• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.23 no.11
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• pp.1020-1026
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• 2013

An accurate railway environmental noise prediction model is required to make the proper solution of the railway noise problems. In this paper, an engineering model for predicting the noise of conventional passenger cars is presented considering the acoustic source strength in octave-band frequencies and the propagation over grounds with varying surface properties. Since the formation of a train can be variable, the source strength of each locomotive and passenger car was estimated by measuring the pass-by noise and analysing the wheel-rail rolling noise. Some validation cases show on the average small differences between the predictions of the present model and the measurement results.

• Journal of Environmental Health Sciences
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• v.31 no.4 s.85
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• pp.260-265
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• 2005

Indoor air quality might be affected by source strength of indoor pollutants, ventilation rate, decay rate, outdoor level, and so on. Although technologies measuring these factors exist directly, direct measurements of all factors are not always practical in most field studies. The purpose of this study was to develop an alternative method to estimate the source strength and deposition constant by application of multiple measurements. For the total duration of 60 days, indoor and outdoor $NO_2$ concentrations every 3 days were measured in 30 houses in Seoul, Asan and Daegu. Using a compartment model by mass balance and linear regression analysis, penetration factor (ventilation divided by sum of air exchange rate and deposition constant) and source strength factor (emission rate divided by sum of air exchange rate and deposition constant) were calculated. Subsequently, the source strength and deposition constant were estimated. Natural ventilation was $1.80{\pm}0.42\;ACH,\;1.11{\pm}0.50\;ACH,\;0.92{\pm}0.26\;ACH$ in Seoul, Asan and Daegu, respectively. Calculated deposition constant(K) and source strength of $NO_2,$ in this study were $0.98{\pm}0.28\;hr^{1}\;and\;16.28{\pm}7.47\;ppb/h,$ respectively.

• The Journal of the Acoustical Society of Korea
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• v.24 no.3
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• pp.166-170
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• 2005

This paper describes the experimental study for the position estimation method of underwater sound source using the Nearfield Acoustic Holography. The result confirms that it can be used in the identification of underwater noise sources. The sound sources in the experimental work consists of 2 spherical projectors and the near-Held sound pressure is measured in the hologram plane. From the cross-power spectra of the measured data, the complex sound pressures on the hologram plane is derived and its spatial transformation gives sound fields in a source region. The obtained sound fields in a source region showed that the position of each sound source and their relative source strength are exactly estimated. In conclusion, this technique can be applied for estimation of each source position and its relative strength contribution for the underwater multiple sound sources.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.22 no.12
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• pp.1715-1725
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• 1998

A two-dimensional transient inverse heat conduction problem involving the estimation of the unknown location, ($X^*$, $Y^*$), and timewise varying unknown strength, $G({\tau})$, of a line heat source embedded inside a rectangular bar with insulated boundaries has been solved simultaneously. The regular conjugate gradient method, RCGM and the modified conjugate gradient method, MCGM with adjoint equation, are used alternately to estimate the unknown strength $G({\tau})$ of the source term, while the parameter estimation approach is used to estimate the unknown location ($X^*$, $Y^*$) of the line heat source. The alternate use of the regular and the modified conjugate gradient methods alleviates the convergence difficulties encountered at the initial and final times (i.e ${\tau}=0$ and ${\tau}={\tau}_f$), hence stabilizes the computation and fastens the convergence of the solution. In order to examine the effectiveness of this approach under severe test conditions, the unknown strength $G({\tau})$ is chosen in the form of rectangular, triangular and sinusoidal functions.

• Journal of Welding and Joining
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• v.34 no.2
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• pp.67-72
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• 2016

Aluminum alloy is one of light weight material and it is used to make LNG tank and ship. However, in order to weld aluminum alloy high density heat source is needed. In this paper, I-butt welding of Al 5083 with 6mm thickness using Plasma-MIG welding was carried out. The experiment was performed to investigate the influence of plasma-MIG welding parameters such as plasma current, wire feeding rate, MIG-welding voltage and welding speed on the tensile strength of weld. In addition we suggested 3 strength estimation models which are second order polynomial regression model, multiple nonlinear regression model and neural network model. The estimation performance of 3 models was evaluated in terms of average error rate (AER) and their values were 0.125, 0.238, and 0.021 respectively. Neural network model which has training concept and reflects non -linearity was best estimation performance.

• Proceedings of the Korean Environmental Sciences Society Conference
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• 2003.05a
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• pp.155-160
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• 2003

Indoor air quality can be affected by indoor sources, ventilation, decay and outdoor levels. Although technologies exist to measure these factors, direct measurements are often difficult. The purpose of this study was to develop an alternative method to characterize indoor environmental factors by multiple indoor and outdoor measurements. Daily indoor and outdoor $NO_2$ concentrations were measured for 30 consecutive days in 28 houses in Brisbane, Australia, and for 21 consecutive days in 37 houses in Seoul, Korea. Using a mass balance model and regression analysis, penetration factor (ventilation rate divided by the sum of ventilation rate and deposition constant) and source strength factor (source strength divided by the sum of ventilation rate and deposition constant) were calculated using multiple indoor and outdoor measurements. Subsequently, the ventilation rate and $NO_2$ source strength were estimated. Geometric means of ventilation rate were 1.44 ACH in Brisbane, assuming a residential $NO_2$ deposition constant of 1.05 $hr^{-1}$, and 1.36 ACH in Seoul, with the measured residential $NO_2$ deposition constant of 0.94 $hr^{-1}$. Source strengths of $NO_2$ were 15.8 $\pm$ 18.2 ${\mu}g$/$m^3$.hr and 44.7 $\pm$ 38.1${\mu}g$/$m^3$.hr in Brisbane and Seoul, respectively. In conclusion, indoor environmental factors were effectively characterized by this method using multiple indoor and outdoor measurements.

