Typically, the fuselage of a modern military aircraft is designed in such a way that the propulsion system is integrated into it. The main reasons are reduction of installation space and minimisation of radar signature. Those requirements can be achieved by using highly bent engine intakes, which are occluding a direct line of sight to the compressor system. Depending on their design, secondary flows and flow separation can be expected due to the strong curvature of the intake system. In this study, a serpentine intake in front of the Larzac 04 test engine is investigated experimentally and its performance compared with and without flow stabilising measures. In detail, a configuration with vortex generators was compared experimentally with a configuration of active flow control by injected air. In order to analyse and compare the efficiency of both systems, the dimensionless total pressure coefficient, the distortion coefficient (DC60) and detailed surface pressure distributions as well as the aerodynamic interface plane are evaluated. In addition, different throttle lines were recorded for surge line evaluation of the low pressure compressor of the Larzac engine and compared for each flow-stabilising measure investigated. It was found that the application of injecting air showed a larger improvement in surge margin and reduction in distortion coefficients compared to the passive flow control.

This study investigates the influence of release timing on the trajectory of internal store separation through numerical solutions of continuity, momentum, energy equations and six degrees of freedom equations in a coupled manner. The internal store separation process in advanced fighter aircraft is analysed using computational fluid dynamics (CFD) and six degrees of freedom equations of motion. Initially, the equations of motion are validated by reenacting the Eglin Air Force Base study, an external store separation example with documented experimental results. Subsequently, validation is extended to the M219 cavity problem. In the internal store separation analysis, a cavity with an L/D ratio of 5, a freestream velocity of 0.85 Mach, and a generic store are utilised. Detached eddy simulation (DES) is applied using both static and dynamic mesh techniques in all numerical solutions. The generic store, positioned within a clean cavity with a 90-degree flap angle, was released at two distinct times, corresponding to the points of maximum and minimum gravitational forces. Interestingly, the results show that releasing the store when the normal force acting on it is at its maximum does not necessarily provide an optimal separation. Specifically, when the force coefficient was at its maximum (0.14), the store collided with the cavity door flap after 0.171465 seconds. In contrast, when the force coefficient was at its minimum (-0.04), the store contacted the cavity door after 0.170295 seconds at the same location. Despite the differences in force magnitudes, the trajectories were nearly identical, suggesting that the timing of the release may not have a significant effect on preventing collision. This further emphasises the need for flow control methods to ensure safe and effective store separation.

In this paper, we designa robust Successive Generalised Dynamic Inversion (SGDI) flight control system for high-performance trajectory tracking of target sun-synchronous orbit Satellite Launch Vehicles (SLVs). The robust SGDI control system is designed to track an optimal reference trajectory such that the desired orbital terminal conditions of the ascent flight phase are achieved. The proposed SGDI is composed of two loops. The attitude control loop employs Dynamically Scaled Generalised Inversion (DSGI) of Servo Constraint Dynamics (SVD) in the deviations of Euler attitude angles from their desired optimal trajectories. The inner-dynamics control loop employs DSGI of an SVD in the SLV angular velocity components. Robustification control elements are augmented within the two loops of the baseline SGDI control system to overcome control performance degradation due to dynamic scaling of the Moore-Penrose generalised inverse, modeling and parametric uncertainties, and exogenous disturbances. The robust SGDI control system works to enforce global convergence of the SLV attitude trajectories to the reference trajectories. The high-performance attributes of the robust SGDI control system are verified via comparisons with a classical sliding mode control system, and by performing numerous runs of Monte Carlo simulations under various types of uncertainties and external wind disturbances.

As avionics systems become increasingly complex, traditional fault prediction methods are no longer sufficient to meet modern demands. This paper introduces four advanced fault prediction methods for avionics components, utilising a multi-step prediction strategy combined with a stacking regressor. By selecting various standard regression models as base regressors, these base regressors are first trained on the original data, and their predictions are subsequently used as input features for training a meta-regressor. Additionally, the Tree-structured Parzen Estimator (TPE) algorithm is employed for hyperparameter optimisation. The experimental results demonstrate that the proposed stacking regression methods exhibit superior accuracy in fault prediction compared to traditional single-model approaches.

The challenging tracking control issue for a space manipulator subject to parametric uncertainty and unknown disturbance is addressed in this paper. An observer-based fixed-time terminal sliding mode control methodology is put forward. Firstly, a nonlinear disturbance observer is introduced for exactly reconstructing the lumped uncertainty without requiring any prior knowledge of the lumped uncertainty. Meanwhile, the estimation time’s upper bound is not only irrelevant to the initial estimation error but can be directly predicted in advance via a specific parameter in the observer. Invoking the estimated information, a fast fixed-time tracking controller with strong robustness is designed, where a novel sliding mode surface incorporated enables faster convergence. The globally fixed-time stability of the closed-loop tracking system is rigorously demonstrated through Lyapunov stability analysis. Finally, numerical simulations and comparisons verify the validity and superiority of the suggested controller.

