April 01, 2019 | by DatapointLabs | views 1241
Keynote address delivered at NAFEMS seminar on "Material Properties in Structural Calculation: Modeling, Calibration, Simulation & Optimization."
April 01, 2019 | by DatapointLabs | views 1241
Keynote address delivered at NAFEMS seminar on "Material Properties in Structural Calculation: Modeling, Calibration, Simulation & Optimization."
March 13, 2019 | by DatapointLabs | views 1290
Multi-scale material models are being increasing applied for high level simulation of complex materials such as UD layups, fabric laminate composites, fiber-filled plastics. These models require data inputs from a variety of material tests which are then assembled into models used in the finite element solvers. We present an infrastructure for the digitalization of such information, where the required material data are collected including a process for maintaining traceability and consistency of the source data. Information about the compositional characteristics and processing history are captured. Built-in software modules or external client tools can be used for calibration of material models with the resulting material file linked to the source data. The accuracy of the reduced order model can be checked by running a validation simulation against a physical test. Models can be published and released into a master CAE materials library output where they can be used to model such materials for a variety of target solvers. This process improves the reliability and accuracy of composites simulation.
October 07, 2017 | by DatapointLabs | views 2845
Physically accurate simulation is a requirement for initiatives such as late-stage prototyping, additive manufacturing, and digital twinning. Simulations use mathematical models to replicate physical reality. Verification and validation (V&V) is an important step for high-fidelity simulation. While verification is a way to check the accuracy of these models, factors such as simulation settings, element type, mesh size, choice of material model, material parameter conversion process, quality and suitability of material property data used can have a large impact on simulation quality. Validation presents a means to check simulation accuracy against a physical experiment. These validations are a valuable tool to measure solver accuracy prior to use in product development. Confidence is gained that the simulation replicates real-life physical behavior.
August 02, 2017 | by DatapointLabs | views 3193
The modeling of material behavior for injection molded plastics is a vital step for good simulation results. We detail the types of material data needed by various injection-molding simulation programs, factors that can affect simulation quality including test techniques and process variables such as moisture content. The case of fiber filled plastics is covered along with the extension to structural analysis applications.
Plastics Visco-elastic Rate Dependency Injection Molding Nonlinear Material Models Structural Analysis Moldflow LS-DYNA Abaqus Moldex3D DIGIMAT SIGMASOFT Multi-CAE Molding Simpoe-Mold Presentations Validation
June 12, 2017 | by DatapointLabs | views 2419
Physically accurate simulation is a requirement for initiatives such as late-stage prototyping, additive manufacturing and digital twinning. The use of mid-stage validation has been shown to be a valuable tool to measure solver accuracy prior to use in simulation. Factors such as simulation settings, element type, mesh size, choice of material model, the material model parameter conversion process, quality and suitability of material property data used can all be evaluated. These validations do not use real-life parts, but instead use carefully designed standardized geometries in a controlled physical test that probes the accuracy of the simulation. With this a priori knowledge, it is possible to make meaningful design decisions. Confidence is gained that the simulation replicates real-life physical behavior. We present three case studies using different solvers and materials, which illustrate the broad applicability of this technique.
May 31, 2017 | by Matereality | views 3328
Systems simulations involve material models for many materials. Since different kinds of simulations may be performed ranging from NVH to crash, such material files exist for a variety of solvers. It is a difficult task to ensure the self-consistency of material nomenclature for all these cases, such that the materials information is current and the right material files are used for each material. We present a system where materials information is uniformly deployed to CAD and CAE from libraries set up in Matereality. Consistent naming conventions and unit systems are used. Material files are linked to source material data for reference and traceability.
May 10, 2017 | by Matereality | views 3730
We describe a new software component that takes into consideration the unique multi-variate nature of LS-DYNA material models. Rate-dependent models require adjustment and tuning of many material parameters to fit the rate-dependent tensile properties. Drawing upon a robust back-end data model, a graphical user interface provides drag and drop capability to allow the user to perform tasks such as model extrapolation beyond tested data, modulus change, rate dependency tuning and failure criteria adjustment while assuring self-consistency of the underlying material model. Unit system conversions are also facilitated, eliminating error and ensuring that material inputs to simulation correctly reflect the intent of the CAE analyst. The utility of the Matereality CAE modelers is illustrated with examples for LS-DYNA material models MAT_019, MAT_024 and MAT_089 LCSR.
