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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 757 records · Page 42

Nondestructive tests of regenerative chambers

The capabilities and limitations of nondestructive evaluation methods were studied to detect and locate bond deficiencies in regeneratively cooled thrust chambers for rocket engines. Flat test panels and a cylinder were produced to simulate regeneratively cooled thrust chamber walls. Planned defects with various bond integrities were produced in the panels to evaluate the sensitivity, accuracy, and limitations of nondestructive methods to define and locate bond anomalies. Holography, acoustic emission, and ultrasonic scan were found to yield sufficient data to discern bond quality when used in combination and in selected sequences. Bonding techniques included electroforming and brazing. Materials of construction included electroformed nickel bonded to Nickel 200 and OFHC copper, electroformed copper bonded to OFHC copper, and 300 series stainless steel brazed to OFHC copper. Variations in outer wall strength, wall thickness, and defect size were evaluated for nondestructive test response.

Malone, G. A.↗

A program to compute three-dimensional subsonic unsteady aerodynamic characteristics using the doublet lattice method, L216 (DUBFLEX). Volume 2: Supplemental system design and maintenance document

The information necessary for execution of the digital computer program L216 on the CDC 6600 is described. L216 characteristics are based on the doublet lattice method. Arbitrary aerodynamic configurations may be represented with combinations of nonplanar lifting surfaces composed of finite constant pressure panel elements, and axially summetric slender bodies composed of constant pressure line elements. Program input consists of configuration geometry, aerodynamic parameters, and modal data; output includes element geometry, pressure difference distributions, integrated aerodynamic coefficients, stability derivatives, generalized aerodynamic forces, and aerodynamic influence coefficient matrices. Optionally, modal data may be input on magnetic field (tape or disk), and certain geometric and aerodynamic output may be saved for subsequent use.

Harrison, B. A.↗

Human operator performance of remotely controlled tasks: Teleoperator research conducted at NASA's George C. Marshall Space Flight Center. Executive summary

The combination of human and machine capabilities into an integrated engineering system which is complex and interactive interdisciplinary undertaking is discussed. Human controlled remote systems referred to as teleoperators, are reviewed. The human factors requirements for remotely manned systems are identified. The data were developed in three principal teleoperator laboratories and the visual, manipulator and mobility laboratories are described. Three major sections are identified: (1) remote system components, (2) human operator considerations; and (3) teleoperator system simulation and concept verification.

Shields, N., Jr.↗

Middle Atmosphere Reference Model Derived from Satellite Data

Zonally averaged temperature and geostrophic zonal wind for each month and for latitudes from 80 S to 80 N with pressure scale height as a vertical coordinate are given tabular form. The pressure scale height is defined as -ln (p/P sub O) where p is pressure and P sub O is surface pressure. The height interval corresponding to one pressure scale height is proportional to absolute temperature, and is 7 km at 240 K. Values in are given at intervals of 0.5 pressure scale heights, i.e., approximately 3,5 km. The geopotential height fields for the principal seasons are given. Temperature, pressure and density with geometric height as the vertical coordinate at invervals of 5 km. The temperature values were obtained from a combination of satellite data above 30 mb with values supplied by the Berlin Free University at 30 mb and the climatology derived by OORT (1983) for 50 mb and below. The geopotential height fields were obtained from these temperature fields by integrating up and down from the 30 mb geopotential height supplied by Berlin Free University. The geostrophic winds were obtained by differentiating these geopotential height fields.

Barnett, J. J.↗

Noble Gas Analysis in the Quest to Find "Regolithic" Howardites

The howardite meteorites consist of approximately 200 polymict breccias of eucrite (basaltic) and diogenite (orthopyroxenitic) material (collectively, the HED group) that originate from the asteroid belt. Infrared reflectance spectroscopy of asteroids and laboratory studies of HEDs have indicated that the asteroid 4-Vesta is the likely parent body, and the partially-demolished south pole may be the source region. Asteroid regolith formation processes may be responsible for a number of observed petrological features including impact melt clasts, reworked clasts and mosaisicm. We have identified such features in a study of 30 howardites and polymict eucrites, and developed a regolith grading scheme based on petrology. However, the true regolithic nature of the howardite suite is not well defined, and previous research has suggested correlations between Ni contents of 300 - 1200 micron / g, a minimal variation in Al2O3 content around 8-9 wt% and the presence of solar wind noble gases are key hallmarks of an ancient regolith on Vesta . Through combined petrological, compositional and noble gas research, we aim to better understand howardite petrological diversity, regolith formation processes on parent asteroids, and to establish what defines a truly "regolithic" howardite. Our research will play an integral part in the interpretation of data gathered by the Dawn mission. Here we report the preliminary results from our noble gas analyses of four howardites: LEW 85313, EET 99408, MET 96500 and PCA 02066. Bulk major element compositional data have been collected, further petrological data for the HED group are reported by our colleagues, whilst trace-element analyses are underway. Our work will investigate the extent of whether previously described Ni, Al2O3 and noble gas characteristics are in fact indicative of a "regolithic" howardite.

