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Dynamic Properties of Polymer, Rubber and Elastomer Materials

Non-linear Viscoelastic Dynamic Properties of Polymer, Rubber and Elastomer Materials

Static testing of materials as per ASTM D412, ASTM D638, ASTM D624 etc can be cate- gorized as slow speed tests or static tests. The difference between a static test and dynamic test is not only simply based on the speed of the test but also on other test variables em- ployed like forcing functions, displacement amplitudes, and strain cycles. The difference is also in the nature of the information we back out from the tests. When related to poly- mers and elastomers, the information from a conventional test is usually related to quality control aspect of the material or the product, while from dynamic tests we back out data regarding the functional performance of the material and the product.

 

Tires are subjected to high cyclical deformations when vehicles are running on the road. When exposed to harsh road conditions, the service lifetime of the tires is jeopardized by many factors, such as the wear of the tread, the heat generated by friction, rubber aging, and others. As a result, tires usually have composite layer structures made of carbon-filled rubber, nylon cords, and steel wires, etc. In particular, the composition of rubber at different layers of the tire architecture is optimized to provide different functional properties. The desired functionality of the different tire layers is achieved by the strategical design of specific viscoelastic properties in the different layers. Zones of high loss modulus material will absorb energy differently than zones of low loss modulus. The development of tires utilizing dynamic characterization allows one to develop tires for smoother and safer rides in different weather conditions.

Figure  Locations of Different Materials in a Tire Design

The dynamic properties are also related to tire performance like rolling resistance, wet traction, dry traction, winter performance and wear. Evaluation of viscoelastic properties of different layers of the tire by DMA tests is necessary and essential to predict the dynamic performance. The complex modulus and mechanical behavior of the tire are mapped across the cross section of the tire comprising of the different materials. A DMA frequency sweep

test is performed on the tire sample to investigate the effect of the cyclic stress/strain fre- quency on the complex modulus and dynamic modulus of the tire, which represents the viscoelastic properties of the tire rotating at different speeds. Significant work on effects of dynamic properties on tire performance has been carried out by Ed Terrill et al. at Akron Rubber Development Laboratory, Inc.

Non-linear Viscoelastic Tire Simulation Using FEA

Non-linear Viscoelastic tire simulation is carried out using Abaqus to predict the hysteresis losses, temperature distribution and rolling resistance of a tire. The simulation includes several steps like (a) FE tire model generation, (b) Material parameter identification, (c) Material modeling and (d) Tire Rolling Simulation. The energy dissipation and rolling re- sistance are evaluated by using dynamic mechanical properties like storage and loss modu- lus, tan delta etc. The heat dissipation energy is calculated by taking the product of elastic strain energy and the loss tangent of materials. Computation of tire rolling is further carried out. The total energy loss per one tire revolution is calculated by;

Ψdiss = ∑ i2πΨiTanδi, (.27)
i=1
where Ψ is the elastic strain energy,
Ψdiss is the dissipated energy in one full rotation of the tire, and
Tanδi, is the damping coefficient.

The temperature prediction in a rolling tire shown in Fig (2) is calculated from the loss modulus and the strain in the element at that location. With the change in the deformation pattern, the strains are also modified in the algorithm to predict change in the temperature distribution in the different tire regions.

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ASTM D5992 Dynamic Properties of Rubber Vibration Products

ASTM D 5992 Test Standard applies to Dynamic Properties of Rubber Vibration Products such as springs, dampers, and flexible load-carrying devices, flexible power transmission couplings, vibration isolation components and mechanical rubber goods. The standard applies to to the measurement of stiffness, damping, and measurement of dynamic modulus.

Dynamic testing is performed on a variety of rubber parts and components like engine mounts, hoses, conveyor belts, vibration isolators, laminated and non-laminated bearing pads, silent bushes etc.   to determine their response to dynamic loads and cyclic loading.

Personalized consultation from AdvanSES engineers can streamline testing and provide the necessary tools and techniques to accurately evaluate material performance under field service conditions.

The quantities of interest for measurements are tan delta, loss modulus, storage modulus, phase etc.  All of these properties are viscoleastic properties and require instruments, techniques and measurement practices of the highest quality.

 

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Dynamic Characterization Testing as Per ASTM D5992 and ISO 4664

ASTM D5992 and ISO 4664-1

ASTM D5992 covers the methods and process available for determining the dynamic prop- erties of vulcanized natural rubber and synthetic rubber compounds and components. The standard covers the sample shape and size requirements, the test methods, and the pro- cedures to generate the test results data and carry out further subsequent analysis. The methods described are primarily useful over the range of temperatures from cryogenic to 200◦C and for frequencies from 0.01 to 100 Hz, as not all instruments and methods will accommodate the entire ranges possible for material behavior.

