Limit analysis and finite element evaluation of lateral pipe–soil interaction resistance

2016 ◽  
Vol 53 (1) ◽  
pp. 14-21 ◽  
Author(s):  
W.O. McCarron
Keyword(s):  
Finite Element ◽  
Monte Carlo ◽  
Shear Strength ◽  
Monte Carlo Simulations ◽  
Limit Analysis ◽  
Soil Conditions ◽  
Cohesive Soils ◽  
Perfectly Plastic ◽  
Soil Shear Strength ◽  
Upper Bound Technique

The lateral breakout soil resistance of pipelines supported on undrained cohesive soils determined from limit analysis and finite element methods are compared for a linearly increasing soil strength profile. The limit analysis solution is based on an upper-bound technique. The finite element solutions are developed from coupled Eulerian–Lagrangian simulations. The capacities determined by the two methodologies are in close agreement for the perfectly plastic soil conditions. The relative ease with which the limit analysis solutions are obtained allows rapid investigation of the implications of uncertainty of the soil shear strength profile and pipe embedment via Monte Carlo simulations. Monte Carlo simulations illustrate the implications of correlated random variables describing the shear strength profile and pipe embedment.

Penetration and uplift resistances of two interfering pipelines buried in clays

2021 ◽  
pp. 2150020
Author(s):  
Sorawit Seehavong ◽  
Suraparb Keawsawasvong
Keyword(s):  
Finite Element ◽  
Shear Strength ◽  
Limit Analysis ◽  
Failure Mechanisms ◽  
Ground Surface ◽  
Linear Increase ◽  
Unit Weight ◽  
Cohesive Soils ◽  
Input Parameters ◽  
Bearing Loads

The primary aim of this paper is to determine penetration and uplift resistances of two interfering pipelines buried in clay with a linear increase in strength. The advanced finite element limit analysis of upper and lower bound theorems is used to perform new limit analysis solutions for both penetration and uplift resistances of two interfering pipelines. The strength profiles of cohesive soils are the cases of normally consolidated clays in deep water by setting the shear strength at the ground surface to be zero and linearly increased with the depth. The twin pipelines have the same geometries and are simultaneously failed at the same magnitude of the failure uplift or bearing loads. There are three considered input parameters including the spacing between the pipes, the embedded depth of the pipes, and the unit weight of soils. All input parameters have significant influences on the penetration and uplift resistances of two interfering pipelines. Failure mechanisms of the problems are also investigated, and stability charts of the penetration and uplift resistances of two interfering pipelines are produced for practical uses in offshore geotechnical engineering.

Finite Element Modeling of a Mechanically Stabilized Earth Trial Wall

2021 ◽  
pp. 036119812110164
Author(s):  
Andrew Lees ◽  
Michael Dobie
Keyword(s):  
Finite Element ◽  
Shear Strength ◽  
Retaining Wall ◽  
Back Analysis ◽  
Soil Parameters ◽  
Failure Behavior ◽  
Valuable Insight ◽  
Deformation And Failure ◽  
First Case ◽  
Soil Shear Strength

Polymer geogrid reinforced soil retaining walls have become commonplace, with routine design generally carried out by limiting equilibrium methods. Finite element analysis (FEA) is becoming more widely used to assess the likely deformation behavior of these structures, although in many cases such analyses over-predict deformation compared with monitored structures. Back-analysis of unit tests and instrumented walls improves the techniques and models used in FEA to represent the soil fill, reinforcement and composite behavior caused by the stabilization effect of the geogrid apertures on the soil particles. This composite behavior is most representatively modeled as enhanced soil shear strength. The back-analysis of two test cases provides valuable insight into the benefits of this approach. In the first case, a unit cell was set up such that one side could yield thereby reaching the active earth pressure state. Using FEA a test without geogrid was modeled to help establish appropriate soil parameters. These parameters were then used to back-analyze a test with geogrid present. Simply using the tensile properties of the geogrid over-predicted the yield pressure but using an enhanced soil shear strength gave a satisfactory comparison with the measured result. In the second case a trial retaining wall was back-analyzed to investigate both deformation and failure, the failure induced by cutting the geogrid after construction using heated wires. The closest fit to the actual deformation and failure behavior was provided by using enhanced fill shear strength.

Plastic Limit Loads for Through-Wall Cracked Pipes Using Finite Element Limit Analysis

2006 ◽  
Vol 321-323 ◽  
pp. 724-728
Author(s):  
Nam Su Huh ◽  
Yoon Suk Chang ◽  
Young Jin Kim
Keyword(s):  
Finite Element ◽  
Limit Analysis ◽  
Structural Integrity ◽  
Three Dimensional ◽  
Limit Load ◽  
Plastic Behavior ◽  
Plastic Limit ◽  
Integrity Assessment ◽  
Perfectly Plastic ◽  
Elastic Perfectly Plastic

The present paper provides plastic limit load solutions for axial and circumferential through-wall cracked pipes based on detailed three-dimensional (3-D) finite element (FE) limit analysis using elastic-perfectly plastic behavior. As a loading condition, both single and combined loadings are considered. Being based on detailed 3-D FE limit analysis, the present solutions are believed to be valuable information for structural integrity assessment of cracked pipes.

