Search NASA⌕ Search

SEARCH · Search NASA

Results for “Symbolic learning”

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.

88 records · Page 5
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Recurrent features of amplitudes in planar $\mathcal{N}$ = 4 super Yang-Mills theory

The planar three-gluon form factor for the chiral stress tensor operator in planar maximally supersymmetric Yang-Mills theory is an analog of the Higgs-to-three-gluon scattering amplitude in QCD. The amplitude (symbol) bootstrap program has provided a wealth of high-loop perturbative data about this form factor, with results up to eight loops available. The symbol of the form factor at L loops is given by words of length 2L in six letters with associated integer coefficients. In this paper, we analyze this data, describing patterns of zero coefficients and relations between coefficients. We find many sequences of words whose coefficients are given by closed-form expressions which we expect to be valid at any loop order. Moreover, motivated by our previous machine-learning analysis, we identify simple recursion relations that relate the coefficient of a word to the coefficients of particular lower-loop words. These results open an exciting door for understanding scattering amplitudes at all loop orders.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Modeling plasticity-mediated void growth at the single crystal scale: A physics-informed machine learning approach

Modeling the evolution of voids during plastic flow as well as their effects on plastic dissipation is critical for both component manufacturing and lifetime estimation purposes. To this end, we propose a rate-dependent constitutive model to homogenize the effects of semi-randomly distributed voids on single crystal plasticity whilst capturing void interaction and plastic anisotropy. Here, this present work focuses on the case of face centered cubic crystals to introduce an anisotropic gauge function applicable within the crystal plasticity formalism. The approach combines analytical methods to describe the micromechanics of the system in combination with symbolic regression to capture analytically intractable mechanisms from data. The hybrid framework uses a physics-informed genetic programming-based symbolic regression algorithm to solve a multiform optimization problem simultaneously producing a new gauge function and a new strain rate equation. This is also a multi-objective optimization problem with many competing objectives. A new search and selection step is introduced to the genetic algorithm that promotes convergence toward a global solution that better satisfies all the objectives. Overall, the symbolic equations produced leverage data-driven methods to achieve greater accuracy than comparable alternatives on an analytically intractable problem while maintaining model transparency.

36 MATERIALS SCIENCE↗
NASA NTRS1996

NASA/DOD Aerospace Knowledge Diffusion Research Project: Survey of Reader Preferences Concerning the Format of NASA Langley-Authored Technical Reports - Paper 58

The U.S. government technical report is a primary means by which the results of federally funded research and development (R&D) are transferred to the U.S. aerospace industry. However, little is known about this information product in terms of its actual use, importance, and value in the transfer of federally funded R&D. Little is also known about the intermediary-based system that is used to transfer the results of federally funded R&D to the U.S. aerospace industry. To help establish a body of knowledge, the U.S. government technical report is being investigated as part of the NASA/DOD Aerospace Knowledge Diffusion Research Project. In this paper, we summarize the literature on the U.S. government technical report and present the results of a survey of U.S. aerospace engineers and scientists that solicited their opinions concerning the format of NASA Langley Research Center (LaRC)-authored technical reports. To learn more about the preferences of U.S. aerospace engineers and scientists concerning the format of NASA LaRC-authored technical reports, we surveyed 133 report producers (i.e., authors) and 137 report users in March-April 1996. Questions covered such topics as (1) the order in which report components are read, (2) components used to determine if a report would be read, (3) those components that could be deleted, (4) the placement of such components as the symbols list, (e) the de-sirability of a table of contents, (5) the format of reference citations, (6) column layout and right margin treatment, and (7) and person and voice. Mail (self-reported) surveys were used to collect the data. The response rates for report producers (i.e., authors) was 68% and for users was 62%.

