Buckling Mode Identification of Steel Decks Using Fiber Optic Strain Sensing and 3D Spatial Data

Abstract Quantification of global and local buckling behavior of steel systems is crucial to determine accurate load capacities of thin‐walled structural steel systems. New forms of instrumentation permit a robust method for measuring global and local buckling deformations during laboratory studies. This paper explores global and local buckling quantification from various forms of instrumentation to capture multiscale strain behavior, including distributed fiber optic sensing and 3D spatial data from infrared optical tracking and point clouds scans. The test case is a profiled steel deck loaded with uniform pressure using a 2.4 m by 4.9 m by 0.9 m vacuum box. Two different experimental layouts were considered, a two‐span deck with a center support and a single‐span deck. An OptiTrack system used infrared optical tracking to measure 3D displacements. The Scaniverse app on an Apple iPad Pro used LiDAR and photogrammetry to create 3D spatial data to determine vertical displacements. Distributed fiber optic strain illustrated the global and local buckling deck behavior by providing continuous longitudinal strain measurements along the deck longitudinal direction on several flanges. A method to integrate the distributed strain to vertical displacements is presented. The findings of this study are expected to contribute to the development of innovative solutions using advanced measurement techniques for global and local buckling measurement.

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Publication Details

Journal
ce/papers
Published
2025-12-01
DOI
https://doi.org/10.1002/cepa.70073
Primary Topic
Structural Health Monitoring Techniques
Type
article
Field-Weighted Citation Impact
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article

Buckling Mode Identification of Steel Decks Using Fiber Optic Strain Sensing and 3D Spatial Data

Richa Dutta Rakhee, Nate Opperman, Monamy Mustaq, Hannah B. Blum et al.
ce/papers
Structural Health Monitoring Techniques
article

Buckling Mode Identification of Steel Decks Using Fiber Optic Strain Sensing and 3D Spatial Data

Richa Dutta Rakhee, Nate Opperman, Monamy Mustaq, Hannah B. Blum, Hyeyoung Koh, Jesse C. Hampton, Gowshikan Arulananthan
article en

Abstract

Abstract Quantification of global and local buckling behavior of steel systems is crucial to determine accurate load capacities of thin‐walled structural steel systems. New forms of instrumentation permit a robust method for measuring global and local buckling deformations during laboratory studies. This paper explores global and local buckling quantification from various forms of instrumentation to capture multiscale strain behavior, including distributed fiber optic sensing and 3D spatial data from infrared optical tracking and point clouds scans. The test case is a profiled steel deck loaded with uniform pressure using a 2.4 m by 4.9 m by 0.9 m vacuum box. Two different experimental layouts were considered, a two‐span deck with a center support and a single‐span deck. An OptiTrack system used infrared optical tracking to measure 3D displacements. The Scaniverse app on an Apple iPad Pro used LiDAR and photogrammetry to create 3D spatial data to determine vertical displacements. Distributed fiber optic strain illustrated the global and local buckling deck behavior by providing continuous longitudinal strain measurements along the deck longitudinal direction on several flanges. A method to integrate the distributed strain to vertical displacements is presented. The findings of this study are expected to contribute to the development of innovative solutions using advanced measurement techniques for global and local buckling measurement.

ce/papersVol. 8(6)
University of Wisconsin System (US), University of Wisconsin–Madison (US), National Postdoctoral Association (US)
Industry, innovation and infrastructure
Openalex Percentile: Top 33%
Structural Health Monitoring Techniques
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Buckling Mode Identification of Steel Decks Using Fiber Optic Strain Sensing and 3D Spatial Data — Richa Dutta Rakhee, Nate Opperman, et al. · ce/papers (2025) | TGRS Research Map | TGRS