Showing papers in "Aerospace Science and Technology in 2020"

Abstract: The rate of fuel mixing inside the combustor is highly significant and effective on the performance of the scramjet engine. In this study, numerical simulations are applied to study the influence of the sinusoidal shock generator on the flow structure of the multi hydrogen jet at supersonic crossflow. The primary focus of this research is to perform flow analysis to determine the role of the shock interaction produced by the presence of the shock generator on the rate of mixing in the downstream of the fuel jets. To simulate the flow, the CFD method with the K-w turbulence model is applied to capture the shock formation inside the domain. According to our results, the mixing rate increases by approximately 40% as the amplitude of the sinusoidal shock generator increases from 2 to 5 mm. Besides, it is found that the fuel distribution becomes uniform when the produced shock generator is more strengthen.

Abstract: The cavity flame holder is a conventional technique for efficient fuel mixing and auto-ignition inside the Scramjet engine. In this study, a computational method is applied to study the impact of the wedge shock generator on the fuel mixing performance inside the combustor at the supersonic flow of M=4. The main focus of the current work is to compare the vortex structure formed inside the cavity in various conditions. To perform simulations, a three-dimensional model with a structure grid is produced to fine reliable solution for our study. To capture the real flow structure, the SST turbulence model is applied for obtaining viscosity. The obtained results demonstrate that the presence of the wedge shock generator increase the mainstream entrains into the cavity. This declines the temperature inside the cavity and strengthens the fuel mixing rate which is highly significant for the efficient combustion process within the scramjet engine. According to our findings, secondary circulation weakens by the amplification of the oblique shock.

Abstract: This paper studies wave propagation in functionally graded metal foam plates reinforced with graphene platelets (GPLs), where various types of porosity and GPL distribution are taken in account. The Halpin–Tsai model is employed to express the material properties of metal foam plates reinforced with GPLs. The governing equations of wave propagation in metal foam plates are derived by Hamilton's principle together with different plate theories, upon which wave dispersion relations in plates are achieved. Then, the validation of proposed model is examined by comparing the natural frequencies calculated in present study and those from literature. Finally, the effects of porosity and GPL distributions, porosity coefficient, GPL volume fraction and geometry on wave dispersion relations are evaluated.

Abstract: Many-objective optimisation is a design problem, having more than 3 objective functions, which is found to be difficult to solve. Implementation of such optimisation on aircraft conceptual design will greatly benefit a design team, as a great number of trade-off design solutions are provided for further decision making. In this paper, a many-objective optimisation problem for an unmanned aerial vehicle (UAV) is posed with 6 objective functions: take-off gross weight, drag coefficient, take off distance, power required, lift coefficient and endurance subject to aircraft performance and stability constraints. Aerodynamic analysis is carried out using a vortex lattice method, while aircraft component weights are estimated empirically. A new self-adaptive meta-heuristic based on decomposition is specifically developed for this design problem. The new algorithm along with nine established and recently developed multi-objective and many-objective meta-heuristics are employed to solve the problem, while comparative performance is made based upon a hypervolume indicator. The results reveal that the proposed optimiser is the best performer for this design task.

Abstract: A new dynamic model of the rotating tapered cantilever cylindrical panel with the graphene coating layers is developed to investigate the vibration characteristics of the rotating pretwisted tapered blade. It is assumed that the graphene platelets (GPLs) are randomly oriented and uniformly dispersed in the top layer and the bottom layer of the rotating pretwisted composite tapered blade. The modified Halpin-Tsai model is used to estimate the effective Young's modulus. The rule of the mixture is used to calculate the effective Poisson's ratio and mass density. Based on the Green strain tensor, an accurate strain-displacement relationship is acquired. The effects of the centrifugal force and Coriolis force are considered in the formulation. The Chebyshev-Ritz method is utilized to obtain the natural frequencies and mode shapes of the rotating pretwisted composite tapered blade with the graphene coating layers. The accuracy of the proposed model is validated through several comparison studies with the results of the present literatures and ANSYS. The free vibration characteristics are analyzed by considering different material and geometry parameters of the rotating pretwisted composite tapered cantilever cylindrical panel with the graphene coating layers, such as the graphene platelet (GPL) geometry, GPL weight fraction, taper ratio, length-to-radius ratio, pretwist angle, presetting angle and rotating speed. The frequency veering and the mode shape shift phenomena are found in the rotating pretwisted tapered cantilever cylindrical panel with the graphene coating layers.

