Ceramic Matrix Composites (CMCs) have emerged as a potential material for next-generation turbine blades due to their exceptional high-temperature resistance. Unlike conventional alloy blades, their unique weaving methods create periodic macro-scale surface roughness with distinct topological features. Previous studies have confirmed that these millimeter-scale groove-ridge structures significantly impact film cooling performance. However, systematic experimental investigation remains insufficient regarding the underlying flow mechanisms, particularly how woven-surface-induced near-wall flow characteristics affect the film cooling. This study models the problem as a jet in crossflow over woven surfaces and then conducts a Refractive-Index-Matching Particle-Image-Velocimetry (RIM–PIV) experiment. By precisely matching the refractive indices of fluid and solid wall, this technique overcomes conventional PIV limitations in near-wall measurements caused by laser reflection and optical distortion, enabling a precise resolution of the near-wall flow field. Results demonstrate that the woven surfaces substantially enhance spatiotemporal instabilities of the near-wall flow, and the swirling strength of the flow is particularly intensified over the ridge structures. The woven surfaces increase upstream hairpin vortex generation, while the ridge-induced lifting flow promotes the vortex detachment. These enhanced vortices intensify the fragmentation of shear vortices in the jet, accelerate jet momentum dissipation, and suppress the elevation of the jet. This leads to a reduced turbulent kinetic energy of the jet, and an attenuation of the windward-side Reynolds shear stress. Furthermore, strengthened interactions between the near-wall shear vortices in the jet and the downstream near-wall vortices lead to significantly enhanced flow instability and intensified shear stress in the jet wake region.

The catalytic recombination, oxidation, and nitridation coupling processes occurring at the gas-solid interface between the high-enthalpy flow and thermal protection materials are key factors influencing the aerodynamic thermal environment. Real-time measurement of the near-wall gas temperature and atomic number density under high-enthalpy conditions is essential for understanding these coupling mechanisms. In this study, laser absorption spectroscopy was employed using the oxygen atomic line at 777.19 nm and the nitrogen atomic line at 868.03 nm to quantitatively determine the translational temperature and species number density at different spatial positions near the surface of a C/SiC composite material. Two optical paths were selected: at position 1, the laser beam center was close to the material surface; at position 2, it was approximately 2 mm away. Simultaneously, the emission spectra of ablation products ( · CN and Si) were collected at position 1. The high-enthalpy aerodynamic thermal environment was generated using a 1 MW high-frequency inductively coupled plasma wind tunnel. Considering the surface temperature and post-ablation morphology of the C/SiC material, two experimental conditions with distinct surface oxidation characteristics were designed. State 1 featured a total enthalpy of 43.2 MJ/kg and a heat flux of 3.7 MW/m², while state 2 had 37.5 MJ/kg and 3.1 MW/m², respectively. The heating duration for both conditions was 120 s. The laser absorption spectroscopy results indicate that, due to shock wave compression effects, position 1 near the wall exhibits lower translational temperature but higher number density compared to position 2 farther from the wall. Both conditions show significant decreases in translational temperature and O/N atom number density at position 1. Concurrently, the prominent · CN radiation observed at position 1 indicates substantial nitridation reactions. Scanning electron microscopy and energy dispersive spectroscopy analyses confirm that the material surface is covered with an SiO₂ layer. Relative to state 2, state 1, characterized by higher enthalpy and heat flux, exhibited a more pronounced reduction in the near-wall number densities of both O and N atoms. This observation, in conjunction with stronger radiative intensity of · CN and Si, as well as a reduced surface oxygen concentration, collectively implies that the surface oxide layer is more prone to volatilization or consumption, and the competitive process between oxidation and nitridation reactions is more intense under state 1. This research demonstrates that spatiotemporally resolved measurements of key parameters, such as the number densities of near-wall species and their radiative spectra, provide critical insights into the complex coupling processes at the gas-solid interface.

