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At least 883 records · Page 49

Uncovering the True Active Sites in Ni–N–C Catalysts for CO 2 Electroreduction

Understanding and designing active sites in single-atom catalysts (SACs) requires going beyond static models to capture their dynamic evolution under realistic electrochemical conditions. Here, in this work, we develop an integrated theoretical framework that accounts for operational conditions, by combining grand canonical density functional theory (GC-DFT) with machine-learning-accelerated sampling, to uncover structure–activity–stability relationships in Ni–N–C SACs for the CO 2 reduction reaction (CO 2 RR). A library of NiN x C 4–x (x = 0–4) motifs─representing coordination defects likely formed during high-temperature synthesis─was systematically evaluated. Under working conditions, these sites were found to undergo hydrogenation, and NiN 3 C 1_ H 1 was identified as the most probable active site. At reducing potentials, hydrogen adsorbs spontaneously at C–Ni bridge sites rather than Ni top sites, while subsurface hydrogen facilitates bent CO 2 adsorption crucial for activation. High CO 2 RR selectivity toward CO arises from site separation: Ni centers drive CO2RR, while the hydrogen evolution reaction (HER) occurs at the C–Ni bridge or N sites and from thermodynamic suppression of HER at moderate hydrogen coverage. At more negative potentials, a shift in the CO 2 RR rate-determining process (RDP) and Ni out-of-surface displacement induced by coadsorption of H and H 2 O jointly reduce activity and selectivity. Thus, both the high CO2RR selectivity of Ni–N–C catalysts and its reversal with more negative potentials can be rationalized by accounting for hydrogenated surfaces. This highlights the necessity of modeling realistic; in situ conditions. This framework provides generalizable insights into the dynamic behavior of active sites in SACs, offering guidance for the rational design of active and robust catalysts for a wide range of electrochemical reactions.

25 ENERGY STORAGE↗

Supermassive black holes and their host galaxies. I. Bulge luminosities from dedicated near-infrared data

In an effort to secure, refine, and supplement the relation between central supermassive black hole masses, M {sub •}, and the bulge luminosities of their host galaxies, L {sub bul}, we obtained deep, high spatial resolution K-band images of 35 nearby galaxies with securely measured M {sub •}, using the wide-field WIRCam imager at the Canada-France-Hawaii-Telescope. A dedicated data reduction and sky subtraction strategy was adopted to estimate the brightness and structure of the sky, a critical step when tracing the light distribution of extended objects in the near-infrared. From the final image product, bulge and total magnitudes were extracted via two-dimensional profile fitting. As a first order approximation, all galaxies were modeled using a simple Sérsic-bulge+exponential-disk decomposition. However, we found that such models did not adequately describe the structure that we observed in a large fraction of our sample galaxies which often include cores, bars, nuclei, inner disks, spiral arms, rings, and envelopes. In such cases, we adopted profile modifications and/or more complex models with additional components. The derived bulge magnitudes are very sensitive to the details and number of components used in the models, although total magnitudes remain almost unaffected. Usually, but not always, the luminosities and sizes of the bulges are overestimated when a simple bulge+disk decomposition is adopted in lieu of a more complex model. Furthermore, we found that some spheroids are not well fit when the ellipticity of the Sérsic model is held fixed. This paper presents the details of the image processing and analysis, while we discuss how model-induced biases and systematics in bulge magnitudes impact the M {sub •}-L {sub bul} relation in a companion paper.

79 ASTRONOMY AND ASTROPHYSICS↗

Covariance-Free Bifidelity Control Variates Importance Sampling for Rare Event Reliability Analysis

Multifidelity modeling has been steadily gaining attention as a tool to address the problem of exorbitant model evaluation costs that makes the estimation of failure probabilities a significant computational challenge for complex real-world problems, particularly when failure is a rare event. To implement multifidelity modeling, estimators that efficiently combine information from multiple models/sources are necessary. In past works, the variance reduction techniques of control variates (CV) and importance sampling (IS) have been leveraged for this task. In this paper, we present the CVIS framework—a creative take on a coupled CV and IS estimator for bifidelity reliability analysis. The framework addresses some of the practical challenges of the CV method by using an estimator for the control variate mean and sidestepping the need to estimate the covariance between the original estimator and the control variate through a clever choice for the tuning constant. Furthermore, the task of selecting an efficient IS distribution is also considered, with a view towards maximally leveraging the bifidelity structure and maintaining expressivity. Additionally, a diagnostic is provided that indicates both the efficiency of the algorithm as well as the relative predictive quality of the models utilized. Finally, the behavior and performance of the framework is explored through analytical and numerical examples.

