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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 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
NASA NTRS2024

The Thermal Structure and Composition of Jupiter's Great Red Spot From JWST/MIRI

Jupiter's Great Red Spot (GRS) was mapped by the James Webb Space Telescope (JWST)/Mid-Infrared Instrument (4.9–27.9 μm) in July and August 2022. These observations took place alongside a suite of visual and infrared observations from; Hubble, JWST/NIRCam, Very Large Telescope/VISIR and amateur observers which provided both spatial and temporal context across the jovian disc. The stratospheric temperature structure retrieved using the NEMESIS software revealed a series of hot-spots above the GRS. These could be the consequence of GRS-induced wave activity. In the troposphere, the temperature structure was used to derive the thermal wind structure of the GRS vortex. These winds were only consistent with the independently determined wind field by JWST/NIRCam at 240 mbar if the altitude of the Hubble-derived winds were located around 1,200 mbar, considerably deeper than previously assumed. No enhancement in ammonia was found within the GRS but a link between elevated aerosol and phosphine abundances was observed within this region. North-south asymmetries were observed in the retrieved temperature, ammonia, phosphine and aerosol structure, consistent with the GRS tilting in the north-south direction. Finally, a small storm was captured north-west of the GRS that displayed a considerable excess in retrieved phosphine abundance, suggestive of vigorous convection. Despite this, no ammonia ice was detected in this region. The novelty of JWST required us to develop custom-made software to resolve challenges in calibration of the data. This involved the derivation of the “FLT-5” wavelength calibration solution that has subsequently been integrated into the standard calibration pipeline.

Jake Harkett↗
NASA NTRS1990

Hanging drop crystal growth apparatus

This invention relates generally to control systems for controlling crystal growth, and more particularly to such a system which uses a beam of light refracted by the fluid in which crystals are growing to detect concentration of solutes in the liquid. In a hanging drop apparatus, a laser beam is directed onto drop which refracts the laser light into primary and secondary bows, respectively, which in turn fall upon linear diode detector arrays. As concentration of solutes in drop increases due to solvent removal, these bows move farther apart on the arrays, with the relative separation being detected by arrays and used by a computer to adjust solvent vapor transport from the drop. A forward scattering detector is used to detect crystal nucleation in drop, and a humidity detector is used, in one embodiment, to detect relative humidity in the enclosure wherein drop is suspended. The novelty of this invention lies in utilizing angular variance of light refracted from drop to infer, by a computer algorithm, concentration of solutes therein. Additional novelty is believed to lie in using a forward scattering detector to detect nucleating crystallites in drop.

Naumann, Robert J.↗
NASA NTRS1989

Method and apparatus for detecting laminar flow separation and reattachment

The invention is a method and apparatus for detecting laminar flow separation and flow reattachment of a fluid stream by simultaneously sensing and comparing a plurality of output signals, each representing the dynamic shear stress at one of an equal number of sensors spaced along a straight line on the surface of an airfoil or the like that extends parallel to the fluid stream. The output signals are concurrently compared to detect the sensors across which a reversal in phase of said output signal occurs, said detected sensors being in the region of laminar separation or reattachment. The novelty in this invention is the discovery and use of the phase reversal phenomena to detect laminar separation and attachment of a fluid stream from any surface such as an airfoil supported therein.

Stack, John P.↗
NASA NTRS1995

Method and Apparatus for Measuring Fluid Flow

The invention is a method and apparatus for monitoring the presence, concentration, and the movement of fluids. It is based on utilizing electromagnetic measurements of the complex permittivity of the fluids for detecting and monitoring the fluid. More particularly the apparatus uses one or more microwave probes which are placed at the locations where the measurements are to be made. A radio frequency signal is transmitted to the probe and the reflected signal is phase and amplitude detected at a rapid rate for the purpose of identifying the fluids, based on their dielectric constant at the probe. The apparatus can be used for multiple purposes including measures of flow rates, turbulence, dispersion, fluid identification, and changes in flow conditions of multiple fluids or multiple states of a single fluid in a flowline or a holding container. The apparatus includes a probe consisting of two electrical conductors separated by an insulator. A radio frequency signal is communicated to the probe and is reflected back from the portion of the probe exposed to the fluid. The radio frequency signal also provides a reference signal. An oscillator generates a second signal which combined with each of the reference signal and the reflected signal to produce signals of lower frequencies to facilitate filtering and amplifying those signals. The two signals are then mixed in a detector to produce an output signal that is representative of the phase and amplitude change caused by the reflection of the signal at the probe exposed to the fluid. The detector may be a dual phase detector that provides two such output signals that are in phase quadrature. A phase shifter may be provided for selectively changing the phase of the reference signal to improve the sensitivity of at least one of the output signals for more accurate readings and/or for calibration purposes. The two outputs that are in quadrature with respect to each other may be simultaneously monitored to account for drift errors. The output signals are digitized and provided to a computer at a sample rate which may be very high. The computer is operable to identify the fluid based on its complex permittivity as may be useful for identifying the flow rates, determining the fluid mixture ratio, detecting impurities in the fluid, and so forth. Novelty is believed to reside in the use of the real part of complex permittivity to measure small difference in permittivity of the fluid.