Multi-scale wavelet analysis along the longitudinal direction was conducted on the large-sample-size time series of instantaneous velocity fields of the turbulent boundary layer over a smooth hydrophilic surface, an isotropic and an anisotropic superhydrophobic surface respectively measured by Time-Resolved Particle Image Velocimetry(TR–PIV), and the distribution of turbulent fluctuating kinetic energy with different longitudinal spatial scales and different normal coordinates was obtained. It was found that the isotropic and anisotropic superhydrophobic surface significantly suppressed the kinetic energy of turbulent fluctuation at all scales. The two types of burst events of the coherent structure were detected respectively by using the positive maxima and negative minima of the wavelet coefficients at each scale. The conditional phase-locked averaged modes of the streamwise fluctuating velocity, normal-wall fluctuating velocity and spanwise fluctuating vorticity of the two burst events were obtained by the conditional phase-locking averaging method at the same scale. It was found that the phase averaged modes of the streamwise and wall-normal fluctuating velocities of the two bursts conformed to the shear layer characteristics of the eject-sweep and swept-eject modes. The phase-locked averaged mode of the fluctuating vorticity corresponded to the structural feature of a quadrupole vortex packet with alternating positive and negative distributions in the streamwise and wall-normal directions, and its streamlines were manifested as a dynamic system of saddle point-focus. Isotropic and anisotropic superhydrophobic surfaces can significantly suppress the burst intensity of coherent structures at various scales.

Adding a trace amount of polymer into turbulent flow can significantly reduce wall friction. This drag reduction technique has been widely applied in fields such as fire-fighting, pipeline transportation, and biomedicine. Polyethylene oxide (PEO) is an efficient drag-reducing polymer, whose performance is affected by multiple parameters. In this study, a gravity-driven circulating pipe-flow system is employed to experimentally investigate the drag reduction characteristics of PEO solution injection in turbulent pipe flow. The effects of Reynolds number, injection angle (seven angles), injection rate and relative molecular mass (total of 7 kinds) on the drag reduction rate (R_D) are systematically examined. A normalized polymer flux K_p, which is suitable for pipe flow, is proposed to collapse the experimental data. Results show that R_D initially increases roughly linearly with lg K_p and then approaches a saturation level. This trend is analogous to the previously reported K-scaling law for polymer injection in turbulent boundary layers. Moreover, the dependence of R_D on molecular weight exhibits an S-shaped trend. By fitting the data with a sigmoidal function, the optimal molecular weight range for maximum drag reduction can be predicted. These findings provide useful guidance for the optimization and prediction of polymer injection parameters in drag-reduced turbulent pipe flows.

Fluidic thrust vectoring control technology has emerged as a critical solution for aircraft attitude control, demonstrating exceptional potential in propulsion-integrated design and flight performance enhancement. Existing supersonic passive ejector-type fluidic thrust vectoring nozzles predominantly employ 2D configurations, and thus are limited to single-axis pitch control. This study designed a multi-axis passive fluidic thrust vectoring nozzle, which feature a divergent section structure with eight circumferentially arranged secondary flow injection channels to achieve multi-axis thrust vectoring control. Through synchronized schlieren visualization and total pressure measurements, the shock wave structures and thrust vectoring characteristics were systematically investigated under diverse control modes. Experimental results demonstrate that at a nozzle pressure ratio (N_PR) of 4.0, thrust vectoring control can be achieved in all 16 circumferential directions by selectively opening and closing secondary flow channels; As the number of closed secondary flow channels increases, the flow vectoring angle gradually increases. The maximum flow vectoring angle in the direction of primary control is 6${\text{°}} , and the linearity is 77.85%; the maximum flow vectoring angle in the direction of secondary control is 5${\text{°}} , and the linearity reaches 96%.

