• Title/Summary/Keyword: Model Uncertainties

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Review of Uncertainties in Applying GIS Data and Hydrological Models to Evaluate the Effectiveness of Best Management Practices (수리모델과 GIS 데이터를 이용한 최적관리방안의 평가에 대한 불확실성의 재고)

  • Lee, Tae-Soo
    • Journal of the Korean association of regional geographers
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    • v.17 no.2
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    • pp.245-258
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    • 2011
  • Best management practices (BMPs) are widely accepted and implemented as a mitigation method for soil erosion and non-point source problems. Estimating the amount of soil erosion and the effectiveness of BMPs using hydrological models help to understand the condition, identify the problems, and make plans for conservation practices in an area, typically a watershed. However, the accuracy and reliability of assessment of BMP impacts estimated by hydrological models can be often questionable due to the uncertainties from various sources including GIS(Geographic Information System) data, scale, and model. This study reviewed the development and the background of hydrological models, and the modeling issues such as the selection of models, scale, and uncertainties of data and models. This study also discussed the advantage of a small scale and spatially distributed model to estimate the impacts of BMPs.

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Uncertainty and Estimation of Health Burden from Particulate Matter in Seoul Metropolitan Region (수도권 대기 중 입자상 물질로 인한 건강부담 추정과 불확실성)

  • Ha, Jongsik;Moon, Nankyoung
    • Journal of Korean Society for Atmospheric Environment
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    • v.29 no.3
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    • pp.275-286
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    • 2013
  • It is well known that exposure to high level of PM (particulate matter) can adversely affect human health. However, little is known about health burden of PM considering the relationship, exposed level of PM, and health level in local communities. And, there is scarcely methodical assessment of uncertainty for application to policies of these assessment results. The scope of this study is divided into two parts: firstly to estimate the death burden of PM10 (particulate matter less then $10{\mu}m$ in diameter) in Seoul metropolitan region, and secondly to evaluate potential uncertainties in these estimates. To estimate the death burden of PM10 in Seoul metropolitan region from 2005~2010, we firstly assessed the relationship between daily mean PM10 and daily death counts in Seoul from 2000~2010, and calculated the death burden of PM10 using BenMAP (Environmental Benefits Mapping and Analysis Program). After that, we identified and characterized uncertainties to substantially influence the results of death burden. The daily mortality risk was increased 1.000227 times (p-value/0.001) associated with $1{\mu}g/m^3$ increase of daily mean PM10 for all ages population, Seoul. And, death burdens of PM10 in Seoul metropolitan region were estimated from 5.51 in 2005 to 5.12 in 2010 per 100,000 people. Finally, we categorized context, model, and input uncertainty and characterized these uncertainties in three dimensions (i.e. location, level, and nature) using uncertainty typology. In our study, we argue that uncertainties need to be identified, assessed, reported and interpreted in order for assessment results to adequately support decision making, such as the establishment of air quality standards based on health burden of air quality.

Analytical and experimental exploration of sobol sequence based DoE for response estimation through hybrid simulation and polynomial chaos expansion

  • Rui Zhang;Chengyu Yang;Hetao Hou;Karlel Cornejo;Cheng Chen
    • Smart Structures and Systems
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    • v.31 no.2
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    • pp.113-130
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    • 2023
  • Hybrid simulation (HS) has attracted community attention in recent years as an efficient and effective experimental technique for structural performance evaluation in size-limited laboratories. Traditional hybrid simulations usually take deterministic properties for their numerical substructures therefore could not account for inherent uncertainties within the engineering structures to provide probabilistic performance assessment. Reliable structural performance evaluation, therefore, calls for stochastic hybrid simulation (SHS) to explicitly account for substructure uncertainties. The experimental design of SHS is explored in this study to account for uncertainties within analytical substructures. Both computational simulation and laboratory experiments are conducted to evaluate the pseudo-random Sobol sequence for the experimental design of SHS. Meta-modeling through polynomial chaos expansion (PCE) is established from a computational simulation of a nonlinear single-degree-of-freedom (SDOF) structure to evaluate the influence of nonlinear behavior and ground motions uncertainties. A series of hybrid simulations are further conducted in the laboratory to validate the findings from computational analysis. It is shown that the Sobol sequence provides a good starting point for the experimental design of stochastic hybrid simulation. However, nonlinear structural behavior involving stiffness and strength degradation could significantly increase the number of hybrid simulations to acquire accurate statistical estimation for the structural response of interests. Compared with the statistical moments calculated directly from hybrid simulations in the laboratory, the meta-model through PCE gives more accurate estimation, therefore, providing a more effective way for uncertainty quantification.

A method for the determination of transient flow rates from pressure measurements (압력측정을 이용한 과도기유량의 결정방법에 관한 연구)

  • 이성래
    • 제어로봇시스템학회:학술대회논문집
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    • 1992.10a
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    • pp.724-729
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    • 1992
  • A transient hydraulic flow rate computation scheme is described here so that the transient hydraulic flow rate can be determined using the dynamic pressure measurements at the ends of a straight flowline with a dynamic, model of the hydraulic line. Simulation results indicate that the method is relatively robust to realistic levels of uncertainties in the fluid properties.

