• Proceedings of the Korean Institute of Navigation and Port Research Conference
• /
• 2005.10a
• /
• pp.289-295
• /
• 2005

LMTT (Linear Motor-based Transfer Techn-ology) is a horizontal transfer system for the yard automation This system is based on PMLSM (Permanent Magnetic Linear Synchronous Motor) toot consists of stator modules on the rail and shuttle car. In this research, the kriging interpolation method with sequential sampling find the optimum design of mover in LMTT. The design variables are considered as the transverse, longitudinal and wheel beam's thicknesses. The objective function is set up as weight, while the constant function are set up as the stresses generated by four loading conditions. The objective function is set up as weight. The optimum results obtained by the suggested method are compared with those by the GENESIS.

• Journal of the Korea institute for structural maintenance and inspection
• /
• v.14 no.5
• /
• pp.119-127
• /
• 2010

This paper provides a new approach for durability prediction of reinforced concrete structures exposed to carbonation. In this method, the prediction can be updated successively by a Bayes' theorem when additional data are available. The stochastic properties of model parameters are explicitly taken into account in the model. To simplify the procedure of the model, the probability of the durability limit is determined based on the samples obtained from the Latin Hypercube Sampling(LHS) technique. The new method may be very useful in design of important concrete structures and help to predict the remaining service life of existing concrete structures which have been monitored. For using the new method, in which the prior distribution is developed to represent the uncertainties of the carbonation velocity using data of concrete structures(3700 specimens) in Korea and the likelihood function is used to monitor in-situ data. The posterior distribution is obtained by combining a prior distribution and a likelihood function. Efficiency of the LHS technique for simulation was confirmed through a comparison between the LHS and the Monte Calro Simulation(MCS) technique.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.18 no.4
• /
• pp.8-14
• /
• 2017

Nonstructural components, such as electrical equipment, have critical roles in the proper functionality of various infrastructure systems. Some of these devices in certain facilities should operate even under strong seismic shaking. However, it is challenging to define each mechanical and operational failure and determine system failure probabilities under seismic shaking due to the uncertainties in earthquake excitations and the diversity of electrical equipment, among other factors. Therefore, it is necessary to develop effective and practical probabilistic models for performance assessment of electrical equipment considering variations in equipment features and earthquakes. This study will enhance the understanding of the effect of rocking behavior on nonstructural equipment, and linear-to-nonlinear behavior of restrainers. In addition, this study will generate probabilistic seismic demand models of rigid equipment for a set of conventional and novel intensity measures.

• Journal of the Earthquake Engineering Society of Korea
• /
• v.2 no.1
• /
• pp.35-46
• /
• 1998

Structural damage is used to be modeled through reductions in the stiffness of structural elements for the purpose of damage estimation of structural system. In this study, the concept of joint damage is employed for more realistic damage assessment of a steel structure. The joint damage is estimated damage based on the mode shape informations using neural networks, The beam-to-column connection in a steel frame structure is represented by a rotational spring at the fixed end of a beam element. The severity of joint damage is defined as the reduction ratio of the connection stiffness with respect to the value of the intact joint. The concept of the substructural identification is used for the localized damage assessment in a large structure. The feasibility of the proposed method is examined using an example with simulated data. It has been found that the joint damages can be reasonably estimated for the case with the measurements of the mode vectors subjected to noise.

• Journal of the Korea Society for Simulation
• /
• v.26 no.3
• /
• pp.23-34
• /
• 2017

This paper is to study the simulation model of depot maintenance system that analyzes logistics supportability such as component availability and cost of target equipment. A depot maintenance system could repair or maintain multiple components simultaneously. The key performance indicators of this system are component availability, repair cycle time, and maintenance cost. The simulation model is based on the engine maintenance process of army aviation depot. This study combines the NOLH(Nearly Orthogonal Latin Hypercube) experimental design method, to composes 33 scenarios, with a multiple regression analysis to find out major factors that influence on key performance indicators. This study is significant in providing a cost-effectiveness analysis on depot maintenance system that is capable of maintaining multiple components at the same time.

• Journal of Ocean Engineering and Technology
• /
• v.33 no.1
• /
• pp.50-60
• /
• 2019

Recently, problems with excessive vibration of the radar masts of large bulk carriers and crude oil tankers have frequently been reported. This paper explores a design method to avoid the resonance of a radar mast installed on a large ship using various design of experiment (DOE) methods. A local vibration test was performed during an actual sea trial to determine the excitation sources of the vibration related to the resonant frequency of the radar mast. DOE methods such as the orthogonal array (OA) and Latin hypercube design (LHD) methods were used to analyze the Pareto effects on the radar mast vibration. In these DOE methods, the main vibration performances such as the natural frequency and weight of the radar mast were set as responses, while the shape and thickness of the main structural members of the radar mast were set as design factors. From the DOE-based Pareto effect results, we selected the significant structural members with the greatest influence on the vibration characteristics of the radar mast. Full factorial design (FFD) was applied to verify the Pareto effect results of the OA and LHD methods. The design of the main structural members of the radar mast to avoid resonance was reviewed, and a normal mode analysis was performed for each design using the finite element method. Based on the results of this normal mode analysis, we selected a design case that could avoid the resonance from the major excitation sources. In addition, a modal test was performed on the determined design to verify the normal mode analysis results.