Pinelli, Thomas E.↗
NASA NTRS1997

NASA/DOD Aerospace Knowledge Diffusion Research Project. Paper 65: Survey of Reader Preferences Concerning the Format of NASA Langley-Authored Technical Reports

The U.S. government technical report is a primary means by which the results of federally funded research and development (R&D) are transferred to the U.S. aerospace industry. However, little is known about this information product in terms of its actual use, importance, and value in the transfer of federally funded R&D. Little is also known about the intermediary-based system that is used to transfer the results of federally funded R&D to the U.S. aerospace industry. To help establish a body of knowledge, the U.S. government technical report is being investigated as part of the NASA/DoD Aerospace Knowledge Diffusion Research Project. In this article, we summarize the literature on the U.S. government technical report and present the results of a survey of U.S. aerospace engineers and scientists that solicited their opinions concerning the format of NASA Langley Research Center (LaRC)-authored technical reports. To learn more about the preferences of U.S. aerospace engineers and scientists concerning the format of NASA LaRC-authored technical reports, we surveyed 133 report producers (i.e., authors) and 137 report users in March-April 1996. Questions covered such topics as: (a) the order in which report components are read; (b) components used to determine if a report would be read; (c) those components that could be deleted; (d) the placement of such components as the symbols list; (e) the desirability of a table of contents; (f) the format of reference citations; (g) column layout and right margin treatment; and (h) writing style in terms of person and voice. Mail (self-reported) surveys were used to collect the data. The response rates for report producers (i.e., authors) was 68% and for users was 62%.

Pinelli, Thomas E.↗
DOE OSTI2024

A Deep Learning Based Framework to Identify Undocumented Orphaned Oil and Gas Wells from Historical Maps: A Case Study for California and Oklahoma

Undocumented Orphaned Wells (UOWs) are wells without an operator that have limited or no documentation with regulatory authorities. An estimated 310,000 to 800,000 UOWs exist in the United States (US), whose locations are largely unknown. These wells can potentially leak methane and other volatile organic compounds to the atmosphere, and contaminate groundwater. In this study, we developed a novel framework utilizing a state-of-the-art computer vision neural network model to identify the precise locations of potential UOWs. The U-Net model is trained to detect oil and gas well symbols in georeferenced historical topographic maps, and potential UOWs are identified as symbols that are further than 100 m from any documented well. A custom tool was developed to rapidly validate the potential UOW locations. We applied this framework to four counties in California and Oklahoma, leading to the discovery of 1301 potential UOWs across >40,000 km 2 . We confirmed the presence of 29 UOWs from satellite images and 15 UOWs from magnetic surveys in the field with a spatial accuracy on the order of 10 m. This framework can be scaled to identify potential UOWs across the US since the historical maps are available for the entire nation.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1997

