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At least 253 records · Page 14

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NASA NTRS1992

Finite element solution of optimal control problems with state-control inequality constraints

It is demonstrated that the weak Hamiltonian finite-element formulation is amenable to the solution of optimal control problems with inequality constraints which are functions of both state and control variables. Difficult problems can be treated on account of the ease with which algebraic equations can be generated before having to specify the problem. These equations yield very accurate solutions. Owing to the sparse structure of the resulting Jacobian, computer solutions can be obtained quickly when the sparsity is exploited.

Bless, Robert R.↗

NASA NTRS1992

Evaluation of an optimal guidance algorithm for aero-assisted orbit transfer

A detailed evaluation is performed of a guidance algorithm for aeroassisted orbit transfer that was developed earlier based on the method of matched asymptotic expansions. It is shown that, by exploiting the structure of the matched asymptotic expansion solution procedure, the original problem which requires the solution of a set of 20 implicit algebraic equations can be reduced to a problem of six implicit equations in six unknowns. The main contribution here is that it was possible to obtain a solution that is near optimal, requires a minimum of computation, and thus can be implemented in real time and on-board the vehicle. Guidance law implementation entails treating the current state as a new initial state and repetitively solving the matched asymptotic expansion problem to obtain the feedback controls.

Melamed, N.↗

NASA NTRS1996

[Formian 2 and a Formian Function for Processing Polyhedric Configurations]

The work began in October 1994 with the following objectives: (1) to produce an improved version of the programming language Formian; and (2) to create a means for computer aided handling of polyhedric configurations including the geodesic forms of all kinds. A new version of Formian, referred to as Formian 2, is being implemented to operate in the Windows 95 environment. It is an ideal tool for configuration management in a convenient and user-friendly manner. The second objective was achieved by creating a standard Formian function that allows convenient handling of all types of polyhedric configurations. In particular, the focus of attention is on polyhedric configurations that are of importance in architectural and structural engineering fields. The natural medium for processing of polyhedric configurations is a programming language that incorporates the concepts of 'formex algebra'. Formian is such a programming language in which the processing of polyhedric configurations can be carried out using the standard elements of the language. A description of this function is included in a chapter for a book entitled 'Beyond the Cube: the Architecture of space Frames and Polyhedra'. A copy of this chapter is appended.

Nooshin, H.↗

DOE OSTI2025

Ensemble Simulation Techniques and Fast Randomized Algorithms

The major goals of the project were to develop and analyze new ensemble simulation techniques, including trajectory stratification and preconditioned MCMC techniques, as well as develop fast numerical linear algebra techniques closely related to ensemble simulation ideas. The trajectory stratification techniques involve simulating in parallel short trajectory fragments of a Markov process confined to a specific region of space‐time and then patching together the statistics gathered to assemble estimates of very general dynamical properties. We have also developed this approach for rare event simulation and extended the techniques to applications requiring a more general framework (such as electronic structure calculations). The preconditioned MCMC techniques involve simulating multiple Markov chains in parallel and then using information from the ensemble to speed the mixing of each individual chain. The fast randomized linear algebra methods are motivated by the diffusion Monte Carlo technique, but are applicable to finding the dominant eigenvalue of (almost) general matrices. For most non‐negative matrices, the schemes result in an error (compared to the power method) that is constant in the dimension of the problem. For more general matrices, we see a very clear sublinear cost trend in computational tests.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2022

