Orbit determination of BDS-3 satellite based on regional ground tracking station and inter-satellite link observations

The BeiDou global navigation satellite system (BDS-3) has established the Ka-band inter-satellite link (ISL) to realize a two-way ranging function between satellites, which provides a new observation technology for the orbit determination of BDS-3 satellites. Therefore, this study presents a BDS satellite orbit determination model based on ground tracking station (GTS) observations and ISL ranging observations firstly to analyze the impact of the ISL ranging observations on the orbit determination of BDS-3 satellites. Subsequently, considering the data fusion processing, the variance component estimation (VCE) algorithm is applied to the parameter estimation process of the satellite orbit determination. Finally, using the measured data from China’s regional GTS observations and BDS-3 ISL ranging observations, the effects of ISL ranging observations on the orbit determination accuracy of BDS-3 satellites are analyzed. Moreover, the impact of the VCE algorithm on the fusion data processing is evaluated from the aspects of orbit determination accuracy, Ka-band hardware delay parameter stability, and ISL ranging observation residuals. The results show that for China’s regional GTSs, the addition of BDS-3 ISL ranging observations can significantly improve the orbit determination accuracy of BDS-3 satellites. The observed orbit determination accuracy of satellite radial component is improved from 48 cm to 4.1 cm. In addition, when the initial weight ratio between GTS observations and ISL ranging observations is not appropriate, the various indicators which include orbit determination accuracy, ISL hardware delay, and ISL observation residuals were observed to have improved after the adjustment of the VCE algorithm. These results validate the effectiveness of the VCE algorithm for the fusion data processing of the GTS observations and ISL ranging observations.     

考虑燃料消耗均衡性的低轨通信星座在轨星座构型重构方法研究

针对低轨（low earth orbit,LEO）通信星座在轨重构问题，分析了低轨通信星座的特点，提出了4个重构指标，即全球平均覆盖率、燃料消耗均衡性、重构总时间和重构总速度增量，并分析了提高轨道高度的重构方式。采用基于分解的多目标进化算法（multiobjective evolutionary algorithm based on decomposition，MOEA/D）对重构进行建模分析。结果表明，模型优化结果可以得出多组最优解，构成帕累托前沿，并得出燃料消耗均衡性最优的解，针对两种失效模式得出的重构总时间均为3.6×105s，速度增量方差分别为261.4m2/s2和293.4m2/s2，这些解均可恢复星座原有的覆盖性能，并使燃料消耗最为均衡。     

一种基于VPL 的元器件快速建模方法

为了更好地落实航空电子模块的可制造性设计审查工作,结合航空电子模块产品特点和技术要求,建设了基于Valor软件的PCB/PCBA设计与检测自动化分析系统.元器件模型库作为该系统的必要组成部分,其覆盖范围和数据精度对审查结果至关重要.本文将从元器件模型库建设必要性、建设过程和建模工艺要求三个方面进行阐述,并提出一种基于Valor VPL的元器件快速建模方法,应用结果表明,该方法能够高效构建满足系统审查精度的元器件模型,使大规模元器件模型库的建设成为可能.     

替代燃料贫油熄火边界影响因素

为了研究燃油以及入口空气压力对于贫油熄火(LBO)边界的影响大小及规律,采用航空煤油(RP-3)、高沸点费托油(FT)和柴油进行了三种不同燃烧室入口压力工况下的贫油熄火实验并进行规律分析。分析结果表明:入口压力对贫油熄火边界的影响(19.17%)要大于燃油性质造成的影响(6.26%)。导致熄火油气比变化的主要因素包括入口空气压力,火焰体积,燃烧室温度,燃油雾化直径以及燃油的热值和密度,其中火焰体积和燃油雾化直径主要受燃油性质影响,而燃烧室温度则与入口压力有很大关系。入口压力影响的贫油熄火油气比变化会受其影响的火焰体积和燃烧室温度变化而削弱。碳数高支链烷烃含量少的燃油可能会提高火焰体积对熄火油气比的影响,使其在低入口压力下有更好的贫油熄火边界。      

Measurement of mass diffusion coefficients of O_2 in aviation fuel through digital holographic interferometry

