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ItemFault-tolerance at your Finger Tips with the TeamPlay Coordination Language(ACM, 2023)Coordination is a well established computing paradigm with a plethora of languages, abstractions and approaches. The functional coordination language TeamPlay follows the approach of exogenous coordination and organises an application as a streaming data-flow graph of independently operating, state-free components. In this work we capitalise on this stringent application architecture for fault-tolerance against both permanent and transient hardware failure. We extend the TeamPlay language by a range of fault-tolerance features to be selected by the system integrator. We further propose a multi-core runtime system that is able to isolate hardware faults and manages to keep an application running flawlessly in the presence of hardware failure by adaptively morphing the application.
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ItemWhirl Flutter Testing of ATTILA Tiltrotor Testbed : Initial Results(Vertical Flight Society, 2024)This paper presents the preliminary results of the recent whirl flutter wind tunnel test campaign performed within the Advanced Testbed for TILtrotor Aeroelastics (ATTILA) project. The Froude-scale ATTILA testbed consists of a semi-span wing with powered tip-mounted proprotor reflecting the proprietary design of the Next Generation Civil TiltRotor (NGCTR). An overview of the ATTILA testbed, wind tunnel test procedures, team organisation and preliminary flutter results are presented. In line with pre-entry dynamic characterization tests, the wind-on test activities in the DNW Large Low-speed Facility (LLF) revealed notable force-dependent nonlinearity in the modal characteristics of, particularly, the wing torsion mode. Further dimensionality was added by early observations that damping in the rotor gimbal degree of freedom, attributed to stiction in the blade pitch mechanism, had the potential to substantially contribute to the damping of the fundamental wing-pylon modes. Nevertheless, the parallel exploitation of multiple monitoring and online modal estimation methodologies enabled a robust identification and safe test progression. The critical flutter mode was found to be configuration dependent, with the wing chord bending mode generally being marginally stable throughout most of the wind speed range, and the wing torsion mode displaying a sharp trend towards negative damping at higher speeds. Despite technical challenges, valuable test data was gathered to advance the experimental methods and support validation of the numerical tools used to obtained clearance for high-speed flight testing of the full-scale NGCTR Technology Demonstrator.
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ItemATTILA Tiltrotor Whirl Flutter Code-to-Test Correlation(Vertical Flight Society, 2025)This paper presents the results of an ongoing correlation study performed using three different comprehensive rotorcraft codes and data obtained from the Advanced Testbed for TILtrotor Aeroelastics (ATTILA) tiltrotor whirl flutter wind tunnel test campaign. The ATTILA testbed consists of a 1:5 scale semi-span wing with a powered, tip-mounted proprotor reflecting the proprietary design of the Next Generation Civil TiltRotor (NGCTR). Experimental dynamic characterization of the testbed has revealed non-negligible structural nonlinearities. Post-test efforts have focused on refining the damping trends extracted from the test data, and correlating the experimental results with numerical predictions. The objective of this paper is to assess the modelling fidelity required and afforded by modern comprehensive aeromechanics codes to predict tiltrotor whirl flutter instability given an industry-representative design that exhibits structural nonlinearities. Baseline numerical flutter models fail to predict some of the observed experimental damping behaviour, but the inclusion of higher fidelity aerodynamics and exploratory friction models improves prediction accuracy. Ongoing modelling and dynamic characterization efforts aim to further clarify the mechanisms influencing the whirl flutter stability of the ATTILA testbed and enhance the predictive capabilities of the numerical methods employed.
