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At least 1,369 records · Page 76

A stochastic-dynamic model for the spatial structure of forecast error statistics

The present investigation is concerned with the presentation of a simplified model of the spatial structure of forecast error statistics, a comparison of the model with actual numerical weather prediction results, and the extent to which simplifying assumptions made in the model are justified. A stochastic-dynamic model is derived for the spatial structure of the global atmospheric mass-field forecast error. The model states that the relative potential vorticity of the forecast error is random. The covariance function of the model's solutions is found to be governed by a simple deterministic equation. The agreement between the stochastic model and actual mass-field forecast errors fields for 12-36 h periods validates the assumptions on which the model is derived. Within this period, the difference between the potential voriticity fields of the atmosphere and of the numerical forecasts used in the comparison is well represented by white noise.

Balgovind, R.↗

OPTICON: Pro-Matlab software for large order controlled structure design

A software package for large order controlled structure design is described and demonstrated. The primary program, called OPTICAN, uses both Pro-Matlab M-file routines and selected compiled FORTRAN routines linked into the Pro-Matlab structure. The program accepts structural model information in the form of state-space matrices and performs three basic design functions on the model: (1) open loop analyses; (2) closed loop reduced order controller synthesis; and (3) closed loop stability and performance assessment. The current controller synthesis methods which were implemented in this software are based on the Generalized Linear Quadratic Gaussian theory of Bernstein. In particular, a reduced order Optimal Projection synthesis algorithm based on a homotopy solution method was successfully applied to an experimental truss structure using a 58-state dynamic model. These results are presented and discussed. Current plans to expand the practical size of the design model to several hundred states and the intention to interface Pro-Matlab to a supercomputing environment are discussed.

Peterson, Lee D.↗

A Comparison of Geographic Information Systems, Complex Networks, and Other Models for Analyzing Transportation Network Topologies

This report reviews six classes of models that are used for studying transportation network topologies. The report is motivated by two main questions. First, what can the "new science" of complex networks (scale-free, small-world networks) contribute to our understanding of transport network structure, compared to more traditional methods? Second, how can geographic information systems (GIS) contribute to studying transport networks? The report defines terms that can be used to classify different kinds of models by their function, composition, mechanism, spatial and temporal dimensions, certainty, linearity, and resolution. Six broad classes of models for analyzing transport network topologies are then explored: GIS; static graph theory; complex networks; mathematical programming; simulation; and agent-based modeling. Each class of models is defined and classified according to the attributes introduced earlier. The paper identifies some typical types of research questions about network structure that have been addressed by each class of model in the literature.

Alexandrov, Natalia↗

An Active Subspace Method for Accelerating Convergence in Delaunay-Based Optimization via Dimension Reduction

Delaunay-based derivative-free optimization, ∆DOGS, is an efficient and provably-convergent global optimization method for the problems which has computationally expensive objection function and the analytical expression for the objective function is not available. ∆-DOGS is a novel optimization scheme in the family of response surface methods (RSMs); however, it suffers from the curse of dimensionality since the computational cost increases dramatically as the number of design parameters increases. As a result, the number of design parameters in ∆-DOGS algorithm is relatively low (n.10). To avoid such problems, this paper proposes a combination of derivative-free optimization, seeking the global minimizer of an expensive and nonconvex objective function f(x) and active subspace method, detecting the directions of the most variability using evaluations of the gradient. The contribution of other directions to the objective function is bounded by a sufficiently small constant. This new algorithm iteratively applied Delaunay-based derivative-free optimization to seek the minimizer on the d-dimensional active subspace that has most function variation. Inverse mapping is needed to project data from active subspace to full-model for evaluating function values. This task is overcome by solving an inequality constrained problem that curves the response surface of the objective function. The test results show that this strategy is effective on a handful of optimization problems.