Arndt, G. Dickey↗
NASA NTRS2011

Directed Incremental Symbolic Execution

The last few years have seen a resurgence of interest in the use of symbolic execution -- a program analysis technique developed more than three decades ago to analyze program execution paths. Scaling symbolic execution and other path-sensitive analysis techniques to large systems remains challenging despite recent algorithmic and technological advances. An alternative to solving the problem of scalability is to reduce the scope of the analysis. One approach that is widely studied in the context of regression analysis is to analyze the differences between two related program versions. While such an approach is intuitive in theory, finding efficient and precise ways to identify program differences, and characterize their effects on how the program executes has proved challenging in practice. In this paper, we present Directed Incremental Symbolic Execution (DiSE), a novel technique for detecting and characterizing the effects of program changes. The novelty of DiSE is to combine the efficiencies of static analysis techniques to compute program difference information with the precision of symbolic execution to explore program execution paths and generate path conditions affected by the differences. DiSE is a complementary technique to other reduction or bounding techniques developed to improve symbolic execution. Furthermore, DiSE does not require analysis results to be carried forward as the software evolves -- only the source code for two related program versions is required. A case-study of our implementation of DiSE illustrates its effectiveness at detecting and characterizing the effects of program changes.

Person, Suzette↗
DOE OSTI2025

Edge AI-Enhanced Traffic Monitoring and Anomaly Detection Using Multimodal Large Language Models

This paper addresses the challenge of traffic monitoring and incident detection in remote areas, utilizing multimodal large language models (LLMs) deployed on edge AI devices. The key novelty of the LLM is to convert real-time video streams into descriptive texts, enabling low-bandwidth transmissions and reliable detection of anomalies and incidents in environments of intermittent connectivity. The model is developed based on fine-tuning open-source LLMs and extending it with multi-modal capabilities to analyze video frames. Our work also involves deploying this model on edge devices such as Nvidia IGX Orin and is planned to be tested in realistic environments in future work. The methodology includes data set curation, iterative model fine-tuning and compression, and hardware-based optimization. This approach aims to enhance traffic safety and response speed in remote areas, marking a significant advancement in the application of AI for traffic monitoring and safety management.

Peruski, Ryan [University of Tennessee, Knoxville ↗
DOE OSTI2024

Management of Risks Associated with Application of Novel Materials in Novel Operating Environments in Novel Reactor Designs

There is currently no widely agreed, detailed general method for licensing a novel plant incorporating novel materials (or materials being deployed in novel environments); in many such situations, there are no directly applicable engineering code cases for decision-makers (including regulators) to rely on. This paper discusses a framework for solving this problem that is based on the Reliability and Integrity Management (RIM) approach delineated in ASME BPVC Section XI Division 2. NRC Regulatory Guide 1.246, Rev. 0, endorses, with conditions, the subject portion of the ASME Code. The proposed framework is meant to support development of a licensing case by addressing certain technical challenges. The framework discussed here is compatible with the Licensing Modernization Project, but applying it in a specific case will call for advances in the state of practice, if not the state of the art. The RIM approach calls for applicants to (a) allocate reliability targets to plant structures, systems, and components (SSCs), (b) show that they are able to relate the currently observed physical condition of each SSC in the program to its failure probability well enough to determine whether the target reliability allocations are being satisfied, allowing for uncertainty related to the novelty of the materials/designs/operating environments, and (c) be able to demonstrate that the proposed program of surveillances will reliably detect unacceptable degradation of an SSC before SSC failure occurs. These challenges are discussed in the paper, and a potentially applicable modeling approach based on cumulative damage rather than failure rates is briefly illustrated.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
NASA NTRS2008