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ItemNumerical analysis of an impeller repair using directed energy deposition: thermal and mechanical analysis(NAFEMS, 2025)This study presents a Finite Element (FE) analysis aimed at predicting the thermal and mechanical behaviour of a repair conducted on an impeller part utilizing direct energy deposition additive manufacturing technique. The impeller, exhibiting wear on its outer edge, undergoes repair through the aforementioned technique. This repair is performed using a Beam Modulo 400 DED machine. The primary objective is to assess the deformation of the impeller post-repair, with a focus on minimizing excessive deformation. The FE model developed for this research focuses on the manufacturing process to provide insights into the thermal and mechanical responses of the repaired impeller. A key aspect of the analysis involves the calibration of the FE model, both thermally and mechanically, which was achieved through dedicated calibration prints. These calibration prints are used to collect thermal measurements and achieve predictable deformations, thus enabling the refinement of the FE model. Thermal physics plays a crucial role in the repair process, as the direct energy deposition technique involves the localized application of heat to deposit material onto the impeller surface. The FE model aims to simulate the thermal distribution throughout the repair process, enabling the prediction of temperature gradients and potential thermal stresses within the impeller structure. Furthermore, the mechanical aspects of the repair are examined to assess the resulting deformation of the impeller. Excessive deformation can compromise the functionality of the repaired part leading to rejection of the part. Through the FE analysis, parameters influencing mechanical behaviour, are investigated to predict the repair process and resulting deformation. The validation of the FE model is crucial to ensure its reliability in predicting the thermal and mechanical outcomes of the repair process. By comparing simulation results with experimental data obtained from the actual prints, the accuracy of the FE model is confirmed, enhancing confidence in its predictive capabilities. Overall, this research contributes to the advancement of additive manufacturing techniques for repair applications by providing a framework for predicting the thermal and mechanical behaviour of repaired components. The insights gained from this study can be used for the optimization of repair processes, leading to enhanced performance and longevity of industrial components such as impellers.
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ItemMachine Learning Assisted Induction Welding Simulations of UD TP-CFRP Laminates(NAFEMS, 2025)The aerospace industry is driving innovation in aircraft technologies and materials to achieve net-zero carbon emissions by 2050. This will require all aspects of the aircraft development, manufacturing, operation and disposal to be scrutinised. To develop fuel-efficient aircraft, integrate net-zero propulsion systems, and to allow for efficient recycling of material, Thermo-Plastic (TP) Carbon Fibre Reinforced Polymer (CFRP) is a promising construction material. Today'™s aircraft are typically constructed along assembly lines where components are joined. The new generation of net-zero aircraft will consist of multi-functional building blocks that require novel joining technologies. Furthermore, high volume assembly is key to support acceptance of more complex innovative aircraft concepts. TP-CFRP can be re-melted to allow for (dis-) assembly of aircraft components or sub-components. One technology that supports rapid assembly and disassembly of thermoplastic components is induction welding. Induction welding offers benefits like rapid contactless welding. However, effective heating of Uni-Directional (UD) TP-CFRP components is crucial for achieving a good quality weld but difficult to monitor and control. Furthermore, certification of induction-welded joints poses significant challenges, necessitating a deeper understanding of the welding process. Advanced 3D Finite Element Method (FEM) modelling can enhance this understanding and aid certification. At last, a good understanding and means of monitoring the welding process will support rapid assembly with minimum inspection intervals of the welding process. This paper presents an efficient and accurate FEM approach for induction welding of TP-CFRP laminates, capturing the multi-physics aspects of induction welding through a coupled electro-magnetic-thermal analysis. The induction heating and welding setup is modelled in detail, including a copper coil moving over a weld line with specific speed, distance, and amperage settings. The electromagnetic FE model accounts for the coil, air, and laminate, predicting the magnetic field and subsequent Eddy currents are generated in the conducting carbon fibres. The fibre orientation and interfaces between plies are explicitly modelled, as they significantly influence the formation of Eddy current loops. To enable real-time simulations for predictive purposes, the computationally expensive electromagnetic part of the simulation is replaced with a Machine Learning (ML) approach, more specifically Artificial Neural Network (ANN). The ANN predicts the 3D Joule heating fields in the TP-CFRP adherends, which are then used in the thermal FE model. The thermal model includes the laminate and accounts for natural convection and radiation. Accurate material characterisation is crucial for both the electromagnetic and thermal models. The induction heating model is validated through comparison with representative experiments, showing an accurate match. In this work the FEM approach is verified with physical experiments of static heating of UD TP-CFRP plates and dynamic heating of two plates forming a lap-joint. In addition, the methodology is extended to induction welding of thick UD TP-CFRP laminates up to 8 mm. By combining ML and physics-based modelling, this research enables the simulation-driven design and optimisation and real-time application of induction welding processes for UD TP-CFRP, reducing the need for physical prototyping and testing; and paves the way for a digital twin that can be used to monitor the induction welding process during manufacturing to support high volume assembly lines of innovative net-zero aircraft.