Worst Multiple Perturbation Load Approach of stiffened shells with and without cutouts for improved knockdown factors

Hao, Peng; Wang, Bo; Li, Gang; Meng, Zeng; Tian, Kuo; Zeng, Dujuan; Tang, Xiaohan

doi:10.1016/j.tws.2014.05.004

Cited by 108 publications

(25 citation statements)

References 42 publications

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“…From Table 5, results indicate that steel conical shells with multiple perturbation load (MPLA) imperfection are more sensitive as compared to cones with single perturbation load (SPLA) imperfection when subjected to axial compression. This is consistent with the result of [17] for composite cones, [13] for composite cylinders and [14] for aluminium alloy cylinders. Furthermore, in contrary to the suggestion by [17], where models with 6 perturbation loads were said to produce the worst result thereby producing the WMPLA for axially compressed stiffened composite conical shells, it can be seen that conical models with 2 multiple perturbation load (two dimples) gives the worst result thereby producing the worst multiple perturbation load (WMPLA) for all the dimple amplitude considered, except for A = 0.28, where 4 multiple perturbation load (four dimples) gives the worst result.…”

Section: Fig 6 Typical Plot Of Experimental Load Versus Axial Shortsupporting

confidence: 92%

“…To answer this question, there is a need to consider influence of multiple perturbation load approach (MPLA) on the buckling behavior of such structures. Numerical investigations into the buckling behaviour of cylindrical shells with multiple perturbation load approach (MPLA) can be found in [13,14]. Whilst, [13] is devoted to axially compressed composite cylinder with multiple perturbation imperfection, [14] was devoted to the aluminium alloy cylindrical shells with multiple perturbation imperfection subjected to axial compression.…”

Section: Introductionmentioning

confidence: 99%

“…Numerical investigations into the buckling behaviour of cylindrical shells with multiple perturbation load approach (MPLA) can be found in [13,14]. Whilst, [13] is devoted to axially compressed composite cylinder with multiple perturbation imperfection, [14] was devoted to the aluminium alloy cylindrical shells with multiple perturbation imperfection subjected to axial compression. Results indicates that the cylindrical shells with MPLA imperfection are more sensitive as compared to cylinders with SPLA imperfection when subjected to axial compression.…”

Section: Introductionmentioning

confidence: 99%

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Instability of Conical Shells with Multiple Dimples under Axial Compression

Ifayefunmi¹,

Mahidan²,

Maslan³

2020

IJRTE

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Abstract: Thin-walled conical shells are primary structures in offshore application. Presence of imperfection can considerably reduce the load carrying capacity of such structures when in use. : two perfect, and the remaining six with MPLA imperfection amplitude, A, of 0.56, 1.12 and 1.68 0.91 to 1.13. This study examines the buckling behavior of axially compressed imperfect steel cones using the multiple perturbation load analysis (MPLA). This is both a numerical and experimental study. Eight conical shell test models were manufactured in pairs and collapsed under axial compression having two equally-spaced dimples on each cones. Experimental test results for all the conical shell models and the accompanying numerical predictions are given in this paper. Repeatability of experimental data was good. The errors within each pair were 3%, 13%, 1% and 0%. In addition, there was a good comparison between experimental and numerical data. The ratio of experimental to numerical buckling loads varies from

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Section: Fig 6 Typical Plot Of Experimental Load Versus Axial Shortsupporting

confidence: 92%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Instability of Conical Shells with Multiple Dimples under Axial Compression

Ifayefunmi¹,

Mahidan²,

Maslan³

2020

IJRTE

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“…Thus, the knockdown effects caused by imperfections should be considered in the design process. The geometry of an imperfect structure can be obtained by modifying the nodal coordinates according to the imperfection vector, which can be formulated as the deviations from the perfect geometry [23].…”

Section: Explicit Dynamic Analysismentioning

confidence: 99%

Generatrix shape optimization of stiffened shells for low imperfection sensitivity

Wang

Hao

et al. 2014

Sci. China Technol. Sci.

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According to previous studies, stiffened shells with convex hyperbolic generatrix shape are less sensitive to imperfections. In this study, the effects of generatrix shape on the performances of elastic and plastic buckling in stiffened shells are investigated. Then, a more general description of generatrix shape is proposed, which can simply be expressed as a convex B-spline curve (controlled by four key points). An optimization framework of stiffened shells with a convex B-spline generatrix is established, with optimization objective being measured in terms of nominal collapse load, which can be expressed as a weighted sum of geometrically imperfect shells. The effectiveness of the proposed framework is demonstrated by a detailed comparison of the optimum designs for the B-spline and hyperbolic generatrix shapes. The decrease of imperfection sensitivity allows for a significant weight saving, which is particularly important in the development of future heavy-lift launch vehicles. stiffened shell, collapse, imperfection sensitivity, generatrix shape, optimization Citation:Wang B, Hao P, Li G, et al. Generatrix shape optimization of stiffened shells for low imperfection sensitivity.

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“…In order to perform less expensive and at the same time representative buckling tests for composite sandwich shells a new scaling methodology was proposed by Balbin et al [42]. An alternative to buckling tests and analytical predictions are lower-bound methods like the single boundary perturbation approach (SBPA) [43], [8] or the worst multiple perturbation load approach (WMPLA) [44], [45]. The SBPA is a numerical design approach which is realized using finite element simulations [46], [47].…”

Section: Introductionmentioning

confidence: 99%

Decision tree-based machine learning to optimize the laminate stacking of composite cylinders for maximum buckling load and minimum imperfection sensitivity

Wagner

Köke

Dähne

et al. 2019

Composite Structures

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Köke, H.; Dähne, S.; Hühne, C.; Niemann, S.; Khakimova, R. Decision tree-based machine learning to optimize the laminate stacking of composite cylinders for maximum buckling load and minimum imperfection sensitivity, Composite Structures AbstractLaunch-vehicle primary structures like cylindrical shells are increasingly being built as monolithic composite and sandwich composite shells. These imperfection sensitive shells are subjected to axial compression due to the weight of the upper structural elements and tend to buckle under axial compression. In the case of composite shells the buckling load and imperfection sensitivity depend on the laminate stacking sequence.Within this paper multi-objective optimizations for the laminate stacking sequence of composite cylinder under axial compression are performed. The optimization is based on different geometric imperfection types and a brute force approach for three different ply angles. Decision tree-based machine learning is applied to derive general design recommendations which lead to maximum buckling load and a minimum imperfection sensitivity.The design recommendation are based on the relative membrane, bending, in-plane shear and twisting stiffnesses. Several optimal laminate stacking sequences are generated and compared with similar laminate configurations from literature. The results show that the design recommendations of this article lead to high-performance cylinders which outperform comparable composite shells considerably. The results of this article may be the basis for future lightweight design of sandwich and monolithic composite cylinders of modern launch-vehicle primary structures. t Wall thickness of cylindrical shells tply Ply thickness u Axial shortening  Ply angle  Ply angle  Ply angle  knockdown factor Wilkins [1975]

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Worst Multiple Perturbation Load Approach of stiffened shells with and without cutouts for improved knockdown factors

Cited by 108 publications

References 42 publications

Instability of Conical Shells with Multiple Dimples under Axial Compression

Instability of Conical Shells with Multiple Dimples under Axial Compression

Generatrix shape optimization of stiffened shells for low imperfection sensitivity

Decision tree-based machine learning to optimize the laminate stacking of composite cylinders for maximum buckling load and minimum imperfection sensitivity

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