Mitigating Grazing Flow Impedance Eduction Errors in Additively Manufactured Porous Liners
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liners↗
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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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Mitigating Grazing Flow Impedance Eduction Errors in Additively Manufactured Porous Liners
Additively manufactured porous metamaterials, including triply periodic minimal surface (TPMS) cores, are promising candidates for aeroengine liners but often behave as extended-reacting treatments under grazing flow. Standard impedance eduction procedures assume locally-reacting behavior and can yield physically inconsistent results for such materials. This study evaluates internal partitions (thin solid walls inserted at regular intervals along the liner’s streamwise extent) as a means of suppressing internal streamwise propagation to improve eduction consistency. Six TPMS configurations were tested in the NASA Langley Grazing Flow Impedance Tube (GFIT) at partition spacings of 4′′, 2′′, and 1′′, as well as unpartitioned, and at Mach numbers up to 0.3. For most geometries, 2′′ partition spacing eliminated impedance discontinuities and substantially improved Prony correlation, though effectiveness varied with core topology. Partitions also altered the acoustic response of the liners: resistance increased, resonance frequencies shifted downward, and peak attenuation decreased while bandwidth broadened in some cases. Because partitions modify the liner itself, the educed impedance characterizes the partitioned system rather than the original unpartitioned core. These results establish partitioning as a practical pathway toward liners that are more compatible with standard eduction methods, while demonstrating that the intervention is itself an acoustic design change.
liners↗
Biocybernetic Closed-Loop System for Mitigating Hazardous States of Awareness
The past century of passenger flight has seen continuous improvement in aviation safety by the aerospace industry. However, while commercial aviation accident rates have continued to decline, human error-related incident and accident rates remain remarkably constant across all types of aviation (Shappell, et al., 2007). Unfortunately, this level of human error is unacceptable when considering projections for increased traffic volume (FAA, 2009), and is likely to yield more incidents and accidents unless a more complete understanding of operator error is achieved and remediations are implemented. One area of interest highlighted by researchers is Hazardous States of Awareness (HSAs) that can result from deficiencies in the design and inappropriate use of human-machine interfaces. Identifying and mitigating HSAs is critical for reducing operator errors. One promising approach uses psychophysiological measures which enable automated systems to adapt to the operator?s state and modify modes of operation to support optimal human performance (Scerbo, 2007). This paper will survey previous research and describe future directions for the application of psychophysiological measures of operators derived from cortical and autonomic assessment to perform real-time adaptive modulation of human-automation task mode mixes. The authors will present a summary of previous work done at NASA LaRC and Old Dominion University using a Psychophysiologically Adaptive System (PAS) in which the level of automation of the NASA Multi-Attribute Task Battery was modulated based on Engagement Indices derived from the users? electroencephalogram (Pope, Bogart, & Bartolome, 1995; for review see, Scerbo, Freeman, & Mikulka, 2003). Future theoretical and methodological directions for this type of closed-loop research will be discussed. Specifically, the capacity for this type of PAS to maintain effective operator state and to enable validation of candidate physiological indices will be described. Consideration will also be given to critical system characteristics (e.g., engagement indices, methods for invoking changes among system states, individual differences among users, etc.) that have been or still need to be studied. The potential of the PAS approach for interactive system design and prototyping will also be described. Examples of adaptive automation flight deck concepts in recent experiments will be highlighted and discussed.
