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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 667 records · Page 37
All sourcesNASA NTRSDOE OSTI
NASA NTRS1999

Unlocking the Keys to Vortex/Flame Interactions in Turbulent Gas-Jet Diffusion Flames--Dynamic Behavior Explored on the Space Shuttle

Most combustion processes in industrial applications (e.g., furnaces and engines) and in nature (e.g., forest fires) are turbulent. A better understanding of turbulent combustion could lead to improved combustor design, with enhanced efficiency and reduced emissions. Despite its importance, turbulent combustion is poorly understood because of its complexity. The rapidly changing and random behavior of such flames currently prevents detailed analysis, whether experimentally or computationally. However, it is possible to learn about the fundamental behavior of turbulent flames by exploring the controlled interaction of steady laminar flames and artificially induced flow vortices. These interactions are an inherent part of turbulent flames, and understanding them is essential to the characterization of turbulent combustion. Well-controlled and defined experiments of vortex interaction with laminar flames are not possible in normal gravity because of the interference of buoyancy- (i.e., gravity) induced vortices. Therefore, a joint microgravity study was established by researchers from the Science and Technology Development Corp. and the NASA Lewis Research Center. The experimental study culminated in the conduct of the Turbulent Gas-Jet Diffusion Flames (TGDF) Experiment on the STS-87 space shuttle mission in November 1997. The fully automated hardware, shown in photo, was designed and built at Lewis. During the mission, the experiment was housed in a Get Away Special (GAS) canister in the cargo bay.

Stocker, Dennis P.↗
DOE OSTI2025

AI-Assisted Conceptual Development of a Pre-Geometric Cosmological Model - An Exercise in AI-Assisted Conceptual Framework Generation, Paper III: Cosmological Structure and Predictions

This paper develops the cosmological consequences of the replication-driven cosmogenesis framework introduced in Paper I and the emergent geometric structure established in Paper II. After the replication epoch freezes out, the coherent sector occupies a finite spectral band and contains a population of excited states. The relaxation of these excited coherent configurations does not produce coherent radiation; instead, all released energy flows into the incoherent substrate, where the randomizer acts as a rapid phase-scrambling mechanism. This process generates an effectively thermal radiation bath, providing a natural reheating mechanism that requires neither inflaton oscillations nor scalar-field potentials, and can be contrasted with standard scenarios of nonperturbative reheating dynamics. Subsequent symmetry-breaking transitions in the coherent vacuum inject additional radiation, yielding a multi-stage thermal history with well-defined energy transfers. We derive the effective equations of state for each component—the cosmological vacuum, the coherent vacuum, and the radiation bath—and show how their interplay produces an FRW-like expansion. The discrete sequence of coherent-state relaxations imprints a distinctive multi-peaked stochastic gravitational-wave background, whose spectral structure reflects the underlying hierarchy of coherent frequencies. Potential observational signatures in the LISA and mid-band frequency ranges are highlighted, providing concrete avenues to test this replication-based cosmological framework in the context of standard cosmological gravitational-wave backgrounds and LISA-oriented forecasts.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1973

Programmable random interval generator

Random pulse generator can supply constant-amplitude randomly distributed pulses with average rate ranging from a few counts per second to more than one million counts per second. Generator requires no high-voltage power supply or any special thermal cooling apparatus. Device is uniquely versatile and provides wide dynamic range of operation.

Lindsey, R. S., Jr.↗
NASA NTRS1973

Statistical determination of space shuttle component dynamic magnification factors

A method is presented of obtaining vibration design loads for components and brackets. Dynamic Magnification Factors from applicable Saturn/Apollo qualification, reliability, and vibroacoustic tests have been statistically formulated into design nomographs. These design nomographs have been developed for different component and bracket types, mounted on backup structure or rigidly mounted and excited by sinusoidal or random inputs. Typical nomographs are shown.

Lehner, F.↗
NASA NTRS1991

Fractal dynamics of bioconvective patterns

Biologically generated cellular patterns, sometimes called bioconvective patterns, are found to cluster into aggregates which follow fractal growth dynamics akin to diffusion-limited aggregation (DLA) models. The pattern formed is self-similar with fractal dimension of 1.66 +/-0.038. Bioconvective DLA branching results from thermal roughening which shifts the balance between ordering viscous forces and disordering cell motility and random diffusion. The phase diagram for pattern morphology includes DLA, boundary spokes, random clusters, and reverse clusters.

