Volume XLII-2/W15
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2/W15, 843–848, 2019
https://doi.org/10.5194/isprs-archives-XLII-2-W15-843-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2/W15, 843–848, 2019
https://doi.org/10.5194/isprs-archives-XLII-2-W15-843-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

  23 Aug 2019

23 Aug 2019

UNDERSTANDING THE EFFECTS OF DOCUMENTATION DETAIL ON DIAGNOSTICS OF HISTORIC STRUCTURES

R. K. Napolitano1, M. Hess2, and B. Glisic1 R. K. Napolitano et al.
  • 1Princeton University, Department of Civil and Environmental Engineering, 59 Olden Street, Princeton, NJ, USA
  • 2University of California San Diego, Department of Structural Engineering, Mail Code 0085, 9500 Gilman Drive, La Jolla, CA, USA

Keywords: levels of detail, documentation, diagnostics, physics-based modelling, laser scanning, masonry

Abstract. Before reinforcements or new construction are added to historic structures, it is important to understand how the existing damage could have arisen. Often to do this, documentation methods such as laser scanning and photogrammetry are used to capture the existing conditions and physics-based models are used to simulate the response of a facsimile structure to various responses. Something that varies quite a bit though is the level of detail used to capture the existing conditions as well as the level of detail used to represent the structure during physics-based modelling. This paper aims to understand the effects of documentation detail on diagnostics of historic structures. To do this, two masonry structures were documented with laser scanners, photographs, and thermal images. For each case study, three-dimensional models of varying fidelity were generated based on the results of simulation. The response of these models to loading conditions was then calculated using a physics-based modelling technique called finite-distinct element modelling. The results for each case study are compared to understand the impacts of geometry on diagnostics; discussion about future tools to augment current practices is included.