Search NASA⌕ Search

SEARCH · Search NASA

Results for “random processes”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,531 records · Page 85
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Continuum of quantum fluctuations in a three-dimensional S=1 Heisenberg magnet

Conventional crystalline magnets are characterized by symmetry breaking and normal modes of excitation called magnons, with quantized angular momentum $\hbar$. Neutron scattering correspondingly features extra magnetic Bragg diffraction at low temperatures and dispersive inelastic scattering associated with single magnon creation and annihilation. Exceptions are anticipated in so-called quantum spin liquids, as exemplified by the one-dimensional spin-1/2 chain, which has no magnetic order and where magnons accordingly fractionalize into spinons with angular momentum $\hbar$/2. This is spectacularly revealed by a continuum of inelastic neutron scattering associated with two-spinon processes. Here, we report evidence for these key features of a quantum spin liquid in the three-dimensional antiferromagnet NaCaNi 2 F 7 . We show that despite the complication of random Na 1+ –Ca 2+ charge disorder, NaCaNi 2 F 7 is an almost ideal realization of the spin-1 antiferromagnetic Heisenberg model on a pyrochlore lattice. Magnetic Bragg diffraction is absent and 90% of the neutron spectral weight forms a continuum of magnetic scattering with low-energy pinch points, indicating NaCaNi 2 F 7 is in a Coulomb-like phase. Our results demonstrate that disorder can act to freeze only the lowest-energy magnetic degrees of freedom; at higher energies, a magnetic excitation continuum characteristic of fractionalized excitations persists.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2026

Efficient many-jet event generation with flow matching

We apply for the first time, to the best of our knowledge, the flow matching method to the problem of phase-space sampling for event generation in high-energy collider physics. By training the model to remap the random numbers used to generate the momenta and helicities of the scattering matrix elements as implemented in the portable partonic event generator pepper, we find substantial efficiency improvements in the studied processes. We focus our study on the highest final-state multiplicities in Drell-Yan and top-antitop pair production used in simulated samples for the Large Hadron Collider, which computationally are the most relevant ones. We find that the unweighting efficiencies improve by factors of 184 and 25, respectively, when compared to the standard approach of using a vegas-based optimization. We also compare continuous normalizing flows trained with flow matching against the previously studied normalizing flows based on coupling layers and find that the former leads to better results, faster training and a better scaling behavior across the studied multiplicity range, while the latter evaluate faster. When combining the advantages of both methods using the regflow approach, we find parton-level unweighted event generation walltime gains of about a factor of 10 at the highest final-state multiplicities.

Bothmann, E. [CERN; Gottingen U.] (ORCID:000000016↗
DOE OSTI2022

PowerNet: Multi-agent Deep Reinforcement Learning for Scalable Powergrid Control

This paper develops an efficient multi-agent deep reinforcement learning algorithm for cooperative controls in powergrids. Specifically, we consider the decentralized inverter-based secondary voltage control problem in distributed generators (DGs), which is first formulated as a cooperative multi-agent reinforcement learning (MARL) problem. We then propose a novel on-policy MARL algorithm, PowerNet, in which each agent (DG) learns a control policy based on (sub-)global reward but local states and encoded communication messages from its neighbors. Motivated by the fact that a local control from one agent has limited impact on agents distant from it, we exploit a novel spatial discount factor to reduce the effect from remote agents, to expedite the training process and improve scalability. Furthermore, a differentiable, learning-based communication protocol is employed to foster the collaborations among neighboring agents. In addition, to mitigate the effects of system uncertainty and random noise introduced during on-policy learning, we utilize an action smoothing factor to stabilize the policy execution. To facilitate training and evaluation, we develop PGSim, an efficient, high-fidelity powergrid simulation platform. Here, experimental results in two microgrid setups show that the developed PowerNet outperforms the conventional model-based control method, as well as several state-of-the-art MARL algorithms. The decentralized learning scheme and high sample efficiency also make it viable to large-scale power grids.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Random Quantum Circuits

