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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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At least 1,261 records · Page 70
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Xylan-cellulose core structure of oat water-extractable β-glucan macromolecule: Insight into interactions and organization of the cell wall complex

Water-extractable β-glucan with high molar mass (HM) determines health benefits of oat food. Oat β-glucan was extracted by a standardized in vitro digestion method and co-existing water-extractable polysaccharide (WEP) fraction and its HM-arabinoxylan (HM-AX) subfraction were isolated to identify their highly acid-resistant subunit and investigate molecular interactions between constituent polymers. The WEP and HM-AX samples consisted of arabinoxylans (AXs) (74 and 76 %, respectively), however, cellulose constituted the secondary component (6.6 and 12.8 %, respectively). Multi-detection HPSEC along with specific enzymatic hydrolysis of AXs revealed the presence of the HM-xylan domain (16 and 34 %, respectively) built of numerous single- and multi-component populations with random coil and rod-like conformations, which were embedded in a xylan matrix with spherical conformation and controlled the macromolecular shape. Unlike single-component populations, the multi-component ones were resistant to hydrolytic action of AX-hydrolyzing enzymes and represented the subunits that anchor matrix polysaccharides onto cellulose surface. These results indicate that water-extractable β-glucan macromolecule comprises as integral element a cellulose core with two linking populations, HM-xylan and low molar mass glucomannan, which are surrounded by a feruloylated AX-arabinan-arabinogalactan composite and next laminated by β-glucan matrix. Here, the stiff cellulose-xylan backbone is the basis of HM β-glucan organization, controlled by its cellulose-like segments.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Mechanical behavior of carbonated MgO-based Engineered Cementitious Composite (ECC) after high temperatures exposure

Carbonated MgO-based Engineered Cementitious Composite (ECC) has ultrahigh tensile ductility and tight crack width control behavior. However, the expectation of improved fire-resistant has not been confirmed. This study explored the alterations to mechanical and microstructure characteristics of this material after exposure to temperatures up to 500 °C. Material mass loss, compressive strength, tensile strength, strain capacity, and matrix fracture toughness were measured. Scanning electron microscopy, mercury intrusion porosimetry, thermogravimetric analysis, and X-ray diffraction were used to probe the degradation of the cement matrix and fibers. The effect of elevated temperature on carbonated MgO-based ECC was further assessed via examination of the micromechanical behavior of the fiber-matrix. The objective of this research was to assess the performance of carbonated MgO-based ECC exposed to fire hazards. The tensile ductility of carbonated MgO-based ECC was found to be enhanced when exposed to ~100 °C as compared with those at room temperature ~20 °C. Further increase in exposure temperature, however, posed a negative impact on the composite compressive strength, ultimate tensile strength, and ability to control crack width. Here the results provide a useful database for further investigations into carbonated MgO-based ECC for fire safety enhancement.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Physical-chemical-mechanical quantitative assessment of the microstructural evolution in Portland-limestone cement pastes exposed to magnesium sulfate attack at low temperature

The changes in structural integrity and microstructure of Portland-limestone cement pastes were investigated in the course of magnesium sulfate attack at low temperature. A deterioration front, consisting of three distinct layers (brucite, gypsum, leached cement matrix), swelled in time due to the expansive nature of the deterioration products, generating cracks and subsequently detaching from the sound cement matrix, continuously promoting the process. Gypsum and thaumasite characterized the leached matrix, which experienced extensive cross-linking of the aluminosilicate structures, as a result of decalcification and dealumination of the calcium silicate hydrates (C(A)SH), impairing the overall mechanical performance. CSH of low packing density was most severely affected by the process, as confirmed by the significant drop in nano-mechanical properties. The increased rate of deterioration with limestone content was tentatively attributed to the prevalent morphology of the CSH phase. Results were validated by thermodynamic simulations, indicating that the real systems did not reach equilibrium.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Getting to the Core of PARAFAC2, A Nonnegative Approach

