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At least 1,387 records · Page 77
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Exogenous electricity flowing through cyanobacterial photosystem I drives CO 2 valorization with high energy efficiency

Nature's biocatalytic processes are driven by photosynthesis, whereby photosystems I and II are connected in series for light-stimulated generation of fuel products or electricity. Externally supplying electricity directly to the photosynthetic electron transfer chain (PETC) has numerous potential benefits, although strategies for achieving this goal have remained elusive. Here we report an integrated photo-electrochemical architecture which shuttles electrons directly to PETC in living cyanobacteria. The cathode of this architecture electrochemically interfaces with cyanobacterial cells that have a lack of photosystem II activity and cannot perform photosynthesis independently. Illumination of the cathode channels electrons from an external circuit to intracellular PETC through photosystem I, ultimately fueling cyanobacterial conversion of CO 2 into acetate. We observed acetate formation when supplying both illumination and exogenous electrons under intermittent conditions (e.g., in a 30 s supply plus 30 min interval condition of both light and exogenous electrons). The energy conversion efficiency for acetate production under programmed intermittent LED illumination (400–700 nm) and exogenous electron supply reached ca. 9%, when taking into account the number of photons and electrons received by the biotic system, and ca. 3% for total photons and electrons supplied to the cyanobacteria. This approach is applicable for generating various CO 2 reduction products by using engineered cyanobacteria, one of which has enabled electrophototrophic production of ethylene, a broadly used hydrocarbon in the chemical industry. The resulting bio-electrochemical hybrid has the potential to produce fuel chemicals with numerous potential advantages over standalone natural and artificial photosynthetic approaches.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Advancing Additive Manufacturing Through Artificial Intelligence–Powered, High-Throughput, Nondestructive Characterization and Process Optimization

This Cooperative Research and Development Agreement (CRADA) between Oak Ridge National Laboratory (ORNL) and ZEISS Industrial Metrology has demonstrated the transformative potential of artificial intelligence (AI)-enabled x-ray computed tomography (XCT) to accelerate the qualification and certification of additively manufactured (AM) parts. At the core of this effort is Simurgh, an AI-powered XCT reconstruction framework jointly advanced by ORNL and ZEISS that integrates computer-aided design (CAD) models, physics-based simulations, and deep learning to overcome the long-standing challenges of metal artifact correction, long scan durations, and limited flaw detectability in dense and geometrically complex components. Simurgh enables high-throughput, high-quality 3D reconstruction from sparse and fast scans, which reduces XCT acquisition times by more than an order of magnitude and simultaneously improves defect detection limits by up to fourfold compared with industry-standard approaches. This capability reduces scan costs by more than 50%, lowers labor overhead, and makes XCT characterization economically viable for routine industrial use. By enabling reliable flaw detection in minutes rather than hours, Simurgh facilitates real-time feedback loops for process parameter optimization, which was highlighted in a recent npj Computational Materials (a Nature journal) issue. In the published study, more than 100 alloy coupons were characterized within a single day. This work represents a tenfold acceleration in the development of novel AM alloys and processes compared with conventional workflows. The ZEISS collaboration has also demonstrated the scalability of Simurgh to diverse application domains, including aerospace, nuclear, automotive, and biomedical components; in these applications, ensuring structural integrity is paramount. By drastically reducing barriers to XCT adoption, this partnership has laid the foundation for digital twins and data-driven certification pipelines and directly addressed bottlenecks in qualifying new materials and designs. Together, ORNL and ZEISS have shown that Simurgh advances the state of the art in nondestructive evaluation and aligns with the broader mission of enabling Industry 4.0 manufacturing ecosystems, in which intelligent, cost-effective, rapid quality assurance is integral to accelerating innovation and ensuring safety in critical applications.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Advancing Additive Manufacturing Through Artificial Intelligence–Powered, High-Throughput, Nondestructive Characterization and Process Optimization