April 06, 2017 | by DatapointLabs | views 2749
Performing simulations that can approximate the material behavior of ductile plastics is daunting. Factors such as nonlinear elasticity, inclusion of volumetric and deviatoric behavior, finding and correctly applying the proper material data to create failure criteria are only a few hurdles. A variety of material models exist, each with numerous settings and varied parameter conversion methods. Combined, these cause a great deal of uncertainty for the FEA user. In previous papers, we delved into material models for both LS-DYNA (MAT089, MAT024, and MAT187) and ABAQUS (*ELASTIC, *PLASTIC) using mid-stage validation as a technique to probe solver accuracy. In this presentation, we summarize our findings on the benefits of this combined approach as a general tool to test and tune simulations for greater reliability.
October 21, 2016 | by DatapointLabs | views 3581
Plastics exhibit non-linear viscoelastic behavior followed by a combination of deviatoric and volumetric plastic deformation until failure. Capturing these phenomena correctly in simulation presents a challenge because of limitations in commonly used material models. We follow an approach where we outline the general behavioral phenomena, then prescribe material models for handling different phases of plastics deformation. Edge cases will then be covered to complete the picture. Topics to be addressed include: Using elasto-plasticity; When to use hyperelasticity; Brittle polymers – filled plastics; Failure modes to consider; Criteria for survival; Choosing materials; Spatial non-isotropy from injection molding; Importance of residual stress; Visco-elastic and creep effects; Strain-rate effects for drop test and crash simulations; Fitting material data to FEA material models; The use of mid-stage validation as a tool to confirm the quality of simulation before use in real-life applications.
Density Rheology Thermal Mechanical Plastics Rubbers Hyperelastic Visco-elastic Plasticity Rate Dependency Yielding/Failure analysis Injection Molding Structural Analysis ANSYS Presentations Validation
October 05, 2016 | by DatapointLabs | views 3290
Hyperelastic material models are complex in nature requiring stress-strain properties in uniaxial, biaxial and shear modes. The data need to be self-consistent in order to fit the commonly used material models. Choosing models and fitting this data to these equations adds additional uncertainty to the process. We present a validation mechanism where, using of a standard validation experiment one can compare results from a simulation and a physical test to obtain a quantified measure of simulation quality. Validated models can be used with greater confidence in the design of real-life components.
October 04, 2016 | by DatapointLabs | views 2981
Finite element analysis of plastics contains assumptions and uncertainties that can affect simulation accuracy. It is useful to quantify these effects prior to using simulation for real-life applications. A mid-stage validation uses a controlled physical test on a standardized part to compare results from simulation to physical experiment. These validations do not use real-life parts but carefully designed geometries that probe the accuracy of the simulation; the geometries themselves can be tested with boundary conditions that can be simulated correctly. In one study, a quasi-static three-point bending experiment of a standardized parallel ribbed plate is performed and simulated, using Abaqus. 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. In a second study, a dynamic dart impact experiment is validated using LS-Dyna probing the multi-axial deformation of a polypropylene until failure.
July 05, 2016 | by Hubert Lobo | views 2990
We will focus on our work related to the testing, modeling and validation of simulation for crash and durability applications, including testing techniques, software tools for material parameter conversion, and the use of a mid-stage validation process that uses standardized experiments to check the accuracy of the simulation prior to use in real-life applications. In addition, we present a short introduction to the Knowmats initiative which seeks to collect posts and links to papers from industry experts as a reference for simulation professionals.
June 24, 2016 | by Massimo Nutini | views 3346
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
September 23, 2015 | by DatapointLabs | views 2701
Thermoplastic 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.
