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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 1,189 records · Page 66
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

A mechanistic damage model for solid oxide fuel cell ceramic materials - Part I: Constitutive modeling

A multiscale mechanistic damage model for solid oxide fuel cell (SOFC) ceramics that combines micromechanics of stiffness reduction due to material porosity change and microcracking with a continuum damage mechanics (CDM) description for the evolution of microcracks up to fracture is developed in this work. The model also accounts for volumetric swelling of the anode due to redox cycling. Porosity change and swelling during redox combined with normal operating thermomechanical loads could increase the stress, strain and damage distributions in SOFC stacks leading them to failure. The proposed model involves three governing parameters: (i) the porosity in terms of the pore or void volume fraction, (ii) material swelling magnitude prescribed at a given loading step, and (iii) the damage variable that describes microcracking caused by thermomechanical loads and swelling. Pores and microcracks in the ceramics are modeled as randomly distributed ellipsoidal inclusions with negligible stiffness by an Eshelby-Mori-Tanaka formulation combined with an inclusion orientation distribution method. Microcracking damage evolution is described by a CDM formulation. Volumetric swelling is treated in a similar way to thermal expansion in the constitutive relations. After validation and numerical checks, the damage model is used to analyze a simplified SOFC positive-electrode/electrolyte/negative-electrode (PEN) structure subjected a redox cycle in addition to thermomechanical loads experienced during normal operation of a SOFC stack.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2023

Design and requirements of a hydrogen component reliability database (HyCReD)

Hydrogen technologies are expected to play a key role in the decarbonization of several sectors including energy storage and transportation. Rigorous investigation and quantification of the risk and reliability issues associated with hydrogen technologies will be critical to ensuring both their wider adoption and safe, economical operations. Quantitative risk assessment (QRA) is an important tool that has been used to enable the safe deployment of many engineering systems, including hydrogen fueling stations and hydrogen storage systems. However, QRA studies require reliability data which is currently lacking for expanding applications of hydrogen systems. Here, to address this gap, we present a new structure for a hydrogen component reliability database (HyCReD) that can be used to generate reliability data to be used in QRA, reliability, safety studies, maintenance planning, and more. Building on our previous work examining four major hydrogen safety data collection tools (West et al., 2022) [1], our approach in this work was to consult scientific literature on reliability data collection as well as a number of existing reliability engineering databases in the oil & gas, chemical processing, and nuclear power plant sectors. The evaluation of these databases led to identifying best practices to be implemented in a data collection framework for a hydrogen component reliability database. Based on these best practices, a set of 24 requirements for the proposed database are presented, covering its characteristics and the types of data to be collected. We define the structure of the HyCReD database and 25 data elements to be collected, spanning system description, failure, shutdown, or near-miss events, and maintenance events. The data elements are then defined according to international standards used in the safety and reliability practice and potential choice lists are provided for each field. Since this database is being piloted for hydrogen fueling stations, a generic station component hierarchy developed by West (2021) [2] is used to standardize system data. Finally, we demonstrate populating the database with information extracted from five narrative reports on hydrogen fueling station incidents.

08 HYDROGEN↗
DOE OSTI2022

Experimentally validated high-fidelity simulations of a liquid jet in supersonic crossflow

Here, utilizing recent advancements in computational schemes for compressible, multiphase flows, this work features a parametric study of a pure liquid jet in supersonic crossflow that involves simulating the atomization process for four values of momentum-flux ratio. These simulations are validated against experimental results measured with high-speed X-ray imaging, which confirm the accuracy of the numerical approach. Also, the effect of numerical resolution on some flow behavior is investigated, revealing convergence of the jet shape and surface instability wavelength. Analysis of the resulting sprays includes statistical descriptions of the liquid distribution, liquid structures created through breakup, interfacial instabilities, and dominant flow features. As the flowrate increases, the spray penetrates further, it becomes more disperse, and less liquid impacts the wall, but the droplet size distribution changes little. The wavelength of instabilities on the windward side of the jet diverges from measured trends in subsonic crossflows. In a visualization of the time-averaged flow, counter-rotating vortices are observed along the jet core and in the wake, affecting the process of primary atomization and early droplet trajectories.

