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Best Material Model for CPVC

Introduction

I have spent a lot of time in my career studying CPVC (chlorinated polyvinyl chloride). It is a material that is similar to PVC, but has better ductility and maintains its stiffness better at high temperatures. CPVC is used in many applications, one common example is cold and hot water delivery pipes. Typically CPVC performs well in this environment, but the material can become brittle if exposed to certain chemicals for an extended period of time. I have worked on at least one legal case related to this embrittlement issue. In preparation for this article, I poked around the basement of my house and I was able to quickly locate CPVC pipes and other plumbing components made from CPVC. Fortunately, none of the pipe clamps that I could see introduced significant strains in the CPVC components. So I expect the lifetime of the parts to be excellent. 

In this article I examine 7 different candidate material models for CPVC, and show that 2 material models are significantly better than the traditional plasticity model. Can you guess which 2 material models are the most accurate?

Experimental Data Used for the CPVC Material Model Study

In this study I used uniaxial tension data at different strain rates. The data that I used comes with MCalibration, so you can easily reproduce my study if you are interested.

CPVC Stress-Strain Data

Figure 1. Experimental data used in the study.

In the following sections I will go through 7 different candidate material models in order from worst to best!

Results #7: Bergstrom-Boyce Model

BB model prediction CPVC

Figure 2. Comparison between the experimental data and predictions from the Bergstrom-Boyce (BB) model. The average error in the model predictions is 22.4%. No good.

Results #6: Abaqus PRF3YP

PRF predictions of CPVC.

Figure 3. The Abaqus Parallel Rhelogical Framework (PRF) model is not able to accurately predict the response of the CPVC. Particularly the unloading behavior is poor. The average error is 15.9%.

Results #5: Isotropic Hardening Plasticity

EPI Prediction CPVC

Figure 4. The isotropic hardening plasticity model does not work well for CPVC. This to be expected – this type of plasticity model never predicts the unloading response  of polymers accurately. The average error is 14.8%.

Results #4: Kinematic Hardening Plasticity

Kinematic hardening plasticity CPVC

Figure 5. The Abaqus combined hardening plasticity model and the Ansys Chaboche models cannot accurately predict the response of CPVC. Again, the unloading response is poorly predicted. Average error: 13.9%.

Results #3: Johnson-Cook Plasticity

Johnson-Cook for CPVC

Figure 6. The Johnson-Cook plasticity model cannot either predict the unloading response with accuracy. The average error in the model predictions is 12.5%.

Results #2: PolyUMod TNV

PolyUMod TNV for CPVC

Figure 7. The PolyUMod TNV model can accurately predict the response of the CPVC! The average error is 4.8%. Not too bad.

Results #1: PolyUMod TN

PolyUMod TN for CPVC

Figure 8. The PolyUMod TN model is the most accurate model and the winner in this study. The average error for this model was 3.5%. This is really good.

Summary CPVC Material Model Study

Here is a comparison between the different material models. The PolyUMod TN and TNV models are the most accurate models for CPVC. If you have not tried these PolyUMod models, then request a free trial license.

Model Comparison CPVC
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