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

Slides:



Advertisements
Similar presentations
Metrics and Databases for Agile Software Development Projects David I. Heimann IEEE Boston Reliability Society April 14, 2010.
Advertisements

Object-Oriented Application Frameworks Much of the cost and effort stems from the continuous re- discovery and re-invention of core concepts and components.
DELOS Highlights COSTANTINO THANOS ITALIAN NATIONAL RESEARCH COUNCIL.
Integrated Design for Production to Ensure Sustainability in Marine Transportation Matthew J. Streeter- Faculty of Engineering and.
Advanced Manufacturing Laboratory Department of Industrial Engineering Sharif University of Technology Session # 14.
University of Minho School of Engineering Institute for Polymer and Composites Uma Escola a Reinventar o Futuro – Semana da Escola de Engenharia - 24 a.
Damage and Optimization Models for Analysis and Design of Discontinuous Fiber Composite Structures Ba Nghiep Nguyen Acknowledgements: PNNL’s Computational.
Aug 9-10, 2011 Nuclear Energy University Programs Materials: NEAMS Perspective James Peltz, Program Manager, NEAMS Crosscutting Methods and Tools.
DESIGN & CAE ACTIVITY Montecarlo, June CAE Design approach to develop applicative solutions in automotive polymer based systems CAE Design approach.
CAE Simulation software provides tools that help manufacturers validate and optimize the design of plastic parts and injection molds by accurately predicting.
Crashworthiness and High Strain Rate Material Testing Test Development for Vehicle Crash Conditions Motivation: The current vehicle design approaches result.
Software Process Models
ACMTRL Collaborative Research: James Sherwood Jennifer Gorczyca University of Massachusetts Lowell Collaborators: Northwestern University Enhancing the.
SIXTH FRAMEWORK PROGRAMME PRIORITY [6.2] [SUSTAINABLE SURFACE TRANSPORT] DEVELOPMENT OF BEST PRACTICES AND IDENTIFICATION OF BREAKTHROUGH TECHNOLOGIES.
M. Cengiz Altan School of Aerospace and Mechanical Engineering The University of Oklahoma NSF/DOE/APC Workshop Future of Modeling in Composites Molding.
Training Manual Aug Probabilistic Design: Bringing FEA closer to REALITY! 2.5 Probabilistic Design Exploring randomness and scatter.
P. H. Foss GM Research and Development Performance Modeling of Polymer Composites Pete Foss Materials and Processes Lab General Motors Research and Development.
Optimal Design for Molded Composite Products and Processes Douglas E. Smith University of Missouri at Columbia NSF/DOE/APC Workshop Future of Modeling.
Design and Optimization: Status & Needs Dr. Wei Chen Associate Professor Integrated DEsign Automation Laboratory (IDEAL) Department of Mechanical Engineering.
1 Dr. Frederica Darema Senior Science and Technology Advisor NSF Future Parallel Computing Systems – what to remember from the past RAMP Workshop FCRC.
April 15, 2005Department of Computer Science, BYU Agent-Oriented Software Engineering Muhammed Al-Muhammed Brigham Young University Supported in part by.
Milestones: Sensors, Control and Automation Group NSF/DOE/APC Workshop: The Future of Modeling in Composites Molding Processes June 9-10, 2004.
Modeling of Natural Fiber- Thermoplastic Composites Manufactured with Molding Processes Laurent Matuana Workshop: Future of Modeling in Composites Molding.
JMG NSF/DOE/APC Future of Modeling in Composites Molding Processes Workshop Sensing, Controls and Automation Group June 9-10, 2004 John M. Griffith.
End-to-End Design of Embedded Real-Time Systems Kang G. Shin Real-Time Computing Laboratory EECS Department The University of Michigan Ann Arbor, MI
Mgw DELPHI RESEARCH LABS DELPHI RESEARCH AREAS u SHORT FIBER REINFORCED THERMOPLASTICS –Fiber orientation and length distribution measurements and predictions.
Improved Fiber Orientation Predictions for Injection Molded Composites Charles L. Tucker III and Jin Wang Department of Mechanical and Industrial Engineering.
State of Kansas Statewide Financial Management System Pre-Implementation Project Steering Committee Meeting January 11, 2008.
Engineering or Mechanical Engineering?
Power Extraction Research Using a Full Fusion Nuclear Environment G. L. Yoder, Jr. Y. K. M. Peng Oak Ridge National Laboratory Oak Ridge, TN Presentation.
2.1.4 High Fidelity Design Tool Development Probabilistic Part Life Methods/Material Requirements Definition Science & Technology Objective(s):
J. McPherson; October Sensitivity of Carbon/Epoxy Laminates to Void Content A Thesis Proposal Submitted to the Graduate.