Noever, David A.↗
NASA NTRS1989

Comet ejection and dynamics of nonspherical dust particles and meteoroids

This paper generalizes the formalism for calculating the ejection velocity of meteoroids and dust from comets and the forces to which such objects are subject in interplanetary space, including the dust tail of comets. It is found that spheres have the smallest cross section of any geometrical figures of the same valume averaged over random orientations, so for a fixed volume and mass, both the ejection velocity and beta reaches a minimum for bodies of spherical shapes. Flakes in random orientation are ejected near 70 percent of the highest ejection velocity for any orientation. Needles in random orientation escape a comet at nearly 90 percent of their maximum velocities. Randomly oriented cylinders of finite thickness escape at lower velocities that are slightly closer to their maximum velocities. The average beta acting on spin-aligned, perfectly absorbing needles is more than half that acting on a sphere of the same material and radius.

Gustafson, Bo A. S.↗
DOE OSTI2026

Data and scripts associated with a manuscript modeling microbial regulation of priming effects

This data package is associated with the publication “Modeling Microbial Regulatory Feedback in Organic Matter Decomposition Identifies Copiotrophic Traits as Key Drivers of Positive Priming” published as a preprint on BioRXiv by Ahamed et al. (2026); https://doi.org/10.1101/2024.08.11.607483. The package contains MATLAB scripts and saved simulation outputs used to implement a cybernetic model of microbial regulation during complex organic matter (OM) decomposition governing priming effects. It includes models of (i) single microbial functional groups (copiotrophic or oligotrophic degraders) and (ii) binary consortia composed of degraders and non-degraders with contrasting or common growth traits. Simulation results were generated using Monte Carlo analyses, with randomized key model parameters across a range of environmental mixing fractions of complex and labile OM. The dataset was created to provide a transparent and reusable computational framework for systematically exploring how microbial growth traits, metabolic regulation, and community composition influence OM decomposition dynamics and priming effects. For details on how to navigate data packages generated by this project, see https://data.ess-dive.lbl.gov/portals/PNNLRiverCorridorSFA/About. In addition to a readme, this data package also includes a file-level metadata (FLMD) file that describes each file and a data dictionary (DD) that describes the variable definitions. This package includes: (1) annotated MATLAB code implementing the system of ordinary differential equations and cybernetic control laws; (2) saved output files containing data (e.g., biomass, substrates, enzyme levels, priming metrics); and (3) scripts for processing saved outputs and regenerating figures. Specifically, the data package contains three main MATLAB scripts: runPrimingModel.m, runPlotData.m, and runPlotSuppFigS1.m, along with this readme and supporting documentation. Users should begin with runPrimingModel.m, which contains the annotated code implementing the system of ordinary differential equations and cybernetic control laws. This script runs the Monte Carlo simulations of microbial OM decomposition and allows users to modify microbial trait definitions, adjust parameter distributions, or define new community configurations. Simulation outputs are automatically saved as .mat files in the folder named SavedData, which stores all pre-generated results included in this package. The second script, runPlotData.m, reads files from the SavedData folder and processes them to regenerate the figures presented in the manuscript. The third script, runPlotSuppFigS1.m, specifically generates Figure S1 in the Supplementary Material of the manuscript. The package also includes the aforementioned files in non-proprietary .txt format. If users intend to use them, they should first save the files in their respective .m or .mat formats prior to execution in MATLAB.

Biomass concentration↗
NASA NTRS1987

The SCOLE design challenge

An NASA program is discussed which was initiated to make direct comparisons of control laws for, first, a mathematical problem, than an experimental test article is being assembled under the cognizance of the Spacecraft Control Branch. The physical apparatus will consist of a softly supported dynamic model of an antenna attached to the Shuttle by a flexible beam. The control objective will include the task of directing the line of sight of the Shuttle/antenna configuration toward a fixed target, under conditions of noisy data, limited control authority and random disturbances. A workshop will be planned to discuss and compare results of the design challange.

Taylor, Larry↗
NASA NTRS2000

Sputtering Erosion in the Ion Thruster

During the first phase of this research, the sputtering yields of molybdenum by low energy (100 eV and higher) xenon ions were measured by using the methods of secondary neutral mass spectrometry (SNMS) and Rutherford backscattering spectrometry (RBS). However, the measured sputtering yields were found to be far too low to explain the sputtering erosions observed in the long-duration tests of ion thrusters. The only difference between the sputtering yield measurement experiments and the ion thruster tests was that the later are conducted at high ion fluences. Hence, a study was initiated to investigate if any linkage exists between high ion fluence and an enhanced sputtering yield. The objective of this research is to gain an understanding of the causes of the discrepancies between the sputtering rates of molybdenum grids in an ion thruster and those measured from our experiments. We are developing a molecular dynamics simulation technique for studying low-energy xenon ion interactions with molybdenum. It is difficult to determine collision sequences analytically for primary ions below the 200 eV energy range where the ion energy is too low to be able to employ a random cascade model with confidence and it is too high to have to consider only single collision at or near the surface. At these low energies, the range of primary ions is about 1 to 2 nm from the surface and it takes less than 4 collisions on the average to get an ion to degrade to such an energy that it can no longer migrate. The fine details of atomic motion during the sputtering process are revealed through computer simulation schemes. By using an appropriate interatomic potential, the positions and velocities of the incident ion together with a sufficient number of target atoms are determined in small time steps. Hence, it allows one to study the evolution of damages in the target and its effect on the sputtering yield. We are at the preliminary stages of setting up the simulation program.

