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178 records · Page 7

Pinned in Microgravity: How Colloidal Suspensions Inhibit Droplet Motion

Understanding the fundamental behavior of colloidal fluids in microgravity is critical for advancing material science, manufacturing, and biological processes. In this study we investigate the dynamics of a droplet containing colloidal suspension when ejected in short term microgravity. These conditions are generated using a 2.2 second drop tower. A custom droplet generator was designed to produce consistent size-controlled droplets containing passive colloidal particles. The particles are suspended in water and subsequently ejected out of a hydrophobic wedge under microgravity conditions, where the droplet ejection time can be predicted [Torres & Weislogel, 2021]. The ejection times will be compared with de-ionized water ejected from the same system to investigate the effects of change in density and surface tension caused by the colloids. Successful passive colloidal ejection will lay the foundation for active colloid research in the future.

colloids

Impact of Inertia, Friction, and Backlash upon Force Control in Telemanipulation

The mechanical behavior of master controllers of telemanipulators has been a concern of both designers and implementors of telerobotic systems. In general, the literature recommends that telemanipulator systems be constructed that minimize inertia, friction, and backlash in an effort to improve telemanipulative performance. For the most part, these recommendations are founded upon theoretical analysis or simply intuition. Although these recommendations are not challenged on their merit, the material results are measured of building and fielding telemanipulators that possess less than ideal mechanical behaviors. Experiments are described in which forces in a mechanical system with human input are evaluated as a function of mechanical characteristics such as inertia, friction, and backlash. Results indicate that the ability of the human to maintain gripping forces was relatively unaffected by dynamic characteristics in the range studied, suggesting that telemanipulator design in this range should be based on task level force control requirements rather than human factors.

Neil A Duffie

Thermoplastic Matrix Composite Design for Cryotanks Using Multiscale Modeling and Bayesian Optimization

Designing lightweight, robust cryogenic storage tanks is critical for future launch vehicles, in-space propellant storage, and hydrogen powered aircraft. This work presents a multiscale modeling and Bayesian optimization framework for the design of thermoplastic matrix composite cryotanks. Molecular dynamics simulations are first used to determine temperature-dependent constituent properties for candidate thermoplastic matrices, which are homogenized to the lamina scale using NASA’s Multiscale Analysis Tool (NASMAT). These lamina properties, in combination with laminate family generation rules, are evaluated in HyperX structural optimization software to identify stacking sequences that meet all cryogenic load requirements. A Bayesian optimization framework is applied, with HyperX in the loop (via the HyperX API) to efficiently search across material and laminate design variables, yielding an optimized cryotank configuration with significant reductions in design cycle time compared to exhaustive search approaches.

thermoplastics

Multiscale Modeling of Fracture Strength in Fibrous Thermal Protection System Materials

This work presents a multiscale modeling approach to predict the fracture strength of fibrous Thermal Protection System (TPS) materials. The model assumes that system failure is initiated at the joints between individual fibers. We investigated three distinct TPS compositions: amorphous silica, alumina and aluminosilicate fibers. Molecular dynamics (MD) simulations were employed to determine the fracture strength values of these fiber joints for both material systems. These fracture strength values were then integrated into simulations of 3D randomly populated fiber structures, where tensile load transfer occurs through the fiber joints. These microscale properties are upscaled through a renormalization approach [1] to predict macroscale tensile strength of 3D random fiber networks, accounting for joint-dominated failure and effective load-bearing area. The study concludes by demonstrating the resulting strength variation as a function of material composition, fiber density, and morphology. We also show validation of results by comparing them against explicit fiber finite element (FE) modeling [2] where fiber joint fracture is represented by cohesive elements.

