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At least 487 records · Page 27

Recommended Representative Isotopic Compositions for Potential VTR Pu Supplies

This document recommends isotopic compositions to represent selected Pu supplies that might be made available for use in VTR driver fuel. These compositions are intended to be conservative representations suitable for determination of environmental impacts associated with use of the selected Pu supplies, but not upper bounds of all possible compositions. The selected Pu supplies under consideration are themselves representations of a more complicated set of possibilities, defined in a manner to allow efficient but conservative analysis of impacts. The source definitions to be considered are as follows: 1) Foreign sources of reactor-grade plutonium. This material would be provided as polished material in an oxide form and is assumed to be transported from Europe (France or England); 2) Domestic, non-weapon sources of plutonium such as unused FFTF fuel, Hanford metal (stored at SRS), and various oxides; 3) Domestic sources of weapons-grade plutonium, including metal from dismantled pits and otherwise excess to stockpile needs.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Recent Shuttle Post Flight MMOD Inspection Highlights

Four significant micro-meteoroid orbital debris (MMOD) impact events on the shuttle are documented: two perforations of the payload bay door radiator sandwich panel along with craters in a crew module window and a wing leading edge reinforced carbon-carbon panel. Results from Scanning Electron Microscope/Energy-Dispersive x-ray Spectroscopy (SEM/EDS) analysis of impact residue are provided in an attempt to identify the source of each impact. Particle sizes that could produce the observed damage are discussed, along with hypervelocity impact testing on representative samples conducted to simulate the impact event.

Hyde, James L.↗

Deformation and damage of composite laminates under impact loading

An analysis was conducted of quasi-isotropic graphite/epoxy plates 8-ply and 16-ply thick clamped around a circumference, subjected to central impact loading. The imparted energy, load history, and transient strains at various locations through the thickness were obtained. The dynamic load history for the thin laminate demonstrates a higher peak load of shorter duration than for the thick laminate, whereas the load record for the thick laminate shows more pronounced fluctuations than for the thin laminate, related to more extensive damage development and flexural oscillations in the former.

Daniel, I. M.↗

Dynamic Life-Cycle Analysis of Fast Pyrolysis Biorefineries: Impacts of Feedstock Moisture Content and Particle Size

The commercialization of biorefineries has been met with significant obstacles due to the technical difficulties of handling solid biomass feedstocks, which are highly variable in physical properties and chemical compositions. An understanding of the principles of unit operations along the supply chain is key to the success of the biofuel industry. This study applies a dynamic life-cycle analysis (DLCA) methodology by developing quantitative relationships between the inputs and outputs for each unit operation based on scientific understanding of the causal effects. Using the DLCA, we assessed system sustainability of drop-in fuel production from fast pyrolysis of pine residues followed by hydro-processing. Life-cycle greenhouse gas (GHG) emissions were calculated for 4641 runs involving two key feedstock parameters: moisture content after field drying and particle size of the feed to pyrolyzer. Moisture contents varied between 25% and 35%, while particle sizes varied between 0.5 and 5 mm in these runs. The life-cycle GHG emissions of these cases vary from 22 to 40 g/MJ. Close examination of each unit operation's contribution to the total GHG emissions reveals that low moisture content after field drying produces savings in energy consumption during feedstock transportation and on-site drying. However, although small particle size leads to overall higher fuel yield, it also requires a significant amount of energy for feedstock size reduction and fuel production. The energy penalty outweighs the benefit of increased fuel yields, especially when fine particles (<1 mm) are used for pyrolysis; thus, small particle size leads to increased GHG emissions overall. The results highlight the trade-offs between the energy demand for preprocessing and the conversion yields, which can be addressed with DLCA.

