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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 991 records · Page 55
All sourcesNASA NTRSDOE OSTI
NASA NTRS2024

StarNAV: An Architecture for Autonomous Spacecraft Navigation by the Relativistic Perturbation of Starlight

Exploration missions to the outer Solar System (e.g., Neptune, Kuiper belt objects) or to the interstellar medium present several challenges for conventional spacecraft designs. One of the greatest challenges is a means for navigation, as Earth-based tracking with the Deep Space Network (DSN) becomes less desirable due to high cost, decreased performance at long ranges, and long light-time delays. Indeed, light time delays at Neptune are over four hours (one way), making control of spacecraft during critical events nearly impossible—and this problem only becomes worse as we move to the Kuiper belt or to interstellar space. The need for autonomous spacecraft navigation is well established and is prominently featured in the 2015 NASA Technology Roadmap (e.g., TA 5.4.2.6 & 5.4.2.8). This has led to investment in various technologies to accomplish this task, with the majority of recent work focusing on optical navigation (OPNAV; TA 5.4.4.1) [1], X-ray pulsar navigation (XNAV; TA 5.6.1) [2], or DSN one-way ranging with the Deep Space Atomic Clock (DSAC; TA 5.4.1.1) [3]. This NIAC study suggests a new (and completely different) way of autonomously navigating a spacecraft anywhere in the Solar System or beyond. We call this new technique StarNAV.

NIAC Phase I↗
DOE OSTI2021

Individual Wave Detection and Tracking within a Rotating Detonation Engine through Computer Vision Object Detection applied to High-Speed Images

Known for their simplistic design and continuous detonation, rotating detonation engines (RDEs) constitute a majority of current pressure gain combustion (PGC) research efforts. Experimental RDE operation times have been continuously extended through the use of rig cooling techniques. As the window of observable behavior is expanded, and as the technology matures toward eventual integration within gas turbines, monitoring techniques must evolve to better match industrial diagnostics. High-speed image analysis techniques prove useful to capture and evaluate the unsteady detonation behavior within the RDE. Traditional image analysis techniques, however, require extensive processing times which prohibit simultaneous monitoring. To better address this problem, a computer vision object detection methodology is proposed to quickly detect individual detonation waves within a single down-axis image. Detonation waves are detected in individual images by the implemented computer vision method You Only Look Once (YOLO) object detection network. In order to detect detonation waves, the network must first be trained using RDE images of interest, for which each required phase of network development is outlined. Detection of waves is improved through proper treatment of the collected image set, variation of Intersection over Union (IoU) and confidence thresholding, and through a parametric study of annotation dimensions. Each detected wave is described by its location and rotational direction, and locations are tracked to calculate wave velocity across each frame, leading to a timestep resolution of 20 µs. Wave velocities are also calculated through a series of frames, leading to a suitable average velocity estimation using as few as 10 frames. Uncertainty analysis accounting for variation in camera framerate, pixel width and annotation centroid locations estimates a total uncertainty of ±4.3% for velocity calculations, using the smallest annotation boxes. This method offers great reductions in processing times, as a step toward real-time monitoring of detonation waves within an RDE. Improving on previous studies, this technique is impartial to wave modes not included in the original training set and calculates wave velocities independent of high-speed pressure data. The ability to isolate waves within predicted bounding boxes will likely facilitate analysis of pixel intensity variation as an estimation of wave strength in future work.

Johnson, Kristyn↗
DOE OSTI2020

Deposit geometry and oxygen concentration spatial variations due to composition change in printed functionally graded components

Functionally graded materials (FGMs) with site specific chemical composition are commonly manufactured by directed energy deposition (DED). Although previous work fabricated an FGM with a compositional variation between a ferritic and austenitic alloy, difficulties arose due to variations in deposit shape with composition change. This problem also occurs for FGMs in literature; however, unlike other cases, the thermophysical properties of these two alloys were similar throughout the build. Here, we investigate the role of chemical composition and surface-active elements on deposit geometry during the manufacture of FGMs by laser DED. Single-track experiments for the relevant FGM compositions are analyzed with results from a well-tested, three-dimensional, transient numerical heat transfer and fluid flow model and thermodynamic calculations. Experiments showed deposit shape varied as a function of composition for constant laser power and scan speed. Thermodynamic analysis indicated that the oxygen solubility in the fusion zone varied significantly for each composition used for the FGM. Numerical modeling revealed that the change in fluid flow caused by Marangoni convection due to dissolved oxygen in the fusion zone were mainly responsible for the changes in deposit shape observed in experiments. Finally, because oxygen can be introduced into the fusion zone through the feedstock as well as the surrounding atmosphere, these findings elucidate a previously unconsidered aspect of process control during DED fabrication of FGMs.