Jaehyun Cho

Prediction of prompt NO(x) in hydrocarbon air flames

The gas turbine industry is directing particular attention to very low NOx combustors, whether for aircraft or land based CCGT systems. These low NOx combustors frequently use liquid fuels or natural gas burning under very lean premixed conditions with air or under rich-lean conditions, although only the first case is studied here. In land based systems, diluted steam or nitrogen are sometimes injected into the combustion chambers to reduce flame temperature. The NOx emissions from such systems are the product of three chemical mechanisms which are interrelated: the hydrocarbon prompt NO, the thermal NO (extended Zeldovich mechanism), and the nitrous oxide route to NO. Formation of NO2 from NO also occurs, as well as emission of carbon monoxide and unburnt hydrocarbons. When the fuel-oxidant proportion decreases towards leaner conditions, flame temperatures are lowered, resulting in the total NO being reduced and the thermal-NO contribution greatly diminished to the benefit of the remaining two mechanisms of NO formation. While knowledge of the elementary reactions and their chemical kinetics concerning methane and simple hydrocarbons combustion has existed for a number of years, its use for computer modeling is limited to simple flow dynamics configurations. Nevertheless, understanding of such combusting flows under a wide range of experimental conditions allows for analogies or speculations with more complex actual systems. Such understanding can be achieved by means of one dimensional laminar premixed flame modeling, with a full chemical mechanism which incorporates the three routes of NO formation. Complementary to this understanding is the modeling of the actual combustion system using a full description of the fluid dynamics coupled with a reduced chemical scheme, which is then compared against the first model. The objective of this investigation is to evaluate the relative importance of the three mechanisms of NO formation in lean premixed methane-air combustion with increasing pressure using the one dimensional plug flow package PREMIX, and to test the validity of a three dimensional model with a global chemical mechanism against the one dimensional model in the atmospheric pressure case. Methane is chosen because it is the only mechanism which is reasonably well known and is a good guide to the behavior of other hydrocarbons. The mixture ratio chosen is richer than that in lean gas turbines, but the combustion of this mixture with the low preheat gives realistic gas turbine final flame temperatures. Conditions of NO2 formation are also analyzed in the one dimensional model and results extrapolated to the case of gas turbines.

Valerie Dupont

Deep RL for Fast Long-Horizon Operations Scheduling on NASA's Carruthers Geocorona Observatory Mission

Spacecraft operations scheduling is a highly constrained, long-horizon combinatorial optimization problem that traditionally relies on heuristics, constraint programming, or manual planning. We present a scalable deep reinforcement learning framework developed and deployed for NASA’s Carruthers Geocorona Observatory mission. Our framework introduces a macro-action abstraction known as activity blocks coupled with dynamic action-masking to navigate the intractably large search space and strictly enforce complex power, thermal, and instrument constraints. The resulting architecture generates globally feasible schedules with overwhelming probability, establishes operational trust, and executes a full training cycle in under six hours, circumventing the need for policy robustness by enabling rapid, on-demand retraining. Further, resulting schedules outperform baseline heuristics in scheduled science quality. The deep reinforcement learning framework was deployed as the default operational scheduler for the Carruthers Geocorona Observatory mission from the outset of the mission, demonstrating that deep reinforcement learning can be trusted for real spacecraft operations under complex, evolving constraints.

Geocorona

A Missed Thrust Framework for Low-Thrust Spiral Trajectories to the NRHO

A framework is developed by which end-to-end optimization of many-revolution low-thrust spiral trajectories can be completed in the presence of missed thrust events. This framework is applied to the Lunar Transit trajectory by which the initial capability of NASA’s Gateway lunar space station will be delivered to a Near Rectilinear Halo Orbit. This low-thrust mission consists of three subphases, each designed according to the specific objectives and dynamical regimes encountered as the mission progresses from a medium Earth insertion orbit to cislunar space. The presented framework accounts for the unique considerations demanded by each mission phase and incorporates appropriate capabilities into a novel mission analysis tool. This methodology enables large scale and reliable analyses of missed thrust events across the end-to-end Lunar Transit to verify the robustness of flight trajectories across the full range of considered launch dates.

