• Computers and Concrete
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• v.10 no.6
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• pp.557-573
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• 2012

This paper discusses the combined application of two different techniques, Neural Networks (NN) and Principal Component Analysis (PCA), for improved prediction of concrete properties. The combination of these approaches allowed the development of six neural networks models for predicting slump and compressive strength of concrete with mineral additives such as blast furnace slag, fly ash and silica fume. The Back-Propagation Multi-Layer Perceptron (BPMLP) with Bayesian regularization was used in all these models. They are produced to implement the complex nonlinear relationship between the inputs and the output of the network. They are also established through the incorporation of a huge experimental database on concrete organized in the form Mix-Property. Thus, the data comprising the concrete mixtures are much correlated to each others. The PCA is proposed for the compression and the elimination of the correlation between these data. After applying the PCA, the uncorrelated data were used to train the six models. The predictive results of these models were compared with the actual experimental trials. The results showed that the elimination of the correlation between the input parameters using PCA improved the predictive generalisation performance models with smaller architectures and dimensionality reduction. This study showed also that using the developed models for numerical investigations on the parameters affecting the properties of concrete is promising.

• Journal of Biomedical Engineering Research
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• v.27 no.6
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• pp.370-375
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• 2006

The purpose of this work is to predict the systolic blood pressure (BP) during exercise from pulse transit time (PTT) for warning of possible danger. PTT was calculated as the time between R-peak of ECG and the peak of differential photoplethysmograph (PPG). For the PTT-BP model, we used regress equations from previous studies and 3 kinds of new models combining linear and nonlinear regress equation. The model parameters were estimated with the data measured under low to middle intensity exercise, and then was tested with the data measured under high intensity exercise. Predicted BP values after high intensity exercise were compared with those measured by cuff-type sphygmomanometer. The results showed that the error between measured and predicted values were acceptable for the monitoring BP. We tested PTT-BP models 1 month after the identification without further calibration. Models could predict the BP and the errors between measured and predicted BP were about 5mmHg. The suggested system is expected to be helpful in recognizing any danger during exercise.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.49 no.1
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• pp.37-42
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• 2000

The radio noise produced by corona discharge in high voltage transmission lines is one of the most important line design considerations. Therefore it is necessary for transmission line designers to pre-evaluate radio noise using prediction formulas or field test results. In this paper, more accurate and useful formulas for predicting radio noise during fair and foul weathers in high voltage AC transmission lines were proposed through comparison with the existing formulas. Also it was verified by comparing with the long-term measured data from operating lines that the proposed formulas are more accurate. The proposed prediction formulas are developed by the applications of nonlinear least squares optimization method to radio noise database collected from lines throughout the world.

• Proceedings of the Korean Geotechical Society Conference
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• 2010.03a
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• pp.369-378
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• 2010

In this study, a computer program to predict the behavior of laterally loaded single pile and pile groups was developed by using a beam-column analysis in which the soils are modeled as nonlinear springs by a family of p-y curves for subgrade modulus. The special attention was given to the lateral displacement of a single pile and pile groups due to the soil condition and the cap rigidity. The analysis considering group effect was carried out for $2{\times}2$ and $3{\times}3$ pile groups with the pile spacing 3.0B, 4.0B and 5.0B. Based on the results obtained, it is found that the overall distributions of deflection, slope, moment, and shear force in a single pile give a reasonable results irrespective of cap connectivity conditions. It is also found that even though there are some deviations in deflection prediction compared with the observed ones, the prediction by present analysis simulates much better the general trend observed by the centrifuge tests than the numerical solution predicted by PIGLET.

• Proceedings of the Korean Geotechical Society Conference
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• 2005.03a
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• pp.831-837
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• 2005

In this study, a computer program to predict the behavior of laterally loaded single pile and pile groups was developed by using a beam-column analysis in which the soils are modeled as nonlinear springs by a family of p-y curves for subgrade modulus. The special attention was given to the lateral displacement of a single pile and pile groups due to the soil condition and the cap rigidity. The analysis considering group effect was carried out for $2\;{\times}\;2\;and\;3\;{\times}\;3$ pile groups with the pile spacing 3.0B, 4.0B and 5.0B. Based on the results obtained, it is found that the overall distributions of deflection, slope, moment, and shear force in a single pile give a reasonable results irrespective of cap connectivity conditions. It is also found that even though there are some deviations in deflection prediction compared with the observed ones, the prediction by present analysis simulates much better the general trend observed by the centrifuge tests than the numerical solution predicted by PIGLET.