Bewley, Thomas R.↗

X-ray Binary Luminosity Function Scaling Relations for Local Galaxies Based on Subgalactic Modeling

We present new Chandra constraints on the X-ray luminosity functions(XLFs)of X-ray binary(XRB)populations, as well as their scaling relations, for a sample of 38 nearby galaxies(D = 3.4–29 Mpc). Our galaxy sample is drawn primarily from the Spitzer Infrared Nearby Galaxies Survey(SINGS)and contains a wealth of Chandra(5.8 Ms total)and multiwavelength data, allowing for star formation rates(SFRs)and stellar masses(M⁎)to be measured on subgalactic scales. We divided the 2478 X-ray-detected sources into 21 subsamples in bins of specific SFR(sSFR ≡ SFR/M⁎)and constructed XLFs. To model the XLF dependence on sSFR, we fit a global XLF model, containing contributions from high-mass XRBs(HMXBs), low-mass XRBs(LMXBs), and background sources from the cosmic X-ray background that respectively scale with SFR, M⁎, and sky area. We find an HMXB XLF that is more complex in shape than previously reported and an LMXB XLF that likely varies with sSFR, potentially due to an age dependence. When applying our global model to XLF data for each individual galaxy, we discover a few galaxy XLFs that significantly deviate from our model beyond statistical scatter. Most notably, relatively low-metallicity galaxies have an excess of HMXBs above≈10^(38)erg/s, and elliptical galaxies that have relatively rich populations of globular clusters(GCs)show excesses of LMXBs compared to the global model. Additional modeling of how the XRB XLF depends on stellar age, metallicity, and GC specific frequency is required to sufficiently characterize the XLFs of galaxies.

Bret D. Lehmer↗

Benchmarking and parameter sensitivity of physiological and vegetation dynamics using the Functionally Assembled Terrestrial Ecosystem Simulator (FATES) at Barro Colorado Island, Panama

Plant functional traits determine vegetation responses to environmental variation, but variation in trait values is large, even within a single site. Likewise, uncertainty in how these traits map to Earth system feedbacks is large. We use a vegetation demographic model (VDM), the Functionally Assembled Terrestrial Ecosystem Simulator (FATES), to explore parameter sensitivity of model predictions, and comparison to observations, at a tropical forest site: Barro Colorado Island in Panama. We define a single 12-dimensional distribution of plant trait variation, derived primarily from observations in Panama, and define plant functional types (PFTs) as random draws from this distribution. We compare several model ensembles, where individual ensemble members vary only in the plant traits that define PFTs, and separate ensembles differ from each other based on either model structural assumptions or non-trait, ecosystem-level parameters, which include (a) the number of competing PFTs present in any simulation and (b) parameters that govern disturbance and height-based light competition. While single-PFT simulations are roughly consistent with observations of productivity at Barro Colorado Island, increasing the number of competing PFTs strongly shifts model predictions towards higher productivity and biomass forests. Different ecosystem variables show greater sensitivity than others to the number of competing PFTs, with the predictions that are most dominated by large trees, such as biomass, being the most sensitive. Changing disturbance and height-sorting parameters, i.e., the rules of competitive trait filtering, shifts regimes of dominance or coexistence between early- and late-successional PFTs in the model. Increases to the extent or severity of disturbance, or to the degree of determinism in height-based light competition, all act to shift the community towards early-successional PFTs. In turn, these shifts in competitive outcomes alter predictions of ecosystem states and fluxes, with more early-successional-dominated forests having lower biomass. It is thus crucial to differentiate between plant traits, which are under competitive pressure in VDMs, from those model parameters that are not and to better understand the relationships between these two types of model parameters to quantify sources of uncertainty in VDMs.

54 ENVIRONMENTAL SCIENCES↗

Simulation of Two-Fluid Flows by the Least-Squares Finite Element Method Using a Continuum Surface Tension Model

In this paper a numerical procedure for simulating two-fluid flows is presented. This procedure is based on the Volume of Fluid (VOF) method proposed by Hirt and Nichols and the continuum surface force (CSF) model developed by Brackbill, et al. In the VOF method fluids of different properties are identified through the use of a continuous field variable (color function). The color function assigns a unique constant (color) to each fluid. The interfaces between different fluids are distinct due to sharp gradients of the color function. The evolution of the interfaces is captured by solving the convective equation of the color function. The CSF model is used as a means to treat surface tension effect at the interfaces. Here a modified version of the CSF model, proposed by Jacqmin, is used to calculate the tension force. In the modified version, the force term is obtained by calculating the divergence of a stress tensor defined by the gradient of the color function. In its analytical form, this stress formulation is equivalent to the original CSF model. Numerically, however, the use of the stress formulation has some advantages over the original CSF model, as it bypasses the difficulty in approximating the curvatures of the interfaces. The least-squares finite element method (LSFEM) is used to discretize the governing equation systems. The LSFEM has proven to be effective in solving incompressible Navier-Stokes equations and pure convection equations, making it an ideal candidate for the present applications. The LSFEM handles all the equations in a unified manner without any additional special treatment such as upwinding or artificial dissipation. Various bench mark tests have been carried out for both two dimensional planar and axisymmetric flows, including a dam breaking, oscillating and stationary bubbles and a conical liquid sheet in a pressure swirl atomizer.

