Numerical deflection and stress prediction of cutout borne damaged composite flat/curved panel structure

Structures ◽  
2021 ◽  
Vol 31 ◽  
pp. 660-670
Author(s):  
Hukum Chand Dewangan ◽  
Subrata Kumar Panda ◽  
Chetan Kumar Hirwani
Keyword(s):  
Curved Panel ◽  
Stress Prediction

Rancang Bangun Sistem Pakar Prediksi Stres Belajar Dengan Neural Network Algoritma Backpropagation

2016 ◽  
Vol 7 (2) ◽  
pp. 105-112
Author(s):  
Adhi Kusnadi ◽  
Idul Putra
Keyword(s):  
Neural Network ◽  
Expert System ◽  
Stress Level ◽  
Network Structure ◽  
Human Being ◽  
Accuracy Rate ◽  
Backpropagation Algorithm ◽  
Stress Prediction ◽  
Index Terms ◽  
Hidden Nodes

Stress will definitely be experienced by every human being and the level of stress experienced by each individual is different. Stress experienced by students certainly will disturb their study if it is not handled quickly and appropriately. Therefore we have created an expert system using a neural network backpropagation algorithm to help counselors to predict the stress level of students. The network structure of the experiment consists of 26 input nodes, 5 hidden nodes, and 2 the output nodes, learning rate of 0.1, momentum of 0.1, and epoch of 5000, with a 100% accuracy rate. Index Terms - Stress on study, expert system, neural network, Stress Prediction

On the use of neural networks for dynamic stress prediction in Francis turbines by means of stationary sensors

2021 ◽  
Vol 170 ◽  
pp. 652-660
Author(s):  
Alexandre Presas ◽  
David Valentin ◽  
Weiqiang Zhao ◽  
Mònica Egusquiza ◽  
Carme Valero ◽  
...  
Keyword(s):  
Neural Networks ◽  
Dynamic Stress ◽  
Stress Prediction

Development of a Residual Stress Simulation Benchmark for a Single Bead-on-Plate Weldment

2006 ◽  
Author(s):  
Peter J. Bouchard ◽  
Lyndon Edwards ◽  
Anastasius G. Youtsos ◽  
Roger Dennis
Keyword(s):  
Residual Stress ◽  
Assessment Procedure ◽  
Defect Assessment ◽  
Best Estimate ◽  
Weld Residual Stress ◽  
Single Bead ◽  
Stress Prediction ◽  
Stainless Steel Bead ◽  
Stress Simulation ◽  
Network Project

Finite element weld residual stress modelling procedures involve complex non-linear analyses where many assumptions and approximations have to be made by the analyst. Weld modelling guidelines for inclusion in the R6 defect assessment procedure are in preparation and will be accompanied by a series of validation benchmarks that can be used to evaluate the accuracy of weld modelling procedures and assess their suitability for use in fracture assessments. It is intended to base one of the benchmarks on a stainless steel bead-on-plate weldment that has been extensively studied by members of Task Group 1 of the NeT European Network project. This paper uses round robin residual stress measurements from the NeT project to derive a statistically based ‘best estimate’ distribution of transverse stress passing through the wall-section at mid-length of the bead-on-plate weldment. The accuracy of a state-of-the-art residual stress prediction is benchmarked against the best estimate measurements using a root mean square error analysis and comparisons of decomposed components of stress. The appropriateness of using the predicted residual stresses in fracture assessments is assessed by comparing stress intensity factors based on the measured and predicted distributions of stress. The results from these studies will be used to help establish accuracy targets and acceptance criteria for the welding benchmark.

scholarly journals Reconstruction of Impact Force on Curved Panel using Piezoelectric Sensors

2012 ◽  
Vol 48 ◽  
pp. 367-374 ◽  
Author(s):  
Vladislav Laš ◽  
Robert Zemčík ◽  
Tomáš Kroupa ◽  
Jan Bartošek
Keyword(s):  
Impact Force ◽  
Piezoelectric Sensors ◽  
Curved Panel
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