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Presentation Summary: Design and Optimization Group NSF/DOE/APC Workshop: The Future of Modeling in Composites Molding Processes June 9-10, 2004.

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Presentation on theme: "Presentation Summary: Design and Optimization Group NSF/DOE/APC Workshop: The Future of Modeling in Composites Molding Processes June 9-10, 2004."— Presentation transcript:

1 Presentation Summary: Design and Optimization Group NSF/DOE/APC Workshop: The Future of Modeling in Composites Molding Processes June 9-10, 2004

2 Vision The development and implementation of a comprehensive composites design environment that generates the geometric configuration, component materials, and processing schedule for industrial products. Design tool to be based on validated simulations, and address uncertainty in the product’s use, its processing, and models used to assess each, and provide desirable performance over its entire life cycle. Composite Design Attributes Usability Extendibility Durability Dimensional stability Reliability Manufacturability Serviceability Recycle ability Disposability etc… cradle to grave length scale Product Design Process Design Material Design

3 Product/Process Design Example Integrated product and process design for short fiber reinforced polymer composites Stiffness and strength defined by fiber direction during manufacturingStiffness and strength defined by fiber direction during manufacturing IPPD enabling technologiesIPPD enabling technologies mold filling fiber orientation material properties product performance polymer melt flow analysis static stress analysis modal analysis thermal stress analysis mold filling simulation fiber orientation prediction material property calculation mold cooling analysis warpage simulation numerical optimization design sensitivity analysis multidisciplinary design methodologies structural optimization

4 State of the Art Numerous software / algorithms available for numerical optimization –VDoc/DOT, ISight, Hyperopt, LMS Optimus, Dakota, IMSL, Excel, Matlab, IMSL, Minpack, etc…. Structural optimization well established –Sizing, Shape, and Topology Metamodeling techniques reduce cost of simulation-based design Enterprise-Driven Multidisciplinary Design Optimization (MDO) developed for niche applications, e.g., aeroelasticity, automotive body structure, etc… Non-deterministic approaches address uncertainty in design –Reliability Analysis Methods, Robust Design, Reliability-Based Design, etc… Optimization and design sensitivity analysis methods developed for numerous manufacturing applications MPP  f(u 1, u 2 ) u1u1 u2u2 g=0 pdf

5 Perceived Gaps Common language needed across materials scientists, product designers, manufacturing process engineers, etc. Validated models needed for all aspects of composites processing –E.g., strength and stiffness prediction from flow simulation Design sensitivities not developed to level of analyses –Fiber orientation –Mechanical properties from process models –Non-isothermal flow, reactive flow Integrated design methodologies not available to end user Optimal design applications are task or discipline focused –I.e., Multidisciplinary design methods rarely not applied to composite molding problems Nondeterministic approaches not applied to composite molding problems

6 Future Research Further develop/validate composite molding process/product models and validate optimization results Development of language/representations for seamless communication Efficient optimization methods that incorporate multidisciplinary variable- fidelity simulation models Development of a user-oriented composites molding design environment –Incorporate design knowledge and experience –Further develop DSA methods for composites molding –Incorporate multidisciplinary design methodologies –Incorporate design under uncertainty tools –Include process control in optimal process design Application / Validation on industrial scale problems under distributed and collaborative design environment

7 1.Address clearly the heterogeneous nature of composite materials

8 2.Identify “defects” or “features” of interest for modeling and design - porosity - texture - interface imperfections - fiber clustering - fiber misalignment

9 3.Develop “metamodels” expressing the effect of microstructure on “performance” or “properties” Multi-scale modeling and topology optimization

10 Experimental/modeling approach Evolve from experimentally-based empirical models  physics-based models Reduce number of experiments required to validate models Length scales for homogenization

11 Some Specific Topics Micromechanics –Process micromechanics: Effects of fiber content, length on the rheology and fiber orientation –Micromechanics of materials: Homogenization accounts for interaction between constituents and defects Continuum mechanics: Need of constitutive models for –Fatigue –Time dependent behaviors (creep, relaxation,..) –Impact –Moisture –Crashworthiness Nonlinear behaviors –Minimization of damage –Improvement of durability (fatigue, creep)

12 Specific numerical issues in BEM


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