Chad L Stephens↗
Radio Metric Errors Due to Mismatch and Offset Between a DSN Antenna Beam and the Beam of a Troposphere Calibration Instrument
Two components of the error of a troposphere calibration measurement were quantified by theoretical calculations. The first component is a beam mismatch error, which occurs when the calibration instrument senses a conical volume different from the cylindrical volume sampled by a Deep Space Network (DSN) antenna. The second component is a beam offset error, which occurs if the calibration instrument is not mounted on the axis of the DSN antenna. These two error sources were calculated for both delay (e.g., VLBI) and delay rate (e.g., Doppler) measurements. The beam mismatch error for both delay and delay rate drops rapidly as the beamwidth of the troposphere calibration instrument (e.g., a water vapor radiometer or an infrared Fourier transform spectrometer) is reduced. At a 10-deg elevation angle, the instantaneous beam mismatch error is 1.0 mm for a 6-deg beamwidth and 0.09 mm for a 0.5-deg beam (these are the full angular widths of a circular beam with uniform gain out to a sharp cutoff). Time averaging for 60-100 sec will reduce these errors by factors of 1.2-2.2. At a 20-deg elevation angle, the lower limit for current Doppler observations, the beam-mismatch delay rate error is an Allan standard deviation over 100 sec of 1.1 x 10 -14 with a 4-deg beam and 1.3 x 10 -15 for a 0.5-deg beam. A 50-m beam offset would result in a fairly modest (compared to other expected error sources) delay error (less than or equal to 0.3 mm for 60-sec integrations at any elevation angle is greater than or equal to 6 deg). However, the same offset would cause a large error in delay rate measurements (e.g., an Allan standard deviation of 1.2 x 10 -14 over 100 sec at a 20-deg elevation angle), which would dominate over other known error sources if the beamwidth is 2 deg or smaller. An on-axis location is essential for accurate troposphere calibration of delay rate measurements. A half-power beamwidth (for a beam with a tapered gain profile) of 1.2 deg or smaller is desired for calibration of all types of radio metrics. A water-vapor radiometer calibration beam of this size with very low sidelobes would require a clear aperture antenna with a diameter of at least 1.5 m if the primary water vapor sensing channel were in the 20-22 GHz range.
R P Linfield↗
A Machine Learning Framework for Error Compensation in Radiative Transfer Calculations
Radiative heat transfer influences the amount of heat flux transferred to the surface of the hypersonic vehicle, which is essential to evaluate the performance of thermal protection systems. The radiative heat flux is found to be computationally prohibitive while accounting for the variation in spatial, angular, and spectral domains. A new methodology has been recently developed to alleviate the cost of computation in the spectral domain by constructing flow-agnostic reduced-order models (ROMs). The developed spectral ROM databases provide grouping strategies that account for non-equilibrium absorption and emission as well as interaction between disparate species due to spectral overlap in associated radiative processes. However, the developed ROMs need to be optimized for a specific combination of interacting gas species and would need to re-calibrated in case individual species are added/omitted. In this work, we use various machine learning (ML) techniques to approximate the radiative intensities determined by a ROM optimized for a specific gas mixture. The ML model relies on the ROM databases developed for a single species which ignores any spectral overlap. Thus, radiation evaluation starts with a simple summation of radiative intensities predicted using these non-calibrated ROMs for the contributing species. The ML framework then provides a correction to account for the interplay in the frequency, i.e., emission of photons by one species and absorption by another, and yields mixture-specific radiation fields. Once trained on the individual ROM databases, the ML framework offers instantaneous corrections that serves as a time/cost effective alternative to the optimization of ROMs for a specific gas mixture. The ML framework is trained on both the high fidelity and ROM evaluated line of sight (LOS) data from Orion, Stardust, and FIRE II cases to obtain a general purpose correction model for earth re-entry scenarios when radiation contributions from both atomic nitrogen and atomic oxygen are considered. A geometric length scale parameter is used in the training process to account for errors introduced in the ROM databases as a consequence of high optical thickness. The efficacy of the ML framework is underscored through extensive analysis of train and test errors with respect to all the re-entry scenarios. The applicability of such an ML framework was further corroborated by embedding it in a state-of-the-art US3D - NERO system for determining the radiative heat flux transferred to the hypersonic vehicle surface.
