Numerical Simulation as tool for development of prototypes (virtual try ... · PDF fileNumerical Simulation as tool for development of prototypes (virtual try-out space) Luděk Kovář

Industry Sector RTD Thematic Area Date

Land Transport Product & System Optimisation 13.11.2001

Numerical Simulation as tool for development of prototypes (virtual try-out space)

Luděk Kovář

MECAS ESI, Pilsen, Czech Republic

Summary: An overview on some recent trends and advances in virtual prototyping and crash simulation oftransport vehicles is given. This overview highlights selected algorithmic solver code advances in theused simulation tools, the use and the modeling of new materials for crash energy absorption, concept car design techniques, massive parallel programming and performance gains, side impact barriermodeling, mechanical occupant surrogate modeling (dummies), biomechanical models human body,as well as extensions of crash simulation techniques to the simulation of drop tests, shock absorption, etc. The shown examples and descriptions testify the extreme progress and diversification crashsimulation techniques have undergone in the past ten years.

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1 Introduction A modern crash simulation software package consists of pre- and post-processing modules and of a numerical solver module. The beneficial industrial use of a crash simulation package depends not only on the effectiveness of the numerical solver code, but to a large extent also on the quality, effectiveness and user-friendliness of the associated pre- and post-processing modules. Two such modules, PAM-GENERIS™ (pre-processing) and PAM-VIEW™ (post-processing) are presently offered with the PAM-SOLID™ solver codes. At the time of writing, both modules undergo extensive restructuring and enhancements that are necessary to assure the full industrial applicability and success of the simulation package. This paper concentrates on recent advances and trends of the numerical solver code, PAM-CRASH™, a member of the PAM-SOLID™ family of codes. The PAM-SOLID™ family of codes consists in PAM-CRASH™, the PAM-SAFE™ occupant safety analysis code, the PAM-STAMP™ sheet stamping code and the PAM-SHOCK™ impact and high frequency response analysis code. The industrial simulation of vehicle crash events has started with the first successful VW Polo frontal crash overnight simulation on a CRAY 1 computer, using PAM-CRASH™. Meanwhile all major passenger car makers employ crash simulation to assist them in the design of crashworthy vehicles, and the simulation of impacts of different natures has spread to other branches of industry (truck crash, railway car crash, container drop, packaging design, airplane crash, etc.). The next logical step has been to extend the methodology to the simulation of passenger safety via the modeling of passive safety devices such as airbags, seat belts, etc., that restrain models of vehicle occupant surrogates (dummies) during crash events. Progress in modeling techniques for dummies has lead to several generations of dummies, followed by biological models of human body. Moreover, the used explicit finite element technique is now being applied to related processes, such as thin sheet metal forming, thermoplastic composite shell forming, pressure and hydroforming, etc., that benefit from the numerical techniques elaborated for large strain/large displacement nonlinear material/ dynamic analyses of structures, modeled by large numbers of thin shell finite elements. The success of the explicit thin shell modeling technique is now reinforced by porting the codes to massively parallel computers that will bring supercomputer power into the design departments, and by increased porting to inexpensive PC-level workstations that will make crash simulation accessible to the smallest suppliers.

2 Algorithmic Advances Despite a considerable level of industrial efficiency and robustness reached by the modern explicit finite element crash simulation solver codes, there is still much room for algorithmic improvements and advances. Some of such efforts are outlined next.

2.1 CONTACT SIMULATION

It should be mentioned that the correct and robust simulation of physical contacts in crash simulation is a prerequisite of its success. Notoriously, however, contact simulation still belongs to the most challenging and complex tasks of programming, not only in mono-processor (or shared memory parallel) code versions, but, in particular, in massively parallel programs using distributed memory. In the first case "rigid wall" constraint or "sliding interface" treatments of contact must be streamlined as much as possible to be computationally efficient, while not loosing accuracy and robustness. For sliding interface type contact algorithms the proven penalty method is the most widely used, and today development efforts aim at rendering this method as transparent as possible to the end user, including the difficulty to achieve success criteria of both, computational efficiency and robustness. For massively parallel programming, the explicit finite element programs are readily parallelized using effective techniques of automatic domain decomposition, where each of the parallel processors is assigned to work on similar chunks of the model with a minimal amount of communication required with other processors. Since contact domains are not static by definition (initially remote parts of the structure do become connected as the structure deforms), initial domain decompositions can quickly become obsolete and the calculation of contacts can lead to serious communications overheads and load-imbalances between processors. For these reasons, the major efforts in massively parallel ports



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of crash simulation codes goes into the effective parallelization of contact algorithms and is pursued actively.