missed thrust

Diffusion Quantum Monte Carlo Calculation of the Austenite and Martensite Phases of NiTi

NiTi is a promising material for smart and active technologies due to its exhibition of the shape memory effect, superelasticity, and biocompatibility. The shape memory effect is tied to the reversible transition between the austenite and martensite phases. A major research direction is to alloy NiTi with Zr, Hf, Pd, Pt, etc., in order to tune the martensitic transition temperature (MTT). Modeling the MTT from first principles is challenging because the lattice dynamics is complicated by anharmonicity and various low-energy structures. Using density functional theory, the energy difference between the austenite and martensite phases of NiTi varies by up to 100 meV/atom depending on the choice of density functional, which is of the same order of the energy difference itself. Consequently, free energy calculations with different functionals can result in estimates of the MTT that vary by several hundred K. Using diffusion quantum Monte Carlo, we calculated the energy difference between the B2 and B19' structures of NiTi to be 70.9 +- 2.5 meV/atom.

Kevin K Ly

Contaminant characterization of five satellite materials

An extensive laboratory test program was performed to characterize outgassing of five satellite materials. The materials were Chemglaze Z-306 over 9922 primer, M-773 adhesive, multilayer insulation, polyurethane foam, and silverized Teflon. The souces were prepared to the specifications of a typical satellite program. Dynamic thermogravimetric mass loss characteristics of these five materials were obtained in vacuum with a beam microbalance. The temperature of the material was linearly raised from 25 C to over 650 C while monitoring the mass loss, rate of mass loss, temperature, and the composition of the outgassed material by residual gas analysis. Isothermal source emission/capture coefficients/reemission parameters were obtained with an array of quartz crystal microbalances (QCM). A detailed test matrix in which the temperatures of the QCMs (-160 C, - 100 C, -40 C, and +10 C) and the source material (125 C, and 90 C, and 50 C) were varied was performed. The array of QCMs was also used to measure the spatial distribution of the source emission. The effects of vacuum ultraviolet radiation on the deposition and reemission parameters was determined.

J A Muscari

Evaluation of Particle Degradation of a Ytterbium Disilicate Gas Turbine Coating in a Combustion Environment

Ytterbium disilicate (Yb2Si2O7) is a state-of-the-art topcoat material used in environmental barrier coatings (EBCs) to protect SiC-SiC composites from water vapor corrosion in gas turbine engines. However, it’s degradation by thermochemical and thermomechanical particle interactions may limit its use in next generation engine systems. Several static furnace tests have been performed on Yb2Si2O7 to elucidate methods of degradation, although dynamic testing in an engine-relevant environment has not been carried out. Ultimately, testing and evaluation of materials that incorporates all environmental damage modes will allow for an accurate assessment of long-term durability and operating lifetime. This work details the investigation of particle-induced erosion and corrosion of Yb2Si2O7 in NASA Glenn’s Erosion Burner Rig Facility. Coating durability was investigated as a function of test temperature, particle size, and deposition rate. Thermal cycling was also incorporated into testing to determine the interplay of heating/cooling cycles with particle degradation. Overall, these analyses will be used to determine coating robustness in an engine relevant environment.

Jamesa L Stokes

Evaluation of Particle Degradation of a Ytterbium Disilicate Gas Turbine Coating in a Combustion Environment

Ytterbium disilicate (Yb2Si2O7) is a state-of-the-art topcoat material used in environmental barrier coatings (EBCs) to protect SiC-SiC composites from water vapor corrosion in gas turbine engines. However, it’s degradation by thermochemical and thermomechanical particle interactions may limit its use in next generation engine systems. Several static furnace tests have been performed on Yb2Si2O7 to elucidate methods of degradation, although dynamic testing in an engine-relevant environment has not been carried out. Ultimately, testing and evaluation of materials that incorporates all environmental damage modes will allow for an accurate assessment of long-term durability and operating lifetime. This work details the investigation of particle-induced erosion and corrosion of Yb2Si2O7 in NASA Glenn’s Erosion Burner Rig Facility. Coating durability was investigated as a function of test temperature, particle size, and deposition rate. Thermal cycling was also incorporated into testing to determine the interplay of heating/cooling cycles with particle degradation. Overall, these analyses will be used to determine coating robustness in an engine relevant environment.