Walking to Olympus: An EVA Chronology

Spacewalkers enjoy a view of Earth once reserved for Apollo, Zeus, and other denizens of Mt. Olympus. During humanity's first extravehicular activity (EVA), Alexei Leonov floated above Gibraltar, the rock ancient seafarers saw as the gateway to the great unknown Atlantic. The symbolism was clear, Leonov stepped past a new Gibraltar when he stepped into space. More than 32 years and 154 EVAs later, Jerry Linenger conducted an EVA with Vladimir Tsibliyev as part of International Space Station Phase 1. They floated together above Gibraltar. Today the symbolism has new meaning: humanity is starting to think of stepping out of Earth orbit, space travel's new Gibraltar, and perhaps obtaining a new olympian view, a close-up look at Olympus Mons on Mars. Walking to Olympus: An EVA Chronology chronicles the 154 EVAs conducted from March 1965 to April 1997. It is intended to make clear the crucial role played by EVA in the history of spaceflight, as well as to chronicle the large body of EVA "lessons learned." Russia and the U.S. define EVA differently. Russian cosmonauts are said to perform EVA any time they are in vacuum in a space suit. A U.S. astronaut must have at least his head outside his spacecraft before he is said to perform an EVA. The difference is based in differing spacecraft design philoso- phies. Russian and Soviet spacecraft have always had a specialized airlock through which the EVA cosmonaut egressed, leaving the main habitable volume of the spacecraft pressurized. The U.S. Gemini and Apollo vehicles, on the other hand, depressurized their entire habitable volume for egress. In this document, we apply the Russian definition to Russian EVAS, and the U.S. definition to U.S. EVAS. Thus, for example, Gemini 4 Command Pilot James McDivitt does not share the honor of being first American spacewalker with Ed White, even though he was suited and in vacuum when White stepped out into space. Non-EVA spaceflights are listed in the chronology to provide context and to display the large num- ber of flights in which EVA played a role. This approach also makes apparent significant EVA gaps, for example, the U.S. gap between 1985 and 1991 following the Challenger accident. This NASA History Monograph is an edited extract from an extensive EVA Chronology and Reference Book being produced by the EVA Project Office, NASA Johnson Space Center, Houston, Texas. The larger work will be published as part of the NASA Formal Series in 1998. The authors gratefully acknowledge the assistance rendered by Max Ary, Ashot Bakunts, Gert-Jan Bartelds, Frank Cepollina, Andrew Chaikin, Phillip Clark, Richard Fullerton, Steven Glenn, Linda Godwin, Jennifer Green, Greg Harris, Clifford Hess, Jeffrey Hoffman, David Homan, Steven Hopkins, Nicholas Johnson, Eric Jones, Neville Kidger, Joseph Kosmo, Alexei Lebedev, Mark Lee, James LeBlanc, Dmitri Leshchenskii, Jerry Linenger, Igor Lissov, James McBarron, Clay McCullough, Joseph McMann, Story Musgrave, Dennis Newkirk, James Oberg, Joel Powell, Lee Saegesser, Andy Salmon, Glen Swanson, Joseph Tatarewicz, Kathy Thornton, Chris Vandenberg, Charles Vick, Bert Vis, David Woods, Mike Wright, John Young, and Keith Zimmerman. Special thanks to Laurie Buchanan, John Charles, Janet Kovacevich, Joseph Loftus, Sue McDonald, Martha Munies, Colleen Rapp, and Jerry Ross. Any errors remain the responsibility of the authors.

Portree, David S. F.↗
NASA NTRS1988

Using a simulation assistant in modeling manufacturing systems

Numerous simulation languages exist for modeling discrete event processes, and are now ported to microcomputers. Graphic and animation capabilities were added to many of these languages to assist the users build models and evaluate the simulation results. With all these languages and added features, the user is still plagued with learning the simulation language. Futhermore, the time to construct and then to validate the simulation model is always greater than originally anticipated. One approach to minimize the time requirement is to use pre-defined macros that describe various common processes or operations in a system. The development of a simulation assistant for modeling discrete event manufacturing processes is presented. A simulation assistant is defined as an interactive intelligent software tool that assists the modeler in writing a simulation program by translating the modeler's symbolic description of the problem and then automatically generating the corresponding simulation code. The simulation assistant is discussed with emphasis on an overview of the simulation assistant, the elements of the assistant, and the five manufacturing simulation generators. A typical manufacturing system will be modeled using the simulation assistant and the advantages and disadvantages discussed.

Schroer, Bernard J.↗
NASA NTRS2009

Theorem Proving in Intel Hardware Design

For the past decade, a framework combining model checking (symbolic trajectory evaluation) and higher-order logic theorem proving has been in production use at Intel. Our tools and methodology have been used to formally verify execution cluster functionality (including floating-point operations) for a number of Intel products, including the Pentium(Registered TradeMark)4 and Core(TradeMark)i7 processors. Hardware verification in 2009 is much more challenging than it was in 1999 - today s CPU chip designs contain many processor cores and significant firmware content. This talk will attempt to distill the lessons learned over the past ten years, discuss how they apply to today s problems, outline some future directions.

O'Leary, John↗
DOE OSTI2021

DEPRECATED AI-Batt-OS (Autonomous Identification of Battery Life Models - Open Source) [SWR 21-17]

