Experimental, analytical, and fuzzy modeling for predicting the flexural capacity of flat sandwich panels

Abstract This study presents a comprehensive investigation into the load-bearing capacity of flat sandwich panels through experimental testing and analytical calculations. Wall sandwich panels with mineral wool cores and steel facings were tested. Notably, the experimental program included not only standard single-span configurations but also two-span and three-span bending schemes, for which established testing standards are currently lacking. These experiments revealed that panel behavior depends significantly on the span length and core thickness, with failure typically governed by shear deformation within the core or local instability of the facings. This research provides a new, extensive dataset specifically generated for the validation of theoretical models. Analytical calculations were performed based on elasticity theory, considering the shear compliance of the core material. Comparison between experimental and analytical results revealed a convergence of under 4% for the single-span model. However, for the two-span and three-span configurations, the error margins were 11% and 27%, respectively. In addition, a sensitivity analysis was conducted for the first time using a fuzzy set theory approach to assess the impact of uncertainties in material characteristics and sandwich geometric parameters on panel displacements. The comprehensive comparison demonstrates the need for improved theoretical models and facilitates a more adequate assessment of sandwich panel modeling results.

Authors

Publication Details

Journal
Journal of Engineering and Applied Science
Published
2026-06-17
DOI
https://doi.org/10.1186/s44147-026-01055-x
Primary Topic
Composite Structure Analysis and Optimization
Type
article
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article

Experimental, analytical, and fuzzy modeling for predicting the flexural capacity of flat sandwich panels

Denys Volchok, Artur Zbiciak, Yuliia Vershkova, Viacheslav Chaban
Journal of Engineering and Applied Science
Composite Structure Analysis and Optimization
article

Experimental, analytical, and fuzzy modeling for predicting the flexural capacity of flat sandwich panels

Denys Volchok, Artur Zbiciak, Yuliia Vershkova, Viacheslav Chaban
article en

Abstract

Abstract This study presents a comprehensive investigation into the load-bearing capacity of flat sandwich panels through experimental testing and analytical calculations. Wall sandwich panels with mineral wool cores and steel facings were tested. Notably, the experimental program included not only standard single-span configurations but also two-span and three-span bending schemes, for which established testing standards are currently lacking. These experiments revealed that panel behavior depends significantly on the span length and core thickness, with failure typically governed by shear deformation within the core or local instability of the facings. This research provides a new, extensive dataset specifically generated for the validation of theoretical models. Analytical calculations were performed based on elasticity theory, considering the shear compliance of the core material. Comparison between experimental and analytical results revealed a convergence of under 4% for the single-span model. However, for the two-span and three-span configurations, the error margins were 11% and 27%, respectively. In addition, a sensitivity analysis was conducted for the first time using a fuzzy set theory approach to assess the impact of uncertainties in material characteristics and sandwich geometric parameters on panel displacements. The comprehensive comparison demonstrates the need for improved theoretical models and facilitates a more adequate assessment of sandwich panel modeling results.

Journal of Engineering and Applied ScienceVol. 73(1)
Openalex Percentile: Top 11%
Composite Structure Analysis and Optimization
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Experimental, analytical, and fuzzy modeling for predicting the flexural capacity of flat sandwich panels — Denys Volchok, Artur Zbiciak, et al. · Journal of Engineering and Applied Science (2026) | TGRS Research Map | TGRS