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AIAA science and technology Forum and Exposition, AIAA SciTech Forum 2025

作者： Johnson, Breanna J. Johnson, Kate E. Jang, Peter Steffes, Stephen R. Fritz, Matthew P. Hawke, Veronica Garcia, Joseph A. Morr, Donald E. NASA Johnson Space Center Flight Mechanics and Trajectory Design Branch HoustonTX77058 United States NASA Johnson Space Center Applied Aeroscience and CFD Branch HoustonTX77058 United States Aerodyne Industries Applied Aeroscience and CFD Branch HoustonTX77058 United States Charles Stark Draper Laboratory Navigation Algorithms and Software Space GNC Group HoustonTX77058 United States Science Technology Corporation Systems Analysis Office Mountain ViewCA United States NASA Ames Research Center NASA Systems Analysis Office Mountain ViewCA94035 United States Millennium Engineering and Integration Company ArlingtonVA22202 United States

ISBN: (数字)9781624107238

ISBN: (纸本)9781624107238

NASA is designing and building a low-cost, scalable, rapidly developed test platform to lower the barrier to entry for entry, descent, and landing (EDL) technologies. This HyperSonic Testing for Entry Platform, HyperSTEP, will enable the low-cost flight demonstration of hypersonic entry technologies, leveraging a publishable government reference design to further enable future government and industry landers. The HyperSTEP vehicle leverages a lifting body shape that was originally designed for a NASA human-class Mars mission concept vehicle, the CobraMRV. Lifting body vehicles offer increased volume efficiency and greater range control capabilities over capsules, making them an attractive class of vehicles to further develop for small to large payload return missions from the Moon, Mars, and beyond. Progress has been made in the development of the HyperSTEP vehicle in the areas of aerodynamics, aerothermodynamics, structural design and packaging, propulsion, guidance navigation and control (GN&C), decelerators (i.e., parachutes), and the thermal protection system (TPS). This paper details progress made in refining the mission concept of operations (ConOps) for the first notional missions and the development of the aerodynamic and aerothermodynamic databases, GN&C, and parachute system, as the project moves into its build and test phase. © 2025, American Institute of Aeronautics and Astronautics Inc, AIAA. All rights reserved.

关键词： NASA

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Mechanism for ice growth on the surface of a spherical water droplet

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Physical Review B 2025年第7期111卷 075426-075426页

作者： Yang Li Prachi Parashar Iver Brevik Clas Persson O. I. Malyi Mathias Boström School of Physics and Materials Science Nanchang University Nanchang 330031 China Institute of Space Science and Technology Nanchang University Nanchang 330031 China John A. Logan College Carterville Illinois 62918 USA Department of Energy and Process Engineering Norwegian University of Science and Technology NO-7491 Trondheim Norway Department of Materials Science and Engineering KTH Royal Institute of Technology SE-100 44 Stockholm Sweden Qingyuan Innovation Laboratory Quanzhou 362801 China Centre of Excellence ENSEMBLE3 Sp. z o. o. Wolczynska Str. 133 01-919 Warsaw Poland Chemical and Biological Systems Simulation Lab Centre of New Technologies University of Warsaw Banacha 2C 02-097 Warsaw Poland

The formation and growth of ice particles, particularly on the surfaces of spherical water droplets, bear profound implications for localized weather systems and global climate. Herein, we develop a theoretical framework for ice nucleation on minuscule water droplets, establishing that 10–5000nm droplets can considerably increase in volume, making a substantial contribution to ice formation within mist, fog, or even cloud systems. We reveal that the Casimir-Lifshitz (van der Waals) interaction within these systems is robust enough to stimulate both water and ice growth on the surfaces of ice-cold spherical water droplets. The significant impacts and possible detectable phenomena from the curvature are demonstrated.

