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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 307 records · Page 17

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NASA NTRS2009

A Survey of New Trends in Symbolic Execution for Software Testing and Analysis

Symbolic execution is a well-known program analysis technique which represents values of program inputs with symbolic values instead of concrete (initialized) data and executes the program by manipulating program expressions involving the symbolic values. Symbolic execution has been proposed over three decades ago but recently it has found renewed interest in the research community, due in part to the progress in decision procedures, availability of powerful computers and new algorithmic developments. We provide a survey of some of the new research trends in symbolic execution, with particular emphasis on applications to test generation and program analysis. We first describe an approach that handles complex programming constructs such as input data structures, arrays, as well as multi-threading. We follow with a discussion of abstraction techniques that can be used to limit the (possibly infinite) number of symbolic configurations that need to be analyzed for the symbolic execution of looping programs. Furthermore, we describe recent hybrid techniques that combine concrete and symbolic execution to overcome some of the inherent limitations of symbolic execution, such as handling native code or availability of decision procedures for the application domain. Finally, we give a short survey of interesting new applications, such as predictive testing, invariant inference, program repair, analysis of parallel numerical programs and differential symbolic execution.

Pasareanu, Corina S.↗

NASA NTRS1981

Computational vision

The range of fundamental computational principles underlying human vision that equally apply to artificial and natural systems is surveyed. There emerges from research a view of the structuring of vision systems as a sequence of levels of representation, with the initial levels being primarily iconic (edges, regions, gradients) and the highest symbolic (surfaces, objects, scenes). Intermediate levels are constrained by information made available by preceding levels and information required by subsequent levels. In particular, it appears that physical and three-dimensional surface characteristics provide a critical transition from iconic to symbolic representations. A plausible vision system design incorporating these principles is outlined, and its key computational processes are elaborated.

Barrow, H. G.↗

DOE OSTI2016

360⁰ -View of Quantum Theory and Ab Initio Simulation at Extreme Conditions: 2014 Sanibel Symposium

The Sanibel Symposium 2014 was held February 16-21, 2014, at the King and Prince, St. Simons Island, GA. It was successful in bringing condensed-matter physicists and quantum chemists together productively to drive the emergence of those specialties. The Symposium had a significant role in preparing a whole generation of quantum theorists. The 54th Sanibel meeting looked to the future in two ways. We had 360⁰-View sessions to honor the exceptional contributions of Rodney Bartlett (70), Bill Butler (70), Yngve Öhrn (80), Fritz Schaefer (70), and Malcolm Stocks (70). The work of these five has greatly impacted several generations of quantum chemists and condensed matter physicists. The “360⁰” is the sum of their ages. More significantly, it symbolizes a panoramic view of critical developments and accomplishments in theoretical and computational chemistry and physics oriented toward the future. Thus, two of the eight 360⁰-View sessions focused specifically on younger scientists. The 360⁰-View program was the major component of the 2014 Sanibel meeting. Another four sessions included a sub-symposium on ab initio Simulations at Extreme Conditions, with focus on getting past the barriers of present-day Born-Oppenheimer molecular dynamics by advances in finite-temperature density functional theory, orbital-free DFT, and new all-numerical approaches.

360-view↗

NASA NTRS1979

Approximate maximum likelihood decoding of block codes

Approximate maximum likelihood decoding algorithms, based upon selecting a small set of candidate code words with the aid of the estimated probability of error of each received symbol, can give performance close to optimum with a reasonable amount of computation. By combining the best features of various algorithms and taking care to perform each step as efficiently as possible, a decoding scheme was developed which can decode codes which have better performance than those presently in use and yet not require an unreasonable amount of computation. The discussion of the details and tradeoffs of presently known efficient optimum and near optimum decoding algorithms leads, naturally, to the one which embodies the best features of all of them.

Greenberger, H. J.↗

NASA NTRS1988

Distributed cooperating processes in a mobile robot control system

A mobile inspection robot has been proposed for the NASA Space Station. It will be a free flying autonomous vehicle that will leave a berthing unit to accomplish a variety of inspection tasks around the Space Station, and then return to its berth to recharge, refuel, and transfer information. The Flying Eye robot will receive voice communication to change its attitude, move at a constant velocity, and move to a predefined location along a self generated path. This mobile robot control system requires integration of traditional command and control techniques with a number of AI technologies. Speech recognition, natural language understanding, task and path planning, sensory abstraction and pattern recognition are all required for successful implementation. The interface between the traditional numeric control techniques and the symbolic processing to the AI technologies must be developed, and a distributed computing approach will be needed to meet the real time computing requirements. To study the integration of the elements of this project, a novel mobile robot control architecture and simulation based on the blackboard architecture was developed. The control system operation and structure is discussed.