This Cooperative Research and Development Agreement (CRADA) between Oak Ridge National Laboratory (ORNL) and ZEISS Industrial Metrology has demonstrated the transformative potential of artificial intelligence (AI)-enabled x-ray computed tomography (XCT) to accelerate the qualification and certification of additively manufactured (AM) parts. At the core of this effort is Simurgh, an AI-powered XCT reconstruction framework jointly advanced by ORNL and ZEISS that integrates computer-aided design (CAD) models, physics-based simulations, and deep learning to overcome the long-standing challenges of metal artifact correction, long scan durations, and limited flaw detectability in dense and geometrically complex components. Simurgh enables high-throughput, high-quality 3D reconstruction from sparse and fast scans, which reduces XCT acquisition times by more than an order of magnitude and simultaneously improves defect detection limits by up to fourfold compared with industry-standard approaches. This capability reduces scan costs by more than 50%, lowers labor overhead, and makes XCT characterization economically viable for routine industrial use. By enabling reliable flaw detection in minutes rather than hours, Simurgh facilitates real-time feedback loops for process parameter optimization, which was highlighted in a recent npj Computational Materials (a Nature journal) issue. In the published study, more than 100 alloy coupons were characterized within a single day. This work represents a tenfold acceleration in the development of novel AM alloys and processes compared with conventional workflows. The ZEISS collaboration has also demonstrated the scalability of Simurgh to diverse application domains, including aerospace, nuclear, automotive, and biomedical components; in these applications, ensuring structural integrity is paramount. By drastically reducing barriers to XCT adoption, this partnership has laid the foundation for digital twins and data-driven certification pipelines and directly addressed bottlenecks in qualifying new materials and designs. Together, ORNL and ZEISS have shown that Simurgh advances the state of the art in nondestructive evaluation and aligns with the broader mission of enabling Industry 4.0 manufacturing ecosystems, in which intelligent, cost-effective, rapid quality assurance is integral to accelerating innovation and ensuring safety in critical applications.

36 MATERIALS SCIENCE↗
NASA NTRS1991

An Explicit Upwind Algorithm for Solving the Parabolized Navier-Stokes Equations

An explicit, upwind algorithm was developed for the direct (noniterative) integration of the 3-D Parabolized Navier-Stokes (PNS) equations in a generalized coordinate system. The new algorithm uses upwind approximations of the numerical fluxes for the pressure and convection terms obtained by combining flux difference splittings (FDS) formed from the solution of an approximate Riemann (RP). The approximate RP is solved using an extension of the method developed by Roe for steady supersonic flow of an ideal gas. Roe's method is extended for use with the 3-D PNS equations expressed in generalized coordinates and to include Vigneron's technique of splitting the streamwise pressure gradient. The difficulty associated with applying Roe's scheme in the subsonic region is overcome. The second-order upwind differencing of the flux derivatives are obtained by adding FDS to either an original forward or backward differencing of the flux derivative. This approach is used to modify an explicit MacCormack differencing scheme into an upwind differencing scheme. The second order upwind flux approximations, applied with flux limiters, provide a method for numerically capturing shocks without the need for additional artificial damping terms which require adjustment by the user. In addition, a cubic equation is derived for determining Vegneron's pressure splitting coefficient using the updated streamwise flux vector. Decoding the streamwise flux vector with the updated value of Vigneron's pressure splitting improves the stability of the scheme. The new algorithm is applied to 2-D and 3-D supersonic and hypersonic laminar flow test cases. Results are presented for the experimental studies of Holden and of Tracy. In addition, a flow field solution is presented for a generic hypersonic aircraft at a Mach number of 24.5 and angle of attack of 1 degree. The computed results compare well to both experimental data and numerical results from other algorithms. Computational times required for the upwind PNS code are approximately equal to an explicit PNS MacCormack's code and existing implicit PNS solvers.

