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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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99 records · Page 6
All sourcesNASA NTRSDOE OSTI
NASA NTRS2012

Chandra Observations of Galaxy Zoo Mergers: Frequency of Binary Active Nuclei in Massive Mergers

We present the results from a Chandra pilot study of 12 massive mergers selected from Galaxy Zoo. The sample includes major mergers down to a host galaxy mass of 10(sup 11) solar mass that already have optical AGN signatures in at least one of the progenitors. We find that the coincidences of optically selected active nuclei with mildly obscured (N(sub H) less than or approximately 1.1 x 10(exp 22) per square centimeter) X-ray nuclei are relatively common (8/12), but the detections are too faint (less than 40 counts per nucleus; f(sub 2-10 keV) less than or approximately 1.2 x 10(exp -13) ergs per second per square centimeter) to separate starburst and nuclear activity as the origin of the X-ray emission. Only one merger is found to have confirmed binary X-ray nuclei, though the X-ray emission from its southern nucleus could be due solely to star formation. Thus, the occurrences of binary AGN in these mergers are rare (0-8%), unless most merger-induced active nuclei are very heavily obscured or Compton thick.

Teng, Stacy H.↗
NASA NTRS2012

Chandra Observations of Galaxy Zoo Mergers: Frequency of Binary Active Nuclei in Massive Mergers

We present the results from a Chandra pilot study of 12 massive galaxy mergers selected from Galaxy Zoo. The sample includes major mergers down to a host galaxy mass of 1011 M that already have optical AGN signatures in at least one of the progenitors. We find that the coincidences of optically selected active nuclei with mildly obscured (N(sub H) approx < 1.1 10(exp 22)/sq cm) X-ray nuclei are relatively common (8/12), but the detections are too faint (< 40 counts per nucleus; (sub -10) keV approx < 1.2 10(exp -13) erg/s/sq cm) to reliably separate starburst and nuclear activity as the origin of the X-ray emission. Only one merger is found to have confirmed binary X-ray nuclei, though the X-ray emission from its southern nucleus could be due solely to star formation. Thus, the occurrences of binary AGN in these mergers are rare (0-8%), unless most merger-induced active nuclei are very heavily obscured or Compton thick.

Teng, Stacy H.↗
NASA NTRS2017

Group Housing During Hindlimb Unloading to Simulate Weightlessness

The rodent hindlimb unloading (HU) model was developed in the 1980s to faciliate the study of mechanisms, responses, and treatments for the adverse effects of spaceflight. A number of variations on unloading systems and cage designs have been developed, although most entail individually housing the HU animals. In this study, we performed hindlimb unloading under group housing conditions. Our preliminary results indicate that HU animals that were group housed for 30 days, displayed musculoskeletal decrements associated with disuse, and further, body weights did not differ compared to age-matched controls. In conclusion, group housing of HU mice provides a novel means to simulate weightlessness under conditions that more closely resemble living conditions of Rodent Research Project ISS flight hardware habitats, and minimizes the social stress of isolation, which is consistent with current animal welfare standards (Guide for the Care and Use of Laboratory Animals: Eighth Edition, National Research Council).

group housing↗
NASA NTRS2019

Estimation of coarse dead wood stocks in intact and degraded forests in the Brazilian Amazon using airborne lidar

Coarse dead wood is an important component of forest carbon stocks, but it is rarely measured in Amazon forests and is typically excluded from regional forest carbon budgets. Our study is based on line intercept sampling for fallen coarse dead wood conducted along 103 transects with a total length of 48 km matched with forest inventory plots where standing coarse dead wood was measured in the footprints of larger areas of airborne lidar acquisitions. We developed models to relate lidar metrics and Landsat time series variables to coarse dead wood stocks for intact, logged, burned, or logged and burned forests. Canopy characteristics such as gap area produced significant individual relations for logged forests. For total fallen plus standing coarse dead wood (hereafter defined as total coarse dead wood), the relative root mean square error for models with only lidar metrics ranged from 33 % in logged forest to up to 36 % in burned forests. The addition of historical information improved model performance slightly for intact forests (31 % against 35 % relative root mean square error), not justifying the use of a number of disturbance events from historical satellite images (Landsat) with airborne lidar data. Lidar-derived estimates of total coarse dead wood compared favorably with independent ground-based sampling for areas up to several hundred hectares. The relations found between total coarse dead wood and variables quantifying forest structure derived from airborne lidar highlight the opportunity to quantify this important but rarely measured component of forest carbon over large areas in tropical forests.

