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At least 739 records · Page 41
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

How to identify different new neutrino oscillation physics scenarios at DUNE

Next generation neutrino oscillation experiments are expected to measure the remaining oscillation parameters with very good precision. They will have unprecedented capabilities to search for new physics that modify oscillations. DUNE, with its broad band beam, good particle identification, and relatively high energies will provide an excellent environment to search for new physics. If deviations from the standard three-flavor oscillation picture are seen however, it is crucial to know which new physics scenario is found so that it can be verified elsewhere and theoretically understood. We investigate several benchmark new physics scenarios by looking at existing long-baseline accelerator neutrino data from NOvA and T2K and determine at what sensitivity DUNE can differentiate among them. We consider sterile neutrinos and both vector and scalar non-standard neutrino interactions, all with new complex phases, the latter of which could conceivably provide absolute neutrino mass scale information. We find that, in many interesting cases, DUNE will have good model discrimination. We also perform a new fit to NOvA and T2K data with scalar NSI.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

Electron emission from bromouracil and uracil induced by protons and radiosensitization

Absolute double differential cross sections (DDCS) of electrons emitted from uracil and 5-bromouracil (BrU) in collisions with protons of energy 200 keV have been measured for various forward and backward emission angles over wide range of electron energies. The measured DDCS are compared with the continuum distorted wave-eikonal initial state (CDW-EIS) calculations. The optimized structure of the BrU was estimated along with the population analysis of all the occupied orbitals using a self-consistent field density. A comparison between the measured DDCS data for the two molecules show that the cross section of low energy electrons emitted from BrU is substantially larger than that for uracil. The BrU-to-uracil DDCS ratios obtained from the present measurements indicate an enhancement of the electron emission by a factor which is as large as 2.0 to 2.5. These electrons being the major agent for damaging the DNA/RNA of the malignant tissues, the present results are expected to provide an important input for the radiosensitization effect in hadron therapy. It is noteworthy to mention that the CDW-EIS calculations for Coulomb ionization cannot predict such enhancement. A large angular asymmetry is observed for uracil with a broad structure, which is absent in case of BrU.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

Reliable extrapolation of deep neural operators informed by physics or sparse observations

Deep neural operators can learn nonlinear mappings between infinite-dimensional function spaces via deep neural networks. As promising surrogate solvers of partial differential equations (PDEs) for real-time prediction, deep neural operators such as deep operator networks (DeepONets) provide a new simulation paradigm in science and engineering. Pure data-driven neural operators and deep learning models, in general, are usually limited to interpolation scenarios, where new predictions utilize inputs within the support of the training set. However, in the inference stage of real-world applications, the input may lie outside the support, i.e., extrapolation is required, which may result to large errors and unavoidable failure of deep learning models. Here, we address this challenge of extrapolation for deep neural operators. First, we systematically investigate the extrapolation behavior of DeepONets by quantifying the extrapolation complexity, via the 2-Wasserstein distance between two function spaces and propose a new strategy of bias–variance trade-off for extrapolation with respect to model capacity. Subsequently, we develop a complete workflow, including extrapolation determination, and we propose five reliable learning methods that guarantee a safe prediction under extrapolation by requiring additional information—the governing PDEs of the system or sparse new observations. The proposed methods are based on either fine-tuning a pre-trained DeepONet or multifidelity learning. We demonstrate the effectiveness of the proposed framework for various types of parametric PDEs. Furthermore, our systematic comparisons provide practical guidelines for selecting a proper extrapolation method depending on the available information, desired accuracy, and required inference speed.

42 ENGINEERING↗
DOE OSTI2022

GenASiS Mathematics: Object-oriented manifolds, operations, and solvers for large-scale physics simulations (version 2)

We report GenASiS Mathematics provides modern Fortran classes furnishing extensible object-oriented functionality for the solution of fields governed by selected partial differential equations. The initial release included extensible object-oriented implementations of simple meshes and the evolution of generic conserved currents thereon. This revision - Version 2 of Mathematics - includes significant reorganization and streamlining of these classes, higher-order reconstruction by a different method, a Poisson solver, coarsening to avoid Courant time step limitations near coordinate singularities, and the offloading of computational kernels to GPUs.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1974

The differential rotation of the solar surface

The large-scale flow in the solar convection zone is discussed. The objective is to deduce from observation the principal physical balances in the governing equations. The simplest set of equations that seem potentially realistic are utilized. It is assumed that magnetic fields are negligible, that mixing-length theory gives an accurate representation of the mean structure, and that rigid-body rotation exists at the base. It is deduced that the zonal glow is geostrophic, the meridional flow is controlled by friction, and diffusive heating balances advective cooling due to vertical motion. Next, a detailed calculation of the latitude profile of surface angular velocity is performed, based on approximate equations containing only the principal balances, and agrees well with observation. Finally, it is demonstrated that the amplitude of the flow may be determined by the constraint that the net equatorward angular momentum flux vanish. The conclusions are consistent with the hypothesis that the flow is primarily a single large axisymmetric convection cell in each hemisphere.

