• 한국컴퓨터정보학회논문지
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• 제28권2호
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• pp.39-46
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• 2023

본 논문은 클라이언트-서버 방식을 사용하는 대규모 1인칭 온라인 슈터 게임(MMOFPS)에서의 네트워크 부하를 줄이기 위한 효율적인 적응적 패킷전송 주기 방법을 제안한다. 플레이어 움직임에 있어서 빠르고 지속적인 변화와 정적이고 선형적인 상태가 다양하게 공존하는 FPS 게임의 특성상 변화의 정도에 따라 서버로의 패킷 전송량을 절약할 수 있는 지점들이 존재하는데, 이를 위해 본 논문에서는 클라이언트가 매 패킷을 전송할 때마다 플레이어의 위치 및 움직임 변수들의 변화량을 측정하여 이를 기반으로 다음번 패킷이 전송되어야 할 시간 간격을 계산한다. 서버 측에서는 받은 패킷의 정보들을 사용하여 다음 패킷이 도착할 때까지의 공백을 메우기 위해 위치 예측을 수행하여 모든 클라이언트에게 브로드캐스팅을 하게 된다. 긴 패킷 전송 간격으로 인한 예측 오차를 줄이기 위하여 전송 간격 최대한계치와 이중 패킷전송 등의 추가적 작업을 수행한다. 결과의 효율성을 보이기 위해 테스트 게임 환경을 구축하여 기존의 고정된 패킷전송 주기 시스템과의 비교분석을 수행하였다.

• 한국기계가공학회지
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• 제21권4호
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• pp.1-13
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• 2022

Household refrigerator cabinets must undergo cyclic testing at -20 ℃ and 65 ℃ for quality control (QC) after their production is complete. These cabinets were assembled from different materials, including acrylonitrile butadiene styrene (ABS), polyurethane (PU) foam, and steel plates. However, different thermal expansion values could be observed owing to differences in the mechanical properties of the materials. In this study, a technique to predict delamination on a refrigerator wall caused by thermal deformation was developed. The mechanical properties of ABS and PU foams were tested, theload factors causing delamination were analyzed, delamination was observed using a high-speed camera, and comparison and verification in terms of stress and strain were performed using a finite element model (FEM). The results indicated that the delamination phenomenon of a refrigerator wall can be defined in two cases. A method for predicting and evaluating delamination was established and applied in an actual refrigerator. To determine the effect of temperature changes on the refrigerator, strain measurements were performed at the weak point and the stress was calculated. The results showed that the proposed FEM prediction technique can be used as a basis for virtual testing to replace future QC testing, thus saving time and cost.

• 한국해양공학회지
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• 제36권3호
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• pp.143-152
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• 2022

To reach a port, a ship must pass through a shallow water zone where seabed effects alter the hydrodynamics acting on the ship. This study examined the maneuvering characteristics of an autonomous surface ship at 3-DOF (Degree of freedom) motion in deep water and shallow water based on the in-port speed of 1.54 m/s. The CFD (Computational fluid dynamics) method was used as a specialized tool in naval hydrodynamics based on the RANS (Reynolds-averaged Navier-Stoke) solver for maneuvering prediction. A virtual captive model test in CFD with various constrained motions, such as static drift, circular motion, and combined circular motion with drift, was performed to determine the hydrodynamic forces and moments of the ship. In addition, a model test was performed in a square tank for a static drift test in deep water to verify the accuracy of the CFD method by comparing the hydrodynamic forces and moments. The results showed changes in hydrodynamic forces and moments in deep and shallow water, with the latter increasing dramatically in very shallow water. The velocity fields demonstrated an increasing change in velocity as water became shallower. The least-squares method was applied to obtain the hydrodynamic coefficients by distinguishing a linear and non-linear model of the hydrodynamic force models. The course stability, maneuverability, and collision avoidance ability were evaluated from the estimated hydrodynamic coefficients. The hydrodynamic characteristics showed that the course stability improved in extremely shallow water. The maneuverability was satisfied with IMO (2002) except for extremely shallow water, and collision avoidance ability was a good performance in deep and shallow water.

