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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 919 records · Page 51
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Expanded genetic variation (SNP) and phenomics (image based) dataset for Populus trichocarpa

The image dataset consists of 11,791 images representing 1,219 genotypes of Populus trichocarpa undergoing in planta regeneration. Genotypes were imaged with a median of four weekly timepoints and a median of two replicates each. A representative and diverse subset of 249 images was annotated using the IDEAS annotation interface (ideas.eecs.oregonstate.edu) and these annotated images were used to train a deep semantic segmentation model (PSPNet), which was deployed for inference over the entire dataset. Annotated classes include specific stages of regeneration (callus and shoot) in addition to unregenerated plant material and background. Statistics of relative tissue area were extracted and used for downstream genetic association mapping in a genome-wide association study. The SNP dataset consists of over 40 million single-nucleotide polymorphisms across 1,323 wild accessions of Populus trichocarpa

09 BIOMASS FUELS↗
NASA NTRS1972

Skylab Saturn 1B flight manual

A Saturn 1B Flight Manual provides launch vehicle systems descriptions and predicted performance data for the Skylab missions. Vehicle SL-2 (SA-206) is the baseline for this manual; but, as a result of the great similarity, the material is representative of SL-3 and SL-4 launch vehicles, also. The Flight Manual is not a control document but is intended primarily as an aid to astronauts who are training for Skylab missions. In order to provide a comprehensive reference for that purpose, the manual also contains descriptions of the ground support interfaces, prelaunch operations, and emergency procedures. Mission variables and constraints are summarized, and mission control monitoring and data flow during launch preparation and flight are discussed.

Source record↗
NASA NTRS1982

Near surface observations

Learning objectives include: (1) developing an understanding of the implications of the term "near surface observations"; (2) associating the appearance of large ground features as seen in satellite imagery with their appearance as seen from the ground; (3) grasping criteria and procedures for selecting training sites on the ground for use in supervised classification; (4) running through an example of training site selection; (5) becoming familiar with several methods of accuracy assessment; (6) becoming aware of the approach and value of making supporting measurements of the spectral and physical properties of materials on the ground and from aircraft; (7) taking note of the different types of instruments used in making specific ground measurements; and (8) appreciating the rationale underlying laboratory and field studies on or near the Earth's surface for the purpose of developing new sensor systems.

Source record↗
NASA NTRS2009

Radial Halbach Magnetic Bearings

Radial Halbach magnetic bearings have been investigated as part of an effort to develop increasingly reliable noncontact bearings for future high-speed rotary machines that may be used in such applications as aircraft, industrial, and land-vehicle power systems and in some medical and scientific instrumentation systems. Radial Halbach magnetic bearings are based on the same principle as that of axial Halbach magnetic bearings, differing in geometry as the names of these two types of bearings suggest. Both radial and axial Halbach magnetic bearings are passive in the sense that unlike most other magnetic bearings that have been developed in recent years, they effect stable magnetic levitation without need for complex active control. Axial Halbach magnetic bearings were described in Axial Halbach Magnetic Bearings (LEW-18066-1), NASA Tech Briefs, Vol. 32, No. 7 (July 2008), page 85. In the remainder of this article, the description of the principle of operation from the cited prior article is recapitulated and updated to incorporate the present radial geometry. In simplest terms, the basic principle of levitation in an axial or radial Halbach magnetic bearing is that of the repulsive electromagnetic force between (1) a moving permanent magnet and (2) an electric current induced in a stationary electrical conductor by the motion of the magnetic field. An axial or radial Halbach bearing includes multiple permanent magnets arranged in a Halbach array ("Halbach array" is defined below) in a rotor and multiple conductors in the form of wire coils in a stator, all arranged so the rotary motion produces an axial or radial repulsion that is sufficient to levitate the rotor. A basic Halbach array (see Figure 1) consists of a row of permanent magnets, each oriented so that its magnetic field is at a right angle to that of the adjacent magnet, and the right-angle turns are sequenced so as to maximize the magnitude of the magnetic flux density on one side of the row while minimizing it on the opposite side. The advantage of this configuration is that it makes it possible to approach the theoretical maximum force per unit area that could be exerted by a given amount of permanent-magnet material. The configuration is named after physicist Klaus Halbach, who conceived it for use in particle accelerators. Halbach arrays have also been studied for use in magnetic-levitation ("maglev") railroad trains. In a radial Halbach magnetic bearing, the basic Halbach arrangement is modified into a symmetrical arrangement of sector-shaped permanent magnets mounted on the outer cylindrical surface of a drum rotor (see Figure 2). The magnets are oriented to concentrate the magnetic field on their radially outermost surface. The stator coils are mounted in a stator shell surrounding the rotor.