Gierasch, P. J.↗
DOE OSTI2025

Understanding the Role of Hydroxyl Functionalization in Linear Poly(Ethylenimine) for Oxidation‐Resistant Direct Air Capture of CO 2

Aminopolymer-based adsorbents are a prominent class of materials being used for direct air capture of CO 2 at the industrial scale. However, improving their working lifetime, specifically by increasing their resilience to oxidative degradation, remains an ongoing challenge. Toward this end, functionalization of aminopolymers with non-amine functionalities such as hydroxyls has emerged in recent years as a promising strategy toward improving adsorbent lifetime. Although there is a growing body of work demonstrating the effectiveness of this approach and investigating the origin of this improved stability, studies to date have primarily focused on branched aminopolymer systems such as branched poly(ethylenimine). In this work, hydroxyl-functionalized linear poly(ethylenimine) is used to continue to probe the underlying protective mechanism of this strategy. A combination of thermogravimetric analysis, NMR relaxometry, differential scanning calorimetry, and computational simulations is used to better understand the relationship between the extent of chemical functionalization, physical properties, and adsorbent performance.

amine-based adsorbent↗
DOE OSTI2021

Identifiability and predictability of integer- and fractional-order epidemiological models using physics-informed neural networks

Here we analyze a plurality of epidemiological models through the lens of physics-informed neural networks (PINNs) that enable us to identify time-dependent parameters and data-driven fractional differential operators. In particular, we consider several variations of the classical susceptible-infectious-removed (SIR) model by introducing more compartments and fractional-order and time-delay models. We report the results for the spread of COVID-19 in New York City, Rhode Island and Michigan states and Italy, by simultaneously inferring the unknown parameters and the unobserved dynamics. For integer-order and time-delay models, we fit the available data by identifying time-dependent parameters, which are represented by neural networks. In contrast, for fractional differential models, we fit the data by determining different time-dependent derivative orders for each compartment, which we represent by neural networks. We investigate the structural and practical identifiability of these unknown functions for different datasets, and quantify the uncertainty associated with neural networks and with control measures in forecasting the pandemic.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Inverse rendering of fusion plasmas: Inferring plasma composition from imaging systems

In this work, we develop a differentiable rendering pipeline for visualising plasma emission within tokamaks, and estimating the gradients of the emission and estimating other physical quantities. Unlike prior work, we are able to leverage arbitrary representations of plasma quantities and easily incorporate them into a non-linear optimisation framework. The efficiency of our method enables not only estimation of a physically plausible image of plasma, but also recovery of the neutral Deuterium distribution from imaging and midplane measurements alone. We demonstrate our method with three different levels of complexity showing first that a poloidal neutrals density distribution can be recovered from imaging alone, second that the distributions of neutral Deuterium, electron density and electron temperature can be recovered jointly, and finally, that this can be done in the presence of realistic imaging systems that incorporate sensor cropping and quantisation.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Development of Manganese and Iron Mixed Metal Oxides for Thermochemical Energy Storage

Energy storage plays an essential role for sustainable and renewable energy use in an effort to reduce carbon emissions. Thermochemical energy storage (TCES) is a favorable alternative to fossil fuel energy systems and a promising solution to the intermittency problem of renewable energy sources (such as solar energy). TCES stores energy in the form of chemical bonds using reversible redox reactions (such as manganese metal oxides). This study developed manganese oxide (Mn2O3) and iron oxide (Fe2O3) with an inert dispersant of silicon dioxide (SiO2) (Mn-Fe-Si) for potential large scale energy storage application. These metal oxides are nontoxic, cheap, and relatively abundant. The materials were prepared with varying metal oxide content using physical mixing in a ball mill, pressure pelletization and calcination at different temperatures. Redox cycle tests were conducted using differential scanning calorimetry combined with thermogravimetric analysis (TGA-DSC). The Mn-Fe-Si materials had higher cyclability and energy release compared to the pure metal oxides and manganese oxide with SiO2. The calcination temperature had a significant effect on releasable energy due to the interactions between the oxides. The Mn-Fe-Si mixture calcined at high temperature (1000oC) showed the highest average energy storage density.

Wilkinson, Olivia↗
NASA NTRS1972

Thin film fuel cell electrodes.

