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All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Artificial Intelligence/Machine Learning Technologies for Advanced Reactors (Workshop Summary Report)

A workshop on artificial intelligence and machine learning (AI/ML) for advanced reactors (AR) was held October 5-6, 2021. The workshop was to be attended in-person at ANL but COVID restrictions forced the workshop to go virtual. The objectives of the workshop were to identify the most promising AI/ML opportunities for improving advanced reactor design, optimizing plant performance, and enhancing economic competitiveness and to develop an understanding of the scientific, engineering and licensing challenges facing their application. The workshop planning committee included GAIN, EPRI and NEI and members of three national laboratories (ANL, INL, and ORNL). The workshop was attended by more than 200 individuals representing academic and scientific institutions and the nuclear power industry. The definition put forth for an AI/ML system was one that perceives its environment and takes actions that maximize its chance of achieving its goals. In this report AI/ML refers to next generation algorithms that include deep learning, statistical analysis and data analytics and associated scientific computing and their potential application to the design, licensing, operation and maintenance of ARs. These methods typically incorporate models built from process data and may also include data generated by simulations that represent the behavior of a system. The workshop was organized in response to the growing interest in application of AI/ML for improving the economic competitiveness of nuclear energy. Increasingly more resources are being allocated to investigating the benefits of AI/ML methods. The DOE created the Artificial Intelligence & Technology Office to promote their development. And within the Office of Nuclear Energy, resources have been allocated to explore and understand the potential benefits of AI/ML. Additionally, the national laboratories are strategically positioned with DOE computing facilities such as Summit, Perlmutter, Aurora and Frontier that support large-scale simulations, hybrid HPC models with AI surrogates, and the exploration of new types of generative models emerging from multi-model data streams and sources. The workshop was organized with members of the AR community to understand the effort and to identify the level of interest and progress in this emerging technology. The workshop discussions focused on identifying opportunities for AI/ML across diverse areas of the nuclear industry and identifying current scientific and engineering challenges for advanced reactors that might be addressed through transformational uses of AI/ML. Discussion panels focused on four high-interest technical domains for advanced reactors: design, maintenance and operations, energy storage, and materials. The results of those discussions are summarized in this report. This includes opportunities that were identified for exploiting AI techniques and methods to improve the efficacy and efficiency of reactor analysis and to improve the operation and optimization of advanced reactors. Advanced reactor developers expressed an interest in learning more about AI/ML methods and their application. This included understanding whether ML methods can provide an advantage over existing nonlinear data regression methods for collapsing high-fidelity simulation results into faster running models. A consensus emerged that AR advances planned for the next decade will benefit from the use of AI/ML tools. The need exists to understand and model complex systems across length scales and modalities. AI/ML is a tool for discovery that can yield a set of engineering principles for use by nuclear engineers, licensing bodies, and operators to solve problems in plant design, safety analyses, autonomous operation, and predictive maintenance. While AI/ML represents a new set of tools, an awareness by the nuclear community of the full potential is still in the early stages so there is a need to increase awareness. It appears that the wide-spread adoption of AI/ML tools for ARs would be facilitated by future educational workshops that describe foundational methods and capabilities and describe successful applications.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2023

Study of Storage Requirements and Costs for Shaping Renewables and Nuclear Energy (FY23 Summary Report)

