A numerical investigation is conducted to assess the effects of shock-wave impingement on the outflow characteristics of shaped film cooling holes under supersonic inflow conditions. The Shear Stress Transport–Stress-Blended Eddy Simulation (SST–SBES) hybrid turbulence model, coupled with the fifth-order WENO-ZQ scheme, is validated for its resolution and accuracy in predicting complex film cooling flow fields. The study systematically explores the interaction mechanisms between upstream shock waves and the boundary layer development around 7-7-7 shaped holes at blowing ratios of M = 0.5 and M = 0.65. Key findings are as follows: (1) The SBES model demonstrates strong capabilities in capturing vortex structures and their evolution within the film cooling domain; (2) in supersonic flat-plate configurations, shock impingement leads to upstream boundary layer thickening and induces separation bubbles, while variations in blowing ratio have limited impact on mainstream pressure distribution; (3) at lower blowing ratios, compression waves generated by aerodynamic bulges within the jet intensify localized boundary layer thickening near the trailing edge, whereas higher blowing ratios alleviate this effect; (4) spectral analysis reveals a distinct − 7/3 power-law scaling at upstream and midstream monitoring points, attributed to shock compression and shear-layer instability caused by jet-mainstream interaction. Downstream, the flow transitions toward a classical inertial subrange behavior with a − 5/3 spectral slope, indicating the saturation of turbulent mixing between the jet and the mainstream.

This work employs a high-resolution large eddy simulation (LES) to reveal the unsteady flow characteristics of transonic turbine cascades. The results show that a distinct dovetail-shaped shock wave structure forms at the trailing edge of the cascade. PS-TE-shock impingement on the adjacent suction surface triggers boundary layer separation and rapid transition to turbulence. Wake shedding originates from shear-driven vortices forming at the trailing-edge shock intersection and detaching periodically. Pressure waves generated during shedding prop agate downstream along the PS-TE-shock, impacting the suction surface boundary layer and influencing its flow. POD analysis further elucidates the pressure wave propagation path.

Carbon fiber reinforced thermoplastic composites (TPCs) attracted significant attentions from the aerospace, transportation, and defense industries, due to their high specific stiffness and specific strength, outstanding thermal stability and good damage resistance, etc. As the demand of TPCs significantly increased for aerospace applications, the development of advanced joining technologies for TPC components becomes critical to ensure the structural integrity of aviation structures. This paper provides a comprehensive review of the historical development and recent advancements in welding technologies for TPCs, including ultrasonic welding, induction welding, resistance welding, and laser welding. Special emphasis is placed on ultrasonic welding due to its growing prominence in the field. The characteristics of various types of welding technologies for TPCs have been systematically discussed. Simultaneously, the strengths of the TPC joints manufactured by different welding technologies have been summarized and compared. The future development trend and research focuses for the welding technologies of TPC components are also proposed.

Fiber-reinforced polymer structures are widely used in applications requiring strong, lightweight materials, such as in aerospace and automotive industries. Despite their high stiffness and strength, these materials often suffer from brittle fracture and shaping difficulties. This contrasts with natural lightweight biomaterials, such as bone, bamboo, and wood, which possess complex hierarchical structures that contribute to exceptional mechanical properties through directed self-assembly. Inspired by the hierarchical structure of bamboo, we propose a cellular face-bridging fiber structure and introduce interface entanglement strategy to achieve lightweight, high strength, toughness and impact resistance of the composite material. The resulting composites exhibits a density of 0.87 g/cm3, a specific strength of approximately 200 MPa/(g/cm3), toughness of nearly 244 kJ/m3, and an ultimate tensile elongation surpassing engineering composites and polymers. It also demonstrates good resistance to high-speed ballistic impact, with specific impact energy absorption comparable to traditional impactresistant materials, such as Kevlar reinforced composites. Multi-scale simulations and experimental analyses reveal that the cellular face-bridging fiber structure, with its physically entanglement interface, enhances strength, toughness, and energy dissipation through fiber breaking, pull-out, interface cracking, and matrix slippage. The composite's thermoplastic processability allows for the fabrication of centimeter-scale structural parts, indicating promising potential for scalable production in lightweight aerospace applications.

