scholarly journals An Empirical Equation for Failure Pressure Prediction of High Toughness Pipeline with Interacting Corrosion Defects Subjected to Combined Loadings Based on Artificial Neural Network

Mathematics ◽  
2021 ◽  
Vol 9 (20) ◽  
pp. 2582
Author(s):  
Suria Devi Vijaya Kumar ◽  
Saravanan Karuppanan ◽  
Mark Ovinis
Keyword(s):  
Numerical Methods ◽  
Compressive Stress ◽  
Empirical Equation ◽  
Training Data ◽  
Test Results ◽  
Element Analysis ◽  
Failure Pressure ◽  
Burst Test ◽  
High Toughness ◽  
Axial Compressive Stress

Conventional pipeline corrosion assessment methods for failure pressure prediction do not account for interacting defects subjected to internal pressure and axial compressive stress. In any case, the failure pressure predictions are conservative. As such, numerical methods are required. This paper proposes an alternative to the computationally expensive numerical methods, specifically an empirical equation based on Finite Element Analysis (FEA). FEA was conducted to generate training data for an ANN after validating the method against full scale burst test results from past research. An ANN with four inputs and one output was developed. The equation was developed based on the weights and biases of an ANN model trained with failure pressure from the FEA of a high toughness pipeline for various defect spacings, defect depths, defect lengths, and axial compressive stresses. The proposed model was validated against actual burst test results for high toughness materials, with a R2 value of 0.99. Extensive parametric study was subsequently conducted to determine the effects of defect spacing, defect length, defect depth, and axial compressive stress on the failure pressure of the pipe. The results of the empirical equation are comparable to the results from numerical methods for the pipes and loadings considered in this study.

scholarly journals Failure Pressure Prediction of High Toughness Pipeline with a Single Corrosion Defect Subjected to Combined Loadings Using Artificial Neural Network (ANN)

Metals ◽  
2021 ◽  
Vol 11 (2) ◽  
pp. 373
Author(s):  
Suria Devi Vijaya Kumar ◽  
Saravanan Karuppanan ◽  
Mark Ovinis
Keyword(s):  
Neural Network ◽  
Internal Pressure ◽  
Compressive Stress ◽  
Element Analysis ◽  
Failure Pressure ◽  
Corrosion Defect ◽  
High Toughness ◽  
Proposed Model ◽  
Axial Compressive Stress ◽  
Artificial Neural Network Ann

Conventional pipeline corrosion assessment methods result in failure pressure predictions that are conservative, especially for pipelines that are subjected to internal pressure and axial compressive stress. Alternatively, numerical methods may be used. However, they are computationally expensive. This paper proposes an analytical equation based on finite element analysis (FEA) for the failure pressure prediction of a high toughness corroded pipeline with a single corrosion defect subjected to internal pressure and axial compressive stress. The equation was developed based on the weights and biases of an Artificial Neural Network (ANN) model trained with failure pressure from finite element analysis (FEA) of a high toughness pipeline for various defect depths, defect lengths, and axial compressive stresses. The proposed model was validated against actual burst test results for high toughness materials and was found to be capable of making accurate predictions with a coefficient of determination (R2) of 0.99. An extensive parametric study using the proposed model was subsequently conducted to determine the effects of defect length, defect depth, and axial compressive stress on the failure pressure of a corroded pipe with a single defect. The application of ANN together with FEA has shown promising results in the development of an empirical solution for the failure pressure prediction of pipes with a single corrosion defect subjected to internal pressure and axial compressive stress.