Cartwright, Julia A.↗

Recent Advances in Techniques for Hyperspectral Image Processing

Imaging spectroscopy, also known as hyperspectral imaging, has been transformed in less than 30 years from being a sparse research tool into a commodity product available to a broad user community. Currently, there is a need for standardized data processing techniques able to take into account the special properties of hyperspectral data. In this paper, we provide a seminal view on recent advances in techniques for hyperspectral image processing. Our main focus is on the design of techniques able to deal with the highdimensional nature of the data, and to integrate the spatial and spectral information. Performance of the discussed techniques is evaluated in different analysis scenarios. To satisfy time-critical constraints in specific applications, we also develop efficient parallel implementations of some of the discussed algorithms. Combined, these parts provide an excellent snapshot of the state-of-the-art in those areas, and offer a thoughtful perspective on future potentials and emerging challenges in the design of robust hyperspectral imaging algorithms

Plaza, Antonio↗

Low-Power Multi-Aspect Space Radiation Detector System

The advanced space radiation detector development team at NASA Glenn Research Center (GRC) has the goal of developing unique, more compact radiation detectors that provide improved real-time data on space radiation. The team has performed studies of different detector designs using a variety of combinations of solid-state detectors, which allow higher sensitivity to radiation in a smaller package and operate at lower voltage than traditional detectors. Integration of all of these detector technologies will result in an improved detector system in comparison to existing state-of-the-art (SOA) instruments for the detection and monitoring of the deep space radiation field.

Wrbanek, John D.↗

Advanced Space Radiation Detector Technology Development

The advanced space radiation detector development team at NASA Glenn Research Center (GRC) has the goal of developing unique, more compact radiation detectors that provide improved real-time data on space radiation. The team has performed studies of different detector designs using a variety of combinations of solid-state detectors, which allow higher sensitivity to radiation in a smaller package and operate at lower voltage than traditional detectors. Integration of multiple solid-state detectors will result in an improved detector system in comparison to existing state-of-the-art (SOA) instruments for the detection and monitoring of the space radiation field for deep space and aerospace applications.

Wrbanek, John D.↗

Advanced Space Radiation Detector Technology Development

The advanced space radiation detector development team at the NASA Glenn Research Center (GRC) has the goal of developing unique, more compact radiation detectors that provide improved real-time data on space radiation. The team has performed studies of different detector designs using a variety of combinations of solid-state detectors, which allow higher sensitivity to radiation in a smaller package and operate at lower voltage than traditional detectors. Integration of multiple solid-state detectors will result in an improved detector system in comparison to existing state-of-the-art instruments for the detection and monitoring of the space radiation field for deep space and aerospace applications.

Wrbanek, John D.↗

Advanced Space Radiation Detector Technology Development

The advanced space radiation detector development team at NASA Glenn Research Center (GRC) has the goal of developing unique, more compact radiation detectors that provide improved real-time data on space radiation. The team has performed studies of different detector designs using a variety of combinations of solid-state detectors, which allow higher sensitivity to radiation in a smaller package and operate at lower voltage than traditional detectors. Integration of multiple solid-state detectors will result in an improved detector system in comparison to existing state-of-the-art instruments for the detection and monitoring of the space radiation field for deep space and aerospace applications.

