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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 271 records · Page 15
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Quantum optimal control of superconducting qubits based on machine-learning characterization

Implementing fast and high-fidelity quantum operations using open-loop quantum optimal control relies on having an accurate model of the quantum dynamics. Any deviations between this model and the complete dynamics of the device, such as the presence of spurious modes or pulse distortions, can degrade the performance of optimal controls in practice. Here, we propose an experimentally simple approach to realize optimal quantum controls tailored to the device parameters and environment while specifically characterizing this quantum system. Concretely, we use physics-inspired machine learning to infer an accurate model of the dynamics from experimentally available data and then optimize our experimental controls on this trained model. We show the power and feasibility of this approach by optimizing arbitrary single-qubit operations in detailed numerical simulations of a superconducting transmon qubit. Furthermore, we demonstrate that this framework produces an accurate description of the device dynamics under arbitrary controls, together with the precise pulses achieving arbitrary single-qubit gates with a high fidelity of ∼99.99%.

Artificial neural networks↗
DOE OSTI2024

Opportunities and new developments for the study of surfaces and interfaces in soft condensed matter at the SIRIUS beamline of Synchrotron SOLEIL

The SIRIUS beamline of Synchrotron SOLEIL is dedicated to X-ray scattering and spectroscopy of surfaces and interfaces, covering the tender to mid-hard X-ray range (1.1–13 keV). The beamline has hosted a wide range of experiments in the field of soft interfaces and beyond, providing various grazing-incidence techniques such as diffraction and wide-angle scattering (GIXD/GIWAXS), small-angle scattering (GISAXS) and X-ray fluorescence in total reflection (TXRF). SIRIUS also offers specific sample environments tailored for in situ complementary experiments on solid and liquid surfaces. Recently, the beamline has added compound refractive lenses associated with a transfocator, allowing for the X-ray beam to be focused down to 10 µm × 10 µm while maintaining a reasonable flux on the sample. This new feature opens up new possibilities for faster GIXD measurements at the liquid–air interface and for measurements on samples with narrow geometries.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2021

Silicate minerals as a direct source of limiting nutrients: Siderophore synthesis and uptake promote ferric iron bioavailability from olivine and microbial growth

Iron is a micronutrient critical to fundamental biological processes including respiration and photosynthesis, and it can therefore impact primary and heterotrophic productivity. Yet in oxic environments, iron is highly insoluble, rendering it, in principle, unavailable as a nutrient for biological growth. Life has “solved” this problem via the invention of iron chelates, known as siderophores, that keep iron available for microbial productivity. In this work, we examined the impact of siderophore synthesis on the speciation, mobility, and bioavailability of iron from rock-forming silicate minerals—shedding new light on the mechanisms by which microbes use mineral substrates to support primary productivity, as well as the consequent effects on silicate dissolution. Growth experiments were performed with Shewanella oneidensis MR-1 in an oxic, iron-depleted minimal medium, amended with olivine minerals as the sole source of iron. Experiments included the wild-type strain MR-1, and a siderophore synthesis gene deletion mutant strain (ΔMR-1). Relative to MR-1, ΔMR-1 exhibited a very pronounced growth penalty and an extended lag phase. However, substantial growth of ΔMR-1, comparable to MR-1 growth, was observed when the mutant strain was provided with siderophores in the form of either filtrate from a well-grown MR-1 culture, or commercially available deferoxamine. These observations suggest that siderophores are critical for S. oneidensis to acquire iron from olivine. Growth-limiting concentrations of deferoxamine amendments were observed to be ≤5–10 µM, concentrations significantly lower than previously recorded as necessary to impact mineral dissolution rates. X-ray photoelectric spectroscopy analyses of the incubated olivine surfaces suggest that siderophores deplete mineral surface layers of ferric iron. Combined, these results demonstrate that low micromolar concentrations of siderophores can effectively mobilize iron bound within silicate minerals, supporting very significant biological growth in limiting environments. The specific mechanism would involve siderophores removing a protective layer of nanometer-thick iron oxides, enhancing silicate dissolution and nutrient bioavailability.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Functional Requirements for the Modeling and Simulation of Advanced (Non-LWR) Reactor Mechanistic Source Term

