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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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At least 919 records · Page 51

Development of the Dust Ejecta Radar Technology (DERT) to Determine Plume-Surface Interaction Ejecta Velocities on Planetary Surfaces

Here we present a novel use of millimeter wave doppler radar to measure the velocity of ejecta generated by the impingement of rocket plumes on a planetary surface. The Dust Ejecta Radar Technology (DERT) provides a unique dataset based on direct measurements of ejecta particle velocities during plume-surface interactions. DERT is a continuous wave (CW) 94 GHz radar unit that is being developed at Kennedy Space Center. DERT has measured velocities of a pendulum (~ 1 m/s), a rotating strip (60 m/s), projected regolith simulant BP-1 (~ 250 m/s) and rifle rounds (~ 820 m/s). Signal-to-Noise Ratios of up to 60 dB have been demonstrated. Data collected from DERT will inform the development of high-fidelity computational models of plume-surface interaction effects and will help address NASA Strategic Knowledge Gaps related to characterizing entry, descent and landing effects, and the risks associated with high-speed ejecta on the lander and lunar surface assets.

PSI↗

Dust Ejecta RADAR Technology (DERT): A Millimeter Wave Doppler Radar to Measure Plume Surface Interaction Ejecta Velocities

A novel method to measure the velocity of ejecta generated by the impingement of rocket plumes on a lunar or planetary surface is presented. Dust Ejecta RADAR Technology (DERT), is a Millimeter Wave Doppler Radar sensor that provides a unique dataset based on direct measurements of ejecta particle velocities during plume-surface interactions, which will help inform risk assessments associated with impacts by high-speed ejecta particles. DERT has measured velocities of a pendulum (~1 m/s), a rotating strip (60 m/s), projected regolith simulant BP-1 (~250 m/s) and rifle rounds (~820 m/s). Signal-to-noise ratios of up to 60 dB with regolith simulant BP-1 have been demonstrated with a CW 94 GHz unit. Data collected from DERT will inform the development of high-fidelity computational models of plume-surface interaction effects and will help address NASA Strategic Knowledge Gaps related to characterizing entry, descent and landing effects, and the risks associated with high-speed ejecta on the lander and lunar surface assets. Recent efforts to develop DERT as a flight instrument are presented as well as the development of a Lunar Regolith Ejecta Simulator (LuRES) system to calibrate DERT.

PSI↗

Development of the Dust Ejecta Radar Technology (DERT) to Determine Plume-Surface Interaction Ejecta Velocities on Planetary Surfaces

Here we present a novel use of millimeter wave doppler radar to measure the velocity of ejecta generated by the impingement of rocket plumes on a planetary surface. The Dust Ejecta Radar Technology (DERT) provides a unique dataset based on direct measurements of ejecta particle velocities during plume-surface interactions. DERT is a continuous wave (CW) 94 GHz radar unit that is being developed at Kennedy Space Center. DERT has measured velocities of a pendulum (~ 1 m/s), a rotating strip (60 m/s), projected regolith simulant BP-1 (~ 250 m/s) and rifle rounds (~ 820 m/s). Signal-to-Noise Ratios of up to 60 dB have been demonstrated. Data collected from DERT will inform the development of high-fidelity computational models of plume-surface interaction effects and will help address NASA Strategic Knowledge Gaps related to characterizing entry, descent and landing effects, and the risks associated with high-speed ejecta on the lander and lunar surface assets.

PSI↗

Acoustic Predictions of the Moog S-250 in Hover

Acoustic predictions were made on the Moog S-250 vehicle to assess one of NASA’s mid-fidelity prediction toolchains for Urban Air Mobility-type vehicles. Experimental data from a 60-foot hover test is used for comparison. The S-250 is an RPM-controlled vehicle in a quadcopter-type configuration with four sets of contra-rotating rotors and powered by eight independently controlled electric motors. The same type of rotor blade used on the S-250 was 3D laser scanned to enable the development of custom-made airfoil tables and more accurate blade loadings. Noise predictions at the first couple of blade-pass frequencies indicate a good comparison to experimental data.

