Recently, feature-based solid modeling systems have been widely used in product design. However, for engineering analysis of a product model, an ed CAD model composed of mid-surfaces is desirable for conditions in which the ed model does not affect analysis result seriously. To meet this requirement, a variety of solid ion methods such as MAT (medial axis transformation) have been proposed to provide an ed CAE model from a solid design model. The algorithm of the MAT approach can be applied to any complicated solid model. However, additional work to trim and extend some parts of the result is required to obtain a practically useful CAE model because the inscribed sphere used in the MAT method generates insufficient surfaces with branches. On the other hand, the mid-surface ion approach supports a practical method for generating a two-dimensional ed model, even though it has difficulties in creating a mid-surface from some complicated parts. In this paper, we propose a dimension reduction approach on solid models based on the midsurface abstraction approach. This approach simplifies the solid model by abbreviating or removing trivial features first such as the fillet, mounting, or protrusion. The geometry of each face is replaced with mid-patches from the simplified model, and then unnecessary topological entities are deleted to generate a clean ed model. Also, additional work, such as extending and stitching mid-patches, completes the generation of a mid-surface model from the patches.
Journal of Korean Society of Industrial and Systems Engineering
/
v.42
no.4
/
pp.145-152
/
2019
All machines deteriorate in performance over time. The phenomenon that causes such performance degradation is called deterioration. Due to the deterioration, the process mean of the machine shifts, process variance increases due to the expansion of separate interval, and the failure rate of the machine increases. The maintenance model is a matter of determining the timing of preventive maintenance that minimizes the total cost per wear between the relation to the increasing production cost and the decreasing maintenance cost. The essential requirement of this model is that the preventive maintenance cost is less than the failure maintenance cost. In the process mean shift model, determining the resetting timing due to increasing production costs is the same as the maintenance model. In determining the timing of machine adjustments, there are two differences between the models. First, the process mean shift model excludes failure from the model. This model is limited to the period during the operation of the machine. Second, in the maintenance model, the production cost is set as a general function of the operating time. But in the process mean shift model, the production cost is set as a probability functions associated with the product. In the production system, the maintenance cost of the equipment and the production cost due to the non-confirming items and the quality loss cost are always occurring simultaneously. So it is reasonable that the failure and process mean shift should be dealt with at the same time in determining the maintenance time. This study proposes a model that integrates both of them. In order to reflect the actual production system more accurately, this integrated model includes the items of process variance function and the loss function according to wear level.
Kim, Dong-uk;Han, Deok-hwa;Kee, Chang-don;Lee, Chul-soo;Lee, Choong-hee
Journal of Advanced Navigation Technology
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v.20
no.1
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pp.23-28
/
2016
In this paper, we verified accuracy of the satellite based augmentation system (SBAS) tropospheric delay correction model for the Korean region. We employed the precise data of the tropospheric zenith path delay (ZPD) which is provided by the international GNSS service (IGS). In addition, we compared the verification results with that of the Saastamoinen model and the Hopfield model. Consequently, the bias residual error of the SBAS tropospheric delay correction model is about 50 mm, whereas the Saastamoinen model and the Hopfield model are more accurate. This residual error by the tropospheric delay model can affect the SBAS user position accuracy, but there is no problem in SBAS accuracy requirement. If we modified the meteorological parameters for SBAS tropospheric model to appropriate in Korean weather environment, we can provide better SBAS service to the Korean user.
A preventive maintenance model, caller FNBM($\alpha$, $\delta$, $\gamma$)model, is proposed to decide an optimal repair number under achieved availability requirements(r) along with taking two types of failures (repairable or irrepairable) into account. In this model, the current system is replaced by a new one in case when it doesn't meet the achieved availability requirement, even though it is repairable failure; Otherwise it is replaced in time of the first irrepairable failure. Assumed that the j-th failure is repairable with probability ${\alpha}_j$ minimal repairs are allowed for repairable failure between replacements. Expected cost rate for preventive maintenance model is developed using NHPP(Non-Homogeneous Poisson Process) in order to determine the optimal number $n^*$, also numerical examples are shown in order to explain the proposed model. Since the proposed FNBM($\alpha$, $\delta$, $\gamma$)model includes Park FNBM model(1979) and Nakagawa FNBM(p)model(1983) this proposed model is thought to be better than previous model, especially for weapon system which requires availability as primary parameter.
