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In an era marked by increasing demands for stability and durability in construction, the importance of damage detection in concrete structures cannot be overstated. As these structures underpin the safety and longevity of vital assets, this paper embarks on a comprehensive exploration of methodologies to enhance precision and reliability in 2D concrete plate damage detection. By focusing on the interpolation of damage index values and leveraging the insights gained from energy loss analysis and the characterization of the time of arrival of signals, we address the pressing need for improved non-destructive damage detection techniques. Our study encompasses a range of simulation attempts, each involving various interpolation parameters, and systematically evaluates their performance. The culmination of this research identifies the most effective combination of techniques and parameters, leading to the best results in damage detection. This multidimensional investigation promises to provide valuable contributions to the field of structural health monitoring, benefiting both researchers and practitioners engaged in the evaluation of concrete structures.

This paper is concerned with the predefined-time exact sliding mode control issue of a class of high-order uncertain nonlinear systems with disturbances. The proposed control scheme is composed of a predefined-time exact disturbance observer and a two-stage predefined-time exact sliding mode controller. The disturbance observer can estimate the system disturbances accurately within an arbitrary predefined observation time, and the time can be set as the handover time between two control stages. The classic sliding mode controller guarantees bounded system states in the first control stage. Then, a predefined-time sliding mode controller is designed based on time-varying tuning function, regulating the system states to exact zero within a final predefined settling time in the second stage. It is shown that the control input signal is always chattering-free with respect to time. The effectiveness and superiority of the proposed control scheme is demonstrated with simulation examples.

In this paper, a novel electric-hydraulic power steering (EHPS) system and a vehicle stability coordination control algorithm are proposed which can not only ensure the accuracy of the trajectory tracking but also solve the coordination control problem between the stability of the lateral control and the stability of the roll in the extreme condition. Firstly, the EHPS system is designed to provide accurate control input of front wheel angle for vehicle lateral dynamics control. Secondly, on the basis of optimal preview theory, a new trajectory tracking fusion controller combined with sliding mode control is proposed to improve the accuracy and stability of the system in the process of vehicle lateral trajectory tracking control. Then, the stability domain boundary function of the phase plane is determined according to the phase plane of the sideslip angle-yaw rate, and the stability margin of the phase plane is calculated during the steering process. Finally, considering the tracking accuracy, lateral stability and roll stability performance in the process of trajectory tracking, the linear weighted algorithm is used to coordinate above three objectives, and the HIL bench test and real vehicle experiment verify that the proposed algorithm has good reliability and effectiveness.

The electro-mechanical brake is a new advancement in railway train braking. Ball-screws are important components of electro-mechanical braking units (EMBUs), and their wear can cause EMBUs to degrade in performance or even fail to function. In this paper, we present a framework for prediction of ball-screw wear with discrete operating conditions as inputs, taking into account the time-varying characteristics of EMBUs. The framework includes determining the contact type, analyzing relative motion, calculating contact deformations, and estimating wear. The contact type is determined based on the quasi-static approach of Hertz theory. A dynamics model using multiple coordinate systems is established to analyze how balls and raceways move in relation to each other. The contact deformations of the ball–raceway contact are determined using numerical calculation. Then, the wear depth increment is calculated using the Archard model. The results of the calculation and the endurance test indicate that the wear on the screw raceway is greater than that on the nut raceway. The effect of velocity is greater than the effect of axial force. The presented calculation framework is reasonable and can be used for predicting EMBU ball-screw wear.

The permanent magnet synchronous motor (PMSM) has been of interest to eco-friendly industries on account of its advantages such as high performance, efficiency, and precision control. However, perturbations due to PMSM parameter uncertainty, load torque, and external disturbance interfere with the construction of PMSM precision control systems. Therefore, a robust control system is needed to avoid unnecessary system movement caused by perturbations. In this paper, sliding mode control (SMC) is adopted to implement a robust control system for the PMSM. In order to reduce the reaching time from the initial system state to the sliding surface and the chattering phenomenon that can cause the system to malfunction, the adaptive quick sliding mode reaching law based on an exponential function and power equation is proposed. Although the SMC is robust to disturbance and parameter uncertainty, unexpected disturbances can destabilize the system. To estimate the unmatched disturbance in a short time, the second-order fast terminal sliding mode observer (SFTSMO) is proposed. The results show that the motor control system based on the proposed method has a fast convergence speed to an objective value, position tracking performance, and robustness.

