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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 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Generalized parton distributions from symbolic regression

AI/ML informed Symbolic Regression is the next stage of scientific modeling. We utilize a highly customizable symbolic regression package “PySR” to model the x and t dependence of the flavor isovector combination Hu-d(x, t, ) at = 0. These PySR models were trained on GPD results provided by both Lattice QCD and phenomenological sources GGL, GK, and VGG. We demonstrate, for the first time, the consistency and systematic convergence of Symbolic Regression by quantifying the disparate models through their Taylor expansion coefficients. In addition to PySR penalizing models with higher complexity and mean-squared error, we implement schemes that test specific physics hypotheses, including force-factorized x and t dependence and Regge behavior in PySR GPDs. We show that PySR can identify factorizing GPD sources based on their response to the Force-Factorized model. Here, knowing the precise behavior of the GPDs, and their uncertainties in a wide range in x and t, crucially impacts our ability to concretely and quantitatively predict hadronic spatial distributions and their derived quantities.

Dotson, Andrew [New Mexico State University, Las C↗
DOE OSTI2023

Towards Geospatial Knowledge Graph Infused Neuro-Symbolic AI for Remote Sensing Scene Understanding

Deep learning has proven its effectiveness in numerous tasks for remote sensing scene understanding. However there is an increasing interest to explore fusion of domain-specific background information to the deep neural network to further improve its performance. Remote sensing researchers are also working towards developing models that generalize and adapt to multiple applications. Generalization challenges coupled with the scarcity of large corpora of high-quality noise-free labelled data, have together fueled an interest for leveraging background information. Knowledge graphs serve as excellent choice to represent domain-specific information in a structured, standardized and extensible manner. Integrating symbolic knowledge representations in the form of Knowledge Graph Embedding (KGE) to perform neuro-symbolic reasoning is an emerging research direction promising significant impacts. This vision paper seeks to position ideas and provoke early thoughts toward advancing neuro-symbolic artificial intelligence in the context of geospatial challenges. Specifically, it conceptualizes and elaborates on an architecture for infusing geospatial knowledge from knowledge graph in a deep neural network pipeline. As guiding case studies - land-use land-cover classification, object detection and instance segmentation can benefit from infusing spatio-contextual information with remote sensing imagery. The discussion further reflects on and articulates the challenges and explainable AI opportunities anticipated when scaling and maintaining large-scale geospatial knowledge graphs.

Potnis, Abhishek↗
NASA NTRS1977

The 100 MSPS symbol synchronizer

The functional characteristics and design of the 100 Mega Symbol per Second (MSPS) symbol synchronizer are described, and test data obtained from the brassboard are presented. It was shown that symbol rates to 100 MSPS can be properly synchronized and detected at signal to noise ratios down to -2 db with detection degradation less than 1.5 db.

Source record↗
NASA NTRS1978

Computerized symbolic manipulation in structural mechanics Progress and potential

Status and recent applications of computerized symbolic manipulation to structural mechanics problems are summarized. The applications discussed include; (1) generation of characteristic arrays of finite elements; (2) evaluation of effective stiffness and mass coefficients of continuum models for repetitive lattice structures; and (3) application of Rayleigh-Ritz technique to free vibration analysis of laminated composite elliptic plates. The major advantages of using computerized symbolic manipulation in each of these applications are outlined. A number of problem areas which limit the realization of the full potential of computerized symbolic manipulation in structural mechanics are examined and some of the means of alleviating them are discussed.

Noor, A. K.↗
NASA NTRS1980

Symbolic-numeric interface: A review

A survey of the use of a combination of symbolic and numerical calculations is presented. Symbolic calculations primarily refer to the computer processing of procedures from classical algebra, analysis, and calculus. Numerical calculations refer to both numerical mathematics research and scientific computation. This survey is intended to point out a large number of problem areas where a cooperation of symbolic and numerical methods is likely to bear many fruits. These areas include such classical operations as differentiation and integration, such diverse activities as function approximations and qualitative analysis, and such contemporary topics as finite element calculations and computation complexity. It is contended that other less obvious topics such as the fast Fourier transform, linear algebra, nonlinear analysis and error analysis would also benefit from a synergistic approach.