Markov chain Monte Carlo↗

Structure and Reactivity of Binuclear Cu Active Sites in Cu-CHA Zeolites for Stoichiometric Partial Methane Oxidation to Methanol

Aluminosilicate zeolites exchanged with copper ions facilitate partial methane oxidation (PMO) to methanol in stoichiometric oxidation and reduction cycles, yet the identities of active Cu sites and details of the reaction mechanism remain debated. Here, we use the high-symmetry chabazite (CHA) zeolite framework as a model support to probe the relationship between bulk composition, Cu speciation, and response to various oxidizing and reducing treatments. Density functional theory and first-principles thermodynamics combined with statistical models reveal that Cu speciation and composition depend strongly on Al configuration and external gas conditions. Cu-CHA samples were synthesized to survey broad regions of Si/Al and Cu/Al composition space and framework Al proximity. Characterization by in situ X-ray absorption and UV–visible spectroscopy during exposure to different oxidation conditions reveal that the extent of Cu oxidation is sensitive to activation conditions and thus that both kinetic and thermodynamic factors influence Cu oxidizability in a given material. Similar characterizations during CO reduction reveal that CO titrates Cu 2+ in amounts suggesting the presence of both O- and O 2 -bridged species. In contrast, CH 4 and autoreduction (He) treatments reduce similar but smaller numbers of Cu sites than CO, implicating O 2 -bridged Cu dimers as a potential common intermediate in the former reduction pathways. Furthermore, a systematic increase in methanol yields (per Cu) in stoichiometric PMO cycles increase with the fraction of binuclear O x -bridged Cu sites suggests these species as active sites, as depicted in an updated PMO reaction mechanism.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Steady state thermo-mechanics and material property definition framework for analyzing DCLL blanket in the fusion nuclear science facility

In this work, a thermo-mechanics model that relies on creating the material property definition framework (MPDF) and multiphysics coupling of the heat transfer and the solid mechanics modules is developed to determine the structural integrity of the recently designed dual cooled lead lithium (DCLL) inboard blanket (IB) for the Fusion Nuclear Science Facility under steady state loads. The MPDF is called to supply fusion relevant neutron irradiation and temperature induced changes in material properties during multiphysics finite element runs, and PbLi temperature profiles are used to approximate Magnetohydrodynamics effect and the nuclear volumetric heating on the PbLi. Neutron irradiation and temperature induced reduction of the yield and ultimate strengths of F82H steel at the first wall (FW) are quantified for one year. A blanket in an assembly with gaps between blanket sectors and another blanket in an assembly with no gaps between blanket sectors, both exposed to radiation damage that lasted for one year are analyzed. Analysis using the elastic ITER structural design criteria for in-vessel components (ITER SDC-IC) design rules and a linear isotropic-hardening-type elastoplastic material model are used where most appropriate. The IB blanket with gaps between blanket sectors will withstand the steady state combined thermal and coolant loads for one year operational period but will fail if no gaps are allowed between blanket sectors. It is recommended that a gap of about 7.62 mm should be provided between IB blanket sectors during assembly which would close up during service, stop neutron streaming, reduce stresses and reduce bending of the FW into the scrape-off layer.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Sensitivity Analysis of Occupant Preferences on Energy Usage in Residential Buildings: Preprint

