Publication

Journal Articles

1.       Han, J. M., & Malkawi, A. (2024). Airvox: efficient computational fluid dynamics prediction using 3D convolutional neural networks for building design. Journal of Building Performance Simulation, 1-16.

2. Han, J.M., Malkawi, A., Han, X. et al (2024). A two-year dataset of energy, environment, and system operations for an ultra-low energy office building. Sci Data 11, 938 .

3.       Han, J. M., Lim, S., Malkawi, A., Han, X., Chen, E. X., Salimi, S., ... & Edwards, K. (2023). Data-informed building energy management (DiBEM) towards ultra-low energy buildings. Energy and Buildings, 281, 112761.

4.       Han, J. M., Choi, E. S., & Malkawi, A. (2022, May). CoolVox: Advanced 3D convolutional neural network models for predicting solar radiation on building facades. In Building Simulation (Vol. 15, No. 5, pp. 755-768). Beijing: Tsinghua University Press.

5.       Han, J. M.*, Ang, Y. Q., Malkawi, A., & Samuelson, H. W. (2021). Using recurrent neural networks for localized weather prediction with combined use of public airport data and on-site measurements. Building and Environment, 192, 107601.

6.       Wu, W., Han, J. M.*, & Malkawi, A. (2021). Simplified direct forcing approach for dynamic modeling of building natural ventilation. Building and Environment, 188, 107509.

7.       Yoon, N.*, Piette, M. A., Han, J. M., Wu, W., & Malkawi, A. (2020). Optimization of window positions for wind-driven natural ventilation performance. Energies, 13(10), 2464.

https://doi.org/10.3390/en13102464

8.       Han, J. M., & Lee, N. (2018). Holistic visual data representation for built environment assessment. International Journal of Sustainable Development and Planning, 13(4), 516-527.

Report & Books

1.       “HouseZero Annual Load Report” Lead editor for internal research report for Harvard Center for Buildings and Cities (2018). Authored by: Han, J. M and CGBC researchers.

2.       “Tall, hot, and zero,” Lead editor for funded 170-page research report for Harvard Center for Buildings and Cities (2018). Authored by: 15 CGBC researchers including Han, J. M.

Conference Papers

1.       Han, J. M., Choi, J., & Choi, Y. Y. (2023). New methods of designing high-rise residential towers with the ventilation effectiveness study: traditional Korean muntins, "Sal". In Proceedings of Building Simulation 2023: 18th Conference of IBPSA, 1931 - 1939.

2.       Han, J. M., Chang, C. K., & Malkawi, A. (2020). ARINet: Using 3D convolutional neural networks to estimate annual radiation intensities on building facades. In Proceedings of the 2020 Building Performance Analysis Conference and SimBuild co-organized by ASHRAE and IBPSA-USA, 252-259.

3.       Han, J. M., Malkawi, A., & Gajos, K. Z. (2019). Eabbit 1.0: New environmental analysis software for solar energy representation. In Proceedings of the 16th International Building Performance Simulation Association Conference, Rome, Italy: IBPSA, 2599-2605.

4.       Han, J. M., & Park, D. (2019). Seasonal optimization of a dynamic thermo-optical ETFE façade system. In Proceedings of the 16th International Building Performance Simulation Association Conference, Rome, Italy: IBPSA, 4887-4893.

5.       Yoon, N., Han, J. M., & Malkawi, A. (2019). Finding the optimum window locations of a single zone: To maximize the wind-driven natural ventilation potential. In Proceedings of the 16th International Building Performance Simulation Association Conference, Rome, Italy: IBPSA, 578-584.

6.       Han, J. M., & Reinhart, C. (2018). Development of the urban surface management software for PVs and stormwater with connectivity to urban modeling interface. In Proceedings of 2018 Building Performance Analysis Conference and SimBuild Co-organized by ASHRAE and IBPSA-USA. Chicago, IL. 92-99.

7.       Park, J., Lei, Y., Song, Y., Rojas, R. M., Han, J. M., Park, J. Y., ... & Loftness, V. (2015). Comparison of the results obtained with simplified IEQ toolkit and robust instrument in POE field studies. In Proceedings of Engineering Sustainability.