36 MATERIALS SCIENCE↗
DOE OSTI2020

materialsCloudCompute

materialsCloudCompute (mCC) is a software package for running easily parallelizable materials science theoretical computations on Amazon Web Services (AWS) infrastructure. mCC provides tools to partition out computational problem into smaller subproblems which can be run in parallel, and ensure that each of those subproblems completes successfully. It utilizes the following AWS services: EC2, S3, and RDS. It operates by launch a managing EC2 instance, which can launch worker instances that perform the calculations. The Managing instance tracks the subproblems and ensures that the Worker instances continue to operation, killing and relaunching them if they fail.

Forbes, David↗
DOE OSTI2024

Model-predictive optimal control of ferrofluidic microrobots in three-dimensional space

Ferrofluid microrobots have emerged as promising tools for minimally invasive medical procedures. Their unique properties to navigate complex fluids and reach otherwise inaccessible regions of the human body have enabled new applications in targeted drug delivery, tissue engineering, and diagnostics. Here, this paper proposes a model-predictive controller for the external magnetic manipulation of ferrofluid microrobots in three dimensions (3D). The internal optimization routine of the controller determines appropriate changes in the applied electromagnetic field to minimize the deviation between the actual and desired trajectories of the microrobot. A linear system governing locomotion is derived and used as the equality constraints of the optimization problems associated with the feedback index. In addition to ferrofluid droplets, the controller presented in this work may be applied to other magnetically-pulled microrobots. Several experiments are performed to validate the controller and showcase its ability to adapt to changes in system parameters such as the desired tracking trajectory and the size, orientation, deformation, and velocity of the microrobot. The accuracy of the controller is analyzed for each experiment, and the average error is found to be within 0.25 mm for small velocities. An additional experiment is performed to demonstrate significant improvement over a PID controller that is optimally tuned using Bayesian optimization. The results presented in this paper suggest that the proposed control algorithm could enable new microrobotic capabilities in minimally invasive medical procedures, lab-on-a-chip applications, and microfluidics.

60 APPLIED LIFE SCIENCES↗
NASA NTRS1971

Determination of the charge of relativistic heavy nuclei from emulsion tracks

The number of delta rays with energies between 50 and 150 keV that are produced by heavy nuclei in emulsions is calculated. The Z(2) dependence predicted by the first Born approximation is corrected by a direct calculation of the Mott exact phase-shift scattering cross section. Comparisons are made with corrections predicted by the second Born approximation. When the phase-shift results are applied to the problem of charge identification, corrections of up to 4 units of charge for 1.457-GeV/nucleon nuclei with charge Z = 75 are found.

Morgan, S. H., Jr.↗
NASA NTRS1972

TDRS multimode transponder program. Phase 1: Design

The use of geosynchronous tracking and data relay satellites (TDRS) which can serve both low data rate users at VHF and high data rate users at other frequencies is considered. The effects of radio frequency interference from the earth and of multipath propagation due to reflections from the earth are expected to pose problems for the TDRS system at VHF. Investigations suggest several modulation techniques that offer promise to overcome these problems. This report provides a complete design of a VHF/UHF multimode transponder and its associated ground support equipment. The transponder is designed for installation aboard an aircraft and will demonstrate candidate modulation techniques to provide the required information for the design of an eventual VHF/UHF transponder suitable for installation in a user satellite, capable of operating as part of a TDRS system.

Cnossen, R. S.↗
NASA NTRS1974

Sequential filter design for precision orbit determination and physical constant refinement

Earth-based spacecraft tracking data have historically been processed with classical least squares filtering techniques both for navigation purposes and for physical constant determination. The small, stochastic nongravitational forces acting on the spacecraft are described to motivate the use of sequential estimation as an alternative to the least squares fitting procedures. The stochastic forces are investigated both in terms of their effect on the tracking data and their influence on estimation accuracy. A flexible sequential filter design which leaves the existing trajectory, variational equations, data observable and partial computations undisturbed is described. A detailed filter design is presented that meets the precision demands and flexibility requirements of deep space navigation and of scientific problems.

Curkendall, D. W.↗
NASA NTRS1983

Radio metric orbit determination for the Giotto mission to Comet Halley

An international fleet of five spacecraft will fly past Comet Halley as it travels through the inner solar system in early 1986. This paper discusses orbit determination problems associated with the Giotto spacecraft, sponsored by the European Space Agency. The large number of spin axis precession maneuvers required to maintain the desired spacecraft attitude creates a new kind of radio metric orbit determination problem for this mission. This paper investigates the accuracy with which the Giotto spacecraft orbit can be determined relative to the earth or the sun, and establishes the sensitivity of this accuracy to the selection of the parameters to be estimated, the form of estimator used, the number of tracking stations employed, the length of the data arc, the selection of data types processed, and the levels of various error sources.