09 BIOMASS FUELS↗

A Systematic Approach to Isolating the Causes and Impacts of Climate Model Bias Employing Analysis Increments

One of the most promising approaches to isolating the causes and understanding the impacts of climate model formulation errors is through the utilization of information contained in short-term forecast errors. The underlying assumption being that by capturing the errors at the very early stages of growth (before nonlinearities develop), we should be able to associate those errors with specific deficiencies in the model's formulation of the relevant physical processes. Here, we provide an example of utilizing the long-term mean of the 6-hourly analysis increments (first guess forecast minus analysis) produced by MERRA-2 to correct the NASA/GEOS AGCM over well-defined regions, thereby allowing us to quantify how the reduced tendency errors in these regions manifest themselves both locally and remotely through large-scale teleconnections to reduce the model's climatological biases. We extend previous work (focused on boreal summer) to address the full annual cycle of model bias. A key result is the large seasonality of the errors over the Tibet region and their impacts on the Northern Hemisphere jet biases, and related precipitation and temperature biases over North American. Attempts to correct the phase and amplitude errors of the climatological boreal winter ridge over western North America (a likely key requirement for improving winter climate forecasts over North America) reveal a surprising complexity in the sources of the errors in what is otherwise manifest as a rather simple PNA-like bias structure.

Schubert, S.↗

Understanding the impacts of inorganic species in woody biomass for preprocessing and pyrolysis–A review

Woody biomass represents an abundant resource for sustainable biofuels, biochemicals, and bioproducts. Technologies for converting woody biomass have been established for decades, and research consistently highlights the critical role of inorganic species and ash plays in feedstock handling and conversion processes, including equipment plugging, corrosion, and catalyst deactivation. A thorough understanding of the variability, transport behavior, and downstream impact of inorganic species in woody biomass is essential for defining feedstock quality specifications and developing effective management strategies for conversion processes. This review compiles critical information in five main sections: 1) inorganic species concentration in woody biomass, based on anatomical fractions and their sources of variability; 2) technique features for quantifying inorganic elemental chemical analysis; 3) impacts of inorganic species on biomass preprocessing; 4) impacts of inorganic species on pyrolysis, and 5) mitigation strategies. Additionally, this review explores future challenges and opportunities in addressing the impacts of inorganic species on biomass quality. These insights aim to support the sustainable development of the biomass-to-bioenergy pipeline and ensure high-quality lignocellulosic feedstocks for efficient downstream conversions. The findings offer valuable guidance to policy makers, industry stakeholders, and researchers in developing effective strategies for managing inorganic species in woody biomass and fostering the sustainable processes for lignocellulosic biorefineries.

09 BIOMASS FUELS↗

Comparative Small-Signal Stability Analysis of Grid-Forming and Grid-Following Inverters in Low-Inertia Power Systems: Preprint

Inverter-based resources (IBRs) are gradually replacing conventional fossil energy in modern power systems, which could make the system susceptible due to insufficient inertia, especially when moving towards a 100% inverter-based power grid. Grid-forming (GFM) and grid-following (GFL) controls are two common inverter control algorithms. However, the corresponding stability issues along with a comparative study on low-inertia power systems should still be investigated. This paper focuses on small-signal stability and conducts a comprehensive analysis of GFM and GFL controls, with emphases on the interactions between synchronous generators and IBRs. The detailed modeling of GFM and GFL inverters, and synchronous generators (SGs) are established. The coupling mechanism of IBRs and SGs is then conducted through participation factor analysis. The impacts of critical parameters on system stability are finally identified. The theoretical analyses are validated through time-domain simulation in MATLAB/Simulink.

grid-following↗

Consequential Analysis of the Greenhouse Gas Emissions Impacts of Actions That Influence the Electric Grid: The Theory and Practice of Using Marginal Emissions Rates

This paper discusses consequential greenhouse gas emissions analysis for actions that influence the electric grid that is, the analytical approach of estimating how such actions change greenhouse gas emissions, relative to what they otherwise would have been without the action. Although the paper starts with general considerations, it ultimately focuses on consequential analysis with marginal emissions rates as an option likely more scalable than others.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Theorizing Land Cover and Land Use Change: The Peasant Economy of Colonization in the Amazon Basin

