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Results for “structural model decomposition”

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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All sourcesNASA NTRSDOE OSTI
NASA NTRS1985

Model-size reduction technique for the analysis of symmetric anisotropic structures

A two-step computational procedure is presented for reducing the size of the analysis model for an anisotropic symmetric structure to that of the corresponding orthotropic structure. The key elements of the procedure are: (1) decomposition of the stiffness matrix into the sum of an orthotropic and nonorthotropic (anisotropic) parts; and (2) successive application of the finite element method and the classical Rayleigh-Ritz technique. The finite element method is first used to generate few global approximation vectors (or modes). Then the amplitudes of these modes are computed by using the Rayleigh-Ritz technique. The global approximation vectors are selected to be the solution corresponding to zero nonorthotropic matrix and its various-order derivatives with respect to an anisotropic tracing parameter (identifying the nonorthotropic material coefficients). The size of the analysis model used in generating the global approximation vectors is identical to that of the corresponding orthotropic structure. The effectiveness of the proposed technique is demonstrated by means of numerical examples and its potential for solving other quasi-symmetric problems is discussed.

Noor, A. K.↗
DOE OSTI2019

The Effect of Nonisothermality on the Early Stages of Spinodal Decomposition

A nonisothertmal model of spinodal decomposition is proposed for a binary system described by the Ginzburg–Landau energy. The initial stages of spinodal decomposition are investigated for a system of simultaneous equations describing the impurity and temperature redistribution. The dispersion equation and the instability growth rate of spinodal structures are obtained. The temperature dependence of the growth rate and the wave number corresponding to the maximum instability is found. The observed difference in the dispersion relations of isothermal and nonisothermal models shows that a criterion for the effect of temperature fluctuations on the spinodal decomposition is given by a dimensionless parameter Γ; for large values of Γ (Γ ≥ 1000), temperature fluctuations in the form of noise are certainly insufficient for spinodal decomposition due to a change in the dispersion structure of the equations, which suggests the need to take into account the nonisothermal behavior of the system.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2020

Linear two-pool models are insufficient to infer soil organic matter decomposition temperature sensitivity from incubations

Abstract Terrestrial carbon (C)-climate feedbacks depend strongly on how soil organic matter (SOM) decomposition responds to temperature. This dependency is often represented in land models by the parameter Q 10 , which quantifies the relative increase of microbial soil respiration per 10 °C temperature increase. Many studies have conducted paired laboratory soil incubations and inferred “active” and “slow” pool Q 10 values by fitting linear two-pool models to measured respiration time series. Using a recently published incubation study (Qin et al. in Sci Adv 5(7):eaau1218, 2019) as an example, here we first show that the very high parametric equifinality of the linear two-pool models may render such incubation-based Q 10 estimates unreliable. In particular, we show that, accompanied by the uncertain initial active pool size, the slow pool Q 10 can span a very wide range, including values as high as 100, although all parameter combinations are producing almost equally good model fit with respect to the observations. This result is robust whether or not interactions between the active and slow pools are considered (typically these interactions are not considered when interpreting incubation data, but are part of the predictive soil carbon models). This very large parametric equifinality in the context of interpreting incubation data is consistent with the poor temporal extrapolation capability of linear multi-pool models identified in recent studies. Next, using a microbe-explicit SOM model (RESOM), we show that the inferred two pools and their associated parameters (e.g., Q 10 ) could be artificial constructs and are therefore unreliable concepts for integration into predictive models. We finally discuss uncertainties in applying linear two-pool (or more generally multiple-pool) models to estimate SOM decomposition parameters such as temperature sensitivities from laboratory incubations. We also propose new observations and model structures that could enable better process understanding and more robust predictive capabilities of soil carbon dynamics.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

$$\varLambda $$ and $$\varSigma $$ Excitations and the Quark Model

Abstract The spectrum of $$\varLambda $$ Λ and $$\varSigma $$ Σ excitations is reviewed taking into account (nearly) all hyperon resonances which were seen in early analyses or in one of the recent partial-wave analyses. The spectrum is compared with the old Isgur–Karl model and the Bonn model. These models allows us to discuss the SU(3) structure of the observed resonances. The SU(3) decomposition is compared with SU(6) relations between the different decay modes. Seven $$\varLambda $$ Λ states are proposed to be classified as SU(3) singlet states. The hyperon spectrum is compared with the spectrum of N and $$\varDelta $$ Δ resonances.

