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At least 1,657 records · Page 92
All sourcesNASA NTRSDOE OSTI
NASA NTRS2010

Turbulence and the Stabilization Principle

Further results of research, reported in several previous NASA Tech Briefs articles, were obtained on a mathematical formalism for postinstability motions of a dynamical system characterized by exponential divergences of trajectories leading to chaos (including turbulence). To recapitulate: Fictitious control forces are introduced to couple the dynamical equations with a Liouville equation that describes the evolution of the probability density of errors in initial conditions. These forces create a powerful terminal attractor in probability space that corresponds to occurrence of a target trajectory with probability one. The effect in ordinary perceived three-dimensional space is to suppress exponential divergences of neighboring trajectories without affecting the target trajectory. Con sequently, the postinstability motion is represented by a set of functions describing the evolution of such statistical quantities as expectations and higher moments, and this representation is stable. The previously reported findings are analyzed from the perspective of the authors Stabilization Principle, according to which (1) stability is recognized as an attribute of mathematical formalism rather than of underlying physics and (2) a dynamical system that appears unstable when modeled by differentiable functions only can be rendered stable by modifying the dynamical equations to incorporate intrinsic stochasticity.

Zak, Michail↗
DOE OSTI2021

Computational Investigation of the Role of Active Site Heterogeneity for aSupported Organovanadium(III) Hydrogenation Catalyst

A crucial consideration for supported heterogeneous catalysts is the nonuniformity of the active sites, particularly for supported organometallic catalysts. Standard spectroscopic techniques, such as X-ray absorption spectroscopy, reflect the nature of the most populated sites, which are often intrinsically structurally distinct from the most active catalytic sites. Additionally, with computational models, often, only a few representative structures are used to depict catalytic active sites on a surface, even though there are numerous observable factors of surface heterogeneity that contribute to the kinetically favorable active species. A previously reported study on the mechanism of a surface organovanadium-(III) catalyst [(SiO 2 )V III (Mes)(THF)] for styrene hydrogenation yielded two possible mechanisms: heterolytic cleavage and redox cycling. These two mechanistic scenarios are challenging to differentiate experimentally since the kinetic readouts of the catalyst are identical. To showcase the importance of modeling surface heterogeneity and its effect on catalytic activity, density functional theory (DFT) computational models of a series of potential active sites of [(SiO 2 )V III (Mes)(THF)] for the reaction pathways are applied in combination with kinetic Monte Carlo (kMC) simulations. Computed results were then compared to the previously reported experimental kinetic study: (1) DFT free-energy reaction pathways indicated the likely active site and pathway for styrene hydrogenation, a heterolytic cleavage pathway requiring a bare tripodal vanadium site. (2) From the kMC simulations, a mixture of different bond lengths from the support oxygen to the metal center was required to qualitatively describe the experimentally observed kinetic aspects of a supported organovanadium(III) catalyst for olefin hydrogenation. This work underscores the importance of modeling surface heterogeneity in computational catalysis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Leveraging prior mean models for faster Bayesian optimization of particle accelerators

Tuning particle accelerators is a challenging and time-consuming task that can be automated and carried out efficiently using suitable optimization algorithms, such as model-based Bayesian optimization techniques. One of the major advantages of Bayesian algorithms is the ability to incorporate prior information about beam physics and historical behavior into the model used to make control decisions. In this work, we examine incorporating prior accelerator physics information into Bayesian optimization algorithms by utilizing fast executing, neural network models trained on simulated or historical datasets as prior mean functions in Gaussian process models. We show that in ideal cases, this technique substantially increases convergence speed to optimal solutions in high-dimensional tuning parameter spaces. Additionally, we demonstrate that even in non-ideal cases, where prior models of beam dynamics do not exactly match experimental conditions, the use of this technique can still enhance convergence speed. Finally, we demonstrate how these methods can be used to improve optimization in practical applications, such as transferring information gained from beam dynamics simulations to online control of the LCLS injector, and transferring knowledge gained from experimental measurements across different operating modes, such as accelerating different ion species at the ATLAS heavy ion accelerator.