• 제어로봇시스템학회:학술대회논문집
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• 1992.10b
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• pp.106-111
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• 1992

In order to achieve stable and efficient use of energy at iron and steel works, a model for the prediction of supply and demand of electric power system is developed on the basis of the information on operation and particular patterns of electric power consumption. The optimal amount of electric power to be purchased and the optimal fuel allocation for the in-house electric power plants are also obtained by a mixed-integer linear programming(MILP) and a nonlinear programming (NLP) solutions, respectively. The validity and the effectiveness of the proposed model are investigated by several illustrative examples. The simulation results show the satisfactory energy saving by the optimal solution obtained through this research.

• Transactions of Materials Processing
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• v.8 no.3
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• pp.283-283
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• 1999

In the present study, the effect of microporosity on the tensile properties of as-cast AZ91D magnesium alloy was investigated through experimental observation and numerical prediction. The test specimens were fabricated by die-casting and gravity-casting. For gravity-casting, the inoculation and use of various metallic moulds were applied to obtain a wide range of microporosity. The deficiency of the interdendritic feeding of the liquid phase acted as d dominant mechanism on the formation of the micropores in the Mg-Al-alloys, rather than the evolution of hydrogen gas. Although tensile strength and elongation has a nonlinear and very intensive dependence upon microporosity, the yield strength appeared to have a linear relationship with microporosity. However, it was possible to quantitatively estimate the linear contribution of microporosity on the individual tensile property far a range of microporosity, which was below about B %. The numerical prediction suggests that the effect of microporosity on fractured strength and elongation decreased as the strain hardening exponent increased. Furthermore. the shape and distribution of micropores may play a more dominant role than local plastic deformation on the tensile behavior of AZ9lD alloy.

• Earthquakes and Structures
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• v.9 no.3
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• pp.455-480
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• 2015

In the last decade, displacement-based (DB) methods have become established design procedures for reinforced concrete (RC) structures. They use strain and displacement measures as seismic performance control parameters. As for other simplified seismic design methods, it is of great interest to prove if they are usually conservative in respect to more refined, nonlinear, time history analyses, and can estimate design parameters with acceptable accuracy. In this paper, the current Direct Displacement-Based Design (DDBD) procedure is evaluated for designing simple single degree of freedom (SDOF) systems with specific reference to simply supported RC bridge piers. Using different formulations proposed in literature for the equivalent viscous damping and spectrum reduction factor, a parametric study is carried out on a comprehensive set of SDOF systems, and an average error chart of the method is derived allowing prediction of the expected error for an ample range of design cases. Following the chart, it can be observed that, for the design of actual RC bridge piers, underestimation errors of the DDBD method are very low, while the overestimation range of the simplified displacement-based procedure is strongly dependent on design ductility.

• Structural Engineering and Mechanics
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• v.66 no.3
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• pp.399-409
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• 2018

This paper demonstrates the potential application of machine learning algorithms for approximate prediction of the load and deflection capacities of the novel type of Laced Steel Concrete-Composite (LSCC) beams proposed by Anandavalli et al. (Engineering Structures 2012). Initially, global and local responses measured on LSCC beam specimen in an experiment are used to validate nonlinear FE model of the LSCC beams. The data for the machine learning algorithms is then generated using validated FE model for a range of values of the identified sensitive parameters. The performance of four well-known machine learning algorithms, viz., Support Vector Regression (SVR), Minimax Probability Machine Regression (MPMR), Relevance Vector Machine (RVM) and Multigene Genetic Programing (MGGP) for the approximate estimation of the load and deflection capacities are compared in terms of well-defined error indices. Through relative comparison of the estimated values, it is demonstrated that the algorithms explored in the present study provide a good alternative to expensive experimental testing and sophisticated numerical simulation of the response of LSCC beams. The load carrying and displacement capacity of the LSCC was predicted well by MGGP and MPMR, respectively.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.22 no.9
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• pp.628-634
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• 2010

This paper presents a feasibility study of a fresh air load reduction system by using an underground double floor space. The fresh air is introduced into the double slab space and passes through the opening bored into the footing beam. The air is cooled by the heat exchange with the inside surface of the double slab space in summer, and heated in winter. This system not only reduces sensible heat load of the fresh air by heat exchange with earth but also reduces latent heat load of the fresh air by ad/de-sorption of underground double slab concrete. In this paper, we proposed a simplified presumption method for the prediction of cooling and heating performance in the system. In conclusion the proposed method has been verified by comparing with the calculated value of the numerical analysis model by using nonlinear two-dimension hygroscopic question.