Korte, John J.↗
NASA NTRS2000

A Novel Approach to Exploring the Mars Polar Caps

The Martian polar caps contain some of the most important scientific sites on the planet. There is much interest in exploring them with a view to understanding their role in the Mars climate system. By gaining access to the stratigraphy of the polar terrain, it is probable that one can access the climate history of the planet. Additionally, investigations aimed at localizing subsurface water--liquid or solid--are not only of great scientific interest but are also germane to the long-term interests of the manned space flight program. A major difficulty with polar exploration is access. Current techniques using chemical propulsion, Holman transfers, and direct-entry landers with aeroshells have limited capability to access the polar terrain. For the near term the authors propose a new approach to solving this transportation issue by using Solar Electric Propulsion (SEP), recently flight demonstrated on NASA's DS1 Mission to an asteroid and a comet. For a longer-term approach there are additional ways in which access to Mars, as well as other planets, can be significantly improved. These include the use of Chaos orbit theory to enable transportation between LaGrange points in the solar system, gossamer structures enabling very low-mass mobility, and advanced ascent vehicles. In this paper the authors describe how a 1000-kG payload can be transported to the surface of Mars and a polar sample obtained and returned to Earth in less than five years using SEP. A vision of how this approach can be integrated into a long-term Mars exploration strategy building toward the future is also discussed.

Brophy, John R.↗
NASA NTRS2020

Toward Transition Modeling in a Hypersonic Boundary Layer at Flight Conditions

An accurate physics-based transition prediction method integrated with computational fluid dynamics (CFD) solvers is pursued for hypersonic boundary layer flows over slender hypersonic vehicles at flight conditions. The geometry and flow conditions are selected to match relevant trajectory locations from the ascent phase of the HIFiRE-1 flight experiment, namely, a 7-degree half-angle cone with 2.5 mm nose radius, freestream Mach numbers in the range of 3.8 – 5.5 and freestream unit Reynolds numbers in the range of 3.3 × 10(exp 6) – 21.4 × 10(exp 6) m(exp -1). Earlier research had shown that the onset of transition during the HIFiRE-1 flight experiment correlated with an amplification factor of N ≈ 13.5 for the planar Mack modes. However, to incorporate the N-factor correlations into a CFD code, we investigate surrogate models for disturbance amplification that avoid the direct computation of stability characteristics. A commonly used approach for low-speed flows is based on an a priori database of stability characteristics for locally similar profiles. However, the results presented in this paper demonstrate that the application of this approach to hypersonic boundary layers over blunt spherical nose-tip cones leads to large, unacceptable errors in the predictions of amplification factors, mainly due to its failure in accounting for the effects of the entropy layer on the boundary-layer profiles along the length of the model. We propose and demonstrate an alternate approach that employs the stability computations for a canonical set of blunt cone configurations to train a physics-informed convolutional neural network model that is shown to provide substantially improved transition predictions for hypersonic flow configurations with entropy-layer effects. Furthermore, the excellent performance of the neural network model is also confirmed for cone configurations with nose radius and half-angle values that do not correspond to those used to build the database. Finally, the convolutional neural network model is shown to outperform the linear stability calculations for underresolved basic states.

Pedro Paredes↗
NASA NTRS2011

Science Hybrid Orbiter and Lunar Relay (SCHOLR) Architecture and Design

Considered both a stepping-stone to deep space and a key to unlocking the mysteries of planetary formation, the Moon offers a unique opportunity for scientific study. Robotic precursor missions are being developed to improve technology and enable new approaches to exploration. Robots, lunar landers, and satellites play significant roles in advancing science and technologies, offering close range and in-situ observations. Science and exploration data gathered from these nodes and a lunar science satellite is intended to support future human expeditions and facilitate future utilization of lunar resources. To attain a global view of lunar science, the nodes will be distributed over the lunar surface, including locations on the far side of the Moon. Given that nodes on the lunar far side do not have direct line-of-sight for Earth communications, the planned presence of such nodes creates the need for a lunar communications relay satellite. Since the communications relay capability would only be required for a small portion of the satellite s orbit, it may be possible to include communication relay components on a science spacecraft. Furthermore, an integrated satellite has the potential to reduce lunar surface mission costs. A SCience Hybrid Orbiter and Lunar Relay (SCHOLR) is proposed to accomplish scientific goals while also supporting the communications needs of landers on the far side of the Moon. User needs and design drivers for the system were derived from the anticipated needs of future robotic and lander missions. Based on these drivers and user requirements, accommodations for communications payload aboard a science spacecraft were developed. A team of interns identified and compared possible SCHOLR architectures. The final SCHOLR architecture was analyzed in terms of orbiter lifetime, lunar surface coverage, size, mass, power, and communications data rates. This paper presents the driving requirements, operational concept, and architecture views for SCHOLR within a lunar surface nodal network. Orbital and bidirectional link analysis, between lunar nodes, orbiter, and Earth, as well as a conceptual design for the spacecraft are also presented

