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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 1,315 records · Page 73
All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

Controlling Combinatorial Complexity in Software and Malware Behavior Computation

Virtually all software is out of intellectual control in that no one knows its full behavior. Software Behavior Computation (SBC) is a new technology for understanding everything software does. SBC applies the mathematics of denotational semantics implemented by function composition in Functional Trace Tables (FTTs) to compute the behavior of programs, expressed as disjoint cases of conditional concurrent assignments. In some circumstances, combinatorial explosions in the number of cases can occur when calculating the behavior of sequences of multiple branching structures. This paper describes computational methods that avoid combinatorial explosions. The predicates that control branching structures such as ifthenelses can be organized into three categories: 1) Independent, resulting in no behavior case explosion, 2) Coordinated, resulting in two behavior cases, or 3) Goaloriented, with potential exponential growth in the number of cases. Traditional FTT-based behavior computation can be augmented by two additional computational methods, namely, Single-Value Function Abstractions (SVFAs) and, introduced in this paper, Relational Trace Tables (RTTs). These methods can be applied to the three predicate categories to avoid combinatorial growth in behavior cases while maintaining mathematical correctness.

Hyperion system↗
DOE OSTI2019

Quantum Networks for Open Science (QNOS) Workshop

Quantum computing systems currently being developed will have extraordinary capabilities to effectively solve complex problems in computational sciences, communication networks, artificial intelligence, and data processing, and will provide a powerful capability for researchers in almost every scientific discipline. Harnessing the full potential of quantum computing will require an ecosystem with a broad spectrum of quantum technologies. Quantum networks are one of the critical and highly anticipated components of this ecosystem. The combination of quantum computing and quantum networks are crucial to the US Department of Energy’s (DOE) mission to provide scientists with the state-of-the-art computational capabilities.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1991

Fast Parallel Computation Of Manipulator Inverse Dynamics

Method for fast parallel computation of inverse dynamics problem, essential for real-time dynamic control and simulation of robot manipulators, undergoing development. Enables exploitation of high degree of parallelism and, achievement of significant computational efficiency, while minimizing various communication and synchronization overheads as well as complexity of required computer architecture. Universal real-time robotic controller and simulator (URRCS) consists of internal host processor and several SIMD processors with ring topology. Architecture modular and expandable: more SIMD processors added to match size of problem. Operate asynchronously and in MIMD fashion.

Fijany, Amir↗
NASA NTRS1992

An alternative to unstructured grids for computing gas dynamic flows around arbitrarily complex two-dimensional bodies

In this paper we describe an approach for dealing with arbitrary complex, two dimensional geometries, the so-called cartesian boundary method. Conceptually, the cartesian boundary method is quite simple. Solid bodies blank out areas of a background, cartesian mesh, and the resultant cut cells are singled out for special attention. However, there are several obstacles that must be overcome in order to achieve a practical scheme. We present a general strategy that overcomes these obstacles, together with some details of our successful conversion of an adaptive mesh algorithm from a body-fitted code to a cartesian boundary code.

Quirk, James J.↗
NASA NTRS1991

A special purpose silicon compiler for designing supercomputing VLSI systems

Design of general/special purpose supercomputing VLSI systems for numeric algorithm execution involves tackling two important aspects, namely their computational and communication complexities. Development of software tools for designing such systems itself becomes complex. Hence a novel design methodology has to be developed. For designing such complex systems a special purpose silicon compiler is needed in which: the computational and communicational structures of different numeric algorithms should be taken into account to simplify the silicon compiler design, the approach is macrocell based, and the software tools at different levels (algorithm down to the VLSI circuit layout) should get integrated. In this paper a special purpose silicon (SPS) compiler based on PACUBE macrocell VLSI arrays for designing supercomputing VLSI systems is presented. It is shown that turn-around time and silicon real estate get reduced over the silicon compilers based on PLA's, SLA's, and gate arrays. The first two silicon compiler characteristics mentioned above enable the SPS compiler to perform systolic mapping (at the macrocell level) of algorithms whose computational structures are of GIPOP (generalized inner product outer product) form. Direct systolic mapping on PLA's, SLA's, and gate arrays is very difficult as they are micro-cell based. A novel GIPOP processor is under development using this special purpose silicon compiler.

Venkateswaran, N.↗
NASA NTRS1995

Computation of wave propagation in a complex flow

A numerical method has been developed in order to address aeroacoustic problems modeled by the linearized Euler equations. A weak formulation of the equations leads to a time-dependent equation for the test functions. The basic solver being one dimensional, two dimensional problems are handled by directional splitting. This method shows low dissipation and dispersion errors.

