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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 343 records · Page 19
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Developing reactors for electrifying bio-methanation: a perspective from bio-electrochemistry

The integration of microbial synthesis with renewable electricity is an emerging route for both CO 2 utilization and seasonal energy storage in the form of stored bio-electrofuels. The major benefits of electrifying bioreactors include: using highly selective bio-catalysts for CO 2 conversion under mild reaction conditions; decoupling the production of more facile electrochemical intermediates, such as hydrogen, at the electrode from the production of bio-catalyzed multi-electron and/or carbon products, such as methane or acetate; using microbes as robust and self-regenerating catalysts enabling higher efficiency and durability in CO 2 conversion systems compared to inorganic catalysis. In this Perspective, we propose research aimed at developing electro-bioreactor components that will increase the productivity of the reactor while maintaining high energy efficiency and biocompatible reaction conditions to fully realize the benefits of electrified bioreactors. Furthermore, these developments include: flow reactors with tailored 3D electrodes to optimally use the reactor volume, electrocatalysts designed for peak performance in neutral pH electrolytes, high conductivity microbial media, and new membrane separator materials with high ion conductivity and low gas permeability. Production of methane via a hybrid electrical-biological approach is taken as a case study to motivate these developments. Finally, an iterative design–manufacture–test cycle, enabled by additive manufacturing and 3D printing technologies, is proposed to rapidly prototype components prior to large-scale manufacturing.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Finite-element boundary-integral simulation of thin wires and inhomogeneous penetrable bodies in subsurface multilayered anisotropic media

With the prevailing presence of drilling wells near the subsurface in mature oil and gas fields, the application of electromagnetic methods can be particularly challenging where the electromagnetic field is affected by the steel casing. In the past decades, borehole-to-surface and crosswell electromagnetic methods have been utilized for monitoring of reservoir and underground CO 2 storage. This paper presents a unified finite-element boundary-integral (FEBI) method capable of simultaneously modeling the complex electromagnetic interactions between thin metallic wires (representing steel casings) with 3D trajectory and arbitrary 3D inhomogeneous penetrable bodies (such as CO 2 plumes or hydrocarbon reservoirs) within anisotropic multilayered subsurface environments. Unlike existing approaches that treat these components separately or require dense discretization, or are limited to vertical wells, our unified formulation preserves flexible electromagnetic coupling while delivering improved computational efficiency. Assuming the background formation is multilayered anisotropic media, the surface integral equation method is applied to model the thin wires and boundaries of the inhomogeneous bodies. Meanwhile, the finite element method is applied to model the volume of inhomogeneous bodies. Here, the performance of the proposed FEBI method is assessed through comparison with reference numerical results and its practical significance is demonstrated through CO 2 plume monitoring scenarios.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Manipulating the 3D organization of the largest synthetic yeast chromosome

Whether synthetic genomes can power life has attracted broad interest in the synthetic biology field. Here, we report de novo synthesis of the largest eukaryotic chromosome thus far, synIV, a 1,454,621-bp yeast chromosome resulting from extensive genome streamlining and modification. We developed megachunk assembly combined with a hierarchical integration strategy, which significantly increased the accuracy and flexibility of synthetic chromosome construction. Besides the drastic sequence changes, we further manipulated the 3D structure of synIV to explore spatial gene regulation. Surprisingly, we found few gene expression changes, suggesting that positioning inside the yeast nucleoplasm plays a minor role in gene regulation. Lastly, we tethered synIV to the inner nuclear membrane via its hundreds of loxPsym sites and observed transcriptional repression of the entire chromosome, demonstrating chromosome-wide transcription manipulation without changing the DNA sequences. Our manipulation of the spatial structure of synIV sheds light on higher-order architectural design of the synthetic genomes.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Best-estimate Modeling of the High Temperature Test Facility with RELAP5-3D

Prismatic HTGRs are a concept of interest for near-term deployment. While plenty of validation data exist for standalone neutronics or multiphysics modeling, the availability of integral effects thermal hydraulics validation data is more limited. The High Temperature Test Facility provides such data and is used as the basis for the High-Temperature Gas-Cooled Reactor Thermal Hydraulics Benchmark. This presentation presents results of best-estimate modeling of HTTF experiments PG-27 and PG-29 using the RELAP5-3D ring model developed at Idaho National Laboratory.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2023

