• Proceedings of the Korean Society of Precision Engineering Conference
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• 2002.05a
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• pp.283-286
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• 2002

In fiber optic sensor, the error of the measurement is influenced by the surface roughness of the target and surroundings, especially the outside light. To reduce or modify this error, the sensitivity of the fiber optic sensor and the noise change by the surface roughness of the target should be known. The purpose of this paper is to observe the sensitivity of the fiber optic sensor and the noise according to the surface roughness of the target.

• Journal of Korean Society of Water and Wastewater
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• v.18 no.6
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• pp.748-757
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• 2004

In this study, we analyzed the sensitivity of parameters which affect the result of ILLUDAS model, in the various rainfall conditions. The three basins including Namgaja, Kings creek, Gray haven were selected for this research. The rainfall conditions are considered in terms of the rainfall frequency, the duration and the distribution. In most cases, the impermeability area ratio, the sewer slope, and the sewer roughness coefficient give more significant effects on the results than others. The results show that as increasing the rainfall frequency, the sensitivity of the parameters, sewer slope and roughness coefficient are rised, while the impermeability area ratio is decreasing. And also, for the duration of rainfall, the impermeability area ratio's sensitivity shows similar tendency. In case of the rainfall distribution, the parameters of the sewer roughness and the impermeability area ratio show more sensitive in Huff distribution. Especially, The impermeability area ratio is the most sensitive parameter in Central blocking and Yen & Chow distributions respectively.

• Journal of Mechanical Science and Technology
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• v.20 no.7
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• pp.1077-1088
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• 2006

This paper describes a numerical investigation on the performance deteriorations of a low speed, single-stage axial turbine due to use of rough blades. Numerical calculations have been carried out with a commercial CFD code, CFX-Tascflow, by using a modified wall function to implement rough surfaces on the stator vane and rotor blade. To assess the stage performance variations corresponding to 5 equivalent sand-grain roughness heights from a transition ally rough regime to a fully rough regime, stage work coefficient and total to static efficiency were chosen. Numerical results showed that both work coefficient and stage efficiency reduced as roughness height increased. Higher surface roughness induced higher blade loading both on the stator and rotor which in turn resulted in higher deviation angles and corresponding work coefficient reductions. Although, deviation angle changes were small, a simple sensitivity analysis suggested that their contributions on work coefficient reductions were substantial. Higher profile loss coefficients were predicted by higher roughness heights, especially on the suction surface of the stator and rotor. Furthermore sensitivity analysis similar to the above, suggested that additional profile loss generations due to roughness were accountable for efficiency reductions.

• Corrosion Science and Technology
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• v.8 no.5
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• pp.193-196
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• 2009

For the estimation of uncertainty in potentiodynamic polarization resistance measurement, the type A uncertainty was measured using type 316 stainless steel in an acidified NaCl solution. Sensitivity coefficients were determined for measurand such as scan rate of potential, temperature of solution, concentration of NaCl, concentration of HCl, surface roughness of specimen and flow rate of purging gas. Sensitivity coefficients were large for the measurand such as the scan rate of potential, temperature of solution and roughness of specimen. However, the sensitivity coefficients were not the major factors influencing the combined standard uncertainty of polarization resistance due to the low values of uncertainty in measurements of the measurands. A major influencing factor was the concentration of NaCl. The value of type A uncertainty was 1.1 times the value of type B uncertainty, and the combined standard uncertainty was 10.5 % of the average value of polarization resistance.

• International Journal of Highway Engineering
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• v.4 no.2 s.12
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• pp.9-18
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• 2002

The main distresses that influence pavement performance are rutting, fatigue cracking, and longitudinal roughness. Thus, it is important to analyze the factors that affect these three distresses, and to develop prediction models. In this paper, three distress prediction models were developed using DataPave program which stores data from a wide variety of pavement sections In the United States. Also, sensitivity studies were conducted to evaluate how the input variables impact on the distresses. The result of sensitivity study for the prediction model of rutting showed that asphalt content, air void, and optimum moisture content of subgrade were the major factors that affect rutting. The output of sensitivity study for the prediction model of fatigue cracking revealed that asphalt consistency, asphalt content, and air void were the most influential variables. The prediction model of longitudinal roughness indicated asphalt consistency, #200 passing percent of subgrade aggregate, and asphalt content were the factors that affect longitudinal roughness.

