• Geomechanics and Engineering
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• v.36 no.5
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• pp.475-487
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• 2024

Many uncertainties affect the stability assessment of rock structures. Some of these factors significantly influence technology decisions. Some of these factors belong to the geological domain, and spatial uncertainty measurements are useful for structural stability analysis. This paper presents an integrated approach to study the stability of rock structures, including spatial factors. This study models two main components: discrete structures (fault zones) and well known geotechnical parameters (rock quality indicators). The geostatistical modeling criterion are used to quantify geographic uncertainty by producing simulated maps and RQD values for multiple equally likely error regions. Slope stability theorem would be demonstrated by modeling local failure zones and RQDs. The approach proided is validated and finally, the slope stability analysis method and fuzzy Laypunov criterion are applied to mining projects with limited measurement data. The goals of this paper are towards access to adequate, safe and affordable housing and basic services, promotion of inclusive and sustainable urbanization and participation, implementation of sustainable and disaster-resilient buildings, sustainable human settlement planning and manage. Simulation results of linear and nonlinear structures show that the proposed method is able to identify structural parameters and their changes due to damage and unknown excitations. Therefore, the goal is believed to achieved in the near future by the ongoing development of AI and fuzzy theory.

• Journal of Korean Society on Water Environment
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• v.36 no.6
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• pp.621-635
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• 2020

Water quality models are scientific tools that simulate and interpret the relationship between physical, chemical and biological reactions to external pollutant loads in water systems. They are actively used as a key technology in environmental water management. With recent advances in computational power, water quality modeling technology has evolved into a coupled three-dimensional modeling of hydrodynamics, water quality, and ecological inputs. However, there is uncertainty in the simulated results due to the increasing model complexity, knowledge gaps in simulating complex aquatic ecosystem, and the distrust of stakeholders due to nontransparent modeling processes. These issues have become difficult obstacles for the practical use of water quality models in the water management decision process. The objectives of this paper were to review the theoretical background, needs, and development status of water quality modeling technology. Additionally, we present the potential future directions of water quality modeling technology as a scientific tool for national environmental water management. The main development directions can be summarized as follows: quantification of parameter sensitivities and model uncertainty, acquisition and use of high frequency and high resolution data based on IoT sensor technology, conjunctive use of mechanistic models and data-driven models, and securing transparency in the water quality modeling process. These advances in the field of water quality modeling warrant joint research with modeling experts, statisticians, and ecologists, combined with active communication between policy makers and stakeholders.

• Journal of the Korean GEO-environmental Society
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• v.15 no.3
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• pp.21-32
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• 2014

This Research have suggested the new estimation method using parameter estimation algorithm to substitute established velocity and friction factor calculation equation. Established calculation equation has some difficulties for estimation and reflecting exactly flow specification cause parameter uncertainty and material uncertainty governed real phenomenon, so this research has used system modeling method for flow specification estimation and suggested estimation method.

• Geomechanics and Engineering
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• v.24 no.3
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• pp.281-293
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• 2021

Uncertainties in geomechanical input parameters which mainly related to inappropriate data acquisition and estimation due to lack of sufficient calibration information, have led wellbore instability not yet to be fully understood or addressed. This paper demonstrates a workflow of employing Quantitative Risk Assessment technique, considering these uncertainties in terms of rock properties, pore pressure and in-situ stresses to makes it possible to survey not just the likelihood of accomplishing a desired level of wellbore stability at a specific mud pressure, but also the influence of the uncertainty in each input parameter on the wellbore stability. This probabilistic methodology in conjunction with Monte Carlo numerical modeling techniques was applied to a case study of a well. The response surfaces analysis provides a measure of the effects of uncertainties in each input parameter on the predicted mud pressure from three widely used failure criteria, thereby provides a key measurement for data acquisition in the future wells to reduce the uncertainty. The results pointed out that the mud pressure is tremendously sensitive to UCS and SHmax which emphasize the significance of reliable determinations of these two parameters for safe drilling. On the other hand, the predicted safe mud window from Mogi-Coulomb is the widest while the Hoek-Brown is the narrowest and comparing the anticipated collapse failures from the failure criteria and breakouts observations from caliper data, indicates that Hoek-Brown overestimate the minimum mud weight to avoid breakouts while Mogi-Coulomb criterion give better forecast according to real observations.

