• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 1997.10a
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• pp.385-390
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• 1997

In recent years there has been an increasing emphasis on shortening design cycles for bringing products to market. This requires the development of computer aided engineering tools which allow analysts to quickly evaluate the effect of design changes on noise, vibration, and harshness. Statistical Energy Analysis (SEA) modeling is a valuable tool for predicting noise and vibration as SEA models are inherently simpler and more robust than deterministic models. SEA modeling can be combined with design sensitivity analysis (DSA) to identify design changes which give the largest performance benefit. This paper describes SEA modeling of an equipment cab. SEA predictions are compared to test data, showing good agreement. The use of design sensitivity analysis in improving cab design is then demonstrated.

• Geomechanics and Engineering
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• v.24 no.4
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• pp.399-406
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• 2021

It is a key issue in the tunnel design to evaluate the stability of the excavation face. Two efficient analytical models in the context of the limit equilibrium method (LEM) and the limit analysis method (LAM) are used to carry out the deterministic calculations of the safety factor. The safety factor obtained by these two models agrees well with that provided by the numerical modelling by FLAC 3D, but consuming less time. A simple probabilistic approach based on the Mote-Carlo Simulation technique which can quickly calculate the probability distribution of the safety factor was used to perform the probabilistic analysis on the tunnel face stability. Both the cumulative probabilistic distribution and the probability density function in terms of the safety factor were obtained. The obtained results show the effectiveness of this probabilistic approach in the tunnel design.

• International conference on construction engineering and project management
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• 2022.06a
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• pp.1194-1201
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• 2022

The existing literature has witnessed the importance of productivity assessment and deducing factors affecting it. However, yet many models have shown limitations in practical applications in actual construction sites for process planning due to uncertainty and lack of data. This research presents a productivity assessment and database generation framework using simulation and compares the results with RSMeans to derive appropriate equipment combinations alternatives for earthwork operations. Data of 15 different conditions was collected from 5 different construction sites. Prediction accuracy above 90% were achieved for the simulation models with average error rate of 7.4%. The construction productivity assessment framework presented in this study is expected to be highly applicable to operation planning for earthwork operations.

• Journal of the Korean Association of Geographic Information Studies
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• v.11 no.3
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• pp.151-165
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• 2008

Ground slope and aspect are important parameters for physical deterministic water balance models like BROOK90 or hydrological models which attempt to calculate evapotranspiration, snowmelt, and net radiation. This study constructs a Digital Elevation Model(DEM) and examines how DEM resolution can change the average ground slope and aspect of a river basin and attempts to evaluate the effects on simulation results of BROOK90, a physical deterministic water balance model. The study area is Byungcheon river basin in Korea. DEM has been constructed using a 1:25,000 digital map with the methods of TIN and Topo To Raster. The total of 20 DEMs with 10m~100m resolution have been constructed, with a 10m interval. It was found that the higher the DEM resolution, the steeper the average ground slope value of the Byungcheon river basin. In turn, the direct solar radiation of a hilly area in the model increased the evapotranspiration and reduced the stream runoff in the Byungcheon river basin. On the other hand, a lower DEM resolution tends to move the average aspect from southeast to south in the Byungcheon river basin. Accordingly, it was found that stream runoff was reduced and evapotranspiration increased.

• Computers and Concrete
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• v.12 no.5
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• pp.585-612
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• 2013

The paper presents quasi-static numerical simulations of the behaviour of short reinforced concrete beams without shear reinforcement under mixed shear-tension failure using the FEM and four various constitutive continuum models for concrete. First, an isotropic elasto-plastic model with a Drucker-Prager criterion defined in compression and with a Rankine criterion defined in tension was used. Next, an anisotropic smeared crack and isotropic damage model were applied. Finally, an elasto-plastic-damage model was used. To ensure mesh-independent FE results, to describe strain localization in concrete and to capture a deterministic size effect, all models were enhanced in a softening regime by a characteristic length of micro-structure by means of a non-local theory. Bond-slip between concrete and reinforcement was considered. The numerical results were directly compared with the corresponding laboratory tests performed by Walraven and Lehwalter (1994). The advantages and disadvantages of enhanced models to model the reinforced concrete behaviour were outlined.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1996.04a
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• pp.525-529
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• 1996