Hydraulic switching actuators are high-efficiency, fast response, and low-cost solutions for hydraulic control systems. One of the challenging problems is throttling losses during valve transitions. Previously, the authors proposed a zero-flowrate switching method to reduce the throttling energy loss of the switching valve, where a hydraulic resonator is applied to make the flowrates through the lines approaching zero before the valves are switched off. The major challenge of this approach is fast switching valves whose transition times are less than 2 ms. In this paper, an improved zero-flowrate switching method is presented. It utilizes the capacity with independent inlet/outlet ports to regulate flowrates through the lines. Models of capacity applied in a simple line with different pressure signals are developed to explore characteristics of the capacity, based on which a complete actuation system is developed. In the complete model, resistance and inductance are optimized to achieve the desired flowrate response. The improved zero-flowrate switching method reduces throttling energy losses by 99.945% compared to a hard switching system. The simulation results demonstrated that the improved zero-flowrate switching method performs as expected in the design condition. A capacity with proper volume is able to regulate flowrates through all the lines to zero, with the help of appropriate resistance and inductance. Compared to the previous zero-flowrate switching method, the novel strategy allows slower switching valves applied in hydraulic actuation systems and achieves better efficiency performance. This research paves a new avenue for reducing throttling energy losses and improves system efficiency in hydraulic switching actuators, as well as most of the hydraulic switch-mode circuits.

People with upper limb disabilities or high quadriplegia have extremely high requirements for the maneuverability and functionality of power wheelchairs. Normal wheelchairs cannot meet travel tasks, while smart customized wheelchairs are expensive and cannot be popularized. Therefore, a novel extension control instrument for power wheelchairs with low cost, strong scalability, and convenient usage is proposed, which can realize the control of the wheelchair by sensing a change of head posture. The device is divided into a head motion sensing unit (HMSU) and a wheelchair assistance control unit (WACU). The mapping relationship between the head attitude and the subject’s motion intention is established. The inertial measurement module in the HMSU collects the head attitude data and uses the Kalman filtering method to obtain the accurate Euler angle. The WACU is fixed on the original controller of the wheelchair. The joystick is inserted into the extended control mechanism and controlled, instead of the hand, through a 2-degree-of-freedom servo system combined with the pinion and rack push rod structure, thus controlling the movement of the wheelchair. In proceeding, the system can also detect the distance of objects in the environment in real time through the three-direction (front, left, right) ultrasonic ranging sensors installed on the WACU, with a certain obstacle avoidance function. The prototype experiments prove that the extension control instrument developed in this paper based on the Kalman filter can quickly and accurately identify head motion and accurately control the movement of the wheelchair. It is easy to operate and has strong universality, which presents a new low-cost solution for the travel of patients with disabilities.

In light of the complex behavior of vibrating structures, their reliable modeling plays a crucial role in the analysis and system design for vibration control. In this paper, the reverse-path (RP) method is revisited, further developed, and applied to modeling a nonlinear system, particularly with respect to the identification of the frequency response function for a nominal underlying linear system and the determination of the structural nonlinearities. The present approach aims to overcome the requirement for measuring all nonlinear system states all the time during operation. Especially in large-scale systems, this might be a tedious task and often practically infeasible since it would require having individual sensors assigned for each state involved in the design process. In addition, the proper placement and simultaneous operation of a large number of transducers would represent further difficulty. To overcome those issues, we have proposed state estimation in light of the observability criteria, which significantly reduces the number of required sensor elements. To this end, relying on the optimal sensor placement problem, the state estimation process reduces to the solution of Kalman filtering. On this ground, the problem of nonlinear system identification for large-scale systems can be addressed using the observer-based conditioned RP method (OBCRP) proposed in this paper. In contrast to the classical RP method, the current one can potentially handle local and distributed nonlinearities. Moreover, in addition to the state estimation and in comparison to the orthogonal RP method, a new frequency-dependent weighting is introduced in this paper, which results in superior nonlinear system identification performances. Implementation of the method is demonstrated on a multi-degree-of-freedom discretized lumped mass system, representing a substitute model of a physical counterpart used for the identification of the model parameters.

Three distinct synchronized switching circuits based on a magnetostrictive actuator are compared in this paper to examine their control mechanisms and circuit characteristics. These circuits include a semi-active shunt circuit, a semi-active current inversion and amplification circuit, and a semi-active automatic current inversion and amplification circuit. Each circuit type employs an additional electronic switch. The synchronized switching method enables the rational control of the circuit current generated by the magnetostrictive actuator to fulfill any desired control strategy. Simulation and experimental results on a 10-bay truss structure reveal that the three circuits can effectively adjust the polarity of the induced current as needed. The three circuits are then compared to thoroughly analyze their unique characteristics and explain their respective advantages and dis-advantages. Using the comparison results, various options available for control circuit design are demonstrated.

Human driving behavior significantly affects vehicle fuel economy and emissions on hilly roads. This paper presents an ecological (eco) driving scheme (EDS) on hilly roads using nonlinear model predictive control (NMPC) in a mixed traffic environment. A nonlinear optimization problem with a relevant prediction horizon and a cost function is formulated using variables impacting the fuel economy of vehicles. The EDS minimizes vehicle fuel usage and emissions by generating the optimum velocity trajectory considering the longitudinal motion dynamics, the preceding vehicle’s state, and slope information from the digital road map. Furthermore, the immediate vehicle velocity and angle of the road slope are used to tune the cost function’s weight utilizing fuzzy inference methods for smooth maneuvering on slopes. Microscopic traffic simulations are used to show the effectiveness of the proposed EDS for different penetration rates on a real hilly road in Fukuoka City, Japan, in a mixed traffic environment with the conventional (human-based) driving scheme (CDS). The results show that the fuel consumption and emissions of vehicles are significantly reduced by the proposed NMPC-based EDS compared to the CDS for varying penetration rates. Additionally, the proposed EDS significantly increases the average speed of vehicles on the hilly road. The proposed scheme can be deployed as an advanced driver assistance system (ADAS).

