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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 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Publication and Impact of Preprints Included in the First 100 Editions of the CDC COVID-19 Science Update: Content Analysis

Preprints are publicly available manuscripts posted to various servers that have not been peer reviewed. Although preprints have existed since 1961, they have gained increased popularity during the COVID-19 pandemic due to the need for immediate, relevant information. The aim of this study is to evaluate the publication rate and impact of preprints included in the Centers for Disease Control and Prevention (CDC) COVID-19 Science Update and assess the performance of the COVID-19 Science Update team in selecting impactful preprints. All preprints in the first 100 editions (April 1, 2020, to July 30, 2021) of the Science Update were included in the study. Preprints that were not published were categorized as “unpublished preprints.” Preprints that were subsequently published exist in 2 versions (in a peer-reviewed journal and on the original preprint server), which were analyzed separately and referred to as “peer-reviewed preprint” and “original preprint,” respectively. Time to publish was the time interval between the date on which a preprint was first posted and the date on which it was first available as a peer-reviewed article. Impact was quantified by Altmetric Attention Score and citation count for all available manuscripts on August 6, 2021. Preprints were analyzed by publication status, publication rate, preprint server, and time to publication. Of the 275 preprints included in the CDC COVID-19 Science Update during the study period, most came from three servers: medRxiv (n=201, 73.1%), bioRxiv (n=41, 14.9%), and SSRN (n=25, 9.1%), with 8 (2.9%) coming from other sources. Additionally, 152 (55.3%) were eventually published. The median time to publish was 2.3 (IQR 1.4-3.7). When preprints posted in the last 2.3 months were excluded (to account for the time to publish), the publication rate was 67.8%. Moreover, 76 journals published at least one preprint from the CDC COVID-19 Science Update, and 18 journals published at least three. The median Altmetric Attention Score for unpublished preprints (n=123, 44.7%) was 146 (IQR 22-552) with a median citation count of 2 (IQR 0-8); for original preprints (n=152, 55.2%), these values were 212 (IQR 22-1164) and 14 (IQR 2-40), respectively; for peer-review preprints, these values were 265 (IQR 29-1896) and 19 (IQR 3-101), respectively. Prior studies of COVID-19 preprints found publication rates between 5.4% and 21.1%. Preprints included in the CDC COVID-19 Science Update were published at a higher rate than overall COVID-19 preprints, and those that were ultimately published were published within months and received higher attention scores than unpublished preprints. These findings indicate that the Science Update process for selecting preprints had a high fidelity in terms of their likelihood to be published and their impact. The incorporation of high-quality preprints into the CDC COVID-19 Science Update improves this activity’s capacity to inform meaningful public health decision-making.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Response Of Salt Intrusion In A Tidal Estuary To Regional Climatic Forcing (FVCOM Output for the baseline scenario)

Salinity distribution in a large tidal estuary is subject to estuarine adjustment under the influences of multiple physical drivers such as freshwater pulses and sea level rise, and is crucial to upstream water quality, aquaculture, and ecosystem functions of the estuary. To better understand the estuarine salinity response to climate change, the unstructured-grid Finite Volume Community Ocean Model was implemented to simulate the salt intrusion in the Delaware Bay Estuary. The model was first validated by multiple observational data sets and subsequently applied in an idealized setting to examine the response of salt front to freshwater pulses in high flow conditions, followed by a long-term drought condition supported by a multi-decadal streamflow drought analysis in the estuary. The model results showed that after the freshwater pulses the salt front location moved further upstream with sea level rise. Under the simulated long-term drought condition, the adjustment timescale of salt intrusion varies nonlinearly with sea level rise. With a significant increase in sea level rise, the adjustment timescale starts to decrease. This shift suggests a transition into a different regime where the estuary becomes more stratified, as indicated by an increasing bulk Simpson number with rising sea levels. These findings have been summarized into a journal manuscript. The data included in this information release request are FVCOM model output associated with the numerical simulations described in the journal manuscript.

