• Composites Research
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• v.33 no.4
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• pp.220-227
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• 2020

When curing the composite, the fibers have little thermal deformation, but the resin changes its properties with time and temperature, which leads to residual stress in the product. Residual stress is caused by the difference in the coefficient of thermal expansion of the fibers and resin during the curing process and the chemical shrinkage of the resin. This difference causes thermal deformation such as spring-in and warpage. Thermal deformation of composite structure is important issue on quality of product, and it should be considered in manufacturing process. In this study, a subroutine was developed to predict thermal deformation by applying 3-D viscoelastic model. The finite element analysis was verified by comparing the results of the plate analysis of the 2-D viscoelastic model. Spring-in of L-shaped structure was predicted and analyzed by applying the 3-D viscoelastic model.

• The Journal of Engineering Geology
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• v.34 no.3
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• pp.381-401
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• 2024

To predict the ground subsidence caused by mines, various evaluation methods were applied to cases of ground subsidence in Korea, and the results were compared and analyzed. Continuous subsidence, which is relatively easily and accurately predicted, was excluded in this analysis. The stress arch - volumetric expansion method, limit equilibrium method, numerical analysis, probabilistic method, and evaluation method of the Korea Mine Rehabilitation and Mineral Resources Corporation (KO MIR) were applied to 36 subsidence cases, including subsidence location, width, and depth, and goaf width, depth, and incline data. The stress arch - volumetric expansion method was the most accurate with an accuracy of ~92%. In the case of the KOMIR method, the regression model is 86.1% accurate, but somewhat lower in accuracy using a triangular pyramidal volume. The stress arch - volumetric expansion and KOMIR methods have the disadvantage of evaluating whether subsidence occurs or not. In the case of the numerical analysis, the accuracy is 72.3% when estimating the subsidence depth, but is slightly lower (55.8%) when estimating the subsidence width. The probabilistic and limit equilibrium methods have similar accuracies of 50.8~63.7%. Given it is possible to determine whether subsidence occurs, and the subsidence location, width, and depth with each method, it is recommended to apply various methods when evaluating sinkhole-type subsidence.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.1141-1141
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• 2001

The aim of the study was to evaluate the performance of 3 calibration methods, modified partial least squares (MPLS), local PLS (LOCAL) and artificial neural network (ANN) on the prediction of chemical composition of forages, using a large NIR database. The study used forage samples (n=25,977) from Australia, Europe (Belgium, Germany, Italy and Sweden) and North America (Canada and U.S.A) with information relative to moisture, crude protein and neutral detergent fibre content. The spectra of the samples were collected with 10 different Foss NIR Systems instruments, which were either standardized or not standardized to one master instrument. The spectra were trimmed to a wavelength range between 1100 and 2498 nm. Two data sets, one standardized (IVAL) and the other not standardized (SVAL) were used as independent validation sets, but 10% of both sets were omitted and kept for later expansion of the calibration database. The remaining samples were combined into one database (n=21,696), which was split into 75% calibration (CALBASE) and 25% validation (VALBASE). The chemical components in the 3 validation data sets were predicted with each model derived from CALBASE using the calibration database before and after it was expanded with 10% of the samples from IVAL and SVAL data sets. Calibration performance was evaluated using standard error of prediction corrected for bias (SEP(C)), bias, slope and R2. None of the models appeared to be consistently better across all validation sets. VALBASE was predicted well by all models, with smaller SEP(C) and bias values than for IVAL and SVAL. This was not surprising as VALBASE was selected from the calibration database and it had a sample population similar to CALBASE, whereas IVAL and SVAL were completely independent validation sets. In most cases, Local and ANN models, but not modified PLS, showed considerable improvement in the prediction of IVAL and SVAL after the calibration database had been expanded with the 10% samples of IVAL and SVAL reserved for calibration expansion. The effects of sample processing, instrument standardization and differences in reference procedure were partially confounded in the validation sets, so it was not possible to determine which factors were most important. Further work on the development of large databases must address the problems of standardization of instruments, harmonization and standardization of laboratory procedures and even more importantly, the definition of the database population.