Earlier work shows that fuel cell electrodes prepared by sputtering thin films of platinum on porous vycor substrates avoid diffusion limitations even at high current densities. The presented study shows that the specific activity of sputtered platinum is not unusually high. Performance limitations are found to be controlled by physical processes, even at low loadings. Catalyst activity is strongly influenced by platinum sputtering parameters, which seemingly change the surface area of the catalyst layer. The use of porous nickel as a substrate shows that pore size of the substrate is an important parameter. It is noted that electrode performance increases with increasing loading for catalyst layers up to two microns thick, thus showing the physical properties of the sputtered layer to be different from platinum foil. Electrode performance is also sensitive to changing differential pressure across the electrode. The application of sputtered catalyst layers to fuel cell matrices for the purpose of obtaining thin total cells appears feasible.

Asher, W. J.↗
NASA NTRS1978

Nature and evolution of the meteorite parent bodies: Evidence from petrology and metallurgy

The physical as well as chemical properties of the meteorite parent bodies are reviewed and it is concluded that many differentiated meteorites were likely formed in asteroidal-sized parents. A new model is developed for the formation of pallasites at the interface between an iron core and olivine mantle in differentiated bodies only about 10 km in diameter, which are later incorporated into a second generation of larger (100 km) parent bodies.

Wood, J. A.↗
NASA NTRS1983

Adaptive grids generated by elliptic systems

It is pointed out that a finite difference grid which moves with the solution of the partial differential equation being solved can improve the accuracy and efficiency of a numerical algorithm. This technique is particularly advantageous in the solution of problems involving boundary layers or shocks where a poorly chosen grid may give a numerical solution which is useless because of poor resolution or extreme oscillations. The present investigation is concerned with the development of a scheme which does not excessively distort the grid. The grid generation algorithm is based on the numerical solution of a system of elliptic differential equations. Holst and Brown (1981) have used a preliminary solution to move points on the boundary of the physical region and then resolved the problem on a new grid generated by an elliptic system. In the current investigation, the grid movement and the solution will develop simultaneously. The solution is used to modify the generating equations, thereby controlling the grid point distributions.

Mastin, C. W.↗
NASA NTRS1984

Recent advances in methods for numerical solution of O.D.E. initial value problems

In the mathematical modeling of physical systems, it is often necessary to solve an initial value problem (IVP), consisting of a system of ordinary differential equations (ODE). A typical program produces approximate solutions at certain mesh points. Almost all existing codes try to control the local truncation error, while the user is really interested in controlling the true or global error. The present investigation provides a review of recent advances regarding the solution of the IVP, giving particular attention to stiff systems. Stiff phenomena are customarily defined in terms of the eigenvalues of the Jacobian. There are, however, some difficulties connected with this approach. It is pointed out that an estimate of the Lipschitz constant proves to be a very practical way to determine the stiffness of a problem.

Bui, T. D.↗
NASA NTRS1986

Biogeochemical cycling in the ocean. Part 1: Introduction to the effects of upwelling along the west coast of North America

Coastal upwelling is examined as it relates to the cycling of chemical species in coastal waters along the west coast of North America. The temporal and spatial features of upwelling phenomena in the Eastern boundary regions of the North Pacific Ocean are presented and discussed in terms of upwelling episodes. Climate conditions affecting upwelling include: thermal effects, wind-induced shear stress which moves surface layers, and the curl of the wind stress vector which is thought to affect the extent and nature of upwelling and the formation of offshore convergent downwelling fronts. These effects and the interaction of sunlight and upwelled nutrients which result in a biological bloom in surface waters is modeled analytically. The roles of biological and chemical species, including the effects of predation, are discussed in that context, and relevant remote sensing and in situ observations are presented. Climatological, oceanographic, biological, physical, chemical events, and processes that pertain to biogeochemical cycling are presented and described by a set of partial differential equations. Simple preliminary results are obtained and are compared with data. Thus a fairly general framework has been laid where the many facets of biogeochemical cycling in coastal upwelled waters can be examined in their relationship to one another, and to the whole, to whatever level of detail or approximation is warranted or desired.

Howe, John T.↗
NASA NTRS1988

Range data description based on multiple characteristics

An algorithm for describing range images based on Mean curvature (H) and Gaussian curvature (K) is presented. Range images are unique in that they directly approximate the physical surfaces of a real world 3-D scene. The curvature parameters are derived from the fundamental theorems of differential geometry and provides visible invariant pixel labels that can be used to characterize the scene. The sign of H and K can be used to classify each pixel into one of eight possible surface types. Due to the sensitivity of these parameters to noise the resulting HK-sing map does not directly identify surfaces in the range images and must be further processed. A region growing algorithm based on modeling the scene points with a Markov Random Field (MRF) of variable neighborhood size and edge models is suggested. This approach allows the integration of information from multiple characteristics in an efficient way. The performance of the proposed algorithm on a number of synthetic and real range images is discussed.

