• Journal of Mechanical Science and Technology
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• v.15 no.12
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• pp.1801-1807
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• 2001

In multiphase flne the bubble size and velocity. To achieve this, one of approaches is to utilize laser phase-Doppler anemometry. However, it was found that the second order refraction has great impact on PDA sizing method when the relative refractive index of media is less than one. In this paper, the problem of second order refraction is investigated and a model of phase-size correlation to eliminate the measurement errors is introduced for bubble sizing. As a result, the model relates the assumption of single scattering mechanism in conventional phase-Doppler anemometry. The results of simulations based on this new model by using Generalized Lorenz Mie Theory (GLMT) are compared with those based on the conventional method. An optimization method for accurately sizing air-bubble in water has been suggested.

• Korean Chemical Engineering Research
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• v.62 no.3
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• pp.214-224
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• 2024

Valves play an essential role in a chemical plant such as regulating fluid flow and pressure. Therefore, optimal selection of the valve size and type is essential task. Valve size and type have been selected based on theoretical formulas about calculating valve sizing coefficient (Cv). However, this approach has limitations such as requiring expert knowledge and consuming substantial time and costs. Herein, this study developed a model for predicting valve sizes and types using machine learning. We developed models using four algorithms: ANN, Random Forest, XGBoost, and Catboost and model performances were evaluated using NRMSE & R² score for size prediction and F1 score for type prediction. Additionally, a case study was conducted to explore the impact of phases on valve selection, using four datasets: total fluids, liquids, gases, and steam. As a result of the study, for valve size prediction, total fluid, liquid, and gas dataset demonstrated the best performance with Catboost (Based on R², total: 0.99216, liquid: 0.98602, gas: 0.99300. Based on NRMSE, total: 0.04072, liquid: 0.04886, gas: 0.03619) and steam dataset showed the best performance with RandomForest (R²: 0.99028, NRMSE: 0.03493). For valve type prediction, Catboost outperformed all datasets with the highest F1 scores (total: 0.95766, liquids: 0.96264, gases: 0.95770, steam: 1.0000). In Engineering Procurement Construction industry, the proposed fluid-specific machine learning-based model is expected to guide the selection of suitable valves based on given process conditions and facilitate faster decision-making.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2001.01a
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• pp.224-229
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• 2001

When a semiconductor package is assembled, various materials such as die attach adhesive, lead frame, EMC (Epoxy Molding Compound), and gold wire are used. For better preconditioning performance, the combination between the packaging materials by studying the compatibility of their properties as well as superior packaging material selection is important. But it is not an easy task to find proper packaging material sets, since a variety of factors like package design, substrate design, substrate size, substrate treatment, die size, die thickness, die passivation, and customer requirements should be considered. This research applies case-based reasoning(CBR) technique to solve this problem, utilizing prior cases that have been experienced. Our particular interests lie in building decision support model to aid the selection of proper die attach adhesive. The preliminary results show that this approach is promising.

• Journal of Power Electronics
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• v.12 no.1
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• pp.164-171
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• 2012

Variable step size maximum power point trackers (MPPTs) are widely used in photovoltaic (PV) systems to extract the peak array power which depends on solar irradiation and array temperature. One essential factor which judges system dynamics and steady state performances is the scaling factor (N), which is used to update the controlling equation in the tracking algorithm to determine a new duty cycle. This paper proposes a novel stability study of variable step size incremental resistance maximum power point tracking (INR MPPT). The main contribution of this analysis appears when developing the overall small signal model of the PV system. Therefore, by using linear control theory, the boundary value of the scaling factor can be determined. The theoretical analysis and the design principle of the proposed stability analysis have been validated using MATLAB simulations, and experimentally using a fixed point digital signal processor (TMS320F2808).

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2003.05a
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• pp.1028-1034
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• 2003

We consider the sensitivity of average inventory cost rate when true values of the parameters In the EOQ model are unknown over known ranges. In particular, In the case that the valid range on the true economic lot size are known. we provide a formula for estimating the lot size under minimax criterion. Moreover, to estimate the valid range, we apply the propagation of errors technique. Then, we present a scheme to find a (valid) lot size. based on the estimated range of the true lot size from the propagation or errors technique.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.58 no.1
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• pp.1-9
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• 2022

In this study, the selection action on the mesh in the net pot for whelk (Buccinum opisthoplectum) is experimentally considered, and the selectivity was compared by the SELECT model and the Nashimoto's method with the probability model according to the contact shape of the mesh and the whelk. The experiments of the mesh size selectivity was conducted for two mesh sizes: 70 mm (inner stretched size 65.4 mm) and 44 mm (inner stretched size 39.5 mm). Selectivity experiments were conducted three times in total for each mesh size used 264 whelks. In addition, Nashimoto's method analyzed the retention probability using probability model for whether the mesh passed or not based on the carapace width of the whelk. As a result of the selectivity analysis, the 50% selection carapace width for the mesh size of 70 mm was similar to 43.62 mm in the SELECT model and 42.64 mm in the Nashimoto's method. However, the 44 mm mesh with relatively small mesh size showed differences of 40.01 mm and 26.80 mm, respectively. As for the mesh size selectivity of whelk, it was found that the smaller the mesh size, the lower the selectivity. In addition, in the selectivity study on the mesh size of whelk, an evaluation method that closely considers the contact shape between the mesh and the target species is required.