This paper addresses the force-tracking problem of aerospace electro-hydraulic load simulators under the influence of high inertia, large loads, and a strong coupling force disturbance. An accurate mathematical model is initially derived to describe the characteristics of the load simulator system, the cause of the surplus force, and the strong phase lag due to large inertia. In order to overcome the position interference of the system and the large phase lag problem, a terminal sliding mode control strategy based on the modified fast double-power reaching law is proposed, based on the accurate mathematical model. This control strategy effectively suppresses the chattering problem of the sliding control and implements the finite time convergence of the system through the design of the reaching law and terminal sliding surface, ensuring the robustness of the system and the accuracy of the force-tracking problem. Finally, a comparison of the simulation and experimental results based on the design of different strategy controllers is performed to verify the effectiveness of the control strategy and system adaptability.

In micro-LED chip repair, a nanopositioner is commonly used to adjust the positioning of the LED chip. However, during the bonding process, the heat generated can cause the positioning system to deform, leading to inaccurate alignment and poor-quality chip repair. To solve this issue, a novel flexible connection structure has been proposed that can eliminate thermal deformation. The principle of this novel flexible connection structure is that the thermal distortion self-elimination performance is achieved via three flexible connection modules (FCM) so that the thermal stress is automatically eliminated. First, the paper introduces the principle of thermal deformation elimination, and then the design and modeling process of the proposed structure are described. A heat transfer model is then developed to determine how temperature is distributed within the structure. A thermal deformation model is established, and the size of the FCM is optimized using a genetic algorithm (GA) to minimize the thermal deformation. Finite element analysis (FEA) is used to simulate and evaluate the thermal distortion self-elimination performance of the optimized mechanism. Finally, experiments are conducted to verify the reliability and accuracy of the simulation results. The simulations and experiments show that the proposed structure can eliminate more than 38% of the thermal deformation, indicating an excellent thermal deformation self-eliminating capability.

The development of intelligent transportation technology has provided a significant impetus for autonomous driving technology. Currently, autonomous vehicles based on Model Predictive Control (MPC) employ motion control strategies based on sampling time, which fail to fully utilize the spatial information of obstacles. To address this issue, this paper proposes a dual-layer MPC vehicle collision-free trajectory tracking control strategy that integrates spatial kinematics and vehicle dynamics. To fully utilize the spatial information of obstacles, we designed a vehicle model based on spatial kinematics, enabling the upper-layer MPC to plan collision avoidance trajectories based on distance sampling. To improve the accuracy and safety of trajectory tracking, we designed an 8-degree-of-freedom vehicle dynamic model. This allows the lower-layer MPC to consider lateral stability and roll stability during trajectory tracking. In collision avoidance trajectory tracking experiments using three scenarios, compared to two advanced time-based algorithms, the trajectories planned by the proposed algorithm in this paper exhibited predictability. The proposed algorithm can initiate collision avoidance at predetermined positions and can avoid collisions in predetermined directions, with all state variables within safe ranges. In terms of time efficiency, it also outperformed the comparative algorithms.

In this paper, a novel control architecture is proposed in which FMPC couples feedback from model predictive control with feedforward linearization. The proposed approach has the computational advantage of only requiring a convex quadratic program to be solved instead of a nonlinear program. Feedforward linearization aims to overcome the robustness issues of feedback linearization, which may be the result of parametric model uncertainty leading to inexact pole-zero cancellation. A DenseNet was trained to learn the inverse dynamics of the system, and it was used to adjust the desired path input for FMPC. Through experiments using quadcopter, we also demonstrated improved trajectory tracking performance compared to that of the PD, FMPC, and FMPC+DNN approaches. The root mean square (RMS) error was used to evaluate the performance of the above four methods. The results demonstrate that the proposed method is effective.

Deployable structures based on origami are widely used in the application of actuators. In this paper, we present a novel family of origami-based deployable structures with constant curvature. Two categories of non-flat-foldable and non-developable degree-4 vertices (NFND degree-4 vertices) are introduced. Pyramid structures are constructed based on the NFND degree-4 vertices. Doubly symmetric and singly symmetric spherical origami tubular cells (SOTCs) are established based on pyramid structures. To construct deployable origami modules using SOTCs, linking units are introduced. The mobility of the SOTCs and origami modules is analyzed using constraint screws. To realize the construction and simulation of deployable structures, kinematic and geometric analyses of the doubly symmetric and singly symmetric SOTCs are performed. Finally, we introduce four cases for deployable structures in spherical actuators based on the combination of multiple origami modules. These case studies demonstrate the potential of these deployable origami structures in the design of spherical actuators.

