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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 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
NASA NTRS2011

AutoBayes Program Synthesis System System Internals

This lecture combines the theoretical background of schema based program synthesis with the hands-on study of a powerful, open-source program synthesis system (Auto-Bayes). Schema-based program synthesis is a popular approach toward program synthesis. The lecture will provide an introduction into this topic and discuss how this technology can be used to generate customized algorithms. The synthesis of advanced numerical algorithms requires the availability of a powerful symbolic (algebra) system. Its task is to symbolically solve equations, simplify expressions, or to symbolically calculate derivatives (among others) such that the synthesized algorithms become as efficient as possible. We will discuss the use and importance of the symbolic system for synthesis. Any synthesis system is a large and complex piece of code. In this lecture, we will study Autobayes in detail. AutoBayes has been developed at NASA Ames and has been made open source. It takes a compact statistical specification and generates a customized data analysis algorithm (in C/C++) from it. AutoBayes is written in SWI Prolog and many concepts from rewriting, logic, functional, and symbolic programming. We will discuss the system architecture, the schema libary and the extensive support infra-structure. Practical hands-on experiments and exercises will enable the student to get insight into a realistic program synthesis system and provides knowledge to use, modify, and extend Autobayes.

Statistical Algorithms↗
NASA NTRS1995

Modeling using optimization routines

Modeling using mathematical optimization dynamics is a design tool used in magnetic suspension system development. MATLAB (software) is used to calculate minimum cost and other desired constraints. The parameters to be measured are programmed into mathematical equations. MATLAB will calculate answers for each set of inputs; inputs cover the boundary limits of the design. A Magnetic Suspension System using Electromagnets Mounted in a Plannar Array is a design system that makes use of optimization modeling.

Thomas, Theodore↗
NASA NTRS1974

Optimizing acoustical treatment

A mathematical linear programming model is presented for optimizing acoustical treatment and interior decoration of concert and other public halls. This method provides the designer with a range of acoustically correct solutions at increased economical efficiency. The mathematical model uses geometrical data about the room, recommended reverberation time values, the architect's choice of given sound absorbing structures and finishing materials. The model permits inclusion of aesthetical considerations about conditioning, proportioning, or, on the contrary, reciprocal exclusion of any classes of material and/or sound absorbing structure.

Beuran, N.↗
NASA NTRS2003

Reaching Mars: multi-criteria R&D portfolio selection for Mars exploration technology planning

The exploration of Mars has been the focus of increasing scientific interest about the planet and its relationship to Earth. A multi-criteria decision-making approach was developed to address the question, Given a Mars program composed of mission concepts dependent on a variety of alternative technology development programs, which combination of technologies would enable missions to maximize science return under a constrained budget?.

R&D technology planning mathematical programming↗
NASA NTRS1983

The YAV-8B simulation and modeling. Volume 2: Program listing

Detailed mathematical models of varying complexity representative of the YAV-8B aircraft are defined and documented. These models are used in parameter estimation and in linear analysis computer programs while investigating YAV-8B aircraft handling qualities. Both a six degree of freedom nonlinear model and a linearized three degree of freedom longitudinal and lateral directional model were developed. The nonlinear model is based on the mathematical model used on the MCAIR YAV-8B manned flight simulator. This simulator model has undergone periodic updating based on the results of approximately 360 YAV-8B flights and 8000 hours of wind tunnel testing. Qualified YAV-8B flight test pilots have commented that the handling qualities characteristics of the simulator are quite representative of the real aircraft. These comments are validated herein by comparing data from both static and dynamic flight test maneuvers to the same obtained using the nonlinear program.

Source record↗
NASA NTRS1984

STABCAR: A program for finding characteristic root systems having transcendental stability matrices

STABCAR can be used to determine the characteristic roots of flexible, actively controlled aircraft, including the effects of unsteady aerodynamics. A modal formulation and a transfer-matrix representation of the control system are employed. Operable in either a batch or an interactive mode, STABCAR can provide graphical or tabular output of the variation of the roots with velocity, density, altitude, dynamic pressure or feedback gains. Herein the mathematical model, program structure, input requirements, output capabilities, and a series of sample cases are detailed. STABCAR was written for use on CDC CYBER 175 equipment; modification would be required for operation on other machines.

Adams, W. M., Jr.↗
NASA NTRS2005

Program Calculates Forces in Bolted Structural Joints

FORTRAN 77 computer program calculates forces in bolts in the joints of structures. This program is used in conjunction with the NASTRAN finite-element structural-analysis program. A mathematical model of a structure is first created by approximating its load-bearing members with representative finite elements, then NASTRAN calculates the forces and moments that each finite element contributes to grid points located throughout the structure. The user selects the finite elements that correspond to structural members that contribute loads to the joints of interest, and identifies the grid point nearest to each such joint. This program reads the pertinent NASTRAN output, combines the forces and moments from the contributing elements to determine the resultant force and moment acting at each proximate grid point, then transforms the forces and moments from these grid points to the centroids of the affected joints. Then the program uses these joint loads to obtain the axial and shear forces in the individual bolts. The program identifies which bolts bear the greatest axial and/or shear loads. The program also performs a fail-safe analysis in which the foregoing calculations are repeated for a sequence of cases in which each fastener, in turn, is assumed not to transmit an axial force.