Wrbanek, John D.↗

Development of a Real-Time GPS/Seismic Displacement Meter: Applications to Civilian Infrastructure in Orange and Western Riverside Counties, California

We propose a three-year applications project that will develop an Integrated Real-Time GPS/Seismic System and deploy it in Orange and Western Riverside Counties, spanning three major strike-slip faults in southern California (San Andreas, San Jacinto, and Elsinore) and significant populations and civilian infrastructure. The system relying on existing GPS and seismic networks will collect and analyze GPS and seismic data for the purpose of estimating and disseminating real-time positions and total ground displacements (dynamic, as well as static) during all phases of the seismic cycle, from fractions of seconds to years. Besides its intrinsic scientific use as a real-time displacement meter (transducer), the GPS/Seismic System will be a powerful tool for local and state decision makers for risk mitigation, disaster management, and structural monitoring (dams, bridges, and buildings). Furthermore, the GPS/Seismic System will become an integral part of California's spatial referencing and positioning infrastructure, which is complicated by tectonic motion, seismic displacements, and land subsidence. Finally, the GPS/Seismic system will also be applicable to navigation in any environment (land, sea, or air) by combining precise real-time instantaneous GPS positioning with inertial navigation systems. This development will take place under the umbrella of the California Spatial Reference Center, in partnership with local (Counties, Riverside County Flood and Water Conservation District, Metropolitan Water District), state (Caltrans), and Federal agencies (NGS, NASA, USGS), the geophysics community (SCIGN/SCEC2), and the private sector (RBF Consulting). The project will leverage considerable funding, resources, and R&D from SCIGN, CSRC and two NSF-funded IT projects at UCSD and SDSU: RoadNet (Real-Time Observatories, Applications and Data Management Network) and the High Performance Wireless Research and Education Network (HPWREN). These two projects are funded to develop both the wireless networks and the integrated, seamless, and transparent information management system that will deliver seismic, geodetic, oceanographic, hydrological, ecological, and physical data to a variety of end users in real-time in the San Diego region. CSRC is interested in providing users access to real-time, accurate GPS data for a wide variety of applications including RTK surveying/GIS and positioning of moving platforms such as aircraft and emergency vehicles. SCIGN is interested in upgrading sites to high-frequency real-time operations for rapid earthquake response and GPS seismology. The successful outcome of the project will allow the implementation of similar systems elsewhere, particularly in plate boundary zones with significant populations and civilian infrastructure. CSRC would like to deploy the GPS/Seismic System in other parts of California, in particular San Diego, Los Angeles County and the San Francisco Bay Area.

Bock, Yehuda↗

SkICAT: A cataloging and analysis tool for wide field imaging surveys

We describe an integrated system, SkICAT (Sky Image Cataloging and Analysis Tool), for the automated reduction and analysis of the Palomar Observatory-ST ScI Digitized Sky Survey. The Survey will consist of the complete digitization of the photographic Second Palomar Observatory Sky Survey (POSS-II) in three bands, comprising nearly three Terabytes of pixel data. SkICAT applies a combination of existing packages, including FOCAS for basic image detection and measurement and SAS for database management, as well as custom software, to the task of managing this wealth of data. One of the most novel aspects of the system is its method of object classification. Using state-of-theart machine learning classification techniques (GID3* and O-BTree), we have developed a powerful method for automatically distinguishing point sources from non-point sources and artifacts, achieving comparably accurate discrimination a full magnitude fainter than in previous Schmidt plate surveys. The learning algorithms produce decision trees for classification by examining instances of objects classified by eye on both plate and higher quality CCD data. The same techniques will be applied to perform higher-level object classification (e.g., of galaxy morphology) in the near future. Another key feature of the system is the facility to integrate the catalogs from multiple plates (and portions thereof) to construct a single catalog of uniform calibration and quality down to the faintest limits of the survey. SkICAT also provides a variety of data analysis and exploration tools for the scientific utilization of the resulting catalogs. We include initial results of applying this system to measure the counts and distribution of galaxies in two bands down to Bj is approximately 21 mag over an approximate 70 square degree multi-plate field from POSS-II. SkICAT is constructed in a modular and general fashion and should be readily adaptable to other large-scale imaging surveys.

Weir, N.↗

Application of the NASA Multiscale Analysis Tool: Multiscale Integration and Interoperability

In order to demonstrate NASMAT’s multiscale operability, a series of illustrative examples will be presented that focus on the application of NASMAT to practical problems. First, the multiscale integration and data recursion is demonstrated by performing a multiscale analysis using only built-in micromechanics methods. NASMAT’s integration is then highlighted by running a multiscale analysis where an external finite element software calls NASMAT. In this case, at each integration point within the finite element model, a local NASMAT analysis is performed to account for failure behavior at the constituent scale. In a similar example, an external program is called from within NASMAT. This case would be relevant for a user wanting to implement an outside micromechanics technique. A combination of these examples is then presented to further illustrate the code’s flexibility when interfacing with outside codes in a multiscale framework. For all examples, data is presented using a custom-developed visualization tool. Additional potential use cases are also addressed. Finally, the plan for upcoming features and added capabilities is discussed.

