Validation and Uncertainty of Material Data

Category: V&V – Best Practice | Revised 2026-10-01
CAE visualization for material data validation theory - technical simulation diagram
Validation and Uncertainty of Material Data

Theory: the fitted test vs the deformation you need

Overview

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We set material constants by fitting curves to test data. Isn't that enough?

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It can be, if the deformation matches the fitted test. The problem is when the part deforms differently. Rubber-like materials respond differently in tension, compression, shear and in-plane biaxial stretching, and some constant combinations match one mode but miss another badly. A clean curve fit is reassuring, but it only reproduces the fitting data and proves nothing about prediction. So you check predictions against tests not used in fitting. That's material data validation.

Reference material (Treloar's rubber, three-term Ogden)

$$ P_{uni} = \sum_{p=1}^{3}\mu_p\left(\lambda^{\alpha_p - 1} - \lambda^{-\alpha_p/2 - 1}\right),\qquad P_{biax} = \sum_{p=1}^{3}\mu_p\left(\lambda^{\alpha_p - 1} - \lambda^{-2\alpha_p - 1}\right) $$

P is nominal stress and λ stretch. Constants μ = 0.618, 0.00118, −0.00981 MPa and α = 1.3, 5.0, −2.0 (Ogden, 1972); initial shear modulus 0.414 MPa. Values from these formulas are treated as "test data".

Mooney–Rivlin model

$$ P_{uni} = 2\left(\lambda - \lambda^{-2}\right)\left(C_{10} + \frac{C_{01}}{\lambda}\right),\qquad P_{biax} = 2\left(\lambda - \lambda^{-5}\right)\left(C_{10} + C_{01}\lambda^2\right) $$

With C01 = 0 it becomes neo-Hookean. Least-squares fits used uniaxial stretches 1.05–3.0 and equibiaxial 1.05–2.5.

Coffee Break Trivia

Treloar's data

In 1944 Treloar tested vulcanised natural rubber in uniaxial tension, equibiaxial tension and pure shear, measuring stress to large stretches. As a classic dataset of different deformation modes on one material, it is still the benchmark for comparing new hyperelastic models. Ogden's 1972 model demonstrated on these data that one set of constants could represent all three modes well.

Worked examples

Example: how fitting choices change predictions

Model and fitC10 (MPa)C01 (MPa)Max uniaxial errorMax equibiaxial errorEquibiaxial stress at λ = 2.0
Neo-Hookean (uniaxial only)0.160022.2%26.6%0.629 MPa
Mooney–Rivlin (uniaxial only)0.1120.1126.6%309.5%2.209 MPa
Mooney–Rivlin (uniaxial + equibiaxial)0.1600.00917.9%20.1%0.774 MPa

The reference equibiaxial stress at λ = 2.0 is 0.806 MPa. At uniaxial λ = 3.0 the uniaxial-only Mooney–Rivlin fit gives 0.863 MPa, exactly matching the reference.

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The Mooney–Rivlin fit that matches uniaxial best is the worst in biaxial.

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C10 and C01 act in similar ways in uniaxial tension, so uniaxial data barely determines how they split. Least squares picks the split that best fits the uniaxial curve, which here inflated C01. In equibiaxial tension C01 is multiplied by λ² and behaves very differently, so an oversized C01 multiplies predicted stress. That's why a 6.6% uniaxial fit was 2.7 times off in biaxial. Including biaxial data keeps C01 small and both errors near 20%. Using uniaxial-only constants is risky for parts dominated by biaxial deformation, such as rubber seals, tyres and inflated membranes.

Steps to validate material data

  1. From part analyses, identify main deformation modes and ranges of strain, temperature and strain rate.
  2. Gather tests covering those ranges (uniaxial, biaxial, shear, volumetric).
  3. Fit tests simultaneously and check constants are physically reasonable (stability etc.).
  4. Check predictions against tests or component tests not used in fitting.
  5. Estimate constant uncertainty from test scatter and assess its effect on results.
Coffee Break Trivia

“Seal contact pressure fell short”

A rubber O-ring leaked in prototype despite analysis showing ample contact pressure. Its constants had been fitted to the supplier's uniaxial tension data alone. In a compressed O-ring cross-section, material near the surface deforms almost biaxially. Refitting with added biaxial and planar tests lowered predicted contact pressure by about 30%, explaining the leak. Increasing squeeze in the design fixed it.

Common mistakes

Mistakes and fixes

MistakeEffectFix
Fitting uniaxial onlyLarge errors elsewhereFit multiple modes
Calling a good fit validationPredictive power unknownTest on unused data
Using beyond test rangeInstability on extrapolationCheck ranges
Ignoring temperature and rateFails under other conditionsTest per condition
Ignoring scatterOverconfident marginsQuantify uncertainty
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Structural AnalysisFluid Analysis (CFD)Thermal Analysis
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