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NASA NTRS1989

Global data bases on distribution, characteristics and methane emission of natural wetlands: Documentation of archived data tape

Global digital data bases on the distribution and environmental characteristics of natural wetlands, compiled by Matthews and Fung (1987), were archived for public use. These data bases were developed to evaluate the role of wetlands in the annual emission of methane from terrestrial sources. Five global 1 deg latitude by 1 deg longitude arrays are included on the archived tape. The arrays are: (1) wetland data source, (2) wetland type, (3) fractional inundation, (4) vegetation type, and (5) soil type. The first three data bases on wetland locations were published by Matthews and Fung (1987). The last two arrays contain ancillary information about these wetland locations: vegetation type is from the data of Matthews (1983) and soil type from the data of Zobler (1986). Users should consult original publications for complete discussion of the data bases. This short paper is designed only to document the tape, and briefly explain the data sets and their initial application to estimating the annual emission of methane from natural wetlands. Included is information about array characteristics such as dimensions, read formats, record lengths, blocksizes and value ranges, and descriptions and translation tables for the individual data bases.

Matthews, Elaine↗

DOE OSTI2023

Carbon Organisms Rhizosphere and Protection in Soil Environment model script and input data for soil moisture-respiration responses in tropical forests

Objectives: Climatic drying is predicted for many tropical forests, yet models remain poorly parameterized for tropical forests, hampering predictions of forest-climate feedbacks. We applied an integrated model–experiment approach, parameterizing an ecosystem model Carbon Organisms Rhizosphere and Protection in the Soil Environment (CORPSE) with tropical forest observational data, and comparing model predictions with a field drying manipulation. We hypothesized that drying would suppress soil CO2 fluxes (i.e., respiration) in already-drier tropical forests, but increases CO2 fluxes in wetter tropical forests by alleviating anaerobiosis. We measured soil CO2 fluxes, soil moisture, soil temperature, and forest floor biomass during wet-dry cycles (2015 – 2022) in four Panamanian forests that vary in rainfall and soil fertility. We used the field data to parameterize and run tests in the model.Results: Measured CO2 fluxes declined in the dry season and peaked in the early wet season ahead of peak soil moisture, resulting in a lower soil moisture optimum for respiration than previously modeled. We used this data to parameterize the model, which then predicted increased soil CO2 fluxes in wetter and fertile forests with drying, and decreased fluxes in drier, infertile forests. In contrast to model predictions, a chronic throughfall exclusion experiment in the forests initially suppressed soil CO2 fluxes across forests, with sustained suppression after four years in the wettest forest only (-28 ± 4% during the dry season), but elevated soil CO2 fluxes in a fertile forest after four years (+75 ± 28% during the late wet season), as predicted by the model. The unexpected negative drying effect in the wettest, most infertile forest could have resulted from reduced vertical flushing of nutrients into soils. Including hydro-nutrient interactions in ecosystem models could improve predictions of tropical forest-climate feedbacks (results presented in Cusack et al. 2023). Datasets included: Code files:CORPSE_array.py: Defines the equations of the CORPSE modelCORPSE_solvers: Functions for running the CORPSE model using either iterative or ordinary differential equation (ODE) solversrun_Panama_sims.py: Read in datasets and run the model simulations for this studyInput data:PanamaGradientEcosystemChem_BT_CPools_20152016CO2_DC_20190615.xlsx: Plot characteristics used in running model simulationsLiCor compiled surface flux only to 2020_03 DC_20200825.xlsx: Surface gas exchange fluxes used in model-data comparisonsPARCHED litterfall data for Ben Sulman LD 20200902.xlsx: Litterfall data used to drive model simulationsInitialization data:state_500y_20190823.csv: Initial state of model pools based on previous spinup runsOutput data:Outputs/prev_moisture_response.csv: Simulations of multiple sites using original model moisture response function.Outputs/updated_moisture_response.csv: Simulations of multiple sites using updated model moisture response function.Outputs/dry15_prev_moisture_response.csv: Simulations with soil moisture reduced by 15%, using original moisture response function.Outputs/dry15_updated_moisture_response.csv: Simulations with soil moisture reduced by 15%, using updated moisture response function.Outputs/dry30_prev_moisture_response.csv: Simulations with soil moisture reduced by 30%, using original moisture response function.Outputs/dry30_updated_moisture_response.csv: Simulations with soil moisture reduced by 30%, using updated moisture response function.Outputs/latestart_prev_moisture_response.csv: Simulations with extended dry season, using original moisture response function.Outputs/latestart_updated_moisture_response.csv: Simulations with extended dry season, using updated moisture response function.Outputs/[site name]_oneyear.csv: One-year simulation for each site in expanded site list using original moisture response function.Outputs/[site name]_oneyear_dried.csv: One-year simulation for each site in expanded site list using original moisture response function, with soil moisture reduced by 25%.Outputs/[site name]_oneyear_updated_moisture_response.csv: One-year simulation for each site in expanded site list using updated moisture response function.Outputs/[site name]_oneyear_updated_moisture_response_dried.csv: One-year simulation for each site in expanded site list using updated moisture response function, with soil moisture reduced by 25%.Field plot location data:There is also a .kml file that includes coordinates for all 32 plots included in the study of four forests (n = 4 throughfall reduction and n = 4 control plots per site).

