• Journal of Aerospace System Engineering
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• v.16 no.6
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• pp.54-63
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• 2022

Recently, electric propulsion aircraft with various propeller mounting positions have been under construction. The position of the propeller relative to the wing can significantly affect the aerodynamic performance of the aircraft. Placing the propeller in front of the wing produces a complex swirl flow behind or around the propeller. The up/downwash induced by the swirl flow can alter the wing's local effective angle of attack, causing a change in the aerodynamic load distribution across the wing's spanwise direction. This study investigated the influence of the distance between a propeller and a wing on the aerodynamic loads on the wing. The swirl flow generated by the propeller was modelled using an actuator disk theory, and the wing's aerodynamics were analysed with the VSPAERO tool. Results of the study were compared to wind tunnel test data and established that both axial and spanwise distance between the propeller and the wing positively affect the wing's lift-to-drag ratio. Specifically, it was observed that the lift-to-drag ratio increases when the propeller is positioned higher than the wing.

• Journal of the Korean Electrochemical Society
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• v.25 no.1
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• pp.1-12
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• 2022

Lithium metal is the most promising anode for next-generation lithium-ion batteries due to its lowest reduction potential (-3.04 V vs. SHE) and high specific capacity (3860 mAh/g). However, the dendritic formation under high charging current density remains one of main technical barriers to be used for commercial rechargeable batteries. To address these issues, tremendous research to suppress lithium dendrite formation have been conducted through new electrolyte formulation, robust protection layer, shape-controlled lithium metal, separator modification, etc. However, Li/Li symmetric cell test is always a starting or essential step to demonstrate better lithium dendrite formation behavior with lower overpotential and longer cycle life without careful analysis. Thus, this review summarizes overpotential behaviors of Li/Li symmetric cells along with theoretical explanations like initial peaking or later arcing. Also, we categorize various overpotential data depending on research approaches and discuss them based on peaking and arcing behaviors. Thus, this review will be very helpful for researchers in lithium metal to analyze their overpotential behaviors.

• The Journal of Korean Academy of Prosthodontics
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• v.60 no.1
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• pp.9-18
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• 2022

In vitro studies are essential to predict the clinical performance of ceramic widely used as restorative materials. Traditional experiments such as fracture toughness and flexural strength have been used to evaluate the properties of brittle ceramics. However, these experiments have a limitation that the load conditions, failure patterns, and load values at which failure occurs are not similar to human occlusal force ranges or clinical failures. On the other hand, the edge chipping test (ECT), which was recently introduced to study chipping fracture of ceramics, has similar failure patterns to clinical trials. In addition, the failure loads from ECT were similar to human occlusal force. ECT can be usefully used in the study of ceramic properties. In this literature review, a more clinically meaningful experimental study of ceramics by examining the meaning and limitations of traditional ceramic failure tests and comparing them with ECT.

• Journal of the Korean Association of Geographic Information Studies
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• v.26 no.3
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• pp.37-51
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• 2023

Spatial information is essential for interpreting urban phenomena. Methodologies for spatializing urban information, especially when it lacks location details, have been consistently developed. Typical methods include Geocoding using structured address information or place names, spatial integration with existing geospatial data, and manual tasks utilizing reference data. However, a vast number of documents produced by administrative agencies have not been deeply dealt with due to their unstructured nature, even when there's demand for spatialization. This research utilizes the natural language processing model BERT to spatialize public documents related to urban planning. It focuses on extracting sentence elements containing addresses from documents and converting them into structured data. The study used 18 years of urban planning public announcement documents as training data to train the BERT model and enhanced its performance by manually adjusting its hyperparameters. After training, the test results showed accuracy rates of 96.6% for classifying urban planning facilities, 98.5% for address recognition, and 93.1% for address cleaning. When mapping the result data on GIS, it was possible to effectively display the change history related to specific urban planning facilities. This research provides a deep understanding of the spatial context of urban planning documents, and it is hoped that through this, stakeholders can make more effective decisions.

• The Journal of Engineering Geology
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• v.32 no.1
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• pp.27-40
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• 2022

Every year landslides cause serious casualties and property damages around the world. As the accurate prediction of landslides is important to reduce the fatalities and economic losses, various approaches have been developed to predict them. Prediction methods can be divided into landslide susceptibility analysis, landslide hazard analysis and landslide risk analysis according to the type of the conditioning factors, the predicted level of the landslide dangers, and whether the expected consequence cased by landslides were considered. Landslide susceptibility analyses are mainly based on the available landslide data and consequently, they predict the likelihood of landslide occurrence by considering factors that can induce landslides and analyzing the spatial distribution of these factors. Various qualitative and quantitative analysis techniques have been applied to landslide susceptibility analysis. Recently, quantitative susceptibility analyses have predominantly employed the physically based model due to high predictive capacity. This is because the physically based approaches use physical slope model to analyze slope stability regardless of prior landslide occurrence. This approach can also reproduce the physical processes governing landslide occurrence. This review examines physically based landslide susceptibility analysis approaches.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.36 no.3
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• pp.173-184
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• 2023

Presently, the general seismic fragility evaluation method for a bridge system composed of member elements with different nonlinear behaviors against strong earthquakes has been to evaluate at the element-level. This study aims to develop a system-level seismic fragility evaluation method that represents a structural system. Because the seismic behavior of bridges is generally divided into transverse and longitudinal directions, this study evaluated the system-level seismic fragility in both directions separately. The element-level seismic fragility evaluation in the longitudinal direction was performed for piers, bridge bearings, pounding, abutments, and unseating. Because pounding, abutment, and unseating do not affect the transverse directional damages, the element-level seismic fragility evaluation was limited to piers and bridge bearings. Seismic analysis using nonlinear models of various structural members was performed using the OpenSEES program. System-level seismic fragility was evaluated assuming that damage between element-levels was serially connected. Pier damage was identified to have a dominant effect on system-level seismic fragility than other element-level damages. In other words, the most vulnerable element-level seismic fragility has the most dominant effect on the system-level seismic fragility.