Eichenberg, Dennis J.↗
DOE OSTI2020

The TRANSCEND University Consortium: An Overview - 20106

The UK government is committed to nuclear energy having an important role in delivering a secure, low-carbon and affordable energy future. Projections indicate that between now and 2035, ∼14 GW of new nuclear generating capacity may be built. Successful delivery of this strategy recognises the need for research and development, skills development and international collaboration as key enablers. One key area is the decommissioning and clean-up of all civil nuclear licensed sites and the implementation of geological disposal of highly active wastes, with a central component being a joined-up approach to nuclear R and D across government, industry and academia which benefits the UK economy and ensures the security of supply. Essential to public acceptance of this strategy remains a demonstrable ability to safely manage and dispose of waste, with acceptance directly linked to having scientifically robust routes for its safe clean-up and disposal. There therefore remains an ongoing need for further research in the areas of decommissioning, immobilisation and management of nuclear waste, and there is significant government and stakeholder support for such research. Given the needs of both new nuclear power generation and legacy wastes, there is a requirement to develop innovative approaches to waste management and decommissioning. Following on from earlier, highly successful projects supported by UK Research and Innovation's Energy Programme, the work of the TRANSCEND (Transformative Science and Engineering for Nuclear Decommissioning) consortium is part of the response to these needs, providing support to a strong and internationally leading group of researchers in this key technology area. The consortium is a collaboration between 11 universities, supported by 8 key industry partners, with a total funding of UK Pounds 9.5 M from the UK Engineering and Physical Research Council, the universities and key project partners. The research being carried out is multidisciplinary and covers both fundamental and applied topics, with 40 research projects clustered in four technical themes: integrated waste management; site decommissioning and remediation; spent fuels; and nuclear materials. Key aims of the consortium are to extend and further develop a relevant academic skill base in the UK associated with the needs of nuclear waste management and decommissioning, to train the next generation of UK researchers, equipping them with skills and experiences relevant to nuclear waste management and decommissioning issues, and to carry out cutting-edge research that has the potential to provide new and innovative pathways to better management of both legacy and future nuclear wastes. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2021

Autonomous reinforcement learning agent for chemical vapor deposition synthesis of quantum materials

Abstract Predictive materials synthesis is the primary bottleneck in realizing functional and quantum materials. Strategies for synthesis of promising materials are currently identified by time-consuming trial and error and there are no known predictive schemes to design synthesis parameters for materials. We use offline reinforcement learning (RL) to predict optimal synthesis schedules, i.e., a time-sequence of reaction conditions like temperatures and concentrations, for the synthesis of semiconducting monolayer MoS 2 using chemical vapor deposition. The RL agent, trained on 10,000 computational synthesis simulations, learned threshold temperatures and chemical potentials for onset of chemical reactions and predicted previously unknown synthesis schedules that produce well-sulfidized crystalline, phase-pure MoS 2 . The model can be extended to multi-task objectives such as predicting profiles for synthesis of complex structures including multi-phase heterostructures and can predict long-time behavior of reacting systems, far beyond the domain of molecular dynamics simulations, making these predictions directly relevant to experimental synthesis.

