Optimization of composite laminate under mechanical and thermal loading using finite element method and machine learning techniques [EMBARGOED]

Abstract

Thin walled composite structures have gained significant traction for diverse engineering uses due to their laminated composition, featuring layers of composite materials with unique properties shaped by fiber orientation. Stress analysis of such thin walled composite sections under mechanical and thermal loads is complex, often requiring optimization to achieve optimal designs. However, the reduced thickness of these structures makes them susceptible to buckling. Incorporating lightning holes reduces weight but compromises stiffness and buckling strength. This study focuses on assessing the buckling strength of thin walled composites with various hole shapes under mechanical and thermal loads. A parametric investigation aims to identify the best material and structural parameters for resilience against both mechanical and thermal stress. Initially, a finite element based numerical approach was used to model the c section thin walled composite structure. Structural and material parameters like spacing ratio, opening ratio, hole shape, fiber orientation, and laminate sequence are systematically varied under mechanical and thermal loads. The resulting data drives the identification of optimal parameter combinations through machine learning algorithms. Multiple techniques are compared to finite element results for accuracy. The simulation model effectively captures changes in critical buckling load under distinct mechanical and thermal conditions due to alterations in structural and material features. The machine learning approach accurately predicts optimal critical buckling load under both scenarios. Furthermore, the study's findings indicate that the optimal critical buckling values for the current problem are achieved with specific parameter combinations. For mechanical loading conditions, the best configuration involves a quasi isotropic structure with a circular hole, an opening ratio of 1.4, and a spacing ratio of 1.6, resulting in a critical buckling load of 8804 N. In the case of thermal loading, an angle ply structure with a circular hole, an opening ratio of 1.4, and a spacing ratio of 1.7 leads to a critical buckling load of 308.2 (T critical). In summary, this thesis comprehensively explores the stability of c section thin walled composite structures with holes under mechanical and thermal loads, utilizing finite element analysis and machine learning.