Aerospace Systems最新文献

The focus of this research is the creation of a deep reinforcement learning approach to tackle the challenging task of robotic gripping through tactile sensor data feedback. Leveraging deep reinforcement learning, we have sidestepped the necessity to design features manually, which simplifies the issue and allows the robot to acquire gripping strategies via trial-and-error learning. Our technique utilizes an off-policy reinforcement learning model, integrating deep deterministic policy gradient structure and twin delayed attributes to facilitate maximum precision in gripping floating items. We have formulated a comprehensive reward function to provide the agent with precise, insightful feedback to facilitate the learning of the gripping task. The training of our model was executed solely in a simulated environment using the PyBullet framework and did not require demonstrations or pre-existing knowledge of the task. We examined a gripping task with a 3-finger Robotiq gripper for a case study, where the gripper had to approach a floating object, pursue it, and eventually grip it. This training methodology in a simulated setting allowed us to experiment with various scenarios and conditions, thereby enabling the agent to develop a resilient and adaptable grip policy.

The position accuracy of GNSS is limited by several errors including multipath error. The multipath error is well known as one of the dominant error sources in most of the high-precision GNSS applications, as its fast-changing and site-dependent nature make it challenging to model and mitigate. The Non-Line-of-Sight (NLOS) signals in combination with the original Line-of-Sight (LOS) signal lead to multipath (MP), which results in erroneous range estimation. To mitigate the effect of multipath, detecting the presence of NLOS/multipath signals plays a vital role. In this paper, GPS and IRNSS signals are considered in simulated multipath environment and in open-sky conditions. A machine learning (ML) approach for classification of LOS/NLOS/multipath is presented in both the environments. In this paper, two classifiers are proposed. The proposed classifiers are trained with signal strength, elevation angle, Doppler shift, delta pseudorange, and pseudorange residuals as attributes. The accuracies of these models are computed and compared and it is found that, among all the algorithms, K-Nearest Neighbors, Decision Tree, and its ensemble functions have demonstrated superior performance. Experimental results are presented using GPS L1, IRNSS L5, and S1 data. A comparative analysis on both the classifiers is also presented. Further, to substantiate these results, another experiment is conducted in a complex real-time dynamic multipath environment and the obtained results are also presented.

Understanding the phenomenon of Shock Wave/Boundary Layer Interaction (SBLI) is critical in developing hypersonic aircraft as it is associated with several penalties, such as huge total pressure loss, boundary layer separation, tremendous temperature rise, fluctuating pressure, and thermal load. The consequences become severe, particularly at hypersonic speeds. Thus, it is essential to control the occurrence of SBLIs to minimize these repercussions. With this in mind, the current study numerically investigates the efficacy of an array of Micro-Vortex Generators (MVGs) placed upstream and at the interaction region in the Mach 5.7 intake. The computational analysis was performed using the finite volume solver Ansys fluent and a 3-dimensional numerical model. MVGs of three different heights (0.5 mm, 0.7 mm, and 1.0 mm) were considered to understand the detailed impact of MVGs height on controlling interactions. The steady-state analysis was carried out using shear stress transport (SST) k–ω turbulence model. Besides, Delayed Detached Eddy Simulation (DES) combined with SST k-omega is specifically considered for unsteady analysis to observe the flow evolution. The quantitative and qualitative analysis has been conducted by examining the static pressure and velocity distributions over the ramp surface and visualizing the shock structures. A maximum of 9.84% reduction in wall static pressure is observed for the MVGs of 1.0 mm height when stationed at the interaction region. The MVGs of 0.7 mm height, placed upstream of the interaction region, are proved to be more efficient than other MVGs. However, pressure recovery and turbulence intensity are maximum for 0.5 mm MVGs, when deployed upstream of the interaction zone.

Doppler collision has a very important issue in satellite-based navigation systems. Navigation with the Indian Constellation (NavIC) comprises seven operational satellites, among which three are geo-stationary (GEO) satellites, and the rest are geosynchronous satellites. Due to the 'small line of sight velocities' of GEO satellites, estimated ranges suffer from the unique challenge of Doppler collision (DC). In this study, we present an analysis of DC events in both static and dynamic conditions, particularly in aerospace applications. We utilize experimental data acquired from the Indian Regional Navigation Satellite System (IRNSS)-GPS-Satellite Based Augmentation System (SBAS) (IGS) receiver located at a low altitude station to develop algorithms for the prediction, avoidance, and mitigation of DC events. The prediction of DC is based on the moving average method. We have devised an efficient algorithm to avoid the occurrence of DC, considering all possible combinations of IRNSS GEO satellites. Additionally, we perform the mitigation of DC using a proposed hybrid approach that involves both the space segment and user segment. The approach is based on repositioning the IRNSS 1C satellite and varying the loop bandwidth of the Delay Locked Loop (DLL). With the implementation of this proposed hybrid approach, the time duration of DC is reduced by 59.16% in static conditions and 16% in dynamic conditions.