NASMAT↗

Validation of a Remote Sensing Based Index of Forest Disturbance Using Streamwater Nitrogen Data

Vegetation disturbances are known to alter the functioning of forested ecosystems by contributing to export ('leakage') of dissolved nitrogen (N), typically nitrate-N, from watersheds that can contribute to acidification of acid-sensitive streams, leaching of base cations, and eutrophication of downstream receiving waters. Yet, at a landscape scale, direct evaluation of how disturbance is linked to spatial variability in N leakage is complicated by the fact that disturbances operate at different spatial scales, over different timescales, and at different intensities. In this paper we explore whether data from synoptic streamwater surveys conducted in an Appalachian oak-dominated forested river basin in western MD (USA) can be used to test and validate a scalable, synthetic, and integrative forest disturbance index (FDI) derived from Landsat imagery. In particular, we found support for the hypothesis that the interannual variation in spring baseflow total dissolved nitrogen (TDN) and nitrate-N concentrations measured at 35 randomly selected stream stations varied as a linear function of the change in FDI computed for the corresponding set of subwatersheds. Our results demonstrate that the combined effects of forest disturbances can be detected using synoptic water quality data. It appears that careful timing of the synoptic baseflow sampling under comparable phenological and hydrometeorological conditions increased our ability to identify a forest disturbance signal.

Eshleman, Keith N.↗

Science in a Team Environment (AKA, How to Play Nicely with Others)

So you want to do NASA funded research in a spaceflight analog? There are several things about participating in an HRP managed analog that may be different from the way you normally do work in your laboratory. The purpose of this presentation is to highlight those differences and explain some of the unique aspects of doing this research. Participation in an HRP funded analog study complement, even if initially selected for funding, is not automatic and involves numerous actions from ISSMP, HRP, and the PI. There are steps that have to be taken and processes to follow before approval and ISSMP-FA integration. After the proposal and acceptance process the Investigator works closely with the Flight Analog team to ensure full integration of their study requirements into a compliment. A complement is comprised of a group of studies requiring a common platform and/or scenario that are able to be integrated on a non-interference basis for implementation. Full integration into the analog platform can be broken down into three phases: integration, preparation, and implementation. These phases occur in order with some overlap in the integration and preparation phase. The ISSMP-FA team integrates, plans and implements analog study complements. Properly defining your research requirements and getting them documented is one of the most critical components to ensure successful integration and implementation of your study, but is also one of the most likely to be neglected by PIs. Requirements that are not documented, or that are documented poorly are unlikely to get done, no matter how much you push. The process to document requirements is two-fold, consisting of an initial individual requirements integration and then a compliment requirements integration. Understanding the requirements in detail and early ensures that the science is not compromised by outside influences. This step is vital to the integration, preparation, and implementation phases. The individual requirements integration is the first step in ensuring that the research fits into an available analog platform or allows for the Flight Analog team to provide information on structural study changes for participation in the analog. At this early point investigators need to understand exactly what their requirements are to produce relevant data and convey their must have needs to the Flight Analog team. The fluid nature of analog platforms allow for minor alterations to the operational structure. Participation in analog research requires flexibility from the investigator to ensure implementation of their research into a flight like analog platform. The compliment integration requires plasticity; investigators are asked to work closely with one another and the Flight Analog team to combine research studies into a single study plan. This study plan's ultimate goal is to facilitate multiple study participation with minimal scientific impact to each individual study. The Flight Analogs team works to find the best compromise for all parties while protecting the flight like atmosphere of a particular analog. Additional restrictions, limitations and constraints may be required by the analog in order to make all of the science work. Many studies need to be combined into each complement and there are a limited number of hours available for data collection. Through data/sample sharing, we can reduce the burden on the test subject, while usually avoiding significant science impacts. Restrictions on food, exercise, medications and sleep cycle are important to consider for your research.

