Knowmats is an informal repository of information related to materials and simulation. The information helps simulation professionals perform best-in-class simulation with a better understanding of how materials are represented in FEA and simulation. read more...
July 11, 2013 | by Datapoint Newsletters | views 4813
Digital Image Correlation Techniques Enhance Composite Testing Capability. Store and Manage Properties of Structured Composites with a Matereality® Database.
May 15, 2007 | by Datapoint Newsletters | views 4800
Links to Datapoint Newsletters published 1995-2007
July 22, 2015 | by Paul Du Bois | views 4800
"Reliable prediction of the behaviour of structures made from polymers is a topic under considerable investigation in engineering practice. Especially, if the structure is subjected to dynamic loading, constitutive models considering the mechanical behaviour properly are still not available in commercial finite element codes. First, we give an overview of material laws for thermoplastics and show how the behaviour can be characterized and approximated by using visco-elasticity and metal plasticity, respectively. Experimental work is presented to point out important phenomena like necking, strain rate dependency, unloading behaviour and damage. A constitutive model including the experimental findings is derived. In particular, different yield surfaces in compression and tension and strain rate dependent failure, the latter with damage induced erosion, need to be taken into account. With the present formulation, standard verification tests can be simulated successfully. Also, an elastic damage model is used to approximate the unloading behaviour of thermoplastics adequately."
Mechanical Rate Dependency Yielding/Failure Analysis Automotive High Speed Testing LS-DYNA Research Papers
November 06, 2008 | by Datapoint Newsletters | views 4796
Simulation Tip: Interpreting Tensile Strength in the True Stress-Strain Environment. Partner Showcase: Abaqus.
October 29, 2013 | by DatapointLabs | views 4793
There 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.
Plastics Aerospace and Defense Automotive Biomedical Material Supplier Electonics/Electrical CAE Vendor/Supplier Nonlinear Material Models Structural Analysis Abaqus Composites SIMULIA Presentations
August 24, 2015 | by Massimo Nutini | views 4792
Optical strain measurement for the mechanical characterization of polymers, and in particular of polyolefins, is becoming a common practice to determine the parameters to be used in a finite element analysis of crash problems. This experimental technique allows measuring the strain locally on the specimen, so that it is particularly suitable when the deformation is localized, as in the case of polymers: therefore a more accurate description of the behaviour of the material is obtained. By so doing, it is possible to describe the material constitutive law in terms of the true, local strain and of the true stress. As these data are those needed by the most complete material models developed for impact calculation, it is clear that this technique is particularly suitable for coupling with the most advanced material models currently available in the F.E. codes, as for instance with Mat 187 (SAMP-1) of LS-Dyna. The local measurement of the strain can also be used for evaluating the volume strain, whose evolution with the increasing strain shows that for PP-based material the deformation is not isochoric in most the cases. The observed increase in the material volume reflects the fact that voids generate and coalesce within the material, possibly resulting in fracture. The measure of the volume strain, computed as the trace of the strain tensor, is here used for determining the damage function utilized by the damage model implemented in SAMP-1. The effective stress is here estimated as the stress which would be measured if the deformation was isochoric, and it can be assessed on the basis of the measurement of the longitudinal local strain only. Corresponding to each value of longitudinal strain, the volume strain is then used to calculate the ratio between the effective and the true stress. Adopting this procedure, the damage function is thus determined without the needs of repeated loading-unloading tests used to derive the damage parameter from the unloading slope, which is furthermore difficult to be measured. As an application, the results of the numerical reproduction of a benchmark test, consisting in a drop test on a polypropylene box, are presented and discussed
Mechanical Plastics Rate Dependency Yielding/Failure Analysis Automotive High Speed Testing LS-DYNA Research Papers
July 15, 2003 | by DatapointLabs | views 4788
Assurance of quality in raw materials, control over production, and a basic understanding of criteria for performance all require a sure and complete knowledge of analytical methods for plastics. The present volume organizes the vast world of plastics analysis into a relatively compact form. A plastics engineer will find familiar territory in such subjects as rheometry, differential scanning calorimetry, and measurement of thermal properties. Polymer physicists and chemists will be at home with spectroscopic analyses, liquid chromatography, and nuclear magnetic resonance. All these topics and many more are covered in twelve chapters written by an impressive array of experts drawn from industry and academia.
September 10, 2015 | by DatapointLabs | views 4786
Molding Views, brought to you by the Injection Molding Division of the Society of Plastics Engineers
Rheology Mechanical Injection Molding Moldflow Moldex3D SIGMASOFT Universal Molding Simpoe-Mold Newsletters
September 23, 2010 | by Datapoint Newsletters | views 4784
DatapointLabs Joins TechNet Alliance. ANSYS Chaboche Model. CAE-INPUT Decks Now Available for ANSYS Polyflow. Foam Modeling in ANSYS.
Foams Metals ANSYS POLYFLOW Blow Molding POLYFLOW Extrusion POLYFLOW Thermoforming Newsletters
July 31, 2015 | by Massimo Nutini | views 4783
Notwithstanding the increasing demand for polymeric materials in an extraordinary variety of applications, the engineers have often only limited tools suitable for the design of parts made of polymers, both in terms of mathematical models and reliable material data, which together constitute the basis for a finite-elements based design. Within this context, creep modelling constitutes a clear example of the needs for a more refined approach. An accurate prediction of the creep behaviour of polymers would definitely lead to a more refined design and thus to a better performance of the polymeric components. However, a limited number of models is available within the f.e. codes, and when the model complexity increases, it becomes sometimes difficult fitting the models parameters to the experimental data. In order to predict the polymer creep behaviour, this paper proposes a solution based on artificial neural networks, where the experimental creep curves are used to determine the parameters of a neural network which is then simply implemented in an Abaqus user subroutine. This allows to avoid the implementation of a complex material law and also the difficulties related to match the experimental data to the model parameters, keeping easily into account the dependence on stress and temperature. After a discussion of the selection of the appropriate network and its parameters, an example of the application of this approach to polyolefins in a simplified test case is presented.
Mechanical Plastics Automotive Biomedical Structural Analysis Abaqus Research Papers Validation
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