A novel framework for liquid propellant engine’s cooling system design by sensitivity analysis based on RSM and multi-objective optimization using PSO

One of the challenges of combustion chamber and nozzle design in a Liquid Propellant Engine (LPE) is to predict the behavior and performance of the cooling system. Therefore, while designing, the optimization of the cooling system is always of great importance. This paper presents the multi-objective optimization of the LPE’s cooling system. To this end, a novel framework has been developed, resulting from the application of the Response Surface Method (RSM) and the correlation coefficients matrix, sensitivity analysis and the The Particle Swarm Optimization (PSO). based on this method, the input variables, constraints, objective functions, and their surfaces were identified. In terms of multi-optimization algorithms, RSM and PSO are utilized to get global optimum. In conclusion, the methodology capability is to optimize the LPE’s cooling system, 6 percentage increase in total heat transfer and 7 bar decrease cooling system pressure loss, which resulted in a 1.2-seconds increase in the specific impulse of the engine.     

A comparative study of ionospheric IRIEup and ISP assimilative models during some intense and severe geomagnetic storms

Three-dimensional (3-D) electron density matrices, computed in the Mediterranean area by the IRI climatological model and IRIEup and ISP nowcasting models, during some intense and severe geomagnetic-ionospheric storms, were ingested by the ray tracing software tool IONORT, to synthesize quasi-vertical ionograms. IRIEup model was run in different operational modes: (1) assimilating validated autoscaled electron density profiles only from a limited area which, in our case, is the Mediterranean sector (IRIEup_re(V) mode); (2) assimilating electron density profiles from a larger region including several stations spread across Europe: (a) without taking care of validating the autoscaled data in the assimilation process (IRIEup(NV)); (b) validating carefully the autoscaled electron density profiles before their assimilation (IRIEup(V)).The comparative analysis was carried out comparing IRI, IRIEup_re(V), ISP, IRIEup(NV), and IRIEup(V) foF2 synthesized values, with corresponding foF2 measurements autoscaled by ARTIST, and then validated, at the truth sites of Roquetes (40.80°N, 0.50°E, Spain), San Vito (40.60°N, 17.80°E, Italy), Athens (38.00°N, 23.50°E, Greece), and Nicosia, (35.03°N, 33.16°E, Cyprus). The outcomes demonstrate that: (1) IRIEup_re(V), performs better than ISP in the western Mediterranean (around Roquetes); (2) ISP performs slightly better than IRIEup_re(V) in the central part of Mediterranean (around Athens and San Vito); (3) ISP performance is better than the IRIEup_re(V) one in the eastern Mediterranean (around Nicosia); (4) IRIEup(NV) performance is worse than the IRIEup(V) one; (5) in the central Mediterranean area, IRIEup(V) performance is better than the IRIEup_re(V) one, and it is practically the same for the western and eastern sectors.Concerning the overall performance, nowcasting models proved to be considerably more reliable than the climatological IRI model to represent the ionosphere behaviour during geomagnetic-ionospheric storm conditions; ISP and IRIEup(V) provided the best performance, but neither of them has clearly prevailed over the other one.     

Predictive fault-tolerant control of an all-thruster satellite in 6-DOF motion via neural network model updating

The problem of controlling an all-thruster spacecraft in the coupled translational-rotational motion in presence of actuators fault and/or failure is investigated in this paper. The nonlinear model predictive control approach is used because of its ability to predict the future behavior of the system. The fault/failure of the thrusters changes the mapping between the commanded forces to the thrusters and actual force/torque generated by the thruster system. Thus, the basic six degree-of-freedom kinetic equations are separated from this mapping and a set of neural networks are trained off-line to learn the kinetic equations. Then, two neural networks are attached to these trained networks in order to learn the thruster commands to force/torque mappings on-line. Different off-nominal conditions are modeled so that neural networks can detect any failure and fault, including scale factor and misalignment of thrusters. A simple model of the spacecraft relative motion is used in MPC to decrease the computational burden. However, a precise model by the means of orbit propagation including different types of perturbation is utilized to evaluate the usefulness of the proposed approach in actual conditions. The numerical simulation shows that this method can successfully control the all-thruster spacecraft with ON-OFF thrusters in different combinations of thruster fault and/or failure.     