This paper addresses deforestation processes in the Amazon basin. It deploys a methodology combining remote sensing and survey-based fieldwork to examine, with regression analysis, the impact household structure and economic circumstances on deforestation decisions made by colonist farmers in the forest frontiers of Brazil. Unlike most previous regression-based studies, the methodology implemented analyzes behavior at the level of the individual property. The regressions correct for endogenous relationships between key variables, and spatial autocorrelation, as necessary. Variables used in the analysis are specified, in part, by a theoretical development integrating the Chayanovian concept of the peasant household with spatial considerations stemming from von Thuenen. The results from the empirical model indicate that demographic characteristics of households, as well as market factors, affect deforestation in the Amazon. Thus, statistical results from studies that do not include household-scale information may be subject to error. From a policy perspective, the results suggest that environmental policies in the Amazon based on market incentives to small farmers may not be as effective as hoped, given the importance of household factors in catalyzing the demand for land. The paper concludes by noting that household decisions regarding land use and deforestation are not independent of broader social circumstances, and that a full understanding of Amazonian deforestation will require insight into why poor families find it necessary to settle the frontier in the first place.

Caldas, Marcellus↗

Choice of 16S ribosomal RNA primers affects the microbiome analysis in chicken ceca

We evaluated the effect of applying different sets of 16S rRNA primers on bacterial composition, diversity, and predicted function in chicken ceca. Cecal contents from Ross 708 birds at 1, 3, and 5 weeks of age were collected for DNA isolation. Eight different primer pairs targeting different variable regions of the 16S rRNA gene were employed. DNA sequences were analyzed using open-source platform QIIME2 and the Greengenes database. PICRUSt2 was used to determine the predicted function of bacterial communities. Changes in bacterial relative abundance due to 16S primers were determined by GLMs. The average PCR amplicon size ranged from 315 bp (V3) to 769 bp (V4–V6). Alpha- and beta-diversity, taxonomic composition, and predicted functions were significantly affected by the primer choice. Beta diversity analysis based on Unweighted UniFrac distance matrix showed separation of microbiota with four different clusters of bacterial communities. Based on the alpha- and beta-diversity and taxonomic composition, variable regions V1–V3(1) and (2), and V3–V4 and V3–V5 were in most consensus. Our data strongly suggest that selection of particular sets of the 16S rRNA primers can impact microbiota analysis and interpretation of results in chicken as was shown previously for humans and other animal species.

59 BASIC BIOLOGICAL SCIENCES↗

Modeling Variable Renewable Energy and Storage in the Power Sector

The emergence of variable renewable energy and battery storage technologies have fundamentally transformed the electric power sector and generated demand for analysis to understand their roles in future energy systems. Although unique characteristics of these resources are well-recognized and require more sophisticated methodologies to capture effectively, guidance is limited on best practices and research gaps. This paper selectively reviews recent literature and draws upon our collective modeling experience to offer recommendations to analysts and consumers of model outputs on approaches for modeling variable renewable energy and storage in long-term electric sector models. We focus on regional- and national-scale models with technological, temporal, and spatial detail given their prevalence in planning and policy analysis, though insights are applicable in other settings. The review highlights how the research frontier has advanced in representing renewables and energy storage over the past decade; however, given the many considerations involved with appropriately capturing salient economic and operational characteristics of renewables, there is a gap between commonly used models and state-of-the-art methods. Model simplifications can materially impact policy analysis associated with power sector decarbonization and high renewables deployment, and improving model representations of variable renewables can enhance insights for policymakers and other stakeholders. This review can point the way for improved methods for established models and designs for emerging ones.

energy and environmental policy↗

Data and code for Daily and Multi-Day Extreme Rainfall Analysis Under Future Climates Using Stochastic Storm Transposition and NEX-GDDP-CMIP6 Over CONUS