• Preventive Nutrition and Food Science
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• v.6 no.3
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• pp.163-169
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• 2001

To produce expanded, minimally hard extrudates from blends of raw pork meat (20%), defatted soy flour (25%), and corn starch using a single-screw extruder, various combinations of feed moisture, process temperature, and screw speed were evaluated. First series of extrusion runs were conducted according to a central composite rotatable design/response surface methodology (RSM). Upon assessing the full model for each response, insignificant terms were eliminated to determine final response surface models. Screw speed within the range evaluated was found to have no significant effect on expansion ratio (ER) or shear force (SF) of extrudates. Since examinations of the response surfaces and their generated grids of predicted values indicated that maximum ER and minimum SF were likely to be attained with a moisture-temperature combination outside the RSM experimental range, the second series of extrusion runs were conducted with several selected combinations of moisture and temperature to determine a practical optimum extrusion condition. The combination of 22.78% feed moisture, 16$0^{\circ}C$ process temperature, and 170 rpm screw speed was chosen as such a condition, and used in the final extrusion. The final product required less force to break than did commercial pretzel sticks.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.22 no.1
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• pp.61-73
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• 2012

The paper presents the novel approach to solve some problems occurred in application of the genetic algorithm to the determination of the optimal tire pattern sequence in order to reduce the tire air-pumping noise which is generated by the repeated compression and expansion of the air cavity between tire pattern and road surface. The genetic algorithm has been used to find the optimal tire pattern sequence having a low level of tire air-pumping noise using the image based air-pumping model. In the genetic algorithm used in the previous researches, there are some problems in the encoding structure and the selection of objective function. The paper proposed single encoding element with five integers, divergent objective function based on evolutionary process and the optimal evolutionary rate based on Shannon entropy to solve the problems. The results of the proposed genetic algorithm with evolutionary process are compared with those of the randomized algorithm without evolutionary process on the two-dimensional normal distribution. It is confirmed that the genetic algorithm is more effective to reduce the peak value of the predicted tire air-pumping noise and the consistency and cohesion of the obtained simulation results are also improved in terms of probability.

• Structural Engineering and Mechanics
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• v.61 no.6
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• pp.693-700
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• 2017

Concrete cover cracking due to the corrosion of steel reinforcing bars is one of the main causes of deterioration in Reinforced Concrete (RC) structures. The oxidation level of the bars causes varying levels of expansion. The rebar expansions could lead to through-thickness cracking of the concrete cover, where depending on the cracking characteristics, the service life of the structures would be affected. In this paper, the effect of geometrical and material parameters, i.e., concrete cover thickness, reinforcing bar diameter, and concrete tensile strength, on the required pressure for concrete cover cracking due to corrosion has been investigated through detailed numerical simulations. ABAQUS finite element software is employed as a modeling platform where the concrete cracking is simulated by means of eXtended Finite Element Method (XFEM). The accuracy of the numerical simulations is verified by comparing the numerical results with experimental data obtained from the literature. Using a previously proposed empirical equation and the numerical model, the time from corrosion initiation to the cover cracking is predicted and then compared to the respective experimental data. Finally, a parametric study is undertaken to determine the optimum ratio of the rebar diameter to the reinforcing bars spacing in order to avoid concrete cover delamination.

• Proceedings of the KWS Conference
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• 2002.10a
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• pp.694-699
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• 2002

In autobody assembly, thin-wall, tubular connections have been used for the frame structure. Recent interest in light materials, such as aluminum or magnesium alloys, has been rapidly growing for weight reduction and fuel efficiency. Due to higher thermal expansion coefficient, low stiffness/strength, and low softening temperature of aluminum and magnesium alloys, control of welding-induced distortion in these connections becomes a critical issue. In this study, the material sensitivity to welding distortion was investigated using a T-tubular connection of three types materials; low carbon steel (A500 Gr. A), aluminum alloy (5456-H116) and magnesium alloy (AZ91C-T6). An uncoupled thermal and mechanical finite element analysis scheme using the ABAQUS software program was developed to model and simulate the welding process, welding procedure and material behaviors. The predicted angular distortions were correlated to the cumulative plastic strains. A unique relationship between distortion and plastic strains exists for all three materials studied. The amount of distortion is proportional to the magnitude and distribution of the cumulative plastic strains in the weldment. The magnesium alloy has the highest distortion sensitivity, followed by the other two materials with the steel connection having the least distortion. Results from studies of thin-aluminum plates show that welding distortion can be minimized by reducing the cumulative plastic strains by preventing heat diffusion into the base metal using a strong heat sink placed directly beneath the weld. A rapid cooling method is recommended to reduce welding distortion of magnesium tubular connections.