To decarbonize electricity generation primarily by using wind and solar resources, it is likely that additional low (or zero) carbon dioxide (CO 2 ) alternatives will be required for ensuring a reliable electricity supply. This study extends the work and modeling framework that we consolidated in FY 2022, by assessing the zero-CO 2 pathways of a Texas power system in which the availability of variable renewable energy (VRE), nuclear energy, and energy storage types (i.e., battery and thermal energy storage [TES]) are considered the sole resources available for expansion. Using the Risk Analysis Virtual Environment (RAVEN) and Holistic Energy Resource Optimization Network (HERON) frameworks, this study investigates the market of two nuclear energy technologies (i.e., large light-water reactors [LWRs] and LWR-type small modular reactors [SMRs]) under two plausible storage coupling scenarios (i.e., electric coupling and direct thermal coupling). We also explore optimal environments for nuclear energy deployment, and identify key performance characteristics that make nuclear energy economically viable in areas with significant intermittent energy sources. Our analysis encompasses 24 cases. We model the least-cost grid systems, highlight the potential for a coupled LWR-TES approach, and utilize SMRs to achieve deep decarbonization in an affordable, technically feasible manner. We also examine seasonal variations in balancing electricity supply and demand, and account for varying performance, costs, and grid constraints. Overall, the findings of our modeling afford valuable insights for supporting future technology investment decisions in the energy sector.

25 ENERGY STORAGE↗
DOE OSTI2017

The Ocean's Vital Skin: Toward an Integrated Understanding of the Sea Surface Microlayer

Despite the huge extent of the ocean’s surface, until now relatively little attention has been paid to the sea surface microlayer (SML) as the ultimate interface where heat, momentum and mass exchange between the ocean and the atmosphere takes place. Via the SML, large-scale environmental changes in the ocean such as warming, acidification, deoxygenation, and eutrophication potentially influence cloud formation, precipitation, and the global radiation balance. Due to the deep connectivity between biological, chemical, and physical processes, studies of the SML may reveal multiple sensitivities to global and regional changes. Understanding the processes at the ocean’s surface, in particular involving the SML as an important and determinant interface, could therefore provide an essential contribution to the reduction of uncertainties regarding ocean-climate feedbacks. This review identifies gaps in our current knowledge of the SML and highlights a need to develop a holistic and mechanistic understanding of the diverse biological, chemical, and physical processes occurring at the ocean-atmosphere interface. We advocate the development of strong interdisciplinary expertise and collaboration in order to bridge between ocean and atmospheric sciences. Although this will pose significant methodological challenges, such an initiative would represent a new role model for interdisciplinary research in Earth System sciences.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2015

Acetate Metabolism in Anaerobes from the Domain Archaea

Acetate and acetyl-CoA play fundamental roles in all of biology, including anaerobic prokaryotes from the domains Bacteria and Archaea, which compose an estimated quarter of all living protoplasm in Earth’s biosphere. Anaerobes from the domain Archaea contribute to the global carbon cycle by metabolizing acetate as a growth substrate or product. They are components of anaerobic microbial food chains converting complex organic matter to methane, and many fix CO2 into cell material via synthesis of acetyl-CoA. They are found in a diversity of ecological habitats ranging from the digestive tracts of insects to deep-sea hydrothermal vents, and synthesize a plethora of novel enzymes with biotechnological potential. Ecological investigations suggest that still more acetate-metabolizing species with novel properties await discovery.

carbon monoxide↗
NASA NTRS1986

Solid lubrication design methodology, phase 2

The high temperature performance of solid lubricated rolling elements was conducted with a specially designed traction (friction) test apparatus. Graphite lubricants containing three additives (silver, phosphate glass, and zinc orthophosphate) were evaluated from room temperature to 540 C. Two hard coats were also evaluated. The evaluation of these lubricants, using a burnishing method of application, shows a reasonable transfer of lubricant and wear protection for short duration testing except in the 200 C temperature range. The graphite lubricants containing silver and zinc orthophosphate additives were more effective than the phosphate glass material over the test conditions examined. Traction coefficients ranged from a low of 0.07 to a high of 0.6. By curve fitting the traction data, empirical equations for slope and maximum traction coefficient as a function of contact pressure (P), rolling speed (U), and temperature (T) can be developed for each lubricant. A solid lubricant traction model was incorporated into an advanced bearing analysis code (SHABERTH). For comparison purposes, preliminary heat generation calculations were made for both oil and solid lubricated bearing operation. A preliminary analysis indicated a significantly higher heat generation for a solid lubricated ball bearing in a deep groove configuration. An analysis of a cylindrical roller bearing configuration showed a potential for a low friction solid lubricated bearing.