Radiation↗
Surface Passivation in LEO to Improve Lunar Dust Adhesion Mitigation
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Lunar Dust↗
Assessment of Near-Angle Scatter on Exo-Earth Coronagraphy
Near-Angle Scatter (NAS) of the host star’s light into the coronagraph dark hole may limit the ability of a potential Habitable Worlds Observatory (HWO) to detect and characterize an Earth-like planet around a Sun-like star. This paper summarizes a 5-year investigation of the impact of NAS on high-contrast coronagraphy. Science requirements were flowed down to a draft flux ratio noise ratio (FRN) error budget with allocations for NAS. The modeled sources of NAS include correlated (low and mid-spatial) surface structure, uncorrelated surface microroughness and coating structure, particulate contamination, micrometeoroid impacts and polarization leakage. The paper develops specifications for these sources of scattered light that meet their FRN error budget allocations, distinguishing between scatter that can and cannot be modulated. The development process utilizes an analytical expression that predicts scatter throughput into the dark hole based on BRDF/BSDF. Using this relationship, Photon Engineering performed a FRED® straylight analysis of the HWO EAC-1 (Exploratory Analytical Case #1) coronagraph to parametrically study predicted scattered light contrast in the dark hole. The model revealed that primary mirror microroughness or contamination is not a significant source of scattered light; the most critical surfaces are the smallest and those located closest to the coronagraph focal plane mask. The assessment found that uncorrelated microstructure, contamination, and micrometeoroid impacts require more investigation and potential significant sources of unmodulated scattered light, and highlights that slow thermal wavefront drift is an order of magnitude more impactful than fast mechanical jitter.
coronagraphy↗
High-Fidelity Modeling Approach for Coupling Thermal, Fluid, and Neutronic Analysis in an NTP Engine
Nuclear thermal propulsion (NTP), with its increased efficiency compared to traditional rocket engines, is a potentially enabling technology for space missions of higher complexity, such as delivering heavy machinery or crew to the moon or other planets. Thus, exploring modeling approaches that can effectively couple the thermal, fluid, and neutronic behaviors of NTP reactors is essential to mitigate cost and schedule challenges with hardware development. This paper details one such approach which utilizes Cardinal to unify reactor physics analysis performed using OpenMC, heat transfer analysis performed using the MOOSE framework, and thermal hydraulic analysis performed using the MOOSE Thermal Hydraulic Module. This approach is demonstrated with a proof of concept that focuses on a legacy reactor geometry from the historic NERVA program. This preliminary model found an overprediction in, when compared to the reference data, axial power peaking and the temperatures of both solids and fluids by roughly 20%. It is clear, however, that the model conserved a number of broad trends, and a few model refinements should reduce the observed error. This approach has definite merit and should enable the production of informative results for more modern NTP systems. This work is a first step in creating a transient reactor model that can be updated across a sequence of time steps based on continually fluctuating, time-dependent boundary conditions.
Nuclear Thermal Propulsion↗
Hermes Environment Risk Mitigation Executive System (HERMES): Applications for Safe Autonomous Aircraft Operations
This presentation discusses use of Core Flight Systems in NASA Langley Research Center's drone flight test environment for autonomy algorithms research.
Battery Prognostics↗
Optimal Battery Charging for Damage Mitigation
Our control philosophy is to charge the NiH2 cell in such a way that the damage incurred during the charging period is minimized, thus extending its cycle life. This requires nonlinear dynamic model of NiH2 cell and a damage rate model. We must do this first. This control philosophy is generally considered damage mitigating control or life-extending control. This presentation covers how NiH2 cells function, electrode behavior, an essentialized model, damage mechanisms for NiH2 batteries, battery continuum damage modeling, and battery life models. The presentation includes graphs and a chart illustrating how charging a NiH2 battery with different voltages and currents affects damages the battery and affects its life. The presentation concludes with diagrams of control system architectures for tracking battery recharging.
