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261.
为更好地理解热力学排气系统(TVS)的运行机理,优化其运行参数,针对节流装置,建立了热力学模型,讨论了节流过程中状态参数的变化规律,对比了单相气体、单相液体节流的性能特性,进一步揭示了焦汤节流效应的原理,分析了不同节流背压下节流前低温工质(液氢和液氧)压力和温度对节流性能的影响,并结合TVS实际应用,阐述了节流最大制冷量的利用效果,提出了优化的TVS工作区间。研究表明:在节流过程不发生相变情况下单相气体节流制冷效应要比单相液体节流制冷效应更加显著;而在节流过程发生相变情况下液体节流至两相后,由于空化吸热导致流体温度降低,对于液氢,0.5MPa的压降可产生接近3 K的温降。对于液体节流,节流前压力对节流过程影响可忽略,〖JP2〗而节流前温度和节流背压对节流过程起主导作用;对于液氢在在轨运行工况下,考虑到节流制冷量的充分利用,同时保证换热过程体积含气率不高于90%,推荐TVS系统中节流背压范围为75~143 kPa。 相似文献
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265.
Marking arbitrary three-dimensional(3D) target curves on given objects with curved surface is required in many industrial fields, such as fabric prepreg placement in composite material part fabrication, product assembly, surface painting for decoration, etc. A shortcut to the solution of this intractable problem is proposed by utilizing a galvanometric laser scanner(GLS) with the aid of a camera. Without using the existing tedious GLS calibration procedures,the proposed method directly establishes a mapping between the 3D coordinates of the laser spots on the object surface and the control voltages of the scanner. A single-hidden layer feedforward neural network(SLFN) is employed to model the mapping. By projecting a dense grid of laser spots on the object to be marked and simultaneously taking only one image, the SLFN model is trained in minutes via a linear solving mechanism. Experiments demonstrate that the trained SLFN model has a good generalization performance for marking 3D target curves. The 3D laser marking errors on experimental objects are less than 0.5 mm. The proposed method is especially suitable for on-site use and can be conveniently extended to multiple GLSs for marking large complex objects. 相似文献
266.
目前,国外多个大型枢纽机场的绕行滑行道运行实例均表明,该滑行道能有效地提高机场运行效率。中国具有近距平行跑道的机场都有条件建设、运行绕滑。设置绕行滑行道能减少近距平行跑道机场的航空器跑道穿越次数,提高运行安全水平和航空器地面滑行效率,降低管制员工作负荷。通过建立有绕滑条件下进场航空器地面滑行路径的选择模型,并使用算例和对虹桥机场SIMMOD模拟计算证明了模型的实用性。计算分析表明,绕滑对减少航空器地面滑行时间作用显著,且机场高峰小时架次愈高作用愈明显。 相似文献
267.
This paper addresses the problem of real-time object tracking for unmanned aerial vehicles. We consider the task of object tracking as a classification problem. Training a good classifier always needs a huge number of samples, which is always time-consuming and not suitable for realtime applications. In this paper, we transform the large-scale least-squares problem in the spatial domain to a series of small-scale least-squares problems with constraints in the Fourier domain using the correlation filter technique. Then, this problem is efficiently solved by two stages. In the first stage, a fast method based on recursive least squares is used to solve the correlation filter problem without constraints in the Fourier domain. In the second stage, a weight matrix is constructed to prune the solution attained in the first stage to approach the constraints in the spatial domain. Then, the pruned classifier is used for tracking. To evaluate proposed tracker's performance, comprehensive experiments are conducted on challenging aerial sequences in the UAV123 dataset. Experimental results demonstrate that proposed approach achieves a state-ofthe-art tracking performance in aerial sequences and operates at a mean speed of beyond 40 frames/s. For further analysis of proposed tracker's robustness, extensive experiments are also performed on recent benchmarks OTB50, OTB100, and VOT2016. 相似文献
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建立了飞行器助推-滑行式燃料最优真空飞行轨迹的最优控制模型,给出了一种更为简单、直观的内点约束条件和横截条件的推导方法,讨论了高效且更为稳定的数值计算方法,提出了两种应用模式,通过与连续推力式和脉冲式飞行方案的比较,说明这种设计方法在节省燃料方面具有优势. 相似文献
270.