With the rapid development of microfluidics, microflow has become an important research area of fluid mechanics. Microcavity is a common type of microchannel structure in microfluidic systems. To elucidate the fluid transport behavior between microchannels and microcavities, as well as the characteristics of laminar vortices in long microcavities, high-speed dye photography and Micro-Particle Image Velocimetry (Micro-PIV) experiments were conducted. The experimental results show that at the Reynolds number Re = 46, an O-shaped flow pattern appears in the microcavity. At Re ranging from 58 to 93, a hook-shaped vortex pattern emerges, accompanied by a U-shaped pattern in the deep region of the cavity. The findings indicate that there is a direct convective transport behavior between the main flow in the microchannel and the laminar vortex. Meanwhile, at Re = 66, primary and secondary vortices occur in a long microcavity with an aspect ratio e = 2. The velocity at the microcavity entrance exponentially decays and becomes nearly zero in the deep region. Unlike the multiple-vortex series observed in macroscale cavities or numerical simulations, at most two vortices occur in the long microcavity in the experiments. The morphological characteristics of the vortices are determined by the Reynolds number and the aspect ratio. The results can provide theoretical guidance for the design of microfluidic devices and offer valuable insights for physiological and pathological studies related to capillary sprouting and growth.

Surface pressure is an important index in the evaluation of the attitude control and motion characteristics of the conwolutional vehicle. In order to determine the full-domain surface pressure distribution of the vehicle during navigation, a surface pressure reconstruction algorithm based on machine learning is proposed. The surface pressure distribution of the convolutional vehicle may vary under different sailing environments. By arranging pressure observation points on the surface of the convolutional vehicle and obtaining the distribution of these pressure date, the corresponding navigational conditions can be characterized. In this paper, the pressure obtained from a finite number of observation points on the surface, as well as their coordinates, are used as input information of the model. Then we can obtain a mapping model from discrete pressure date to the full domain pressure distribution. To investigate the performance of the model, full-domain surface pressure prediction experiments are conducted on several different test datasets. The results demonstrate that our machine learning-based model can achieve high-precision surface pressure reconstruction, and the relative error of the predicted value can be reduced to within 10%.

Viscous drag is one of the main sources of civil aircraft drag, and turbulent drag plays a dominant role in viscous drag, so it is of great engineering and scientific significance to carry out turbulence drag reduction control. In this paper, under the condition of a zero pressure gradient experiment, the drag reduction control of the plate boundary layer with isotropic permeating materials fused with micro-blowing is studied. The results show that the isotropic permeable material can significantly reduce the friction drag of the plate surface, and the maximum local drag reduction rate in this paper can reach 55.4%. In addition, compared with the control of a single isotropic permeable material, the isotropic permeating material integrated with micro-blowing not only improves the drag reduction rate in the local region but also increases the flow area of the downstream drag reduction region due to the “memory" of the influence of micro-blowing on the turbulent structure, improving the efficiency of drag reduction. Hot-wire velocity measurement results show that the isotropic permeable material with microblowing can reduce the velocity gradient of the viscous bottom layer of the boundary layer and reduce the momentum exchange between the inner and outer layers. The flow visualization technology of Time-Resolved Particle Image Velocimetry (TR−PIV) showed that the isotropic permeable material integrated with micro-blowing could increase the thickness of the turbulent boundary layer and the pulsation intensity of the flow direction. At the same time, the large-scale high-speed strip structure in the steam-wise direction break down into small-scale structure. The self-holding process and sweeping process near the wall are suppressed, thus achieving drag reduction.

Temperature is considered to be one of the most concerned parameters to quantitatively describe flow characteristics, of which the measurement accuracy directly affects the prediction of aerodynamic, aerothermal and thermal protection performance of hypersonic vehicles. Based on the principles of Coherent Anti-Stokes Raman Scattering (CARS), a CARS spectral computation and vib-rotational temperature inversion program is proposed for characterizing the thermodynamic non-equilibrium properties of the high-temperature gas flow field. And corresponding accuracy from 1000 K to 2300 K is verified in a static environment. A non-equilibrium microwave plasma flow is built and its vibrational temperature and rotational temperature with different pressures, N₂ volumetric flow rate, and compositions are obtained by using the developed program. The results show that within the range of experimental conditions, with pressure increasing, the vibrational temperature and rotational temperature decrease, while the thermodynamic non-equilibrium degree increases but corresponding increase rate decreases. With N₂ volumetric flow rate increasing, the vibrational temperature and rotational temperature first increase and then decrease, while the thermodynamic non-equilibrium degree exhibits an opposite trend. With Ar volume fraction increasing, the vibrational temperature first increases and then decreases, and the rotational temperature increases, while the thermodynamic non-equilibrium degree decreases.

