Structured chaos: redefining the design of buckling-critical cylindrical shells

Experimental studies on axially compressed cylindrical shells have historically shown large variability in buckling loads, often challenging existing theoretical models. Our analysis reveals that this scatter follows a structured, regime-dependent trend—formalized here as the mechanistic design curve (MDC). This curve captures a systematic transition between three dominant failure mechanisms as a function of slenderness: global collapse (Regime 1), transitional recovery (Regime 2) and localized instability (Regime 3). Through large-scale Monte Carlo simulations incorporating measured geometric imperfections and localized buckling triggers, we demonstrate how buckling behaviour evolves across these regimes, exhibiting a characteristic dip–recovery–decline pattern in knockdown factors. The MDC framework is validated using decades of experimental data on both cylindrical and conical shells, revealing consistent regime boundaries despite variations in geometry and manufacturing quality. By unifying physics-based mechanisms with statistical robustness, the MDC replaces empirical lower-bound approaches (e.g. NASA SP-8007) with predictive, regime-aware design rules. Case studies demonstrate weight savings exceeding 14%—and up to 31% in optimized configurations—while maintaining safety, highlighting the MDC's potential to transform lightweight shell design. This work reinterprets historical scatter and reveals that what appeared chaotic is, in fact, governed by hidden structure.

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Publication Details

Journal
Proceedings of the Royal Society A Mathematical Physical and Engineering Sciences
Published
2025-09-01
DOI
https://doi.org/10.1098/rspa.2025.0196
Primary Topic
Structural Analysis and Optimization
Type
article
Field-Weighted Citation Impact
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article

Structured chaos: redefining the design of buckling-critical cylindrical shells

H.N.R. Wagner, Steffen Niemann, Regina Khakimova, Christian Hühne et al.
Proceedings of the Royal Society A Mathematical Physical and Engineering Sciences
Structural Analysis and Optimization
article

Structured chaos: redefining the design of buckling-critical cylindrical shells

H.N.R. Wagner, Steffen Niemann, Regina Khakimova, Christian Hühne, Meng Wang, Jing Zhang
article en

Abstract

Experimental studies on axially compressed cylindrical shells have historically shown large variability in buckling loads, often challenging existing theoretical models. Our analysis reveals that this scatter follows a structured, regime-dependent trend—formalized here as the mechanistic design curve (MDC). This curve captures a systematic transition between three dominant failure mechanisms as a function of slenderness: global collapse (Regime 1), transitional recovery (Regime 2) and localized instability (Regime 3). Through large-scale Monte Carlo simulations incorporating measured geometric imperfections and localized buckling triggers, we demonstrate how buckling behaviour evolves across these regimes, exhibiting a characteristic dip–recovery–decline pattern in knockdown factors. The MDC framework is validated using decades of experimental data on both cylindrical and conical shells, revealing consistent regime boundaries despite variations in geometry and manufacturing quality. By unifying physics-based mechanisms with statistical robustness, the MDC replaces empirical lower-bound approaches (e.g. NASA SP-8007) with predictive, regime-aware design rules. Case studies demonstrate weight savings exceeding 14%—and up to 31% in optimized configurations—while maintaining safety, highlighting the MDC's potential to transform lightweight shell design. This work reinterprets historical scatter and reveals that what appeared chaotic is, in fact, governed by hidden structure.

Proceedings of the Royal Society A Mathematical Physical and Engineering SciencesVol. 481(2321)
Jiangsu University of Science and Technology (CN), Composite Components (Czechia) (CZ), Technische Universität Braunschweig (DE)
Openalex Percentile: Top 75%
Structural Analysis and Optimization
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