Pallini, R. A.↗
NASA NTRS1990

Goldstone intracomplex connected element interferometry

Interferometric observations of the radio source pair 3C 84 and OE 400 were made on the 21 km baseline between Deep Space Station (DSS) 13 and DSS 15 to explore the angular navigation potential of intracomplex connected element interferometry (CEI). The differential phase-delay observable formed from pairs of 3 minute scans exhibited a precision of 1 psec, while the actual scatter of the phase-delay residuals for eleven scans over the 90 minute observing session was about 10 psec, consistent with the expected few millimeter fluctuations in the wet tropospheric path delay. Fitting for the position of OE 400 relative to 3C 84 yielded an error ellipse with a semi-minor axis of 60 nrad. Given the short data arc in this experiment, the orthogonal direction in the plane of the sky is not well determined; however, a second baseline or a data arc spanning a larger fraction of the source mutual visibility window could provide simultaneous determination of both right ascension and declination. Examination of the phase-delay residuals supports the accuracy of the cycle ambiguity resolution. However, reliable phase ambiguity resolution will pose the most significant challenge to routine use of CEI for spacecraft tracking, particularly when the a priori spacecraft source position is not well known. Several approaches for ambiguity resolution are briefly outlined.

Edwards, C. D.↗
NASA NTRS1991

Steady state toroidal magnetic field at earth's core-mantle boundary

Measurements of the dc electrical potential near the top of earth's mantle have been extrapolated into the deep mantle in order to estimate the strength of the toroidal magnetic field component at the core-mantle interface. Recent measurements have been interpreted as indicating that at the core-mantle interface, the magnetic toroidal and poloidal field components are approximately equal in magnitude. A motivation for such measurements is to obtain an estimate of the strength of the toroidal magnetic field in the core, a quantity important to our understanding of the geomagnetic field's dynamo generation. Through the use of several simple and idealized calculation, this paper discusses the theoretical relationship between the amplitude of the toroidal magnetic field at the core-mantle boundary and the actual amplitude within the core. Even with a very low inferred value of the toroidal field amplitude at the core-mantle boundary, (a few gauss), the toroidal field amplitude within the core could be consistent with a magnetohydrodynamic dynamo dominated by nonuniform rotation and having a strong toroidal magnetic field.

Levy, Eugene H.↗
NASA NTRS1991

Characteristics of ejecta and alluvial deposits at Meteor Crater, Arizona and Odessa Craters, Texas: Results from ground penetrating radar

Previous ground penetrating radar (GRP) studies around 50,000 year old Meteor Crater revealed the potential for rapid, inexpensive, and non-destructive sub-surface investigations for deep reflectors (generally greater than 10 m). New GRP results are summarized focusing the shallow sub-surfaces (1-2 m) around Meteor Crater and the main crater at Odessa. The following subject areas are covered: (1) the thickness, distribution, and nature of the contact between surrounding alluvial deposits and distal ejecta; and (2) stratigraphic relationships between both the ejecta and alluvium derived from both pre and post crater drainages. These results support previous conclusions indicating limited vertical lowering (less than 1 m) of the distal ejecta at Meteor Crater and allow initial assessment of the gradational state if the Odessa craters.

Grant, J. A.↗
NASA NTRS1992

Percolation analysis of nonlinear structures in scale-free two-dimensional simulations

Results are presented of applying percolation analysis to several two-dimensional N-body models which simulate the formation of large-scale structure. Three parameters are estimated: total area (a(c)), total mass (M(C)), and percolation density (rho(c)) of the percolating structure at the percolation threshold for both unsmoothed and smoothed (with different scales L(s)) nonlinear with filamentary structures, confirming early speculations that this type of model has several features of filamentary-type distributions. Also, it is shown that, by properly applying smoothing techniques, many problems previously considered detrimental can be dealt with and overcome. Possible difficulties and prospects with the use of this method are discussed, specifically relating to techniques and methods already applied to CfA deep sky surveys. The success of this test in two dimensions and the potential for extrapolation to three dimensions is also discussed.

