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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 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
NASA NTRS2012

Evaluation of Underwater Adhesives and Friction Coatings for In Situ Attachment of Fiber Optic Sensor System for Subsea Applications

Integrity and performance monitoring of subsea pipelines and structures provides critical information for managing offshore oil and gas production operation and preventing environmentally damaging and costly catastrophic failure. Currently pipeline monitoring devices require ground assembly and installation prior to the underwater deployment of the pipeline. A monitoring device that could be installed in situ on the operating underwater structures could enhance the productivity and improve the safety of current offshore operation. Through a Space Act Agreement (SAA) between the National Aeronautics and Space Administration (NASA) Johnson Space Center (JSC) and Astro Technology, Inc. (ATI), JSC provides technical expertise and testing facilities to support the development of fiber optic sensor technologies by ATI. This paper details the first collaboration effort between NASA JSC and ATI in evaluating underwater applicable adhesives and friction coatings for attaching fiber optic sensor system to subsea pipeline. A market survey was conducted to examine different commercial ]off ]the ]shelf (COTS) underwater adhesive systems and to select adhesive candidates for testing and evaluation. Four COTS epoxy based underwater adhesives were selected and evaluated. The adhesives were applied and cured in simulated seawater conditions and then evaluated for application characteristics and adhesive strength. The adhesive that demonstrated the best underwater application characteristics and highest adhesive strength were identified for further evaluation in developing an attachment system that could be deployed in the harsh subsea environment. Various friction coatings were also tested in this study to measure their shear strengths for a mechanical clamping design concept for attaching fiber optic sensor system. A COTS carbide alloy coating was found to increase the shear strength of metal to metal clamping interface by up to 46 percent. This study provides valuable data for assessing the feasibility of developing the next generation fiber optic senor system that could be retrofitted onto existing subsea pipeline structures.

Tang, Henry H.↗
DOE OSTI2026

INR-TEM: Robust cavity detection in multifocus TEM images via implicit neural representations

When characterizing materials using transmission electron microscopy (TEM) images, detecting and quantifying small features in microstructures, such as cavities, pose significant challenges. Off-the-shelf object detection models, including YOLOv8, show considerable performance degradation, particularly when images vary in resolution and the objects of interest possess a low percentage of the total image region of interest. In this study, we introduce a novel detection pipeline that incorporates an implicit neural representation (INR)-based detection method, INR-TEM, and two-modality imaging (e.g., under-focused and over-focused images typically acquired during materials characterization) to improve object detection performance. The INR-TEM method incorporates a pixel-wise prediction principle inspired by pixel-wise centerness weighting. INR-TEM demonstrates superior robustness to resolution variability, maintaining high detection accuracy even at low image resolutions compared to YOLOv8. To leverage INR-TEM effectively in real-world two-modality characterization applications, we further integrate a two-stage motion correction pipeline designed explicitly for aligning multifocus TEM images. The alignment process, comprising keypoint (based on scale-invariant feature transform, SIFT) and intensity matching, significantly mitigates the adverse effects of perceived motion-induced image degradation during through-focal TEM imaging, directly enhancing INR-TEM’s detection capability over conventional single-focus images. Our integrated INR-TEM cavity detection framework notably improves performance across various cavity sizes, outperforming off-the-shelf YOLOv8 detections that rely on a single image modality.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
NASA NTRSDate not supplied

Science Yield Estimates and Sensitivities With the AstroPIC Integrated Photonic Coronagraph for the Habitable Worlds Observatory