Distributed intelligent self-organized mission planning of multi-UAV for dynamic targets cooperative search-attack

This article studies the cooperative search-attack mission problem with dynamic targets and threats, and presents a Distributed Intelligent Self-Organized Mission Planning (DISOMP) algorithm for multiple Unmanned Aerial Vehicles (multi-UAV). The DISOMP algorithm can be divided into four modules: a search module designed based on the distributed Ant Colony Optimization (ACO) algorithm, an attack module designed based on the Parallel Approach (PA) scheme, a threat avoidance module designed based on the Dubins Curve (DC) and a communication module designed for information exchange among the multi-UAV system and the dynamic environment. A series of simulations of multi-UAV searching and attacking the moving targets are carried out, in which the search-attack mission completeness, execution efficiency and system suitability of the DISOMP algorithm are analyzed. The simulation results exhibit that the DISOMP algorithm based on online distributed down-top strategy is characterized by good flexibility, scalability and adaptability, in the dynamic targets searching and attacking problem.     

Bayesian network-based extraction of lunar impact craters from optical images and DEM data

Impact craters are among the most noticeable geomorphological features on the planetary surface and yield significant information about terrain evolution and the history of the solar system. Thus, the recognition of impact craters is an important branch of modern planetary studies. Aiming at addressing problems associated with the insufficient and inaccurate detection of lunar impact craters, a decision fusion method within the Bayesian network (BN) framework is developed in this paper to handle multi-source information from both optical images and associated digital elevation model (DEM) data. First, we implement the edge-based method for efficiently searching crater candidates which are the image patches that can potentially contain impact craters. Secondly, the multi-source representations of an impact crater derived from both optical images and DEM data are proposed and constructed to quantitatively describe the two-dimensional (2D) and three-dimensional (3D) morphology, consisting of Histogram of Oriented Gradient (HOG), Histogram of Multi-scale Slope (HMS) and Histogram of Multi-scale Aspect (HMA). Finally, a BN-based framework integrates the multi-source representations of impact craters, which can provide reductant and complementary information, for distinguishing craters from non-craters. To evaluate the effectiveness and robustness of the proposed method, experiments were conducted on three lunar scenes using both orthoimages from the Lunar Reconnaissance Orbiter (LRO) and DEM data acquired by the Lunar Orbiter Laser Altimeter (LOLA). Experimental results demonstrate that integrating optical images with DEM data significantly decreases the number of false positives compared with using optical images alone, with F₁-score of 84.8% on average. Moreover, compared with other existing fusion methods, our proposed method was quite advantageous especially for the detection of small-scale craters with diameters less than 1000 m.     

Direction finding for two-dimensional incoherently distributed sources with Hadamard shift invariance in non-uniform orthogonal arrays

This paper proposes a novel algorithm for Two-Dimensional (2D) central Direction-of-Arrival (DOA) estimation of incoherently distributed sources. In particular, an orthogonal array structure consisting of two Non-uniform Linear Arrays (NLAs) is considered. Based on first-order Taylor series approximation, the Generalized Array Manifold (GAM) model can first be established to separate the central DOAs from the original array manifold. Then, the Hadamard rotational invariance relationships inside the GAMs of two NLAs are identified. With the aid of such relationships, the central elevation and azimuth DOAs can be estimated through a search-free polynomial rooting method. Additionally, a simple parameter pairing of the estimated 2D angular parameters is also accomplished via the Hadamard rotational invariance relationship inside the GAM of the whole array. A secondary but important result is a derivation of closed-form expressions of the Cramer-Rao lower bound. The simulation results show that the proposed algorithm can achieve a remarkably higher precision at less complexity increment compared with the existing low-complexity methods, which benefits from the larger array aperture of the NLAs. Moreover, it requires no priori information about the angular distributed function.     