Quantum circuits—built from local unitary gates and local measurements—are a new playground for quantum many-body physics and a tractable setting to explore universal collective phenomena far from equilibrium. These models have shed light on longstanding questions about thermalization and chaos, and on the underlying universal dynamics of quantum information and entanglement. In addition, such models generate new sets of questions and give rise to phenomena with no traditional analog, such as dynamical phase transitions in quantum systems that are monitored by an external observer. Quantum circuit dynamics is also topical in view of experimental progress in building digital quantum simulators that allow control of precisely these ingredients. Randomness in the circuit elements allows a high level of theoretical control, with a key theme being mappings between real-time quantum dynamics and effective classical lattice models or dynamical processes. Many of the universal phenomena that can be identified in this tractable setting apply to much wider classes of more structured many-body dynamics.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2022

Hybrid AI-ML and FE-based Digital Twin Predictive Modeling Framework for a PWR Coolant System Components: Updates on Multi-Time-Series-3D-Location Dependent Usages Factor Prediction

The long-term operation (LTO) of nuclear power plants (NPP) beyond their original design life of 40 years can lead to more material damage associated with cyclic fatigue under thermal-mechanical loading cycles and associated long-term exposure of reactor material to the deleterious reactor-coolant environments. However, under this LTO condition, the reactor components can still safely operate but may require more frequent Nondestructive Evaluation (NDE) of reactor components. Requiring frequent NDE inspections may lead to frequent NPP shutdowns which can lead to power outages and additional NDE inspection cost-related economic loss. The economic loss can be minimized by reducing uncertainty in life estimation of safety-critical pressure boundary components and by implementing a more digital approach such as using upcoming digital-twin (DT) technology for predicting the structural states (e.g., time and location dependent inside/outside thickness temperature, stress, strain, plastic deformation, etc.) and associated fatigue life of a component in real time. The DT framework is based on limited experimental data, Artificial-intelligence (AI)-Machine-Learning (ML) and multiphysics-computationalmechanics such as finite element- (FE) based models. Given the real-time thermal-hydraulic process measurements from several existing plant sensors, the overall goal of the DT framework is to predict the cumulative usages factors or equivalent fatigue lives in real time and at any random 3D location of the components. This includes inaccessible locations such as inside the thickness or location of a component. This prediction can be at thousands to millions of 3D point clouds or locations like conventional FE-based models, but without running an FE model in real time.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
NASA NTRS1975

Use of LANDSAT imagery for wildlife habitat mapping in northeast and east central Alaska

The author has identified the following significant results. Two scenes were analyzed by applying an iterative cluster analysis to a 2% random data sample and then using the resulting clusters as a training set basis for maximum likelihood classification. Twenty-six and twenty-seven categorical classes, respectively resulted from this process. The majority of classes in each case were quite specific vegetation types; each of these types has specific value as moose habitat.

Lent, P. C.↗
NASA NTRS1978

Mercurian global tectonics - A consequence of tidal despinning

The surface of Mercury exhibits a global tectonic system consisting of an ancient set of NE and NW tending lineaments and a younger set of planimetrically arcuate escarpments interpreted as thrust of high-angle reverse faults. The trends, distribution, and age relations of these tectonic features can be explained by a combination of tidal despinning and global contraction of the planet. In our model, early tidal despinning resulted in conjugate shear fractures trending roughly N60 deg E and N60 deg W which were subsequently modified by a variety of surface processes to produce the presently visible set of lineaments. Continued despinning plus global contraction produced thrust faults with roughly north-south trends. Final contraction may have postdated despinning and produced randomly oriented thrust faults. All of these events predated the formation of Caloris basin, because basin-associated deposits blanket both lineaments and arcuate thrust faults.

Melosh, H. J.↗
NASA NTRS1983

A theory of Jovian decameter radiation

A theory of the Jovian decameter radiation is presented based on the assumed existence of beams of energetic electrons in the inner Jovian magnetosphere. Beam-like electron distributions are shown to be unstable to the growth of both upper hybrid and lower hybrid electrostatic waves. The upconversion of these waves to fast extraordinary mode electromagnetic radiation is calculated by using a fluid model. Two possibilities are considered. First, a random phase approximation is made which leads to a very conservative estimate of intensity that can be expected in decameter radiation. The alternative possibility is also considered, viz, that the upconversion process is coherent. A comparison of both processes suggests that an incoherent interaction may be adequate to account for the observed intensity of decametric radiation, except perhaps near the peak of the spectrum (8 MHz). The coherent process is intrinsically more efficient and can easily produce the observed intensity near 8 MHz if only 0.01% of the energy in the beam is converted to electrostatic energy.

