Do you know the critical tearing energy of your rubber material?
Critical tearing energy is an important parameter to study crack growth in rubber under fatigue loading and it’s evaluation becomes imperative for the design and evaluation of rubber products. To prevent crack growth and sudden fatigue failures, one of the technique is to improve the tearing energy of rubber. Evaluation and testing of tearing energy properties is of utmost importance.
In automotive, aerospace and biomedical applications, soft elastomers and rubbers often handle cyclic loads and displacement cycles during their entire service duty cycle. When going through long periods of cyclic loading, catastrophic failure frequently happens becuase of crack formation, growth followed by propagation.
A proper treatment of the rubber material testing service conditions and material degradation phenomena like strain softening is of prime importance in the testing of rubbers specimens for FEA material characterization. The accuracy and reliability of obtained test data depends on how the mechanical conditioning and representational service conditions of the material have been accounted for in the test data. To simulate a component in unused and unaged conditions, the mechanical conditioning requirements are different than the ones for simulating a component that has gone through extensive field service and aging under different environmental conditions.
To simulate performance of a material or component by Finite Element Analysis (FEA) it should be tested under the same deformation modes to which original assembly will be subjected. The uniaxial tension tests are easy to perform and are fairly well understood but if the component assembly experiences complex multiaxial stress states then it becomes imperative to test in other deformation modes. Planar (pure shear), biaxial and volumetric (hydrostatic) tests need to be performed along with uniaxial tension test to incorporate the effects of multiaxial stress states in the FEA model.
Material stiffness degradation phenomena like Mullin’s effect at high strains and Payne’s effect at low strains significantly affect the stiffness properties of rubbers. After the first cycle of applied strain and recovery the material softens, upon subsequent stretching the stiffness is lower for the same applied strain.
Despite all the history in testing hyperelastic and viscoelastic materials, there is a lack of a methodical and standard testing protocol for pre-conditioning. Comprehensive studies on the influence of pre-conditioning are not available. Readers are referred to Austrell and Remache, et al,. There are no guidelines for sample pre-conditioning in ASTM D412. However, British Standard BS 903 suggests to perform 5 cycles of pre-conditioning to improve test reproducibility.
There are five (5) different techniques to carry out pre-conditioning and material testing of general elastomer samples.
1. The first technique pertains to a mechanical test where the the testing of the sample is carried out under one single stretch at a speed recommended by the ASTM D412 specification.
2. In the second testing technique the sample is stretched at a constant speed up to the maximum relevant strain brought back to the initial position. Cyclic stretching is then carried out for anywhere for 1 to 7 cycles. The speed of the initial stretch and the number of subsequent cyclic stretches needs to be same. The data curve is then shifted to the origin by zeroing out the stress and strain and used for curve-fitting procedure.
3. In the third testing protocol the sample is stretched to a fraction of the full material stretch capability and brought back to the initial position and cycled back again to this fractional position anywhere from 2 to 7 cycles. The stretch in the sample is then increased to the second level and cycled back to initial position multiple times. The sample is stretched back to an even higher position and cycled back. This progressively continues until the maximum strain capability of the material is reached. This protocol is known as progressive pre-conditioning.
4. In the fourth testing technique the sample is stretched to a fraction of the total stretch capability and relaxed for anywhere from 30 seconds to 120 seconds as per the material. The sample is then again stretched to a higher limit and relaxed again. This is continued until the maximum stretchable capability of the material. This particular technique stretches the material and allows the material to fully creep and relax at each interval so that all the stress softening is accounted for in the test data.
5. In the fifth testing technique the sample is tested under a single stretch but the speed or the rate of stretch is very slow. This ultra-slow speed test is carried out so that the material can creep, relax, and the cross-links in the elastomer are given enough time to expand-contract and come to a balanced position during the stretching. This technique is a combination of the two above testing techniques.
These five (5) testing protocols involve the stretching of the material to different limits under different conditions and suitably cycling the material. The suitability of one testing technique over the other is debatable and one should adopt the technique that most closely resembles the operating conditions of the material and what one expects to back out from the Finite Element Analysis. Figures (1.11) through (1.14) shows the results from using the different testing protocols on a 55 durometer Natural Rubber Compound that finds general application in an automotive engine mount.