42 ENGINEERING↗
DOE OSTI2021

A statistical mechanics approach to macroscopic limits of car-following traffic dynamics

Herein we study the derivation of macroscopic traffic models from car-following vehicle dynamics by means of hydrodynamic limits of an Enskog-type kinetic description. We consider the superposition of Follow-the-Leader (FTL) interactions and relaxation towards a traffic-dependent Optimal Velocity (OV) and we show that the resulting macroscopic models depend on the relative frequency between these two microscopic processes. If FTL interactions dominate then one gets an inhomogeneous Aw–Rascle–Zhang model, whose (pseudo) pressure and stability of the uniform flow are precisely defined by some features of the microscopic FTL and OV dynamics. Conversely, if the rate of OV relaxation is comparable to that of FTL interactions then one gets a Lighthill–Whitham–Richards model ruled only by the OV function. We further confirm these findings by means of numerical simulations of the particle system and the macroscopic models. Unlike other formally analogous results, our approach builds the macroscopic models as physical limits of particle dynamics rather than assessing the convergence of microscopic to macroscopic solutions under suitable numerical discretisations.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Towards data-driven constitutive modelling for granular materials via micromechanics-informed deep learning

The analytical description of path-dependent elastic-plastic responses of a granular system is highly complicated because of continuously evolving microstructures and strain localisation within the system undergoing deformation. This study offers an alternative to the current analytical paradigm by developing micromechanics-informed machine-learning based constitutive modelling approaches for granular materials. A set of critical variables associated with the constitutive behaviour of granular materials are identified through an incremental stress-strain relationship analysis. Depending on the strategy to exploit the priori micromechanical knowledge, three different training strategies are explored. The first model uses only the measurable external variables to make stress predictions; the second model utilises a directed graph to link all the external strain sequences and internal microstructural evolution variables into a single prediction model comprised of a series of sub-mappings, and the third model explicitly integrates the physically important non-temporal properties with external strain paths into training through an enhanced Gated Recurrent Unit (GRU). These three models show satisfactory agreement with unseen test specimens based on multi-directional loading cases. The basic features and potential applications of each model are explained. Lastly, the key factors for constitutive training and limitations of the current work are also discussed in detail.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Modeling the non-Schmid crystallographic slip in MAX phases

We present a crystal plasticity constitutive relation for the description of experimentally observed non-Schmid crystallographic slip in a class of ternary carbides and nitrides commonly referred to as MAX phases. In the constitutive relation, we assume that the evolution of the slip system strength in MAX phases has two components – a classical component that depends on the Taylor cumulative shear strain and a non-Schmid component that depends on the stress normal to the slip plane. The non-Schmid crystal plasticity constitutive relation is then used to carry out finite element simulations of micropillar compression of single crystals of two MAX phases, Ti 2 AlC and Ti 3 AlC 2 . The finite element simulations not only quantitatively predict the stress – strain response of a wide range of crystallographic orientations of the micropillars but also rationalize the non-uniform deformation and the deformed shape of the micropillars observed in the experiments for the two materials. As a result, parametric studies are also carried out to quantify the role of the non-Schmid effect and understand the effects of key experimental parameters on the stress – strain response of the micropillars of the two MAX phases.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Effect of hydrogen on plasticity of $α$-Fe: A multi-scale assessment

A multi-scale study was carried out to quantify the effect of interstitial hydrogen concentration on plasticity in $α$-Fe. Here, in this work, the influence of hydrogen on the screw dislocation glide behavior was examined across several length-scales. The insights obtained were integrated to provide an accurate continuum description for the effect of hydrogen on the dislocation based plasticity in polycrystalline $α$-Fe. At the outset of this work, a new Fe—H interatomic potential was formulated that enhanced the atomistic estimation of the variation in dislocation glide behavior in presence of hydrogen. Next, the dislocation core reconstruction observed due to the addition of hydrogen using atomistic simulations was validated with the help of large-scale DFT calculations based on the DFT-FE framework. Several atomistic simulations were carried out to comprehensively quantify the effect of hydrogen on the non-Schmid behavior exhibited during the dislocation glide in $α$-Fe. Finally, crystal plasticity simulations were carried out to understand the effect of hydrogen on the meso-scale deformation behavior of polycrystalline $α$-Fe.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Mentorship Initiatives in Radiation Oncology: A Scoping Review of the Literature