AbstractOrganic polymer‐based composite materials with favorable mechanical performance and functionalities are keystones to various modern industries; however, the environmental pollution stemming from their processing poses a great challenge. In this study, by finding an autonomous phase separating ability of fungal mycelium, a new material fabrication approach is introduced that leverages such biological metabolism‐driven, mycelial growth‐induced phase separation to bypass high‐energy cost and labor‐intensive synthetic methods. The resulting self‐regenerative composites, featuring an entangled network structure of mycelium and assembled organic polymers, exhibit remarkable self‐healing properties, being capable of reversing complete separation and restoring ≈90% of the original strength. These composites further show exceptional mechanical strength, with a high specific strength of 8.15 MPa g.cm−3, and low water absorption properties (≈33% after 15 days of immersion). This approach spearheads the development of state‐of‐the‐art living composites, which directly utilize bioactive materials to “self‐grow” into materials endowed with exceptional mechanical and functional properties.

In numerical simulations, achieving high accuracy without significantly increasing computational cost is often a challenge. To address this issue, this paper proposes an improved finite volume Weighted Essentially Non-Oscillatory (WENO) scheme for structured grids. By employing a single-point quadrature rule to perform flux integration on the control volume faces, this scheme is designed for use in NUAA-Turbo three-dimensional fluid solvers based on structured grids, utilizing RANS and RANS/LES coupling to simulate turbomachinery flows. Firstly, the new WENO scheme is validated against classical numerical test cases to evaluate its stability and reliability in handling discontinuities, double Mach reflection problems, and Rayleigh–Taylor (RT) instability. Compared to the original scheme, this improved finite-volume WENO scheme demonstrates better stability near discontinuities and more effectively resolves flow features at the same grid resolution. Next, for engineering applications related to turbomachinery, such as compressor and turbine characteristics, calculations using RANS are performed and the results obtained with WENO-ZQ3 and WENO-JS3 are compared. Finally, the new fifth-order WENO scheme is applied to RANS/LES coupling simulations of turbine wake and film cooling. The results indicate that the improved finite-volume WENO scheme provides better stability and accuracy in engineering applications. For instance, the average error in calculating compressor efficiency characteristics is reduced from 0.76% to 0.05%, the error in turbine vane pressure distribution compared to the experimental values is within 1%, and the error in film cooling efficiency centerline distribution compared to the experimental values is within 3%. Additionally, the qualitative results of turbine wake and film cooling show that even with a small number of grid points, more detailed flow physics can be captured, thereby reducing computational costs in aerodynamic applications.

The pigeon robot has attracted significant attention in the field of animal robotics thanks to its outstanding mobility and adaptive capability in complex environments. However, research on pigeon robots is currently facing bottlenecks, and achieving fine control over the motion behavior of pigeon robots through brain–machine interfaces remains challenging. Here, we systematically quantify the relationship between electrical stimulation and stimulus-induced motion behaviors, and provide an analytical method to demonstrate the effectiveness of pigeon robots based on electrical stimulation. In this study, we investigated the influence of gradient voltage intensity (1.2–3.0 V) on the indoor steering motion control of pigeon robots. Additionally, we discussed the response time of electrical stimulation and the effective period of the brain–machine interface. The results indicate that pigeon robots typically exhibit noticeable behavioral responses at a 2.0 V voltage stimulus. Increasing the stimulation intensity significantly controls the steering angle and turning radius (p < 0.05), enabling precise control of pigeon robot steering motion through stimulation intensity regulation. When the threshold voltage is reached, the average response time of a pigeon robot to the electrical stimulation is 220 ms. This study quantifies the role of each stimulation parameter in controlling pigeon robot steering behavior, providing valuable reference information for the precise steering control of pigeon robots. Based on these findings, we offer a solution for achieving precise control of pigeon robot steering motion and contribute to solving the problem of encoding complex trajectory motion in pigeon robots.