• Journal of Welding and Joining
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• v.9 no.3
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• pp.41-51
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• 1991

The thermomechanical coupling phenomena in the resistance welding process is complicated due to interactions of mechanical, thermal and electrical factors. Although experimental investigations of resistance spot welding have been carried out, but there are a few by computer simulation. so the purpose of this research is to decrease the time and cost much required in experimental investigation by carrying out the analysis of the resistance spot welding process through computer simulation based on the finite element method. The tool used in the computer simulation is the commercial ANSYS program package. A two dimensional axisymetric model is used to simulate the resistance spot welding for two stainless steel sheets of equal thickness and parametric study is carried out for variable welding current, workpieces of unequal thickness and dissimilar materials. The results from the computer simulation are in good agreement with the experimental one. Through these results, such items as stress distribution, temperature profiles, thermal expansion and weld nugget formation are predicted. Reliability and applicability of finite element models have been demonstrated to simulate and to analyze the resistance spot welding process.

• Publications of The Korean Astronomical Society
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• v.15 no.spc1
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• pp.147-151
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• 2000

Symbiotic stars, believed to be binary systems of a mass-losing giant and a white dwarf with an emission nebula, are known to exhibit very broad wings around Hex that extend to $\~10^3km\;s^{-1}$. The wing formation mechanism is not a settled matter and recently Lee (2000) proposed that Raman scattering of Ly$\beta$ by neutral hydrogen is responsible for the broad H$\alpha$ wings. In this model, it is predicted that. the Hex wings will be polarized depending on the geometric and kinematic distribution of the scatterers relative to the UV emission region. In this paper, we investigate the polarization of Hex wings in symbiotic stars. Noting that many symbiotic stars possess bipolar nebular morphology, we assume that the distribution of neutral scatterers follows the similar pattern with a receding velocity of several tens of km $s^{-1}$ that mimics the expansion of the neutral envelope of the nebula. It is found that the red wing is more strongly polarized than the blue and main part and that the polarization direction is along the equatorial plane. We obtain a typical degree of polarization $\~10$ percent, however, it varies depending on the detailed distribution of H I scatterers We conclude that spectropolarimetry will provide very important information on the origin of the Hex wings.

• Journal of information and communication convergence engineering
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• v.11 no.1
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• pp.30-44
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• 2013

Traffic congestion has become a serious problem with the recent exponential increase in the number of vehicles. In urban areas, almost all traffic congestion occurs at intersections. One of the ways to solve this problem is road expansion, but it is difficult to realize in urban areas because of the high cost and long construction period. In such cases, traffic signal control is a reasonable method for reducing traffic jams. In an actual situation, the traffic flow changes randomly and its randomness makes the control of traffic signals difficult. A prediction of traffic jams is, therefore, necessary and effective for reducing traffic jams. In addition, an autonomous distributed (stand-alone) point control of each traffic light individually is better than the wide and/or line control of traffic lights from the perspective of real-time control. This paper describes a stochastic optimum control of crossroads and multi-way traffic signals. First, a stochastic model of traffic flows and traffic jams is constructed by using a Bayesian network. Secondly, the probabilistic distributions of the traffic flows are estimated by using a cellular automaton, and then the probabilistic distributions of traffic jams are predicted. Thirdly, optimum traffic signals of crossroads and multi-way intersection are searched by using a modified particle swarm optimization algorithm to realize real-time traffic control. Finally, simulations are carried out to confirm the effectiveness of the real-time stochastic optimum control of traffic signals.