Journal of the Korean Society of Food Science and Nutrition
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v.26
no.4
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pp.704-713
/
1997
This study was conducted to describe qualitatively the protein metabolism of pigs during growth depending on the feed protein quality and to describe quantitatively amino acids requirements, using a simulation model. The used model has a non-linear structure. In the used model, the protein utilization system of a pig, which is in the non-steady-state, is described with 15 flux equations and 11 differential equations and is composed with two compartments. Protein deposition(g/day) of pigs on the 30th, 60th, 90th, and 120th day of feeding duration with three-quality protein, beginning with body weight 20kg, were calculated according to the empirical model, PAF(the product of amino acid functions) of Menke, and was used as object function for the simulation. The mean of relative difference between the simulated protein deposition and PAF calculated values, lied in a range of 8.8%. The simulated protein deposition showed different behavior according to feed protein quality. In the high-quality protein, it showed paraboloidal form with extending growth simulation up to 150eh day. So the maximum of protein deposition was acquired on the 105th day of simulate growth time and then it decreased fast. In the low-quality protein, this form of protein deposition in the course of simulated growth did not appear until 150th day. The simulated protein mass also showed a difference in accordance with feed protein quality. The difference was small on the 30th day of simulated growth, but with duration of the simulated growth it was larger. On the 150th day the simulated protein deposition of high quality protein was 1.5 times higher as compared to the low-quality protein. The simulated protein synthesis and break-down rates(g/day) in the whole body showed a parallel behavior in the course of growth, according to feed protein quality. It was found that the improvement of feed protein quality increased protein deposition in the whole body through a increase of both protein synthesis and breakdown during growth. Also protein deposition efficiency, which was calculated from simulated protein deposition and protein synthesis, showed a difference in dependence on the protein qualify of feed protein. The protein deposition efficiency was higher in pigs fed with high quality protein, especially at the simulation time 30th day. But this phenomena disappeared with growth, so on the 150th day of growth, the protein deposition of the high feed protein quality was lowest among the three different quality of feed protein. The simulated total requirement of the 10 essential amino acids for the growth of pigs was 28.1(g/100g protein), similar to NRC. The requirement of lysine was 4.2(g/100g protein).
In this study, a model was developed to predict for Disinfection By-Products (DBPs) generated in water supply networks and consumer premises, before and after the introduction of advanced water purification facilities. Based on two-way ANOVA, which was carried out to statistically verify the water quality difference in the water supply network according to introduce the advanced water treatment process. The water quality before and after advanced water purification was shown to have a statistically significant difference. A multiple regression model was developed to predict the concentration of DBPs in consumer premises before and after the introduction of advanced water purification facilities. The prediction model developed for the concentration of DBPs accurately simulated the actual measurements, as its coefficients of correlation with the actual measurements were all 0.88 or higher. In addition, the prediction for the period not used in the model development to verify the developed model also showed coefficients of correlation with the actual measurements of 0.96 or higher. As the prediction model developed in this study has an advantage in that the variables that compose the model are relatively simple when compared with those of models developed in previous studies, it is considered highly usable for further study and field application. The methodology proposed in this study and the study findings can be used to meet the level of consumer requirement related to DBPs and to analyze and set the service level when establishing a master plan for development of water supply, and a water supply facility asset management plan.
Magazine of the Korean Society of Agricultural Engineers
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v.26
no.2
/
pp.106-124
/
1984
Monthly streanflow of watersheds is one of the most important elements for the planning, design, and management of water resources development projects, e.g., determination of storage requirement of reservoirs and control of release-water in lowflow rivers. Modeling of longterm runoff is theoretically based on water-balance analysis for a certain time interval. The effect of the casual factors of rainfall, evaporation, and soil-moisture storage on streamflow might be explained by multiple regression analysis. Using the basic concepts of water-balance and regression analysis, it was possible to develop a generalized model called the Regionalized Regression Model for Monthly Streamflow in Korean Watersheds. Based on model verification, it is felt that the model can be reliably applied to any proposed station in Korean watersheds to estimate monthly streamflow for the planning, design, and management of water resources development projects, especially those involving irrigation. Modeling processes and properties are summarized as follows; 1. From a simplified equation of water-balance on a watershed a regression model for monthly streamflow using the variables of rainfall, pan evaporation, and previous-month streamflow was formulated. 2. The hydrologic response of a watershed was represented lumpedly, qualitatively, and deductively using the regression coefficients of the water-balance regression model. 3. Regionalization was carried out to classify 33 watersheds on the basis of similarity through cluster analysis and resulted in 4 regional groups. 4. Prediction equations for the regional coefficients were derived from the stepwise regression analysis of watershed characteristics. It was also possible to explain geographic influences on streamflow through those prediction equations. 5. A model requiring the simple input of the data for rainfall, pan evaporation, and geographic factors was developed to estimate monthly streamflow at ungaged stations. The results of evaluating the performance of the model generally satisfactory.
