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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 1,135 records · Page 63

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NASA NTRS2003

Infrared Thermography Flight Experimentation

Analysis was done on IR data collected by DFRC on May 8, 2002. This includes the generation of a movie to initially examine the IR flight data. The production of the movie was challenged by the volume of data that needed to be processed, namely 40,500 images with each image (256 x 252) containing over 264 million points (pixel depth 4096). It was also observed during the initial analysis that the RTD surface coating has a different emissivity than the surroundings. This fact added unexpected complexity in obtaining a correlation between RTD data and IR data. A scheme was devised to generate IR data near the RTD location which is not affected by the surface coating This scheme is valid as long as the surface temperature as measured does not change too much over a few pixel distances from the RTD location. After obtaining IR data near the RTD location, it is possible to make a direct comparison with the temperature as measured during the flight after adjusting for the camera s auto scaling. The IR data seems to correlate well to the flight temperature data at three of the four RID locations. The maximum count intensity occurs closely to the maximum temperature as measured during flight. At one location (RTD #3), there is poor correlation and this must be investigated before any further progress is possible. However, with successful comparisons at three locations, it seems there is great potential to be able to find a calibration curve for the data. Moreover, as such it will be possible to measure temperature directly from the IR data in the near future.

Blanchard, Robert C.↗

NASA NTRS2022

TechEdSat-13: The First Flight of a Neuromorphic Processor

Neuromorphic processors, inspired by the wiring of the brain, permit certain classes of Artificial Intelligence/Machine Learning (AI/ML) algorithms to run far more efficiently. Ultimately, such systems will make the small- and nano-satellite platforms even more useful in terms of greatly improved power, communication and internal data management. In addition, on-board processing of images and data will help to not only rapidly interpret the information, but also reduce the amount of data that needs to be transmitted to ground stations. This initial flight experiment uses the Intel/Loihi processor combined with a custom interface board and three communication channels to run the AI/ML scripts. These will vary with increasing length and complexity during the course of the mission. The algorithms will use the (at first) limited sensor data to ‘learn’ - with comparisons to similar architecture in comparable ground experiments. Some of the applications for successor flights in the TES-n flight series include Cognitive Communications, whereby the overall communication system is optimized per overflight – by optimizing timing and data transmission functions. Lastly, the performance of the Loihi 14nm process technology will be monitored for performance in the LEO radiation environment, thus looking for induced hardware and software errors. This information will help guide future radiation protection techniques to extend the lifetime and overall utility. The TES-13 is a 3U nanosat successfully launched by the Virgin Orbit Launcher-1 on January 13, 2022, and will presage more flights and AI/ML applications to come.

TechEdSat↗

NASA NTRSDate not supplied

TechEdSat-13: The First Flight of an AI/ML Neuromorphic Processor

Neuromorphic processors, inspired by the wiring of the brain, permit certain classes of Artificial Intelligence/Machine Learning (AI/ML) algorithms to run far more efficiently. Ultimately, such systems will make the small- and nano-satellite platforms even more useful in terms of greatly improved power, communication and internal data management. In addition, on-board processing of images and data will help to not only rapidly interpret the information, but also reduce the amount of data that needs to be transmitted to ground stations. This initial flight experiment uses the Intel/ Loihi processor combined with a custom interface board and three communication channels to run the AI/ML scripts. These will vary with increasing length and complexity during the course of the mission. The algorithms will use the (at first) limited sensor data to ‘learn’ - with comparisons to similar architecture in comparable ground experiments. Some of the applications for successor flights in the TES-n flight series include Cognitive Communications, whereby the overall communication system is optimized per overflight – by optimizing timing and data transmission functions. Lastly, the performance of the Loihi 14nm process technology will be monitored for performance in the LEO radiation environment, thus looking for induced hardware and software errors. This information will help guide future radiation protection techniques to extend the lifetime and overall utility. The TES-13 is a 3U nanosat successfully launched by the Virgin Orbit Launcher-1 on January 13, 2022, and will presage more flights and AI/ML applications to come.