Although mentorship is described extensively in academic medical literature, there are few descriptions of mentorship specific to radiation oncology. The goal of the current study was to investigate the state of mentorship in radiation oncology through a scoping review of the literature.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2021

COVID-19 Vaccine-Induced Radiation Recall Phenomenon

Radiation recall phenomenon (RRP) is an uncommon, late occurring, acute inflammatory skin reaction that emerges in localized areas coincident with previously irradiated radiation therapy (RT) treatment fields. RRP has been known to be triggered by a number of chemotherapy agents. To the best of our knowledge, this report is the first description of RRP after administration of the Pfizer-BioNTech vaccine for COVID-19, or any other currently available vaccine against COVID-19. Acute skin reactions were observed in 2 RT patients with differing timelines of RT and vaccinations. In both cases however, the RRP presented within days of the patient receiving the second dose of vaccine. For each RT course, the treatment planning dosimetry of the radiation fields was compared with the area of the observable RRP. RRP developed within the borders of treatment fields where prescription dose constraints were prioritized over skin sparing. Our observation is currently limited to 2 patients. The actual incidence of RRP in conjunction with Pfizer-BioNTech vaccine or any other vaccine against COVID-19 is unknown. For patients with cancer being treated with radiation with significant dose to skin, consideration should be given to the probability of RRP side effects from vaccinations against COVID-19.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2024

Multiscale simulation of spatially correlated microstructure via a latent space representation

When deformation gradients act on the scale of the microstructure of a part due to geometry and loading, spatial correlations and finite-size effects in simulation cells cannot be neglected. We propose a multiscale method that accounts for these effects using a variational autoencoder to encode the structure–property map of the stochastic volume elements making up the statistical description of the part. In this paradigm the autoencoder can be used to directly encode the microstructure or, alternatively, its latent space can be sampled to provide likely realizations. Furthermore, we demonstrate the method on three examples using the common additively manufactured material AlSi10Mg in: (a) a comparison with direct numerical simulation of the part microstructure, (b) a push forward of microstructural uncertainty to performance quantities of interest, and (c) a simulation of functional gradation of a part with stochastic microstructure.

Elastoplasticity↗
DOE OSTI2021

Multimodal Analysis of Spatially Heterogeneous Microstructural Refinement and Softening Mechanisms in Three-Pass Friction Stir Processed Al4Si Alloy

Multiple thermally and thermomechanically induced microstructural refinement mechanisms can be activated in metallic alloys when subjected to solid phase processing methods such as friction stir processing (FSP). In this work, we provide detailed descriptions of the relationship between region-specific microstructural refinement mechanisms and the variation in microhardness, through a systematic and multimodal microstructural characterization of an FSP-processed 75% cold-rolled Al-4 at.% Si model binary alloy. Spatially resolved high-energy synchrotron X-ray diffraction, electron backscattered diffraction, and scanning transmission electron microscopy were used to understand the spatially heterogeneous microstructural evolution due to FSP. Results provide insights into how mechanisms such as static recovery, static recrystallization, dynamic recovery and recrystallization, geometric and continuous dynamic recrystallization, and particle-stimulated static or dynamic grain nucleation may occur heterogeneously in the microstructure as a function of the distance from the stir zone in processed alloys, directly influencing the degree of softening. The systematic analysis of microstructures and hardness in the FSP-processed model binary alloy given in this work highlights the rich microstructural domains that can be uniquely harnessed through solid phase processing of metallic alloys.