36 MATERIALS SCIENCE↗
DOE OSTI2020

UC LANL Postdoc Entrepreneur Fellowship Cohort Four

Three Laboratory postdoctoral researchers have been selected for this year's cohort of Entrepreneur Fellows. The six-month fellowship program - a joint initiative of the University of California and Los Alamos, now in its fourth year - supports early career scientists explore applications and evaluate market opportunities for their technologies. The Lab selects Entrepreneur Fellows based on the potential for their projects to have both scientific and commercial impact. The fellows receive six months of facilitated training and mentoring, as well as funding to engage in customer discovery, market exploration and technology advancement

36 MATERIALS SCIENCE↗
DOE OSTI1991

Nuclear Safety [Vol. 32, No. 1, January-March 1991]

Nuclear Safety is a review journal that covers significant developments in the field of nuclear safety. Its scope includes the analysis and control of hazards associated with nuclear energy, operations involving fissionable materials, and the products of nuclear fission and their effects on the environment. Primary emphasis is on safety in reactor design, construction, and operation; however, the safety aspects of the entire fuel cycle, including fuel fabrication, spent-fuel processing, nuclear waste disposal, handling of radioisotopes, and environmental effects of these operations, are also treated. Table of Contents for this issue follows. GENERAL SAFETY CONSIDERATIONS: 1 The Safety Review and Approval Process for Space Nuclear Power Sources, G. L. Bennett; 19 Report on the American Nuclear Society International Topical Meeting: "The Safety, Status, and Future of Non-Commercial Reactors and Irradiation Facilities", E. G. Silver; 35 Book Review: Fission Product Transport Processes in Reactor Accidents, Proceedings to the International Centre tor Heat and Mass Processes T. S. Kress; 38 Fast Reactor Technology in the 1990s: A Summary of the 1990 International Fast Reactor Safety Meeting, A. E. Levin; ACCIDENT ANALYSIS: 56 Effects of Chemical Phenomena on LWR Severe Accident Fission Product Behavior, A. P. Malinauskas and T. S. Kress; CONTROL AND INSTRUMENTATION: 65 Technical Note: Safety Parameter Display Systems—10 Years Later, R. J. Eckenrode; 68 Potential Application of Neural Networks to the Operation of Nuclear Power Plants, R. E. Uhrig; DESIGN FEATURES: 80 Twenty-First DOE/NRC Nuclear Air-Cleaning Conference, R. R. Bellamy, D. W. Moeller, and M. W. First; 91 Impact of an Apparent Radiation Embrittlement Rate on the Life Expectancy of PWR Vessel Supports, R. D. Cheverton, G. C. Robinson, W. E. Pennell, and R. K. Nanstad; ENVIRONMENTAL EFFECTS: 103 Technical Note: The Impact of Offsite Factors on the Safety Performance of Small Nuclear Power Plants, Yu. D. Baranaev and A. N. Viktorov; WASTE AND SPENT FUEL MANAGEMENT: 109 Activities Related to Waste Management, Compiled by E. G. Silver; OPERATING EXPERIENCES: 118 Reactor Shutdown Experience, Compiled by J. W. Cletcher; 121 Selected Safety-Related Events, Compiled by G. A. Murphy; 123 Operating U.S. Power Reactors, Compiled by E. G. Silver; RECENT DEVELOPMENTS: 140 General Administrative Activities, Compiled by E. G. Silver; 150 Reports, Standards, and Safety Guides, D. S. Queener; 155 Status of Power-Reactor Licensing Activities, Compiled by E. G. Silver; 157 Proposed Rule Changes as of Sept. 30, 1990; ANNOUNCEMENTS: 79 MIT Offers Summer Program on Nuclear Power Reactor Safety; 108 Harvard School of Public Health Offers Several Short Courses; 139 Short Course and Workshop on Nuclear Criticality Safety at University of New Mexico; 160 SCK/CEN Announces Training Course on Emergency Planning and Response; 161 The Authors; 164 Indexes to Nuclear Safety, Volume 31