• Tribology and Lubricants
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• 제39권1호
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• pp.28-34
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• 2023

Because of their cleanliness, low friction, and high stiffness, aerostatic bearings are used in numerous applications. Aerostic bearings that use porous materials as means of flow restriction have higher stiffness than other types of bearings and have been successfully applied as guide bearings, which have high motion accuracy requirements. However, the performances of porous bearings exhibit strong nonlinearity and can vary considerably depending on design parameters. Therefore, accurate prediction of the performance characteristics of porous bearings is necessary or their successful application. This study presents a porous bearing design and performance analysis for a spindle used in wafer polishing. The Reynolds and Darcy flow equations are solved to calculate the pressures in the lubrication film and porous busing, respectively. To verify the validity of the proposed analytical model, the calculated pressure distribution in the designed bearing is compared with that derived from previous research. Additional parametric studies are performed to determine the optimal design parameters. Analytical results show that optimal design parameters that obtain the maximum stiffness can be derived. In addition, the results show that cross-coupled stiffness increases with rotating speed. Thus, issues related to stability should be investigated at the design stage.

• 대한방사선기술학회지:방사선기술과학
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• 제45권6호
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• pp.491-502
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• 2022

The purpose of this study was to retrospectively investigate the upper and lower control limits of treatment planning parameters using EBT film based delivery quality assurance (DQA) results and to analyze the results of statistical process control (SPC) in helical tomotherapy (HT). A total of 152 patients who passed or failed DQA results were retrospectively included in this study. Prostate (n = 66), rectal (n = 51), and large-field cancer patients, including lymph nodes (n = 35), were randomly selected. The absolute point dose difference (DD) and global gamma passing rate (GPR) were analyzed for all patients. Control charts were used to evaluate the upper and lower control limits (UCL and LCL) for all the assessed treatment planning parameters. Treatment planning parameters such as gantry period, leaf open time (LOT), pitch, field width, actual and planning modulation factor, treatment time, couch speed, and couch travel were analyzed to provide the optimal range using the DQA results. The classification and regression tree (CART) was used to predict the relative importance of variables in the DQA results from various treatment planning parameters. We confirmed that the proportion of patients with an LOT below 100 ms in the failure group was relatively higher than that in the passing group. SPC can detect QA failure prior to over dosimetric QA tolerance levels. The acceptable tolerance range of each planning parameter may assist in the prediction of DQA failures using the SPC tool in the future.

• 한국전산구조공학회논문집
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• 제36권1호
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• pp.39-48
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• 2023

철도교량의 설계는 장기간에 걸쳐 수행되고 대규모의 부지를 대상으로 하기 때문에 다양한 환경적인 요인과 불확실성을 동반하게 된다. 이러한 연유로 초기 설계단계에서 충분히 검토하였더라도 설계변경이 종종 발생하고 있다. 특히 철도교량과 같은 대규모 시설물의 설계변경은 많은 시간과 인력을 소모하며, 매번 모든 절차를 반복하는 것은 매우 비효율적이다. 본 연구에서는 딥러닝 알고리즘 중 전이학습을 통해 설계변경 전의 학습 결과를 활용하여 설계변경 후의 학습의 효율성을 향상시킬 수 있는 기법을 제안하였다. 분석을 위해 기개발한 철도교량 딥러닝 기반 예측 시스템을 활용하여 시나리오들을 작성하고 데이터베이스를 구축하였다. 제안된 기법은 설계변경 전 기존 도메인에서 학습에 사용한 8,000개의 학습데이터 대비 새로운 도메인에서 1,000개의 데이터만을 학습하여 유사한 정확도를 나타내었고 보다 빠른 수렴속도를 가지는 것을 확인하였다.

• Structural Engineering and Mechanics
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• 제86권1호
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• pp.119-137
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• 2023

The purpose of this research is to assess the performance of CBN and ceramic tools during the dry turning of gray cast iron EN GJL-350. During the turning operation, the variable machining parameters are cutting speed, feed rate, depth of cut and type of the cutting material. This contribution consists of two sections, the first one deals with the performance evaluation of four materials in terms of evolution of flank wear, surface roughness (2D and 3D) and cutting forces. The focus of the second section is on statistical analysis, followed by modeling and optimization. The experiments are conducted according to the Taguchi design L₃₂ and based on ANOVA approach to quantify the impact of input factors on the output parameters, namely, the surface roughness (Ra), the cutting force (Fz), the cutting power (Pc), specific cutting energy (Ecs). The RSM method was used to create prediction models of several technical factors (Ra, Fz, Pc, Ecs and MRR). Subsequently, the desirability function approach was used to achieve a multi-objective optimization that encompasses the output parameters simultaneously. The aim is to obtain optimal cutting regimes, following several cases of optimization often encountered in industry. The results found show that the CBN tool is the most efficient cutting material compared to the three ceramics. The optimal combination for the first case where the importance is the same for the different outputs is Vc=660 m/min, f=0.116 mm/rev, ap=0.232 mm and the material CBN. The optimization results have been verified by carrying out confirmation tests.