Skillman, Thomas L., Jr.↗

NASA NTRS2014

Development Context Driven Change Awareness and Analysis Framework

Recent work on workspace monitoring allows conflict prediction early in the development process, however, these approaches mostly use syntactic differencing techniques to compare different program versions. In contrast, traditional change-impact analysis techniques analyze related versions of the program only after the code has been checked into the master repository. We propose a novel approach, De- CAF (Development Context Analysis Framework), that leverages the development context to scope a change impact analysis technique. The goal is to characterize the impact of each developer on other developers in the team. There are various client applications such as task prioritization, early conflict detection, and providing advice on testing that can benefit from such a characterization. The DeCAF framework leverages information from the development context to bound the iDiSE change impact analysis technique to analyze only the parts of the code base that are of interest. Bounding the analysis can enable DeCAF to efficiently compute the impact of changes using a combination of program dependence and symbolic execution based approaches.

Change Awareness↗

NASA NTRS2014

Development Context Driven Change Awareness and Analysis Framework

Recent work on workspace monitoring allows conflict prediction early in the development process, however, these approaches mostly use syntactic differencing techniques to compare different program versions. In contrast, traditional change-impact analysis techniques analyze related versions of the program only after the code has been checked into the master repository. We propose a novel approach, DeCAF (Development Context Analysis Framework), that leverages the development context to scope a change impact analysis technique. The goal is to characterize the impact of each developer on other developers in the team. There are various client applications such as task prioritization, early conflict detection, and providing advice on testing that can benefit from such a characterization. The DeCAF framework leverages information from the development context to bound the iDiSE change impact analysis technique to analyze only the parts of the code base that are of interest. Bounding the analysis can enable DeCAF to efficiently compute the impact of changes using a combination of program dependence and symbolic execution based approaches.

Sarma, Anita↗

DOE OSTI2022

Analytical Modeling of Exoplanet Transit Spectroscopy with Dimensional Analysis and Symbolic Regression

Abstract The physical characteristics and atmospheric chemical composition of newly discovered exoplanets are often inferred from their transit spectra, which are obtained from complex numerical models of radiative transfer. Alternatively, simple analytical expressions provide insightful physical intuition into the relevant atmospheric processes. The deep-learning revolution has opened the door for deriving such analytical results directly with a computer algorithm fitting to the data. As a proof of concept, we successfully demonstrate the use of symbolic regression on synthetic data for the transit radii of generic hot-Jupiter exoplanets to derive a corresponding analytical formula. As a preprocessing step, we use dimensional analysis to identify the relevant dimensionless combinations of variables and reduce the number of independent inputs, which improves the performance of the symbolic regression. The dimensional analysis also allowed us to mathematically derive and properly parameterize the most general family of degeneracies among the input atmospheric parameters that affect the characterization of an exoplanet atmosphere through transit spectroscopy.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2022

GSoFa: Scalable Sparse Symbolic LU Factorization on GPUs

Decomposing a matrix $\mathbf {A}$ into a lower matrix $\mathbf {L}$ and an upper matrix $\mathbf {U}$, which is also known as LU decomposition, is an essential operation in numerical linear algebra. For a sparse matrix, LU decomposition often introduces more nonzero entries in the $\mathbf {L}$ and $\mathbf {U}$ factors than in the original matrix. A symbolic factorization step is needed to identify the nonzero structures of $\mathbf {L}$ and $\mathbf {U}$ matrices. Attracted by the enormous potentials of the Graphics Processing Units (GPUs), an array of efforts have surged to deploy various LU factorization steps except for the symbolic factorization, to the best of our knowledge, on GPUs. This article introduces gSoFa, the first GPU-based symbolic factorization design with the following three optimizations to enable scalable LU symbolic factorization for nonsymmetric pattern sparse matrices on GPUs. First, here we introduce a novel fine-grained parallel symbolic factorization algorithm that is well suited for the Single Instruction Multiple Thread (SIMT) architecture of GPUs. Second, we tailor supernode detection into a SIMT friendly process and strive to balance the workload, minimize the communication and saturate the GPU computing resources during supernode detection. Third, we introduce a three-pronged optimization to reduce the excessive space consumption problem faced by multi-source concurrent symbolic factorization. Taken together, gSoFa achieves up to 31× speedup from 1 to 44 Summit nodes (6 to 264 GPUs) and outperforms the state-of-the-art CPU project, on average, by 5×. Notably, gSoFa also achieves up to 47 percent of the peak memory throughput of a V100 GPU in the Summit Supercomputer.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2026