Residential buildings, accounting for 37% of the total electricity consumption in the United States, are suitable for demand-side management (DSM) programs to support effective and economical operation of the power system. A home energy management system (HEMS) enables residential buildings to participate in such programs. It is important to account for occupant preferences in HEMS to ensure occupant satisfaction while participating in DSM programs. For example, people who prefer a higher thermal comfort level are likely to consume more energy. In this study, we used foresee™, a HEMS developed by the National Renewable Energy Lab (NREL), to perform a sensitivity analysis of occupant preferences with the following objectives: minimize utility cost, minimize carbon footprint, and maximize thermal comfort. To incorporate the preferences into the HEMS, the SMARTER method was used to derive a set of weighting factors for each objective. We performed week-long building energy simulations using a model of a home in Fort Collins, Colorado, where there is mandatory time-of-use electricity rate structure. The foreseeTM HEMS was used to control the home with six different sets of occupant preferences. The study shows that occupant preferences can have a significant impact and is important to consider when modeling residential buildings. Results show that the HEMS could achieve energy reduction ranging from 3% to 21%, cost savings ranging from 5% to 24%, and carbon emission reduction ranging from 3% to 21%, while maintaining a low thermal discomfort level ranging from 0.78 K-hour to 6.47 K-hour in a one-week period during winter. These outcomes quantify the impact of varying occupant preferences and will be useful for controlling the electrical grid and developing HEMS solutions.

carbon footprint↗

SAM Code Enhancements for Fission Product Tracking of Noble Gases and Metals in MSRs

This report documents fiscal year 2026 enhancements to the System Analysis Module (SAM) for modeling fission product transport in liquid-fueled molten salt reactors (MSRs). The work advances three principal areas: noble gas transport, noble metal deposition, and user interface improvements. The noble gas transport capability integrates drift-flux gas transport, Henry’s law two-film interphase mass transfer with pressure-based nucleation suppression, Knudsen-regime pore diffusion into porous graphite with a conjugate salt-graphite interface constraint, built-in material properties, five Sherwood-number mass transfer correlations including three derived from high-fidelity NekRS simulations, and xenon-135 reactivity feedback through SAM’s point-kinetics model. This work also presents a comprehensive verification test suite, including new analytically verified cases for pressure-dependent onset of interphase gas transfer in a stagnant vertical pipe, a postulated FLiBe-graphite Xe extraction permeator, a gravity riser with a fission-product source, and a descending pipe with gas redissolution driven by hydrostatic pressure. A machine learning framework for bubble rise velocity prediction in molten salt systems is developed and benchmarked on molten-salt and diverse aqueous bubble datasets. The best-performing fine-tuned transfer-learning networks achieve an 82% reduction in RMSE relative to the Clift correlation, and is implemented directly in SAM. The noble metal transport capability is developed, including a liquid-wall deposition model and a gas-surface flotation mechanism that transfers insoluble particles entrained by sparging gas to wetted structures. Verification tests and demonstration cases cover the surface deposition, flotation efflux, and flotation shedding. Finally, a new [SpeciesTransport] input structure replaces positional global vectors with selfcontained, order-independent, named species blocks, simplifies the specification of multiphase species and decay chains, and remains fully compatible with existing SAM input files. Together, these developments improve the physical fidelity, verification basis, and usability of SAM for system-level analyses of fissionproduct behavior in MSRs.

Mui, Travis (ORCID:0000000303736470)↗

HST observations of the inner coma of Comet Levy 1990c

Data reduction procedures which will make it possible to model the nucleus of future targets of cometary space missions were tested on the basis of observations of Comet Levy 1990c by the HST on September 27, 1990. Faint hemispherical shells expanding in the coma, which is structured as a sunward fan deflected by solar radiation pressure, were observed. The Eddington fountain model makes it possible to infer the ejection times of the expanding shells and the initial velocity of the dust. Three shells ejected at time intervals of 11.5 and 12.5 h with an initial velocity of 0.35 km/s were observed for dust grains of 3-micron size. The lag angle of the fan is between 10 and 15 deg, thus suggesting a time delay of the most active sublimation of 1 h after midday. The observed time periodicities suggest a nucleus rotating in 24 h with a surface characterized by two active areas placed almost exactly in opposite hemispheres, even if a longer rotation period and a more complex nucleus topography can be excluded.

