A5030146723- Probabilistic and Robust Engineering Design
- Advanced Multi-Objective Optimization Algorithms
- Statistical Distribution Estimation and Applications
- Engineering Applied Research
- Optimal Experimental Design Methods
- Machine Fault Diagnosis Techniques
- Reliability and Maintenance Optimization
- Fatigue and fracture mechanics
- Maritime Navigation and Safety
- Fault Detection and Control Systems
- Structural Integrity and Reliability Analysis
- Refrigeration and Air Conditioning Technologies
- Engineering Diagnostics and Reliability
- Manufacturing Process and Optimization
- Maritime Transport Emissions and Efficiency
- Mechanical Engineering and Vibrations Research
- Risk and Safety Analysis
- Technology and Data Analysis
- Hydraulic and Pneumatic Systems
- Advanced Algorithms and Applications
- Advanced battery technologies research
- Advanced Statistical Methods and Models
- Supercapacitor Materials and Fabrication
- Ship Hydrodynamics and Maneuverability
- Advanced machining processes and optimization
Pusan National University
2015-2024
University of Iowa
2007-2024
Dong-A University
2024
Colorado State University
2017
Keimyung University
2012-2015
This paper proposes a novel second-order reliability method (SORM) using noncentral or general chi-squared distribution to improve the accuracy of analysis in existing SORM. Conventional SORM contains three types errors: (1) error due approximating nonlinear limit state function by quadratic at most probable point standard normal U-space, (2) U-space parabolic surface, and (3) calculation probability failure after making previous two approximations. The proposed first type only, which is...
As oil prices continue to rise internationally, shipping costs are also increasing rapidly. In order reduce fuel costs, an economical route must be determined by accurately predicting the estimated arrival time of ships. A common method in evaluation ship speed involves computing total resistance a using theoretical analysis; however, equations cannot applied for most ships under various operating conditions. this study, machine learning approach was proposed predict over ground automatic...
This study presents a novel ship route planning algorithm that takes into account both operational economy and safety by integrating the A* with collision avoidance evaluates risk index (CRI) between own target ship. The CRI-based defines penalty zone, allowing to explore safe routes based on International Regulations for Preventing Collisions at Sea 1972 (COLREGs) performs an adaptive effective node search extended local map grid according various encounter situations. proposed is validated...
This study presents a methodology for computing stochastic sensitivities with respect to the design variables, which are mean values of input correlated random variables. Assuming that an accurate surrogate model is available, proposed method calculates component reliability, system or statistical moments and their by applying Monte Carlo simulation model. Since used, computational cost sensitivity analysis affordable compared use actual models. The copula used joint distribution score...
With soaring oil prices worldwide, determining the most optimal routes for economical ship operation has become an important issue. Optimizing is economically operation, but it also essential to meet standards of environmental regulations recently imposed by International Maritime Organization. For this purpose, various algorithms have been developed ensure ships via utilization marine climate data and Automatic Identification System (AIS) data. However, such require a large amount...
머신러닝 기법의 발달과 함께 기계에서 발생하는 다양한 종류(진동, 온도, 유량 등)의 데이터를 활용하여 기계의 상태를 진단하고 이상 탐지 및 비정상 분류 연구도 활발히 진행되고 있다. 특히 진동 활용한 회전 상태 진단은 전통적인 기계 모니터링 분야로 오랜 기간 동안 연구가 진행되었고, 연구 방법 또한 매우 다양하다. 본 연구에서는 가정용 에어컨에 사용되는 로터리 압축기에 가속도계를 직접 설치하여 수집하는 실험을 진행하였다. 데이터 부족 문제를 해결하기 위해 분할을 수행하였으며, 시간 영역에서의 데이터로부터 통계적, 물리적 특징들을 추출한 후, Chi-square 검증을 통해 고장 모델의 주요 특징을 추출하였다. SVM(Support Vector Machine) 모델은 압축기의 정상 혹은 유무를 분류하기 개발되었으며, 파라미터 최적화를 정확도를 개선하였다.
This study aims to optimize the endurance test mode for military vehicles more closely simulate actual operational conditions. To achieve this, a modified bi-objective optimization approach was developed, combining two system-level objectives relative damage of chassis and powertrain with six corresponding component-level constraints. The employs NSGA II(Non-dominated Sorting Genetic Algorithm II) generate diverse set optimal solutions. results, evaluated using CRM(Coefficient Residual Mass)...
This study investigates an enhancement of carbon-based materials, including multi-walled carbon nanotubes (MWCNTs) and graphite, through Ion Assisted Reaction (IAR) metal nanoparticle deposition using Physical Vapor Deposition. The IAR process employed Ar + ion beams in reactive gas environments, effectively introducing hydrophilic functional groups such as hydroxyl (-OH) carboxyl (-COOH) on the MWCNT surfaces. modification significantly improved dispersion behavior treated MWCNTs,...