Figure 1.11: Uniaxial Tension Test Results
Figure 1.12: Single Stretch Followed by 3 Cycles of Stretching to the Maximum
Figure (1.12) shows the results from comparisons carried out on a uniaxial compression test for an engine mount material characterization. Two protocols were employed to carry out the material characterization. Progressive straining and cycling was carried out first. The material was strained 3 times before reaching the ultimate strain of approximately 75 %. The material was subsequently tested using ultra slow straining protocol. As can be seen the test data output for FEA input is the same using both the techniques. This result confirms the observation by Austrell in his work on conditioning of material samples for characterization i.e., Mullins effect can be negated when enough time is allowed for the material to relax, creep, and flow during the rubber material testing.
Figure 1.13: Progressive Pre-conditioning with Stretching to 3 levels and Cyclic Stretches
Figure 1.14: Progressive Relaxation, Stretching and Relaxation to Maximum Levels
1.2 Guidelines for Rubber Material Testing
Rubber compounds are formulated from recipes of ingredient materials. Depending on the time, location and environment while mixing the compounds, properties are known to vary from batch to batch.
• All testing to characterize a material compound should be performed on the same batch.
• Laboratory validations will help to correlate test specimen slabs against the real components to make sure they have identical cure history.
• Small compression buttons can be extracted from components and compared with slab data.
• The testing should be carried out at the temperature at which the component is expected to perform under field service conditions.
• For seals and o-rings, aging in oils and solutions can be carried out prior to testing.
• Input of more than one test data type in FEA software will increase simulation accuracy by an order of magnitude
We at AdvanSES are capable of developing a custom testing protocol for compliance with international standards or for quality assurance. Materials testing services offered by AdvanSES include:
Composition: Whe you need to know with certainty what materials are used in the manufacture of thermoplastics, rubber materials etc.
Shear Test: Materials testing designed to measure shear strength of rubber and composites. These tests show how much stress a specimen can take before failure and is often times used to test and compare the strength of adhesives.
Flexural Test: When a product like an I-beam or girder used in construction must support a predetermined amount of weight without sagging, a flexure materials test is often performed to verify that the specimen can withstand a certain level of stress without flexing.
Environment and High Temperature Exposure Test: When it comes to determining the lifespan of materials, especially elastomer materials intended for outdoor use, exposure to high temperature and oils is carried out to check the degradation of materials.
Tensile/Compression Tests: From plastics and metals to adhesives and rubbers, tensile/compression testing is a form of materials testing that places specimens under precise compressive loads to measure their ability to withstand compression before deformation occurs.
Fatigue Tests: Fatigue tests are important to determine the endurance or breaking load a material can withstand before failing as well as the number of repeated loading cycles it can endure. Fatigue testing looks at a materials limit to withstand stresses and environment degradation. We can conduct stress controlled and strain controlled high cycle fatigue tests from room temperature to 250C on material samples, parts and components.
Applications of Materials Testing:
1) Quality Control 2) Regulatory Compliance 3) Design Development 4) Failure Analysis 5) Performance Prediction 6) Finite Element Analysis Material Constants Data
AdvanSES announces that its Testing Laboratory has attained ISO/IEC 17025:2017 accreditation vide NABL certificate No. TC-9168. ISO/IEC 17025:2017 is the highest recognized quality standard in the world for calibration and testing laboratories. Accreditation means the lab consistently produces precise and accurate test data and has implemented a rigorous quality management system. The stringent processes in the audits for the accreditation relate to the operations, efficiency and effectiveness of the laboratory. Test data from the laboratory is benchmarked for accuracy, reliability and consistency.
Receiving the accreditation means that test reports and certificates generated from AdvanSES laboratory can now be generally accepted from one country to another without further testing.
The scope of the accreditation covers tests and properties in the field of rubbers, plastics and composite materials. It is one of the few labs in the world accredited to perform internationally recognized fatigue standards like ASTM D7791.
AdvanSES today is one of the few companies in the world who provide expert problem solving services using Finite element analysis (FEA), provides new product development and material testing and analysis.
Space research and application demands stringent requirements from materials, making it imperative that they are tested rigorously, by multiple methods and techniques to fully characterize their performance and their ability to handle degradation, mechanical fatigue under extreme conditions.
AdvanSES provides full mechanical characterization of specialty polymers, rubber and in-homogeneous materials, for use in demanding atmospheric and space applications. Mechanical fatigue testing is a core area for us and we can test materials for HCF, LCF as well as elevated temperatures.
We can provide the following testing protocols for your rubbery materials;
A thermoplastic, or thermosoftening plastic, is a plastic polymer material that becomes pliable or moldable at a certain elevated temperature and solidifies upon cooling. Most thermoplastics have a high molecular weight. The polymer chains associate by intermolecular forces, which weaken rapidly with increased temperature, yielding a viscous liquid.
