Strengthening the materials core of manufacturing enterprises
Materials in simulation
Topics covered: Damage in mineral filled polypropylene under impact conditions; damage modeling and parameter identification (prior art, LyondellBasell contributions, debate in the CAE community); experimental and numerical validation; next steps
Read full postThis book is intended to be a companion to the NAFEMS book, "An Introduction to the Use of Material Models in FE". It informs Finite Element Analysis users of the manner and methodologies by which materials are tested in order to calibrate material models currently implemented in various FEA programs. While the authors seek first to satisfy the basic material models outlined in the companion book, they make important extensions to FEA used in currently active areas including explicit simulation.
Read full postSimulations contain assumptions and uncertainties that a designer must evaluate to obtain a measure of accuracy. The assumptions of the product design can be differentiated from the ones for the solver and material model through the use of a mid-stage validation. An open loop validation uses a controlled test on a standardized part to compare results from a simulation to the physical experiment. From the validation, confidence in the material model and solver is gained. In this study, the material properties of a polypropylene are tested to characterize for an *ELASTIC *PLASTIC model in ABAQUS. A validation of a quasi-static three-point bending experiment of a parallel ribbed plate is then performed and simulated. A comparison of the strain fields resulting from the complex stress state on the face of the ribs obtained by digital image correlation (DIC) vs. simulation is used to quantify the simulation's fidelity.
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 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.
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 postThe limitations of modeling materials for simulation are discussed, including lack of clarity in material model requirements, gaps between the material data and the model to which it will be fitted, issues in obtaining pertinent properties, difficulties in parameter conversion (fitting), and preparation of input files for the software being used. Means to address these limitations are presented, including understanding the model completely, measuring the correct data with precision on the right material, selecting the best model for the data and ensuring the best fit of the model to the data, validating the model against a simple experiment, and following best practices to create an error-free input file.
Read full postOver the past couple of decades, standard test methods and material models have existed for rubber-like materials. These materials were classified under the category of Hyperelastic materials. Well established physical test methods and computational procedures exist for the characterization of the material behavior in tension, compression, shear volumetric response, tear strength etc. However, effective modeling of the fracture behavior of hyperelastic materials using finite element techniques is very challenging. In this paper, we make an attempt to demonstrate the use of such standard test methods and the applicability of such test data for performing finite element analyses of complex nonlinear problems using Abaqus. Our goal is to demonstrate the effective use of standard physical test data to model multi-axial loading situations and fracture of hyperelastic materials through tear tests and indentation test simulations.
Read full postHigh strain rate material modelling of polymers for use in crash and drop testing has been plagued by a number of problems. These include poor quality and noisy data, material models unsuited to polymer behaviour and unclear material model calibration guidelines. The modelling of polymers is thus a risky proposition with a highly variable success rate. In previous work, we tackled each of the above problems individually. In this paper, we summarize and then proceed to present a material modelling strategy that can be applied for a wide variety of polymers.
Read full postWe seek to lay down a framework to help us understand the different behavioral classes of foams. Following a methodology that we previously applied to plastics, we will then attempt to propose the right LS-DYNA material models that best capture these behaviours. Guidelines for model selection will be presented as well as best practices for characterization. Limitations of existing material models will be discussed.
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