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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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The Mars Exploration Rover (MER) mission utilizes the Mars Pathfinder (MPF) parachute design. The MPF parachute drag coefficient is a driver for the MER entry, descent, and landing (EDL) design. As a result, a good estimate of the performance of the MPF parachute at Mars is required.
Knowing little about how porosity and permeability are distributed at depth, we commonly develop models of groundwater by treating the subsurface as a homogeneous black box even though porosity and permeability vary with depth. One reason for this depth variation is that infiltrating meteoric water reacts with minerals to affect porosity in localized zones called reaction fronts. We are beginning to learn to map and model these fronts beneath headwater catchments and show how they are distributed. The subsurface landscapes defined by these fronts lie subparallel to the earth-air interface but with lower relief. They can be situated above, below, or at the water table. These subsurface landscapes of reaction are important because porosity developed from weathering can control subsurface water storage. In addition, porosity often changes at the weathering fronts, and when this affects permeability significantly, the front can act like a valve that re-orients water flowing through the subsurface. We explore controls on the positions of reaction fronts under headwater landscapes by accounting for the timescales of erosion, chemical equilibration, and solute transport. One strong control on the landscape of subsurface reaction is the land surface geometry, which is in turn a function of the erosion rate. In addition, the reaction fronts, like the water table, are strongly affected by the lithology and water infiltration rate. We hypothesize that relationships among the land surface, reaction fronts, and the water table are controlled by feedbacks that can push landscapes toward an “ideal hill”. In this steady state, reaction-front valves partition water volumes into shallow and deep flowpaths. Furthermore, these flows dissolve low- and high-solubility minerals, respectively, allowing their reaction fronts to advance at the erosion rate. This conceptualization could inform better models of subsurface porosity and permeability, replacing the black box.
A rhenium metal complex tethered to a silicon quantum dot allows exploration of the effects of catalyst anchoring and Re–Si energetic alignment on photocatalytic CO 2 reduction activity.
The degradation of antenna performance during hypersonic re-entry is a well known phenomenon that can lead to complete radio blackout. Recent additions to the Empire code establish it as a tool for the study and analysis of the problem. Coupling to the Sandia Parallel Aerodynamics and Reentry Code (SPARC) enables the electromagnetic analysis of realistic re-entry plasma profiles. The geometric flexibility afforded by both Empire and SPARC allow the consideration of arbitrary vehicle and antenna configurations. We have used this tool to study antenna performance during re-entry when the boundary layer becomes turbulent. A concise description of line-of-sight transmissions, which employs advanced statistical methods, was developed. New insights into the low altitude reflectometer readings of RAM-C2 are offered. Techniques for the reconstruction of the re-entry plasma profile from reflectometer data were explored.
Recent breakthroughs in natural language processing show that attention mech- anism in Transformer networks, trained via masked-token prediction, enables models to capture the semantic context of the tokens and internalize the grammar of language. While the application of Transformers to communication systems is a burgeoning field, the notion of context within physical waveforms remains under-explored. This paper addresses that gap by re-examining inter-symbol con- tribution (ISC) caused by pulse-shaping overlap. Rather than treating ISC as a nuisance, we view it as a deterministic source of contextual information embedded in oversampled complex baseband signals. We propose Masked Symbol Model- ing (MSM), a framework for the physical (PHY) layer inspired by Bidirectional Encoder Representations from Transformers methodology. In MSM, a subset of symbol-aligned samples is randomly masked, and a Transformer predicts the missing symbol identifiers using the surrounding “in-between” samples. Through this objective, the model learns the latent syntax of complex baseband waveforms. We illustrate MSM’s potential by applying it to the task of demodulating sig- nals corrupted by impulsive noise, where the model infers corrupted segments by leveraging the learned context. Our results suggest a path toward receivers that interpret, rather than merely detect communication signals, opening new avenues for context-aware PHY layer design.