Klempt, E.↗
DOE OSTI2016

On the Structure Sensitivity of Formic Acid Decomposition on Cu Catalysts

Catalytic decomposition of formic acid (HCOOH) has attracted substantial attention since HCOOH is a major by-product in biomass reforming, a promising hydrogen carrier, and also a potential low temperature fuel cell feed. Despite the abundance of experimental studies for vapor-phase HCOOH decomposition on Cu catalysts, the reaction mechanism and its structure sensitivity is still under debate. In this work, self-consistent, periodic density functional theory calculations were performed on three model surfaces of copper—Cu(111), Cu(100) and Cu(211), and both the HCOO (formate)-mediated and COOH (carboxyl)-mediated pathways were investigated for HCOOH decomposition. The energetics of both pathways suggest that the HCOO-mediated route is more favorable than the COOH-mediated route on all three surfaces, and that HCOOH decomposition proceeds through two consecutive dehydrogenation steps via the HCOO intermediate followed by the recombinative desorption of H 2 . On all three surfaces, HCOO dehydrogenation is the likely rate determining step since it has the highest transition state energy and also the highest activation energy among the three catalytic steps in the HCOO pathway. The reaction is structure sensitive on Cu catalysts since the examined three Cu facets have dramatically different binding strengths for the key intermediate HCOO and varied barriers for the likely rate determining step—HCOO dehydrogenation. Cu(100) and Cu(211) bind HCOO much more strongly than Cu(111), and they are also characterized by potential energy surfaces that are lower in energy than that for the Cu(111) facet. Coadsorbed HCOO and H represents the most stable state along the reaction coordinate, indicating that, under reaction conditions, there might be a substantial surface coverage of the HCOO intermediate, especially at under-coordinated step, corner or defect sites. Therefore, under reaction conditions, HCOOH decomposition is predicted to occur most readily on the terrace sites of Cu nanoparticles. Finally, as a result, we hereby present an example of a fundamentally structure-sensitive reaction, which may present itself as structure-insensitive in typical varied particle-size experiments.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2015

Numerical studies and metric development for validation of magnetohydrodynamic models on the HIT-SI experiment

We present application of three scalar metrics derived from the Biorthogonal Decomposition (BD) technique to evaluate the level of agreement between macroscopic plasma dynamics in different data sets. BD decomposes large data sets, as produced by distributed diagnostic arrays, into principal mode structures without assumptions on spatial or temporal structure. These metrics have been applied to validation of the Hall-MHD model using experimental data from the Helicity Injected Torus with Steady Inductive helicity injection experiment. Each metric provides a measure of correlation between mode structures extracted from experimental data and simulations for an array of 192 surface-mounted magnetic probes. Numerical validation studies have been performed using the NIMROD code, where the injectors are modeled as boundary conditions on the flux conserver, and the PSI-TET code, where the entire plasma volume is treated. Initial results from a comprehensive validation study of high performance operation with different injector frequencies are presented, illustrating application of the BD method. Using a simplified (constant, uniform density and temperature) Hall-MHD model, simulation results agree with experimental observation for two of the three defined metrics when the injectors are driven with a frequency of 14.5 kHz.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Conservative projection-based data-driven model order reduction of a fluid-kinetic spectral solver

Kinetic simulations are computationally intensive due to six-dimensional phase space discretization. Many kinetic spectral solvers use the asymmetrically weighted Hermite expansion due to its conservation and fluid-kinetic coupling properties, i.e., the lower-order Hermite moments capture and describe the macroscopic fluid dynamics, and higher-order Hermite moments describe the microscopic kinetic dynamics. We leverage this structure by developing a parametric data-driven reduced-order model based on the proper orthogonal decomposition, which projects the higher-order kinetic moments while retaining the fluid moments intact. We demonstrate analytically and numerically that the method ensures local and global mass, momentum, and energy conservation. The numerical results show that the proposed method effectively replicates the high-dimensional spectral simulations at a fraction of the computational cost and memory, as validated on the weak Landau damping and two-stream instability benchmark problems.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2016

Isospin decomposition of γ N → N * transitions within a dynamical coupled-channels model

Here, by extending the dynamical coupled-channels analysis performed in our previous work to include the available data of photoproduction of pi mesons off neutrons, the transition amplitudes for the photoexcitation of the neutron-to-nucleon resonances, γn → N*, at the resonance pole positions are determined. The combined fits to the data for both the proton- and neutron-target reactions also revise our results for the resonance pole positions and the γp → N* transition amplitudes. Our results allow an isospin decomposition of the γN → N* transition amplitudes for the isospin I = 1/2 N* resonances, which is necessary for testing hadron structure models and gives crucial inputs for constructing models of neutrino-induced reactions in the nucleon resonance region.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2017

