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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 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
NASA NTRS1999

A Direct Comparison Between EUV Coronal Flux and Helium Resonance Line Photon Flux from SOHO/CDS Data

In the wealth of EUV spectroscopic and imaging data gathered by the SOHO and TRACE missions, a prominent role is played by the helium resonance emission. For example, He I lines are among the most intense features in CDS/NIS spectra, while the EIT 304 waveband (dominated by He II emission) is routinely employed to map the structure of the solar chromosphere and transition region. However, no 'standard' model has emerged so far that is able to interpret observed He spectra/images to a satisfactory degree of self-consistency. Recent research on the problem of the formation of the solar helium spectrum tends to rule out a dominant role of coronal radiation in exciting He resonance lines. However, while evidence for this result is strong, it is based on indirect tests. Here we present a preliminary assessment of this issue based on a more direct approach, which involves a measure with CDS/GIS of the photoionizing EUV radiation. This measure can be directly compared with the observed flux in the main He I and He II resonance lines observed with CDS/NIS2.

Andretta, V.↗
DOE OSTI2019

Radiative Flux Analysis (RADFLUXANAL) Value-Added Product: Retrieval of Clear-Sky Broadband Radiative Fluxes and Other Derived Values

The Radiative Flux Analysis (RADFLUX) is a technique for using surface broadband radiation measurements for detecting periods of clear (i.e., cloudless) skies, and using the detected clear-sky data to fit functions that are then used to produce continuous clear-sky estimates. The clear-sky estimates and measurements are then used in various ways to infer cloud macrophysical properties. This value-added product (VAP) is based on methodologies developed by Dr. Charles N. Long as referenced in the papers below. It is an updated version of an earlier value-added data product called the Shortwave (SW) Clear-Sky Detection and Fitting Algorithm (SWCLRID). Two major improvements were made over the SWCLRID data product: 1) input data were first run through the Data Quality Assessment for Atmospheric Radiation Measurement (ARM) Radiation Data (QCRAD) VAP to better screen for data quality, and 2) additional processing was implemented to also include longwave (LW) clear sky estimates and derived values.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Flux REaction TArget Prioritization (Flux RETAP) v1

Metabolic engineering is evolving rapidly as a result of new advances in synthetic biology and automation, as well as the irruption of machine learning (ML). ML has been shown to provide the predictive power synthetic biology lacked and needed, and to be able to effectively guide the metabolic engineering process. However, current technical limitations prevent the independent application of ML approaches to metabolic engineering without the use of previous biological knowledge in the form of a prioritized list of desirable engineering targets. Here, we present FluxRETAP, a simple and computationally inexpensive method that leverages the prior mechanistic knowledge embedded in genome-scale metabolic models (GSMs) for suggesting targets for genetic overexpression, downregulation or deletion, with the final goal of increasing metabolite production. FluxRETAP captured 100% of reaction targets experimentally verified to improve Escherichia coli isoprenol production in the literature accessible to us, 50% of targets that experimentally improved taxadiene production in E. coli and ~60% of genetic targets from a verified minimal constrained cut-set in Pseudomonas putida while providing additional high priority targets that could be tested. Overall, FluxRETAP is an efficient algorithm for identifying a prioritized list of testable genetic and reaction targets which can also be utilized in ML pipelines.

Czajka, Jeffrey [Battelle Memorial Institute, Paci↗