Liu, Jinliang↗
DOE OSTI2024

E3SMv2 simulation output from sensitivity study on cloud formation

This dataset contains E3SMv2 simulation output files discussed in the manuscript approved for IR in PNNL-SA-206024. The dataset was used to examine the occurrences of ultra-low cloud droplet number concentrations in E3SMv2. Submitting the manuscript to a peer-reviewed journal will require making the model output publicly available. We plan to use DataHub for that.

Wan, Hui [PNNL] (ORCID:0000000152944116)↗
DOE OSTI2023

E3SMv1 simulation output from sensitivity study on aerosol process coupling

This dataset contains annual mean and 6-hourly output data from a set of E3SMv1 simulations that demonstrates the impact of numerical process coupling on the simulated dust life cycle. The simulations are documented and analyzed in the attached manuscript (pdf file). Publishing the manuscript in a peer-reviewed journal will require making the model output publicly available. We plan to use DataHub for that. The data files to be uploaded are currently saved on Compy under /compyfs/wanh895/scidac_share/cflx_2023/

Wan, Hui↗
DOE OSTI2023

Yield, chemistry, and TEA/LCA data for 84 switchgrass (Panicum virgatum L.) variants

Switchgrass yield, chemistry, technoeconomic assessment (TEA), and life cycle assessment (LCA) data referenced in the manuscript "Economics and Sustainability impacts of yield and composition variation in bioenergy crops: Panicum virgatum L.", Happs, et. al. (manuscript in revision at ACS Sustainable Chemistry & Engineering). These results are based on analysis of yield data generated from a set of switchgrass common garden experiments established by the Center for Bioenergy Innovation (CBI; https://cbi.ornl.gov/). These data include estimates of commercial-scale yields and characterization of biomass chemistry (fermentable carbohydrate fraction) for 84 different switchgrass variants from a genome-wide association study population, as well as estimates of minimum fuel selling price and various life-cycle footprint metrics for cellulosic ethanol produced from that switchgrass biomass.

switchgrass, biofuels↗
DOE OSTI2021

Dataset for Evaluation of Extreme Weather Impacts on Utility-Scale Photovoltaic Plant Performance in the United States

This dataset is a fusion of three data types (operations and maintenance tickets, weather data, and production data) that was used to support machine learning analysis and evaluation of drivers for low performance at photovoltaic (PV) sites during compound, extreme weather events. After being processed with machine learning, the data was used in the "Evaluation of Extreme Weather Impacts on Utility-scale Photovoltaic Plant Performance in the United States" manuscript. Additional details are captured in the associated manuscript.

AI↗
DOE OSTI2025

IBPSA Project 2 BOPTEST: An update on the test cases available in the framework for testing advanced control strategies in buildings

Project 2 develops software infrastructure, test cases, and extensions for the Building Optimization Testing Framework (BOPTEST) to address the expanding needs of building and urban energy system controls through open international collaboration. This paper provides an overview of the new test cases available as of BOPTEST version 0.7.1. Each test case is developed using open-source Modelica libraries and Spawn of EnergyPlus, enabling the creation of high-fidelity building models that incorporate envelope dynamics, Heating Ventilation and Air Conditioning (HVAC) systems, and explicit control representations. Currently, eight test cases are available, with five additional cases under development. These test cases cover a wide range of climates, building types, and HVAC systems. This paper compiles and summarizes test case descriptions, cites original manuscripts that developed them for a more detailed description, and reports baseline control performance metrics. Furthermore, two example applications are presented: one illustrating different levels of control, from supervisory to low-level, and another demonstrating how Model Predictive Control (MPC) solutions must be adapted from continuous to integer to control some building actuators.

Zanetti, Ettore↗
DOE OSTI2023

Corrigendum: The survivor strain: Isolation and characterization of Phormidium yuhuli AB48, a filamentous phototactic cyanobacterium with biotechnological potential

In the published article, there was an error. The introduction to this manuscript includes a typographical error which misstates the maximum salinity and pH previously observed in related cyanobacterial species. This error does not impact any analyses or conclusions reached in this manuscript.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

ACCRUE—An Integral Index for Measuring Experimental Relevance in Support of Neutronic Model Validation