Abstract: Based on nonsingular terminal sliding mode control (NTSMC), a flight controller is proposed in this paper for a quadrotor with a total rotor failure. The proposed method is a finite-time position and attitude tracking approach with strong robustness. At first, the fault-tolerant controller for the quadrotor with a total rotor failure is derived, and the model uncertainties and wind disturbances are considered. The dynamic model of the quadrotor is introduced and divided into two control loops: the inner control loop and the outer control loop. Based on the division of the control system, the NTSMC based inner controller is designed which makes the attitude dynamics converge to the desired attitude in finite-time. And the NTSMC based outer controller is derived which generates the desired attitude for the inner controller and makes the dynamics converge to the desired position in finite-time. The stability of the closed-loop system is analyzed by Lyapunov theory and the stability conditions are obtained. Then, in order to improve the practicability of the control algorithm, a flight controller for a fault-free quadrotor is proposed which has a similar structure compared with the fault-tolerant one. A fault detection and isolation method is applied to detect the fault and reconfigure the flight controllers. Moreover, two estimation methods for external disturbance and model uncertainties are applied to enhance the robustness of the proposed flight controller. The estimated wind disturbances results are introduced into the outer controller to compensate for the effect of disturbance while the model uncertainties estimator is applied in the inner control loop. Finally, numerical simulation results show the great performance of the proposed flight control method.

Abstract: Designing assembly relationship during operation always involves the analyses of many components and multi-discipline interaction, and seriously influences the reliability and work efficiency of complex machinery. To improve the assembly relationship design, distributed collaborative improved support-vector regression (DCISR) method and multilevel nested model are developed to effectively perform the reliability-based design optimization (RBDO) of the assembly relationship. In the DCISR method, the improved support-vector regression (ISR) is developed as the basis function of the DCISR model for reliability analysis, by adopting multi-population genetic algorithm (MPGA) to find the optimal model parameters. The proposed multilevel nested model is considered as optimization model for optimizing the assembly relationship. The developed approach and model were applied to the RBDO of turbine blade-tip running clearance in respect of nonlinear material parameters and transient loads. As revealed in this study, all optimal solutions satisfy the design requirements of both the blade-tip clearance and the corresponding assembly components. The optimized clearance is reduced by 10% approximately under the reliability premise, by optimally balancing the working efficiency and reliability of the blade-tip. In term of the comparisons of methods and models, it is illustrated that the presented DCISR method holds higher computational efficiency and precision, and the multilevel nested model has higher precision in the RBDO of operating assembly relationship. The efforts of this study provide the efficient method and model to optimally design the complex operating assembly relationship, and thereby enrich mechanical reliability method.

Abstract: To improve the dynamic reliability analysis of complex structures like turbine blisk, moving extremum surrogate modeling strategy (MESMS) is proposed in respect of multi-physics coupling with various dynamics/uncertainties. In this strategy, extremum thought is adopted to handle the dynamic process of input parameters and output response, and the importance sampling (IS) method is utilized to extract efficient samples and improve the efficiency of dynamic reliability estimation, and moving least square (MLS) method is used to select good samples from training samples with local compact support region to establish a precise surrogate model. The dynamic reliability analysis of turbine blisk radial deformation with fluid-thermo-structural interaction is performed to validate the developed MESMS in approximate precision and simulation performance by comparing to other methods. As shown in this study, (i) the reliability degree of turbine blisk is 0.9975 when the allowable value of radial deformation is 2.6856 × 10−3 m subject to 3 sigma levels; (ii) the proposed MESMS processes high modeling accuracy and efficiency due to small error; (iii) the MESMS holds high simulation performance in efficiency and accuracy owing to outstanding computational consumption and simulation. These results demonstrate that the MESMS is effective and applicable in structural reliability estimation regarding dynamics and uncertainties. The efforts of this paper provide a useful insight for performing the reliability-based design optimization of complex structures besides turbine blisk.