43 PARTICLE ACCELERATORS↗
NASA NTRS1971

Simulation of Mariner Mars 1971 spacecraft

Preparation for the Mariner Mars 1971 mission is reported, including an extensive training program for operations personnel during which the primary source of spacecraft data was a computer program simulating the spacecraft. The objectives of a simulation model for training purposes differed from objectives appropriate to a design or analysis model. Model subsystems were designed to provide realistic telemetry data reflecting changes due both to commands and environmental parameters affecting the spacecraft at various times during the mission. The spacecraft is modeled along two separate functional lines. Boolean operations are concentrated in the spacecraft logic model, which determines the spacecraft state or mode, while mathematical operations or algorithms are executed in computational subsystem models. Although logic parameters are interrogated as a part of each computational pass, actual logic model processing occurs only when a change-of-state input is generated by the operations organization. The program design, some of the special characteristics of each of the modeled subsystems, and how the model was used in support of mission operations training are presented.

Ausman, N. E., Jr.↗
NASA NTRS1992

On recontamination and directional-bias problems in Monte Carlo simulation of PDF turbulence models

Turbulent combustion can not be simulated adequately by conventional moment closure turbulent models. The probability density function (PDF) method offers an attractive alternative: in a PDF model, the chemical source terms are closed and do not require additional models. Because the number of computational operations grows only linearly in the Monte Carlo scheme, it is chosen over finite differencing schemes. A grid dependent Monte Carlo scheme following J.Y. Chen and W. Kollmann has been studied in the present work. It was found that in order to conserve the mass fractions absolutely, one needs to add further restrictions to the scheme, namely alpha(sub j) + gamma(sub j) = alpha(sub j - 1) + gamma(sub j + 1). A new algorithm was devised that satisfied this restriction in the case of pure diffusion or uniform flow problems. Using examples, it is shown that absolute conservation can be achieved. Although for non-uniform flows absolute conservation seems impossible, the present scheme has reduced the error considerably.

Hsu, Andrew T.↗
NASA NTRS1991

Second-order near-wall turbulence closures - A review

Advances in second-order near-wall turbulence closures are summarized. All closures under consideration are based on high-Reynolds-number models. Most near-wall closures proposed to date attempt to modify the high-Reynolds-number models for the dissipation function and the pressure redistribution term so that the resultant models are applicable all the way to the wall. The asymptotic behavior of the near-wall closures is examined and compared with the proper near-wall behavior of the exact Reynolds-stress equations. It is found that three second-order near-wall closures give the best correlations with simulated turbulence statistics. However, their predictions of near-wall Reynolds-stress budgets are considered to be incorrect. A proposed modification to the dissipitation-rate equation remedies part of those predictions. It is concluded that further improvements are required if a complete replication of all the turbulence properties and Reynolds-stress budgets by a statistical model of turbulence is desirable.

So, R. M. C.↗
NASA NTRS1999

Development of Response Surface Models for Rapid Analysis & Multidisciplinary Optimization of Launch Vehicle Design Concepts

Multdisciplinary design optimization (MDO) is an important step in the design and evaluation of launch vehicles, since it has a significant impact on performance and lifecycle cost. The objective in MDO is to search the design space to determine the values of design parameters that optimize the performance characteristics subject to system constraints. Vehicle Analysis Branch (VAB) at NASA Langley Research Center has computerized analysis tools in many of the disciplines required for the design and analysis of launch vehicles. Vehicle performance characteristics can be determined by the use of these computerized analysis tools. The next step is to optimize the system performance characteristics subject to multidisciplinary constraints. However, most of the complex sizing and performance evaluation codes used for launch vehicle design are stand-alone tools, operated by disciplinary experts. They are, in general, difficult to integrate and use directly for MDO. An alternative has been to utilize response surface methodology (RSM) to obtain polynomial models that approximate the functional relationships between performance characteristics and design variables. These approximation models, called response surface models, are then used to integrate the disciplines using mathematical programming methods for efficient system level design analysis, MDO and fast sensitivity simulations. A second-order response surface model of the form given has been commonly used in RSM since in many cases it can provide an adequate approximation especially if the region of interest is sufficiently limited.

