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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 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Axion dark matter experiment: Run 1B analysis details

Searching for axion dark matter, the ADMX Collaboration acquired data from January to October 2018, over the mass range 2.81–3.31 μeV, corresponding to the frequency range 680–790 MHz. Using an axion haloscope consisting of a microwave cavity in a strong magnetic field, the ADMX experiment excluded Dine-Fischler-Srednicki-Zhitnisky (DFSZ) axions at 90% confidence level and 100% dark matter density over this entire frequency range, except for a few gaps due to mode crossings. This paper explains the full ADMX analysis for run 1B, motivating analysis choices informed by details specific to this run.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2021

Axion Dark Matter Experiment: Detailed design and operations

Axion dark matter experiment ultra-low noise haloscope technology has enabled the successful completion of two science runs (1A and 1B) that looked for dark matter axions in the 2.66–3.1 μeV mass range with Dine–Fischler–Srednicki–Zhitnisky sensitivity. Therefore, it is the most sensitive axion search experiment to date in this mass range. Here, we discuss the technological advances made in the last several years to achieve this sensitivity, which includes the implementation of components, such as the state-of-the-art quantum-noise-limited amplifiers and a dilution refrigerator. Furthermore, we demonstrate the use of a frequency tunable microstrip superconducting quantum interference device amplifier in run 1A, and a Josephson parametric amplifier in run 1B, along with novel analysis tools that characterize the system noise temperature.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

Impact of Detailed Parameter Modeling of Open-Cycle Gas Turbines on Production Cost Simulation: Preprint

Flexible resources are increasingly important as variable renewable energy deployment in the power system increases. Although many systems are transitioning away from fossil fuels, open-cycle gas turbines are likely to play an important balancing role for some time, thus requiring accurate modeling of their operational parameters. This paper explores the impact of detailed representation of three operational parameters - start- up costs, run-up rates, and forced outage rates - in the production cost model of a system as it adopts higher levels of wind and solar. Using PLEXOS simulations of the NREL-118 bus test system, the study examines how more detailed parameter modeling affects outcomes such as the number of start-ups and shutdowns, ramping and total generation costs for open-cycle gas turbines, as renewable energy levels increase. The results suggest the value of detailed parameter modeling and continued research on combustion turbines' ability to provide flexibility.

economic dispatch↗
DOE OSTI2024

A deep learning-guided automated workflow in LipidOz for detailed characterization of fungal fatty acid unsaturation by ozonolysis

Understanding fungal lipid biology and metabolism is critical for antifungal target discovery as lipids play central roles in cellular processes. Nuances in lipid structural differences can significantly impact their functions, making it necessary to characterize lipids in detail to enable and understanding of their roles in these complex systems. In particular, lipid double bond (DB) locations are an important component of lipid structure that can only be determined using a few specialized analytical techniques. Ozone-induced dissociation mass spectrometry (OzID-MS) is one such technique that uses ozone to break lipid DBs, producing pairs of characteristic fragments that allow the determination of DB positions. In this work we apply OzID-MS and LipidOz software to analyze the complex lipids of Saccharomyces cerevisiae yeast strains transfected with different fatty acid desaturases from Histoplasma capsulatum to determine the specific unsaturated lipids produce. The automated data analysis in LipidOz made the determination of DB positions from this large dataset more practical, but manual verification for all targets was still time-consuming. The DL model reduces manual involvement in data analysis, but since it was trained using mammalian lipid extracts, the prediction accuracy on yeast-derived data was reduced. We addressed both shortcomings by retraining the DL model to act as a pre-filter to prioritize targets for automated analysis, providing confident manually verified results but requiring less computational time and manual effort. Our workflow resulted in the determination of novel DB positions and enzymatic specificity.

mass spectrometry, deep learning, Lipidomics, doub↗
DOE OSTI2018

Direct numerical simulations of reacting flows with detailed chemistry using many-core/GPU acceleration

A new direct numerical simulation (DNS) code for multi-component gaseous reacting flows has been developed at KAUST, with the state-of-the-art programming model for next generation high performance computing platforms. The code, named KAUST Adaptive Reacting Flows Solver (KARFS), employs the MPI+X programming, and relies on Kokkos for “X” for performance portability to multi-core, many-core and GPUs, providing innovative software development while maintaining backward compatibility with established parallel models and legacy code. The capability and potential of KARFS to perform DNS of reacting flows with large, detailed reaction mechanisms is demonstrated with various model problems involving ignition and turbulent flame propagations with varying degrees of chemical complexities.

Computer Science↗
NASA NTRS1972

Comparison of the radiation flux profiles and spectral detail from three detailed nongray radiation models at conditions representative of hypervelocity earth entry

The radiation models were compared on the basis of the approaches used for the transport calculations and absorption coefficients and of results obtained for the radiation flux profiles and spectral distributions. The calculated results were for shock layer conditions representative of manned earth reentry from an interplanetary mission. The three models are RATRAP, RADICAL, and MDAC. The results show that significant differences exist in the radiation flux computed by the three models. The RADICAL model was found to depend on fewer approximations, to include more detail, and to require less computer time than the other models.

Suttles, J. T.↗
NASA NTRS1976

Formulation of detailed consumables management models for the development (preoperational) period of advanced space transportation system. Volume 1: Detailed requirements for the mission planning processor

Detailed requirements for the mission planning processor are documented. The mission planning processor is a user oriented tool for consumables management and is part of the total consumables subsystem management concept. A quasi top-down approach was applied to the design of the mission planning processor. Interface requirements, input/output, and data base concepts were considered before computational processing. Existing analytical models were investigated for applicability before new models were developed. The mission planning processor was designed for an interactive system using demand terminals for input/outputdisplay and interfacing with an updateable mission data bank. The control and support routines provide the user interface, peripheral data handling, program control, and support functions required by the mission planning processor for execution on an interactive system. A description, interface requirements, definition of internal variables, listing of input data, processing flow diagram, and listing of output data are presented for each routine.

Connelly, L. C.↗