Abstract: Penetration and distribution of fuel inside the supersonic combustor significantly influence on the overall performance of the scramjet This research employed the numerical technique to examine the mixing performance of the multi-hydrogen jets at supersonic airflow when the downstream step exists in the downstream of the jet CFD simulations are conducted to disclose the feature of multi jets when a downstream step is applied The effects of back step height, free stream Mach number and fuel jet pressure on the mixing efficiency of the four hydrogen jets are disclosed Our study indicates that decreasing the back step height from 3 mm to 15 mm increases the mixing rate up to 28% in downstream of the multi jets Besides, the formation of the normal shock in upstream of the jet reduces fuel mixing while the normalized mixing factor of fuel jets enhances in downstream of injectors

Abstract: This paper presents an intelligent cooperative mission planning scheme for unmanned aerial vehicle (UAV) swarm, to search and attack the time-sensitive moving targets in uncertain dynamic environment, by using a hybrid artificial potential field and ant colony optimization (HAPF-ACO) method. In the search-attack mission environment of UAV swarm under the dynamic topology interaction, a time-sensitive target probability map is established. Based on the HAPF, the target attraction field, threat repulsive field and repulsive field are constructed for the environmental cognition. A distributed ACO algorithm is designed to improve the UAVs' global searching capability. For this mission planning problem, four time-sensitive moving target types and four constraint types of UAV swarm are considered, which will contribute to the practical applications of the HAPF-ACO. Several simulations are carried out to exhibit the superiority on the task execution efficiency and obstacle and collision avoidance performance of the proposed intelligent cooperative mission planning scheme.

Abstract: This paper proposes an active fault-tolerant control strategy for a quadrotor helicopter against actuator faults and model uncertainties while explicitly considering fault estimation errors based on adaptive sliding mode control and recurrent neural networks. Firstly, a novel adaptive sliding mode control is proposed. In virtue of the proposed adaptive schemes, the system tracking performance can be guaranteed in the presence of model uncertainties without stimulating control chattering. Then, due to the fact that model-based fault estimation schemes may fail to correctly estimate fault magnitudes in the presence of model uncertainties, a fault estimation scheme is proposed by designing a parallel bank of recurrent neural networks. With the trained networks, the severity of actuator faults can be precisely estimated. Finally, by synthesizing the proposed fault estimation scheme with the developed adaptive sliding mode control, an active fault-tolerant control mechanism is established. Moreover, the issue of actuator fault estimation error is explicitly considered and compensated by the proposed adaptive sliding mode control. The effectiveness of the proposed active fault-tolerant control strategy is validated through real experiments based on a quadrotor helicopter subject to actuator faults and model uncertainties. Its advantages are demonstrated in comparison with a model-based fault estimator and a conventional adaptive sliding mode control.

Abstract: Auxetic lattice cylindrical shell consisting of re-entrant lattice cell has superior mechanics performance due to negative Poisson's ratio (NPR). In this work, finite element models were established and finite element method (FEM) was adopted to explore the deformation behaviors and energy absorption of re-entrant auxetic lattice cylindrical shells and the SILICOMB lattice cylindrical shell in different crushing velocity. Result indicated that the deformation behaviors of auxetic lattice cylindrical shells are expressed as NPR mode, and different deformation behaviors (‘Z’ mode, ring mode, diamond mode and mixed mode) of lattice sandwich cylindrical shells are mainly determined by the ratio of the core wall thickness to the skin. The SILICOMB lattice cylindrical shell has better performance than the conventional hexagon honeycomb lattice cylindrical shell when crushing under high velocity. Meanwhile, the SILICOMB sandwich cylindrical shell has the best performance on the specific energy absorption among these four configurations and the maximum increment is 20.77%. The design of the auxetic and the SILICOMB cylindrical shells may provide a new idea which can be applied in practical application as impact resistance structures on aerospace.