Jamesa L Stokes

Effects of Adverse Weather on Aerodynamics [Les Effets des Conditions Météorologiques Adverses sur I'Aérodynamique]

The 19 technical papers developed for the AGARD Fluid Dynamics Panel (FDP) Specialists' Meeting on "Effects of Adverse Weather on Aerodynamics" held from 28th April—i May 1991 in Toulouse, France are documented in this Conference Proceedings. In addition, introductory material from the Program Chairman and the results of the Round Table Discussion held after the meeting are also included. The FDP organized this meeting to provide a timely review of the progress being made in advancing the state-of-the-art of predicting, simulating, and measuring the effects of icing, anti-icing fluids, and various forms of precipitation on the aerodynamic characteristics of flight vehicles. Topics included results from both theoretical and experimental programs and material related to procedures and regulations for certification and operation. International participation for the meeting included authors from eight nations and representatives from most of the 16 NATO nations.

Precipitation - meteorology

Laser Beam Welding Benchmark Experiments Performed in Reduced Gravity and Vacuum

Laser beam welding (LBW) is affected by the extreme temperatures, reduced pressure, and reduced gravity present in space environments. Gravity and pressure especially influence its melt pool and solidification dynamics. A compact, modular vacuum chamber adaptable to flight platforms from parabolic to orbital currently hosts an experiment to investigate the combined influence of reduced gravity and pressure on LBW. A swappable cartridge contains a rotating platen on which customizable workpieces can be welded under vacuum, greatly increasing experimental throughput. Instrumentation includes weld and thermal cameras observing the process, thermocouples placed on workpieces, accelerometers, and vacuum sensors. Experimental data gathered during the welding process will be combined with post-flight nondestructive evaluation, metallography, and mechanical testing to provide validation datasets for computational modeling. Phase I of this effort involves a parabolic flight campaign in low gravity while an anticipated Phase II would proceed to in-space demonstration to access extended duration microgravity.

in-space welding

Controlled Parametric Forcing During Directional Solidification of a Bulk Organic Alloy Under Microgravity

The response of dendritic microstructures to step-like pulling velocity conditions is investigated using microgravity directional solidification experiments conducted on DECLIC-DSI combined with phase-field simulations. Under a constant pulling velocity of 1.5 µm/s, the evolution toward steady-state growth is characterized in terms of primary spacing, dendrite drift, and tip dynamics. For the first time, side-view observations enabled direct measurement of tip radius and sidebranching frequency. When step-like oscillations of the pulling velocity are imposed, the dendritic array exhibits a strongly period-dependent response: short periods lead to rapid tip adaptation, whereas longer periods induce a phase lag between tip position and morphology, resulting in progressive tip flattening and, above a critical period, interface destabilization and dendrite splitting. Quantitative phase-field simulations, including a realistic thermal field and stochastic noise, reproduce the experimental observations and provide insight into the governing mechanisms, highlighting the role of characteristic relaxation times, sequence-dependent effects, and the irreversible reorganization of the microstructure following splitting.

Microgravity

Design of A CVD Reactor for the Deposition of Diamond in A Microgravity Environment

There is a growing body of theoretical and experimental evidence suggesting that the uniformity, rate, adhesion, quality, and other key properties of Chemical Vapor Deposition (CVD) diamond coatings are influenced by the gas mixing kinetics in the thermal plasma environment of the reaction chamber. The implementation of, for example, Microwave Plasma Enhanced Chemical Vapor Deposition (MPECVD) process in microgravity has, thus, been suggested. Such a diamond deposition system, which overcomes the limitations of present systems and which is distiguishable from them by the use of high pressure MPECVD and recirculation of the would be effluent hydrogen and carbon, is described. Given the key fact that there is nothing in the effluent of the MPECVD process that is truly a byproduct or 'waste', the system can, at least in principle, lend itself to being closed loop yet dynamic. The exhaust contains hydrogen and carbon species which can be recirculated to the plasma reactor, that is, since there are no unusable reaction byproducts, the effluent can be fed back to the reaction chamber with no detriment, thus allowing deployment in a microgravity environment.

