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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 19 records

Morphology as a basis for taxonomy of large spirochetes symbiotic in wood-eating cockroaches and termites: Pillotina gen. nov., nom. rev.; Pillotina calotermitidis sp. nov., nom. rev.; Diplocalyx gen. nov., nom. rev.; Diplocalyx calotermitidis sp. nov., nom. rev.; Hollandina gen. nov., nom.[TRUNCATED]

The purposes of this paper are (i) to present a framework for the morphometric analysis of large uncultivable spirochetes that are symbiotic in wood-eating cockroaches and termites; (ii) to revive, in accordance with the rules of the International Code of Nomenclature of Bacteria, the names of three genera (Pillotina, Diplocalyx, and Hollandina) and three species (Pillotina calotermitidis, Diplocalyx calotermitidis, and Hollandina pterotermitidis) for the same organisms to which the names were originally applied, because these names were not included on the 1980 Approved Lists of Bacterial Names; and (iii) to formally propose the name Clevelandina reticulitermitidis for a new genus and species of spirochetes from the termite Reticulitermes tibialis. None of these genera and species has been cultivated either axenically or in mixed culture; hence, all are based on type-descriptive material.

Non-NASA Center

Derivation of A Representative Elementary Volume (REV) for Upscaled Two-Phase Flow in Porous Media

Relative permeability plays an important role in the upscaling of multiphase flow in porous media from the pore scale to the Darcy scale. The entire concept of relative permeability is contingent on the existence of a representative elementary volume (REV). As we move to smaller samples to measure relative permeability, such as with digital core analysis, the concept of a classical REV has become increasingly unlikely when using the conventional approach to defining a representative volume. The “‘conventional”’ understanding of an REV is that a large enough volume must be considered such that spatial variability averages out. In digital rock methods, such as pore-scale simulations based on micro-computed tomography (CT) images, the domain size is typically 2 to 4 mm. This is approximately the length scale of a single-phase flow REV using the classic REV approach. However, the single-phase perspective does not consider the complex dynamics and fluctuations often observed in multiphase flow systems, even at centimeter-scale experiments and/or simulations. A fundamental question is, therefore, whether the domain size commonly used in digital rock simulations can provide a consistent energy budget such that the concept of relative permeability exists. Based on first principles, relative permeability accounts for the rate of energy dissipated in a stationary process. If the dynamics are fluctuating, the energy dissipated can vary but will average out over a long enough timescale. The key to determining the validity of the relative permeability is the timescale of the measurement, not the spatial scale. The conventional REV theory assumes that spatial, temporal, and ensemble averages are equivalent in an ergodic system, but it does not provide a way to test this assumption. We provide a formal way to identify the timescale where the relative permeability accurately captures energy dissipation as a way to validate relative permeability measurements and quantitatively assess their accuracy. This result will be tested for a practical SCAL test, determining how long a flow experiment needs to be run to accurately characterize the rate of energy dissipation by the flow. The outcome will be a best practice guide for the determination of relative permeability from core-scale experiments and/or digital core simulations that ensure the energy budget is fully accounted for in the relative permeability coefficient.

Mcclure, James [Virginia Tech, Blacksburg]

REV-INR: Regularized Evidential Implicit Neural Representation for Uncertainty-Aware Volume Visualization

Applications of Implicit Neural Representations (INRs) have emerged as a promising deep learning approach for compactly representing large volumetric datasets. These models can act as surrogates for volume data, enabling efficient storage and on-demand reconstruction via model predictions. However, conventional deterministic INRs only provide value predictions without insights into the model’s prediction uncertainty or the impact of inherent noisiness in the data. This limitation can lead to unreliable data interpretation and visualization due to prediction inaccuracies in the reconstructed volume. Identifying erroneous results extracted from model-predicted data may be infeasible, as raw data may be unavailable due to its large size. To address this challenge, we introduce REV-INR, Regularized Evidential Implicit Neural Representation, which learns to predict data values accurately along with the associated coordinate-level data uncertainty and model uncertainty using only a single forward pass of the trained REV-INR during inference. By comprehensively comparing and contrasting REV-INR with existing well-established deep uncertainty estimation methods, we show that REV-INR achieves the best volume reconstruction quality with robust data (aleatoric) and model (epistemic) uncertainty estimates using the fastest inference time. Consequently, we demonstrate that REV-INR facilitates assessment of the reliability and trustworthiness of the extracted isosurfaces and volume visualization results, enabling analyses to be solely driven by model-predicted data.