A number of industry vendors are leading a resurgence in advanced reactor development. As the assurance of public safety from the accidental release of radionuclides to the environment is central to regulatory licensing and the reactor design process, the development of a mechanistic source term (MST) assessment has been identified by the advanced reactor industry as a foremost priority. In contrast to historic light-water reactor (LWR) source term analysis efforts, an MST attempts to realistically model the release and transport of radionuclides from the source to the environment for specific scenarios, while accounting for retention or transmutation phenomena and associated uncertainties. This work seeks to aid in the development of MST modeling and simulation tools by performing a preliminary identification of functional requirements for the major advanced reactor types.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2021

A Pathway for the Development of Advanced Reactor Mechanistic Source Term Modeling and Simulation Capabilities

Source term analysis, or the estimation of the potential radionuclide release to the environment during reactor events, is a central focus of the reactor licensing process and a vital part of risk-informed reactor design approaches. A mechanistic source term (MST) analysis is designed to realistically model the release and transport of radionuclides from the source to the environment for specific scenarios, while accounting for retention or transmutation phenomena and associated uncertainties. The objective of MST analyses, in comparison to bounding or conservative source term assessments, is to provide a non-biased representation of reactor risk and improve the information available for siting, emergency planning, and reactor design decisions. In support of the advanced reactor community in its pursuit of MST analysis capabilities, this work outlines a recommended research pathway for the development of MST modeling and simulation (mod/sim) tools.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2024

The Release of the Simplified Radionuclide Transport (SRT) Code (V.2.1)

Reactor licensing centers on the protection of the public and environment from the inadvertent release of radioactive material. Therefore, mechanistic source term analysis, or the realistic evaluation of radionuclide transport from the source to the environment for specific transient scenarios, is vital to reactor licensing efforts. Developed to resolve a gap in mechanistic source term modeling capabilities for sodium fast reactors (SFRs), the Simplified Radionuclide Transport (SRT) code created by Argonne National Laboratory (Argonne) is now utilized by advanced reactor vendors, universities, and research institutions to support a multitude of design, licensing, and research efforts. Recently, SRT version 2.1 was released, which includes improvements to code models and verification and validation (V&V) suite to support the SRT user community. The following work provides an overview of the improvements made as part of the release of SRT version 2.1. This effort is supported by the U.S. Department of Energy Office of Nuclear Energy (DOE:NE) Advanced Reactor Technologies (ART) Fast Reactor Program (FRP), as part of the program’s support of national laboratory design and safety analysis computer codes utilized by the fast reactor industry. The expansion of SRT code capabilities and improvements to code V&V associated with version 2.1 are in response to user requests and lessons learned from recent source term analyses performed by Argonne and advanced reactor vendors. They also align with the evolving role of SRT, from research and development tool to software utilized for reactor licensing calculations. The report is structured in alignment with the code improvements, as outlined in Figure 1-1. Section 2 provides background information on SRT, including its history, capabilities, and utilization. Section 3 details new code capabilities as part of version 2.1, while Section 4 focuses on the expansion of the code’s V&V suite. Lastly, Section 5 provides a summary and discussion of next steps.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

Initial Demonstration of New Griffin Technologies for Simulating the Running-In Phase of Pebble Bed Reactors

Griffin is a reactor multiphysics modeling application based on MOOSE (Multiphysics Object-Oriented Simulation Environment) and specifically targeting transient modeling of advanced reactors. Griffin has been used recently to model pebble-bed reactors for the Nuclear Regulatory Commission (NRC) Office of Nuclear Regulatory Research and the Advanced Reactor Technology program. This modeling work has focused thus far on the direct calculation of equilibrium cores. This report documents an initial demonstration of a new running-in simulation capability. The new running-in capability is verified using the existing direct equilibrium core calculation capability. A simplified pebble-bed reactor model is then used to demonstrate the running-in simulation capability. This demonstration shows that Griffin is able to simulate years of operation during the running-in phase efficiently with each depletion step taking only several seconds. Two new technologies are also presented in this report which have been developed in Griffin that will be essential for improved accuracy both of the direct equilibrium core computation and the new running-in simulation capability. The first technology is an online cross section generation capability specifically targeted for pebble-bed reactors. This will improve the accuracy of the depletion calculation as the cross sections are generated at the exact core status. This also avoids the difficult step of pre-generating a separate standalone multigroup cross section set. Secondly, a newly implemented discretization for discontinuous finite element method (DFEM) SN transport in cylindrical (RZ) coordinates, which can be solved efficiently using the existing SN sweep solver, is discussed and some results are shown demonstrating the usefulness of the additional accuracy transport provides over a diffusion approximation.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