Trase, Kathryn K.↗
NASA NTRS2017

Rotational Spectral Unmixing of Exoplanets: Degeneracies Between Surface Colors and Geography

Unmixing the disk-integrated spectra of exoplanets provides hints about heterogeneous surfaces that we cannot directly resolve in the foreseeable future. It is particularly important for terrestrial planets with diverse surface compositions like Earth. Although previous work on unmixing the spectra of Earth from disk-integrated multi-band light curves appeared successful, we point out a mathematical degeneracy between the surface colors and their spatial distributions. Nevertheless, useful constraints on the spectral shape of individual surface types may be obtained from the premise that albedo is everywhere between 0 and 1. We demonstrate the degeneracy and the possible constraints using both mock data based on a toy model of Earth, as well as real observations of Earth. Despite the severe degeneracy, we are still able to recover an approximate albedo spectrum for an ocean. In general, we find that surfaces are easier to identify when they cover a large fraction of the planet and when their spectra approach zero or unity in certain bands.

Fujii, Yuka↗
DOE OSTI2020

Initial Field Testing in the Deep Subsurface for the Thermal Breakout Project for Measuring In Situ Stress

The current state-of-the-art technology for in situ stress measurements involves an integrated approach that combines borehole breakout observations, drilling-induced tensile fractures, and hydraulic fracturing tests (i.e., mini-fracs); however, this methodology has several limitations that often prevent successful in situ stress measurements. One major limitation is that breakouts do not appear in every borehole and are generally a natural occurrence that cannot easily be controlled. Because borehole breakouts are used to measure the maximum horizontal in situ stress magnitude, the absence of borehole breakouts presents a major data gap for in situ stress measurements. As a response to this data gap a new thermal breakout technology is being developed that will provide a method for thermally inducing borehole breakouts and obtaining consistent measurements of the maximum horizontal stress magnitude. This thermal breakout technology involves heating the borehole and increasing the thermoelastic compressive stress in the rock until a breakout develops, which is directly correlated to the maximum horizontal stress magnitude. An initial component of the thermal breakout project involves developing a prototype downhole tool and performing field testing in the deep subsurface. The primary objective of the initial tool development and field testing is to provide a physical proof of concept for the thermal breakout technology. Three thermal breakout field tests were performed at approximately 4850 feet deep in the Sanford Underground Research Facility. Each test was performed in a borehole that had been previously used for overcoring stress measurements. The third and final test successfully created two diametrically opposed breakouts after deploying the thermal breakout tool for approximately 3 hours of continuous heating. Post-analysis of the thermally induced breakouts confirmed that the thermal breakout orientation directly corresponds to the known in situ stress orientation and magnitude.

Voegeli, Sam↗
DOE OSTI2025

Machine learning model inputs, outputs, and scripts associated with “Artificial intelligence-guided iterations between observations and modeling significantly improve environmental predictions”