Stellarator Design Exploration Using Symbolic-Regression Neutronics Surrogates

Systems codes require fast, simplified models to rapidly evaluate fusion power plant concepts, but neutronics analyses are often a computational bottleneck. Here, to address this, surrogate models for key neutronics responses have been developed using 3-D neutronics-ready models built with the open-source code ParaStell from a database of stellarator equilibria. Neutronics responses such as tritium breeding ratio (TBR), nuclear heating, and neutron-induced radiation damage displacements per atom (dpa) were simulated using OpenMC. Through sensitivity analysis and symbolic regression (SR), simple power-law formulas were derived connecting these neutronics responses to global stellarator parameters, including fusion power, plasma surface area, and plasma elongation. Validation shows these formulas can predict the simulation results with low error, enabling quick and accurate assessment of neutronics requirements in stellarator design exploration activities with systems codes.

Modeling↗

DOE OSTI2020

The inversion formula and 6j symbol for 3d fermions

In this work we study the 6 j symbol of the 3 d conformal group for fermionic operators. In particular, we study 4-point functions containing two fermions and two scalars and also those with four fermions. By using weight-shifting operators and harmonic analysis for the Euclidean conformal group, we relate these spinning 6 j symbols to the simpler 6 j symbol for four scalar operators. As one application we use these techniques to compute 3 d mean field theory (MFT) OPE coefficients for fermionic operators. We then compute corrections to the MFT spectrum and couplings due to the inversion of a single operator, such as the stress tensor or a low-dimension scalar. These results are valid at finite spin and extend the perturbative large spin analysis to include non-perturbative effects in spin.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2023

Language model-accelerated deep symbolic optimization

Symbolic optimization methods have been used to solve varied challenging and relevant problems such as symbolic regression and neural architecture search. However, the current state of the art typically learns each problem from scratch and is unable to leverage pre-existing knowledge and datasets that are available for many applications. Here, inspired by the similarity between sequence representations learned in natural language processing and the formulation of symbolic optimization as a discrete sequence optimization problem, we propose language model-accelerated deep symbolic optimization (LA-DSO), a method that leverages language models to learn symbolic optimization solutions more efficiently. We demonstrate LA-DSO in two tasks: symbolic regression, which allows us to perform extensive experimentation due to its low computation requirements, and computational antibody optimization, which shows that our proposal accelerates learning in challenging real-world problems.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2020

A supernodal all-pairs shortest path algorithm

We show how to exploit graph sparsity in the Floyd-Warshall algorithm for the all-pairs shortest path (Apsp) problem. Floyd-Warshall is an attractive choice for Apsp on high-performing systems due to its structural similarity to solving dense linear systems and matrix multiplication. However, if sparsity of the input graph is not properly exploited, Floyd-Warshall will perform unnecessary asymptotic work and thus may not be a suitable choice for many input graphs. To overcome this limitation, the key idea in our approach is to use the known algebraic relationship between Floyd-Warshall and Gaussian elimination, and import several algorithmic techniques from sparse Cholesky factorization, namely, fill-in reducing ordering, symbolic analysis, supernodal traversal, and elimination tree parallelism. When combined, these techniques reduce computation, improve locality and enhance parallelism. We implement these ideas in an efficient shared memory parallel prototype that is orders of magnitude faster than an efficient multi-threaded baseline Floyd-Warshall that does not exploit sparsity. Our experiments suggest that the Floyd-Warshall algorithm can compete with Dijkstra's algorithm (the algorithmic core of Johnson's algorithm) for several classes sparse graphs.

