Monocrystalline blades used in gas turbines exhibit material anisotropy, and the orientation of the anisotropy axis affects the deformation of the bladed disk. Considering the orientation of the anisotropy axis as a random design parameter, the uncertainty and sensitivity analysis for static blade deformations are presented for the first time. The following two cases are analyzed using a realistic bladed disk model with friction contacts: (i) deformation of the tuned bladed disks considering the uncertainty in anisotropy orientation and variations in fir tree root geometry and (ii) deformation of mistuned bladed disks with uncertain blade crystal orientations. For efficient uncertainty and sensitivity analysis, the applicability of the following surrogate models are explored: (i) an ensemble of regression trees (random forest) and (ii) gradient‐based polynomial chaos expansion. Faster convergence in statistical characteristics has been obtained using a surrogate model compared to that obtained from finite element model based Monte Carlo simulation. From sensitivity analysis, it has been inferred that the uncertainty in static displacements of a blade in a bladed disk is primarily due to the uncertainty in anisotropy angles of that blade itself and secondarily due to the interaction of different blade anisotropy angles.

Single crystal blades used in high pressure turbine bladed disks of modern gas-turbine engines exhibit material anisotropy. In this paper the sensitivity analysis is performed to quantify the effects of blade material anisotropy orientation on deformation of a mistuned bladed disk under static centrifugal load. For a realistic, high fidelity model of a bladed disk both: (i) linear, and (ii) non-linear friction contact conditions at blade roots and shrouds are considered. The following two kinds of analysis are performed: (i) local sensitivity analysis, based on first order derivatives of system response w.r.t design parameters, and (ii) statistical analysis using polynomial chaos expansion. The polynomial chaos expansion is used to transfer the uncertainty in random input parameters to uncertainty in static deformation of the bladed disk. An effective strategy, using gradient information, is proposed to address the “curse of dimensionality” problem associated with statistical analysis of realistic bladed disk.

Single crystal blades used in high pressure turbine bladed disks of modern gas-turbine engines exhibit material anisotropy. In this paper, the sensitivity analysis is performed to quantify the effects of blade material anisotropy orientation on deformation of a mistuned bladed disk under static centrifugal load. For a realistic, high fidelity model of a bladed disk both: (i) linear and (ii) nonlinear friction contact conditions at blade roots and shrouds are considered. The following two kinds of analysis are performed: (i) local sensitivity analysis (LSA), based on first-order derivatives of system response with respect to design parameters, and (ii) statistical analysis using polynomial chaos expansion (PCE). The PCE is used to transfer the uncertainty in random input parameters to uncertainty in static deformation of the bladed disk. An effective strategy, using gradient information, is proposed to address the “curse of dimensionality” problem associated with statistical analysis of realistic bladed disk.

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High-pressure turbines of modern gas-turbine engines use single crystal blades that exhibit material anisotropy. Due to manufacturing tolerances, each blade in the bladed disk will have different crystal anisotropy axis orientation, thereby creating mistuning in the structure. In this paper, the blade anisotropy angles are considered as uncertain design parameters to study the variation in forced response of a mistuned bladed disk. For realistic, high fidelity model of a bladed disk, linear bonded contact conditions at blade roots and shrouds are considered. The following two kinds of analysis are performed: (a) statistical analysis using polynomial chaos expansion and (b) global sensitivity analysis using Sobol indices. An effective strategy based on gradient information is used to minimize the computational cost involved in statistical and sensitivity analysis. For the first time, the possibility of introducing intentional blade material anisotropy mistuning to reduce the amplification of forced response is investigated.