The experimental apparatus to measure the mass diffusion coefficients of O2 in aviation fuel was constructed based on the digital holographic interferometry method. The theory of mass diffusion coefficient and interference image processing were introduced in detail. The accuracy of the experiment was verified by measuring the mass diffusion coefficient of 0.33 mol/L KCl in aqueous solution at 298.15 K. The mass diffusion coefficients of O_2 in RP3 and RP5 aviation fuels were measured at temperature from 278.15 K to 333.15 K, and the Arrhenius equation was employed to fit the experimental data. In terms of the Stokes-Einstein equation, the viscosities of these two aviation fuels were tested to estimate the correlation among mass diffusion coefficient, viscosity and temperature. A uniform polynomial calculation correlation was proposed to predict the mass diffusion coefficients of O_2 in both RP3 and RP5 aviation fuels, and its accuracy is considerably higher than that of the Stokes-Einstein equation.     

翼身融合运输机分布式电推进系统设计及油耗评估

针对翼身融合运输机开展了分布式电推进系统的总体设计与油耗评估。通过数值计算完成了70t载质量翼身融合飞机的气动设计与优化。在巡航马赫数为0.80和10km高度的设计点,最大升阻比达到了24。通过求解积分边界层方程组,完成了电推进系统的总体设计。电推进系统包含10个推进风扇,风扇直径为1.45m，压比为1.35，巡航功率为2.94MW。建立了考虑燃烧过程的发动机一维性能模型,对发动机油耗进行了评估,获得了不同发动机循环参数下燃油消耗。建模结果表明,基于翼身融合布局和分布式电推进技术,可使运输机的油耗较C-17节省近50%。      

基于遗传-支持向量机的对置活塞二冲程柴油机气口高度优化

以某对置活塞二冲程柴油机为研究对象,基于一维仿真模型,利用遗传-支持向量机的方法,以油耗为优化目标,进行不同转速工况下进排气口高度组合的自动化寻优。结果表明:在1200r/min下,优化的进、排气口无量纲化高度组合为［0.075,0.105］,所得最小油耗为220.32g/(kW·h);对置活塞二冲程柴油机的气口最优高度应随着转速的提高逐渐增大;且在高转速(大于1600r/min)下,排气口最优高度增加趋势更加明显。      

Detection of hydrothermal alteration zones using ASTER data in Nimu porphyry copper deposit,south Tibet,China

Advanced space-borne thermal emission and reflection radiometer (ASTER) data were evaluated for the hydrothermal alteration mapping of the Nimu porphyry copper deposit, southern Tibet. According to the metallogenic model for porphyry copper, we chose hydrothermal alteration mineral association and then established a remote sensing model. Relative absorption-band depth (RBD) and simple band combination methods in visible near infrared (VNIR) and shortwave infrared (SWIR) bands were used to retrieve information about lithological distributions. Principal component analyses (PCA) were applied to extract the prospecting information based on the spectral information of argillization mineral association, propylitization mineral association, and iron stained (limonite) effects. Results of the study match up well with known copper occurrences and a circular structure in study area, while circular structures usually have close relationship with mineralization. Combined with field validation, ASTER data are proved able to characterise the alteration zone of these porphyry deposits. With VNIR and SWIR bands, argillic, propylitic and ferritization alterations in a single deposit can be effectively discriminated.     

Application of a PCA-DBN-based surrogate model to robust aerodynamic design optimization

An efficient method employing a Principal Component Analysis (PCA)-Deep Belief Network (DBN)-based surrogate model is developed for robust aerodynamic design optimization in this study. In order to reduce the number of design variables for aerodynamic optimizations, the PCA technique is implemented to the geometric parameters obtained by parameterization method. For the purpose of predicting aerodynamic parameters, the DBN model is established with the reduced design variables as input and the aerodynamic parameters as output, and it is trained using the k-step contrastive divergence algorithm. The established PCA-DBN-based surrogate model is validated through predicting lift-to-drag ratios of a set of airfoils, and the results indicate that the PCA-DBN-based surrogate model is reliable and obtains more accurate predictions than three other surrogate models. Then the efficient optimization method is established by embedding the PCA-DBN-based surrogate model into an improved Particle Swarm Optimization (PSO) framework, and applied to the robust aerodynamic design optimizations of Natural Laminar Flow (NLF) airfoil and transonic wing. The optimization results indicate that the PCA-DBN-based surrogate model works very well as a prediction model in the robust optimization processes of both NLF airfoil and transonic wing. By employing the PCA-DBN-based surrogate model, the developed efficient method improves the optimization efficiency obviously.