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At least 433 records · Page 24

Alabama Carbon Storage: Bringing Data to the People

The Gulf Coastal Plain of Alabama has proven potential for geologic carbon storage and current interest in the area for large carbon capture and storage (CCS) projects is high. Extensive CCS relevant data exist in the records of the Geological Survey of Alabama and State Oil and Gas Board of Alabama, however, most of this data is not publicly available or is scattered in separate databases, file cabinets, and tables in publications. The “Alabama Carbon Storage: Data Sharing and Engagement” (ACS-DSE) project seeks to accelerate the responsible development of large CCS projects in the Gulf Coastal Plain of Alabama and offshore in state waters through a publicly accessible database of geologic carbon storage models and data across the region. The ACS-DSE draws on the over 150 years of geologic research and over 20 years of experience in CCS research to place relevant geologic, geophysical, and infrastructure data on a single web platform. Datasets available will include formation depths and elevations, geologic structures, reservoir properties, digital well logs (LAS files), existing penetrations, and geologic models. In addition to downloadable datasets, links to CCS related regulatory agencies and other sources of information will be included (for example, Class VI UIC permitting regulations and pipeline regulations). By making these datasets and models available in commonly used formats on a public website, the project will increase transparency in decision making and decrease the data acquisition time for industry.

01 COAL, LIGNITE, AND PEAT↗

C-HER Metadata Overview: Approach, Standards, and Rigor for the Centralized Health and Exposomic Resource

The Centralized Health and Exposomic Resource (C-HER) unifies environmental, demographic, geographic, and health-related data for exposomic research. The source data differ in format, geographic coverage, time period, resolution, terminology, and documentation. We use a common metadata framework to describe those differences and to record how each data resource has been processed, documented, and ingested. This document relates only to the C-HER metadata framework. It explains the information that is recorded for each resource, the standards used to organize that information, the conditions for metadata completeness, and the relationship between metadata and quality review. It is intended for those who need to understand what C-HER metadata communicates and how it supports appropriate use of the data. It is not an implementation specification or procedure. It does not document the database schema, source code, deployment configuration, transformation algorithms, or dataset-specific QA/QC thresholds. Those materials are maintained separately.

MacFarland, Midgie [ORNL] (ORCID:0009000807354078)↗

The 2021 update of the EPA’s adverse outcome pathway database

The EPA developed the Adverse Outcome Pathway Database (AOP-DB) to better characterize adverse outcomes of toxicological interest that are relevant to human health and the environment. Here we present the most recent version of the EPA Adverse Outcome Pathway Database (AOP-DB), version 2. AOP-DB v.2 introduces several substantial updates, which include automated data pulls from the AOP-Wiki 2.0, the integration of tissue-gene network data, and human AOP-gene data by population, semantic mapping and SPARQL endpoint creation, in addition to the presentation of the first publicly available AOP-DB web user interface. Potential users of the data may investigate specific molecular targets of an AOP, the relation of those gene/protein targets to other AOPs, cross-species, pathway, or disease-AOP relationships, or frequencies of AOP-related functional variants in particular populations, for example. Version updates described herein help inform new testable hypotheses about the etiology and mechanisms underlying adverse outcomes of environmental and toxicological concern.

59 BASIC BIOLOGICAL SCIENCES↗

Adapting Nuclear Forensics from Light Water to Molten Salt Reactors: A Survey of Emerging Needs

Rising interest in molten salt reactors for commercial power production presents an opportunity to evaluate the techniques used to characterize materials of nuclear forensic interest. Since extensive research has been performed to identify and develop signatures of light water reactor (LWR) materials (e.g. uranium ore concentrates and uranium dioxide fuel pellets), we use this as a basis to explore possibilities for molten salt signature development. Through this comparative method, nuclear forensic signatures used today to identify the provenance of nuclear materials found out of regulatory control are adapted to molten salt reactor (MSR) fuel cycle materials. Radiological, elemental composition, isotopic composition, and model age signatures will likely not need large adaptations before being applied to MSR materials but may need to expand to be applicable to both thorium- and uranium-fueled systems. The liquid nature of molten salt fuel may erase signatures related to production and irradiation history that are informative for typical LWR materials. However, it may also lead to opportunities for new signatures, such as cooling rate–controlled morphology. Targets identified for further research include radiological attributes of fuel salts; elemental, chemical, and isotopic analysis of salts with differing production routes; morphological effects of various thermodynamic environments; and relevant fuel cycle radiochronometers. Additionally, the comparative nature of the proposed signatures implies a need for MSR-relevant databases and the production of salt standard reference materials.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Hydropower Evaluation Framework for Wildfire Resilient Microgrids