Acoustic prediction↗

Development of a Discrepancy Checker for the Digital Twin in a Supervisory Control System for a Thermal Energy Delivery System

Defined as a virtual representation of a physical object, process, or service, and used to support real-world decision-making, a digital twin (DT) can be utilized to combine classical and novel frameworks in sensors, state predictions, and multi-input/multi-output systems, and to enable optimal autonomous operations. However, a DT’s usefulness largely depends on its ability to adequately mirror the state of its physical counterpart, and this adequacy should be reflected by the level of uncertainty in the underlying simulation models when estimating and predicting quantities of interest (QOIs). Moreover, simulation models in a DT may involve multiple fidelities of representations—ranging from physics-based models to data-driven ones—but classical uncertainty quantification (UQ) methods struggle to handle numerous uncertainty sources, nor are they designed for real-time applications. This work presents a UQ-based discrepancy checking and diagnosis tool for a DT-based supervisory control system applied to a thermal energy delivery system (TEDS) at Idaho National Laboratory. The discrepancy checker was developed using metadata from an automated DT development process, and these metadata included different combinations of physical model forms and model parameters, training data and hyperparameters for surrogate models, and design parameters for supervisory control systems. Next, correlations between the uncertainty results and the metadata were established and then applied to the DT operations. The discrepancy checker evaluates the discrepancies between model predictions from virtual and sensor measurements and backtraces them to the corresponding major sources of uncertainty. The discrepancy checker showed reasonable performance in detecting discrepancies and diagnosing sources of uncertainty in testing scenarios.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗

ECAR-7932 Rev 0 Large Eddy Simulation of MARVEL Reactor Core Subchannel to Evaluate Model Uncertainty of Reynolds-Averaged Navier-Stokes Equation Based Computational Fluid Dynamics Analysis

In the previous work (ECAR-7210), the peak cladding temperature of the MARVEL microreactor has been evaluated by steady-state Reynolds-Averaged Navier-Stokes (RANS) based computational fluid dynamics (CFD) simulations. Although numerical uncertainties of RANS-based CFD simulations has been assessed in ECAR-7210, the model uncertainty of RANS turbulence models must be investigated to resolve the issues related to inaccurate prediction of turbulent heat flux and flow pulsation in a tight lattice rod bundle using the steady-state RANS simulations. Consequently, this ECAR conducted a high-fidelity CFD analysis utilizing Large Eddy Simulation (LES) to generate reference data and investigated the model uncertainty of RANS-based CFD simulations.

21 - SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLAN↗

Analysis and Optimization of Seismo-Acoustic Monitoring Networks with Bayesian Optimal Experimental Design

The Bayesian optimal experimental design (OED) problem seeks to identify data, sensor configurations, or experiments which can optimally reduce uncertainty. The goal of OED is to find an experiment that maximizes the expected information gain (EIG) about quantities of interest given prior knowledge about expected data. Therefore, within the context of seismic monitoring, we can use Bayesian OED to configure sensor networks by choosing sensor locations, types, and fidelity in order to improve our ability to identify and locate seismic sources. In this work, we develop the framework necessary to use Bayesian OED to optimize the ability to locate seismic events from arrival time data of detected seismic phases. In order to do utilize Bayesian OED we must develop four elements:1. A likelihood function that describes the uncertainty of detection and travel times; 2. A Bayesian solver that takes a prior and likelihood to identify the posterior; 3. An algorithm to compute EIG; and, 4. An optimizer that finds a sensor network which maximizes EIG. Once we have developed this framework, we can explore many relevant questions to monitoring such as: how and what multiphenomenology data can be used to optimally reduce uncertainty, how to trade off sensor fidelity and earth model uncertainty, and how sensor types, number, and locations influence uncertainty

47 OTHER INSTRUMENTATION↗

Considerations for the Use of Remote Gaze Tracking to Assess Behavior in Flight Simulators

Complex user interfaces (such as those found in an aircraft cockpit) may be designed from first principles, but inevitably must be evaluated with real users. User gaze data can provide valuable information that can help to interpret other actions that change the state of the system. However, care must be taken to ensure that any conclusions drawn from gaze data are well supported. Through a combination of empirical and simulated data, we identify several considerations and potential pitfalls when measuring gaze behavior in high-fidelity simulators. We show that physical layout, behavioral differences, and noise levels can all substantially alter the quality of fit for algorithms that segment gaze measurements into individual fixations. We provide guidelines to help investigators ensure that conclusions drawn from gaze tracking data are not artifactual consequences of data quality or analysis techniques.