Enhancing Molecular Isotope Detection with a Chirp Tuned Optical Centrifuge

This paper gives a brief experimental overview on creating a chirp-tunable optical centrifuge with the goal of amplifying the isotope shift of a given molecule. Results for this experiment were recorded with a CO 2 plume as the probed material. Beyond amplification of the isotope shift, this technology could be modified to alter magnetic field characteristics of common molecules as well as simulating high temperature gases found in combustion environments. Our specific design uses double mirror and grating stretcher and will include a unique tuning feature for customization of the beam’s red and blue components' temporal chirp, allowing for quick reactivity to varying task requirements. The design and parameters will be discussed, as well as the methods used to model the optical centrifuge. Although this experiment is ongoing, results have been gathered previously that display the efficacy of the optical centrifuge. For the probed CO 2 sample, Raman Shifts centered around a wavenumber of 60 and 275 were recorded with durations of 1000 and 800 picoseconds, respectively.

47 OTHER INSTRUMENTATION↗
DOE OSTI2024

Ecosystems and Networks Integrated with Genes and Molecular Assemblies (ENIGMA): Molecular and Computational Technologies for Environmental Microbiology (Final Scientific/Technical Report)

The ENIGMA science focus area (SFA) is a multi-disciplinary, multi-institutional research effort focused on addressing foundational knowledge gaps in environmental microbial communities by studying groundwater and sediment microbiomes in the shallow subsurface at the contaminated Oak Ridge Reservation (ORR). We seek to discover and characterize the reciprocal interactions between the microbial communities and the geochemical and geophysical parameters of the shallow subsurface within the contamination plume. The primary goal of this subcontract was to develop experimental and computational tools to advance our understanding of microbial adaptation and community assembly in contaminated environments, with specific efforts in high-throughput genomic methods, microbial ecology tools, and studies of heavy metal contamination impacts.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Multiscale and Machine Learning Modeling for Process-informed Microstructure Prediction in Additively Manufactured Materials Using MALAMUTE

Advanced Materials and Manufacturing Technologies (AMMT) program under the Department of Energy Office of Nuclear Energy, aims to develop and qualify additively-manufactured materials for nuclear applications. The key challenges to these efforts are the microstructural variabilities observed on the AM products and their impact on the properties and performance of the material in extreme environments. AMMT is using a combination of high-through-put experimental and modeling techniques to accelerate the qualification efforts. Conventionally, in-situ and ex-situ characterizations and testing are performed to correlate different aspects of the AM process to the final product and its performance. However, adopting a trial-and-error approach to experimentally evaluate the vast range of process parameters required to capture the microstructural variabilities is cost-prohibitive. Modeling and simulation provide a comparatively inexpensive way to understand and correlate the microstructural evolution to the processing conditions. The modeling and simulation work-packages within the AMMT program aims to use physics-based and machine learning modeling capabilities to develop a digital twin for AM that can correlate the process conditions to the final product and establish a process-structure-property-performance (PSPP) correlation for AM materials. The melting and subsequent solidification that occurs during the AM process is a complex phenomenon that requires multiscale multiphysics analysis. Idaho National Laboratory’s (INL) Multiphysics Object-Oriented Simulation Environment (MOOSE), specifically the MOOSE Application Library for Advanced Manufacturing UTilitiEs (MALAMUTE) software, provides an ideal platform for developing the multiphysics multiscale model to explore the intricacies of the microstructural evolution during the AM processes within a single framework. Furthermore, given that such full-fidelity simulations can be computationally intensive, reduced order models are necessary to explore the PSPP space for AM materials in an efficient, reliable, and cost-effective way. This work package focuses on understanding the role of process variabilities on the various microstructural characteristics of the AM materials. Microstructures unique to AM materials, such as compositional micro-heterogeneity and dislocation cells, are of particular interest here since they can influence the creep properties and radiation performance. In fiscal year (FY) 24, we significantly advanced upon our work in the last fiscal year, both on physics-based and ML models. The alloy solidification model available in MOOSE has been extended to incorporate the thermodynamic properties and free energy relevant to 316SS. The model demonstrates the Cr segregation that occurs during solidifcation. It is demonstrated that rate of solidification and solute segregation is primarily influence by the cooling rate dictating the level of freezing. This work captures the microstructural variabilities at the subgrain level that are often missing in the part-scale models. With an aim to connect the microstructural evolution model to realistic process conditions, a reduced order model is developed for predicting the thermal conditions around meltpool from high-fidelity process simulations. Furthermore, machine learning approach is used to accelerate the temperature prediction during the AM process. In the following years, MALAMUTE will be used to connect different aspects of the models and quantitatively predict the microstructural evolution. The developed ML-based surrogate model will consider the process conditions as the input to predict the microstructural features in a cost-effective way. The generated microstructures can be used by other work packages under AMMT to evaluate the properties and environmental response of the material at the mesoscale. Thus, this work help identify the key microstructural features at the subgrain level that are significant in property/performance prediction of the AM products. This work will provide inputs to the large-scale process variability models to reevaluate and validate assumptions/simplifications made in the part-scale models. Furthermore, through active learning this work will help identify the data need from both modeling and experimental sides for development of a robust digital twin for AM.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Multiscale and Machine Learning Modeling for Process-informed Microstructure Prediction in Additively Manufactured Materials using MALAMUTE