Dominik, Kurt G.↗
NASA NTRS1993

Precision X-band Doppler and ranging navigation for current and future Mars exploration missions

This paper describes a navigation error covariance analysis of two scenarios derived from the Mars Observer mission and the planned Mars Environmental SURvey (MESUR) Pathfinder mission, respectively. The analysis was performed to establish the potential navigational performance of the X-band tracking system in NASA's Deep Space Network, and to evaluate the sensitivity of the predicted performance to variations in the quantity of data acquired, the ground system error modeling assumptions, and data reduction schemes. The simulated data arcs used in the analysis are representative of the actual data arcs that will be used to predict the aim point for the Mars orbit insertion maneuver, in the case of Mars Observer, and the interplanetary trajectory aim point corresponding to the target Mars landing site in the case of MESUR Pathfinder. The results indicate that with a suitable sequential data reduction scheme and accurate calibrations of instrumentation, transmission media, and platform model parameters, navigation accuracies of 5 to 15 km (1 sigma) can be achieved, equivalent to 15 to 40 nrad in geocentric angle uncertainty.

Estefan, Jeffrey A.↗
NASA NTRS2000

Dynamic Capability of an Operating Stirling Convertor

The NASA John H. Glenn Research Center and the US Department of Energy are currently developing a Stirling convertor for use as an advanced spacecraft power system for future NASA deep-space missions. NASA Headquarters has recently identified the Stirling technology generator for potential use as the spacecraft power system for two of NASA's new missions, the Europa Orbiter and the Solar Probe missions (planned for launch in 2006 and 2007 respectively). As part of the development of this power system, a Stirling Technology Demonstration Convertor was vibration tested at NASA John H. Glenn Research Center to verify its survivability and capability of withstanding the harsh dynamic environment typically seen by the spacecraft when it is launched by an expendable launch vehicle. The Technology Demonstration Convertor was fully operational (producing power) during the random vibration testing. The output power of the convertor and other convertor performance indicators were measured during the testing, and these results are discussed in this paper. Numerous accelerometers and force gauges also were used to provide information on the dynamic characteristics of the Technology Demonstration Convertor and as an indication of any possible damage due to the vibration. These measurements will also be discussed in this paper. The vibration testing of the Stirling Technology Demonstration Convertor was extremely successful. The Technology Demonstration Convertor survived all its vibration testing with no structural damage or functional performance degradation. As a result of this testing, the Stirling convertor's capability to withstand vibration has been demonstrated, enabling its usage in future spacecraft power systems.

Goodnight, Thomas W.↗
NASA NTRS2010

The Vertical Structure of Relative Humidity and Ozone in the Tropical Upper Troposphere: Intercomparisons Among In Situ Observations, A-Train Measurements and Large-Scale Models

In situ measurements in the tropics have shown that in regions of active convection, relative humidity with respect to ice in the upper troposphere is typically close to saturation on average, and supersaturations greater than 20% are not uncommon. Balloon soundings with the cryogenic frost point hygrometer (CFH) at Costa Rica during northern summer, for example, show this tendency to be strongest between 11 and 15.5 km (345-360 K potential temperature, or approximately 250-120 hPa). this is the altitude range of deep convective detrainment. Additionally, simultaneous ozonesonde measurements show that stratospheric air (O3 greater than 150 ppbv) can be found as low as approximately 14 km (350 K/150 hPa). In contrast, results from northern winter show a much drier upper troposphere and little penetration of stratospheric air below the tropopause at 17.5 km (approximately 383 K). We show that these results are consistent with in situ measurements from the Measurement of Ozone and water vapor by Airbus In-service airCraft (MOZAIC) program which samples a wider, though still limited, range of tropical locations. To generalize to the tropics as a whole, we compare our insitu results to data from two A-Train satellite instruments, the Atmospheric Infrared Sounder (AIRS) and the Microwave Limb Sounder (MLS) on the Aqua and Aura satellites respectively. Finally, we examine the vertical structure of water vapor, relative humidity and ozone in the NASA Goddard MERRA analysis, an assimilation dataset, and a new version of the GEOS CCM, a free-running chemistry-climate model. We demonstrate that conditional probability distributions of relative humidity and ozone are a sensitive diagnostic for assessing the representation of deep convection and upper troposphere/lower stratosphere mixing processes in large-scale analyses and climate models.