Landau discriminants

Scattering amplitudes in quantum field theories have intricate analytic properties as functions of the energies and momenta of the scattered particles. In perturbation theory, their singularities are governed by a set of nonlinear polynomial equations, known as Landau equations, for each individual Feynman diagram. The singularity locus of the associated Feynman integral is made precise with the notion of the Landau discriminant, which characterizes when the Landau equations admit a solution. In order to compute this discriminant, we present approaches from classical elimination theory, as well as a numerical algorithm based on homotopy continuation. These methods allow us to compute Landau discriminants of various Feynman diagrams up to 3 loops, which were previously out of reach. For instance, the Landau discriminant of the envelope diagram is a reducible surface of degree 45 in the three-dimensional space of kinematic invariants. We investigate geometric properties of the Landau discriminant, such as irreducibility, dimension and degree. In particular, we find simple examples in which the Landau discriminant has codimension greater than one. Furthermore, we describe a numerical procedure for determining which parts of the Landau discriminant lie in the physical regions. In order to study degenerate limits of Landau equations and bounds on the degree of the Landau discriminant, we introduce Landau polytopes and study their facet structure. Finally, we provide an efficient numerical algorithm for the computation of the number of master integrals based on the connection to algebraic statistics.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2021

Investigating phase transitions from local crystallographic analysis based on statistical learning of atomic environments in 2D MoS 2 -ReS 2

Traditionally, phase transitions are explored using a combination of macroscopic functional characterization and scattering techniques, providing insight into the average properties and symmetries of the lattice but local atomic level mechanisms during phase transitions generally remain unknown. Here, we explore the mechanisms of a phase transition between the trigonal prismatic and distorted octahedral phases of layered chalcogenides in the 2D MoS 2 - ReS 2 system from the observations of local degrees of freedom, namely atomic positions by Scanning Transmission Electron Microscopy (STEM). We employ local crystallographic analysis based on statistical learning of atomic environments to build a picture of the transition from the atomic level up and determine local and global variables controlling the local symmetry breaking. In particular, we argue that the dependence of the average symmetry breaking distortion amplitude on global and local concentration can be used to separate local chemical as well as global electronic effects on transition. This approach allows exploring atomic mechanisms beyond the traditional macroscopic descriptions, utilizing the imaging of compositional fluctuations in solids to explore phase transitions over a range of realized and observed local stoichiometries and atomic configurations.

25 ENERGY STORAGE↗

DOE OSTI2023

Scalable computations for nonstationary Gaussian processes

Nonstationary Gaussian process models can capture complex spatially varying dependence structures in spatial datasets. However, the large number of observations in modern datasets makes fitting such models computationally intractable with conventional dense linear algebra. In addition, derivative-free or even first-order optimization methods can be very slow to converge when estimating many spatially varying parameters. In this paper, we present a computational framework which couples an algebraic block diagonal plus low-rank covariance matrix approximation with stochastic trace estimation to facilitate the efficient use of second-order solvers for maximum likelihood estimation of Gaussian process models with many parameters. We demonstrate the effectiveness of these methods by simultaneously fitting 192 parameters in the popular nonstationary model of Paciorek and Schervish using 107,600 sea surface temperature anomaly measurements.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS1980

Full-coverage film cooling. I - Three-dimensional measurements of turbulence structure. II - Prediction of the recovery-region hydrodynamics

Hydrodynamic measurements of turbulence structure were performed with a triaxial hot wire in the full coverage and the recovery regions following an array of injection holes under isothermal conditions at ambient temperature and pressure for blowing ratios of 0.9 and 0.4. High levels of turbulence kinetic energy (TKE) were determined for low blowing, and low TKE levels were found for the high blowing levels; in the recovery region, the flow can be represented by a model with an outer boundary layer and a 2-dimensional inner boundary layer. Recovery region hydrodynamics can be modelled by considering that a new boundary layer started to grow immediately after the end of blowing; the Prandtl mixing length distributions calculated from the values of mean velocity and turbulent shear stresses were consistent with the presence of a dual boundary layer structure in the recovery region. The program used here contains a one-equation model of turbulence, using turbulence kinetic energy with an algebraic mixing length; this 2-dimensional, finite difference program can predict the mean velocity and turbulence kinetic energy profiles based on initial values, boundary conditions, and a closure condition.

