• Journal of the Korean Society of Clothing and Textiles
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• v.16 no.4 s.44
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• pp.443-455
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• 1992

The purpose of this study is to verify the theoretical model on the clothing satisfaction. Research problems are as following; 1. To identify a causal model on the clothing satisfaction. 2. To examine the causal model by the brand levels. 3. To examine the causal model by the consumer characteristics. The empirical study of the above research problems is carried out by the longitudinal survey. The subjects selected for the final analysis are 362 women living in Seoul and Pusan. The results of our analysis are as following; 1. The main causal course of the clothing satisfaction is that the brand level and the consumer expectation $\rightarrow$ the expectation $\rightarrow$ the perceived performance ($\rightarrow$ the disconfirmation) $\rightarrow$ the clothing satisfaction. Those relevant variables explain $70\%$ of the clothing satisfac-tion variance. Especially, the influence of the perceived performance appears to be greater than that of the disconfirmation. 2. According to our analysis, the expectation influences the clothing satisfaction indirectly through the perceived performance. Especially, the normative expectation exhibits the contrast effect on the disconfirmation, while the predictive expectation exhibits the assimilation effect on the perceived performance. 3. The clothing satisfaction model differs by the brand levels (high price brand vs. moderate price brand) and by the consumer involvement levels (high involvement vs. low involvement). The relevant variables explain $65\%$ of the clothing satisfaction variance in the high price brand, while they explain $77\%$ in the moderate price brand. In the high involvement group, the relevant variables explain $78\%$ of the clothing satisfaction variance and $60\%$ in the low involvement group. In both involvement groups, the most critical direct variable is the perceived perfor-mance. In conclusion, we find that the clothing satisfaction can be explained by three constructs, the expectation, the perceived performance and the disconfirmation. The hypothesis that the two dimensions of the expectation explain the clothing satisfaction better is empirically supported in our study. Finally, we find that the clothing satisfaction models differ between two brand levels and consumer involvement levels.

• Journal of KIISE:Computing Practices and Letters
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• v.15 no.7
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• pp.469-477
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• 2009

In mobile systems, energy efficiency is critical to extend battery life. Therefore, power consumption should be taken into account to develop software in addition to performance, Efficient software design in power and performance is possible if accurate power prediction is accomplished during the execution of software, In this paper, power estimation model is developed using statistical analysis, The proposed model analyzes processor behavior Quantitatively using the data of performance monitoring events and power consumption collected by executing various benchmark programs, And then representative hardware events on power consumption are selected using hierarchical clustering, The power prediction model is established by regression analysis in which the selected events are independent variables and power is a response variable, The proposed model is applied to a PXA320 mobile processor based on Intel XScale architecture and shows average estimation error within 4% of the actual measured power consumption of the processor.

• Nuclear Engineering and Technology
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• v.41 no.6
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• pp.785-796
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• 2009

A KALIMER-600 concept which is a type of sodium-cooled fast reactor, has been developed at KAERI. It uses sodium as a primary coolant and is a pool-type reactor to enhance safety. Also, a supercritical carbon dioxide ($CO_2$) Brayton cycle is considered as an alternative to an energy conversion system to eliminate the sodium water reaction and to improve efficiency. In this study, a simplified model for analyzing the thermodynamic performance of the KALIMER-600 coupled with a supercritical $CO_2$ Brayton cycle was developed. To develop the analysis model, a commercial modular modeling system (MMS) was adopted as a base engine, which was developed by nHance Technology in USA. It has a convenient graphical user interface and many component modules to model the plant. A new user library for thermodynamic properties of sodium and supercritical $CO_2$ was developed and attached to the MMS. In addition, some component modules in the MMS were modified to be appropriate for analysis of the KALIMER-600 coupled with the supercritical $CO_2$ cycle. Then, a simplified performance analysis code was developed by modeling the KALIMER-600 plant with the modified MMS. After evaluating the developed code with each component data and a steady state of the plant, a simple power reduction and recovery event was evaluated. The results showed an achievable capability for a performance analysis code. The developed code will be used to develop the operational strategy and some control logics for the operation of the KALIMER-600 with a supercritical $CO_2$ Brayton cycle after further studies of analyzing various operational events.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.33 no.11
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• pp.909-915
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• 2009

In this paper, a study of performance improvement for a centrifugal vertical pump having specific speed of 330 is introduced. The existing model has high efficiency but needs better NPSH required performance. Such that new pump model is designed to obtain larger suction specific speed. 6 design parameters considered to affect pump performance are selected for impeller design. Key design parameters are investigated using by design of experiments and CFD, and impeller inlet diameter is increased to get better suction performance. The amount of inlet diameter increase is determined by using cavitation analysis. The results show that new design model has higher efficiency and better NPSH required performance than the existing model.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.11 no.5
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• pp.108-122
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• 2001

As bridge design is advancing toward the performance-based design. it becomes increasingly important to monitor and re-evaluate the long-term structural performance of bridges. Such information is essential in developing performance criteria for design. In this research. sensor systems for long-term structural performance monitoring have been installed on two highway bridges. Pre1iminary vibration measurement and data analysis have been performed on these instrumented bridges. On one bridge, ambient vibration data have been collected. based on which natural frequencies and mode shapes have been extracted using various methods and compared with those obtained by the preliminary finite element analysis. On the other bridge, braking and bumping vibration tests have been carried out using a water truck In addition to ambient vibration tests. Natural frequencies and mode shapes have been derived and the results by the breaking and bumping vibration tests have been compared. For the development of a three dimensional baseline finite element model, the new methodology using a neural network is proposed. The proposed one have been verified and applied to develop the baseline model of the bridge.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.10 no.1
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• pp.148-155
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• 2006