Al-Hujazi, Ezzet↗
NASA NTRS1948

A general small-deflection theory for flat sandwich plates

A small-deflection theory is developed for the elastic behavior of orthotropic flat plates in which deflections due to shear are taken into account. In this theory, which covers all types of flat sandwich construction, a plate is characterized by seven physical constants (five stiffnesses and two Poisson ratios) of which six are independent. Both the energy expression and the differential equations are developed. Boundary conditions corresponding to simply supported, clamped, and elastically restrained edges are considered.

Libove, Charles↗
NASA NTRS1999

High Order Approximations for Compressible Fluid Dynamics on Unstructured and Cartesian Meshes

The development of high-order accurate numerical discretization techniques for irregular domains and meshes is often cited as one of the remaining challenges facing the field of computational fluid dynamics. In structural mechanics, the advantages of high-order finite element approximation are widely recognized. This is especially true when high-order element approximation is combined with element refinement (h-p refinement). In computational fluid dynamics, high-order discretization methods are infrequently used in the computation of compressible fluid flow. The hyperbolic nature of the governing equations and the presence of solution discontinuities makes high-order accuracy difficult to achieve. Consequently, second-order accurate methods are still predominately used in industrial applications even though evidence suggests that high-order methods may offer a way to significantly improve the resolution and accuracy for these calculations. To address this important topic, a special course was jointly organized by the Applied Vehicle Technology Panel of NATO's Research and Technology Organization (RTO), the von Karman Institute for Fluid Dynamics, and the Numerical Aerospace Simulation Division at the NASA Ames Research Center. The NATO RTO sponsored course entitled "Higher Order Discretization Methods in Computational Fluid Dynamics" was held September 14-18, 1998 at the von Karman Institute for Fluid Dynamics in Belgium and September 21-25, 1998 at the NASA Ames Research Center in the United States. During this special course, lecturers from Europe and the United States gave a series of comprehensive lectures on advanced topics related to the high-order numerical discretization of partial differential equations with primary emphasis given to computational fluid dynamics (CFD). Additional consideration was given to topics in computational physics such as the high-order discretization of the Hamilton-Jacobi, Helmholtz, and elasticity equations. This volume consists of five articles prepared by the special course lecturers. These articles should be of particular relevance to those readers with an interest in numerical discretization techniques which generalize to very high-order accuracy. The articles of Professors Abgrall and Shu consider the mathematical formulation of high-order accurate finite volume schemes utilizing essentially non-oscillatory (ENO) and weighted essentially non-oscillatory (WENO) reconstruction together with upwind flux evaluation. These formulations are particularly effective in computing numerical solutions of conservation laws containing solution discontinuities. Careful attention is given by the authors to implementational issues and techniques for improving the overall efficiency of these methods. The article of Professor Cockburn discusses the discontinuous Galerkin finite element method. This method naturally extends to high-order accuracy and has an interpretation as a finite volume method. Cockburn addresses two important issues associated with the discontinuous Galerkin method: controlling spurious extrema near solution discontinuities via "limiting" and the extension to second order advective-diffusive equations (joint work with Shu). The articles of Dr. Henderson and Professor Schwab consider the mathematical formulation and implementation of the h-p finite element methods using hierarchical basis functions and adaptive mesh refinement. These methods are particularly useful in computing high-order accurate solutions containing perturbative layers and corner singularities. Additional flexibility is obtained using a mortar FEM technique whereby nonconforming elements are interfaced together. Numerous examples are given by Henderson applying the h-p FEM method to the simulation of turbulence and turbulence transition.

Barth, Timothy↗
NASA NTRS1983

Physical aging in graphite/epoxy composites

Sub-Tg annealing has been found to affect the properties of graphite/epoxy composites. The network epoxy studied was based on the chemistry of tetraglycidyl 4,4'-diamino-diphenyl methane (TGDDM) crosslinked by 4,4'-diamino-diphenyl sulfone (DDS). Differential scanning calorimetry, thermal mechanical analysis, and solid-state cross-polarized magic-angle-spinning nuclear magnetic resonance spectroscopy have been utilized in order to characterize this process of recovery towards thermodynamic equilibrium. The volume and enthalpy recovery as well as the 'thermoreversibility' aspects of the physical aging are discussed. This nonequilibrium and time-dependent behavior of network epoxies are considered in view of the increasingly wide applications of TGDDM-DDS epoxies as matrix materials of structural composites in the aerospace industry.

Kong, E. S. W.↗