TechEdSat↗

DOE OSTI2023

PiCAM: A Raspberry Pi-based open-source, low-power camera system for monitoring plant phenology in Arctic environments

Time-lapse cameras have been widely used as a tool to monitor the timing of seasonal vegetation growth. These simple, relatively inexpensive systems can provide high-frequency observations of leaf development and demography which are critical data sets needed to characterize plant phenology from species to landscapes. This is important for understanding how plants are responding to global changes, as well as for validating satellite-derived phenology products. However, in remote regions including the high-latitude Arctic, deploying time-lapse cameras could be challenging. The remoteness and lack of widespread power and telecommunications infrastructure limit options for the installation, maintenance and retrieval of data and equipment, and make it difficult for cameras to survive in extreme weather (e.g. long cold winters). To improve our understanding of Arctic phenology, new technologies are required to address these challenges. Here, we present a novel, low-power, compact, lightweight time-lapse camera system, called power-interval camera automation module (PiCAM). The PiCAM was designed with explicit consideration to simplify deployment (i.e. without a need for external power supplies) of camera systems and to address the challenges of camera survival in harsh Arctic environments. In this paper, we describe the design, setup and technical details of the PiCAM and provide a roadmap for how to build and operate these systems. As proof of concept, we deployed 26 PiCAMs at three low-Arctic tundra sites on the Seward Peninsula, Alaska in early August 2021 for characterizing Arctic plant phenology. Of the 26 PiCAMs, 70% remained active at the point of our revisit in late July 2022 despite the extreme winter temperatures they experienced (< –30°C, heavy snow cover). We extracted key plant phenology metrics from the PiCAMs and captured strong differences across key Arctic plant species. We showed that the PiCAM has the potential to be widely used for monitoring plant phenology across the broader Arctic region, addressing the need for ground-based understanding of Arctic phenological diversity to develop knowledge of plant response to climate change and to validate remote sensing products.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2020

Demonstration of NEAMS Multiphysics Tools for Fast Reactor Applications

The SHARP toolkit is a high-fidelity reactor simulation tool developed under the U.S. Department of Energy, Office of Nuclear Energy Advanced Modeling and Simulation (NEAMS) Campaign. SHARP toolkit is comprised of the neutronics module PROTEUS thermal hydraulics module Nek5000, and structural mechanics module Diablo. During FY17 and FY18, the PROTEUS and Nek5000 components of SHARP were applied to solve challenging sodium-cooled fast reactor (SFR) problems. In particular, selected hot channel factors (HCF) for a prototype metal-fueled SFR design (the AFR-100) were analyzed in high fidelity, and the “SHARP zooming capability” for SFRs was developed and demonstrated to reduce computational expense for full core problems in cases where detailed data is needed in selected fuel assemblies. After the previous success applying SHARP to challenging SFR problems, the focus in FY19 and FY20 expanded to additional fast reactor applications including lead cooled fast reactors (LFR) and sodium cooled fast reactors (SFR). The specific technical tasks were (1) assessment of hot channel factors for LFR, for which no data currently exists, and (2) demonstration of zooming capability in assemblies of the Versatile Test Reactor (VTR). First-of-a-kind hot channel factor (HCF) estimation for LFR with high fidelity codes (PROTEUS/Nek5000) was successfully demonstrated in this study which began in FY19 and continued in FY20. Selected HCF were computed and compared with SFR data (AFR-100, EBR-II). The findings confirm that different reactor types, design parameters and uncertainties lead to different HCFs. Careful estimation of HCF for a specific design is necessary to obtain appropriate HCFs. In addition to improvement in HCF accuracy, high fidelity tools generate data to help the designer better understand the mechanism of the impact from these uncertainties. For example, the impact of cladding thickness manufacturing tolerance resulted in non-intuitive effects in the corner pins of the LFR assembly. This procedure of computing HCF using high fidelity models shows promise and flexibility for being repeated for any arbitrary reactor of choice. Along with the application on SFR and LFR, the capability of the tools has also been matured to deal with different reactor types and designs. Progress was made towards extending the previously demonstrated SHARP zooming capability to non-fueled SFR assemblies. In particular, in FY19 a gamma transport capability was implemented in both high fidelity PROTEUS solvers in order to accurately account for heat deposition caused by gamma particles, which accounts for ~10% of total core power. Neutronics verification cases were carried out for a candidate Versatile Test Reactor (VTR) design using the new gamma transport capability in PROTEUS. Comparisons were made with continuous energy MCNP calculations and shown to agree well. The models for the full core design with heterogeneous control and fuel assemblies is in progress for PROTEUS-SN and completed with MCNP. The MCNP power distributions were transferred to Nek5000 to perform thermal hydraulic calculations of the control and fuel assembly.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