To achieve high-fidelity large eddy simulation (LES) predictions of complex flows while keeping computational costs manageable, this study integrates a high-order WENO-ZQ scheme into the LES framework. The WENO-ZQ scheme has been extensively studied for its accuracy, robustness, and computational cost in inviscid flow applications. This study extended the WENO-ZQ scheme to viscous flows by integrating it into a three-dimensional structured grid LES CFD solver. High-fidelity simulations of turbulent boundary layer flow and supersonic compression ramp flows were conducted, with the scheme being applied for the first time to study laminar boundary layer transition and separation flows in the high-load, low-pressure turbine PakB cascade. Classic numerical case validations for viscous conditions demonstrate that the WENO-ZQ scheme, compared to the same-order WENO-JS scheme, exhibits lower dispersion and dissipation errors, faster convergence, and better high-frequency wave resolution. It maintains high-resolution accuracy with fewer grid points. In application cases, the WENO-ZQ scheme accurately captures the three-dimensional flow characteristics of shockwave–boundary layer interactions in supersonic compression ramps and shows high accuracy and resolution in predicting separation and separation-induced transition in low-pressure turbines.

To conduct high-precision and high-resolution numerical simulation of complex flow structures in turbomachinery, a high-order finite volume weighted essentially non-oscillatory (WENO) scheme for the large eddy simulation (LES) is improved and embedded into the three-dimensional viscous unsteady CFD solver NUAA-Turbo. Firstly, the spectral characteristics and unsteady convergence of the improved WENO scheme are studied. Compared with the classical WENO scheme, the improved WENO scheme has better dissipation and dispersion characteristics and faster convergence speed. Then, the coefficient CW of the Wall-Adapting Local Eddy-viscosity (WALE) model is calibrated by decaying homogeneous isotropic turbulence (DHIT) test case. Finally, the scheme is applied to conduct high-precision LES calculations of turbulent boundary layer flow, supersonic compression corner flow, and low-pressure turbine cascade separation flow. The numerical simulation results show that this WENO scheme has excellent shock wave capture ability and turbulence resolution and can capture more flow field details with less mesh size, greatly reducing the computational cost and laying a foundation for large-scale engineering application of LES.

In numerical simulations, achieving high accuracy without significantly increasing computational costs is often challenging. To address this, this paper presents an improved finite volume weighted essentially non-oscillatory (WENO) scheme tailored for applicability in computational fluid dynamics (CFD) and implemented in the flow solver NUAA-Turbo for simulating turbomachinery flows using both RANS and RANS/LES coupling. Firstly, the new WENO scheme is validated against classic numerical test cases to assess its stability and reliability in handling discontinuities, the Double problem, and Raleigh-Taylor (RT) instability issues. Compared to the original format, this enhanced finite volume WENO scheme demonstrates superior stability near discontinuities and resolves flow features with the same grid resolution more effectively. Next, for engineering applications related to turbomachinery, such as compressor and turbine characteristics, computations are performed using RANS, and the results obtained using WENO-ZQ3 and WENO-JS3 are compared. Finally, the new fifth-order WENO scheme is applied to RANS/LES coupled simulations of turbine wakes and film cooling. The results show that the enhanced finite volume WENO scheme offers improved stability and accuracy in engineering applications, allowing for high-precision calculations with fewer grid points to capture more detailed flow physics, thereby reducing computational costs in aerodynamic applications.

How to develop new recycled composite materials to meet the growing global demand for sustainable materials is of great interest. In this paper, by leveraging the growth of mycelium to anchor CNTs, the self-regenerative mycelium-CNTs composite materials (MCCs) are created. It demonstrates good strength (similar to 30 MPa), self- healing (restore similar to 98 % original strength), and self-sensing properties. Finally, a human care-computer interaction device is developed to demonstrate the application of this technology. Our manufacturing process utilizes the autonomous growth of living cells grown in in vitro cultures to produce regenerable living composites that do not require harsh chemical processing and polluting exhaust emissions. The final mechanical properties are comparable to commercial polymer plastics, and their functional properties can be further tuned by introducing nanoparticles.

The existing Bug algorithms, which are the same as wall-following algorithms, offer good performance in solving local minimum problems caused by potential fields. However, because of the odometer drift that occurs in actual environments, the performance of the paths planned by these algorithms is significantly worse in actual environments than in simulated environments. To address this issue, this article proposes a new Bug algorithm. The proposed algorithm contains a potential field function that is based on the relative velocity, which enables the potential field method to be extended to dynamic scenarios. Using the cumulative changes in the internal and external angles and the reset point of the robot during the wall-following process, the condition for state switching has been redesigned. This improvement not only solves the problem of position estimation deviation caused by odometer noise but also enhances the decision-making ability of the robot. The simulation results demonstrate that the proposed algorithm is simpler and more efficient than existing wall-following algorithms and can realise path planning in an unknown dynamic environment. The experimental results for the Kobuki robot further validate the effectiveness of the proposed algorithm.

