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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 433 records · Page 24
All sourcesNASA NTRSDOE OSTI
NASA NTRS2018

Apodized Pupil Lyot Coronagraphs Designs for Future Segmented Space Telescopes

A coronagraphic starlight suppression system situated on a future flagship space observatory offers a promising avenue to image Earth-like exoplanets and search for biomarkers in their atmospheric spectra. One NASA mission concept that could serve as the platform to realize this scientific breakthrough is the Large UV/Optical/IR Surveyor (LUVOIR). Such a mission would also address a broad range of topics in astrophysics with a multi-wavelength suite of instruments. The apodized pupil Lyot coronagraph (APLC) is one of several coronagraph design families that the community is assessing as part of NASAs Exoplanet Exploration Program Segmented aperture coronagraph design and analysis (SCDA) team. The APLC is a Lyot-style coronagraph that suppresses starlight through a series of amplitude operations on the on-axis eld. Given a suite of seven plausible segmented telescope apertures, we have developed an object-oriented software toolkit to automate the exploration of thousands of APLC design parameter combinations. This has enabled us to empirically establish relationships between planet throughput and telescope aperture geometry, inner working angle, bandwidth, and contrast level.In parallel with the parameter space exploration, we have investigated several strategies to improve the robust-ness of APLC designs to fabrication and alignment errors. We also investigate the combination of APLC withwavefront control or complex focal plane masks to improve inner working angle and throughput. Preliminaryscientic yield evaluations based on design reference mission simulations indicate the APLC is a very competitiveconcept for surveying the local exoEarth population with a mission like LUVOIR.

coronagraphic starlight suppression system↗
NASA NTRS2018

The Segmented Aperture Interferometric Nulling Testbed (SAINT) III: Control Systems Analysis and Preliminary Results

This work presents a detailed current performance analysis for the telescope, pointing, and coronagraph com- ponent subsystems of the Segmented Aperture Interferometric Nulling Testbed (SAINT). The project pairs an active segmented mirror with the Visible Nulling Coronagraph (VNC) towards demonstrating capabilities for the future space observatories needed to directly detect and characterize Earth-sized worlds around nearby stars. We describe approaches to optimize subsystem wavefront sensing and control parameters, summarizing relevant scal- ing relations between these parameters, residual errors, and observed contrast measurements. Preliminary results from diagnostic testing under various control states are presented along with intermediate contrast measurements towards demonstrating the full system.

Hicks, Brian A.↗
NASA NTRSDate not supplied

Segmentation of Lightweight Ablator Micro-Tomography Using Deep Learning

Ablative thermal protection systems (TPS) are essential for high speed entry of planetary atmospheres, such as those of Earth and Mars. Upon entry the kinetic energy of the spacecraft is converted into thermal energy, leading to high heat fluxes at the wall of the craft. Because of this extreme heating, a robust ablative TPS material must be selected. A common material selection today is phenolic-impregnated carbon ablator (PICA), which is a low-density carbon material known for producing dust that is not suitable to a cleanroom environment. To mitigate dust created by a PICA heatshield, a silicone-based spray called NuSil is applied to the surface of the TPS, creating PICA-NuSil (PICA-N). PICA-N has been observed to have a different material response from regular PICA during high enthalpy flow testing, producing surface temperatures up to 200K less than those seen for PICA [1]. To better understand this phenomenon, it is critical that robust methods of PICA-N material characterization are developed. The purpose of this project is to investigate Object Research Systems’ (ORS) Dragonfly deep learning tools as a means of accurately segmenting and characterizing PICA-N. Systematic testing of this software has shown that Dragonfly deep learning tools have strong potential for accurate segmentation/ characterization of PICA-N and other TPS materials.

Micro-tomography↗
NASA NTRS1994

Segmented Ion Engine Operation and Performance

The continuing trend toward smaller and smaller planetary spacecraft to enable the use of smaller, less expensive launch vehicles has motivated an examination of new approaches to reduce the size and mass of xenon ion propulsion systems for these new spacecraft. A system is proposed which is based on the use of a single 4x15-cm segmented ion thruster operated from a single internally redundant power processing unit. An engine input power throttling range of 380 to 4640 W is projected. The design and operation over a power range of 600 to 2400 W of a laboratory model segmented ion engine equipped with carbon-carbon grids is presented. There appear to be no problems associated with interactions with multiple ion sources operating from a single set of high voltage power supplies, neutralization of multiple ion sources from a single centrally located neutralizer, or operation of flat, thin carbon-carbon grids.

ion↗
NASA NTRS2021

Results From The Laboratory Demonstration Of A PIAACMC Coronagraph With A Segmented Aperture