关键词： Van der Waals forces

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LPI radar signal detection based on radial integration of Choi-Williams time-frequency image

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Journal of systems Engineering and Electronics 2015年第5期26卷 973-981页

作者： Yongjian Liu Peng Xiao Hongchao Wu Weihua Xiao Science and Technology on Complex Aviation Systems Simulation Laboratory Aviation University of Air Force

This paper mainly revolves the time-frequency image of low probability of intercept(LPI) radar signals and carries out research work on image features selection and extraction and recognition. Since Choi-Williams distribution(CWD) uses the exponential kernel of bilinear generalized class of time-frequency distribution, it has an excellent time-frequency aggregation. And it is suitable for detecting LPI radar signals in a low signal-to-noise ratio(SNR) condition. A radial integration method based on the integral rotating factor is proposed to detect LPI radar signals when the signals’ time-frequency image is obtained. First, the digital image processing method is used to preprocess the LPI radar signals’ time-frequency images after CWD transformation; then, the radial integration method based on the integral rotating factor is used to detect LPI radar signals in the binary images. The analytic results of real data show that the method has a good performance on detecting LPI radar signals in a low SNR condition. Additionally,the method is simple and takes less logic resources and has the potential of real-time detection of LPI radar signals.

关键词： low probability of intercept(LPI) integral rotating factor signal detection image processing

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Rate-distortion weighted SPIHT algorithm for interferometer data processing

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Journal of systems Engineering and Electronics 2011年第4期22卷 547-556页

作者： Jing Ma Jindong Fei Dong Chen Science and Technology on Space Systems Simulation Laboratory Beijing Simulation Center Beijing 100854 E R. China Institute of Telecommunication Satellite China Academy of Space Technology Beijing 100094 P. R. China

As one of the next generation imaging spectrometers, the interferential spectrometer （iS） possesses the advantages of high throughput, multi-channel and great resolution. The data of IS are produced in the spatial domain, but optical applications are in the Fourier domain. Traditional compression methods can only protect the visual quality of interferometer data in the spatial do- main but ignore the distortion in the Fourier domain. The relation between the distortion in the Fourier domain and the compression in the spatial domain is analyzed. By mathematical proof and val- idation with experiments, the relation between spatial and Fourier domains is discovered, and the significance in the Fourier domain is more important as optical path difference （OPD） increasing in the spatial domain. Based on this relation, a novel coding scheme is proposed, which can compress data in the spatial domain while reducing the distortion in the Fourier domain. In this scheme, the bit stream of the set partitioning in hierarchical trees （SPIHT） is truncated by adaptively lifting rate-distortion slopes according to the priorities of OPD based on rate-distortion optimization theory. Experimental results show that the proposed method can provide better protection of spectrum curves in the Fourier domain while maintaining a comparable visual quality in the spatial domain.

关键词： interferential spectrometer （IS） multi-spectrum compression set partitioning in hierarchical trees （SPIHT）.

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Flexible BiSel/NiO-based X-ray synapses bridging the functions of detection and memory

arXiv

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arXiv 2025年

作者： Wang, Qiao Li, Pengfei Song, Yushou Li, Jalu Xiao, Haiying Wang, Yuqing Ma, Guoliang Tsai, Hsu-Sheng Hu, Ping-An Key Laboratory of Micro-Systems and Micro-Structures Manufacturing Harbin Institute of Technology Harbin150001 China School of Chemistry and Chemical Engineering Harbin Institute of Technology Harbin150001 China College of Nuclear Science and Technology Harbin Engineering University Harbin150001 China School of Materials Science and Engineering Harbin Institute of Technology Harbin150001 China Laboratory for Space Environment and Physical Sciences Harbin Institute of Technology Harbin150001 China School of Physics Harbin Institute of Technology Harbin150001 China

Currently, the X-ray detectors are widely used in medical imaging, industrial inspection, aerospace, and other fields, as the market demand for high-efficiency, flexible, and low-power detectors is increased. Although the traditional inorganic X-ray detection materials have achieved great success and effectiveness, they have their own limitations and let alone flexibility/bendability and memory function. In this study, we present the design of a BiSeI/NiO-VNi-based X-ray synaptic detector and its application in the simulation of biological synaptic processes. Herein, the BiSeI, a quasi-1D inorganic semiconductor, stands out as an ideal choice for the X-ray detectors, especially for flexible and portable devices due to its large atomic number, large photoelectric absorption coefficient, and mechanical plasticity. Meanwhile, the NiO-based materials provide the memory function required for the intelligent detection systems. Moreover, our devices offer notable advantages in terms of low power consumption, compared with traditional X-ray detectors. The BiSeI/NiO-VNi detectors demonstrate advanced features with an ultrahigh sensitivity of 1.35×106 μC Gyair−1 cm−2, an ultralow detection limit of 34 nGy s−1, and include the paired-pulse facilitation (PPF) and the transition from short- to long-term memory, maintaining the functionality on flexible substrates. This design represents a significant step toward the development of intelligent and flexible X-ray detectors. Copyright © 2025, The Authors. All rights reserved.

