Aerospace Systems最新文献

The paper presents three-body interception simulation model, to study the survivability of airborne target against an interceptor, by launching a repeater-type countermeasure system termed as deceiver. State space representation of interceptor, target dynamic states along with autopilot, RF seeker is developed for three-dimensional engagement scenario. The trajectory of deceiver released from target is presented by propagating the discrete-state translational equations of motion. Classical proportional navigation guidance steers the interceptor towards the airborne moving target (or deceiver) based on the echo power received computed using Friis transmission formula. Effective jamming capability of deceiver on interceptor at different seeker acquisition ranges is indicated by ratio of power received from deceiver and target known as jammer-to-signal ratio. Numerical simulations are conducted to study the survivability chances of platform, when the deceiver is deployed from the target aircraft with interceptor approaching from side, head-end, tail-end, top. Miss distances of interceptor from platform and deceiver, interceptor lateral acceleration limits are presented. Monte carlo simulation studies are performed, and probability of platform survival when deceiver is released at different homing ranges of interceptor, as well as for deceiver amplifier gain variations are presented. This study also provides important system design parameters such as deceiver operation time to decide the battery specifications for electronics, and subsequently the overall system design.

In this paper, a series of low-Reynolds number airfoils were explored in application to the Long-Endurance Mars Exploration Flying Vehicle (LEMFEV) project. The end goal of the study was twofold:

• to identify the most effective airfoil or airfoil-boundary layer trip combination for the given aircraft in cruise and unveil the underlying physical mechanism for this effectiveness;

• to determine if the operating range of angles of attack for the selected airfoil could be expanded by placing the boundary layer trips in a relatively aft position such that they affected the boundary layer at a higher angle of attack.

The paper presented two sample specifications for the LEMFEV project; discussed the effect of turbulence on the performance of airfoils under the given conditions; justified the selection of an amplification factor for simulations; developed and justified the measure of merit for airfoil selection and optimization; as well as considered boundary layer trips as a means of enhancing the performance of the selected airfoil. For design and analysis, MATLAB and X-FOIL were used. The analysis showed that for the given design conditions, both considered sample mission profiles were performed better by an airplane with the SD7037-092-88 airfoil. Furthermore, for this airfoil and design conditions, boundary layer trips would only increase drag at lift coefficients where they forced transition, and the boundary layer trips didn’t expand the airfoil's operating range of angles of attack. In other words, eliminating the bubble had a detrimental effect on the lift-to-drag ratio of the airfoil. The friction drag increase due to early transition by far outweighed the pressure drag produced by the laminar bubble.

The need for revolutionary techniques to augment aerodynamic efficiency is paramount for achieving substantial reductions in drag and consequent fuel consumption. This paper revolves around exploiting zinc oxide nanostructures to increase boundary layer adhesion and delay stall in airfoils. Zinc oxide nanostructures are employed to induce vortices, re-energize the airflow and function as nano flow control device. The work on this paper commenced with the proof of concept by means of comprehensive computational simulation utilizing COMSOL software and ended with experimental lab tests. A meticulous two-step process involving the sol–gel method and dip coating was employed to grow nanorods on the wing’s surface. Initial prototyping utilized 3D printing, and subsequent aluminum samples were produced using sand casting techniques. The coated wing specimen underwent rigorous wind tunnel testing to assess its aerodynamic performance under controlled airflow conditions. This thorough approach facilitated a profound understanding of the coated wing's behavior, enabling insights for further optimization. The results revealed a significant 16% delay in stall and an average 4% reduction in drag. This pioneering approach not only optimizes aircraft aerodynamics but also mitigates fuel costs and environmental impact. Moreover, the study's observations offer avenues for future exploration, including the fine-tuning of coating parameters and exploring diverse applications of ZnO nanorods in aerospace engineering.

