• Steel and Composite Structures
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• v.10 no.2
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• pp.129-149
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• 2010

The objective of this study is to formulate a general 3D material-structural analysis framework for the thermomechanical behavior of steel-concrete structures in a fire environment. The proposed analysis framework consists of three sequential modeling parts: fire dynamics simulation, heat transfer analysis, and a thermomechanical stress analysis of the structure. The first modeling part consists of applying the NIST (National Institute of Standards and Technology) Fire Dynamics Simulator (FDS) where coupled CFD (Computational Fluid Dynamics) with thermodynamics are combined to realistically model the fire progression within the steel-concrete structure. The goal is to generate the spatial-temporal (ST) solution variables (temperature, heat flux) on the surfaces of the structure. The FDS-ST solutions are generated in a discrete form. Continuous FDS-ST approximations are then developed to represent the temperature or heat-flux at any given time or point within the structure. An extensive numerical study is carried out to examine the best ST approximation functions that strike a balance between accuracy and simplicity. The second modeling part consists of a finite-element (FE) transient heat analysis of the structure using the continuous FDS-ST surface variables as prescribed thermal boundary conditions. The third modeling part is a thermomechanical FE structural analysis using both nonlinear material and geometry. The temperature history from the second modeling part is used at all nodal points. The ABAQUS (2003) FE code is used with external user subroutines for the second and third simulation parts in order to describe the specific heat temperature nonlinear dependency that drastically affects the transient thermal solution especially for concrete materials. User subroutines are also developed to apply the continuous FDS-ST surface nodal boundary conditions in the transient heat FE analysis. The proposed modeling framework is applied to predict the temperature and deflection of the well-documented third Cardington fire test.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.38 no.4
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• pp.159-167
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• 2015

We consider a wafer lot transfer/release planning problem from semiconductor wafer fabrication facilities to probing facilities with the objective of minimizing the deviation of workload and total tardiness of customers' orders. Due to the complexity of the considered problem, we propose a two-level hierarchical production planning method for the lot transfer problem between two parallel facilities to obtain an executable production plan and schedule. In the higher level, the solution for the reduced mathematical model with Lagrangian relaxation method can be regarded as a coarse good lot transfer/release plan with daily time bucket, and discrete-event simulation is performed to obtain detailed lot processing schedules at the machines with a priority-rule-based scheduling method and the lot transfer/release plan is evaluated in the lower level. To evaluate the performance of the suggested planning method, we provide computational tests on the problems obtained from a set of real data and additional test scenarios in which the several levels of variations are added in the customers' demands. Results of computational tests showed that the proposed lot transfer/planning architecture generates executable plans within acceptable computational time in the real factories and the total tardiness of orders can be reduced more effectively by using more sophisticated lot transfer methods, such as considering the due date and ready times of lots associated the same order with the mathematical formulation. The proposed method may be implemented for the problem of job assignment in back-end process such as the assignment of chips to be tested from assembly facilities to final test facilities. Also, the proposed method can be improved by considering the sequence dependent setup in the probing facilities.

• Korea journal of population studies
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• v.35 no.2
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• pp.29-53
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• 2012

This research studies how women's hourly wages affect childbearing using data from the National Longitudinal Survey of Youth. The results of discrete time hazard model show that the relationship between women's hourly wage and fertility is dynamic. Overall relationship looks negative, but they are not consistent across education levels. Women who have a high school diploma or less have a tendency to decrease childbearing when their wages increase. But women who have some college experience or a college degree are likely to have children when their wages increase. It means that only for highly educated women who are likely to be in high paying decent jobs, the rise of income can be used as a resource for reconciling the mother's and worker's roles. Or, for less educated women who are likely to be in the low paying jobs, the rise of income is not large enough to lessen role incompatibility.

• Safety and Health at Work
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• v.12 no.3
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• pp.377-383
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• 2021

Background: This study investigated the longitudinal associations between the degrees of positive and negative spillover in work-life balance (WLB) at baseline and reports of depressive mood at a 2-year follow-up in Korean women employees. Methods: We used a panel study design data of 1386 women employees who participated in the Korean Longitudinal Survey of Women and Families in both 2014 and 2016. Depressive mood was measured using the "10-item Center for Epidemiologic Studies Depression Scale." Associations between the positive and negative spillover in WLB at baseline and reports of new incidence of depressive mood at 2-year follow-up were explored using a multivariate logistic regression model. Results: Negative spillover in WLB at baseline showed a significant linear association with reports of depressive mood at 2-yearfollow-up after adjusting for age, education level, marital status, number of children, and positive spillover (P = 0.014). The highest scoring group in negative spillover (fourth quartile) showed a significant higher odds ratio of 1.95 compared with the lowest scoring group (first quartile; P = 0.036). Conclusion: Positive spillover in WLB showed a U-shaped association with depression. The degrees of positive and negative spillover in WLB among Korean women employees at baseline were associated with new incidence of depressive mood within 2 years. To prevent depression of female workers, more discrete and differentiated policies on how to maintain healthy WLB are required.