2.2 ADAPTIVE MESHING

In crash simulation of thin-walled components and structures, adaptive meshing techniques aim at automatic local refinements of thin shell finite element meshes near areas of large deformations. In the simulation of industrial sheet metal stamping this problem has been solved, and the PAM-STAMP™ member of the PAM-SOLID™ family of simulation codes is equipped with industrial options of uniform and automatic adaptive thin shell mesh refinement and derefinement. The first reason why adaptive meshing algorithms are more difficult to implement for crash simulation is that mesh adaptivity must be made compatible with a wider variety of contact treatments and rigid wall contact/impact options. Although contact is the principal driving mechanism in sheet stamping, its treatment is simpler due to the imposed tool geometries and the virtual absence of sheet self-contact. In crash simulation, self-contact is often preponderant but less amenable for implementation with automatic adaptive meshing. The second reason why the utilization of adaptive meshing may be less obvious, even dangerous, in crash simulation is the possibility of localization of plastic hinges or crush zones. The reason for such localization may reside in the fact that refined mesh areas become numerically less stiff than the original coarser grid, which is exactly what is expected, but that subsequent plastic hinges and crush zones in the not yet refined mesh may be masked by the added flexibility or reduced numerical resistance of the refined areas, which is an undesirable effect. The refinement criteria must therefore be chosen carefully, and the original mesh must not be too coarse in order to avoid such localization.

3 Material Models More and more emphasis is given to the design, calibration and validation of material models for the description of the behavior of aluminum alloys, plastics, foams, rubbers and composites. Material models that describe the behavior of all these types of materials are available in the PAM-SOLID™ code family, and some models are highlighted below.

3.1 GENERAL ELASTO-PLASTIC/STRAIN RATE/DAMAGE MODEL

Several isotropic and anisotropic elasto-plastic with strain-rate dependent plasticity and damaging material models are implemented for the finite elements of the PAM-SOLID™ family. This approach can be applied in principle to any type of material. The basic undamaged stress-strain law, ( )pεσ 0 with a small or zero reference strain rate, is post-multiplied by a strain rate dependency function, ( )ppf εε &, and by a damage function, ( )( )pdg ε , where the damage parameter ( ) 10 ≤≤ pd ε and

. The strain-rate function tends to increase the yield stress and the damage function reduces the material resistance. The indicated general damage description is due to Lemaitre-Chaboche and applies to arbitrary materials (metals, plastics, composites, foams, etc.). For ductile metals, the Gurson damage law is implemented. It acts on plastic strain and translates the effects of nucleation, growth and finally coalescence of micro-voids on the material behavior.

dg −= 1

3.2 ALUMINUM ALLOYS

The plastic behavior of aluminum alloys can be described by the Hill 1990 non-quadratic yield function for anisotropic materials. This law has been implemented in the PAM-STAMP™ member of the PAM-SOLID™ family and it has been applied to the simulation of deep drawing of aluminum sheets.

3.3 PLASTICS

Elasto-plastic material model with possible elastic stiffening, common in plastics, can be considered. For a purely softening true stress-strain law plastic instability ("necking") occurs as soon as the



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numerical value of the plastic stress, σ , falls to the value of the tangent modulus, . This instability soon leads to localization of plastic strain and specimen rupture after the plastic strain has reached a specified rupture limit. The original plastic hardening curve is modified for realistic behavior of plastics to stiffen for higher plastic strains, which limits the plane-stress condition of necking,

TE

TE=σ , to the

range 21 εεε << . The original neck develops as before, but it is now arrested by the stiffening of the material after the finite elements of the necked area have been stretched beyond a plastic strain value

2ε . The neck then can spread to the neighbor elements.