Saklani, Shanu [Indian Institute of Technology, Ka

Development of a Geothermal Module in reV: Quantifying the Geothermal Potential While Accounting for the Geospatial Intersection of the Grid Infrastructure and Land Use Characteristics: Preprint

The Renewable Energy Potential (reV) model is a geospatial platform for estimating technical potential and developing renewable energy supply curves, initially developed for wind and solar technologies. The model evaluates deployment constraints, considering land use, environmental, and cultural factors, and estimates the distance to existing grid features to connect future plants (Maclaurin et al., 2021). A pressing deficiency in the reV model, however, is representation of geothermal electricity generation technologies. To address this gap, we developed a novel geothermal generation module for reV that allows for representation and analysis at the same level of detail as other renewable technologies. This paper describes our process for evaluating data sources for the modeling, and presents five preliminary reV geothermal results. More specifically, we present two sets of resource data that represent upper and lower bounds for geothermal potential. We then present several sensitivity runs using the upper bound resource data; the results are encouraging that levelized cost of electricity (LCOE) can be reduced by optimizing the location and estimated capacity of the spatially diverse geothermal resource while considering the distance to existing grid infrastructure. Our preliminary supply curves and levelized cost of electricity (LCOE) results should be considered with care due to the highly uncertainty in geothermal resource potential data. We present median LCOE values for the conterminous U.S. for five scenarios: four hydrothermal (3.5km depth) and one EGS (4.5km depth). The capital and operating costs for each respective technology are modeled. We also compare results using two different resource data sources.

exclusions

reVRt (reV Routing) [SWR-25-112]

The reV Routing (reVRt) tool is a computational framework for modeling and optimizing transmission infrastructure requirements for electrical grid connections. By employing a spatially-aware least-cost-path methodology, it allows users to incorporate a wide range of factors including siting constraints, regional component costs, land composition costs, point-of-interconnection costs, and network upgrade costs. Additionally, the tool enables advanced follow-on analyses, such as land characterization for potential transmission line routes, to support informed decision-making. Although it's designed to integrate seamlessly with the reV model, the reV Routing tool is versatile and can also be utilized independently for standalone analyses in transmission planning and resource assessment scenarios.

Pinchuk, Pavlo (Paul) [National Renewable Energy L

Powered By reV [Slides]

The reV model empowers users to calculate energy capacity, generation, and cost based on geospatial intersection with grid infrastructure and land-use characteristics. The tool can model a single site up to an entire continent at temporal resolutions ranging from five minutes to hourly, spanning a single year or multiple decades. By automating access to resource data at unprecedented scale, fidelity, and flexibility, the reV model integrates formerly disparate analysis frameworks in the fields of resource modeling, technical potential, and energy cost supply curves.

29 ENERGY PLANNING, POLICY, AND ECONOMY

Comparative Study of Enhanced Geothermal System Supply Curves Across CONUS from Two Temperature Models Using the Renewable Energy Potential Model (reV)

Enhanced geothermal systems (EGS) have had recent breakthroughs within the geothermal sector. These breakthroughs are reflected in the National Renewable Energy Laboratory (NREL) 2024 Annual Technology Baseline and will result in updated EGS supply curves (i.e., the available resource capacity relative to cost). Our research uses NREL's Renewable Energy Potential (reV) model to compare EGS supply curves across the conterminous United States (CONUS) for two different temperature models: the Stanford temperature model (STM) and the Southern Methodist University temperature model (SMU). The reV model provides the levelized cost of energy (LCOE) at a consistent resolution across CONUS, taking into consideration transmission costs and constraints as well as technical exclusions pertaining to sensitive cultural, ecological, or infrastructure locations. In addition to a countrywide analysis of both models, we also conducted a regional analysis of Texas. We observed the STM had, on average, lower temperatures across different depths, resulting in slightly higher mean and median LCOEs as compared to the SMU temperature model at the same depths. In the regional analysis for Texas, however, when we compared only the common points between the two temperature models, the STM had lower median and mean LCOEs compared to SMU due to higher temperatures at depths greater than 5 km.

enhanced geothermal systems

reVeal: the reV Extension for Analyzing Large Loads [SWR-25-147]

reVeal (the reV Extension for Analyzing Large Loads) is an open-source geospatial software package for modeling the site-suitability and spatial patterns of deployment of large sources of electricity demand under future scenarios. reVeal is part of the reV ecosystem of tools [https://nrel.github.io/reV/#rev-ecosystem].

Pinchuk, Pavlo (Paul) [National Laboratory of the

Microsemi RTG4 Rev C Field Programmable Gate Array Single Event Effects (SEE) Heavy-Ion Test Report

The goal of this study was to perform an independent investigation of single event destructive and transient susceptibility of the Microsemi RTG4 device. The devices under test were the Microsemi RTG4 field programmable gate array (FPGA) Rev C. The devices under test will be referenced as the DUT or RTG4 Rev C throughout this document. The DUT was configured to have various test structures that are geared to measure specific potential susceptibilities of the device. DesignDevice susceptibility was determined by monitoring the DUT for Single Event Transient (SET) and Single Event Upset (SEU) induced faults by exposing the DUT to a heavy ion beam. Potential Single Event Latch-up (SEL) was checked throughout heavy-ion testing by monitoring device current.