A key challenge for the introduction of any design changes, e.g., advanced fuel concepts, first-of-a-kind nuclear reactor designs, etc., is the cost of the associated experiments, which are required by law to validate the use of computer models for the various stages, starting from conceptual design, to deployment, licensing, operation, and safety. To achieve that, a criterion is needed to decide on whether a given experiment, past or planned, is relevant to the application of interest. This allows the analyst to select the best experiments for the given application leading to the highest measures of confidence for the computer model predictions. The state-of-the-art methods rely on the concept of similarity or representativity, which is a linear Gaussian-based inner-product metric measuring the angle—as weighted by a prior model parameters covariance matrix—between two gradients, one representing the application and the other a single validation experiment. This manuscript emphasizes the concept of experimental relevance which extends the basic similarity index to account for the value accrued from past experiments and the associated experimental uncertainties, both currently missing from the extant similarity methods. Accounting for multiple experiments is key to the overall experimental cost reduction by prescreening for redundant information from multiple equally-relevant experiments as measured by the basic similarity index. Accounting for experimental uncertainties is also important as it allows one to select between two different experimental setups, thus providing for a quantitative basis for sensor selection and optimization. The proposed metric is denoted by ACCRUE, short for Accumulative Correlation Coefficient for Relevance of Uncertainties in Experimental validation. Using a number of criticality experiments for highly enriched fast metal systems and low enriched thermal compound systems with accident tolerant fuel concept, the manuscript will compare the performance of the ACCRUE and basic similarity indices for prioritizing the relevance of a group of experiments to the given application.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

An entropy-based debiasing approach to quantifying experimental coverage for novel applications of interest in the nuclear community

This manuscript proposes a novel information-theoretic approach to the quantification of experimental relevance, i.e., coverage, to achieve optimal data assimilation results for nuclear engineering applications. Specifically, this work posits the need for a new metric, called coverage (q C ) of an application’s quantity of interest, i.e., eigenvalue or power peaking for an advanced reactor concept, defined herein as the theoretically maximum achievable reduction in the quantity’s uncertainty given measurements from a pool of experiments in a manner that is independent of the data assimilation procedure employed. Currently, reduction in a quantity’s uncertainty is strongly biased by the underlying assumptions of the assimilation procedure to account for the under-determined nature of such problems and the similarity criterion employed to identify relevant experiments. To address this challenge, this work has developed a coverage metric, q C , based on mutual information, which establishes a new conceptual framework for assessing coverage, one that is independent of the model parameters and responses degree of variations in both the experimental and application domains, i.e., linear vs non-linear, and their prior uncertainty distributions, i.e., Gaussian vs. non-Gaussian. The q C is an entropic measure capable of addressing coverage for general nonlinear problems with non-Gaussian uncertainties and inclusive of the measurement uncertainties from multiple experiments. Numerical experiments from manufactured analytical problems as well as a set of benchmarks from the ICSBEP handbook are employed to demonstrate its theoretical and practical performance as compared to the c k -based experiment selection methodology, commonly employed in the neutronic community. The manuscript then employs other well-known adaptations to existing data assimilation methodologies for nonlinear and non-Gaussian problems capable of achieving the coverage posited by q C .

Bayesian data assimilation↗
DOE OSTI2022

Cooperative Research and Infectious Disease Surveillance: A 2021 Epilogue

As the world looks forward to turning a corner in the face of the COVID-19 pandemic, it becomes increasingly evident that international research cooperation and dialogue is necessary to end this global catastrophe. Last year, we initiated a research topic: “Infectious Disease Surveillance: Cooperative Research in Response to Recent Outbreaks, Including COVID-19,” which aimed at featuring manuscripts focused on the essential link between surveillance and cooperative research for emerging and endemic diseases, and highlighting scientific partnerships in countries under-represented in the scientific literature. Here we recognize the body of work published from our manuscript call that resulted in over 50 published papers. This current analysis describes articles and authors from a variety of funded and unfunded international sources. The work exemplifies successful research and publications which are frequently cooperative, and may serve as a basis to model further global scientific engagements.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

Public values failure associated with Hurricane Ian power outages

Power outages from extreme weather events can diminish community resilience, making it difficult for the areas impacted to bounce back after such events. For socially vulnerable populations, the frequency and duration of power outages can be even more severe. Governments have an obligation to protect public values, or those values that are most fundamental to society, which includes equitable resilience. Using Jørgensen and Bozeman's inventory of public values, this manuscript explores how power outages from extreme weather events create public values failures. More specifically, the manuscript evaluates intraorganizational aspects of public administration during power outages in Florida during Hurricane Ian in 2022. Framing power outages as a public values failure may motivate greater time and effort toward improving equitable access to more resilient power systems.