For UAV swarm confrontation, group motion control is the key of UAV swarm to accomplish the assigned task, in which target assignment is the premise of group movement of UAVs. Most of the target assignment algorithms used in the traditional unmanned aerial vehicle (UAV) swarm confrontation are centralized, which can match and optimize targets in the static environment of limited aircraft units. However, many limitations will be generated if applied to the dynamic confrontation tasks of large-scale UAV clusters. Moreover, the countermeasures of the traditional UAV swarm countermeasure model are relatively simple and not suitable for the complex countermeasures task requirements in reality. To solve the above problems, a group motion control method using the extend consensus-based bundle algorithm (ECBBA) algorithm is proposed in this paper to carry out the dynamic grouping behavior of UAV swarm. The distributed target assignment algorithm is assembled to improve the efficiency of grouping, supporting the UAV dynamic real-time target assignment, for implementing large-scale group dynamic confrontation. The proposed group motion control strategy of UAV swarm is designed, based on the control of single-group motion and the setting of confrontation behavior. The effectiveness of the proposed ECBBA-based group motion control strategy is verified by simulation experiments.

The questions connected with automation of testing of professional skills for aviation personnel on aircraft on-board facilities taking into account psychophysiological peculiarities of all tested persons are considered. The aim of the study is to find additional means of tightening the quality control of professional training for aviation personnel, taking into account the psychophysiological aspect of this control. To achieve the above-mentioned goal, the issues of tightening control for aviation personnel competence level during their training on computer simulators in conditions as close as possible to the real operating conditions of aviation equipment were solved. The research material is the obtained and processed information about the number of recorded changes in operating conditions of aviation equipment, the maximum speed for aviation personnel reaction to changes in its operating conditions, the median speed for aviation personnel reaction to changes in these conditions, the minimum speed of its reaction to changes in the same conditions, the number of decisions made by aviation personnel, the number of correctly made decisions, the number of incorrectly made decisions, and the maximum speed of decision-making by aviation personnel. In the process of research, the procedures of directed enumeration and comparative analysis for aviation personnel training results on computer simulators. When conducting the research, methods of software and hardware-software modeling for aviation personnel operation procedures on aircraft on-board facilities were used. The use of the so-called FLIGHTESTS as a set of individual tasks with control questions and electronic forms for the report on the performance of these tasks and answers to control questions is proposed. These FLIGHTESTS can and should be considered the basis for unerroric to assess the professional competence for aviation personnel. This unerroric will provide additional opportunities to tighten the quality control of professional training for aviation personnel.

To study the flow and heat transfer performance over the flat tip of high pressure (HP) turbine under transient conditions more accurately, a dynamic boundary condition model from one stable operating state to another stable operating state is established. The changes of model include inlet total temperature, inlet total pressure, inlet flow angle, and tip clearance. Furthermore, the steady-state solution is performed at the typical moments of the transient state, to study the feasibility of steady state replacing transient state performance. The results show that the heat transfer performance of the blade tip under transient conditions mainly focus on the pressure side. The separation vortex formed at the edge of the pressure side significantly affects the distribution of the heat transfer coefficient. The flow and heat transfer performance obtained under steady-state conditions are close to those under transient conditions. The maximum deviation of heat transfer coefficient and total pressure recovery coefficient at each typical moment does not exceed 0.1%.

Global Navigation Satellite System (GNSS) Signal-In-Space (SIS) quality directly affects positioning integrity, which is an important metric for safety–critical applications. BeiDou Global Navigation Satellite System (BDS-3) broadcasts two new signals interoperable with GPS and Galileo, i.e., B1C and B2a. They are expected to serve civil aviation applications, following the Standards and Recommended Practices (SARPs) released by International Civil Aviation Organization (ICAO). Therefore, the SIS accuracy and integrity performance of BDS-3 B1C and B2a are evaluated in this work. The SIS Range Errors (SISREs) are achieved by comparing the broadcast satellite positions and clock offsets derived from Civil Navigation Message (CNAV) with the precise products from International GNSS Service (IGS). Specifically, given that the IGS precise products are referring to the equivalent phase center of BeiDou Regional System (BDS-2) B1I + B3I ionosphere-free combination, Differential Code Bias (DCB) from IGS is applied to realize time synchronization. This synchronization method is also meaningful to different frequencies in other constellations and supports the en-route, approaching, and landing phases. By analyzing 1-year data, an overall SIS characteristic picture of the 18 BDS-3 MEO satellites is presented here. The results show that most BDS-3 satellites are subject to an overbounding User Range Accuracy (URA) of 0.5 m to 0.85 m and a fault probability of (1.4953times {10}^{-5}) to (1.1975times {10}^{-4}), with an integrity performance much better than that of BDS-2 and comparable to that of GPS. BDS-3 is now ready to serve civil aviation and other safety–critical applications.

The paper presents the results of the development of the takeoff mass technique for all-electric aircraft (AEA) at the early stages of design. The process of determining the relative mass of aircraft batteries is described. The technique was verified by comparing the values obtained from the developed expressions with the values of existing AEA. A method for determining the mass of the AEA power plant was developed and described. General recommendations are given on the application of the obtained expressions for the design of AEA.

The increasing number of orbiting satellites has motivated the development of active debris removal and on-orbit servicing missions. The KAIST Satellite Technology and Research Center plans to capture and de-orbit Korea’s first satellite, KITSAT-1, as one of the active debris removal missions. For the success of the project, mission planning for orbit transfer and rendezvous should be performed under consideration of the feasibility of required fuel. In this conceptual study, we designed a trajectory that could capture KITSAT-1 with a small satellite under 200 kg. The results was that the final relative RIC distance and the distance rate to KITSAT-1 are less than 0.01 km and 0.01 m/s order, and the required fuel mass was about 76 kg, which is feasible for a small capture satellite.