The Advanced Materials and Manufacturing Technologies (AMMT) program under the Department of Energy Office of Nuclear Energy aims to develop and qualify additively manufactured materials for nuclear applications. One key challenge to this is the microstructural variability observed in the additively manufactured products and their impact on the properties and performance of the material in extreme environments. AMMT is using a combination of high-throughput experimental and modeling techniques to accelerate qualification. Conventionally, in-situ and ex-situ characterizations and testing are performed to correlate different aspects of the additive manufacturing process to the final product and its performance. However, adopting a trial-and-error approach to experimentally evaluate the vast range of process parameters required to capture microstructural variability is cost-prohibitive. Modeling and simulation provide a comparatively inexpensive way to understand and correlate the microstructural evolution to the processing conditions. The modeling and simulation work-packages within the AMMT program aims to use physics-based and machine learning models to develop a digital twin for additive manufacturing that can correlate the process conditions to the final product and establish a process-structure-property-performance (PSPP) correlation. The melting and subsequent solidification that occurs during the additive process is a complex phenomenon that requires multiscale multiphysics analysis. This work package focuses on understanding the role of process variabilities on the unique microstructural characteristics of additively manufactured materials. Microstructural features at the subgrain level, such as compositional micro-heterogeneity and dislocation cells, are of particular interest here since they can influence the creep properties and radiation performance. Idaho National Laboratory’s Multiphysics Object-Oriented Simulation Environment (MOOSE), specifically the MOOSE Application Library for Advanced Manufacturing UTilitiEs (MALAMUTE) software, provides an ideal platform for developing the multiphysics multiscale model to explore the intricacies of the microstructural evolution during the AM processes within a single framework. Furthermore, given that such full-fidelity simulations can be computationally intensive, reduced order models are necessary to explore the PSPP space for additively manufactured materials in an efficient, reliable, and cost-effective way. This work focuses on capturing the microstructural variabilities at the subgrain level that are often missing in the part-scale models. In fiscal year 2025, we significantly advanced upon our work in the last fiscal year, in terms of the predictive capabilities of the physics-based and ML models, by adding the capabilities to capture subgrain-level micro-segregation during solidification using phase-field model and to predict the time-dependent dynamics of the AM process through the MOGPAR model. The alloy solidification model in MOOSE incorporates the thermodynamic properties and free energy relevant to 316 stainless steel. The model demonstrates the Cr and Ni segregation that occurs during solidification, including that the rate of solidification. The microstructural evolution model is connected to the process conditions via the surrogate model developed in this work. This enables predictions of the final microstructure in conjunctions with the manufacturing process. This work supports AMMT's rapid qualification goals by laying the foundation for an efficient and cost-effective model establishing the PSPP correlation for AM. The generated microstructures and predicted micro-segregation can be used by other work packages under AMMT to evaluate the properties and environmental response of the material at the mesoscale. Thus, this work helps to identify the key microstructural features at the subgrain level that are significant in property and performance predictions of additively manufactured components. This work will also provide inputs to the large-scale process variability models to reevaluate and validate assumptions and simplifications made in the part-scale models. Furthermore, through active learning this work can help identify the data need from both modeling and experimental sides for development of a robust digital twin for additive manufacturing and accelerate the AMMT's qualification efforts.