Abstract: In the present era, the demand for self-powered electronic instruments is increasing and their energy consumption is decreasing. The ability to extract energy from the operating environment is of great importance in advanced industrial applications particularly in the field of aerospace. In this research, a flag-flutter based piezoelectric (PZT) energy harvester is modeled based on fluid-structure interaction (FSI) that represents an important area of research for the development of innovative energy harvesting solution. The possibility to harvest energy from Limit Cycle Oscillations (LCOs) by means of piezoelectric transduction is investigated via numerical and experimental tests. Moreover, the flutter instability of a cantilevered flag with piezoelectric (PZT) and Aluminium (Al) patches, subjected to an axial flow has been investigated. The numerical simulations are performed in MSC Nastran software and the experimental campaign is performed in a subsonic wind-tunnel. The practical interest of this instability mechanism, which can lead to self-sustained oscillations, is the possible application in flow energy harvesting. Furthermore, the critical velocities for different length of flags are also predicted numerically and experimentally. The numerical results are in good agreement with experiments, as well as with results in the literature. The maximum power output obtained by the designed harvester experimentally is found to be 1.12 mW for 66.6 kΩ resistance. The presented model is suitable to harvest energy and to drive wireless sensors.

Abstract: Experimental analysis of base pressure in suddenly expanded compressible flow from nozzles at different Mach numbers is performed. Intensive experimentation is carried out to investigate the base pressure and wall pressure of flow expanding from the nozzles into the enlarged duct. Microjets to actively control the flow are adopted to increase the base pressure. Experiments were conducted for Mach numbers (one sonic and rest supersonic) from 1 to 3, nozzle pressure ratio (NPR) from 3 to 11. The duct length considered from 10 to 1, and the area ratios tested were from 2.56 to 6.25 are the variables whose effect on base and wall pressure is studied using response surface methodology. The K-means algorithm performs a clustering analysis of this enormous data, which provides useful information and patterns. Regression of both the pressures using a random forest classification algorithm is carried out. The response surface analysis reveals that microjets are efficient when the flow is under the influence of a favorable pressure gradient. The base pressure reduces from maximum to minimum when the flow regime changes from over to correct expansion by increasing the NPR. Lower area ratio and higher duct length have a minimum effect on base pressure. The wall pressure flow field is unaffected due to the presence of the microjets. K-means clustering revealed that a high percentage of base pressure is in the lower range. This necessitates the importance of increasing the base pressure to reduce the base drag. Random forest algorithm has proved to be a handy tool for predicting base pressure and wall pressure and similar highly non-linear data.

Abstract: This paper presents an estimator-based minimal learning parameter (EMLP) neuroadaptive dynamic surface containment control design capable of guaranteeing transient and steady-state behavior for multiple quadrotors with uncertainties, such that the followers can be driven into the convex hull constituted by multiple dynamic leaders with prescribed bounded errors. To facilitate the control design, the quadrotor dynamics is decomposed into translational and rotational subsystems. For each subsystem, in order to enable smooth and rapid learning of unknown system uncertainties and reduce the computational load in traditional neural network (NN), the estimation errors, instead of tracking errors, are used to regulate NN weights and only one NN learning parameter is required for adaptive neural approximation with the aid of MLP, which is more feasible for real-time implementation. Additionally, dynamic surface control (DSC) technique is introduced in control design to extract the time derivative of virtual control laws, and thus the issue of “explosion of complexity” can be circumvented. As an extension, prescribed performance function and error transformation technique are utilized to address the preselected containment synchronization error constraints problem. Finally, the stability analysis is established to prove that all error signals are uniformly ultimately bounded (UUB). Simulation results illustrate the effectiveness and superiority of the proposed control scheme.

Abstract: In this paper, the nonlinear dynamic response of a FG multilayer beam-type nanocomposite reinforced with graphene nanoplatelet (GNP) by considering the initial geometric imperfection is investigated on the basis of nonlocal strain gradient Euler-Bernoulli beam theory. Four patterns of GNP distribution incorporating the uniform distribution (UD) and O-, X-, and A- FG pattern distributions are taken into account and the effective elastic properties of the beam-type nanocomposite are evaluated in the framework of Halpin-Tsai scheme. The first-order vibrational mode is employed to represent the initial geometric imperfection of the nonlinear FG beam-type nanocomposite. Correspondingly, the nonlinear amplitude-frequency response of the imperfect FG multilayer beam-type nanostructures subjected to the excitation resonance is analyzed with the aid of multiple scale method. Firstly, the present model is validated with a comparison of two previous works. Then, a comprehensive investigation is conducted to evaluate the effects of GNP distributed pattern, weight fraction of GNPs, geometric imperfection amplitude, boundary condition, excitation amplitude, nonlocal and strain gradient size scale parameters on the nonlinear frequency-response of FG multilayer beam-type nanostructures. The current work is beneficial for the application of GNP as reinforcement to enhance mechanical performances of nanostructures.