• Journal of electromagnetic engineering and science
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• v.6 no.1
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• pp.47-52
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• 2006

The objective of this study is to evaluate the effects of size and permittivity on the specific absorption rate(SAR) values of rat brains during microwave exposure at mobile phone frequency bands. A finite difference time domain (FDTD) technique with perfect matching layer(PML) absorbing boundaries is used for this evaluation process. A color coded digital image of the Sprague Dawley(SD) rat based on magnetic resonance imaging(MRI) is used in FDTD calculation with appropriate permittivity values corresponding to different tissues for 3, 4, 7, and 10 week old rats. This study is comprised of three major parts. First, the rat model structure is scaled uniformly, i.e., the rat size is increased without change in permittivity. The simulated SAR values are compared with other experimental and numerical results. Second, the effect of permittivity on SAR values is examined by simulating the microwave exposure on rat brains with various permittivity values for a fixed rat size. Finally, the SAR distributions in depth, and the brain-averaged SAR and brain 1 voxel peak SAR values are computed during the microwave exposure on a rat model structure when both size and permittivity have varied corresponding to different ages ranging from 3 to 10 weeks. At 900 MHz, the simulation results show that the brain-averaged SAR values decreased by about 54 % for size variation from the 3 week to the 10 week-old rat model, while the SAR values decreased only by about 16 % for permittivity variation. It is found that the brain averaged SAR values decreased by about 63 % when the variations in size and permittivity are taken together. At 1,800 MHz, the brain-averaged SAR value is decreased by 200 % for size variation, 9.7 % for permittivity variation, and 207 % for both size and permittivity variations.

• Journal of Energy Engineering
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• v.25 no.1
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• pp.69-75
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• 2016

Bubble size is a key parameter for an accurate prediction of bubble behaviours in the multi-dimensional two-phase flow. In the current STAR CCM+ CFD code, a mechanistic bubble size model $S{\gamma}$ is available for the prediction of bubble size in the flow channel. As another model, Yun model is developed based on DEBORA that is subcooled boiling data in high pressure. In this study, numerical simulation for the gas-liquid two-phase flow was conducted to validate and confirm the performance of $S{\gamma}$ model and Yun model, using the commercial CFD code STAR CCM+ ver. 10.02. For this, local bubble models was evaluated against the air-water data from DEDALE experiments (1995) and Hibiki et al. (2001) in the vertical pipe. All numerical results of $S{\gamma}$ model predicted reasonably the two-phase flow parameters and Yun model is needed to be improved for the prediction of air-water flow under low pressure condition.

• Structural Engineering and Mechanics
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• v.73 no.6
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• pp.631-640
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• 2020

Using backup plate is one of the most commonly used methods to decrease drilling-induced delamination of composite laminates. It has been shown that, the size of the delamination zone is related to the vertical element of cutting force named as thrust force. Also, direct control of thrust force is not a routine task, because, it depends on both drilling parameters and mechanical properties of the composite laminate. In this research, critical feed rate and thrust force are predicted analytically for delamination initiation in drilling of composite laminates with backup plate. Three common theories, linear elastic fracture mechanics, classical laminated plate and mechanics of oblique cutting, are used to model the problem. Based on the proposed analytical model, the effect of drill radius, chisel edge size, and backup plate size on the critical thrust force and feed rate are investigated. Experimental tests were carried out to prove analytical model.

• Transactions of Materials Processing
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• v.20 no.7
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• pp.491-497
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• 2011

This work describes a method for determining material parameters included in recrystallization and grain growth models of metallic materials. The focus is on the recrystallization and grain growth models of Ni-Fe based superalloy, Alloy 718. High temperature compression test data at different strain, strain rate and temperature conditions were chosen to determine the material parameters of the model. The critical strain and dynamically recrystallized grain size and fraction at various process conditions were generated from the microstructural analysis and strain-stress relationships of the compression tests. Also, isothermal heat treatments were utilized to fit the material constants included in the grain growth model. Verification of the determined material parameters is carried out by comparing the average grain size data obtained from other compression tests of the Alloy 718 specimens with the initial grain size of $59.5{\mu}m$.