September 15, 2015 | by Altair Engineering | views 2974
With the growing interest in additive manufacturing in the aerospace industry, there is a desire to accurately simulate the behavior of components made by this process. The layer by layer print process appears to create a morphology that is different from that from conventional manufacturing processes. This can have dramatic impact on the material properties, which in turn, can affect how the material is modeled in simulation. We tested an additively manufactured metal part for mechanical properties and validated the material model used in a linear static simulation.
August 24, 2015 | by Altair Engineering | views 2396
Import your Matereality CAE Material cards directly into HyperWorks.
July 28, 2015 | by Paul Du Bois | views 2805
FAA William J Huges Technical Center (NJ) conducts a research project to simulate failure in aeroengines and fuselages, main purpose is blade-out containment studies. This involved the implementation in LS-DYNA of a tabulated generalisation of the Johnson-Cook material law with regularisation to accommodate simulation of ductile materials.
April 29, 2015 | by Patrick Cunningham | views 2767
This demonstration showing how to analyze plastic parts using finite element analysis was given by Patrick Cunningham at CAE Associates' Accurate FEA of Engineering Plastics seminar, held on October 14, 2014 in Tarrytown, NY.
March 12, 2015 | by DatapointLabs | views 3558
Finite-element analysis and injection-molding simulation are two technologies that are seeing widespread use today in the design of plastic components. Limitations exist in our ability to mathematically describe the complexity of polymer behavior to these software packages. Material models commonly used in finite-element analysis were not designed for plastics, making it difficult to correctly describe non-linear behavior and plasticity of these complex materials. Time-based viscoelastic phenomena further complicate analysis. Dealing with fiber fillers brings yet another layer of complexity. It is vital to the plastics engineer to comprehend these gaps in order to make good design decisions. Approaches to understanding and dealing with these challenges, including practical strategies for everyday use, will be discussed.
November 21, 2014 | by DatapointLabs | views 2852
Thermoplastic materials are one of the largest categories of materials to be injection molded. Simulation of the injection molding process requires sophisticated and exact material properties to be measured. This presentation will discuss the testing required to characterize a material for use in SIGMASOFT, as well as the significance of material model parameters. Differences in testing methodology for amorphous and semi-crystalline polymers will be covered, along with step-by-step implementation into the software to produce a successful injection molding simulation simulation.
October 28, 2014 | by DatapointLabs | views 2928
It has long been desired to quantify the accuracy of simulation results. Through developments in digital image correlation (DIC) techniques, it is now possible to quantify the deviation between simulation and real life experimentation. In this paper, three-dimension DIC measurements of deformed parts are compared to deformed surfaces predicted in simulation. Using DIC, it is possible to import deformed surface elements from simulation and map the magnitude of deviation from the measurements of the actual deformed shape.
October 08, 2014 | by DatapointLabs | views 2729
LS-DYNA software contains a wealth of material models that allow for the simulation of transient phenomena. The Matereality® CAE Modeler is a generalized pre-processor software used to convert material property data into material parameters for different material models used in CAE. In a continuation of previously presented work, we discuss the extension of the CAE Modeler software to commonly used material models beyond MAT_024. Software enhancements include advanced point picking to perform extrapolations beyond the tested data, as well as the ability to fine-tune the material models while scrutinizing the trends shown in the underlying raw data. Advanced modeling features include the ability to tune the rate dependency as well as the initial response. Additional material models that are quite complex and difficult to calibrate are supported, including those for hyperelastic and viscoelastic behavior. As before, the written material cards are directly readable into the LS-DYNA software, but now they can also be stored and catalogued in a material card library for later reuse.
September 21, 2014 | by DatapointLabs | views 2654
Plastics exhibit non-linear viscoelastic behavior followed by a combination of deviatoric and volumetric plastic deformation until failure. Capturing these phenomena correctly in simulation presents a challenge because of the inadequacy of currently used material models. We follow an approach where we outline the general behavioral phenomena, then prescribe material models for handling different phases of plastics deformation. Edge cases will then be covered to complete the picture. Topics to be addressed include: Using elasto-plasticity; When to use hyperelasticity; Brittle polymers – filled plastics; Failure modes to consider; Criteria for survival; Choosing materials; Spatial non-isotropy from injection molding; Importance of residual stress; Visco-elastic and creep effects; Strain-rate effects for drop test and crash simulations; Fitting material data to FEA material models.
