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Posts in Category: 'Biomedical'


Datapoint Newsletter: Fall 2022, Vol. 28.2

DatapointLabs Invests in New Testing Capabilities, Expands Market Reach

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Thermal Mechanical Aerospace and Defense Biomedical Electonics/Electrical Composites Newsletters


Determination and Use of Material Properties for Finite Element Analysis: Book Review

This 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.

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Mechanical Plastics Rubbers Foams Metals Hyperelastic Viscoelastic Plasticity Rate Dependency Yielding/Failure Analysis Aerospace and Defense Automotive Biomedical Building Materials Consumer Products Energy and Petroleum Material Supplier Furniture Industrial Goods CAE Vendor/Supplier Packaging Home Appliances Research Laboratory High Speed Testing Nonlinear Material Models Structural Analysis LS-DYNA Abaqus ANSYS DIGIMAT SOLIDWORKS MSC.DYTRAN MSC.MARC MSC.NASTRAN NX Nastran PAM-COMFORT PAM-CRASH Altair RADIOSS SIMULIA Book Review


Using an Intermediate Validation Step to Increase CAE Confidence

Simulations 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.

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Plastics Plasticity Automotive Biomedical Consumer Products Material Supplier Toys/Sporting Goods Furniture Packaging Home Appliances Nonlinear Material Models Structural Analysis Abaqus Research Papers Validation


Mold Tempering: Conformal Cooling - yes or no?

The tempering layout for injection molds is often designed departing from previous experiences. The manufacturing feasibility is the main driver when deciding where to place cooling lines. However, often the relevance of the tempering in the process profitability or in the part quality is underestimated, and due to the lack of better information sometimes the resulting tempering performs far from the optimum. As a consequence, the molding efficiency is reduced, the part quality is compromised and, once the mold is already built, sometimes expensive trial-and-error is required to bring the mold to an optimum configuration.

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Rheology Thermal Plastics Automotive Biomedical Injection Molding SIGMASOFT Newsletters


Ejection system design: Optimization with SIGMASOFT Virtual Molding

As 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.

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Rheology Plastics Rubbers Viscoelastic Automotive Biomedical Injection Molding SIGMASOFT Newsletters


Cold Runner Design - Getting the whole picture matters

The profitability of a molded rubber product depends to a large extent on the mold efficiency. To achieve the maximum productivity, besides the larges possible number of cavities it is desirable to minimize the rubber consumption and to produce parts without defects.

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Rheology Rubbers Automotive Biomedical Injection Molding SIGMASOFT Newsletters


Creep modelling of Polyolefins using artificial neural networks

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.

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Mechanical Plastics Automotive Biomedical Structural Analysis Abaqus Research Papers Validation


Providing an Experimental Basis in Support of FEA 

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.

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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


The Use of Digital Image Correlation (DIC) and Strain Gauges to Validate Simulation 

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.

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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


Validating Simulation Using Digital Image Correlation 

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.

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Plastics Aerospace and Defense Automotive Biomedical Material Supplier Electonics/Electrical CAE Vendor/Supplier Nonlinear Material Models Structural Analysis Abaqus Composites SIMULIA Presentations


Mechanical and Visco-Elastic Properties of UHMWPE for In-Vivo Applications 

Ultra-high molecular weight polyethylene (UHMWPE) is used extensively in orthopedic applications within the human body. Components made from these materials are subject to complex loading over extended periods of time. Modeling of components used in such applications depends heavily on having material data under in-vivo conditions. We present mechanical and visco-elastic properties measured in saline at 37C. Comparisons to conventionally measured properties at room temperature are made.

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Plastics Biomedical Blow Molding Extrusion Injection Molding Nonlinear Material Models Structural Analysis Moldflow Abaqus ANSYS SIGMASOFT Papers POLYFLOW Blow Molding POLYFLOW Extrusion POLYFLOW Thermoforming


Understanding and Coping with Material Modeling Limitations in FEA 

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.

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Plastics Rubbers Foams Aerospace and Defense Automotive Biomedical Consumer Products Material Supplier Toys/Sporting Goods Electonics/Electrical Industrial Goods Packaging Home Appliances Presentations


Simulating Plastics in Drop and Crash Tests 

If you want a crash simulation involving plastics to yield useful results, it is important to model the material behavior appropriately. The high strain rates have a significant effect on the properties, and failure can be ductile or brittle in nature, depending on a number of factors.

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Plastics Aerospace and Defense Automotive Biomedical Consumer Products Material Supplier Toys/Sporting Goods Industrial Goods Packaging High Speed Testing Nonlinear Material Models Structural Analysis LS-DYNA Abaqus ANSYS MSC.DYTRAN PAM-CRASH Altair RADIOSS Research Papers


Material Modeling and Mold Analysis 

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.

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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


Characterization and Modeling of Non-linear Behavior of Plastics 

A considerable amount of CAE today is devoted to the simulation of non-metallic materials, many of which exhibit non-linear behavior. However, most material models to date are still based on metals theory. This places severe restrictions on the proper description of their behavior in CAE. In this paper, we describe non-linear elastic behavior and its interrelationship with plastic behavior in plastics. Special attention is given to the differentiation between visco-elastic (recoverable) strain and plastic (non-recoverable) strain. The goal of this work is to have a material model for plastics that can describe both loading and unloading behavior accurately and provide an accurate measure of damage accumulation during complex loading operations.

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Plastics Rubbers Aerospace and Defense Automotive Biomedical Consumer Products Material Supplier Toys/Sporting Goods Packaging Home Appliances Nonlinear Material Models Structural Analysis Abaqus Research Papers


Practical Issues in the Development and Implementation of Hyperelastic Models

Hyperelastic models are used extensively in the finite element analysis of rubber and elastomers. These models need to be able to describe elastomeric behavior at large deformations and under different modes of deformation. In order to accomplish this daunting task, material models have been presented that can mathematically describe this behavior [1]. There are several in common use today, notably, the Mooney-Rivlin, Ogden and Arruda Boyce. Each of these has advantages that we will discuss in this article. Further, we will examine the applicability of a particular material model for a given modeling situation.

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Rubbers Foams Aerospace and Defense Automotive Biomedical Nonlinear Material Models Structural Analysis Abaqus ANSYS SOLIDWORKS MSC.MARC NX Nastran Research Papers