Selkirk, Henry B.↗
NASA NTRS1993

Precision X-Band Doppler and Ranging Navigation For Current and Future Mars Exploration Missions

This paper describes a navigation error convariance analysis of two scenarios derived from the Mars Observer mission and the planned Mars Environmental Survey (MESUR) Pathfinder mission, respectively. The analysis was performed to establish the potential navigational performance of the X-band tracking system in NASA's Deep Space Network, and to evaluate the sensitivity of the Predicted performance to variations in the quantity of data acquired, the ground system error modeling assumptions, and data reduction schemes.

Precision↗
NASA NTRS2019

Navigation accuracy at Jupiter and Saturn using optical observations of planetary satellites

Autonomous on-board navigation has the potential to enable new types of missions and decrease reliance on NASA’s Deep Space Network for navigation purposes. Previous results have shown that navigating with only optical images of asteroids is feasible for inner planet cruise. In this study, we show that images of natural satellites can be used to navigate during approach and tour phases around the gas giants. We investigate the Jupiter and Saturn systems here, and specifically assess the performance of optical-only navigation for the Juno, Europa Clipper, and Cassini trajectories. Early approach phases and tours at Jupiter would require radiometric data to navigate, but the performance of optical-only data rivals the as-flown performance for Cassini at Saturn.

Broschart, Stephen B.↗
NASA NTRS2021

Space Biology Research and Biosensor Technologies: Past, Present, and Future

In light of future missions beyond low Earth orbit (LEO) and the potential establishment of bases on the Moon and Mars, the effects of the deep space environment on biology need to be examined in order to develop protective countermeasures. Although many biological experiments have been performed in space since the 1960s, most have occurred in LEO and for only short periods of time. These LEO missions have studied many biological phenomena in a variety of model organisms, and have utilized a broad range of technologies. However, given the constraints of the deep space environment, upcoming deep space biological missions will be largely limited to microbial organisms and plant seeds using miniaturized technologies. Small satellites such as CubeSats are capable of querying relevant space environments using novel, miniaturized instruments and biosensors. CubeSats also provide a low-cost alternative to larger, more complex missions, and require minimal crew support, if any. Several have been deployed in LEO, but the next iterations of biological CubeSats will travel beyond LEO. They will utilize biosensors that can better elucidate the effects of the space environment on biology, allowing humanity to return safely to deep space, venturing farther than ever before.

space biology↗
NASA NTRSDate not supplied

Nuclear Electric Propulsion for Outer Planet Science Missions

Nuclear electric propulsion (NEP) combines the high specific impulse of electric thrusters with a constant power source that can operate anywhere in the solar system. Current investments in fission surface power offer a starting point for development of an NEP capability for deep space science missions, with a mission to the Saturn system illustrating the potential of such a system. Minimum time of flight transits, maximum payload delivery, and a sample return from Enceladus are considered. The NEP system can deliver payloads to the Saturn system with similar transit times to the Cassini spacecraft without requiring the planetary flyby maneuvers, and when coupled with a heavy-lift launch vehicle an NEP-powered spacecraft can complete a Saturn transit significantly faster than Cassini. High payload masses can be delivered on a longer trajectory at the expense of transit time. Replacing a portion of the payload with propellant allows for a high degree of maneuverability upon reaching the Saturn system. An Enceladus sample return mission closes when utilizing the NEP system for the Saturn departure and Earth return burns.