August 12, 2014 | by DatapointLabs | views 3207
Material specifications define properties for incoming materials to meet required criteria. We present software that manages creation of material specifications, input of properties and material composition; and provides a way to evaluate qualification per specification. While it is designed for OEM/Tier n environments, it is also applicable for materials suppliers.
Automotive Moldflow LS-DYNA Abaqus ANSYS Moldex3D DIGIMAT SIGMASOFT SOLIDWORKS ADINA ANSYS FIDAP B-Sim Cadmould HyperXtrude MSC.DYTRAN MSC.MARC MSC.NASTRAN Multi-CAE Molding NX Nastran PAM-CRASH PAM-FORM PlanetsX Polycad POLYFLOW Blow Molding POLYFLOW Extrusion POLYFLOW Thermoforming PolyXtrue RADIOSS Simpoe-Mold T-Sim VEL VISI Flow WinTXS Presentations
May 13, 2014 | by DatapointLabs | views 3047
Plastics appeared as design materials of choice about 30 years ago. They brought with them huge design challenges because their multi-variable, non-linear nature was not well understood by engineers trained to work in a linear elastic world. We outline a 20 year journey accompanying our customers in their efforts to understand and simulate these remarkable materials to produce the highly reliable plastic products of today. We discuss challenges related to processes such as injection molding vs. blow-molding; coping with filled plastics; the difficulties of modeling polymers for crash applications. We include our latest findings related to volumetric yield in polymers and its relationship to failure. We describe the material database technology that was created to store this kind of multi-variable data and the analytical tools created to help the CAE engineer understand and use plastics material data.
Plastics Automotive Blow Molding High Speed Testing Injection Molding Nonlinear Material Models Structural Analysis Moldflow LS-DYNA Abaqus ANSYS Moldex3D DIGIMAT Multi-CAE Crash Multi-CAE Molding Multi-CAE Structural PAM-CRASH Presentations
April 30, 2014 | by DatapointLabs | views 2511
The 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.
Plastics Rubbers Foams Metals Automotive Biomedical Building Materials Consumer Products Energy and Petroleum Material Supplier Toys/Sporting Goods Electonics/Electrical Industrial Goods CAE Vendor/Supplier Mold Maker/Designer Nonlinear Material Models Structural Analysis Abaqus Composites SIMULIA Presentations
February 13, 2014 | by DatapointLabs | views 2567
As 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.
Plastics Metals Aerospace and Defense Automotive Biomedical Building Materials Consumer Products Material Supplier Toys/Sporting Goods Electonics/Electrical Industrial Goods CAE Vendor/Supplier Mold Maker/Designer Structural Analysis ANSYS Presentations
October 29, 2013 | by DatapointLabs | views 2676
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.
April 07, 2013 | by DatapointLabs | views 2579
Today, CAE is integrated with modern automotive product development. This creates new challenges for departments that support new product development. In the materials arena, the testing is elevated to much higher levels of sophistication and precision to accommodate the complex material models used in CAE. It is no longer simple matter to convert raw data into material model parameters. We present an end-to-end strategy that gives automakers a well managed pathway to transforming to simulation-based design. We operate a quick-turnaround expert material testing lab to support high-end CAE and product development. We provide a data management software designed specifically to capture and display material data of any complexity. The software can transform raw material data into material parameter files for most commonly used simulations. The CAE Modeler software is of adequate sophistication to fit equations to data, visualize material models along with raw data, and output material cards. Examples for high strain-rate crash material modeling will be presented.
May 08, 2011 | by DatapointLabs | views 2840
DatapointLabs' TestPaks (material testing + model calibration + Abaqus input decks) for rate-dependent, hyperelastic, viscoelastic, NVH, and the use of Abaqus CAE Modeler to transform raw data into material cards will be presented. A representative from Idiada will present a case study explaining the use of DatapointLabs’ material data and TestPaks for simulation.
