Prediction of residual stress fields after shot-peening of TRIP780 steel with second-order and artificial neural network models based on multi-impact finite element simulations
Article dans une revue avec comité de lecture
Auteur
Date
2021Journal
Journal of Manufacturing ProcessesRésumé
Shot-peening is a mechanical surface treatment widely employed to enhance the fatigue life of metallic components by generating compressive residual stress fields below the surface. These fields are mainly impacted by the selection of the process parameters. The aim of this work is to propose a hybrid approach to conduct two predictive models: second-order model and feed-forward artificial neural network model. For this purpose, a 3D multiple-impact finite element model coupled to a central composite design of experiments was employed. A parametric analysis was also conducted to investigate the effect of the shot diameter, the shot velocity, the coverage, and the impact angle on the induced residual stress profile within a TRIP780 steel. It was found that both models predict with good agreement, the residual stress profile as a function of the process parameters and can be used in shot-peening optimization due to their responsiveness.
Fichier(s) constituant cette publication
Cette publication figure dans le(s) laboratoire(s) suivant(s)
Documents liés
Visualiser des documents liés par titre, auteur, créateur et sujet.
-
Communication avec acteLI, Tingcheng; LOU, Ruding; POLETTE, Arnaud; SHAO, Zilong; NOZAIS, Dominique; PERNOT, Jean-Philippe (2022)Even if 3D acquisition systems are nowadays more and more efficient, the resulting point clouds nevertheless contain quality defects that must be taken into account beforehand, in order to better anticipate and control ...
-
Article dans une revue avec comité de lectureSHAH GHAZANFAR, Ali; POLETTE, Arnaud; PERNOT, Jean-Philippe; GIANNINI, Franca; MONTI, Marina (SPRINGER, 2022-03-17)Due to its capacity to evolve in a large solution space, the Simulated Annealing (SA) algorithm has shown very promising results for the Reverse Engineering of editable CAD geometries including parametric 2D sketches, ...
-
Article dans une revue avec comité de lectureHU, Sijie; POLETTE, Arnaud; PERNOT, Jean-Philippe (Springer Science and Business Media LLC, 2022-04-13)Identifcation and ftting is an important task in reverse engineering and virtual/augmented reality. Compared to the traditional approaches, carrying out such tasks with a deep learning-based method have much room to ...
-
Article dans une revue avec comité de lecturePEUZIN-JUBERT, Manon; NOZAIS, Dominique; MARI, Jean-Luc; PERNOT, Jean-Philippe; POLETTE, Arnaud (Elsevier BV, 2021-12)At present, optical sensors are being widely used to realize high quality control or reverse engineering of products, systems, buildings, environments or human bodies. Although the intrinsic characteristics of such ...
-
Article dans une revue avec comité de lectureSHAH GHAZANFAR, Ali; GIANNINI, Franca; MONTI, Marina; PERNOT, Jean-Philippe; POLETTE, Arnaud (Springer Science and Business Media LLC, 2020-02-18)This paper introduces a new ftting approach to allow an efcient part-by-part reconstruction or update of editable CAD models fitting the point cloud of a digitized mechanical parts′ assembly. The idea is to make use ...