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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 NTRS2020

Ultraviolet and X-ray properties of Coma’s ultra-diffuse galaxies

Many ultra-diffuse galaxies (UDGs) have been discovered in the Coma cluster, and there is evidence that some, notably Dragonfly 44, have Milky Way-like dynamical masses despite dwarf-like stellar masses. We used X-ray, ultraviolet (UV), and optical data to investigate the star formation and nuclear activity in the Coma UDGs, and we obtained deep UV and X-ray data (Swift and XMM–Newton) for Dragonfly 44 to search for low-level star formation, hot circumgalactic gas, and the integrated emission from X-ray binaries. Among the Coma UDGs, we find UV luminosities consistent with quiescence but NUV−r colours indicating star formation in the past Gyr. This indicates that the UDGs were recently quenched. The r-band luminosity declines with projected distance from the Coma core. The Dragonfly 44 UV luminosity is also consistent with quiescence, with SFR<6×10^−4M(ʘ)/yr,and no X-rays are detected down to a sensitivity of 10^38erg/s. This rules out a hot corona with a M>10^8M(ʘ) within the virial radius, which would normally be expected for a dynamically massive galaxy. The absence of bright, low-mass X-ray binaries is consistent with the expectation from the Galaxy total stellar mass, but it is unlikely if most low-mass X-ray binaries form in globular clusters, as Dragonfly 44 has a very large population. Based on the UV and X-ray analysis, the Coma UDGs are consistent with quenched dwarf galaxies, although we cannot rule out a dynamically massive population.

Chris H. Lee↗
NASA NTRS2020

TPSAS-NF1676L-35670-DND

We demonstrate that a low-cost spacecraft bus based on the Propulsive ESPA architecture, launched as a directed facility alongside a mission to the outer solar system, enables innovative and viable SIMPLEx-class missions to the outer solar system and achieve high-value science objectives. As a case study, we present a Propulsive ESPA bus that could be launched with the Dragonfly mission toward the Saturn System and carry two small spacecraft weighing up to 130 kg each. We advocate a mission architecture that enables delivering multiple small missions to the Saturn System on a stand-alone Carrier-Relay Spacecraft (CRSC) that flies independently, and poses zero impact on the Dragonfly Mission. To accommodate this architecture, the launch vehicle will require an upgrade from Dragonfly's notional Atlas V 411 to Atlas V 541. Raising the SIMPLEx cost cap from the current $55M, and excluding Phase E costs will also make outer-planet missions viable in the SIMPLEx program. We have identified multiple high-value mission concepts that fit within the 130 kg limit. As examples, we present concepts for Saturn Probe, Saturn Ring In-Situ Explorer, Magnetospheric Explorer, and Enceladus Plume Sampler.

Kunio M Sayanagi↗
NASA NTRSDate not supplied

Progress on Inverse Estimation Technique of Non-Linear Pitch Damping Coefficient Curves Using Free-Flight CFD Generated Trajectories

Characterization of entry vehicle pitch damping coefficient curves is crucial to ensure appropriate re-entry and overall mission success. The pitch damping coefficient (C_(m_q )+C_(m_α ̇ )) is used to encapsulate the oscillatory growth or decay of a body during a trajectory. The inverse estimation technique utilizes an existing Free-Flight CFD (FF-CFD) dataset and wraps a reconstruction algorithm in an optimizer. The reconstruction integrates the planar equations of motion derived by Schoenenberger, Queen [1] using Python’s scipy.integrate.solve_ivp. The optimizer’s objective function is the normalized 𝐿2 residual of the angle of attack peaks between the reconstructed trajectory and the original data produced with FF-CFD. Inclusion of the peak times in this residual calculation allows for simultaneous optimization of the pitch moment coefficient, C_(m_α ). This residual equation is shown below in Eq. 1. The optimizer scipy.optimize.minimize was used with the gradient-based Powell method for the analysis presented, however the differential evolution method was investigated as means of comparison, and was found to produce marginally lower residual values with prohibitively longer run times. Further, the pitch damping curve is found by fitting a cubic interpolation function to a set of (α, (C_(m_q )+C_(m_α ̇ ))) control points, where the α points are held constant and the (C_(m_q )+C_(m_α ̇ )) values are the optimized parameters. The pitch moment curve uses a linear interpolation between the minimum and maximum α in the dataset. FF-CFD generated trajectories using the Dragonfly capsule geometry with the Genesis ballistic range model parameters were simulated and used for this analysis. These FF-CFD trajectories simulate planar motion, as restricted by the reconstructing the equations of motion, of three different cases: 1-DoF (free-to-pitch), 2-DoF (free-to-pitch and heave), and 3-DoF (free-to-pitch, heave, and decelerate). Pitch damping coefficient curves generated using this inverse estimation curve technique with FF-CFD 1-DoF Dragonfly data are found in Fig. 1. Preliminary results reconstructing ballistic range shots using these FF-CFD derived predictions of the pitch damping curve (Fig. 1) are shown in Fig. 2. It should be noted that the ballistic range shot used a Genesis model whereas the FF-CFD data used a Dragonfly geometry, however these geometries are similar.

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