Image-based multiscale modeling with spatially varying microstructures from experiments: Demonstration with additively manufactured metal in fatigue and fracture
Not Available
Kafka, Orion L. (ORCID:0000000323338154)↗
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Results for “WINGS - VIBRATION”
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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Development of computational framework for titanium alloy phase transformation prediction in laser powder-bed fusion additive manufacturing
Not Available
Liang, Zhi (ORCID:0000000310418606)↗
Tidal Turbine Test, Downeast Turbines, July 12, 2021
Downeast Turbines tested a tidal turbine prototype with novel rotor/channel system and lateral effluent discharge apparatus (LEDA), during five days of testing in the flume at Alden Lab. Three days of testing (July 12-14, 2021) focused on turbine power metrics of torque and rpm, which were low, and then two days of follow-up testing (July 27-28, 2021) focused on LEDA performance metrics of pressure differential and rates of volumetric flow, with encouraging results. Next step is to to characterize, and even optimize, configurations of the LEDA, using 3D-CFD as a helpful tool, to refine its shape and explore its limits of performance as a means of effluent discharge that augments performance of an instream turbine. An improved configuration of the LEDA will be re-combined with the rotor/channel system of the turbine prototype, and ultimately, the rotor will be re-sized (enlarged), to better match the LEDA's performance capabilities in drawing through a rate of volumetric flow. This submission is Downeast Turbines' Post Access Report for the test event. It includes the files described here (next below), and several reference links. "Downeast TEAMER-Post-Access-Report...docx" is a document file containing the report. "Appendices A, B, and C" are included in this file, and so are "Figures #1-7." "Appendix D - Test Data Workbooks.zip" is an archive file containing all post access data (raw data tables, calculating tables, and graphs), presented in fourteen Excel workbooks as described in the report. "Appendix E - Post Access Figures.zip" is an archive file containing "Figures #8-52," of the report.
16 TIDAL AND WAVE POWER↗
Time‐Dependent Density Functional Theory of Narrow Band Gap Semiconductors Using a Screened Range‐Separated Hybrid Functional
Abstract Predicting the band structure and optical absorption spectra of narrow band gap semiconductors is challenging for electronic structure methods. Here, it is shown shown that density functional theory can yield accurate band structures and time‐dependent density functional theory (TDDFT) can yield accurate optical absorption spectra for these systems. This is achieved by using a screened range‐separated hybrid (SRSH) functional with a single empirical parameter, fit to reproduce the experimental band gap. By comparing TDDFT results based on the SRSH approach with those obtained based on the Heyd–Scuseria–Ernzerhof functional it is shown that screened long‐range exact exchange improves the accuracy of the TDDFT spectra for these systems.
Wing, Dahvyd↗
Utilizing Oxygen Redox in Layered Cathode Materials from Multiscale Perspective
We report in high-capacity layered oxide cathode materials, utilization of lattice oxygen as a redox center is considered to be one of the most promising approaches to overcome the capacity limitation set by conventional transition metal redox centers. However, rapid material degradation is often associated with oxygen oxidation, leading to formidable challenges in utilizing oxygen redox. Further mechanistic understanding of the oxygen activities thus becomes critical to better control oxygen redox reactions. This review summarizes recent advances for investigating oxygen redox reactions in cathode materials from a multiscale perspective, i.e., from the atomistic level to the microstructure regime. First the mechanistic aspects of oxygen redox and the consequences of this reaction on various electrode degradation pathways during battery operation (e.g., oxygen loss, transition metal migration, irreversible phase transition), relating structural changes at the crystallographic scale to those at the macro scale, are discussed. Then recent developments based on atomic and microstructure modifications that are promising for improving the reversibility of oxygen redox reaction or mitigating the harmful processes arising from oxidation of the oxygen centers under high operating voltage are recounted. The analysis is concluded with a commentary on further research directions toward optimizing the oxygen activity for high-capacity charge storage.