Abstract: Landing of unmanned aerial vehicles (UAVs) is a difficult problem because of their light weight, external disturbances, and strong coupling between the longitudinal and lateral modes. This paper presents the design of a new automatic landing system for fixed wing UAVs subject to wind gusts and errors of the measurement sensors. Using the airplane nonlinear model, a new control approach is proposed. It unifies the backstepping and the dynamic inversion methods to directly control the roll and the yaw angles of the UAV, the flight altitude and the speed (longitudinal plane) by ensuring a constant forward velocity during all the three landing stages. The wind gusts and the three components of the UAV velocity are estimated with a disturbance observer, as part of the auto-landing system. The novel control architecture is software implemented and validated by complex numerical simulations. The obtained characteristics prove the finite time stability and robustness of the new automatic landing system even in the case of landing affected by wind gusts and errors of the sensors.

Abstract: Persistent surveillance in a complex unknown urban area by an unmanned aerial vehicle (UAV) swarm is a low-cost, promising future application for anti-terrorism, disaster monitoring, and battlefield situational awareness. Based on over-simplified simulated surroundings and a UAV dynamic model, a few remarkable approaches have been proposed; however, they typically rely on non-sensor-based inputs and prior knowledge on the environment or targets. To overcome these limitations, based on simulated city blocks, a two-level quasi-distributed control framework is proposed for realizing the continuous control of a UAV swarm in two defined surveillance phases. With the support of a well-trained and corrected artificial neural network (ANN) in low-level UAV manoeuvre control for target homing and collision avoidance, several preliminary high-level target allocation strategies are designed for a cooperative overall objective based on the synchronization of local surveillance data. Then, via a series of numerical simulations, an optimal high-level strategy combination is identified. Finally, the surveillance performance of this strategy combination is evaluated under various swarm sizes and UAV launching patterns. The simulation results demonstrate that the proposed control framework is applicable for UAV swarm control in the persistent surveillance of unknown urban areas.

Abstract: The evaluation of flexible mechanism involving multi-body dynamics with high nonlinearity and transients urgently requires an efficient evaluation method to enhance its reliability and safety. In this work, an enhanced network learning method (ENLM) is proposed to improve the modeling precision and simulation efficiency in flexible mechanism reliability evaluation, by introducing generalized regression neural network (GRNN) and multi-population genetic algorithm (MPGA) into extremum response surface method (ERSM). In the ENLM modeling, the ERSM is adopted to reasonably handle transients (time-varying) problem in motion reliability analysis by considering one extreme value in whole response process; the GRNN is applied to address high-nonlinearity in surrogate modeling; the MPGA is utilized to find the optimal model parameters in ENLM modeling. In respect of the developed ENLM, the motion reliability of two-link flexible robot manipulator (TFRM) was evaluated, with regard to the related input random parameters to material density, elastic modulus, section sizes, and deformations of components. In term of this study, it is illustrated that (i) the comprehensive reliability of flexible robot manipulator is 0.951 when the allowable deformation is 1.8×10−2 m; (ii) the maximum deformations of member-1 and member-2 obey normal distributions with the means of 1.45×10−2 m and 1.69×10−2 m as well as the standard variances of 6.77×10−4 m and 4.08×10−4 m, respectively. The comparison of methods demonstrates that the ENLM improves the modeling precision by 3.29% and reduces the simulation efficiency by 1.19 s under 10 000 simulations, and the strengths of the ENLM with high modeling precision and high simulation efficiency become more obvious with the increase of simulations. The efforts of this study provide a learning-based reliability analysis way (i.e., ENLM) for the motion reliability design optimization of flexible mechanism and enrich mechanical reliability theory.

