Accurate temperature predictions are essential to the optimization of gas turbine component design. This paper provides an update on the application of recent developments in heat transfer boundary condition derivation and finite element model validation. Computational fluid dynamics (CFD) is increasingly being used to determine cooling flow distributions and convective heat fluxes on a range of components. Validation of the CFD methodology for internal cavity heat transfer is also a key focus of major research programmes. In this paper, further results are presented for selected engine and rig cavities. A fully coupled CFD/finite element thermal model solution is also demonstrated. Increasingly, the application of optimization techniques to the thermal model calibration process is showing that significant savings in analysis time can be achieved for a given accuracy of ‘match’. The optimization process is described and sample results are presented from the calibration of a typical thermal model. Finally, the impact of these new analysis techniques on the derivation of thermal boundary conditions in gas turbine component cavities and the implications for compliance with Airworthiness Authority regulations are summarized with respect to offering an improved temperature prediction validation strategy.
Traditionally the optimization of a turbomachinery engine casing for tip clearance has involved either 2D transient thermo-mechanical simulations or 3D mechanical simulations. The following paper illustrates that 3D transient whole engine thermomechanical simulations can be used within tip clearance optimizations and that the eciency of such optimizations can be improved when a multi-delity surrogate modeling approach is employed. These simulations are employed in conjunction with a rotor sub-optimization utilizing surrogate models of rotordynamics performance, stress,
This paper presents a 3D thermo-mechanical modelling method to calculate compressor local tip running clearances. The method requires a solid geometry representation of the compressor casings and main engine structures, including local geometry features such as thrust lugs, gearbox, sump, offtake bosses and struts. The finite element model is capable of predicting asymmetric temperature and displacement distributions for transient and steady-state conditions as a result of thermal, pressure and mechanical loads (e.g. thrust, gas torques, gravity, gusts, etc). This methodology has been applied to calculate local tip clearances on the intermediate pressure compressor of a civil aero-engine. The results from the 3D solid model have been compared to those obtained with more conventional analysis tools (i.e. 2D axisymmetric thermo-mechanical models and 3D isothermal shell and beam models) in order to build confidence in the new methodology. Local tip running clearances were measured on the intermediate pressure compressor by means of capacitance probes. Measured local closures for a typical square cycle including a low power idle phase and high power max take-off phase have been compared to predicted local closures to establish the validity of the new methodology.
This paper describes the GSI-UPM system for SemEval-2019 Task 5, which tackles multilingual detection of hate speech on Twitter. The main contribution of the paper is the use of a method based on word embeddings and semantic similarity combined with traditional paradigms, such as n-grams, TF-IDF and POS. This combination of several features is finetuned through ablation tests, demonstrating the usefulness of different features. While our approach outperforms baseline classifiers on different sub-tasks, the best of our submitted runs reached the 5th position on the Spanish subtask A.
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