The Habitable Worlds Observatory (HWO) flagship has a goal to survey ~100 of the nearest stellar systems and their habitable zones in order to detector and spectroscopically characterize ~25 potentially “Earth-like planets” (or “Exoearths”). The HWO telescope will feature a >6-m diameter aperture and a coronagraph that will suppress starlight by ten orders of magnitude to enable the detection and characterization of Earth analogues in the habitable zone. Three Exploratory Analytic Cases (EACs) are currently considering different aperture configurations for HWO including on-axis and off-axis apertures and both different hexagonal and keystone segmentation configurations. Photonic Integrated Circuits (PICs) offer a path to miniaturize traditional, bulk optics coronagraph functionality reducing risk margins and increasing mission science exoearth yields for the HWO mission. We have developed a simulation pipeline that enables evaluation of the AstroPIC photonic integrated coronagraph through to estimates mission yields. We present sensitivities to aberrations for different types of segmentation and low-order aberrations for HWO EACs demonstrating that AstroPIC is suitable for both on-axis and off-axis configurations. We perform a parametric sweep of the exoearth science yield sensitivities in terms of key coronagraph parameters including coronagraphic end-to-end throughput, inner working angle, robustness to aberrations, and bandwidth. We consider both a hybrid and a pure photonic architecture; a pure integrated photonic architecture provides the greatest potential in science yield improvements, although a hybrid PIC limited in its numbers of modes can provide complementary science to a traditional, bulk-optic coronagraph and increasing the estimated science yield when operated jointly.

Photonics↗
DOE OSTI2025

Discovery, characterization, and application of chromosomal integration sites in the hyperthermophilic archaeon Sulfolobus islandicus

Sulfolobus islandicus , an emerging archaeal model organism, offers unique advantages for metabolic engineering and synthetic biology applications owing to its ability to thrive in extreme environments. Although several genetic tools have been established for this organism, the lack of well-characterized chromosomal integration sites has limited its potential as a cellular factory. Here, in this work, we systematically identified and characterized 13 artificial CRISPR RNAs targeting eight integration sites in S. islandicus using the CRISPR-COPIES pipeline and a multi-omics-informed computational workflow. We leveraged the endogenous CRISPR-Cas system to integrate the reporter gene lacS and validated heterologous expression through a β-galactosidase assay, revealing significant positional effects. As a proof of concept, we utilized these sites to genetically manipulate lipid ether composition by overexpressing glycerol dibiphytanyl glycerol tetraether (GDGT) ring synthase B (GrsB). This study expands the genetic toolbox for S. islandicus and advances its potential as a robust platform for archaeal synthetic biology and industrial biotechnology.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS2012

Enabling Earth Science Through Cloud Computing

Cloud Computing holds tremendous potential for missions across the National Aeronautics and Space Administration. Several flight missions are already benefiting from an investment in cloud computing for mission critical pipelines and services through faster processing time, higher availability, and drastically lower costs available on cloud systems. However, these processes do not currently extend to general scientific algorithms relevant to earth science missions. The members of the Airborne Cloud Computing Environment task at the Jet Propulsion Laboratory have worked closely with the Carbon in Arctic Reservoirs Vulnerability Experiment (CARVE) mission to integrate cloud computing into their science data processing pipeline. This paper details the efforts involved in deploying a science data system for the CARVE mission, evaluating and integrating cloud computing solutions with the system and porting their science algorithms for execution in a cloud environment.

science data system↗
NASA NTRS1981

Applications study of advanced power generation systems utilizing coal-derived fuels. Volume 1: Executive summary

The technology status of phosphoric acid and molten carbon fuel cells, combined gas and steam turbine cycles, and magnetohydrodynamic energy conversion systems was assessed and the power performance of these systems when operating with medium-Btu fuel gas whether delivered by pipeline to the power plant or in an integrated mode in which the coal gasification process and power system are closely coupled as an overall power plant was evaluated. Commercially available combined-cycle gas turbine systems can reach projected required performance levels for advanced systems using currently available technology. The phosphoric acid fuel cell appears to be the next most likely candidate for commercialization. On pipeline delivery, the systems efficiency ranges from 40.9% for the phosphoric acid fuel cell to 63% for the molten carbonate fuel cell system. The efficiencies of the integrated power plants vary from approximately 39-40% for the combined cycle to 46-47% for the molden carbonate fuel cell systems. Conventional coal-fired steam stations with flue-gas desulfurization have only 33-35% efficiency.

