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The purpose of this article is to present numerical investigations of flow control with piezoelectric actuators on a backward facing step (BFS) and fluidic vortex generators on a NACA0015 aerofoil for the reattachment and separation control through the manipulation of the Reynolds stresses.

The unsteady flow phenomena associated with both devices are simulated using Spalart–Allmaras-based hybrid Reynolds averaged Navier-Stokes (RANS)/large eddy simulation (LES) models (detached eddy simulation (DES), delayed detached eddy simulation (DDES) and improved delayed detached eddy simulation (IDDES)), using an in-house computational fluid dynamics (CFD) solver. Results from these computations are compared with experimental observations, enabling their reliable assessment through the detailed investigation of the Reynolds stresses and also the separation and reattachment.

All the hybrid RANS/LES methods investigated in this article predict reasonable results for the BFS case, while only IDDES captures the separation point as measured in the experiments. The oscillating surface flow control method by piezoelectric actuators applied to the BFS case demonstrates that the Reynolds stresses in the controlled case decrease, and that a slightly nearer reattachment is achieved for the given actuation. The fluidic vortex generators on the surface of the NACA0015 case force the separated flow to fully reattach on the wing. Although skin friction is increased, there is a significant decrease in Reynolds stresses and an increase in lift to drag ratio.

The value of this article lies in the assessment of the hybrid RANS/LES models in terms of separation and reattachment for the cases of the backward-facing step and NACA0015 wing, and their further application in active flow control.

This paper proposes new methods of fault detection for fuel systems in order to improve system availability. Novel fault systems are required for environmentally friendly lean burn combustion, but can carry high risk failure modes particularly through their control valves. The purpose of the developed technology is the rapid detection of these failure modes, such as valve sticking or impending sticking, and therefore to reduce this risk. However, sensing valve state is challenging due to hot environmental temperatures, which results in a low reliability for conventional position sensing.

Starting with the business needs elicited from stakeholders, a quality functional deployment process is performed to derive sensing system requirements. The process acknowledges the difference between test-bed and in-service aerospace needs through weightings on requirements and maps these customer requirements to systems performance metrics. The design of the system must therefore optimise the sensor suite, on- and off-board signal processing and acquisition strategy.

Against this systems engineering process, two sensing strategies are outlined which illustrate the span of solutions, from conventional gas path sensing with advanced signal processing to novel non-invasive sensing concepts. While conventional sensing may be feasible within a test cell, the constraints of aerospace in-service operation may necessitate more novel alternatives. Acoustic emission (detecting very high frequency surface vibration waves) sensing technology is evaluated to provide a non-invasive, remote and high temperature tolerant solution. Through this comparison, the considerations for the end-to-end system design are highlighted to be critical to sensor deployment success in-service.

The paper provides insight into different means of addressing the important problem of monitoring faults in combustor systems in gas turbines. By casting of the complex design problem within a systems engineering framework, the outline of a toolset for solution evaluation is provided.

The paper provides three areas of significant contributions: a diversity of methods to diagnosing fuel system malfunctions by measuring changes fuel flow distributions, through novel means, and the combustor exit temperature profiles (cause and effect); the use of analytical methods to support the selection (types and quantities) and placement of sensors to ensure adequate state awareness while minimising their impact on the engine system cost and weight; and an end-to-end data processing approach to provide optimised information for the engine maintainers allowing informed decision-making.