• Proceedings of the Korean Environmental Health Society Conference
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• 2004.12a
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• pp.45-50
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• 2004

Indoor air quality can be affected by indoor sources, ventilation, decay and outdoor levels. Alt hough technologies exist to measure these factors, direct measurements are often difficult. The purpose of this study was to develop an alternative method to characterize indoor environmental factors by multiple indoor and outdoor measurements. Daily indoor and outdoor NO2 concentrations were measured for 30 consecutive days in 28 houses in Brisbane, Australia, and for 21 consecutive days in 37 houses in Seoul, Korea. Using a mass balance model and regression analysis, penetration factor (ventilation rate divided by the sum of ventilation rate and deposition constant) and source strength factor (source strength divided by the sum of ventilation rate and deposition constant) were calculated using multiple indoor and outdoor measurements. Subsequently, the ventilation rate and NO2 source strength were estimated. Geometric means of ventilation rate were 1.44 ACH in Brisbane, assuming a residential NO2 deposition constant of 1.05 hr-1, and 1.36 ACH in Seoul, with the measured residential NO2 deposition constant of 0.94 hr-1. Source strengths of N02 were 15.8 ${\pm}$ 18.2 ${\mu}$g/m3${\cdot}$hr and 44.7 ${\pm}$ 38.1 ${\mu}$g/m3${\cdot}$hr in Brisbane and Seoul, respectively. In conclusion, indoor environmental factors were effectively characterized by this method using multiple indoor and outdoor measurements.

• Journal of Environmental Science International
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• v.13 no.7
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• pp.645-653
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• 2004

Indoor air quality is affected by source strength of pollutants, ventilation rate, decay rate, outdoor level, and so on. Although technologies measuring these factors exist directly, direct measurements of all factors are not always practical in most field studies. The purpose of this study was to develop an alternative method to estimate these factors by application of multiple measurements. For the total duration of 30 days, daily indoor and outdoor $NO_2$ concentrations were measured in 30 houses in Brisbane, Australia, and for 21 days in 40 houses in Seoul, Korea, respectively. Using a box model by mass balance and linear regression analysis, penetration factor (ventilation divided by sum of air exchange rate and deposition constant) and source strength factor (emission rate divided by sum of air exchange rate and deposition constant) were calculated, Sub-sequently, the ventilation and source strength were estimated. In Brisbane, the penetration factors were $0.59\pm0.14$ and they were unaffected by the presence of a gas range. During sampling period, geometric mean of natural ventilation was estimated to be $l.l0\pm1.5l$ ACH, assuming a residential $NO_2$ decay rate of 0.8 hr^{-1}$ in Brisbane. In Seoul, natural ventilation was $1.15\pm1.73$ ACH with residential $NO_2$ decay rate of 0.94 hr^{-1}$ Source strength of $NO_2$ in the houses with gas range $(12.7\pm9.8$ ppb/hr) were significantly higher than those in houses with an electric range $(2.8\pm2,6$ ppb/hr) in Brisbane. In Seoul, source strength in the houses with gas range were $l6.8\pm8.2$ ppb/hr. Conclusively, indoor air quality using box model by mass balance was effectively characterized.

• Journal of Korean Society of Occupational and Environmental Hygiene
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• v.10 no.1
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• pp.160-169
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• 2000

Daily indoor and outdoor nitrogen dioxide ($NO_2$) concentration for 30 days were measured in 28 houses with questionnaire of housing characteristics in Brisbane, Australia. Using mass balance equation and regression analysis, penetration factors and source strength factors were calculated. The penetration factors of 27 houses except one house were between zero and 1, though penetration factor should be between zero and 1 by means of mass balance equation. Relationship between indoor and outdoor concentrations in each 27 house was calculated using regression analysis. According to the obtained linear regression equation, the slope means penetration factor and the intercept means source strength factor. Calculated mean and standard deviation of coefficients of determination ($R^2$) in electric and gas range houses were $0.70{\pm}0.13$ and $0.57{\pm}0.21$, respectively. The source strength factors were more than zero in 27 houses. Mean and standard deviation of slopes in electric and gas range houses were $0.65{\pm}0.18$ and $0.56{\pm}0.12$, respectively. Mean and standard deviation of intercepts in electric and gas range houses were $1.49{\pm}1.25$ and $5.77{\pm}3.55$, respectively. Air exchange rate and source strength were calculated from penetration factor and source strength factor, respectively. Geometric mean and standard deviation of calculated air exchange rates in 27 houses were $1.1/hr{\pm}1.5$. Presence of gas range was the most significant factor contributing to indoor $NO_2$ level in house characteristics (p=0.003). In gas range houses, source strengths ranged from 4.1 to $33.1cm^3/hr{\cdot}m^3$ with a mean $12.7cm^3/hr{\cdot}m^3$ and a standard deviation 9.8. The source strengths of gas range houses were significantly different from those of electric range houses by t-test (p<0.001)

• Proceedings of the Korean Sanitation Conference
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• 2000.11a
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• pp.65-84
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• 2000