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Low-risk transmission performance including elastic deformation, loaded contact pattern, load distribution and loaded transmission error is of paramount significance to the actual manufacturing for non-orthogonal aviation spiral bevel gears. The advanced digital twin technology is introduced into tooth flank grinding. A new digital twin modeling considering low-risk transmission performances is proposed. In the modeling, low-risk transmission performance driven simulation, sensitivity analysis and robust control are developed, respectively Firstly, data-driven tooth surface modeling is developed by simulating free-form tooth surface grinding including gear tilt method and pinion double helical method. With local geometric boundary setup meshing stiffness is determined by using local Rayleigh–Ritz solution. Then, to deal with the sensitivity of gear assembly, an improved tooth contact analysis (TCA) is developed. Moreover, numerical loaded tooth contact analysis (NLTCA) is performed to build a bridge between of low-risk performances and hypoid generator parameters. The low-risk transmission performance driven control model is established by using hypoid generator parameters modification. Finally, sensitivity analysis strategy-based robust control model is solved by using Levenberg–Marquardt method for accurate hypoid generator parameters having modification amount. The provided numerical instance can verify the proposed method. • The free-form tooth flank grinding for the new non-orthogonal aerospace spiral bevel gears. • NLTCA for establishing data-driven function relation. • Tooth flank geometric accuracy control by considering loaded contact deformation predication. • Optimal control strategy by selecting a small of machine settings based on sensitivity analysis. • Digital twin modeling considering both geometric and low-risk transmission performances. [ABSTRACT FROM AUTHOR]

• Numerical prediction methods for elastic behavior of anisotropic and quasi-isotropic webs are proposed. • The iterative calculation methods of meshing behavior for two hybrid metal-composite gears are unified. • The calculation accuracy and efficiency of the proposed method are verified. • Detailed discussion on effects of hybrid gears replacing full metal gears. • Multi-parameter design to reduce mesh stiffness fluctuations. Thin-web structures are the primary strategy for lightweight gears in the aerospace and automotive fields, but current research mainly focuses on metal thin web, lacking understanding of the application of anisotropic and quasi-isotropic composite thin-web gears. Focusing on accurate and efficient calculations of mesh stiffness and load sharing ratio, this work develops a unified numerical analysis method to assess the meshing behavior of the two hybrid metal-composite gears. Multi-scale numerical prediction methods for elastic properties of anisotropic composite and homogeneous laminated webs are established, and two tooth-loading deformation calculation methods for metal-composite-metal gear bodies with different web widths are developed separately. A numerical analysis method is proposed by unifying the iterative calculation process of the two hybrid gears through deformation coordination relationships, which is also applicable to full metal gears. Finally, extensive comparisons with the finite element method (FEM) and existing numerical method verify the proposed analytical method (PAM). The investigation results reveal the impact of replacing full metal gears with these two hybrid gears on the meshing behavior and further elucidate the advantages of using composite webs for micro and macro parameters design in adjusting the mass and stiffness and reducing mesh stiffness fluctuations. This work provides a new analytical method for the structural design and performance assessment of lightweight hybrid metal-composite gear systems. [ABSTRACT FROM AUTHOR]

The linear filtering model is widely adopted because it can effectively control the areal autocorrelation function (AACF). However, these methods either constrain only half of the AACF or add the assumption of symmetry along one coordinate axis, which leads to a limited scope of applicability of the model. In this paper, a new AACF constraint for all spatial information is present. The new constraint function can provide objectives for all AACFs, and thus both isotropic rough surfaces, anisotropic surfaces of arbitrary orientation, and cross-textured surfaces can be reconstructed. The numerical experimental results show that the AACF fits well for isotropic as well as arbitrarily oriented anisotropic surfaces. For cross-textures surfaces, the errors are significant, indicating that the linear filtering model still has potential for improvement. • The generalized form of the optimization objective of the linear filter reconstruction model is presented. • Rough surface reconstruction problems with arbitrary texture orientations merged into a unified model. • L-BFGS algorithm is adopted to solve the optimization problem in the reconstructed model. [ABSTRACT FROM AUTHOR]