Ng, E. W.↗
NASA NTRS1981

Computerized symbolic manipulation in nonlinear finite element analysis

The potential of using computerized symbolic manipulation in the development of nonlinear finite elements is discussed. Three tasks which can be efficiently performed using computerized symbolic manipulation are identified: (1) generation of algebraic expressions for the stiffness coefficients of nonlinear finite elements, (2) generation of FORTRAN source code for numerical evaluation of stiffness coefficients, and (3) checking the correctness of the FORTRAN statements for the arrays of coefficients. The symbolic and algebraic manipulation system MACSYMA is used in the present study. Two sample MACSYMA programs are presented for the development of the nonlinear stiffness coefficients of two-dimensional, shear-flexible, doubly-curved deep shell elements. The first program is for displacement models and the second program is for mixed models with discontinuous stress-resultant fields at interelement boundaries.

Noor, A. K.↗
NASA NTRS1982

Determination of eigenvalues of dynamical systems by symbolic computation

A symbolic computation technique for determining the eigenvalues of dynamical systems is described wherein algebraic operations, symbolic differentiation, matrix formulation and inversion, etc., can be performed on a digital computer equipped with a formula-manipulation compiler. An example is included that demonstrates the facility with which the system dynamics matrix and the control distribution matrix from the state space formulation of the equations of motion can be processed to obtain eigenvalue loci as a function of a system parameter. The example chosen to demonstrate the technique is a fourth-order system representing the longitudinal response of a DC 8 aircraft to elevator inputs. This simplified system has two dominant modes, one of which is lightly damped and the other well damped. The loci may be used to determine the value of the controlling parameter that satisfied design requirements. The results were obtained using the MACSYMA symbolic manipulation system.

Howard, J. C.↗
NASA NTRS1983

Symbol Stream Combining Versus Baseband Combining for Telemetry Arraying

The objectives of this article are to investigate and analyze the problem of combining symbol streams from many Deep Space Network stations to enhance bit signal-to-noise ratio and to compare the performance of this combining technique with baseband combining. Symbol stream combining (SSC) has some advantages and some disadvantages over baseband combining (BBC). The SSC suffers almost no loss in combining the digital data and no loss due to the transmission of the digital data by microwave links between the stations. The BBC suffers 0.2 dB loss due to alignment and combining the IF signals and 0.2 dB loss due to transmission of signals by microwave links. On the other hand, the losses in the subcarrier demodulation assembly (SDA) and in the symbol synchronization assembly (SSA) for SSC are more than the losses in the SDA and SSA for BBC. It is shown that SSC outperforms BBC by about 0.35 dB (in terms of the required bit energy-to-noise spectral density for a bit error rate of 1,000) for an array of three DSN antennas, namely 64 m, 34m(T/R) and 34m(R).

Divsalar, D.↗
NASA NTRS1984

Signal-to-noise Ratio and Combiner Weight Estimation for Symbol Stream Combining

A method is presented for signal to noise ratio (SNR) and symbol stream combiner weight estimation. The SNR estimator employs absolute value moments as in an earlier method. The main contribution is that a new algorithm is derived for the combiner weight estimator to remove the large bias at low SNRs. The new algorithm is simulated to combine two independent symbol streams at various SNRs. As an example, the combining two symbol streams at SNRs of -1 dB and -7 dB, conbiner weight estimates using 1000 samples for the -1 dB stream and 10,000 samples for the -7 dB stream achieve an output SNR of -0.039 dB, which is just 0.012 dB below the theoretical limit achievable with perfect knowledge of the SNRs.

Vo, Q. D.↗
NASA NTRS1984

Symbol-stream Combiner: Description and Demonstration Plans

A system is described and demonstration plans presented for antenna arraying by symbol stream combining. This system is used to enhance the signal-to-noise ratio of a spacecraft signals by combining the detected symbol streams from two or more receiving stations. Symbol stream combining has both cost and performance advantages over other arraying methods. Demonstrations are planned on Voyager 2 both prior to and during Uranus encounter. Operational use is possible for interagency arraying of non-Deep Space Network stations at Neptune encounter.

Hurd, W. J.↗
NASA NTRS1986

Effects of quantization on symbol stream combining in a convolutionally coded system

Symbol stream combining has been proposed as a method for arraying signals at different antennas. If the received symbol streams are recorded on tape, it is desirable to limit the required storage without significantly affecting the performance. It is shown that 4-bit quantized symbols introduce an E sub b/N sub o penalty of only 0.05 dB.