Tailoring biogenic straw insulation from additive manufacturing

In the pursuit of carbon-storing materials that could help accomplish high levels of building sustainability, wheat straw has emerged as a promising alternative to fossil fuel-based building materials. Straw is 100% biodegradable and abundant agricultural waste used in the construction 400 years ago, and it has been reported to have the lowest embodied carbon when measured against other typical insulating materials. Here, in this study, we report additive manufacturing of carbon-sequestration insulation panel materials by upcycling cellulose fibrils from wheat straw. Cellulose obtained from alkaline and 2,2,6,6-tetramethylpiperidine-1-oxyl radical-mediated oxidation shows thermal conductivity of 0.036 W m -1 K -1 , alongside elastic and flexural modulus of 900 MPa and 502 MPa, respectively. In addition, an in-situ hydrophobic treatment in the cellulose-based insulation panels is achieved with an average water contact angle of 133.7° Furthermore, the extrusion-based additive manufacturing of a 3D-printable ink obtained by mixing the cellulose and silica aerogel precursor is accomplished, with the printed material exhibiting structural integrity, thus showing great potential towards the development of state-of-the-art, sustainable materials for carbon-sequestration building applications.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Rapid Quantification of 237 U Specific Activity for Nuclear Forensics

In the event of an unattributed nuclear explosion, rapid assessment of the short-lived uranium isotope activity and mass can provide valuable information for subsequent forensic analysis. Rapid analysis in the field is enabled by using microfluidic chemistry and deployable instrumentation. Here, this work presents a flow chemistry system, controlled in LabVIEW, that integrates three functionalities: (1) selective extraction of uranium from the sample matrix via a 3D-printed supported liquid membrane module; (2) UV–visible absorbance spectrophotometry to measure the total uranium concentration in the strip flow; and (3) a portable CdTe γ-ray spectrometer coupled to a 3D-printed flow cell to measure 237 U activity concentration in the strip solution. The system was calibrated using standard solutions, and its functionality was demonstrated using a solution of depleted uranium spiked with 237 U. Uranium concentrations of 40–5000 μg/mL were directly quantified online using a 100 mm optical flow cell, while concentrations of 0.5–10 μg/mL were quantified online using a colorimetric reagent. The mass concentration measurement takes approximately 60 min while the activity concentration via γ-ray spectrometry varies depending on the activity of 237 U, with 1 kBq/mL requiring about 30 min of acquisition time to obtain <10% uncertainty at 1σ. This platform provides a fieldable approach for quantifying uranium mass and radioactivity relevant to postdetonation nuclear debris.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Airy light-sheet Raman imaging

Light-sheet fluorescence microscopy has greatly improved the speed and overall photostability of optically sectioning cellular and multi-cellular specimens. Similar gains have also been conferred by light-sheet Raman imaging; these schemes, however, rely on diffraction limited Gaussian beams that hinder the uniformity and size of the imaging field-of-view, and, as such, the resulting throughput rates. Here, we demonstrate that a digitally scanned Airy beam increases the Raman imaging throughput rates by more than an order of magnitude than conventional diffraction-limited beams. Overall, this, spectrometer-less, approach enabled 3D imaging of microparticles with high contrast and 1 µm axial resolution at 300 msec integration times per plane and orders of magnitude lower irradiation density than coherent Raman imaging schemes. We detail the apparatus and its performance, as well as its compatibility with fluorescence light-sheet and quantitative-phase imaging towards rapid and low phototoxicity multimodal imaging.

47 OTHER INSTRUMENTATION↗
DOE OSTI2021

CMDV-RRM: Representation of Clouds and Convection Across Scales in E3SM (Final Report)

We have made three accomplishments as a participant of the LLNL-led CMDV-RRM project. The first is the derivation of 3D high-resolution atmospheric variational analysis (VAR) at 2 x 2 km resolution by integrating ARM data and operational analysis for a domain of approximately 450 x 400 km centered at the ARM SGP facility for several MC3E convective events and used the analyzed data to evaluate E3SM RRM and as forcing data for E3SM SCM. The second accomplishment is the demonstration of elevated maximum moist static energy during the night over the ARM SGP that was not accounted for in the default E3SM convection scheme. The third accomplishment is the explanation of the cause of the dry and warm biases over the SGP common to many climate models by using ARM data. We found that the precipitation deficit associated with lack of strong rainfall events in the summer is the main cause of the warm bias over the SGP.