Wu, Jie↗

Lunar electromagnetic scattering. IV - Transfer functions in the long-wavelength limit

The theory for asymmetric lunar magnetic induction in the long-wavelength limit, applicable to induction in the solar wind and magnetosheath plasmas at frequencies no higher than about 0.01 Hz, is presented. The lunar response to arbitrary ambient field orientations can be synthesized from the responses to field fluctuations parallel and perpendicular to the cavity axis. Radial and tangential transfer functions for a particular lunar electrical conductivity model are shown as functions of frequency and angular distance from the cavity axis for parallel and perpendicular field directions. Transfer functions based on asymmetric theory are significantly different from those based on symmetric approximations. Conductivity profiles from inversions of a given data set are strongly dependent on the theory incorporated in the inversions, the nature of the driving field, and the assumed location of the observer. Thus lunar conductivity models from surface and orbital magnetometer data, obtained either on the dayside or the nightside of the moon, must be determined using asymmetric theory.

Schwartz, K.↗

Low Reynolds number kappa-epsilon modeling with the aid of direct simulation data

The constant C(sub mu) and the near-wall damping function f(sub mu) in the eddy-viscosity relation of the kappa-epsilon model are evaluated from direct numerical simulation (DNS) data for developed channel and boundary layer flow at two Reynolds numbers each. Various existing f(sub mu) model functions are compared with the DNS data, and a new function is fitted to the high-Reynolds-number channel flow data. The epsilon-budget is computed for the fully developed channel flow. The relative magnitude of the terms in the epsilon-equation is analyzed with the aid of scaling arguments, and the parameter governing this magnitude is established. Models for the sum of all source and sink terms in the epsilon-equation are tested against the DNS data, and an improved model is proposed.

Rodi, W.↗

Low Reynolds number k-epsilon modelling with the aid of direct simulation data

The constant C sub mu and the near-wall damping function f sub mu in the eddy-viscosity relation of the k-epsilon model are evaluated from direct numerical simulation (DNS) data for developed channel and boundary layer flow at two Reynolds numbers each. Various existing f sub mu model functions are compared with the DNS data, and a new function is fitted to the high-Reynolds-number channel flow data. The epsilon-budget is computed for the fully developed channel flow. The relative magnitude of the terms in the epsilon-equation is analyzed with the aid of scaling arguments, and the parameter governing this magnitude is established. Models for the sum of all source and sink terms in the epsilon-equation are tested against the DNS data, and an improved model is proposed.

Rodi, W.↗

Machine Learning-Assisted Recovery of Delicate Kinetic Information from Transient Reactor Experiments

Identifying active sites and their roles in chemical reaction steps remains a vital challenge in heterogeneous catalysis. Transient experiments offer a unique way to probe active sites and distinguish subtle kinetic features. Although physics-based analysis methods may be well-developed, they can be highly susceptible to experimental noise, and smoothing methods may erase or even distort important features; a smooth curve is not always the best curve. We demonstrate a new workflow for the direct interpretation of intrinsic kinetic information from exit flux curves measured in transient reactor experiments. This workflow contains three artificial neural networks (ANNs), including a noise reducer, a concentration predictor, and a rate predictor to analyze experimental data, followed by the virtual TAP (VTAP) physics-based reactor model and density functional theory (DFT) calculations of adsorption energies on specific sites. We use this workflow to analyze the data from experiments titrating Pt/Al 2 O 3 and Pt/SiO 2 catalysts with carbon monoxide (CO) in the temporal analysis of products (TAP) reactor. Our workflow separates the time-evolving chemical reaction and mass transfer information contained in the TAP pulse response. The existence of strong- and weak-binding sites on the Pt/Al 2 O 3 catalyst is observed in the catalyst titration experiment in the transient reactor. The structures of the strong- and weak-binding sites are then identified by using DFT calculations. We find that the Pt/SiO 2 catalyst has only strong-binding sites, which aligns with the inactive support effect of SiO 2 . We demonstrate how machine learning methods provide unique insights with high-resolution data analysis that cannot be achieved by using state-of-the-art physics-based methods.