The Swift Observatory is a Middle-Class Explorer (MIDEX) mission that is a rapidly re-pointing spacecraft with immediate data distribution capability to the astronomical community. Its primary objectives are to characterize and determine the origin of Gamma Ray Bursts (GRBs) and to use the collected data on GRB phenomena in order to probe the universe and gain insight into the physics of black hole formation and early universe. The main components of the spacecraft are the Burst Alert Telescope (BAT), Ultraviolet and Optical Telescope (UVOT), X-Ray Telescope (XRT), and Optical Bench (OB) instruments coupled with the Swift spacecraft (S/C) bus. The Swift Observatory will be tested at the Space Environment Simulation (SES) chamber at the Goddard Space Flight Center from May to June 2004 in order to characterize its thermal behavior in a vacuum environment. In order to simulate the independent thermal zones required by the BAT, XRT, UVOT, and OB instruments, the spacecraft is mounted on a chariot structure capable of maintaining adiabatic interfaces and enclosed in a modified, four section MSX fixture in order to accommodate the strategic placement of seven cryopanels (on four circuits), four heater panels, and a radiation source burst simulator mechanism. There are additionally 55 heater circuits on the spacecraft. To mitigate possible migration of silicone contaminants from BAT to the XRT and UVOT instruments, a contamination enclosure is to be fabricated around the BAT at the uppermost section of the MSX fixture. This paper discuses the test requirements and implemented thermal vacuum test configuration for the Swift Observatory.
On November 4, 2010 the already "in-flight" Deep Impact spacecraft flew within 700km of comet 103P/Hartley 2 as part of its extended mission EPOXI, the 5th time to date any spacecraft visited a comet. In 2005, the spacecraft had previously imaged a probe impact comet Tempel 1. The EPOXI flyby marked the first time in history that two comets were explored with the same instruments on a re-used spacecraft-with hardware and software originally designed and optimized for a different mission. This made the function of the attitude determination and control subsystem (ADCS) critical to the successful execution of the EPOXI flyby. As part of the spacecraft team preparations, the ADCS team had to perform thorough sequence reviews, key spacecraft activities and onboard calibrations. These activities included: review of background sequences for the initial conditions vector, sun sensor coefficients, and reaction wheel assembly (RWA) de-saturations; design and execution of 10 trajectory correction maneuvers; science calibration of the two telescope instruments; a flight demonstration of the fastest turns conducted by the spacecraft between Earth and comet point; and assessment of RWA health (given RWA problems on other spacecraft).
Aggressive design goals have been set for future aero-propulsion systems with regards to fuel economy, noise, and emissions. To meet these challenging goals, advanced propulsion concepts are being explored and current operating margins are being re-evaluated to find additional concessions that can be made. One advanced propulsion concept being evaluated is a geared turbofan with a variable area fan nozzle (VAFN), developed by NASA. This engine features a small core, a fan driven by the low pressure turbine through a reduction gearbox, and a shape memory alloy (SMA)-actuated VAFN. The VAFN is designed to allow both a small exit area for efficient operation at cruise, while being able to open wider at high power conditions to reduce backpressure on the fan and ensure a safe level of stall margin is maintained. The VAFN is actuated via a SMA-based system instead of a conventional system to decrease overall weight of the system, however, SMA-based actuators respond relatively slowly, which introduces dynamic issues that are investigated in this work. This paper describes both a control system designed specifically for issues associated with SMAs, and dynamic analysis of the geared turbofan VAFN with the SMA actuators. Also, some future recommendations are provided for this type of propulsion system.
A new operational amplifier chip based on silicon-on-insulator technology was evaluated for potential use in extreme temperature environments. The CHT-OPA device is a low power, precision operational amplifier with rail-to-rail output swing capability, and it is rated for operation between -55 C and +225 C. A unity gain inverting circuit was constructed utilizing the CHT-OPA chip and a few passive components. The circuit was evaluated in the temperature range from -190 C to +200 C in terms of signal gain and phase shift, and supply current. The investigations were carried out to determine suitability of this device for use in space exploration missions and aeronautic applications under wide temperature incursion. Re-restart capability at extreme temperatures, i.e. power switched on while the device was soaked at extreme temperatures, was also investigated. In addition, the effects of thermal cycling under a wide temperature range on the operation of this high performance amplifier were determined. The results from this work indicate that this silicon-on-insulator amplifier chip maintained very good operation between +200 C and -190 C. The limited thermal cycling had no effect on the performance of the amplifier, and it was able to re-start at both -190 C and +200 C. In addition, no physical degradation or packaging damage was introduced due to either extreme temperature exposure or thermal cycling. The good performance demonstrated by this silicon-on-insulator operational amplifier renders it a potential candidate for use in space exploration missions or other environments under extreme temperatures. Additional and more comprehensive characterization is, however, required to establish the reliability and suitability of such devices for long term use in extreme temperature applications.