Hartley, Tom T.↗
Polyimide/Carbon Nanotube Composite Films for Electrostatic Charge Mitigation
Low color, space environmentally durable polymeric films with sufficient electrical conductivity to mitigate electrostatic charge (ESC) build-up have potential applications on large, deployable, ultra-light weight Gossamer spacecraft as thin film membranes on antennas, solar sails, thermal/optical coatings, multi-layer insulation blankets, etc.. The challenge has been to develop a method to impart robust electrical conductivity into these materials without increasing solar absorptivity (alpha ) or decreasing optical transparency or film flexibility. Since these spacecraft will require significant compaction prior to launch, the film portion of the spacecraft will require folding. The state-of-the-art clear, conductive coating (e.g. indium-tin-oxide, ITO) is brittle and cannot tolerate folding. In this report, doping a polymer with single-walled carbon nanotubes (SWNTs) using two different methods afforded materials with good flexibility and surface conductivities in the range sufficient for ESC mitigation. A coating method afforded materials with minimal effects on the mechanical, optical, and thermo-optical properties as compared to dispersal of SWNTs in the matrix. The chemistry and physical properties of these nanocomposites are discussed.
Smith, Joseph G., Jr.↗
Incremental Learning for Passive Microwave Precipitation Retrievals using Advanced Technology Microwave Sounder
Spaceborne passive microwave (PMW) radiometry is central to global precipitation monitoring, yet retrieval uncertainties remain substantial, particularly for cross-track sounders whose variable footprints and channel configurations are optimized for atmospheric temperature and moisture profiling rather than precipitation. Consequently, existing operational products often exhibit angular-dependent biases, limited effective swath utilization, unrealistic rainfall probability distributions, and systematic misclassification of precipitation phase. These limitations are further compounded by the scarcity of globally accurate and representative precipitation observations, as training data from the Dual-frequency Precipitation Radar (DPR) and the Cloud Profiling Radar (CPR) are spatially sparse, lack uniform global coverage, and exhibit heterogeneous error characteristics across precipitation regimes. To address these challenges, this study presents a supervised retrieval algorithm that incrementally trains an ensemble of extreme gradient-boosted decision trees by augmenting base learners with pre-training on reanalysis data and post-training on coincident DPR and CPR observations matched with the Advanced Technology Microwave Sounder (ATMS). By transferring prior information from reanalysis to posterior constraints from radar observations and adopting a sequential detection–estimation strategy for precipitation phase and rate retrieval, the proposed approach yields retrievals across the full ATMS swath that are largely free from persistent deficiencies in current Global Precipitation Measurement (GPM) passive microwave operational products. In particular, the method resolves bimodal artifacts in rainfall retrievals and mitigates systematic high-latitude snowfall biases, including overestimation across the Arctic and underestimation across the Antarctic. Validation against independent Multi-Radar Multi-Sensor (MRMS) data over the Contiguous United States (CONUS) further demonstrates improved performance in precipitation phase detection and rate estimation relative to both reanalysis and current GPM PMW products.
Mahyar Garshasbi↗
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↗
The Benard Problem: A Comparison of Finite Difference and Spectral Collocation Eigen Value Solutions
The application of spectral methods, using a Chebyshev collocation scheme, to solve hydrodynamic stability problems is demonstrated on the Benard problem. Implementation of the Chebyshev collocation formulation is described. The performance of the spectral scheme is compared with that of a 2 nd order finite difference scheme. An exact solution to the Marangoni-Benard problem is used to evaluate the performance of both schemes. The error of the spectral scheme is at least seven orders of magnitude smaller than finite difference error for a grid resolution of N = 15 (number of points used). The performance of the spectral formulation far exceeded the performance of the finite difference formulation for this problem. The spectral scheme required only slightly more effort to set up than the 2 nd order finite difference scheme. This suggests that the spectral scheme may actually be faster to implement than higher order finite difference schemes.