The exploration of Uranus, a key archetype for ice giant planets and a gateway to understanding distant exoplanets, is acquiring increasing interest in recent years, especially after the Uranus Orbiter and Probe (UOP) mission has been prioritized in the Planetary Science Decadal Survey 2023–2032. This paper presents the results of numerical simulations aimed at providing experimental constraints on the parameterized post-Newtonian (PPN) parameter γ, a measure of space–time curvature in general relativity (GR), during the cruise phase of a spacecraft travelling to Uranus. Leveraging advanced radio tracking systems akin to those aboard the JUICE and BepiColombo missions, we explore the potential of solar conjunction experiments (SCEs) to refine current measurements of γ by exploiting the spacecraft’s long journey in the outer Solar System. We discuss the anticipated enhancements over previous estimates, underscoring the prospect of detecting violations of GR. Our simulations predict that by using an advanced radio tracking system, it is possible to obtain an improvement in the estimation of γ up to more than an order of magnitude with respect to the latest measurement performed by the Cassini–Huygens mission in 2002, contingent on the calibration capabilities against solar plasma noise. The results reveal that a number of SCEs during the mission can substantially strengthen the validation of GR. In tandem with fundamental physics tests, the use of radio links during SCEs presents a valuable opportunity to dissect the solar corona’s plasma dynamics, contributing to solar physics and space weather forecasting. This paper also enumerates methodologies to analyze electron density, localize plasma features, and deduce solar wind velocity, enriching the scientific yield of the experiments beyond the primary objective of testing GR during the cruise phase of a mission to Uranus.

A novel distributed-vector-propulsion UAV (DVPUAV) is introduced in this paper, which has the capability of Vertical takeoff and landing (VTOL), and can realize relatively high-speed cruise. As the core of the DVPUAV, the propulsion wing designed under the guidance of the integration idea is not only a lifting body but also a propulsion device and a control mechanism. However, this kind of aircraft has a series of difficult problems with complex aero-propulsion coupling, flight modes switching, and so many inputs and control coupling. In order to describe this coupling effect to improve the accuracy of dynamics, an aero-propulsion coupling model is developed, considering both computation reliability and real-time. Afterward, a unique control framework is designed for the DVPUAV. By optimizing control logic, this control framework realizes the decoupling of longitudinal and lateral directional control and even the decoupling of roll and yaw control. Next, based on the Iterative linear quadratic regulator (ILQR), a new Model Predictive Control (MPC) controller with the ability to solve complex nonlinear problems is proposed which achieves the unification of the controller for the full flight envelope. Finally, the good performance of the control framework and controller is verified in the whole process of the flight simulation from take-off to landing.

Tilt-duct Unmanned Aerial Vehicles (UAV) combine the high-speed efficiency of fixed-wing aircrafts with vertical takeoff and landing (VTOL) and the hover capabilities of rotary-wing aircrafts while maximizing the advantages of ducted fans in terms of noise reduction, efficiency, and safety, making it a pivotal direction for the future of aviation such as urban air mobility. This paper concentrates on the design and optimization of the primary structures of a laboratory-designed reference tilt-duct UAV. Firstly, the general data of the reference tilt-duct UAV are presented. According to the load conditions, the overall structural layout design for the wing, fuselage, and empennage is carried out, where special attention has been paid to account for the requirements of VTOL/hover and cruise flight modes. Based on the structural layout, finite element models (FEM) are established and static analyses are performed. The results indicate that the design can fulfill the structural requirements during a flight mission. Furthermore, based on the Method of Feasible Directions (MFD) algorithm, we have carried out the optimization of the composite wing box that incorporates manufacturing constraints. Via optimization, the total mass of the wing box is reduced by 38.6%, i.e., from 3.73 kg to 2.29 kg. The results indicate that the combination of composite materials with a tilt-duct configuration holds significant potential for future high-efficiency and environmentally friendly aviation.

During the landing and taxiing process of aircraft, the frame-type landing gear (FTLG) usually generates large pitch vibrations under external excitation. Excessive vibration increases localized loads on the landing gear, which may lead to localized failure of the structure. To minimize this undesirable vibration, a passive oil–pneumatic pitch-stabilizing buffer (PSB) is designed in this paper to provide pitch damping. This paper applies the basic principles of dynamics to establish a dynamic model of FTLG considering the influence of PSB. And based on the design of experiments (DOE) method, by changing the filling parameters and structural parameters of PSB, the results of the changes of the frame vibration angle, angular velocity, and landing gear load are obtained, so as to analyze the effects of different parameters on the dynamic performance of the landing gear in the landing and taxiing process. The results demonstrate that increasing the oil damping coefficient of PSB and decreasing the installation angle of PSB on the main strut during the landing period resulted in less frame vibration and lower wheelset load ratios, but increased the landing overloads of landing gears. In the taxiing phase, increasing the PSB air spring stiffness can effectively reduce the frame vibration caused by the uneven road surface. The PSB structural parameters have little effect on the dynamic performance of FTLG.

