• Journal of the Korea Institute of Building Construction
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• v.21 no.3
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• pp.195-202
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• 2021

Concrete quality is mainly managed through the reliable prediction and control of compressive strength. Although related industries have established a relevant datasets based on the mixture proportions and compressive strength gain, whereas they have not been shared due to various reasons including technology leakage. Consequently, the costs and efforts for quality control have been wasted excessively. This study aimed to develop a web-based numerical model, which would present diverse optimal values including concrete strength prediction to the user, and to establish a sustainable database (DB) collection system by inducing the data entered by the user to be collected for the DB. The system handles the overall technology related to the concrete. Particularly, it predicts compressive strength at a mean accuracy of 89.2% by applying the artificial neural network method, modeled based on extensive DBs.

• Proceedings of the Korean Society For Composite Materials Conference
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• 2000.11a
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• pp.245-248
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• 2000

Modern aircraft composite structures are designed using a damage tolerance philosophy. This design philosophy envisions sufficient strength and structural integrity of the aircraft to sustain major damage and to avoid catastrophic failure. The only reasonable way to treat on the same basis all the conditions and uncertainties participating in the design of damage tolerant composite aircraft structures is to use the probability-based approach. Therefore, the model has been developed to assess the probability of structural failure (POSF) and associated risk taking into account the random mechanical loads, random temperature-humidity conditions, conditions causing damages, as well as structural strength variations due to intrinsic strength scatter, manufacturing defects, operational damages, temperature-humidity conditions. The model enables engineers to establish the relationship between static/residual strength safety margins, production quality control requirements, in-service inspection resolution and criteria, and POSF. This make possible to estimate the cost associated with the mentioned factors and to use this cost as overall criterion. The methodology has been programmed into software.

• Transactions on Electrical and Electronic Materials
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• v.7 no.2
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• pp.81-86
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• 2006

In this paper, the response surface modeling of the control of the pretilt angle in the nematic liquid crystal on the homogeneous polyimide surface with different surface treatment is investigated. The pretilt angle is one of the main factors to determine the alignment of the liquid crystal display. The pretilt angle is measured to analyze the variation of the characteristics on the various process conditions. The rubbing strength and the hard baking temperature are considered as input factors. After the design of experiments is performed, the process model is then explored using the response surface methodology. The analysis of variance is used to analyze the statistical significance and the effect plots are also investigated to examine the relationship between the process parameters and the response.

• Proceedings of the Acoustical Society of Korea Conference
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• 1994.06a
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• pp.785-790
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• 1994

The active noise control which regards the acoustic power as a target function to be minimized, is analyzed to test its feasibility of which simplifies the measurement system compared with the global acoustic energy based active noise control system. In fact, it is found that the acoustic power based active noise control strategy is equally likely as good as the global acoustic energy based active noise control method if the acoustic field of interest is diffusive or very low model density one. In the intermediate model density field, we also demonstrate that the power based control gives the similar results as the energy based control in terms of global sound energy reduction for the lightly damped enclosure which might be most important system in practical application. From all the theoretical and power based control strategy is dependent on the characteristics of the acoustic field to be controlled; i.e., the model density distribution, the degree of reverberation, and on the strength of modal interaction of the control source with the primary source; i.e., the location of control source.

• Journal of Korean Society for Quality Management
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• v.7 no.2
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• pp.22-28
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• 1979

The problem considered in this paper is to select the vital factor effect to the product quality through the experimental design and analysis of response surface, so as to control the quality improvement of industrial product. In this time, even through the mathematical model is unknown it could be applicable to control the quality of industrial products and to determine optimum operating condition for many technical fields, particulary, for industrial manufacturing process. When a set of data is available from an experimental design, it is often of interest 1:0 fit polynominal repression model in independent variables (eg, time, temperature, pressure, etc) the optimize the response variable (eg. yield, strength etc). This paper proposes a method known to obtain the optimum operating condition, and how to find the condition by using table of orthogonal array experiments, and optimization methodology of statistical model. A criterion can be applied determining to optimum operating conditions in manufacturing industry and improving the fit of response surface which may be used for prediction of responses and quality control of industrial products.

