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Best Practice – 4+1 errors in material modeling for FEM structural simulations and how to avoid them

Structural simulations are also an important design tool in the development of die-cast parts. Without them, design flaws that could lead to component failure would probably only be discovered during testing or even when the actual component is in use.

Like injection molding simulation, this simulation method contributes to accelerated product development, minimization of project and component costs, and increased product safety. However, the following errors should be avoided, especially in the area of material modeling of plastics for structural simulation:

  1. Overestimation of stiffness
    • Problem: A material model with fiber reinforcement is created using the official technical data sheet (TDS) and the information it contains about the modulus of elasticity, or at best reduced globally by a factor.
    • Explanation and consequence: The modulus of elasticity is determined on an injection-molded shoulder pull bar, which usually has a fiber orientation of ~80%. The assumed stiffness, i.e., 80% fiber orientation (or reduced by a factor), is applied globally to the model. The deformation results are not representative (overestimation or underestimation of stiffness).
    • Solution: Simulation with an anisotropic material model. Using an integrative simulation, the fiber orientation tensors are exported from the injection molding simulation and mapped to the component.

 

 

Image 1: Comparison of the deformations in sectional view between the isotropic structural analysis (left) and the two anisotropic calculations. One with a central injection point (center) and the other with the T-piece rotated by 90° (right).
  1. No consideration of temperature dependence
  • Problem: The mechanical properties of plastics are highly temperature-dependent and do not follow a linear pattern.
  • Explanation and consequence: Failure to model the exact temperature dependence leads to incorrect results in the simulation evaluation, in contrast to the actual thermal boundary conditions of the assembly that prevail later on.
  • Solution: The specifications created for the project should contain precise data and information (e.g., temperature collectives and worst-case load cases) so that temperature influences can be taken into account in the first simulation loops.
  1. Careless interpolation of measurement data
  • Problem: As already mentioned in point two, the influence of temperature on the mechanical properties of plastics is not easy to estimate and leads to errors if incorrect observations are made or temperatures are interpolated without careful consideration.
  • Explanation and consequence: While stress-strain curves behave predictably at temperatures well below the glass transition point Tg, for example, this behavior changes abruptly around Tg.
  • Solution: The glass transition temperature must be critically considered in the design. Under clear boundary conditions, tensile tests should be carried out experimentally at the appropriate temperature.
Image 2: Modulus of elasticity versus temperature of PPS-GF40
  1. Conversion of true/technical strain from test data
  • Problem: Since measuring true stress-strain values would be very time-consuming, only technical stress-strain values are usually recorded. However, due to the strong necking of plastics, these technical stress-strain curves are only suitable for evaluation at low strains. In addition, results from FEM simulations are generally considered to be true values.
  • Explanation & consequence: If this is not taken into account, stresses may be incorrectly estimated and the component may be incorrectly designed.
  • Solution: Scripts are suitable for taking into account technical and true stress/strain and for the corresponding conversion for the creation of material models and evaluations.

Bonus: Errors in the evaluation

Failure criteria and strength characteristics

  • Problem: While the comparative stress hypothesis has been used for evaluation and empirical values for strengths in metallic materials for around 100 years, this is not the case for plastics. In addition, process-related local inhomogeneous material structures must be considered more clearly, as these create weak points in the workpiece.
  • Explanation & consequence: If evaluation criteria are used incorrectly or if weld seams and flow lines are not taken into account, stresses in the material are incorrectly assessed and component failure can occur.
  • Solution: The new VDI 2016 (status: preliminary draft) provides a very good overview of the approach to strength assessment for plastic components. In addition, strength characteristics should always be determined in relation to the application (e.g., weld seam strengths under temperature).

Conclusion

Structural simulations are therefore an essential tool for designing injection molded parts and make a significant contribution to efficiency, safety, and cost-effectiveness in product development. However, typical errors can significantly impair the informative value of simulations, particularly when modeling plastics. The most common stumbling blocks include overestimating stiffness due to inadequately adjusted E-moduli, neglecting highly temperature-dependent material properties, and careless interpolation of measurement data. Incorrect interpretation of technical vs. true strain data and inappropriate strength criteria can also lead to misjudgments. The solution lies in a precise database, realistic modeling (e.g., anisotropic material models, temperature-dependent parameters), and practical validation. By taking these aspects into account, you can lay the foundation for robust simulation results and thus for reliable, cost-efficient plastic components. We would be happy to support you in your project with our expertise in modeling and simulation as well as with material data from our laboratory.

Advantages of working with BARLOG Plastics

  1. Accelerated product development: Close interdisciplinary cooperation between the necessary departments ensures targeted and reliable results.
  2. Extensive material and process know-how: Years of expertise enable efficient component development and early validation of technical solutions.
  3. Minimize project costs: Choosing the right simulation methods reduces development risks and helps avoid project costs due to late error detection.

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