@article {681031, title = {Architectural Design Considerations for Healthy Sleep Environments in Low-Energy Buildings }, journal = {Building and Environment}, year = {Working Paper}, author = {Han, J. M. and Samuelson, H. W. and Other researchers} } @article {681030, title = {Computationally efficient CFD prediction using 3D convolutional neural networks for the building design}, journal = {Applied Energy}, year = {Working Paper}, author = {Han, J. M. and Malkawi, A.} } @article {681029, title = {Machine learning guided semi-empirical model for natural ventilation assessment.}, journal = {Renewable and Sustainable Energy Review}, year = {Working Paper}, author = {Han, J. M. and Wu, W. and Malkawi, A.} } @article {681028, title = {New metric for naturally ventilated building design and operation of windows at home in U.S. during COVID-19.}, journal = {Building and Environment}, year = {Submitted}, author = {Han, J. M. and S. Lim and Malkawi, A.} } @article {681020, title = {CoolVox: Advanced 3D convolutional neural network models for predicting solar radiation on building fa{\c c}ades}, journal = {Building Simulation }, year = {2021}, author = {Han, J. M.* and Choi, E. S. and Malkawi, A.} } @article {681021, title = {Using recurrent neural networks for localized weather prediction with combined use of public airport data and on-site measurements}, journal = {Building and Environment}, volume = {192}, number = {107601}, year = {2021}, abstract = {Weather data is a crucial input for myriad applications in the built environment, including building energymodeling and daylight analysis. Building science practitioners and researchers have been able to select from avariety of weather files, such as Weather Year for Energy Calculation 2 (WYEC2) and the Typical MeteorologicalYear (TMY). However, commonly used weather files are typically synthesized to represent trends over a relativelylonger periods of time, and are often unable to accurately depict climatic conditions that result from localcontexts, such as the heat island effect, wind flow, even local temperature and relative humidity. This results indiscrepancies in building performance simulations.This study proposes a methodology using recurrent neural networks to generate synthetic localized weatherdata that are significantly more accurate and representative of local conditions than standard weather files. Thepredictions were validated against actual on-site measurements, and achieved a low mean square error of 2.96and over 185\% improvement in validation accuracy. Overall, the performance of selected models has shown over100\% improvements in test accuracy compared with standard weather files and weather station data at thenearest airport. The proposed methodology can be used to morph generic weather files to accurately representlocalized conditions, or generate localized data for a longer time span with only a subset of data available/collected. This is useful for downstream built environment applications, especially building energy modeling,since representative weather data capturing trends of temperature and other variables will result in enhancedaccuracies of the building energy models. The method can also be used in urban analysis pipelines to enhanceresilience against climate change.}, author = {Han, J. M.* and Ang, Y.Q. and Malkawi, A. and Samuelson, H. W.} } @conference {681024, title = {ARINet: Using 3D convolutional neural networks to estimate annual radiation intensities on building facades.}, booktitle = {The 2020 Building Performance Analysis Conference and SimBuild co-organized by ASHRAE and IBPSA-USA}, year = {2020}, pages = {252-259}, author = {Han, J. M. and Chang, C. K. and Malkawi, A.} } @article {681022, title = {Simplified direct forcing approach for dynamic modeling of building natural ventilation.}, journal = {Building and Environment}, volume = {188}, number = {107509}, year = {2020}, abstract = {Natural ventilation is a promising approach to provide passive cooling in highly energy efficient buildings. Awidely applied method to evaluate the performance of natural ventilation is computational fluid dynamics (CFD).However, dynamic modeling of natural ventilation from 1 h to the next is very challenging because state-of-theartCFD simulations treat windows as fixed wall boundary surfaces. The objective of this study is to propose adirect forcing approach to implement dynamic window operations in CFD simulations. The direct forcingapproach marks a band of computational cells according to window positions, and adds an ad-hoc body force tothe momentum equations and turbulence production term to the kinetic energy equation. The direct forcingapproach shows a high level of performance when predicting volume flow rates through window apertures. Therelative deviation was found to vary between 2.2\% and 14\%, depending on the reference wind speeds. Directforcing also showed good performance when predicting the height of the neutral plane when the wind incidentangle was less than 135{\textopenbullet}. The direct forcing approach can be applied to study the dynamic daily or weekly CO2variations in naturally ventilated buildings with predefined control algorithms. Future work will consider theinfluence of wall shear stresses and zero normal velocity to improve the accuracy of the direct forcing approachas applied to wind incident angles larger than 135{\textopenbullet}.}, author = {Wu, W. and Han, J. M.* and Malkawi, A.} } @article {681023, title = {Optimization of window positions for wind-driven natural ventilation performance.}, journal = {Energies}, volume = {13}, number = {2464}, year = {2020}, author = {Yoon, N.*, Piette, M. A., Han, J. M., Wu, W., \& Malkawi, A.} } @conference {681027, title = {Finding the optimum window locations of a single zone: To maximize the wind-driven natural ventilation potential.}, booktitle = {The 16th International Building Performance Simulation Association Conference}, year = {2019}, pages = {578-584}, address = {Rome, Italy}, author = {Yoon, N. and Han, J. M. and Malkawi, A.} } @conference {681025, title = {Eabbit 1.0: New environmental analysis software for solar energy representation}, booktitle = {The 16th International Building Performance Simulation Association Conference}, year = {2019}, pages = {2599-2605}, address = {Rome, Italy}, author = {Han, J. M. and Malkawi, A. and Gajos, K. Z.} } @article {681026, title = {Seasonal optimization of a dynamic thermo-optical ETFE fa{\c c}ade system.}, journal = {The 16th International Building Performance Simulation Association Conference}, year = {2019}, pages = {4887-4893}, author = {Han, J. M. and Park, D.} } @conference {637323, title = {Development of the urban surface management software for PVs and stormwater with connectivity to urban modeling interface}, booktitle = {2018 Building Performance Analysis Conference and SimBuild Co-organized by ASHRAE and IBPSA-USA}, year = {2018}, address = {Chicago, IL}, url = {https://www.ashrae.org/File\%20Library/Conferences/Specialty\%20Conferences/2018\%20Building\%20Performance\%20Analysis\%20Conference\%20and\%20SimBuild/Papers/C014.pdf}, author = {Jung Min Han and Reinhart, Christoph} } @article {637322, title = {Holistic visual data representation for built environment assessment}, journal = {Sustainable development and planning}, volume = {13}, number = {4}, year = {2018}, pages = {516-527}, url = {https://www.witpress.com/Secure/ejournals/papers/SDP130403f.pdf}, author = {Jung Min Han and Namju Lee} } @mastersthesis {637321, title = {Green Design Decision-Making Toolbox (GDDT) Vol 1. Photovoltaics and Green roofs}, year = {2016}, type = {Masters Thesis}, author = {Jung Min Han} } @proceedings {637320, title = {Comparison of the results obtained with simplified IEQ toolkit and robust instrument in POE field studies}, journal = {Engineering Sustainability 2015}, year = {2015}, author = {Park, Jihyun and Yue Lei and Ye Song and Jung Min Han and June Young Park and Jie Zhao and Azizan Aziz and Vivian Loftness and Ruben Moron Rojas} }