This paper presents a framework for characterizing hydropower plants based on plant and site attributes, assessing their feasibility to function within microgrids during periods of wildfire-induced outages. A set of nine metrics is developed to assign scores to hydropower plants, considering their suitability for forming wildfire-resilient microgrids, their capability to operate within such microgrids, and their simulated performance during wildfire events. A comprehensive database is constructed, comparing hydropower plants according to their suitability and capability metrics. To evaluate the performance score of a specific hydropower plant, namely the Hills Creek plant situated in a wildfire-prone region of Oregon, a case study is conducted, simulating a wildfire scenario. The results of steady-state and dynamic simulations demonstrate that the Hills Creek hydropower plant can effectively provide crucial microgrid services and power nearby communities during a prolonged wildfire-related outages.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Design Basis Document / Owner’s Technical Specification for Nitrate Salt Systems in CSP Projects (Final Technical Report)

The number of commercial coal, gas, and nuclear projects built over the past 100 years number in the thousands. As such, there is a large database, available to a wide range of commercial engineering contractors, on proven designs. In essence, unsuccessful designs have, through generations of iterations, been identified and then deleted from further consideration. In contrast, the number of commercial parabolic trough projects using nitrate salt for the thermal storage media is perhaps 60. Further, the number of commercial central receiver projects using nitrate salt as the working fluid is on the order of 20, including estimates for China. Given the relative immaturity of salt technology, and commercial pressures to successfully bid new solar projects into a mature electricity market, solar projects often promise more than has been delivered. The Design Basis Document / Owner’s Technical Specification is a first step in the iteration process. The report describes the successful features of commercial projects, outlines a range equipment and system failures in projects that didn’t operate as intended, and provides a draft set of design changes intended to correct the known problems. The product of the study is 3 volumes of technical material; one volume is on parabolic trough technologies; a second is on central receiver technologies, and the third is on potential design changes to parabolic trough and central receiver projects. The 3 volumes, which total some 590 pages, can be found at https://www.solardynllc.com/csp-plant-technologies. One of the principal topics in the report is the use of functional or prescriptive specifications. Functional specifications describe what the equipment needs to do, consistent with the minimum legal requirements of the local jurisdictions. The details of how this is to be accomplished is developed by the engineering contractor. Prescriptive specifications, which are developed by the Owner, prescribe to the engineering contractor how the functional requirements are to be met. This arrangement ensures that the favorable experience from a previous project is repeated. One example is the design code for the hot salt tank in central receiver projects. The closest design basis is API Standard 650 Welded Steel Tanks for Oil Storage. However, the maximum design temperature in API 650 is 260 °C. As such, solar projects have typically adopted a hybrid Code approach, in which allowable material stresses are taken from ASME Section II Materials. Further, since the tanks experience daily changes in temperature and in (static) pressure, and since portions of the tank can operate at stresses beyond the elastic range, the low cycle fatigue life of the tank is conducted using the rules of Section VIII Division 2. However, in a recent study by NREL, the principal damage mechanism was identified as creep rather than fatigue. Further, design stresses permitted under Section VIII Division 2, corresponding to a fatigue life of 30 years, result in projected creep lifetimes of only 2 to 5 years. An alternate design approach, prescribed by the Owner, would be based on Code sections intended for high temperature service in the creep regime. A candidate is Section III Division 5. Granted, this is a nuclear code section, and it’s use would not likely be mandated by local jurisdictions. However, the effects of creep have been deemed to be of sufficient importance that one nuclear project developer, and one central receiver project developer, have stipulated in the tank design specification that the equipment be designed to the requirements of Section III Division 5.