42 ENGINEERING↗
DOE OSTI2026

Mu2e Target Thermal Test Project

The Mu2e experiment requires a production target capable of operating under extreme thermal conditions caused by an 8 GeV proton beam. This project’s objective supports the development of the Mu2e Production Target by testing the Stickman model’s thermal behavior. To test this, Angel Flores Luviano has assisted Jonathan Williams in progressing this project by contributing to the development of a Radiative Cooling Test Fixture (RCTF) that will be used to evaluate the thermal behavior of the new production target model. Engineering calculations were performed to analyze thermal performance and pressure drop within the cold well and water cooling circuit, and determine optimal sizing for key components of the water system. An engineering note was made to document the calculations. CAD models of the water circuit piping, thermocouple mount, and radiator chimney were developed, and prototype test rig components were fabricated using 3D printing. Future work will focus on conti nued RCTF development which includes control system integration, heater hardware design, and interfaces that can be scaled up to increase thermal capacity.

Luviano, Angel Flores [Unlisted]↗
DOE OSTI2022

Applying 3D Geologic Modeling Workflows to the Argillite Reference Case (Rev. 1)

The objective of this short report is to document the application of our 3D geologic modeling workflow to an argillite (shale) host rock. Over the past four years, our team at Los Alamos National Laboratory has developed a geologic modeling workflow that can be applied to generic alluvial basins such as those found in the western United States. In “frontier” or “exploratory” basins where data are sparse, the first steps are to collect, evaluate and integrate available subsurface data into conceptual geologic models. Those models form the basis for constructing the geologic framework model, a 3D geocellular model ideally constrained by seismic and borehole data. To date we have constructed our models using “synthetic” well data derived from conceptual models, without the prospect of validating our workflow using “real” subsurface data. We were tasked to investigate whether our workflow designed for alluvial basin sediments could be applied to other potential repository host rocks. This task also provided the opportunity to work with high-quality subsurface data collected specifically for siting and evaluating a nuclear waste repository. Nagra, the Swiss governmental agency responsible for the disposal of the nation’s radioactive waste, generously provided us with data from two deep boreholes drilled through their argillaceous target formation. The aim of our proof-of-concept demonstration is to evaluate whether geostatistical methods offer a viable approach to property modeling in argillaceous rocks. Nagra provided us with the well data on the condition that we maintain confidentiality with all transferred information and results. Fortunately, Nagra posts numerous technical reports on its public website that describe the subsurface geology in great detail. All of the information and illustrations in this report related to the Swiss repository enterprise are taken from the Nagra public website.

58 GEOSCIENCES↗
DOE OSTI2022

Intelligent Process Visualization through Nuclear Operation Process Modeling, Reasoning, and Object Detection from Field Videos (Final Report)

This report is a deliverable for the “Final Report” task of DOE NEET Project 19-16790, "Context-Aware Safety Information Display for Nuclear Field Workers." This project's overall goal is to test the hypothesis that integrating computer vision and process reasoning methods will enable proactive visualization of the safe operation and maintenance processes of Nuclear Power Plants (NPP) for field workers. Augmented Reality (AR) glasses adopting such proactive safety information visualization techniques can significantly increase personnel safety and reduce the NPP’s operating costs. The current practice of monitoring NPPs requires workers to switch between digital models, data, and physical workspaces in identifying relevant but potentially occluded objects and in assessing the risks of operation and maintenance processes. On the other hand, frequently changed field conditions require field workers to report to supervisors for real-time guidance. Such guidance is essential to ensure that changing conditions will not invalidate or endanger the work order and other ongoing processes that may jeopardize NPP operations. Additionally, incorrect recognition of equipment objects can result in communication errors and safety problems. AR techniques can assist engineers in viewing the physical workspaces with objects labeled with detailed operation procedures and safety reminders during field operations. The project team developed an “Intelligent Context-Aware Safety Information Display” (ICAD) for supporting Nuclear Power Plant (NPP) field workers in achieving safe and efficient execution of a series of operational tasks in uncertain and changing workspaces of an NPP. Before designing the ICAD-AR prototype, the project team synthesized NPP operational knowledge models through literature review studies, surveys, interviews with domain experts, and knowledge modeling. The project team conducted an extensive study of the operational procedures of various NPPs, and digital technologies that can support the safe and efficient execution of those procedures in different NPP operational contexts. This literature review helped the project team conduct surveys and interviews with nuclear engineers and field workers to identify three categories of information. The NPP knowledge modeling efforts reveal that the three categories of information identified have different levels of importance in a typical procedure of carrying out a series of tasks to achieve a specific NPP operation goal (e.g., shutdown, mode changes). These three categories of information include 1) Workspace dynamics – the changing spatial arrangements of workspaces, tools, protection equipment, and supporting materials, 2) Workflow prognostics – the dynamic dependencies between different parts of an NPP that functionally support and influence each other in terms of safety and efficiency, and 3) Hazards – objects and spaces that contain hazardous materials or physical conditions that can pose risks to workers or mechanical systems. The project team has profiled the importance levels of these categories of information into a knowledge model. This knowledge model specifies what types of information are more critical for a given task in a given workspace so that computers can automatically identify critical objects and sensors in a scene for delivering context-ware safety information to field workers through AR devices. Significant research development of this project results in technical research outcomes and a prototyping system that illustrates the technical feasibility of establishing an ICAD-AR system supporting the proactive safety information display for nuclear field workers. This final report summarizes the project team’s technological achievements in the past three years. Overall, the project team completed the development and integration of five techniques into a prototype ICAD Augmented Reality (ICAD-AR) system and demonstrated the developed system’s real-time execution in a mechanical room. The project team completed the analysis of using this prototype in other types of workspaces based on 3D image data and digital design models collected from two additional workspaces (a water treatment plant and a flow loop training facility). The integrated techniques include 1) Natural Language Processing (NLP) algorithms supporting the generation and updates of nuclear fieldwork process models based on text analysis of work packages and operation manuals; 2) sensor log analysis for predicting control actions in given sensor reading contexts; 3) computer vision algorithms for automatic localization and navigation of workers; 4) object detection algorithms for identifying task-related objects and correlated sensors for safety checking; 5) AR technique as a platform for supporting the integration. The testing results of these five techniques have shown that 1) the sensor log analysis model can predict the next control action with an accuracy of 0.883; 2) the trained natural language processing model can extract more than 80% of the critical information from paper-based procedures (PBPs); 3) the navigation algorithm with the integration of Visual Inertial Odometry (VIO) and Non-Recursive Bayesian Filter methods make operator’s trajectory estimation resilient to drift error; 4) the computer vision algorithm can detect task-specific and safety-critical objects with an average accuracy of 95.3%. The project team used work procedures collected from a flow loop training facility and two datasets collected from two mechanical rooms simulating the workspaces of NPPs to demonstrate the technical capabilities of the developed ICAD-AR prototype. The demonstration validated the technical feasibility of establishing the ICAD-AR system for nuclear field workers and identified the challenges in 1) automatic text analysis of work packages; 2) use of limited samples of sensor logs for predicting the proper timings of control actions; 3) reliably tracking workers and their task progress in mechanical rooms with many similar objects.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2022