eye tracking↗

HRMA calibration handbook: EKC gravity compensated XRCF models

This document, consisting of hardcopy printout of explanatory text, figures, and tables, represents one incarnation of the AXAF high resolution mirror assembly (HRMA) Calibration Handbook. However, as we have envisioned it, the handbook also consists of electronic versions of this hardcopy printout (in the form of postscript files), the individual scripts which produced the various figures and the associated input data, the model raytrace files, and all scripts, parameter files, and input data necessary to generate the raytraces. These data are all available electronically as either ASCII or FITS files. The handbook is intended to be a living document and will be updated as new information and/or fabrication data on the HRMA are obtained, or when the need for additional results are indicated. The SAO Mission Support Team (MST) is developing a high fidelity HRMA model, consisting of analytical and numerical calculations, computer software, and databases of fundamental physical constants, laboratory measurements, configuration data, finite element models, AXAF assembly data, and so on. This model serves as the basis for the simulations presented in the handbook. The 'core' of the model is the raytrace package OSAC, which we have substantially modified and now refer to as SAOsac. One major structural modification to the software has been to utilize the UNIX binary pipe data transport mechanism for passing rays between program modules. This change has made it possible to simulate rays which are distributed randomly over the entrance aperture of the telescope. It has also resulted in a highly efficient system for tracing large numbers of rays. In one application to date (the analysis of VETA-I ring focus data) we have employed 2 x 10(exp 7) rays, a substantial improvement over the limit of 1 x 10(exp 4) rays in the original OSAC module. A second major modification is the manner in which SAOsac incorporates low spatial frequency surface errors into the geometric raytrace. The original OSAC included the ability to use Legendre-Fourier polynomials to describe deviations from the basic optical prescription. To this we have added bicubic splines to address a deficiency in the handling of the sharper deformations in the areas of mirror support pads. SAO has developed software (TRANS-FIT) to translate the most common finite element analysis models into these forms for incorporation into the raytrace program.

Tananbaum, H. D.↗

CFD Assessment of Aerodynamic Degradation of a Subsonic Transport Due to Airframe Damage

A computational study is presented to assess the utility of two NASA unstructured Navier-Stokes flow solvers for capturing the degradation in static stability and aerodynamic performance of a NASA General Transport Model (GTM) due to airframe damage. The approach is to correlate computational results with a substantial subset of experimental data for the GTM undergoing progressive losses to the wing, vertical tail, and horizontal tail components. The ultimate goal is to advance the probability of inserting computational data into the creation of advanced flight simulation models of damaged subsonic aircraft in order to improve pilot training. Results presented in this paper demonstrate good correlations with slope-derived quantities, such as pitch static margin and static directional stability, and incremental rolling moment due to wing damage. This study further demonstrates that high fidelity Navier-Stokes flow solvers could augment flight simulation models with additional aerodynamic data for various airframe damage scenarios.

Frink, Neal T.↗

Representations of Materials for Machine Learning

High-throughput data generation methods and machine learning (ML) algorithms have given rise to a new era of computational materials science by learning the relations between composition, structure, and properties and by exploiting such relations for design. However, to build these connections, materials data must be translated into a numerical form, called a representation, that can be processed by an ML model. Data sets in materials science vary in format (ranging from images to spectra), size, and fidelity. Predictive models vary in scope and properties of interest. Here, we review context-dependent strategies for constructing representations that enable the use of materials as inputs or outputs for ML models. Furthermore, we discuss how modern ML techniques can learn representations from data and transfer chemical and physical information between tasks. Finally, we outline high-impact questions that have not been fully resolved and thus require further investigation.

36 MATERIALS SCIENCE↗

Electrochemical behavior of SnCl 2 and influence of Cu and Ni ions in molten LiCl−KCl−CaCl 2 eutectic

Reliable transport and thermodynamic data for multivalent ions in complex molten salts are scarce, limiting model fidelity for electrorefining and impurity control. Here, we report a comprehensive electrochemical characterization of SnCl₂ in LiCl–KCl–CaCl₂ (50.5–44.2–5.3 mol%) at 685 K, including the effects of Ni 2+ and Cu + impurities. Using cyclic voltammetry (CV), chronoamperometry (CA), and chronopotentiometry (CP), we quantified Sn 2+ and Ni 2+ diffusion with exceptional agreement across methods: Sn 2+ averaged (1.03 ± 0.10) × 10 −5 cm 2 s −1 , and Ni 2+ averaged (0.75 ± 0.19) × 10 −5 cm 2 s −1 . The tight confidence-interval overlap across CV, CA, and CP strengthens confidence in these values and is uncommon in molten chloride studies. Open-circuit-potential measurements provided standard apparent reduction potentials that closely match LiCl–KCl literature, indicating minimal shift with CaCl₂ present. The Sn 2+ /Sn couple behaves as a reversible two-electron soluble–insoluble process at 685 K; the Sn 4+ /Sn 2+ couple transitions to soluble–soluble behavior near 788 K, which may correlate with the decomposition of surface bound chlorostannates, though direct characterization remains to be established. In mixed systems, Cu+/Cu overlaps Sn 2+ /Sn, limiting Cusingle bondSn electroseparation, whereas the larger potential gap between Ni 2+ /Ni and Sn 2+ /Sn supports selective Ni removal. These internally consistent transport and thermodynamic data establish a validated basis for process modeling and optimization of Sn electrorefining and impurity management in LiCl–KCl–CaCl₂.