1) Hardness (ASTM D2240): The resistance of a plastic material to indentation. It is measured on a durometer machine. Normal specificationa is plus or minus 5 and three scales are used: Shore A for flexible, Shore C for semi rigid and Shore D for rigid. Usually a delayed reading of 10 or 15 seconds is used.
2) Tensile Strength (ASTM D638): The maximum nominal stress sustained by a test specimen being pulled from both ends, at a specific temperature and a specific rate of stretching. Specification is a minimum amount in MegaPascals, (N/mm2).
3) Elongation (ASTM D638): The amount of increased length of a material until breakage. Specification is a minimum percentage.
5) Creep and Stress Relaxation: Creep is the property of a material to expand or deform continuously over a period of time under the application of a constant force. Creep is one of the most widespread failure mechanism of thermoplastic materials.
AdvanSES has a history of completing FEA projects for customers from automotive, aerospace, biomedical and consumer durables background. All our projects are delivered using state of the art commercial FEA softwares.
We offer a complete range of Finite Element Analysis FEA consulting services for solving structural, thermal, fatigue, and fluid flow pressure problems. We work with our customers to analyze product behavior, predict service life, and understand failures. Our FEA engineers help our customers make early design choices. Our proactive approach helps our customers expedite products into the market.
Some our strengths in Finite Element Analysis (FEA) are detailed below;
Non-linear Materials: Our regular work includes characterization and implmentation of complex material models for hyperelasticity, elasto-plasticity and viscoelasticity. We can work on any kind of materials to implement them successfully in FEA models.
2) Verifications and Validations: Any kind of simulation without a strong verification and validation basis will mostly fail on expert scrutiny. We have extensive experience in verifications and validations procedures in our laboratory. We can replicate field service conditions, setup custom test rigs and characterize products under static and dynamic loads.
3) Contact-Impact: We offer implementation of full physics in contact, drops and high speed impact analysis.
The finite element method (FEM) is a numerical method
used to solve a mathematical model of a given structure or system, which are
very complex and for which analytical solution techniques are generally not
possible, the solution can be found using the finite
element method. The finite element
method can thus be said to be a variational formulation method using the principle of minimum potential
energy where the unknown quantities of interests are approximated by continuous piecewise polynomial functions. These quantities
of interest can be different according to the chosen system, as the finite
element method can be and is used in various
different fields such as structural mechanics, fluid mechanics, accoustics, electromagnetics,
etc. In the field of structural mechanics the primary field of interest is the
displacements and stresses in the system.
It is important to understand that FEM only gives an approximate solution of the prob- lem and is a numerical approach to get the real result of the variational formulation of partial differential equations. A finite element based numerical approach gives itself to a number of assumptions and uncertainties related to domain discretizations, mathematical shape functions, solution procedures, etc. The widespread use of FEM as a primary tool has led to a product engineering lifecycle where each step from ideation, design development, to product optimization is done virtually and in some cases to the absence of even prototype testing.
This fully virtual product development and analysis methodology leads to a situation where a misinterpreted approximation or error in applying a load condition may be car- ried out through out the engineering lifecycle leading to a situation where the errors get cumulative at each stage leading to disastrous results. Errors and uncertainties in the ap- plication of finite element method (FEM) can come from the following main sources, 1) Errors that come from the inherent assumptions in the Finite element theory and 2) Errors and uncertainties that get built into the system when the physics we are seeking to model get transferred to the computational model. A common list of these kind of errors and uncertainties are as mentioned below;
Errors and uncertainties from the solver.
Level of mesh refinement and the choice of element type.
Averaging and calculation of stresses and strains from the primary solution variables.
Uncertainty in recreating the geometrical domain on a computer.
Approximations and uncertainties in the loading and boundary conditions of the model.
Errors coming from chosing the right solver types for problems, e.g. Solvers for eigen value problems.
The long list of error sources and uncertainties in the procedure makes it desirable that a framework of rules and criteria are developed by the application of which we can make sure that the finite element method performs within the required parameters of accuracy, reliability and repeatability. These framework of rules serve as verification and validation procedures by which we can consistently gauge the accuracy of our models, and sources of errors and uncertainties be clearly identified and progressively improved to achieve greater accuracy in the solutions. Verifications and Validations are required in each and every development and problem solving FEA project to provide the confidence that the compu- tational model developed performs within the required parameters. The solutions provided by the model are sufficiently accurate and the model solves the intended problem it was developed for.
