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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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A test of the hierarchical model of litter decomposition
Our basic understanding of plant litter decomposition informs the assumptions underlying widely applied soil biogeochemical models, including those embedded in Earth system models. Confidence in projected carbon cycle–climate feedbacks therefore depends on accurate knowledge about the controls regulating the rate at which plant biomass is decomposed into products such as CO 2 . Here we test underlying assumptions of the dominant conceptual model of litter decomposition. The model posits that a primary control on the rate of decomposition at regional to global scales is climate (temperature and moisture), with the con- trolling effects of decomposers negligible at such broad spatial scales. Using a regional-scale litter decomposition experiment at six sites spanning from northern Sweden to southern France—and capturing both within and among site variation in putative controls—we find that contrary to predictions from the hierarchical model, decomposer (microbial) biomass strongly regulates decomposition at regional scales. Furthermore, the size of the microbial biomass dictates the absolute change in decomposition rates with changing climate variables. Our findings suggest the need for revision of the hierarchical model, with decomposers acting as both local- and broad-scale controls on litter decomposition rates, necessitating their explicit consideration in global biogeochemical models.
Metal-insulator transition in Na{sub x}WO{sub 3}: Photoemission spectromicroscopy study
We have investigated the validity of percolation model, which is quite often invoked to explain the metal-insulator transition in sodium tungsten bronzes, Na{sub x}WO{sub 3} by photoelectron spectromicroscopy. The spatially resolved direct spectromicroscopic probing on both the insulating and metallic phases of high quality single crystals of Na{sub x}WO{sub 3} reveals the absence of any microscopic inhomogeneities embedded in the system within the experimental limit. Neither any metallic domains in the insulating host nor any insulating domains in the metallic host have been found to support the validity of percolation model to explain the metal-insulator transition in Na{sub x}WO{sub 3}.
FJK - A cap-free fragment approach with embedding Fock potentials
We present a cap-free fragment-based approach for Hartree-Fock calculations where full Fock potentials are used for monomer embedding. In this FJK (Fragmentation with Coulomb (J) and exchange (K) embedding) method the system is divided into fragments by heterolytic fission of covalent bonds. The one-electron operators for each fragment are built including the mean-field Coulomb and exchange potential of all the remaining monomers. The description is improved by iterative updates of the monomer potentials within which the method converges to the full system Hartree-Fock result. It is shown that a small number of iterations is sufficient to yield errors in the absolute energy comparable to those usually observed in density fitting procedures. Conformational energies of organic molecules are used as benchmark, demonstrating the robustness of the procedure.
Extraction of effective solid-liquid interfacial free energies for full 3D solid crystallites from equilibrium MD simulations
Molecular dynamics simulations of an embedded atom copper system in the NPH ensemble are used to study the e ective solid-liquid interfacial free energy of quasispherical solid crystals within a liquid. This is within the larger context of MD simulations of this system undergoing solidi cation, where single individually-prepared crystallites of di erent sizes grow until they reach a thermodynamically stable nal state. The resulting equilibrium shapes possess the full structural details expected for solids with weakly anisotropic surface free energies (in these cases, ~5 % radial attening and rounded [111] octahedral faces). The simplifying assumption of sphericity and perfect isotropy leads to an e ective interfacial free energy as appearing in the Gibbs-Thomson equation, which we determine to be ~179 erg/cm 2 , roughly independent of crystal size for radii in the 50 - 250 A range. This quantity may be used in atomistically-informed models of solidi cation kinetics for this system.
Even-handed subsystem selection in projection-based embedding
Projection-based embedding offers a simple framework for embedding correlated wavefunction methods in density functional theory. Partitioning between the correlated wavefunction and density functional subsystems is performed in the space of localized molecular orbitals. However, during a large geometry change—such as a chemical reaction—the nature of these localized molecular orbitals, as well as their partitioning into the two subsystems, can change dramatically. This can lead to unphysical cusps and even discontinuities in the potential energy surface. In this work, we present an even-handed framework for localized orbital partitioning that ensures consistent subsystems across a set of molecular geometries. We illustrate this problem and the even-handed solution with a simple example of an S N 2 reaction. Applications to a nitrogen umbrella flip in a cobalt-based CO 2 reduction catalyst and to the binding of CO to Cu clusters are presented. In both cases, we find that even-handed partitioning enables chemically accurate embedding with modestly sized embedded regions for systems in which previous partitioning strategies are problematic.