NASA NTRS1977

Thermochemical characterization of polymers for improved fire safety

Apparatus has been constructed for studying the thermal decomposition of polymers as a function of temperature. Such data is needed to evaluate the toxic threat presented by polymeric materials under fire conditions such as the smoldering fire of the type that occurs in closed areas such as coat closets in which anaerobic decomposition of polymers occurs. The apparatus allows the products of thermal decomposition to be collected and analyzed by infrared spectrometry and mass spectrometry. Data obtained from dog hair, an aromatic polyamide, polyphenylene sulfide, and polybenzimidazole are presented. It was found that significant amounts of toxic gas were evolved from dog hair at temperatures as low as 250 C, while temperatures in excess of 500 C were necessary in order for the evolution of toxic gas from the aromatic polymers to become significant.

Lerner, N. R.↗

DOE OSTI2023

Deep Learning on Multimodal Chemical and Whole Slide Imaging Data for Predicting Prostate Cancer Directly from Tissue Images

Prostate cancer is one of the most common cancers globally and is the second most common cancer in the male population in the US. Here we develop a study based on correlating the hematoxylin and eosin (H&E)-stained biopsy data with MALDI mass-spectrometric imaging data of the corresponding tissue to determine the cancerous regions and their unique chemical signatures and variations of the predicted regions with original pathological annotations. We obtain features from high-resolution optical micrographs of whole slide H&E stained data through deep learning and spatially register them with mass spectrometry imaging (MSI) data to correlate the chemical signature with the tissue anatomy of the data. We then use the learned correlation to predict prostate cancer from observed H&E images using trained coregistered MSI data. This multimodal approach can predict cancerous regions with ~80% accuracy, which indicates a correlation between optical H&E features and chemical information found in MSI. Further, we show that such paired multimodal data can be used for training feature extraction networks on H&E data which bypasses the need to acquire expensive MSI data and eliminates the need for manual annotation saving valuable time. Two chemical biomarkers were also found to be predicting the ground truth cancerous regions. This study shows promise in generating improved patient treatment trajectories by predicting prostate cancer directly from readily available H&E-stained biopsy images aided by coregistered MSI data.

60 APPLIED LIFE SCIENCES↗

NASA NTRS1997

Synthetic Data for Testing TRMM Radar Algorithms

Test data are required to test algorithms for the TRMM Precipitation Radar. These data are needed to test the design of the computer codes under development for the operational phase of the mission, and also to test and evaluate alternative or improved precipitation retrieval algorithms. Over a number of years we have developed and used a 3-dimensional radar model for simulating spaceborne precipitation radars. We have adapted this code to produce data files as close as possible to the TRMM file specifications. In this paper, we will describe the model as it is currently implemented, and show some samples of the synthetic data sets.

Jones, Jeffrey A.↗

DOE OSTI2025

Evaluating the factors influencing accuracy, interpretability, and reproducibility in the use of machine learning classifiers in biology to enable standardization

The complexity and variability of biological data has promoted the increased use of machine learning methods to understand processes and predict outcomes. These same features complicate reliable, reproducible, interpretable, and responsible use of such methods, resulting in questionable relevance of the derived. outcomes. Here we systematically explore challenges associated with applying machine learning to predict and understand biological processes using a well- characterized in vitro experimental system. We evaluated factors that vary while applying machine learning classifers: (1) type of biochemical signature (transcripts vs. proteins), (2) data curation methods (pre- and post-processing), and (3) choice of machine learning classifier. Using accuracy, generalizability, interpretability, and reproducibility as metrics, we found that the above factors significantly mod- ulate outcomes even within a simple model system. Our results caution against the unregulated use of machine learning methods in the biological sciences, and strongly advocate the need for data standards and validation tool-kits for such studies.