Field Programmable Gate Array (FPGA)

X-33 (Rev-F) Aeroheating Results of Test 6770 in NASA Langley 20-Inch Mach 6 Air Tunnel

Aeroheating characteristics of the X-33 Rev-F configuration have been experimentally examined in the Langley 20-Inch Mach 6 Air Tunnel (Test 6770). Global surface heat transfer distributions, surface streamline patterns, and shock shapes were measured on a 0.013-scale model at Mach 6 in air. Parametric variations include angles-of-attack of 20-deg, 30-deg, and 40-deg; Reynolds numbers based on model length of 0.9 to 4.9 million; and body-flap deflections of 10-deg and 20-deg. The effects of discrete roughness elements on boundary layer transition, which included trip height, size, and location, both on and off the windward centerline, were investigated. This document is intended to serve as a quick release of preliminary data to the X-33 program; analysis is limited to observations of the experimental trends in order to expedite dissemination.

Berry, Scott A.

Haloarcula marismortui (Volcani) sp. nov., nom. rev., an extremely halophilic bacterium from the Dead Sea

An extremely halophilic red archaebacterium isolated from the Dead Sea (Ginzburg et al., J. Gen. Physiol. 55: 187-207, 1970) belongs to the genus Haloarcula and differs sufficiently from the previously described species of the genus to be designated a new species; we propose the name Haloarcula marismortui (Volcani) sp. nov., nom. rev. because of the close resemblance of this organism to "Halobacterium marismortui," which was first described by Volcani in 1940. The type strain is strain ATCC 43049.

NASA Discipline Number 52-30

CritView User’s Guide Rev. 2

This document serves as a user’s guide for the CritView code, version 1.05. It supersedes the previous revision (Rev. 1), which was applicable to version 1.04 of CritView. This release of CritView also includes version 1.09 of the database, which replaces version 1.08. The CritView code is used as an electronic equivalent of a nuclear criticality handbook (e.g., ARH-600). This code takes an electronic data library and allows the user to plot data as needed. This approach has two distinct advantages over a paper handbook. First, the database can be easily expanded to include additional data sources (e.g., other handbooks, configurations, or modeling techniques). Secondly, the code provides flexibility by allowing the user to easily change the units and parameters of the plots.

Finfrock, Scott H. [Savannah River Nuclear Solutio

Calendar Year 2024 Underground Test Area Annual Sampling Letter Report, Nevada National Security Site, Nevada, Rev. 1

The Underground Test Area (UGTA) Sampling Plan for Corrective Action Units (CAUs) 101 and 102: Central and Western Pahute Mesa, Nevada National Security Site (NNSS), Nevada (referred to herein as “the Plan”) (DOE/EMNV, 2025) describes the approach for collecting and analyzing groundwater samples to meet the objectives of the U.S. Department of Energy (DOE), Environmental Management (EM) Nevada Program’s UGTA Activity. The Plan is designed to ensure compliance with the UGTA Quality Assurance Plan (QAP) (DOE/EMNV, 2024), and the Federal Facility Agreement and Consent Order (FFACO) (1996, as amended).

54 ENVIRONMENTAL SCIENCES

Erratum: Description of the Proton-Decaying 0$^{+}_{2}$ Resonance of the 𝛼 Particle [Phys. Rev. Lett. 131 , 242502 (2023)]

As pointed out by P. Yin, H. Li, A. M. Shirokov, X. Zhao, and J. P. Vary, due to the incorrect normalization of the charge density, our definition of the monopole form factor 𝐹rel⁡(𝑞 2 ) was different from that used in other papers [1,2] by a factor of 1/𝑍. Furthermore, this resulted in the overall incorrect normalization of the monopole form factor in this Letter.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS

Erratum: Centrality-Dependent Modification of Jet-Production Rates in Deuteron-Gold Collisions at $\sqrt{𝑠_{𝑁⁢𝑁}}$ = 200 GeV [Phys. Rev. Lett. 116, 122301 (2016)]

We previously reported jet-production rates in 𝑝 + 𝑝 and 𝑑 + Au collisions at $\sqrt{𝑠_{𝑁⁢𝑁}}$ = 200 GeV recorded in 2008 with the PHENIX detector at the Relativistic Heavy Ion Collider. Subsequently, we found that electronic noise in the electromagnetic calorimeter was not completely removed by the tower-timing cuts used in the analysis. We have conducted an independent re-analysis of the data that eliminated noisy towers by removing them completely from the analysis. These cuts remove any contributions from instrumental noise, but reduce the overall acceptance for electromagnetic clusters by ≈16% and hence the overall statistical power of the data. Finally, this re-analysis found that instrumental noise in the electromagnetic calorimeter led to an artificial increase in the jet yield for both the 𝑝 + 𝑝 and 𝑑 + Au collisions.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS