In this study used Computational Fluid Dynamic analysis to examine NOx reduction in hydrogen combustion, analyzing six conditions with varying air/fuel ratios, temperatures, and concentrations. Results were compared between two combustor shapes and previous experimental data. Findings showed increased air/fuel ratios decreased flame temperature and increased post-combustion O2. NOx emissions peaked at high temperatures and low O2. Numerical results aligned with previous experimental trends, validating the approach. Combustor shape differences, reflecting variations in fuel and air pipes, significantly affected flow rates and combustion positions. This reduced NOx emissions up to a certain air/fuel ratio, but excessive increases diminished this effect. The study highlights the complex relationship between combustor design, operating conditions, and NOx emissions. Further research is needed to optimize NOx reduction by considering pipe numbers and combustion locations. Future studies should explore various combustor geometries, fine-tune air/fuel ratios, and investigate additional parameters influencing NOx formation and reduction in hydrogen combustion systems.

Microclimate analysis was conducted through actual measurement according to land use status in urban, and CFD analysis was conducted to analyze and predict the microclimate characteristics of urban, and compared and analyzed with the actual measurement results. It was measured in high-rise areas and parks, and the temperature of the park area was 0.4 to 0.6℃ lower, and the relative humidity was 1.0 to 3.0% higher. The correlation coefficient was obtained by comparing the results of the computational fluid analysis with the results of the computational fluid analysis at the actual location located within the CFD analysis area for validation. The seasonal correlation coefficients are all higher than 0.8, so it is judged that they can be applied to microclimate analysis in urban area. The computational fluid analysis was divided into three areas (low-rise, low and high-rise, and high-rise) centered on the A2 point. On average, the low-rise area was 0.1 to 0.4% higher than the high-rise area. In the low and high-rise area and high-rise area, the pith of buildings are wide, so the airflow is smooth, so it is judged that the temperature is relatively low.

Micro-climate measurements and computational fluid analysis were conducted to use it as basic data for the preservation and management of the old house of Kim Myung-kwan, a traditional building that is National Folk Cultural Property No. 26. As a result of the actual measurement, the temperature and humidity are relatively evenly distributed indoors unlike outdoors, but the temperature and humidity vary depending on the time change and the installation location in the outdoors. It was found that the temperature increases after dawn and the temperature varies depending on the installation position around 14:00–15:00, when the temperature becomes the highest. In particular, the temperature was high at the outdoor measurement point adjacent to the building and the fence. As a result of the computational fluid analysis, the temperature was high in the buildings and fences in the old house or in the area adjacent to the building, and it was about 1℃ higher than the surrounding area. In this area, it is judged that the thickening of wood will occur more severely than in other locations, and special preservation management is required.

전산유동 수치모형을 이용하여 다양한 대기안정도 상태하에서 부산광역시내 승학산과 구덕산의 초고해상도 풍력자원을 평가하였다. 연구에 사용된 수치모형은 중규모와 미규모 기상현상의 재현에 널리 사용되는 전산유동 수치모형인 A2C이다. 대기안정도가 강할 때, 위치에너지의 크기가 상대적으로 강해지기 때문에 산을 넘어가는 경향이 나타난다. 반면 대기안정도가 약해지면서 산악후면의 후류 발생이 증대되며, 난류에너지가 증가한다. 그리고 연평균 풍력밀도, 난류운동에너지, 연직 바람전단력 분석을 통하여 구덕산 정상의 남쪽 부근이 다른 구역보다 가용 풍력자원이 풍부함을 확인하였다.

This study forecasts changes in thermal environment and microclimate change per new building construction and assignment of green space in urban area using Computational Fluid Dynamics(CFD) simulation. The analysis studies temperature, humidity and wind speed changes in 4 different given conditions that each reflects; 1) new building construction; 2) no new building construction; 3) green spaces; and 4) no green spaces. Daily average wind speed change is studied to be; Case 2(2.3 m/s) ＞ Case 3. The result of daily average temperate change are; Case 3(26.5℃) ＞ Case 4(24. 6℃) ＞ Case 2(23.9℃). This result depicts average of 2.5℃ temperature rise post new building construction, and decrease of approximately 1.8℃ when green space is provided. Daily average absolute humidity change is analysed to be; Case 3(15.8 g/kg') ＞ Case 4(14.1 g/kg') ＞ Case 2(13.5 g/kg'). This also reveals that when no green spaces is provided, 2.3 g/kg' of humidity change occurs, and when green space is provided, 0.6 g/kg change occurnd 4(1.8 m/s), which leads to a conclusion that daily average wind velocity is reduced by 0.5 m/s per new building construction in a building complex.