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The power extraction performance of two semi-active flapping airfoils at biplane configuration is analyzed in this work through numerical approach. Two NACA0015 airfoils, which are regarded as an energy extraction turbine, are arranged in a biplane configuration to perform forced counter pitching motion and are subsequently induced in a plunging motion. A numerical code based on finite volume method to solve the Navier-Stokes equations coupled with finite center difference method to solve the passive plunging motion governing equation is developed to simulate the interaction between the two semi-active flapping airfoils and fluid. Results show that the semi-active flapping airfoil cannot absorb more power from the fluid with biplane arrangement, but this arrangement is beneficial for the power extraction efficiency of the airfoil. Analysis of the fluid field of the airfoil reveals that the wing-wing interaction can promote the vortex evolution and reduce the vortex magnitude of the suction side of the biplane airfoils with appropriate initial distance (hs = 2.5d). As a result, the maximum plunging of the biplane airfoils is smaller than that of the single airfoil. The smaller maximum plunging displacement contributes to the increase in power extraction efficiency.

This work proposes a lightweight object detection network model ShuffleNet-SSD (S-SSD) to solve the problem of single shot multibox detector (SSD) network model where it cannot meet the real-time performance requirement in the task of object detection and recognition of indoor mobile robot. This model is suitable for indoor mobile robot by improving the SSD network model based on ShuffleNet network. The main idea of the improvement is that S-SSD replaces VGG-16 network as the basic feature extraction network of SSD network model with ShuffleNet network. The proposed model is based on the design of deep separable convolution, point-by-point grouping convolution, and channel rearrangement. It retains the design idea of multiscale feature graph detection of SSD network model. This model ensures a slight decline in detection accuracy while greatly reduces the amount of computation generated by the network operation, thereby greatly improving the detection rate. A data set for the task of object detection and recognition of indoor mobile robot is made. The S-SSD lightweight network model is superior to the original SSD network model and tiny-YOLO lightweight network model in terms of detection accuracy and detection rate, and can simultaneously meet the requirement of detection accuracy and real-time performance in the task of indoor object detection and recognition of mobile robot. These findings are verified through the comparative experiments of object detection accuracy and detection rate and real-time object detection and recognition of mobile robot under the actual indoor scene.

To address the problem that the energy capture efficiencies of existing flapping airfoil power generators are lower than those of traditional turbine generators, a dual‐layer flapping airfoil structure was adopted to improve the energy capture performance of the semiactive flapping airfoil, inspired by the multiwing flying mode of dragonflies in nature. The influence of the dual‐layer flapping airfoil structure on the energy capture performance of a semiactive flapping airfoil was systematically analyzed by a Taguchi experimental design and computational fluid dynamics simulations. The results showed that the dual‐layer flapping airfoil structure mainly improved the energy capture efficiency of the flapping airfoil by increasing the lift force and reducing the maximum sweep distance. Under the optimized parameter combination, the energy capture efficiency of the dual‐layer flapping airfoil reached 28.80%, which was 17.74% higher than that of the single‐layer flapping airfoil. Furthermore, the influence of the dual‐layer flapping airfoil structure on the energy capture performance of a semiactive flapping airfoil was related to the mass ratio of the system, and a larger mass ratio (M* ≥ 40) caused the performance of the dual‐layer flapping airfoil to deteriorate. Analysis of the vortices around the flapping airfoil revealed that there were more attached vortices on the surface of the dual‐layer flapping airfoil, but the increase in the mass ratio led to an advance of the separation of the leading edge vortex, which was the reason that the dual‐layer flapping airfoil with a smaller mass ratio had a better energy capture performance. Dual‐layer flapping airfoil structure is proposed to improve the energy capture performance of the semiactive flapping airfoil. The energy capture efficiency of the optimized dual‐layer flapping airfoil was increased by 17.74% with a mass ratio M* of 20. The leading edge vortex of the dual‐layer flapping airfoil was stronger with a proper mass ratio, which advanced the energy capture efficiency.