Platts, S. H.↗

Bayesian Optimized Deep Ensemble for Uncertainty Quantification of Deep Neural Networks: a System Safety Case Study on Sodium Fast Reactor Thermal Stratification Modeling

Deep neural networks (DNNs) are increasingly important to scientific computing and engineering system simulations. Accurate uncertainty quantification (UQ) for DNNs is critical in safety-sensitive engineering domains. Traditional Deep Ensemble (DE) methods, while easy to implement, frequently suffer from poorly calibrated uncertainty estimates and limited predictive accuracy due to reliance on fixed architectures with varied weight initializations. To address these issues, we introduce a workflow that combines Bayesian Optimization (BO) and DE. The workflow is modular, scalable, and integrates parallel BO initialized with Sobol sequences to individually optimize the hyperparameters of each ensemble member. This method enhances ensemble diversity, improves predictive accuracy, and provides reliable uncertainty estimates. We evaluate the proposed BODE approach in a sodium fast reactor thermal stratification modeling case study, where we used a densely connected convolutional neural network to predict turbulent viscosity during the reactor transient with consideration of data noise. We benchmark its performance against several optimization approaches, including baseline deep ensemble, evolutionary algorithm-optimized ensemble, ensemble formed via random search combined with greedy selection, and a BO ensemble using random initialization. Here, our results demonstrate superior performance of the developed BODE approach. In noise-free scenarios, BODE notably reduces incorrect aleatoric uncertainty and significantly enhances predictive accuracy. Under conditions of 5% and 10% Gaussian noise, BODE adaptively quantifies uncertainty proportional to data noise, achieving up to an 80% reduction in root mean square error compared to baseline methods and producing well-calibrated prediction intervals.

Bayesian optimization↗

Integration of Wireless Sensor Networks and Battery-free RFID for Advanced Reactors

To address an important need for Nuclear Power Plants (NPPs) to significantly reduce the amount of the required cables for sensor data communications, this Phase I SBIR effort successfully developed and demonstrated a novel low-cost proof-of-concept prototype of a secure wireless sensor network backbone communications system. This system combines commercially available low power, low cost XBEE wireless communications network and passive (battery-free) Radio Frequency Identification (RFID) systems to report individual sensor data and their location through the containment wall for rapid response to anomalies in nuclear facilities. This WIreless Sensing and Locating (WISLO) system network architecture allows non-intrusive wireless collection of sensor data with the sensor’s accurate location information from inside of the instrumentation or containment area with minimal need for power sources. The multi-node sensor data in the containment area is wirelessly transmitted to outside through the metal reinforced concrete walls without the need for any batteries. The WISLO system could be readily used in current reactor fleet and future advanced reactors, as well as in small modular reactors (SMR). The WISLO system is the first dual frequency battery-free trough the wall communications backbone system developed specifically for use in nuclear power plants. It not only can modernize the sensor monitoring practices in the existing reactor fleet, but also offers a secure, low-cost solution to advanced reactors and SMRs by removing cables and issues related to them such as cable integrity, reporting delays, and installation and maintenance costs. The intent is to improve process safety, reliability, efficiency, and cost effectiveness to the monitoring and maintenance process in current and future plants. As we address the next productization and manufacturing capabilities in the next phase, this system will serve the needs of many commercial and government applications in remote monitoring of sensor data that demand battery-free transmission of sensor data such as Internet-of-Things (IOT).

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Machine-Learning-Driven Discovery of Water Splitting BaFe 2 O 4 and Human-in-the-Loop Improvement via Al-Substitution for Increased Thermal Stability

Thermochemical hydrogen (TCH) production offers a promising method for converting thermal energy into hydrogen fuel through heat-driven redox cycles of metal oxides. Here, in this work a defect graph neural network (dGNN) was used to predict oxygen vacancy formation energies ΔH V O combined with Materials Project predictions of oxygen chemical potential stability to screen candidate oxides via high-throughput database analysis. BaFe 2 O 4 was identified as a promising material for experimental validation based on its predicted ΔH V O , oxygen chemical potential stability range, and potential for tunable substitutions to improve thermal properties. Experimental validation using thermogravimetric analysis (TGA), stagnation flow reactor (SFR), X-ray diffraction (XRD), and electron microscopy confirmed positive water-splitting behavior but also revealed limitations in thermal stability under aggressive reduction conditions. To address this, a human-in-the-loop modification strategy was employed introducing Al substitution in BaFe 2–x Al x O 4 ; this modification improves thermal stability, alters the crystal structure and enhances overall performance. These results demonstrate a combined computational and experimental workflow in which machine learning accelerates identification of promising candidates, while targeted experimental design enables optimization of functional performance. This approach advances the development of robust, cost-effective TCH materials and highlights the importance of integrating data-driven discovery with human-guided materials design in paving the way for scalable hydrogen production technologies.

organic↗