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Geological heterogeneity: Goal-oriented simplification of structure and characterization needs
Geological heterogeneity, i.e. the spatial variability of discrete hydrogeological units, is investigated in an aquifer analog of glacio-fluvial sediments to determine how such a geological structure can be simplified for characterization needs. Here, the aquifer analog consists of ten hydrofacies whereas the scarcity of measurements in typical field studies precludes such detailed spatial models of hydraulic properties. Of particular interest is the role of connectivity of the hydrofacies structure, along with its effect on the connectivity of mass transport, in site characterization for predicting early arrival times. Transport through three realizations of the aquifer analog is modeled with numerical particle tracking to ascertain the fast flow channel through which early arriving particles travel. Three simplification schemes of two-facies models are considered to represent the aquifer analogs, and the velocity within the fast flow channel is used to estimate the apparent hydraulic conductivity of the new facies. The facies models in which the discontinuous patches of high hydraulic conductivity are separated from the rest of the domain yield the closest match in early arrival times compared to the aquifer analog, but assuming a continuous high hydraulic conductivity channel connecting these patches yields underestimated early arrivals times within the range of variability between the realizations, which implies that the three simplification schemes could be advised but pose different implications for field measurement campaigns. Overall, the results suggest that the result of transport connectivity, i.e. early arrival times, within realistic geological heterogeneity can be conserved even when the underlying structural connectivity is modified.
Consumer safety-oriented scheduling of rotating power outages during heat waves
Extreme heat events have widespread effects on power systems, reducing available generation capacity, limiting transmission capabilities, and causing unusual demand patterns on the consumer side. As these combined effects expose bulk transmission systems to potential large-scale blackouts, utilities may be required to schedule and apply rotating outages, by temporarily and alternately disconnecting distribution substations to reduce overload. However, utilities lack mechanisms to inform these events, exacerbating the negative effects of heat waves on affected communities. This paper introduces a novel framework for scheduling rotating outages during heat waves while considering impacts on consumers’ safety. Instead of random sequential load shedding, we propose a methodology to rotate power outages considering a metric that quantifies the indoor overheating risk of groups of consumers during a power outage. The overheating risk is derived from a detailed building simulation using CityBES, where the buildings are modeled based on available data—use type, year built, floor area, number of stories, location—while presence of air conditioning and occupancy are calibrated from smart meter data. Based on the metric, an algorithm to schedule the rotating outages is applied to prioritize feeders for disconnection at each hour according to their overheating risk to meet a utility load reduction target. Applied to two substations and seven feeders in the Portland General Electric territory, the results show that this approach effectively leads to the lowest overheating risk during the resulting outage schedules, with an average 10.1% lower overheating compared to uninformed schedules.
The impact of defect density, grain size, and Cu orientation on thermal oxidation of graphene-coated Cu
Not Available
Development of a cosmic ray oriented trigger for the fluorescence telescope on EUSO-SPB2
The Extreme Universe Space Observatory on a Super Pressure Balloon 2 (EUSO-SPB2), in preparation, aims to make the first observations of Ultra-High Energy Cosmic Rays (UHECRs) from near space using optical techniques. EUSO-SPB2 will prototype instrumentation for future satellite-based missions, including the Probe of Extreme Multi-Messenger Astrophysics (POEMMA) and K-EUSO. The payload will consist of two telescopes. The first is a Cherenkov telescope (CT) being developed to quantify the background for future below-the-limb very high energy (E 10 PeV) astrophysical neutrino observations, and the second is a fluorescence telescope (FT) being developed for detection of UHECRs. The FT will consist of a Schmidt telescope, and a 6192 pixel ultraviolet camera with an integration time of 1.05 s. The first step in the data acquisition process for the FT is a hardware level trigger in order to decide which data to record. In order to maximize the number of UHECR induced extensive air showers (EASs) which can be detected, a novel trigger algorithm has been developed based on the intricacies and limitations of the detector. Finally, the expected performance of the trigger has been characterized by simulations and, pending hardware verification, shows that EUSO-SPB2 is well positioned to attempt the first near-space observation of UHECRs via optical techniques.
The effects of crystal orientation and common coal impurities on electronic conductivity in copper–carbon composites
Not Available
Hoobas: A highly object-oriented builder for molecular dynamics
Polydispersity and random sequences are ubiquitous features of polymers, and molecular dynamics simulations can help elucidate the impact of disorder in polymer systems. However, currently available packages for building polymer topologies do not enable the user to include randomness in a straightforward fashion. Here, we introduce Hoobas, a molecular builder package that easily handles polydispersity using a prototype-builder design pattern. This enables fast and easy building of systems comprised of thousands of distinct objects. It is written in the Python programming language, which ensures compatibility with a wide range of molecular dynamics packages and tools, as well as easy integration into most workflows.
Jacobian-based model diagnostics and application to equation oriented modeling of a carbon capture system
It can be difficult to identify the specific variables or equations responsible for convergence issues in large mathematical programming models. The Institute for the Design of Advanced Energy Systems Integrated Platform (IDAES-IP) contains a tool to identify poorly scaled constraints and variables by searching for rows and columns of the Jacobian matrix with small L2-norms. A singular value decomposition is then performed to identify degenerate sets of equations and remaining scaling issues. Here, this work presents a flowsheet developed for post-combustion carbon capture using a monoethanolamine (MEA) solvent system as a case study. This work takes the reader through the entire process of model diagnostics and reformulation, from a basic introduction to the mathematics behind these model diagnostics to the reformulations necessary to make the model numerically robust, including a significantly modified enhancement factor model.
Topology optimization of fiber-reinforced structures with discrete fiber orientations for additive manufacturing
Not provided.