Toughened Unipiece Fibrous Reinforced Oxidation-resistant Composite (TUFROC) and its successor, Advanced TUFROC, are state-of-the-art thermal protection systems (TPS) for high temperature reusable applications. Originally designed for use on the wing-leading edge of X-37B, TUFROC is an insulative tiled system consisting of a low-conductivity ceramic base, a carbonaceous cap, and multiple coatings for thermal performance. The improved Advanced TUFROC has demonstrated reusability up to 2900 °F and single use capabilities exceeding 3200 °F. This effort explores the evolution of Advanced TUFROC when exposed to re-entry like conditions via arc jet testing. Chemical reactions and constituent migration resulting from the aerothermal heating are known to occur and are studied in detail. Further, the interaction between the multiple constituents and layers will be discussed as this is believed to have a significant impact on the overall performance. Characterization includes structural analysis via optical microscopy, scanning electron microscopy and energy-dispersive x-ray spectroscopy.
The principal objective of the research reported here is the re-design, analysis and optimization of our newly developed neural network fuzzy adaptive controller model for complex processes capable of learning fuzzy control rules using process data and improving its control through on-line adaption. The learned improvement is according to a performance objective function that provides evaluative feedback; this performance objective is broadly defined to meet long-range goals over time. Although fuzzy control had proven effective for complex, nonlinear, imprecisely-defined processes for which standard models and controls are either inefficient, impractical or cannot be derived, the state of the art prior to our work showed that procedures for deriving fuzzy control, however, were mostly ad hoc heuristics. The learning ability of neural networks was exploited to systematically derive fuzzy control and permit on-line adaption and in the process optimize control. The operation of neural networks integrates very naturally with fuzzy logic. The neural networks which were designed and tested using simulation software and simulated data, followed by realistic industrial data were reconfigured for application on several platforms as well as for the employment of improved algorithms. The statistical procedures of the learning process were investigated and evaluated with standard statistical procedures (such as ANOVA, graphical analysis of residuals, etc.). The computational advantage of dynamic programming-like methods of optimal control was used to permit on-line fuzzy adaptive control. Tests for the consistency, completeness and interaction of the control rules were applied. Comparisons to other methods and controllers were made so as to identify the major advantages of the resulting controller model. Several specific modifications and extensions were made to the original controller. Additional modifications and explorations have been proposed for further study. Some of these are in progress in our laboratory while others await additional support. All of these enhancements will improve the attractiveness of the controller as an effective tool for the on line control of an array of complex process environments.
Although machine learning (ML) has emerged as a powerful tool for rapidly assessing grid contingencies, prior studies have largely considered a static grid topology in their analyses. This limits their application, since they need to be re-trained for every new topology. Here, this paper explores the development of generalizable graph convolutional network (GCN) models by pre-training them across a range of grid topologies and contingency types. We found that a GCN model with auto-regressive moving average (ARMA) layers with a line graph representation of the grid offered the best predictive performance in predicting voltage magnitudes (VM) and voltage angles (VA). We introduced the concept of phantom nodes to consider disparate grid topologies with a varying number of nodes and lines. For pre-training the GCN ARMA model across a variety of topologies, distributed graphics processing unit (GPU) computing afforded us significant training scalability. The predictive performance of this model on grid topologies that were part of the training data is substantially better than the direct current (DC) approximation. Although direct application of the pre-trained model to topologies that are not part of the grid is not particularly satisfactory, fine-tuning with small amounts of data from a specific topology of interest significantly improves predictive performance. In general, this paper highlights the feasibility of training large-scale GNN models to assess the reliability of power grids by considering a wide variety of grid topologies and contingency types. With the advent of foundational models in ML and the exponential increase in GPU computing clusters, generalizable ML models will significantly enhance how utilities manage power systems and make decisions in real-time or near-real-time.