Phase stability, ordering tendencies, and magnetism in single-phase fcc Au-Fe nanoalloys

Bulk Au-Fe alloys separate into Au-based fcc and Fe-based bcc phases, but L1 0 and L1 2 orderings were reported in single-phase Au-Fe nanoparticles. Motivated by these observations, we study the structural and ordering energetics in this alloy by combining density functional theory (DFT) calculations with effective Hamiltonian techniques: a cluster expansion with structural filters, and the configuration-dependent lattice deformation model. The phase separation tendency in Au-Fe persists even if the fcc-bcc decomposition is suppressed. The relative stability of disordered bcc and fcc phases observed in nanoparticles is reproduced, but the fully ordered L1 0 AuFe, L1 2 Au 3 Fe, and L1 2 AuFe 3 structures are unstable in DFT. But, a tendency to form concentration waves at the corresponding [001] ordering vector is revealed in nearly-random alloys in a certain range of concentrations. Furthermore, this incipient ordering requires enrichment by Fe relative to the equiatomic composition, which may occur in the core of a nanoparticle due to the segregation of Au to the surface. Effects of magnetism on the chemical ordering are also discussed.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Seamlessly joining length scales: From atomistic thermal graphs to anisotropic continuum conductivity

Thermal transport in complex solids is governed by local structure, defects, and anisotropy, yet most continuum models still rely on oversimplified and homogenized conductivities. Here, we bridge atomistic and continuum descriptions by building finite element (FE) models directly from the site-projected thermal conductivity (SPTC), an atomic-level decomposition of the Green–Kubo thermal conductivity. We introduce a toolkit, the “Simulator Collection for Atomic-to-Continuum Scales (SCACS)”, which uses a graph neural network to predict SPTC on large atomic structures, coarse-grains these fields into anisotropic conductivity tensors, and embeds them into the heat-flow FE equation with a customized, anisotropy-aware adaptive mesh refinement scheme. Applied to silicon nanostructures, the resulting FE models act as representative volume elements, reproduce bulk conductivities, and capture interfacial and defect-driven anisotropy while maintaining thermodynamic consistency. Additionally, SCACS predicts experimental conductance trends and fields. This work demonstrates a general route for transferring atomistic transport information into device-scale thermal simulations with physics-based approximations.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2016

Hierarchical Model for the Analysis of Scattering Data of Complex Materials

Interpreting the results of scattering data for complex materials with a hierarchical structure in which at least one phase is amorphous presents a significant challenge. Often the interpretation relies on the use of large-scale molecular dynamics (MD) simulations, in which a structure is hypothesized and from which a radial distribution function (RDF) can be extracted and directly compared against an experimental RDF. This computationally intensive approach presents a bottleneck in the efficient characterization of the atomic structure of new materials. Here, we propose and demonstrate an approach for a hierarchical decomposition of the RDF in which MD simulations are replaced by a combination of tractable models and theory at the atomic scale and the mesoscale, which when combined yield the RDF. We apply the procedure to a carbon composite, in which graphitic nanocrystallites are distributed in an amorphous domain. We compare the model with the RDF from both MD simulation and neutron scattering data. Ultimately, this procedure is applicable for understanding the fundamental processing-structure-property relationships in complex magnetic materials.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Space–time reduced order model for large-scale linear dynamical systems with application to Boltzmann transport problems

A classical reduced order model for dynamical problems involves spatial reduction of the problem size. However, temporal reduction accompanied by the spatial reduction can further reduce the problem size without losing much accuracy, which results in a considerably more speed-up than the spatial reduction only. Recently, a novel space–time reduced order model for dynamical problems has been developed [17], where the space–time reduced order model shows an order of a hundred speed-up with a relative error of 10 –4 for small academic problems. However, in order for the method to be applicable to a large-scale problem, an efficient space–time reduced basis construction algorithm needs to be developed. Here we present the incremental space–time reduced basis construction algorithm. The incremental algorithm is fully parallel and scalable. Additionally, the block structure in the space–time reduced basis is exploited, which enables the avoidance of constructing the reduced space–time basis. These novel techniques are applied to a large-scale particle transport simulation with million and billion degrees of freedom. The numerical example shows that the algorithm is scalable and practical. Also, it achieves a tremendous speed-up, maintaining a good accuracy. Finally, error bounds for space-only and space–time reduced order models are derived.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
NASA NTRS1993

