Proposal of electromagnetic inspection of opposite side defect in steel using 3-D nonlinear FEM taking account of minor loop and residual magnetization

2016 ◽  
Author(s):  
S. Yoshioka ◽  
T. Tujigou ◽  
Y. Gotoh
Keyword(s):  
Residual Magnetization ◽  
Nonlinear Fem ◽  
Minor Loop

scholarly journals Postbuckling Analysis Of A Rectangular Plate Loaded In Compression

2015 ◽  
Vol 15 (2) ◽  
Author(s):  
Jozef Havran ◽  
Martin Psotný
Keyword(s):  
Rectangular Plate ◽  
User Program ◽  
Nonlinear Fem ◽  
Buckling Mode ◽  
Energy Principle ◽  
Initial Imperfections ◽  
Potential Energy Principle ◽  
Total Potential ◽  
The Stability ◽  
Minimum Total Potential Energy

Abstract The stability analysis of a thin rectangular plate loaded in compression is presented. The nonlinear FEM equations are derived from the minimum total potential energy principle. The peculiarities of the effects of the initial imperfections are investigated using the user program. Special attention is paid to the influence of imperfections on the post-critical buckling mode. The FEM computer program using a 48 DOF element has been used for analysis. Full Newton-Raphson procedure has been applied.

Mechanisms of Third-order Harmonic in TC-SAW Resonators Using a Nonlinear FEM Model

2021 ◽  
Author(s):  
Peng Guan ◽  
Ruchuan Shi ◽  
Yang Yang ◽  
Peng Qin ◽  
Tao Han
Keyword(s):  
Nonlinear Fem ◽  
Third Order ◽  
Fem Model ◽  
Saw Resonators

Optimization of Flexible Pipes Dynamic Analysis Using Artificial Neural Networks

2016 ◽  
Author(s):  
Victor Chaves ◽  
Luis V. S. Sagrilo ◽  
Vinícius Ribeiro Machado da Silva
Keyword(s):  
Dynamic Analysis ◽  
Fem Simulation ◽  
Training Data ◽  
Local Analysis ◽  
Flexible Pipe ◽  
Nonlinear Fem ◽  
Irregular Wave ◽  
Flexible Pipes ◽  
Artificial Neural ◽  
Hybrid Methodology

Irregular wave dynamic analysis is an extremely computational expensive process on flexible pipes design. One emerging method that aims to reduce these computational costs is the hybrid methodology that combines Finite Element Analyses (FEA) and Artificial Neural Network (ANN). The proposed hybrid methodology aims to predict flexible pipe tension and curvatures in the bend stiffener region. Firstly using short FEA simulations to train the ANN, and then using only the ANN and the prescribed floater motions to get the rest of the response histories. Two approaches are developed with respect to the training data. One uses an ANN for each sea state in the wave scatter diagram and the other develops an ANN for each wave incidence direction. In order to evaluate the accuracy of the proposed approaches, a local analysis is applied, based on the predicted tension and curvatures, to calculate stresses in tension armour wires and the corresponding flexible pipe fatigue lifes. The results are compared to those from full nonlinear FEM simulation.

STUDIES OF F ON SUPERCONDUCTIVITY IN HIGH-Tc (Bi,Pb)SrCaCu(O,F) SUPERCONDUCTORS

1993 ◽  
Vol 07 (17) ◽  
pp. 1127-1132
Author(s):  
JIANGUO CAI ◽  
XIAOLONG ZHANG ◽  
XIANGHUA ZHOU ◽  
QIN WEI
Keyword(s):  
Critical Current Density ◽  
Flux Pinning ◽  
Weak Link ◽  
Meissner Effect ◽  
Experimental Methods ◽  
Residual Magnetization ◽  
High Tc ◽  
Bean Model ◽  
Pinning Potential ◽  
The Difference

In this article, the experimental results of the superconductivity in high-Tc (Bi,Pb) 2 Sr 2 Ca 2 Cu 3( O y, F x), x = 0–0.84, is described. Its critical current density Jc is about ten times larger than that of undoped F sample undergoing the same technology. The causes for the increase in Jc are studied by several experimental methods. The difference in quantity between Meissner effect and shield effect indicates that the effect on superconductivity is from the weak-link regions of the superconductor grains. SEM shows that F atoms doped in BPSCCO superconductor can make its grains grow larger, arrange regularly, and increase in touch area. These changes strengthen the netty link between grains. The magnitude of residual magnetization of F-doped sample is eight times as large as that of the undoped one. The flux pinning potential U0 is calculated from the Bean model. The U0 in F-doped sample (when H = 64 Oe, x = 0.64) is eight times as large as that in the undoped one.

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