In this paper, the authors present a novel method of performing PARAFAC2 factorization of three-way data using a compact representation of that data. In the standard PARAFAC2 algorithm, two modes of the data are recovered directly during the decomposition while the third mode is returned as a transformation matrix, which is then used to rotate sets of orthogonal third-mode basis factors into interpretable factors. In our new method, the data are first decomposed into a core matrix and orthogonal factor loading matrices in the first two modes as well as sets of orthogonal factors in the third mode (as in standard PARAFAC2). The core matrix is then decomposed using a the standard PARAFAC2 strategy to produce transformation matrices in all three modes. The algorithm is particularly useful for very large data sets and essentially permits imposition of nonnegativity in all three modes.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Use of Fisher's Ratio assisted multivariate curve resolution- alternating least squares for discovery-based analysis using ultrahigh pressure liquid chromatography-high resolution mass spectrometry

Non-targeted analysis of complex chemical mixtures can be difficult considering the convoluted nature of the matrix and the potential unknown chemical differences between samples or classes of samples. Ultrahigh pressure liquid chromatography coupled to quadrupole time-of-flight mass spectrometry (UHPLC-QTOF) is an ideal technique to probe chemical differences for a wide variety of samples. While UHPLC-QTOF can discover minute chemical differences down to low part per billion (ppb) concentrations with a high degree of confidence, the application of high-resolution mass spectrometry can yield massive amounts of information (∼ 10 gb per sample) that cannot be analyzed manually. Therefore, the application of chemometric techniques is mandatory for the interrogation of complex samples. Fisher's ratio (FR) assisted multivariate curve resolution-alternating least squares (MCR-ALS) was used to the discover and identify the chemical differences between two classes of materials: 1) a pond water matrix and 2) the matrix spiked with a pharmaceutical standard mix containing 17 compounds. Thirteen of the seventeen spiked compounds were discovered using FR analysis, and then five were successfully deconvoluted using MCR-ALS wherein the number of curves chosen were automatically determined using singular value decomposition (SVD). In conclusion, the use of an automated FR assisted MCR-ALS will aid in discovering trace levels of chemical components without the need for the researcher to provide potentially biased input which will aid in non-targeted workflow.

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

Bayesian learning of orthogonal embeddings for multi-fidelity Gaussian Processes

Uncertainty propagation in complex engineering systems often poses significant computational challenges related to modeling and quantifying probability distributions of model outputs, as those emerge as the result of various sources of uncertainty that are inherent in the system under investigation. Gaussian Processes regression (GPs) is a robust meta-modeling technique that allows for fast model prediction and exploration of response surfaces. Multi-fidelity variations of GPs further leverage information from cheap and low fidelity model simulations in order to improve their predictive performance on the high fidelity model. In order to cope with the high volume of data required to train GPs in high dimensional design spaces, a common practice is to introduce latent design variables that are typically projections of the original input space to a lower dimensional subspace, and therefore substitute the problem of learning the initial high dimensional mapping, with that of training a GP on a low dimensional space. Here in this paper, we present a Bayesian approach to identify optimal transformations that map the input points to low dimensional latent variables. The \projection" mapping consists of an orthonormal matrix that is considered a priori unknown and needs to be inferred jointly with the GP parameters, conditioned on the available training data. The proposed Bayesian inference scheme relies on a two-step iterative algorithm that samples from the marginal posteriors of the GP parameters and the projection matrix respectively, both using Markov Chain Monte Carlo (MCMC) sampling. In order to take into account the orthogonality constraints imposed on the orthonormal projection matrix, a Geodesic Monte Carlo sampling algorithm is employed, that is suitable for exploiting probability measures on manifolds. We extend the proposed framework to multi-fidelity models using GPs including the scenarios of training multiple outputs together. We validate our framework on three synthetic problems with a known lower-dimensional subspace. The benefits of our proposed framework, are illustrated on the computationally challenging aerodynamic optimization of a last-stage blade for an industrial gas turbine, where we study the effect of an 85-dimensional shape parameterization of a three-dimensional airfoil on two output quantities of interest, specifically on the aerodynamic efficiency and the degree of reaction

