@article{wang_li_liu_hu_wang_2024, title={Parametric Modeling and Column Grid Analysis of the Sakyamuni Pagoda at Fogong Temple: Insights into the Yingxian Wooden Pagoda}, volume={14}, ISSN={["2075-5309"]}, DOI={10.3390/buildings14082464}, abstractNote={The Sakyamuni Pagoda of Fogong Temple, also known as the Yingxian Wooden Pagoda or the Wooden Pagoda of Ying County, is China’s oldest and tallest wooden pagoda. This pagoda was constructed in 1056 and has faced many challenges, including earthquakes, wars, and mistreatment. However, it is currently in danger of potential collapse due to severe structural challenges. Preserving this historic monument requires interdisciplinary collaboration across architectural history, materials science, and engineering. This paper proposes the development of a parametric model to build the pagoda that can be used for future preservation efforts. While not precisely reflecting the pagoda’s current condition, with the changes in inputs, the geometries of the structural members can be updated in real time, which offers adaptability crucial for preservation efforts. With the understanding of the original construction techniques, including its leaning column systems, the model not only helps preservation but also reveals the creativity of the architects or the craftsmen at the time. The 3D model, which includes more than 32,000 pieces along with the parametric files that can generate the column grid and dougongs, has been published along with this paper, and those files are available in the Data Availability Statement. In summary, the full digital model presented alongside this paper, unavailable elsewhere to the general public, serves as a practical preservation tool that can also be used for raising awareness for this cultural heritage site.}, number={8}, journal={BUILDINGS}, author={Wang, Daoru and Li, Stephanie Yanqiu and Liu, Ruguan and Hu, Jianxin and Wang, Ang}, year={2024}, month={Aug} }
 @article{vivek nanda_baran_tateosian_nelson_hu_2023, title={Classification of tree forms in aerial LiDAR point clouds using CNN for 3D tree modelling}, volume={44}, ISSN={0143-1161 1366-5901}, url={http://dx.doi.org/10.1080/01431161.2023.2282405}, DOI={10.1080/01431161.2023.2282405}, abstractNote={ABSTRACT Three-dimensional models of trees that correspond to the real-world forms of the trees on the ground are used in urban planning, solar power estimation, and other disciplines. Previous studies have focused on generating 3D tree models from high-density point cloud data such as Terrestrial Laser Scanning (TLS) data, which is expensive and limited to small spatial extents. However, there has been limited exploration of inexpensive solutions to model trees over large spatial extents. The goal of this study is to use widely available discrete return Airborne Laser Scanning (ALS) data along with field-captured tree photographs and Google Street View (GSV) images to develop 3D equivalents of trees over larger spatial extents. To this end, we designed a process to assign representative 3D models for individual trees in discrete return ALS point clouds. This study demonstrates the use of a Convolutional Neural Network (CNN) model and 3D models generated with Structure from Motion (SfM) for the realistic modelling of deciduous non-overlapping trees from discrete return ALS data. We classified and labelled the crown shapes of deciduous trees in a study area into four classes based on GSV images of trees. We delineated and segmented non-overlapping deciduous trees from ALS data and reduced them to 2D images using voxel point counts. Next, we trained a CNN architecture to match the 2D images to the corresponding classes observed from GSV images. For each class, we created a representative 3D tree model using field-captured circumnavigational photos of trees and SfM. To demonstrate 3D visualization using the 3D tree models, we created a 3D visualization of the trees surrounding a parking lot. The trained CNN model from this study can be used to classify non-overlapping deciduous trees from discrete return ALS data and subsequently visualize near-realistic 3D tree models of trees.}, number={22}, journal={International Journal of Remote Sensing}, publisher={Informa UK Limited}, author={Vivek Nanda, Vishnu Mahesh and Baran, Perver and Tateosian, Laura and Nelson, Stacy A. C. and Hu, Jianxin}, year={2023}, month={Nov}, pages={7156–7186} }
 @book{hu_2022, place={San Diego, CA}, title={Building Environmental Control Systems Illustrated}, ISBN={9781793575883}, publisher={Cognella Academic Publishing}, author={Hu, Jianxin}, year={2022} }
 @article{beasley_monsur_hu_dunn_madden_2022, title={The bacterial community of childcare centers: potential implications for microbial dispersal and child exposure}, volume={17}, ISSN={["2524-6372"]}, DOI={10.1186/s40793-022-00404-6}, abstractNote={Abstract
                Background
                Bacterial communities within built environments reflect differences in sources of bacteria, building design, and environmental contexts. These communities impact the health of their occupants in many ways. Children interact with the built environment differently than do adults as a result of their unique behaviors, size, and developmental status. Consequently, understanding the broader bacterial community to which children are exposed will help inform public health efforts and contribute to our growing understanding of the bacterial community associated with childcare centers.
              
