A method of optimizing probe placement in a turbomachine is disclosed which includes determining wavenumber (Wn) of N dominant wavelets generated by upstream and downstream stators and blade row interactions formed around an annulus, establishing a design matrix A utilized in developing flow properties around the annulus having a dimension of m×(2N+1), iteratively modifying probe positions placed around the annulus and determining a condition number of the design matrix A for each set of probe positions until a predetermined threshold is achieved for the condition number representing optimal probe position, wherein the condition number is defined as norm A.Math.norm A+, wherein A+ represents inverse of A for a square matrix and a Moore-Penrose pseudoinverse of A for a rectangular matrix.

The aircraft-engine gas turbine includes an outer sealing ring for sealing an array of rotor blades that can be attached to a housing by a clamping mechanism (80) in a friction fit, and a plurality of ring segments (20.sub.i, 20.sub.i+1), wherein a free axial path length (a.sub.f) of a sealing ring segment counter to the direction of through-flow is at least as large as an axial engagement (a.sub.1) of a rotation locking member (10) of the outer sealing ring (a.sub.f≧a.sub.1), which is free of form fit counter to the direction of through-flow, and/or an axial overhang (a.sub.2) of a radial mounting rail (23) of the outer sealing ring (a.sub.f≧a.sub.2), and/or an axial offset (a.sub.3, a.sub.4) of a sealing fin (31, 41); and/or a quotient of a specific clearance sum of the outer sealing ring attached to the housing in a friction fit.

An airfoil includes an airfoil wall that defines a leading end, a trailing end, and pressure and suction sides that join the leading end and the trailing end. The airfoil wall includes a wishbone-shaped fiber layer structure that has a pair of arms that merge into a single leg. The pair of arms are formed by first and second S-shaped fiber layers each of which is comprised of a network of fiber tows. The first and second S-shaped fiber layers merge to form the single leg. The single leg comprises fiber tows from each of the first and second S-shaped fiber layers that are interwoven, and the single leg forms at least a portion of the trailing end of the airfoil wall.

A method of optimizing probe placement in a turbomachine is disclosed which includes establishing a design matrix A of size m×(2N+1) utilized in developing flow properties around an annulus of a turbomachine, where m represents the number of datapoints at different circumferential locations around the annulus, and N represents dominant wavelets generated by upstream and downstream stators and blade row interactions formed around an annulus, wherein m is greater or equal to 2N+1, and optimizing probe positioning by iteratively modifying probe positions placed around the annulus and for each iteration determining a condition number of the design matrix A for each set of probe positions until a predetermined threshold is achieved for the condition number representing an optimal probe layout.

An engine component for a gas turbine engine, the engine component comprising a cooling architecture comprising at least one unit cell having a set of walls with a thickness, the set of walls defining fluidly separate conduits having multiple openings, each of the multiple openings having a hydraulic diameter; wherein the thickness (t) and the hydraulic diameter (D.sub.H) relate to each other by an equation:

[00001]$\frac{{\left(D_H+2t\right)}^2}{{\left(\left(D_H+2t\right)/D_H\right)}^{1/3}}$

to define a performance area factor (PAF).

The present invention belongs to the technical field of control of aero-engines, and proposes an adaptive boosting algorithm-based turbofan engine direct data-driven control method. First, a turbofan engine controller is designed based on the Least Squares Support Vector Machine (LSSVM) algorithm, and further, the weight of a training sample is changed by an adaptive boosting algorithm so as to construct a turbofan engine direct data-driven controller combining a plurality of basic learners into strong learners. Compared with the previous solution only adopting LS SVM, the present invention enhances the control precision, improves the generalization ability of the algorithm, and effectively solves the problem of sparsity of samples by the adaptive boosting method. By the adaptive boosting algorithm-based turbofan engine direct data-driven control method designed by the present invention.

The present invention belongs to the technical field of control of aero-engines, and proposes an adaptive boosting algorithm-based turbofan engine direct data-driven control method. First, a turbofan engine controller is designed based on the Least Squares Support Vector Machine (LSSVM) algorithm, and further, the weight of a training sample is changed by an adaptive boosting algorithm so as to construct a turbofan engine direct data-driven controller combining a plurality of basic learners into strong learners. Compared with the previous solution only adopting LS SVM, the present invention enhances the control precision, improves the generalization ability of the algorithm, and effectively solves the problem of sparsity of samples by the adaptive boosting method. By the adaptive boosting algorithm-based turbofan engine direct data-driven control method designed by the present invention.

An airfoil includes an airfoil wall that defines a leading end, a trailing end, and pressure and suction sides that join the leading end and the trailing end. The airfoil wall includes a wishbone-shaped fiber layer structure that has a pair of arms that merge into a single leg. The pair of arms are formed by first and second S-shaped fiber layers each of which is comprised of a network of fiber tows. The first and second S-shaped fiber layers merge to form the single leg. The single leg comprises fiber tows from each of the first and second S-shaped fiber layers that are interwoven, and the single leg forms at least a portion of the trailing end of the airfoil wall.

The method can include generating a first duty cycle value for the PWM; monitoring a current value of a parameter; generating a duty cycle limit value for the PWM, including activating more than one duty cycle limit functions based on corresponding activation conditions, the corresponding activation conditions based on the current value of the parameter, each of the more than one duty cycle limit functions generating a corresponding duty cycle limit subvalue when the corresponding activation conditions are met, and setting the duty cycle limit value to a sum of the generated duty cycle limit subvalues; setting a second duty cycle value for the PWM, as the first duty cycle value or as the duty cycle limit if the first duty cycle value exceeds the duty cycle limit; and, applying the PWM at the second duty cycle value to the valve.

A method of optimizing probe placement in a turbomachine is disclosed which includes establishing a design matrix A of size m×(2N+1) utilized in developing flow properties around an annulus of a turbomachine, where m represents the number of datapoints at different circumferential locations around the annulus, and N represents dominant wavelets generated by upstream and downstream stators and blade row interactions formed around an annulus, wherein m is greater or equal to 2N+1, and optimizing probe positioning by iteratively modifying probe positions placed around the annulus and for each iteration determining a condition number of the design matrix A for each set of probe positions until a predetermined threshold is achieved for the condition number representing an optimal probe layout.