Yavuzkurt, S.↗

NASA NTRS1987

Grid generation for the solution of partial differential equations

A general survey of grid generators is presented with a concern for understanding why grids are necessary, how they are applied, and how they are generated. After an examination of the need for meshes, the overall applications setting is established with a categorization of the various connectivity patterns. This is split between structured grids and unstructured meshes. Altogether, the categorization establishes the foundation upon which grid generation techniques are developed. The two primary categories are algebraic techniques and partial differential equation techniques. These are each split into basic parts, and accordingly are individually examined in some detail. In the process, the interrelations between the various parts are accented. From the established background in the primary techniques, consideration is shifted to the topic of interactive grid generation and then to adaptive meshes. The setting for adaptivity is established with a suitable means to monitor severe solution behavior. Adaptive grids are considered first and are followed by adaptive triangular meshes. Then the consideration shifts to the temporal coupling between grid generators and PDE-solvers. To conclude, a reflection upon the discussion, herein, is given.

Eiseman, Peter R.↗

NASA NTRS1990

Investigation of automated task learning, decomposition and scheduling

The details and results of research conducted in the application of neural networks to task planning and decomposition are presented. Task planning and decomposition are operations that humans perform in a reasonably efficient manner. Without the use of good heuristics and usually much human interaction, automatic planners and decomposers generally do not perform well due to the intractable nature of the problems under consideration. The human-like performance of neural networks has shown promise for generating acceptable solutions to intractable problems such as planning and decomposition. This was the primary reasoning behind attempting the study. The basis for the work is the use of state machines to model tasks. State machine models provide a useful means for examining the structure of tasks since many formal techniques have been developed for their analysis and synthesis. It is the approach to integrate the strong algebraic foundations of state machines with the heretofore trial-and-error approach to neural network synthesis.

Livingston, David L.↗

NASA NTRS1989

Grid generation for the solution of partial differential equations

Eiseman, Peter R.↗

DOE OSTI2022

Causal diamonds, cluster polytopes and scattering amplitudes

The “amplituhedron” for tree-level scattering amplitudes in the bi-adjoint φ 3 theory is given by the ABHY associahedron in kinematic space, which has been generalized to give a realization for all finite-type cluster algebra polytopes, labelled by Dynkin diagrams. In this letter we identify a simple physical origin for these polytopes, associated with an interesting (1 + 1)-dimensional causal structure in kinematic space, along with solutions to the wave equation in this kinematic “spacetime” with a natural positivity property. The notion of time evolution in this kinematic spacetime can be abstracted away to a certain “walk”, associated with any acyclic quiver, remarkably yielding a finite cluster polytope for the case of Dynkin quivers. The A n–3 , B n–1 /C n–1 and D n polytopes are the amplituhedra for n-point tree amplitudes, one-loop tadpole diagrams, and full integrand of one-loop amplitudes. We also introduce a polytope D¯ n , which chops the D n polytope in half along a symmetry plane, capturing one-loop amplitudes in a more efficient way.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

NASA NTRS1999

Combining Automated Theorem Provers with Symbolic Algebraic Systems: Position Paper

In contrast to pure mathematical applications where automated theorem provers (ATPs) are quite capable, proof tasks arising form real-world applications from the area of Software Engineering show quite different characteristics: they usually do not only contain much arithmetic (albeit often quite simple one), but they also often contain reasoning about specific structures (e.g. graphics, sets). Thus, an ATP must be capable of performing reasoning together with a fair amount of simplification, calculation and solving. Therefore, powerful simplifiers and other (symbolic and semi-symbolic) algorithms seem to be ideally suited to augment ATPs. In the following we shortly describe two major points of interest in combining SASs (symbolic algebraic systems) with top-down automated theorem provers (here: SETHEO [Let92, GLMS94]).