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS2003

Black Hole Masses in Three Seyfert Galaxies

We analyze published reverberation mapping data for three Seyfert galaxies (NGC 3227, NGC 3516, and NGC 4593) to refine the mass estimate for the supermassive black hole in the center of each object. Treatment of the data in a manner more consistent with other large compilations of such masses allows us to more securely compare our results to wider samples of data, e.g., in the investigation of the M(sub bh-sigma*) relationship for active and quiescent galaxies.

Onken, C. A.↗

NASA NTRS2004

Automatic Generation of Algorithms for the Statistical Analysis of Planetary Nebulae Images

Analyzing data sets collected in experiments or by observations is a Core scientific activity. Typically, experimentd and observational data are &aught with uncertainty, and the analysis is based on a statistical model of the conjectured underlying processes, The large data volumes collected by modern instruments make computer support indispensible for this. Consequently, scientists spend significant amounts of their time with the development and refinement of the data analysis programs. AutoBayes [GF+02, FS03] is a fully automatic synthesis system for generating statistical data analysis programs. Externally, it looks like a compiler: it takes an abstract problem specification and translates it into executable code. Its input is a concise description of a data analysis problem in the form of a statistical model as shown in Figure 1; its output is optimized and fully documented C/C++ code which can be linked dynamically into the Matlab and Octave environments. Internally, however, it is quite different: AutoBayes derives a customized algorithm implementing the given model using a schema-based process, and then further refines and optimizes the algorithm into code. A schema is a parameterized code template with associated semantic constraints which define and restrict the template s applicability. The schema parameters are instantiated in a problem-specific way during synthesis as AutoBayes checks the constraints against the original model or, recursively, against emerging sub-problems. AutoBayes schema library contains problem decomposition operators (which are justified by theorems in a formal logic in the domain of Bayesian networks) as well as machine learning algorithms (e.g., EM, k-Means) and nu- meric optimization methods (e.g., Nelder-Mead simplex, conjugate gradient). AutoBayes augments this schema-based approach by symbolic computation to derive closed-form solutions whenever possible. This is a major advantage over other statistical data analysis systems which use numerical approximations even in cases where closed-form solutions exist. AutoBayes is implemented in Prolog and comprises approximately 75.000 lines of code. In this paper, we take one typical scientific data analysis problem-analyzing planetary nebulae images taken by the Hubble Space Telescope-and show how AutoBayes can be used to automate the implementation of the necessary anal- ysis programs. We initially follow the analysis described by Knuth and Hajian [KHO2] and use AutoBayes to derive code for the published models. We show the details of the code derivation process, including the symbolic computations and automatic integration of library procedures, and compare the results of the automatically generated and manually implemented code. We then go beyond the original analysis and use AutoBayes to derive code for a simple image segmentation procedure based on a mixture model which can be used to automate a manual preproceesing step. Finally, we combine the original approach with the simple segmentation which yields a more detailed analysis. This also demonstrates that AutoBayes makes it easy to combine different aspects of data analysis.

