• Proceedings of the KSRS Conference
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• v.1
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• pp.406-408
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• 2006

Various geological thematic maps such as grain size or ground water level maps have been generated by interpolating sparsely sampled ground survey data. When there are sampled data at a limited number of locations, to use secondary information which is correlated to primary variable can help us to estimate the attribute values of the primary variable at unsampled locations. This paper applies two multivariate geostatistical algorithms to integrate remote sensing imagery with sparsely sampled ground survey data for spatial estimation of grain size: simple kriging with local means and kriging with an external drift. High-resolution IKONOS imagery which is well correlated with the grain size is used as secondary information. The algorithms are evaluated from a case study with grain size observations measured at 53 locations in the Baramarae beach of Anmyeondo, Korea. Cross validation based on a one-leave-out approach is used to compare the estimation performance of the two multivariate geostatistical algorithms with that of traditional ordinary kriging.

• The Korean Journal of Ceramics
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• v.4 no.2
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• pp.122-127
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• 1998

Conductivities of polycrystalline ceria doped with several rare earth oxides were measured by AC admittance and DC four probe method. The conductions were separated into grain and grain boundary contributions using the complex admittance technique as well as grain size dependence of conductivity. The grain size dependence of polycrystalline conductivity, which can be adequately described by the so-called brick layer model, appears to give a more reliable measure of the grain conductivity compared to the complex admittance method. Polycrystalline resistivity(1/conductivity) increases linearly with the reciprocal of grain size. The intercept of resistivity vs. inverse grain size plot gives a measure of the grain resistivity and the slope gives a measure of the grain boundary resistivity. It was also noted that errors involved in the analysis of experimental data may be different between the complex admittance method and the impedance method. A greater resolution of the spectra was found in the complex admittance method, insofar as the present work is concerned, suggesting that the commonly used equivalent circuit may require re-evaluation.

• Advances in nano research
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• v.14 no.2
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• pp.155-164
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• 2023

Grain size in sheet metals in one of the main parameters in determining formability. Grain size control in industry requires delicate process control and equipment. In the present study, effects of grain size on the formability of steel sheets is investigated. Experimental investigation of effect of grain size is a cumbersome method which due to existence of many other effective parameters are not conclusive in some cases. On the other hand, since the average grain size of a crystalline material is a statistical parameter, using traditional methods are not sufficient for find the optimum grain size to maximize formability. Therefore, design of experiment (DoE) and artificial intelligence (AI) methods are coupled together in this study to find the optimum conditions for formability in terms of grain size and to predict forming limits of sheet metals under bi-stretch loading conditions. In this regard, a set of experiment is conducted to provide initial data for training and testing DoE and AI. Afterwards, the using response surface method (RSM) optimum grain size is calculated. Moreover, trained neural network is used to predict formability in the calculated optimum condition and the results compared to the experimental results. The findings of the present study show that DoE and AI could be a great aid in the design, determination and prediction of optimum grain size for maximizing sheet formability.

• Journal of Welding and Joining
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• v.24 no.1
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• pp.77-87
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• 2006

Considering ferrite grain size in the base metal, the prediction model for $A_{c3}$ temperature and prior austenite grain size at just above $A_{c3}$ temperature was proposed. In order to predict $A_{c3}$ temperature, the Avrami equation was modified with the variation of ferrite grain size, and its kinetic parameters were measured from non-isothermal data during continuous heating. From calculation using a proposed model, $A_{c3}$ temperatures increased with increasing ferrite grain size and heating rate. Meanwhile, by converting the phase transformation kinetic model that predicts the ferrite grain size from austenite grain size during cooling, a prediction model for prior austenite grain size at just above the $A_{c3}$ temperature during heating was developed.

• Journal of The Korean Society of Agricultural Engineers
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• v.55 no.6
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• pp.127-133
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• 2013

The purpose of this study was to investigate maximum and minimum grain size which eroded by wind according to soil and wind conditions, such as top soil water content, roughness, land slope, wind velocity and proportion of grain size under 0.84mm. For performing this study, portable wind erosion tunnel was designed and utilized during field test, which facilitated measuring actual wind erosions under artificially controlled wind conditions. In the result, maximum, minimum grain size had strong negative correlation with roughness while weak positive correlation with wind velocity. Also, Slope which means the effect of gravity also influence grain size erodible by winds. Based on these results, regression equations were suggested for predicting maximum and minimum grain sizes by using multiple linear regression analysis from SPSS 20.0. The equation for maximum grain size erodible by winds showed a good agreement with the observed data with $R^2$=0.896. Other equation for minimum grain size had $R^2$=0.777.

