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An adaptive knowledge-based data-driven approach for turbulence modeling using ensemble learning technique under complex flow configuration: 3D PWR sub-channel with DNS data
This work describes a new approach to increase the accuracy of Reynolds-averaged Navier–Stokes (RANS) in modeling turbulence flow leveraging the machine learning technique. Traditionally, different turbulence models for Reynolds stress are developed for different flow patterns based on human knowledge. Each turbulence model has a certain application domain and prediction uncertainty. In recent years, with the rapid improvements of machine learning techniques, researchers start to develop an approach to compensate for the prediction discrepancy of traditional turbulence models with statistical models and data. However, the approach has deficiencies in several aspects. For example, the amount of human knowledge introduced to the statistical model couldn’t be controlled, which makes the statistical model learn from a very naïve stage and limits its application. In this work, a new approach is developed to address those deficiencies. Here, the new approach uses the “ensemble learning” technique to control the amount of human knowledge introduced into the statistical model. Therefore, the new approach could be adaptive to the multiple application domains. In conclusion, according to the results of case study, the new approach shows higher accuracy than both traditional turbulence models and the previous machine learning approach.
Core design and performance of the Westinghouse lead fast reactor with UO 2 and MOX configurations
For this work, Westinghouse partnered with Argonne National Laboratory to design, model and optimize UO 2 - and MOX-fueled core designs for a medium size (950 MWt) Lead Fast Reactor that was pursued by Westinghouse. Using Argonne’s suite of reactor analysis codes together with Westinghouse fuel cost economic models, thousands of candidate cores were considered to achieve the economics-optimized cores presented in this paper. This optimization process considered detailed reactor physics, fuel performance, transient performance, and fuel economics models. The reactor performance of the resulting optimized UO 2 - and MOX-fueled core designs are described and compared in this paper. Both cores show fuel performance and transient behavior that is considered acceptable for the optimization presented herein, while further testing campaigns on material performance in high-temperature liquid lead will be required to confirm acceptability at the operating conditions chosen. A multi-batch strategy was selected for the UO 2 core for best fuel utilization with minimum fuel inventory costs. A single-batch fuel management was instead selected for the MOX core to maximize cycle length and minimize the impact of the longer refueling outage resulting from the higher decay heat of the discharged MOX fuel relative to the discharged UO 2 fuel, requiring a longer cooling time before dry-lift of discharged fuel could take place.
Coexisting normal and intruder configurations in 32 Mg
Situated in the so-called “island of inversion,” the nucleus 32 Mg is considered as an archetypal example of the disappearance of magicity at N = 20. We report on high statistics in-beam spectroscopy of 32 Mg with a unique approach, in that two direct reaction probes with different sensitivities to the underlying nuclear structure are employed at the same time. More specifically, states in 32 Mg were populated by knockout reactions starting from 33 Mg and 34 Si, lying inside and outside the island of inversion, respectively. The momentum distributions of the reaction residues and the cross sections leading to the individual final states were confronted with eikonal-based reaction calculations, yielding a significantly updated level scheme for 32 Mg and spin-parity assignments. By fully exploiting observables obtained in this measurement, a variety of structures coexisting in 32 Mg was unraveled. Comparisons with theoretical predictions based on shell-model overlaps allowed for clear discrimination between different structural models, revealing that the complete theoretical description of this key nucleus is yet to be achieved.
Intruder configurations in 29 Ne at the transition into the island of inversion: Detailed structure study of 28 Ne
Detailed γ-ray spectroscopy of the exotic neon isotope 28 Ne has been performed for the first time using the one-neutron removal reaction from 29 Ne on a liquid hydrogen target at 240 MeV/nucleon. Based on an analysis of parallel momentum distributions, a level scheme with spin-parity assignments has been constructed for 28 Ne and the negative-parity states are identified for the first time. The measured partial cross sections and momentum distributions reveal a significant intruder p-wave strength providing evidence of the breakdown of the N=20 and N=28 shell gaps. Only a weak, possible f-wave strength was observed to bound final states. Large-scale shell-model calculations with different effective interactions do not reproduce the large p-wave and small f-wave strength observed experimentally, indicating an ongoing challenge for a complete theoretical description of the transition into the island of inversion along the Ne isotopic chain.
A preliminary NASA compliant conformal coating for optimized space radiation shielding configurations and its mass attenuation coefficients
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Trading off energy storage and payload – An analytical model for freight train configuration
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Atomic Level Interactions and Suprastructural Configuration of Plant Cell Wall Polymers in Dialkylimidazolium Ionic Liquids
Ionic liquids (ILs) have been widely investigated for the pretreatment and deconstruction of lignocellulosic feedstocks. However, the modes of interaction between IL-anions and cations, and plant cell wall polymers, namely, cellulose, hemicellulose, and lignin, as well as the resulting ultrastructural changes are still unclear. In this study, we investigated the atomic level and suprastructural interactions of microcrystalline cellulose, birch wood xylan, and organosolv lignin with 1,3-dialkylimidazolium ILs having varying sizes of carboxylate anions. Analysis by 13 C NMR spectroscopy indicated that cellulose and lignin exhibited stronger hydrogen bonding with acetate ions than with formate ions, as evidenced by greater chemical shift changes. Small-angle X-ray scattering analysis showed that while both cellulose and xylan adopted a single-stranded conformation in acetate-ILs, twice as many acetate ions were bound to one anhydroglucose unit than to an anhydroxylose unit. Further, we also determined that a minimum of seven representative carbohydrate units must interact with an anion for that IL to effectively dissolve cellulose or xylan. Lignin is associated as groups of four polymer molecules in formate-ILs and dispersed as single molecules in acetate-ILs, which indicates that it is highly soluble in the latter. In summary, our study demonstrated that 1,3-dialkylimidazolium acetates displayed stronger binding interactions with cellulose and lignin, as compared to formates, and thus have superior potential to fractionate these polymers from lignocellulosic feedstocks.
Rapid Prediction of a Liquid Structure from a Single Molecular Configuration Using Deep Learning
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Cluster-MLP: An Active Learning Genetic Algorithm Framework for Accelerated Discovery of Global Minimum Configurations of Pure and Alloyed Nanoclusters
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Active Learning Configuration Interaction for Excited-State Calculations of Polycyclic Aromatic Hydrocarbons
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