Fulle, M.↗

ASTRO-H Soft X-Ray Telescope (SXT)

ASTRO-H is an astrophysics satellite dedicated for X-ray spectroscopic study non-dispersively and to carry out survey complementally, which will be borne out of US-Japanese collaborative effort. Among the onboard instruments there are four conically approximated Wolter-I X-ray mirrors, among which two of them are soft X-ray mirrors\ of which the energy range is from a few hundred eV to 15 keY, currently being fabricated in the X-ray Optics Lab at Goddard Space Flight Center. The focal point instruments will be a calorimeter (SXS) and a CCD camera (SXI), respectively. The reflectors of the mirror are made of heat-formed aluminum substrate of the thickness gauged of 152 micron, 229 micron, and 305 micron of the alloy 5052 H-19, followed by epoxy replication on gold-sputtered smooth Pyrex cylindrical mandrels to acquire the X-ray reflective surface. The epoxy layer is 10 micron nominal and surface gold layer of 0.2 micron. Improvements on angular response over the Astro-El/Suzaku mirrors come from error reduction on the figure, the roundness, and the grazing angle/radius mismatching of the reflecting surface, and tighter specs and mechanical strength on supporting structure to reduce the reflector positioning and the assembly errors. In this paper, we report the results of calibration of the engineering model of SXT (EM), and project the quality of the flight mirrors.

Soong, Yang↗

Wall-Modeled Large-Eddy Simulations of Jet Noise in Flight Conditions

A campaign of wall-modeled large-eddy simulations (WMLES) using structured curvilinear overlapping grids has been performed with the Launch Ascent and Vehicle Aerodynamics (LAVA) computational fluid dynamics (CFD) software to predict jet noise for single-stream axisymmetric round jets. The simulations address the new Prediction Uncertainty Reduction (PUR) technical challenge within the context of NASA’s Commercial Supersonic Technology (CST) project. The focus of this effort is to generate a simulation database for single-stream axisymmetric round nozzles at several operating points both for static (no ambient co-flow), and in-flight (M ͚ =0.3 co-flow) conditions. The operating conditions range in jet exit Mach number from 0.38 to 1.1 with nozzle temperature ratios (NTR) from 0.84 to 2.7. The effect of the flight-stream on far-field noise sound spectra is assessed. Comparison of LES predictions to microphone array measurements demonstrate good agreement within the resolved frequency range. A dip in the predicted low frequency noise spectra for observers between 120° and 145° is observed. This dip is smaller for lower Mach numbers and seems to be correlated to the Mach wave radiation angle. The Mach 1.1 jet shows broadband-shock associated noise. While the onset of BBSN appears to be captured correctly in WMLES, some differences in its magnitude and the prominent frequency at which it occurs persist between the experiment and the simulations. The effect of the outer nozzle boundary layer state created by the co-flow is assessed and shows to be important for accurate comparisons with experiments. A change of 2.5dB between a slip-wall condition and a artificially thickened turbulent boundary layer was observed. In addition, simulations were performed with an alternative nozzle geometry that includes a internal plug and has twice the nozzle exit diameter. These two configurations resulted in very comparable spectra which is consistent with experimental observations. A generally stronger deviation from experimental results is observed for in-flight cases compared to static conditions. The applicability and correct usage of acoustic analogies used for far-field propagation with strong turbulent co-flows needs to be investigated more systematically using canonical problems to improve comparisons between experiments and WMLES. This is especially true for coherent noise sources seen in BBSN.