14 SOLAR ENERGY↗

BETO 2021 Peer Review - Inverse Bioproduct Design Through Machine Learning and Molecular Simulation

This work aims to identify performance advantaged bioproducts (PABPs) through property prediction, which will guide experimental synthesis. The impact of this work will be faster market adoption of bioproducts with greater performance relative to incumbent products. We have identified >106 bioproduct candidates, but only some will have superior performance to create a market pull. High-throughput property prediction, enabled by machine learning, and elucidation of structure-function relationships, enabled by molecular simulation, provide a hypothesis driven approach for down selection of candidate biomolecules to pursue experimentally. To enable machine learning and molecular simulation for bioproduct discovery, automated structure generation and embedding must capture relevant features for prediction, databases must cover domains applicable to biobased products, and best practices for simulation of polymer systems must be developed. To address these challenges, we have established bioproduct relevant datasets, developed high-throughput polymer structure generation, and built end-to-end neural networks that have predicted 8 properties for >1.4 x 106 biopolymers. A molecular simulation pipeline for building, running, and analyzing polymers and polymer additives is being used to predict performance and develop design principles of biobased products. In collaboration with the PABP synthesis project, these computational tools are guiding synthesis and informing design of PABPs.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Near-wall model for compressible turbulent boundary layers based on an inverse velocity transformation

In this work, a near-wall model, which couples the inverse of a recently developed compressible velocity transformation (Griffin et al., Proc. Natl Acad. Sci., vol. 118, 2021, p. 34) and an algebraic temperature–velocity relation, is developed for high-speed turbulent boundary layers. As input, the model requires the mean flow state at one wall-normal height in the inner layer of the boundary layer and at the boundary-layer edge. As output, the model can predict mean temperature and velocity profiles across the entire inner layer, as well as the wall shear stress and heat flux. The model is tested in an a priori sense using a wide database of direct numerical simulation high-Mach-number turbulent channel flows, pipe flows and boundary layers (48 cases, with edge Mach numbers in the range 0.77–11, and semi-local friction Reynolds numbers in the range 170–5700). The present model is significantly more accurate than the classical ordinary differential equation (ODE) model for all cases tested. The model is deployed as a wall model for large-eddy simulations in channel flows with bulk Mach numbers in the range 0.7–4 and friction Reynolds numbers in the range 320–1800. When compared to the classical framework, in the a posteriori sense, the present method greatly improves the predicted heat flux, wall stress, and temperature and velocity profiles, especially in cases with strong heat transfer. In addition, the present model solves one ODE instead of two, and has a computational cost and implementation complexity similar to that of the commonly used ODE model.

42 ENGINEERING↗

Using cloud radar to investigate the effect of rainfall on migratory insect flight

The fate of migrating insects that encounter rainfall in flight is a critical consideration when modelling insect movement, but few field observations of this common phenomenon have ever been collected due to the logistical challenges of witnessing these encounters. Operational cloud radars have been deployed around the world by meteorological agencies to study precipitation physics, and as a byproduct, provide a rich database of insect observations that is freely available to researchers. Although considered unwanted ‘clutter’ by the meteorologists who collect the data, the analysis method presented here enables ecologists to delineate co-occurring signals from insects and raindrops. We present a method that uses image processing techniques on cloud radar velocity spectra to examine the fate of migrating insects when they encounter precipitation. By analysing velocity spectra, we can distinguish flying insects from falling rain and compare the relative density of insects in flight before, during and after the rainfall. We demonstrate the method on a case of insect migration in Oklahoma, USA. Using this method, we show the first reconstructed images of migrating insect layers in flight during rainfall. Our analysis shows that mild to moderate rainfall diminishes the number of insects aloft but does not cause full termination of migratory flight, as has previously been suggested. We hope this technique will spur further investigations of how changing weather conditions impact insect migration, and enable some of the first of such studies in regions of the world that are underrepresented in the literature.