J Raymond Lee Skarda↗
The Effects of Lunar Dust on EVA Systems During the Apollo Missions
Mission documents from the six Apollo missions that landed on the lunar surface have been studied in order to catalog the effects of lunar dust on Extra-Vehicular Activity (EVA) systems, primarily the Apollo surface space suit. It was found that the effects could be sorted into nine categories: vision obscuration, false instrument readings, dust coating and contamination, loss of traction, clogging of mechanisms, abrasion, thermal control problems, seal failures, and inhalation and irritation. Although simple dust mitigation measures were sufficient to mitigate some of the problems (i.e., loss of traction) it was found that these measures were ineffective to mitigate many of the more serious problems (i.e., clogging, abrasion, diminished heat rejection). The severity of the dust problems were consistently underestimated by ground tests, indicating a need to develop better simulation facilities and procedures.
James R Gaier↗
The Effects of Lunar Dust on EVA Systems During the Apollo Missions
Mission documents from the six Apollo missions that landed on the lunar surface have been studied in order to catalog the effects of lunar dust on Extra-Vehicular Activity (EVA) systems, primarily the Apollo surface space suit. It was found that the effects could be sorted into nine categories: vision obscuration, false instrument readings, dust coating and contamination, loss of traction, clogging of mechanisms, abrasion, thermal control problems, seal failures, and inhalation and irritation. Although simple dust mitigation measures were sufficient to mitigate some of the problems (i.e., loss of traction) it was found that these measures were ineffective to mitigate many of the more serious problems (i.e., clogging, abrasion, diminished heat rejection). The severity of the dust problems were consistently underestimated by ground tests, indicating a need to develop better simulation facilities and procedures.
James R Gaier↗
Use of Global Positioning System Measurements to Determine Geocentric Coordinates and Variations in Earth Orientation
Geocentric tracking station coordinates and short-period Earth-orientation variations can be measured with Global Positioning System (GPS) measurements. Unless calibrated, geocentric coordinate errors and changes in Earth orientation can lead to significant deep-space tracking errors. Ground-based GPS estimates of daily and subdaily changes in Earth orientation presently show centimeter-level precision. Comparison between GPS-estimated Earth-rotation variations, which are the differences between Universal Time 1 and Universal Coordinated Time (UT1-UTC), and those calculated from ocean tide models suggests that observed subdaily variations in Earth rotation are dominated by oceanic tidal effects. Preliminary GPS estimates for the geocenter location (from a 3-week experiment) agree with independent satellite laser-ranging estimates to better than 10 cm. Covariance analysis predicts that temporal resolution of GPS estimates for Earth orientation and geocenter improves significantly when data collected from low Earth-orbiting satellites as well as from ground sites are combined. The low Earth GPS tracking data enhance the accuracy and resolution for measuring high-frequency global geodynamical signals over time scales of less than 1 day.
R P Malla↗
Comparison and Application of Battery Modeling Methods for Conceptual Electric Aircraft
Growing interest in design and optimization of electrified aircraft propulsion concepts prompts the need for accurate, flexible, and efficient methods to model battery systems. Presented in this paper are three battery modeling methods that have been used at NASA’s Glenn Research Center, each representing different mathematical or electrical approaches. Thévenin equivalent circuit, normalization, and curve-fitting methods are compared against battery cell test data for the X-57 Maxwell electric aircraft technology demonstrator. The methods are then applied in a simple multidisciplinary optimization context using NASA’s Six-Passenger Electric Quadrotor concept to determine their applicability and performance. The normalization method achieves the highest accuracy for steady and unsteady discharge rates with a voltage mean error percentage of 0.423% and 1.186%, respectively. Optimal quadrotor mission range between the models varies up to 0.5 nmi, identifying current battery modeling methods as a potentially significant contributor to mission analysis error. A set of relevant tools and techniques for conceptual battery modeling are identified in this paper, with conclusions made on the utility of each modeling approach for various design challenges.
power↗