Wing-Body Aeroelasticity Using Finite-Difference Fluid/Finite-Element Structural Equations on Parallel Computers

This paper presents a procedure for computing the aeroelasticity of wing-body configurations on multiple-instruction, multiple-data (MIMD) parallel computers. In this procedure, fluids are modeled using Euler equations discretized by a finite difference method, and structures are modeled using finite element equations. The procedure is designed in such a way that each discipline can be developed and maintained independently by using a domain decomposition approach. A parallel integration scheme is used to compute aeroelastic responses by solving the coupled fluid and structural equations concurrently while keeping modularity of each discipline. The present procedure is validated by computing the aeroelastic response of a wing and comparing with experiment. Aeroelastic computations are illustrated for a High Speed Civil Transport type wing-body configuration.

Byun, Chansup↗
NASA NTRS1996

Wing-Body Aeroelasticity on Parallel Computers

This article presents a procedure for computing the aeroelasticity of wing-body configurations on multiple-instruction, multiple-data parallel computers. In this procedure, fluids are modeled using Euler equations discretized by a finite difference method, and structures are modeled using finite element equations. The procedure is designed in such a way that each discipline can be developed and maintained independently by using a domain decomposition approach. A parallel integration scheme is used to compute aeroelastic responses by solving the coupled fluid and structural equations concurrently while keeping modularity of each discipline. The present procedure is validated by computing the aeroelastic response of a wing and comparing with experiment. Aeroelastic computations are illustrated for a high speed civil transport type wing-body configuration.

Guruswamy, Guru P.↗
DOE OSTI2023

Theoretical Multinary Perovskite Oxides Dataset

Perovskite oxides (ternary chemical formula ABO3) are a diverse class of materials with applications including heterogeneous catalysis, solid-oxide fuel cells, thermochemical conversion, and oxygen transport membranes. However, their multicomponent chemical space is underexplored due to the immense number of possible compositions. To expand the number of computed compounds we report a dataset of 66,516 theoretical multinary oxides, 59,708 of which are perovskites. First, the AA'BB'O6 compositions were generated in the a-b+a- Glazer tilting mode using the computationally-inexpensive Structure Prediction and Diagnostic Software (SPuDS) program. Next, we optimized these structures with DFT using parameters compatible with the Materials Project (MP) database. Our dataset contains these optimized structures and their formation (ΔHf) and decomposition enthalpies (ΔHd) computed relative to MP tabulated elemental references and competing phases, respectively. This dataset can be mined, used to train machine learning models, and rapidly and systematically expanded by optimizing more SPuDS-generated AA'BB'O6 perovskite structures using MP-compatible DFT calculations

Bare, Zachary↗
DOE OSTI2016

Strain phase separation: Formation of ferroelastic domain structures

Phase decomposition is a well-known process leading to the formation of two-phase mixtures. Here we show that a strain imposed on a ferroelastic crystal promotes the formation of mixed phases and domains, i.e., strain phase separation with local strains determined by a common tangent construction on the free energy versus strain curves. It is demonstrated that a domain structure can be understood using the concepts of domain/phase rule, lever rule, and coherent and incoherent strain phase separation, in a complete analogy to phase decomposition. The proposed strain phase separation model is validated using phase-field simulations and experimental observations of PbTiO 3 and BiFeO 3 thin films as examples. Finally, the proposed model provides a simple tool to guide and design domain structures of ferroelastic systems.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
NASA NTRS2007

Calculational and Experimental Investigations of the Pressure Effects on Radical - Radical Cross Combinations Reactions: C2H5 + C2H3