59 BASIC BIOLOGICAL SCIENCES↗

NASA NTRS1992

Tangential, semisubmerged, and internal store carriage and separation

Accounts are presented of tangential, semisubmerged, and internal store carriage drag, as well as of the results to date of stores-separation investigations employing both computational and experimental methods. It is demonstrated that CFD can contribute to the data base needed for internal stores carriage design and trade studies. Attention is given to the case of an internally carried store separating from its bay at supersonic speeds, where various kinds of interference are encountered. A code is developed for the simulation of these unsteady flows through time-accurate computations; computation results are noted to closely reproduce experiment data.

Wilcox, Floyd J., Jr.↗

NASA NTRS1995

Coral Pigments: Quantification Using HPLC and Detection by Remote Sensing

Widespread coral bleaching (loss of pigments of symbiotic dinoflagellates), and the corresponding decline in coral reef health worldwide, mandates the monitoring of coral pigmentation. Samples of the corals Porites compressa and P. lobata were collected from a healthy reef at Puako, Hawaii, and chlorophyll (chl) a, peridinin, and Beta-carotene (Beta-car) were quantified using reverse-phase high performance liquid chromatography (HPLC). Detailed procedures are presented for the extraction of the coral pigments in 90% acetone, and the separation, identification, and quantification of the major zooxanthellar pigments using spectrophotometry and a modification of the HPLC system described by Mantoura and Llewellyn (1983). Beta-apo-8-carotenal was found to be inadequate as in internal standard, due to coelution with chl b and/or chl a allomer in the sample extracts. Improvements are suggested, which may result in better resolution of the major pigments and greater accuracy in quantification. Average concentrations of peridinin, chl a, and Beta-car in corals on the reef were 5.01, 8.59, and 0.29, micro-grams/cm(exp 2), respectively. Average concentrations of peridinin and Beta-car did not differ significantly between the two coral species sampled; however, the mean chl a concentration in P. compressa specimens (7.81 ,micro-grams/cm(exp 2) was significantly lower than that in P. lobata specimens (9.96 11g/cm2). Chl a concentrations determined spectrophotometrically were significantly higher than those generated through HPLC, suggesting that spectrophotometry overestimates chl a concentrations. The average ratio of chl a-to-peridinin concentrations was 1.90, with a large (53%) coefficient of variation and a significant difference between the two species sampled. Additional data are needed before conclusions can be drawn regarding average pigment concentrations in healthy corals and the consistency of the chl a/peridinin ratio. The HPLC pigment concentration values contribute to the limited database of pigment concentrations in healthy corals, from which quantitative definitions of 'healthy' vs. 'bleached' coral may emerge. They also serve as ground-truth, corresponding to fluorescence data collected from the reef at Puako using airborne remote sensing of laser induced fluorescence. Fluorescence spectra from several overflights using the NASA AOL (airborne oceanographic lidar) system show consistent chlorphyll fluorescence peaks around 685 nm, as well as consistence peaks in the 400-600 nm range which may emanate from granules in the coral tissue. These data, along with results from previous studies of coral fluorescence, suggest that remote sensing of laser-induced fluorescence may become a rapid and efficient means of monitoring coral pigmentation and coral reef bleaching.