CST↗

Studying methane migration mechanisms at Walker Ridge, Gulf of Mexico, via 3D methane hydrate reservoir modeling

We have developed a 3D methane hydrate reservoir simulator to model marine methane hydrate systems. Our simulator couples highly nonlinear heat and mass transport equations and includes heterogeneous sedimentation, in-situ microbial methanogenesis, the influence of pore size contrast on solubility gradients, and the impact of salt exclusion from the hydrate phase on dissolved methane equilibrium in pore water. Using environmental parameters from Walker Ridge in the Gulf of Mexico, we first simulate hydrate formation in and around a thin, dipping, planar sand stratum surrounded by clay lithology as it is buried to 295mbsf. We find that with sufficient methane being supplied by organic methanogenesis in the clays, a 200x pore size contrast between clays and sands allows for a strong enough concentration gradient to significantly drop the concentration of methane hydrate in clays immediately surrounding a thin sand layer, a phenomenon that is observed in well log data. Building upon previous work, our simulations account for the increase in sand-clay solubility contrast with depth from about 1.6% near the top of the sediment column to 8.6% at depth, which leads to a progressive strengthening of the diffusive flux of methane with time. By including an exponentially decaying organic methanogenesis input to the clay lithology with depth, we see a decrease in the aqueous methane supplied to the clays surrounding the sand layer with time, which works to further enhance the contrast in hydrate saturation between the sand and surrounding clays. Significant diffusive methane transport is observed in a clay interval of about 11m above the sand layer and about 4m below it, which matches well log observations. The clay-sand pore size contrast alone is not enough to completely eliminate hydrate (as observed in logs), because the diffusive flux of aqueous methane due to a contrast in pore size occurs slower than the rate at which methane is supplied via organic methanogenesis. Therefore, it is likely that additional mechanisms are at play, notably bound water activity reduction in clays. Three-dimensionality allows for inclusion of lithologic heterogeneities, which focus fluid flow and subsequently allow for heterogeneity in the methane migration mechanisms that dominate in marine sediments at a local scale. Incorporating recently acquired 3D seismic data from Walker Ridge to inform the lithologic structure of our modeled reservoir, we show that even with deep adjective sourcing of methane along highly permeable pathways, local hydrate accumulations can be sourced either by diffusive or advective methane flux; advectively-sourced hydrates accumulate evenly in highly permeable strata, while diffusively-sourced hydrates are characterized by thin strata-bound intervals with high clay-sand pore size contrasts.

Nole, Michael↗

A Fully Non-metallic Gas Turbine Engine Enabled by Additive Manufacturing

The Non-Metallic Gas Turbine Engine project, funded by NASA Aeronautics Research Institute (NARI), represents the first comprehensive evaluation of emerging materials and manufacturing technologies that will enable fully nonmetallic gas turbine engines. This will be achieved by assessing the feasibility of using additive manufacturing technologies for fabricating polymer matrix composite (PMC) and ceramic matrix composite (CMC) gas turbine engine components. The benefits of the proposed effort include: 50 weight reduction compared to metallic parts, reduced manufacturing costs due to less machining and no tooling requirements, reduced part count due to net shape single component fabrication, and rapid design change and production iterations. Two high payoff metallic components have been identified for replacement with PMCs and will be fabricated using fused deposition modeling (FDM) with high temperature capable polymer filaments. The first component is an acoustic panel treatment with a honeycomb structure with an integrated back sheet and perforated front sheet. The second component is a compressor inlet guide vane. The CMC effort, which is starting at a lower technology readiness level, will use a binder jet process to fabricate silicon carbide test coupons and demonstration articles. The polymer and ceramic additive manufacturing efforts will advance from monolithic materials toward silicon carbide and carbon fiber reinforced composites for improved properties. Microstructural analysis and mechanical testing will be conducted on the PMC and CMC materials. System studies will assess the benefits of fully nonmetallic gas turbine engine in terms of fuel burn, emissions, reduction of part count, and cost. The proposed effort will be focused on a small 7000 lbf gas turbine engine. However, the concepts are equally applicable to large gas turbine engines. The proposed effort includes a multidisciplinary, multiorganization NASA - industry team that includes experts in ceramic materials and CMCs, polymers and PMCs, structural engineering, additive manufacturing, engine design and analysis, and system analysis.

manufacturing↗

Efficient Space–Time Reduced Order Model for Linear Dynamical Systems in Python Using Less than 120 Lines of Code