Robson, F. L.↗
NASA NTRS2005

Automated generation of image products for Mars Exploration Rover Mission tactical operations

This paper will discuss, from design to implementation, the methodologies applied to MIPL's automated pipeline processing as a 'system of systems' integrated with the MER GDS. Overviews of the interconnected product generating systems will also be provided with emphasis on interdependencies, including those for a) geometric rectificationn of camera lens distortions, b) generation of stereo disparity, c) derivation of 3-dimensional coordinates in XYZ space, d) generation of unified terrain meshes, e) camera-to-target ranging (distance) and f) multi-image mosaicking.

products↗
DOE OSTI2025

Hypermut 3: identifying specific mutational patterns in a defined nucleotide context that allows multistate characters

Abstract Motivation The detection of APOBEC3F- and APOBEC3G-induced mutations in virus sequences is useful for identifying hypermutated sequences. These sequences are not representative of viral evolution and can therefore alter the results of downstream sequence analyses if included. We previously published the software Hypermut, which detects hypermutation events in sequences relative to a reference. Two versions of this method are available as a webtool. Neither of these methods consider multistate characters or gaps in the sequence alignment. Results Here, we present an updated, user-friendly web and command-line version of Hypermut with functionality to handle multistate characters and gaps in the sequence alignment. This tool allows for straightforward integration of hypermutation detection into sequence analysis pipelines. As with the previous tool, while the main purpose is to identify G to A hypermutation events, any mutational pattern and context can be specified. Availability and implementation Hypermut 3 is written in Python 3. It is available as a command-line tool at https://github.com/MolEvolEpid/hypermut3 and as a webtool at https://www.hiv.lanl.gov/content/sequence/HYPERMUT/hypermutv3.html.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

PROTOCALC, a W -band Polarized Calibrator for Cosmic Microwave Background Telescopes: Application to Simons Observatory and CLASS

Current- and next-generation cosmic microwave background (CMB) experiments will measure polarization anisotropies with unprecedented sensitivities. The need for high precision in these measurements underscores the importance of gaining a comprehensive understanding of instrument properties, with a particular emphasis on the study of the beam properties, and especially their polarization characteristics and the measurement of the polarization angle. In this context, a major challenge lies in the scarcity of millimeter polarized astrophysical sources with sufficient brightness and calibration knowledge to meet the stringent accuracy requirements of future CMB missions. This led to the development of a drone-borne calibration source designed for the frequency band centered on approximately 90 GHz, matching a commonly used channel in ground-based CMB measurements. The Prototype Calibrator for Cosmology, PROTOCALC, has undergone thorough in-lab testing, and its properties have been subsequently modeled through simulation software integrated into the standard Simons Observatory analysis pipeline. Moreover, the PROTOCALC system has been tested in the field, having been deployed twice on calibration campaigns with CMB telescopes in the Atacama Desert. The data collected constrain the roll angle of the source with a statistical accuracy of 0$^°_•$045.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2026

AMVOS: Additive Manufacturing Video Object Segmentation Dataset

This dataset provides labeled video frames from four additive manufacturing (AM) processes for video object segmentation (VOS) tasks. It contains 90 video segments comprising 900 individually annotated frames across five AM datasets: laser hot-wire directed energy deposition (LHW-DED), tungsten inert gas wire arc additive manufacturing (TIG-WAAM), plasma arc welding (PAW), visible-light polymer extrusion (visPolymer), and near-infrared polymer extrusion (irPolymer). Each video segment consists of 10 contiguous frames with corresponding pixel-level object instance annotations. Depending on the process, two of four object classes are labeled per frame: Melt Pool, Feed Wire, Nozzle, or Material. Raw frames are provided as .jpg files and annotations as palettized .png files. The dataset follows the directory structure of established VOS benchmarks (DAVIS, YouTube-VOS, MOSE), enabling direct integration into VOS model training and evaluation pipelines for foundation model fine-tuning, domain adaptation, or zero-shot performance benchmarking. Data was collected at Oak Ridge National Laboratory's Manufacturing Demonstration Facility.

Wetzel, Jon [ORNL]↗
NASA NTRS2000

Parallel integrated frame synchronizer chip

A parallel integrated frame synchronizer which implements a sequential pipeline process wherein serial data in the form of telemetry data or weather satellite data enters the synchronizer by means of a front-end subsystem and passes to a parallel correlator subsystem or a weather satellite data processing subsystem. When in a CCSDS mode, data from the parallel correlator subsystem passes through a window subsystem, then to a data alignment subsystem and then to a bit transition density (BTD)/cyclical redundancy check (CRC) decoding subsystem. Data from the BTD/CRC decoding subsystem or data from the weather satellite data processing subsystem is then fed to an output subsystem where it is output from a data output port.