3.4 MORE MATERIALS

For the description of side impact barriers, paddings, flesh foam of mechanical dummies, etc., a variety of foam materials is available in the PAM-SOLID™ package that can adequately model the collapse, compaction, viscous, hysteresis and rate-dependent behavior of these materials. For the description of rubbers and rubber-like materials in the modeling of tires, engine supports, parts of dummies, etc., a variety of hyper-elastic quasi-incompressible material models have been implemented. For the simulation of crash events that involve fiber and fabric reinforced composites, bi-phase brittle damaging material models have been implemented. New material models are added to answer the growing demand of more and more industry to cope with their specific products. Trade applications: Multi-trade solution Integrated solution (VTOS®):

Virtual testing Value chains Full virtual prototyping e.g. Crash-test e.g. Passenger safety e.g. Body in White Car body Manufacturing Body with trims

Testing Product

performance VP

Testing Usage Environment

VE Assembly

Safety Body-shop Crash

Parts

Tools Welding Stamp

Testing ManufacturingProcesses VM

On-going Present Future

Fig. 1 Evolution from trade applications to integrated solutions



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4 Trends in Virtual Prototyping Today a mature CAD world is ready to deliver to Production Industries a fully integrated solution encompassing CAD/CAM/CAE and PDM functionalities. Designated “Digital Mock-Up” (DMU) makes this solution available for the whole product on-line, with its individual parts and components described, selected and assembled on the computer. However try-out tools, process tuning and performance validation testing in the lab are still necessary using costly and time consuming real prototypes. Further industrial demand is therefore to numerically simulate the manufacturability of each new product including all its parts and assemblies, to fine tune the processes, and to predict and minimize the effects of fabrication defects and tolerances on the overall product performance. Important for this solution is to achieve a realistic modeling of material physics, describing engineering materials both in their “virgin” state from the producer, and in their modified “formed” state coming out of the fabrication processes. This is the goal of Virtual Manufacturing (VM). Existing PAM-SOLID™ family tools, which can be used to simulate processes of VM, can be seen in Fig. 2. Realistic modeling of the test configurations required for product certification as well as for verification of planned operation in a realistic usage environment, is the goal of Virtual Prototyping (VP). There is trend to include all numerical models of tested parts as realistic as possible, including “formed” state coming out as result of VM (coupling PAM-STAMP™ and PAM-CRASH™ or step further SYSWELD, tool for simulation of welding, with PAM-STAMP™ and PAM-CRASH™) (Fig. 1) on the one hand side and improve and enlarge group of material models to be able predict and accurately describe process of failure of critical parts on the other hand side. PAM-SOLID™ family codes applicable for VP projects solution can be seen in Fig. 3.

5 Safety Aspects Today try-out space direction and methods are followed by computer simulation, but we can expect new virtual testing procedures, which go step further in comparison with traditional testing approaches. Besides the development of deformable impact barriers (side and offset front), airbag models and models of mechanical dummies (Hybrid III, EUROSID, DOT-SID, BIOSID, Child Dummies, etc.) - (Fig. 4), biomechanical models of human parts and complete human model were introduced (Fig. 5). This activity will probably grow considerably in the near future, because simulation with calibrated biomechanical models appears to be the only way to evaluate the direct response of the human body to crash events. At ESI several such models are under further development.

6 Conclusions The major thrust areas for continued developments comprise the linking of the simulation packages into CAD systems, more material models, more accurate element formulations and contact algorithms, made possible through increased computing power, larger models, the use of multi-physics (e.g., thermo-coupling, solid-fluid interaction) and continued porting to massively parallel computers and clustered workstations. For detailed information visit http://www.esi.fr.

7 References [1] A. de Rouvray.: "CAE Trends in Virtual Prototyping and Manufacturing and ESI Group Business

Positioning", 9 th User Conference & Exhibition - EUROPAM 2000, Nantes, France, 2000 [2] Haug E., Clinckemaillie J., Ni X., Pickett A. K., Queckbörner T.: Recent Trends and Advances in

Crash Simulation and Design of Vehicles, ICD Symposium, University of Valenciennes, 1995



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http://www.esi.fr/

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Fig. 2 Virtual prototyping codes developed by ESI GROU

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Fig. 3 Virtual manufacturing codes developed by ESI GROU

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Fig. 4 Dummy family FE models



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Fig. 5 Biomechanical models, H-MODEL



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Numerical Simulation as tool for development of prototypes (virtual try ... · PDF fileNumerical Simulation as tool for development of prototypes (virtual try-out space) Luděk Kovář