The trichromatic mask single-color camera 3D PIV technology uses an optical trichromatic mask element to modulate the imaging light path of a color camera, combining color information with perspective information. This enables the RGB channels of the color-sensitive chip to record images of tracer particles from three perspectives, achieving single-camera 3D flow field measurements. Color cameras typically use a single sensor with a Bayer mask to capture color images. To obtain complete three-channel information of tracer particles, the missing color components in the Bayer image must be restored through demosaicing to extract the three-perspective images. This paper employs High Quality Linear Interpolation (HQLI) algorithms, Gradient Based Threshold Free (GBTF) algorithms, and deep learning algorithms based on U-Net++ neural networks to demosaic particle Bayer images. The quality of three-perspective image extraction by these three algorithms is evaluated using image evaluation metrics and the impact on particle reconstruction quality Q. Simulation experiments on artificially synthesized Gaussian vortex 3D flow fields are conducted to analyze the impact of these algorithms on measurement error. Zero-Net Mass Flux (ZNMF) jet experiments are utilized to study the demosaicing of experimental particle images and analyze the results of transient velocity fields. The results demonstrate that, compared to traditional algorithms (HQLI, GBTF), the deep learning algorithm based on U-Net++ neural networks can more effectively extract three-perspective images of particles, thereby reducing measurement error.

To address the need for measuring soot concentration distributions in complex and spatially constrained combustion flow fields, such as the outlet of aero-engine combustors, this study developed the Two-color-Scheimpflug Laser-Induced Incandescence (2C-Scheimpflug LII) technique and a corresponding measurement system, which obtains soot volume fraction distribution images by employing an oblique imaging method. The technique and measurement system validation experiments were first conducted under specific conditions using three typical ethylene/air flames (McKenna, Gülder, and Santoro). Comparisons with measurement results obtained by other researchers under the same conditions demonstrate the feasibility of the 2C-Scheimpflug LII system. The test results in standard flames show that the lower detection limit of soot volume fraction measurements of our system is approximately 2.0 × 10⁻⁹. Further, the 2C-Scheimpflug LII technique was applied to measure the spatial distribution of soot volume fractions at the transverse cross-section of the outlet and the longitudinal section of a single-sector, dual-swirler aero-engine model combustor. The preliminary results show that the soot volume fraction distribution at the combustor outlet exhibits high instantaneous variability and randomness, while within the combustor, the soot volume fraction displays a V-shaped distribution.

Trichromatic mask particle image velocimetry employs optical elements to alter imaging paths, integrating color and perspective information for single-camera three-dimensional flow velocity measurements. Due to the small imaging viewing angle between three perspectives, conventional algebraic reconstruction techniques yield elongated particle distributions and low directional resolution along the imaging depth direction. To mitigate elongation effects and enhance three-dimensional particle reconstruction quality, convolutional neural networks (CNNs) are applied. Utilizing the AIPR (Artificial Intelligence Particle Reconstruction) architecture, an algorithm tailored for small viewing angle in trichromatic mask PIV is developed. Evaluation involves synthetic image data and artificial flow fields varying in different viewing angles and particle concentration. Results demonstrate that compared to traditional algebraic methods, the proposed method improves reconstruction quality by 30% at the particle concentration of 0.05 ppp. Additionally, it achieves a reconstruction speed of up to 2.8 times faster than traditional methods, enabling the rapid three-dimensional reconstruction of the particle field and enhancing axial reconstruction quality.