Al4Si, Friction Stir Processing, Geometric Dynamic↗
DOE OSTI2022

Phase stability in cast and additively manufactured Al-rich Al-Cu-Ce alloys

Additively manufactured (AM) eutectic Al alloy systems have been studied extensively for advantageous thermal stability and mechanical properties due to their refined microstructures. Al-Cu-Ce alloys are one subset of these AM eutectic alloys. Here we studied phase stability in AM Al-Cu-Ce alloys and compared it to that of conventionally cast ones. A new phase, Al 8 Cu 3 Ce, was identified in the microstructures of both AM and cast Al-Cu-Ce alloys. This Al 8 Cu 3 Ce phase was not previously included on experimental or thermodynamically calculated phase diagrams of the Al-Cu-Ce system. Therefore, we performed additional thermodynamic modeling of the system. These models were experimentally validated with cast and subsequently heat-treated Al-Cu-Ce alloys. We found that despite the refined microstructure of the AM alloys, the phases formed were consistent with the cast alloys, suggesting that AM processing did not significantly alter the formation and stability of phases from that in the conventional alloys. In conclusion, this work has resolved inconsistent previous descriptions of the Al-Cu-Ce ternary phase diagram in the Al-rich region and resulted in the addition of the Al 8 Cu 3 Ce as an equilibrium phase above 500 °C.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Scattering by whistler-mode waves during a quiet period perturbed by substorm activity

We study the dynamics of radiation belt electrons during a 10-day quiet period perturbed by substorm activity and preceding a high-speed stream (HSS), aiming at a global description of the radiation belts in L-shell, L in [2, 6], and energy [0.1, 10] MeV. We combine Van Allen Probes observations and Fokker-Planck numerical simulations of pitch-angle diffusion. The Fokker-Planck model uses event-driven pitch angle diffusion coefficients from whistler-mode waves, built from the wave properties and the ambient plasma density measurements from the Van Allen Probes. We first find this event has some similar characteristics to regular quiet times previously studied; a widely extended plasmasphere within which we observe strong and varying whistler-mode waves. These ambient conditions lead to strong pitch-angle scattering, which contributes to the creation of a wide slot region as well as a significant decay of the outer radiation belts, which are observed and qualitatively well simulated. In addition, we find the substorm activity causes short duration (within ± 4h) decay of the plasma density and a lowering amplitude of the whistler-mode waves within the plasmasphere, both causing opposite effects in terms of pitch angle diffusion. This leads to a diminution of pitch-angle diffusion at the time of the main substorm activity. Conversely, whistler-mode waves become enhanced in the time periods between the substorm injections. All effects cumulated, we find an enhancement of pitch angle diffusion by whistler-mode waves above L~4.7 during the 10-day period. This directly relates to the combination of quietness and substorm activity which allows pitch angle diffusing of up to 1 MeV electrons in the outer belt. Relativistic electrons of 1–2 MeV remain trapped in the outer belt, from L~4.7 to L~5.2, forming, in both the observations and the simulations, a distinct pocket of remnant electrons.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

KEBLM: Knowledge-Enhanced Biomedical Language Models

Pretrained language models (PLMs) have demonstrated strong performance on many natural language processing (NLP) tasks. Despite their great success, these PLMs are typically pretrained only on unstructured free texts without leveraging existing structured knowledge bases that are readily available for many domains, especially scientific domains. As a result, these PLMs may not achieve satisfactory performance on knowledge-intensive tasks such as biomedical NLP. Comprehending a complex biomedical document without domain-specific knowledge is challenging, even for humans. Inspired by this observation, we propose a general framework for incorporating various types of domain knowledge from multiple sources into biomedical PLMs. We encode domain knowledge using lightweight adapter modules, bottleneck feed-forward networks that are inserted into different locations of a backbone PLM. For each knowledge source of interest, we pretrain an adapter module to capture the knowledge in a self-supervised way. We design a wide range of self-supervised objectives to accommodate diverse types of knowledge, ranging from entity relations to description sentences. Once a set of pretrained adapters is available, we employ fusion layers to combine the knowledge encoded within these adapters for downstream tasks. Each fusion layer is a parameterized mixer of the available trained adapters that can identify and activate the most useful adapters for a given input. Our method diverges from prior work by including a knowledge consolidation phase, during which we teach the fusion layers to effectively combine knowledge from both the original PLM and newly-acquired external knowledge using a large collection of unannotated texts. After the consolidation phase, the complete knowledge-enhanced model can be fine-tuned for any downstream task of interest to achieve optimal performance. Extensive experiments on many biomedical NLP datasets show that our proposed framework consistently improves the performance of the underlying PLMs on various downstream tasks such as natural language inference, question answering, and entity linking. These results demonstrate the benefits of using multiple sources of external knowledge to enhance PLMs and the effectiveness of the framework for incorporating knowledge into PLMs. Finally, while primarily focused on the biomedical domain in this work, our framework is highly adaptable and can be easily applied to other domains, such as the bioenergy sector.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
DOE OSTI2021

