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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↗
DOE OSTI2018

A Detailed Model of Rear-Side Irradiance for Bifacial PV Modules

We describe and validate a method for modeling irradiance on the back surface of bifacial PV modules at the scale of individual cells using view factors. We compare model results with irradiance measurements on the back of PV modules in various configurations. Our analysis illustrates the relative accuracy of the model as well as the potential variation in back surface irradiance among the cells.

14 SOLAR ENERGY↗
DOE OSTI2020

The {sup 136}Xe + {sup 198}Pt Reaction: a Detailed Re-examination

We extend previous measurements of the transfer product yields in the reaction of E-c.m. = 450 MeV Xe-136 with Pt-198 by measurements of the product yields using Gammasphere. By recording events occurring in beam bursts and in between beam bursts, we are able to extend the number of measured product yields from 78 to 171 nuclides. Our new data span a much wider range of Z and A than observed in previous work and when compared to theoretical predictions, these new measurements provide a more stringent and thorough test of models of multi-nucleon transfer (MNT) reactions.

Desai, V. V.↗