Structural behavior of stone cantilever stairs: Strain monitoring under controlled loading and numerical modeling

Antonio Maria D'Altri, Yolanda Jin, Jessica Chen, Tiffany Agyarko, Guy Nordenson, Branko Glisic

Research output: Contribution to journalArticlepeer-review

Abstract

In this paper, the structural behavior of a stone cantilever (or cascade) staircase is investigated through an integration of strain monitoring and numerical modeling. The originality of this work is in the first ever application of this combined approach, where numerical modeling is integrated with actual strain measures on a historic cantilever staircase subjected to controlled loading. The main challenge is indeed modeling a complex staircase geometry together with unknown actual boundary conditions. The Museum of the City of New York staircase, composed of marble treads, is used as case study. Fiber-optic sensors are installed in the intrados of a representative tread. Experimental strain data are collected under human loads, with different loading schemes. A 3D solid finite element model of the staircase, where each tread interacts with the adjacent ones through contact, is used to simulate the loading cases. Various boundary conditions are considered and compared with the experimental data, allowing to identify the most plausible actual boundary condition of the treads. Experimental strain data and numerical results show a good agreement. Consequently, new insights on the structural behavior of stone cantilever stairs and their outstanding structural performance are gathered.

Original languageEnglish (US)
Article number110238
JournalJournal of Building Engineering
Volume95
DOIs
StatePublished - Oct 15 2024

All Science Journal Classification (ASJC) codes

  • Civil and Structural Engineering
  • Architecture
  • Building and Construction
  • Safety, Risk, Reliability and Quality
  • Mechanics of Materials

Keywords

  • Fiber optic strain sensor
  • Finite element model
  • Spiral stairs
  • Stone cantilever staircase
  • Structural health monitoring

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