This post references customer papers presented at the 2016 Science in the Age of Experience conference that focused on advanced material modeling. I was a session chair for several of these presentations.
One of the mainstays of any cutting edge use of the Abaqus software is a discussion of advanced material modeling (constitutive modeling). This discussion tends to span many, or all, industries, and the recent Science in the Age of Experience conference was no exception. There were many papers and presentations by our customers on the use of advanced material models in both Abaqus/Standard and Abaqus/Explicit. Some of these papers were presented under a dedicated industry track, whereas others were presented within the “Materials” or “Composites” track.
Two themes on advanced material modeling are recognized here:
- Better material models for polymers and plastics.
- Focus on modeling thermomechanically coupled events and processes with high fidelity material models.
Abaqus users in many industries are working towards better material models for elastomers, polymers and plastics. The papers by Volgers (elastomer), Pannneerselvam (polymer), and Karim (polymer) all showcase the movement to higher fidelity material models. The latter two papers also showcase the use of the new PRF (Parallel Rheological Framework) model in Abaqus for capturing nonlinear viscoelasticity.
The papers by Brown, Arias, and Nyaaba all showcase the theme around modeling of thermomechanically coupled events or processes. The first paper focuses on metals in forging events, and the latter two focus on rubber applications where mechanical hysteresis generates significant heat. The paper by Nyaaba touches on both the use of the new PRF model (for nonlinear viscoelasticity) and its use in a tire application which generates heat due to the rubber’s viscoelastic hysteresis.
Continue reading to view the customer papers referenced above from the 2016 Science in the Age of Experience conference
Predicting and Designing Integrated Safety Syringe for Shelf Life Using Advanced Nonlinear Constitutive Models in Abaqus, Dinesh Panneerselvam, Scott Russo, Jyoti Gupta, Unilife Medical Solutions
Abstract: The Medical device industry is a highly regulated industry with patient safety being paramount. Ensuring the highest quality and patient safety demands that the device performs as desired from the time it is manufactured, through the shelf life of the product, and during use. Plastics used in medical devices can undergo degradation in mechanical properties over time during the product shelf life depending on the design of the device. It is therefore important to take this aspect of plastic behavior into account during material selection and device design.
Plastics under constant load for long periods of time exhibit creep deformations. Testing devices for creep can be a lengthy process often leading to delay in design iterations to yield the optimum design and subsequently time to market. Computational modeling and FEA simulations with advanced material models can predict material behavior with a high degree of accuracy and can provide deep insights into how the device will perform over time resulting in valuable feedback for design iterations and often reducing design iteration cycles.
In this paper, the short term and long term behavior of polycarbonate is modeled using hyperelastic-nonlinear viscoelastic model based on the parallel rheological framework. Constitutive model is calibrated against uniaxial tension and long term creep test data, is used to predict strain as a function of time in polycarbonate components of the Unifill FinesseTM Integrated Safety Syringe. Model predictions are validated against long term real time as well as accelerated aging test data. Typically these tests run for months.
In summary, through this work, time consuming expensive design iterations through testing were reduced to a few cycles with accurate modeling and material creep strain predictions making use of advanced nonlinear constitutive models in ABAQUS demonstrating how FEA simulations can be leveraged as an effective tool in product development process to save time and cost and in bringing high quality products faster to the market. Read the full paper
Prediction of Nonlinear Viscoelastic Recovery of Thermoplastic Polymers using Abaqus Parallel Rheological Framework (PRF) Model, Mohammed Karim, Zhenyu Zhang, and Ye Zhu, DuPont Performance Materials
Abstract: Thermoplastic polymers show significant nonlinear viscoelastic behavior due to which, after removing the applied load, these materials have some viscoelastic recovery over time before permanent deformation or set occurs. In this work, Abaqus PRF model is used to predict this time dependent viscoelastic recovery. Unlike linear viscoelastic model in Abaqus, PRF model can predict the typical nonlinear viscoelastic behavior of thermoplastic materials.