月球表层采样样品智能确认方法

表层采样是月球采样探测的重要方式，样品智能确认有助于提升工作效率与复杂问题处理能力。结合月球表层采样铲挖工作过程，分析了铲挖过程中臂载相机图像的特点，模仿有人参与识别过程，提出了层次解耦的月球样品智能识别流程，利用深度学习方法构建了一类深度卷积识别网络，完整地描述了图像、特征、标记在网络中的正反传递关系，并在月球表层采样地面试验中进行了验证，结果表明该方法对不同光照、不同背景、不同过程、不同形态的样品，具有较好的泛化识别能力，误识别率优于8.1%，平均单幅识别时间约0.7 s。     

GNSS观测数据ZTD建模的质量控制方法

针对目前基于GNSS观测数据的对流层天顶总延迟(ZTD)模型缺乏有效质量控制手段的现状,提出了一套综合考虑数据量、网格分辨率以及模型稳定性的ZTD建模质量控制方法,并采用内华达大地测量实验室(NGL)解算的高空间分辨率GNSS对流层数据,选取了近十年德国及周边区域[47°N-55°N,5°E-15°E]183个测站的实测ZTD,对该方法进行了校验。实验结果表明:在该质量控制方法下建立的新模型精度稳定,平均均方根误差(RMS)为3.4 cm,相对于UNB3m、EGNOS、GPT2w+Saas平均改善了42.4%、35.8%、33.3%。本文提出的质量控制方法有效提升了基于GNSS观测数据的ZTD模型的性能,对于ZTD建模研究具有一定的参考价值。     

L-band nighttime scintillations at the northern edge of the EIA along 95°E during the ascending half of the solar cycle 24

The characteristics of nighttime ionospheric scintillations measured at the L-band frequency of 1.575 GHz over Dibrugarh (27.5°N, 95°E, MLAT ～ 17°N, 43° dip) during the ascending half of the solar cycle 24 from 2010 to 2014 have been investigated and the results are presented in this paper. The measurement location is within or outside the zone of influence of the equatorial ionization anomaly depending on solar and geomagnetic activity. Maximum scintillation is observed in the equinoxes irrespective of solar activity with clear asymmetry between March and September. The occurrence frequency in the solstices shifts from minimum in the June solstice in low solar activity to a minimum in the December solstice in high solar activity years. A significant positive correlation of occurrence of scintillations in the June solstice with solar activity has been observed. However, earlier reports from the Indian zone (～75°E) indicate negative or no correlation of scintillation in June solstice with solar activity. Scintillations activity/occurrence in solstices indicates a clear positive correlation with Es recorded simultaneously by a collocated Ionosonde. In equinoxes, maximum scintillations occur in the pre-midnight hours while in solstices the occurrence frequency peaks just after sunset. The incidence of strong scintillations (S₄ ≥ 0.4) increases with increase in solar activity. Strong (S₄ ≥ 0.4) ionospheric scintillations accompanied by TEC depletions in the pre-midnight period is attributed to equatorial irregularities whereas the dusk period scintillations are related to the sporadic-E activity. Present results thus indicate that the current location at the northern edge of the EIA behaves as low as well as mid-latitude location.     

Analytical Calculation Model for Mach Wave Parameters

When a wave shaper is embedded in a liner,Mach wave will emerge above the liner,which affects the head shape of an explosively formed projectile.Mach wave parameters,including radius and pressure need to be determined to effectively match Mach wave with the liner,so that a good head shape can be obtained.An analytical calculation model for Mach wave parameter is presented based on three-shock theory,and the theoretical values agree well with the experimental ones.The analysis shows that when the radius of the wave shaper is constant,the radius of the Mach wave increases,whereas the pressure decreases while increasing the distance between the liner and the wave shaper.When the distance between the liner and the wave shaper is constant,the radius of the Mach wave increases,whereas the pressure decreases when decreasing the radius of the wave shaper.