Ray, Pradosh K.↗
NASA NTRS2003

Mitigating Upsets in SRAM-Based FPGAs from the Xilinx Virtex 2 Family

Static random access memory (SRAM) upset rates in field programmable gate arrays (FPGAs) from the Xilinx Virtex 2 family have been tested for radiation effects on configuration memory, block RAM and the power-on-reset (POR) and SelectMAP single event functional interrupts (SEFIs). Dynamic testing has shown the effectiveness and value of Triple Module Redundancy (TMR) and partial reconfiguration when used in conjunction. Continuing dynamic testing for more complex designs and other Virtex 2 capabilities (i.e., I/O standards, digital clock managers (DCM), etc.) is scheduled.

SEE testing↗
NASA NTRS2010

Broken Ergodicity in Ideal, Homogeneous, Incompressible Turbulence

We discuss the statistical mechanics of numerical models of ideal homogeneous, incompressible turbulence and their relevance for dissipative fluids and magnetofluids. These numerical models are based on Fourier series and the relevant statistical theory predicts that Fourier coefficients of fluid velocity and magnetic fields (if present) are zero-mean random variables. However, numerical simulations clearly show that certain coefficients have a non-zero mean value that can be very large compared to the associated standard deviation. We explain this phenomena in terms of broken ergodicity', which is defined to occur when dynamical behavior does not match ensemble predictions on very long time-scales. We review the theoretical basis of broken ergodicity, apply it to 2-D and 3-D fluid and magnetohydrodynamic simulations of homogeneous turbulence, and show new results from simulations using GPU (graphical processing unit) computers.

Morin, Lee↗
NASA NTRS1973

A model based technique for the design of flight directors

A new technique for designing flight directors is discussed. This technique uses the optimal-control pilot/vehicle model to determine the appropriate control strategy. The dynamics of this control strategy are then incorporated into the director control laws, thereby enabling the pilot to operate at a significantly lower workload. A preliminary design of a control director for maintaining a STOL vehicle on the approach path in the presence of random air turbulence is evaluated. By selecting model parameters in terms of allowable path deviations and pilot workload levels, a set of director laws is achieved which allows improved system performance at reduced workload levels. The pilot acts essentially as a proportional controller with regard to the director signals, and control motions are compatible with those appropriate to status-only displays.

Levison, W. H.↗
NASA NTRS1983

The wake model for azimuthal brightness variations in Saturn's A-ring

A dynamical model offering a possible explanation for azimuthal brightness variations in Saturn's ring A is considered. The orbits of ring particles encountering a massive moonlet (radius = about 100 m) are integrated numerically. It is seen that a density wake is produced if the random velocities of the ring particles are much smaller than 1 cm/s.

Karttunen, H.↗
NASA NTRS1988

A mathematical problem and a Spacecraft Control Laboratory Experiment (SCOLE) used to evaluate control laws for flexible spacecraft. NASA/IEEE design challenge

The problen of controlling large, flexible space systems has been evaluated using computer simulation. In several cases, ground experiments have also been used to validate system performance under more realistic conditions. There remains a need, however, to test additional control laws for flexible spacecraft and to directly compare competing design techniques. A program is discussed which has been initiated to make direct comparisons of control laws for, first, a mathematical problem, then and experimental test article being assembled under the cognizance of the Spacecraft Control Branch at the NASA Langley Research Center with the advice and counsel of the IEEE Subcommittee on Large Space Structures. The physical apparatus will consist of a softly supported dynamic model of an antenna attached to the Shuttle by a flexible beam. The control objective will include the task of directing the line-of-sight of the Shuttle antenna configuration toward a fixed target, under conditions of noisy data, control authority and random disturbances.

Taylor, Lawrence W., Jr.↗
NASA NTRS1984

A mathematical problem and a Spacecraft Control Laboratory Experiment (SCOLE) used to evaluate control laws for flexible spacecraft. NASA/IEEE design challenge

Discussed here is a NASA program which was initiated to make direct comparisons of control laws for a mathematical problem. An experimental test item is being assembled under the cognizance of the Spacecraft Control Branch at Langley Research Center. The physical apparatus will consist of a softly supported dynamic model of an antenna attached to the Space Shuttle by a flexible beam. The control objective will include the task of directing the line of sight of the Shuttle/antenna configuration toward a fixed target, under conditions of noisy data, limited control authority, and random disturbances.