Matthew E Duchek↗
DOE OSTI2025

Applications of Nickelate perovskites for neuromorphic computing from electronic structure and Machine Learning

While the limit of Moore's law is presently being reached with current microelectronic technologies, we need to develop new paradigms that overcome this limitation. In that respect, neuromorphic computing is a concept that emulates the neural behavior and response of the human brain, and it has been recognized as a promising alternative approach. In this research project, we will perform multi-fidelity scale bridging to explore the potential use of materials with metal to insulator transition for neuromorphic applications. In particular, rare earth nickelates are promising for such purposes, as the transition in these materials is quite sensitive to a broad set of different external stimuli. Our multi-fidelity approach will bridge the high-fidelity electronic structure calculations with classical potentials. We will bridge dynamical mean field theory with a classical atomistic representation via a deep learning force field. The neural network is trained with energies, charges, and forces obtained by accurate electronic structure theories based on Dynamical Mean Field Theory. The configurational space is generated from known crystal phases, ab initio molecular dynamics with exchange-correlation functionals corrected with the Hubbard model, disordered phases with different concentrations of oxygen vacancies, and nonsymmetrical positions and induced strain by grain interfaces or contact with a substrate. Strategies to train the model with a reduced number of training examples are obtained from active learning methods, and new structures for improving the learning process are generated by using machine learning autoencoders. This classical potential will be validated through a diversity of electronic structure methods and represents an important step to combine the flexibility and accuracy of first-principles with the speed of classical potentials. The generated multi-fidelity surrogate model will be used to understand the role of strain, oxygen vacancies, proton doping, the variation of the crystal phase, substrate effects, vibrational effects as the octahedral rotation, grain boundaries and defect effects on the response of a Metal to Insulator Transition (MIT) in correlated materials. Long time and large-scale simulations will help understand the role of different stimuli to control the hysteresis of the MIT, as it has been experimentally suggested. Selected configurations will be analyzed with higher-level theories to provide an accurate electronic description and to study how the orbitals and charges are rearranged under different conditions.

36 MATERIALS SCIENCE↗
NASA NTRSDate not supplied

Solar White Thermal Coating for Cryogenic Propulsion Systems

NASA is currently conducting research into the potential of storing cryogenic fluid in low Earth orbit (LEO). Having cryogenic propellant readily available for high-performance propulsion systems can be very beneficial for deep space missions in the near future. One of the key challenges to storing cryogenic fluid in LEO is minimizing boil-off. To address the challenge, NASA is evaluating new concepts in thermal insulation. One recent experimental study evaluated the feasibility of using Yttrium Oxide (Y2O3), formed into tiles or spray coating that can potentially be used as a thermal coating for cryogenic propellant storage applications in deep space. Due to its temperature and wavelength dependent optical properties, this “solar white” material can reflect a vast majority of the Sun’s radiative energy while having a very high infrared emissivity for rejecting heat to deep space. As a part of the material development and proof of concept testing, multiple tests have been run at KSC and GRC to demonstrate the performance of the material. At GRC, the tests were run using the Deep Space Solar Simulator (DS3) which contains a thermal vacuum chamber in which the solar white sample was exposed to a deep space environment (< 10 K, optically dense walls) while under full illumination via solar lamp. In order to improve the use of the test results and apply them to spacecraft, there is a need to be able to model the material properties within NASA’s standard thermal modeling tools. As such, it was set out to verify a thermal model of one of the experiments using Thermal Desktop with Sinda. The thermal model of the DS3 test setup includes the solar white sample along with a solar lamp simulator capable of outputting heat at varying wavelengths. The model was developed in order to validate the test results and also to help predict results that will be obtained in future tests. This paper will review the modeling methods and thermal analysis results for various test cases that were run within the DS3 facility.

Cryogenic↗