Lafon, Philippe↗
NASA NTRSDate not supplied

When the Eyes Don't Have It: Autonomous Control of Deep Space Vehicles for Human Spaceflight

NASA has been charged with expanding human presence into the solar system. The next phase of exploration will focus on learning how to develop and sustain habitats on the moon for eventual missions to Mars. The Gateway Lunar Orbiting Platform (G-LOP) is a modular spacecraft being built for cis-lunar orbit and offers a true deep space environment for gaining experience for human missions to Mars. The mission concept for Gateway involves long uncrewed periods between missions; therefore, Gateway requires increased self-reliance to separate the spacecraft from Earth-bound control and oversight. This complicates the human-in-the-loop (HITL) concept and requires major adjustments to the traditional automation human-computer interaction paradigm. This paper discusses the design, development, and verification of complex human-computer interactions with the autonomous systems managers which will control the Gateway spacecraft.

Julia M. Badger↗
NASA NTRS1992

Wall functions for the kappa-epsilon turbulence model in generalized nonorthogonal curvilinear coordinates

A k-epsilon turbulence model suitable for compressible flow, including the new wall function formulation, has been incorporated into an existing compressible Reynolds-averaged Navier-Stokes code, F3D. The low Reynolds number k-epsilon model of Chien (1982) was added for comparison with the present method. A number of features were added to the F3D code including improved far-field boundary conditions and viscous terms in the streamwise direction. A series of computations of increasing complexity was run to test the effectiveness of the new formulation. Flow over a flat plate was computed by using both orthogonal and nonorthogonal grids, and the friction coefficients and velocity profiles compared with a semi-empirical equation. Flow over a body of revolution at zero angle of attack was then computed to test the method's ability to handle flow over a curved surface. Friction coefficients and velocity profiles were compared to test data. All models gave good results on a relatively fine grid, but only the wall function formulation was effective with coarser grids. Finally, in order to demonstrate the method's ability to handle complex flow fields, separated flow over a prolate spheroid at angle of attack was computed, and results were compared to test data. The results were also compared to a k-epsilon model by Kim and Patel (1991), in which one equation model patched in at the wall was employed. Both models gave reasonable solutions, but improvement is required for accurate prediction of friction coefficients in the separated regions.

Sondak, D. L.↗
DOE OSTI2025

Reproducibility of fixed-node diffusion Monte Carlo across diverse community codes: The case of water–methane dimer

Fixed-node diffusion quantum Monte Carlo (FN-DMC) is a widely trusted many-body method for solving the Schrödinger equation, known for its reliable predictions of material and molecular properties. Furthermore, its excellent scalability with system complexity and near-perfect utilization of computational power make FN-DMC ideally positioned to leverage new advances in computing to address increasingly complex scientific problems. Even though the method is widely used as a computational gold standard, reproducibility across the numerous FN-DMC code implementations has yet to be demonstrated. This difficulty stems from the diverse array of DMC algorithms and trial wave functions, compounded by the method’s inherent stochastic nature. Here, this study represents a community-wide effort to assess the reproducibility of the method, affirming that yes, FN-DMC is reproducible (when handled with care). Using the water–methane dimer as the canonical test case, we compare results from eleven different FN-DMC codes and show that the approximations to treat the non-locality of pseudopotentials are the primary source of the discrepancies between them. In particular, we demonstrate that, for the same choice of determinantal component in the trial wave function, reliable and reproducible predictions can be achieved by employing the T-move, the determinant locality approximation, or the determinant T-move schemes, while the older locality approximation leads to considerable variability in results. These findings demonstrate that, with appropriate choices of algorithmic details, fixed-node DMC is reproducible across diverse community codes—highlighting the maturity and robustness of the method as a tool for open and reliable computational science.