Verification procedure includes checking the design, the software code and also investigate if the computational model accurately represents the physical system. Validation is more of a dynamic procedure and determines if the computational simulation agrees with the physical phenomenon, it examines the difference between the numerical simulation and the experimental results. Verification provides information whether the computational model is solved correctly and accurately, while validation provides evidence regarding the extent to which the mathematical model accurately correlates to experimental tests.
In addition to complicated
discretization functions, partial differential equations repre- senting physical systema, CFD and FEA both use
complicated matrices and PDE solution algorithms to solve physical systems.
This makes it imperative to carry out verification and validation activities
separately and incrementally during the model building to ensure reliable processes. In order to
avoid spurious results and data contamination giving out false signals, it is
important that the verification process is carried out before the valida- tion
assessment. If the verification process fails the the model building process
should be discontinued further until the verification is established. If the
verification process suc- ceeds, the
validation process can be carried further for comparison with field service and
1.2 Brief History of Standards and Guidelines for Verifi- cations and Validations
Finite element analysis found widespread use with the release of NASA Structural Anal- ysis Code in its various versions and flavous. The early adopters for FEA came from the aerospace and nuclear engineering background. The first guidelines for verification and validation were issued by the American Nuclear Society in 1987 as Guidelines for the Ver- ification and Validation of Scientific and Engineering Computer Programs for the NuclearIndustry.
The first book on the subject was written by Dr. Patrick Roache in 1998 titled Verification and Validation in Computational Science and Engineering, an update of the book appeared in 2009.
In 1998 the Computational Fluid Dynamics Committee on
Standards at the American Institute of Aeronautics and Astronautics released
the first standards document Guide for
the Verification and Validation of Computational Fluid Dynamics Simulations.
The US Depeartment of Defense through Defense Modeling and Simulation Office
releaseed the DoD Modeling and
Simulation, Verification, Validation, and Accreditation Document in 2003.
The American Society of Mechanical Engineers (ASME) V
and V Standards Commit- tee released
the Guide for Verification and Validation in
Computational Solid Mechanics (ASME V and V-10-2006).
In 2008 the National Aeronautics and
Space Administration Standard for Models
and Simulations for the first time developed a set of guidelines that provided a numerical score for
verification and validation efforts.
American Society of Mechanical Engineers
V and V Standards Committee
V and V-20 in 2016 provided
an updated Standard for Verification and Validation in Computational Fluid Dynamics and Heat Transfer .
1.3 Verifications and Validations :- Process and Procedures
shows a typical product design cycle in a fast-paced industrial product de- velopment group. The product interacts
with the environment in terms of applied loads,
boundary conditions and ambient atmosphere. These factors form the
inputs into the com- putational model
building process. The computational model provides us with predictions and
solutions of what would happen to the product under different service conditions.
is important to note that going from the physical
world to generating a computational model
involves an iterative process where
all the assumptions, approximations and their effects on the the quality of the computational model are iterated
upon to generate the most optimum
computational model for representing the physical world.
Figure 1.1: Variation on the Sargent Circle Showing the Verification and Validation Procedures in a Typical Fast Paced Design Group
The validation process between the
computational model and the physical world also involves an iterative process,
where experiments with values of loads and boundary con- ditions are solved and
the solution is compared to output from the physical world. The computational
model is refined based upon the feedbacks obtained during the procedure.
The circular shapes of the process
representation emphasizes that computational mod- eling and in particular
verification and validation procedures are iterative in nature and require a
continual effort to optimize them.
The blue, red and green colored
areas in Figure(1.3)
highlight the iterative validation and
verification activities in the process. The standards and industrial guidelines
clearly mention the distinctive nature of code and solution
verifications and validations at different levels.
The green highlighted region falls in the domain of the laboratory performing
the experiments, it is equally important
that the testing
laboratory understands both the process and procedure of verification and
Code verification seeks to ensure
that there are no programming mistakes or bugs and that the software
provides the accuracy
in terms of the implementation of the numerical al- gorithms or construction of the solver. Comparing
the issue of code verification and calcu- lation verification of softwares, the main point of difference is that calculation verification
Figure 1.2: Verification and Validation Process
involves quantifying the discretization error in a numerical simulation. Code verification is rather upstream in the process and is
done by comparing numerical results with analytical solutions.
