2013
Biel, Andreas; Ziegmann, Gerhard; Meiners, Dieter; Deniz, Onur; Horst, Peter
Optimization of the Structure and the Infusion Process of a CFRP Fuselage Stiffener, according to the Fiber Reorientation by the Draping Process Konferenzbeitrag
In: SETEC, 2013.
Abstract | BibTeX | Schlagwörter: Composite Structures, Draping Simulation, Fuselage, Infusion Process
@inproceedings{Biel2013,
title = {Optimization of the Structure and the Infusion Process of a CFRP Fuselage Stiffener, according to the Fiber Reorientation by the Draping Process},
author = {Andreas Biel and Gerhard Ziegmann and Dieter Meiners and Onur Deniz and Peter Horst},
year = {2013},
date = {2013-09-11},
booktitle = {SETEC},
abstract = {Design optimization plays a vital role in Aerospace Industry due to its challenging requirements that are not only based on mechanical aspects but also in manufacturing processes. Besides, manufacturing processes cause imperfections and variations on the structure which could be estimated by advanced simulations that result in expensive computation processes. On the other hand, it has been an issue to obtain global optima of the objective function of structures such as CFRP stiffened fuselage panels whose mechanical system responses are generally evaluated by Finite Element calculations.
This paper proposes a global optimization process on an innovative CFRP fuselage panel which simultaneously covers stability criterion and draping simulation of fiber textiles that is considered as a manufacturing effect. Genetic algorithms were chosen as an optimization technique to reach global optima. A parametric FEM model generator was developed under periodic boundary conditions in order to obtain buckling modes and corresponding failure criterions during the parameter variation. The shear angles of the fibers arising due to the draping process were considered as production constraint and represented with the surrogate model by RBF-ANN in the optimization loop. Different infusion strategies are simulated in a final step to find the optimal resin infusion process for the obtained fuselage stiffener.
This method presents an optimization frame that covers the production failures of draping process and its influence on structural design. Furthermore this optimization process can be modified with other undetermined production constraints that are predicted by simulation.},
keywords = {Composite Structures, Draping Simulation, Fuselage, Infusion Process},
pubstate = {published},
tppubtype = {inproceedings}
}
Design optimization plays a vital role in Aerospace Industry due to its challenging requirements that are not only based on mechanical aspects but also in manufacturing processes. Besides, manufacturing processes cause imperfections and variations on the structure which could be estimated by advanced simulations that result in expensive computation processes. On the other hand, it has been an issue to obtain global optima of the objective function of structures such as CFRP stiffened fuselage panels whose mechanical system responses are generally evaluated by Finite Element calculations.
This paper proposes a global optimization process on an innovative CFRP fuselage panel which simultaneously covers stability criterion and draping simulation of fiber textiles that is considered as a manufacturing effect. Genetic algorithms were chosen as an optimization technique to reach global optima. A parametric FEM model generator was developed under periodic boundary conditions in order to obtain buckling modes and corresponding failure criterions during the parameter variation. The shear angles of the fibers arising due to the draping process were considered as production constraint and represented with the surrogate model by RBF-ANN in the optimization loop. Different infusion strategies are simulated in a final step to find the optimal resin infusion process for the obtained fuselage stiffener.
This method presents an optimization frame that covers the production failures of draping process and its influence on structural design. Furthermore this optimization process can be modified with other undetermined production constraints that are predicted by simulation.
This paper proposes a global optimization process on an innovative CFRP fuselage panel which simultaneously covers stability criterion and draping simulation of fiber textiles that is considered as a manufacturing effect. Genetic algorithms were chosen as an optimization technique to reach global optima. A parametric FEM model generator was developed under periodic boundary conditions in order to obtain buckling modes and corresponding failure criterions during the parameter variation. The shear angles of the fibers arising due to the draping process were considered as production constraint and represented with the surrogate model by RBF-ANN in the optimization loop. Different infusion strategies are simulated in a final step to find the optimal resin infusion process for the obtained fuselage stiffener.
This method presents an optimization frame that covers the production failures of draping process and its influence on structural design. Furthermore this optimization process can be modified with other undetermined production constraints that are predicted by simulation.
Deniz, Onur; Biel, Andreas; Horst, Peter; Ziegmann, Gerhard; Schmidt, Carsten
Simulation Based Design Optimization of a Cfrp Fuselage Panel According to Draping Process of Carbon Fibre Textiles Using Evolutionary Algorithms and Response Surface Methods Konferenzbeitrag
In: Sampe, 2013.
