• Journal of Aerospace System Engineering
• /
• v.13 no.6
• /
• pp.17-25
• /
• 2019

PHM (Prognostics and Health Management) of aircraft engines is applied to predict the remaining useful life before failure or the lifetime limit. There are two methods to establish a predictive model for this: The physics-based method and the data-driven method. The physics-based method is more accurate and requires less data, but its application is limited because there are few models available. In this study, the data-driven method is applied, in which a multi-layer perceptron based neural network algorithms is applied for the life prediction. The neural network is trained using the data sets virtually made by the C-MAPSS code developed by NASA. After training the model, it is applied to the test data sets, in which the confidence interval of the remaining useful life is predicted and validated by the actual value. The performance of proposed method is compared with previous studies, and the favorable accuracy is found.

• Geotechnical Engineering
• /
• v.9 no.4
• /
• pp.7-16
• /
• 1993

Calibration chamber tests were conducted on open -ended model piles driven into dried siliceous sands with different soil conditions in order to clarify the effect of soil conditions on plug capacity, The model pile used in the test series was devised so that the bearing capacity of an open -ended pile could be measured out into three components , outside shaft resistance. plug resistance and tip resistance. Under several assumption, the value of earth pressure coefficient in the soil plug is calculated. It is gradually reduced with increase in the longitudinal distance from the pile tip. At the bottom of soil plug, it tends to decrease with increase in the penetration depth and relative density, and to increase with the increase of ambient pressure. In comparison of measured and calculated plug capacities using the one -dimensional analysis, we note that API code and one -dimensional analysis combined with P suggested by Randolph et al. and O'Neill et al. result in great underestimation of the plug capacity. Therefore, based on the test results, an empirical equation was suggested to compute the earth pressured coefficient to be used in the calculation of plug capacity using the one -dimensional analysis. and it produces proper plug capacities for all soil conditions.

• Structural Engineering and Mechanics
• /
• v.85 no.5
• /
• pp.635-644
• /
• 2023

The design of honeycomb sandwich structures is often challenging because these structures can be tailored from a variety of possible cores and face sheets configurations, therefore, the design of sandwich structures is characterized as a time-consuming and complex task. A data-driven computational approach that integrates the analytical method and Artificial Neural Network (ANN) is developed by the authors to rapidly predict the design of sandwich structures for a targeted maximum structural deflection. The elaborated ANN reverse design approach is applied to obtain the thickness of the sandwich core, the thickness of the laminated face sheets, and safety factors for composite sandwich structure. The required data for building ANN model were obtained using the governing equations of sandwich components in conjunction with the Monte Carlo Method. Then, the functional relationship between the input and output features was created using the neural network Backpropagation (BP) algorithm. The input variables were the dimensions of the sandwich structure, the applied load, the core density, and the maximum deflection, which was the reverse input given by the designer. The outstanding performance of reverse ANN model revealed through a low value of mean square error (MSE) together with the coefficient of determination (R2) close to the unity. Furthermore, the output of the model was in good agreement with the analytical solution with a maximum error 4.7%. The combination of reverse concept and ANN may provide a potentially novel approach in designing of sandwich structures. The main added value of this study is the elaboration of a reverse ANN model, which provides a low computational technique as well as savestime in the design or redesign of sandwich structures compared to analytical and finite element approaches.

• Journal of Korean Society on Water Environment
• /
• v.25 no.6
• /
• pp.984-993
• /
• 2009

There have been growing concerns of algal growth at Daecheong reservoir due to eutrophication with excess nutrient inflow. Rainfall-driven runoff and pollutant from watershed are responsible for eutrophication of the Daecheong reservoir. In this study, two subwatersheds of the Daecheong reservoir were selected and water quality characteristics were analyzed. The L-THIA ArcView GIS model was used for evaluation of direct runoff and water quality. The $R^2$ and the EI value for direct runoff were 0.95 and 0.93 at Wol-oe watershed and were 0.81, 0.71 at An-nae watershed, respectively. The $R^2$ for SS, T-P were 0.53, 0.95 at Wol-oe watershed and 0.89, 0.89 at An-nae watershed, respectively. It has been proven that the L-THIA ArcView GIS model could be used for evaluating direct runoff and pollutant load from the watershed with reasonable accuracies.

• The Journal of Fisheries Business Administration
• /
• v.55 no.1
• /
• pp.37-53
• /
• 2024

In the post-COVID-19, the food industry is rapidly reshaping its market structure toward online distribution. Rapid delivery system driven by large distribution platforms has ushered in an era of online distribution of fresh seafood that was previously limited. This study surveyed 1,000 consumers nationwide to determine their online seafood purchasing behaviors. The research methodology used factor analysis of consumer lifestyle and Heckman's ordered probit sample-selection model. The main results of the analysis are as follows. First, quality, freshness, selling price, product reviews from other buyers, and convenience are particularly important considerations when consumers purchase seafood from online shopping. Second, online retailers and the government must prepare measures to expand seafood consumption by considering household characteristics and consumer lifestyles. Third, it was analyzed that consumers trust the quality and safety of seafood distributed online platforms. It is not possible to provide purchase incentives to consumers who consider value consumption important, so improvement measures are needed. The results of this study are expected to provide implications on consumer preferences to online platforms, seafood companies, and producers, and can be used to establish future marketing strategies.

