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TRANSCRIPT
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Composite Materials Simulation and Modeling for Enhanced Lightweight
Body StructuresVenkat Aitharaju, William R. Rodgers
General Motors Global Research and Development02/20/2019
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Outline• Mass Breakup of an Automobile• Automotive Lightweighting• Composites in the Vehicle Body• Challenges for Composites Automotive Structures• Predictive Models for Composites• Extension of Simulation Models• Conclusions
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Mass Breakup of an Automobile
Body structures comprise the highest fraction of vehicle body Electric vehicles are likely to be heavier, light weighting is critical to increase the range and competitive advantage between different OEM’s
20%
6%
8%6%
10%17%
33%
Typical Gas Powered Vehicle
Body structureBody closurePowertrainExteriorInteriorChassisBattery
31%
10%32%
9%
18%
Typical Electric Vehicle
Body structureBody closurePowertrainExteriorInterior
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Mass Breakup of an Automobile• Body structure is one of the heaviest pieces of the vehicle and
therefore poses a significant opportunity for lightweighting for improved fuel economy and reduced emissions.
• For battery powered vehicles, added battery weight requires increased lightweighting from the structures for increased range and efficiency.
Due to these extraordinary demands posed by next generation vehicles, composites are being considered seriously for the next level of lightweighting.
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Automotive LightweightingPotential lightweighting materials over current steel:
High strength steels: 10 to 15%, Glass fiber composites: 20 to 30%,Aluminum : 25 to 35%,Magnesium 35 to 50%,Carbon fiber composites: 50 to 65%.
Composites have a major role to play in mixed material strategies for lightweighting.
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Composites in the Vehicle Body
Closures – several applications are already on record using sheet molding compounds (SMC) and continuous carbon fiber thermosets.
Underbody – few applications are seen in the industry – Example, I3.
Structure – in I3 and I7, race cars and some premium vehicles.
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Challenges for Composites in Automotive Structures
Multiple Design options – fiber types, matrix, etc.
Multiple process options – RTM, compression molding
Performance requirements - crash, durability
Variability - material, process, joining, final performance
Numerical models to predict accurately the behavior of composites is the key and it will only meet the automotive design time lines. This will only enable large scale implementation of composites in structural areas of automobile!
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Predictive Models for Composites• Manufacturing • Structural performance• Stochastics Manufacturing has a strong influence on the performance.
An integrated approach for modeling, including both manufacturing and structural performance, will optimize the design.
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Stochastic manufacturing engine(PAM-RTM, PAM-
FORM, PAM-DISTORTION)
Optimization for mass, cost and performance
(Isight)
Stochastic performance engine(LS-DYNA)
PDF of Manufacturing
material property data
PDF of process parameters
PDF of Mechanical
property input data
PDF of fill time, fiber angles,
residual stress, degree of cure.
Multiscale Designer
PDF of performance
Input
output
Integrated Process Flow for Accurate Predictive Tools – GM Development
Manufacturing output is critical input for structural simulation
Variability is accounted for by working with the probability distribution functions of the data
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ICME Components - Composites
Materials Process
Design
Experiments, mechanics theory, computational models are integrated underICME framework.
Fluid infusion in porous mediaFluid viscosityThermal effectsResin curingAir pockets, residual stressesFiber angle changes
Fracture criteriaProgressive failure modelsSimulation process
FiberResin Fiber sizingTow architecturesPrepregThermoplastic sheetMaterial characterization
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Manufacturing MethodsThermosets:• Resin transfer molding – a) traditional b) C-RTM c) HP-RTM• Prepreg compression molding• Filament winding• Pultrusion• Sheet molding compoundsThermoplastics• Compression molding• Tape Laying/Compression Molding
Resin transfer molding and prepreg compression molding are high volumemanufacturing methods for automotive composites considered.