Abstract | BibTeX | Schlagwörter: Composite Structures, Design Optimization, Draping Simulation, Fuselage
@inproceedings{Deniz2013,
title = {Simulation Based Design Optimization of a Cfrp Fuselage Panel According to Draping Process of Carbon Fibre Textiles Using Evolutionary Algorithms and Response Surface Methods},
author = {Onur Deniz and Andreas Biel and Peter Horst and Gerhard Ziegmann and Carsten Schmidt},
year = {2013},
date = {2013-05-03},
booktitle = {Sampe},
journal = {Sampe},
abstract = {Design optimization plays a vital role in Aerospace Industry due to its challenging requirements that are not only based on mechanical aspects but also in manufacturing processes. Besides, manufacturing processes cause imperfections and variations on the structure which could be estimated by advanced simulations that result in expensive computations. On the other hand, it has been an issue to obtain global optima of the objective function of structures such as CFRP stiffened fuselage panels whose mechanical system responses are generally evaluated by Finite Element calculations.
This paper proposes a global optimization process on an innovative CFRP fuselage panel which simultaneously covers stability criterion and draping simulation of fiber textiles that is considered as a manufacturing effect. Genetic algorithms were chosen as an optimization technique to reach global optima. During the optimization process, a modified Response Surface Method that is based on artificial neural networks (RBF-ANN) [1] is carried out in order to reduce the computational effort and to couple the simulation inputs and outputs in the optimization frame.
A parametric FEM model generator was developed under periodic boundary conditions in order to obtain buckling modes and corresponding failure criterions during the parameter variation. The shear angles of the fibers arising due to draping process were considered as production constraint and represented with the surrogate model by RBF-ANN in the optimization loop.
This method presents an optimization frame that covers the production failures of draping process and its influence on structural design. Furthermore this optimization process can be modified with other undetermined production constraints that are predicted by simulation.
REFERENCES
[1] K.Lindhorst, M. C. Haupt, P. Horst, “ Usage of time domain surrogate model approaches for transient, nonlinear aerodynamics within aero-structural coupling schemes” presented in"30th AIAA Applied Aerodynamics Conference", 25-28th June 2012, New Orleans, USA
},
keywords = {Composite Structures, Design Optimization, Draping Simulation, Fuselage},
pubstate = {published},
tppubtype = {inproceedings}
}
Design optimization plays a vital role in Aerospace Industry due to its challenging requirements that are not only based on mechanical aspects but also in manufacturing processes. Besides, manufacturing processes cause imperfections and variations on the structure which could be estimated by advanced simulations that result in expensive computations. On the other hand, it has been an issue to obtain global optima of the objective function of structures such as CFRP stiffened fuselage panels whose mechanical system responses are generally evaluated by Finite Element calculations.
This paper proposes a global optimization process on an innovative CFRP fuselage panel which simultaneously covers stability criterion and draping simulation of fiber textiles that is considered as a manufacturing effect. Genetic algorithms were chosen as an optimization technique to reach global optima. During the optimization process, a modified Response Surface Method that is based on artificial neural networks (RBF-ANN) [1] is carried out in order to reduce the computational effort and to couple the simulation inputs and outputs in the optimization frame.
A parametric FEM model generator was developed under periodic boundary conditions in order to obtain buckling modes and corresponding failure criterions during the parameter variation. The shear angles of the fibers arising due to draping process were considered as production constraint and represented with the surrogate model by RBF-ANN in the optimization loop.
This method presents an optimization frame that covers the production failures of draping process and its influence on structural design. Furthermore this optimization process can be modified with other undetermined production constraints that are predicted by simulation.
REFERENCES
[1] K.Lindhorst, M. C. Haupt, P. Horst, “ Usage of time domain surrogate model approaches for transient, nonlinear aerodynamics within aero-structural coupling schemes” presented in"30th AIAA Applied Aerodynamics Conference", 25-28th June 2012, New Orleans, USA
This paper proposes a global optimization process on an innovative CFRP fuselage panel which simultaneously covers stability criterion and draping simulation of fiber textiles that is considered as a manufacturing effect. Genetic algorithms were chosen as an optimization technique to reach global optima. During the optimization process, a modified Response Surface Method that is based on artificial neural networks (RBF-ANN) [1] is carried out in order to reduce the computational effort and to couple the simulation inputs and outputs in the optimization frame.
A parametric FEM model generator was developed under periodic boundary conditions in order to obtain buckling modes and corresponding failure criterions during the parameter variation. The shear angles of the fibers arising due to draping process were considered as production constraint and represented with the surrogate model by RBF-ANN in the optimization loop.
This method presents an optimization frame that covers the production failures of draping process and its influence on structural design. Furthermore this optimization process can be modified with other undetermined production constraints that are predicted by simulation.
REFERENCES
[1] K.Lindhorst, M. C. Haupt, P. Horst, “ Usage of time domain surrogate model approaches for transient, nonlinear aerodynamics within aero-structural coupling schemes” presented in"30th AIAA Applied Aerodynamics Conference", 25-28th June 2012, New Orleans, USA