42 ENGINEERING↗
DOE OSTI2022

Krylov subspace recycling for evolving structures

Krylov subspace recycling is a powerful tool when solving a long series of large, sparse linear systems that change only slowly over time. In PDE constrained shape optimization, these series appear naturally, as typically hundreds or thousands of optimization steps are needed with only small changes in the geometry. In this setting, however, applying Krylov subspace recycling can be a difficult task. As the geometry evolves, in general, so does the finite element mesh defined on or representing this geometry, including the numbers of nodes and elements and element connectivity. This is especially the case if re-meshing techniques are used. As a result, the number of algebraic degrees of freedom in the system changes, and in general the linear system matrices resulting from the finite element discretization change size from one optimization step to the next. Changes in the mesh connectivity also lead to structural changes in the matrices. In the case of re-meshing, even if the geometry changes only a little, the corresponding mesh might differ substantially from the previous one. Obviously, this prevents any straightforward mapping of the approximate invariant subspace of the linear system matrix (the focus of recycling in this work) from one optimization step to the next; similar problems arise for other selected subspaces. In this paper, we present an algorithm to map an approximate invariant subspace of the linear system matrix for the previous optimization step to an approximate invariant subspace of the linear system matrix for the current optimization step, for general meshes. This is achieved by exploiting the map from coefficient vectors to finite element functions on the mesh, combined with interpolation or approximation of functions on the finite element mesh. We demonstrate the effectiveness of our approach numerically with several proof of concept studies for a specific meshing technique.

42 ENGINEERING↗
DOE OSTI2022

The effect of stress on the migration of He gas bubbles under a thermal gradient in Fe by phase-field modeling

Here a phase-field model is parameterized to study the effect of elastic stresses on the migration of He gas bubbles in Fe under a temperature gradient. Stresses caused by the gas bubble pressure and residual stress in the Fe matrix are considered. The dependence of He bubble migration velocity on the magnitude of the residual stress, average temperature, temperature gradient, and bubble size is measured. In agreement with a theoretical model based on surface diffusion, simulation results demonstrate that He bubbles move towards the high temperature region with velocities in Fe that are orders of magnitude faster than previously reported in UO 2 . It is found that local stresses in the matrix caused by the He bubble have negligible effect on the bubble migration process; however, residual stresses in the Fe matrix, potentially caused by processing or irradiation, can modestly modify bubble kinetics through pressure dependence of the He diffusion coefficients. Compressive residual stress decreases diffusion coefficients for bulk and surface diffusion mechanisms, thus reducing the migration velocity of the gas bubble. In contrast, tensile residual stress increases the diffusion coefficients, resulting in an increase in the gas bubble migration velocity. This pressure dependence is also consistent with a theoretical model. This phase field model lays the foundation for analysis of bubble coalescence-induced fracture in He bubble-containing steels.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Efficient discontinuous Galerkin implementations and preconditioners for implicit unsteady compressible flow simulations

This work presents and compares efficient implementations of high-order discontinuous Galerkin methods: a modal matrix-free discontinuous Galerkin (DG) method, a hybridizable discontinuous Galerkin (HDG) method, and a primal formulation of HDG, applied to the implicit solution of unsteady compressible flows. The matrix-free implementation allows for a reduction of the memory footprint of the solver when dealing with implicit time-accurate discretizations. HDG reduces the number of globally-coupled degrees of freedom relative to DG, at high order, by statically condensing element-interior degrees of freedom from the system in favor of face unknowns. The primal formulation further reduces the element-interior degrees of freedom by eliminating the gradient as a separate unknown. This paper introduces a p-multigrid preconditioner implementation for these discretizations and presents results for various flow problems. Benefits of the p-multigrid strategy relative to simpler, less expensive, preconditioners are observed for stiff systems, such as those arising from low-Mach number flows at high-order approximation. The p-multigrid preconditioner also shows excellent scalability for parallel computations. Finally, additional savings in both speed and memory occur with a matrix-free/reduced version of the preconditioner.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Effects of graphene surface functionalities towards controlled reinforcement of a lignin based renewable thermoplastic rubber

