Overall Parameters Design of Air-Launched Rockets Using Surrogate Based Optimization Method

In this paper, the design and optimization method of rocket parameters based on the surrogate model and the trajectory simulation system of the 3-DOF air-launched rockets were established. The Gaussian kernel width determination method based on the relationship between local density and width is used to ensure the efficiency and reliability of the optimization method, and at the same time greatly reduces the amount of calculation. An adaptive sampling point updating method was established, which includes three stages: location sampling, exploration sampling, and potential optimal sampling of the potential feasible region. The adaptive sampling is realized by the distance constraint. Based on the precision of the surrogate model, the convergence end criterion was established, which can achieve efficient and reliable probabilistic global optimization. The objective function of the optimization problem was deduced to determine the maximum load mass and reasonable constraints were set to ensure that the rocket could successfully enter orbit. For solid engine rockets with the same take-off mass as Launcherone, the launch altitude and target orbit were optimized and analyzed, and verified by 3-DOF trajectory simulation. The surrogate-based optimization algorithm solved the problem of the overall parameter design optimization of the air-launched rocket and it provides support for the design of air-launched solid rockets.

QUANTIFICATION OF UNCERTAINTY IN MANOEUVRING CHARACTERISTICS FOR DESIGN OF UNDERWATER VEHICLES

The prediction of manoeuvring characteristics of underwater vehicles during design involves approximations at various stages. This paper attempts to quantify some of the uncertainties involved in the manoeuvring characteristics of underwater vehicles. The first source of uncertainty is in idealization of mathematical model selected for trajectory simulation. This is illustrated for alternative mathematical models in trajectory simulation programs. Next, the values of the hydrodynamic coefficients (HDCs) in the equations of motion have their own levels of uncertainty, depending upon the methods used to determine them. The sensitivity of trajectory simulation results to uncertainty levels in various HDCs is examined. Finally, the level of uncertainty in full-scale measurements of manoeuvres of underwater vehicles is discussed and estimated. It emerges that the cumulative errors in the prediction process during design need to be reduced further, in order to maintain their levels of uncertainty below those of the validation process.

An Alternative Operation Scheme to Improve the Efficiency of a Stark Decelerator

A Stark decelerator can slow down polar molecules to very low velocities. When the velocities are very low, the number of cold molecules obtained is very small. In order to obtain a higher quantity of cold molecules, inspired by the work of Reens et al. [Phys. Rev. Res. 2 (2020) 033 095], we propose an alternative method of operating a Stark decelerator. Through the trajectory simulation of OH molecules in the decelerator, we find that the number of cold molecules can be greatly increased by one order of magnitude at both low and high final velocities on a Stark decelerator consisting of around 150 electrodes. This development is due to the improved longitudinal and the transverse focusing property provided by the new switching schemes and the high-voltage configurations on the decelerator unit.

Integral Modeling for Deviation Correction Trajectory of the Mechanical Vertical Drilling System

The deviation correction trajectory of the mechanical vertical drilling system (MVDS) is very important because it is the final embodiment of performance. However, it is impossible to obtain it at the design stage, except when using simulation methods. In this paper, tool face angle model and other theoretical models were established, respectively, and the trajectory simulation method was created through model coupling. Next, the method was used to simulate the trajectory of MVDS under two typical working conditions. The results indicate that the critical deviation angle is the deviation control accuracy of the MVDS. The existence of critical deflection angle makes MVDS correct deviation and change azimuth at the same time, resulting in the trajectory being a three-dimensional curve, which has the tendency of drifting to the left. Furthermore, the deviation and azimuth change rate are constantly changing in the process of drilling. The results also show that the MVDS is unable to correct the horizontal displacement of the downhole. The proposed method and analysis results are helpful to find out and solve the problem of the current design as soon as possible, and to provide guidance for the subsequent structure optimization.

Effect of Cutting Parameters on Chips and Burrs Formation With Traditional Micromilling and Ultrasonic Vibration Assisted Micromilling

In the traditional micromilling(TMM) of Inconel718 alloy, due to the influence of material plasticity and size effect, relatively large burr will be produced. In order to solve the burr problem in micromilling, ultrasonic vibration in feed direction is applied to the workpiece to complete vibration cutting. Combined with trajectory simulation and cutting experiment, the burr formation mechanism of TMM and ultrasonic vibration assisted micromilling(UVAMM) was studied. The results show that when the ratio of amplitude(A) to feed per tooth(ƒz) is greater than 0.5, continuous cutting changes to intermittent cutting. Compared with TMM, UVAMM improves chip breaking ability, facilitates the propagation of burr crack and effectively inhibits the formation of burr. However, due to the influence of cutting edge radius, A/ƒz should be set larger. When the chip breaking condition is reached, the burr shape is usually tearing or flocculent. Under the conditions of low speed(n), large ƒz and large A, the burr suppression is more obvious.

Deep Q-Learning for Two-Hop Communications of Drone Base Stations

In this paper, we address the application of the flying Drone Base Stations (DBS) in order to improve the network performance. Given the high degrees of freedom of a DBS, it can change its position and adapt its trajectory according to the users movements and the target environment. A two-hop communication model, between an end-user and a macrocell through a DBS, is studied in this work. We propose Q-learning and Deep Q-learning based solutions to optimize the drone’s trajectory. Simulation results show that, by employing our proposed models, the drone can autonomously fly and adapts its mobility according to the users’ movements. Additionally, the Deep Q-learning model outperforms the Q-learning model and can be applied in more complex environments.