Ghuman, Parminder Singh↗
NASA NTRS2011

Automatic Tie Pointer for In-Situ Pointing Correction

The MARSAUTOTIE program generates tie points for use with the Mars pointing correction software "In-Situ Pointing Correction and Rover Microlocalization," (NPO-46696) Soft ware Tech Briefs, Vol. 34, No. 9 (September 2010), page 18, in a completely automated manner, with no operator intervention. It takes the place of MARSTIE, although MARSTIE can be used to interactively edit the tie points afterwards. These tie points are used to create a mosaic whose seams (boundaries of input images) have been geometrically corrected to reduce or eliminate errors and mis-registrations. The methods used to find appropriate tie points for use in creating a mosaic are unique, having been designed to work in concert with the "MARSNAV" program to be most effective in reducing or eliminating geometric seams in a mosaic. The program takes the input images and finds overlaps according to the nominal pointing. It then finds the most interesting areas using a scene activity metric. Points with higher scene activity are more likely to correlate successfully in the next step. It then uses correlation techniques to find matching points in the overlapped image. Finally, it performs a series of steps to reduce the number of tie points to a manageable level. These steps incorporate a number of heuristics that have been devised using experience gathered by tie pointing mosaics manually during MER operations. The software makes use of the PIG library as described in "Planetary Image Geometry Library" (NPO-46658), NASA Tech Briefs, Vol. 34, No. 12 (December 2010), page 30, so it is multi-mission, applicable without change to any in-situ mission supported by PIG. The MARSAUTOTIE algorithm is automated, so it requires no user intervention. Although at the time of this reporting it has not been done, this program should be suitable for integration into a fully automated mosaic production pipeline.

Deen, Robert G/↗
NASA NTRSDate not supplied

Transitioning a Flexible and Scalable Satellite Ground Station Observation Network (GSON) Framework to an Operational Environment

Obtaining accurate and timely satellite observations is of paramount importance in fields like disaster management, weather diagnoses/forecasting, and Earth Sciences remote sensing. Stored mission data (SMD), from low Earth orbiting (LEO) satellite sensors, provides important observations for these fields and applications, however data access to SMD can be delayed from one and half hours to three hours from the time the observations were made. This data latency poses a significant impact on data product optimal use. We developed a Ground Station Observation Network (GSON) that utilizes commercial ground station as a service (GSaaS) providers to acquire low latency direct broadcast (DB) data from AQUA, SNPP, and JPSS-1 satellites using antennas located in strategic locations around the world. We will discuss techniques to improve the deployment efficiency and code reliability and quality of the GSON framework. Topics include right-sizing and containerization of the code to facilitate integration and adaptation with continuous delivery (CD) pipeline, locating non-code assets in referenceable repositories separated from code, adaptation of pipelines as code and simplification of CD, intersecting with code quality tests and checks as part of the pipeline execution and deployment, and establishing distributed repositories, registries, and system identities in a way that mitigates compromise to the CD pipeline. These techniques enable deployment of processing systems that are both highly specific but also dynamically modifiable. This new class of system allows for a flexible and scalable deployment while avoiding the “black box” issues that can plague large system deployments.

cluster↗
NASA NTRS2023

The Case for Solar Full-disk Spectral Diagnostics: Chromosphere to Corona

In the context of the recent call for white papers for the Decadal Survey for Solar and Space Physics (Heliophysics) 2024–2033, we present the argument that spatially-resolved spectral diagnostics over the full solar disk should be made a high-priority goal in Heliophysics and lead to the development of a mission concept that has the potential to become a cornerstone of the Heliophysics System Observatory (HSO). We claim that a mission providing consistent full-disk sampling of plasma properties (Doppler-shifts, non-thermal velocities, electron densities, elemental composition, etc.) of the chromosphere-corona system at the dynamic timescales of solar eruptive phenomena will revolutionize the field by adding the spectral diagnostics capability to the highly successful concept of full-disk imaging, everywhere, all the time, represented by the Solar Dynamics Observatory (SDO). We argue for it to be developed by the end of the current Decadal Survey cycle around the lessons learned from spectroscopic missions in the current NASA development pipeline, that include innovative strategies for faster integration of large fields-of-view, and comprehensive temperature coverage.