Fracture Mode Prediction Method for Pipe With Wall-Thinning by Using the History Data of Strain Ratio

2008 ◽  
Author(s):  
Irwan Herman ◽  
Toshiyuki Meshii
Keyword(s):  
Fracture Mode ◽  
Prediction Method ◽  
Strain Ratio ◽  
Burst Pressure ◽  
Test Results ◽  
Element Analysis ◽  
Load Increment ◽  
History Data ◽  
Burst Test ◽  
Wall Thinning

In this study, based on the burst test results of pipes with wall-thinning, we have investigated the effect of flaw length δz and pipe size (mean radius Rm) on the burst pressure by using finite element analysis (FEA). Then, the history data of strain ratio εz/εθ along the load increment was used for the fracture mode prediction. Moreover, effect of the wall thickness at the flaw portion t1 on the fracture mode was investigated. Finally, fracture mode prediction method for pipes with wall-thinning was proposed.

scholarly journals Failure Pressure Prediction of a Corroded Pipeline with Longitudinally Interacting Corrosion Defects Subjected to Combined Loadings Using FEM and ANN

2021 ◽  
Vol 9 (3) ◽  
pp. 281
Author(s):  
Michael Lo ◽  
Saravanan Karuppanan ◽  
Mark Ovinis
Keyword(s):  
Neural Network ◽  
Finite Element ◽  
Training Data ◽  
Percentage Error ◽  
Learning Tools ◽  
Ann Model ◽  
Element Analysis ◽  
Failure Pressure ◽  
Corrosion Defects ◽  
Artificial Neural Network Ann

Machine learning tools are increasingly adopted in various industries because of their excellent predictive capability, with high precision and high accuracy. In this work, analytical equations to predict the failure pressure of a corroded pipeline with longitudinally interacting corrosion defects subjected to combined loads of internal pressure and longitudinal compressive stress were derived, based on an artificial neural network (ANN) model trained with data obtained from the finite element method (FEM). The FEM was validated against full-scale burst tests and subsequently used to simulate the failure of a pipeline with various corrosion geometric parameters and loadings. The results from the finite element analysis (FEA) were also compared with the Det Norske Veritas (DNV-RP-F101) method. The ANN model was developed based on the training data from FEA and its performance was evaluated after the model was trained. Analytical equations to predict the failure pressure were derived based on the weights and biases of the trained neural network. The equations have a good correlation value, with an R2 of 0.9921, with the percentage error ranging from −9.39% to 4.63%, when compared with FEA results.

A method for the simultaneous derivation of tensile and compressive behaviour of materials under Bauschinger effect using bend tests

2006 ◽  
Vol 220 (10) ◽  
pp. 1509-1518 ◽  
Author(s):  
G Urriolagoitia-Sosa ◽  
J F Durodola ◽  
A Lopez-Castro ◽  
N A Fellows
Keyword(s):  
Compressive Stress ◽  
Bauschinger Effect ◽  
Experimental Testing ◽  
Kinematic Hardening ◽  
Theoretical Data ◽  
Test Results ◽  
Stress Strain ◽  
Element Analysis ◽  
Strain Behaviour ◽  
Hardening Rules

Some materials exhibit Bauschinger effect as a consequence of strain hardening. The effect leads to asymmetric tensile and compressive stress-strain behaviour. If the hardening behaviour in either tension or compression is known, combined isotropic/kinematic hardening rules can be used to estimate the hardening behaviour in the other. These rules are, however, only approximate empirical relationships that are derived from the analysis of separate tensile and compressive test results. This article presents a method for the simultaneous derivation of tensile and compressive stress-strain behaviour from bending tests only. The information required is strains at the top and bottom surfaces of beams and moment as load is incrementally applied. The derivation of the method is based on the application of tensile and moment equilibrium conditions. The proposed method is tested on theoretical data obtained from finite-element analysis and as well as on data from actual experimental testing. The agreement between the results obtained is very good.

scholarly journals Influence of Circumferential Flaw Length on Internal Burst Pressure of a Wall-Thinned Pipe

2012 ◽  
Author(s):  
Masataka Tsuji ◽  
Toshiyuki Meshii
Keyword(s):  
Finite Element Analysis ◽  
Fracture Mode ◽  
Experimental Results ◽  
The Other ◽  
Burst Pressure ◽  
Test Results ◽  
Element Analysis ◽  
Burst Test ◽  
Axial Crack ◽  
Planar Flaw