NOTE: The manuscript associated with this data package is currently in review. The data may be revised based on reviewer feedback. Upon manuscript acceptance, this data package will be updated with the final dataset and additional metadata. This data package is associated with the manuscript “Artificial intelligence-guided iterations between observations and modeling significantly improve environmental predictions” (Malhotra et al., in prep). This effort was designed following ICON (integrated, coordinated, open, and networked) principles to facilitate a model-experiment (ModEx) iteration approach, leveraging crowdsourced sampling across the contiguous United States (CONUS). New machine learning models were created every month to guide sampling locations. Data from the resulting samples were used to test and rebuild the machine learning models for the next round of sampling guidance. Associated sediment and water geochemistry and in situ sensor data can be found at https://data.ess-dive.lbl.gov/datasets/doi:10.15485/1923689, https://data.ess-dive.lbl.gov/datasets/doi:10.15485/1729719, and https://data.ess-dive.lbl.gov/datasets/doi:10.15485/1603775. This data package is associated with two GitHub repositories found at https://github.com/parallelworks/dynamic-learning-rivers and https://github.com/WHONDRS-Hub/ICON-ModEx_Open_Manuscript. In addition to this readme, this data package also includes two file-level metadata (FLMD) files that describes each file and two data dictionaries (DD) that describe all column/row headers and variable definitions. This data package consists of two main folders (1) dynamic-learning-rivers and (2) ICON-ModEx_Open_Manuscript which contain snapshots of the associated GitHub repositories. The input data, output data, and machine learning models used to guide sampling locations are within dynamic-learning-rivers. The folder is organized into five top-level directories: (1) “input_data” holds the training data for the ML models; (2) “ml_models” holds machine learning (ML) models trained on the data in “input_data”; (3) “examples” contains files for direct experimentation with the machine learning model, including scripts for setting up “hindcast” run; (4) “scripts” contains data preprocessing and postprocessing scripts and intermediate results specific to this data set that bookend the ML workflow; and (5) “output_data” holds the overall results of the ML model on that branch. Each trained ML model resides on its own branch in the repository; this means that inputs and outputs can be different branch-to-branch. There is also one hidden directory “.github/workflows”. This hidden directory contains information for how to run the ML workflow as an end-to-end automated GitHub Action but it is not needed for reusing the ML models archived here. Please see the top-level README.md in the GitHub repository for more details on the automation. The scripts and data used to create figures in the manuscript are within ICON-ModEx_Open_Manuscript. The folder is organized into four folders which contain the scripts, data, and pdf for each figure. Within the “fig-model-score-evolution” folder, there is a folder called “intermediate_branch_data” which contains some intermediate files pulled from dynamic-learning-rivers and reorganized to easily integrate into the workflows. NOTE: THIS FOLDER INCLUDES THE FILES AT THE POINT OF PAPER SUBMISSION. IT WILL BE UPDATED ONCE THE PAPER IS ACCEPTED WITH ANY REVISIONS AND WILL INCLUDE A DD/FLMD AT THAT POINT. We thank the United States Forest Service, Washington Department of Fish and Wildlife, Washington Department of Natural Resources, Cowiche Canyon Conservatory, Washington State Parks and Recreation Commission (Scientific Research Permit #210901), and the Confederated Tribes and Bands of the Yakama Nation for access to field locations where the samples labeled “SSS” were collected. We also thank the Yakama Nation Tribal Council and Yakama Nation Fisheries for working with us to facilitate sample collection and optimization of data usage according to their values and worldview. WHONDRS consortium members were asked to provide any acknowledgments for the collection of samples labeled “CM” and the following is a list of acknowledgments that were submitted with their corresponding Site IDs: (MART) Research activities were conducted in part on the Wind River Experimental Forest within the Gifford Pinchot National Forest; (MP- 100379) Philadelphia is part of Lenapehoking, the ancestral homelands of the Lenape peoples; (MP-102398) Land surveyed is the ancestral homelands of the Nookhose'iinenno (Arapaho), Tsis tsis'tas (Cheyenne), and Nuuchu (Ute); (MP-100749 and MP- 100747) Georgia Coastal Ecosystem LTER, OCE-1832178; (SP-70 and SP-72) Eastern Shoshone, Shoshone-Bannock; (MP- 102944) Funded by Oregon Watershed Enhancement Board. On the traditional lands of the Confederated Tribes of the Siletz, Confederated Tribes of the Grand Rhonde, and the Clatsop-Nehalem Confederated Tribe; (MP- 100607) Holiday Creek is located on the traditional territory of the Monacan Indian Nation; (SP-45) Lafayette Blue Springs State Park; (MP-102420) NSF DEB-2016749; (MP-100019) New Hampshire Agriculture Experiment Station; (SP-35) Rayonier (land owner; https://www.rayonier.com/); (MP- 101276) US Department of Energy, Office of Science, Biological and Environmental Research, Subsurface Biogeochemical Research, Watershed Dynamics and Evolution SFA at ORNL; (MP- 103224) Watershed Dynamics and Evolution SFA at ORNL; (MP- 101584) Traditional lands of the Oceti Sakowin (Dakota, Lakota, Nakoda) and Anishinaabe Peoples.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Direct pulse-level compilation of arbitrary quantum logic gates on superconducting qutrits

