PSI - Issue 5

ScienceDirect Available online at www.sciencedirect.com Av ilable o line at ww.sciencedire t.com ienceDirect Structural Integrity Procedia 00 (2016) 000 – 000 Procedia Structu al Integrity 5 (2017) 107–114 Available online at www.sciencedirect.com ScienceDirect Structural Integrity Procedia 00 (2017) 000 – 000

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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. 2nd International Conference on Structural Integrity, ICSI 2017, 4-7 September 2017, Funchal, Madeira, Portugal Impact force re onstruction in composite panels Giulia Sarego a *, Lorenzo Cappellini a , Mirco Zaccariotto a,b , Ugo Galvanetto a,b a Department of Industrial Engineering, University of Padova, via Venezia 1, 35131, Padova, Italy b Centre for Studies and Activities for Space “G.Colombo” CISAS , University of Padova, via Venezia 15, 35131, Padova, Italy Passive sensing is a branch of stru tural health mo i oring which aims at detecting positions nd intensities of impacts occurring on aeronautical structures. Impacts are one of the main causes f damage in composite panels, limiting the application of these modern components on aircraft. In particular, impacts can cause the so called barely visible impact damage which, if not detected rapidly, can grow and lead to catastrophic failure. The determination of the impact location and the reconstruction of impact force is necessary to evaluate the health of the structure. These data may be measured indirectly from the measurements of responses of sensors located on the system subjected to the impact. The impact force reconstruction is a complex inverse problem, where the cause is to be inferred from its consequences. Inverse problems are in general ill-posed and ill-conditioned. Therefore, several techniques have been employed in the last four decades and have proven to be effective within certain limitations. Among these methods, transfer function based methods have been mainly validated for low-energy impact where the linear assumption should be valid. Nonlinearities may affect the accuracy in the reconstruction process and thus in the evaluation of damage other techniques have been adopted, such as artificial neural networks (ANN) or genetic algorithms (GA). In this study, a stiffened pa el model developed in Abaqus/CAE is first validated, then nu erical simulati ns are used to obtain data for s veral impacts, characterized by differ nt impact locations a d different energy (by chan ing t e impactor mass and/or velocity). Geometrical onlinearities of the dynamic system ar considered in order to represent accurately the mechanics of the composite panel. Then the complex nonlinear behavior will be modeled through a nonlinear system identification approach, such as ANN, and an intelligent algorithm with global search capabilities, such as GA, will be used in sequence to accurately recovery the impact force p ak and, therefore, properly evaluate the h alth status of the structure. © 2017 The Authors. Published by Elsevier B.V. Peer-review under re ponsibility of the Sci ntific Com ittee of ICSI 2017. Madeira, Portugal ineer s t ed. Therefore, several techniques have been employed in the last four been mainly validated for low-e rs. Published by Elsevier B.V. e y © 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. Abstract

Keywords: impact force reconstruction; neural networks; genetic algorithms; stiffened composite panel.

* Corresponding author. Tel.: +39-049-827-6794. E-mail address: giulia.sarego@unipd.it

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.2017.07.075 * Corresponding author. Tel.: +351 218419991. E-mail address: amd@tecnico.ulisboa.pt 2452-3216 © 2017 The Authors. Published by Elsevier B.V. Peer-review under responsibility of the Scientific Committee of ICSI 2017.

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