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Pipeline Stress Test Simulation Under Freeze-Thaw Cycling via the XGBoost-Based Prediction Model
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This study conducted ten freeze-thaw cyclic tests to clarify the effect of freeze-thaw cycles on the forces acting on the buried oil pipeline. The stress evolution in the Q345 steel pipeline versus the number of freeze-thaw cycles was obtained. The test results were consistent with the COMSOL simulation of the effect of different moisture contents on the pipeline bottom stress. Besides the proposed XGBoost model, eleven machine-learning stress prediction models were also applied to 10–20 freeze-thaw cycling tests. The results showed that during the freeze-thaw process, the compressive stress at the pipeline bottom did not exceed −69.785 MPa. After eight freeze-thaw cycles, the extreme value of the principal stress of -252.437MPa, i.e., 73.17% of the yield stress, was reached. When the initial moisture content exceeded 20%, the eighth freeze-thaw cycle’s pipeline stress decreased remarkably. The XGBoost model effectively predicted the pipeline’s principal stress in each cycle of 10 freeze-thaw cyclic tests, with R2 = 0.978, MSE = 0.021, and MAE = 0.102. The above compressive stress fluctuated from −131.226 to −224.105 MPa. The predicted values well matched the experimental ones, being in concert with the “ratcheting effect” predicted by the freeze-thaw cycle theory. The results obtained provide references for the design, operation, and maintenance of buried oil pipelines.
Frontiers Media SA
Title: Pipeline Stress Test Simulation Under Freeze-Thaw Cycling via the XGBoost-Based Prediction Model
Description:
This study conducted ten freeze-thaw cyclic tests to clarify the effect of freeze-thaw cycles on the forces acting on the buried oil pipeline.
The stress evolution in the Q345 steel pipeline versus the number of freeze-thaw cycles was obtained.
The test results were consistent with the COMSOL simulation of the effect of different moisture contents on the pipeline bottom stress.
Besides the proposed XGBoost model, eleven machine-learning stress prediction models were also applied to 10–20 freeze-thaw cycling tests.
The results showed that during the freeze-thaw process, the compressive stress at the pipeline bottom did not exceed −69.
785 MPa.
After eight freeze-thaw cycles, the extreme value of the principal stress of -252.
437MPa, i.
e.
, 73.
17% of the yield stress, was reached.
When the initial moisture content exceeded 20%, the eighth freeze-thaw cycle’s pipeline stress decreased remarkably.
The XGBoost model effectively predicted the pipeline’s principal stress in each cycle of 10 freeze-thaw cyclic tests, with R2 = 0.
978, MSE = 0.
021, and MAE = 0.
102.
The above compressive stress fluctuated from −131.
226 to −224.
105 MPa.
The predicted values well matched the experimental ones, being in concert with the “ratcheting effect” predicted by the freeze-thaw cycle theory.
The results obtained provide references for the design, operation, and maintenance of buried oil pipelines.
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