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2021

A study of real-world micrograph data quality and machine learning model robustness

Abstract Machine-learning (ML) techniques hold the potential of enabling efficient quantitative micrograph analysis, but the robustness of ML models with respect to real-world micrograph quality variations has not been carefully evaluated. We collected thousands of scanning electron microscopy (SEM) micrographs for molecular solid materials, in which image pixel intensities vary due to both the microstructure content and microscope instrument conditions. We then built ML models to predict the ultimate compressive strength (UCS) of consolidated molecular solids, by encoding micrographs with different image feature descriptors and training a random forest regressor, and by training an end-to-end deep-learning (DL) model. Results show that instrument-induced pixel intensity signals can affect ML model predictions in a consistently negative way. As a remedy, we explored intensity normalization techniques. It is seen that intensity normalization helps to improve micrograph data quality and ML model robustness, but microscope-induced intensity variations can be difficult to eliminate.

36 MATERIALS SCIENCE↗
NASA NTRS1997

An Exposure Prevention Plan for an Anhydrous Ammonia Handling System

In July of 1996, the Industrial Hygiene Team of the Environmental Management Office at NASA Lewis Research Center was contacted by the Space Station Program Office to conduct ammonia awareness training for a team of engineers and technicians. The team was tasked with assembling and operating an ammonia handling system for testing of a photovoltaic radiator at the NASA Plum Brook Station Space Power Facility. The ammonia handling system supports a radiator designed to radiate excess heat from a photovoltaic array module used to provide power to the International Space Station. The system would consist of a hazardous materials trailer equipped with an anhydrous ammonia tank, heater, accumulator, chiller, and flow bench. Meetings were held with representatives from the Space Station Program Office, the engineers and Plum Brook safety personnel. Guidance was also provided by representatives from Kennedy Space Center. Determinations were made concerning the locations and types of potential exposures and a plan was developed which included training, personal protective equipment, engineering controls and emergency response. Various organizations including the Plum Brook Safety Committee, the Lewis Environmental Management Office, the Test Readiness Review Board and the Program Office all had requirements that had to be met in order to satisfy themselves that all personnel involved in the operation of the system would be safe. What resulted was a comprehensive plan that provided more than adequate safety measures and succeeded in protecting all personnel from the hazards of the ammonia system. Testing of the photovoltaic radiator was successful and although ammonia leaks were detected and maintenance of the system was ongoing, no one was injured. It was felt that the training and controls in place allowed for a comfort level that did not interfere with the operations.

Cathy L Padolewski↗
DOE OSTI2025

Out-of-distribution detection with non-parametric density estimation for models predicting processing history of uranium ore concentrates

The rapid advancement in machine learning (ML) and computer vision (CV) coincides with the growth of interest in deploying these ML/CV models in numerous fields from medicine to social science. Similar to those areas, we have witnessed a great number of works in materials science employing ML/CV models – neural networks in particular – in their studies in recent years. These models have proven to obtain accurate performance in various tasks. However, these models struggle to attain a similar performance when encountering test samples coming from a distribution that is different from the training set. More importantly, they fail without providing any warning to the users. Therefore, we propose a framework for detecting out-of-distribution (OOD) samples to alert users when a human intervention might be necessary in this work. Specifically, we explore the use of a non-parametric density estimation method to detect OOD samples. Here, we assess OOD detection capability of the proposed framework on ML models developed for categorizing precipitation routes of U 3 O 8 when encountering OOD datasets that contain samples (1) undergone different imaging acquisition process, (2) undergone different material synthesis process, and (3) different materials than ID set. Through those experiments, we achieve an average area under the receiver operating characteristic (AUROC) of at least 91% on average in detecting OOD samples. With minimal overhead cost and superior performance, the proposed framework enables a reliable and safe system when deploying in real-world scenarios.