Figures(.43and.44) show the results from a frequency sweep test on five (5) different elastomer compounds. Results of Storage modulus and Tan delta are plotted.

 

Figure .43: Plot of Storage Modulus Vs Frequency from a Frequency Sweep Test

 

The frequency sweep tests have  been carried out by applying a pre-compression of  10 % and subsequently a displacement amplitude of 1 % has been applied in the positive and negative directions. Apart from tests on cylindrical and square block samples ASTM D5992 recommends the dual lap shear test specimen in rectangular, square and cylindri- cal shape specimens. Figure (.45) shows the double lap shear shapes recommended in the standard.

Figure .44: Plot of Tan delta Vs Frequency from a Frequency Sweep Test

 

Figure .45: Double Lap Shear Shapes

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DYNAMIC PROPERTIES OF POLYMER MATERIALS AND THEIR MEASUREMENTS

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Dynamic Properties of Polymer Materials and their Measurements

Polymer materials in their basic form exhibit a range of characteristics and behavior from elastic solid to a viscous liquid. These behavior and properties depend on the temperature, frequency and time scale at which the material or the engineering component is analyzed.
The viscous liquid polymer is defined as by having no definite shape and flow deformation under the effect of applied load is irreversible. Elastic materials such as steels and aluminium deform instantaneously under the application of load and return to the original
state upon the removal of load, provided the applied load is within the yield or plastic limits of the material. An elastic solid polymer is characterized by having a definite shape that deforms under external forces, storing this deformation energy and giving it back upon
the removal of applied load. Material behavior which combines both viscous liquid and solid like features is termed as Viscoelasticity. These viscoelastic materials exhibit a time dependent behavior where the applied load does not cause an instantaneous deformation,
but there is a time lag between the application of load and the resulting deformation. We also observe that in polymeric materials the resultant deformation also depends upon the speed of the applied load.

Characterization of dynamic properties play an important part in comparing mechanical properties of different polymers for quality, failure analysis and new material qualification. Figures 1.4 and 1.5 show the responses of purely elastic, purely viscous and of a viscoelastic material. In the case of purely elastic, the stress and the strain (force and resultant deformation) are in perfect sync with each other, resulting in a phase angle of 0. For a purely viscous response the input and resultant deformation are out of phase by 90o. For a
viscoleastic material the phase angle lies between 0 and 90 degree. Generally the measurements of viscoelastic materials are represented as a complex modulus E* to capture both viscous and elastic behavior of the material. The stress is the sum of an in-phase response and out-of-phase responses.

The so x Cosdelta  term is in phase with the strain, while the term so x Sindelta is out of phase with the applied strain. The modulus E’ is in phase with strain while, E” is out of phase with the strain. The E’ is termed as storage modulus, and E” is termed as the loss modulus.
E’ = s0 x cosdelta
E” = s0 x sindelta

Tan delta = Loss factor = E”/E’

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Limitations of Hyperelastic Material Models

Limitations of Hyperelastic Material Models

Introduction:

Polymeric rubber components are widely used in automotive, aerospace and biomedical systems in the form of vibration isolators, suspension components, seals, o-rings, gaskets etc. Finite element analysis (FEA) is a common tool used in the design and development of these components and hyperelastic material models are used to describe these polymer materials in the FEA methodology. The quality of the CAE carried out is directly related to the input material property and simulation technology. Nonlinear materials like polymers present a challenge to successfully obtain the required input data and generate the material models for FEA. In this brief article we review the limitations of the hyperleastic material models used in the analysis of polymeric materials.

 

 Theory:

A material model describing the polymer as isotropic and hyperelastic is generally used and a strain energy density function (W) is used to describe the material behavior. The strain energy density functions are mainly derived using statistical mechanics, and continuum mechanics involving invariant and stretch based approaches.

Statistical Mechanics Approach

The statistical mechanics approach is based on the assumption that the elastomeric material is made up of randomly oriented molecular chains. The total end to end length of a chain (r) is given by

 

Where µ and lm are material constants obtained from the curve-fitting procedure and Jel is the elastic volume ratio.

Invariant Based Continuum Mechanics Approach

The Invariant based continuum mechanics approach is based on the assumption that for a isotropic, hyperelastic material the strain energy density function can be defined in terms of the Invariants. The three different strain invariants can be defined as

I1 = l12+l22+l32

I2 = l12l22+l22l32+l12l32

I3 = l12l22l32

With the assumption of material incompressibility, I3=1, the strain energy function is dependent on I1 and I2 only. The Mooney-Rivlin form can be derived from Equation 3 above as

W(I1,I2) = C10 (I1-3) + C01 (I2–3)…………………………………………………………(4)

With C01 = 0 the above equation reduces to the Neo-Hookean form.

