Multi-objective optimization of fiber reinforced composite laminates for strength, stiffness and minimal mass
We present a methodology for the multi-objective optimization of laminated composite materials that is based on an integer-coded genetic algorithm. The fiber orientations and fiber volume fractions of the laminae are chosen as the primary optimization variables. Simplified micromechanics equations a...
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| Vydáno v: | Computers & structures Ročník 84; číslo 29; s. 2065 - 2080 |
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| Hlavní autoři: | , |
| Médium: | Journal Article |
| Jazyk: | angličtina |
| Vydáno: |
Oxford
Elsevier Ltd
01.11.2006
Elsevier Science |
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| ISSN: | 0045-7949, 1879-2243 |
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| Abstract | We present a methodology for the multi-objective optimization of laminated composite materials that is based on an integer-coded genetic algorithm. The fiber orientations and fiber volume fractions of the laminae are chosen as the primary optimization variables. Simplified micromechanics equations are used to estimate the stiffnesses and strength of each lamina using the fiber volume fraction and material properties of the matrix and fibers. The lamina stresses for thin composite coupons subjected to force and/or moment resultants are determined using the classical lamination theory and the first-ply failure strength is computed using the Tsai–Wu failure criterion. A multi-objective genetic algorithm is used to obtain Pareto-optimal designs for two model problems having multiple, conflicting, objectives. The objectives of the first model problem are to maximize the load carrying capacity and minimize the mass of a graphite/epoxy laminate that is subjected to biaxial moments. In the second model problem, the objectives are to maximize the axial and hoop rigidities and minimize the mass of a graphite/epoxy cylindrical pressure vessel subject to the constraint that the failure pressure be greater than a prescribed value. |
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| AbstractList | We present a methodology for the multi-objective optimization of laminated composite materials that is based on an integer-coded genetic algorithm. The fiber orientations and fiber volume fractions of the laminae are chosen as the primary optimization variables. Simplified micromechanics equations are used to estimate the stiffnesses and strength of each lamina using the fiber volume fraction and material properties of the matrix and fibers. The lamina stresses for thin composite coupons subjected to force and/or moment resultants are determined using the classical lamination theory and the first-ply failure strength is computed using the Tsai-Wu failure criterion. A multi-objective genetic algorithm is used to obtain Pareto-optimal designs for two model problems having multiple, conflicting, objectives. The objectives of the first model problem are to maximize the load carrying capacity and minimize the mass of a graphite/epoxy laminate that is subjected to biaxial moments. In the second model problem, the objectives are to maximize the axial and hoop rigidities and minimize the mass of a graphite/epoxy cylindrical pressure vessel subject to the constraint that the failure pressure be greater than a prescribed value. |
| Author | Pelletier, Jacob L. Vel, Senthil S. |
| Author_xml | – sequence: 1 givenname: Jacob L. surname: Pelletier fullname: Pelletier, Jacob L. – sequence: 2 givenname: Senthil S. surname: Vel fullname: Vel, Senthil S. email: senthil.vel@maine.edu |
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| Keywords | Composite pressure vessel Stacking sequence Combinatorial optimization Laminated composite materials Genetic algorithm Stratified material Fiber reinforced material Rupture Epoxy resin Pressure vessel Biaxial load Fracture criterion Modeling Composite material Optimization Optimal design Graphite fiber Matrix fiber interface Loadbearing capacity Fiber orientation Stiffness Cylindrical shell Rupture strength |
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| SubjectTerms | Applied sciences Combinatorial optimization Composite pressure vessel Composites Computational techniques Exact sciences and technology Forms of application and semi-finished materials Fracture mechanics (crack, fatigue, damage...) Fundamental areas of phenomenology (including applications) Genetic algorithm Laminated composite materials Mathematical methods in physics Mechanical engineering. Machine design Physics Polymer industry, paints, wood Solid mechanics Stacking sequence Steel design Steel tanks and pressure vessels; boiler manufacturing Structural and continuum mechanics Technology of polymers |
| Title | Multi-objective optimization of fiber reinforced composite laminates for strength, stiffness and minimal mass |
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