Convolutional neural networks↗
DOE OSTI2025

Predictive Assessment of the Chemical Composition of Coal Ash in Reserve at U.S. Disposal Sites

In the United States, more than 2 Gt of coal combustion residuals (i.e., coal ash) are stored in hundreds of disposal units. Recent federal regulations mandate the closure or retrofitting of most coal ash impoundments, presenting significant challenges for waste management. These regulatory pressures also present opportunities to reuse coal ash. However, the quality and quantity of discarded coal ash across the U.S. are not well known, even though this information is crucial for spurring its reuse for conventional and new material applications. This study describes a predictive model for the major element composition of coal ash in reserve at disposal sites of major U.S. coal-fired power plants. This model was constructed from coal purchase records of 705 power stations from 1973 to 2022 and was trained on coal ash composition data, showing that coal ash elemental composition is strongly associated with the source of feedstock coal. The model showed regional shifts in the major element contents of ash produced by power plants in the last 50 years, particularly for calcium and iron (expressed as %CaO and %Fe2O3), as power stations changed their source of coal over this time frame. Our approach enables an estimation of chemical composition for ash stored in waste impoundments at individual power stations. Such information can help to delineate the regional market resource potential of supplementary cements for concrete and other material innovations that would utilize coal ash harvested from disposal sites across the U.S.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2020

Active learning for robust, high-complexity reactive atomistic simulations

Machine learned reactive force fields based on polynomial expansions have been shown to be highly effective for describing simulations involving reactive materials. Nevertheless, the highly flexible nature of these models can give rise to a large number of candidate parameters for complicated systems. In these cases, reliable parameterization requires a well-formed training set, which can be difficult to achieve through standard iterative fitting methods. In this paper, we present an active learning approach based on cluster analysis and inspired by Shannon information theory to enable semi-automated generation of informative training sets and robust machine learned force fields. The use of this tool is demonstrated for development of a model based on linear combinations of Chebyshev polynomials explicitly describing up to four-body interactions, for a chemically and structurally diverse system of C/O under extreme conditions. We show that this flexible training database management approach enables development of models exhibiting excellent agreement with Kohn–Sham density functional theory in terms of structure, dynamics, and speciation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Echo state network for coarsening dynamics of charge density waves

An echo state network (ESN) is a type of reservoir computer that uses a recurrent neural network with a sparsely connected hidden layer. Compared with other recurrent neural networks, one great advantage of ESN is the simplicity of its training process. Yet, despite the seemingly restricted learnable parameters, ESN has been shown to successfully capture the spatial-temporal dynamics of complex patterns. Here we build an ESN to model the coarsening dynamics of charge-density waves (CDWs) in a semiclassical Holstein model, which exhibits a checkerboard electron density modulation at half-filling stabilized by a commensurate lattice distortion. The inputs to the ESN are local CDW order parameters in a finite neighborhood centered around a given site, while the output is the predicted CDW order of the center site at the next time step. Special care is taken in the design of couplings between hidden layer and input nodes to ensure lattice symmetries are properly incorporated into the ESN model. Since the model predictions depend only on CDW configurations of a finite domain, the ESN is scalable and transferrable in the sense that a model trained on dataset from a small system can be directly applied to dynamical simulations on larger lattices. Furthermore, our work opens avenues for efficient dynamical modeling of pattern formations in functional electron materials.

