Existing buildings and historic structures play key roles in the communities they are a part of. Not only are they an important part of cultural legacy, but they also are crucial in surmounting engineering challenges like the design of sustainable infrastructure, space shortages, increased costs of construction, and the lowering life cycle costs. By reusing or recycling existing and historic structures, communities can reduce their carbon costs, decrease the amount of solid waste they are contributing to landfills, and save on new construction materials. Before existing structures can be preserved or renovated however, an assessment of the existing building must be completed. This process must comprise documenting where damages are, understanding how existing damages originated and assessing the current capacity of a structure. My research is in hybrid! analytics which lies at the intersection of architectural engineering, computer science, and historic preservation. Hybrid analytics, a nascent field, is the combination of physics-based modeling and data-driven modeling for the end goal of making real-time predictions and monitoring in the context of Digital Twin a reality. This new field leverages the decipherability and clear-box nature of physics-based modeling, with accuracy and pattern recognition techniques of data-driven machine learning algorithms.
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Recent Publications
Data-driven evaluation of building materials using Ground Penetrating Radar
Alam, A. N., Reinhart, W. F. & Napolitano, R. K., Oct 15 2024, In: Journal of Building Engineering. 95, 110188.Research output: Contribution to journal › Article › peer-review
Addressing machine learning bias to foster energy justice
Chen, C. F., Napolitano, R., Hu, Y., Kar, B. & Yao, B., Oct 2024, In: Energy Research and Social Science. 116, 103653.Research output: Contribution to journal › Short survey › peer-review
Understanding critical masonry building attributes shaping vulnerability to blast loads: Data-driven insights from the 2020 Beirut explosion
Kallas, J. & Napolitano, R., Aug 2024, In: International Journal of Disaster Risk Reduction. 110, 104640.Research output: Contribution to journal › Article › peer-review
Assessing the behavior of historic masonry buildings to tornadic events: A comparative study of code-based analysis and point cloud based simulation
Kaushal, S. S., Gutierrez Soto, M. & Napolitano, R., Sep 2024, In: Engineering Failure Analysis. 163, 108539.Research output: Contribution to journal › Article › peer-review
Three-Dimensional Digital Documentation of Tornado-Damaged Heritage Buildings
Kaushal, S. S., Gutierrez Soto, M. & Napolitano, R., Oct 1 2024, In: Journal of Structural Engineering (United States). 150, 10, 04724002.Research output: Contribution to journal › Article › peer-review
On determining structural wall layout during the adaptive reuse process of historic masonry buildings
Paulino, D. M. S., Ligler, H. & Napolitano, R., Oct 15 2024, In: Journal of Building Engineering. 95, 110178.Research output: Contribution to journal › Article › peer-review
Evaluating Human Expert Knowledge in Damage Assessment Using Eye Tracking: A Disaster Case Study
Saleem, M. R., Mayne, R. & Napolitano, R., Jul 2024, In: Buildings. 14, 7, 2114.Research output: Contribution to journal › Article › peer-review
AUTOMATED LARGE-SCALE DAMAGE DETECTION on HISTORIC BUILDINGS in POST-DISASTER AREAS USING IMAGE SEGMENTATION
Kallas, J. & Napolitano, R., Jun 24 2023, In: International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives. 48, M-2-2023, p. 797-804 8 p.Research output: Contribution to journal › Conference article › peer-review
Image-based 3D modeling as a damage prioritization tool for historic buildings in post-disaster areas: The case of the 2020 Beirut blast
Kallas, J. & Napolitano, R., Jul 1 2023, In: Journal of Cultural Heritage. 62, p. 314-321 8 p.Research output: Contribution to journal › Article › peer-review
STRUCTURAL ANALYSIS of POST-DISASTER MASONRY STRUCTURES MODELED USING CLOUD2FEM SOFTWARE
Kaushal, S. S., Gutierrez Soto, M. & Napolitano, R., Jun 24 2023, In: International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives. 48, M-2-2023, p. 827-834 8 p.Research output: Contribution to journal › Conference article › peer-review
Understanding the Performance of Historic Masonry Structures in Mayfield, KY after the 2021 Tornadoes
Kaushal, S. S., Gutierrez Soto, M. & Napolitano, R., Sep 1 2023, In: Journal of Cultural Heritage. 63, p. 120-134 15 p.Research output: Contribution to journal › Article › peer-review
Roadmap on measurement technologies for next generation structural health monitoring systems
Laflamme, S., Ubertini, F., Di Matteo, A., Pirrotta, A., Perry, M., Fu, Y., Li, J., Wang, H., Hoang, T., Glisic, B., Bond, L. J., Pereira, M., Shu, Y., Loh, K. J., Wang, Y., Ding, S., Wang, X., Yu, X., Han, B. & Goldfeld, Y. & 5 others, , Sep 2023, In: Measurement Science and Technology. 34, 9, 093001.Research output: Contribution to journal › Article › peer-review
A Grammar-Based Approach for Generating Spatial Layout Solutions for the Adaptive Reuse of Sobrado Buildings
Paulino, D. M. S., Ligler, H. & Napolitano, R., Mar 2023, In: Buildings. 13, 3, 722.Research output: Contribution to journal › Article › peer-review
Displacement-based structural identification using differentiable physics
Rahnamay Farnod, B., Reinhart, W. F. & Napolitano, R. K., Oct 15 2023, In: Engineering Structures. 293, 116632.Research output: Contribution to journal › Article › peer-review
Analysis of gaze patterns during facade inspection to understand inspector sense-making processes
Saleem, M. R., Mayne, R. & Napolitano, R., Dec 2023, In: Scientific reports. 13, 1, 2929.Research output: Contribution to journal › Article › peer-review