Physically adversarial thermal hydraulics evaluation of deep learning models for pressurized water reactors
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Active learning scheme to train neural network potentials for molecular simulations.
In this work, the initial kinetics of water dissociation on two facets of δ-plutonium, δ-Pu(111) and δ-Pu(100), are explored through density functional theory in order to understand how water dissociation occurs on these facets. We explored the dissociation of water via the formation of hydroxyls, atomic hydrogen, and atomic oxygen species on each facet. We calculate low energetic barriers for water to split to adsorbed hydrogen and hydroxyl species at 0.19 eV for δ-Pu(111) and 0.07 eV for δ-Pu(100). The hydroxyl has a barrier of 0.64 and 0.37 eV to cleave the hydrogen–oxygen bond on δ-Pu(111) and δ-Pu(100), respectively. Due to the highly exergonic adsorption free energy of atomic oxygen of −2.10 eV, the metallic surfaces are found to be fully covered in oxygen, even with the inclusion of oxygen lateral interactions. When combined with the reaction thermodynamics, this free energy of adsorption forms a molecular oxygen desorption barrier greater than 9.51 eV (918 kJ/mol). These results, combined with simulated temperature programed desorption spectra, indicate that oxygen formed via water dissociation on δ-Pu (111) and (100) facets induces an irreversible poison that prevents further reaction of water directly on metallic plutonium surfaces, most likely due to the strong hybridization of the Pu and O valence states. Therefore, these results imply that another mechanism is responsible for the continuously experimentally measured water dissociation, which is most likely due to the Pu oxide.
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Our society is transitioning fast into the digital age, spurred by development of cheap and new sensing technology, breakthroughs in computing, and development of efficient algorithms for optimization. This transition is also visible in the field of wastewater treatment and is driving new model developments, especially by exploiting the large data sets available with many utilities. Not surprisingly, WRRmod2021 had featured a strong session on ‘data-driven models and digitalization’ focused on this hot topic. At the same time, engineering practice calls for more robust models for performance evaluation and optimization of both conventional facilities and innovative processes. As a result, the WRRmod2021 program also exhibited sessions on modelling of new process units (e.g., aerobic granular sludge), modelling of the nitrogen cycle, and integrated/plant-wide modelling.
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Climate change is intensifying the hydrologic cycle, leading to more frequent and severe rainfall-driven (pluvial) flooding in urban areas. In the mid-Atlantic US cities, aging and under-designed stormwater infrastructure is increasingly strained by these events, resulting in recurring damage to property and disruptions to transportation networks. In this study, we combine community engagement with hydrologic modeling to develop and evaluate potential urban flood adaptation strategies. Over a three-year period, local technical experts and community representatives met regularly to discuss flooding concerns, identify priorities, and co-develop adaptation strategies. These discussions informed the development of an urban flooding model (EPA Storm Water Management Model) for the Baltimore Harbor watershed, the focus location of this study. The flooding model integrates complex surface and subsurface stormwater infrastructure data, local expert knowledge, and community insights. We simulate stakeholder-prioritized adaptations, such as green and gray infrastructure strategies. Model results demonstrate that enhanced infrastructure maintenance is the most effective adaptation for reducing flood depths, but has varied effects across the watershed, and can increase flooding in some locations. Spatially concentrated greening provides limited benefit to the watershed as a whole, but moderate benefit in community priority areas. Together, these adaptations have the potential to reduce flood depths by as much as 58% in some locations, greatly reducing property damage and mobility impacts, primary concerns of stakeholders. Future work will implement robust optimization tools to search for adaptations which meet stakeholder objectives and perform highly under varied future climate conditions. This work contributes to the expanding literature on collaborative modeling and demonstrates that community-engaged approaches can enhance model credibility and generate more actionable insights for communities seeking to strengthen climate resilience.
Apollo spacecraft landing simulation to determine impact water pressures, accelerations, and landing dynamics
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The author has identified the following significant results. Processing and analysis of CCT's for numerous ground truth supported passes over Kansas reservoirs has demonstrated that sun angle and atmospheric conditions are strong influences on water reflectance levels as detected by ERTS-1 and can suppress the contributions of true water quality factors. Band ratios, on the other hand, exhibit very little dependence on sun angle and sky conditions and thus are more directly related to water quality. Band ratio levels can be used to reliably determine suspended load. Other water quality indicators appear to have little or no affect on reflectance levels.
The author has identified the following significant results. ERTS MSS ratios derived from CCT's are very effective for quantitative detection of suspended solid up to at least 900 ppm. The relatively high inorganic suspended solids, characteristic of midcontinent reservoirs, dominates the reflected energy present in the four MSS bands. Dissolved solids concentrations up to 500 ppm and algal nutrients up to 20 ppm are not detectable. The MSS5/MSS4 ratio may be weakly correlated with total chlorophyll above approximately 8 micrograms/liter.
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As an extension of a previous study (Saltzman and Tang, 1985) in which water vapor and cloud were confined to the lower half of the atmosphere in a growing baroclinic wave, the vertical flux of moisture across the middle (e.g., 500 mb) level to and from the upper level is now allowed for. The results show that there is a tendency for the upper-level maximum mixing ratio to shift to the east relative to the lower-level maximum mixing ratio. This is consistent with the eastward tilt with height of the common form cloud in the cold-conveyor cross-section and the poleward tilt of the cloud in the warm-conveyor cross-section as observed by Carlson (1980).
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Observations by Gwinn, Moran, & Reid of the proper motions of water masers in W49N show that they have elongated distribution expanding from a common center. Features with high space velocity only occur far from the center, while low-velocity features occur at all distances. We propose that these observations can be interpreted in terms of a shell of shocked molecular gas that is driven by the expanding cocoon of a high-velocity protostellar jet. We present three-dimensional numerical simulations in support of this interpretation and argue that this source provides a unique oppurtunity for a detailed study of jet-driven cocoons.