25 ENERGY STORAGE↗
Energetic Electron Precipitation Driven by Electromagnetic Ion Cyclotron Waves from ELFIN’s Low Altitude Perspective
We review comprehensive observations of electromagnetic ion cyclotron (EMIC) wave-driven energetic electron precipitation using data collected by the energetic electron detector on the Electron Losses and Fields InvestigatioN (ELFIN) mission, two polar-orbiting low-altitude spinning CubeSats, measuring 50-5000 keV electrons with good pitch-angle and energy resolution. EMIC wave-driven precipitation exhibits a distinct signature in energy-spectrograms of the precipitating-to-trapped flux ratio: peaks at >0.5 MeV which are abrupt (bursty) (lasting ~17 s, or ΔL ~ 0.56) with significant substructure (occasionally down to sub-second timescale). We attribute the bursty nature of the precipitation to the spatial extent and structuredness of the wave field at the equator. Multiple ELFIN passes over the same MLT sector allow us to study the spatial and temporal evolution of the EMIC wave - electron interaction region. Case studies employing conjugate ground-based or equatorial observations of the EMIC waves reveal that the energy of moderate and strong precipitation at ELFIN approximately agrees with theoretical expectations for cyclotron resonant interactions in a cold plasma. Using multiple years of ELFIN data uniformly distributed in local time, we assemble a statistical database of ~50 events of strong EMIC wave-driven precipitation. Most reside at L ~ 5 – 7 at dusk, while a smaller subset exists at L ~ 8 – 12 at post-midnight. The energies of the peak-precipitation ratio and of the half-peak precipitation ratio (our proxy for the minimum resonance energy) exhibit an L-shell dependence in good agreement with theoretical estimates based on prior statistical observations of EMIC wave power spectra. The precipitation ratio’s spectral shape for the most intense events has an exponential falloff away from the peak (i.e., on either side of ~ 1.45 MeV). It too agrees well with quasi-linear diffusion theory based on prior statistics of wave spectra. It should be noted though that this diffusive treatment likely includes effects from nonlinear resonant interactions (especially at high energies) and nonresonant effects from sharp wave packet edges (at low energies). Sub-MeV electron precipitation observed concurrently with strong EMIC wave-driven >1 MeV precipitation has a spectral shape that is consistent with efficient pitch-angle scattering down to ~ 200-300 keV by much less intense higher frequency EMIC waves at dusk (where such waves are most frequent). At ~100 keV, whistler-mode chorus may be implicated in concurrent precipitation. These results confirm the critical role of EMIC waves in driving relativistic electron losses. Nonlinear effects may abound and require further investigation.
79 ASTRONOMY AND ASTROPHYSICS↗
Neutron Diffraction Residual Stress Study of a AA2219-T87 Self-Reacting Friction Stir Weld
2219-T87 is a precipitation hardenable aluminum-copper alloy which sees wide use in structural aerospace components. Thick panels of this alloy are joined via self-reacting friction welding (SRFSW); however, this thermomechanical process can result in significant loss of the alloy’s strengthening precipitates and large residual stresses which are detrimental to mechanical behavior and performance. High-resolution maps of the residual strain and stress states along the normal, transverse, and longitudinal directions of 2219-T87 SRFSW were obtained using neutron diffraction measurements. Residual stress had the highest tensile value in the heat-affected zone (HAZ) and the largest compressive stress in the base metal region of the normal and transverse directions. Line profile residual stress distributions displayed an “M”-shaped distribution in each direction with the longitudinal direction being the most pronounced while 2D residual stresses displayed an hourglass-shaped pattern. Further, average maximal longitudinal residual stress values ranged from 60.6 to 85.6% of yield. Microhardness testing across the transverse weld section produced a “V”-shaped curve with slight hardness recovery in the stir zone. Maximal and minimal microhardness values were observed in the base metal (154 HV) and thermomechanically affected zone (82 HV), respectively. Microstructural evolution was recorded using optical microscopy and showed decreasing grain size from the HAZ to the stir zone.
36 MATERIALS SCIENCE↗
Optimizing feed modulation for coupled methane and NO x conversion over Pd-Pt/Mn 0.5 Fe 2.5 O 4 /Al 2 O 3 monolith catalyst
Here the impacts of feed modulation (frequency, amplitude) and catalyst design (composition and architecture) parameters are reported for the conversion of methane and NO x over a dual-layer Pt+Pd/Al 2 O 3 + Mn 0.5 Fe 2.5 O 4 /Al 2 O 3 monolith. CH 4 and NO x conversion data show that the dual-layer catalyst outperforms single-layer samples having the same catalyst loadings, with and without spinel. Close proximity of the PGM and MFO functions in the mixed-layer catalyst lowers the CH 4 conversion at high temperature while separating the PGM and spinel layers with an intermediate Al 2 O 3 layer does not. Methane conversion enhancement is linked to its nonmonotonic dependence on O 2 . The performance gains are tied to a transient activity spike that occurs during the lean-to-rich feed transition when water is present in the feed. The transient spike is attributed to the removal of CO and H 2 products via reactions with stored O 2 in the spinel, eliminating inhibition of methane steam reforming.