Figure 1.3: Guidance for Verification and Validation as per ASME 10.1
1.4 Guidelines for Verifications and Validations
The first step is the verification of the code or software
to confirm that the software
is work- ing as it was
intended to do. The idea behind code verification is to identify and remove any
bugs that might have been generated
while implementing the numerical algorithms or
because of any programming errors. Code verification is primarily a
responsibility of the code developer and softwares like Abaqus, LS-Dyna
etc., provide example
problems man- uals, benchmark manuals to show the
verifications of the procedures and algorithms they have implemented.
Next step of calculation verification
is carried out to quantify the error in a computer simulation due to factors
like mesh discretization, improper convergence criteria, approxi- mation in material
properties and model generations. Calculation verification provides with an
estimation of the error in the solution because of the mentioned factors.
Experience has shown us that insufficient mesh discretization is the primary
culprit and largest
contributor to errors in calculation verification.
Validation processes for material models, elements, and numerical algorithms are gen- erally part of FEA and CFD software help manuals. However, when it comes to establishing the validity of the computational model that one is seeking to solve, the validation procedure has to be developed by the analyst or the engineering group.
following validation guidelines were developed at Sandia National
Labs[Oberkampf et al.] by experimentalists working on wind tunnel
programs, however these are
applicable to all problems from computational
Guideline 1: The validation experiment
should be jointly designed by the FEA group and the experimental engineers. The
experiments should ideally be designed so that the validation domain falls
inside the application domain.
Guideline 2: The designed experiment
should involve the full physics of the system, including the loading and
Guideline 3: The solutions of the
experiments and from the computational model should be totally independent of each other.
Guideline 4: The experiments and the validation process should start from the system level solution to the component level.
Guideline 5: Care should be taken that operator bias or process bias does not
contami- nate the solution or the validation process.
1.5 Verification & Validation in FEA
1.5.1 Verification Process of an FEA Model
In the case of automotive product development problems, verification of components like silent blocks and bushings, torque rod bushes, spherical bearings etc., can be carried. Fig- ure(1.4) shows the rubber-metal bonded component for which calculations have been carried out. Hill, Horton and have shown that under radial loads the stiffness of the bushing can be given by,
Figure 1.4: Geometry Dimensions of the
Figure 1.5: Geometry of the Silent Bushing
and G= Shear Modulus = 0.117e0.034xHs, Hs = Hardness of the material. Replacing the geometrical values
Krs= 8170.23N/mm, (1.3)
for a 55 durometer
natural rubber compound. The finite element model for the bushing
is shown in Figure(1.9) and the stiffness from the FEA comes to 8844.45
N/mm. The verification and validation quite often recommends that a difference of less than 10% for a
comparison of solutions is a sound basis for a converged value.
For FEA with non-linear materials
and non-linear geometrical conditions, there are
multiple steps that one has to carry out to ensure that the material
models and the boundary
conditions provide reliable solutions.
Element Test: The unit element test
as shown in in Figure(1.7)
shows a unit cube element. The material properties are input and output
stress-strain plots are compared to the inputs. This provides
a first order validation of whether the material
Figure 1.6: Deformed Shape of the Silent Bushing
properties are good enough to provide sensible
outputs. The analyst
him/her self can carry
out this validation procedure.
Experimental Characterization Test: FEA is now carried out on a characterization test such as a tension test or a compression test. This provides a checkpoint of whether the original input material data can be backed out from the FEA. This is a moderately difficult test as shown in Figure(1.8). The reasons for the difficulties are because of unquantified properties like friction and non-exact boundary conditions.
Comparison to Full Scale Experiments: In these validation steps, the parts and com- ponent products are loaded up on a testing rig and service loads and boundary con- ditions are applied. The FEA results are compared to these experiments. This step provides the most robust validation results as the procedure validates the finite ele- ment model as well as the loading state and boundary conditions. Figure(1.9) shows torque rod bushing and the validation procedure carried out in a multi-step analysis.
Experience shows that it is best to go linearly in the validation procedure from step 1 through 3, as it progressively refines one’s material model, loading, boundary conditions. Directly jumping to step 3 to complete the validation process faster adds upto more time with errors remaining unresolved, and these errors go on to have a cumulative effect on the quality of the solutions.