Scattering off molecules far from equilibrium
We report that pump-probe gas phase X-ray scattering experiments, enabled by the development of X-ray free electron lasers, have advanced to reveal scattering patterns of molecules far from their equilibrium geometry. While dynamic displacements reflecting the motion of wavepackets can probe deeply into the reaction dynamics, in many systems, the thermal excitation embedded in the molecules upon optical excitation and energy randomization can create systems that encompass structures far from the ground state geometry. For polyatomic molecular systems, large amplitude vibrational motions are associated with anharmonicity and shifts of interatomic distances, making analytical solutions using traditional harmonic approximations inapplicable. More generally, the interatomic distances in a polyatomic molecule are not independent and the traditional equations commonly used to interpret the data may give unphysical results. Here, we introduce a novel method based on molecular dynamic trajectories and illustrate it on two examples of hot, vibrating molecules at thermal equilibrium. When excited at 200 nm, 1,3-cyclohexadiene (CHD) relaxes on a subpicosecond time scale back to the reactant molecule, the dominant pathway, and to various forms of 1,3,5-hexatriene (HT). With internal energies of about 6 eV, the energy thermalizes quickly, leading to structure distributions that deviate significantly from their vibrationless equilibrium. The experimental and theoretical results are in excellent agreement and reveal that a significant contribution to the scattering signal arises from transition state structures near the inversion barrier of CHD. In HT, our analysis clarifies that previous inconsistent structural parameters determined by electron diffraction were artifacts that might have resulted from the use of inapplicable analytical equations.
Data-Consistent Inversion for Stochastic Input-to-Output Maps
Data-consistent inversion is a recently developed measure-theoretic framework for solving a stochastic inverse problem involving models of physical systems. The goal is to construct a probability measure on model inputs (i.e., parameters of interest) whose associated push-forward measure matches (i.e., is consistent with) a probability measure on the observable outputs of the model (i.e., quantities of interest). Previous implementations required the map from parameters of interest to quantities of interest to be deterministic. This work generalizes this framework for maps that are stochastic, i.e., contain uncertainties and variation not explainable by variations in uncertain parameters of interest. Generalizations of previous theorems of existence, uniqueness, and stability of the data-consistent solution are provided while new theoretical results address the stability of marginals on parameters of interest. A notable aspect of the algorithmic generalization is the ability to query the solution to generate independent identically distributed samples of the parameters of interest without requiring knowledge of the so-called stochastic parameters. This work therefore extends the applicability of the data-consistent inversion framework to a much wider class of problems. This includes those based on purely experimental and field data where only a subset of conditions are either controllable or can be documented between experiments while the underlying physics, measurement errors, and any additional covariates are either uncertain or not accounted for by the researcher. Finally, numerical examples demonstrate application of this approach to systems with stochastic sources of uncertainties embedded within the modeling of a system and a numerical diagnostic is summarized that is useful for determining if a key assumption is verified among competing choices of stochastic maps.
COMPLEXITY ON DWARF GALAXY SCALES: A BIMODAL DISTRIBUTION FUNCTION IN SCULPTOR
In our previous work, we presented Schwarzschild models of the Sculptor dwarf spheroidal galaxy demonstrating that this system could be embedded in dark matter halos that are either cusped or cored. Here, we show that the non-parametric distribution function recovered through Schwarzschild's method is bimodal in energy and angular momentum space for all of the best-fitting mass models explored. We demonstrate that this bimodality is directly related to the two components known to be present in Sculptor through stellar population analysis, although our method is purely dynamical in nature and does not use this prior information. It therefore constitutes independent confirmation of the existence of two physically distinct dynamical components in Sculptor and suggests a rather complex assembly history for this dwarf galaxy.
Coupled Approximation of U.S. Driving Speed and Volume Statistics using Spatial Conflation and Temporal Disaggregation
The advent of mobile devices with embedded global positioning systems has allowed commercial providers of real-time traffic data to develop highly accurate estimates of network-level vehicle speeds. Traffic speed data have far outpaced the availability and accuracy of real-time traffic volume information. Limited to a relatively small number of permanent and temporary traffic counters in any city, traffic volumes typically only cover a handful of roadways, with inconsistent temporal resolution. This work addressed this data gap by coupling a commercial data set of typical traffic speeds (by roadway and time of week) from TomTom to the U.S. Federal Highway Administration's Highway Performance Monitoring System database of annual average daily traffic (AADT) counts by roadway. This work is technically novel in its solution for establishing a national crosswalk between independent network geometries using spatial conflation and big data techniques. The resulting product is a national data set providing traffic speed and volume estimates under typical conditions for all U.S. roadways with AADT values.