• Fisheries and Aquatic Sciences
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• v.2 no.2
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• pp.210-217
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• 1999

Chemical oxygen demand (COD), phytoplankton cell number and chlorophyll-a concentration (Chl-a), sediment mean grain size and ignition loss were studied to determine their temporal trends in the study area. Historical data of COD, cell number and Chl-a were gathered from the late 1960s or early 1980s to 1997, and trends in temporal domain were obtained from a simple regression. Sediments for grain size and ignition loss (as organic contents in sediments) were sampled from the Chokchon macrotidal flat bimonthly from September 1990 to November 1996, and were analyzed using the decomposition method of time series analysis. In general, the first three data showed increasing trends based on regression analysis. The trends of sediment grain size fluctuated in a neutral pathway while those of ignition loss yielded no increasing pattern. In contrast with the suggestions from Ahn and Choi (1998) who reported a coarsening variation in sediment grain size to be a cause of the directional and remarkable changes of macrofaunal communities in this area, we could not find such a corresponding variation pattern from our samples. In diagnosing eutrophication, a paradoxical phenomenon was encountered between the trends in water column (COD, cell number and Chl-a) and sediment (ignition loss) data. In this paper, we inferred the possible processes that produce the discrepancy. Some explanations and biological responses to eutrophication were predicted and discussed.

• Journal of The Geomorphological Association of Korea
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• v.27 no.2
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• pp.19-28
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• 2020

Grain size analysis is the most basic procedure for identifying the origin, transport and sedimentation processes of sediments, and is widely used in geomorphology and sedimentology. Traditionally, grain size was determined by a sieve-pippette method, but the use of automated analyzers is increasing in recent years. These analyzers have many advantages over traditional techniques, but the measurement results are not always the same. It is still difficult to solve the pretreatment problem such as incomplete diffusion and residual organic matter, and inappropriate results may be obtained. This study compared image-based grain size analysis and sieve analysis to verify its statistical reliability, and conducted experiments to enhance the measurement accuracy using shape parameters. The results showed that the image-based analysis overestimated the grain size of sand dunes by about 7% compared to the sieve analysis, but the two measurements were not statistically different. In addition, by using shape parameters, such as aspect ratio, sphericity, and convexity, improved statistics were obtained compared to the original data. Using the morphological properties of the individual grains is a complementary method to the incomplete pretreatment of the grain size analysis process, and at the same time, it will contribute to improving the accuracy and reliability of the results.

• Proceedings of the Korean Powder Metallurgy Institute Conference
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• 2006.09a
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• pp.344-345
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• 2006

The linear intercept (LI) method was used to quantitatively measure the intercepts of WC grains in nano-grained WC-10Co hardmetal. When the surveyed intercept numbers of WC grain exceeded 200, the statistic data for the mean grain size of WC were reproduced. The discriminative minimal grain size of used LI method was 12 nm; the maximum intercept of WC grain was 109 nm; the average intercept of WC grains was 45 nm and the corresponding 3D mean grain size of WC was 70 nm which is agreeable with the XRD outcome.

• 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 $59.5{\mu}m$.

• Transactions of Materials Processing
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• v.9 no.6
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• pp.663-669
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• 2000

A material model has been presented, at the continuum level, for the representation of superplastic deformation coupled with microstructural evolution. The model presented enables the effects of the spatial variation of distributions of grain size to be predicted at the process level. The model has been tested under conditions of both homogeneous and inhomogeneous stress and strain by carrying out detailed comparison of predicted distributions of grain size and their evolutions with experimentally obtained data. Experimental measurements have shown the extent of the spatial variation of the distribution of grain size that exists in the titanium alloy, Ti-6Al-4V. It is shown that whilst not large, the variations in grain size distributions are sufficient to lead to the development of inhomogeneous deformation in test pieces, which ultimately result in localisation of strain and failure.