Optimization for CFRP pultrusion process based on genetic algorithm-neural network

International Journal of Material Forming

Volumn 3, Issue SUPPL. 2, 2010, Pages 1391-1399

  Chen, Xingkai ^a   Xie, Huaiqin ^a   Chen, Hui ^b   Zhang, Fuhua ^c  

^a HARBIN INSTITUTE OF TECHNOLOGY   (China)

^b Harbin FRP Institute   (China)

^c SHANGHAI MARITIME UNIVERSITY   (China)

Author keywords

Carbon fiber reinforced polymer; Fiber Bragg grating sensor; Genetic algorithm; Neural network; Optimization; Pultrusion

Indexed keywords

ARTIFICIAL NEURAL NETWORK; BI-OBJECTIVE OPTIMIZATION; CARBON FIBER REINFORCED POLYMER; DECOUPLING METHODS; DEGREE OF CURE; DIE TEMPERATURES; FIBER BRAGG GRATING SENSOR; GOVERNING EQUATIONS; PROCESSING PARAMETERS; PULTRUSION PROCESS; REAL TIME; RESIN CURING; SIMULATED RESULTS; SIMULATION PROCEDURES;

CARBON FIBERS; CURING; DIFFERENTIAL SCANNING CALORIMETRY; ELECTRIC SENSING DEVICES; FIBER BRAGG GRATINGS; FIBER OPTIC COMPONENTS; FIBER OPTIC SENSORS; FIBER REINFORCED PLASTICS; FIBERS; FINITE ELEMENT METHOD; GENETIC ALGORITHMS; OPTIMIZATION; POLYMERS; PULTRUSION; REINFORCED PLASTICS; RESINS; VIBRATION MEASUREMENT;

NEURAL NETWORKS;

EID: 77956691483     PISSN: 19606206     EISSN: 19606214     Source Type: Journal    
DOI: 10.1007/s12289-010-0684-5     Document Type: Article

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