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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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NASA NTRSDate not supplied

Accounting for the Influence of Decorrelation in Microphone Phased Array Deconvolution Methods

Microphone phased arrays are a common tool for use in aeroacoustic wind tunnel testing. The analysis of acquired array data is known to suffer from decorrelation effects, where the coherence of an acoustic wave measured by a pair of microphones is degraded as the wave passes through a turbulent free shear layer or boundary layer. This paper describes, in detail, how to mitigate the influence of decorrelation effects when processing array data with deconvolution methods. This is done using the DAMAS algorithm as an example, applied to recent airframe noise test data acquired in the NASA Langley 14- by 22-Foot Subsonic Tunnel. Two ways of handling the turbulent propagation modeling, both assuming plane wave propagation, are described. Results show that while turbulence model fit parameters may differ, both methods output extremely similar deconvolution results. Further improvements likely require more accurate mean shear layer data prior to developing more involved turbulence models.

microphone array↗
NASA NTRSDate not supplied

Guanine Oxidation in the Genome, not RNA Editing, Accounts for Single Nucleotide Variation in the Exome of Mice Flown on Board the ISS

We have conducted a further analysis of single nucleotide variation (somatic mutation) in mice flown aboard the ISS. We used data archived in GeneLab from a cohort of 18-week-old mice were flown to the ISS, housed in the Rodent Habitat and therefore subjected to microgravity for 37 days. Mice of similar age, sex and the same strain were used for ground controls housed in identical hardware and simulating, but not matching ISS environmental conditions (temperature, humidity and gas atmosphere). Primary data consists of next generation RNA sequencing for the tissues examined: eye, liver, skeletal muscle and kidney. We used novel software, developed at NASA Ames Research Center and deployed on the NASA Ames Supercomputer, to perform variant calling for single point mutations. Unexpectedly, we discovered a high degree of somatic mutation in ISS-flown mice, compared to controls. We found that the extent of somatic mutation correlated with the degree of gene expression in the four tissue types, with the highest degree of somatic mutation observed in genes with the highest degree of expression. Careful analysis that included measurement of specific nucleotide changes that occurred demonstrated that guanine substitutions were the most frequent, consistent with the hypothesis that reactive oxygen species-mediated guanine oxidation was responsible for the hypermutation events. By contrast, adenine substitutions would be expected if gene editing were responsible for the somatic mutation. These types of substitutions were much less frequent. The implication of these findings for astronaut health in a variety of mission scenarios will be discussed.

International Space Station↗
NASA NTRS2023

Accounting for Herbaceous Communities in Process-Based Models Will Advance Our Understanding of “Grassy” Ecosystems

Grassland and other herbaceous communities cover significant portions of Earth's terrestrial surface and provide many critical services, such as carbon sequestration, wildlife habitat, and food production. Forecasts of global change impacts on these services will require predictive tools, such as process-based dynamic vegetation models. Yet, model representation of herbaceous communities and ecosystems lags substantially behind that of tree communities and forests. The limited representation of herbaceous communities within models arises from two important knowledge gaps: first, our empirical understanding of the principles governing herbaceous vegetation dynamics is either incomplete or does not provide mechanistic information necessary to drive herbaceous community processes with models; second, current model structure and parameterization of grass and other herbaceous plant functional types limits the ability of models to predict outcomes of competition and growth for herbaceous vegetation. In this review, we provide direction for addressing these gaps by: (1) presenting a brief history of how vegetation dynamics have been developed and incorporated into earth system models, (2) reporting on a model simulation activity to evaluate current model capability to represent herbaceous vegetation dynamics and ecosystem function, and (3) detailing several ecological properties and phenomena that should be a focus for both empiricists and modelers to improve representation of herbaceous vegetation in models. Together, empiricists and modelers can improve representation of herbaceous ecosystem processes within models. In so doing, we will greatly enhance our ability to forecast future states of the earth system, which is of high importance given the rapid rate of environmental change on our planet.

biogeochemistry↗