Goldstein, M. L.↗
NASA NTRS1984

SARSAT 406 MHz system technical evaluation

The location accuracy, access to spacecraft, uplink margin, and interference problems of the COSPAS-SARSAT system are reviewed. Over 90% of positions are accurate to within 5 km, in local mode, slightly worse in global mode. The random access parameters of SARSAT provide for the location of up to 90 beacons with a uniform distribution in the satellite visibility circle (2600 km radius). The ratio of messages correctly processed on board to messages transmitted to the satellite is 0.8, increasing as number of beacons decreases. Interference, particularly over western Europe and the United States degrades performance, but sources can be located.

Goudy, P.↗
NASA NTRS2003

Columbia Accident Investigation Board Report

The Columbia Accident Investigation Board's independent investigation into the tragic February 1, 2003, loss of the Space Shuttle Columbia and its seven-member crew lasted nearly seven months and involved 13 Board members, approximately 120 Board investigators, and thousands of NASA and support personnel. Because the events that initiated the accident were not apparent for some time, the investigation's depth and breadth were unprecedented in NASA history. Further, the Board determined early in the investigation that it intended to put this accident into context. We considered it unlikely that the accident was a random event; rather, it was likely related in some degree to NASA's budgets, history, and program culture, as well as to the politics, compromises, and changing priorities of the democratic process. We are convinced that the management practices overseeing the Space Shuttle Program were as much a cause of the accident as the foam that struck the left wing. The Board was also influenced by discussions with members of Congress, who suggested that this nation needed a broad examination of NASA's Human Space Flight Program, rather than just an investigation into what physical fault caused Columbia to break up during re-entry. Findings and recommendations are in the relevant chapters and all recommendations are compiled in Chapter 11. Volume I is organized into four parts: The Accident; Why the Accident Occurred; A Look Ahead; and various appendices. To put this accident in context, Parts One and Two begin with histories, after which the accident is described and then analyzed, leading to findings and recommendations. Part Three contains the Board's views on what is needed to improve the safety of our voyage into space. Part Four is reference material. In addition to this first volume, there will be subsequent volumes that contain technical reports generated by the Columbia Accident Investigation Board and NASA, as well as volumes containing reference documentation and other related material.

Gehman, Harold W., Jr.↗
NASA NTRS2010

Design Considerations for Human Rating of Liquid Rocket Engines

I.Human-rating is specific to each engine; a. Context of program/project must be understood. b. Engine cannot be discussed independently from vehicle and mission. II. Utilize a logical combination of design, manufacturing, and test approaches a. Design 1) It is crucial to know the potential ways a system can fail, and how a failure can propagate; 2) Fault avoidance, fault tolerance, DFMR, caution and warning all have roles to play. b. Manufacturing and Assembly; 1) As-built vs. as-designed; 2) Review procedures for assembly and maintenance periodically; and 3) Keep personnel trained and certified. c. There is no substitute for test: 1) Analytical tools are constantly advancing, but still need test data for anchoring assumptions; 2) Demonstrate robustness and explore sensitivities; 3) Ideally, flight will be encompassed by ground test experience. III. Consistency and repeatability is key in production a. Maintain robust processes and procedures for inspection and quality control based upon development and qualification experience; b. Establish methods to "spot check" quality and consistency in parts: 1) Dedicated ground test engines; 2) Random components pulled from the line/lot to go through "enhanced" testing.

Parkinson, Douglas↗
NASA NTRS2009

Statistical Prediction of Solar Particle Event Frequency Based on the Measurements of Recent Solar Cycles for Acute Radiation Risk Analysis