To efficiently harvest low-speed water energy, a novel fully passive flapping wing two electromagnetic hydroelectric generator (FPWTEMG)was developed in this work, and combined with Taguchi experimental testing and numerical simulation, the influence of the three key parameters: pitch amplitude (φ), pitch-axis position (l/c), and offset distance (d) on the generator's performance was systematically analyzed. The results show that, in the orthogonal experiments, the peak power of the generator with the optimal parameter combination can be increased by 114.4% compared with that of the worst parameter combination. Through further Taguchi experimental optimization, with the optimized parameter combination of φ=80°, l/c=0.45, and d=0mm, the FPWTEMG can achieve a peak power of 729.06 mW which performs an improvement of approximately 120.93% over the single electromagnetic hydroelectric generator. Further analysis of the flow-field structure on the wing surface reveals that stable and high-intensity vortices are formed on the wing surface of the optimized parameter combination generator, which results in higher pressure differentials and greater fluid forces on the upper and lower wing surfaces, thus leading the generator FPWTEMG having better energy harvesting performance.

The effect of varying damping coefficient C∗, spring coefficient K∗, and mass ratio M∗ on the semiactive flapping wing power extraction performance was numerically studied in this paper. A numerical code based on Finite Volume method to solve the two-dimensional Navier-Stokes equations and coupled with Finite Center Difference method to solve the passive plunging motion equation is developed. At a Reynolds number of 3400 and the pitching axis at quarter chord from the leading edge of the wing, the power extraction performance of the semiactive flapping wing with different damping coefficient, spring coefficient, and mass ratio is systematically investigated. The optimal set of spring coefficient is found at a value of 1.00. However, the variation of mass ratio M∗ cannot increase the maximum mean power coefficient and power efficiency, but it can influence the value of damping coefficient C∗ at which the wing achieves the maximum mean power coefficient and power efficiency. Moreover, insensitivity of the mean power coefficient and power efficiency to the variation of damping coefficient C∗ is observed for the wing with smaller mass ratio, which indicates the wing with smaller M∗ has better working stability.

Data quality and spatial resolution play an important role in the study of debris flow morphology and its evolution, contributing to the characterization of the related hazard. Satellites imagery exhibits substantial errors in mountainous regions with pronounced elevation variability. Formerly developed backpack-type advanced channel detection and mapping system (AscDAMs) could fulfill this requirement. However, owing to manpower constraints, the efficiency and coverage of AscDAMs remain limited. Although unmanned aerial vehicles (UAV) with autonomous exploration capability can be expected to overcome these limitations, the existing algorithms are not suitable for the semi-enclosed environment such as debris flow gullies. To allow UAV-based autonomous data acquisition inside debris flow channel, this study proposes a novel auto-exploration system, named AscDAMs 2.0, by transitioning the deployment of sensors from backpack-type platform to UAV. The new algorithm includes a point cloud merger, a height estimator, and an optimal direction calculator, which enable the UAV to automatically navigate and map the complex mountainous debris flow channel. AscDAMs 2.0 was successfully tested in Chutou Gully and Banzi Gully in Wenchuan County (China) achieving a spatial resolution of 0.1 m for mapping debris flow channel morphology. Compared to backpack-type mapping systems, AscDAMs 2.0 enables remote-controlled and faster surveys, acquiring more data while minimizing operational risks during data acquisition in hazardous environments. AscDAMs 2.0 demonstrates the potential for frequent, regular detection of debris flow channels, offering applications in risk assessment, hazard mitigation, and disaster forecasting and early warning.