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

• Journal of Astronomy and Space Sciences
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• v.39 no.4
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• pp.145-158
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• 2022

The dynamics of the outer zone radiation belt has received a lot of attention mainly due to the correlation between the occurrence of enhancing relativistic electron flux and spacecraft operation anomalies or even failures (e.g., Baker et al. 1994). Relativistic electron events are often observed during great storms associated with ultra low frequency (ULF) waves. For example, a large buildup of relativistic electrons was observed during the great storm of March 24, 1991 (e.g., Li et al. 1993; Hudson et al. 1995; Mann et al. 2013). However, the dominant processes which accelerate magnetospheric radiation belt electrons to MeV energies are not well understood. In this paper, we present observations of Pc5 ULF waves in the recovery phase of the Bastille day storm of July 16, 2000 and electron and proton flux simultaneously oscillating with the same frequencies as the waves. The mechanism for the observed electron and proton flux modulations is examined using ground-based and satellite observations. During this storm time, multiple packets of discrete frequency Pc5 ULF waves appeared associated with energetic particle flux oscillations. We model the drift paths of electrons and protons to determine if the particles drift through the ULF wave to understand why some particle fluxes are modulated by the ULF waves and others are not. We also analyze the flux oscillations of electrons and protons as a function of energy to determine if the particle modulations are caused by a ULF wave drift resonance or advection of a particle density gradient. We suggest that the energetic electron and proton modulations by Pc5 ULF waves provide further evidence in support of the important role that ULF waves play in outer radiation belt dyanamics during storm times.

• Journal of Advanced Navigation Technology
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• v.22 no.2
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• pp.57-63
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• 2018

In the case of aircraft-launched guided weapons, various interface tests such as MIL-STD-1760 based power source, discrete signal, MUX communication as well as BIT of missile can verify system safety and reliability. The purpose of this case study is to develop a test bench based on MIL-STD-1760E for interoperability testing between aircraft and weapons. We proposed a testing method of the launch sequence based on the defined TIME LINE in the development phase of the missile system from the application of the power of the missile to the targeting, the transfer order, and the missile separation process. Furthermore, it will be a reference model that can maximize the verification scope in the development phase of the air to surface missile system by simulating abnormal situation to the inert missile using the error insertion function.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.5
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• pp.1610-1629
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• 2021

Failures frequently occurred in manufacturing machines due to complex and changeable manufacturing environments, increasing the downtime and maintenance costs. This manuscript develops a novel deep learning-based method named Multi-Domain Convolutional Neural Network (MDCNN) to deal with this challenging task with vibration signals. The proposed MDCNN consists of time-domain, frequency-domain, and statistical-domain feature channels. The Time-domain channel is to model the hidden patterns of signals in the time domain. The frequency-domain channel uses Discrete Wavelet Transformation (DWT) to obtain the rich feature representations of signals in the frequency domain. The statistic-domain channel contains six statistical variables, which is to reflect the signals' macro statistical-domain features, respectively. Firstly, in the proposed MDCNN, time-domain and frequency-domain channels are processed by CNN individually with various filters. Secondly, the CNN extracted features from time, and frequency domains are merged as time-frequency features. Lastly, time-frequency domain features are fused with six statistical variables as the comprehensive features for identifying the fault. Thereby, the proposed method could make full use of those three domain-features for fault diagnosis while keeping high distinguishability due to CNN's utilization. The authors designed massive experiments with 10-folder cross-validation technology to validate the proposed method's effectiveness on the CWRU bearing data set. The experimental results are calculated by ten-time averaged accuracy. They have confirmed that the proposed MDCNN could intelligently, accurately, and timely detect the fault under the complex manufacturing environments, whose accuracy is nearly 100%.

• The Journal of the Korea institute of electronic communication sciences
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• v.16 no.6
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• pp.1153-1160
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• 2021

This paper proposes a routing algorithm that determines the optimal path using deep reinforcement learning in software-defined networks. The deep reinforcement learning model for learning is based on DQN, the inputs are the current network state, source, and destination nodes, and the output returns a list of routes from source to destination. The routing task is defined as a discrete control problem, and the quality of service parameters for routing consider delay, bandwidth, and loss rate. The routing agent classifies the appropriate service class according to the user's quality of service profile, and converts the service class that can be provided for each link from the current network state collected from the SDN. Based on this converted information, it learns to select a route that satisfies the required service level from the source to the destination. The simulation results indicated that if the proposed algorithm proceeds with a certain episode, the correct path is selected and the learning is successfully performed.

• Nuclear Engineering and Technology
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• v.54 no.8
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• pp.3059-3072
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• 2022

A Jacobian-Free Newton Krylov Two-Nodal Coarse Mesh Finite Difference algorithm based on Nodal Expansion Method (NEM_TNCMFD_JFNK) is successfully developed and proposed to solve the three-dimensional (3D) and multi-group reactor physics models. In the NEM_TNCMFD_JFNK method, the efficient JFNK method with the Modified Incomplete LU (MILU) preconditioner is integrated and applied into the discrete systems of the NEM-based two-node CMFD method by constructing the residual functions of only the nodal average fluxes and the eigenvalue. All the nonlinear corrective nodal coupling coefficients are updated on the basis of two-nodal NEM formulation including the discontinuity factor in every few newton steps. All the expansion coefficients and interface currents of the two-node NEM need not be chosen as the solution variables to evaluate the residual functions of the NEM_TNCMFD_JFNK method, therefore, the NEM_TNCMFD_JFNK method can greatly reduce the number of solution variables and the computational cost compared with the JFNK based on the conventional NEM. Finally the NEM_TNCMFD_JFNK code is developed and then analyzed by simulating the representative PWR MOX/UO₂ core benchmark, the popular NEACRP 3D core benchmark and the complicated full-core pin-by-pin homogenous core model. Numerical solutions show that the proposed NEM_TNCMFD_JFNK method with the MILU preconditioner has the good numerical accuracy and can obtain higher computational efficiency than the NEM-based two-node CMFD algorithm with the power method in the outer iteration and the Krylov method using the MILU preconditioner in the inner iteration, which indicates the NEM_TNCMFD_JFNK method can serve as a potential and efficient numerical tool for reactor neutron diffusion analysis module in the JFNK-based multiphysics coupling application.