03 NATURAL GAS↗
Coupled methane and NO x conversion on Pt + Pd/Al 2 O 3 monolith: Conversion enhancement through feed modulation and Mn 0.5 Fe 2.5 O 4 spinel addition
The performance of a dual-layer Pt-Pd/Al 2 O 3 washcoated monolith promoted by an Al 2 O 3 -supported Mn 0.5 Fe 2.5 O 4 spinel base layer was evaluated with the objective to develop a catalyst with a lower loading of Platinum group metal (PGM) for stoichiometric natural gas vehicle (NGV) emission control. Flow reactor results show that a combination of a lean/rich modulated feed and spinel addition gives enhanced methane and NO conversions compared to a steady-state feed having the same overall composition. Washcoated catalysts – PGM-only, spinel-only, PGM + spinel – were compared over a wide range of operating conditions. The results show a decrease in the methane conversion light-off temperature of up to 85 °C for an application-relevant feed (CH 4 + NO + H 2 + CO + O 2 + H 2 O + CO 2 ) while a moderate 40 °C decrease was observed for a simple feed (CH 4 + O 2 + H 2 O + CO 2 ). In the absence of spinel the modulation enhancement is negatively impacted at high methane conversion (> 80 %). The data show that the O 2 storage and release property of the spinel is needed to fully exploit the modulation enhancement. The mechanism responsible for the enhancement is linked to suppression of O 2 inhibition on the methane oxidation rate near the stoichiometric neutral point (λ = 1). Sufficiently fast cycling achieves a balance between a metallic and oxidic precious metal crystallites favorable for methane activation. The addition of spinel moves this balance closer to the λ = 1 feed, enabling a high oxidation efficiency with lower byproduct NH 3 selectivity. Enhancement in the NO conversion follows the methane conversion due to an easier NO reduction under the slightly rich of stoichiometric feed. Comparison of the PGM + spinel catalysts to PGM-only catalysts shows that the addition of spinel in combination with modulation can achieve the same activity with a lower PGM loading.
03 NATURAL GAS↗
Modulated CH4 oxidation over PGM/Spinel oxide dual layer catalysts: Experiments and modeling
Not Available
Chen, Pak Wing↗
Predictive multiscale modeling for Unidirectional Carbon Fiber Reinforced Polymers
This paper presents a predictive multiscale modeling scheme for Unidirectional (UD) Carbon Fiber Reinforced Polymers (CFRP). A bottom-up modeling procedure is discussed for predicting the performance of UD structures. UD material responses are computed from high fidelity Representative Volume Elements (RVEs). A data-driven Reduced Order Modeling approach compresses RVEs into Reduced Order Models so material responses can be computed in a concurrent fashion along with the structural level simulation. The approach presented in this paper is validated against experimental data and is believed to provide design guidance for future fiber reinforced polymers development.
36 MATERIALS SCIENCE↗
Stochastic nonlinear analysis of unidirectional fiber composites using image-based microstructural uncertainty quantification
Here, we present a data-driven nonlinear uncertainty quantification and propagation framework to study the microstructure-induced stochastic performance of unidirectional (UD) carbon fiber reinforced polymer (CFRP) composites. The proposed approach integrates (1) microscopic image characterization, (2) stochastic microstructure reconstruction, and (3) efficient multiscale finite element simulations enabled by self-consistent clustering (SCA) analysis. To model the complex microstructural variability, the proposed UQ methods take the non-Gaussian uncertainty sources into account through a distribution-free sampling approach leveraging nonparametric and asymptotic statistical tools. A hierarchical conditional sampling strategy enables the simultaneous sampling of multiple sources of uncertainties. Our approach provides insights into the impact of microstructural variabilities, which are shown to have an increasing impact on the nonlinear responses of UD CFRP parts under progressive compression loading and ultimately on the failure rate over time. We discover that before CFRP parts start to fail, a characteristic time period emerges with distinctive uncertainty distributions specific to the microstructure variability and the probability of failure. Identifying the failure time period is crucial to the reliability prediction, which is an essential component of CFRP design.