• Korean Journal of Materials Research
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• v.13 no.2
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• pp.111-114
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• 2003

Effects of substrate materials on the microstructure and the sensitivity of $SnO_2$thin film gas sensors have been studied. Various substrates were studied, such as oxidized silicon, sapphire, polished alumina, and unpolished alumina. It was observed that strong correlation exists between the electrical resistance and the CO gas sensitivity of the manufactured sensors and the surface roughness of $SnO_2$thin films, which in turn was related to the surface roughness of the original substrates. X$SnO_2$thin film gas sensor on unpolished alumina with the highest surface roughness showed the highest initial resistance and CO gas sensitivity. The transmission electron microscopy observation indicated that shape and size of the columnar microstructure of the thin films were not critically affected by the type of substrates.

• Journal of Korean Society for Geospatial Information Science
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• v.15 no.2 s.40
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• pp.33-42
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• 2007

A physical-based aggregation method was suggested to estimate surface roughness, which adequately represents the spatial heterogeneity of vegetation factors, from land cover property obtained from the remote sensing data. For the sensitivity analysis of surface roughness, the peak flow, peak time, and total volume were simulated by the NWS-PC. Effects of surface roughness estimated by three different integration methods (predominant, arithmetic mean, and aggregation approach) on the conceptual rainfall-runoff model parameters was analyzed. In the preliminary sensitivity test to surface roughness, the peak time had 10% variation and total volume had 2% variation. The peak time increased with surface roughness. A physical-based aggregation method was better than the existing method in the Soyanggang Dam basin for the results of STDEV, RMSE, NSE, and PME, but difference between them were small. The parameters related on the total baseflow were changed significantly with change of the surface roughness.

• Journal of Korean Society of Water and Wastewater
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• v.23 no.2
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• pp.181-187
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• 2009

In this study, a runoff hydrograph and runoff volume were calculated by using the kinetic wave theory for small urban watersheds based on the concept of low impact development(LID), and the effective imperviousness was estimated based on these calculations. The degree of sensitivity of the effective imperviousness of small watersheds to the impervious to pervious area ratio, infiltration capability, watershed slope, roughness coefficient and surface storage depth was then analyzed. From this analysis, the following conclusions were obtained: The effective imperviousness and paved area reduction factor decreased as the infiltration capability of pervious area increased. As the slope of watersheds becomes sharper, the effective imperviousness and the paved area reduction factor display an increasing trend. As the roughness coefficient of impervious areas increases, the effective imperviousness and the paved area reduction factor tend to increase. As the storage depth increases, the effective imperviousness and the paved area reduction factor show an upward trend, but the increase is minimal. Under the conditions of this study, it was found that the effective imperviousness is most sensitive to watershed slope, followed by infiltration capability and roughness coefficient, which affect the sensitivity of the effective imperviousness at a similar level, and the storage depth was found to have little influence on the effective imperviousness.

• Journal of Korea Water Resources Association
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• v.31 no.1
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• pp.115-120
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• 1998

In this paper, a depth-averaged two-dimensional transport model is introduced, and its error bound is presented as the results of sensitivity analysis. The results show that the calculated SS concentration is highly dependant on Manning roughness coefficient, mixing coefficient. fall velocity. and critical shear stress. On the other hand, water level and dispersion coefficient are proved to be less significant in the variation of SS concentration.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2007.11a
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• pp.65-65
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• 2007

Microstructure and surface roughness of the sensing materials should be improved to use them in advanced sensor applications because the uneven surface roughness degrades the light reflection, pattern resolution, and devices performance. Chemical mechanical polishing (CMP) processing was selected for improving the surface roughness of $CeO_2$ which is one of the well known materials for the oxygen gas sensors. Surface roughness and removal rate of spin coated $CeO_2$ thin films were examined with a change of CMP process parameters such as down force and table speed. The optimized process condition, reflected by the surface roughness with the hillock-free surface as well as the excellent removal rate with the good uniformity, was obtained. The effects of the improved surface roughness on the sensing property of $CeO_2$ thin films were also confirmed. The improved sensitivity of $CeO_2$ thin films for oxygen sensors were obtained after CMP process by the improved surface characteristics. Therefore, we conclude that sensing property of $CeO_2$ thin film is strongly dependent on the surface roughness of $CeO_2$ thin films by using CMP process.