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Strut-Tie Model Approach Associated with 3-Dimensional Grid Elements for Design of Structural Concrete - (I) Proposal of Approach (3차원 격자요소를 활용한 콘크리트 구조부재의 스트럿-타이 모델 설계 방법 - (I) 방법의 제안)

  • Kim, Byung Hun;Yun, Young Mook
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.34 no.2
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    • pp.425-436
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    • 2014
  • Although the strut-tie model approaches of current design codes are regarded as the valuable methods for designs of structural concretes with D-regions, the approaches have to be improved because of the uncertainties in terms of the concepts and provisions for designs of 3-dimensional structural concretes. To improve the uncertainties, a new strut-tie model approach is proposed in this study. In the proposed approach, the concepts of employing a 3-dimensional grid element allowing load transfers in all directions at a node to construct a strut-tie model, a numerical analysis approach to determine the effective strengths of concrete struts and nodal zones by reflecting the effects of reinforcing bars and 3-dimensional stress state, and maximum areas of struts and ties to examine their load carrying capacities are integrated into the strut-tie model approaches of current design codes.

Sensitivity Analysis of Hydrodynamic and Reaction Parameters in Gasoline Transport Conceptual Aquifer Model Based on Hydrogeological Characteristics of Korea (국내 대수층 특성을 반영한 포화대 내 유류오염물질 거동 개념 모델에서 수리동역학적 및 반응 입력인자 민감도 평가)

  • Joo, Jin Chul;Lee, Dong Hwi;Moon, Hee Sun;Chang, Sun Woo;Lee, Soo-Hyoung;Lee, Eunhee;Nam, Kyoungphile
    • Journal of Soil and Groundwater Environment
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    • v.25 no.1
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    • pp.37-52
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    • 2020
  • Sensitivity analysis of hydrodynamic and reaction parameters in conceptual model reflecting aquifer characteristics of Korea was performed to evaluate the uncertainty in the predicted concentrations. Among the hydrodynamic input parameters, both hydraulic conductivity (Kx) and hydraulic gradient (I) affected transport behaviors of contaminants, and resulted in same convergence concentrations with continuous injections of contaminant. However, longitudinal dispervisity (αL) affected both transport behaviors and the convergence concentrations of contaminants. Compared to the hydrodynamic parameters, growth kinetic and degradation parameters (μm & Kc) more significantly affected both transport behaviors and the convergence concentrations of contaminants, indicating those parameters had higher sensitivity indices causing the uncertainties of model predictions. Considering that the sensitivity indices of both hydrodynamic and reaction parameters were a function of transport distance of groundwater, the parameters with higher sensitivity indices, a priori, need to be investigated using conceptual model reflecting site-specific aquifer characteristics before field investigation. After determining the parameters with higher sensitivity indices, the detail field investigations for the selected hydrodynamic and reaction parameters were warranted to reduce the uncertainties of model predictions.

Future Inflow Simulation Considering the Uncertainties of TFN Model and GCMs on Chungju Dam Basin (TFN 모형과 GCM의 불확실성을 고려한 충주댐 유역의 미래 유입량 모의)

  • Park, Jiyeon;Kwon, Ji-Hye;Kim, Taereem;Heo, Jun-Haeng
    • Journal of Korea Water Resources Association
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    • v.47 no.2
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    • pp.135-143
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    • 2014
  • In this study, Chungju inflow was simulated for climate change considering the uncertainties of GCMs and a stochastic model. TFN (Transfer Function Noise) model and 4 different GCMs (CNRM, CSIRO, CONS, UKMO) based on IPCC AR4 A2 scenario were used. In order to evaluate uncertainty of TFN model, 100 cases of noises are applied to the TFN model. Thus, 400 cases of inflow results are simulated. Future inflows according to the GCMs show different rates of changes for the future 3 periods relative to the past 30-years reference period. As the results, the summer inflow shows increasing trend and the spring inflow shows decreasing trend based on AR4 A2 scenario.

Trajectory Estimation of a Moving Object using Kohonen Networks

  • Ju, Jin-Hwa;Lee, Dong-Hui;Lee, Jae-Ho;Lee, Jang-Myung
    • 제어로봇시스템학회:학술대회논문집
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    • 2004.08a
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    • pp.2033-2036
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    • 2004
  • A novel approach to estimate the real time moving trajectory of an object is proposed in this paper. The object position is obtained from the image data of a CCD camera, while a state estimator predicts the linear and angular velocities of the moving object. To overcome the uncertainties and noises residing in the input data, a Kalman filter and neural networks are utilized. Since the Kalman filter needs to approximate a non-linear system into a linear model to estimate the states, there always exist errors as well as uncertainties again. To resolve this problem, the neural networks are adopted in this approach, which have high adaptability with the memory of the input-output relationship. Kohonen Network(Self-Organized Map) is selected to learn the motion trajectory since it is spatially oriented. The superiority of the proposed algorithm is demonstrated through the real experiments.

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