Brazilian Amazon↗
NASA NTRSDate not supplied

Flow Reconstruction in A Transonic Turbine Cascade Using Physics-Informed Neural Networks (PINNS)

This paper investigates the application of Physics-Informed Neural Networks (PINNs) for the analysis of turbine blades in a transonic cascade. The 2-D flow field in a transonic turbine cascade is reconstructed in three ways: the traditional forward approach (PINN not trained on experimental data), by training the PINN using discrete sets of experimentally measured pressure at midspan, and in the inverse sense where no inlet or outlet pressure boundary conditions are applied. Comparisons between the PINN solutions to measured data are made. This is repeated for three different turbine blades with distinct loading characteristics. Good agreement is shown between a CFD calculation of the CMC7 blade, and the PINN model trained with all data. The PINN is trained utilizing all available data, half the available data, data from only the leading edge region, and data from only the trailing edge region. The forward problem results deviate the most from experimental data but show promise. Solutions from the assisted training cases show that the PINN can reconstruct the flow field with acceptable accuracy when trained on measurements along the entire blade. In the inverse case, it is shown that to simultaneously achieve acceptable errors for inlet Mach number and outlet isentropic Mach number, the PINN must be trained on the static pressure data along the entire blade.

Machine Learning↗
NASA NTRSDate not supplied

GT2024-128885: Flow Reconstruction in a Transonic Turbine Cascade using Physics-Informed Neural Networks (PINNs)

This presentation investigates the application of Physics-Informed Neural Networks (PINNs) for the analysis of turbine blades in a transonic cascade. PINNs are a machine learning method trained on losses calculated from reconstructed governing equations, assigned boundary/initial conditions, and measured data. We reconstruct the 2-D flow field in a transonic turbine cascade in two ways: the traditional forward approach (without training/experimental data) and by training the PINN using experimental data. We then compare the PINN solutions to measured data. This is repeated for three different turbine blades with distinct loading characteristics. The experimental data used for training is the static pressure measurements along the suction and pressure sides of each blade. The PINN is trained utilizing all available data, half the available data, data from only the leading edge region, and data from only the trailing edge region. It's shown that the PINN can reconstruct the flow field in all cases with acceptable errors. Cases where the PINN is trained on all the data, and even half the data, resulted in the lowest errors. The exit Mach number is inferred for each case and compared to the experimentally calculated value.

Machine Learning↗
NASA NTRSDate not supplied

Fluidic Fence Flow Control on A 30° Swept Wing in Compressible Freestreams

A 30° swept wing with a NACA 64(3)-618 airfoil cross-section was evaluated in four different freestream conditions with Mach numbers increasing from 0.05 to 0.7 using computational fluid dynamics simulations. Active flow control (AFC) through a streamwise row of vortex generating jets was applied at 70% span, blowing inboard to obstruct the development of spanwise flow and increase lift outboard of the control location. The effectiveness of the AFC was evaluated at α = 5° and 10° as freestream Mach number increased and the AFC mass flow coefficient was held constant. Increases to lift coefficient were reduced at higher Mach numbers, but the ratio of change in lift coefficient and the AFC momentum coefficient remained roughly constant. The fluidic fence caused decreased pressure coefficients on the outboard wing sections, but this region of decreased pressure coefficient moved aft on the chord with increasing Mach number. Mach 0.7 is higher than the critical Mach number of the wing and produced interesting interplay with the AFC, as the suction surface shock moved forward on the inboard wing section but moved aft on the outboard wing section.

Evan J McFadden↗
NASA NTRSDate not supplied

Fluidic Fence Flow Control on A 30° Swept Wing in Compressible Freestreams

A 30° swept wing with a NACA 64(3)-618 airfoil cross-section was evaluated in four different freestream conditions with Mach numbers increasing from 0.05 to 0.7 using computational fluid dynamics simulations. Active flow control (AFC) through a streamwise row of vortex generating jets was applied at 70% span, blowing inboard to obstruct the development of spanwise flow and increase lift outboard of the control location. The effectiveness of the AFC was evaluated at α = 5° and 10° as freestream Mach number increased and the AFC mass flow coefficient was held constant. Increases to lift coefficient were reduced at higher Mach numbers, but the ratio of change in lift coefficient and the AFC momentum coefficient remained roughly constant. The fluidic fence caused decreased pressure coefficients on the outboard wing sections, but this region of decreased pressure coefficient moved aft on the chord with increasing Mach number. Mach 0.7 is higher than the critical Mach number of the wing and produced interesting interplay with the AFC, as the suction surface shock moved forward on the inboard wing section but moved aft on the outboard wing section.

Evan J McFadden↗
DOE OSTI2024

Out-of-plane curved fluidic oscillator

Various implementations include, an out-of-plane feedback-type fluidic oscillator. including a first portion, a second portion, a middle portion coupled between the first portion and the middle portion, and an axis of rotation. The middle portion includes a first side, a second side opposite and spaced apart from the first side, and a middle plane, an interaction chamber, a fluid supply inlet, an outlet nozzle, a first feedback a channel, and a second feedback channel. The first side is coupled to the first portion, and the second side is coupled to the second portion. The first side, the second side, and the middle plane extend circumferentially around the axis of rotation. The middle plane is disposed equally distanced from the first side and the second side. The fluid stream oscillates as it flows through the interaction chamber such that the fluid stream oscillates as the fluid stream exits the outlet nozzle.

Hossain, Mohammad Arif↗