A high-precision attitude control satellite uses an angular momentum exchange device such as a flywheel or a control moment gyro as the actuator for attitude stability control. Once the accumulation of angular momentum exceeds the upper limit of the angular momentum exchange device, the satellite will lose its attitude control ability. Therefore, it is necessary to unload the angular momentum exchange device to ensure the attitude control ability of the satellite platform. The angular momentum accumulation of GEO(Geosynchronous Orbit, GEO) satellites with asymmetric structure can reach 40 Nms per day, and the accumulation speed is more than 20 times that of GEO satellites with symmetrical structure. Therefore, it is necessary to carry out angular momentum unloading for GEO satellites with asymmetric structure every day. The previous method of angular momentum unloading using electric propulsion has weak unloading capacity, which is not suitable for angular momentum unloading of asymmetric satellites. This paper presents a method of angular momentum unloading using a four-joint mechanical arm plus an electric thruster. Large angular momentum unloading with near-zero burn-up can be achieved through the thrust generated by station keeping. In addition, the problem of attitude and orbit coupling control can be solved by controlling the thrust direction of the electric thruster with a mechanical arm.

The healthy operation of aircraft engines is crucial for flight safety, and accurate Remaining Useful Life prediction is one of the core technologies involved in aircraft engine prognosis and health management. In recent years, deep learning-based predictive methods within data-driven approaches have shown promising performance. However, for engines experiencing a single fault, such as a High-Pressure Compressor fault, existing deep learning-based predictive methods often face accuracy challenges due to the coupling relationship between different fault modes in the training dataset that includes a mixture of multiple fault modes. In this paper, we propose the FC-AMSLSTM method, a novel approach for Remaining Useful Life prediction specifically targeting High-Pressure Compressor degradation faults. The proposed method effectively addresses the limitations of previous approaches by fault classification and decoupling fault modes from multiple operating conditions using a decline index. Then, attention mechanisms and multi-scale convolutional neural networks are employed to extract spatiotemporal features. The long short-term memory network is then utilized to model RUL estimation. The experiments are conducted using the Commercial Modular Aero-Propulsion System Simulation dataset provided by NASA. The results demonstrate that compared to other prediction models, the FC-AMSLSTM method effectively reduces RUL prediction error for HPC degradation faults under multiple operating conditions.

In the research field of rotorcraft aerodynamics, there are two fundamental challenges: resolving the complex vortex structures in rotor wakes and representing the moving rotor blades in the ambient airflow. In this paper, we address the first challenge by utilizing a third-order unstructured finite volume solver, which exhibits lower numerical dissipation than its second-order counterpart. This allows for sufficient resolution of small vortex structures on relatively coarse meshes. With this flow solver, the second challenge is addressed by modeling each rotor as an actuator disk (i.e., the actuator disk model (ADM)) or modeling each blade as an actuator line (i.e., the actuator line model (ALM)). Both of the two models are equipped with an improved tip loss correction, which is introduced in detail in the methodology section. In the section of numerical experiments, the numerical convergence properties of the two types of solvers have been compared in the case of two-dimensional infinite wing. In addition, the relationship between the ALM and the lifting line theory is discussed in the cases of fixed-wing calculations. Another goal of these cases is to validate the tip loss correction presented. The validation of the ALM/ADM and comparisons of computational efficiency are also demonstrated in simulations involving both hover and forward flight rotors. It was found that the combination of the third-order finite volume solver and the ALM/ADM with the improved tip loss correction presents an efficient way of performing the aerodynamic analysis of rotor-induced downwash flow.

In this paper, an optimisation procedure is introduced that uses a significantly cheaper, and CFD-free, objective function for aerodynamic optimisation than conventional CFD-driven approaches. Despite the reduced computational cost, we show that this approach can still drive the optimisation scheme towards a design with a similar reduction in drag coefficient for wave drag-dominated problems. The approach used is ‘CFD-free’, i.e., it does not require any computational aerodynamic analysis. It can be applied to geometries discretised using meshes more conventionally used for ‘standard’ CFD-based optimisation approaches. The approach outlined in this paper makes use of the transonic area rule and its supersonic extension, exploiting a mesh-based parameterisation and mesh morphing methodology. The paper addresses the following question: ‘To what extent can an optimiser perform (wave) drag minimisation if using ‘area ruling’ alone as the objective (fitness) function measurement?’. A summary of the wave drag approximation in transonic and supersonic regimes is outlined along with the methodology for exploiting this theory on a typical CFD surface mesh to construct an objective function evaluation for a given geometry. The implementation is presented including notes on the considerations required to ensure stability, and error minimisation, of the numerical scheme. The paper concludes with the results from a number of (simple and complex geometry) examples of a drag-minimisation optimisation study and the results are compared with an approach using full-fidelity CFD simulation. The overall conclusions from this study suggest that the approach presented is capable of driving a geometry towards a similar shape to when using full-fidelity CFD at a significantly lower computational cost. However, it cannot account for any constraints, driven by other aerodynamic factors, that might be present within the problem.

