution. The proposed method utilises all available consolidation data during dissipation of the excess pore water pressure to determine the required model parameters. Moreover, the reference time in the elastic visco-plastic model can readily be adopted as a unit of time; denoting creep is included in the numerical predictions explicitly from the very first time steps. In this paper, the settlement predictions of thick soft clay layers are presented and discussed to evaluate and compare the accuracy and reliability of the proposed method against the graphical procedure to obtain the model parameters. In addition, comparison of the available experimental results to the numerical predictions confirms the accuracy of the numerical procedure.

• Transactions of the Korean Society of Mechanical Engineers
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• v.18 no.2
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• pp.432-445
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• 1994

From a theoretical analysis point of view, the 2-stage precipitator is decomposed into two units: charging cell and collecting cell. Collection efficiency predictions of the two-stage parallel-plate electrostatic precipitator have been performed theoretically incorporating with the charging and the collecting cells. Particle trajectorise passing the charging cell have been modeled as a simple one. Particle charge distribution at the outlet of the charging cell is calculated through integration of the present unipolar combined charging rate along the entire particle trajectory, and average charge of particles at the outlet of the charging cell is obtained from the particle charge distribution. As for the collecting cell, the diminution of particle concentration along the longitudinal direction of the collecting cell is investigated considering the conventional Deutsch's theory and the laminar theory. One should note that the collection efficiency formula derived is based on monodisperse aerosols. It has been confirmed through the analysis that predictions of particle charge by applying White's unipolar diffusion charging theory overpredict actual cases in the continuum regime, while predictions by Fuch's unipolar diffusion charging theory indicate the reasonable result in the same regime. Theoretical predictions of collection efficiency are also compared with the available experimental results. Comparisons show that the experimental results are consistently located in the collection efficiency region bounded by the two limits, the Deutsch and the laminar collection efficiencies. Finally design parameters of the 2-stage electrostatic precipitator have been investigated systematically through the one-variable-at-a-time method in terms of collection efficiency. Applied voltages on the corona wire of the charging cell and the plate of the collecting cell, and the average air velocity have been selected as the design parameters.

• Computers and Concrete
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• v.34 no.1
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• pp.1-14
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• 2024

The design of disturbed regions in reinforced concrete structures usually applies the well known Strut and Tie Method (STM). As an alternative, the Stringer-Panel Method (SPM), an intermediate model between STM and the Finite Element Method (FEM), consists in dividing a structure into two distinct elements: the stringers (which carry axial forces) and panels (which carry shear forces). SPM has already showed good applicability in manual calculations and computer implementations, and its most known application was SPanCAD, an AutoCAD plugin for linear and nonlinear analysis by SPM. Unfortunately, SPanCAD was discontinued by the developers, and it's not compatible with the most recent versions of AutoCAD. So, this paper aims to present a computer program that was developed as an upgrade to the latter: the Stringer Panel Modelling Tool (SPMTool), which is intended to be an auxiliary design tool and it presents improvements, in comparison to SPanCAD. It is possible to execute linear and nonlinear analysis by three distinct formulations: Modified Compression Field Theory (MCFT), Disturbed Stress Field Model (DSFM) and Softened Membrane Model (SMM). The nonlinear results were compared to experimental data of reinforced concrete elements that were not designed by SPM; these elements were also analyzed in SPanCAD. On overall, SPMTool made more realistic predictions to the behavior of the analyzed structures than SPanCAD. Except for DSFM predictions for corbels (1.24), in overall average, the ultimate load predictions were conservative (0.85 to 0.98), which is a good aspect for a design tool. On the other hand, the cracking load predictions presented overestimations (1.06 to 1.47) and higher variations (25.59% to 34.25%) and the post-cracking behavior could not be accurately predicted; for this use case, a more robust finite element software is recommended.