Special Polymer/Carbon Composite Films for Detecting SO2

A family of polymer/carbon films has been developed for use as sensory films in electronic noses for detecting SO2 gas at concentrations as low as 1 part per million (ppm). Most previously reported SO2 sensors cannot detect SO2 at concentrations below tens of ppm; only a few can detect SO2 at 1 ppm. Most of the sensory materials used in those sensors (especially inorganic ones that include solid oxide electrolytes, metal oxides, and cadmium sulfide) must be used under relatively harsh conditions that include operation and regeneration at temperatures greater than 100 C. In contrast, the present films can be used to detect 1 ppm of SO2 at typical opening temperatures between 28 and 32 C and can be regenerated at temperatures between 36 and 40 C. The basic concept of making sensing films from polymer/carbon composites is not new. The novelty of the present family of polymer/carbon composites lies in formulating the polymer components of these composites specifically to optimize their properties for detecting SO2. First-principles quantum-mechanical calculations of the energies of binding of SO2 molecules to various polymer functionalities are used as a guide for selecting polymers and understanding the role of polymer functionalities in sensing. The polymer used in the polymer-carbon composite is a copolymer of styrene derivative units with vinyl pyridine or substituted vinyl pyridine derivative units. To make a substituted vinyl pyridine for use in synthesizing such a polymer, poly(2-vinyl pyridine) that has been dissolved in methanol is reacted with 3-chloropropylamine that has been dissolved in a solution of methanol. The methanol is then removed to obtain the copolymer. Later, the copolymer can be dissolved in an appropriate solvent with a suspension of carbon black to obtain a mixture that can be cast and then dried to obtain a sensory film.

Homer, Margie↗
NASA NTRS1989

Doppler-corrected differential detection of MPSK

An open-loop technique is presented for estimating and correcting Doppler frequency shift in an M-ary differential phase-shift-keyed (MDPSK) receiver. The novelty of the scheme is based on the observation that whereas the change in phase of the received signal over a full symbol contains the sum of the data (phase) and the Doppler-induced phase shift, the same change in phase over half a symbol (within a given symbol interval) contains only the Doppler-induced phase shift. Thus, by proper processing, the latter can be estimated and removed from the former. Analytical and simulation results are given for the variance of the above estimator, and the error probability performance of the MDPSK receiver is evaluated in the presence of the Doppler correction. Next, the practical considerations associated with the application of this technique on bandlimited Nyquist channels are discussed and incorporated into the final design. It is shown that the receiver can, in the absence of timing jitter, be designed to allow combined Doppler correction and data detection with no penalty due to intersymbol interference (ISI). The effects of ISI due to timing jitter are assessed by computer simulation.

Simon, Marvin K.↗
DOE OSTI2025

ACCELERATED DEPLOYMENT OF NOVEL MATERIALS BASED ON RELIABILITY INTEGRITY MANAGEMENT USING CUMULATIVE DAMAGE MODELING

There is currently no widely agreed, detailed general method for licensing a novel plant incorporating novel materials (or materials being deployed in novel environments); in many such situations, there are no directly applicable engineering code cases for decision-makers (including regulators) to rely on. This paper discusses a framework for solving this problem that is based on the Reliability and Integrity Management (RIM) approach delineated in ASME BPVC Section XI Division 2. NRC Regulatory Guide 1.246, Rev. 0, endorses, with conditions, the subject portion of the 2019 ASME Code. The proposed framework is meant to support development of a licensing case by addressing certain remaining technical challenges. The framework discussed here is compatible with the Licensing Modernization Project, but applying it in a specific case will call for advances in the state of practice, if not the state of the art. The RIM approach calls for applicants to (a) allocate reliability targets to plant structures, systems, and components (SSCs), (b) show that they are able to relate the currently observed physical condition of each SSC in the program to its failure probability well enough to determine whether the target reliability allocations are being satisfied, allowing for uncertainty related to the novelty of the materials/designs/operating environments, and (c) be able to demonstrate that the proposed program of surveillances will reliably detect unacceptable degradation of an SSC before SSC failure occurs. A modeling approach potentially applicable to item (b), based on cumulative damage modeling rather than failure rates, is briefly illustrated.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗
NASA NTRS1996

Digital Mammography with a Mosaic of CCD-Arrays

The present invention relates generally to a mammography device and method and more particularly to a novel digital mammography device and method to detect microcalcifications of precancerous tissue. A digital mammography device uses a mosaic of electronic digital imaging arrays to scan an x-ray image. The mosaic of arrays is repositioned several times to expose different portions of the image, until the entire image is scanned. The data generated by the arrays during each exposure is stored in a computer. After the final exposure, the computer combines data of the several partial images to produce a composite of the original x-ray image. An aperture plate is used to reduce scatter and the overall exposure of the patient to x-rays. The novelty of this invention is that it provides a digital mammography device with large field coverage, high spatial resolution, scatter rejection, excellent contrast characteristics and lesion detectability under clinical conditions. This device also shields the patient from excessive radiation, can detect extremely small calcifications and allows manipulation and storage of the image.

