• Journal of the Korean Society of Combustion
• /
• v.15 no.4
• /
• pp.1-8
• /
• 2010

Mild combustion is considered as a promising combustion technology for energy saving and low emission of combustion product gases. In this paper, the controllability of reaction region in mild combustion is examined by using co-axial air nozzle. For this purpose, numerical approach is carried out. Propane is considered for fuel and air is considered for oxidizer and the temperature of air is assumed 900K slightly higher than auto ignition temperature of propane. But unlike main air, the atmospheric condition of co-axial air is considered. Various cases are conducted to verify the characteristics of Co-Axial air burner configuration. The use of coaxial air can affect reaction region. These modification help the mixing between fuel and oxidizer. Then, reaction region is reduced compare to normal burner configuration. The enhancement of main air momentum also affects on temperature uniformity and reaction region. The eddy dissipation concept turbulence/chemistry interaction model is used with two step of global chemical reaction model.

• Journal of Korean Society for Atmospheric Environment
• /
• v.19 no.E2
• /
• pp.75-81
• /
• 2003

Variational data assimilation, which is recently introduced to the air quality modeling, is a promising tool for obtaining optimal estimates of initial conditions and other important parameters such as emission and deposition rates. In this paper. two advanced techniques for variational data assimilation, based on the adjoint and quasi-inverse methods, are tested for a simple air quality problem. The four-dimensional variational assimilation (4D-Var) requires to run an adjoint model to provide the gradient information in an iterative minimization process, whereas the inverse 3D-Var (I3D-Var) seeks for optimal initial conditions directly by running a quasi -inverse model. For a process with small dissipation, I3D-Vu outperforms 4D-Var in both computing time and accuracy. Hybrid application which combines I3D-Var and standard 4D-Var is also suggested for efficient data assimilation in air quality problems.

• Environmental Sciences Bulletin of The Korean Environmental Sciences Society
• /
• v.4 no.1
• /
• pp.11-23
• /
• 2000

Photochemical air quality models are essential tools in predicting future air quality and assessing air pollution control strategies. To evaluate air quality using a photochemical air quality model, emission inventories are important inputs to these models. Since most emission inventories are provided at a county-level, these emission inventories need to be geographically allocated to the computational grid cells of the model prior to running the model. The conventional method for the spatial allocation of these emissions uses "spatial surrogate indicators", such as population for mobile source emissions and county area for biogenic source emissions. In order to examine the applicability of such approximations, more detailed spatial surrogate indicators were developed using Geographic Information System(GIS) tools to improve the spatial allocation of mobile and boigenic source emissions, The proposed spatial surrogate indicators appear to be more appropriate than conventional spatial surrogate indicators in allocating mobile and biogenic source emissions. However, they did not provide a substantial improvement in predicting ground-level ozone(O3) concentrations. As for the carbon monoxide(CO) concentration predictions, certain differences between the conventional and new spatial allocation methods were found, yet a detailed model performance evaluation was prevented due to a lack of sufficient observed data. The use of the developed spatial surrogate indicators led to higher O3 and CO concentration estimates in the biogenic source emission allocation than in the mobile source emission allocation.llocation.

• Journal of the Korea Convergence Society
• /
• v.10 no.9
• /
• pp.161-166
• /
• 2019

This study examines the flows near the different side mirrors by analyzing the flow due to air resistance at A, B and C models of automotive side mirrors. Model A is a square-shaped side-mirror. Model B is a triangular side-mirror and model C is an oval-shaped side-mirror. The air resistance of the side-mirror while driving is reduced and the automotive power can be reduced by changing the design of automotive side-mirror. As analysis result, as the pressure of air resistance against side mirror becomes larger, it can be seen that the air flow rate becomes great. Therefore, it can be estimated that the smaller the pressure of air resistance, the smaller the flow rate and the better the air flow. Therefore, it can be acknowledged that model B is the best model. As the design data of the automotive side mirror obtained on the basis of this study result are utilized, the esthetic sense can be shown while driving a car at real life.

• Journal of Korea Multimedia Society
• /
• v.16 no.12
• /
• pp.1465-1474
• /
• 2013

In this paper, air pollutant tracing models using perceptron neural network(PNN) and non-negative least square(NNLS) are proposed. When the measured values of the air pollution and the contribution concentration of each source by chemical transport modeling are given, they estimate and trace the amount of the air pollutants emission from each source. Two kinds of emissions data are used in the experiments : CH4 and N2O of Geumgo-dong landfill greenhouse gas, and PM10 of 17 areas in Northeast Asia and eight regions of the Korean Peninsula. Emission values were calculated using pseudo inverse method, PNN and NNLS. Pseudo inverse method could be used for the model, but it may have negative emission values. In order to deal with the problem, we used the PNN and NNLS methods. As a result, the estimation using the NNLS is closer to the measured values than that using PNN. The proposed tracing models have better utilization and generalization than those of conventional pseudo inverse model. It could be used more efficiently for air quality management and air pollution reduction.

• ETRI Journal
• /
• v.46 no.5
• /
• pp.915-927
• /
• 2024

We obtain the air quality index (AQI) for a descriptive system aimed to communicate pollution risks to the population. The AQI is calculated based on major air pollutants including O₃, CO, SO₂, NO, NO₂, benzene, and particulate matter PM2.5 that should be continuously balanced in clean air. Air pollution is a major limitation for urbanization and population growth in developing countries. Hence, automated AQI prediction by a deep learning method applied to time series may be advantageous. We use a seasonal autoregressive integrated moving average (SARIMA) model for predicting values reflecting past trends considered as seasonal patterns. In addition, a transductive long short-term memory (TLSTM) model learns dependencies through recurring memory blocks, thus learning long-term dependencies for AQI prediction. Further, the TLSTM increases the accuracy close to test points, which constitute a validation group. AQI prediction results confirm that the proposed SARIMA-TLSTM model achieves a higher accuracy (93%) than an existing convolutional neural network (87.98%), least absolute shrinkage and selection operator model (78%), and generative adversarial network (89.4%).

• Journal of Advanced Navigation Technology
• /
• v.21 no.3
• /
• pp.264-271
• /
• 2017

This paper presents air traffic control simulation model for generating 4D trajectory, and aircraft dynamic model based on 4D trajectory information. With aircraft parameters from BADA and Total Energy Model, the trajectory is defined through modified Bezier curve and the simulation supports two aircraft control methods based on controlled time of arrival (CTA) or airspeed. The simulation results shown that flight time and path were almost identical to the defined trajectory, and derived the differences of each control methods according to wind conditions. Based on the simulation model developed in this study, it is expected to be applied to various air traffic management researches. Future studies will focus on applying optimization techniques in order to minimize the difference between generated trajectories and actual flight routes. This work will increase utilization of developed simulation futhermore.

• Journal of the Korean Society of Industry Convergence
• /
• v.12 no.1
• /
• pp.11-18
• /
• 2009

The air flow and heat transfer characteristics of an air jet impinging on a pedestal heat source has been investigated numerically to examine the effects of geometric parameters such as nozzle-to-pedestal spacing, nozzle diameter and pedestal size. Also, the parameters of Reynolds number, air jet power, supplied heat and thermal conductivity of pedestal have been studied to reveal how these affect the average Nusselt number. Hence, a two-dimensional turbulent model has been developed and adopted to simulate the fluid flow and heat transfer phenomena numerically. The results obtained from the model show that the nozzle-to-pedestal spacing, relative size of nozzle to pedestal and Reynolds number of air jet have a significant influence on the cooling characteristics of heated pedestal. Furthermore, some useful guidelines could be given to the application of cooling the heated pedestal.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
• /
• v.11 no.5
• /
• pp.642-646
• /
• 1999

Factors governing the rate of heat exchange comprise the air temperature, the speed of air movement, relative humidity, and relation indoors. Recently, there are many researches on the transient analysis of indoor environmental factors such as the dry bulb temperature, relative humidity and air velocity in miniature models. The purpose of this study is to measure the environmental factors and to analyze and evaluate the characteristics of indoor environment with the different envelope structures using a granite dome model. According to the variation of humidity, the state of interior relative humidity for clay model has an equal tendency, although a little range of variation is shown in comparison to the cement model.

• Journal of Korean Society for Atmospheric Environment
• /
• v.17 no.E2
• /
• pp.43-51
• /
• 2001

A report by the national research council in the United States suggested that many lung cancer deaths each year be associated with breathing radon in indoor air. Most of the indoor radon comes directly from soil beneath the basement of foundations. Recently, radon released from groundwater is found to contribute to the total inhalation risk from indoor air. This study presents the quantitative assessment of human exposures to radon released from the groundwater into indoor air. At first, a three-compartment model is developed to describe the transfer and distribution of radon released from groundwater in a house through showering, washing clothes, and flushing toilets. Then, to estimate a daily human exposure through inhalation of such radon for an adult. a physiologically-based pharmacokinetic(PBPK) model is developed. The use of a PBPK model for the inhaled radon could provide useful information regarding the distribution of radon among the organs of the human body. Indoor exposure patterns as input to the PBPK model are a more realistic situation associated with indoor radon pollution generated from a three-compartment model describing volatilization of radon from domestic water into household air. Combining the two models for inhaled radon in indoor air can be used to estimate a quantitative human exposure through the inhalation of indoor radon for adults based on two sets of exposure scenarios. The results obtained from the present study would help increase the quantitative understanding of risk assessment issues associated with the indoor radon released from groundwater.