Fischer, Bernd↗

NASA NTRS1993

Outgassing Data for Selecting Spacecraft Materials

Outgassing data, derived from tests at 398 K (125 C) for 24 hours in vacuum as per ASTM E-595-90, have been compiled for numerous materials designed for spacecraft use. The data presented are the total mass loss (TML) and the collected volatile condensable materials (CVCM). The various materials are compiled by likely usage, and then in alphabetical order.

Campbell, William A.↗

DOE OSTI2024

CO2-Locate: A Dynamic Database and Tool for Accessing National Oil and Gas Well Data to Inform Carbon Storage Projects

The CO2-Locate Database is a growing compilation of publicly available wellbore resources that have been merged based on common attributes across data sources with an attribute schema developed to be consistent across disparate resources, reduce data gaps, and eliminate record redundancy. The first version of CO2-Locate has been published to Energy Data eXchange (EDX) and includes the integrated public wells dataset as well as additional geospatial summary layers of key wellbore characteristics to protect proprietary resources. Additionally, the CO2-Locate database has been deployed into a web application, enabling easy access, data filtering capabilities, and visualization of U.S. wellbore infrastructure by stakeholders to inform injection site selection and risk assessments.

Dyer, Alec S. [NETL Site Support Contractor, Natio↗

NASA NTRS2000

Cockpit weather information system

Weather information, periodically collected from throughout a global region, is periodically assimilated and compiled at a central source and sent via a high speed data link to a satellite communication service, such as COMSAT. That communication service converts the compiled weather information to GSDB format, and transmits the GSDB encoded information to an orbiting broadcast satellite, INMARSAT, transmitting the information at a data rate of no less than 10.5 kilobits per second. The INMARSAT satellite receives that data over its P-channel and rebroadcasts the GDSB encoded weather information, in the microwave L-band, throughout the global region at a rate of no less than 10.5 KB/S. The transmission is received aboard an aircraft by means of an onboard SATCOM receiver and the output is furnished to a weather information processor. A touch sensitive liquid crystal panel display allows the pilot to select the weather function by touching a predefined icon overlain on the display's surface and in response a color graphic display of the weather is displayed for the pilot.

Tu, Jeffrey Chen-Yu↗

NASA NTRS2001

Thermodynamic Data for Fifty Reference Elements

This report is a compilation of thermodynamic functions of 50 elements in their reference state. The functions are: C(sup 0, sub p), {H(T)-H(sup 0)(0)}, S(sup 0)(T), and - {G(sup 0)(T) - H(sup 0)(0)} for the elements Ag, Al, Ar, B, Ba, Be, Br2, C, Ca, Cd, Cl2, Co, Cr, Cs, Cu, F2, Fe, Ge, H2, He, Hg, I2, K, Kr, Li, Mg, Mn, Mo, N2, Na, Nb, Ne, Ni, O2, P, Pb, Rb, S, Si, Sn, Sr, Th, Th, Ti, U, V, W, Xe, Zn, and Zr. Deuterium D, and electron gas e(sup -) are also included. The data are tabulated as functions of temperature as well as given in the form of least-squares coefficients for two functional forms for C(sup 0, sub p) with integration constants for enthalpy and entropy. One functional form for C(sup 0, sub p) is a fourth-order polynomial and the other has two additional terms, one with T(sup -1) and the other with T(sup -2). The gases Ar, D2, e(sup -), H2, He, Kr, N2, Ne, O2, and Xe are tabulated for temperatures from 100 to 20 000 K. The remaining gases Cl2 and F2 are tabulated from 100 to 6000 K. The polynomial functional form for C(sup 0, sub p) for all these gases is split into two temperature intervals of 200 to 1000 K and 1000 to 6000 K. The second functional form for (sup 0, sub p) has an additional interval from 6000 to 20 000 K for the gases tabulated to 20 000 K. The fits are constrained so that the properties match at the common temperature endpoints. The temperature ranges for the condensed species vary with range of the data, phase changes, and shapes of the C(sup 0, sub p) curves.