Buder, Daniel A.↗
NASA NTRS1978

Engineering description of the OMS/RCS/DAP modes used in the HP-9825A High Fidelity Relative Motion Program (HFRMP)

Simplified mathematical models are reported for the space shuttle's Orbital Maneuvering System (OMS), Reaction Control System (RCS), and on-orbit Digital Autopilot (DAP) that have been incorporated in the High-Fidelity Relative Motion Program (HFRMP) for the HP-9825A desk-top calculator. Comparisons were made between data generated by the HFRMP and by the Space Shuttle Functional Simulator (SSFS), which models the cited shuttle systems in much greater detail. These data include propellant requirements for representative translational maneuvers, rotational maneuvers, and attitude maintenance options. Also included are data relating to on-orbit trajectory deviations induced by RCS translational cross coupling. Potential close-range stationkeeping problems that are suggested by HFRMP simulations of 80 millisecond (as opposed to 40 millisecond) DAP cycle effects are described. The principal function of the HFRMP is to serve as a flight design tool in the area of proximity operations.

Wilson, S. W.↗
DOE OSTI2025

Genetic programming for the nuclear many-body problem: a guide

Genetic Programming (GP) is an evolutionary algorithm that generates computer programs, or mathematical expressions, to solve complex problems. In this Guide, we demonstrate how to use GP to develop surrogate models to mitigate the computational costs of modeling atomic nuclei with ever increasing complexity. The computational burden escalates when uncertainty quantification is pursued, or when observables must be globally computed for thousands of nuclei. By studying three models in which the mean field depends on the total particle density self-consistently, we show that by constructing reduced order models supported by GP one can speed up many-body computations by several orders of magnitude with a negligible loss in accuracy.

dimensionality reduction↗
DOE OSTI2025

Workforce planning: a review of methodologies

Workforce planning deals with determining the number of employees and associated skills necessary to meet the future operational needs of an organization. A workforce system consists of six elements: recruitment, attrition, promotion, training, retention, and scheduling. Historically, several workforce modeling and analysis methodologies have been developed to capture these elements. This paper reviews the results of workforce and manpower models published within peer-reviewed literature between 1959 and 2021 to provide an in-depth analysis of current models. The focus of this review is on analytical, simulation, and empirical models found in literature that were collected based on a citation requirement and keyword search criteria. Results demonstrate the trends in workforce modeling research and discuss the common uses of each model type and the advantages/disadvantages related to each model. Based on the common attributes of workforce systems, the discussion focuses on the most frequently used model type for each element and the best use for each model. Lastly, recommendations are made for the development of workforce models that allow the most comprehensive view of the workforce systems of the future.

42 ENGINEERING↗
DOE OSTI2025

Hyperplane decision trees as piecewise linear surrogate models for chemical process design

Recent trends in chemical engineering research point towards an increasing reliance on data-driven modeling approaches. Neural networks, for instance, have proven to be accurate when data is plentiful and high-dimensional, but in many cases, they require computationally-intensive training procedures. Here, in this work, we describe hyperplane decision trees (HT) as a highly expressive and low-compute machine learning model architecture. These models are locally linear and have linear decision boundaries, resulting in a piecewise linear model of the data. This property allows them to be converted into mixed-integer linear constraints which can be globally optimized. Our open-source PyTorch implementation of this method is a fast, flexible, and accessible way to build accurate piecewise linear models of data.

Decision trees↗
DOE OSTI2026

Classical combinatorial optimization scaling for random Ising models on 2D heavy-hex graphs

Motivated by near term quantum computing hardware limitations, combinatorial optimization problems that can be addressed by current quantum algorithms and noisy hardware with little or no overhead are used to probe capabilities of quantum algorithms such as the quantum approximate optimization algorithm. In this study, a specific class of near term quantum computing hardware defined combinatorial optimization problems, Ising models on heavy-hex graphs both with and without geometrically local cubic terms, are examined for their classical computational hardness via empirical computation time scaling quantification. Specifically the time-to-solution (TTS) metric using the classical heuristic simulated annealing is measured for finding optimal variable assignments (ground states), as well as the time required for the optimization software Gurobi to find an optimal variable assignment. Because of the sparsity of these Ising models, the classical algorithms are able to find optimal solutions efficiently even for large instances (i.e. 100 000 spin variables). The Ising models both with and without geometrically local cubic terms exhibit average-case linear-time or weakly quadratic scaling when solved exactly using Gurobi, and the Ising models with no cubic terms show evidence of exponential-time TTS scaling when sampled using simulated annealing. These findings point to the necessity of developing and testing more complex, namely more densely connected, optimization problems in order for quantum computing to ever have a practical advantage over classical computing. Our results are another illustration that different classical algorithms can indeed have exponentially different running times, thus making the identification of the best practical classical technique important in any quantum computing vs. classical computing comparison.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