Cottone, Mary C.↗

NASA NTRS2011

Comparative Study of 3-Dimensional Woven Joint Architectures for Composite Spacecraft Structures

The National Aeronautics and Space Administration (NASA) Exploration Systems Mission Directorate initiated an Advanced Composite Technology (ACT) Project through the Exploration Technology Development Program in order to support the polymer composite needs for future heavy lift launch architectures. As an example, the large composite structural applications on Ares V inspired the evaluation of advanced joining technologies, specifically 3D woven composite joints, which could be applied to traditionally manufactured barrel segments. Implementation of these 3D woven joint technologies may offer enhancements in damage tolerance without sacrificing weight. However, baseline mechanical performance data is needed to properly analyze the joint stresses and subsequently design/down-select a preform architecture. Six different configurations were designed and prepared for this study; each consisting of a different combination of warp/fill fiber volume ratio and preform interlocking method (z-fiber, fully interlocked, or hybrid). Tensile testing was performed for this study with the enhancement of a dual camera Digital Image Correlation (DIC) system which provides the capability to measure full-field strains and three dimensional displacements of objects under load. As expected, the ratio of warp/fill fiber has a direct influence on strength and modulus, with higher values measured in the direction of higher fiber volume bias. When comparing the z-fiber weave to a fully interlocked weave with comparable fiber bias, the z-fiber weave demonstrated the best performance in two different comparisons. We report the measured tensile strengths and moduli for test coupons from the 6 different weave configurations under study.

Jones, Justin S.↗

DOE OSTI2026

Investigation and Diagnosis of Faulty Data Channels in CMS Outer Tracker Module Testing

The High-Luminosity Large Hadron Collider (HL-LHC) is currently undergoing upgrades to improve its luminosity. In parallel, this requires an upgrade to the Compact Muon Solenoid (CMS)’s Outer Tracker, consisting of Pixel-Strip (PS) and Strip-Strip (2S) modules that can accurately track the path of charged particles originating from the collisions. It follows that such complex modules call for extensive testing, requiring a sophisticated Data Acquisition (DAQ) system that can perform specific tests to assess their performance. In addition, errors caused by the hardware of a given testing station, and its associated data channel, need to be accurately identified to guarantee proper testing of modules. We have developed a software extension to the Phase-II Outer Tracker Analyzer of Test Outputs (POTATO), which is a specialized software designed to analyze and grade all of the module tests through a centralized database. This extension categorizes and analyzes module test results by its station and data channel. Its analysis can be used to identify trends in grading that indicate issues in these channels’ grading process rather than in the individual modules. This poster shows our methodology and results for identifying faulty data channels. Using this extension, we can quickly diagnose and address problems in our DAQ system, ensuring proper evaluation corrections for each module.

Chen, Angus [Fermilab]↗

DOE OSTI2026

Investigation and Diagnosis of Faulty Data Channels in CMS Outer Tracker Module Testing

Chen, Angus [Fermilab]↗

NASA NTRS1992

PCIPS 2.0: Powerful multiprofile image processing implemented on PCs

Over the years, the processing power of personal computers has steadily increased. Now, 386- and 486-based PC's are fast enough for many image processing applications, and inexpensive enough even for amateur astronomers. PCIPS is an image processing system based on these platforms that was designed to satisfy a broad range of data analysis needs, while requiring minimum hardware and providing maximum expandability. It will run (albeit at a slow pace) even on a 80286 with 640K memory, but will take full advantage of bigger memory and faster CPU's. Because the actual image processing is performed by external modules, the system can be easily upgraded by the user for all sorts of scientific data analysis. PCIPS supports large format lD and 2D images in any numeric type from 8-bit integer to 64-bit floating point. The images can be displayed, overlaid, printed and any part of the data examined via an intuitive graphical user interface that employs buttons, pop-up menus, and a mouse. PCIPS automatically converts images between different types and sizes to satisfy the requirements of various applications. PCIPS features an API that lets users develop custom applications in C or FORTRAN. While doing so, a programmer can concentrate on the actual data processing, because PCIPS assumes responsibility for accessing images and interacting with the user. This also ensures that all applications, even custom ones, have a consistent and user-friendly interface. The API is compatible with factory programming, a metaphor for constructing image processing procedures that will be implemented in future versions of the system. Several application packages were created under PCIPS. The basic package includes elementary arithmetics and statistics, geometric transformations and import/export in various formats (FITS, binary, ASCII, and GIF). The CCD processing package and the spectral analysis package were successfully used to reduce spectra from the Nordic Telescope at La Palma. A photometry package is also available, and other packages are being developed. A multitasking version of PCIPS that utilizes the factory programming concept is currently under development. This version will remain compatible (on the source code level) with existing application packages and custom applications.