A classical reduced order model (ROM) for dynamical problems typically involves only the spatial reduction of a given problem. Recently, a novel space–time ROM for linear dynamical problems has been developed [Choi et al., Space–tume reduced order model for large-scale linear dynamical systems with application to Boltzmann transport problems, Journal of Computational Physics, 2020], which further reduces the problem size by introducing a temporal reduction in addition to a spatial reduction without much loss in accuracy. The authors show an order of a thousand speed-up with a relative error of less than 10−5 for a large-scale Boltzmann transport problem. In this work, we present for the first time the derivation of the space–time least-squares Petrov–Galerkin (LSPG) projection for linear dynamical systems and its corresponding block structures. Utilizing these block structures, we demonstrate the ease of construction of the space–time ROM method with two model problems: 2D diffusion and 2D convection diffusion, with and without a linear source term. For each problem, we demonstrate the entire process of generating the full order model (FOM) data, constructing the space–time ROM, and predicting the reduced-order solutions, all in less than 120 lines of Python code. We compare our LSPG method with the traditional Galerkin method and show that the space–time ROMs can achieve O(10−3) to O(10−4) relative errors for these problems. Depending on parameter–separability, online speed-ups may or may not be achieved. For the FOMs with parameter–separability, the space–time ROMs can achieve O(10) online speed-ups. Finally, we present an error analysis for the space–time LSPG projection and derive an error bound, which shows an improvement compared to traditional spatial Galerkin ROM methods.

97 MATHEMATICS AND COMPUTING↗

Interior structure of Jupiter - Theory of gravity sounding

Using relatively simple interior models and a fourth-order theory of figures, it is found that there are basically two extremes of interior structure which agree with current gravity data. One extreme is a 'solar'-composition envelope with 10 to 15 earth masses of heavy material in a core; the other extreme has nearly uniform 'solar' composition but with approximately an additional 30 earth masses of heavy material distributed essentially uniformly. Thus, Jupiter is not of 'solar' composition. It is shown how additional gravity data and improvement in knowledge of the molecular hydrogen equation of state will permit a significant reduction in the number of possible models.

Hubbard, W. B.↗

Chemical Kinetic Method for Active-Site Quantification in Fe-N-C Catalysts and Correlation with Molecular Probe and Spectroscopic Site-Counting Methods

Mononuclear Fe ions ligated by nitrogen (FeN x ) dispersed on nitrogen-doped carbon (Fe-N-C) serve as active centers for electrocatalytic O 2 reduction and thermocatalytic aerobic oxidations. Despite their promise as replacements for precious metals in a variety of practical applications, such as fuel cells, the discovery of new Fe-N-C catalysts has relied primarily on empirical approaches. In this context, the development of quantitative structure–reactivity relationships and benchmarking of catalysts prepared by different synthetic routes and by different laboratories would be facilitated by the broader adoption of methods to quantify atomically dispersed FeN x active centers. In the present study, we develop a kinetic probe reaction method that uses the aerobic oxidation of a model hydroquinone substrate to quantify the density of FeN x centers in Fe- N-C catalysts. The kinetic method is compared with low-temperature Mössbauer spectroscopy, CO pulse chemisorption, and electrochemical reductive stripping of NO derived from NO 2 – on a suite of Fe-N-C catalysts prepared by diverse routes and featuring either the exclusive presence of Fe as FeN x sites or the coexistence of aggregated Fe species in addition to FeN x . The FeN x site densities derived from the kinetic method correlate well with those obtained from CO pulse chemisorption and Mössbauer spectroscopy. The broad survey of Fe-N-C materials also reveals the presence of outliers and challenges associated with each site quantification approach. Furthermore, the kinetic method developed here does not require pretreatments that may alter active-site distributions nor specialized equipment beyond reaction vessels and analytical instrumentation (e.g., NMR).

