• Journal of the Semiconductor & Display Technology
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• v.19 no.4
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• pp.59-64
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• 2020

In this paper, we found the solution using data based machine learning regression method to check the pore shape, to solve the problem of the experiment quantity occurring when producing scaffold with the 3d printer. Through experiments, we learned secured each print condition and pore shape. We have produced the scaffold from scaffold pore shape defect prediction model using multiple linear regression method. We predicted scaffold pore shapes of unsecured print condition using the manufactured scaffold pore shape defect prediction model. We randomly selected 20 print conditions from various predicted print conditions. We print scaffold five times under same print condition. We measured the pore shape of scaffold. We compared printed average pore shape with predicted pore shape. We have confirmed the prediction model precision is 99 %.

• The Journal of Engineering Geology
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• v.29 no.4
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• pp.367-381
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• 2019

We investigate pore pressure conditions and reservoir compaction associated with oil and gas production using 3 different permeability models, which are all based on one-dimensional radial flow diffusion model, but differ in considering permeability evolution during production. Model 1 assumes the most simplistic constant and invariable permeability regardless of production; Model 2 considers permeability reduction associated with reservoir compaction only due to pore pressure drawdown during production; Model 3 also considers permeability reduction but due to the effects of both pore pressure drawdown and coupled pore pressure-stress process. We first derive a unified stress-permeability relation that can be used for various sandstones. We then apply this equation to calculate pore pressure and permeability changes in the reservoir due to fluid extraction using the three permeability models. All the three models yield pore pressure profiles in the form of pressure funnel with different amounts of drawdown. Model 1, assuming constant permeability, obviously predicts the least amount of drawdown with pore pressure condition highest among the three models investigated. Model 2 estimates the largest amount of drawdown and lowest pore pressure condition. Model 3 shows slightly higher pore pressure condition than Model 2 because stress-pore pressure coupling process reduces the effective stress increase due to pore pressure depletion. We compare field data of production rate with the results of the three models. While models 1 and 2 respectively overestimates and underestimates the production rate, Model 3 estimates the field data fairly well. Our result affirms that coupling process between stress and pore pressure occurs during production, and that it is important to incorporate the coupling process in the permeability modeling, especially for tight reservoir having low permeability.

• Journal of the Semiconductor & Display Technology
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• v.18 no.4
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• pp.46-50
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• 2019

In this paper, We used the regression model of machine learning for improve the print quantity problem when which print scaffold with 400 ㎛ pore using FDM 3d printer. We have difficult to experiment with changing all factors in the field. So we reduced print quantity by selected two factors that most impact the pore size. We printed and measured scaffold 5 times under same conditions. We created regression model using scaffold pore size and print conditions. We predicted pore size of untested print condition using the regression model. After print scaffold with 400 ㎛ pore, we printed scaffold 5 times under same conditions. We compare the predicted scaffold pore size and the measured scaffold pore size. We confirmed that error is less than 1 % and we verified the results quantitatively.

• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.4
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• pp.135-144
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• 2015

Fingerprint pores have proven to be useful features for fingerprint recognition and several pore-based fingerprint recognition systems have been reported recently. In order to recognize fingerprints using pore information, it is very important to extract pores reliably and accurately. Existing pore extraction methods utilize 2D model fitting to detect pore centers. This paper proposes a pore extraction method using 1D Gaussian model which is much simpler than 2D model. During model fitting process, 1D model requires less computational cost than 2D model. The proposed method first calculates local ridge orientation; then, ridge mask is generated. Since pore center is brighter than its neighboring pixels, pore candidates are extracted using a $3{\times}3$ filter and a $5{\times}5$ filter successively. Pore centers are extracted by fitting 1D Gaussian model on the pore candidates. Extensive experiments show that the proposed pore extraction method can extract pores more effectively and accurately than other existing methods, and pore matching results show the proposed pore extraction method could be used in fingerprint recognition.

• Computers and Concrete
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• v.11 no.4
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• pp.317-336
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• 2013

In this study, the pore structure of Portland cement paste is experimentally characterized by MIP (mercury intrusion porosimetry) and nitrogen adsorption, and simulated by a newly developed status-oriented computer model. Cement pastes with w/c=0.3, 0.4 and 0.5 at ages from 1 day to 120 days are comprehensively investigated. It is found that MIP cannot generate valid pore size distribution curves for cement paste. Nevertheless, nitrogen adsorption can give much more realistic pore size distribution curves of small capillary pores, and these curves follow the same distribution mode. While, large capillary pores can be effectively characterized by the newly developed computer model, and the validity of this model has been proved by BSE imaging plus image analysis. Based on the experimental findings and numerical simulation, a hypothesis is proposed to explain the formation mechanism of the capillary pore system, and the realistic representation of the pore structure of hydrated cement paste is established.