Portable embedded systems which mainly handle multimedia applications involve the problem that frequent accesses to fetch data from memory make running time increased. To cope with the problem, embedded processors have adopted data prefetching schemes. From a power point of view, which is a main performance indicator of embedded systems, this paper analyzed to investigate how data prefetching schemes influence on system's performance. To solve the problem, we proposed a power-consumption analysis model of a memory system with data prefetching scheme and measured the power dissipated during running application programs. As a result data prefetching schemes have application program's running time reduced but have system's power increased. Also we proposed a performance analysis model considering execution time and power consumption for embedded system with data prefetching schemes.

• Smart Structures and Systems
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• v.26 no.2
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• pp.175-184
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• 2020

Conventional Monte Carlo simulation-based methods for seismic risk assessment of water networks often require excessive computational time costs due to the hydraulic analysis. In this study, an Artificial Neural Network-based surrogate model was proposed to efficiently evaluate the flow-based system reliability of water distribution networks. The surrogate model was constructed with appropriate training parameters through trial-and-error procedures. Furthermore, a deep neural network with hidden layers and neurons was composed for the high-dimensional network. For network training, the input of the neural network was defined as the damage states of the k-dimensional network facilities, and the output was defined as the network system performance. To generate training data, random sampling was performed between earthquake magnitudes of 5.0 and 7.5, and hydraulic analyses were conducted to evaluate network performance. For a hydraulic simulation, EPANET-based MATLAB code was developed, and a pressure-driven analysis approach was adopted to represent an unsteady-state network. To demonstrate the constructed surrogate model, the actual water distribution network of A-city, South Korea, was adopted, and the network map was reconstructed from the geographic information system data. The surrogate model was able to predict network performance within a 3% relative error at trained epicenters in drastically reduced time. In addition, the accuracy of the surrogate model was estimated to within 3% relative error (5% for network performance lower than 0.2) at different epicenters to verify the robustness of the epicenter location. Therefore, it is concluded that ANN-based surrogate model can be utilized as an alternative model for efficient seismic risk assessment to within 5% of relative error.

• Journal of the Korean Society of Hazard Mitigation
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• v.9 no.5
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• pp.93-102
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• 2009

A prediction of streamflow based on multi-objective function is presented to check the performance of Probability Distributed Model(PDM) in Miho stream basin, Chungcheongbuk-do, Korea. PDM is a lumped conceptual rainfall runoff model which has been widely used for flood prevention activities in UK Environmental Agency. The Monte Carlo Analysis Toolkit(MCAT) is a numerical analysis tools based on population sampling, which allows evaluation of performance, identifiability, regional sensitivity and etc. PDM is calibrated for five model parameters by using MCAT. The results show that the performance of model parameters(cmax and k(q)) indicates high identifiability and the others obtain equifinality. In addition, the multi-objective function is applied to PDM for seeking suitable model parameters. The solution of the multi-objective function consists of the Pareto solution accounting to various trade-offs between the different objective functions considering properties of hydrograph. The result indicated the performance of model and simulated hydrograph are acceptable in terms on Nash Sutcliffe Effciency*(=0.035), FSB(=0.161), and FDBH(=0.809) to calibration periods, validation periods as well.

• Journal of the Korean Solar Energy Society
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• v.40 no.1
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• pp.49-60
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• 2020

This study reviewed selected specific windows and reviewed the window performance certification criteria including KS F 2278 and KS L 9107 and analyzed the change in performance based on the change of area. This study also compared the heating and cooling loads of an apartment house applied with window performance reviewed in consideration of insulation and SHGC performance and actual size based on KS F 2278. The analyzed window was a double window composed of aluminum and PVC and the building was the apartment house model of 141 ㎡. The analysis results were as follows. First, as the window glass's thermal performance is superior to frame, the performance degraded in reduced area. In case of selected window, the 1 m × 1m window's thermal performance and SHGC decreased by 35% and 37% respectively compared to 2 m × 2 m window. Secondly, in the comparison of performance for increasing area with 2 m × 2 m and 3 m × 3 m windows, the 3 m × 3 m window's thermal performance and SHCG increased about 14%. Third, in the comparison of heating and cooling loads of the analyzed model considering the apartment house model applied with window performance derived from KS F 2278 and actual figures, the model's total heating and cooling loads increased by 33% with cooling decreasing by 36% and heating increasing by 77%. Above analysis results show that evaluation of window performance based on criteria such as KS F 2278 and KS L 9107 may lead to distortion of performances different from actual products. Thus, it is necessary to suggest new evaluation criteria.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.36 no.2
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• pp.105-112
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• 2023

In this study, structural analyses were conducted to analyze the performance of a bridge to which friction pendulum systems (FPSs) were applied using different friction models. A Coulomb friction model and a rate dependent friction model were constructed using the friction coefficient of a PVDF/MgO friction material to analyze the effect of different friction analysis models. The Coulomb friction model uses a single friction coefficient regardless of friction velocity, while the rate dependent friction model can reflect the change in the friction coefficient with friction velocity. Nonlinear time history and seismic fragility analyses were conducted to confirm responses of the bridge. The seismic responses of a deck and a column were used to evaluate the performance of the base isolated bridge, and a friction model that can effectively evaluate the performance of isolated bridges was analyzed.