Tight formation flight, as a significant way for fixed-wing unmanned aerial vehicle (UAV) to execute missions, generates synergistic aerodynamic effects that significantly influence the motion decision-making and control of UAVs. In aerial refueling missions, this is manifested as complex aerodynamic effects such as vortices affecting the path planning of the refueling UAV. This paper proposes a path-planning method for fixed-wing UAVs to conduct aerial refueling under the constraints of synergistic aerodynamics. Firstly, an environment constraint model for vortex distribution is obtained from aerodynamic experimental data of the refueling formation. Subsequently, by utilizing the differential flatness property of fixed-wing UAVs, the nonlinear system states and control variables are mapped to linear functions of flat outputs. This allows the establishment of segment constraints for the path, enabling the use of a key-point heuristic algorithm in the flat output space to generate the aerial refueling flight path. Furthermore, a flat output minimum snap algorithm is applied for multi-constraint optimization of the flight path, resulting in a smooth and feasible optimal path. Simulation experiments demonstrate the effectiveness and advancement of the proposed path-planning method under the influence of vortices.

A numerical analysis has been conducted to study the role of hindfoil initial pitch angle on aerodynamic performance of dragonfly hovering flight. The inclined oscillation of two elliptic airfoils with tandem arrangment at (:Re=157) is analysed using 2D numerical simulation. The pitch amplitude ((:{alpha:}_{m})) is kept constant for both foils and hindfoil initial pitch angle ((:{alpha:}_{{o}_{h}})) is varied from (:{15}^{o}) to (:{75}^{o}) for three different phase oscillations: (:varphi:=:{0}^{o}), (:{90}^{o}) and (:{180}^{o}). The results indicate, for (:{alpha:}_{{o}_{h}}) < (:{45}^{o}), the lower (:{alpha:}_{{o}_{h}}) reduces total lift for all phase differences. It occurs due to the detrimental wake capture and downward dipole jet encountered by hindfoil during downstroke, resulting in less hindfoil (:stackrel{-}{{C}_{V}}). However, for (:{alpha:}_{{o}_{h}}) > (:{45}^{o}), lift enhancement of up to (:46:%) is observed with increase in (:{alpha:}_{{o}_{h}}) during (:varphi:=:{180}^{o}). Also, the higher thrust is obtained during lower (:{alpha:}_{{o}_{h}}) and it reduces with increase in (:{alpha:}_{{o}_{h}}).

The paper examines computational schemes for calculating the gradient of fluid dynamic quantities using grids of various types. The Green–Gauss method and the least squares method (LSM) used to develop a hybrid gradient calculation scheme are considered. It is demonstrated that the accuracy of gradient calculations may vary depending on the geometry of the control volume: the Green–Gauss method exhibits lower errors for strongly elongated thin cells and cells with curved edges, while for cells with orthogonal edges, it is preferable to use LSM. In order to improve the accuracy of calculations on unstructured grids, a hybrid gradient calculation scheme is proposed. This scheme computes the gradient by summing values derived from both the Green–Gauss method and LSM, given the weight function that incorporates the geometry of the control volume. The paper presents a formula for the weight function, which determines the contribution of each method within the hybrid scheme. The developed scheme is applied to the problem of supersonic flow around a cylinder with a needle on two unstructured grids, namely truncated hexagons and tetrahedra. It is shown that the proposed hybrid scheme reduces the error in calculating the aerodynamic characteristics of a streamlined object.