Advanced simulations and calculations on quantum computers require high-fidelity implementations of quantum operations. The universal gateset approach builds complex unitaries from a small set of primitive gates, often resulting in a long gate sequence, which is typically a leading factor in the total accumulated error. Compiling a complex unitary for processors with higher-dimensional logical elements, such as qutrits, exacerbates the accumulated error per unitary, since an even longer gate sequence is required. Optimal control methods promise time- and resource-efficient compact gate sequences and, therefore, higher fidelity. These methods generate pulses that can directly implement any complex unitary on a quantum device. In this work, we demonstrate that any arbitrary qubit and qutrit gate can be realized with high fidelity, which can significantly reduce the length of a gate sequence. We generate and test pulses for a large set of randomly selected arbitrary unitaries on several quantum processing units (QPUs): the Lawrence Livermore National Laboratory Quantum Device and Integration Testbed’s (QuDIT’s) standard QPU and three of Rigetti’s QPUs: Ankaa-2, Ankaa-9Q-1, and Aspen-M-3. On the QuDIT platform’s standard QPU, the average fidelity of random qutrit gates is 97.9 ± 0.5% measured with conventional QPT and 98.8 ± 0.6% from QPT with gate folding. Rigetti’s Ankaa-2 achieves random qubit gates with an average fidelity of 98.4 ± 0.5% (conventional QPT) and 99.7 ± 0.1% (QPT with gate folding). On Ankaa-9Q-1 and Aspen-M-3, the average fidelities with conventional qubit QPT measurements were higher than 99% (see Appendix). Here we show that optimal control gates are robust to drift for at least 3 h and that the same calibration parameters can be used for all implemented gates. Our work promises that the calibration overheads for optimal control gates can be made small enough to enable efficient quantum circuits based on this technique.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2022

Production Agency Quality Assurance Management Execution Strategy [Thesis]

There are multiple federal directives that Los Alamos National Laboratory (LANL) must follow for the proper implementation of quality assurance, strategic planning, and execution of manufacturing and surveillance operations. Recent assessments identified that manufacturing in all processing areas is dynamic due to influencing scope changes, design modifications, funding adjustments, and staff attrition. In response, this project was started to develop a comprehensive PAQ execution strategy to support the success of LANL’s manufacturing mission. This project’s method for developing an updated architecture was to create an integrated, flexible, reliable, and agile strategic process. The execution plan has five deliverables: 1) an integrated schedule view of PAQ work scope, 2) a resource management plan that aligns with the required scope, 3) a metrics monitoring dashboard, 4) a project management plan for sustaining NAP 401.1A implementation, and 5) a risk management plan. The research design is a mixed-method approach focused on data collection for each deliverable. The methodology entails qualitative and quantitative research, metrics monitoring, data analysis, and the creation of a dashboard. The qualitative methods used include literature reviews and interviews. The quantitative methods include resource, financial, schedule and survey data analysis. Preliminary and final results were peer reviewed by subject matter experts both within the ALDWP organization and deployed support.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2024

High-Power Oak Ridge Converter (ORC) for Extreme Fast Charging Applications

This project report presents a novel power converter system called Oak Ridge Converter (ORC), a patented technology developed by the Oak Ridge National Laboratory (ORNL) for XFC wireless EV charging systems. ORC integrates the grid interface converter (also known as the active front-end rectifier with power factor correction) with the high-frequency inverter stage, promoting size and cost-effective charging technology with reduced infrastructure costs. The integration of the front-end rectifier with the high-frequency inverter truly eliminates one power conversion stage and achieves more than 33% size, weight, volume, and cost reduction on the wireless charging systems. Furthermore, ORC eliminates the primary side direct current (DC) bus bulk capacitors that are usually aluminum electrolytic capacitors and replaces them with very small, cost-effective, highly reliable, and high-temperature operation-capable alternate current (AC) film capacitors. ORC is also applicable to both single-phase and poly-phase couplers. When used with polyphase couplers, ORC further improves the power density of the overall system with higher power density power electronics. Moreover, ORC is inherently bidirectional and allows the system to provide power back to the grid for grid ancillary or grid support services. The ORC, based on a patented ORNL technology, is an excellent approach to resolving the high-power charging problems as described above, which directly converts the 60 hertz (Hz) line frequency into high frequency (i.e., 85 kilohertz (kHz)) to use with a high-frequency isolation transformer or wireless charging coils while eliminating the primary side number of power conversion stages from two to one. The result of the project is a prototype and reference design for a high-power wireless charging system—including power electronics, magnetics, and thermal—serving as a baseline for product development. The proposed system results are demonstrated for 270 kW of output power, with the system's overall efficiency of 92% from the AC grid, achieving less than 3% current total harmonic distortion (THD) and around 0.99 power factor (PF).