McBride, Bonnie J.↗

NASA NTRS1993

Thermodynamic data for fifty reference elements

This report is a compilation of thermodynamic functions of 50 elements in their standard reference state. The functions are C(sub p)(sup 0), (H(sup 0)(T) - H(sup 0)(0)), S(sup 0)(T), and -(G(sup 0)(T) - H(sup 0)(O)) for the elements Ag, Al, Ar, B, Ba, Be, Br2, C, Ca, Cd, Cl2, Co, Cr, Cs, Cu, F2, Fe, Ge, H2, He, Hg, I2, K, Kr, Li, Mg, Mn, Mo, N2, Na, Nb, Ne, Ni, O2, P, Pb, Rb, S, Si, Sn, Sr, Ta, Th, Ti, U, V, W, Xe, Zn, and Zr. Deuterium D2 and electron gas e(sup -) are also included. The data are tabulated as functions of temperature as well as given in the form of least-squares coefficients for two functional forms for C(sub p)(sup 0) with integration constants for enthalpy and entropy. One functional form for C(sub p)(sup 0) is a fourth-order polynomial and the other has two additional terms, one with T(exp -1) and the other with T(exp -2). The gases Ar, D2, e(sup -), H2, He, Kr, N2, Ne, O2, and Xe are tabulated for temperatures from 100 to 20,000 K. The remaining gases Cl2 and F2 are tabulated from 100 to 6000 K and 1000 to 6000 K. The second functional form for C(sub p)(sup 0) has an additional interval from 6000 to 20,000 K for the gases tabulated to 20,000 K. The fits are constrained so that the match at the common temperature endpoints. The temperature ranges for the condensed species vary with range of the data, phase changes, and shapes of the C(sub p)(sup 0) curves.

Mcbride, Bonnie J.↗

DOE OSTI2020

XPlacer Machine Learning Guided Data Placement

XPlacer Machine Learning Guided Data Placement uses machine learning model to assist programmers to select the data placement advises for application running on HPC system with Nvidia GPUs. XPlacer Machine Learning Guided Data Placement consists three components: (1) 4 revised benchmarks from Rodinia benchmarks; (2) compiler script and execution script to generate variants, and collect training data for the machine learning model; (3) the scripts to post-process the collected data and generate the machine leaning model.

Liao, Chunhua↗

DOE OSTI2021

Constituent counting rule and ω photoproduction

Not Available

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2022

Decay spectroscopy of the blocked fission product 130 $\mathrm{I}$

We report numerous applications rely on the identification and quantification of fission products with the activation technique, where γ-rays emitted in the decay are used to estimate the initial activity of the radionuclide of interest. 130 I is a so-called blocked fission product, which can be produced only directly through fission, a property that makes it particularly attractive for nuclear forensics. A source of 130 I was produced using a (p,n) reaction on enriched 130 Te at the Brookhaven Tandem Van de Graaff and its decay was studied with Gammasphere at Argonne National Laboratory. Two new levels were identified, and over 25 transitions were added, removed or re-placed in the level scheme, with intensity measurements made down to I γ = 0.00066 per 100 decays. The uncertainty on the intensities of the strongest transitions, those that are commonly used to quantify the activity of the radionuclide, was improved by a factor of 2 compared to the previous best assessment and discrepancies in the literature values were resolved. A detailed angular correlation analysis further permitted the determination of a number of spin assignments for excited levels and mixing ratios for γ-ray transitions

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2023

National Critical Minerals Data Dashboard

The Critical Minerals (CM) Data Dashboard provides data-driven insights to help unlock the potential of conventional and unconventional CM resources in the United States. The dashboard focuses on 12 CM essential for producing zero-emission transportation and clean power technology. More information about these CM and potential resources is available in our CM Story Map. Dashboard data sets can be filtered geographically using the options provided along the top of the dashboard. Data sets can also be filtered by various attributes using the options in the expandable side panel on the left side of the screen. The data sets in this dashboard were compiled from multiple sources including the USGS, USEPA, OSMRE, and DHS., Users are encouraged to provide feedback/suggestions on the function and content of the dashboard, as well as any issues that may arise.