54 ENVIRONMENTAL SCIENCES↗

User Guide for BLADE_LC_processor.py

BLADE_LC_processor.py is an optional script within the BLADE (Bolide Light-curve Analysis and Discrimination Explorer) open-source software package. It converts per-event light curve CSVs plus a metadata table into maps, plots, a per-sample trajectory file, and an aggregate summary. It anchors each trajectory at peak brightness, assumes constant speed and entry angle across the event, and propagates altitude and ground track relative to that anchor. The script converts the input azimuth internally to a travel bearing for the map and trajectory. Outputs include event folders with figures and a consolidated CSV containing start, peak, and end altitudes and all original metadata, sorted newest to oldest. For further background, users are referred to the foundational publication: Silber, E. A., Sawal, V. (2025), “BLADE: An Automated Framework for Classifying Light Curves from the Center for Near-Earth Object Studies Fireball Database,” The Astronomical Journal, doi: 10.3847/1538-3881/adeb55.

97 MATHEMATICS AND COMPUTING↗

Primary and Low-Strain Creep Models for 9Cr Tempered Martensitic Steels Including the Effects of Irradiation Softening and High-Helium Re-Hardening

Primary and low-strain creep represents a very important integrity challenge to large, complex structures, like fusion reactors. Here, we develop a predictive empirical primary creep model for 9Cr tempered martensitic steels (TMS), relating the applied stress (σ) to strain (ε), time (t) and temperature (T). The most accurate model is based on the applied σ normalized by the steel’s T-dependent ultimate tensile stress (σo), σ/σo(T). The model, fit to 17 heats of 9Cr TMS, yielded a σ root mean square error (RMSE) of ≈±11 MPa. Notably, the model also provides robust predictions for all the other TMS, when calibrated only by the fusion candidate Eurofer97 database. The model was extended to explore two possible effects of neutron irradiation, which produces both displacements per atom (dpa) and helium (He in atomic parts per million, appm) damage. These effects, which have not been previously considered, include: (a) softening, as a function of dpa, at T > ≈400–450 °C, in low-He fission environments (<1 He/dpa); and (b) subsequent re-hardening in high-He (≥10 He/dpa) fusion first-wall environments. The irradiation effect models predict (a) accelerated primary creep due to irradiation softening; and (b) fully arrested creep due to high-He re-hardening.

Alam, Md Ershadul (ORCID:0000000345968026)↗

State Policies and Programs for Community Solar

The purpose of this dataset is to summarize current community solar policies and related stipulations by state in the United States. The dataset is updated multiple times per year. The current version is the first file located below. Previous versions of the dataset published before August of 2024 can be found in the dataset below labeled “ARCHIVE_State Policies and Programs for Community Solar_Before 08.24.“ This list has been reviewed, but errors may exist, and the list may not be comprehensive. NLR invites input to update or add to the database. Please submit updates, additions, and corrections to Jenna Harmon (Jenna.Harmon@nlr.gov) and Sonja Berdahl (sonja.berdahl@nlr.gov).

14 SOLAR ENERGY↗

Do we have globally representative data to understand soil processes?

Understanding and modeling soils and soil organic matter (SOM) are central to a variety of human needs, from food production to ecosystem management. Soil data have been collected for over a century, but the global spatial and process representativeness of soil data remains unclear. We assessed the representativeness of currently available soil data that could be used to understand a variety of SOM processes. We used 16 open-source soil databases and data from over 281,000 unique locations globally, categorizing the databases into three main data types necessary to understand SOM processes: soil carbon stocks and fluxes, mechanistic drivers of these stocks and fluxes, and soil carbon gain or loss potential. We found that stock and driver data have extensive global coverage. However, data on soil carbon gain or loss potential, particularly data describing change in soils over time such as time series data, are severely limited in their global coverage. We conclude that while significant strides have been made in measuring soil carbon stocks and fluxes, and their drivers, we are limited in global data related to changes in soils over time. Our recommendations for soil data generators are to ensure precise metadata reporting and prioritizing sampling in underrepresented areas like tropical, arctic, mountainous, wetland and arid regions. We also encourage designing revisit schemes that explicitly support change detection and reporting multi-modal datasets that can aid in model development. Targeted measurement of low coverage soil data types and regions is necessary for a range of applications including current and future biogeochemical predictions, and their management and policy implications.