Stretch Based Continuum Mechanics Approach

The Stretch based continuum mechanics approach is based on the assumption that the strain energy potential can be expressed as a function of the principal stretches rather than the invariants. The Stretch based Ogden form of the strain energy function is defined as

where µi and αi are material parameters and for an incompressible material Di=0.

Neo-Hookean and Mooney-Rivlin models described above are hyperelastic material models where, the strain energy density function is calculated from the invariants of the left Cauchy-Green deformation tensor, while in the Ogden material model the  strain energy density function is calculated from the principal deformation stretch ratios.

 

The Neo-Hookean model, one of the earliest material model is based on the statistical thermodynamics approach of cross-linked polymer chains and as can be studied is a first order material model. The first order nature of the material model makes it a lower order predictor of high strain values. It is thus generally accepted that Neo-Hookean material model is not able to accurately predict the deformation characteristics at large strains.

The material constants of Mooney-Rivlin material model are directly related to the shear modulus ‘G’ of a polymer and can be expressed as follows:

G = 2(C10 + C01 ) …………………………….…(6)

Mooney-Rivlin model defined in equation (4) is a 2nd order material model, that makes it a better deformation predictor that the Neo-Hookean material model. The limitations of the Mooney-Rivlin material model makes it usable upto strain levels of about 100-150%.

Ogden model with N=1,2, and 3 constants is the most widely used model for the analysis of suspension components, engine mounts and even in some tire applications. Being of a different formulation that the Neo-Hookean and  Mooney-Rivlin models, the Ogden model is also a higher level material models and makes it suitable for strains of upto 400 %. With the third order constants the use of Ogden model make it highly usable for curve-fitting with the full range of the tensile curve with the typical ‘S’ upturn.

Discussion and Conclusions:

The choice of the material model depends heavily on the material and the stretch ratios (strains) to which it will be subjected during its service life. As a rule-of-thumb for small strains of approximately 100 % or l=2.0, simple models such as Mooney-Rivlin are sufficient but for higher strains a higher order material model as the Ogden model may be required to successfully simulate the ”upturn” or strengthening that can occur in some materials at higher strains.

REFERENCES:

  1. ABAQUS Inc., ABAQUS: Theory and Reference Manuals, ABAQUS Inc., RI, 02
  2. Attard, M.M., Finite Strain: Isotropic Hyperelasticity, International Journal of Solids and Structures, 2003
  1. Bathe, K. J., Finite Element Procedures Prentice-Hall, NJ, 96
  2. Bergstrom, J. S., and Boyce, M. C., Mechanical Behavior of Particle Filled Elastomers,Rubber Chemistry and Technology, Vol. 72, 2000
  3. Beatty, M.F., Topics in Finite Elasticity: Hyperelasticity of Rubber, Elastomers and Biological Tissues with Examples, Applied Mechanics Review, Vol. 40, No. 12, 1987
  4. Bischoff, J. E., Arruda, E. M., and Grosh, K., A New Constitutive Model for the Compressibility of Elastomers at Finite Deformations, Rubber Chemistry and Technology,Vol. 74, 2001
  5. Blatz, P. J., Application of Finite Elasticity Theory to the Behavior of Rubber like Materials, Transactions of the Society of Rheology, Vol. 6, 196
  6. Kim, B., et al., A Comparison Among Neo-Hookean Model, Mooney-Rivlin Model, and Ogden Model for Chloroprene Rubber, International Journal of Precision Engineering & Manufacturing, Vol. 13.
  7. Boyce, M. C., and Arruda, E. M., Constitutive Models of Rubber Elasticity: A Review, Rubber Chemistry and Technology, Vol. 73, 2000.
  8. Srinivas, K., Material Characterization and FEA of a Novel Compression Stress Relaxation Method to Evaluate Materials for Sealing Applications, 28th Annual Dayton-Cincinnati Aerospace Science Symposium, March 2003.
  9. Srinivas, K., Material Characterization and Finite Element Analysis (FEA) of High Performance Tires, Internation Rubber Conference at the India Rubber Expo, 2005.
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SERVICE LIFE PREDICTION OF POLYMER RUBBER COMPONENTS USING ACCELERATED AGING AND ARRHENIUS EQUATION

Introduction:

Polymeric rubber components are widely used in automotive, aerospace and biomedical systems in the form of seals, o-rings, gaskets, vibration isolators, suspension components etc. The service life of these systems is governed by the useful life of the polymeric materials used in these different applications. Aerospace and biomedical systems are expected to have service life in decades, while automotive components are expected to fully last the 5 years 100,000 warranted miles. Polymeric rubber components can get degraded when exposed to chemical and environmental degradants like ozone, UV rays, oxygen, thermal cycling, engine oils, water etc., and also due to mechanical service stress and strain conditions. It becomes very important to predict life of polymeric and rubber components under these degrading service environments. The most common approach is to accelerate the ageing of a material using elevated temperature tests combined with an extrapolation technique to predict the life time of the material/product at lower temperatures.

