The capture of a target spacecraft by a chaser is an on-orbit docking operation that requires an accurate, reliable, and robust object recognition algorithm. Vision-based guided spacecraft relative motion during close-proximity maneuvers has been consecutively applied using dynamic modeling as a spacecraft on-orbit service system. This research constructs a vision-based pose estimation model that performs image processing via a deep convolutional neural network. The pose estimation model was constructed by repurposing a modified pretrained GoogLeNet model with the available Unreal Engine 4 rendered dataset of the Soyuz spacecraft. In the implementation, the convolutional neural network learns from the data samples to create correlations between the images and the spacecraft’s six degrees-of-freedom parameters. The experiment has compared an exponential-based loss function and a weighted Euclidean-based loss function. Using the weighted Euclidean-based loss function, the implemented pose estimation model achieved moderately high performance with a position accuracy of 92.53 percent and an error of 1.2 m. The in-attitude prediction accuracy can reach 87.93 percent, and the errors in the three Euler angles do not exceed 7.6 degrees. This research can contribute to spacecraft detection and tracking problems. Although the finished vision-based model is specific to the environment of synthetic dataset, the model could be trained further to address actual docking operations in the future.

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Abstract:The aim of this paper is to numerically investigate cooling performances of a non-film-cooled turbine vane coated with a thermal barrier coating (TBC) at two turbulence intensities (Tu = 8.3% and 16.6%). Computational fluid dynamics (CFD) with conjugate heat transfer (CHT) analysis is used to predict the surface heat transfer coefficient, overall and TBC effectiveness, as well as internal and average temperatures under a condition of a NASA report provided by Hylton et al. [NASA CR-168015]. The following interesting phenomena are observed: (1) At each Tu, the TBC slightly dampens the heat transfer coefficient in general, and results in the quantitative increment of overall cooling effectiveness about 16-20%, but about 8% at the trailing edge (TE). (2) The protective ability of the TBC increases with Tu in many regions, that is, the leading edge (LE) and its neighborhoods on the suction side (SS), as well as the region from the LE to the front of the TE on the pressure side (PS), because the TBC causes the lower enhancement of the heat transfer coefficient in general at the higher Tu. (3) Considering the internal and average temperatures of the vane coated with two different TBCs, although the vane with the lower thermal conductivity protects more effectively, its role in the TE region reduces more significantly. (4) For both TBCs, the increment of Tu has a relatively small effect on the reduction of the average temperature of the vane.

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