• Journal of the Korean Geotechnical Society
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• v.39 no.7
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• pp.31-37
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• 2023

Since tunnels are built underground, it is impossible to check visually the location and degree of deterioration of steel ribs. Therefore, in tunnel maintenance, GPR images are generally used to detect steel ribs. While research on GPR image analysis employing artificial neural networks has primarily focused on detecting underground pipes and road damage, there have been limited applications for analyzing tunnel GPR data, specifically for steel rib detection, both internationally and domestically. In this study, a one-step object detection algorithm called YOLO, based on a convolutional neural network, was utilized to automate the localization of steel ribs using GPR data. The performance of the algorithm is then analyzed. Two datasets were employed for the analysis. A dataset comprising 512 original images and another dataset consisting of 2,048 augmented images. The omission rate, which represents the ratio of undetected steel ribs to the total number of steel ribs, was 0.38% for the model using the augmented data, whereas the omission rate for the model using only the original data was 7.18%. Thus, from an automation standpoint, it is more practical to employ an augmented dataset.

• The Journal of Bigdata
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• v.8 no.1
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• pp.157-165
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• 2023

Seafood is a major source of protein in many countries and its consumption is increasing. In Korea, consumption of seafood is increasing, but self-sufficiency rate is decreasing, and the importance of safety management is increasing as the amount of imported seafood increases. There are hundreds of species of aquatic products imported into Korea from over 110 countries, and there is a limit to relying only on the experience of inspectors for safety management of imported aquatic products. Based on the data, a model that can predict the customs inspection results of imported aquatic products is developed, and a machine learning classification model that determines the non-conformity of aquatic products when an import declaration is submitted is created. As a result of customs inspection of imported marine products, the nonconformity rate is less than 1%, which is very low imbalanced data. Therefore, a sampling method that can complement these characteristics was comparatively studied, and a preprocessing method that can interpret the classification result was applied. Among various machine learning-based classification models, Random Forest and XGBoost showed good performance. The model that predicts both compliance and non-conformance well as a result of the clearance inspection is the basic random forest model to which ADASYN and one-hot encoding are applied, and has an accuracy of 99.88%, precision of 99.87%, recall of 99.89%, and AUC of 99.88%. XGBoost is the most stable model with all indicators exceeding 90% regardless of oversampling and encoding type.

• Journal of Korea Water Resources Association
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• v.55 no.4
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• pp.257-266
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• 2022

Inundation damage is increasing every year due to localized heavy rain and an increase of rainfall exceeding the design frequency. Accordingly, the importance of hydraulic structures for flood control and defense is also increasing. The hydraulic structures are designed according to its purpose and performance, and the amount of flood is an important calculation factor. However, in Korea, design rainfall is used as input data for hydrological analysis for the design of hydraulic structures due to the lack of sufficient data and the lack of reliability of observation data. Accurate probability rainfall and its temporal distribution are important factors to estimate the design rainfall. In practice, the regression equation of temporal distribution for the design rainfall is calculated using the cumulative rainfall percentage of Huff's quartile method. In addition, the 6^th order polynomial regression equation which shows high overall accuracy, is uniformly used. In this study, the optimized regression equation of temporal distribution is derived using the variable selection method according to the principle of parsimony in statistical modeling. The derived regression equation of temporal distribution is verified through the significance test. As a result of this study, it is most appropriate to derive the regression equation of temporal distribution using the stepwise selection method, which has the advantages of both forward selection and backward elimination.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.2A
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• pp.259-267
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• 2008

The ultimate strengths of reinforced concrete deep beams are governed by the capacity of the shear resistance mechanism composed of concrete and shear reinforcing bars, and the structural behaviors of the beams are mainly controlled by the mechanical relationships according to the shear span-to-effective depth ratio, flexural reinforcement ratio, load and support conditions, and material properties. In this study, a simple indeterminate strut-tie model reflecting all characteristics of the ultimate strengths and complicated structural behaviors is presented for the design of simply supported reinforced concrete deep beams. In addition, a load distribution ratio, defined as a magnitude of load transferred by a vertical truss mechanism, is proposed to help structural designers perform the design of simply supported reinforced concrete deep beams by using the strut-tie model approaches of current design codes. In the determination of a load distribution ratio, a concept of balanced shear reinforcement ratio requiring a simultaneous failure of inclined concrete strut and vertical steel tie is introduced to ensure the ductile shear failure of reinforced concrete deep beams, and the prime design variables including the shear span-to-effective depth ratio, flexural reinforcement ratio, and compressive strength of concrete influencing the ultimate strength and behavior are reflected upon based on various and numerous numerical analysis results. In the companion paper, the validity of presented model and load distribution ratio was examined by employing them to the evaluation of the ultimate strengths of various simply supported reinforced concrete deep beams tested to failure.