Della Pia, Flaviano [Univ. of Cambridge (United Ki↗
DOE OSTI2016

Catalytic Deoxydehydration of Carbohydrates and Polyols to Chemicals and Fuels

As the world's fossil fuel resources are being depleted and their costs increase, there is an urgent need to discover and develop new processes for the conversion of renewable, biomass resources into fuels and chemical feedstocks. Research and development in this area have been given high priority by both governmental agencies and industry. To increase the energy content and decrease the boiling points of biomass-derived carbohydrates and polyols to the useful liquid range it is necessary to chemically remove water (dehydrate) and, preferably, oxygen (deoxygenate/reduce). The poly-hydroxylic nature of carbohydrates is attractive for their use as functionalized chemical building blocks, but it presents a daunting challenge for their selective conversion to single product chemicals or fuels. The long term, practical objective of this project is to develop catalytic processes for the deoxydehydration (DODH) of biomass-derived carbohydrates and polyols to produce unsaturated alcohols and hydrocarbons of value as chemical feedstocks and fuels; DODH: polyol + reductant --(LMOx catalyst)--> unsaturate + oxidized reductant + H2O. Limited prior studies have established the viability of the DODH process with expensive phosphine reductants and rhenium-catalysts. Initial studies in the PI's laboratory have now demonstrated: 1) the moderately efficient conversion of glycols to olefins by the economical sulfite salts is catalyzed by MeReO3 and Z+ReO4-; 2) effective phosphine-based catalytic DODH of representative glycols to olefins by cheap LMoO2 complexes; and 3) computational studies (with K. Houk, UCLA) have identified several Mo-, W-, and V-oxo complexes that are likely to catalyze glycol DODH. Seeking practically useful DODH reactions of complex polyols and new understanding of the reactivity of polyoxo-metal species with biomass-oxygenates we will employ a two-pronged approach: 1) investigate experimentally the reactivity, both stoichiometric and catalytic, of polyoxo-complexes and practical reductants with representative polyols to establish structure/reactivity relationships and reaction mechanisms; and b) carry out parallel computational studies of these reactions and their mechanisms- both analytical and predictive. Our prioritized action plan is: (1) to optimize the catalytic efficiency, assess the substrate scope/selectivity, and address key mechanistic aspects of Re-catalyzed, sulfite-driven DODH reactions; (2) use the findings from (1), together with computational predictions, to discover new, effective non-precious metal catalysts for sulfite-driven DODH reactions; and 3) to initiate exploratory studies of CO- and H2-driven DODH. Successful execution of this research project will: 1) provide practical chemical processes for the conversion of biomass into useful chemicals and fuels: 2) bring fundamental new understanding of chemical reactions involving metal-oxo catalysts; and 3) provide educational and technical training of future energy scientists.

09 BIOMASS FUELS↗
NASA NTRS1972

Computer-graphics studies of dipole-dipole collisions - Evidence for neutral collision complexes.

Extension of three-dimensional computer-graphics studies of orientation-dependent forces to multiple reflection behavior in dipole-dipole collisions. The collision pairs DCl-DCl and HCl-HCl are studied for rotational temperatures of 25, 77, and 300 K and translational temperatures of 77 and 300 K. The probability of a multiple reflection collision is a very sensitive inverse function of hard-core reflection distance for fixed temperatures. A brief comparison of the results is made with two-dimensional results of Clarke and Smith (1970) for CHF3-CHF3.

Dugan, J. V., Jr.↗
DOE OSTI2022

aphBO-2GP-3B: a budgeted asynchronous parallel multi-acquisition functions for constrained Bayesian optimization on high-performing computing architecture

High-fidelity complex engineering simulations are often predictive, but also computationally expensive and often require substantial computational efforts. The mitigation of computational burden is usually enabled through parallelism in high-performance cluster (HPC) architecture. Optimization problems associated with these applications is a challenging problem due to the high computational cost of the high-fidelity simulations. In this paper, an asynchronous parallel constrained Bayesian optimization method is proposed to efficiently solve the computationally expensive simulation-based optimization problems on the HPC platform, with a budgeted computational resource, where the maximum number of simulations is a constant. The advantage of this method are three-fold. Firstly, the efficiency of the Bayesian optimization is improved, where multiple input locations are evaluated parallel in an asynchronous manner to accelerate the optimization convergence with respect to physical runtime. This efficiency feature is further improved so that when each of the inputs is finished, another input is queried without waiting for the whole batch to complete. Second, the proposed method can handle both known and unknown constraints. Third, the proposed method samples several acquisition functions based on their rewards using a modified GP-Hedge scheme. The proposed framework is termed aphBO-2GP-3B, which means asynchronous parallel hedge Bayesian optimization with two Gaussian processes and three batches. The numerical performance of the proposed framework aphBO-2GP-3B is comprehensively benchmarked using 16 numerical examples, compared against other 6 parallel Bayesian optimization variants and 1 parallel Monte Carlo as a baseline, and demonstrated using two real-world high-fidelity expensive industrial applications. The first engineering application is based on finite element analysis (FEA) and the second one is based on computational fluid dynamics (CFD) simulations.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

Rapid Calculation of Max-Min Fair Rates for Multi-Commodity Flows in Fat-Tree Networks

Max-min fairness is often used in the performance modeling of interconnection networks. Existing methods to compute max-min fair rates for multi-commodity flows have high complexity and are computationally infeasible for large networks. In this paper, we show that by considering topological features, this problem can be solved efficiently for the fat-tree topology that is widely used in data centers and high performance compute clusters. Several efficient new algorithms are developed for this problem, including a parallel algorithm that can take advantage of multi-core and shared-memory architectures. Using these algorithms, we demonstrate that it is possible to find the max-min fair rate allocation for multi-commodity flows in fat-tree networks that support tens of thousands of nodes. We evaluate the run-time performance of the proposed algorithms and show improvement in orders of magnitude over the previously best known method. Finally, we further demonstrate a new application of max-min fair rate allocation that is only computationally feasible using our new algorithms.

97 MATHEMATICS AND COMPUTING↗