A full authority digital engine controller (FADEC) based system is also disclosed. The system includes a processor, and a tangible, non-transitory memory configured to communicate with the processor, the tangible, non-transitory memory having instructions stored thereon that, in response to execution by the processor, cause the FADEC to perform operations. The operations may include measuring a first temperature at a first sensor disposed at a first known location of an engine, measuring a second temperature at a second sensor disposed at a second known location of the engine, and estimating at least one of a stress or a strain of a part or component in the engine based on the first temperature and the second temperature. The system may control fuel flow and/or other engine effectors during a thrust transient to limit the estimated stress or the estimated strain of the component from exceeding a predetermined threshold.

An exemplary 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 of substantially identical gas turbine engine components, determining a variance model of the first set of substantially identical gas turbine engine components, and determining a plurality of predicted response models based at least in part on the variance model, each of the predicted response models corresponding to one of an engine type and an engine assembly, and each of the predicted response models being configured to determine a predicted response of including a gas turbine engine component from the first set of substantially identical gas turbine engine components in the corresponding one of the engine type and the engine assembly. The system then identifies as-manufactured parameters of a second engine component, and applies the as-manufactured parameters of the second engine component to each of the predicted response models, thereby generating a predicted response output from each of the predicted response models. An optimum predicted response from each of the generated predicted response models is identified and the engine type or engine assembly that corresponds with the optimum predicted response is associated with a unique part identifier of the second engine component.

There is provided a gas turbine engine comprising a low pressure shaft and a high pressure shaft; wherein the low pressure shaft connects a fan to a fan drive turbine, and the high pressure shaft connects a high pressure turbine to a compressor section. The low pressure shaft and the high pressure shaft are arranged such that when operating at idle the idle shaft speed ratio is greater than 6.05. The idle shaft speed ratio is the ratio of the speed of the high pressure shaft to the speed of the low pressure shaft at idle conditions.

A turbine system includes a compressor section, an inlet cooling system coupled upstream of the compressor section and configured to cool ambient air entering the compressor section, and a turbine section coupled in flow communication with the compressor section and including at least one hot gas path component. The system further includes a controller configured to receive feedback parameters indicative of a temperature of the at least one hot gas path component, estimate a remaining life of the at least one hot gas path component based on the received feedback parameters, determine a desired power output of the turbine system based on the estimated remaining life of the at least one hot gas path component and a cooling capacity of the inlet cooling system, and control operation of the turbine system to cause the turbine system to generate the desired power output.

Magnetic chip detectors for detecting magnetic chips in a lubrication fluid are provided. The chip detector includes a first electric terminal, a second electric terminal and a magnet. The second electric terminal is spaced apart from the first electric terminal to define a gap between the first and second electric terminals. The gap exposes a cavity formed in the magnet for collecting magnetic chips. The cavity accommodates the accumulation of smaller and relatively harmless magnetic chips without triggering an alarm to reduce the occurrence of nuisance alarms.

A wash optimization system and related methods are provided that increase the efficiency and the effectiveness of engine washes. A system comprising at least one processor receives sensor data representing one or more measured parameters of a turbine engine and determines at least one performance parameter based on the sensor data. The at least one performance parameter represents one or more particulate values associated with the turbine engine. The system generates a health state for the turbine engine based on the at least one performance parameter and generates a wash identifier based on the health state of the turbine engine.

A system includes a gas turbine engine and a controller operable to determine a closing threshold with respect to an upper limit and an opening threshold with respect to a lower limit of a movement range of an effector of the gas turbine engine based on an on-board model, where the upper limit and the lower limit are defined for a target parameter of the gas turbine engine. The controller determines a projected state of the target parameter absent a correction command to the effector, applies a closing correction to the effector based on determining that the projected state of the target parameter would result in being above the closing threshold, and applies an opening correction to the effector based on determining that the projected state of the target parameter would result in being below the opening threshold.

A system and method for determining particulate accumulation in a gas turbine engine includes sensing the number, size, and type of particulate at a first position on the gas turbine engine and supplying first data representative thereof, where the first position located at a first side of a gas turbine engine component; sensing the number, size, and type of particulate at a second position on the gas turbine engine and supplying first data representative thereof, where the second position located at a second side of the gas turbine engine component and downstream of the first position; and processing the first data and the second data to determine the mass of the particulate accumulated on the gas turbine engine component.

Systems, program products, and methods for adjusting operating limit (OL) thresholds for compressors of gas turbine systems based on mass flow loss are disclosed herein. The systems may include at least one computing device in communication with the gas turbine system, sensor(s) measuring operational characteristic(s) of the gas turbine system, and a pressure sensor measuring an ambient fluid pressure surrounding the gas turbine system. The computing device(s) may be configured to adjust operational parameters of the gas turbine system by performing processes including determining a mass flow loss between an estimated, first mass flow rate and a calculated, second mass flow rate for the compressor of the gas turbine system, and adjusting an OL threshold for the compressor of the gas turbine system based on the mass flow loss. The OL threshold for the compressor may be below a predetermined surge threshold for the compressor.

In one embodiment, a method includes sensing first operations for one or more turbine systems in a fleet of turbine systems via a plurality of sensors disposed in the one or more turbine systems before a first wash operation. The method further includes sensing second operations for the one or more turbine systems via the one or more sensors after the water wash operation. The method also includes deriving at least one forecasting model based on the sensing first operations and the sensing second operations, wherein the at least one forecasting model is configured to predict a performance of a turbine system of the one or more turbine systems. The method additionally includes applying the at least one forecasting model to derive a predictive improvement in the performance for the turbine system.