| People | Locations | Statistics |
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| Naji, M. |
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| Motta, Antonella |
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| Aletan, Dirar |
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| Mohamed, Tarek |
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| Ertürk, Emre |
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| Taccardi, Nicola |
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| Kononenko, Denys |
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| Petrov, R. H. | Madrid |
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| Alshaaer, Mazen | Brussels |
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| Bih, L. |
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| Casati, R. |
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| Muller, Hermance |
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| Kočí, Jan | Prague |
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| Šuljagić, Marija |
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| Kalteremidou, Kalliopi-Artemi | Brussels |
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| Azam, Siraj |
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| Ospanova, Alyiya |
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| Blanpain, Bart |
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| Ali, M. A. |
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| Popa, V. |
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| Rančić, M. |
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| Ollier, Nadège |
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| Azevedo, Nuno Monteiro |
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| Landes, Michael |
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| Rignanese, Gian-Marco |
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Hühne, Christian
in Cooperation with on an Cooperation-Score of 37%
Topics
Publications (27/27 displayed)
- 2024Increased accuracy of service life prediction for fiber metal laminates by consideration of the manufacturing-induced residual stress statecitations
- 2024Bolt-bearing behavior of hybrid CFRP-steel laminates at low temperaturecitations
- 2024STRUCTURAL PART STIFFNESS TEST IN COMPARISON TO THE FE-PREDICTION. A TEST COMBINING CONTINUOUS STRUCTURE WITH COMPLEX INTERFACES
- 2024Equivalent plate formulation of Double-Double laminates for the gradient-based design optimization of composite structurescitations
- 2024Local Surface Toughening – A boltless crack stopping technology for aerospace structures
- 2024Validation of static residual strength analyses of fiber composite bonded joints
- 2023Steigerung der Robustheit von strukturellen Klebungen mittels Surface Toughening am Beispiel HAP
- 2023Anisotropic flexure hinges: Manufacturing and mechanical characterization forapplication in pressure-actuated morphing structures
- 2023THERMAL CONDUCTIVITY CHARACTERIZATION OF A CFRP SINGLE-LAP JOINT
- 2023Curvature Analysis of asymmetric Specimes for the residual stress quantification in fiber metal laminates
- 2023Comparison of Continuum Shell and Solid Element-Based Modeling Strategies for Mesoscale Progressive Damage Analysis of Fiber Compositescitations
- 2023Investigations on Guided Ultrasonic Wave Dispersion Behavior in Fiber Metal Laminates Using Finite Element Eigenvalue Analysiscitations
- 2023Anisotropic flexure hinges: Manufacturing and mechanical characterization for application in pressure-actuated morphing structurescitations
- 2023Gradient-based Design Optimization of Composite Structures using Double-Double Laminates
- 2023Aeroelastic Analysis of Actuated Adaptive Wingtips Based on Pressure-Actuated Cellular Structures
- 2023Effect of low temperature on mode I and mode II interlaminar fracture toughness of CFRP-steel hybrid laminatescitations
- 2022Polyetherimide-Reinforced Smart Inlays for Bondline Surveillance in Composites
- 2022In-situ quantification of manufacturing-induced strains in fiber metal laminates with strain gages
- 2022Applicability of Asymmetric Specimens for Residual Stress Evaluation in Fiber Metal Laminatescitations
- 2020Surface toughening - An industrial approach to increase the robustness of pure adhesive joints with film adhesivescitations
- 2019Decision Tree-based Machine Learning to Optimize the Laminate Stacking of Composite Cylinders for Maximum Buckling Load and Minimum Imperfection Sensitivity
- 2016Degradation analysis of fibre-metal laminates under service conditions to predict their durability
- 2016Experimental investigations on residual stresses during the fabrication of intrinsic CFRP-steel laminates
- 2013Effective lightweight design of a rocket interstage ring through mixed-integer optimization
- 2012Experimental identification of process parameters inducing warpage of autoclave-processed CFRP partscitations
- 2011A semi-analytical simulation strategy and its application to warpage of autoclave-processed CFRP partscitations
- 2005Robuster Entwurf beulgefährdeter, unversteifter Kreiszylinderschalen aus Faserverbundwerkstoff ; Robust Design of Unstiffened Cylindrical Shells made of Composite Material
Places of action
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article
Decision Tree-based Machine Learning to Optimize the Laminate Stacking of Composite Cylinders for Maximum Buckling Load and Minimum Imperfection Sensitivity
Abstract
Launch-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.