36 MATERIALS SCIENCE↗
Intensive and extensive margins of the peak load: Measuring adaptation with mixed frequency panel data
In this work we investigate the response of daily electricity peak load to daily maximum temperatures across states in Europe and India. We propose a method that decomposes short- from medium/long-run effects, retains the high frequency nature of the load-weather covariation and treats economic growth as a modulating factor. By simultaneously exploiting variation in unexpected daily weather anomalies and decade-long climatic changes in each location we decompose transitory - intensive margin - adjustments from permanent - extensive margin - adjustments. We find that the shocks over the long-run differ substantially from the short-run dynamics. Furthermore, we find evidence that per capita income modulates the adjustments over the short- and long-run. We project that in response to climate change around 2050 the peak load may increase by up to 20%-30% in Southern Europe and in several states in India, depending on the degree of warming and the evolution of socio-economic conditions. Even with a limited scope to two world regions, we identify that the structure of the economy and differences in future income growth matter in shaping the adaptation to climate change. Our decomposition allows to identify how future weather anomalies can further amplify the relative increase associated to the shift in the climate norm. Assuming that the interannual variability of maximum temperatures follows the distribution observed in the past, we find a doubling of the impacts of climate change during the summer in Europe. Uncertainty around the distribution of future weather anomalies may lead to further unexpected peak load amplifications. Our results have important policy implications for power systems’ generation capacity, transmission and storage, as we show that the challenges to accommodate the peak load in days with extreme temperatures may substantially increase already around mid-century.
29 ENERGY PLANNING, POLICY, AND ECONOMY↗
Inhibitory effects of some hydrocolloids on the formation of heterocyclic amines in roast beef
Not Available
Zhang, Nana↗
Efficient hybrid explicit-implicit learning for multiscale problems
Splitting method is a powerful method to handle application problems by splitting physics, scales, domain, and so on. Many splitting algorithms have been designed for efficient temporal discretization. Here, in this paper, our goal is to use temporal splitting concepts in designing machine learning algorithms and, at the same time, help splitting algorithms by incorporating data and speeding them up. We propose a machine learning assisted splitting scheme which improves the efficiency of the scheme meanwhile preserves the accuracy. We consider a recently introduced multiscale splitting algorithms, where the multiscale problem is solved on a coarse grid. To approximate the dynamics, only a few degrees of freedom are solved implicitly, while others explicitly. This splitting concept allows identifying degrees of freedom that need implicit treatment. In this paper, we use this splitting concept in machine learning and propose several strategies. First, the implicit part of the solution can be learned as it is more difficult to solve, while the explicit part can be computed. This provides a speed-up and data incorporation for splitting approaches. Secondly, one can design a hybrid neural network architecture because handling explicit parts requires much fewer communications among neurons and can be done efficiently. Thirdly, one can solve the coarse grid component via PDEs or other approximation methods and construct simpler neural networks for the explicit part of the solutions. We discuss these options and implement one of them by interpreting it as a machine translation task. This interpretation of the splitting scheme successfully enables us using the Transformer since it can perform model reduction for multiple time series and learn the connection between them. We also find that the splitting scheme is a great platform to predict the coarse solution with insufficient information of the target model: the target problem is partially given and we need to solve it through a known problem which approximates the target. Our machine learning model can incorporate and encode the given information from two different problems and then solve the target problems. We conduct four numerical examples and the results show that our method is stable and accurate.
97 MATHEMATICS AND COMPUTING↗
NH-PINN: Neural homogenization-based physics-informed neural network for multiscale problems
Physics-informed neural network (PINN) is a data-driven approach to solving equations. It is successful in many applications; however, the accuracy of the PINN is not satisfactory when it is used to solve multiscale equations. Homogenization approximates a multiscale equation by a homogenized equation without multiscale property; it includes solving cell problems and the homogenized equation. The cell problems are periodic, and we propose an oversampling strategy that significantly improves the PINN accuracy on periodic problems. The homogenized equation has a constant or slow dependency coefficient and can also be solved by PINN accurately. We hence proposed a 3-step method, neural homogenization based PINN (NH-PINN), to improve the PINN accuracy for solving multiscale problems with the help of homogenization.
97 MATHEMATICS AND COMPUTING↗