Conventional Resources↗

DOE OSTI2020

Sitewide Environmental Impact Statement Site 300 and Arroyo Mocho Lawrence Livermore National Laboratory Alameda and San Joaquin Counties, California (Mid-Term Report)

At the request of Lawrence Livermore National Security (LLNS), Nomad Ecology (Nomad) conducted sensitive botanical resource surveys, and vegetation mapping and classification of the 7,000-acre Lawrence Livermore National Laboratory (LLNL) Experimental Test Site (Site 300) and 17 acres surrounding the Arroyo Mocho pumping station and the access road to the pumping station (Arroyo Mocho). In addition to surveying for sensitive botanical resources, Nomad also compiled existing rare plant and vegetation data provided by LLNL from past monitoring and environmental impact evaluations. The results of these efforts will provide supporting information for a Site-wide Environmental Impact Statement (SWEIS). These surveys were conducted during the months of April – June, and August 2020. Rare plant surveys were scheduled for February and March 2020; however, February surveys were not initiated because the contract for this work was not finalized, and March surveys were cut short due to the timing of the Covid-19 shelter in place. February and March rare plant surveys are scheduled for 2021; therefore, the rare plant survey results in this report should be considered incomplete until the 2021 surveys are conducted. A total of 10 special status plant species were recorded within Site 300 and Arroyo Mocho. Of these 10, three were not previously recorded within the study areas, and include Hospital Canyon larkspur (Delphinium californicum subsp. interius), Jepson’s woolly sunflower (Eriophyllum jepsonii), and Michael’s rein orchid (Piperia michaelii), which all occur at Arroyo Mocho. Special status plant species known from these two sites total 23 rare plant occurrences (populations), which represent an estimated 50,929 rare plant individuals. This total of all special status plant species breaks down to one occurrence of a federally and/or state listed plant species (98 individuals), six occurrences of California Rare Plant Rank (CRPR) 1 & 2 species (49,010 individuals), and 16 occurrences of CRPR 3 & 4 species (1,821 individuals). A total of 35 vegetation communities were mapped at Site 300, of which 20 are considered Sensitive Natural Communities. A total of nine vegetation communities were mapped at Arroyo Mocho, of which two are considered Sensitive Natural Communities.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

Final Site 300 Sensitive Botanical Resource Report for the Sitewide Environmental Impact Statement, Lawrence Livermore National Laboratory, Alameda and San Joaquin Counties, California

At the request of Lawrence Livermore National Security (LLNS), Nomad Ecology (Nomad) conducted sensitive botanical resource surveys, and vegetation mapping and classification of the 7,000-acre Lawrence Livermore National Laboratory (LLNL) Experimental Test Site (Site 300). In addition to surveying for sensitive botanical resources, Nomad also compiled existing rare plant and vegetation data provided by LLNL from past monitoring and environmental impact evaluations. The results of these efforts will provide supporting information for a Site-wide Environmental Impact Statement (SWEIS). These surveys were conducted during the months of April-June, and August 2020, and February and March 2021. Rare plant surveys were originally scheduled for February and March 2020; however, February surveys were not initiated because the contract for this work was not finalized, and March surveys were cut short due to the timing of the Covid-19 shelter in place. Therefore, February and March rare plant surveys were conducted in 2021. A total of seven special status plant species were recorded within Site 300. Special status plant species known from the site total 26 rare plant occurrences (populations), which represent an estimated 14,077 rare plant individuals. This total of all special status plant species breaks down to one occurrence of a federally and/or state listed plant species (98 individuals), five occurrences of California Rare Plant Rank (CRPR) 1 & 2 species (11,553 individuals), and 20 occurrences of CRPR 3 & 4 species (2,426 individuals). A total of 35 vegetation communities were mapped at Site 300, of which 20 are considered Sensitive Natural Communities.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

Queued Up: 2025 Edition – Characteristics of Power Plants Seeking Transmission Interconnection As of the End of 2024 [Slides]