Adsorption↗

Lattice QCD estimates of thermal photon production from the QGP

Thermal photons produced in heavy-ion collision experiments are an important observable for understanding quark-gluon plasma (QGP). The thermal photon rate from the QGP at a given temperature can be calculated from the spectral function of the vector current correlator. Extraction of the spectral function from the lattice correlator is known to be an ill-conditioned problem, as there is no unique solution for a spectral function for a given lattice correlator with statistical errors. The vector current correlator, on the other hand, receives a large ultraviolet contribution from the vacuum, which makes the extraction of the thermal photon rate difficult from this channel. We therefore consider the difference between the transverse and longitudinal part of the spectral function, only capturing the thermal contribution to the current correlator, simplifying the reconstruction significantly. The lattice correlator is calculated for light quarks in quenched QCD at T = 470 MeV ( ∼ 1.5 T c ), as well as in 2 + 1 flavor QCD at T = 220 MeV ( ∼ 1.2 T p c ) with m π = 320 MeV . In order to quantify the nonperturbative effects, the lattice correlator is compared with the corresponding NLO + LPM LO estimate of correlator. The reconstruction of the spectral function is performed in several different frameworks, ranging from physics-informed models of the spectral function to more general models in the Backus-Gilbert method and Gaussian process regression. We find that the resulting photon rates agree within errors. Published by the American Physical Society 2024

Astronomy & Astrophysics↗

Modeling DOE Standard Canister Configurations with Updated Surface Chemistry

Road-ready and final disposition packaging configurations for the advanced test reactor (ATR) fuel currently specifies storage within helium backfilled DOE sealed standard canisters. The aluminum cladding of the ATR fuel contains an oxyhydroxide layer of boehmite/bayerite that generates hydrogen when subjected to irradiation. Understanding the effect of this hydrogen buildup over time to important for long term storage considerations. Previous modeling efforts have built a coupled CFD-chemical model to simulate the temperature gas phase concentrations within the DOE sealed standard canisters. These models have coupled the temperature conditions to both the gas phase radiolysis chemistry and the surface chemistry associated with the oxyhydroxide layer. Continued experimental work has identified trends for aluminum surrogate samples with oxyhydroxide layers for tests done at higher dose rates. At low initial doses a fast generation rate of hydrogen occurs which starts to roll over to a lower generation rate as the total dose applied in increased. A previous study created a small-scale chemical model was built to replicate a mini-canister surrogate system at SRNL as well as for the smaller capsule tests performed at INL. The previous iteration of the model utilized step function for its G-values for the hydrogen generation over a 200-year period. This model makes an update to the surface chemistry to account for theorized surface chemistry reactions allowing for oxygen to remain bounded to the oxyhydroxide layer. As additional experiments continue, the kinetic fits may be adjusted to adapt to new data. Three canister configurations are modeled – the base 18-inch, 15-foot DOR standard canister with 30 ATR fuel elements, an 18-inch, 10-foot DOE standard canister with 32 ATR fuel elements and a 24-inch, 10-foot DOE standard canister with 40 ATR fuel elements. In previous reports, the primary sensitivity of the canister conditions was identified as the decay heat of the fuel and the dried condition of the fuel. Only these parameters are studied in the report. For the nominal case with dried fuel, the hydrogen generation is only about 2%, so it is even less than the flammability limit if it were exposed to oxygen. For the densely packed 18-inch case the total hydrogen concentration is only around 4% with the nominal decay heat. For the densely packed 24-inch case the total hydrogen concentration is only 2.5%, roughly 20% higher than the original packing design, and still under flammability conditions if exposed to oxygen.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Lunar Prospector Orbit Determination Uncertainties Using the High Resolution Lunar Gravity Models

The Lunar Prospector (LP) mission began on January 6, 1998, when the LP spacecraft was launched from Cape Canaveral, Florida. The objectives of the mission were to determine whether water ice exists at the lunar poles, generate a global compositional map of the lunar surface, detect lunar outgassing, and improve knowledge of the lunar magnetic and gravity fields. Orbit determination of LP performed at the Jet Propulsion Laboratory (JPL) is conducted as part of the principal science investigation of the lunar gravity field. This paper will describe the JPL effort in support of the LP Gravity Investigation. This support includes high precision orbit determination, gravity model validation, and data editing. A description of the mission and its trajectory will be provided first, followed by a discussion of the orbit determination estimation procedure and models. Accuracies will be examined in terms of orbit-to-orbit solution differences, as a function of oblateness model truncation, and inclination in the plane-of-sky. Long term predictions for several gravity fields will be compared to the reconstructed orbits to demonstrate the accuracy of the orbit determination and oblateness fields developed by the Principal Gravity Investigator.