Sun↗
NASA NTRS2018

NASA Pilot-Engaged Expert Response Using IBM Watson Technology: Prototype Evaluation of Knowledge Retrieval System

NASA Langley Research Center and IBM have been investigating the use of IBM Watson technology in aerospace research and development. One application of Watson technology is the Pilot-Engaged Expert Response (PEER) use case. The PEER system is envisioned as an in-cockpit advisor that will act as a source of situationally-relevant information for pilots and other flight crew members to assist in decision making about real-time events and situations that arise in the course of aircraft operations. PEER will make available vast stores of knowledge and information quickly and directly, putting important informational resources where they are needed most. IBM has worked with NASA to develop an architecture and articulate a roadmap for the development of the PEER system. That vision is built around Watson Discovery Advisor (WDA) software solution, derived from IBM's Jeopardy!-winning automatic question answering system. PEER makes use of WDA's sophisticated question-answering capabilities as its core, adding important User Interface components and other customizations for the cockpit environment, including communication with flight systems and other external data sources. The development plan for PEER includes four development stages, with the current project constituting the first phase. In this project, a prototype instance of PEER was successfully adapted to the aviation domain, enabling users to ask questions about aviation topics and receive useful and accurate answers to these questions. Major tasks accomplished include the development of procedures for domain adaptation through automatic lexicon extraction from domain glossaries; generation of question-answer training data which was used to train the system; and assessment of the effectiveness of domain adaptation, which showed a dramatic improvement in the ability of the PEER system to answer domain-relevant questions. In addition, the vision for the PEER system was pushed forward by the articulation of a plan for the automatic enhancement of question-answering with contextual information. This initial phase focused on two main goals: 1) the targeted domain adaptation of the underlying WDA system to the aviation domain; and, 2) the design of the software systems needed to leverage flight-contextual data. Domain adaptation of the WDA system proceeds via three main activities: Domain data ingestion, lexical customization and model training. A textual corpus consisting of 1,147 individual documents with more than 7.5 million words of text was ingested into the system and this served as the basis of all further development. A domain lexicon of over 3,500 aviation-domain terms was semi-automatically generated from domain documents and used to train the system. In addition, a set of over 500 question-answer (QA) pairs relevant to the PEER use case was developed; these were used to train and assess the system. These important first steps established the basis for the PEER system. In addition, steps were taken towards the integration of the PEER system into the cockpit environment with the development of a functional design for the Contextual Data Augmentation (CDA) subsystem. This subsystem brings to bear contextual data to improve system responses. It has three main submodules: the Contextual Data Collection module, the Contextual Data Selection module, and the Contextual QA Augmentation module. These modules form a processing pipeline that addresses the problems associated with automatically integrating information from external resources into the knowledge-retrieval mechanism.

Machine learning↗
DOE OSTI2024

Hydrogen Generation and Industrial Heat Opportunities for Nuclear Plants in the Gulf Coast