Abstract: The reconstruction of the displacement field of a structure (shape sensing) has become crucial for the Structural Health Monitoring of aerospace structures and for the progress of the recently developing morphing structures. As a consequence, shape sensing techniques based on discrete surface strains measurements have seen a consistent expansion in the last few years. In this paper, the three main shape sensing methods, the Modal Method, the Ko's displacements theory and the inverse Finite Element Method, are presented. The most recent and also novel improvements are discussed and added to the methods' formulations. Then, the three methods are numerically applied to a complex aerospace structure such as that of a composite wing box experiencing bending and twisting deformations. For the first time, a detailed investigation on the optimal strain sensors configuration is performed for all the three techniques simultaneously. Finally, the methods' performances, in terms of accuracy of the reconstruction and of number of required sensors, are compared. The three methods show different characteristics that make them suitable for different applications, depending on the level of accuracy and the number of strain information required. The iFEM is proven to be the more accurate but the more demanding in terms of required sensors; the Ko's displacement theory is capable of giving a rough estimation of the displacement field, but requires a small amount of sensors; the Modal Method represents a trade-off between the other two in terms of accuracy and number of sensors required.

Abstract: Dynamic buckling optimization in laminated truncated nanocomposite conical aircraft shell in moisture and temperature environments as well as magnetic fields is considered in this article. The structural layers are hybrid nanocomposite consist of polymer, carbon nanotubes (CNT) and carbon fibers based on Halpin-Tsai model. Utilizing theory of Mindlin, the final equations are solved and derived by method of Bolotin and differential quadrature method (DQM). In the optimization process utilizing improved meta-heuristic algorithm basis Grey Wolf optimization (GWO), the instability and frequency of the structure are utilized to define the subjective and objective functions. The GWO is improved using an adjusting randomly process with normal distribution. The main contribution of this study is maximizing the inequality and frequency constraint to control its instability. In the optimization procedure, the cone semi vertex angle, moisture and layers number change are optimized and the temperature influences, carbon fiber volume percentage, magnetic field and CNT radius are considered. The outcome shows that the proposed improved GWO may provide better abilities to search the global conditions compared to GWO because of rising flexibility to study optimum conditions of this complex problem. It is observed that the optimum frequency of system without retrofitting by CNTs is lower than the case of ω CNT ≠ 0 .

Abstract: We present a novel guidance law that uses observations consisting solely of seeker line-of-sight angle measurements and their rate of change. The policy is optimized using reinforcement meta-learning and demonstrated in a simulated terminal phase of a mid-course exo-atmospheric interception. Importantly, the guidance law does not require range estimation, making it particularly suitable for passive seekers. The optimized policy maps stabilized seeker line-of-sight angles and their rate of change directly to commanded thrust for the missile's divert thrusters. Optimization with reinforcement meta-learning allows the optimized policy to adapt to target acceleration, and we demonstrate that the policy performs better than augmented zero-effort miss guidance with perfect target acceleration knowledge. The optimized policy is computationally efficient and requires minimal memory, and should be compatible with today's flight processors.

Abstract: This paper presents an experimental study on the combustion stability characteristics and flame/flow dynamics in a multi-nozzle, lean premixed prevaporized (LPP), swirl-stabilized gas turbine model combustor with different swirler configurations in the presence of self-excited combustion instability. The flame structure was characterized using high-speed OH⁎ chemiluminescence imaging and the flow field across the centerline of three interacting flames was measured by high-speed planar Particle Image Velocimetry (PIV). Two sets of the swirler configurations were considered in this paper, featuring different combinations of swirl rotational directions. The first one consisted of three co-rotating swirlers, whereas the central swirler in the second configuration was replaced by a swirler with counter-rotation direction. These two configurations were termed as COS and CNS combustors respectively in the rest of the paper. It was found that these two combustors exhibited similar stable and unstable operating domains in terms of different equivalence ratios and inlet air velocities. At the same test condition, the amplitude of dominant instability of COS combustor was 130 dB, which was stronger than that of CNS combustor (120 dB). Phase-averaged PIV measurements showed that both COS and CNS combustor featured three recirculation zones downstream the swirlers, and high axial velocity was present after the merging of the adjacent flames. These two flow structures varied periodically, but in different manners for COS and CNS combustors. Phase-averaged OH⁎ chemiluminescence images indicated that the flame was primarily anchored in recirculation zones close to the swirler and most of the heat release was found to occur in flame interaction regions, where large-scale reaction intensity variations occurred. Furthermore, a greater phase delay between heat release rate and acoustic pressure was observed in CNS combustor, which contributed to a weaker instability comparing with that in the COS combustor.