• Journal of the Architectural Institute of Korea Structure & Construction
• /
• v.36 no.5
• /
• pp.177-185
• /
• 2020

The building energy performance indicator, called Energy Performance Index (EPI), has been used for the past decades in South Korea. It has a list of design variables assigned with weighting factors (a, b). Unfortunately, the current EPI method is not performance-based but very close to a prescriptive rating. With this in mind, this study aims to propose a new performance-based EPI method. For this purpose, a global sensitivity analysis method, Sobol, is employed. The Sobol method is suitable for complex nonlinear models and can decompose all the output variance due to every input. The Sobol sensitivity index of each variable is defined as 0 to 1 (0 to 100%), and the sum of all sensitivity indices is equal to 1 (100%). In this study, an office building was modeled using EnergyPlus and then the Latin Hypercube Sampling (LHS) was conducted to generate a surrogate model to EnergyPlus. The sensitivity index was suggested to replace weight (a) in the existing EPI. In addition, the discrete weight (b) in the existing EPI was replaced by a set of continuous regression functions. Due to the introduction of the sensitivity index and the continuous regression functions, the new proposed approach can provide far more accurate outcome than the existing EPI (R²: 0.83 vs. R²: 0.01 for cooling, R²: 0.66 vs. R²: 0.01 for total energy). The new proposed approach proves to be more rational, objective and performance-based than the existing EPI method.

• International Journal of Naval Architecture and Ocean Engineering
• /
• v.12 no.1
• /
• pp.71-84
• /
• 2020

In order to improve the performance of marine centrifugal pump, a centrifugal pump whose specific speed is 66.7 was selected for the research. Outlet diameter D2, outlet width b2, blade outlet angle β2, blade wrap φ and blade number z of the impeller were chosen as the variables. The maximum weighted average efficiency and the minimum vibration intensity at the base were calculated as objectives. Based on the Latin Hypercube method, the impeller was numerically optimized. The numerical results show that after optimization, the amplitudes of pressure fluctuation on the main frequency at different monitoring points decrease in varying degrees. The radial force on impeller decreases obviously under off-design flow rates and is more symmetrical during the operation of the pump. The variation of the axial force is relatively small, which has no obvious relationship with the rotating angle of the impeller. The energy performance and vibration experiment was performed for verifying. The test results show that the weighted average efficiency under 0.8Qd, 1.0Qd and 1.2Qd increases by 4.3% after optimization. The maximal vibration intensity at M1-M4 on the pump base reduced from 0.36 mm/s to 0.25 mm/s, decreasing by 30.5%. In addition, the vibration velocities of bracket in pump side and outlet flange also have significant reductions.

• Journal of the Korean Society of Systems Engineering
• /
• v.18 no.2
• /
• pp.75-93
• /
• 2022

Machine learning (ML) data-driven meta-model is proposed as a surrogate model to reduce the excessive computational cost of the physics-based model and facilitate the real-time prediction of a nuclear power plant's transient response. To forecast the transient response three machine learning (ML) meta-models based on recurrent neural networks (RNNs); specifically, Long Short Term Memory (LSTM), Gated Recurrent Unit (GRU), and a sequence combination of Convolutional Neural Network (CNN) and LSTM are developed. The chosen accident scenario is a control element assembly withdrawal at power concurrent with the Loss Of Offsite Power (LOOP). The transient response was obtained using the best estimate thermal hydraulics code, MARS-KS, and cross-validated against the Design and control document (DCD). DAKOTA software is loosely coupled with MARS-KS code via a python interface to perform the Best Estimate Plus Uncertainty Quantification (BEPU) analysis and generate a time series database of the system response to train, test and validate the ML meta-models. Key uncertain parameters identified as required by the CASU methodology were propagated using the non-parametric Monte-Carlo (MC) random propagation and Latin Hypercube Sampling technique until a statistically significant database (181 samples) as required by Wilk's fifth order is achieved with 95% probability and 95% confidence level. The three ML RNN models were built and optimized with the help of the Talos tool and demonstrated excellent performance in forecasting the most probable NPP transient response. This research was guided by the Systems Engineering (SE) approach for the systematic and efficient planning and execution of the research.

• Earthquakes and Structures
• /
• v.26 no.4
• /
• pp.311-326
• /
• 2024

Transmission tower structures are particularly susceptible to damage and even collapse under strong seismic ground motions. Conventional seismic analyses of transmission towers are usually performed by considering only ground motion uncertainty while ignoring structural uncertainty; consequently, the performance evaluation and failure prediction may be inaccurate. In this context, the present study numerically investigates the seismic responses and failure mechanism of transmission towers by considering multiple sources of uncertainty. To this end, an existing transmission tower is chosen, and the corresponding three-dimensional finite element model is created in ABAQUS software. Sensitivity analysis is carried out to identify the relative importance of the uncertain parameters in the seismic responses of transmission towers. The numerical results indicate that the impacts of the structural damping ratio, elastic modulus and yield strength on the seismic responses of the transmission tower are relatively large. Subsequently, a set of 20 uncertainty models are established based on random samples of various parameter combinations generated by the Latin hypercube sampling (LHS) method. An uncertainty analysis is performed for these uncertainty models to clarify the impacts of uncertain structural factors on the seismic responses and failure mechanism (ultimate bearing capacity and failure path). The numerical results show that structural uncertainty has a significant influence on the seismic responses and failure mechanism of transmission towers; different possible failure paths exist for the uncertainty models, whereas only one exists for the deterministic model, and the ultimate bearing capacity of transmission towers is more sensitive to the variation in material parameters than that in geometrical parameters. This research is expected to provide an in-depth understanding of the influence of structural uncertainty on the seismic demand assessment of transmission towers.