Large solar particle events (SPEs) present significant acute radiation risks to the crew members during extra-vehicular activities (EVAs) or in lightly shielded space vehicles for space missions beyond the protection of the Earth's magnetic field. Acute radiation sickness (ARS) can impair performance and result in failure of the mission. Improved forecasting capability and/or early-warning systems and proper shielding solutions are required to stay within NASA's short-term dose limits. Exactly how to make use of observations of SPEs for predicting occurrence and size is a great challenge, because SPE occurrences themselves are random in nature even though the expected frequency of SPEs is strongly influenced by the time position within the solar activity cycle. Therefore, we developed a probabilistic model approach, where a cumulative expected occurrence curve of SPEs for a typical solar cycle was formed from a non-homogeneous Poisson process model fitted to a database of proton fluence measurements of SPEs that occurred during the past 5 solar cycles (19 - 23) and those of large SPEs identified from impulsive nitrate enhancements in polar ice. From the fitted model, the expected frequency of SPEs was estimated at any given proton fluence threshold (Phi(sub E)) with energy (E) >30 MeV during a defined space mission period. Corresponding Phi(sub E) (E=30, 60, and 100 MeV) fluence distributions were simulated with a random draw from a gamma distribution, and applied for SPE ARS risk analysis for a specific mission period. It has been found that the accurate prediction of deep-seated organ doses was more precisely predicted at high energies, Phi(sub 100), than at lower energies such as Phi(sub 30) or Phi(sub 60), because of the high penetration depth of high energy protons. Estimates of ARS are then described for 90th and 95th percentile events for several mission lengths and for several likely organ dose-rates. The ability to accurately measure high energy protons (50-300 MeV) in real-time is shown to be a crucial issue for crew protection.

Myung-Hee, Y. Kim↗
DOE OSTI2022

Comprehensive Analysis of the Neutrino Process in Core-collapsing Supernovae

We investigate the neutrino flavor change effects due to neutrino self-interaction and shock wave propagation, as well as the matter effects on the neutrino process in core-collapsing supernovae (CCSNe). For the hydrodynamics, we use two models: a simple thermal bomb model and a specified hydrodynamics model for SN1987A. For the presupernova model, we take an updated model, adjusted to explain SN1987A, which employs recent developments in the (n, γ) reaction rates for nuclei near the stability line (A ~ 100). As for the neutrino luminosity, we adopt two different models: equivalent neutrino luminosity and nonequivalent luminosity models. The latter is taken from a synthetic analysis of CCSN simulation data, which quantitatively presented the results obtained by various neutrino transport models. Relevant neutrino-induced reaction rates are calculated using a shell model for light nuclei and a quasiparticle random phase approximation model for heavy nuclei. For each model, we present abundances of the light nuclei ( 7 Li, 7 Be, 11 B, and 11 C) and the heavy nuclei ( 92 Nb, 98 Tc, 138 La, and 180 Ta) produced by the neutrino process. The light nuclei abundances turn out to be sensitive to the Mikheyev–Smirnov–Wolfenstein (MSW) region around O-Ne-Mg layer while the heavy nuclei are mainly produced prior to the MSW region. Through detailed analyses, we find that neutrino self-interaction becomes a key ingredient, in addition to the MSW effect, for understanding the neutrino process and the relevant nuclear abundances. The normal mass hierarchy is shown to be more compatible with the meteorite data. The main nuclear reactions for each nucleus are also investigated in detail.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Model validation and error attribution for a drifting qubit

Qubit performance is often reported in terms of a variety of single-value metrics, each providing a facet of the underlying noise mechanism limiting performance. However, the value of these metrics may drift over long timescales, and reporting a single number for qubit performance fails to account for the low-frequency noise processes that give rise to this drift. Here, in this work, we demonstrate how we can use the distribution of these values to validate or invalidate candidate noise models. We focus on the case of randomized benchmarking (RB), where typically a single error rate is reported but this error rate can drift over time when multiple passes of RB are performed. We show that using a statistical test as simple as the Kolmogorov-Smirnov statistic on the distribution of RB error rates can be used to rule out noise models, assuming the experiment is performed over a long enough time interval to capture relevant low frequency noise. With confidence in a noise model, we show how care must be exercised when performing error attribution using the distribution of drifting RB error rate.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2023

Intensity of sample processing methods impacts wastewater SARS-CoV-2 whole genome amplicon sequencing outcomes