Fundamental and practical limits of planar tracking solar concentrators
Planar microtracking provides an alternate paradigm for solar concentration that offers the possibility of realizing high-efficiency embedded concentrating photovoltaic systems in the form factor of standard photovoltaic panels. Here, we investigate the thermodynamic limit of planar tracking optical concentrators and establish that they can, in principal, achieve the sine limit of their orientationally-tracked counterparts provided that the receiver translates a minimum distance set by the field of view half-angle. We develop a phase space methodology to optimize practical planar tracking concentrators and apply it to the design of a two surface, catadioptric system that operates with > 90% optical efficiency over a 140° field of view at geometric gains exceeding 1000×. These results provide a reference point for subsequent developments in the field and indicate that planar microtracking can achieve the high optical concentration ratio required in commercial concentrating photovoltaic systems.
Multiscale analysis in solids with unseparated scales: fine-scale recovery, error estimation, and coarse-scale adaptivity
There are several engineering applications in which the assumptions of homogenization and scale separation may be violated, in particular, for metallic structures constructed through additive manufacturing. Instead of resorting to direct numerical simulation of the macroscale system with an embedded fine scale, an alternative approach is to use an approximate macroscale constitutive model, but then estimate the model-form error using a posteriori error estimation techniques and subsequently adapt the macroscale model to reduce the error for a given boundary value problem and quantity of interest. Here, we investigate this approach to multiscale analysis in solids with unseparated scales using the example of an additively manufactured metallic structure consisting of a polycrystalline microstructure that is neither periodic nor statistically homogeneous. As a first step to the general nonlinear case, we focus here on linear elasticity in which each grain within the polycrystal is linear elastic but anisotropic.
Tensor Basis Gaussian Process Models of Hyperelastic Materials
In this study, we develop Gaussian process regression (GPR) models of isotropic hyperelastic material behavior. First, we consider the direct approach of modeling the components of the Cauchy stress tensor as a function of the components of the Finger stretch tensor in a Gaussian process. We then consider an improvement on this approach that embeds rotational invariance of the stress-stretch constitutive relation in the GPR representation. This approach requires fewer training examples and achieves higher accuracy while maintaining invariance to rotations exactly. Finally, we consider an approach that recovers the strain-energy density function and derives the stress tensor from this potential. Although the error of this model for predicting the stress tensor is higher, the strain-energy density is recovered with high accuracy from limited training data. The approaches presented here are examples of physics-informed machine learning. They go beyond purely data-driven approaches by embedding the physical system constraints directly into the Gaussian process representation of materials models.
Proposed Activities to Address Regulatory Gaps and Challenges for Licensing Advanced Reactors Using Seismic Isolation
Over the last decade, particularly since implementation of the certified design regulatory approaches outlined in 10 CFR 52, “Licenses, Certifications, and Approvals for Nuclear Power Plants,” interest has been increasing in the use of seismic isolation (SI) technology to support seismic safety in nuclear facilities. In 2009, the United States (U.S.) Nuclear Regulatory Commission (NRC) initiated research activities to develop new guidance targeted at isolated facilities because SI is being considered for nuclear power plants in the U.S. One product of that research, which was developed around a risk-informed regulatory approach, is a draft NRC NUREG series (NUREG/CR) report that investigates and discusses considerations for use of SI in otherwise traditionally founded large light water reactors (LWRs). A coordinated effort led to new provisions for SI of LWRs in the American Society of Civil Engineers standard ASCE/SEI 4-16, “Seismic Analysis of Safety Related Nuclear Structures.” The risk-informed design philosophy that underpinned development of the technical basis for these documents led to a set of proposed performance objectives and acceptance criteria intended to serve as the foundation for future NRC guidance on the use of SI and related technology. Although the guidance provided in the draft SI NUREG/CR report and ASCE/SEI 4 16 provides a sound basis for further development of nuclear power plant designs incorporating SI, these initial documents were focused on surface-founded or near-surface-founded LWRs and were, necessarily, limited in scope. For example, there is limited information in both the draft NUREG/CR report and ASCE/SEI 4-16 related to nonlinear analysis of soil-structure systems for deeply-embedded reactors, the isolation of components, and the use of vertical isolation systems. Also not included in the draft SI NUREG/CR report are special considerations for licensing of isolated facilities using the certified design approach in 10 CFR 52 and a detailed discussion of seismic probabilistic risk assessments for isolated facilities.