March 10, 2011 | by DatapointLabs | views 2537
The testing of materials for use in crash and safety simulations and the conversion of test data into material models is a process that is not well standardized in the industry. Consequently, CAE users face uncertainty and risk in this process that can have a negative impact on simulation quality. In this workshop, we present approaches currently used in the US for the gathering of high quality test data plus the acclaimed Matereality CAE Modeler software that is used to transform high strain-rate data into crash material cards.
January 19, 2011 | by DatapointLabs | views 2341
We present a methodology for DIGIMAT users to perform the DIGIMAT MX reverse engineering process to obtain material parameter inputs for crash, elasto-plastic, creep and visco-elasticity. The injection-molding process used involves a standardized plaque geometry with fully developed flow, with test specimens taken from a specific plaque location. A standardized testing procedure is applied and the resulting DIGIMAT MX inputs are handled in a streamlined data stream, which saves time and improves the reliability of the reverse engineering process. The DIGIMAT MX reverse engineering itself can be performed as a service in collaboration with e-Xstream. This gives the user a speedy and tightly controlled process for performing complex finite element analysis with filled plastics
July 21, 2010 | by DatapointLabs | views 2704
The 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.
Plastics Rubbers Foams Aerospace and Defense Automotive Biomedical Consumer Products Material Supplier Toys/Sporting Goods Electonics/Electrical Industrial Goods Packaging Home Appliances Presentations
May 28, 2010 | by DatapointLabs | views 2492
Material modeling has become increasing important as ANSYS software has added analysis capabilities such as non-linear CAE, crash, CFD, and manufacturing process simulation. Poor material representaion brings risk to CAE and product development. Material data needs for various material models are discussed.
May 26, 2010 | by DatapointLabs | views 2392
Many material models are available for crash simulation. However, common models are not designed for plastics. We present best practices developed for adapting common models to plastics, as well as best testing protocols to generate clean, accurate rate-dependent data. In addition, we present a streamlined process to convert raw data to LS-DYNA material cards, and harmonized material datasets that allow the same raw data to be used for other crash and rate-dependent analysis software.
February 18, 2009 | by DatapointLabs | views 2618
Abaqus’ Non-linear NVH capability permits the capture of material behavior of rubber seals and bushings, plastic parts and foam inserts which have a significant influence on the simulation. In this presentation, we discuss material calibration procedures for this application.
May 16, 2008 | by DatapointLabs | views 2843
We present a perspective on material modeling as applied to mold analysis requirements. Melt-solid transitions and the case for a unified material model are discussed, along with prediction of post-filling material behavior and shrinkage, and the impact of viscous heating on flow behavior and material degradation.
Plastics Rubbers Foams Metals Aerospace and Defense Automotive Biomedical Consumer Products Energy and Petroleum Electonics/Electrical Industrial Goods CAE Vendor/Supplier Packaging Home Appliances Blow Molding Extrusion Injection Molding Nonlinear Material Models Moldflow Composites Presentations Gels Oils/Lubricants Waxes
November 27, 2007 | by DatapointLabs | views 2826
Many LS-DYNA models are used for plastics crash simulation. However, common models are not designed for plastics. We present best practices developed for adapting common models to plastics, as well as best testing protocols to generate clean, accurate rate-dependent data.
Metals Aerospace and Defense Automotive Consumer Products Material Supplier Industrial Goods Packaging High Speed Testing Nonlinear Material Models Structural Analysis LS-DYNA Abaqus ANSYS MSC.DYTRAN PAM-CRASH Presentations
September 13, 2000 | by DatapointLabs | views 2550
We discuss open issues in material models for plastics and propose better means of acquiring the right material data for Moldflow simulations using current testing technologies.
March 16, 1999 | by DatapointLabs | views 2798
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.
July 14, 1998 | by DatapointLabs | views 2544
We discuss material properties in injection molding simulations, including the definition of property requirements, identification of evaluation parameters, and the role of material properties at each stage of the injection molding process, from mold filling through cooling, post-filling and shrinkage/warpage considerations.