Scientific objectives and payloads of the lunar sample return mission—Chang’E-5

Zhou, C.; Jia, Yingzhuo; Liu, Jianzhong; Li, Huijun; Fan, Yun; Zhang, Zhanlan; Liu, Yang; Jiang, Yuanyuan; Zhou, Bin; He, Zhiping; Yang, Jianfeng; Hu, Yongfu; Liu, Zhenghao; Qin, Lang; Lv, Bohan; Fu, Zhongliang; Yan, Jun; Wang, Chi; Zou, Yongliao

doi:10.1016/j.asr.2021.09.001

Cited by 74 publications

(33 citation statements)

References 15 publications

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“…This study focuses on impact glasses returned from the Moon by the Chang’e-5 mission ( 21 ). The Chang’e-5 landing site is located on a relatively young [~2 billion year (Ga) old] basaltic unit ( 22 , 23 ), designated as Em4 (the fourth oldest Eratosthenian-aged mare basalt in the region), at a distance of at least ~150 km from the nearest compositionally distinct highlands and mare basalt terranes ( 24 , 25 ).…”

Section: Introductionmentioning

confidence: 99%

Constraining the formation and transport of lunar impact glasses using the ages and chemical compositions of Chang’e-5 glass beads

et al. 2022

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Impact glasses found in lunar soils provide a possible window into the impact history of the inner solar system. However, their use for precise reconstruction of this history is limited by an incomplete understanding of the physical mechanisms responsible for their origin and distribution and possible relationships to local and regional geology. Here, we report U-Pb isotopic dates and chemical compositions of impact glasses from the Chang’e-5 soil and quantitative models of impact melt formation and ejection that account for the compositions of these glasses. The predominantly local provenance indicated by their compositions, which constrains transport distances to <~150 kilometers, and the age-frequency distribution are consistent with formation mainly in impact craters 1 to 5 kilometers in diameter. Based on geological mapping and impact cratering theory, we tentatively identify specific craters on the basaltic unit sampled by Chang’e-5 that may have produced these glasses and compare their ages with the impact record of the asteroid belt.

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Section: Introductionmentioning

confidence: 99%

Constraining the formation and transport of lunar impact glasses using the ages and chemical compositions of Chang’e-5 glass beads

et al. 2022

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“…The Chang'E-5 (CE-5) was China's first lunar sample-return mission. On 1 December 2020, CE-5 landed on the Moon at 43.06 • N, 51.92 • W and collected 1731 g of lunar regolith samples by scooping and drilling [1,2]. Studying the age and composition of these samples will constrain the impact chronology of the inner Solar System and the thermal evolution of the Moon, while researching the subsurface structures in the regolith will reveal the impact gardening history of the lunar surface.…”

Section: Introductionmentioning

confidence: 99%

“…Figure 1b illustrates a low-angle illumination Lunar Reconnaissance Orbiter (LRO) Narrow-Angle Camera (NAC) image of the CE-5 landing site, showing that many large rocks (>1 m) are exposed on the southern crater wall of Xu Guangqi. Despite the success of sample collection, the drill of CE-5 only penetrated ~1 m into the regolith [16], and the majority of the samples were derived from 0-73.8 cm depth [1], smaller than the planned 2 m sampling depth [2]. In this study, we will examine the CE-5 LRPR data to study the subsurface structure and explore the possible reason for the shallow penetration depth of the CE-5 drill.…”

Section: Introductionmentioning

confidence: 99%

Shallow Regolith Structure and Obstructions Detected by Lunar Regolith Penetrating Radar at Chang’E-5 Drilling Site

2022

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This work analyzes the observations from the Lunar Regolith Penetrating Radar (LRPR) onboard Chang’E-5 to reconstruct the subsurface structure of the regolith under the lander at the drilling site. This is the first stationary Ground-Penetrating Radar (GPR) array to operate on the Moon. Imaging results of pre-drilling and post-drilling measurements show that the thickness of local regolith is larger than 2 m. Within the LRPR’s detection range, we do not find any continuous layer. Instead, irregular, high-density zones are identified in the regolith. Two of these zones are on the drilling trajectory at ~30 cm and ~70 cm, consistent with the recorded drilling process. We speculate a rock fragment from the deeper, high-density zone obstructed the drill, which led to an early termination of the drilling. Based on our interpretation of subsurface structure, we modeled the LRPR echoes using a finite-difference time-domain method. The same imaging algorithm was also applied to the simulation data. The modeled data verify our inference of the regolith structure under the lander.

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“…Figure 1 shows the overall structure of the MoonRockNet. The VGG16 [7] and U-Net are combined as the coding path of the network, while added a hybrid dilation convolution layer to the original U-Net architecture. The input of the network is a three-channel RGB image with a resolution of 512 512 u , and the output is a 1D array represent the rocks type predicted by the network.…”

Section: Mrnet (Moonrocknet)mentioning

confidence: 99%

Using MRNet to Predict Lunar Rock Categories Detected by Chang’e 5 Probe

Cui

Zou

Zhang

2022

Advances in Transdisciplinary Engineering

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China’s Chang’e 5 mission has been a remarkable success, with the Chang’e 5 lander traveling on the Oceanus Procellarum to collect images of the lunar surface. Over the past half century, people have brought back some lunar rock samples, but its quantity does not meet the need for research. Under current circumstances, people still mainly rely on the analysis of rocks on the lunar surface through the detection of lunar rover. The Oceanus Procellarum, chosen by Chang’e 5 mission, contains various kinds of rock species. Therefore, we first applied to the National Astronomical Observatories of the China under the Chinese Academy of Sciences for the Navigation and Terrain Camera (NaTeCam) of the lunar surface image, and established a lunar surface rock image data set CE5ROCK. The data set contains 100 images, which randomly divided into training, validation and test set. Experimental results show that the identification accuracy testing on convolutional neural network (CNN) models like AlexNet or MobileNet is about to 40.0%. In order to make full use of the global information in Moon images, this paper proposes the MRNet (MoonRockNet) network architecture. The encoding structure of the network uses VGG16 for feature extraction, and the decoding part adds dilated convolution and commonly used U-Net structure on the original VGG16 decoding structure, which is more conducive to identify more refined but more sparsely distributed types of lunar rocks. We have conducted extensive experiments on the established CE5ROCK data set, and the experimental results show that MRNet can achieve more accurate rock type identification, and outperform other existing mainstream algorithms in the identification performance.

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Scientific objectives and payloads of the lunar sample return mission—Chang’E-5

Cited by 74 publications

References 15 publications

Constraining the formation and transport of lunar impact glasses using the ages and chemical compositions of Chang’e-5 glass beads

Constraining the formation and transport of lunar impact glasses using the ages and chemical compositions of Chang’e-5 glass beads

Shallow Regolith Structure and Obstructions Detected by Lunar Regolith Penetrating Radar at Chang’E-5 Drilling Site

Using MRNet to Predict Lunar Rock Categories Detected by Chang’e 5 Probe

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