Magnetic Designs of New First Target Beamline Magnets for the ORNL SNS Upgrade

The Spallation Neutron Source (SNS) at ORNL currently is being upgraded from 1.0 GeV to 1.3 GeV. Several water-cooled magnets should be upgraded to transport 30% of higher beam energy. New chicane, injection/extraction septum, and Lambertson magnets were designed. Designing the magnets was a challenging task because the new magnets required good combined integrated field quality and needed to occupy the old magnets space but with about 20% greater integrated magnetic field. Additional strong requirements applied to the magnets fringe field do not disturb the circulating beam. The special field profiles had to be provided in foil areas between magnets. The analysis described here was based on OPERA3D simulations. A special technique was used for analyzing the integrated field harmonics. Initially, the particle track was simulated, and integrated field components were calculated along this track for the reference radius, which were used for the harmonics analysis. In addition, 3D field maps were provided for beam optics simulations. The final beamline analysis confirmed good beam transmission and low losses.

3d field maps↗
DOE OSTI2024

3D Multiresolution Velocity Model Fusion with Probability Graphical Models

ABSTRACT The variability in spatial resolution of seismic velocity models obtained via tomographic methodologies is attributed to many factors, including inversion strategies, ray-path coverage, and data integrity. Integration of such models, with distinct resolutions, is crucial during the refinement of community models, thereby enhancing the precision of ground-motion simulations. Toward this goal, we introduce the probability graphical model (PGM), combining velocity models with heterogeneous resolutions and nonuniform data point distributions. The PGM integrates data relations across varying resolution subdomains, enhancing detail within low-resolution (LR) domains by utilizing information and prior knowledge from high-resolution (HR) subdomains through a maximum posterior problem. Assessment of efficacy, utilizing both 2D and 3D velocity models—consisting of synthetic checkerboard models and a fault-zone model from Ridgecrest, California—demonstrates noteworthy improvements in accuracy, compared to state-of-the-art fusion techniques. Specifically, we find reductions of 30% and 44% in computed travel-time residuals for 2D and 3D models, respectively, as compared to conventional smoothing techniques. Unlike conventional methods, the PGM’s adaptive weight selection facilitates preserving and learning details from complex, nonuniform HR models and applies the enhancements to the LR background domain.

