• International Journal of Automotive Technology
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• 제7권6호
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• pp.703-714
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• 2006

The growing concern surrounding rollover incidences and consequences of Sports Utility Vehicles(SUV) have prompted to investigate the sensitivity of critical vehicle parameters on rollover. In this paper, dynamic rollover simulation of Sports Utility Vehicles is carried out using a validated nonlinear vehicle model in Matlab/Simulink. A standard model is considered and critical vehicle parameters like CG height, track width and wheel base are varied within chosen specified limits to study its influence on roll behavior during a Fishhook steering maneuver. A roll stability criterion based on Two Wheel Lift Off(TWLO) phenomenon is adopted for rollover propensity prediction. Further dynamic rollover characteristics of the vehicle are correlated with Static Stability Factor(SSF), Roll Stability Factor(RSF) and Two Wheel Lift Off Velocity(TWLV). These findings will be of immense help to SUV chassis designers to determine safety limits of critical vehicle parameters and minimize rollover incidences.

• 한국콘크리트학회:학술대회논문집
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• 한국콘크리트학회 2004년도 추계 학술발표회 제16권2호
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• pp.773-776
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• 2004

The so-called Life Cycle Cost (LCC) analysis on reinforced concrete bridge can provide useful information for initial design and maintenance plan of the RC bridge. This paper proposes an LCC prediction equation and a sensitivity analysis method for RC bridges. An LCC equation for the RC bridge which includes initial investment cost, maintenance cost, and demolition cost was derived and verified from the data for design and construction of an RC slab bridge. In order to solve uncertainty problem on actual discount rate and material characteristics in the analysis of LCC of concrete bridges, a sensitivity analysis method on the LCC using the Monte Carlo simulation technique was suggested.

• 대한조선학회논문집
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• 제42권5호
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• pp.458-465
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• 2005

Sensitivity Analysis(SA) is used to predict how the model response varies according to changes in the model parameters. With SA, confidences in models which are developed to approximate certain processes and their predictions can be increased. The influences of hydrodynamic coefficients on the prediction of manoeuvrability are examined by SA of direct method. The equations of motion used are the standard equations of motion for submarine(Gertler 1967), and submerged bodies with three different appendages are considered. Through numerical simulations of three kinds of sea trials, the sensitivities of motions to hydrodynamic coefficients are found. Changes of sensitivities during trials are found to be highly dependent on the actuator scenarios and geometry of submerged body.

• Coupled systems mechanics
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• 제11권2호
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• pp.133-149
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• 2022

The accurate prediction of elastoplasticity under prescribed workloads is essential in the optimization of engineering structures. Mechanical experiments are carried out with the goal of obtaining reliable sets of material parameters for a chosen constitutive law via inverse identification. In this work, two sample geometries made of high strength steel plates were evaluated to determine the optimal configuration for the identification of Ludwik's nonlinear isotropic hardening law. Finite element model updating(FEMU) was used to calibrate the material parameters. FEMU computes the parameter changes based on the Hessian matrix, and the sensitivity fields that report changes of computed fields with respect to material parameter changes. A sensitivity analysis was performed to determine the influence of the sample geometry on parameter identifiability. It was concluded that the sample with thinned gauge region with a large curvature radius provided more reliable material parameters.

• 한국대기환경학회:학술대회논문집
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• 한국대기환경학회 2009년도 추계학술대회 논문집
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• pp.283-285
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• 2009

• 한국지구과학회:학술대회논문집
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• 한국지구과학회 2002년도 춘계학술발표 논문요약집
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• pp.41-41
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• 2002

• 대기
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• 제29권1호
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• pp.21-39
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• 2019