Space exploration demands robust spacecraft(SC) subsystems to endure the harsh conditions of space and ensure mission success. Attitude determination and control subsystems (ADCS), as a significant subsystem within SC, are essential for providing the necessary pointing accuracy and stability, and failures in the ADCS can lead to mission failure. Therefore, robust design, thorough testing, and Fault Detection, Isolation and Identification(FDII) techniques are crucial for spacecraft operations. This paper focuses on developing advanced FDII techniques for reaction wheels(RW) within ADCS, evaluating the Prony-based FDII technique for RW, considering its accuracy, time complexity, and memory usage, and Additionally, it introduces new machine learning-based FDII techniques, including enhancements to the Prony-based FDII technique, to manage single faults more effectively. The new proposed techniques used to explore the novel area of multiple faults within the same subsystem. Results indicate that the proposed FDII techniques significantly improve fault detection accuracy, isolation time, and memory efficiency compared to traditional techniques. These advancements enhance the reliability and longevity of spacecraft missions, ensuring that critical subsystems like ADCS operate effectively in the challenging conditions of space. The contributions presented in the paper are introducing three different FDII machine learning-based techniques that support identifying five types of single faults in spacecraft ADCS RW, outperform the Prony-based FDII technique for spacecraft ADCS RW in terms of time and memory complexity, and Finally, improves the fault tolerance of the spacecraft system by detecting Multiple fault combinations that may occur at the same time in one system.

A comprehensive simulation model is established to design the altitude adjustment of the stratospheric airship with the application of the adjustable ballonets for pitch control. A series of mathematical models, including atmosphere, thermal, dynamics and kinematics, airship pressure and pitch control, are developed to achieve the altitude adjustment when the stratospheric airship flying at the stationary phase. The altitude adjustment strategy takes the thermodynamics, dynamics, and pressure control requirements together into consideration, to better fulfill the realistic flight conditions. Based on these models, the characteristics of stratospheric airship’s flight performance are simulated and discussed in detail. The results show that taking adjustable ballonets as the actuator can realize the pitch and pressure control simultaneously and satisfy the requirements of the flight missions. Furthermore, stratospheric airship can achieve altitude adjustment with the application of adjustable ballonets and propulsion system coordinately. Moreover, the simulation model can accurately present the interaction of thermodynamics, pressure, and dynamics, which better satisfies the realistic flight situation. The results and conclusions presented herein contribute to the design and operation of stratospheric airship.

Trajectory prediction (TP) of ballistic missile (BM) is a critical task in the field of military and defense security. However, influenced by various external factors, including target maneuverability, interference, and atmospheric conditions, BMs encounter complex forces during the boost flight phase, making their trajectories complex and variable. Furthermore, the conventional numerical integration and polynomial fitting TP methods are highly dependent on fixed motion models and precise initial observations, so they tend to engender error accumulation and inaccurate predictions. Thus, in terms of this issue, this paper proposed a TP method based on adaptive tracking and Gaussian Process Regression (GPR) to achieve stability in short-term TP for boost phase BM. Specifically, a database of trajectories for boost phase BM is created and used for training GPR predictive models, in which the unknown noise's covariance matrix is dynamically adjusted according to the statistical characteristics of observations to provide more precise trajectory data for model training. At the same time, incremental learning is adopted to add tracking results from real-time tests to improve further and update the predictive model. Additionally, the output uncertainty of GPR is also beneficial for decision-making systems usually making decisions in accordance with the uncertainty. Simulation results based on the GEO dual-satellite positioning system show that the absolute average TP RMSE of the boost phase BM of our proposed method can be less than 0.35 km, 0.51 km, and 0.62 km in future 20 s, 40 s, and 60 s, which outperforms those of the numerical integration method of 2.1 km, 3.7 km, and 6.9 km and the function approximation method of 0.89 km, 3.1 km, and 6.1 km. This paper provides a significant reference for the positioning, tracking, and prediction of BM in boost phase.

In this paper, adaptive optimizer-based deep neural network approaches are used to predict nonlinear aerodynamic model using flight test data of standard aircraft. Adaptive optimizers namely Adam and RMSprop algorithms are chosen to model the force and moment coefficients during steady stall phenomena. The effectiveness of these two methods are being investigated and validated. The estimated results from adaptive optimizer based methods are statistically analysed and compared with the conventionally used maximum likelihood method. Comparison results from the above methods are found to be relatively better than the maximum likelihood estimates in terms of RMSE and correlation. Moreover, the adaptive optimization methods are proven to be advantageous over conventionally used methods which strongly depend on solving equations of motion.