DEPRECATED. This repository was archived by the owner on Jun 30, 2026. It is now read-only. Open source implementation of some of the methods utilized by AI-Batt, a battery lifetime modeling and analysis toolkit provided by the National Laboratory of the Rockies (NLR). This software demonstrates the use of bi-level optimization and symbolic regression techniques to semi-autonomously identify algebraic models predicting the capacity fade of lithium-ion batteries during calendar aging. Modeling the degradation of batteries is a complex task, due to the difficulty in separating the time-dependent and time-independent factors impacting cell level degradation, across multiple data series with different numbers of measurements and/or data quality. Bi-level optimization enables model parameters to be optimized to either the entire data set or to individual data series, allowing statistical disambiguation of global behaviors (data series independent) and local behaviors (data series dependent). Symbolic regression is used to automatically search for optimal low-dimesional models predicting the variation of locally optimized parameters versus time-independent experimental variables from millions of possible models, resulting in a more accurate and repeatable model identification process than is possible by a manual search. The provided tools also implement cross-validation and bootstrap resampling schemes, empowering statistical model comparison/selection and quantification of model uncertainties. An example script replicates the results from the manuscript "Challenging Practices of Algebraic Battery Life Models through Statistical Validation and Model Identification via Machine-Learning", submitted to ECS. All code is written in MATLAB. Requires the Statistics and Machine Learning Toolbox. Contact Dr. Paul Gasper at Paul.Gasper@nlr.gov for any questions.

Gasper, Paul [National Renewable Energy Lab. (NREL↗
DOE OSTI2026

A Data-Driven Method for Modeling Creep-Fatigue Stress- Strain Behavior Using Neural ODEs

In this paper, we introduce a data-driven machine learning approach for modeling one-dimensional stress–strain behavior under cyclic loading, utilizing experimental data from the nickel-based Alloy 617. The study employs uniaxial creep–fatigue test data acquired under various loading histories and compares two distinct neural network-based ODE models. The first model, known as the black-box model, comprehensively describes the strain–stress relationship using a Neural ODE equation. To interpret this black-box model, we apply the Sparse Identification of Nonlinear Dynamical Systems (SINDy) technique, transforming the black-box model into an equation-based model using symbolic regression. The second model, the Neural flow rule model, incorporates Hooke’s Law for the linear elastic component, with the nonlinear part characterized by a Neural ODE. Both models are trained with experimental data to accurately reflect the observed stress–strain behavior. We conduct a detailed comparison with the standard Chaboche model, which includes three back stresses. Our results demonstrate that the neural network-based ODE models precisely capture the experimental creep–fatigue mechanical behavior, exceeding the standard Chaboche model’s accuracy. Furthermore, an interpretable model derived from the black-box neural ODE model through symbolic regression achieves accuracy comparable to the Chaboche model, enhancing its interpretability. The results highlight the potential of neural network-based ODE models to depict complex creep–fatigue behavior, eliminating the necessity for experts to define a specific, material-focused model form.

creep-fatigue↗
NASA NTRSDate not supplied

Application of a Bayesian Framework for Plasticity Model Selection

Interpretable Machine Learning (IML) has performed well when tasked with deriving constitutive material models. However, IML has been shown to prefer models that overfit noise in data, which tends to lead to bloat and a decrease in interpretability. Due to these issues, the ability of IML to reliably derive models that fit the data and are both interpretable and generalizable is limited. A method developed recently has shown promise to improve upon traditional IML by using a Bayesian fitness definition for the evolution of free-form models with non-deterministic parameters. This framework was developed for genetic-programming-based symbolic regression(GPSR) and involves model parameter estimation using Sequential Monte Carlo sampling (SMC).The method has demonstrated a reduction in bloat when dealing with noisy data in comparison to conventional GPSR. The results of this framework applied to stress-strain data for copper show models that more effectively predict the experimental data better than was previously shown with GPSR.