The effect of the circumferential angle of a flaw θ on the internal burst pressure pf of pipes with artificial wall-thinned flaws is examined. When evaluating pf of wall-thinned straight pipes, the effect of θ has been conventionally not regarded as important. Therefore, a burst pressure equation for an axial crack inside a cylinder (Fig. 1, left), such as Kiefner’s equation [1] is widely used [2], [3]. However, it should be noted that there exist the following implicit assumptions when applying the equation for planar flaws to non-planar flaws. 1) The fracture mode of a non-planar flaw under consideration is identical with that of the crack. 2) The effect of θ, which is not considered for an axial crack on pf, is small or negligible. However, from the systematic burst test results of carbon pipes with artificial wall-thinned flaws, Meshii [4] showed that these implicit assumptions may not be correct. On the other hand, the significance of the effect of the fracture mode on pf and the condition for θ to affect pf are not clear. Therefore, in this paper, Meshii’s experimental results are evaluated in farther detail. The purpose of the evaluation was set to clarify the effect of θ on pf. Specifically, the significance of flaw configuration (axial length δz and wall-thinning ratio t1/t) was studied in relation to θ and pf. In addition, a simulation of the effect by a Finite Element Analysis (FEA) was attempted. From the experimental results, θ tended to affect pf in cases with large δz, and t1/t also was correlated to a decrease in pf with the increase of θ. These tendencies were successfully simulated by the elastic-plastic FEA. This effect means the burst pressure predicted for a crack with identical ligament thickness decreases with the increase of θ, so that the effect by θ on pf should not be ignored.

Finite Element Analysis of Reinforced Concrete Beams with Exterior FRP Shell

2011 ◽  
Vol 243-249 ◽  
pp. 1461-1465
Author(s):  
Chuan Min Zhang ◽  
Chao He Chen ◽  
Ye Fan Chen
Keyword(s):  
Mechanical Properties ◽  
Finite Element Analysis ◽  
Finite Element ◽  
Reinforced Concrete ◽  
Concrete Beams ◽  
Reinforced Concrete Beams ◽  
Test Results ◽  
Contact Interface ◽  
Accurate Calculation ◽  
Element Analysis

The paper makes an analysis of the reinforced concrete beams with exterior FRP Shell in Finite Element, and compares it with the test results. The results show that, by means of this model, mechanical properties of reinforced concrete beams with exterior FRP shell can be predicted better. However, the larger the load, the larger deviation between calculated values and test values. Hence, if more accurate calculation is required, issues of contact interface between the reinforced concrete beams and the FRP shell should be taken into consideration.

Finite Element Analysis of Drum on the New Type Self-Driven Towing Machine for Cable

2011 ◽  
Vol 55-57 ◽  
pp. 664-669
Author(s):  
Jin Ning Nie ◽  
Hui Wang ◽  
De Feng Xie
Keyword(s):  
Finite Element Analysis ◽  
Finite Element ◽  
Stress Analysis ◽  
Compressive Stress ◽  
Wire Rope ◽  
Ansys Software ◽  
Element Analysis ◽  
Structure Improvement ◽  
Improvement Measures ◽  
New Type

According to the situation that the dual-friction drums on the new type towing machine lack stress analysis when designed, the safety is difficult to test and verify. The pull of wire rope in various positions was derived and calculated, so both compressive stress and tangent friction force generated by the pull of wire rope were calculated. The result made by ANSYS software demonstrates the safety of the left drum which suffers from larger loads, structure improvement measures are put forward for the drum.

THE DYNAMIC IMPACT RESPONSE OF PP∕PA BLENDS UNDER MULTI-AXIAL COMPRESSIVE STRESS STATE

2008 ◽  
Author(s):  
Shi Shaoqiu ◽  
Yu Bing ◽  
Yan Linbao ◽  
Alberto D’Amore ◽  
Domenico Acierno ◽  
...  
Keyword(s):  
Stress State ◽  
Compressive Stress ◽  
Impact Response ◽  
Dynamic Impact ◽  
Axial Compressive Stress
Sign in / Sign up

Export Citation Format

Share Document