36 MATERIALS SCIENCE↗

Validation of Material Models For Automotive Carbon Fiber Composite Structures Via Physical And Crash Testing (VMM Composites Project)

As automotive fuel economy requirements increase, the push for reducing overall vehicle weight will likely include the consideration of materials that have not previously been part of mainstream vehicle design and manufacturing, including carbon fiber composites. Vehicle manufacturers currently rely on computer-aided engineering (CAE) methods as part of the design and development process, so going forward, the ability to accurately and predictably model carbon fiber composites will be necessary. If composites are to be used for structural components, this need applies to both, crash and quasi-static modeling. This final report covers the results of a five-year, $6.89M, 50% cost-shared research project between Department of Energy (DOE) and the US Advanced Materials Partnership (USAMP) under Cooperative Agreement DE-EE-0005661 known as “Validation of Material Models for Automotive Carbon Fiber Composite Structures Via Physical and Crash Testing (VMM).” The objective of the VMM Composites Project was to validate and assess the ability of physics-based material models to predict crash performance of automotive primary load-carrying carbon fiber composite structures. Simulation material models that were evaluated included micro-mechanics based meso-scale models developed by the University of Michigan (UM) and micro-plane models by Northwestern University (NWU) under previous collaborations with the DOE and Automotive Composites Consortium/USAMP, as well as five commercial crash codes: LS-DYNA, RADIOSS, VPS/PAM-CRASH, Abaqus, and GENOA-MCQ. CAE predictions obtained from seven organizations were compared with experimental results from quasi-static testing and dynamic crash testing of a thermoset carbon fiber composite front-bumper and crush-can (FBCC) system gathered under multiple loading conditions. This FBCC design was developed to demonstrate progressive crush, virtual simulation, tooling, fabrication, assembly, non-destructive evaluation and crash testing advances in order to assess the correlation of the predicted results to the physical tests. The FBCC was developed to meet a goal of 30-35% mass reduction while aiming for equivalent energy absorption as a steel component for which baseline experimental results were obtained from testing in the same crash modes. The project also evaluated crash performance of thermoplastic composite structures fabricated from commercial prepreg materials and low cost carbon fiber sourced from Oak Ridge National Laboratory. The VMM Project determined that no set of predictions from a CAE supplier were found to be universally accurate among all the six crash modes evaluated. In general, crash modes that were most dependent on the properties of the prepreg were more accurate than those that were dependent on the behavior of the joints. The project found that current CAE modeling methods or best practices for carbon fiber composites have not achieved standardization, and accuracy of CAE is highly reliant on the experience of its users. Coupon tests alone are not sufficient to develop an accurate material model, but it is necessary to bridge the gap between the coupon data and performance of the actual structure with a series of subcomponent level tests. Much of the unreliability of the predictions can be attributed to shortcomings in our ability to mathematically link the effects of manufacturing and material variability into the material models. This is a subject of ongoing research in the industry. The final report is organized by key technical tasks to describe how the validation project developed, modeled and compared crash data obtained on the composite FBCC to the multiple sets of CAE predictions. Highlights of the report include a discussion of the quantitative comparison between predictions and experimental data, as well as an in-depth discussion of remaining technological gaps that exist in the industry, which are intended to spur innovations and improvements in CAE technology.

36 MATERIALS SCIENCE↗

Microstructure-process relationships in monolithic U-10Mo fuel foil single-pass rolling: A parametric simulation study

In this work, a previously validated coupling of Kinetic Monte Carlo (KMC) Potts Model and finite element method (FEM) simulations was implemented to investigate the effects of microstructural features in as-cast and homogenized monolithic U-10Mo foils on the emergent microstructure after rolling and reheating. Parameters that could potentially affect recrystallization behavior of the rolled U-10Mo foils were considered: grain size distribution, uranium carbide (UC) size distribution, UC volume fraction, spatial distribution of UC, and rolling reduction magnitude. Grain structure and the magnitude of rolling reduction have the strongest influence on recrystallization kinetics and the fabricated grain size distribution. The UC distribution had only a weak effect on the recrystallization kinetics and final microstructures. While particle-stimulated nucleation (PSN) occurred in simulation more frequently as grain size increased, its incidence did not appear to considerably affect the recrystallization kinetics or grain size distribution.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