• Journal of Korean Tunnelling and Underground Space Association
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• v.24 no.4
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• pp.317-326
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• 2022

This research performed single fiber pull-out test to evaluate the effect between fineness modulus of cement composites and the fiber bond performance (bond strength and pull-out energy). A synthetic fiber (polypropylene) and a steel fiber (hooked ends type) were inserted in the middle of dog bone shape specimens which were designed with fine aggregates of F. M. 1.96, 2.69, 3.43. The experiment results showed bond strength and pullout energy of synthetic fiber are improved as fineness modulus of cement composites increases. It is considered that the frictional resistance between synthetic fiber and cement composite increases as fineness modulus of cement composite increases and consume more energy while pull out the fiber from cement composite. However bond performance of steel fiber which resist pull out by mechanical behavior is less effected on fineness modulus of cement composite. It is considered that the mechanical fixedness of hooked ends exerts a greater effect on the pullout resistance than the frictional resistance between the cement composite and the steel fiber so F. M. of fine aggregate has a relatively small effect on the pullout resistance with the steel fiber.

• Geophysics and Geophysical Exploration
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• v.26 no.3
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• pp.114-125
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• 2023

The physics-informed neural network (PINN) has been proposed to overcome the limitations of various numerical methods used to solve partial differential equations (PDEs) and the drawbacks of purely data-driven machine learning. The PINN directly applies PDEs to the construction of the loss function, introducing physical constraints to machine learning training. This technique can also be applied to wave equation modeling. However, to solve the wave equation using the PINN, second-order differentiations with respect to input data must be performed during neural network training, and the resulting wavefields contain complex dynamical phenomena, requiring careful strategies. This tutorial elucidates the fundamental concepts of the PINN and discusses considerations for wave equation modeling using the PINN approach. These considerations include spatial coordinate normalization, the selection of activation functions, and strategies for incorporating physics loss. Our experimental results demonstrated that normalizing the spatial coordinates of the training data leads to a more accurate reflection of initial conditions in neural network training for wave equation modeling. Furthermore, the characteristics of various functions were compared to select an appropriate activation function for wavefield prediction using neural networks. These comparisons focused on their differentiation with respect to input data and their convergence properties. Finally, the results of two scenarios for incorporating physics loss into the loss function during neural network training were compared. Through numerical experiments, a curriculum-based learning strategy, applying physics loss after the initial training steps, was more effective than utilizing physics loss from the early training steps. In addition, the effectiveness of the PINN technique was confirmed by comparing these results with those of training without any use of physics loss.

• Journal of Korean Tunnelling and Underground Space Association
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• v.11 no.4
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• pp.395-401
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• 2009

One of the key design factors for the ventilation and safety system at extra long tunnel is the airflow velocity induced by the natural ventilation force. Despite of the importance, it has not been widely studied due to the complicated influencing variables and the relationship among them is difficult to quantify. At this moment none of the countries in the world defines its specific value on verified ground. It is also the case in Korea. The recent worldwide disasters by tunnel fires and demands for better air quality inside tunnel by users require the optimization of the tunnel ventilation system. This indicates why the natural ventilation force is necessary to be thoroughly studied. This paper aims at predicting the natural ventilation force at a 11 km-long tunnel which is in the stage of detailed design and will be the longest vehicle tunnel in Korea. The concept of barometric barrier which can provide the maximum possible natural ventilation force generated by the topographic effect on the external wind is applied to estimate the effect of wind pressure and the chimney effect caused by the in and outside temperature difference is also analyzed.

• The Journal of the Convergence on Culture Technology
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• v.9 no.6
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• pp.245-250
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• 2023

Digital twin technology, which copies information from real space into virtual space, is being used in a variety of fields.Interest in digital twins is increasing, especially in advanced manufacturing fields such as Industry 4.0-based smart manufacturing. Operating a digital twin system generates a large amount of data, and the data generated has different characteristics depending on the technology field, so it is necessary to efficiently manage resources and use an optimized digital twin platform technology. Research on digital twin pipelines has continued, mainly in the advanced manufacturing field, but research on high-speed pipelines suitable for data in the plant field is still lacking. Therefore, in this paper, we propose a pipeline design method that is specialized for digital twin data in the plant field that is rapidly poured through Apache Kafka. The proposed model applies plant information on a Revit basis. and collect plant-specific data through Apache Kafka. Equipped with a lightweight CFD engine, it is possible to create a digital twin model that is more suitable for the plant field than existing digital twin technology for the manufacturing field.

• Journal of Korean Tunnelling and Underground Space Association
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• v.26 no.1
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• pp.39-58
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• 2024

Tunnel Boring Machines (TBM) use multiple disc cutters to excavate tunnels through rock. These cutters wear out due to continuous contact and friction with the rock, leading to decreased cutting efficiency and reduced excavation performance. The rock's abrasivity significantly affects cutter wear, with highly abrasive rocks causing more wear and reducing the cutter's lifespan. The Cerchar Abrasivity Index (CAI) is a key indicator for assessing rock abrasivity, essential for predicting disc cutter life and performance. This study aims to develop a new method for effectively estimating CAI using rock strength, petrological characteristics, linear regression, and machine learning. A database including CAI, uniaxial compressive strength, Brazilian tensile strength, and equivalent quartz content was created, with additional derived variables. Variables for multiple linear regression were selected considering statistical significance and multicollinearity, while machine learning model inputs were chosen based on variable importance. Among the machine learning prediction models, the Gradient Boosting model showed the highest predictive performance. Finally, the predictive performance of the multiple linear regression analysis and the Gradient Boosting model derived in this study were compared with the CAI prediction models of previous studies to validate the results of this research.