Theory and Technique:

One of the most widely used techniques to predict lifetimes of polymeric materials is the use of Arrhenius equation. The technique utilizes accelerated thermal aging of the materials under controlled conditions. Failure times and degradation rate studies are carried out at elevated temperatures and the data is used to extrapolate material performance to ambient conditions. Arrhenius extrapolations assume that a chemical degradation process is controlled by a reaction rate ‘k’,

k = A  e^{-Ea/(RT)}  OR  ln k = ln A +  {-Ea/(RT)}      ———————————(1)

where Ea is the Arrhenius activation energy, R is the universal gas constant (8.314 J/mol °K), T the absolute temperature and A the pre-exponential factor. A log-plot of degradation times (1/k) versus inverse temperature (1/T in °K) is expected to result in a straight line. The linear interpolations along this line can be used to predict properties to lower temperatures.

To be able to successfully use the Arrhenius equation, accelerated testing must be carried out at a minimum of four temperatures above the product application temperature.  To accurately estimate the degradation rate it is important to use a material property which exhibits sufficient range to assure a reliable and accurate determination of the property during the accelerated aging process.  Properties like tensile modulus, tear strength, stress relaxation modulus can be used to study the accelerated aging process and degradation rates.

Figure 1: Tensile Strength of Material at Various Temperatures and Aging Times

 

The identification of ageing mechanisms and the evaluation of dependence of these mechanisms on the mechanical properties of components is important. To successfully apply life prediction technique using the Arrhenius equation, the predominant degradation process has to systematically identified and an appropriate accelerated aging test to replicate the degradation process has to be carried out. The degradation process and failures of aged laboratory samples needs to be correlated to the components in the field. The accelerated aging temperatures need to be suitably chosen to correlate field degradation rates. Generally, a test time of one decade is equivalent to a temperature rise of 10°C

Figure 2: Arrhenius Plot Showing the Degradation Times and Inverse Temperature

 

Key Assumptions:

In most applications involving temperature acceleration replicating a failure mechanism, a degradation process might involve multiple steps with each of the steps having its own rate constants and activation energy. It is assumed that these phenomena can be approximated over the full temperature range by the Arrhenius equation.  It is also assumed that the chemical degradation process plays  major part in the failure mechanism, if the failure is a stress induced one then the Arrhenius equation method cannot be usefully employed. Method assumes that the chemical deterioration induced in the lab is directly correlated to the service life in the field.

Limitations and Benefits:

Arrhenius extrapolation to predict service life using accelerated aging  and degradation exhibits some limitations and many reports showing that temperature effects on degradation kinetics cannot always be described using the Arrhenius equation have been published. However, Arrhenius extrapolation being easy to perform, reproducible, replicable and practically relevant in large amount of field service applications is widely used for lifetime prediction of polymers in different environments.

 

Conclusions:

Various approaches can be applied to determine life of elastomer components used in engineering applications.  It is imperative to define their failure modes and failure mechanisms and establish verification and correlations between field service conditions and laboratory testing samples. The Arrhenius method provides a quantifiable determination of the service life of elastomer components in engineering applications.

 

References:

  1. Celina, M., Gillen, K.T., Assink, R. K., Accelerated Aging and Lifetime Prediction: Review of Non-Arrhenius Behavior due to Two Competing Processes, Polymer Degradation and Stability, Vol. 90, 2005
  2. Leyden, Jerry., Failure Analysis in Elastomer Technology: Special Topics, Rubber Division, 2003
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  4. Bernstein, and Gillen K.T., Predicting the lifetime of Flurorosilicone O-rings, Polymer Degradation and Stability, 2009
  5. Mott, C. M. Roland, Ageing of Natural Rubber in Air and Seawater, Rubber Chemistry and Technology, 2001
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  8. Srinivas, K., Systematic Experimental and Computational Mechanics Failure Analysis Methodologies for Polymer Components, ARDL Technical Report, March 2008.
  9. Dowling, N. E., Mechanical Behavior of Materials, Engineering Methods for Deformation, Fracture and Fatigue Prentice-Hall, NJ, 99
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