Carranza, Eric↗

Documenting AUTOGEN and APGEN Model Files

A computer program called "autogen hypertext map generator" satisfies a need for documenting and assisting in visualization of, and navigation through, model files used in the AUTOGEN and APGEN software mentioned in the two immediately preceding articles. This program parses autogen script files, autogen model files, PERL scripts, and apgen activity-definition files and produces a hypertext map of the files to aid in the navigation of the model. This program also provides a facility for adding notes and descriptions, beyond what is in the source model represented by the hypertext map. Further, this program provides access to a summary of the model through variable, function, sub routine, activity and resource declarations as well as providing full access to the source model and source code. The use of the tool enables easy access to the declarations and the ability to traverse routines and calls while analyzing the model.

Gladden, Roy E.↗

Model-Driven Development of Reliable Avionics Architectures for Lunar Surface Systems

This paper discusses a method used for the systematic improvement of NASA s Lunar Surface Systems avionics architectures in the area of reliability and fault-tolerance. This approach utilizes an integrated system model to determine the effects of component failure on the system s ability to provide critical functions. A Markov model of the potential degraded system modes is created to characterize the probability of these degraded modes, and the system model is run for each Markov state to determine its status (operational or system loss). The probabilistic results from the Markov model are first produced from state transition rates based on NASA data for heritage failure rate data of similar components. An additional set of probabilistic results are created from a representative set of failure rates developed for this study, for a variety of component quality grades (space-rated, mil-spec, ruggedized, and commercial). The results show that careful application of redundancy and selected component improvement should result in Lunar Surface Systems architectures that exhibit an appropriate degree of fault-tolerance, reliability, performance, and affordability.

Borer, Nicholas↗

Bayesian Monte Carlo Evaluation Framework for Imperfect Data and Models [Abstract]

Nuclear data evaluation methods conventionally make the following assumptions: prior and posterior probability distribution functions (PDFs) of all model parameters and data are normal (Gaussian); the linear approximation is sufficiently accurate for minimization of a cost function (even for non-linear models); and that both the model (of, e.g., neutron cross section) and experimental data (including their covariance data) are perfect. These assumptions are inherent to the well-known generalized linear least squares (GLLS) minimization method commonly used for evaluations of resolved resonance region (RRR) neutron cross sections. However, these assumptions are often not justified due to the presence of non-normal PDFs, non-linear models (e.g. R -matrix formalism), and inherent imperfections in data and models (e.g. discrepant data sets, discrepancies between the previous evaluation and newly measured data, or imperfect covariance data). We remove the said assumptions in a mathematical framework of Bayes’ theorem, and implement it using the Metropolis-Hastings Monte Carlo method. Parameters of a new kind are introduced to parameterize inherent imperfections, e.g. , any discrepancies between the theoretical model and measured data. These new parameters enable evaluators to quantify their expert judgement about any discrepancies or imperfections in a reproducible manner. We demonstrate the framework with an ongoing evaluation of 233 U in the eV region using the ENDF-B/VIII library and transmission data measured by Guber, et al. , and compare the posterior parameters to those obtained by conventional evaluation methods.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

A kinetic line-driven radiation operator and its application to Gyrokinetics

A velocity dependent, kinetic model for line radiation is developed for continuum kinetic codes. It has been implemented in the full-f gyrokinetic code Gkeyll. The total radiation for a charge state is modeled as an advection in velocity space with a form of $\nabla_v \cdot(v\nu(v)f(v))$, guaranteeing particle conservation. The velocity dependence (in the form of an effective frequency $\nu(v)$) is found through fitting the energy loss of the operator, i.e. the second velocity moment, to the radiation data in the OpenADAS database. Therefore, each individual transition does not need to be evaluated every time step, significantly reducing the computational cost of including line radiation in a kinetic model. The dependence on velocity instead of the usual, temperature, allows the radiation to be computed from non-Maxwellian electron distribution functions: We benchmark the model against a collisional radiative model using isotropic non-Maxwellian distribution functions. A velocity dependent model of radiation can more accurately describe the radiation in the more kinetic regimes expected in reactor-scale devices. The velocity dependence qualitatively captures the quantum mechanical need for a minimum velocity before any radiation occurs.

kinetic↗