36 - MATERIALS SCIENCE↗
DOE OSTI2022

The Effect of Environment on Galaxy Spiral Arms, Bars, Concentration, and Quenching

For a sample of 4378 nearby spiral and S0 galaxies, Yu & Ho used Fourier analysis of Sloan Digital Sky Survey images to show that the strengths of the spiral arms and the pitch angles of the arms are inversely correlated with central concentration. In the current study, we search for trends in the Yu & Ho spiral arm parameters with environment and specific star formation rate (sSFR). When comparing galaxies with similar concentrations, we do not find a significant difference in the arm strengths or pitch angles of spiral galaxies in clusters compared to field galaxies. When differences in concentration are taken into account, we also find no significant difference in the parameter f3 for cluster spirals compared to field spirals, where f3 is the normalized m = 3 Fourier amplitude. When concentration is held fixed, both arm strength and pitch angle are correlated with sSFR, but f3 is not. These relations support the suggestion by Davis et al. of a "fundamental plane" of spiral structure involving pitch angle, bulge stellar mass, and gas surface density. We discuss these results in terms of theories of spiral arm production and quenching in galaxies. To aid comparison with earlier studies based on Galaxy Zoo, we explore how the Yu & Ho parameters relate to similar parameters measured by Galaxy Zoo (i.e., f3 versus the number of arms, pitch angle versus winding parameter, and concentration versus bulge class).

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1972

Ion thruster performance calibration.

The calibration of a typical 20-cm diameter ion thrustor was examined to determine performance penalties that must be assessed in projecting measured performance into a space environment. Four specific areas were investigated. These include (1) double ion content of the beam, (2) back ingestion from the vacuum facility, (3) beam spreading, and (4) propellant flow rate measurements. The double ion content was measured and found to be as high as 5.5% at an arc voltage of 35 volts. Back ingestion was observed to become significant above tank pressures of 6 microtorr. Beam spreading reduced effective thrust on the order of 2.5%.

Pawlik, E. V.↗
NASA NTRS1973

The limits of the adaptation of life to extreme conditions (in connection with problems of exobiology)

Accommodation is discussed as a universal evolutionary principle which essentially will apply to all life forms, regardless of chemical base (carbon, silicon, etc.). Life forms must either adapt to extreme conditions or perish, and for any life form an extremum factor is any significant deviation in environmental parameters. The possibility of life forms existing in specific extraterrestrial environments is discussed, and a conclusion is drawn which unequivocally states that through many forms of accommodation life is possible in many different environments.

Aksenov, S. I.↗
NASA NTRS1973

Introduction

Probable climatic extremes of terrestrial environment data specifically applicable for NASA space vehicles and associated equipment development are considered. Design guideline values are established for the following environmental parameters: (1) Thermal (temperature and solar radiation); (2) humidity; (3) precipitation; (4) winds; (5) pressure; (6) density; (7) electricity (atmospheric); (8) corrosion (atmospheric); (9) sand and dust; (10) fungi and bacteria; (11) atmospheric oxidants; (12) composition of the atmosphere; and (13) inflight thermodynamic properties.

Daniels, G. E.↗
NASA NTRS1976

Payload/orbiter contamination control requirement study

The Spacelab carrier induced contaminant environment and Spacelab's ability to meet established contamination control criteria for the shuttle program are determined. The primary areas of on-going activity include updating, refining, and improving the Spacelab Contamination Computer Model and contamination analysis methodology; establishing the resulting adjusted induced environment predictions for comparison with the applicable criteria; determining Spacelab design and operational requirements necessary to meet the criteria; conducting mission feasibility analyses of the combined Spacelab/orbiter contaminant environment for specific proposed missions and payload mixes; and establishing a preliminary Spacelab mission support plan and model interface requirements. A summary is given of these activities conducted to date including any modifications in approach or methodology utilized in the contamination assessment of the Spacelab vehicle. The emphasis is placed on the Spacelab modeling efforts.

Bareiss, L. E.↗
NASA NTRS1975

On the origin of molecular 'handedness' in living systems

Elementary particle effects (beta-decay) provide only a weakly handed radiation in the biologically effective energy ranges. Global magnetic effects coupled to sunlight are randomized by paleomagnetic reversals. A persistent terrestrial handed bias at possible local biopoetic sites offers a more promising explanation for the origin of the 'handedness' of the molecules found among living systems on earth. Magnetite in lava flows maintains a handed bias for surface catalysis through many magnetic reversals. Indirect evidence for the hypothesis that magnetite contaminated with sulfur is a possible biopoetic site (Granick, 1957) has been provided by the molecular structure of ferredoxin - a single strand of the 14 primordial amino acids wrapped around an FeS core. Lava flows have been suggested as biopoetic sites by Fox (1964), since their temperature and chemical composition might allow for the rapid synthesis of prebiotic compounds at the surface of the primitive earth. The additional fact that magetite in lava flows also provides a persistent handed site for surface catalysis offers a further argument for the experimental investigation of this specific biopoetic environment.

Noyes, H. P.↗