Ice crystal icing occurs in jet engine compressors, which can severely degrade jet engine performance. In this paper, two different numerical calculation methods, the Eulerian method and the Lagrangian method, were used to evaluate the dynamics, mass transfer, heat transfer, phase transition and trajectory of ice crystals. Then, we studied the effects of initial diameter, initial sphericity, initial temperature of ice crystal, and relative humidity of airflow on the phase transition and collection characteristics of ice crystal particles. Results indicate that the non-spherical characteristics of ice crystals have a significant impact on their impingement limits and collection characteristics. The collection coefficient of unmelted ice crystals is positively correlated with the initial particle diameter and sphericity, and negatively correlated with the initial particle temperature and the relative humidity of airflow. The melting rate of ice crystal particles on the impact surface increases exponentially with the initial diameter of the particles, linearly increases with the relative humidity of the airflow and initial temperature of the particles, and exponentially decreases with the sphericity of the particles.

Many of the reports created at assembly lines, where all components of an aircraft are installed, frequently indicate that errors threaten safety. The proposed methodology in this study evaluates error prediction and risk mitigation to prevent failures and their consequences. The results linked to a typical electrical harness manufacture of a military aircraft estimated reductions of 93% in time and 90% in error during the creation of engineering manufacturing processes using AI techniques. However, traditional risk assessments methods struggle to identify and mitigate errors effectively. Thus, developing an advanced methodology to ensure systems safety is needed. This paper addresses how innovative AI technology solutions can overcome these challenges, mitigate error risks, and enhance safety in aerospace. Technologies, such as artificial intelligence, predictive algorithms, machine learning, and automation, can play a key role in enhancing safety. The aim of this study is to develop a model that considers the factors that can potentially contribute to error creation, through an artificial intelligence (AI) approach. The specific AI techniques used such as support vector machine, random forest, logistic regression, K-nearest neighbor, and XGBoost (Python 3.8.5) show good performance for use in error mitigation. We have compared the modeled values obtained in this study with the experimental ones. The results confirm that the best metrics are obtained by using support vector machine and logistic regression. The smallest deviation between the measured and modeled values for these AI methods do not exceed 5%. Furthermore, using advancements in machine learning methods can enhance error mitigation in aerospace. The use of AutoML can play a key role in automatically finding an appropriate model which provides the best performance metrics and therefore the most reliable forecast for data prediction and error mitigation.

Aggressive flight has become increasingly important for expanding the applications of quadrotors. The typical characteristic of large and rapid changes in commands poses stringent demands on the maneuverability of quadrotors. Ensuring flight stability alone is not enough; dynamic responses must also be selectively constrained, presenting quadcopter flight control with daunting challenges. The prescribed performance control (PPC) method is seen as having the potential to solve this problem by allowing for the constrained control of specified performance, leading to extensive research. However, its practical application still faces challenges, such as the system divergence caused by errors exceeding boundaries due to sudden command mutations. This paper presents a robust dynamic event-triggered PPC (DETPPC) method for an aggressive quadrotor flight. By assessing the direction and proximity of tracking errors approaching constraint boundaries, a dynamic event-triggered compensation mechanism for performance function boundaries is established to mitigate the divergence caused by error surpassing and to preserve preset control over the targeted metrics. Controllers were designed for both the translational and rotational subsystems of the quadrotor, and stability analysis was conducted based on Lyapunov functions. Simulation tests on agile trajectory tracking and abrupt attitude control were carried out, demonstrating the effectiveness of the proposed method.

In light of the satellite rejection environment and how aircraft can obtain high-precision positioning, this paper proposes a collaborative correction algorithm for aircraft based on the rank-defect network. Aiming at the problem of insufficient anchor points, which result in insufficient observations and the divergence of aircraft inertial navigation errors, this algorithm can effectively improve the navigation performance of cluster aircraft. On the basis of the observation information provided by the anchor aircraft, the observation information between aircraft is fully utilized to improve the observability of the aircraft cluster positioning method. At the same time, the pseudo-observation equation of heterogeneous aircraft cluster positioning is introduced, and the divergence of inertial navigation positioning errors caused by insufficient observations is suppressed by the pseudo-observation solution. On the basis of introducing the pseudo-observation equation, the inertial navigation error is solved and corrected by the Newton iterative method and the divergence of the inertial navigation position error is restrained. Compared with an aircraft cluster positioning method that does not use the inertial navigation error co-correction based on the pseudo-observation solution, this paper can achieve better overall cluster positioning accuracy when the available observations are insufficient, which is suitable for practical applications.

The aviation industry has proposed multiple solutions to reduce fuel consumption, air pollution, and noise at airports, one of which involves deploying electric trucks for aircraft towing between the stand and the runway. However, the introduction of tow trucks results in increased surface traffic, posing challenges from the perspective of air traffic controllers (ATCOs). Various solutions involving automated planning and execution have been proposed, but many are constrained by their inability to manage multiple active runways simultaneously, and their failure to account for the tow truck battery state of charge during assignments. This paper presents a novel system for taxi operations that employs autonomous tow trucks to enhance ground operations and address deficiencies in existing approaches. The system focuses on identifying conflict-free solutions that minimise taxi-related delays and route length while maximising the efficient use of the tow trucks. The algorithm operates at a strategic level and uses a centralised approach. It has the capacity to cater for multiple active runways and considers factors such as the tow truck battery state of charge and availability of charging stations. Furthermore, the proposed algorithm is capable of scheduling and routing tow trucks for aircraft taxiing without generating traffic conflicts.

