Fatigue Life Prediction for Polymeric Composite Materials Subjected to Bending Loads at Elevated Tem

1
Fatigue Life Prediction for Polymeric Composite
Materials Subjected to Bending Loads at Elevated
Temperatures

• C. Mahieux, J. Jackson, S. Pipik, S. Case,
• and K. Reifsnider
• Materials Response Group
• Virginia Tech
• Blacksburg, VA 24061-0219, USA

2
Outline

• Motivation for the research
• Modeling philosophy
• Development of experimental inputs
• Modeling predictions and comparison to data
• Conclusions
• Ongoing and future work

3
Use of flexible pipe in offshore oil industry
(Wellstream Inc.)

• Advantages of Polymer Composite material in
  flexible pipes
• 30 weight reduction - greater depths, lower deck
  loads
• Corrosion resistance - longer life, more fluid
  options

4
Typical loading environment

• Mechanical loads
• Tensile loads due to hanging weight
• Cyclic Bending loads due to wave-motion
• Positive and negative internal pressures
• Environmental loads
• Exposure to elevated temperatures
• Exposure to aggressive chemicals

5
Material

• Carbon Fiber/Polyphenylene Sulfide (PPS)
• Manufactured by Baycomp, Ontario Canada

6
The use of remaining strength as a state variable

• Track remaining strength of the critical element
  during the fatigue process
• Define a scalar failure function based upon
  tensor strength and stresses use this failure
  function for calculations
• May include the effects of changing loading
  conditions

Sult
Stress or Strength
Life Curve
t1
t2
Time
7
Mathematical representation

• Some possible choices
• Maximum stress/strain
• Tsai-Hill/Tsai-Wu

• Define a failure criterion, Fa, and a remaining
  strength in terms of that failure criterion, Fr
• From kinetics we have the change in remaining
  strength over the interval
• Fa is constant over
  
• For the special case in which is equal to zero

8
Mathematical representation

• For step loading, introduce the concept of
  "pseudo-time" based on the idea of equivalent
  damage

9
Mathematical representation

• Calculate change in remaining strength over the
  interval

10
Approach for variable loading with rupture and
fatigue acting

• Divide each step of loading into time increments
• Treat each increment as a stress rupture problem
  (constant applied stress and temperature)
• Reduce residual strength due to time dependent
  damage accumulation
• Refine number of intervals until residual
  strength converges
• Input next load level
• Check for load reversal. If load reversal,
  increment by 1/2 cycle and reduce residual
  strength due to fatigue damage accumulation

11
Prediction of combined rupture and fatigue on
coupon level

• Characterize elevated temperature effect with
  bending rupture tests at temperature
• Characterize fatigue effect with room temperature
  fatigue tests
• Combine effects using analysis and compare to
  experimental results

12
Characterize temperature effect

• Bending rupture tests at 75C and 90C

13
Characterize temperature effect(time to rupture)
End-loaded bending rupture test results at 90C
14
Characterize temperature effect(remaining
strength)
End-loaded bending rupture test results at 90C
15
Characterize fatigue effect(cycles to failure)
End-loaded bending fatigue tests
16
Characterize fatigue effect(cycles to failure)
End-loaded bending fatigue tests
17
Predict of elevated temperature fatigue behavior
18
Predict of elevated temperature fatigue behavior
19
Conclusions

• A life prediction method for composites based
  upon remaining strength has been developed. The
  general approach is
• Conduct characterization tests and model behavior
  (under a single condition)
• Combine effects using life prediction analysis
• Validate life prediction using controlled
  experimental results
• Poor prediction at 90C
• Better prediction at 75C

20
Ongoing/Future work

• Refine analysis to eliminate discrepancies
  between model/experiments
• Further understanding of the failure process
  less reliance on phenomenological expressions
• Conducting additional experiments to
  validate/repudiate the approach

21
Acknowledgements

• Air Force Office of Scientific Research
• National Science Foundation
• NASA Langley Research Center