The phase-induced amplitude apodization complex mask coronagraph (PIAACMC) provides high throughput and small inner working angle with little loss in image quality. Coronagraph compatibility with segmented apertures is essential for the success of habitable planet characterization with future large aperture space telescopes, such as the Large UV/Optical/Infrared (LUVOIR) and HabEx telescope mission concepts. The PIAACMC is compatible with such segmented telescope apertures with little loss of performance. We report the contrast and other performance results of a PIAACMC coronagraph with a LUVOIR-like pupil mask assembled and tested in a vacuum chamber at the JPL high contrast imaging testbed (HCIT). The goals of the demonstration were to achieve 1e-9 mean contrast over a semi-annular field of view from 2 λ/D to 8 λ/D, first with monochromatic light at 650nm, and then over a 10% spectral bandwidth. In addition, the measurement of jitter and its effect on PIAACMC performance will be discussed. As the success of electric field conjugation (EFC) to achieve best contrast on the testbed is dependent upon a diffraction model of the coronagraph, we will also discuss variations of the testbed and its diffraction model with the PIAACMC design, including suspected sources of knowledge error in the EFC diffraction model.

Wilson, Daniel↗
NASA NTRS2022

Bayesian Deep Learning for Segmentation for Autonomous Safe Planetary Landing

Hazard detection is critical for enabling autonomous landing on planetary surfaces. Current state-of-the-art methods leverage traditional computer vision approaches to automate the identification of safe terrain from input digital elevation models (DEMs). However, performance for these methods can degrade for input DEMs with increased sensor noise. In the last decade, deep learning techniques have been developed for various applications. Nevertheless, their applicability to safety-critical space missions has often been limited due to concerns regarding their outputs’ reliability. In response to these limitations, this paper proposes an application of the Bayesian deep learning segmentation method for hazard detection. The developed approach enables reliable, safe landing site detection by i) generating simultaneously a safety prediction map and its uncertainty map via Bayesian deep learning and semantic segmentation, and ii) using the uncertainty map to filter out the uncertain pixels in the prediction map so that the safe site identification is performed only based on the certain pixels (i.e., pixels for which the model is certain about its safety prediction). Experiments are presented with simulated data based on a Mars HiRISE digital terrain model by varying uncertainty threshold and noise levels to demonstrate the performance of the proposed approach.

Kento Tomita↗
DOE OSTI2025

Effective Defect Detection Using Instance Segmentation for NDI

Ultrasonic testing is a common Non-Destructive Inspection (NDI) method used in aerospace manufacturing. However, the complexity and size of the ultrasonic scans make it challenging to identify defects through visual inspection or machine learning models. Using computer vision techniques to identify defects from ultrasonic scans is an evolving research area. In this study, we used instance segmentation to identify the presence of defects in the ultrasonic scan images of composite panels that are representative of real components manufactured in aerospace. We used two models based on Mask- RCNN (Detectron 2) and YOLO 11 respectively. Additionally, we implemented a simple statistical pre-processing technique that reduces the burden of requiring custom-tailored pre-processing techniques. Our study demonstrates the feasibility and effectiveness of using instance segmentation in the NDI pipeline by significantly reducing data pre-processing time, inspection time, and overall costs.

computer vision techniques↗
DOE OSTI2026

Synergistic Evolution of Segmental Motion and Cooperative Relaxation within the Amorphous Phase of Organic Mixed Ionic-Electronic Conductors

Organic mixed ionic-electronic conductors (OMIECs) facilitate a variety of electrochemical processes and feature a heterogeneous microstructure composed of both crystalline and amorphous phases. However, structural evolution in amorphous regions during electrochemical doping remains poorly understood, limiting our understanding of mixed conduction mechanisms. Here, in this work, we develop operando chip calorimetry to probe amorphous phase evolution in poly­(3,4-ethylenedioxythiophene):poly­(styrenesulfonate) (PEDOT:PSS) under swelling and electrochemical (de)­doping. Our results reveal that amorphous regions providing ionic transport pathways and those within electronic transport channels undergo heterogeneous, yet synergistic, evolution during electrochemical modulation. The cooperative interplay between segmental motion and relaxation maintains ionic conductivity and intergrain electronic transport upon electrowetting and doping, while facilitating efficient ion hopping and adaptable chain conformations during dedoping. Such synergies are more pronounced in loose structures featuring a fibrillar morphology, which exhibit lower glass transition temperatures (T g ) and higher fragility (m). High-throughput robotic screening further establishes a strong correlation between elevated m/T g ratios and enhanced mixed conduction. These findings elucidate the role of the amorphous phase in the synthesis of OMIECs and underscore the potential of operando chip calorimetry in uncovering structure–property relationships in electroactive polymers.

amorphous phase↗
DOE OSTI2025

Block segmentation in feature space for realtime object detection in high granularity images

Computer vision has applications in object detection, image recognition and classification, and object tracking. One of the challenges of computer vision is the presence of useful information at multiple distance scales. Filtering techniques may sacrifice details at small scales in order to prioritize the analysis of large-scale features of the image. We present a strategy for coarse-graining multidimensional data while maintaining fine-grained detail for subsequent analysis. The algorithm is based on fixed-size block segmentation in the feature space. We apply this strategy to solve the long-standing challenge of detecting particle trajectories at the Large Hadron Collider in real time.