Geochemistry & Geophysics↗
DOE OSTI2025

Building a Long-Lived 3D Multimode Quantum Processing Unit with TESLA Cavities

Superconducting radio-frequency (SRF) cavities, such as TESLA-shaped cavities, are excellent candidates for long-lived quantum memories. Integrating these cavities with nonlinear elements, such as transmons, enables universal quantum control; however, this integration can often introduce unwanted losses. In this talk, we present the successful integration of a long-lived 2-cell TESLA cavity with an ancillary qubit, forming a quantum processing unit (QPU) that allows for robust control while maintaining coherence. We demonstrate universal control of the QPU through various schemes, including ancilla-cavity sideband and echoed conditional displacement (ECD) methods, enabling fault-tolerant high-fidelity preparation of large Fock states and fast entanglement generation. These results illustrate the versatility and efficiency of our 3D quantum processing unit, paving the way for advanced quantum computing applications.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Comprehensive characterization of the structure of Zr-based metallic glasses

Structure of metallic glasses fascinates as the generic amorphous structural template for ubiquitous systems. Its specification necessitates determination of the complete hierarchical structure, starting from short-range-order (SRO) → medium-range-order (MRO) → bulk structure and free volume (FV) distribution. This link has largely remained elusive since previous investigations adopted one-technique-at-a-time approach, focusing on limited aspects of any one domain. Reconstruction of structure from experimental data inversion is non-unique for many of these techniques. As a result, complete and precise structural understanding of glass has not emerged yet. In this work, we demonstrate the first experimental pathway for reconstruction of the integrated structure, for and glasses. Our strategy engages diverse (×7) multi-scale techniques [XAFS, 3D-APT, ABED/NBED, FEM, XRD, PAS, FHREM] on the same glass. This strategy complemented mutual limitations of techniques and corroborated common parameters to generate complete, self-consistent and precise parameters. Further, MRO domain size and inter-void separation were correlated to identify the presence of FV at MRO boundaries. This enabled the first experimental reconstruction of hierarchical subset: SRO → MRO → FV → bulk structure. The first ever image of intermediate region between MRO domains emerged from this link. We clarify that determination of all subsets is not our objective; the essence and novelty of this work lies in directing the pathway towards finite solution, in the most logical and unambiguous way.

36 MATERIALS SCIENCE↗
DOE OSTI2023

3D-equivariant graph neural networks for protein model quality assessment

Quality assessment (QA) of predicted protein tertiary structure models plays an important role in ranking and using them. With the recent development of deep learning end-to-end protein structure prediction techniques for generating highly confident tertiary structures for most proteins, it is important to explore corresponding QA strategies to evaluate and select the structural models predicted by them since these models have better quality and different properties than the models predicted by traditional tertiary structure prediction methods. We develop EnQA, a novel graph-based 3D-equivariant neural network method that is equivariant to rotation and translation of 3D objects to estimate the accuracy of protein structural models by leveraging the structural features acquired from the state-of-the-art tertiary structure prediction method—AlphaFold2. We train and test the method on both traditional model datasets (e.g. the datasets of the Critical Assessment of Techniques for Protein Structure Prediction) and a new dataset of high-quality structural models predicted only by AlphaFold2 for the proteins whose experimental structures were released recently. Our approach achieves state-of-the-art performance on protein structural models predicted by both traditional protein structure prediction methods and the latest end-to-end deep learning method—AlphaFold2. It performs even better than the model QA scores provided by AlphaFold2 itself. The results illustrate that the 3D-equivariant graph neural network is a promising approach to the evaluation of protein structural models. Integrating AlphaFold2 features with other complementary sequence and structural features is important for improving protein model QA.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

System Calibration Including Time Delay Estimation for GNSS/INS-Assisted Pushbroom Scanners Onboard UAV Platforms

Unmanned aerial vehicles (UAVs ) equipped with imaging sensors and integrated global navigation satellite system/inertial navigation system (GNSS/INS ) units are used for numerous applications. Deriving reliable 3D coordinates from such UAVs is contingent on accurate geometric calibration, which encompasses the estimation of mounting parameters and synchronization errors. Through a rigorous impact analysis of such systematic errors, this article proposes a direct approach for spatial and temporal calibration (estimating system parameters through a bundle adjustment procedure) of a GNSS/INS -assisted pushbroom scanner onboard a UAV platform. The calibration results show that the horizontal and vertical accuracies are within the ground sampling distance of the sensor. Unlike for frame camera systems, this article also shows that the indirect approach is not a feasible solution for pushbroom scanners due to their limited ability for decoupling system parameters. This finding provides further support that the direct approach is recommended for spatial and temporal calibration of UAV pushbroom scanner systems.

47 OTHER INSTRUMENTATION↗