Unal, Resit↗
NASA NTRS2011

Ontological Modeling for Integrated Spacecraft Analysis

Current spacecraft work as a cooperative group of a number of subsystems. Each of these requiresmodeling software for development, testing, and prediction. It is the goal of my team to create anoverarching software architecture called the Integrated Spacecraft Analysis (ISCA) to aid in deploying the discrete subsystems' models. Such a plan has been attempted in the past, and has failed due to the excessive scope of the project. Our goal in this version of ISCA is to use new resources to reduce the scope of the project, including using ontological models to help link the internal interfaces of subsystems' models with the ISCA architecture.I have created an ontology of functions specific to the modeling system of the navigation system of a spacecraft. The resulting ontology not only links, at an architectural level, language specificinstantiations of the modeling system's code, but also is web-viewable and can act as a documentation standard. This ontology is proof of the concept that ontological modeling can aid in the integration necessary for ISCA to work, and can act as the prototype for future ISCA ontologies.

ontological modeling↗
DOE OSTI2020

Reaction Mechanism of Vapor-Phase Formic Acid Decomposition over Platinum Catalysts: DFT, Reaction Kinetics Experiments, and Microkinetic Modeling

A combination of periodic density functional theory (DFT, PW91-GGA) calculations, reaction kinetics experiments, and mean-field microkinetic modeling is used to derive insights on the reaction mechanism and determine the nature of the active site under reaction conditions for the vapor-phase decomposition of formic acid (FA, HCOOH) over Pt/C catalysts. Microkinetic models formulated using DFT energetics derived on the clean Pt(100) and Pt(111) required large parameter adjustments to reproduce the experimentally measured apparent activation energies and reaction orders. Further, these models predicted high surface coverage of adsorbed carbon monoxide (CO*), inconsistent with the environment of the active site in the DFT calculations on the clean surfaces. Consequently, we reperformed DFT calculations for the entire reaction network on partially CO*-covered (4/9 monolayer, ML) Pt(111) and Pt(100). The resultant microkinetic models, with thermochemistry and kinetics explicitly dependent on CO* coverage, were able to reproduce the experimentally determined activation energies and reaction orders, in addition to being self-consistent in CO* coverage. Our results suggest that Pt(100) is likely poisoned by CO* under typical reaction conditions and does not contribute significantly to the experimentally observed reactivity. Instead, we find that Pt(111) better represents the active site for FA decomposition reaction on Pt/C catalysts. The optimized model on 4/9 ML CO*-covered Pt(111) suggests that the reaction occurs via the carboxyl (COOH*) intermediate and that the spectator CO*-assisted pathways play a significant role under reaction conditions. Lastly, this study underscores the importance of spectator species on the energetics and the mechanism of a catalytic reaction and their key role in developing a model that better addresses the nature of the active site under realistic catalytic reaction conditions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Modeling quasielastic interactions of monoenergetic kaon decay-at-rest neutrinos

Monoenergetic muon neutrinos at 236 MeV are readily produced in intense medium-energy proton facilities (≳2–3GeV) when a positive kaon decays at rest (KDAR; K + →μ + ν μ ). These neutrinos provide a unique opportunity to both study the neutrino interaction and probe the nucleus with a monoenergetic weak-interaction-only tool. We present cross-section calculations for quasielastic scattering of these 236-MeV neutrinos off 12 C and 40 Ar, paying special attention to low-energy aspects of the scattering process. Our model takes the description of the nucleus in a mean-field approach as the starting point, where we solve Hartree-Fock equations using a Skyrme type nucleon-nucleon interaction. Thereby, we introduce long-range nuclear correlations by means of a continuum random-phase approximation (CRPA) framework where we solve the CRPA equations using a Green's function method. The model successfully describes (e,e') data on 12 C and 40 Ca in the kinematic region that overlaps with the KDAR ν μ phase space. In addition to these results, we present future prospects for precision KDAR cross-section measurements and applications of our calculations in current and future experiments that will utilize these neutrinos.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