• Magazine of the Korean Society of Agricultural Engineers
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• v.45 no.4
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• pp.137-143
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• 2003

The initial condition of $\Delta \sigma_3 \;=\; \Delta u$ is used for analyzing the time dependent behavior of ground. This is based on the concept that the coefficient of pore water B is the unity on the condition of saturation. but some measured consolidation data in the field showed that the pore water pressure was not dissipated as time elapsed but it was maintained constant value or it's dissipation rate was slower than that of the predicted. and so the measured data of pore water pressure was not consistent with that of settlement. In this study, the rheological model for the pore water pressure behavior on undrained condition was induced and compared with the experiment data of the literature. The result showed that the suggested model was consistent well with the result of experiment, but the suggested model could not explain the effect of the decrease of void ratio according to consolidation.

• Proceedings of the Korean Geotechical Society Conference
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• 2004.03b
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• pp.714-721
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• 2004

The purpose of this study is to find out the similitude laws for dissipation velocity of excess pore pressure after liquefaction according to magnitude of input accelerations and height of model soils from the results of impulse load tests. In impulse load tests, model soils were constructed to the height of 25cm, 50cm, and 100cm in acrylic tubes whose inside diameters were 19cm and 38cm respectively, and impulse loads were applied at the bottom of each model soil to liquefy the entire model soil. Excess pore pressure distribution by depth and settlement of soil surface were measured in each test. Dissipation curves of excess pore pressure measured in each tests were simulated by solidification theory, and dissipation velocities of excess pore pressure were determined from the slope of simulated dissipation curves. From the results of impulse load tests, dissipation velocity of excess pore pressure was not affected by magnitude of input acceleration, and from this fact, dissipation process was proved to be different from dynamic phenomenon. However, dissipation velocity of excess pore pressure increased as height of model soil increased and showed little difference as diameter of model soil increased. Therefore, the similitude law for dissipation velocity could be expressed by the similitude law for model height to 0.2 without regard to the diameter of model soil.

• Journal of Hydrogen and New Energy
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• v.21 no.4
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• pp.328-339
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• 2010

A new gasification model for coal char was developed considering the effects of pore structure and solid reaction product (ash) and compared with conventional models. Among various parameters reflecting microscopic pore structure, initial pore surface per unit volume of char was found to have the largest effect on carbon conversions. Reaction studies showed that the proposed model can predict carbon conversion more accurately over a broader range of reaction degree compared to the conventional models. Therefore the model proposed in this study would be useful for the design of pilot or commercial scale gasifiers.

• Journal of the Semiconductor & Display Technology
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• v.19 no.1
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• pp.36-41
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• 2020

In this paper, We need to change all print factors when which print scaffold with 400 ㎛ pore using FDM 3d printer. Therefore the print quantity is 10 billion times, So we are difficult to print on workplace. To solve the problem, we used the prediction model based machine learning regression. We preprocessed and learned the securing print condition data, and we produced different kinds of prediction models. We predicted the pore size of scaffolds not securing with new print condition data using prediction models. We have derived the print conditions that satisfy the pore size of 400 ㎛ among the predicted print conditions of pore size. We printed the scaffolds 5 times on the condition. We measured the pore size of the printed scaffold and compared the average pore size with the predicted pore size. We confirmed that error was less than 1%, and we were identify the model with the highest pore size prediction performance of scaffold.

• Nuclear Engineering and Technology
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• v.48 no.4
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• pp.1002-1008
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• 2016

An understanding of the coarsening process of the large fission gas pores in the high burn-up structure (HBS) of irradiated $UO_2$ fuel is very necessary for analyzing the safety and reliability of fuel rods in a reactor. A numerical model for the description of pore coarsening in the HBS based on the Ostwald ripening mechanism, which has successfully explained the coarsening process of precipitates in solids is developed. In this model, the fission gas atoms are treated as the special precipitates in the irradiated $UO_2$ fuel matrix. The calculated results indicate that the significant pore coarsening and mean pore density decrease in the HBS occur upon surpassing a local burn-up of 100 GWd/tM. The capability of this model is successfully validated against irradiation experiments of $UO_2$ fuel, in which the average pore radius, pore density, and porosity are directly measured as functions of local burn-up. Comparisons with experimental data show that, when the local burn-up exceeds 100 GWd/tM, the calculated results agree well with the measured data.