This data package provides inputs, codes, and outputs for a comprehensive analysis of projected changes in extreme precipitation across 10 regions of the continental United States, using 34 downscaled Earth System Models (ESMs) from the NASA Earth Exchange Global Daily Downscaled Projections, Coupled Model Intercomparison Project Phase 6 (NEX-GDDP-CMIP6) dataset. These models are part of the Coupled Model Intercomparison Project Phase 6 (CMIP6), a coordinated climate modeling framework widely used to assess climate change impacts. The analysis applies a stochastic storm transposition method to quantify changes in extreme rainfall under two Shared Socioeconomic Pathway (SSP) climate scenarios—SSP2-4.5 (moderate emissions) and SSP5-8.5 (high emissions)—compared to historical conditions (1995–2014 vs. 2081–2100). The dataset includes rainfall depth estimates for extreme events with return periods from 2 to 500 years across multiple storm durations (1, 3, and 5 days) for each of the 10 U.S. regions. Weighted ensemble statistics are derived from individual ESM performance against historical precipitation patterns, enabling robust uncertainty quantification through both sign-based and permutation-test-based model agreement assessments. Key analyses address: (1) relative changes in extreme precipitation for each climate scenario, (2) differences between SSP scenarios (SSP5-8.5 vs. SSP2-4.5), (3) contrasts between rare and frequent events, and (4) variations between multi-day and daily storm durations. The workflow produces ensemble statistics—median, 5th, 25th, 75th, and 95th percentiles—along with model agreement metrics that identify regions and event types with robust climate change signals. The dataset includes: processed rainfall depth outputs (netCDF format) from the RainyDay Python package, ESM weights from historical performance evaluation using DayMet observations, ensemble statistics across all storm dimensions, and figures summarizing key findings.

54 ENVIRONMENTAL SCIENCES↗

How Flood Hazards in a Warming Climate Could Be Amplified by Changes in Spatiotemporal Patterns and Mechanisms of Water Available for Runoff

Prior research on climate change impacts on flooding has primarily focused on changes in extreme rainfall magnitudes, often neglecting snow processes and spatiotemporal storm patterns, such as hyetograph shapes and areal reduction factors (ARFs). This study examines projected changes in extreme water available for runoff (W) events in two snow-dominated basins in the western United States: the Yakima River Basin (YRB) in Washington State and the Walker River Basin (WRB) spanning the California-Nevada border. We analyze changes in W magnitudes, mechanisms, hyetograph shapes, and ARFs, and study their compounded impacts on flood hazard. Our findings suggest increased extreme W magnitudes across a large portion of the basins, with steeper or flatter hyetographs, and higher ARF values under the future climate. These changes are driven by a shift from seasonal snowmelt to more rain-on-snow events at higher elevations and by increased rainfall at lower elevations. We then use a single event-based rainfall-runoff model to estimate flood hazard changes based on extreme W magnitudes, hyetograph shapes, ARFs, and their compounded impacts. Our analysis reveals that focusing solely on the magnitude of changes in extreme W can significantly underestimate future flood hazards and uncertainties. Ignoring future changes in spatiotemporal patterns can underestimate future flood hazards by 63% and underestimate the uncertainty in future flood events by 18% in the WRB. These results underscore the necessity of incorporating spatiotemporal dynamics into future flood hazard assessments to provide a more accurate evaluation of potential impacts.

54 ENVIRONMENTAL SCIENCES↗

The role of analysis error in the convergence of reanalysis production streams in MERRA-2