Deployable and foldable tape-spring booms are widely used in aerospace technologies, especially for large-scale membrane structures. Semi-circular (STEM) and lenticular (CTM) boom cross-sections were invented for specific applications since these configurations have either a concise structure or a high twisting stiffness. Moreover, a triangular cross-section (TRAC) boom was proposed years ago, as its more scattered configuration could afford a higher bending stiffness after deployment. Meanwhile, blossoming is one of the most serious failure modes during boom deployment, and is commonly caused by a relatively high load acting on the boom tip. For the sake of avoiding blossoming failure, the highest load a boom can withstand should be found theoretically for a better design. This paper aims at acquiring the highest tip load (i.e., driving force) a TRAC boom can withstand through establishing an analytical model. Furthermore, a numerical analysis is carried out to provide some verification, whose modeling and analysis method has been verified by a comparison with the experimental data from previous investigations. The research in this paper gives more guidance for the design of deployable TRAC tape-spring booms.

This paper created a flight trajectory model of five uncrewed aerial vehicles (UAVs) in the geocentric coordinate system, provided the UAVs fly in the specified formation. Based on this model, equations for determining the position of a selected member of a group of UAVs were created, provided that the group communicates with each other in its telecommunications network. The simulation confirmed that if we know the exact coordinates of the four member UAVs of the group and their distances from the leader of the group, then the mean value of the error in determining its position in flight is equal to 0.044 m, and the variance is equal to 2.9 m2. We consider these errors to be methodological errors of the proposed method. Next, we checked how the error of determining the position of the group leader depends on the distance measurement errors between the individual UAVs and the group leader. The simulation confirmed that if errors in measuring the distance between individual UAVs and the group leader are from 0.01 m to 12.0 m, the mean values of group commander position determination errors range from 0.11 m to 34.6 m. The simulation result showed that to accurately determine the group commander’s position, the distance measurement errors between individual UAVs and the group commander must be less than 1.9 m. The research results showed that the telemetry method can be used to determine the position of individual members of the UAV group. The advantage of this method is that it does not require the reception of signals from satellite navigation systems, which can be interfered with under certain conditions. The disadvantage of the method is the need to synchronize the time bases of individual UAVs that communicate in the telecommunications network.

With reference to the trajectory-based operation (TBO) requirements proposed by the International Civil Aviation Organization (ICAO), this paper concentrates on the study of four-dimensional trajectory (4D Trajectory) prediction technology in busy terminal airspace, proposing a data-driven 4D trajectory prediction model. Initially, we propose a Spatial Gap Fill (Spat Fill) method to reconstruct each aircraft’s trajectory, resulting in a consistent time interval, noise-free, high-quality trajectory dataset. Subsequently, we design a hybrid neural network based on the seq2seq model, named Attention-TCN-GRU. This consists of an encoding section for extracting features from the data of historical trajectories, an attention module for obtaining the multilevel periodicity in the flight history trajectories, and a decoding section for recursively generating the predicted trajectory sequences, using the output of the coding part as the initial input. The proposed model can effectively capture long-term and short-term dependencies and repetitiveness between trajectories, enhancing the accuracy of 4D trajectory predictions. We utilize a real ADS-B trajectory dataset from the airspace of a busy terminal for validation. The experimental results indicate that the data-driven 4D trajectory prediction model introduced in this study achieves higher predictive accuracy, outperforming some of the current data-driven trajectory prediction methods.

To address the problem of low accuracy and efficiency in trajectory planning algorithms for interceptors facing multiple constraints during the midcourse guidance phase, an improved trajectory convex programming method based on the lateral distance domain is proposed. This algorithm can achieve fast trajectory planning, reduce the approximation error of the planned trajectory, and improve the accuracy of trajectory guidance. First, the concept of lateral distance domain is proposed, and the motion model of the midcourse guidance segment in the interceptor is converted from the time domain to the lateral distance domain. Second, the motion model and multiple constraints are convexly and discretely transformed, and the discrete trajectory convex model is established in the lateral distance domain. Third, the deep reinforcement learning algorithm is used to learn and train the initial solution of trajectory convex programming, and a high-quality initial solution trajectory is obtained. Finally, a dynamic adjustment method based on the distribution of approximate solution errors is designed to achieve efficient dynamic adjustment of grid points in iterative solving. The simulation experiments show that the improved trajectory convex programming algorithm proposed in this paper not only improves the accuracy and efficiency of the algorithm but also has good optimization performance.