Wood, L. J.↗
NASA NTRS1985

Advances and trends in structures and dynamics; Proceedings of the Symposium, Washington, DC, October 22-25, 1984

Among the topics discussed are developments in structural engineering hardware and software, computation for fracture mechanics, trends in numerical analysis and parallel algorithms, mechanics of materials, advances in finite element methods, composite materials and structures, determinations of random motion and dynamic response, optimization theory, automotive tire modeling methods and contact problems, the damping and control of aircraft structures, and advanced structural applications. Specific topics covered include structural design expert systems, the evaluation of finite element system architectures, systolic arrays for finite element analyses, nonlinear finite element computations, hierarchical boundary elements, adaptive substructuring techniques in elastoplastic finite element analyses, automatic tracking of crack propagation, a theory of rate-dependent plasticity, the torsional stability of nonlinear eccentric structures, a computation method for fluid-structure interaction, the seismic analysis of three-dimensional soil-structure interaction, a stress analysis for a composite sandwich panel, toughness criterion identification for unidirectional composite laminates, the modeling of submerged cable dynamics, and damping synthesis for flexible spacecraft structures.

Noor, A. K.↗
DOE OSTI2024

Third-integer Resonant Extraction Regulation System for Mu2e

A third-integer resonant slow extraction system is being developed for Fermilab's Delivery Ring to deliver protons to the upcoming Mu2e experiment. The timescale of the extraction (or spill) duration is 43 milliseconds, which is extremely short and unprecedented. Additionally, the experiment's strict and challenging requirements on the quality of the spill at this time scale has led to the development of a new Spill Regulation System (SRS) design. The SRS primarily consists of three components - slow regulation, fast regulation, and harmonic content suppressor. Contributions to the first two components of the SRS, i.e., Slow Regulation and Fast Regulation subsystems, will be presented in which new adaptive learning algorithm schemes for the slow regulation of the spill -- validated using particle tracking simulations -- shall be described. In addition to these novel methods for the enhancement of the spill regulation system, results of employing Machine Learning in enhancing the performance of the resonant extraction are also presented. At the forefront of applying ML techniques to solve non-linear accelerator control problems, this work includes optimizing the PID gains as well as the replacement of the traditional PID controller using Recurrent Neural Networks and Gated Recurrent Unit (GRU) ML models to achieve efficiencies greater than a PID controller. Cutting-edge on-going Reinforcement Learning efforts, including an actor-critic family of learning algorithms, to regulate the spill rate will be reviewed, as well as present analytical calculations pertaining the transit time of particles in a third-integer resonant extraction. Detailed numerical investigations and validations of such calculations, the model of which could be exported and reliably used in future analytical modeling of any resonant extraction, are discussed.

43 PARTICLE ACCELERATORS↗
DOE OSTI2021

Individual Wave Detection and Tracking within a Rotating Detonation Engine through Computer Vision Object Detection applied to High-Speed Images

Known for their simplistic design and continuous detonation, rotating detonation engines (RDEs) constitute a majority of current pressure gain combustion (PGC) research efforts. Experimental RDE operation times have been continuously extended through the use of rig cooling techniques. As the window of observable behavior is expanded, and as the technology matures toward eventual integration within gas turbines, monitoring techniques must evolve to better match industrial diagnostics. High-speed image analysis techniques prove useful to capture and evaluate the unsteady detonation behavior within the RDE. Traditional image analysis techniques, however, require extensive processing times which prohibit simultaneous monitoring. To better address this problem, a computer vision object detection methodology is proposed to quickly detect individual detonation waves within a single down-axis image. Detonation waves are detected in individual images by the implemented computer vision method You Only Look Once (YOLO) object detection network. In order to detect detonation waves, the network must first be trained using RDE images of interest, for which each required phase of network development is outlined. Detection of waves is improved through proper treatment of the collected image set, variation of Intersection over Union (IoU) and confidence thresholding, and through a parametric study of annotation dimensions. Each detected wave is described by its location and rotational direction, and locations are tracked to calculate wave velocity across each frame, leading to a timestep resolution of 20 µs. Wave velocities are also calculated through a series of frames, leading to a suitable average velocity estimation using as few as 10 frames. Uncertainty analysis accounting for variation in camera framerate, pixel width and annotation centroid locations estimates a total uncertainty of ±4.3% for velocity calculations, using the smallest annotation boxes. This method offers great reductions in processing times, as a step toward real-time monitoring of detonation waves within an RDE. Improving on previous studies, this technique is impartial to wave modes not included in the original training set and calculates wave velocities independent of high-speed pressure data. The ability to isolate waves within predicted bounding boxes will likely facilitate analysis of pixel intensity variation as an estimation of wave strength in future work.