The United States (U.S.) nuclear-generation fleet stands as a critical national strategic asset, playing a pivotal role in achieving climate goals. Operating on light-water reactor (LWR) technologies, this fleet provides the largest share of U.S. carbon-free electrical generation, ensuring 24/7 clean-energy stability. With a proven track record of reliability while operating at high-capacity factors, consistently above 90%, the existing nuclear fleet serves as a cornerstone for sustainable energy. The Department of Energy’s (DOE’s) Light Water Reactor Sustainability (LWRS), Flexible Plant Operations and Generation pathway addresses U.S. nuclear power plant (NPP) grid integration challenges in the face of evolving energy landscapes. Research at Idaho National Laboratory (INL) highlights the potential synergy between high-temperature steam-electrolysis (HTSE) technology and nuclear steam and electricity during periods of high renewable grid penetration. Large-scale nuclear-integrated hydrogen production through HTSE presents significant potential for decarbonizing such energy-intensive sectors as oil refining, petrochemicals, ammonia, and fertilizers. The strategic advantage lies in the nuclear sector’s capability to deliver clean electrical and/or steam output during periods of low demand. Nuclear-produced hydrogen—with its ability to provide high-purity clean H 2 well below the national standard of 1 kg of CO 2 per kg of H 2 —represents a breakthrough methodology. This emphasizes the crucial role NPPs can fill in addressing the increasing need for clean hydrogen, establishing them as essential contributors to decarbonization. This report specifically delves into hydrogen-generation opportunities from the U.S. Gulf Coast region. This study aims to assess NPP capabilities for hydrogen production and to identify practical nearby industrial and pipeline-operator off-takers for nuclear-integrated hydrogen production as well as to present some specific case-study analysis showing the conditions under which nuclear hydrogen production and sale can be profitable. Also considered in this report is preliminary analysis of nuclear-heat opportunities accessible near Waterford NPP via transportation of hypothetical steam pipelines and heat-exchange equipment.

08 HYDROGEN↗
NASA NTRS2008

Orchestrator Telemetry Processing Pipeline

Orchestrator is a software application infrastructure for telemetry monitoring, logging, processing, and distribution. The architecture has been applied to support operations of a variety of planetary rovers. Built in Java with the Eclipse Rich Client Platform, Orchestrator can run on most commonly used operating systems. The pipeline supports configurable parallel processing that can significantly reduce the time needed to process a large volume of data products. Processors in the pipeline implement a simple Java interface and declare their required input from upstream processors. Orchestrator is programmatically constructed by specifying a list of Java processor classes that are initiated at runtime to form the pipeline. Input dependencies are checked at runtime. Fault tolerance can be configured to attempt continuation of processing in the event of an error or failed input dependency if possible, or to abort further processing when an error is detected. This innovation also provides support for Java Message Service broadcasts of telemetry objects to clients and provides a file system and relational database logging of telemetry. Orchestrator supports remote monitoring and control of the pipeline using browser-based JMX controls and provides several integration paths for pre-compiled legacy data processors. At the time of this reporting, the Orchestrator architecture has been used by four NASA customers to build telemetry pipelines to support field operations. Example applications include high-volume stereo image capture and processing, simultaneous data monitoring and logging from multiple vehicles. Example telemetry processors used in field test operations support include vehicle position, attitude, articulation, GPS location, power, and stereo images.

Powell, Mark↗
DOE OSTI2025

Improved guided-wave acoustic defect detection and localization in pipes under varying temperature conditions using deep learning

Early defect detection in pipelines is critical across industries, particularly in the oil and gas sector, where failures result in significant maintenance costs and operational disruptions. Acoustic guided-wave techniques are widely used for nondestructive evaluation of pipeline defects due to their long-distance propagation capability. However, environmental variations, sensitivity limitations, and complex signal interpretation challenges limit the effectiveness of traditional signal processing approaches with guided-wave signals. Recent advances in deep learning methods have demonstrated remarkable success in solving complex real-world problems in many fields. In particular, deep-learning-based signal processing holds substantial promise to overcome limitations and challenges of conventional signal processing. This study presents a deep learning framework for pipeline inspection using acoustic guided-wave signals under temperature varying environments. The proposed framework employs a dual-path one-dimensional convolutional autoencoder that combines defect detection, localization, and temperature prediction functions. The proposed system utilizes multi-mode and broadband acoustic waves with an optimized number of sensors that provide high accuracy while retaining practical simplicity. Experimental validation is performed on a carbon steel pipe. The results indicate exceptional defect detection accuracy and precise defect localization with a mean absolute error of 66 mm. The proposed technique also predicts the effective average temperature of the pipe with a mean absolute error of 0.2°C. Comparative analysis shows superior performance of the proposed method over a traditional method previously developed by the authors' team. These results highlight the potential of integrating deep learning methods into guided-wave pipeline inspection systems to improve reliability under varying environmental conditions.

42 ENGINEERING↗