In this report, we describe methods to enhance mechanical properties of a renewable thermoplastic rubber by incorporating functional graphene platelets into an equal-mass mixture of lignin, a feedstock from plant biomass, and a nitrile-butadiene rubber having 41 mol % acrylonitrile content (NBR41) that form a nanocomposite. Not all lignins yield mechanically strong material when they are combined with NBR41, and thus, limit its use for such rubbery products. Here, we evaluate different graphene oxides (GO) and reduced graphene oxides (rGO) dry-powders with different surface areas, functionality, and wettability in the synthesis of performance-enhanced nanocomposites of soft lignin/NBR41 matrix via a solvent-free, high shear reactive process. High surface area GO (HSGO) platelets with strong hydrophilicity exhibit good dispersion in the multiphase lignin/NBR41 composites with lignin dispersion varying from 200 to 2000 nm, resulting in superior reinforcement over other graphene derivatives. The addition of 1–4 wt % HSGO increased the tensile stress of the lignin/NBR41 thermoplastic rubber matrix by 60–160% (15–24 MPa) and the modulus by 200–700% (60–140 MPa). Scanning electron microscopy and small angle X-ray scattering results show that the well-dispersed HSGO platelets effectively disrupt the lignin-rich aggregates in NBR41 matrix, resulting in both strength and stiffness enhancements in the formed nanocomposites. This report on performance enhancement of lignin-based renewable polymers via the production of nanocomposite would increase potential for ‘finding the value of lignin’—a grand challenge associated with modern biorefineries.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Graphene nanoplatelet for enhancement the mechanical properties and durability characteristics of alkali activated binder

The effects of the addition of graphene nanoplatelets (GNPs) on the microstructure, heat of hydration, mechanical properties and durability characteristics of alkali activated binders were investigated. A simple mixing process led to reasonably uniform dispersion of GNPs in the matrix, with minor agglomeration of GNPs detected via scanning electron microscopy. Tests on engineering properties indicated that the compressive strength of the alkali activated binder increased with the addition of GNPs at relatively low concentrations. Gains were also realized in the abrasion resistance and moisture sorptivity of the binder with GNPs addition. The heat of hydration investigations indicated that the addition of GNPs accelerates the hydration process and increases the amount of hydration products, especially at early ages. Scanning electron microscope investigations further indicated that GNPs could impede the development of microcracks and mitigate their propagation within matrix; indications of good bonding between the GNPs and the alkali activated matrix were also noted.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Water and heat: New constraints on the evolution of the CV chondrite parent body

This paper focuses on the post-accretion history of CV3 chondrites, through a combination of petrographic and mineralogical characterization, magnetic measurements, spectral (Raman and Infrared) and thermo-gravimetric analysis of 31 meteorites (including 7 falls, 21 Antarctic and 3 non-Antarctic finds) spanning a wide metamorphic range. We classify the 21 Antarctic chondrites and the Bukhara fall into the CV Red , CV OxA , and CV OxB subgroups. We establish quantitative parameters relevant for this sub-classification. In comparison to CV Ox , CV Red chondrites are characterized by (i) a lower abundance of matrix, (ii) a higher abundance of metal, (iii) the presence of Ni-poor sulfides. In comparison to CV OxB , CV OxA are characterized by (i) similar matrix abundance, (ii) a higher abundance of metal, (iii) the presence of metal almost exclusively under the form of awaruite, (iv) lower Ni content of sulfides, (v) lower magnetic susceptibility and saturation remanence. In this work, both CV Ox (CV OxA and CV OxB ) and CV Red experienced aqueous alteration, and contain oxyhydroxides and phyllosilicates. We show that the abundance of these hydrated secondary minerals observed today in individual CV chondrites decreases with their peak metamorphic temperature. This is interpreted either as partial dehydration of these secondary minerals or limited hydration due to the rapid exhaustion of the water reservoir during parent body thermal metamorphism. Moreover, the lower abundance of oxyhydroxides (that have a lower thermal stability than phyllosilicates and may in large part postdate the peak of thermal metamorphism) in more metamorphosed CV chondrites is interpreted as lower availability of aqueous fluids during retrograde metamorphism in these meteorites. Lastly, we show that in comparison to CV OxB , CV OxA are systematically (i) more metamorphosed, (ii) less hydrated, (iii) depleted in ferromagnetic minerals, (iv) but enriched in metal in the form of secondary awaruite. CV OxA may be thermally metamorphosed CV OxB . CV Red are significantly different from CV Ox (matrix abundances, alteration products, opaque minerals), but span the same wide metamorphic range. This could be indicative of a laterally heterogeneous CV parent body, or suggest the existence of distinct parent bodies for CV Ox and CV Red chondrites.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