Electronic Structure Theory and Novel Materials

This grant supported research on electronic structure and materials theory, with focus on three main issues: (i) novel techniques to deal with correlation in the electronic ground-state, (ii) topological materials, (iii) the phase diagram of lattice spin models. Regarding (i), we applied to the homogeneous electron liquid an approach that we previously developed in the context of molecular systems. In this scheme the electronic occupation probabilities and the natural spin orbitals are used to construct an approximate two-body density matrix for the electronic ground-state. Regarding (ii) we used standard electronic structure methods based on density functional theory to model topological materials and interpret experimental observations. Finally, regarding (iii) we further developed a numerical approach to compute the renormalized couplings within real space renormalization group theory in the context of lattice spin models. The main findings were the following. (i) We found that with our approximate two-body density matrix, which works well for small molecules, is not sufficiently accurate for condensed phase systems. Missing a systematic way of improving on the adopted approximations, we decided not to pursue this approach. (ii) We performed two studies. In one, we investigated the influence of Te defects on the topological properties of a WTe2 monolayer, finding that while Te vacancies, even in modest concentration, destroy the topological character, Te adatoms do not, consistent with a recent experiment. In another study, we predicted Weyl semimetal character and strong anomalous Hall effect in the Heusler compensated ferrimagnet Ti2MnAl. (iii) We developed a new Monte Carlo method to do real space renormalization group calculations for lattice spin models. We subsequently extended the scheme to deal with lattice spin models in presence of quenched disorder, finding that the approach can distinguish systems with finite and strong disorder. In the finite disorder case, the method allows one to find with good approximation the critical coupling distribution and the critical exponents.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2022

Supervised learning and the finite-temperature string method for computing committor functions and reaction rates

A central object in the computational studies of rare events is the committor function. Though costly to compute, the committor function encodes complete mechanistic information of the processes involving rare events, including reaction rates and transition-state ensembles. Under the framework of transition path theory, Rotskoff et al. [Proceedings of the 2nd Mathematical and Scientific Machine Learning Conference, Proceedings of Machine Learning Research (PLMR, 2022), Vol. 145, pp. 757–780] proposes an algorithm where a feedback loop couples a neural network that models the committor function with importance sampling, mainly umbrella sampling, which collects data needed for adaptive training. Here, in this work, we show additional modifications are needed to improve the accuracy of the algorithm. The first modification adds elements of supervised learning, which allows the neural network to improve its prediction by fitting to sample-mean estimates of committor values obtained from short molecular dynamics trajectories. The second modification replaces the committor-based umbrella sampling with the finite-temperature string (FTS) method, which enables homogeneous sampling in regions where transition pathways are located. We test our modifications on low-dimensional systems with non-convex potential energy where reference solutions can be found via analytical or finite element methods, and show how combining supervised learning and the FTS method yields accurate computation of committor functions and reaction rates. We also provide an error analysis for algorithms that use the FTS method, using which reaction rates can be accurately estimated during training with a small number of samples. The methods are then applied to a molecular system in which no reference solution is known, where accurate computations of committor functions and reaction rates can still be obtained.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS2006

Problem Formulation for Optimal Array Modeling and Planning

In this paper we describe an optimal modeling and planning framework for the future large array of DSN antennas. This framework takes into account the array link performance models, reliability models, constrain models, and objective functions, and determines the optimal sub-array clusters configuration that will support the maximum number of concurrent missions based on mission link properties, antenna element reliabilities, mission requests, and array operation constraints. ..

modeling↗
DOE OSTI2025

Investigating late-stage particle production in pp collisions with balance functions

Balance functions have been regarded in the past as a method of investigating the late-stage hadronization found in the presence of a strongly-coupled medium. They are also used to constrain mechanisms of particle production in large and small collision systems. Charge balance functions for inclusive and identified particle pairs are reported as a function of charged particle multiplicity in proton–proton collisions simulated with the PYTHIA8 and the EPOS4 models. The charge balance functions of inclusive, pion, kaon, and proton pairs exhibit amplitudes and shapes that depend on particle species and differ significantly in the two models due to the different particle production mechanisms implemented in PYTHIA and EPOS. The shapes and amplitudes also evolve with multiplicity in both models. In addition, the evolution of the longitudinal rms width and that of balance functions integrals with multiplicity (and average transverse momentum) feature significant differences in the two models.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
NASA NTRS1980

A mathematical model of post-instability in continuum mechanics

The post-instability can appear in the form of failure of hyperbolicity or in the form of cascade instability (stretching of vorticity in an inviscid fluid or instability of the Navier-Stokes equations). All the cases are characterized by an unlimited decrease of the scale of the motions, in the course of which the derivatives of the corresponding functions tend to infinity, though the functions themselves remain finite. Such an instability shows that the corresponding state of a continuum cannot be properly simulated by smooth functions. Hence, the original model must be corrected by giving up the requirement about differentiability and enlarging the class of functions. Applications to a model of an inviscid fluid and to a model of turbulence are discussed.