carbon fluxes↗

The Cost of Decarbonization and Energy Upgrade Retrofits for US Homes

Cost is a major barrier when upgrading homes to reduce carbon emissions required to meet DOE’s climate-related goals. This report summarizes a nationwide effort to gather home energy upgrade project cost data along with household energy performance data. The goal was to develop cost benchmarks and to guide future R&D efforts aimed at cost compression and scaling of the residential upgrade market. The cost data were compiled for both total project costs and costs of individual measures. The majority of energy savings were modeled, with some models using measured site data for calibration. The database was analyzed using clustering techniques to find common energy and CO2 reduction approaches. The individual measures were combined into archetypal solutions to determine least-cost approaches to maximizing energy and carbon savings. Several financial analyses were preformed to examine other cost metrics beyond first cost. Project data was obtained for 1,739 projects, from 15 states and 12 energy programs, with a total of 10,512 individual measures. The database includes a wide-array of projects, ranging from single-measure HVAC upgrades to net-zero energy whole home remodels. Projects were predominantly single-family detached dwellings with wood frame construction. Most of the data was obtained from energy programs because they had recorded the necessary information and were willing to share with this study. This sample of convenience can provide broad guidance and national cost benchmarks, but lacks sufficient detail to draw more disaggregated conclusions, such as geographical trends. The majority of data contributions were obtained without compensation from sources where the required data was already in some sort of structured format. We compensated sources to enter data from individual projects into a structured data format for about 500 projects, with an average cost of about $40 per project. The database was highly skewed to lower cost, lower impact projects due to the nature of the sample of convenience. Less than 10% of projects had savings greater than 50%. The cost data for individual measures in the database are being used in other DOE efforts on residential energy use/decarbonization. This data collection effort should continue in order to provide the best-informed guidance for DOE and industry R&D, as well as deployment efforts (including policy and program planning).

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Baseline Postirradiation Examination of the FUTURIX-FTA Experiments

Postirradiation Examination (PIE) results from the baseline examination of the FUTURIX-FTA irradiation experiment are presented in this report. The FUTURIX-FTA irradiation was designed to study the fuel performance of candidate transmutation fuels. The FUTURIX-FTA experiment was conducted in the true fast neutron spectrum conditions of the Phénix sodium fast test reactor in France. FUTURIX-FTA contained several compositions that were also irradiated as part of the AFC-1 test in cadmium filtered positions in the Idaho National Laboratory (INL) Advanced Test Reactor (ATR) that approximate the neutron spectrum of a fast reactor. This experiment was a joint collaboration between the Department of Energy (DOE) in the U.S. and the Commissariat á l'Energie Atomique et aux Energies Alternatives (CEA) in France. A joint agreement between DOE and CEA was established in 2004 to conduct an irradiation experiment of metallic and nitride fuels in the Phénix reactor at CEA. Both the FUTURIX-FTA tests and the AFC-1 tests were conducted for the DOE Advanced Fuels Campaign (AFC) that is part of Fuel Cycle Research & Development (FCRD) program. These programs seek to develop and demonstrate the technologies needed to transmute long-lived transuranic actinide isotopes contained in spent nuclear fuel via fast reactor technology. The long term goal of this work is to reduce the radiotoxicity of future high level waste repositories. Post-irradiation examination of irradiated fuels experiments provides data related to in reactor fuel performance and input into future fuel design choices. The compositions of the FUTURIX-FTA pins were designed to test if minor actinides could be incorporated into the fuel of a fast reactor without significantly changing fuel performance observed for previously well studied fuels. The fuel performance of metallic fuel in fast reactors has been well documented. Likewise the irradiation performance of nitride fuels in fast reactors has also been documented. However the existing database for nitride fuels is much smaller than the database for metal fuels.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

EvoNet: A phylogenomic and systems biology approach to identify genes underlying plant survival in marginal, low‐N soils