Exploration of natural isotopic variations of the element rhenium (Re) is in its infancy, with initial studies revealing isotopic fractionation in a variety of geological materials. Here, in this work, we investigate Re isotope variation as a new geochemical tool, given its redox-sensitive properties and affinity for organic matter and sulfides. In this work, Re abundance and isotope ratio data were collected from uranium ore concentrates (UOCs) across a variety of depositional ages, locations, geologic settings, and deposit types. Ore types from which the UOC were derived include sandstone, unconformity, and quartz-pebble (QP) conglomerate. To isolate Re from the U-rich matrix of UOCs, a new purification method utilizing DGA ion exchange resin was developed. We found that UOCs exhibit a wide range of Re isotope ratios, with sandstone ore-derived UOCs having the isotopically lightest values, QP conglomerate ore-derived UOCs having the heaviest, and unconformity ore-derived UOCs in between (with some overlap with sandstone UOCs). The Re isotope ratio range observed in UOCs extends previously reported values by more than a factor of two. Industrial processing (e.g., incomplete recovery of Re from ore, contamination, fractionation during processing) may play a role in the isotopic variability in the UOCs. However, systematic differences between ore types suggest that the depositional setting is a significant factor. For nuclear forensic investigations, Re isotopic compositions combined with data from other isotopic systems provide geochemical signatures that can aid in provenance assessment of UOCs. Regardless of the specific causes for the wide range of Re isotope ratios in UOCs, these initial data indicate Re is a promising tool for nuclear forensic investigations on samples from early in the nuclear fuel cycle.
We report point defects and compensation in zinc telluride have been subjects of study for several decades due to the compound’s scientific/technological applications. Despite this, there remains some disagreement in the literature as to the fine details of its defect chemistry. Recently, it has also come under renewed interest due to the emerging Cd( 1–x )Zn x Te( 1–y )Se y material family, used in nuclear radiation detector applications. In this article, we use state-of-the-art computational tools to re-examine the native defect chemistry of ZnTe and explore how it changes upon addition of selenium using density functional theory with screened hybrid exchange–correlation functionals, thermochemical models of the equilibration environment, and statistical mechanics models of the point defect ensemble.
In the pursuit of highly stable and selective metal–organic frameworks (MOFs) for the adsorption of caustic acid gas species, an entire series of rare earth MOFs have been explored. Each of the MOFs in this series (RE-DOBDC; RE = La, Ce, Pr, Nd, Sm, Eu, Gd, Tb, Dy, Ho, Er, Tm, Yb, and Lu; DOBDC = 2,5-dihydroxyterepthalic acid) was synthesized in the tetragonal space group I4/m. Crystallized MOF samples, specifically Eu-DOBDC, were seen to have a combination of monodentate and bidentate binding when synthesized under typical reaction conditions, resulting in a contortion of the structure. However, extended crystallization times determined that this binding is kinetically controlled and that the monodentate binding option was crystallographically eliminated by extended reaction times at higher temperatures. Furthermore, this series allows for the direct study of the effect of the metal center on the structure of the of the MOF; herein, the lanthanide metal ionic radii contraction across the periodic table results in a reduction of the MOF pore size and lattice parameters. Scanning electron microscopy–energy-dispersive spectroscopy was used to investigate the stages of crystal growth for these RE-DOBDC MOFs. All MOFs, except Er-DOBDC had a minimum of two stages of growth. These analogues were demonstrated by analysis of neutron diffraction (PND) to exhibit a cooperative rotational distortion of the secondary building unit, resulting in two crystallographically distinct linker sublattices. Computational modeling efforts were used to show distinct differences on acid gas (NO 2 and SO 2 ) binding energies for RE-DOBDC MOFs when comparing the monodentate/bidentate combined linker with the bidentate-only linker crystal structures.