Pressure-dependent product yields have been experimentally determined for the cross-radical reaction C2H5 + C2H3. These results have been extended by calculations. It is shown that the chemically activated combination adduct, 1-C4H8*, is either stabilized by bimolecular collisions or subject to a variety of unimolecular reactions including cyclizations and decompositions. Therefore the "apparent" combination/disproportionation ratio exhibits a complex pressure dependence. The experimental studies were performed at 298 K and at selected pressures between about 4 Torr (0.5 kPa) and 760 Torr (101 kPa). Ethyl and vinyl radicals were simultaneously produced by 193 nm excimer laser photolysis of C2H5COC2H3 or photolysis of C2H3Br and C2H5COC2H5. Gas chromatograph/mass spectrometry/flame ionization detection (GC/MS/FID) were used to identify and quantify the final reaction products. The major combination reactions at pressures between 500 (66.5 kPa) and 760 Torr are (1c) C2H5 + C2H3 yields 1-butene, (2c) C2H5 + C2H5 yields n-butane, and (3c) C2H3 + C2H3 yields 1,3-butadiene. The major products of the disproportionation reactions are ethane, ethylene, and acetylene. At moderate and lower pressures, secondary products, including propene, propane, isobutene, 2-butene (cis and trans), 1-pentene, 1,4-pentadiene, and 1,5-hexadiene are also observed. Two isomers of C4H6, cyclobutene and/or 1,2-butadiene, were also among the likely products. The pressure-dependent yield of the cross-combination product, 1-butene, was compared to the yield of n-butane, the combination product of reaction (2c), which was found to be independent of pressure over the range of this study. The [ 1-C4H8]/[C4H10] ratio was reduced from approx.1.2 at 760 Torr (101 kPa) to approx.0.5 at 100 Torr (13.3 kPa) and approx.0.1 at pressures lower than about 5 Torr (approx.0.7 kPa). Electronic structure and RRKM calculations were used to simulate both unimolecular and bimolecular processes. The relative importance of C-C and C-H bond ruptures, cyclization, decyclization, and complex decompositions are discussed in terms of energetics and structural properties. The pressure dependence of the product yields were computed and dominant reaction paths in this chemically activated system were determined. Both modeling and experiment suggest that the observed pressure dependence of [1-C4H8]/[C4H10] is due to decomposition of the chemically activated combination adduct 1-C4H8* in which the weaker allylic C-C bond is broken: H2C=CHCH2CH3 yields C3H5 + CH3. This reaction occurs even at moderate pressures of approx.200 Torr (26 kPa) and becomes more significant at lower pressures. The additional products detected at lower pressures are formed from secondary radical-radical reactions involving allyl, methyl, ethyl, and vinyl radicals. The modeling studies have extended the predictions of product distributions to different temperatures (200-700 K) and a wider range of pressures (10(exp -3) - 10(exp 5) Torr). These calculations indicate that the high-pressure [1-C4H8]/[C4H10] yield ratio is 1.3 +/- 0.1.

Fahr, Askar↗
DOE OSTI2017

A finite element/level set model of polyurethane foam expansion and polymerization

Polyurethane foams are used widely for encapsulation and structural purposes because they are inexpensive, straightforward to process, amenable to a wide range of density variations (1 lb/ft3 - 50 lb/ft3), and able to fill complex molds quickly and effectively. Computational model of the filling and curing process are needed to reduce defects such as voids, out-of-specification density, density gradients, foam decomposition from high temperatures due to exotherms, and incomplete filling. This paper details the development of a computational fluid dynamics model of a moderate density PMDI structural foam, PMDI-10. PMDI is an isocyanate-based polyurethane foam, which is chemically blown with water. The polyol reacts with isocyanate to produces the polymer. PMDI- 10 is catalyzed giving it a short pot life: it foams and polymerizes to a solid within 5 minutes during normal processing. To achieve a higher density, the foam is over-packed to twice or more of its free rise density of 10 lb/ft3. The goal for modeling is to represent the expansion, filling of molds, and the polymerization of the foam. This will be used to reduce defects, optimize the mold design, troubleshoot the processed, and predict the final foam properties. A homogenized continuum model foaming and curing was developed based on reaction kinetics, documented in a recent paper; it uses a simplified mathematical formalism that decouples these two reactions. The chemo-rheology of PMDI is measured experimentally and fit to a generalized- Newtonian viscosity model that is dependent on the extent of cure, gas fraction, and temperature. The conservation equations, including the equations of motion, an energy balance, and three rate equations are solved via a stabilized finite element method. The equations are combined with a level set method to determine the location of the foam-gas interface as it evolves to fill the mold. Understanding the thermal history and loads on the foam due to exothermicity and oven curing is very important to the results, since the kinetics, viscosity, and other material properties are all sensitive to temperature. Results from the model are compared to experimental flow visualization data and post-test X-ray computed tomography (CT) data for the density. Several geometries are investigated including two configurations of a mock structural part and a bar geometry to specifically test the density model. We have found that the model predicts both average density and filling profiles well. However, it under predicts density gradients, especially in the gravity direction. Further model improvements are also discussed for future work.

36 MATERIALS SCIENCE↗