Johnson, Kristyn↗
DOE OSTI2019

Tungsten Alloy Laser Track Cracking Analysis

Tungsten exhibits many favorable properties such as a high melting point and high density. However, the hard and brittle nature of the material makes it difficult to work and machine. Tungsten can be alloyed with other elements to lower the material’s ductile-to-brittle transition temperature, thereby making it more ductile and workable at room temperature. While helpful for conventional manufacturing methods, the alloy poses a problem for additive manufacturing (AM) applications. The lower melting and vaporization point of the solute leads to increased vaporization. This in combination with intense localized heating and rapid cooling that occurs during AM processes creates residual stress in parts that contributes to cracking and increased porosity.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Topological Kondo effect with spinful Majorana fermions

Motivated by the importance of studying topological superconductors beyond the mean-field approximation, we here investigate mesoscopic islands of time-reversal-invariant topological superconductors. We characterize the spectrum in the presence of strong order-parameter fluctuations in the presence of an arbitrary number of Kramers pairs of Majorana edge states and study the effect of coupling the Coulomb blockaded island to external leads. In the case of an odd fermionic parity on the island, we derive an unconventional Kondo Hamiltonian in which metallic leads couple to both topological Majorana degrees of freedom (which keep track of the parity in different leads) and the overall spin 1 2 in the island. For the simplest case of a single wire (two pairs of Majorana edge states), we demonstrate that anisotropies are irrelevant in the weak coupling renormalization group flow. This permits us to solve the Kondo problem in the vicinity of a Toulouse-type point using Abelian bosonization. We demonstrate a residual ground-state entropy of ln ( 2 ) , which is protected by spin-rotation symmetry, but reduced to ln ( 2 ) (as in the spinless topological Kondo effect) by symmetry-breaking perturbations. In the symmetric case, we further demonstrate the simultaneous presence of both Fermi-liquid and non-Fermi-liquid-like thermodynamics (depending on the observable) and derive charge and spin transport signatures of the Coulomb blockaded island. Published by the American Physical Society 2024

Materials Science↗
DOE OSTI2019

Signal Processsing for Sounding Rocket Flights: Campaign No. 2 Results

Sounding rockets provide both a viable and convenient alternative to more costly missile flights with one of the major objectives being to test various types of sensors for monitoring components of high interest as well as developing real-time signal processing techniques. Signal processing, especially in real-time, presents an extreme challenge in this noisy flight environment. The estimation and tracking of modal frequencies from vibrating structures is the an important set of features that can provide information about the components under test; therefore, high resolution multichannel spectral processing is required. In this report we discuss the application of both single/multichannel techniques that can be applied to solve this challenging problem in the case of noisy, uncertain accelerometer measurements. The approach involves the selection of methods capable of producing reliable spectral estimates corresponding to the modal frequencies of a vibrating structure.

42 ENGINEERING↗
NASA NTRS1980

Summary of Aerodynamic Vibration Effects on ALL Turret

The effects of the airborne environment on a pointing and tracking system using a turret external to an aircraft are summarized. The data covered a series of flight tests and a span of seven years. The two major airborne effects were shown to be direct pressure loading of optical elements and vibrations of the entire turret. The direct optical loading problem was minimized by fence designs for the turret.

Merritt, P.↗
NASA NTRS1983

Orbit determination and prediction study for Dynamic Explorer 2

Definitive orbit determination accuracy and orbit prediction accuracy for the Dynamic Explorer-2 (DE-2) are studied using the trajectory determination system for the period within six weeks of spacecraft reentry. Baseline accuracies using standard orbit determination models and methods are established. A promising general technique for improving the orbit determination accuracy of high drag orbits, estimation of random drag variations at perigee passages, is investigated. This technique improved the fit to the tracking data by a factor of five and improved the solution overlap consistency by a factor of two during a period in which the spacecraft perigee altitude was below 200 kilometers. The results of the DE-2 orbit predictions showed that improvement in short term prediction accuracy reduces to the problem of predicting future drag scale factors: the smoothness of the solar 10.7 centimeter flux density suggests that this may be feasible.

Smith, R. L.↗
NASA NTRS1984

The accuracy of altimetric surfaces

Estimates of the shape of the sea surface as determined from satellite altimeters have become of increasing importance in geophysics, geodesy and physical oceanography. The most effective error reduction procedures used in producing these surfaces have been some version of a crossing-arc analysis. The problem with this procedure is the absence of an easy means of evaluating the noise structure of the final result. By recasting the problem as one of objective mapping (optimal estimation) the error reduction is optimized and an explicit estimate is obtained of the wave-number structure of the final altimetric surface. Examples, suitable to a small computer, have been generated to show that the error reduction along the sub-satellite tracks is very great, with most of the residual lying in long wavelengths.

Wunsch, C.↗