• Tribology and Lubricants
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• v.35 no.5
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• pp.300-309
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• 2019

Gas foil thrust bearings (GFTBs) support axial loads in oil-free, high speed rotating machinery using air or gas as a lubricant. Due to the inherent low viscosity of the lubricant, GFTBs often have super-laminar flows in the film region at operating conditions with high Reynolds numbers. This paper develops a mathematical model of a GFTB with turbulent flows and validates the model predictions against those from the literature. The pressure distribution, film thickness distribution, load carrying capacity, and power loss are predicted for both laminar and turbulent flow models and compared with each other. Predictions for an air lubricant show that the GFTB has high Reynolds numbers at the leading edge where the film thickness is large and relatively low Reynolds numbers at the trailing edge. The predicted load capacity and power loss for the turbulent flow model show little difference from those for the laminar flow model even at the highest speed of 100 krpm, because the Reynolds numbers are smaller than the critical Reynolds number. On the other hand, refrigerant (R-134a) lubricant, which has a higher density than air, had significant differences due to high Reynolds numbers in the film region, in particular, near the leading and outer edges. The predicted load capacity and power loss for the turbulent flow model are 2.1 and 2.3 times larger, respectively, than those for the laminar flow model, thus implying that the turbulent flow greatly affects the performance of the GFTB.

• Journal of Korean Association for Spatial Structures
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• v.15 no.1
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• pp.75-84
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• 2015

This paper presents the dimensionless wall distance, y+ effect on SST turbulent model for wind turbine blade. The National Renewable Energy Laboratory (NREL) Phase VI wind turbine was used for the study, which the wind tunnel and structural test data has publicly available. The near wall treatment and turbulent characteristics have important role for proper CFD simulation. Most of the CFD development in this area is focused on advanced turbulence model closures including second moment closure models, and so called Low-Reynolds (low-Re) number and two-layer turbulence models. However, in many cases CFD aerodynamic predictions based on these standard models still show a large degree of uncertainty, which can be attributed to the use of the $\epsilon$-equation as the turbulence scale equation and the associated limitations of the near wall treatment. The present paper demonstrates the y+ definition effect on SST (Shear Stress Transport) turbulent model with advanced automatic near wall treatment model and Gamma theta transitional model for transition from lamina to turbulent flow using commercial ANSYS-CFX. In all cases the SST model shows to be superior, as it gives more accurate predictions and is less sensitive to grid variations.

• Structural Engineering and Mechanics
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• v.9 no.4
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• pp.323-338
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• 2000

An analytical approach for the prediction of the behaviour of steel-fiber reinforced concrete beams subjected to torsion is described. The analysis method employs a special stress-strain model with a non-linear post cracking branch for the material behaviour in tension. Predictions of this model for the behaviour of steel-fiber concrete in direct tension are also presented and compared with results from tests conducted for this reason. Further in this work, the validation of the proposed torsional analysis by providing comparisons between experimental curves and analytical predictions, is attempted. For this purpose a series of 10 steel-fiber concrete beams with various cross-sections and steel-fiber volume fractions tested in pure torsion, are reported here. Furthermore, experimental information compiled from works around the world are also used in an attempt to establish the validity of the described approach based on test results of a broad range of studies. From these comparisons it is demonstrated that the proposed analysis describes well the behaviour of steel-fiber concrete in pure torsion even in the case of elements with non-rectangular cross-sections.

• Proceedings of the Korean Society for Bioinformatics Conference
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• 2005.09a
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• pp.167-172
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• 2005

This paper introduces a method which improves the performance of the identification of splice sites in the genomic DNA sequence of eukaryotes. This method combines a low order Markov model in series with a neural network for the predictions of splice sites. The lower order Markov model incorporates the biological knowledge surrounding the splice sites as probabilistic parameters. The Neural network takes the Markov encoded parameters as the inputs and produces the prediction. Two types of neural networks are used for the comparison. This method reduces the computational complexity and shows encouraging accuracy in the predictions of splice sites when applied to several standard splice site dataset.

• Nuclear Engineering and Technology
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• v.29 no.2
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• pp.158-166
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• 1997

Integrated performance test of Chemical and Volume Control System was successfully performed in 1994. However, an extensive effort to correct hardware and software problems in the letdown line was required mainly due to the lack of adequate simulation code to predict the test accurately. Although the LTC computer code was used during the YGN 3'||'&'||'4 NSSS design process, the code can not satisfactorily predict the test due to it insufficient letdown line modeling. This study developed a numerical model to simulate the letdown test by modifying the current LTC code, and then verified the model by comparing with the test data. The comparison shows that the modified LTC computer code can predict the transient behavior of letdown system lese very well. Especially, the model was verified to be able to predict the "Stiction (composition of stick and friction)" phenomena which caused instantaneous fluctuations in the letdown backpressure and flowrate. Therefore, it is concluded that the modified LTC computer code with the ability of calculating the "Stiction" phenomena will be very useful for future plant design and test predictions.predictions.