Taylor, Lawrence W., Jr.↗
NASA NTRS1994

Physical Models of Cognition

This paper presents and discusses physical models for simulating some aspects of neural intelligence, and, in particular, the process of cognition. The main departure from the classical approach here is in utilization of a terminal version of classical dynamics introduced by the author earlier. Based upon violations of the Lipschitz condition at equilibrium points, terminal dynamics attains two new fundamental properties: it is spontaneous and nondeterministic. Special attention is focused on terminal neurodynamics as a particular architecture of terminal dynamics which is suitable for modeling of information flows. Terminal neurodynamics possesses a well-organized probabilistic structure which can be analytically predicted, prescribed, and controlled, and therefore which presents a powerful tool for modeling real-life uncertainties. Two basic phenomena associated with random behavior of neurodynamic solutions are exploited. The first one is a stochastic attractor ; a stable stationary stochastic process to which random solutions of a closed system converge. As a model of the cognition process, a stochastic attractor can be viewed as a universal tool for generalization and formation of classes of patterns. The concept of stochastic attractor is applied to model a collective brain paradigm explaining coordination between simple units of intelligence which perform a collective task without direct exchange of information. The second fundamental phenomenon discussed is terminal chaos which occurs in open systems. Applications of terminal chaos to information fusion as well as to explanation and modeling of coordination among neurons in biological systems are discussed. It should be emphasized that all the models of terminal neurodynamics are implementable in analog devices, which means that all the cognition processes discussed in the paper are reducible to the laws of Newtonian mechanics.

Zak, Michail↗
NASA NTRS2008

The Formation of Filament Threads in a Sheared Magnetic Field

This slide presentation reviews the mechanism that form the filament threads in the sheared magnetic field of the solar photosphere. There are observations of the filaments, a chart showing the magnetic field configuration for the filaments, and charts that show the thermal instability, and thermal conduction. Discussion of the question "How is it possible for a magnetic field to inhibit heat flow in a coronal plasma without simultaneously restricting the mass flow required for the growth of density condensations?" is reviewed. Equations that are used in the model are given. The characteristics of dynamic condensations are reviewed. There are charts that show the density perturbations for principal dynamic condensation mode and 1st harmonic. The characteristics of the kinematic condensations are also discussed. The types of perturbations that were studied are: (1) Generic perturbation with T(sub 0) < T(sub c) (2) Generic perturbation with T(sub 0) = T(sub c) (3) Random perturbation with T(sub 0)< T(sub c).

condensational instability↗
DOE OSTI2026

Semi-Analytical Hierarchical Bayesian Inference of Nonlinear Model Structure in Stochastic Dynamics: Applied to Compartmental Models of Infectious Diseases

A Bayesian computational framework for parsimonious inference in stochastic nonlinear dynamical systems is presented. This framework enables the concurrent estimation of system states, time-varying parameters, time-invariant parameters, and the optimal sparsity structure of the model parameters. Because differential equation-based models are often simplified mechanistic or phenomenological representations, robust inference from noisy measurement data requires explicit treatment of model error and uncertainty. Model error and time-varying parameters can be represented as random processes, enabling inference while making minimal assumptions about the underlying sources of discrepancy and variability. Adopting stochastic differential equation representations affords the model significant flexibility, but can also render it susceptible to overfitting during statistical inversion, where the inferred model may track noise rather than the underlying signal. To alleviate the effects of overfitting and to enable the discovery of the optimal sparse representation of the time-invariant parameters, a Bayesian sparse learning algorithm is embedded within the framework. This sparse learning framework adopts an approximate hierarchical Bayesian setting defined by a series of semi-analytical expressions. The model structure inference framework is validated using a stochastic compartmental model for tracking and forecasting active cases of an infectious disease. Compartmental models describe population-level infectious disease dynamics through interactions among population fractions grouped by disease state. Mathematically, such models consist of a system of coupled ordinary differential equations. This example adopts an expressive compartmental model that includes multiple possible interactions between disease states, motivated by early uncertainty surrounding COVID-19 reinfection dynamics and their implications for long-term epidemic forecasting. The sparse learning exercise permits the inference of a priori unknown epidemiological dynamics from simulated public health data, discovering the nested compartmental model that optimizes the trade-off between average data-fit and model complexity. It is shown that inducing sparsity among the model parameters eliminates redundant interactions between compartments, equivalently revealing the optimal coupling structure between differential equations.

97 MATHEMATICS AND COMPUTING↗