Wastewater SARS-CoV-2 surveillance has been deployed since the beginning of the COVID-19 pandemic to monitor the dynamics in virus burden in local communities. Genomic surveillance of SARS-CoV-2 in wastewater, particularly efforts aimed at whole genome sequencing for variant tracking and identification, are still challenging due to low target concentration, complex microbial and chemical background, and lack of robust nucleic acid recovery experimental procedures. The intrinsic sample limitations are inherent to wastewater and are thus unavoidable. Here, we use a statistical approach that couples correlation analyses to a random forest-based machine learning algorithm to evaluate potentially important factors associated with wastewater SARS-CoV-2 whole genome amplicon sequencing outcomes, with a specific focus on the breadth of genome coverage. We collected 182 composite and grab wastewater samples from the Chicago area between November 2020 to October 2021. Samples were processed using a mixture of processing methods reflecting different homogenization intensities (HA + Zymo beads, HA + glass beads, and Nanotrap), and were sequenced using one of the two library preparation kits (the Illumina COVIDseq kit and the QIAseq DIRECT kit). Technical factors evaluated using statistical and machine learning approaches include sample types, certain sample intrinsic features, and processing and sequencing methods. The results suggested that sample processing methods could be a predominant factor affecting sequencing outcomes, and library preparation kits was considered a minor factor. Finally, a synthetic SARS-CoV-2 RNA spike-in experiment was performed to validate the impact from processing methods and suggested that the intensity of the processing methods could lead to different RNA fragmentation

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Reconstructing parent microstructures in martensitic and pearlitic Ti-Cu

Evaluating the microstructural evolution of parent phases has long been a challenge in metals with a partial or complete solid state transformation. Most parent microstructure evolution has to be inferred from the product microstructure, with some information permanently lost. Parent microstructure reconstructions relying on orientation relationships and EBSD data are a useful tool to overcome this challenge, though much background knowledge is required to do so. Here, this work introduces a reconstruction process for a eutectoid composition Ti-Cu binary alloy to evaluate the high temperature β-Ti phase from martensitic and pearlitic product microstructures. Martensitic microstructures were accurately reconstructed, enabling elucidation of β-Ti grain size and texture, and the employed script included for scientific reference. Pearlitic microstructures did not reconstruct effectively with the current process. However, new insight into the interfacial crystallographic orientations of pearlitic Ti-Cu microstructures was gleaned via this analysis, and future investigations of interest are discussed accordingly. Ultimately, these findings demonstrate tools widely implemented on conventional titanium and ferrous alloys can also be applied to understand parent microstructures in Ti-Cu and other alloys of emerging interest. This is especially of use as new manufacturing processes for such materials require understanding how parent phase microstructures respond to new, novel material processing such as AM.

36 MATERIALS SCIENCE↗
NASA NTRS2009

Extending Newtonian Dynamics to Include Stochastic Processes

A paper presents further results of continuing research reported in several previous NASA Tech Briefs articles, the two most recent being Stochastic Representations of Chaos Using Terminal Attractors (NPO-41519), [Vol. 30, No. 5 (May 2006), page 57] and Physical Principle for Generation of Randomness (NPO-43822) [Vol. 33, No. 5 (May 2009), page 56]. This research focuses upon a mathematical formalism for describing post-instability motions of a dynamical system characterized by exponential divergences of trajectories leading to chaos (including turbulence as a form of chaos). The formalism involves fictitious control forces that couple the equations of motion of the system with a Liouville equation that describes the evolution of the probability density of errors in initial conditions. These stabilizing forces create a powerful terminal attractor in probability space that corresponds to occurrence of a target trajectory with probability one. The effect in configuration space (ordinary three-dimensional space as commonly perceived) is to suppress exponential divergences of neighboring trajectories without affecting the target trajectory. As a result, the post-instability motion is represented by a set of functions describing the evolution of such statistical quantities as expectations and higher moments, and this representation is stable.

Zak, Michail↗
NASA NTRSDate not supplied

Microstructure Quantification and Random Forest Regression Models for Li4Ti5O12–Ni Property Prediction

All-solid-state structural lithium-ion batteries are sought to enable all-electric propulsion in next generation aerospace concepts through improved safety and systems level weight savings. In this work, the influence of processing conditions on microstructural evolution was evaluated for anode composites of strain-free Li4Ti5O12 and metallic nickel current collector. Beyond size distributions, this study explored methods of quantifying microstructural features that describe changes in the spatial distribution and coalescence of nickel particles as a function of sample composition and sintering conditions. Processing-microstructure-property relationships were described by microstructure quantifiers including nickel particle count per area, nearest neighbor distance distribution, and edge-to-edge distance distribution. Machine learning methods were applied to compare the relative influence of processing conditions and microstructural features on electrical conductivity and mechanical strength to optimize for simultaneous energy storage and load bearing performance. Insights gained from this work inform future evaluation of alternative energy storage materials and microstructures for multifunctional performance, and generation of microstructural descriptors strengthens modeling across length scales.

anode↗