Two types of testing, stress relaxation and cyclic loading at three different strain levels, are used to calibrate the coefficients of PRF model. SIMULIA’s optimization tool Isight is used to optimize these coefficients. Using the optimized coefficients, the PRF model is able to predict the time dependent nonlinear viscoelastic recovery of thermoplastic polymers. Read the full paper
Coupled Thermomechanical Forging Simulations and the Effect of Material Constitutive Laws, Stuart Brown, Nagi Elabbasi, and Eric Schmitt, Veryst Engineering
Abstract: Correct hot forming design relies on accurate prediction of forming loads, material deformation, and material properties. This is particularly true for coupled thermomechanical analyses, where die/workpiece contact will change local deformations and temperatures. These strains and thermal histories can change the material microstructures and resulting product properties.
This presentation examines the influence of different material and contact models within a hot forging simulation and discusses the consequences on ultimate product performance. We use rate-independent plasticity and compare the results with the Anand internal variable, viscoplastic model available within Abaqus. We also use different contact conditions with varying pressure sensitivity for heat transfer. The simulations demonstrate that constitutive model selection has a strong effect on the final predicted properties of the forging. Read the full paper
Improving Rubber Tread Designs Against Heat Build-Up Under Cyclic Loading Using Strain Energy, Sergio Arias, Dr. Bahram Sarbandi, Priyantha Sriwardene, Camso
Abstract: Heat generation in rubber is a complex phenomenon that occurs when a rubber component is being cyclically loaded. The development of this heat build-up comes from the viscoelastic nature of rubber compounds that occurs during the loading and unloading processes, and it is a difficult mechanism to quantify numerically. A lot of research on this particular and characteristic behavior of rubber has been done essentially since the invention of rubber. Over the course of the last decade or so, there have been numerous breakthroughs in the area of heat generation, and finite element codes are beginning to provide solutions to study this behavior.
However, it is still a very complex parameter to measure and validate for practical purposes. As a result, an alternate way to devise a method to improve the designs of treads in our tracks against the development of heat build-up is to study the strain energy. The purpose of this research is to understand how we can use the strain energy generated under one full load cycle and utilize this to design a new and better generation of treads that can meet the constant increasing demands for performance in the world of rubber tracks. Read the full paper
FEA Prediction of Off-Road Tire Temperature Distribution, W. Nyaaba, S. Frimpong, G. Somua-Gyimah and G. Galecki, Missouri University of Science and Technology
Abstract: Excessive heat generation and retention in ultra-large dump truck tires is among the most common causes of tire failures in the surface mining industry. Accurate prediction of an operating tire temperature profile involves the use of advanced numerical models and solution schemes to mimic the complete elastomeric materials response to operating conditions. The internally generated heat in a tire is a function of its viscoelastic energy dissipation during rolling. Previous research studies have inaccurately predicted off-the-road (OTR) tire heat generation rates and temperatures by the use of linear viscoelasticity to approximate the rather nonlinear viscoelastic rubber material.
This paper presents an accurate approach to predicting OTR tire temperature distributions taking into account the true mechanical response of the filled rubber compounds used in tires. Rubber nonlinear viscoelasticity was modeled using the recently implemented parallel rheological framework (PRF) in Abaqus. Stress relaxation test data for two regional compounds (tread and carcass) were used to calibrate the PRF material model parameters using the data matching component of Isight. A fully coupled thermal-stress analysis procedure in Abaqus/Explicit was adopted to compare temperature distributions of a typical Michelin 59/80R63 tire modeled using two material theories: (i) linear viscoelasticity, and (ii) nonlinear viscoelasticity. The results obtained show that tire temperature distributions are more accurately predicted by the PRF material model than by the Prony series model. Read the full paper
Want to read more customer papers?
If you’re interested in reading other papers presented at the 2016 Science in the Age of Experience, please access the complete conference proceedings in the SIMULIA Learning Community¹.