Jalink, Antony, Jr.↗
NASA NTRSDate not supplied

Nearest-Neighbor Machine Learning Feature Selection for Interpretation of Microbial Molecular Signatures from Isotope Ratio Mass Spectrometry Data

Mass spectrometry (MS) promises to be a powerful tool for potential biosignature detection during astrobiological missions on ocean worlds in our solar system. Accurate and generalizable machine learning methods could enhance science return on investment by predicting seawater chemistry and classifying isotopic biosignatures, either as a signature consistent with microbial life (biotic) or as a novelty (unclassified/unique). However, machine learning models are likely to be complex and involve interactions between MS features, making biosignatures difficult to interpret. Feature selection methods provide biological and chemical context that help interpret the mechanisms of machine learning models, but these methods also need the ability to detect complex interactions. Previously, we developed a machine learning feature selection algorithm called nearest-neighbor projected distance regression (NPDR) that has the ability to identify important model features that involve complex interactions and automatically reduce correlation and the dimensionality in a high-dimensional variable space. The standard distance metrics used in NPDR – Manhattan and Euclidean – assume the multivariate data are isotropic, which is often violated in real data due to differences in the covariance between variables. Thus, we extend NPDR to include a random forest distance, and other anisotropic distance metrics, for computing nearest neighbors. We also augment the isotope-ratio MS data with time-series features from the raw MS signal to improve biotic classification. We test NPDR on our novel experimental ocean world seawater analog MS data. We measure isotope fractionations of volatile CO 2 that could be measured in exospheres or plumes. Samples include baseline abiotic conditions using a range of possible seawater chemistry consistent with Europa and Enceladus, and biotic samples that include microbes in these seawaters. We use penalized NPDR with random forest proximity to identify interpretable microbial molecular signatures. We compare features with random forest importance, and we train a classifier that discriminates between biotic and abiotic samples with high accuracy. These ML-trained ocean-world analog MS data could be used to assist in identifying biosignatures during future missions.

geochemistry↗
NASA NTRS2013

High-Collection-Efficiency Fluorescence Detection Cell

A new fluorescence cell has been developed for the laser induced fluorescence (LIF) detection of formaldehyde. The cell is used to sample a flow of air that contains trace concentrations of formaldehyde. The cell provides a hermetically sealed volume in which a flow of air containing formaldehyde can be illuminated by a laser. The cell includes the optics for transmitting the laser beam that is used to excite the formaldehyde and for collecting the resulting fluorescence. The novelty of the cell is its small size and simple design that provides a more robust and cheaper alternative to the state of the art. Despite its simplicity, the cell provides the same sensitivity to detection as larger, more complicated cells.

Hanisco, Thomas↗
DOE OSTI2025

Population ecology and biogeochemical implications of ssDNA and dsDNA viruses along a permafrost thaw gradient

Anthropogenic-driven climate change is accelerating permafrost thaw, threatening to release vast carbon stores through increased microbial activity. While microbial roles are increasingly studied, the contributions of viruses remain largely unexplored, in part due to soil-associated technical challenges that have hindered their detection and characterization. Here, we applied an optimized virion enrichment workflow along a permafrost thaw gradient, identifying 9,963 viral populations (vOTUs), including single- and double-stranded DNA viruses, with 99.9% novelty compared to other soils. Hosts were predicted for 38% of vOTUs, spanning nine archaeal, and 36 bacterial phyla, 22% of which were linked to metagenome-assembled genomes, including key carbon-cycling taxa. Genomic analyses revealed 811 putative auxiliary metabolic genes (AMGs) from 658 vOTUs, nearly half involved in carbon processing. These included 59 glycoside hydrolases (GH) across nine GH families, 45 for monosaccharide degradation, and seven involved in short-chain fatty acid and C1 metabolism, linking viruses to both early and late stages of carbon turnover. Additionally, six vOTUs carried racD, which may stabilize microbial necromass and promote long-term carbon storage. Viral and AMG functional diversity increased with thaw stage, indicating that viruses might participate in a broadening range of microbial metabolic processes as permafrost thaws. These findings expand our understanding of virus contributions in microbial carbon processing and suggest their important role in deciphering soil carbon fate under changing climate conditions.