Pollara, F.↗
NASA NTRS1987

Integration of symbolic and algorithmic hardware and software for the automation of space station subsystems

Expert systems that require access to data bases, complex simulations and real time instrumentation have both symbolic as well as algorithmic computing needs. These needs could both be met using a general computing workstation running both symbolic and algorithmic code, or separate, specialized computers networked together. The later approach was chosen to implement TEXSYS, the thermal expert system, developed to demonstrate the ability of an expert system to autonomously control the thermal control system of the space station. TEXSYS has been implemented on a Symbolics workstation, and will be linked to a microVAX computer that will control a thermal test bed. Integration options are explored and several possible solutions are presented.

Gregg, Hugh↗
NASA NTRS1988

Integration of symbolic and algorithmic hardware and software for the automation of space station subsystems

Expert systems that require access to data bases, complex simulations and real time instrumentation have both symbolic and algorithmic needs. Both of these needs could be met using a general purpose workstation running both symbolic and algorithmic codes, or separate, specialized computers networked together. The later approach was chosen to implement TEXSYS, the thermal expert system, developed by the NASA Ames Research Center in conjunction with the Johnson Space Center to demonstrate the ability of an expert system to autonomously monitor the thermal control system of the space station. TEXSYS has been implemented on a Symbolics workstation, and will be linked to a microVAX computer that will control a thermal test bed. The integration options and several possible solutions are presented.

Gregg, Hugh↗
NASA NTRS1987

Symbolic modeling of flexible manipulators

An algorithm is presented to symbolically derive the full nonlinear dynamic equations of motion of multilink flexible manipulators. Lagrange's assumed modes method is the basis of new algorithm and adapted in a way suitable for symbolic manipulation by digital computers. It is applied to model a two-link flexible arm by means of a commercially available symbolic manipulation program. The advantages of the algorithm and simulation results are discussed.

Cetinkunt, Sabri↗
NASA NTRS1990

Exact closed-form expressions for the performance of the split-symbol moments estimator of signal-to-noise ratio

Previously, the performance of the split-symbol moments estimator (SSME) of signal-to-noise ratio (SNR) has been evaluated by means of approximate expressions for the estimator mean and variance. These are asymptotic formulas in the sense that they become accurate as the number of estimator samples gets large. Here, exact closed-form expressions are obtained for the same quantities. These expressions confirm the accuracy of the previously derived asymptotic results, and, unlike the asymptotic formulas, they are useful even when the number of samples is small. It is also shown that the conventional split-symbol estimator can be trivially scaled to form a signal-to-noise ratio estimator which is precisely unbiased (as long as the estimate is based on more than two split-symbols).

Dolinar, S.↗
NASA NTRS1990

Application of symbolic computations to the constitutive modeling of structural materials

In applications involving elevated temperatures, the derivation of mathematical expressions (constitutive equations) describing the material behavior can be quite time consuming, involved and error-prone. Therefore intelligent application of symbolic systems to faciliate this tedious process can be of significant benefit. Presented here is a problem oriented, self contained symbolic expert system, named SDICE, which is capable of efficiently deriving potential based constitutive models in analytical form. This package, running under DOE MACSYMA, has the following features: (1) potential differentiation (chain rule), (2) tensor computations (utilizing index notation) including both algebraic and calculus; (3) efficient solution of sparse systems of equations; (4) automatic expression substitution and simplification; (5) back substitution of invariant and tensorial relations; (6) the ability to form the Jacobian and Hessian matrix; and (7) a relational data base. Limited aspects of invariant theory were also incorporated into SDICE due to the utilization of potentials as a starting point and the desire for these potentials to be frame invariant (objective). The uniqueness of SDICE resides in its ability to manipulate expressions in a general yet pre-defined order and simplify expressions so as to limit expression growth. Results are displayed, when applicable, utilizing index notation. SDICE was designed to aid and complement the human constitutive model developer. A number of examples are utilized to illustrate the various features contained within SDICE. It is expected that this symbolic package can and will provide a significant incentive to the development of new constitutive theories.

Arnold, Steven M.↗
NASA NTRS1991

The analysis of control trajectories using symbolic and database computing

The research broadly concerned the symbolic computation, mixed numeric-symbolic computation, and data base computation of trajectories of dynamical systems, especially control systems. It was determined that trees can be used to compute symbolically series which approximate solutions to differential equations.

Grossman, Robert↗