plasticity↗
NASA NTRS2005

ASK Magazine; No. 21

THIS ISSUE FEATURES A VISUAL DEPICTION OF THE ACADEMY of Program and Project Leadership (APPL). I imagine a variety of initial reactions to the drawing. One might be, "What is a cartoon doing in a magazine about project management?" Or perhaps, "Wow, nice colors-and fun." Another may be to closely search the image for signs, symbols and meaning. Still another, to read a new level of innovation and creativity into the picture. Undoubtedly, some readers will raise questions about the cost. Of course, any reaction is a sign of engagement. The stronger, the more energized the emotional and cognitive processing, the better. It is a sign of attention and interaction. For I've heard it said, "You only need to worry if they don t care one way or the other." So what is the point of the picture? To stimulate interest, raise questions, promote discussion, and maybe raise a smile.. .That, at least, was my initial reaction when I was introduced to the work of Nancy Hegedus, who helps to create these drawings for Root Learning Inc. At the NASA PM Conference, I was first shown the work Nancy had been doing with the help of Goddard s Knowledge Management Architect, Dr. Ed Rogers. I was immediately drawn into the power of visualization as a tool for more effective learning, communicating, and conveying complex knowledge concepts. We need new tools in today s world, where information and data overwhelms by sheer volume. There are articles, pamphlets, communications, and white papers-all aiming to convince and influence. Reactions to these tend to be either avoidance or mind-numbing, heavy-eyed consent; the message never registers or enters the soul. That s one of the reasons that APPL s Knowledge Sharing Initiative (KSI) has turned to storytelling as a memorable way of transfer- ring knowledge, inspiring imitation of best practices, and spurring reflection. ASK Magazine s recent fourth birthday marks an important milestone in APPL s continuing quest to provide ongoing support to project managers and to promote mission success. And similar to storytelling, the power of visualization is receiving increasing attention in recent years as a way to stimulate engagement. Pictures and visual graphs are viewed as one of the most effective ways for displaying, describing, and generating discussion about quantitative and technically complex information. Prototypes, models, and simulations are considered essential for stimulating innovation through open and engaging discussions. There has also been extensive writing on the use of visual graphics, pictures, and cartoons to facilitate memory, creativity, openness, attention-and even well-being. For many of these reasons, I am excited to have a colorful visual depiction of the APPL world included in ASK. Without the addition of text or slides, the intent is to invite people into the world of the APPL mission-as well as its products, services, customers, and partners- in a fun and engaging manner. As project leaders strive to find ways to encourage engagement, learning, and transmission of knowledge, traditional technologies are proving to be as valuable as modern technologies. (But for those who want more information in the form of texts and slide presentations, we certainly have an abundance of those as well.)

Laufer, Alexander↗
NASA NTRS1990

The composite load spectra project

Probabilistic methods and generic load models capable of simulating the load spectra that are induced in space propulsion system components are being developed. Four engine component types (the transfer ducts, the turbine blades, the liquid oxygen posts and the turbopump oxidizer discharge duct) were selected as representative hardware examples. The composite load spectra that simulate the probabilistic loads for these components are typically used as the input loads for a probabilistic structural analysis. The knowledge-based system approach used for the composite load spectra project provides an ideal environment for incremental development. The intelligent database paradigm employed in developing the expert system provides a smooth coupling between the numerical processing and the symbolic (information) processing. Large volumes of engine load information and engineering data are stored in database format and managed by a database management system. Numerical procedures for probabilistic load simulation and database management functions are controlled by rule modules. Rules were hard-wired as decision trees into rule modules to perform process control tasks. There are modules to retrieve load information and models. There are modules to select loads and models to carry out quick load calculations or make an input file for full duty-cycle time dependent load simulation. The composite load spectra load expert system implemented today is capable of performing intelligent rocket engine load spectra simulation. Further development of the expert system will provide tutorial capability for users to learn from it.

Newell, J. F.↗
NASA NTRS1995

Looking at Earth from Space: Teacher's Guide with Activities for Earth and Space Science

The Maryland Pilot Earth Science and Technology Education Network (MAPS-NET) project was sponsored by the National Aeronautics and Space Administration (NASA) to enrich teacher preparation and classroom learning in the area of Earth system science. This publication includes a teacher's guide that replicates material taught during a graduate-level course of the project and activities developed by the teachers. The publication was developed to provide teachers with a comprehensive approach to using satellite imagery to enhance science education. The teacher's guide is divided into topical chapters and enables teachers to expand their knowledge of the atmosphere, common weather patterns, and remote sensing. Topics include: weather systems and satellite imagery including mid-latitude weather systems; wave motion and the general circulation; cyclonic disturbances and baroclinic instability; clouds; additional common weather patterns; satellite images and the internet; environmental satellites; orbits; and ground station set-up. Activities are listed by suggested grade level and include the following topics: using weather symbols; forecasting the weather; cloud families and identification; classification of cloud types through infrared Automatic Picture Transmission (APT) imagery; comparison of visible and infrared imagery; cold fronts; to ski or not to ski (imagery as a decision making tool), infrared and visible satellite images; thunderstorms; looping satellite images; hurricanes; intertropical convergence zone; and using weather satellite images to enhance a study of the Chesapeake Bay. A list of resources is also included.