M L Languell

Low Temperature Life-Cycle Testing of a Lithium-Ion Battery for Low-Earth-Orbiting Spacecraft

A flight-qualified, lithium-ion (Li-ion) battery developed for the Mars Surveyor Program 2001 Landeris undergoing life-testing at low temperature under a low-Earth-orbit (LEO) profile to assess its capability to provide long term energy storage for aerospace missions. NASA has embarked upon an ambitious course to return humans to the moon by 2015-2020 in preparation for robotic and human exploration of Mars and robotic exploration of the moons of outer planets. Li-ion batteries are excellent candidates to provide power and energy storage for multiple aspects of these missions due to their high specific energy, high energy density, and excellent low temperature performance. Laboratory testing of Li-ion technology is necessary in order to assess lifetime, characterize multi-cell battery-level performance under aerospace conditions, and to gauge safety aspects of the technology. Life-cycle testing provides an opportunity to examine battery-level performance and the dynamics of individual cells in the stack over the entire life of the battery. Data generated through this testing will be critical to establish confidence in the technology for its widespread use in manned and unmanned missions.

Reid, Concha

The Cassini/Huygens Doppler Wind Experiment: Results from the Titan Descent

The primary objective of the Doppler Wind Experiment (DWE), one of the six scientific investigations comprising the payload of the ESA Huygens Probe, is a determination of the wind velocity in Titan's atmosphere. Measurements of the Doppler shift of the S-band (2040 MHz) carrier signal to the Cassini Orbiter and to Earth were recorded during the Probe descent in order to deduce wind-induced motion of the Probe to an accuracy better than 1 m s-1. An experiment with the same scientific goal was performed with the Galileo Probe at Jupiter. Analogous to the Galileo experience, it was anticipated that the frequency of the Huygens radio signal could be measured on Earth to obtain an additional component of the horizontal winds. Specific secondary science objectives of DWE include measurements of: (a) Doppler fluctuations to determine the turbulence spectrum and possible wave activity in the Titan atmosphere; (b) Doppler and signal level modulation to monitor Probe descent dynamics (e.g., spinrate/spinphase, parachute swing); (c) Probe coordinates and orientation during descent and after impact on Titan.

M K Bird

A Radiometric Consistent Spectral Fingerprinting Algorithm for Continuity Products of Hyperspectral Sounders

A radiometric consistent climate fingerprinting methodology has been developed to derive long-term temperature, water vapor, cloud, trace gases, and surface skin temperature anomaly time series from the hyper-spectral sounder measurements of multiple platforms. The spectral fingerprinting methodology requires the use of radiative kernels that are radiometrically consistent with observations. Radiative kernels are built using space-time averaged Jacobians that are physically retrieved from observations under all sky conditions. The physical retrieval algorithm uses the Principal Component based Radiative Transfer Model (PCRTM) for the forward simulation. The incorporation of multiple scattering simulation in PCRTM allows the direct radiative relationship between single field-of-view (FOV) radiance observations and corresponding thermal dynamic variables including cloud properties to be established. Therefore, radiance ?closure? can be achieved under all-sky conditions by the fingerprinting scheme. This methodology has been used to derive climate anomalies from the space-time averaged spectra of AIRS/AMSU and CrIS/ATMS. The use of a consistent fingerprinting scheme provides an effective mean of generating continuity product by merging observations from different platforms and therefore facilitating the long-term climate trend study.

Wan Wu