Abstract: This paper presents the first attempt to study the probabilistic stability characteristics of functionally graded (FG) graphene platelets (GPLs) reinforced beams by taking into account the multidimensional probability distributions, such as stochastic porosity and GPL distribution patterns as well as random material properties. For this purpose, a non-inclusive Chebyshev metamodel (CMM), which is implemented on deterministic analysis using discrete singular convolution (DSC) method with excellent computational efficiency and accuracy, is proposed and used to obtain both deterministic and probabilistic results including probability density functions (PDFs), cumulative density functions (CDFs), means and standard deviations of the critical buckling load. The present analysis is rigorously validated through direct comparisons against the results obtained by a direct quasi-Monte Carlo simulation (QMCS) method and those available in open literature. The influences of material properties, porosity distribution, GPL dispersion pattern and boundary condition on probabilistic buckling behaviour of the FG-GPL beam are comprehensively investigated. The global sensitivity analysis is also conducted. The results suggest that the critical buckling load of the FG-GPL beam is most sensitive to porosity distribution, followed by porosity coefficient and GPL weight fraction.

Abstract: A free-floating space robot exhibits strong dynamic coupling between the arm and the base, and the resulting position of the end of the arm depends not only on the joint angles but also on the state of the base. Dynamic modeling is complicated for multiple degree of freedom (DOF) manipulators, especially for a space robot with two arms. Therefore, the trajectories are typically planned offline and tracked online. However, this approach is not suitable if the target has relative motion with respect to the servicing space robot. To handle this issue, a model-free reinforcement learning strategy is proposed for training a policy for online trajectory planning without establishing the dynamic and kinematic models of the space robot. The model-free learning algorithm learns a policy that maps states to actions via trial and error in a simulation environment. With the learned policy, which is represented by a feedforward neural network with 2 hidden layers, the space robot can schedule and perform actions quickly and can be implemented for real-time applications. The feasibility of the trained policy is demonstrated for both fixed and moving targets.

Abstract: Fluid-structure interaction can be utilized to harvest the low-speed wind energy for sustaining the low-power sensors for structural health monitoring. To enhance the low-speed wind energy harvesting, this study proposes the novel spindle-like and butterfly-like bluff bodies by coupling both the vortex-induced vibration (VIV) and galloping phenomena. Comprehensive wind tunnel experiments are conducted to investigate the advantages of the two bluff bodies in terms of the bluff body cross-sections and installment directions. The experimental results demonstrate that for both the spindle-like and butterfly-like bluff bodies, the vertical installment and small width ratio are beneficial to the performance in a broad range of wind speeds. Compared to a conventional galloping-based energy harvester, owing to the coupling between the VIV and galloping, the vertical spindle-like bluff body with the smallest width ratio can reduce the threshold wind speed of activating the energy harvesting function by over 13%, and improve the maximum voltage output by over 160%. Finally, taking the spindle-like bluff body as an example, the computational fluid dynamics (CFD) studies are conducted by using XFlow software to interpret the physical insight of performance enhancement. The CFD results show that the vertical installment direction and a small width ratio play an important role. The two designs can lead to a stronger aerodynamic force due to the fast vortex shedding, which improves the energy conversion efficiency from the flow-induced vibrations.

