1. Baek, S, Kim, J, and Kang, J (2024) Impact of Green Infrastructure on PM10 in Port-Adjacent Residential Complexes:A Finite Volume Method-Based Computational Fluid Dynamics Study.
Sustainable Cities and Society, Vol. 00, pp. 105815.
2. Biljecki, F, Ledoux, H, Stoter, J, and Zhao, J (2014) Formalisation of the level of detail in 3D city modelling. Computers, Environment and Urban Systems, Vol. 48, pp. 1-15.
3. Cho, S.H, and Shin, K.S (1995) The effect on the heating and cooling load of building by slat angle variation of venetian blind. Korean Journal of Air-Conditioning and Refrigeration Engineering, Vol. 7, No. 2, pp. 171-183.
4. Cudzik, J, Aydoğan, M, and Güler, B (2023) Level of detail categorization for the application in urban design. Space &Form, Vol. 55, pp. 9-28.
5. Fink, T, and Koenig, R (2019) Integrated Parametric Urban Design in Grasshopper/Rhinoceros 3D. Demonstrated on a Master Plan in Vienna.
6. Franke, J, Hirsch, C, Jensen, A.G, Krüs, H.W, Schatzmann, M, Westbury, P.S, et al (2004). Recommendations on the use of CFD in predicting pedestrian wind environment.
In Cost action C. Vol. 14: pp. C.1.1-C1.11
https://research.tue.nl/en/publications/recommendations-on-the-use-of-cfd-in-wind-engineering.
7. Gwacheon City Government (2020). Gwacheon City's 2nd detailed implementation plan for climate change adaptation policy. (2020-2024). Gwacheon: Gwacheon City Government.
8. Henriksen, H. J, Schneider, R, Koch, J, Ondracek, M, Troldborg, L, Seidenfaden, I. K, et al (2022) A new digital twin for climate change adaptation, water management, and disaster risk reduction (HIP digital twin).
Water, Vol. 15, No. 1, pp. 25.
9. Kim, G, and Lee, G (2024) Validation of CFD Models of Urban Microclimates Under High Temperature and Humidity Conditions During Daytime Heatwaves in Dense Low-rise Areas.
Building and Environment, Vol. 266, pp. 112087.
10. Kim, J, and Kang, J (2022) Evaluating the efficiency of fog cooling for climate change adaptation in vulnerable groups:A case study of Daegu Metropolitan City.
Building and Environment, Vol. 217, pp. 109120.
11. Kim, J, and Kang, J (2023a) Development of hazard capacity factor design model for net-zero:Evaluation of the flood adaptation effects considering green-gray infrastructure interaction.
Sustainable Cities and Society, Vol. 96, pp. 104625.
12. Kim, J, and Kang, J (2023b) AI based temperature reduction effect model of fog cooling for human thermal comfort:Climate adaptation technology.
Sustainable Cities and Society, Vol. 95, pp. 104574.
13. Kim, J, Ahn, J, and Kang, J (2024) Adaptive wildfire spread prediction for complex terrain:modeling the effectiveness of sprinkler systems.
Fire Ecology, Vol. 20, No. 1, pp. 75.
14. Kim, J, Lee, J.M, and Kang, J (2023) Smart cities and disaster risk reduction in South Korea by 2022:The case of Daegu.
Heliyon, Vol. 9, No. 8, pp. e18794.
15. Korean Government (2010). Framework Act on Low Carbon, Green Growth. Seoul: Korean Government.
16. Lee, G.W (2021) The impacts of creation of small green areas within urban regeneration projects on the formation of wind paths and the thermal environment:focused on Indongchon, one of the urban regeneration and revitalization areas in Daegu.
KIEAE Journal, Vol. 21, No. 5, pp. 91-100.
17. Lee, J, Kim, J, and Yoon, J (2014) CFD Simulations of the Ground Surface Temperature and Air Temperature, Air flow Coupled with Solar Radiation.
KIEAE Journal, Vol. 14, No. 3, pp. 65-70.
18. Marion, M, and Temam, R (1998) Navier-Stokes equations:Theory and approximation.
Handbook of Numerical Analysis, Vol. 6, pp. 503-689.
19. Morón, C, Saiz, P, Ferrández, D, and Felices, R (2018) Comparative analysis of infrared thermography and CFD modelling for assessing the thermal performance of buildings.
Energies, Vol. 11, No. 3, pp. 638.
20. Park, S, Kim, J, and Kang, J (2024a) Exploring optimal deep tunnel sewer systems to enhance urban pluvial flood resilience in the gangnam region, South Korea.
Journal of Environmental Management, Vol. 357, pp. 120762.
21. Park, S, Kim, J, Kim, Y, and Kang, J (2024b) Participatory Framework for Urban Pluvial Flood Modeling in the Digital Twin Era.
Sustainable Cities and Society, Vol. 108, pp. 105496.
22. Qi, Y, Li, H, Pang, Z, Gao, W, and Liu, C (2022) A case study of the relationship between vegetation coverage and urban heat island in a coastal city by applying digital twins.
Frontiers in Plant Science, Vol. 13, pp. 861768.
23. Schaeffer, R, Szklo, A.S, de Lucena, A.F.P, Borba, B.S.M.C, Nogueira, L.P.P, Fleming, F.P, et al (2012) Energy sector vulnerability to climate change:A review.
Energy, Vol. 38, No. 1, pp. 1-12.
24. Shaharuddin, S, Abdul Maulud, K.N, Syed Abdul Rahman, S.A.F, and Che Ani, A.I (2022) Digital twin for indoor disaster in smart city:A systematic review.
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol. 46, pp. 315-322.
25. Swanson, M, and Hobbs, A (2014). Urban heat island effect:Comparing thermal and radiation effects of asphalt and concrete pavements on adjacent buildings using CFD methods. p 33-39. London: CRC Press.
26. Tominaga, Y, Mochida, A, Yoshie, R, Kataoka, H, Nozu, T, Yoshikawa, M, et al (2008) AIJ guidelines for practical applications of CFD to pedestrian wind environment around buildings.
Journal of wind engineering and industrial aerodynamics, Vol. 96, No. 10-11, pp. 1749-1761.
27. Wang, X, and Li, Y (2016) Predicting urban heat island circulation using CFD.
Building and Environment, Vol. 99, pp. 82-97.
28. Zou, Y, Zhao, X, and Chen, Q ((2018, February). Comparison of STAR-CCM+and ANSYS Fluent for simulating indoor airflows. In: Zeng J, ed.
Building simulation. Vol. 11: p 165-174. Berlin Heidelberg: Springer.