Kim, Hyun-Soo;Ha, Mun-Keun;Baek, Myeong-Chul;Kim, Soo-Young;Park, Jong-Woo;Chun, Ho-Hwan
Journal of the Society of Naval Architects of Korea
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v.41
no.6
/
pp.120-125
/
2004
There are very few numbers of 115K FPP (Fixed Pitch Propulsion) Tankers for the Baltic ice class IA because the minimum power requirement of FMA (Finish- Swedish Maritime Association) needs quite large engine power and the 40 m Beam is out of calculation range of FMA minimum power requirements. The shipyard has no choice except to increase the engine power to satisfy FMA minimum power requirement Rule. And the operation cost, efficiency of hullform and its building cost are not good from the ship owners' point of view To solve this problem, the experience of ice breaking tanker development and the ice tank test results were adopted. The main idea to reduce the ice resistance is by reducing waterline angle at design load waterline. The reason behind the main idea is to reduce the ice-clearing force. Two hull forms were developed to satisfy Baltic Ice class IA. Two ice tank tests and one towing tank test was performed at MARC (Kvaener-Masa Arctic Research Center) and SSMB (Samsung Ship Model Basin) facilities, respectively. The purpose of these tests was to verify the performance in ice and open water respectively The hull form 2 shows less speed loss compared to Hull form 1 in open water operation but hull form 2 shows very good ice clearing ability. finally the Hull Form 2 satisfying Baltic ice class IA. The merit of this hull form is to use the same engine capacity and no major design changes in hull form and other related designs But the hull structure has to be changed according to the ice class grade. The difference in two hull form development methods, ice model test methods and analysis methods of ice model test will be described in this paper.
Jeong, Jae Yong;Lee, Ju Hong;Choi, Bum Ghi;Song, Jae Won
Smart Media Journal
/
v.11
no.3
/
pp.9-17
/
2022
Algorithmic trading, which uses algorithms to trade financial products, has a problem in that the results are not stable due to many factors in the market. To alleviate this problem, ensemble techniques that combine trading algorithms have been proposed. However, there are several problems with this ensemble method. First, the trading algorithm may not be selected so as to satisfy the minimum performance requirement (more than random) of the algorithm included in the ensemble, which is a necessary requirement of the ensemble. Second, there is no guarantee that an ensemble model that performed well in the past will perform well in the future. In order to solve these problems, a method for selecting trading algorithms included in the ensemble model is proposed as follows. Based on past data, we measure the contribution of the trading algorithms included in the ensemble models with high performance. However, for contributions based only on this historical data, since there are not enough past data and the uncertainty of the past data is not reflected, the contribution distribution is approximated using the Dirichlet distribution, and the contribution values are sampled from the contribution distribution to reflect the uncertainty. Based on the contribution distribution of the trading algorithm obtained from the past data, the Transformer is trained to predict the future contribution. Trading algorithms with high predicted future contribution are selected and included in the ensemble model. Through experiments, it was proved that the proposed ensemble method showed superior performance compared to the existing ensemble methods.
Journal of the military operations research society of Korea
/
v.34
no.3
/
pp.41-51
/
2008
Advanced high-tech weapons have enormous affect on combat strength in modern warfare. However, lack of maintenance can cause decrease in equipment operating rate as well as decrease in expectation on demonstrative effect of combat strength during wartime. Therefore it is essential for combat readiness that the optimum requirement of equipment maintenance cost are forecasted and included in the budget. In this paper, the trend of equipment maintenance cost about K-111 1/4t military vehicle is first analyzed by evaluating the performance data of field operation. Secondly, based on above analyzed results, the forecasting model of equipment maintenance cost is designed. Finally, by applying this forecasting model, suggestion and estimation method of equipment maintenance cost have presented for the foreseeable future.
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