Methods and apparatus are disclosed to determine material parameters of a turbine rotor. An example apparatus includes a rotor geometry determiner to determine a geometry of the rotor, a node radius calculator to calculate radial node locations of radial nodes including a first radial node, a thermocouple interface to record first temperature values over an interval, a first thermal stress calculator to calculate first thermal stress values at one or more of the radial nodes over the interval, a node temperature calculator to calculate second temperature values at respective internal nodes of the first radial node, a reference value lookup to lookup first material parameter information, a second thermal stress calculator to determine second thermal stress values, a thermal stress comparator to calculate a difference between the thermal stress values, and, in response to the difference not satisfying a threshold, a material parameter adjuster to determine material parameters.

A method for monitoring a status of a reduction gear of a gas turbine includes the steps of: obtaining measurements of parameters accomplished during an operating phase of the gas turbine, these parameters including temperatures of a lubricating oil of the reduction gear at the inlet and at the outlet of the reduction gear, a parameter representing a speed of the gas turbine, as well as at least one context parameter; selecting measurements; normalizing temperatures of the lubricating oil using the measurements of the context parameter; evaluating a thermal efficiency of the reduction gear by using a physical model defining the thermal efficiency based on a difference between the temperature of the lubricating oil; and determining a status of the reduction gear depending on a step of comparing the evaluated thermal efficiency with respect to a reference signature.

A compressor controller for operating a compressor within an industrial automation environment is provided. The compressor controller includes a control module, configured to control the compressor via control settings, and a machine learning module, coupled with the control module. The machine learning module is configured to receive a set of supervised data related to the compressor, and to train with the supervised data to produce a Newtonian physics model representing the inputs and outputs of the compressor within the industrial automation environment. The machine learning module is also configured to receive performance data related to the compressor, receive environment data related to the compressor, and to process the performance data and environment data to produce predicted future performance data for the compressor, and to produce control settings for the compressor.

The method can include determining a mass flow rate W of working fluid circulating through the compressor stage, determining a control parameter value associated to the geometrical configuration of the variable geometry element based on the determined value of mass flow rate W; and changing the geometrical configuration of the variable geometry element in accordance with the determined control parameter value.

A method for actively calculating a capability of an electronically controlled valve is provided. The method including the steps of: a) operating the electronically controlled valve in accordance with a task; b) testing the electronically controlled valve in order to determine a range of movement of the electronically controlled valve in accordance with an initial gain, wherein the testing of the electronically controlled valve occurs after the valve has been operated in accordance with the task; c) determining a new gain required for providing a predetermined range of movement of the electronically controlled valve; and d) repeating steps a-c at least once, wherein the new gain is used to operate the valve in accordance with the task.

Disclosed is a computer-implemented method for controlling an engine system of a vehicle comprising: determining an operating condition of the vehicle; determining one or more contextual conditions relevant to the vehicle; selecting, based upon both the determined operating condition and the determined one or more contextual conditions, a control profile for the engine system from a directory comprising a plurality of control profiles having different control characteristics; applying the selected control profile to a controller of the engine system; and controlling the engine system with the controller in accordance with the selected control profile. Also disclosed are an engine control system, a gas turbine engine, and an aircraft.

A seal assembly includes a rotating seal runner having an outer radial surface, and one or more rotationally stationary seal rings located radially outboard of the seal runner. Each seal ring has an inner radial surface, with the inner radial surface and the outer radial surface defining a sealing interface therebetween. An axially extending shape of the inner radial surface is selected utilizing a predicted shape of the outer radial surface at a selected operating condition of the seal assembly.

A method for qualifying a gas turbine engine component includes creating a first set of substantially identical gas turbine engine components via a uniform manufacturing procedure, determining a set of as-manufactured parameters of each gas turbine engine component in the first set, and determining a variance model of the first set. The variance model includes a representative parameter profile, which includes a plurality of component parameter profiles. The sum of each of the component parameter profiles is the representative parameter profile. The method also includes determining at least one predicted response models based at least in part on the variance model, identifying as-manufactured parameters of a second engine component, applying the as-manufactured parameters of the second engine component to the at least one predicted response models, thereby generating a predicted response output, and qualifying the second engine component for usage in at least one gas turbine engine corresponding to the at least one predicted response model.

A qualification system for gas turbine engine components includes a computer system configured to receive a set of measured parameters for each gas turbine engine component in a plurality of substantially identical gas turbine engine components, and determine a variation model based on the set of measured parameters. The computer system includes at least one simulated engine model configured to determine a predicted operation of each gas turbine engine component in the plurality of substantially identical gas turbine engine components, a correlation system configured to correlate variations in the set of parameters for each of the gas turbine engine components with a set of the predicted operations of each gas turbine engine, thereby generating a predictive model based on the variations. The computer system also includes a qualification module configured to generate a qualification formula based on the predictive model. The qualification formula is configured to receive a set of measured parameters of an as-manufactured gas turbine engine component and determine when the as manufactured gas turbine engine component is qualified for inclusion in at least one engine.

The present disclosure discloses a method for capturing a trip sign of a turbine due to a high bearing temperature based on correlation and a device therefor. By combining a temperature of a target bearing and related operating parameters thereof, this method can capture possible abnormal trip online. According to the present disclosure, it is not necessary to add additional detection equipment, and it does not need to establish a complex physical model for turbine bearings, and only the historical data of the operating parameters of the temperature of the target bearing and generator set operating parameters related to the temperature of the target bearing are required to complete the establishment of the model for capturing abnormal sign before the trip, which is convenient for popularization and application.