Figure 1.7: Unit Cube Single Element Test
Figure 1.8: FEA of Compression Test
1.5.2 Validation Process of an FEA Model
shows the experimental test setup for validation of the bushing model. Radial loading is chosen to be the primary
deformation mode and load vs. displacement results are compared. The
verification process earlier carried out established the veracity of the FEA model and the current validation analysis applies the loading in multiple Kilonewtons. Results show a close match
between the experimental and FEA results. Figures(1.10) and
Figure 1.9: Experimental Testing and Validation FEA for the Silent
show the validation setup and solutions for a tire model and engine mount. The
complexity of a tire simulation is due to the nature of the tire geometry, and
the presence of multiple rubber compounds, fabric and steel belts. This makes
it imperative to establish the
validity of the simulations.
Figure 1.10: Experimental Testing and
Validation FEA for a Tire Model
Figure 1.11: Experimental Testing and Validation FEA for a Passenger
Car Engine Mount
An attempt was made in the article
to provide information on the verification and validation
processes in computational solid mechanics.
went through the history of adoption of verification and validation processes and
their integration in computational mechanics processes and tools. Starting from
1987 when the first guidelines were issued in a specific field of application, today we are at a stage where the processes have been standardized and all major industries have found their path of adoption.
Verification and validations are now an integral part of computational mechanics processes to increase integrity and reliability of the solutions. Verification is done primarily at the software level and is aimed at evaluating whether the code has the capability to offer the correct solution to the problem, while validation establishes the accuracy of the solution. ASME, Nuclear Society and NAFEMS are trying to make the process more standardized, and purpose driven.
Uncertainty quantification has not included in this current review, the next update of this article will include steps for uncertainty quantification in the analysis.
American Nuclear Society, Guidelines for the Verification and Validation of Scientific and Engineering Computer Programs for the Nuclear Industry 1987.
Roache, P.J, American Nuclear Society, Verification and Validation in Computational Science and Engineering, Hermosa Publishing, 1998.
American Institute of Aeronautics and Astronautics, AIAA Guide for the Verification and Validation of Computational Fluid Dynamics Simulations (G-077-1998), 1998.
U.S. Department of Defense, DoD Modeling and Simulation (M-S) Verification, Validation, and Accreditation, Defense Modeling and Simulation Office, Washington DC.
Thacker, B. H., Doebling S. W., Anderson M. C., Pepin J. E., Rodrigues E. A., Concepts of Model Verification and Validation, Los Alamos National Laboratory, 2004.
Standard for Models And Simulations, National Aeronautics and Space Administration, NASA-STD-7009, 2008.
Oberkampf, W.L. and Roy, C.J., Verification and Validation in Computational Simulation, Cambridge University Press, 2009.
Austrell, P. E., Olsson, A. K. and Jonsson, M. 2001, A Method to analyse the non- Linear dynamic behaviour of rubber components using standard FE codes, Paper no 44, Conference on Fluid and Solid Mechanics.
Austrell, P. E., Modeling of Elasticity and Damping for Filled Elastomers,Lund University.
A proper treatment of the rubber material service conditions and material degradation phenomena like strain softening is of prime importance in the testing of rubbers specimens for FEA material characterization. The accuracy and reliability of obtained test data depends on how the mechanical conditioning and representational service conditions of the material have been accounted for in the test data. To simulate a component in unused and unaged conditions, the mechanical conditioning requirements are different than the ones for simulating a component that has gone through extensive field service and aging under different environmental conditions. To simulate performance of a material or component by Finite Element Analysis (FEA) it should be tested underthe same deformation modes to which original assembly will be subjected. The uniaxial tension tests are easy to perform and are fairly well understood but if the component assembly experiences complex multiaxial stress states then it becomes imperative to test in other deformation modes. Planar (pure shear), biaxial and volumetric (hydrostatic) tests need to be performed along with uniaxial tension test to incorporate the effects of multiaxial stress states in the FEA model.
Material stiffness degradation phenomena like Mullin’s effect at high strains and Payne’s effect at low strains significantly affect the stiffness properties of rubbers. After the first cycle of applied strain and recovery the material softens, upon subsequent stretching the stiffness is lower for the same applied strain. Despite all the history in testing hyperelastic and viscoelastic materials, there is a lack of a methodical and standard testing protocol for pre-conditioning. Comprehensive studies on the influence of hyperelastic material testing pre-conditioning is not available.
1) Mechanical Testing of Polymers, Metals and Composite Materials 2) Fatigue and Durability Testing 3) Dynamic Mechanical Analysis (DMA) of Materials and Components 4) Hyperelastic, Viscoelastic Material Characterization Testing 5) Data Cards for Input into FEA, CAE softwares 6) FEA Services 7) Custom Test Setups with NI Labview DAQ