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Modeling Challenges For HP-RTMDraping• Non-crimp fabric behavior including stitch behaviorInjection• Coupled fluid flow, heat transfer from exotherm, resin viscosity and curing changes• Fluid structure coupling at high injection pressures• Permeability change as fabrics shearCuring• Polymer curing, exothermDemolding• Structural problem under residual stresses – mismatch of CTE of fiber and resin,
cooling down
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HP-RTM• Injection strategy should enable the use of fast curing resin (fill times
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Structural Performance Models –Multiscale Models
Fibrous Woven
NCF
Chopped 2D Chopped 3D
Random
Square LatticeHoneycomb
Lattice Plain Weave 8 Harness Weave4 Harness Weave
Multi-scale Approach
Nonlinear plasticity of resinReduced Order Models – Unique development
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An Impact Beam – Sled Test
Top View
Side ViewTop View
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Intrusion Beam (Sled Test): Comparison of Simulation and experiment
ExperimentSimulation
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Intrusion Beam (Sled Test)
Force-Displacement
Very good match given thecomplexity of the shape and test parameters
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Damage Comparison (Sled Test)
Expe
rimen
t
Sim
ulat
ion
Top
Bottom
Side
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Stochastic Models• Variability is endemic in composites – from materials,
process, structural design, to performance.• Understanding the variability influencing the final
performance is critical in the design, monitoring.• From modeling side, variability of each of the
parameter increases the computational expense enormously.
• Very few developments to date are available!
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Stochastic Models• GM and USC are working together to develop state of
the art models to include stochastic parameters for both manufacturing and structural performance.
• Polynomial chaos expansion (PCE) methods were used to create the developments and several problems were evaluated. These are computationally efficient compared to Latin Hypercube and Mano-Carlo Methods.
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Stochastic Manufacturing - Draping, Injection, Curing and Demolding
A total of 74 variables were considered in this integrated problem. This problem is computationally challenging and was solved using state of the art methods developed in this project at USC.
Draping Injection Curing Distortion
Stochastic Variables
Initial orientation of fabric (5D)Elasticity of fibers (4D)Draping process (2D)
Mechanical and thermal properties of resins (18D)Temperature boundary conditions (3D)
FiberOrientations, permeabilityas function ofOrientation
Parameters dictating the curing kinetics (8D)Temperature cycle (1D)
Ply mechanical, thermal, and chemical properties (33)
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Specially Varying Fields –Model Development Elasto-plastic response
𝜎𝜎 = 𝐾𝐾 𝜀𝜀𝑛𝑛
• Spatial correlation length corresponds to RVE of unit cell or microstructure• Models are still computationally efficient!
𝑛𝑛
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Extension of Simulation Models• Accurate simulation models not only provide ways to
optimize the design, manufacturing process, maximize the through-put, etc., but also provide a clear picture of business case of cost modeling.
• Cost modeling utilizes essential features of simulation such as process planning, operation, required tooling, and labor. This provides an upfront understanding of the business case.
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Cost Modeling
Crucial data from process simulation
• Process steps• Preform size• Cycle time• Press selection
Empirical + Experience
• Die cost based on volume• Automation• Floor space• % of scrap• downtime• Press allocation• maintenance
Software – Siemens PlantSim(very recent software in development)
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Software – Siemens PlantSim4 major components of the an assembly
Cutting/Lay-upOvens for Pre-forming (2 molds per oven)
Preform trimming
Final RTM Molding Press
Final Trim
Final Assembly
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Conclusion
• Composites offer significant lightweightingopportunities that are not yet completely explored.
• Development of predictive tools for composites is a must for large scale implementation to achieve the next level of lightweighting.
• Significant efforts are ongoing to improve the predictability of simulations models.
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Acknowledgments• Satvir Aashat• Ali Seyed Yaghoubi• Gurpinder Dhaliwal• Selina Zhao• Praveen Pasupuleti• Roger Ghanem• Jacob Fish
Composite Materials Simulation and Modeling for Enhanced Lightweight� Body StructuresOutlineMass Breakup of an AutomobileMass Breakup of an AutomobileAutomotive LightweightingComposites in the Vehicle BodyChallenges for Composites in Automotive StructuresPredictive Models for CompositesSlide Number 9ICME Components - CompositesManufacturing MethodsModeling Challenges For HP-RTMSlide Number 13Structural Performance Models – Multiscale ModelsAn Impact Beam – Sled Test Intrusion Beam (Sled Test): Comparison of Simulation and experimentIntrusion Beam (Sled Test)Damage Comparison (Sled Test) Stochastic ModelsStochastic ModelsStochastic Manufacturing - Draping, Injection, Curing and DemoldingSlide Number 22Extension of Simulation ModelsCost Modeling Slide Number 25ConclusionAcknowledgments