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2026

Automatic Volume Balancing for Online Refueling in Molten Salt Reactor Simulations with SCALE

This work introduces recently implemented capabilities in the SCALE code system’s TRITON reactor physics sequence that improve molten salt reactor (MSR) modeling: (1) a volume balancing option, which automatically balances the volumes of the fed material with a corresponding material removal to maintain fixed mixture volumes in the neutron transport model and accurate densities, and (2) continuous feed from mixtures, which enables users to define material feed streams directly from salt mixture definitions rather than individual nuclides. The new capabilities were demonstrated via SCALE/TRITON simulations of two representative MSR concepts. Simulations of the 180 MWth molten chloride fast reactor—a system with a fixed fuel salt volume in the reactor core—applied continuous refueling with fresh fuel salt. The results confirm approximately constant reactivity when the new volume balancing capability is used. Additionally, excellent agreement with a manual feed-and-drain method for volume balancing further verified the new implementation. Simulations of the 400 MWth EIRENE reactor, an integral MSR in which the salt volume may grow over time within the reactor core, demonstrated the capability to represent growing salt volume within the TRITON depletion calculation. Compared with reference solutions, the results show consistent trends in reactivity and isotopic evolution, confirming that these new user-friendly capabilities provide accurate, physically consistent approaches for modeling MSRs in SCALE.

Elzohery, Rabab [ORNL] (ORCID:0000000160043633)↗
NASA NTRS2011

Space-Based Sensorweb Monitoring of Wildfires in Thailand

We describe efforts to apply sensorweb technologies to the monitoring of forest fires in Thailand. In this approach, satellite data and ground reports are assimilated to assess the current state of the forest system in terms of forest fire risk, active fires, and likely progression of fires and smoke plumes. This current and projected assessment can then be used to actively direct sensors and assets to best acquire further information. This process operates continually with new data updating models of fire activity leading to further sensing and updating of models. As the fire activity is tracked, products such as active fire maps, burn scar severity maps, and alerts are automatically delivered to relevant parties.We describe the current state of the Thailand Fire Sensorweb which utilizes the MODIS-based FIRMS system to track active fires and trigger Earth Observing One / Advanced Land Imager to acquire imagery and produce active fire maps, burn scar severity maps, and alerts. We describe ongoing work to integrate additional sensor sources and generate additional products.

sensorweb↗
NASA NTRS2018

Medical Data Architecture Project Status

The Medical Data Architecture (MDA) project supports the Exploration Medical Capability (ExMC) risk to minimize or reduce the risk of adverse health outcomes and decrements in performance due to in-flight medical capabilities on human exploration missions. To mitigate this risk, the ExMC MDA project addresses the technical limitations identified in ExMC Gap Med 07: We do not have the capability to comprehensively process medically-relevant information to support medical operations during exploration missions. This gap identifies that the current in-flight medical data management includes a combination of data collection and distribution methods that are minimally integrated with on-board medical devices and systems. Furthermore, there are a variety of data sources and methods of data collection. For an exploration mission, the seamless management of such data will enable a more medically autonomous crew than the current paradigm. The medical system requirements are being developed in parallel with the exploration mission architecture and vehicle design. ExMC has recognized that in order to make informed decisions about a medical data architecture framework, current methods for medical data management must not only be understood, but an architecture must also be identified that provides the crew with actionable insight to medical conditions. This medical data architecture will provide the necessary functionality to address the challenges of executing a self-contained medical system that approaches crew health care delivery without assistance from ground support. Hence, the products supported by current prototype development will directly inform exploration medical system requirements.