Berzins-Delahay↗

Scale bridging damage model for quasi-brittle metals informed with crack evolution statistics

Computationally efficient methods for bridging length scales, from highly resolved micro/meso-scale models that can explicitly model crack growth, to macro-scale continuum models that are more suitable for modeling large parts, have been of interest to researchers for decades. In this work, an improved brittle damage model is presented for the simulation of dynamic fracture in continuum scale quasi-brittle metal components. Crack evolution statistics, including the number, length, and orientation of individual cracks, are extracted from high-fidelity, finite discrete element method (FDEM) simulations and used to generate effective material moduli that reflect the material’s damaged state over time. This strategy allows for the retention of small-scale physical behaviors such as crack growth and coalescence in continuum scale hydrodynamic simulations. However, the high-fidelity simulations required to generate the crack statistics are computationally expensive. Thus, steps were taken to produce a flexible constitutive model to reduce the number of costly high-fidelity simulations needed to produce accurate results. A new stress based degradation criterion is introduced for the degradation of individual material zones. This allows for the development of a heterogeneous damage distribution within the bulk material. Then a flow stress model is added to the hydrodynamic simulation to account for plasticity in quasi-brittle materials. As a result, the effective moduli model can be applied to a larger range of materials. The effective moduli constitutive model is used to simulate beryllium flyer plate experiments. The results from the continuum scale simulations using statistics from a single high-fidelity simulation are found to be in excellent agreement with numerical and experimental velocity interferometer data. The same set of crack statistics are used to extrapolate the results of a higher rate flyer plate case using the effective moduli model. In conclusion, the extension of this model to higher rate cases shows promise for further reducing the number of costly high-fidelity simulations needed to generate crack statistics.

36 MATERIALS SCIENCE↗

Analysis of Simulated and Experimental Noise Sources of Boeing 777 Main Gear Model via CLEAN in 3D

Previously obtained experimental and simulated phased microphone array data for the NASA 26%-scale model of a six-wheel main landing gear, with and without a toboggan-shaped noise reduction fairing, were analyzed using the CLEAN technique in three dimensions. The model is a high-fidelity representation of the Boeing 777-200 aircraft main landing gear. The reprocessing of the acoustic data was undertaken to address the deficiencies encountered in the source localization (beamform) maps and the integrated farfield spectra at mid to high frequencies in our previous study, where conventional array processing techniques were applied to the same data sets. Application of the CLEAN approach resulted in higher quality beamform maps with many of the previously observed side lobes either eliminated or suppressed significantly. As a result, integration of the experimentally and computationally based maps showed substantial improvement in the quality of the high-frequency spectral content relative to the corresponding spectra generated via conventional array processing, thus extending the good agreement achieved between the measured and predicted farfield spectra from 8 kHz to 14 kHz in model-scale frequencies. In addition, an examination of the simulated surface pressure fluctuations, off-surface flow field, and three-dimensionally constructed noise sources was conducted to determine the cause of the subtle discrepancies between measured and predicted sound pressure levels that occur in the 1,800 Hz to 4,000 Hz model-scale frequency range.

Ravetta, Patricio↗

Neutral buoyancy simulation of space telerobotics operations

A number of neutral buoyancy versions of space telerobots have been tested in the Space Research Laboratory to understand the potential roles for telerobotic systems in space operations. Particular attention is given to details of the well-modeled dynamic environment, the existence of sizable data base on EVA operations in neural buoyancy with correlation to flight experience, and routine access to a number of high-fidelity mockups of past and planned operational spacecraft. The compromises necessary for the design and construction of neutral buoyancy telerobotic systems are discussed, and data from a number of past simulations, including correlation of neutral buoyancy structural assembly with EVA flight data, and preliminary tests of telerobotic servicing of Hubble Space Telescope are summarized.