Biological strong and tough materials have been providing original structural designs for developing bioinspired high-performance composites. However, new synergistic strengthening and toughening mechanisms from bioinspired structures remain yet to be explored and employed to upgrade current carbon material reinforced polymer composites, which are keystone to various modern industries. In this work, from bamboo, the featured cell face-bridging fibers, are abstracted and embedded in a cellular network structure, and develop an epoxy resin/carbon composite featuring biomimetic architecture through a fabrication approach integrating freeze casting, carbonization, and resin infusion with carbon fibers (CFs) and carbon nanotubes (CNTs). Results show that this bamboo-inspired crack-face bridging fiber reinforced composite simultaneously possesses a high strength (430.8 MPa) and an impressive toughness (8.3 MPa m1/2 ), which surpass those of most resin-based nanocomposites reported in the literature. Experiments and multiscale simulation models reveal novel synergistic strengthening and toughening mechanisms arising from the 2D faces that bridge the CFs: sustaining and transferring loads to enhance the overall load-bearing ability and furthermore, incorporating CNTs pullout that resembles the intrinsic toughening at the molecular to nanoscale and strain delocalization, crack branching, and crack deflection as the extrinsic toughening at the microscale. These constitute a new effective and efficient strategy to develop simultaneously strong and tough composites through abstracting and implenting novel bioinspired structures, which contributes to addressing the long-standingly challenging attainment of both high strength and toughness for advanced structural materials.

The use of industrial robots for grinding CFRP is a green processing method. This method not only allows in-situ repair to reduce unnecessary waste of resources, but also produces no excessive contaminants. The effect of various process parameters, including grinding directions, the mesh size of grinding heads and rotating speed, on the grinding quality of Carbon Fiber Reinforced Polymers (CFRP) using industrial robots was investigated. The mechanism of grinding defects was also studied. According to the experimental results, the CFRP grinding process is mainly controlled by the rotating speed, number of grinding heads, and grinding direction. In particular, high-speed grinding helps to improve the surface quality of CFRP. In turn, the use of diamond grinding heads with too small or too large particles may reduce surface quality. Grinding quality changes with the grinding direction. In the grinding direction between 0° and 90°, the surface roughness increases with the angle (but drops at 60°), and The same trend is observed in the grinding direction between 90° and 150°, whereby the surface roughness increases with the angle (but drops at 120°). The surface quality of CFRP is thereby improved after grinding in the direction of 0°, 60°, 120° and 180°. Furthermore, the fiber pull-out occurs, when the feed direction and fiber orientation are aligned. Finally, the low-frequency vibration easily causes fiber pull-out defects.

IntroductionThe robo-pigeon using homing pigeons as a motion carrier has great potential in search and rescue operations due to its superior weight-bearing capacity and sustained flight capabilities. However, before deploying such robo-pigeons, it is necessary to establish a safe, stable, and long-term effective neuro-electrical stimulation interface and quantify the motion responses to various stimuli.MethodsIn this study, we investigated the effects of stimulation variables such as stimulation frequency (SF), stimulation duration (SD), and inter-stimulus interval (ISI) on the turning flight control of robo-pigeons outdoors, and evaluated the efficiency and accuracy of turning flight behavior accordingly.ResultsThe results showed that the turning angle can be significantly controlled by appropriately increasing SF and SD. Increasing ISI can significantly control the turning radius of robotic pigeons. The success rate of turning flight control decreases significantly when the stimulation parameters exceed SF > 100 Hz or SD > 5 s. Thus, the robo-pigeon's turning angle from 15 to 55° and turning radius from 25 to 135 m could be controlled in a graded manner by selecting varying stimulus variables.DiscussionThese findings can be used to optimize the stimulation strategy of robo-pigeons to achieve precise control of their turning flight behavior outdoors. The results also suggest that robo-pigeons have potential for use in search and rescue operations where precise control of flight behavior is required.

