Influences of milling and grinding on machined surface roughness and fatigue behavior of GH4169 superalloy workpieces

Surface topography of superalloy GH4169 workpieces machined by milling and grinding is different significantly. Meanwhile, surface roughness, as one of the main indicators of machined surface integrity, has a great influence on the fatigue behavior of workpieces. Based on analyzing the formation mechanism and characteristics of surface roughness utilizing different machining processes and parameters, the machined surface roughness curve can be decoupled into two parts utilizing frequency spectrum analysis, which are kinematic surface roughness curve and stochastic surface roughness curve. The kinematic surface roughness curve is influenced by machining process,parameters, geometry of the cutting tool or wheel, the maximum height of which is expressed as R'_z.By subtracting the kinematic part from the measurement curve, the stochastic surface roughness curve and its maximum height R'_zcan be obtained, which is influenced by the defects of cutting tool edge or abrasive grains, built-up edges(BUE), cracks, high frequency vibration and so on. On the other hand, the results of decoupling analysis of surface roughness curves indicate that Raand Rz values of milling GH4169 are 2–5 times and 1–3 times as high as those of grinding, while R'_zvalue of milling is 13.85%–37.7% as high as that of grinding. According to the results of fatigue life tests of specimens machined by milling and grinding, it can be concluded that fatigue behavior of GH4169 decreases with the increase of R'_zmonotonically, even utilizing different machining processes.     

Intrinsic component filtering for fault diagnosis of rotating machinery

Fault diagnosis of rotating machinery has always drawn wide attention. In this paper, Intrinsic Component Filtering (ICF), which achieves population sparsity and lifetime consistency using two constraints: $l_{1/2}$ norm of column features and $l_{3/2}$ -norm of row features, is proposed for the machinery fault diagnosis. ICF can be used as a feature learning algorithm, and the learned features can be fed into the classification to achieve the automatic fault classification. ICF can also be used as a filter training method to extract and separate weak fault components from the noise signals without any prior experience. Simulated and experimental signals of bearing fault are used to validate the performance of ICF. The results confirm that ICF performs superior in three fault diagnosis fields including intelligent fault diagnosis, weak signature detection and compound fault separation.     

Effect of rotor-mounted protrusion on sealing performance and flow structure in rotor-stator cavity

This paper presents an experimental investigation on the effect of protrusion radial position and height on the sealing performance and flow structure in the rotor-stator cavity. The rotor-mounted protrusions are assembled at three radial positions and are set to three heights. The cavity is equipped with three rim seals: a radial seal, an axial seal and a seal with double fins on the stator. The annulus Reynolds number is set at $4.39\times {10}^5$ and the rotational Reynolds number ranges from $7.51\times {10}^5$ to $1.20\times {10}^6$. Heat and mass transfer analogy is applied. Pressure and ${\mathrm{C}\mathrm{O}}_2$ concentration are measured. The experimental results show that in cavities with different rim seals, radial distributions of the sealing efficiency, pressure and swirl ratio are basically the same. The sealing performance is improved by protrusions compared with the cavity without protrusion and improves with the increase of protrusion radial position and height. The effect of protrusion increases with the increase of the rotational Reynolds number. The windage loss and the flow resistance introduced by protrusions are investigated. It is found that induced windage loss and flow resistance decrease with the increase of protrusion radial position but increase with the protrusion height.     

Capturing transition and non-transition flows with a new shear stress transport model

A new Shear Stress Transport(SST) k-ω model is devised to integrate salient features of both the non-transitional SST k-ω model and correlation-based γ-Reθtransition model. An exceptionally simplified approach is applied to extend the New SST(NSST) model capabilities toward transition/non-transition predictions. Bradshaw’s stress-intensity factor ■ can be parameterized with the wall-distance dependent Reynolds number ■; however, as the Reyis replaced by a ‘‘flow-structure-adaptive” parameter Rμ=...     

A transition prediction method for flow over airfoils based on high-order dynamic mode decomposition

This article presents a novel approach for predicting transition locations over airfoils, which are used to activate turbulence model in a Reynolds-averaged Navier-Stokes flow solver. This approach combines Dynamic Mode Decomposition (DMD) with e^N criterion. The core idea is to use a spatial DMD analysis to extract the modes of unstable perturbations from a steady flowfield and substitute the local Linear Stability Theory (LST) analysis to quantify the spatial growth of Tollmien–Schlichting (TS) waves. Transition is assumed to take place at the stream-wise location where the most amplified mode’s N-factor reaches a prescribed threshold and a turbulence model is activated thereafter. To improve robustness, the high-order version of DMD technique (known as HODMD) is employed. A theoretical derivation is conducted to interpret how a spatial high-order DMD analysis can extract the growth rate of the unsteady perturbations. The new method is validated by transition predictions of flows over a low-speed Natural-Laminar-Flow (NLF) airfoil NLF0416 at various angles of attack and a transonic NLF airfoil NPU-LSC-72613. The transition locations predicted by our HODMD/e^N method agree well with experimental data and compare favorably to those obtained by some existing methods (LST/e^N or $\gamma -\stackrel{￣}{R{e}_{\theta \text{t}}}$). It is shown that the proposed method is able to predict transition locations for flows over different types of airfoils and offers the potential for application to 3D wings as well as more complex configurations.     

Frictional behavior during cold ring compression process of aluminum alloy 5052

The friction is the considerable boundary condition in bulk metal forming. In this paper, the ring compression test was used to evaluate the friction coefficient and factor in Coulomb friction model and Tresca friction model for the plastic deformation of aluminum alloy AA5052. The micro-macro analysis method combining surface morphology and micro-texture was used to explore the friction behaviors in AA5052 cold forming process. In general, the magnitude (μ or m) of friction changes before and after a deformation threshold during ring compression. The maximum change rate of the magnitude (μ or m) before and after the deformation threshold is close to 18.5% under the present experimental conditions, and the change rate decreases with increasing loading speed. The lubrication using MoS₂ is better than that using oil at lower speeds (0.15 mm/s, 1.5 mm/s), but the lubrications for MoS₂ and oil are similar at higher speeds (15 mm/s). The surface roughness, three-dimensional topography, and surface texture of compressed ring have a sudden change around the deformation threshold, which deviate from the previous evolution trend. The increased friction after deformation threshold also promotes the formation of sufficient shear strain layer in the subsurface plane of the compressed ring, and then it hinders the formation of the typical deformation textures with β-oriented line and promotes the appearance of shear textures such as $\left\{\text{001}\right\}〈\text{110}〉$, $\left\{\text{111}\right\}〈\mathit{uvw}〉$ and $\left\{\mathit{hkl}\right\}〈110〉$ textures.