Smartphone Based Stress Prediction

Author(s):  
Thomas Stütz ◽  
Thomas Kowar ◽  
Michael Kager ◽  
Martin Tiefengrabner ◽  
Markus Stuppner ◽  
...  
Keyword(s):  
2016 ◽  
Vol 7 (2) ◽  
pp. 105-112
Author(s):  
Adhi Kusnadi ◽  
Idul Putra

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


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

2021 ◽  
Vol 205 ◽  
pp. 109751
Author(s):  
Andrzej Nycz ◽  
Yousub Lee ◽  
Mark Noakes ◽  
Deo Ankit ◽  
Christopher Masuo ◽  
...  

Author(s):  
Peter J. Bouchard ◽  
Lyndon Edwards ◽  
Anastasius G. Youtsos ◽  
Roger Dennis

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.


2019 ◽  
Vol 64 ◽  
pp. 138-145 ◽  
Author(s):  
Gao Hui ◽  
Oleg Gaidai ◽  
Arvid Naess ◽  
Gaute Storhaug ◽  
Xiaosen Xu

Author(s):  
Michael L. Benson ◽  
Patrick A. C. Raynaud ◽  
Frederick W. Brust

Residual stress prediction contributes to nuclear safety by enabling engineering estimates of component service lifetimes. Subcritical crack growth mechanisms, in particular, require residual stress assumptions in order to accurately model the degradation phenomena. In many cases encountered in nuclear power plant operations, the component geometry permits two-dimensional (i.e., axisymmetric) modeling. Two recent examples, however, required three-dimensional modeling for a complete understanding of the weld residual stress distribution in the component. This paper describes three-dimensional weld residual stress modeling for two cases: (1) branch connection welds off reactor coolant loop piping and (2) a mockup to demonstrate the effectiveness of the excavate and weld repair process.


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