Electric transmission system operators (ISOs, RTOs, or utilities) require proposed power plants seeking to connect to the transmission grid to undergo a series of impact studies before they can be built. This process establishes what new transmission equipment or upgrades may be needed before a project can connect to the system and assigns the costs of that equipment. The lists of projects in this process are known as “interconnection queues”. In collaboration with interconnection.fyi, Berkeley Lab compiled, aggregated, and cleaned interconnection queue data from >50 transmission grid operators (7 ISO/RTOs and 49 non-ISO balancing areas), which collectively represent ~97% of currently installed U.S. electric generating capacity. The dataset includes requests submitted to queues through the end of 2024, and only includes requests seeking to connect to the transmission grid (not distribution-connected or behind-the-meter projects). The files below include both a PDF report and an Excel data file. The PDF report analyzes interconnection data and metrics through the end of 2024. The Excel data file includes (a) the full project-level interconnection queue dataset through 2024, (b) a codebook (data dictionary) describing each data field, and (c) 35 additional tabs featuring tables summarizing a range of interconnection metrics. Key highlights from the Queued Up: 2025 Edition (featuring data through 2024) include: • As of the end of 2024, there were ~10,300 projects actively seeking grid interconnection in the U.S., representing 1,400 GW of generation and approximately 890 GW of storage. • Historic withdrawal rates alongside relatively fewer new requests resulted in a 12% decrease in total active queue volume compared to the prior year. • Active natural gas capacity (136 GW, +72% year-over-year) increased in 2024, while solar (956 GW, -12%), storage (890 GW, -13%), and wind (271 GW, -26%) capacity decreased. • 408 GW of capacity already has a draft or executed interconnection agreement (IA) but has not yet reached commercial operations. • The time projects spend in queues before reaching COD is increasing. For the regions with available data, the median duration from IR to COD has doubled from <2 years for projects built in 2000-2007 to over 4 years for those built in 2018-2024. • Ultimately, most of this proposed capacity will not be built. Only 13% of capacity that submitted interconnection requests from 2000-2019 had reached commercial operations by the end of 2024; 77% of that capacity had been withdrawn and 10% was still active. • FERC Order 2023 and various other reforms are being implemented. These are important measures to reduce interconnection bottlenecks and enhance grid system reliability, but it is too early to measure and assess their full impact. • New additions for the 2025 edition include: (a) additional detail on data processing and gaps; (b) updates on interconnection reforms; (c) new analysis on interconnection agreements, and more.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2026

Generator Interconnection Costs to the Transmission System in non-ISO Balancing Authorities [Slides]

Electric transmission system operators—including Independent System Operators (ISOs), Regional Transmission Organizations (RTOs), and utilities—require proposed power plants to undergo a series of interconnection studies before connecting to the grid. These studies assess what transmission upgrades or new infrastructure may be necessary and assign the associated costs to the project. Lawrence Berkeley National Laboratory has compiled, aggregated, and cleaned interconnection cost data, originally for ISOs/RTOs, and now for five non-ISO Balancing Authorities: PacifiCorp, Bonneville Power Authority, Duke Energy Progress, Duke Energy Carolinas and Duke Energy Florida. Insufficient transparency in interconnection cost data may contribute to rapidly expanding interconnection queues, with active queue capacities tripling between 2020 and 2024 in the studied BAs. Most projects withdraw after receiving high interconnection cost estimates. Interconnection costs have increased since the early 2000s, with average costs for "complete" projects reaching $194/kW between 2018 and 2024. Active queue projects and withdrawn projects incur substantially higher costs, primarily due to rising network upgrade costs. Recent interconnection costs in non-ISO balancing authorities are higher than in ISO regions, potentially due to a greater willingness to pay among developers. Utility-scale solar, wind, and storage projects have interconnection costs that exceed those for natural gas. However, when focusing on projects that do not withdraw from the queue, the interconnection costs for these technologies are more similar to natural gas projects. Other key findings include: (1) Larger generation projects benefit from lower proportional interconnection costs, (2) capacity transmission service (NRIS) often requires additional network investments, and (3) projects with high network upgrade costs are often clustered geographically. The dataset includes results from 2,104 interconnection studies conducted between 2000 and 2024, covering projects that are operational, withdrawn, or still progressing through the study process. The Excel file contains (a) the complete project-level interconnection cost dataset, and (b) seven additional tabs summarizing cost metrics across dimensions such as time, market structure, cost category (point of interconnection vs. broader network upgrades), fuel type, service type (ERIS vs. NRIS), generator size, and geography.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2026

Queued Up: 2026 Edition, Characteristics of Power Plants Seeking Transmission Interconnection As of the End of 2025 [Slides]

24 POWER TRANSMISSION AND DISTRIBUTION↗