In recent years, there has been an increasing interest in the research and development of hybrid airships for various applications. Airship design involves multiple design parameters from various disciplines that interact mutually. Existing design methodologies, however, are often limited to fixed shapes and geometry. This paper provides a comprehensive parametric design approach for the sizing of multi-lobed hybrid air vehicles for low- and high-altitude applications. The proposed design techniques are robust so that the designer has the freedom to change the number of lobes, the relative location of lobes, the envelope profile, and the optimiser for the design optimisation process. The outcomes of the proposed methodology are envelope volume, wetted surface area, length and span of the envelope, sizing and layout of the solar array, and sizing and layout of the fins. The modeling techniques highlighted in this paper are very efficient for the design and optimisation of multi-lobed airships in the conceptual design phase with a large design exploration space. The robustness of the shape generation algorithms is tested on some of the standard envelope profiles of airships. The effect of the shape and geometry of the multi-lobed envelope on added mass is demonstrated through the added mass estimation using Boundary Element Method.

A sliding mode corrector is presented for disturbance rejection in position sensing using relatively accurate velocity measurement. The corrector design is based on a robust second-order sliding mode (2-sliding mode), which makes the fusion of position and velocity on a sliding surface to reject disturbance. Even when the frequency bands of disturbance and actual position signal overlap, or large-magnitude disturbance exists, the corrector can still provide the accurate and smoothed estimate of position. The proposed corrector is applied to a jet UAV navigation and control. In the unmanned aerial vehicle (UAV) system, the disturbances exist in position and attitude measurements, and the uncertainties exist in the system dynamics. For the UAV trajectory tracking control, the system model is constructed in the earth-fixed frame, and the constructed model is fit for observer design to estimate system uncertainties. The control laws are designed according to the correction of position and attitude by the correctors and the estimation of system uncertainties by an existing observer. Finally, the flight experiment demonstrates the effectiveness of the proposed method.

To enhance the performance of anti-ship missiles cooperative attack, this paper proposes a finite-time trajectory shaping-based cooperative guidance law (TSCGL). Firstly, the cooperative guidance model is established on segmented linearisation of the missile’s heading angle. Then, a trajectory shaping guidance law for a single missile is derived by a weighted optimal energy cost function and Schwarz inequality. On this basis, a finite-time TSCGL is proposed combined with trajectory shaping technology and finite-time theory. The desirable finite-time convergence performance can ensure a simultaneous attack. Through an improved method of time-to-go estimation, it is independent of small-angle assumption and relaxes the launching conditions of the missiles. Additionally, the proposed finite-time TSCGL can achieve better damage performance through energy management. Finally, simulation results demonstrate the effectiveness and superiority of the proposed finite-time TSCGL.

This paper proposes a methodology to define and quantify the precision uncertainties in aerothermodynamic cycle model comparisons. The total uncertainty depends on biases and random errors commonly found in such comparisons. These biases and random errors are classified and discussed based on observations found in the literature. The biases account for effects such as differences in model inputs, the configurations being simulated, and thermodynamic packages. Random errors consider the effects on the physics modeling and numerical methods used in cycle models. The methodology is applied to a comparison of two cycle models, designated as the model subject to comparison and reference model, respectively. The former is the so-called Aerothermodynamic Generic Cycle Model developed in-house at the Laboratory of Applied Research in Active Control, Avionics and AeroServoElasticity (LARCASE); the latter is an equivalent model programmed in the Numerical Propulsion System Simulation (NPSS). The proposed methodology is intended to quantify the bias and random errors effects on different cycle parameters of interest, such as thrust, specific fuel consumption, among others. Each bias and random errors are determined by deliberately preventing the effects from other biases and random errors. The methodology presented in this paper can be extended to other cycle model comparisons. Moreover, the uncertainty figures derived in this work are recommended to be used in other model comparisons when no better reference is available.

The objective of this research is to predict the delays in the departure of scheduled commercial flights through a methodology that uses predictive tools based on machine learning/deep learning (ML/DL), with supervised training in regression, based on the available flight datasets. Since the novel contribution of this work is, first, to make the comparison of the predictions in terms of means and statistical variance of the different ML/DL models implemented and, second, to determine the coefficients of the importance of the features or flight attributes, using ML methods known as permutation importance, it is possible to rank the importance of flight attributes by their influence in determining the delay time and reduce the problem of selecting the most important flight attributes. From the results obtained, it is worth mentioning that the model that presents the best performance is the ensemble or combinatorial method of random forest regressor models, with an acceptable prediction range (measured with the root-mean-square-error).

In this paper, an adaptive neural output-constrained control algorithm is proposed for a class of non-affine kinetic kill vehicle (KKV) systems. The key point is that the non-affine control law can be designed and the output of the KKV system conform to the output limit with the aid of the proposed method. Due to the aerodynamic moments, the actual control torque is non-affine, which can be addressed by introducing an integral process to the design of the controller. Besides, in order to improve the control precision, a nonlinear mapping is put forward so that the output constraint can be transformed to the constraint of the introduced dynamic signal that can be simply achieved. From the simulation results it can be concluded that the states of the KKV system can track the desired trajectories in spite of different working conditions and the control precision is higher compared with other control methods.

This paper aims to present a vertical take-off and landing unmanned aerial vehicle (VTOL UAV) configuration and numerically simulate its flight transition from hover to cruise and from cruise to hover. It can tilt the canard and wing along with two attached propellers. Additionally, two fixed front propellers are pointing upwards. Multi-body equations of motion are derived for this concept of aircraft, which are used to compute the flight transition trajectory from hover to cruise configuration. Furthermore, a transition control algorithm based on gain scheduling is described, which stabilises the aircraft while it accelerates from hover to cruise, gradually tilting the wing along with its propellers, sequentially switching between equilibrium states, as the stability cost functions thresholds are reached. The transition control algorithm of the conceptual aircraft model is numerically simulated.

In this study, fretting wear in riveted lap joints of aluminium alloy plates was investigated. For the fretting test, 6061-T6 aluminium alloy plates, which are widely used in aircraft construction, and blind rivets were used. Experiments were carried out using a computer controlled Instron testing machine. Fretting surface roughness, microhardness was investigated by metallographic techniques and scanning electron microscopy.

Tensile load cycles in the riveted lap joint were found to cause damage to all surfaces. Two contact surfaces where friction occurs were investigated. The contact surface of the lower plate with the upper plate, and the contact surface of the lower plate with the rivet head. As load and cycles increased, fretting scars and surface roughness increased.

Consequently, it has been determined that fretting damages occur between the contact surface of the plates and between the plate and the rivet contact surface.

A high-load counter-rotating compressor is optimised based on the method of coupling aerodynamic optimisation technology and computational fluid dynamics, and the flow structures in the passage are analysed and evaluated by vorticity dynamics diagnosis. The results show that the aerodynamic performance of optimised compressor are obviously improved at both design point and off-design point. By comparing the distribution characteristics of vorticity dynamics parameters on the blade surface before and after the optimisation, it is found that BVF (boundary vorticity flux) and circumferential vorticity can effectively capture high flow loss regions such as shock waves and secondary flow in the passage. In addition, the BEF (Boundary enstrophy flux) diagnosis method based on the theory of boundary enstrophy flux is developed, which expands the application scenario of the boundary vorticity dynamics diagnosis method. The change of vorticity dynamics parameters shows blade geometric parameters’ influence on the passage’s viscous flow field, which provides a theoretical basis for the aerodynamic optimisation design.