The Delplot kinetic method applied to systems with adsorbates: Hydrodeoxygenation of benzofuran on a bimetallic CoPd phosphide catalyst supported on KUSY

The Delplot method provides a means of analyzing conversion and selectivity data to derive a reaction sequence and has been applied so far to gas-phase or liquid-phase species. This study analyses the applicability of the method for catalytic reactions and considers for the first time adsorbed intermediates. The method is applied to a contact time study of the hydrodeoxygenation (HDO) of benzofuran at 0.5 MPa and 350 °C over a catalyst consisting of bimetallic CoPd phosphide supported on a potassium ion-exchanged ultra-stable Y (KUSY) zeolite. Both simple and detailed reaction networks were derived. The simple networks considered only gas-phase species and were modeled by a first-order sequence of steps, whereas the detailed network took into account adsorbed intermediates and was simulated using a rake mechanism. The networks were compared using F-statistics, which accounted for the differences in the number of fitting parameters. The detailed network gave a better fit to the experimental data because it represented a more realistic description of the transformation. A suggested sequence from the Delplot method was consistent with the simple network but not with the detailed network. The lack of applicability of the Delplot analysis to the network with adsorbates was linked to overly large equilibrium constants, a determination supported by Delplot fitting for a model sequence. Further, this study indicated the inapplicability of the Delplot method in determining reaction sequences that involve adsorbed species with large equilibrium constants for formation.

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

Best practices in catalysis: A perspective

Catalysis, from its roots in petrochemical refining and conversion, has emerged as a transdisciplinary field that now encompasses synthesis of materials and molecules that enable applications in energy conversion and storage, environmental remediation, medicine, plastics, and fertilizer production, among numerous others. A handful of disciplines can claim relevance and success over such an extended period of time and continue to claim a preeminent role in defining the state-of-the-art in science and technology. Syncretic and rapid advancements in formulation and spectroscopic characterization of materials and molecules useful as catalysts, high-level density functional and molecular orbital theory calculations, and a strong foundation in concepts of physical chemistry, thermodynamics, and chemical kinetics offer new and abundant opportunities at the present day for addressing the grand challenge of controlling chemical transformations using catalysis. Here, we examine what we have learned of concepts that underpin heterogeneous catalysis but more importantly, how we learned to archive our knowledge in context of a set of best practices and standards that have emerged in the course of our learnings—ones we seek to highlight herein. Our perspective emphasizes concepts in synthesis, characterization, kinetics, and theory, because these four elements combined enable description of molecular acts that happen on surfaces and how fast they occur. In revisiting best practices in heterogeneous catalysis in these sub-fields and in authorship and peer review we aspire to augment clarity, reproducibility, and rigor in the science and practice of catalysis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Trace Fe activates perovskite nickelate OER catalysts in alkaline media via redox-active surface Ni species formed during electrocatalysis

The accurate description of activity trends among perovskite-oxide oxygen-evolution-reaction (OER) catalysts using electronic-structure descriptors requires that the bulk structure of the catalyst is comparable to that of the surface. Few studies have addressed the dynamic nature of the catalyst's structure during the OER and the consequential implications for understanding activity. Here, we use a combination of electrochemical and materials-characterization techniques to study the surface reconstruction and the associated formation of a new redox-active phase on LaNiO 3 particles, LaNiO 3 epitaxial films, and an analogous Ruddlesden-Popper phase, La 2 NiO 4 . Small, but characteristic, redox features corresponding to Ni redox in nominally amorphous NiO x H y are observed during cyclic voltammetry of these initially fully crystalline materials. The size of these redox features grows with prolonged cycling and contributes to an increased surface area as determined from electrochemical impedance spectroscopy (EIS). Here we find the OER activity is strongly dependent on soluble Fe species in the electrolyte, common impurities in alkaline media. These observations are consistent with the reconstruction of the crystalline surface to form NiO x H y species and subsequent activation by adsorption of Fe forming the well-known and extremely active NiFeO x H y OER catalyst.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