The conventional observations of the Korea Meteorological Administration (KMA) and National Centers for Environmental Prediction (NCEP) are compared in the numerical weather forecast system at the Korea Institute of Atmospheric Prediction Systems (KIAPS). The weather forecasting system used in this study is consists of Korea Integrated Model (KIM) as a global numerical weather prediction model, three-dimensional variational method as a data assimilation system, and KIAPS Package for Observation Processing (KPOP) as an observation pre-processing system. As a result, the forecast performance of NCEP observation was better while the number of observation is similar to the KMA observation. In addition, the sensitivity of forecast performance was investigated for each SONDE, SURFACE and AIRCRAFT observations. The differences in AIRCRAFT observation were not sensitive to forecast, but the use of NCEP SONDE and SURFACE observations have shown better forecast performance. It is found that the NCEP observations have more wind observations of the SONDE in the upper atmosphere and more surface pressure observations of the SURFACE in the ocean. The results suggest that evenly distributed observations can lead to improved forecast performance.

• Computers and Concrete
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• 제22권2호
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• pp.197-207
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• 2018

In the present study, group method of data handling networks (GMDH) are adopted and evaluated for shear strength prediction of both FRP-reinforced concrete members with and without stirrups. Input parameters considered for the GMDH are altogether 12 influential geometrical and mechanical parameters. Two available and very recently collected comprehensive datasets containing 112 and 175 data samples are used to develop new models for two cases with and without shear reinforcement, respectively. The proposed GMDH models are compared with several codes of practice. An artificial neural network (ANN) model and an ANFIS based model are also developed using the same databases to further assessment of GMDH. The accuracy of the developed models is evaluated by statistical error parameters. The results show that the GMDH outperforms other models and successfully can be used as a practical and effective tool for shear strength prediction of members without stirrups ($R^2=0.94$) and with stirrups ($R^2=0.95$). Furthermore, the relative importance and influence of input parameters in the prediction of shear capacity of reinforced concrete members are evaluated through parametric and sensitivity analyses.

• Structural Engineering and Mechanics
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• 제83권3호
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• pp.363-375
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• 2022

Flexural capacity prediction is a challenging problem for externally prestressed concrete beams (EPCBs) due to the unbonded phenomenon between the concrete beam and external tendons. Many prediction equations have been provided in previous research but typically ignored the differences in deformation mode between internal and external unbonded tendons. The availability of these equations for EPCBs is controversial due to the inconsistent deformation modes and ignored second-order effects. In this study, the deformation characteristics and collapse mechanism of EPCB are carefully considered, and the ultimate deflected shape curves are derived based on the simplified curvature distribution. With the compatible relation between external tendons and the concrete beam, the equations of tendon elongation and eccentricity loss at ultimate states are derived, and the geometric interpretation is clearly presented. Combined with the sectional equilibrium equations, a rational and simplified flexural capacity prediction method for EPCBs is proposed. The key parameter, plastic hinge length, is emphatically discussed and determined by the sensitivity analysis of 324 FE analysis results. With 94 collected laboratory-tested results, the effectiveness of the proposed method is confirmed, and comparisons with the previous formulas are made. The results show the better prediction accuracy of the proposed method for both stress increments and flexural capacity of EPCBs and the main reasons are discussed.

• 대한의용생체공학회:의공학회지
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• 제39권2호
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• pp.69-79
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• 2018

The present study proposes an algorithm that can discriminate between normal subjects and paroxysmal atrial fibrillation (PAF) patients, which is conducted using electrocardiogram (ECG) without PAF events. For this, time-domain features and random forest classifier are used. Time-domain features are obtained from Poincare plot, Lorenz plot of ${\delta}RR$ interval, and morphology analysis. Afterward, three features are selected in total through feature selection. PAF patients and normal subjects are classified using random forest. The classification result showed that sensitivity and specificity were 81.82% and 95.24% respectively, the positive predictive value and negative predictive value were 96.43% and 76.92% respectively, and accuracy was 87.04%. The proposed algorithm had an advantage in terms of the computation requirement compared to existing algorithm, so it has suggested applicability in the more efficient prediction of PAF.