Steele, Colleen↗
DOE OSTI2025

Security Analysis of a Class of Secured Spread Spectrum Systems

Abstract—A method of adding physical layer security to a class of spread spectrum systems has been recently proposed. In this paper, we look into the rate at which an eavesdropper may gain information about the system to decipher the data symbols. The Shannon mutual information is used to measure the rate of information that may be gained by an eavesdropper. The k-nearest neighbors (k-NN) method is used to obtain the estimates of relevant entropy values which will be then used to quantify the rate of information recovery as more data are being transmitted. It turns out that such information recovery requires adoption of special methods that avoid any destructive bias in the estimates. Details of these methods are also presented.

97 - MATHEMATICS AND COMPUTING↗
NASA NTRS2009

NASA Tech Briefs, July 2009

Topics covered include: Dual Cryogenic Capacitive Density Sensor; Hail Monitor Sensor; Miniature Six-Axis Load Sensor for Robotic Fingertip; Improved Blackbody Temperature Sensors for a Vacuum Furnace; Wrap-Around Out-the-Window Sensor Fusion System; Wide-Range Temperature Sensors with High-Level Pulse Train Output; Terminal Descent Sensor Simulation; A Robust Mechanical Sensing System for Unmanned Sea Surface Vehicles; Additive for Low-Temperature Operation of Li-(CF)n Cells; Li/CFx Cells Optimized for Low-Temperature Operation; Number Codes Readable by Magnetic-Field-Response Recorders; Determining Locations by Use of Networks of Passive Beacons; Superconducting Hot-Electron Submillimeter-Wave Detector; Large-Aperture Membrane Active Phased-Array Antennas; Optical Injection Locking of a VCSEL in an OEO; Measuring Multiple Resistances Using Single-Point Excitation; Improved-Bandwidth Transimpedance Amplifier; Inter-Symbol Guard Time for Synchronizing Optical PPM; Novel Materials Containing Single-Wall Carbon Nanotubes Wrapped in Polymer Molecules; Light-Curing Adhesive Repair Tapes; Thin-Film Solid Oxide Fuel Cells; Zinc Alloys for the Fabrication of Semiconductor Devices; Small, Lightweight, Collapsible Glove Box; Radial Halbach Magnetic Bearings; Aerial Deployment and Inflation System for Mars Helium Balloons; Steel Primer Chamber Assemblies for Dual Initiated Pyrovalves; Voice Coil Percussive Mechanism Concept for Hammer Drill; Inherently Ducted Propfans and Bi-Props; Silicon Nanowire Growth at Chosen Positions and Orientations; Detecting Airborne Mercury by Use of Gold Nanowires; Detecting Airborne Mercury by Use of Palladium Chloride; Micro Electron MicroProbe and Sample Analyzer; Nanowire Electron Scattering Spectroscopy; Electron-Spin Filters Would Offer Spin Polarization Greater than 1; Subcritical-Water Extraction of Organics from Solid Matrices; A Model for Predicting Thermoelectric Properties of Bi2Te3; Integrated Miniature Arrays of Optical Biomolecule Detectors; A Software Rejuvenation Framework for Distributed Computing; Kurtosis Approach to Solution of a Nonlinear ICA Problem; Robust Software Architecture for Robots; R4SA for Controlling Robots; Bio-Inspired Neural Model for Learning Dynamic Models; Evolutionary Computing Methods for Spectral Retrieval; Monitoring Disasters by Use of Instrumented Robotic Aircraft; Complexity for Survival of Living Systems; Using Drained Spacecraft Propellant Tanks for Habitation; Connecting Node; and Electrolytes for Low-Temperature Operation of Li-CFx Cells.

Source record↗