The first continuum gyrokinetic calculations of electrostatic ion scale turbulence are presented for the case of a diverted tokamak geometry. The simulation model solves the long-wavelength limit of the full-F gyrokinetic equation for ion species coupled to the quasi-neutrality equation for electrostatic potential variations, where a fluid model is used for an electron response. Furthermore, in order to facilitate simulations of highly-anisotropic microturbulence in the presence of strong magnetic shear and a magnetic X-point, a numerical algorithm utilizing a locally field-aligned multiblock coordinate system has been developed and implemented in the 5D finite-volume code COGENT. In this approach, the toroidal direction is divided into blocks, such that within each block, the cells are field-aligned and a non-matching grid interface is allowed at block boundaries. The toroidal angle corresponds to the “coarse” field-aligned coordinate, whereas the poloidal cross section, comprised of the radial and poloidal directions, is finely gridded to resolve short-scale perpendicular turbulence structures and to support accurate re-mapping (interpolation) at block boundaries. The 5D simulations explore cross-separatrix ion scale turbulence in the presence of a self-consistent radial electric field and address the effects of magnetic-shear stabilization in the X-point region.
Navier-Stokes analyses are employed to explore the driving mechanisms controlling asymmetric vortical flows with Re(D) = 0.8 million (Reynolds number based on maximum diameter) over a 3.5 caliber tangent-ogive cylinder at large angles of attack (alpha = 20, 30, and 40 degrees). All flowfield results are steady-state solutions to the three-dimensional, incompressible Navier-Stokes equations in the thin-layer approximation. The numerical results are temporally and spatially fully converged, and are in good agreement with experimental data. The major findings are: (1) for alpha not less than 30 degrees, the vortex flows are genuinely asymmetric yet recurrent; (2) asymmetric vortex patterns are highly sensitive toward such parameters as machine accuracy, grid topology, etc., unless triggered by a slight deformation (similar to an out-of-round nose tip) in the neighborhood of the apex; and (3) for alpha = 20 degrees, the flow is symmetric for both circular and elliptic cross-sectional shapes of the nose tip.
The Molten Chloride Reactor Experiment (MCRE) will be the first reactor featuring a fast-spectrum molten chloride circulating nuclear fuel system in the world. Planning for equipment removal and disposal (ERD) of MCRE has identified several technology gaps due to the unique environment of this nuclear experiment. Some of the gaps arise from the application of existing disassembly and/or sizing methods to novel material forms or in novel configurations. Others arise from unknown material behavior. This paper summarizes proposed test plans for ERD validation experiments to address these complicated or unknown equipment removal procedures. At the Waste Management Symposia in 2024, the Idaho National Laboratory (INL) MCRE ERD team presented the challenges associated with hosting multiple nuclear experiments in series with only brief transition periods between systems. Such difficulties include higher dose rates, the presence of radioisotopes infrequently encountered in reactor decommissioning and radioactive waste management, lack of intrinsic remote-operations infrastructure in the test bed, space constraints in the test bed, and contamination minimization requirements. To address these challenges, remote or semi-remote technologies are planned to be implemented in a non-hot cell environment with limited space availability. The team also discussed how a systems engineering approach is being used for conceptual development and design of equipment removal systems to address these challenges. For example, to reduce constraints for the removal of more difficult components, non-activated, noncontaminated elements are planned to be taken out first where possible. Still, there are complexities associated with the remaining components. In this work, the operational framework for MCRE ERD was reviewed for technical gaps and open questions, and test plans were drafted to address these areas. The tests plans were written for the following categories: vision systems, pipe cutting, drill/grout/filler, flush salt, and miscellaneous, with the miscellaneous group consisting of tests like techniques for removing bearings and reflector bricks. The test plans explore material, infrastructure, and staffing requirements needed for test execution. The test plans additionally focus on the evaluation of success. Determining the outcome of a test is imperative - as these explorative actions have the potential to rearrange or re-scope planned ERD activities. Success criteria identified thus far include required tool output, required area(s), debris production and mitigation, and repeatability. Test plans are an essential aspect of the systems engineering approach to MCRE ERD. They are used as the beginning steps in defining use cases for the ERD system. Performance of the validation tests is expected to begin in the summer of 2025 and will take approximately 9 to 12 months to complete. Execution of these plans will be expedited by specifying test needs ahead of time, facilitating efficient interactions with any subcontractors tasked with running the requested tests. Evaluating the outcomes of these tests will inform MCRE ERD procedures and timing and will also identify additional technical constraints for the MCRE ERD System. This upfront process optimization effort will help the project save time and resources at the end of the experiment.