• 문화기술의 융합
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• 제9권3호
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• pp.727-730
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• 2023

전세계적으로 온실가스 및 미세먼지 저감을 위한 탄소중립 정책에 따라 전기차보급이 확대될 전망이다. 전기자동창의 운용은 열악한 환경에서 사용되고 충전과 방전 등을 거듭할수록 에너지밀도가 낮아지고 내부분리막의 손상등의 이유로 건전성이 떨어짐에 따라 차량의 주행거리가 줄고, 충전 속도가 느려지는 이유로 대략 5~10년 정도 사용한 배터리들은 폐배터리로 분류하며 이 같은 이유로 배터리 화재 및 폭발 등의 위험성이 높아 지게 됩에 따라 배터리의 진단 및 SOH의 추정이 필수적이라 할 수 있다. 배터리 SOH추정은 매우 중요한 요소로 현재는 배터리 충방전을 반복하면서 소요되는 시간, 온도, 전압을 측정하여 배터리의 상태를 평가하는데 정확도가 낮다. 불안정한 폐배터리를 다수의 반복적 충전과 방전을 통해 진단하는 과정에서 화재 및 폭발의 취약점을 보완하여 신뢰성이 높은 폐배터리의 상태데이터를 취득할 수 있는 기반을 마련하고 본 논문에서는 리튬이온 배터리의 SOH예측을 위해 테슬라 폐배터리를 이용한 방전 용량 측정을 바탕으로 획득한 데이터를 서포트 벡터 머신 기반으로 예측하고자 하였다.

• Tribology and Lubricants
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• 제40권3호
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• pp.103-110
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• 2024

Gas foil thrust bearings (GFTBs) are oil-free self-acting hydrodynamic bearings that support axial loads with a low friction during airborne operation. They need solid lubricants to reduce dry-friction between the runner and top foil and minimize local wears on their surfaces during start-up and shutdown processes. In this study, we evaluate the lift-off speeds and load capacity performance of a GFTB with Polytetrafluoroethylene (PTFE) surface coating by measuring drag torques during a series of experimental tests at increasing ambient temperatures of 25, 75 and 110℃. An electric heat gun provides hot air to the test GFTB operating in the closed booth to increase the ambient temperature. Test results show that the increasing ambient temperature delays the lift-off speed and decreases the load capacity of the test GFTB. An early developed prediction tool well predicts the measured drag torques at 60 krpm. After all tests, post inspections of the surface coating of the top foil are conducted. Scanning electron microscope (SEM) images imply that abrasive wear and oxidation wear are dominant during the tests at 25℃ and 110℃, respectively. A quantitative energy dispersive spectroscopy (EDS) microanalysis reveals that the weight percentages of carbon, oxygen, and nitrogen decrease, while that of fluorine increases significantly during the highest-temperature tests. The study demonstrates that the increasing ambient temperature noticeably deteriorates the static performances and degrades the surface coating of the test GFTB.

• Geomechanics and Engineering
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• 제37권1호
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• pp.65-72
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• 2024

Water ingress poses a common and intricate geological hazard with profound implications for tunnel construction's speed and safety. The project's success hinges significantly on the precision of estimating water inflow during excavation, a critical factor in early-stage decision-making during conception and design. This article introduces an optimized model employing the gene expression programming (GEP) approach to forecast tunnel water inflow. The GEP model was refined by developing an equation that best aligns with predictive outcomes. The equation's outputs were compared with measured data and assessed against practical scenarios to validate its potential applicability in calculating tunnel water input. The optimized GEP model excelled in forecasting tunnel water inflow, outperforming alternative machine learning algorithms like SVR, GPR, DT, and KNN. This positions the GEP model as a leading choice for accurate and superior predictions. A state-of-the-art machine learning-based graphical user interface (GUI) was innovatively crafted for predicting and visualizing tunnel water inflow. This cutting-edge tool leverages ML algorithms, marking a substantial advancement in tunneling prediction technologies, providing accuracy and accessibility in water inflow projections.