Periodic orbit families around asteroids serve as potential trajectories for space probes, mining facilities, and deep space stations. Bifurcations of these families provide additional candidate orbits for efficient trajectory design around asteroids. While various bifurcations of periodic orbit families around asteroids have been extensively studied, period-multiplying bifurcations have received less attention. This paper focuses on studying period-multiplying bifurcations of periodic orbit families around asteroids. In particular, orbits with periods of approximately 7 and 17 times that of the rotational period of asteroid 216 Kleopatra were computed. The computation of high-period orbits provides insights into the numerical aspects of simulating long-duration trajectories around asteroids. The previous literature uses single-shooting and multiple-shooting methods to compute bifurcations of periodic orbit families around asteroids. Computational difficulties were encountered while using the shooting methods to obtain period-multiplying bifurcations of periodic orbit families around asteroids. This work used the Legendre–Gauss collocation method to compute period-multiplying bifurcations around asteroids. This study recommends the use of collocation methods to obtain long-duration orbits around asteroids when computational difficulties are encountered while using shooting methods.

Superconducting electric motors are required in order to deliver lower-carbon aviation. Critical to the success and viability of operating superconducting electric motors in aviation is keeping the superconducting coils at their operating temperature. This paper examines the challenges of keeping a superconducting motor cold if it were used on a single aisle passenger aircraft such as an Airbus A320. The cooling problem is defined and different cooling scenarios are investigated to determine viability. The investigation has shown that for a motor with a superconducting rotor only (copper stator), a Stirling-type cryocooler would be sufficient. However, if the motor is to be fully superconducting, then the cooling loads of the stator, which are much higher, make mechanical refrigeration impractical and the only option is to cool the motor with the heat sink of a liquid hydrogen fuel.

As the only flying mammal in nature, bats have superb flight skills and aerodynamic characteristics that have been the subject of research by scholars from all over the world. In recent years, the research on bionic flapping-wing aircraft has made good progress. However, such research mostly uses birds or insects as the research objects, and there are few studies on bat-imitating flapping-wing aircraft. This paper combines the characteristics of bats’ flexible wings to model and analyze the aerodynamic theory and parameters of the flexible wings of bat-like flapping aircraft. The longitudinal dynamic and kinematic model design of bat-like flapping aircraft is based on the pitch angle of LQR. In terms of height control, the controller uses energy control methods to complete the closed-loop longitudinal channel control of the bat-like flapping aircraft. Finally, this study performed the simulation and flight experimentation of the designed bat-like flapping aircraft, demonstrating the correctness of this system.

The high clearance spray is a type of large and efficient agricultural machinery used for plant protection, and path tracking control is the key to ensure the efficient and safe operation of spray. Sliding mode control and other methods are commonly used abroad to track vehicles, while fuzzy control, neural networks and other methods are commonly used at home. However, domestic and foreign research on autonomous agricultural machinery is mainly focused on tractors and other machinery, while research on self-propelled spray in high clearance is less abundant. This paper takes the path tracking algorithm in the integrated navigation system of spray as the main research goal, studies the path tracking control algorithm for straight lines and turning curves that can realize the automatic driving of spray by establishing the path tracking algorithm for unmanned spray based on dual control strategies, designs the path tracking controller, including the preview model theoretical path tracking controller and variable domain fuzzy controller, and determines the preview model through the design of the preview model theoretical path tracking controller. The lateral and longitudinal errors of the model algorithm are analyzed, and the driving characteristics under the complex spray road surface are analyzed. The design of the variable domain fuzzy predictor theory path tracking controller is proposed, and the design of the road model selection controller is calculated and analyzed in detail, including the determination of the road roughness coefficient and the selection of the range of the difference between the average value of the excitation before and after sampling, which improves the performance of the spray path tracking algorithm. The experiment shows that the proposed path tracking control algorithm can meet the path tracking requirements of unmanned spray in the current road environment, and provide a reliable solution for the automatic control of high clearance spray.

The proper fallowing of soil maintains or even improves its yield potential. The aim of this research was to compare five methods of soil protection with high production potential on the yield and quality of strategic plants. The tested methods consisted of five variants: bare fallow—BF; natural fallow—NF; fodder galega (Galega orientalis Lam.)—FG; a mixture of fodder galega (Galega orientalis Lam.) with smooth brome (Bromus inermis)—FG+SB; and smooth brome (Bromus inermis)—SB. The soil had been set aside for 9 years, after which time the fallows were terminated and the fields were cropped with winter oilseed rape, winter wheat, and spring wheat in three consecutive years. After the end of fallowing, the content of Nog. and Ctot., pH, and forms of available macro- and microelements in the soil were determined. The influence of each type of fallow on the yield of seeds/grain, straw, total protein, crude fat, and the content of macronutrients in the seeds/grain and straw of the grown crops was determined. Regarding the yields of the crops, the best solution was long-term soil protection via sowing fodder galega or a mixture of fodder galega and smooth brome. A field previously maintained as a fallow with these plants (singly or in combination) could produce over twice-as-high yields of wheat and oilseed rape as those harvested from a field established on bare fallow. The yields of the cereals and oilseed rape obtained in this study prove that food security and environmental protection issues can be reconciled. The methods for protecting farmland temporarily excluded from agricultural production presented in this paper correspond perfectly to the framework of the Green Deal for Europe. Arable land excluded from cultivation can be used to overcome new challenges facing modern agriculture.