A physics-informed multi-agents model to predict thermo-oxidative/hydrolytic aging of elastomers

This paper introduces a novel physics-informed multi-agents constitutive model to propose prediction in quasi-static constitutive behavior of cross-linked elastomer and the loss of mechanical performance during environmental aging. The presented model is used to simulate the effect of single-mechanism chemical aging (i.e. thermal-inducedor hydrolytic aging) on the behavior of the material in this hybrid framework. Those environmental single-mechanism damages change the polymer matrix over time due to massive chain scission, chain formations, and changing the arrangement of molecules in the polymer matrix. Here we propose a data-driven super-constrained machine-learned engine to represent damage in the polymer matrix and capture the changes in material behavior, including its inelastic features such as Mullins effect and permanent set in the course of aging. We have simplified the 3D stress–strain tensor mapping problem into a small number of super-constrained 1D mapping problems by means of a sequential order reduction. An assembly of multiple replicated conditional neural-network learning-agents (L-agents) is trained to systematically simplify the high-dimensional mapping problem into multiple 1D problems, each represented by a different type of agent. Our hybrid framework is designed to capture the effect of deformation history, aging time, and aging temperature. The model is validated with respect to a comprehensive set of experiments specifically designed to benchmark model capabilities and also against available data in the literature. Thermodynamic consistency and frame independency have been verified. Besides acceptable predictive abilities, a significant reduction of computational cost to predict behavior at multiple states of deformation is the most significant feature of this model.

42 ENGINEERING↗
DOE OSTI2022

Effects of internal swelling on residual elasticity of a quasi-brittle material through a composite sphere model

This work describes the development of a micromechanical-based constitutive model accounting for the effect of internal expansion on the residual elasticity of a Hashin composite material. This material is made of spherical inclusions that are subjected to gradual swelling within a quasi-brittle matrix. The main focus of this work is to describe and analyze the material mechanical response, with an additional focus on the internal swelling’s effect on the stress–strain response and residual elasticity. Microstructural features and parameters of major importance for the mechanical responses were identified. The innovative characteristics of the proposed approach are summarized as follows: (1) a full determination of the physics of a complete-damage problem throughout the whole process of inclusion swelling with upscaling techniques, which transfers the microcrack-related properties from the lower scale to upper scale; and (2) an evolution of the mechanical fields and the corresponding residual elasticity for various inclusion swelling levels. Concerning the matrix–inclusion composite, it was hypothesized that only the matrix was susceptible to cracking, with varied degrees of damage, whereas the inclusions behave elastically and the elastic modulus of the expanding inclusions remains constant. It is to emphasize that the gradual swelling of inclusions is modeled by an increasing strain in the current micromechanical-based constitutive model, and the microcracks are represented by a set of randomly oriented penny-shaped microcracks with identical radii (namely, closed cracks). The main contribution of the current research is to establish the exact mathematical solutions for the mechanical fields (stress, strain) caused by the swelling of the inclusions (mechanical loading) and derive the effective residual elasticity of a composite (structural response) subject to internal expansion and quasi-brittle damage. Based on the assumption of closed cracks that could be extended to open cracks in the upcoming work, the results proposed by the present paper help to understand the non-linear mechanical behavior of quasi-brittle materials subject to microcracking and provide a theoretical framework to be used as academical benchmark for numerical simulations.