Akin, David L.↗

EdgeAI: Machine learning via direct attached accelerator for streaming data processing at high shot rate x-ray free-electron lasers

We present a case for low batch-size inference with the potential for adaptive training of a lean encoder model. We do so in the context of a paradigmatic example of machine learning as applied in data acquisition at high data velocity scientific user facilities such as the Linac Coherent Light Source-II x-ray Free-Electron Laser. We discuss how a low-latency inference model operating at the data acquisition edge can capitalize on the naturally stochastic nature of such sources. We simulate the method of attosecond angular streaking to produce representative results whereby simulated input data reproduce high-resolution ground truth probability distributions. By minimizing the mean-squared error between the decoded output of the latent representation and the ground truth distributions, we ensure that the encoding layers and resulting latent representation maintains full fidelity for any downstream task, be it classification or regression. We present throughput results for data-parallel inference of various batch sizes, some with throughput exceeding 100 k images per second. We also show in situ training below 10 s per epoch for the full encoder–decoder model as would be relevant for streaming and adaptive real-time data production at our nation’s scientific light sources.

97 MATHEMATICS AND COMPUTING↗

Near-Real-Time Detection and Monitoring of Dust Events by Satellite (SeaWIFS, MODIS, and TOMS)

Over the last few years satellites have given us increasingly detailed information on the size, location, and duration of dust events around the world. These data not only provide valuable feedback to the modelling community as to the fidelity of their aerosol models but are also finding increasing use in near real-time applications. In particular, the ability to locate and track the development of aerosol dust clouds on a near real-time basis is being used by scientists and government to provide warning of air pollution episodes over major urban area. This ability has also become a crucial component of recent coordinated campaigns to study the characteristics of tropospheric aerosols such as dust and their effect on climate. One such recent campaign was ACE-Asia, which was designed to obtain the comprehensive set of ground, aircraft, and satellite data necessary to provide a detailed understanding of atmospheric aerosol particles over the Asian-Pacific region. As part of ACE-Asia, we developed a near real-time data processing and access system to provide satellite data from the polar-orbiting instruments Earth Probe TOMS (in the form of absorbing aerosol index) and SeaWiFS (in the form of aerosol optical thickness, AOT, and Angstrom exponent). The results were available via web access. The location and movement information provided by these data were used both in support of the day-to-day flight planning of ACE-Asia and as input into aerosol transport models. While near real-time SeaWiFS data processing can be performed using either the normal global data product or data obtained via direct broadcast to receiving stations close to the area of interest, near real-time MODIS processing of data to provide aerosol retrievals is currently only available using its direct broadcast capability. In this paper, we will briefly discuss the algorithms used to generate these data. The retrieved aerosol optical thickness and Angstrom exponent from SeaWiFS will be compared with those obtained from various AERONET sites over the Asian-Pacific region. The TOMS aerosol index will also be compared with AERONET aerosol optical thickness over different aerosol conditions, and comparisons between the MODIS and SeaWiFS data will also be presented. Finally, we will discuss the climate implication of our studies using the combined satellite and AERONET observations.

Hsu, N. Christina↗

Near-Real-Time Forecast of Satellite-Based Soil Moisture Using Long Short-Term Memory with an Adaptive Data Integration Kernel

Nowcasts, or near-real-time (NRT) forecasts, of soil moisture based on the Soil Moisture Active and Passive (SMAP) mission could provide substantial value for a range of applications including hazards monitoring and agricultural planning. To provide such a NRT forecast with high fidelity, we enhanced a time series deep learning architecture, long short-term memory (LSTM), with a novel data integration (DI) kernel to assimilate the most recent SMAP observations as soon as they become available. The kernel is adaptive in that it can accommodate irregular observational schedules. Testing over the CONUS, this NRT forecast product showcases predictions with unprecedented accuracy when evaluated against subsequent SMAP retrievals. It showed smaller error than NRT forecasts reported in the literature, especially at longer forecast latency. The comparative advantage was due to LSTM’s structural improvements, as well as its ability to utilize more input variables and more training data. The DI-LSTM was compared to the original LSTM model that runs without data integration, referred to as the projection model here. We found that the DI procedure removed the autocorrelated effects of forcing errors and errors due to processes not represented in the inputs, for example, irrigation and floodplain/lake inundation, as well as mismatches due to unseen forcing conditions. The effects of this purely data-driven DI kernel are discussed for the first time in the geosciences. Furthermore, this work presents an upper-bound estimate for the random component of the SMAP retrieval error.

54 ENVIRONMENTAL SCIENCES↗