• Progress in Medical Physics
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• v.10 no.2
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• pp.73-81
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• 1999

Scatter correction for single photon emission computed tomography (SPECT) plays an important role to improve image quality and quantitation. The purpose of this study was to investigate three scatter correction methods using Monte Carlo simulation. Point source and Jaszack phantom filled with Tc-99m were simulated by Monte Carlo code, SIMIND. For scatter correction, we applied three methods, Compton window (CW) method, triple window (TW) method, and dual photopeak window (DPW) method. Point sources located at various depths along the center line within a 20-cm phantom were simulated to calculate the window ratios and corresponding scatter fractions by evaluating the polynomial coefficients for DPW method. Energy windows were located in W$_1$=92-125 keV, W$_2$=124-126 keV, W$_3$=136-140 keV, W$_4$=140-141 keV, and W$_{5}$=154-156 keV. The results showed that in Jaszack phantom with cold sphere and hot sphere, the TW gave the closest contrast and percentage recovery to the ideal image, respectively, while CW overestimated and DPW underestimated the contrast of ideal one. All three scatter correction methods showed an improved image contrast. In conclusion, scatter correction is essential for improving image contrast and accurate quantification. The choice of scatter correction method should be made on the basis of accuracies and ease of implementation.

• Journal of Korea Water Resources Association
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• v.47 no.1
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• pp.25-35
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• 2014

The objective of this study is to evaluate TOPLATS land surface model performance through comparison of results of water and energy balance analysis. The study area is selected Nakdong river basin and high resolution hydrometeorological components of which spatio-temporal resolution is 1 hr and 1 km are simulated during 2003 to 2013. The simulated daily and monthly depth of flows are well fitted with the observed one on Andong and Hapcheon dam basin. In results of diurnally analysis of energy components, change pattern throughout the day of net radiation, latent heat, sensible heat, and ground heat under energy balance analysis have higher accuracy than ones under water balance analysis at C3 and C4 sites. Especially, root mean square errors of net radiation and latent heat at C4 site are shown very low as 22.18 $W/m^2$ and 7.27 $W/m^2$, respectively. Mean soil moisture and evapotranspiration in summer and winter are simulated as 36.80%, 33.08% and 222.40 mm, 59.95 mm, respectively. From this result, when we need high resolution hydrometeorological components, energy balance analysis is more reasonable than water balance analysis. And this results will be used for monitor and forecast of weather disaster like flood and draught using spatial hydrometeorological information.

• Journal of Nuclear Fuel Cycle and Waste Technology(JNFCWT)
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• v.11 no.3
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• pp.245-251
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• 2013

The energy band and the G-factor method were compared to determine the exposure rate from the measured spectrum using a NaI(Tl) scintillation detector. First, G-factors of a 3"${\Phi}X3$" NaI(Tl) detector mounted to a EFRD 3300, which means the environmental radiation monitor, in Korea Atomic Energy Research Institute (KAERI) were calculated for several directions of incident photons through the MCNP modeling, and the optimum G-factor applicable to that monitor was then determined by comparing the results both the energy band method and the G-factor method. The results for these spectrometric determinations were also compared with the dose rate from a HPIC radiation monitor around a EFRD 3300. The measured value at the EFRD 3300 based on a 3"${\Phi}X3$" NaI(Tl) detector was $7.7{\mu}R/h$ and its difference was shown about $3{\mu}R/h$, when compared with the results from a HPIC radiation moditor. Since a HPIC is known to be able to measure cosmic rays with the relatively high energy, the difference between them was caused by cosmic rays which were not detected in a 3"${\Phi}X3$" NaI(Tl) detector.

• Korean Journal of Construction Engineering and Management
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• v.20 no.2
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• pp.53-59
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• 2019

As solve the shortage problems of storage space for exhibition facilities, the South Korean government is establishing plans to expand storage space for exhibition facilities. From a medium- to long-term perspective, an energy-efficient storage space for exhibition facility is needed to implement efficient state budget execution and achieve national greenhouse gas reduction goals. In this regard, this study analyzed the energy consumption of storage space for exhibition facilities according to the use of absorption materials. To this end, a case study was conducted on 12 storage spaces for exhibition facilities in South Korea. Compared to the storage space using the absorption material, the storage space without using the absorption material showed an increase in HVAC system operation time by 47.50% during summer periods and 58.85% in non-summer periods. In particular, the analysis found that in the case of storage for 'H' exhibition facility, the energy cost was reduced by 2,721,700 won/year after remodeling work using the absorption material. It is expected that the findings of this study can help the government and the person in charge from construction companies to construct energy-efficient storage space room for exhibition facilities.

• Journal of the Korean Institute of Landscape Architecture
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• v.47 no.3
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• pp.12-21
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• 2019

In order to investigate the effect of various pavement materials (artificial grass, natural grass, and clay sand) on the human thermal environment, the microclimate data in early autumn (air temperature, humidity, wind speed, and shortwave and longwave radiation) were measured and compared on each surface. The mean air temperature, humidity and wind speed of the pavement materials did not differ significantly and showed the greatest difference in the mean radiant temperature. Natural grass, which has the highest albedo, has the highest amount of shortwave radiation. The artificial turf had the highest surface temperature and the highest amount of longwave radiation. In the human thermal environment index PET, artificial grass > clay sand > natural grass. Natural grass had a maximum 2/3 level lower and a mean 1/2 level lower in PET as compared to artificial grass. The clay sand pavement had a maximum 2/3 level lower and a mean 1/3 level lower than the artificial grass. Natural grass had a maximum 1/3 level lower than the clay sand pavement. Their UTCIs showed smaller differences than the PETs. Therefore, it is necessary to carefully choose materials from the planning stage when designing outdoor spaces, including playgrounds.