2-dimensional systems↗
DOE OSTI2021

Power Plant Testing of Ultrasonic Measurements of Temperature Distributions and Heat Fluxes to Heat Exchange Surfaces

Extreme environmental conditions are common in energy conversion applications, in which the most hardened insertion sensors often do not perform reliably for long. On the other hand, ultrasonic measurements can be acquired noninvasively, with sensitive components kept away from the damaging environment. We have previously developed the ultrasonic method for measuring the spatial distribution of temperatures in solid materials applicable when large thermal gradients are present. In the developed approach, we use the echogenically segmented ultrasound propagation path, structured to contain engineered or naturally occurring echogenic features, to produce a train of echoes in response to an external pulse of ultrasonic excitation. This paper outlines the testing results of this approach applied to the temperature distribution measurements to a waterwall of a 500 MW power-plant utility boiler. The validation results obtained over the prolonged power plant test show that the estimated temperature profile is correctly captured, and the measurement accuracy can be comparable with traditional insertion sensors, such as thermocouples. Overall, the testing has confirmed that the developed approach has matured to become an attractive alternative to conventional sensing in solving challenging problems of long-term temperature measurements in extreme environments. Heat fluxes and thermal stresses in the structure can then be characterized noninvasively using the measured temperature distribution as the basis.

Walton, Kenneth↗
NASA NTRS1981

Teaching/learning principles

The potential remote sensing user community is enormous, and the teaching and training tasks are even larger; however, some underlying principles may be synthesized and applied at all levels from elementary school children to sophisticated and knowledgeable adults. The basic rules applying to each of the six major elements of any training course and the underlying principle involved in each rule are summarized. The six identified major elements are: (1) field sites for problems and practice; (2) lectures and inside study; (3) learning materials and resources (the kit); (4) the field experience; (5) laboratory sessions; and (6) testing and evaluation.

Hankins, D. B.↗
NASA NTRS1989

Forging Long Shafts On Disks

Isothermal-forging apparatus produces long shafts integral with disks. Equipment based on modification of conventional isothermal-forging equipment, required stroke cut by more than half. Enables forging of shafts as long as 48 in. (122 cm) on typical modified conventional forging press, otherwise limited to making shafts no longer than 18 in. (46cm). Removable punch, in which forged material cools after plastic deformation, essential novel feature of forging apparatus. Technology used to improve such products as components of gas turbines and turbopumps and of other shaft/disk parts for powerplants, drive trains, or static structures.

Tilghman, Chris↗
DOE OSTI2024

Production of High Specific Activity 155 Tb, 161 Tb and 203 Pb for Research and Clinical Applications: Effective Target Design, Target Material Recycling and Radioisotope Separation (Final Technical Report)

The overall objectives of this project were (1) to develop methods for the production and separation of a diagnostic and therapeutic or “theranostic” pair of radioisotopes, terbium-155 ( 155 Tb) and terbium-161 ( 161 Tb) and (2) to train graduate students and postdoctoral fellows in technologies and methods used in radionuclide production. Radionuclides can be incorporated into drugs called radiopharmaceuticals that target a specific disease (e.g., cancer). The need for theranostic radionuclides is escalating with the clinical translation of radiopharmaceuticals due to their implementation in personalized medicine, which has demonstrated enhanced patient treatments. High purity and high specific activity radionuclides are critical for theranostic agent development, for example to maintain diagnostic image quality, to minimize radiation dose to the patient, and to increase uptake in the targeted tissue (e.g., tumor), especially in the case of receptor- and antigen-targeted agents. The 155 Tb (diagnostic) and 161 Tb (therapeutic) radioisotopes that were generated through this project are a theranostic pair with demonstrated potential for the development and translation into individualized, targeted, and dosimetry-driven radiotherapies. However, the development of such radiotherapies has been hindered by the lack of a routine and reliable supply of these isotopes in the United States. Methods for the production, separation, and supply of 155 Tb and 161 Tb were investigated and developed in this project. Further, the strong emphasis throughout the project on the training of graduate students and postdoctoral fellows has helped to ensure and enhance the nuclear science workforce through the training of the next generation of highly qualified scientists in nuclear and radiochemistry. This grant also continued a collaboration between scientists at the University of Washington (UW), the University of Missouri (MU) and Brookhaven National Laboratory (BNL). All three institutions were involved in the project, but to different degrees on the various tasks through which the overall objectives were met.

07 ISOTOPE AND RADIATION SOURCES↗