A new biogeochemical modelling framework (FLaMe-v1.0) for lake methane emissions on the regional scale: development and application to the European domain
This study presents a new physical-biogeochemical modelling framework for simulating lake methane (CH 4 ) emissions at regional scales. The new model, FLaMe-v1.0 (Fluxes of Lake Methane), rests on an innovative, computationally efficient lake clustering approach that enables the simulation of CH 4 emissions across a large number of lakes. Building on the Canadian Small Lake Model (CSLM) that simulates the lake physics, we develop a suite of biogeochemical modules to simulate transient dynamics of organic Carbon (C), Oxygen (O 2 ), and CH 4 . We first test the performance of FLaMe-v1.0 by analyzing physical and biogeochemical processes in two theoretical lakes with characteristics that can be considered representative for many lakes (an oligotrophic, deep lake driven by cold climate versus a eutrophic, shallow lake driven by warm climate). Next, we evaluate the model by comparing simulated and observed timeseries of CH 4 emissions in four well-surveyed lakes. We then apply FLaMe-v1.0 at the European scale to evaluate simulated diffusive and ebullitive lake CH 4 fluxes against in-situ measurements in both boreal and central European regions. Finally, we provide a first assessment of the spatio-temporal variability in CH 4 emissions from European lakes with a surface area comprised between 0.1–1000 km 2 (n= 108 407, total area = 1.33 × 105 km 2 ), indicating a total emission of 0.97 ± 0.23 Tg CH 4 yr −1 , with the uncertainty constrained by combining FLaMe-v1.0 and machine learning techniques. Moreover, 30 % and 70 % of these CH 4 emissions are through diffusive and ebullitive pathways, respectively. Annually averaged CH 4 emission rates per unit lake area during 2010–2016 have a South-to-North decreasing gradient, resulting in a mean over the European domain as 7.39 g CH 4 m −2 yr −1 . Our simulations reveal a strong seasonality (with ice-blocking effects accounted for) in European lake CH 4 emissions, with nearly ten times higher emissions during late summer than during winter. This pronounced seasonal variation highlights the importance of accounting for the sub-annual variability in CH 4 emissions to accurately constrain regional CH 4 budgets. In the future, FLaMe-v1.0 could be embedded into Earth System Models to investigate the feedback between climate warming and global lake CH 4 emissions.
Coupled Approximation of U.S. Driving Speed and Volume Statistics Using Spatial Conflation and Temporal Disaggregation
The advent of mobile devices with embedded global positioning systems has allowed commercial providers of real-time traffic data to develop highly accurate estimates of network-level vehicle speeds. Traffic speed data have far outpaced the availability and accuracy of real-time traffic volume information. Limited to a relatively small number of permanent and temporary traffic counters in any city, traffic volumes typically only cover a handful of roadways with inconsistent temporal resolution. This work addressed this data gap by coupling a commercial dataset of typical traffic speeds (by roadway and time of week) from TomTom to the U.S. FHWA's Highway Performance Monitoring System database of annual average daily traffic (AADT) counts by roadway. This work is technically novel in its solution for establishing a national crosswalk between independent network geometries using spatial conflation and big data techniques. The resulting product is a national dataset providing traffic speed and volume estimates under typical conditions for all U.S. roadways with AADT values.
Embedding global barrier and collective in a torus network
Embodiments of the invention provide a method, system and computer program product for embedding a global barrier and global interrupt network in a parallel computer system organized as a torus network. The computer system includes a multitude of nodes. In one embodiment, the method comprises taking inputs from a set of receivers of the nodes, dividing the inputs from the receivers into a plurality of classes, combining the inputs of each of the classes to obtain a result, and sending said result to a set of senders of the nodes. Embodiments of the invention provide a method, system and computer program product for embedding a collective network in a parallel computer system organized as a torus network. In one embodiment, the method comprises adding to a torus network a central collective logic to route messages among at least a group of nodes in a tree structure.
Density matrix embedding in an antisymmetrized geminal power bath
Density matrix embedding theory (DMET) has emerged as a powerful tool for performing wave function-in-wave function embedding for strongly correlated systems. In traditional DMET, an accurate calculation is performed on a small impurity embedded in a mean field bath. Here, we extend the original DMET equations to account for correlation in the bath via an antisymmetrized geminal power (AGP) wave function. The resulting formalism has a number of advantages. First, it allows one to properly treat the weak correlation limit of independent pairs, which DMET is unable to do with a mean-field bath. Second, it associates a size extensive correlation energy with a given density matrix (for the models tested), which AGP by itself is incapable of providing. Third, it provides a reasonable description of charge redistribution in strongly correlated but non-periodic systems. Thus, AGP-DMET appears to be a good starting point for describing electron correlation in molecules, which are aperiodic and possess both strong and weak electron correlation.