关键词： X ray detectors

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Differentiable optimization of multiple freeform lenses for high-performance tilted illumination

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Optics Letters 2025年第11期50卷 3505-3508页

作者： Tang, Haisong Feng, Zexin Luo, Yi Mao, Xianglong Beijing Engineering Research Center of Mixed Reality and Advanced Display School of Optics and Photonics Beijing Institute of Technology Beijing100081 China MOE Key Laboratory of Optoelectronic Imaging Technology and Systems Beijing Institute of Technology Beijing100081 China Beijing National Research Center for Information Science and Technology Department of Electronic Engineering Tsinghua University Beijing100084 China The New Technology Laboratory of Space Photon Information Xi’an Institute of Optics and Precision Mechanics Chinese Academy of Sciences Shaanxi Xi’an710119 China

We present an optimization framework for designing multiple freeform lenses to achieve high-performance oblique illumination. The optimization process involves two steps: optimizing the irradiance distribution on an intermediate plane and fine-tuning the surface parameters to achieve the desired tilted target irradiance distribution. The framework could be used to design freeform illumination systems with an arbitrary number of lenses without significantly increasing the computational resource requirements. Leveraging differentiable ray tracing (DRT), we design a compact system with double freeform lenses, realizing a high tilt angle (TA) of 78.86◦ and an average spacing-to-height ratio (SHR) of 3.77. It holds significant potential for applications in the design of vehicle headlights, industrial vision inspection, and decoration lighting. © 2025 Optica Publishing Group. All rights, including for text and data mining (TDM), Artificial Intelligence (AI) training, and similar technologies, are reserved.

关键词： Illumination design Lens design Optical systems Ray tracing systems design Total internal reflection

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New self-calibration schemes for accelerometers in platform INS

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Journal of systems Engineering and Electronics 2015年第5期26卷 1032-1042页

作者： Hong Cai Anliang Li Yuan Cao College of Aerospace Science and Engineering National University of Defence Technology Science and Technology on Complex Land Systems Simulation Laboratory

To ensure success of precise navigation, it is necessary to carry out in-field calibration for the accelerometers in platform inertial navigation system(PINS) before a mission is *** continuous self-calibration methods are not fit for fast calibration of accelerometers because the platform misalignments have to be estimated precisely and the nonlinear coupling terms will affect accuracy. The multi-position methods with a "shape of motion" algorithm also have some existing disadvantages: High precision calibration results cannot be obtained when the accelerometer’s output data are used directly and it is difficult to optimize the calibration scheme. Focusing on this field, this paper proposes new fast self-calibration methods for the accelerometers of PINS. A data compression filter is employed to improve the accuracy of parameter estimation because it is impossible to obtain non-biased estimation for accelerometer parameters when using the "shape of motion" algorithm. Besides, continuous calibration schemes are designed and optimized by the genetic algorithm(GA) to improve the observability of parameters. simulations prove that the proposed methods can estimate the accelerometer parameter more precisely than traditional continuous methods and multi-position methods, and they are more practical to deal with urgent situations than multi-position methods.

关键词： self-calibration accelerometers data compression genetic algorithm

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Text2Earth: Unlocking Text-driven Remote Sensing Image Generation with a Global-Scale Dataset and a Foundation Model

arXiv

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arXiv 2025年

作者： Liu, Chenyang Chen, Keyan Zhao, Rui Zou, Zhengxia Shi, Zhenwei The Department of Aerospace Intelligent Science and Technology School of Astronautics The State Key Laboratory of Virtual Reality Technology and Systems Beihang University Beijing100191 China The Key Laboratory of Spacecraft Design Optimization and Dynamic Simulation Technologies Ministry of Education China Shanghai Artificial Intelligence Laboratory Shanghai200232 China Shen Yuan Honors College of Beihang University Beijing100191 China The Department of Electrical and Computer Engineering National University of Singapore Singapore117583 Singapore