CRESCENDO Full virtuality in design and product development within the extended enterprise Naples, 28 Nov
GOLD Guaranteed Operation and Low DMC SEAMLESS AIRCRAFT HEALTH MANAGEMENT FOR A PERMANENT SERVICEABLE FLEET Birmingham (UK) December 05, 2007.
Schedule (years) Design Optimization Approach for FML Wing Structure Background The aerospace industry is gaining significant interest in the application.
Lecture 9: Chapter 9 Architectural Design
IT Requirements Management Balancing Needs and Expectations.
PRIVÉ ET CONFIDENTIEL © Bombardier Inc. ou ses filiales. Tous droits réservés. SMART TESTING BOMBARDIER THOUGHTS FAA Bombardier Workshop Montreal
Business Process Change and Discrete-Event Simulation: Bridging the Gap Vlatka Hlupic Brunel University Centre for Re-engineering Business Processes (REBUS)
© 2012 xtUML.org Bill Chown – Mentor Graphics Model Driven Engineering.
1 Introduction to Software Engineering Lecture 1.
CRESCENDO CRESCENDO Philippe HOMSI Paul WEBSTER
Software Engineering Prof. Ing. Ivo Vondrak, CSc. Dept. of Computer Science Technical University of Ostrava
©Ian Sommerville 2004 Software Engineering. Chapter 28Slide 1 Chapter 28 Process Improvement.
Framework for MDO Studies Amitay Isaacs Center for Aerospace System Design and Engineering IIT Bombay.
FDT Foil no 1 On Methodology from Domain to System Descriptions by Rolv Bræk NTNU Workshop on Philosophy and Applicablitiy of Formal Languages Geneve 15.
Design, Optimization, and Control for Multiscale Systems
Chapter 27 The Engineering Design Process. Learning Objectives Describe the various factors that are changing the design process Discuss the steps in.
Advanced Simulation Techniques for the coupled Fatigue and NVH Optimization of Engines. K+P Software, Schönbrunngasse 24, A Graz / Austria Tel.:
Operations Research The OR Process. What is OR? It is a Process It assists Decision Makers It has a set of Tools It is applicable in many Situations.
Architecture View Models A model is a complete, simplified description of a system from a particular perspective or viewpoint. There is no single view.
Probabilistic Design Systems (PDS) Chapter Seven.
Robust Design: The Future of Engineering Analysis in Design
On scale effects in composite modeling Larissa Gorbatikh Department of Mechanical Engineering The University of New Mexico Co-Sponsored by the National.
Advanced Software Engineering Lecture 4: Process & Project Metrics.
High Risk 1. Ensure productive use of GRID computing through participation of biologists to shape the development of the GRID. 2. Develop user-friendly.
BG 5+6 How do we get to the Ideal World? Tuesday afternoon What gaps, challenges, obstacles prevent us from attaining the vision now? What new research.
One Team: Relevant... Ready... Responsive... Reliable Basic Research Program Particle-Scale Distribution of Soil Moisture in Porous Media 24 January 2007.
Thermal and Building Systems Thermo-fluid systems dynamic modeling Environmental friendly refrigerants and cycles Integrated building/HVAC modeling Building.
Panel Discussion: Discussion on Trends in Multi-Physics Simulation
Integrating MBSE into a Multi-Disciplinary Engineering Environment A Software Engineering Perspective Mark Hoffman 20 June 2011 Copyright © 2011 by Lockheed.
WP3. Optimization using computer methods properties of new materials and structural elements made of them Brief description of the WP3 Jānis Šliseris Senior.
The Systems Engineering Context
Complexity Time: 2 Hours.
OPTIFRAME : Project Overview
MURI Annual Review Meeting Randy Moses November 3, 2008
postgrad. Sergiy Korotunov prof. Galyna Tabunshchyk
Atomistic simulations of contact physics Alejandro Strachan Materials Engineering PRISM, Fall 2007.
Composites virtualization
Presentation transcript:

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

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

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

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

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

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

1.Address clearly the heterogeneous nature of composite materials

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

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

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

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)

Specific numerical issues in BEM