Smirnov, O. M.↗

NASA NTRS1979

User-oriented end-to-end transport protocols for the real-time distribution of telemetry data from NASA spacecraft

A set of standard telemetry protocols for downlink data flow facilitating the end-to-end transport of instrument data from the spacecraft to the user in real time is proposed. The direct switching of data by autonomous message 'packets' that are assembled by the source instrument on the spacecraft is discussed. The data system consists thus of a format on a message rather than word basis, and such packet telemetry would include standardized protocol headers. Standards are being developed within the NASA End-to-End Data System (NEEDS) program for the source packet and transport frame protocols. The source packet protocol contains identification of both the sequence number of the packet as it is generated by the source and the total length of the packet, while the transport frame protocol includes a sequence count defining the serial number of the frame as it is generated by the spacecraft data system, and a field specifying any 'options' selected in the format of the frame itself.

Hooke, A. J.↗

NASA NTRSDate not supplied

Results of the NASA Prediction Uncertainty Reduction Tech Challenge

In January 2021 the Advanced Air Vehicles Program approved a new Tech Challenge (TC) to be run out of the Commercial Supersonic Technology (CST) Project. The objective of the TC was to bring uncertainties in the empirical noise modeling for civilian supersonic aircraft into the same range as that of conventional aircraft. The TC goal statement was to “Produce data and demonstrate tools that reduce the uncertainty in predicting Landing & Takeoff Noise levels of supersonic-relevant designs by 5 EPNdB and are ready for use in studies to inform FAA rule-making.” To make the required improvements in noise prediction methods for supersonic aircraft, NASA decided to validate and use high-fidelity numerical simulations to acquire the needed noise data on supersonic propulsion configurations. High-fidelity component designs were developed, such as a two-stage propulsor behind a supersonic inlet designed by General Electric Aviation and variable area exhaust systems using input from recent contracts with GE and Rolls Royce. A noise database was generated as a function of geometric and flow parameters, providing corrections to the empirical noise models and added new input variables to describe the complexities created by the supersonic-specific design features. Statistically, the new models were able to predict the acoustic impact of supersonic-specific features, the reduction in uncertainty being reduced from the baseline 7.8 EPNdB at the beginning of the TC to 2.0 EPNdB at the end.

noise prediction↗

DOE OSTI2026

CMIP7 data request: Earth system priorities and opportunities

This paper presents a comprehensive overview of the Coupled Model Intercomparison Project Phase 7 (CMIP7) request for data pertaining to Earth systems science, and provides justification for the resources needed to produce this data. Topics within the CMIP7 Earth System (CMIP7-ES) theme centre around tracking of flows of energy, carbon, water and other fluxes across domains, and constraining feedbacks between these cycles and the climate system. These topics are summarized in this paper as scientific “opportunities” describing specific model intercomparison experiments and use cases for next-generation Earth System Model (ESM) output. These opportunities were submitted by modelling groups and scientific consortia following an extended public consultation process. Contained within each opportunity are requests for groups of Climate & Forecasting (CF) variables, which are bundled into variable groups representing all data required to address the opportunities' needs. Novel opportunities in CMIP7 compared with previous phases will include running `emissions-driven' simulations that integrate carbon emissions and removal scenarios with updated representations of the global carbon cycle, expanded variable groups needed to model marine trophic interactions and biogeochemistry, and data needed to understand the risk of global tipping points, among others. The production of these variables will close key gaps and uncertainties identified during previous rounds of CMIP, and support the 7th Intergovernmental Panel on Climate Change Assessment Report (AR7). We argue that CMIP7-ES data will be broadly used by scientific, policy, governmental, industry, and other communities that rely on climate model projections for research and decision making. As an author group we also reflect on the evolution of the CMIP7-ES data request as a part of a deliberative process in support of the global CMIP program.

54 ENVIRONMENTAL SCIENCES↗