Recently, generative foundation models have significantly advanced large-scale text-driven natural image generation and have become a prominent research trend across various vertical domains. However, in the remote sensing field, there is still a lack of research on large-scale text-to-image (text2image) generation technology. Existing remote sensing image-text datasets are small in scale and confined to specific geographic areas and scene types. Besides, existing text2image methods have struggled to achieve global-scale, multi-resolution controllable, and unbounded image generation. To address these challenges, this paper presents two key contributions: the Git-10M dataset and the Text2Earth foundation model. Git-10M is a global-scale image-text dataset comprising 10.5 million image-text pairs, 5 times larger than the previous largest one. The dataset contains essential resolution information and covers a wide range of geographic scenes and contains essential geospatial metadata, significantly surpassing existing datasets in both size and diversity. Building on Git-10M, we propose Text2Earth, a 1.3 billion parameter generative foundation model based on the diffusion framework to model global-scale remote sensing scenes. Text2Earth integrates a resolution guidance mechanism, enabling users to specify image resolutions. A dynamic condition adaptation strategy is proposed for training and inference to improve image generation quality. Text2Earth not only excels in zero-shot text2image generation but also demonstrates robust generalization and flexibility across multiple tasks, including unbounded scene construction, image editing, and cross-modal image generation. This robust capability surpasses previous models restricted to the basic fixed size and limited scene types. On the previous text2image benchmark dataset, Text2Earth outperfoms previous models with a significant improvement of +26.23 FID and +20.95% Zero-shot Cls-OA metric. Our project page is https://chen-y

关键词： Optical remote sensing

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New progress in geometric computing for image and video processing

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Frontiers of Computer science 2012年第6期6卷 769-775页

作者： Jinjiang LI Hanyi GE Department of Computer Science and Technology Tsinghua UniversityBeijing 100084China Science and Technology on Complex Systems Simulation Laboratory Beijing 100101China

In recent years, geometry-based image and video processing methods have aroused significant interest. This paper considers progress from four aspects： geometric characteristics and shape, geometric transformations, e... 详细信息

关键词： image video geometric computing geometric patterns embedded geometry structure

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A weakly supervised pavement crack segmentation based on adversarial learning and transformers

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Multimedia systems 2025年第3期31卷 1-21页

作者： Apedo, Yvon Tao, Huanjie School of Computer Science Northwestern Polytechnical University Xi’an People’s Republic of China Engineering and Research Center of Embedded Systems Integration (Northwestern Polytechnical University) Ministry of Education Xi’an People’s Republic of China National Engineering Laboratory for Integrated Aero-Space-Ground-Ocean Big Data Application Technology Xi’an People’s Republic of China

While pixel-level crack segmentation has demonstrated significant potential in infrastructure inspections, its reliance on detailed annotations poses challenges for widespread adoption due to the time-consuming and expensive nature of such labeling. In response, weakly supervised crack segmentation has garnered attention as it eliminates the need for pixel-level annotations. However, existing methods, primarily based on class activation maps (CAM), involve complex training processes and suffer from poor performance due to misalignment between CAM-generated labels and the true target in the image. To address these challenges, we propose a weakly supervised approach for crack segmentation that simultaneously generates synthetic crack images and performs segmentation through adversarial learning. Unlike traditional methods that rely on coarse labels, our approach leverages synthetic crack images with corresponding labels, effectively eliminating issues of misalignment and noisy pseudo-labels. Our method introduces an encoder-decoder architecture for the segmentation model, incorporating a Transformer-based Feature Enhancement module (TFE) in the encoder. This module is specifically designed to capture long-range dependencies and efficiently integrate both high- and low-level features. Additionally, the model includes a Hilo block to extract both high- and low-frequency information from the images, along with a Progressive Shrinking Decoder (PSD) to aggregate and refine adjacent feature maps. Extensive experiments were conducted, and our model achieved an ODS of 67.12% on the CrackForest dataset, 60.11% on the Crack500 dataset, and 44.80% on the AEL dataset. These results demonstrate that our model outperforms several existing weakly supervised pavement segmentation methods across these datasets.

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