Computer vision↗
DOE OSTI2024

Imaging and Segmenting Grains and Subgrains Using Backscattered Electron Techniques

We present two new methods of processing data from backscattered electron signals in a scanning electron microscope to image grains and subgrains. The first combines data from multiple backscattered electron images acquired at different specimen geometries to (1) better reveal grain boundaries in recrystallized microstructures and (2) distinguish between recrystallized and unrecrystallized regions in partially recrystallized microstructures. The second utilizes spherical harmonic transform indexing of electron backscatter diffraction patterns to produce high angular resolution orientation data that enable the characterization of subgrains. Subgrains are produced during high-temperature plastic deformation and have boundary misorientation angles ranging from a few degrees down to a few hundredths of a degree. Here, we also present an algorithm to automatically segment grains from combined backscattered electron image data or grains and subgrains from high angular resolution electron backscatter diffraction data. Together, these new techniques enable rapid measurements of individual grains and subgrains from large populations.

36 MATERIALS SCIENCE↗
DOE OSTI2025

A Region-Growing Segmentation Approach to Delineating Timberline from Satellite-Derived Tree Fractional Cover Products

Timberline marks the transitions from continuous forests to sparse forests and tundra landscapes. As the spatial distribution and dynamics of timberline are closely associated with regional energy and carbon balance, mapping timberline is important to a wide range of environmental and ecological studies. However, current timberline delineation approaches remain under-developed. We proposed an automatic timberline delineation method based on a seeded region-growing segmentation technique and satellite-derived products of tree fractional cover. We applied our approach to the West Siberian Plain and Alaska treeline regions as defined by the Circumpolar Arctic Vegetation Map. The results demonstrate the effectiveness of the proposed method for the accurate delineation of the timberlines that spatially align well with very-high-resolution satellite images. Based on the delineated timberlines, we find regional-scale tree encroachment to be not as substantial as previously reported. The proposed approach can be applied to understanding climate-induced forest responses and inform forest management practices.

Circumpolar Arctic Vegetation Map↗
NASA NTRS2005

NASA's Global Precipitation Mission Ground Validation Segment

NASA is designing a Ground Validation Segment (GVS) as one of its contributions to the Global Precipitation Measurement (GPM) mission. The GPM GVS provides an independent means for evaluation, diagnosis, and ultimately improvement of the GPM spaceborne measurements and precipitation products. NASA's GPM GVS concept calls for a combination of direct observations executed within a Multidimensional Observing Volume (MOV) and model-based analyses executed by a Satellite Simulator Model (SSM). The MOV consists of ground-based instruments that measure local surface and atmospheric properties required for GPM validation. The SSM utilizes MOV measurements in a forward numerical model. The goal of the SSM forward modeling is calculation of the following properties: top-of-atmosphere microwave radiative quantities to within sensor noise of those measured by the GPM Core Satellite, precipitation quantities identical to those generated by the standard GPM precipitation retrieval algorithms, and quantitative/objective error estimates of both sets of quantities. At present, the GVS is in the early design stage and various scenarios have been generated to assess how it will be used in the GPM era. The GPM GVS will be operational in the year prior to the launch of the GPM core satellite, which has a launch date scheduled for December 2010.

GVS (GROUND VALIDATION SEGMENT)↗
NASA NTRS2006

Performance of Dispersed Fringe Sensor in the Presence of Segmented Mirror Aberrations - Modeling and Simulations

Wavefront aberrations will lower the DFS fringe visibility and DFS signal SNR. The specific effect of wavefront aberration on DFS depends on the aberration type. Due to the "pixel spatial filter" effect the extracted DFS signal can tolerate moderate amount of wavefront aberrations..By averaging piston detection results from multiple traces extracted from fringe images DFS can further increase its robustness against wavefront aberration. Line-of-sight jitter can cause significant loss of fringe visibility will affect more on the aberrated system..Modeling results have shown that gravity sag on the JWST segment mirror during I&T will lower the DHS fringe visibility by factor of 2-3X and lower the DHS signal intensity by factor of approx.5X. Under gravity sag the RMS DHS detection error approx. 100 nm.

James Webb Space Telescope (JWST)↗