Entress, Rebecca M.↗
DOE OSTI2020

AATTENUATION—The Atmospheric Attenuation Model for CSP Tower Plants: A Look-Up Table for Operational Implementation

Attenuation of solar radiation between the receiver and the heliostat field in concentrated solar power (CSP) tower plants can reduce the overall system performance significantly. The attenuation varies strongly with time and the average attenuation at different sites might also vary strongly from each other. If no site specific attenuation data is available, the optimal plant design cannot be determined and rough estimations of the attenuation effect are required leading to high uncertainties of yield analysis calculations. The attenuation is caused mainly by water vapor content and aerosol particles in the lower atmospheric layer above ground. Although several on-site measurement systems have been developed during recent years, attenuation data sets are usually not available to be included during the plant project development. An Atmospheric Attenuation (AATTENUATION) model to derive the atmospheric transmittance between a heliostat and receiver on the basis of common direct normal irradiance (DNI), temperature, relative humidity, and barometric pressure measurements was developed and validated by the authors earlier. The model allows the accurate estimation of attenuation for sites with low attenuation and gives an estimation of the attenuation for less clear sites. However, the site-dependent coefficients of the AATTENUATION model had to be developed individually for each site of interest, which required time-consuming radiative transfer simulations, considering the exact location and altitude, as well as the pre-dominant aerosol type at the location. This strongly limited the application of the model despite its typically available input data. In this manuscript, a look-up table (LUT) is presented which enables the application of the AATTENUATION model at the site of interest without the necessity to perform the according complex radiative transfer calculations for each site individually. This enables the application of the AATTENUATION model for virtually all resource assessments for tower plants and in an operational mode in real time within plant monitoring systems around the world. The LUT also facilitates the generation of solar attenuation maps on the basis of long-term meteorological data sets which can be considered during resource assessment for CSP tower plant projects. The LUTs are provided together with this manuscript as supplementary files. The LUT for the AATTENUATION model was developed for a solar zenith angle (SZA) grid of 1°, an altitude grid of 100 m, 7 different standard aerosol types and the standard AFGL atmospheres for mid-latitudes and the tropics. The LUT was tested against the original version of the AATTENUATION model at 4 sites in Morocco and Spain, and it was found that the additional uncertainty introduced by the application of the LUT is negligible. With the information of latitude, longitude, altitude above mean sea level, DNI, relative humidity (RH), ambient temperature (Tair), and barometric pressure (bp), the attenuation can be now derived easily for each site of interest.

14 SOLAR ENERGY↗
DOE OSTI2024

Engineering Microgrids Amid the Evolving Electrical Distribution System

Non-wires alternatives and microgrid technologies are maturing and present great opportunities for electric utilities to increase the benefits they offer to their customers. They have the potential to decrease the cost of resolving traditional electrical system loading issues, contribute to carbon emissions reductions, and improve the electrical distribution system’s resilience to extreme weather events. The authors of this manuscript present a review of the research on microgrids and their practical applications. This is leveraged with the past work of the authors of this manuscript and other authors to develop specific objectives for microgrids, practical criteria for engineers to consider when deploying microgrids, stochastic methods to optimize microgrid designs, and black start requirements. This guidance is then used for the design of actual networked microgrids being deployed with adaptive boundaries.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Analysis of the Innovation Trend in Cell-Free Synthetic Biology