• Journal of The Korean Society of Agricultural Engineers
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• v.58 no.4
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• pp.57-66
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• 2016

Harmonized World Soil Database (HWSD) including the global soil information has been implemented to the runoff analysis in many watersheds of the world. However, its accuracy can be a critical issue in the modeling because of the limitation the low resolution reflecting the physical properties of soil in a watershed. Accordingly, this study attempted to assess the effect of HWSD in modeling by comparing parameters of the rainfall-runoff model using HWSD with the detailed soil map. For this, Grid based Rainfall-runoff Model (GRM) was employed in the Hyangseok watershed. The results showed that both of two soil maps in the rainfall-runoff model are able to well capture the observed runoff. However, compared with the detailed soil map, HWSD produced more uncertainty in the GRM parameters related to soil depth and hydraulic conductivity during the calibrations than the detailed soil map. Therefore, the uncertainty from the limited information on soil texture in HWSD should be considered for better calibration of a rainfall-runoff model.

• Journal of the Institute of Convergence Signal Processing
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• v.3 no.2
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• pp.76-82
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• 2002

The objective of this paper is to design a robust controller for a flexible robot arm manipulator using LMI(Linear Matrix Inequality) theory, and confirm its effectiveness through experimentation. We first describe a modeling Process of the flexible arm in order to get a mathematical model, and then discuss how to approximately obtain the uncertainty of the model for robust control. As to the control system design, we adopt the LMI-based H$_{\infty}$ synthesis algorithm which has the merits of eliminating the regularity restrictions attached to the Riccati-based methods. As a result of this, we can cope with the parameter variation (that is, modeling uncertainty) due to the tip-load variation. Finally we confirm the effectiveness of the controller through experiment and simulation.

• Proceedings of the IEEK Conference
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• 2002.07a
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• pp.627-630
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• 2002

A methodology based on factorial design and Motto Carlo methods is developed and implemented for incorporating uncertainties within a multiphase subsurface flow and transport simulation system. Due to uncertainties in intrinsic permeability and longitudinal dispersivity, the predicted output is also uncertain based on the well-developed multiphase compositional simulator. The simulation results reveal that the uncertainties in input parameters pose considerable influences on the predicted output, and the mean and variance of permeability will have significant impacts on the modeling output. The proposed method offers an effective tool for evaluating uncertainty in multiphase flow simulation system.

• Journal of the Korean Society of Safety
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• v.31 no.1
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• pp.25-32
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• 2016

A sensitivity analysis of FDS(Fire Dynamics Simulator) results for the input uncertainty of heat release rate (Q) which might be the most influencing parameter to fire behaviors was performed. The calculated results were compared with experimental data obtained by the OECD/NEA PRISME project. The sensitivity of FDS results with the change in Q was also compared with the empirical correlations suggested in previous literature. As a result, the change in the specified Q led to the different dependence of major quantities such as temperature and species concentrations for the over- and under-ventilated fire conditions, respectively. It was also found that the sensitivity of major quantities to uncertain value of Q showed the significant difference in results obtained using the previous empirical correlations.

• Journal of the Korean Society for Precision Engineering
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• v.25 no.12
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• pp.89-99
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• 2008

In this paper, the position tracking control problem of the servo system with nonlinear dynamic friction is issued. The nonlinear dynamic friction contains a directly immeasurable friction state variable and the uncertainty caused by incomplete parameter modeling and its variations. In order to provide the efficient solution to these control problems, we propose the composite control scheme, which consists of the robust friction state observer, the FNN approximator and the approximation error estimator with sliding mode control. In first, the sliding mode controller and the robust friction state observer is designed to estimate the unknown internal state of the LuGre friction model. Next, the FNN estimator is adopted to approximate the unknown lumped friction uncertainty. Finally, the adaptive approximation error estimator is designed to compensate the approximation error of the FNN estimator. Some simulations and experiments on the servo system assembled with ball-screw and DC servo motor are presented. Results show the remarkable performance of the proposed control scheme. The robust friction state observer can successfully identify immeasurable friction state and the FNN estimator and adaptive approximation error estimator give the robustness to the proposed control scheme against the uncertainty of the friction parameters.

• Journal of Korea Water Resources Association
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• v.50 no.11
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• pp.745-758
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• 2017

The copula-based models have been successfully applied to hydrological modeling including drought frequency analysis and time series modeling. However, uncertainty estimation associated with the parameters of these model is not often properly addressed. In these context, the main purposes of this study are to develop the Bayesian inference scheme for bivariate copula functions. The main applications considered are two-fold: First, this study developed and tested an approach to copula model parameter estimation within a Bayesian framework for drought frequency analysis. The proposed modeling scheme was shown to correctly estimate model parameters and detect the underlying dependence structure of the assumed copula functions in the synthetic dataset. The model was then used to estimate the joint return period of the recent 2013~2015 drought events in the Han River watershed. The joint return period of the drought duration and drought severity was above 100 years for many of stations. The results obtained in the validation process showed that the proposed model could effectively reproduce the underlying distribution of observed extreme rainfalls as well as explicitly account for parameter uncertainty in the bivariate drought frequency analysis.