Schumann, Johann↗

NASA NTRS1983

Stability and Interaction of Coherent Structure in Supersonic Reactive Wakes

A theoretical formulation and analysis is presented for a study of the stability and interaction of coherent structure in reacting free shear layers. The physical problem under investigation is a premixed hydrogen-oxygen reacting shear layer in the wake of a thin flat plate. The coherent structure is modeled as a periodic disturbance and its stability is determined by the application of linearized hydrodynamic stability theory which results in a generalized eigenvalue problem for reactive flows. Detailed stability analysis of the reactive wake for neutral, symmetrical and antisymmetrical disturbance is presented. Reactive stability criteria is shown to be quite different from classical non-reactive stability. The interaction between the mean flow, coherent structure and fine-scale turbulence is theoretically formulated using the von-Kaman integral technique. Both time-averaging and conditional phase averaging are necessary to separate the three types of motion. The resulting integro-differential equations can then be solved subject to initial conditions with appropriate shape functions. In the laminar flow transition region of interest, the spatial interaction between the mean motion and coherent structure is calculated for both non-reactive and reactive conditions and compared with experimental data wherever available. The fine-scale turbulent motion determined by the application of integral analysis to the fluctuation equations. Since at present this turbulence model is still untested, turbulence is modeled in the interaction problem by a simple algebraic eddy viscosity model. The applicability of the integral turbulence model formulated here is studied parametrically by integrating these equations for the simple case of self-similar mean motion with assumed shape functions. The effect of the motion of the coherent structure is studied and very good agreement is obtained with previous experimental and theoretical works for non-reactive flow. For the reactive case, lack of experimental data made direct comparison difficult. It was determined that the growth rate of the disturbance amplitude is lower for reactive case. The results indicate that the reactive flow stability is in qualitative agreement with experimental observation.

Menon, Suresh↗

NASA NTRS1971

Project MAC

On-line programming for the following topics is discussed: (1) artificial intelligence, (2) automata theory, (3) cellular automata, (4) computation structures, (5) computer systems research, (6) dynamic modeling, computer graphics, and computer networks, (7) education, (8) implicit computation, (10) interactive management systems, (11) interactive algebraic manipulation, and (12) programming languages.

Licklider, J. C. R.↗

NASA NTRS1972

Stability of large-scale systems with stable and unstable subsystems.

The purpose of this paper is to develop new methods for constructing vector Liapunov functions and broaden the application of Liapunov's theory to stability analysis of large-scale dynamic systems. The application, so far limited by the assumption that the large-scale systems are composed of exponentially stable subsystems, is extended via the general concept of comparison functions to systems which can be decomposed into asymptotically stable subsystems. Asymptotic stability of the composite system is tested by a simple algebraic criterion. With minor technical adjustments, the same criterion can be used to determine connective asymptotic stability of large-scale systems subject to structural perturbations. By redefining the constraints imposed on the interconnections among the subsystems, the considered class of systems is broadened in an essential way to include composite systems with unstable subsystems. In this way, the theory is brought substantially closer to reality since stability of all subsystems is no longer a necessary assumption in establishing stability of the overall composite system.

Grujic, Lj. T.↗

NASA NTRS1982

Research on numerical algorithms for large space structures

Numerical algorithms for large space structures were investigated with particular emphasis on decoupling method for analysis and design. Numerous aspects of the analysis of large systems ranging from the algebraic theory to lambda matrices to identification algorithms were considered. A general treatment of the algebraic theory of lambda matrices is presented and the theory is applied to second order lambda matrices.

Denman, E. D.↗

NASA NTRS1984

A high-accuracy optical linear algebra processor for finite element applications

Optical linear processors are computationally efficient computers for solving matrix-matrix and matrix-vector oriented problems. Optical system errors limit their dynamic range to 30-40 dB, which limits their accuray to 9-12 bits. Large problems, such as the finite element problem in structural mechanics (with tens or hundreds of thousands of variables) which can exploit the speed of optical processors, require the 32 bit accuracy obtainable from digital machines. To obtain this required 32 bit accuracy with an optical processor, the data can be digitally encoded, thereby reducing the dynamic range requirements of the optical system (i.e., decreasing the effect of optical errors on the data) while providing increased accuracy. This report describes a new digitally encoded optical linear algebra processor architecture for solving finite element and banded matrix-vector problems. A linear static plate bending case study is described which quantities the processor requirements. Multiplication by digital convolution is explained, and the digitally encoded optical processor architecture is advanced.

Casasent, D.↗