• Journal of Digital Convergence
• /
• v.10 no.8
• /
• pp.73-80
• /
• 2012

Consulting industry is a knowledge intensive business service industry to lead to knowledge creation as well as support high value creation of other industries. While the consulting industry has a great ripple effect on whole industries, there is a lack of interest in the consulting industry. Thus, this study investigates a ripple effect of the consulting service on the national economy using an Input-Output analysis. We summarize some of our findings as follows. First, A production of 1.0 won in the business consulting industry induces production of 0.6933 won in 2005 and 0.7851 in 2009; value-added of 0.2881 won in 2005 and 0.3039 won in 2009. A production of 1.0 billion won in the business consulting industry Industry produces employment for 0.1124 persons in 2005 and 0.1207 persons in 2009. Second, the supply shortage of 1.0 won in the business consulting industry prevents other industries from producing 2.6759 won in 2005 and 3.0145 won in 2009. Third, a 10% increase in the price level of the business consulting industry raises the overall price level from 0.1691% in 2005 to 0.2161% in 2009. The research results show that consulting industry has been increasing a effect on Korea national economy.

• Knowledge Management Research
• /
• v.17 no.1
• /
• pp.73-89
• /
• 2016

The digital culture contents is one of the fastest growing industry in Korea and it accounts for 60% of the digital contents industry. This paper attempts to analyze economic impacts of the digital culture contents industry using input-output analysis. This study investigated the production-inducing effect, value-added-inducing effect and employment-inducing effect of the digital culture contents industry based on a demand-driven model. In addition, the study dealt with the supply shortage effect and sectoral price effect of the digital culture contents industry using a supply-driven model and the Leontief price model, including the inter-industry linkage effects of 29 sectors with the digital culture contents industry sector. Some interesting findings were drawn from the study. First, production of 1.0 won in the digital culture contents industry results in production-inducing effect of 2.39542 won, value-added effect of 1.29895 won and employment-inducing effect of 0.39657 persons in other industries. Second, the supply shortage of 1.0 won in the digital culture contents industry prevents other industries from producing 0.56631 won. Third, a 1% increase in the price level of the digital culture contents industry raises the overall price level by 0.06017%. Finally, very high backward linkage effects were found, but forward linkage effects were minimal.

• Journal of Energy Engineering
• /
• v.23 no.2
• /
• pp.83-92
• /
• 2014

This paper attempts to conduct a comparative analysis on the economic effects of integrated-energy and manufactured gas supply sectors. To this end, an input-output (I-O) analysis is applied using most recently published 2011 I-O table. In particular, the two sectors are specified as exogeneous to identify the economic effects on own and other sectors. Production-inducing effect, value-added creation effect, and employment-inducing effect are quantified based on demand-driven model. Supply shortage effect and price pervasive effect are analyzed employing supply-driven model and Leontief price model, respectively. The results show that production-inducing effect, value-added creation effect, and employment-inducing effect of integrated-energy and manufactured gas supply sectors are estimated to be 1.5461 vs. 1.0297, 0.4759 vs. 0.1941, and 2.2885 vs. 0.4053 respectively. Price pervasive effects of the 10% increase in integrated-energy and manufactured gas supply sectors are computed to be 0.0127% and 0.1585%, respectively. This information can be utilized in forecasting the economic effects of introducing integrated-energy or manufactured gas as a heating source and the impacts of a rise in price of integrated-energy or manufactured gas on price level of other sectors.

• Journal of Energy Engineering
• /
• v.23 no.2
• /
• pp.74-82
• /
• 2014

The government is planning to expand the bio-gas supply as a method for mitigating greenhouse gas emissions to deal with climate change. By means of a policy instrument, the government is considering an introduction of the Renewable Fuel Standard (RFS) whose targets include bio-gas. This paper attempts to look into the economic effects of expanding the bio-gas supply by applying an input-output (I-O) analysis using a 2011 I-O table. The bio-gas supply sector consists of liquefied petroleum gas supply sector and city gas supply sector, based on the tenets of introducing the RFS. The production-inducing effect, value-added creation effect, and employment-inducing effect of the bio-gas sector are analyzed. The supply shortage effect and the price pervasive effect are also investigated. The results show that the production or investment of 1.0 won in the bio-gas supply sector induces the production of 1.0539 won and the value-added of 0.1998 won in the national economy. Moreover, the production or investment of 1.0 billion won, supply shortage of 1.0 won, and a price increase of 10.0% in the bio-gas supply sector touch off the employment of 0.5279 person, 1.6229 won, and an increase in overall price level by 0.0183%, respectively.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
• /
• v.30 no.4
• /
• pp.159-166
• /
• 2018

The Korean fenestration energy consumption efficiency rating system only considers thermal performance of the heat transfer coefficient (U-value) and airtightness excluding optical characteristics of the solar heat gain coefficient (SHGC). This study analyzed annual heating and cooling energy requirements on the middle floor of apartment by optical and thermal performance of windows to evaluate the suitability of the rating system. One hundred and twenty-eight windows were analyzed using THERM and WINDOW 7.4, and energy simulation for a reference model of an apartment house facing south was performed using TRNSYS 17. The results showed that window performance was the main factor in the heating and cooling load. The heating load of the reference model was 539 kWh to 2,022 kW, and the cooling load was 376 kWh to 1,443 kWh. The coefficient of determination ($R^2$) of the heating and cooling loads driven from the SHGC were 0.7437 and 0.9869, which are more compatible than those from the U-value, 0.0558 and 0.4781. Therefore, it is not reasonable to evaluate the energy performance of windows using only the U-value, and the Korean fenestration energy consumption efficiency rating system requires a new evaluation standard, including SHGC.