• Journal of the Korea Concrete Institute
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• v.11 no.5
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• pp.131-137
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• 1999

The use of higher strength materials with the strength methed of design has resulted in more slender member and shallower sections. For this reason, it is necessary to satisfy the requirements of serviceability even though the structural safety is the most important limit state. This paper is only concerned with the control of deflections in the serviceability. In this study, an analytical model is presented to predict the deflections of reinforced concrete beams to given loading and environmental conditions. This model is based on the finite element approach in which a finite element is generally divided into a number of stiffening effect due to cracking, creep and shrinkage. Comparisons are made with available measured deflections reported by others to assess the capability of the layered beam model. The calculated values of instantaneous and long-term deflection show good agreement with experimental results in the range of tension stiffening parameter $\beta$ between 2.5 and 3.0.

• Journal of Distribution Research
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• v.16 no.2
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• pp.95-118
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• 2011

The purpose of this study is as follows. First, we investigate empirically the effects of social network properties such as social network density and centrality of a franchisee on its information sharing with various subjects such as the franchisor and other franchisees in the franchise system. Second, we examine exploratively if tie strength between a franchisee and its franchisor plays a moderating role on the relationship between social network properties and information sharing. The study model was established as shown in

• Structural Engineering and Mechanics
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• v.45 no.6
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• pp.837-851
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• 2013

In construction industry, strength is a primary criterion in selecting a concrete for a particular application. The concrete used for construction gains strength over a long period of time after pouring the concrete. The characteristic strength of concrete is defined as the compressive strength of a sample that has been aged for 28 days. Neither waiting for 28 days for such a test would serve the rapidity of construction, nor would neglecting it serve the quality control process on concrete in large construction sites. Therefore, rapid and reliable prediction of the strength of concrete would be of great significance. On this backdrop, the method is proposed to establish a predictive relationship between properties and proportions of ingredients of concrete, compaction factor, weight of concrete cubes and strength of concrete whereby the strength of concrete can be predicted at early age. Multiple regression analysis was carried out for predicting the compressive strength of concrete containing Portland Pozolana cement using statistical analysis for the concrete data obtained from the experimental work done in this study. The multiple linear regression models yielded fairly good correlation coefficient for the prediction of compressive strength for 7, 28 and 40 days curing. The results indicate that the proposed regression models are effectively capable of evaluating the compressive strength of the concrete containing Portaland Pozolana Cement. The derived formulas are very simple, straightforward and provide an effective analysis tool accessible to practicing engineers.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.273-273
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• 2000

We present a new scheme to increase the performance of edge-preserving image smoothing from the parameter tuning of a Markov random field (MRF) function. The method is based on automatic control of the image smoothing-strength in MRF model ing in which an introduced parameter function is based on control of enforcing power of a discontinuity-adaptive Markov function and edge magnitude resulted from discontinuities of image intensity. Without any binary decision for the edge magnitude, adaptive control of the enforcing power with the full edge magnitude could improve the performance of discontinuity-preserving image smoothing.

• Journal of Korean Society for Quality Management
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• v.18 no.1
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• pp.129-147
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• 1990

This study is to refer to the optimization problems when the stress and strength follow the time dependent model, considering a decision making process in the design methodology from reliability viewpoint. Reliability of a component can be expressed and computed if the probability distributions for the stress and strength in the time dependent case are known. The factors which determine the parameters of the distributions for stress and strength random variables can be controlled in design problems. This leads to the problem of finding the optimal values of these parameters subject to resources and design constraints. This paper is to present techniques for solving the optimization problems at the design stage like as minimizing the total cost to be spent on controlling the stress and strength parameters for random variables subject to the constraint that the component must have a specified reliability, alternatively, maximizing the component reliability subject to certain constraints on amount of resources available to control the parameters. The derived expressions and computations of reliability in the time dependent case and some optimization models of these cases are discussed. The special structure of these models is exploited to develop the optimization techniques which are illustrated by design examples.