Decision environments involve a high degree of uncertainty as well as multiple, conflicting goals. Although traditional goal programming offers a means of considering multiple, conflicting goals and arrives at a satisficing solution in a deterministic manner, its major drawback is that decision makers often specify aspiration level of each goal as a single number. To overcome the problem of setting aspiration levels, chance constrained programming can be incorporated into goal programming formulation so that sampling information can be utilized to describe uncertainty distribution. Another drawback of goal programming is that it does not provide a systematic approach to set priorities and trade-offs among conflicting goals. To overcome this weekness, the analytic hierarchy process(AHP) is used in the model. Also, most goal programming models in the literature are of a linear form, although some nonlinear models have been presented. Consideration of risk in technological coefficients and right hand sides, however, leads to nonlinear goal programming models, which require a linear approximation to be solved. In this paper, chance constrained reformulation with linear approximation is presented for a 0-1 goal programming problem whose technological coefficients and right hand sides are stochastic. The model is presented with a numerical example for the purpose of demonstration.

• Transactions of the Korean hydrogen and new energy society
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• v.18 no.3
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• pp.265-274
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• 2007

A study has been conducted to clarify NO emission behavior through preferential diffusion effects of $H_2$ and H in methane-hydrogen diffusion flames. A comparison is made by employing three species diffusion models. Special concerns are focused on what is the deterministic role of the preferential diffusion effects in flame structure and NO emission. The behavior of maximum flame temperatures with three species diffusion models is not explained by scalar dissipation rate but the nature of chemical kinetics. The preferential diffusion of H into reaction zone suppresses the populations of the chain carrier radicals and then flame temperature while that of $H_2$ produces the increase of flame temperature. These preferential diffusion effects of $H_2$ and H are also discussed about NO emissions through the three species diffusion models.

• Communications for Statistical Applications and Methods
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• v.25 no.5
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• pp.471-488
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• 2018

In this paper, we propose extending proportional hazards frailty models to allow a discrete distribution for the frailty variable. Having zero frailty can be interpreted as being immune or cured. Thus, we develop a new survival model induced by discrete frailty with zero-inflated power series distribution, which can account for overdispersion. This proposal also allows for a realistic description of non-risk individuals, since individuals cured due to intrinsic factors (immunes) are modeled by a deterministic fraction of zero-risk while those cured due to an intervention are modeled by a random fraction. We put the proposed model in a Bayesian framework and use a Markov chain Monte Carlo algorithm for the computation of posterior distribution. A simulation study is conducted to assess the proposed model and the computation algorithm. We also discuss model selection based on pseudo-Bayes factors as well as developing case influence diagnostics for the joint posterior distribution through ${\psi}-divergence$ measures. The motivating cutaneous melanoma data is analyzed for illustration purposes.

• Nuclear Engineering and Technology
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• v.46 no.5
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• pp.619-632
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• 2014

The Best Estimate Plus Uncertainty (BEPU) method has been widely used to evaluate the uncertainty of a best-estimate thermal hydraulic system code against a figure of merit. This uncertainty is typically evaluated based on the physical model's uncertainties determined by expert judgment. This paper introduces the application of data assimilation methodology to determine the uncertainty bands of the physical models, e.g., the mean value and standard deviation of the parameters, based upon the statistical approach rather than expert judgment. Data assimilation suggests a mathematical methodology for the best estimate bias and the uncertainties of the physical models which optimize the system response following the calibration of model parameters and responses. The mathematical approaches include deterministic and probabilistic methods of data assimilation to solve both linear and nonlinear problems with the a posteriori distribution of parameters derived based on Bayes' theorem. The inverse problem was solved analytically to obtain the mean value and standard deviation of the parameters assuming Gaussian distributions for the parameters and responses, and a sampling method was utilized to illustrate the non-Gaussian a posteriori distributions of parameters. SPACE is used to demonstrate the data assimilation method by determining the bias and the uncertainty bands of the physical models employing Bennett's heated tube test data and Becker's post critical heat flux experimental data. Based on the results of the data assimilation process, the major sources of the modeling uncertainties were identified for further model development.

• Journal of Intelligence and Information Systems
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• v.12 no.4
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• pp.39-51
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• 2006

This study addresses how to plan purchasing and leasing of containers to satisfy the demand on containers. The problem can be further decomposed into the long-term planning and the short-term scheduling. The long-term plan specifies the composition of owned containers, long-term leasing containers, and short-term containers. The short-term plan considers the seasonality of demand and determines the time of leasing and the amount of the short-term and the long-term leasing containers. The length of the planning horizon is 10-20 years for the long-term planning, while it is one year for the short-term planning. The time unit is one year for the long-term planning, while it is one month for the short-term planning. This study discusses how to estimate the demand of containers and proposes deterministic models for scheduling purchasing and leasing of containers.