Cell-free synthetic biology is a maturing field that aims to assemble biomolecular reactions outside cells for compelling applications in drug discovery, metabolic engineering, biomanufacturing, diagnostics, and education. Cell-free systems have several key features. They circumvent mechanisms that have evolved to facilitate species survival, bypass limitations on molecular transport across the cell wall, enable high-yielding and rapid synthesis of proteins without creating recombinant cells, and provide high tolerance towards toxic substrates or products. Here, we analyze ~750 published patents and ~2000 peer-reviewed manuscripts in the field of cell-free systems. Three hallmarks emerged. First, we found that both patent filings and manuscript publications per year are significantly increasing (five-fold and 1.5-fold over the last decade, respectively). Second, we observed that the innovation landscape has changed. Patent applications were dominated by Japan in the early 2000s before shifting to China and the USA in recent years. Finally, we discovered an increasing prevalence of biotechnology companies using cell-free systems. Our analysis has broad implications on the future development of cell-free synthetic biology for commercial and industrial applications.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Hydroxyl Conducting Hydrogels Enable Low-Maintenance Commercially Sized Rechargeable Zn–MnO2 Batteries for Use in Solar Microgrids

Zinc (Zn)–manganese dioxide (MnO2) rechargeable batteries have attracted research interest because of high specific theoretical capacity as well as being environmentally friendly, intrinsically safe and low-cost. Liquid electrolytes, such as potassium hydroxide, are historically used in these batteries; however, many failure mechanisms of the Zn–MnO2 battery chemistry result from the use of liquid electrolytes, including the formation of electrochemically inert phases such as hetaerolite (ZnMn2O4) and the promotion of shape change of the Zn electrode. This manuscript reports on the fundamental and commercial results of gel electrolytes for use in rechargeable Zn–MnO2 batteries as an alternative to liquid electrolytes. The manuscript also reports on novel properties of the gelled electrolyte such as limiting the overdischarge of Zn anodes, which is a problem in liquid electrolyte, and finally its use in solar microgrid applications, which is a first in academic literature. Potentiostatic and galvanostatic tests with the optimized gel electrolyte showed higher capacity retention compared to the tests with the liquid electrolyte, suggesting that gel electrolyte helps reduce Mn3+ dissolution and zincate ion migration from the Zn anode, improving reversibility. Cycling tests for commercially sized prismatic cells showed the gel electrolyte had exceptional cycle life, showing 100% capacity retention for >700 cycles at 9.5 Ah and for >300 cycles at 19 Ah, while the 19 Ah prismatic cell with a liquid electrolyte showed discharge capacity degradation at 100th cycle. We also performed overdischarge protection tests, in which a commercialized prismatic cell with the gel electrolyte was discharged to 0 V and achieved stable discharge capacities, while the liquid electrolyte cell showed discharge capacity fade in the first few cycles. Finally, the gel electrolyte batteries were tested under IEC solar off-grid protocol. It was noted that the gelled Zn–MnO2 batteries outperformed the Pb–acid batteries. Additionally, a designed system nameplated at 2 kWh with a 12 V system with 72 prismatic cells was tested with the same protocol, and it has entered its third year of cycling. This suggests that Zn–MnO2 rechargeable batteries with the gel electrolyte will be an ideal candidate for solar microgrid systems and grid storage in general.

25 ENERGY STORAGE↗
DOE OSTI2022

The Local Topological Free Energy of the SARS-CoV-2 Spike Protein

The novel coronavirus SARS-CoV-2 infects human cells using a mechanism that involves binding and structural rearrangement of its Spike protein. Understanding protein rearrangement and identifying specific amino acids where mutations affect protein rearrangement has attracted much attention for drug development. In this manuscript, we use a mathematical method to characterize the local topology/geometry of the SARS-CoV-2 Spike protein backbone. Our results show that local conformational changes in the FP, HR1, and CH domains are associated with global conformational changes in the RBD domain. The SARS-CoV-2 variants analyzed in this manuscript (alpha, beta, gamma, delta Mink, G614, N501) show differences in the local conformations of the FP, HR1, and CH domains as well. Finally, most mutations of concern are either in or in the vicinity of high local topological free energy conformations, suggesting that high local topological free energy conformations could be targets for mutations with significant impact of protein function. Namely, the residues 484, 570, 614, 796, and 969, which are present in variants of concern and are targeted as important in protein function, are predicted as such from our model.

60 APPLIED LIFE SCIENCES↗