Strengthening the materials core of manufacturing enterprises
Materials in simulation
Materials in simulation
Practical knowledge for simulation professionals who need to understand how material behavior is tested, modeled, and represented in FEA.
We discuss developments in viscosity modeling. New models are not generalized, but are designed to predict expected trends for polymers and incorporate both Newtonian and shear-thinning behavior.
Read full post"Today the automotive industry is faced with the demand to build light fuel-efficient vehicles while optimizing its crashworthiness and stiffness. A wide variety of new metallic and polymeric materials have been introduced to account for these increased requirements. Numerical analysis can significantly support this process if the analysis is really predictive. Within the numerical model a correct characterization of the material behaviour – including elasto-viscoplastic behaviour and failure - is substantial. The particular behaviour of each material group must be covered by the material model. The user material model MF GenYld+CrachFEM allows for a modular combination of phenomenological models (yield locus, strain hardening, damage evolution, criteria for fracture initiation) to give an adequate representation of technical materials. This material model can be linked to LS-DYNA when using the explicit-dynamic time integration scheme. This paper gives an overview on the material characterization of ultra high strength steels (with focus on failure prediction), non-reinforced polymers (with focus on anisotropic hardening of polymers), and structural foams (with focus on compressibility and stress dependent damage evolution) with respect to crash simulation. It will be shown that a comprehensive material model - including damage and failure behaviour - enables a predictive simulation without iterative calibration of material parameters. A testing programme has been done for each material group in order to allow a fitting of the parameters of the material model first. In a second step different component tests have been carried out, which were part of a systematic procedure to validate the appropriate predictions of the crash behaviour with LS-Dyna and user material MF_GenYld+CrachFEM for each material group."
Read full postThe use of CAE in design decision-making has created a need for proven simulation accuracy. The two areas where simulation touches the ground are with material data and experimental verification and validation (V&V). Precise, well designed and quantitative experiments are key to ensure that the simulation initiates with correct material behavior. Similar validation experiments are needed to verify simulation and manage the risk associated with this predictive technology.
Read full post"A general purpose orthotropic elasto-plastic computational constitutive material model has been developed to accurately predict the response of composites subjected to high velocity impact. The three-dimensional orthotropic elasto-plastic composite material model is being implemented initially for solid elements in LS-DYNA® as MAT213. In order to accurately represent the response of a composite, experimental stress-strain curves are utilized as input, allowing for a more general material model that can be used on a variety of composite applications. The theoretical details are discussed in a companion paper. This paper documents the implementation, verification and validation of the material model using the T800-F3900 fiber/resin composite material."
Read full postAs the demand for functional integration and the need of design differentiation in manufactured products increase, the complexity of plastic parts increases as well; thus some previous knowledge on effective ejection systems becomes insufficient and the challenges in the design of ejection systems grow consistently.
Read full postThere is interest in quantifying the differences between simulation and real life experimentation. This kind of work establishes a baseline for more complex simulations bringing a notion of traceability to the practice of CAE. We present the use of digital image correlation as a way to capture strain fields from component testing and compare these to simulation. Factors that are important in ensuring fidelity between simulation and experiment will be discussed.
Read full postMolding Views, brought to you by the Injection Molding Division of the Society of Plastics Engineers
Read full postThermoplastic materials are one of the largest categories of materials to be injection molded. Moisture-sensitive materials can lead to issues in the molding process. Simulation of the injection molding process requires sophisticated and exact material properties to be measured. This presentation discusses the testing required to characterize a thermoplastic material for use in SIGMASOFT, as well as the effects of moisture on viscosity measurement of a moisture-sensitive material. Consequences of basing designs on wet or dry materials are covered. Implementation of material data into the software to produce a successful injection molding simulation simulation is described.
Read full postAs part of Cornell University's mechanical engineering curriculum and study of classical beam theory, an aluminium beam is deformed to a specific load. Theoretical strains are calculated at certain points along the beam using beam theory, and then verified by using strain gauges placed at these points on the beam. This experiment is then extended to simulation of the same test setup in simulation software, where strains are analyzed at the same points. Discrepancies between the simulation, theory, and strain gauge results have often plagued the test, especially when incorporating more complex beam design. Through use of digital image correlation (DIC) it is possible to pinpoint some of the problem areas in the beam analysis and provide a better understanding of the localized strains that occur at any point in the deformed beam. The use of DIC provides a full field validation of simulation data, rather than a single spot check that strain gauges can provide. This validation technique helps to eliminate error that is associated with strain gauge placement and the possibility of missing strain hot spots that can arise when analyzing complex deformations or geometries.
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