Zak, M.↗
DOE OSTI2023

Haplotype‐resolved genome assembly of Populus tremula × P. alba reveals aspen‐specific megabase satellite DNA

SUMMARY Populus species play a foundational role in diverse ecosystems and are important renewable feedstocks for bioenergy and bioproducts. Hybrid aspen Populus tremula × P. alba INRA 717‐1B4 is a widely used transformation model in tree functional genomics and biotechnology research. As an outcrossing interspecific hybrid, its genome is riddled with sequence polymorphisms which present a challenge for sequence‐sensitive analyses. Here we report a telomere‐to‐telomere genome for this hybrid aspen with two chromosome‐scale, haplotype‐resolved assemblies. We performed a comprehensive analysis of the repetitive landscape and identified both tandem repeat array‐based and array‐less centromeres. Unexpectedly, the most abundant satellite repeats in both haplotypes lie outside of the centromeres, consist of a 147 bp monomer PtaM147, frequently span >1 megabases, and form heterochromatic knobs. PtaM147 repeats are detected exclusively in aspens (section Populus ) but PtaM147‐like sequences occur in LTR‐retrotransposons of closely related species, suggesting their origin from the retrotransposons. The genomic resource generated for this transformation model genotype has greatly improved the design and analysis of genome editing experiments that are highly sensitive to sequence polymorphisms. The work should motivate future hypothesis‐driven research to probe into the function of the abundant and aspen‐specific PtaM147 satellite DNA.

Zhou, Ran↗
NASA NTRS1993

The three-point correlation function in an ensemble of three-dimensional simulations

We evaluate the three-point function in Fourier space for an ensemble of three-dimensional 128 exp 3 numerical simulations with initial power spectra characterized by spectral index n = +1, 0, -1, -2, -3, with no high-frequency cutoff and with cutoff k(c) = 16 or k(c) = 4. To remove dependences on scale and on time, we present results as the reduced amplitude Q in the hierarchical model as a function of the dimensionless variable kd(rms), where d(rms) is the mean square displacement of a particle from its initial position. For scale-free initial conditions, there is no evolution in Q. For initial conditions with a cutoff, Q evolves until the scale of the cutoff is in the nonlinear regime; the results afterwards are no different from those with no initial cutoff. The transition from quasi-linear to nonlinear regimes is followed. In the quasi-linear regime, our results agree well with gravitational perturbation theory predictions, including a marked dependence on the shape of the configuration. In the nonlinear regime, the value of Q for scale-invariant initial conditions is remarkably independent of evolution epoch, of scale, and of configuration shape, and depends on spectral index roughly as Q = 3/(3 + n).

Fry, J. N.↗
NASA NTRS2003

Numerical Simulations of STOVL Hot Gas Ingestion in Ground Proximity Using a Multigrid Solution Procedure

A multi grid solution procedure for the numerical simulation of turbulent flows in complex geometries has been developed. A Full Multigrid-Full Approximation Scheme (FMG-FAS) is incorporated into the continuity and momentum equations, while the scalars are decoupled from the multi grid V-cycle. A standard kappa-Epsilon turbulence model with wall functions has been used to close the governing equations. The numerical solution is accomplished by solving for the Cartesian velocity components either with a traditional grid staggering arrangement or with a multiple velocity grid staggering arrangement. The two solution methodologies are evaluated for relative computational efficiency. The solution procedure with traditional staggering arrangement is subsequently applied to calculate the flow and temperature fields around a model Short Take-off and Vertical Landing (STOVL) aircraft hovering in ground proximity.

Wang, Gang↗