Although MXene sheets are highly conductive, it is still challenging to prepare MXene complex functional materials for flexible electronics by simple and effective methods. In 3D printing, especially direct ink writing (DIW), different materials are used to create complex 3D shapes by formulating inks with controlled rheological properties. Herein, a printable MXene ink is developed, exhibiting good rheological properties, to print different complex shapes, and potentially manufacture electronic devices such as sensors. Then, we fabricated a highly sensitive hierarchical structure MXene composite materials composed of two layers of bionic micro-spine microstructure and network structure, formed by 3D printing and freeze casting. The obtained MXene composite materials exhibit good pressuring sensing properties with a sensitivity of 17.5 kPa(-1), a fast response time (<100 ms), and excellent cycle stability exceeding 10,000 cycles. The sensing mechanism suggesting that the hierarchical structure can effectively improve the sensitivity and response time. It also has good potential application in the monitoring of human health activities, including the detection of human joint activities, walking, pressure distribution, and other sports.

Dynamic hump is an active control method, which has been proved to be able to suppress laminar flow separation on the suction surface of high-loaded low-pressure turbine (LPT) blades at low Reynolds number (Re). This paper further discusses the effectiveness of dynamic hump with different parameters for flow separation control. The Pak-B cascade working at Re = 25,000 was selected as the research object, and a small-sized two-dimensional dynamic hump designed in a half-sinusoidal configuration was placed just upstream of the peak velocity point on the suction surface. At inlet free-stream turbulence intensity (FSTI or Tu) of 1.5

Control at beyond-visual ranges is of great significance to animal-robots with wide range motion capability. For pigeon-robots, such control can be done by the way of onboard preprogram, but not constitute a closed-loop yet. This study designed a new control system for pigeon-robots, which integrated the function of trajectory monitoring to that of brain stimulation. It achieved the closed-loop control in turning or circling by estimating pigeons' flight state instantaneously and the corresponding logical regulation. The stimulation targets located at the formation reticularis medialis mesencephali (FRM) in the left and right brain, for the purposes of left- and right-turn control, respectively. The stimulus was characterized by the waveform mimicking the nerve cell membrane potential, and was activated intermittently. The wearable control unit weighted 11.8 g totally. The results showed a 90% success rate by the closed-loop control in pigeon-robots. It was convenient to obtain the wing shape during flight maneuver, by equipping a pigeon-robot with a vivo camera. It was also feasible to regulate the evolution of pigeon flocks by the pigeon-robots at different hierarchical level. All of these lay the groundwork for the application of pigeon-robots in scientific researches.

为了实现在室内空旷环境中跟随机器人对移动目标物的定位和动态跟踪,设计了一种基于环形红外阵列的移动机器人自动跟随系统.利用具有主动式环形大视场的测距罗盘作为环境感知传感器.测距罗盘由数个红外测距传感器组成周向阵列,实现对360°环向10～80 cm范围内移动目标物的二维定位,使跟随机器人可以快速确定其与移动目标物之间的距离和偏航角,实现对目标物的精准定位.依据目标物的位置信息并利用PD(proportion-differentiation,比例-微分)控制器控制跟随机器人的移动,使跟随机器人保持与目标物的相对距离和相对角度,实现对移动目标物的自动跟随.在上位机操作界面可以实时显示跟随机器人的运动轨迹及其对周围未知环境的探测情况.通过实验证明了测距罗盘可以有效定位目标,满足机器人跟随移动目标物的设计要求.测距罗盘和自动跟随系统的可靠性较高,可以为机器人集群编队提供装置保障.

A flexible sensor with excellent pressure, temperature, and bending sensitivity is fabricated based on the conductive skeleton material with hierarchical porous structure. The conductive skeleton material is composed of carbon fibres (CFs) and multiwalled carbon nanotubes (MWCNTs), in which lay perpendicular to each other CFs are used as conductive frames, while MWCNTs are served as bridges to connect the CFs and increase the conductive network formation. Owing to the unique structure and the conductive materials, the as-prepared sensor exhibits a high-pressure sensing performance of 42.7 kPa (0-1 kPa), fast response, relaxation times of<100 ms, wide working range of 0-60 kPa, and high stability over more than 6000 cycles. Furthermore, the fabricated sensor presents a high thermal sensitivity of 2.46 C- 1 between 30 and 40 degrees C, excellent bending sensitivity of 95.5 % rad- 1 in the working range of 0-180 degrees, and great flexibility (over 1000 cycles), demonstrating its potential applications in multifunctional wearable electronics.