Sao, Piyush↗

NASA NTRS1976

Space shuttle orbital maneuvering system failure detection and identification software requirements (uncontrolled)

Candidate designs and their software implementation are presented for the Orbital Maneuvering System (OMS) Failure Detection and Identification (FDI) algorithms in the Redundance Management (RM) module of the Space Shuttle Guidance, Navigation, and Control (GN&C) software. The OMS engine FDI algorithm monitors OMS engine thrust performance, and the OMS actuator FDI algorithm monitors OMS gimbal actuator performance. The software functional requirements of the algorithms are described along with the objective of each algorithm. A list of the assumptions which have governed its design, input/output requirements, a functional description of the algorithm (including a functional block diagram), and input interface requirements are given. The HAL (the language of the space shuttle flight computer) software formulation of the algorithms is considered including structured flowcharts of the procedures, estimates of flight computer core storage and CPU time, and processing requirements. A glossary of the symbols used to define the software requirements and formulations is included.

Damario, L. A.↗

NASA NTRS1976

Signal design study for shuttle/TDRSS Ku-band uplink

The adequacy of the signal design approach chosen for the TDRSS/orbiter uplink was evaluated. Critical functions and/or components associated with the baseline design were identified, and design alternatives were developed for those areas considered high risk. A detailed set of RF and signal processing performance specifications for the orbiter hardware associated with the TDRSS/orbiter Ku band uplink was analyzed. Performances of a detailed design of the PN despreader, the PSK carrier synchronization loop, and the symbol synchronizer are identified. The performance of the downlink signal by means of computer simulation to obtain a realistic determination of bit error rate degradations was studied. The three channel PM downlink signal was detailed by means of analysis and computer simulation.

Source record↗

NASA NTRS1994

Computer-aided operations engineering with integrated models of systems and operations

CONFIG 3 is a prototype software tool that supports integrated conceptual design evaluation from early in the product life cycle, by supporting isolated or integrated modeling, simulation, and analysis of the function, structure, behavior, failures and operation of system designs. Integration and reuse of models is supported in an object-oriented environment providing capabilities for graph analysis and discrete event simulation. Integration is supported among diverse modeling approaches (component view, configuration or flow path view, and procedure view) and diverse simulation and analysis approaches. Support is provided for integrated engineering in diverse design domains, including mechanical and electro-mechanical systems, distributed computer systems, and chemical processing and transport systems. CONFIG supports abstracted qualitative and symbolic modeling, for early conceptual design. System models are component structure models with operating modes, with embedded time-related behavior models. CONFIG supports failure modeling and modeling of state or configuration changes that result in dynamic changes in dependencies among components. Operations and procedure models are activity structure models that interact with system models. CONFIG is designed to support evaluation of system operability, diagnosability and fault tolerance, and analysis of the development of system effects of problems over time, including faults, failures, and procedural or environmental difficulties.

Malin, Jane T.↗

NASA NTRS1977

A special purpose symbolic manipulation program for the derivation of the equations of motion for large flexible structures

This paper outlines a computer program especially tailored to the task of deriving explicit equations of motion for structures with point-connected substructures. The special purpose program is written in FORTRAN and is designed for performing the specific algebraic operations encountered in the derivation of explicit equations of motion. The derivation is by the Lagrangian approach. Using an orderly kinematical procedure and a discretization and/or truncation scheme, it is possible to write the kinetic and potential energy of each substructure in a compact vector-matrix form. Then, if each element of the matrices and vectors encountered in the kinetic and potential energy is a known algebraic expression, the computer program performs the necessary operations to evaluate the kinetic and potential energy of the system explicitly. Lagrange's equations for small motions about equilibrium can be deduced directly from the explicit form of the system kinetic and potential energy.

Hale, A. L.↗

NASA NTRS1990

Research on conceptual/innovative design for the life cycle

The goal of this research is developing and integrating qualitative and quantitative methods for life cycle design. The definition of the problem includes formal computer-based methods limited to final detailing stages of design; CAD data bases do not capture design intent or design history; and life cycle issues were ignored during early stages of design. Viewgraphs outline research in conceptual design; the SYMON (SYmbolic MONotonicity analyzer) algorithm; multistart vector quantization optimization algorithm; intelligent manufacturing: IDES - Influence Diagram Architecture; and 1st PRINCE (FIRST PRINciple Computational Evaluator).

Cagan, Jonathan↗