Abstract: A computer-implemented method controls input of at least a portion of a first training data set into a first machine learning algorithm. The first training data set includes data quantifying damage to a first compressor and data quantifying a first operating parameter of the first compressor. The first machine learning algorithm is executed, and data quantifying the first operating parameter is received as an output of the first machine learning algorithm. The first machine learning algorithm is trained using the received data output from the first machine learning algorithm and data quantifying the first operating parameter of the first compressor. The trained first machine learning algorithm is configured to enable determination of operability of a second compressor of a gas turbine engine.

Abstract: A computer-implemented method comprising: controlling input of data quantifying damage received by a compressor of a gas turbine engine into a first machine learning algorithm; receiving data quantifying a first operating parameter of the compressor as an output of the first machine learning algorithm; and determining operability of the compressor by comparing the received data quantifying the first operating parameter of the compressor with a threshold.

Abstract: A computer-implemented method comprising: controlling input of data quantifying damage received by a compressor of a gas turbine engine into a first machine learning algorithm; receiving data quantifying a first operating parameter of the compressor as an output of the first machine learning algorithm; and determining operability of the compressor by comparing the received data quantifying the first operating parameter of the compressor with a threshold.

Abstract: A computer-implemented method comprising: receiving an operability determination for a compressor of a gas turbine engine, the operability determination being determined using an output from a machine learning algorithm trained using data quantifying damage received by compressor blades of a compressor; determining one or more actions to be performed using the received operability determination; and generating control data using the determined one or more actions.

Abstract: A computer-implemented method comprising: controlling input of data quantifying damage received by a compressor of a gas turbine engine into a first machine learning algorithm; receiving data quantifying a first operating parameter of the compressor as an output of the first machine learning algorithm; and determining operability of the compressor by comparing the received data quantifying the first operating parameter of the compressor with a threshold.

Abstract: A computer-implemented method comprising: controlling input of at least a portion of a first training data set into a first machine learning algorithm, the first training data set including: data quantifying damage to a first compressor; and data quantifying a first operating parameter of the first compressor; executing the first machine learning algorithm; receiving data quantifying the first operating parameter as an output of the first machine learning algorithm; and training the first machine learning algorithm using: the received data output from the first machine learning algorithm; and data quantifying the first operating parameter of the first compressor, the trained first machine learning algorithm being configured to enable determination of operability of a second compressor of a gas turbine engine.

Abstract: An aerofoil member that extends between radially inner and radially outer endwalls which define a gas annulus of the compressor. Aerofoil member has a leading edge, a trailing edge, a pressure surface and a suction surface such that successive cross-sections through the aerofoil member transverse to the radial direction provide respective aerofoil sections. The external shape of the aerofoil member is defined by the stacking of the aerofoil sections on a stacking axis which passes through a reference point common to each aerofoil section. The aerofoil member has lean produced by the projection of the stacking axis onto a plane normal to the engine axis intersecting a first one of the endwalls at an angle of from 5° to 25° to the circumferential direction direction such that the pressure surface faces the first endwall.

Abstract: A blade for an axial flow machine having a pressure surface, suction surface and trailing edge. The blade has a cross-sectional aerofoil profile including: a region of maximum curvature corresponding to the trailing edge of the blade and defining a trailing edge radius of curvature r; a trailing edge region extending from the trailing edge and having a chordwise extent equal to curvature r's trailing edge radius; a taper region adjacent the trailing edge region, the taper region having a chordwise extent greater than the curvature r's trailing edge radius and no more than 15% of the blade's chord; a body region adjacent the taper region; a pressure surface boundary corresponding to the blade's pressure surface; and a suction surface boundary corresponding to the blade's suction surface. A thickness between the pressure and suction surface boundaries reduces within the taper region towards the trailing edge by at least 50%.

Abstract: An aerofoil member that extends between radially inner and radially outer endwalls which define a gas annulus of the compressor. Aerofoil member has a leading edge, a trailing edge, a pressure surface and a suction surface such that successive cross-sections through the aerofoil member transverse to the radial direction provide respective aerofoil sections. The external shape of the aerofoil member is defined by the stacking of the aerofoil sections on a stacking axis which passes through a reference point common to each aerofoil section. The aerofoil member has lean produced by the projection of the stacking axis onto a plane normal to the engine axis intersecting a first one of the endwalls at an angle of from 5° to 25° to the circumferential direction direction such that the pressure surface faces the first endwall.

Abstract: This disclosure concerns aerofoils for an axial flow compressor. The compressor has an array of aerofoils angularly spaced about its axis of rotation. The aerofoils have leading and trailing edges extending in a direction spanning a flow region defined between a radially inner rotor component and a radially outer casing. Each aerofoil has opposing pressure and suction surfaces extending between the leading and trailing edges and terminating at a free end of the aerofoil. Each aerofoil leans towards the pressure surface by an angle of between 10° and 80° in the vicinity of the aerofoil tip. The aggressive negative lean towards the tip may help reduce over-tip leakage flow in use.

Abstract: A blade for an axial flow machine having a pressure surface, suction surface and trailing edge. The blade has a cross-sectional aerofoil profile including: a region of maximum curvature corresponding to the trailing edge of the blade and defining a trailing edge radius of curvature r; a trailing edge region extending from the trailing edge and having a chordwise extent equal to curvature r?s trailing edge radius; a taper region adjacent the trailing edge region, the taper region having a chordwise extent greater than the curvature r?s trailing edge radius and no more than 15% of the blade's chord; a body region adjacent the taper region; a pressure surface boundary corresponding to the blade's pressure surface; and a suction surface boundary corresponding to the blade's suction surface. A thickness between the pressure and suction surface boundaries reduces within the taper region towards the trailing edge by at least 50%.