To meet the development needs of aeroengines for high thrust-to-weight ratios and fuel-air ratios, a high temperature rise triple-swirler main combustor was designed with a total fuel-air ratio of 0.037, utilising advanced technologies including staged combustion, multi-point injection and multi-inclined hole cooling. Fluent software was used to conduct numerical simulations under both takeoff and idle conditions, thereby obtaining the distribution characteristics of the velocity and temperature fields within the combustor, as well as the generation of pollutants. The simulation results indicate that under takeoff conditions, the high temperature rise triple-swirler combustor achieves a total pressure loss coefficient of less than 6% and a combustion efficiency exceeding 99%. Under takeoff conditions, the OTDF and RTDF values are 0.144 and 0.0738, respectively. The mole fraction of NOx emissions is 3,700ppm, while the mole fraction of soot emissions is 2.55×10−5ppm. Under idle conditions, the triple-swirler combustor maintains a total pressure loss coefficient of less than 6% and a combustion efficiency greater than 99.9%. The OTDF and RTDF values are 0.131 and 0.0624, respectively. The mole fractions of CO and UHC emissions are both 0×10−32ppm at the calculation limit of Fluent software.

A distributed cooperative guidance law without numerical singularities is proposed for the simultaneous attack a stationary target by multiple vehicles with field-of-view constraints. Firstly, the vehicle engagement motion model is transformed into a multi-agent model. Then, based on the state-constrained consensus protocol, a coordination control law with field-of-view (FOV) constraints is proposed. Finally, the cooperative guidance law has been improved to make it more suitable for practical application. Numerical simulations verified the effectiveness and robustness of the proposed guidance law in the presence of acceleration saturation, communication delays and measurement noise.

This paper develops a novel full-state-constrained intelligent adaptive control (FIAC) scheme for a class of uncertain nonlinear systems under full state constraints, unmodeled dynamics and external disturbances. The key point of the proposed scheme is to appropriately suppress and compensate for unmodeled dynamics that are coupled with other states of the system under the conditions of various disturbances and full state constraints. Firstly, to guarantee that the time-varying asymmetric full state constraints are obeyed, a simple and valid nonlinear error transformation method has been proposed, which can simplify the constrained control problem of the system states into a bounded control problem of the transformed states. Secondly, considering the coupling relationship between the unmodeled dynamics and other states of the controlled system such as system states and control inputs, a decoupling approach for coupling uncertainties is introduced. Thereafter, owing to the employed dynamic signal and bias radial basis function neural network (BIAS-RBFNN) improved on traditional RBFNN, the adverse effects of unmodeled dynamics on the controlled system can be suppressed appropriately. Furthermore, the matched and mismatched disturbances are reasonably estimated and circumvented by a mathematical inequality and a disturbance observer, respectively. Finally, numerical simulations are provided to demonstrate the effectiveness of the proposed FIAC strategy.

In order to improve the performance of $k - \omega $ SST model in turbomachinery, previous studies have used the machine-learning (ML) technique to obtain turbulence models (for example, the ML-RANS EQ model). However, these models do not lead to satisfactory results in complex flows in turbomachinery. In this study, we use non-equilibrium training dataset to obtain a new turbulence model (i.e., the ML-RANS TR-NE-EQ model). Calculations in various cases of turbine cascade flows show that ML-RANS TR-NE-EQ model performs obviously better than ML-RANS EQ model as well as $k - \omega $ SST model.

The axisymmetric nozzle mechanism is the core part for thrust vectoring of aero engine, which contains complex rigid-flexible coupled multibody system with joints clearance and significantly reduces the efficiency in modeling and calculation, therefore the kinematics and dynamics analysis of axisymmetric vectoring nozzle mechanism based on deep neural network is proposed. The deep neural network model of the axisymmetric vector nozzle is established according to the limited training data from the physical dynamic model and then used to predict the kinematics and dynamics response of the axisymmetric vector nozzle. This study analyses the effects of joint clearance on the kinematics and dynamics of the axisymmetric vector nozzle mechanism by a data-driven model. It is found that the angular acceleration of the expanding blade and the driving force are mostly affected by joint clearance followed by the angle, angular velocity and position of the expanding blade. Larger joint clearance results in more pronounced fluctuations of the dynamic response of the mechanism, which is due to the greater relative velocity and contact force between the bushing and the pin. Since axisymmetric vector nozzles are highly complex nonlinear systems, traditional numerical methods of dynamics are extremely time-consuming. Our work indicates that the data-driven approach greatly reduces the computational cost while maintaining accuracy, and can be used for rapid evaluation and iterative computation of complex multibody dynamics of engine nozzle mechanism.