Biological and medical sciences↗
NASA NTRS2006

Testing the TPF Interferometry Approach before Launch

One way to directly detect nearby extra-solar planets is via their thermal infrared emission, and with this goal in mind, both NASA and ESA are investigating cryogenic infrared interferometers. Common to both agencies' approaches to faint off-axis source detection near bright stars is the use of a rotating nulling interferometer, such as the Terrestrial Planet Finder interferometer (TPF-I), or Darwin. In this approach, the central star is nulled, while the emission from off-axis sources is transmitted and modulated by the rotation of the off-axis fringes. Because of the high contrasts involved, and the novelty of the measurement technique, it is essential to gain experience with this technique before launch. Here we describe a simple ground-based experiment that can test the essential aspects of the TPF signal measurement and image reconstruction approaches by generating a rotating interferometric baseline within the pupil of a large singleaperture telescope. This approach can mimic potential space-based interferometric configurations, and allow the extraction of signals from off-axis sources using the same algorithms proposed for the space-based missions. This approach should thus allow for testing of the applicability of proposed signal extraction algorithms for the detection of single and multiple near-neighbor companions...

interferometry↗
NASA NTRS2014

Property Differencing for Incremental Checking

This paper introduces iProperty, a novel approach that facilitates incremental checking of programs based on a property di erencing technique. Speci cally, iProperty aims to reduce the cost of checking properties as they are initially developed and as they co-evolve with the program. The key novelty of iProperty is to compute the di erences between the new and old versions of expected properties to reduce the number and size of the properties that need to be checked during the initial development of the properties. Furthermore, property di erencing is used in synergy with program behavior di erencing techniques to optimize common regression scenarios, such as detecting regression errors or checking feature additions for conformance to new expected properties. Experimental results in the context of symbolic execution of Java programs annotated with properties written as assertions show the e ectiveness of iProperty in utilizing change information to enable more ecient checking.

Yang, Guowei↗
DOE OSTI2026

A Bayesian inferencing framework for ultrasound wave speed measurements in metal additive manufacturing

Process-related changes during metal additive manufacturing introduce microstructural variability in the material properties of printed parts, directly affecting component reliability. Accurate estimation of these property variations with part performance are essential for quality assurance. Ultrasound testing offers a non-destructive means to estimate mechanical properties and detect defects; however, conventional analysis methods often neglect the influence of microstructural variability, limiting their effectiveness. Here, this research presents a Bayesian inference technique for quantifying wave speed uncertainty from ultrasound measurements of metal additive manufactured parts. By integrating prior ultrasound data with a Bayesian model, the proposed approach generates posterior density estimates of wave speed that systematically account for manufacturing-induced variability and uncertainty. The novelty of this research lies in applying a Bayesian framework to analyze experimental ultrasound measurements within the context of metal additive manufacturing variability. The method enhances the accuracy of wave speed estimation by 64%, defect position by 50% and increases confidence associated with wave speed variance by 30% across different porosity levels, thereby providing a robust foundation for improved decision-making and increased reliability in additively manufactured components.

Additive manufacturing↗
DOE OSTI2025

Fracture Network Quantification during CO2 Injection

This is the presentation prepared for the ARMA 2025 (59th US Rock Mechanics/Geomechanics Symposium) Conference held in Santa Fe, New Mexico, June 8-11, 2025. Accurate mapping and quantification of these networks are essential to ensure the integrity of CO2 storage reservoirs, understand and reduce potential leakage, and maintain long-term environmental safety. This study presents a novel machine learning-driven approach, integrated with geomechanical analysis, to quantify fracture networks and assess their spatial distribution during CO2 injection. This paper combines microseismic monitoring data with principles of hydraulic diffusivity and geomechanical analysis to characterize reservoir scale fracture network. The novelty of our approach lies in its capacity to assimilate time-dependent pressure data and microseismicity into a cohesive framework, which not only identifies microseismic triggering fronts but also tracks fracture distribution during active injection. Besides, leveraging image log data and analysis our approach also provides another angle of the insights to solidate the fracture networks understanding and geomechanical impacts. Key results from our study include the detection of over 100 distinct fracture clusters across the injection site, with fracture orientations strongly correlated with the prevailing in-situ stress field.

CO2 storage and sequestration↗