                Methods
                We sampled childcare centers to survey the variation in bacterial community composition across five surfaces found inside and outside twelve classrooms and six centers using 16S rRNA marker gene amplicon sequencing. We then correlated these bacterial community analyses of surfaces with environmental and demographic measures of illumination and classroom occupant density.
              
                Results
                The childcare environment was dominated by human-associated bacteria with modest input from outdoor sources. Though the bacterial communities of individual childcare centers differed, there was a greater difference in the bacterial community within a classroom than among centers. Surface habitats—fomites—within the classroom, did not differ in community composition despite differing proximity to likely sources of bacteria, and possible environmental filters, such as light. Bacterial communities did correlate with occupant density and differed significantly between high and low usage surfaces.
              
                Conclusions
                Our results suggest built environments inhabited by young children are similar to functionally equivalent built environments inhabited by adults, despite the different way young children engage with their environment. Ultimately, these results will be useful when further interrogating microbial dispersal and human exposure to microorganisms in built environments that specifically cater to young children.
              }, number={1}, journal={ENVIRONMENTAL MICROBIOME}, author={Beasley, D. E. and Monsur, M. and Hu, J. and Dunn, R. R. and Madden, A. A.}, year={2022}, month={Mar} }
 @article{mohsenin_hu_2017, title={DAYLIGHT PREDICTION IN INDIVIDUAL FLOORS USING WELL INDEX}, volume={10}, ISSN={["1899-0142"]}, DOI={10.21307/acee-2017-024}, abstractNote={Abstract
               This research is focused on assessing daylight performance in different floors based on the building proportion. Previous studies showed that atrium with the same Well Index (proportion) will receive the same daylight. This study aims to examine the relation between daylight in different floors of a building, using Well Index.
               Using DIVA for Rhino and DesignBuilder as the optimized daylight and energy simulation tools, this paper employs Daylight Autonomy (DA) and thermal performance as measured metrics.
               The research findings have demonstrated that Well Index can be a valid indicator to characterize proportion for assessing daylight at individual floors in buildings. This methodology improves the existing research method by proving that spaces with the same Well Index will have very close dynamic daylight metrics under the same condition, assumptions and material properties.}, number={2}, journal={ARCHITECTURE CIVIL ENGINEERING ENVIRONMENT}, author={Mohsenin, Mahsan and Hu, Jianxin}, year={2017}, month={Jun}, pages={109–114} }
 @article{mohsenin_hu_2015, title={Assessing daylight performance in atrium buildings by using Climate Based Daylight Modeling}, volume={119}, ISSN={0038-092X}, url={http://dx.doi.org/10.1016/J.SOLENER.2015.05.011}, DOI={10.1016/J.SOLENER.2015.05.011}, abstractNote={This research focuses on daylight assessment in office buildings with different atrium types, proportions and roof aperture designs. The goal is to assess and optimize atrium type and proportions to improve energy efficiency of atrium buildings. This paper investigates daylight metrics in central, attached and semi-enclosed atrium types with different proportions and roof aperture designs, such as monitor and horizontal skylight. Daylight performance is measured based on the proportions of an atrium that are defined by Well Index (WI), used to characterize atria. Climate-Based Daylight Modeling (CBDM) is applied as the assessment strategy with U.S Climate Zone 3 as the climatic setting. Spatial Daylight Autonomy (sDA) and Annual Solar Exposure (ASE) are adopted as the dynamic daylight metrics to compare the results. This study also validates DIVA for Rhino as the simulation tool by comparing daylight results of the computer simulation with the same scale-model. This research applies both scale-model and computer simulation methods to assess daylight and energy performance in atrium buildings based on Well Index. This paper then employs DIVA simulation tool to assess daylight performance based on the Well Index. The results demonstrate that Well Index is a reliable indicator to characterize atrium proportion and confirm that Well Index works with (CBDM). Having assessed the impact of design parameters, such as climate, building thickness, material reflectance, material transmittance, furniture and monitor roof glazing height, the study potentially provides architects with an atrium design database for U.S. Climate Zone 3. This database compares daylight metrics for Well Index of 0.5, 1 and 2 in central, attached and semi-enclosed atrium types using different roof aperture designs.}, journal={Solar Energy}, publisher={Elsevier BV}, author={Mohsenin, Mahsan and Hu, Jianxin}, year={2015}, month={Sep}, pages={553–560} }
 @inproceedings{malekafzali ardakan_ghobad_hu_place_2013, title={Comparison of climate-based daylighting in two integrated simulation tools: DIVA and OpenStudio}, booktitle={PLEA2013 - 29th Conference, Sustainable Architecture for a Renewable Future}, author={Malekafzali Ardakan, A. and Ghobad, L. and Hu, Jianxin and Place, Wayne}, year={2013}, pages={1–7} }