Quantum Corrections Based on the 2-D Schrödinger Equation for 3-D Finite Element Monte Carlo Simulations of Nanoscaled FinFETs

2014 ◽  
Vol 61 (2) ◽  
pp. 423-429 ◽  
Author(s):  
Jari Lindberg ◽  
Manuel Aldegunde ◽  
Daniel Nagy ◽  
Wulf G. Dettmer ◽  
Karol Kalna ◽  
...  
Keyword(s):  
Finite Element ◽  
Monte Carlo ◽  
Schrödinger Equation ◽  
Monte Carlo Simulations ◽  
Schrodinger Equation ◽  
Quantum Corrections

scholarly journals Influence of Data Splitting on Performance of Machine Learning Models in Prediction of Shear Strength of Soil

2021 ◽  
Vol 2021 ◽  
pp. 1-15 ◽  
Author(s):  
Quang Hung Nguyen ◽  
Hai-Bang Ly ◽  
Lanh Si Ho ◽  
Nadhir Al-Ansari ◽  
Hiep Van Le ◽  
...  
Keyword(s):  
Machine Learning ◽  
Monte Carlo ◽  
Shear Strength ◽  
Mean Squared Error ◽  
Absolute Error ◽  
Engineering Properties ◽  
Stable Model ◽  
Predictive Capability ◽  
Effective Manner ◽  
Soil Shear Strength

The main objective of this study is to evaluate and compare the performance of different machine learning (ML) algorithms, namely, Artificial Neural Network (ANN), Extreme Learning Machine (ELM), and Boosting Trees (Boosted) algorithms, considering the influence of various training to testing ratios in predicting the soil shear strength, one of the most critical geotechnical engineering properties in civil engineering design and construction. For this aim, a database of 538 soil samples collected from the Long Phu 1 power plant project, Vietnam, was utilized to generate the datasets for the modeling process. Different ratios (i.e., 10/90, 20/80, 30/70, 40/60, 50/50, 60/40, 70/30, 80/20, and 90/10) were used to divide the datasets into the training and testing datasets for the performance assessment of models. Popular statistical indicators, such as Root Mean Squared Error (RMSE), Mean Absolute Error (MAE), and Correlation Coefficient (R), were employed to evaluate the predictive capability of the models under different training and testing ratios. Besides, Monte Carlo simulation was simultaneously carried out to evaluate the performance of the proposed models, taking into account the random sampling effect. The results showed that although all three ML models performed well, the ANN was the most accurate and statistically stable model after 1000 Monte Carlo simulations (Mean R = 0.9348) compared with other models such as Boosted (Mean R = 0.9192) and ELM (Mean R = 0.8703). Investigation on the performance of the models showed that the predictive capability of the ML models was greatly affected by the training/testing ratios, where the 70/30 one presented the best performance of the models. Concisely, the results presented herein showed an effective manner in selecting the appropriate ratios of datasets and the best ML model to predict the soil shear strength accurately, which would be helpful in the design and engineering phases of construction projects.

Robustness of Residual Stresses in Castings and an Improved Process Window

2009 ◽  
Author(s):  
Magnus Hofwing ◽  
Niclas Stro¨mberg
Keyword(s):  
Finite Element ◽  
Monte Carlo ◽  
Thermal Expansion ◽  
Monte Carlo Simulations ◽  
Young’S Modulus ◽  
Thermal Expansion Coefficient ◽  
Expansion Coefficient ◽  
Young's Modulus ◽  
Process Window ◽  
Quadratic Response

In this work the robustness of residual stresses in finite element simulations with respect to deviations in mechanical parameters in castings is evaluated. Young’s modulus, the thermal expansion coefficient and the hardening are the studied parameters. A 2D finite element model of a stress lattice is used. The robustness is evaluated by comparing purely finite element based Monte Carlo simulations and Monte Carlo simulations based on linear and quadratic response surfaces. Young’s modulus, the thermal expansion coefficient and the hardening are assumed to be normal distributed with a standard deviation that is 10% of their nominal value at different temperatures. In this work an improved process window is also suggested to show the robustness graphically. By using this window it is concluded that least robustness is obtained for high hardening values in combination to deviations in Young’s modulus and the thermal expansion coefficient. It is also concluded that quadratic response surface based Monte Carlo simulations substitute finite element based Monte Carlo simulations satisfactory. Furthermore, the standard deviation of the responses are evaluated analytically by using the Gauss formula, and are compared to results from Monte Carlo simulations. The analytical solutions are accurate as long as the Gauss formula is not utilized close to a stationary point.

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