Abstract: This paper presents an analytical investigation on the nonlinear buckling behavior of graphene platelets reinforced dielectric composite (GPLRDC) arches with rotational end restraints under applied electric and uniform radial load. The effective materials properties of GPLRDC, including the elastic modulus and dielectric permittivity, are estimated by employing effective medium theory (EMT). The analytical solutions for nonlinear equilibrium, critical load of limit point buckling and bifurcation buckling of the GPLRDC arch are derived according to the principle of virtual work. The critical geometric parameters and electric voltage governing the buckling mode switching behavior are also identified and discussed. The effects of graphene platelets (GPLs) weight fraction, size and geometry, applied DC voltage, AC frequency, as well as geometry of the arch on the buckling behavior are examined comprehensively. It is found that the dielectric property of the GPLRDC has significant effects on the buckling behavior of the GPLRDC when the GPLs concentration exceeds the percolation threshold. The nonlinear buckling behavior of the GPLRDC is quite sensitive to the AC frequency within a certain range. Furthermore, the change of the applied voltage can switch the buckling mode and even the number of limit points of the GPLRDC arch.

Abstract: The purpose of this paper is to perform a numerical study regarding the implementation of dielectric barrier discharge plasma micro-actuators for load alleviation on a NACA 23012 oscillating blade in a freestream flow. The work aims to evaluate the feasibility of using multiple dielectric barrier discharge (multi-DBD PAs) plasma actuators as a novel approach for load alleviation and stability control of airfoils in unsteady flow. A 6-actuators configuration, positioned at the trailing edge, is designed and tested. In this configuration, half of the actuators operate on the suction surface and the others on the pressure surface. In particular, the actuators located on the suction surface reduce the airfoil lift force if the induced body force is in a direction that is opposite of the main flow, because they lead to a slight and local increment of pressure on the surface. Instead, when actuators produce a body force aligned with the streamwise direction, they lead to a slight reduction of pressure, increasing lift. Contrarily, the actuators located on the pressure surface increase the lift, if the induced body force is in the direction opposite of the flow and reduce the lift in the opposite case. The effects of plasma actuators on the flow are incorporated into Navier–Stokes equations as a body force vector into the momentum equation. Different switching on/off laws of the actuators have been are compared, in order to reduce the loads amplitude of the airfoil, and to increase the stability of the blade response to the flow, and thus, alleviating fatigue phenomena on the blade and enhancing its aeroelastic stability. The effect of the phase of the plasma actuators switching law was evaluated for different pitching oscillation reduced frequencies, ranging from 0.1 to 0.5. The results underline the capability of DBD-PAs to control and reduce unsteady loads on an oscillating airfoil, improving also the airfoil stability if the phase of the actuation force is optimized for each pitching oscillation reduced frequency.

Abstract: In this paper, a four-nodded straight-sided geometric element is proposed for shear buckling problem of functionally graded material (FGM) composite and carbon nanotube (CNT) reinforced composite skew plate. By using the transformation rule, quadrilateral plate field is mapped into a square domain in the computational space using discrete singular convolution (DSC) method. Related governing equations of skew plate buckling and boundary conditions of the problem are transformed from the physical domain into a square computational domain by using the geometric transformation based singular convolution. The discretization process is achieved via the DSC method together with numerical differential and two-different regularized kernel such as regularized Shannon's delta (RSD) and Lagrange delta sequence (LDS) kernels. The accuracy of the present DSC results is first verified via exiting results in literature. Then, some parametric studies have been presented to show the effects of CNT volume fraction, CNT distribution pattern, geometry of skew plate and skew angle on the shear buckling responses of FG-CNTR composite skew plates with different boundary conditions. Some new results related to critical buckling of FGM and CNT reinforced composite skew plate have been presented which can serve as benchmark solutions for future investigations.

Abstract: In this article, a robust fuzzy controller based on the Linear Quadratic Regulator (LQR) method is presented and optimized by Multi-Objective High Exploration Particle Swarm Optimization (MOHEPSO) for a nonlinear 4 Degree-Of-Freedom (DOF) quadrotor. The LQR approach is applied after linearization via Jacobean matrices. The fuzzy system is designed using triangular and trapezoidal membership functions with the center average defuzzifier and singleton fuzzifier to regulate the LQR gains for each degree of freedom because of the uncertainties and nonlinearities. Then, the fuzzy system is optimized using MOHEPSO to find the best slopes for the membership functions with regard to minimization of the errors and control efforts. Finally, the obtained results are presented for a nonlinear 4DOF multi-purpose (for marine, ground and aerial maneuvers) quadrotor system designed and fabricated in Sirjan University of Technology, Sirjan, Iran, to assure the effectiveness of the proposed approach.