无蒙皮复合材料网格结构设计与分析

无蒙皮复合材料网格结构是复合材料结构中承载效率最高的结构形式,但其设计成型较其他复合材料网格结构更为困难。本文以工程应用为目的,考虑工艺成型问题,定性与定量分析相结合。按网格形式选择、典型结构工程计算、有限元优化计算、确定工程方案及试验验证五个层次分级优化。最终达到结构形式、设计计算、工艺成型等各方面综合最优的效果。生产出的无蒙皮复合材料网格结构满足工程应用要求,同时找到了工艺成型薄弱环节,为制造最优结构创造了条件。     

模块化可重构无人机机翼结构优化方法研究

模块化可重构无人机设计工况复杂、约束多样，需要根据不同设计思想的特点研究适用的优化方法才能得到最优方案。本文开展针对多模型的同步优化方法研究，给出不同构型机翼翼根弯矩约束方法，提出多构型机翼结构前后梁弯矩比例约束下的同步优化技术，并以某模块化可重构无人机机翼为对象进行应用验证。结果表明：与文献中模块化机翼优化结果相比，本文多构型机翼结构同步优化方法在解决整机翼更换的模块化可重构机翼结构优化问题时具有很高的适用性和收敛性，以及广阔的工程推广价值。     

一种靶场试验遥测数据处理与分析系统的设计与实现

针对靶场试验遥测数据特点,设计了一种遥测数据处理分析系统。作为靶场测试流程和飞行结果判别的重要环节,遥测数据处理分析系统软件实现了繁杂测试数据处理与发布、数据管理和数据判读与服务等功能。该系统的设计与实现为靶场数字化建设提供了重要支撑,具有较强的实用性与推广价值。     

Martian Buildings: Design loading

Multiplanetary life has been studied by scientists as a way to supply energy or sustain human life in the future. Mars is likely to be man’s first destination, colonization using onsite structural construction would be one of the main options. The first step to designing a reliable building is to know the applied structural loads and to have an accurate design load combination. Due to lack of complete knowledge, short span of recorded data, Martian environment, and hazardous environment that Martian structures face, constructed Martian structures should behave appropriately under the highest likely live, dead and environmental loads either simultaneously or as a worst-case scenario. The present study evaluated and calculated probable Martian structural loads, including live, internal pressure, snow, gravity (dead), dust accumulation, thermal stress, wind, marsquake, asteroid, and meteoroid impact loads and their effects. Information was gathered from previous studies and valid data from Martian landers, rovers and orbiters. Wind loads were calculated based on the over 6.5 years of data recorded by Vikings 1 and 2, temperature and winds for InSight (TWINS) sensor. A wind shear exponent and wind profile have been proposed for a Martian flat terrain construction site. Marsquake lateral loads, frequency content and seismicity were assessed using data from the seismic experiment for interior structure (SEIS) and the Viking 2 seismometer. Considering the high influx of micrometeoroids, their penetration distance, impact loads and their effects on structures were calculated. The annual probability of an asteroid impact on a settlement was assessed for a 30-year mission. A load map for Martian residential buildings that considers the worst-case scenario in which a Martian structure should be designed based on them has been proposed.     

An architecture decomposition method of pneumatic catapult system based on OPM and DSM

The architecture strategy of the Unmanned Aerial Vehicle (UAV) pneumatic launch system should continue to evolve to adapt to complex and variable operating environments. Architecture representation, decomposition perspective, and cluster analysis play a vital role in the early phase of system architecture development. In order for the system to emerge anticipated and desirable intrinsic functional properties, an architecture decomposition method based on the Object-Process Methodology (OPM) and Design Structure Matrix (DSM) is put forward in this paper. The OPM is proposed to model the UAV launch process formally, and the matrix representation of the architecture of the pneumatic launch system is established. After the extension of the definition and operations of DSM, with the Idicula-Gutierrez-Thebeau Algorithm plus (IGTA + ) clustering algorithm, the transformation of the pneumatic launch system architecture from process decomposition to function decomposition is demonstrated in this paper. The analysis shows that the architecture decomposition of the pneumatic launch system meets the functional requirements of stakeholders.     

Surrogate role of machine learning in motor-drive optimization for more-electric aircraft applications

Motor drives form an essential part of the electric compressors, pumps, braking and actuation systems in the More-Electric Aircraft (MEA). In this paper, the application of Machine Learning (ML) in motor-drive design and optimization process is investigated. The general idea of using ML is to train surrogate models for the optimization. This training process is based on sample data collected from detailed simulation or experiment of motor drives. However, the Surrogate Role (SR) of ML may vary for different applications. This paper first introduces the principles of ML and then proposes two SRs (direct mapping approach and correction approach) of the ML in a motor-drive optimization process. Two different cases are given for the method comparison and validation of ML SRs. The first case is using the sample data from experiments to train the ML surrogate models. For the second case, the joint-simulation data is utilized for a multi-objective motor-drive optimization problem. It is found that both surrogate roles of ML can provide a good mapping model for the cases and in the second case, three feasible design schemes of ML are proposed and validated for the two SRs. Regarding the time consumption in optimizaiton, the proposed ML models can give one motor-drive design point up to 0.044 s while it takes more than 1.5 mins for the used simulation-based models.     

Downwash modelling for three-lifting-surface aircraft configuration design

This paper introduces a semi-empirical model to predict the downwash gradient at the horizontal tail of a three-lifting-surface aircraft. The superposition principle applied to well established formulations valid for two lifting surfaces is not a reasonable approach to calculate the downwash of a canard-wing-tail layout, and this paper demonstrates that such a basic technique leads to incorrect results. Therefore, an ad hoc prediction model is proposed that considers the combined nonlinear effec...