36 MATERIALS SCIENCE↗
DOE OSTI2020

A multi-physics constitutive model to predict hydrolytic aging in quasi-static behaviour of thin cross-linked polymers

The effect of hydrolytic aging on mechanical quasi-static responses of rubber-like materials, in particular, the idealized Mullins effect and permanent set have been modeled. The effect of hydrolytic damage on the mechanical integrity of the polymer matrix is modeled as the direct competition of two micro-structural phenomena (i) chain scission and (ii) reduction of cross-links. Both phenomena and their correlation were modeled and thus, the strain energy of the polymer matrix is written with respect to three independent mechanisms; i) the shrinking original matrix that has not been attacked by water, ii) conversion of the first network to a new network due to the reduction of the cross-links, and iii) energy loss from network degradation due to water attacks to polymer active agents. The proposed model satisfies the Clausius-Duhem inequality and is thus physically feasible. The model is validated with respect to sets of our experimental data and other sets available in the literature. The proposed model is based on the assumption of homogeneous diffusion and mainly relevant for thin samples. In view of its accuracy, interpret-ability, and deep insight it provides into the nature of damage accumulation, the model is a good choice for further implementation in FE applications.

42 ENGINEERING↗
DOE OSTI2023

WeakIdent: Weak formulation for identifying differential equation using narrow-fit and trimming

Data-driven identification of differential equations is an interesting but challenging problem, especially when the given data are corrupted by noise. When the governing differential equation is a linear combination of various differential terms, the identification problem can be formulated as solving a linear system, with the feature matrix consisting of linear and nonlinear terms multiplied by a coefficient vector. This product is equal to the time derivative term, and thus generates dynamical behaviors. The goal is to identify the correct terms that form the equation to capture the dynamics of the given data. We propose a general and robust framework to recover differential equations using a weak formulation with two new mechanisms, narrow-fit and trimming, for both ordinary and partial differential equations (ODEs and PDEs). The weak formulation facilitates an efficient and robust way to handle noise, and two new mechanisms, narrow-fit and trimming, improve the coefficient support and value recoveries respectively. For each sparsity level, Subspace Pursuit is utilized to find an initial set of support from the large dictionary. Then, we focus on highly dynamic regions (rows of the feature matrix), and error normalize the feature matrix in the narrow-fit step. The support is further updated via trimming the terms that contribute the least. Finally, the support set of features with the smallest Cross-Validation error is chosen as the result. A comprehensive set of numerical experiments are presented for both systems of ODEs and PDEs with various noise levels. The proposed method gives a robust recovery of the coefficients, and a significant denoising effect which can handle up to 100% noise-to-signal ratio for some equations. We compare the proposed method with several state-of-the-art algorithms for the recovery of differential equations.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Dopant segregation in YAG single crystal fibers grown by the laser heated pedestal growth technique

In this work, we report self-segregation of dopants in a crystal matrix within a single crystal (SC) fiber. Neodymium and holmium-doped yttrium aluminum garnet (YAG) fibers were grown using the Laser Heated Pedestal Growth (LHPG) technique and cross-sectional dopant concentration was measured using electron-probe micro-analysis. It was observed that the degree of auto-segregation of the rare-earth dopant depended on the difference in ionic size of the dopant ion and the Y 3+ ion in the YAG matrix. While holmium showed little tendency to self-segregate, the concentration of neodymium ions varied as much as 25% across the cross-section of the fiber. Strong correlation between the dopant concentration profile and fiber draw speed was also demonstrated. Since the local refractive index depends on the concentration of dopants, a refractive index profile can be achieved by a dopant profile across the fiber cross-section. Engineered index profiles can be realized by varying growth conditions, dopants, crystal matrix, etc. Such an approach is promising in applications such as the development of monolithic SC fibers with graded-index profiles.

36 MATERIALS SCIENCE↗