medical data architecture↗
NASA NTRS2018

Medical Data Architecture (MDA) Project Status

The Medical Data Architecture (MDA) project supports the Exploration Medical Capability (ExMC) risk to minimize or reduce the risk of adverse health outcomes and decrements in performance due to in-flight medical capabilities on human exploration missions. To mitigate this risk, the ExMC MDA project addresses the technical limitations identified in ExMC Gap Med 07: We do not have the capability to comprehensively process medically-relevant information to support medical operations during exploration missions. This gap identifies that the current in-flight medical data management includes a combination of data collection and distribution methods that are minimally integrated with on-board medical devices and systems. Furthermore, there are a variety of data sources and methods of data collection. For an exploration mission, the seamless management of such data will enable a more medically autonomous crew than the current paradigm. The medical system requirements are being developed in parallel with the exploration mission architecture and vehicle design. ExMC has recognized that in order to make informed decisions about a medical data architecture framework, current methods for medical data management must not only be understood, but an architecture must also be identified that provides the crew with actionable insight to medical conditions. This medical data architecture will provide the necessary functionality to address the challenges of executing a self-contained medical system that approaches crew health care delivery without assistance from ground support. Hence, the products supported by current prototype development will directly inform exploration medical system requirements.

medical data architecture↗
DOE OSTI2020

Consequence Analysis of Residual Water in a Storage Canister - 20484

Recent observations from projects sponsored under the DOE-Nuclear Energy Spent Fuel and Waste Disposition campaign show that residual free water, well above the 0.4 gm-moles that correspond to a 3 torr rebound pressure after a 30-minute hold following prototypic drying, may remain within SNF canisters used for long-term dry storage. Specifically, experimental observations in an Integrated Research Project showed subzero temperatures and a local pocket of frozen water in a mockup fuel assembly subjected to an industry practiced drying process. In gas sampling and analysis from the High Burnup (HBU) Demonstration project, using a fully loaded and dried SNF canister, indicated presence of 100 g of residual water had remained in the canister. The effects of residual water in terms of potential adverse impacts on the condition of the SNF and the canister internals during long-term dry storage has been rigorously evaluated to address inadvertent residual water contents. The impact of residual water on the fuel and canister internals, with a focus on the oxidation of the cladding and of postulated exposed (breached-clad) fuel, were evaluated using an integrated set of time-dependent environmental conditions with semi-empirical materials oxidation models. An 'integration model,' with coupled sub-models, developed and previously used by the Center for Nuclear Waste Regulatory Analysis (CNWRA), was applied and expanded with improved sub-models for water radiolysis, and for cladding and fuel oxidations. Cladding oxidation models for various alloys were developed using the rate constants for various cladding alloys in the dry storage temperature range. A burnup-dependent fuel oxidation model was developed; it accounted for inhibition effect of fission products on fuel oxidation rates. The potential for extension of the initial breach flaw (1 mm hole) was evaluated by two separate mechanics criteria. In the first case, a critical cladding strain criterion was used. In the second case, a critical stress intensity was used to evaluate stability of a planar axial flaw postulate. A failure condition exists when a sufficient amount of fuel oxidation (at the postulated breached-clad location) causes fuel pellet swelling to load the cladding to meet a mechanics criterion for flaw extension. The integration model's results provide the following insights. The radiolysis-generated oxygen is consumed with a partitioning between the cladding and the fuel. The extent of cladding oxidation is no more than 2 μm additional consumption of the cladding metal even with 10 moles of residual water, indicating that changes in cladding conditions due to water are expected to be negligible. The conditions for cladding failure (breach opening size extension) directly correlates with the extent of fuel oxidation. Fuel oxidation significant to extend the breach could occur even with 5.5 moles of residual water. The results indicate that fuel oxidation vis-a-vis cladding oxidation is more likely under a higher radiation field, i.e., when radiolytic decomposition of the residual water occurs in few years compared to several decades, and that the conditions to cause failure are increased with fuel and cladding temperatures approaching the peak storage temperature limit of 400 deg. C. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