Due to production time constraints, most reanalyses are produced in multiple parallel streams instead of a single continuous one. These streams cover separate segments of the reanalysis time period with short overlaps to allow reconstruction of the official record. A fundamental assumption justifying this approach is that the streams will be assimilating the same observations during the periods where they overlap, and so will eventually converge to a similar atmospheric state, making discontinuities at stream junctions negligible. This assumption is revisited in this work by examining the impact of analysis error on the differences between MERRA-2 overlapping streams in three historical periods. Comparison results are shown in terms of standard deviations of stream differences as well as the spectral decomposition of the variance of their differences. Residual differences were found at the end of each year of overlap, with larger values observed in the earlier segments of the presatellite era. By drawing parallels with analysis error statistics estimated from the GMAO OSSE system, these differences are shown to reflect the varying constraint of data with the varying observing network, and to further carry the imprint of errors that the data assimilation process is not able to mitigate. As such, they are unlikely to be reduced by longer spinup periods. The ability of data assimilation to ensure continuity in the parallel streams is put into question when the observing system coverage is inadequate or simply when the data assimilation system as a whole is suboptimal.

Amal El Akkraoui↗

The impact of the FGGE observing systems in the Southern Hemisphere

Results of studies carried out at the Australian Numerical Meteorology Research Centre (ANMRC) and the Australian Bureau of Meteorology to assess the impact of FGGE on numerical weather prediction in the Southern Hemisphere are presented. These studies inducate that the FGGE data base had a significant impact on analysis and numerical weather prediction. From the operational standpoint, the most outstanding contribution was made by the drifting buoy data that enabled reliable routine surface pressure analyses to be made over the entire hemisphere. The results of a limited study using the MNMRC data assimilation scheme show that the quality of prediction to 48 hours hinges crucially on both the buoy pressure data and satellite temperature soundings with single level satellite winds having a small impact.

Puri, K.↗

Analysis of Space Shuttle Ground Support System Fault Detection, Isolation, and Recovery Processes and Resources

As part of the FDIR (Fault Detection, Isolation, and Recovery) Project for the Constellation Program, a task was designed within the context of the Constellation Program FDIR project called the Legacy Benchmarking Task to document as accurately as possible the FDIR processes and resources that were used by the Space Shuttle ground support equipment (GSE) during the Shuttle flight program. These results served as a comparison with results obtained from the new FDIR capability. The task team assessed Shuttle and EELV (Evolved Expendable Launch Vehicle) historical data for GSE-related launch delays to identify expected benefits and impact. This analysis included a study of complex fault isolation situations that required a lengthy troubleshooting process. Specifically, four elements of that system were considered: LH2 (liquid hydrogen), LO2 (liquid oxygen), hydraulic test, and ground special power.

Gross, Anthony R.↗

Homogenous Voltage-Matched Strings Using Three-Terminal Tandem Solar Cells: Fundamentals and End Losses

Strings constructed from three-terminal tandem (3TT) solar cells offer the performance benefits of voltage-matching (which reduces sensitivity to spectral variation), but without the subcell voltage isolation required by four-terminal cells. However, the circuitry for a 3TT string can become complex, making circuit analysis more challenging. Here, we illustrate the essential features of “homogenous” voltage-matched (VM) 3TT strings, for which all 3TT cells in the string are nominally identical (with the same design/doping sequence, such that they can be fabricated on the same manufacturing line). Several representative VM string configurations are explicitly considered, and used to describe the general construction of string I(V) curves. End losses intrinsic to these strings are discussed in detail, along with mitigation strategies to minimize their impact. Our analysis agrees with experimental results for eight-cell strings constructed from GaInP/GaAs 3TT devices.

14 SOLAR ENERGY↗

Dynamic analysis of a pre-and-post ice impacted blade

The dynamic characteristics of an engine blade are evaluated under pre-and-post ice impact conditions using the NASA in-house computer code BLASIM. The ice impacts the leading edge of the blade causing severe local damage. The local structural response of the blade due to the ice impact is predicted via a transient response analysis by modeling only a local patch around the impact region. After ice impact, the global geometry of the blade is updated using deformations of the local patch and a free vibration analysis is performed. The effects of ice impact location, size and ice velocity on the blade mode shapes and natural frequencies are investigated. The results indicate that basic nature of the mode shapes remains unchanged after impact and that the maximum variation in natural frequencies occurs for the twisting mode of the blade.

Abumeri, G. H.↗