Vertical axis wind turbine is a special type of wind-force electric generator which is capable of working in the complicated wind environment. The self-starting aerodynamics is one of the most important considerations for this kind of turbine. This article aims at providing a systematic synthesis on the self-starting aerodynamic characteristics of vertical axis wind turbine based on the numerical analysis approach. First, the physical model of vertical axis wind turbine and its parameter definitions are presented. Secondary, the interaction model between the vertical axis wind turbine and fluid is developed by using the weak coupling approach; the numerical data of this model are then compared with the wind tunnel experimental data to show its feasibility. Third, the effects of solidity and fixed pitch angle on the self-starting aerodynamic characteristics of the vertical axis wind turbine are analyzed systematically. Finally, the quantification effects of the solidity and fixed pitch angle on the self-starting performance of the turbine can be obtained. The analysis in this study will provide straightforward physical insight into the self-starting aerodynamic characteristics of vertical axis wind turbine.

Understanding the effect of fluctuating wind on the aerodynamic performance of the wing is important for designing practical using flapping-wing micro air vehicles (FMAV). This paper aims at providing a systematic synthesis on the fluctuating wind influence on the performance of the three dimensional lumped flexibility wing based on the numerical analysis approach. The fluctuating wind is simplified as a sine type function, and the flexibility of the wing is modeled as the passive pitching motion by connecting a rigid wing to a torsional spring at the root of the wing. The interaction between the fluctuating wind and the lumped flexibility wing is performed on a high-resolution computational grid. The evaluation is based on validation with published experiment data. The results indicate that the fluctuating wind cannot enhance the flexible wings’ propulsive and lifting performance simultaneously, however, it influences the aerodynamic characteristics of the wing greatly. Comparing to the rigid wing, the suppress leading edge vortex and trailing edge vortex are observed of the flexible wing under appropriate fluctuating wind, which leads the flexible wing to not only have better propulsive and lifting performance, but also flight stability performance.

The biplane counter-flapping wing is a special type of wing flapping which is inspired from the fish and insect in nature. The propulsive performance is one of the most important considerations for this kind of flapping wing. This paper is aimed at providing a systematic synthesis on the propulsive characteristics of two flapping wings at biplane configuration based on the numerical analysis approach. Firstly, parameters of this special flapping wing are presented. Secondly, the numerical method for simultaneously solving the incompressible flow and counter-flapping motion of the wing is illustrated, and the method is then validated. Thirdly, the effects of phase angle and mean wing spacing on the propulsive characteristics of the biplane counter-flapping wing are analyzed. Finally, the quantification effects of the phase angle and mean wing spacing on the propulsive characteristics of the biplane counter-flapping wing can be obtained. The analysis results in this study will provide useful guidelines to design an effectively propulsive system applying for the flapping micro air or underwater vehicle.

Aiming at the problems that the robot being in the process of navigation cannot meet the requirements of real-time and accuracy at the same time, moreover is too close to obstacles and lacks the initiative to avoid obstacles, a Voronoi diagram algorithm for improved skeleton extraction suitable for dynamic environment is proposed. On the one hand, firstly the grid map is preprocessed by binarization, corrosion and expansion, so the reduced skeleton map suitable for navigation is obtained, then the reduced skeleton map is extracted for searching the global path, finally the improved cubic spline smoothing algorithm is used to optimize the global path each planned, thus overcoming the defects of bloated and tortuous in the path obtaining by original Voronoi diagram algorithm. On the other hand, the position information of all obstacles is obtained by a single scan lidar. Firstly, segmenting and linearly fitting all laser point clouds to remove the known obstacles in the map. Then to mark new possible dynamic obstacles with circles of appropriate size. Secondly detecting dynamic obstacles by the alteration of their center coordinates, moreover, solving their motion equations. Finally expanding the cost map along the speed direction of dynamic obstacles and combining DWA dynamic window method to realize dynamic obstacle avoidance. Compared with the original DWA algorithm, it can predict the motion state of dynamic obstacles in advance, which improves the safety of the robot in the dynamic environment. Moreover, the effectiveness of the algorithm is verified by many simulation experiments and real environment experiments.