PSI - Issue 5

ScienceDirect Available online at www.sciencedirect.com Av ilable o line at ww.sciencedirect.com cienceDirect Structural Integrity Procedia 00 (2016) 000 – 000 Procedia Structu al Integrity 5 (2017) 997–10 4 Available online at www.sciencedirect.com ScienceDirect Structural Integrity Procedia 00 (2017) 000 – 000 Available online at www.sciencedirect.com ScienceDirect Structural Integrity Procedia 00 (2017) 000 – 000

www.elsevier.com/locate/procedia www.elsevier.com/locate/procedia

www.elsevier.com/locate/procedia

XV Portuguese Conference on Fracture, PCF 2016, 10-12 February 2016, Paço de Arcos, Portugal Thermo-mechanical modeling of a high pressure turbine blade of an airplane gas turbine engine P. Brandão a , V. Infante b , A.M. Deus c * a Department of Mechanical Engineering, Instituto Superior Técnico, Universidade de Lisboa, Av. Rovisco Pais, 1, 1049-001 Lisboa, Portugal b IDMEC, Department of Mechanical Engineering, Instituto Superior Técnico, Universidade de Lisboa, Av. Rovisco Pais, 1, 1049-001 Lisboa, Portugal c CeFEMA, Department of Mechanical Engineering, Instituto Superior Técnico, Universidade de Lisboa, Av. Rovisco Pais, 1, 1049-001 Lisboa, Portugal Abstract During their operation, modern aircraft engine components are subjected to increasingly demanding operating conditions, especially the high pressure turbine (HPT) blades. Such conditions cause these parts to undergo different types of time-dependent degradation, one of which is creep. A model using the finite element method (FEM) was developed, in order to be able to predict the creep behaviour of HPT blades. Flight data records (FDR) for a specific aircraft, provided by a commercial aviation company, were used to obtain thermal and mechanical data for three different flight cycles. In order to create the 3D model needed for the FEM analysis, a HPT blade scrap was scanned, and its chemical composition and material properties were obtained. The data that was gathered was fed into the FEM model and different simulations were run, first with a simplified 3D rectangular block shape, in order to better establish the model, and then with the real 3D mesh obtained from the blade scrap. The overall expected behaviour in terms of displacement was observed, in particular at the trailing edge of the blade. Therefore such a model can be useful in the goal of predicting turbine blade life, given a set of FDR data. Neural networks and genetic algorithms for the evaluation of coatings thicknesses in thermal barriers by infrared thermography dat H.Halloua a , A.Elhassnaoui b , A.Saifi a , A. Elamiri a , A.Obbadi a , Y.Errami a , S.Sahnoun a, * a Laboratory of Electronics, Instrumentation, and Energetic, Faculty of Sciences, B.P 20. 24000 El Jadida, Morocco. b Industrial Engineering Laboratory, Faculty of Science and Technology, BP: 523,Beni Mellal, Morocco Abstract In the context of using non-destructive thermal control methods for the coatings thicknesses evaluation in thermal barriers. We have treated the laser-pulsed thermography data with the neural networks to model the relationship between the thermal response and the coating thickness. The algorithms based on the error gradient computation are used during the learning step. Indeed, the initial weights of the network found and the number of data processed facilitated the convergence of these algorithms. In this work we presented a neural network training method using pre-processing of data by principal component analysis(PCA) to optimize the number of network inputs and the genetic algorithm for the optimum initial weights determination in the network training by the back propagation algorithm. The two algorithms recombinatio allowed th thicknesses valuation with deviations less than 5%. © 2017 The Authors. Published by Elsevier B.V. Peer-review under responsibility of the Scientific Committee of ICSI 2017. Keywords: Non-destructive testing, pulsed laser Infrared thermography, artificial neural network, genetic algorithms, principal component Analysis, finite element method. The mal barri coati gs systems are deposited on hot parts in order to insulate them thermally and protect them from heat (Clarke & Phillpot (2005)). The coating thicknesses evaluation in these structures is very important in the integrity control of these parts. The latter are used in many industrial sectors using non-destructive testing methods 2nd International Conference on Structural Integrity, ICSI 2017, 4-7 September 2017, Funchal, Madeira, Portugal Neural networks and genetic algorithms for the evaluation f coatings thicknesses in thermal barriers by infrared thermography data H.Halloua a , A.Elhassnaoui b , A.Saifi a , A. Elamiri a , A.Obbadi a , Y.Errami a , S.Sahnoun a, * a Laboratory of Electro ics, Instrumen ation, nd Energetic, F culty of Sciences, B.P 0. 24000 E Jadida, M rocco. b Industrial Engineer g Laboratory, Fac lty f Scie ce and Technology, BP: 523 Beni Mellal, Morocco Abstract In the context of using non-dest uctive t ermal control m thods for the c atings thickn sses evaluation i rmal b rri rs. W have treated the laser-pulsed therm graphy data with th neural networks to model th relationship betw en the th rmal r spons a d the coating thick ss. The algorithms based on the error gradi nt computation are used during le rning step. Indeed, the initial weights of the network found and the number of data processed facilitated the convergenc of these algorithms. In this work we pr sented a neural ne work training method using pre-processing of dat by principal co pone t a alysis(PCA) o optimize numbe of n work inputs and the genetic algorithm f r the ptimum ini ial weight det rmin ti in the etw rk training by he back propagation algorithm. The two algorithms r combination allowed th t icknesses evaluation with deviations less than 5%. © 2017 The Authors. Published by Elsevier B.V. Peer-review under responsibility of the Scientific Committee of ICSI 2017. Keywords: Non-d structiv testing, pulsed laser Infrared thermography, artificial neural network, genetic algorithms, principal component Analysis, finite element method. 1. Introduction Thermal b ri r coatings systems are dep sited on hot parts in order to insulate them thermally and protect them from heat (Clarke & Phillpot (2005)). The coating thicknesses evaluation in the e structur is very important in the integrity control of these parts. The latter are used in many industrial sectors using non-destructive testing methods © 2017 The Authors. Published by Elsevier B.V. Peer-review under responsibility of the Scientific Committee of ICSI 2017 © 2016 The Authors. Published by Elsevier B.V. Peer-review under responsibility of the Scientific Committee of PCF 2016. Keywords: High Pressure Turbine Blade; Creep; Finite Element Method; 3D Model; Simulation. 2nd International Conference on Structural Integrity, ICSI 2017, 4-7 September 2017, Funchal, Madeira, Portugal 1. Introduction

* Corresponding author. Tel.: +212-661-347-441. E-mail address: ssahnoun@gmail.com * Correspon ing author. Tel.: +212-661-347-441. E-mail address: ssahnoun@gmail.com

2452-3216 © 2016 The Authors. Published by Elsevier B.V. Peer-review under responsibility of the Scientific Committee of PCF 2016. 2452-3216  2017 The Authors. Published by Elsevier B.V. Peer-review under responsibility of the Scientific Committee of ICSI 2017 10.1016/j.prostr.2017.07.153 * Corresponding author. Tel.: +351 218419991. E-mail address: amd@tecnico.ulisboa.pt 2452 3216 © 2017 Th Authors. Published by Elsevier B.V. Peer-review under responsibility of the Scientific Committee of ICSI 2017. 2452-3216 © 2017 The Authors. Published by Elsevier B.V. Peer-review under responsibility of the Scientific Committee of ICSI 2017.