The DOE‐BER “EvoNet” project investigates the genetic and molecular basis of plant resilience in extreme environments. We do this by identifying key genes that enable “extreme survivor” species to thrive in the nitrogen-poor soils of Chile’s hyper-arid Atacama Desert. Our collections focus on 32 Atacama extremophile species, including seven grass species with potential biofuel applications. To identify genes-of-importance to survival we compared genomic and transcriptomic profiles of extremophile species that thrive in the Atacama to those of closely related “sister” species from nitrogen-rich arid and mesic regions of California. Deep RNA sequencing and de novo transcriptome assembly across these triplet species sets supported a phylogenomic framework for identifying positively selected genes associated with adaptive divergence. Our integrative analysis combined ecological and environmental data, metagenomics, evolutionary and systems biology, and metabolomics. This enabled us to create an unprecedented framework for systematically understanding how non-model plants have adapted to survive in extreme conditions. Our resulting database of positively selected ortholog groups in the extremophile plants offers promising targets for engineering crop and biofuel species with enhanced resilience to drought and extreme weather. Additionally, our newest dataset explores and exploits a complementary metabolomic approach. This new aspect provides innovative strategies to manipulate plant cell metabolism, further supporting efforts to improve agricultural productivity in the face of extreme climates. Importantly, our combined evolutionary- and metabolomic-based strategies focused on convergent patterns of adaptation, providing a genetic and metabolomic toolkit for improving crop and biofuel resilience across diverse plant species. Finally, our novel exploration of ecological and evolutionary dynamics delivered to the community a phylogenomic computational pipeline called “PhyloGeneious.” Our continued adaptations of this pipeline are publicly available to expedite evolutionary genomic research for future scientific discoveries. In total, our DOE-BER has provided genomic, metabolomic, and computational strategies to understand how extremophile plants provide evolutionary and physiological targets for improving agricultural and biofuel production.

59 BASIC BIOLOGICAL SCIENCES↗

Database of Nonaqueous Proton-Conducting Materials

This work presents the assembly of 48 papers, representing 74 different compounds and blends, into a machine-readable database of nonaqueous proton-conducting materials. SMILES was used to encode the chemical structures of the molecules, and we tabulated the reported proton conductivity, proton diffusion coefficient, and material composition for a total of 3152 data points. The data spans a broad range of temperatures ranging from -70 to 260 °C. To explore this landscape of nonaqueous proton conductors, DFT was used to calculate the proton affinity of 18 unique proton carriers. The results were then compared to the activation energy derived from fitting experimental data to the Arrhenius equation. It was found that while the widely recognized positive correlation between the activation energy and proton affinity may hold among closely related molecules, this correlation does not necessarily apply across a broader range of molecules. This work serves as an example of the potential analyses that can be conducted using literature data combined with emerging research tools in computation and data science to address specific materials design problems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Improvement of aerosol optical depth data for localized solar resource assessment

Solar irradiance, especially for direct normal irradiance (DNI), is sensitive to the atmospheric aerosols, which can strongly extinguish DNI over areas with elevated aerosol loadings. The National Solar Radiation Database (NSRDB), developed by the National Renewable Energy Laboratory (NREL), uses AOD from MERRA-2 reanalysis and is further downscaled from 0.5° to 2-km based on elevation. However, the elevation-based downscaling may not accurately represent AOD, especially over the areas with large AOD gradients. This study examined whether the 1-km MODIS MAIAC satellite-retrieved AOD product can better represent the AOD distribution and be used to improve solar irradiance assessment. We focused on areas with relatively high AOD over North America (California, and New York City, US, and Mexico City in Mexico, in particular). The evaluation of MAIAC AOD and MERRA-2 AOD against ground-truth AERONET AOD shows that MAIAC AOD exhibits smaller RMSE by about 0.05 and higher correlation coefficient by 0.1-0.6 than MERRA-2 AOD. In addition, MERRA-2 AOD shows larger negative bias. The simulated DNI using MAIAC AOD (DNIMAIAC) and using MERRA-2 AOD (DNINSRDB) were evaluated with DNI observations. The results show the performance of DNIMAIAC is better than that of DNINSRDB with smaller RMSE by 0.5-1.5%, smaller positive mean bias by 0.8-3.1% and comparable correlation for the 3 sites analyzed. Overall, 1-km MAIAC AOD shows higher accuracy than 2-km elevation-based MERRA-2 AOD, leading to better performance of the simulated DNI using MAIAC AOD. Therefore, 1-km MAIAC AOD can be used to improve the accuracy of solar resource assessment.

14 SOLAR ENERGY↗