• Asian Journal of Atmospheric Environment
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• v.2 no.1
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• pp.1-13
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• 2008

A numerical simulation method has been developed to predict atmospheric flow and stack gas diffusion using a calculation domain of several km around a stack under complex terrain conditions containing buildings. The turbulence closure technique using a modified k-$\varepsilon$-type model under a non hydrostatic assumption was used for the flow calculation, and some of the calculation grids near the ground were treated as buildings using a terrain-following coordinate system. Stack gas diffusion was predicted using the Lagrangian particle model, that is, the stack gas was represented by the trajectories of released particles. The numerical model was applied separately to the flow and stack gas diffusion around a cubical building and to a two-dimensional ridge in this study, before being applied to an actual terrain containing buildings in our next study. The calculated flow and stack gas diffusion results were compared with those obtained by wind tunnel experiments, and the features of flow and stack gas diffusion, such as the increase in turbulent kinetic energy and the plume spreads of the stack gas behind the building and ridge, were reproduced by both calculations and wind tunnel experiments. Furthermore, the calculated profiles of the mean velocity, turbulent kinetic energy and concentration of the stack gas around the cubical building and the ridge showed good agreement with those of wind tunnel experiments.

• Journal of Korean Society for Atmospheric Environment
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• v.13 no.1
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• pp.65-77
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• 1997

A theoretical and numerical investigation on the boundary-layer flow over a two- or three-dimensional hill is presented. The numerical model is based on the finite volume method with boundary-fitted coordinates. The k-$\varepsilon$ turbulence model with modified wall function and the low-Reynolds-number model are employed. The hypothesis of Reynolds number independency for the atmospheric boundary-layer flow over aerodynamically rough terrain is confirmed by the numerical simulation. Comparisons of the mean velocity profiles and surface pressure distributions between the numerical predictions and the wind-tunnel experiments on the flow over a hill show good agreement. The linear theory provides generally good prediction of speed-up characteristics for the gentle-sloped hills. The flow separation occurs in the hill slope of 0.5 and the measured reattachment points are compared with the numerical prediction. It is found that the k- $\varepsilon$ turbulence model is reasonably accurate in predicting the attached flow, while the low- Reynolds-number model is more suitable to simulate the separated flows.ows.

• Journal of Korean Society for Atmospheric Environment
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• v.14 no.6
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• pp.643-650
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• 1998

Many atmospheric dispersion models have been based on the Gaussian distribution concept of plume spread. In application of Gaussian plume dispersion models, vertical dispersion coefficient 3 has been known as a sensitive variable. Vertical diffusivity K2 (=Oz2/2t) tends to increase with surface roughness, and the value of K3 in urban area is larger than that in rural area due to heat emission as well as increased roughness. Though Pasquill proposed a modification scheme for qz vs x system of Pasquill-Gifford under consideration of roughness effect in 1976, there appears not to be realistic reexamination on the modification scheme. In this study literature review on the effect of terrain or roughness on venical plume dispersion has been carried out in order to improve the prediction results of atmospheric pollution concentration. Again a few research objectives on vertical atmospheric dispersion in complex terrain were Proposed.

• Journal of Korean Society for Atmospheric Environment
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• v.7 no.2
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• pp.105-113
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• 1991

An investigation is carried out for the role of topography in governign the mesoscale distribution of $SO_2$ concentration in Seoul. The three dimensional wind fields computed for a given synoptic meteorological condition by an atmospheric mesoscale model in the terrain following coordinate have been employed to compute the three dimensional mesoscale distributions of $SO_2$ concentration by the diffusion model in Seoul area. Terrain may affect the mesoscale distributions of $SO_2$ concentration through its influence on the mesoscale wind fields. This study discusses only the terrain effect on the concentration through its modification of the wind. This effect is to produce higher concentration in lower area according to the structure of divergence fields derived from and atmospheric mesoscale model.

• Journal of Korean Society for Atmospheric Environment
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• v.15 no.5
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• pp.625-638
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• 1999

Air quality modeling for coastal urban region has been composed of a complex system including meteorological, chemical and physical processes and emission characteristics in complex terrain. In this study, we studied about an effect prediction for deposition phenomenon affecting on air quality in Pusan metopolitan metropolitan city. In air quality modeling including ship sources, a situation considered deposition process habe better result than not considered when compared with observed value. Air pollutants emitted into urban air during the daytime nearly removed through urban atmosphere polluted. Also these phenomena correlated concentration variation connent with sea/land breezes and terrain effect. Therefore we conclude that the concentration was low at daytime when deposition flux is high, and deposition effect on industrial complex and Dongrae region is considerable in particular.

• Korean Journal of Environment and Ecology
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• v.9 no.1
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• pp.70-76
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• 1995

Digital elevation model for analysing terrain of Odaesan National Park was constructed by 1：50.000 topographical map. The fifty five percent of total area is located in higher than 900m in elevation, while ninty percent of the conservation area in Pirobong is above 1,100m. In other word, seventy percent of Odaesan National Park area has the slope of more than 20$^{\circ}$and is steep mountain. The aspect of the mountain mainly turned out to be eastward and westward.

• Journal of Korean Society for Atmospheric Environment
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• v.16 no.2
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• pp.151-158
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• 2000

Since Pusan metropolitanarea where is composed complex terrain is connected to sea the sea-land breeze circulation and the mountain-valley circulation are apt to form A regional scale circulation system is formed at a region which has complex terrain because of curves of its and affect to the dispersion and advection of air pollutants. LCM Local Circulation Model which a propriety was verified described that sea breeze and valley wind at the daytime and land breeze and mountain wind at the nighttime were well devellped over the Pusan metropolital area. Next for the investigation of accuracy of simulated results an observed value at Kae-Kum and Su-Young on the pusan metropolitan area were compared with it at those points. From the comparison of the temperature and horizontal velocity between the results of LCM and an observed values they have a similar trend of a diurnal variation. For the prediction of dispersion and transportation of air pollutants the wind field should be calculated with high accuracy. A numerical simulation using LCM can provide more accuracy results around Pusan metropolitan area.

• Journal of the Korea Institute of Military Science and Technology
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• v.13 no.5
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• pp.894-902
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• 2010

This paper presents a vision-based robust off-road terrain classification method against environmental variation. As a supervised classification algorithm, we applied a neural network classifier using wavelet features extracted from wavelet transform of an image. In order to get over an effect of overall image feature variation, we adopted environment sensors and gathered the training parameters database according to environmental conditions. The robust terrain classification algorithm against environmental variation was implemented by choosing an optimal parameter using environmental information. The proposed algorithm was embedded on a processor board under the VxWorks real-time operating system. The processor board is containing four 1GHz 7448 PowerPC CPUs. In order to implement an optimal software architecture on which a distributed parallel processing is possible, we measured and analyzed the data delivery time between the CPUs. And the performance of the present algorithm was verified, comparing classification results using the real off-road images acquired under various environmental conditions in conformity with applied classifiers and features. Experiments show the robustness of the classification results on any environmental condition.

• Journal of Institute of Control, Robotics and Systems
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• v.19 no.8
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• pp.702-708
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• 2013

Underwater TRN (Underwater Terrain Referenced Navigation) estimates an underwater vehicle state by measuring a distance between the vehicle and undersea terrain, and comparing it with the known terrain database. TRN belongs to absolute navigation methods, which are used to compensate a drift error of dead reckoning measurements such as IMU (Inertial Measurement Unit) or DVL (Doppler Velocity Log). However, underwater TRN is different to other absolute methods such as USBL (Ultra-Short Baseline) and LBL (Long Baseline), because TRN is independent of the external environment. As a magnetic-field-based navigation, TRN is a kind of geophysical navigation. This paper develops an EKF (Extended Kalman Filter) formulation for underwater TRN. A filter propagation part is composed by an inertial navigation system, and a filter update is executed with echo-sounder measurement. For large-initial-error cases, an adaptive EKF approach is also presented, to keep the filter be stable. At the end, simulation studies are given to verify the performance of the proposed TRN filter. With simplified sensor and terrain database models, the simulation results show that the underwater TRN could support conventional underwater navigation methods.

• Journal of the Korean Society for Precision Engineering
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• v.28 no.1
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• pp.56-62
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• 2011

Terrain recognition ability is crucial to the performance of legged robots in an outdoor environment. For instance, a robot will not easily walk and it will tumble or deviate from its path if there is no information on whether the walking surface is flat, rugged, tough, and slippery. In this study, the ground surface recognition ability of robots is discussed, and to enable walking robots to recognize the surface state and changes, a central moment method was used. The values of the sensor signals (load cell) of robots while walking were detected in the supported section and were analyzed according to signal variance, skewness, and kurtosis. Based on the results of such analysis, the surface state was detected and classified.