Composable Ledgers for Distributed Synchronic Web Archiving
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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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We study the connections between three quantities that can be used as diagnostics for quantum chaos, i.e., the out-of-time-order correlator (OTOC), Loschmidt echo (LE), and complexity. We generalize the connection between OTOC and LE for infinite dimensions and extend it for higher-order OTOCs and multi-fold LEs. Novel applications of this intrinsic relation are proposed. We also investigated the relationship between a specific circuit complexity and LE by using the inverted oscillator model and made a conjecture about their relationship. These relationships signal a deeper connection between these three probes of quantum chaos.
NLR Engage™ is a free, open-access energy system planning tool that allows multiple users/stakeholders to develop and collaborate on capacity expansion models. The tool, developed at the National Laboratory of the Rockies (NLR), provides a collaborative and easy-to-use interface built on Calliope, a multi-scale energy systems modeling framework. Visit the NLR hosted webtool at https://engage.nlr.gov/en/login/?next=/en/
The software provides a framework to build a fast look up layer that reflects the holdings of an archive or database and operates between search/discovery system and disk storage. The software utilizes Bloom filter (BF) data structure. The discovery service powered by the Bloom filter layer comes with a very high level of accuracy yet space-saving, since BF compresses data to fit into RAM.
We present an open-source Python-based framework that can be used for objective evaluation of Atmospheric Rivers (ARs) in climate models. With a comprehensive pool of pre-defined metrics, this package is useful for systematic AR evaluation across a range of model simulations, such as the MIPs in CMIP5/6 models and large ensemble experiments.
Foldy is a cloud-based application that allows non-computational biologists to easily utilize advanced AI-based structural biology tools, including AlphaFold and DiffDock. With many deployment options, it can be employed by individuals, labs, universities, and companies in the cloud without requiring hardware resources, but it can also be configured to utilize locally available computers. Foldy enables scientists to predict the structure of proteins and complexes up to 6000 amino acids with AlphaFold, visualize Pfam annotations, and dock ligands with AutoDock Vina and DiffDock. In our manuscript, we detail Foldy’s interface design, deployment strategies, and optimization for various user scenarios. We demonstrate its application through case studies including rational enzyme design and analyzing proteins with domains of unknown function. Furthermore, we compare Foldy’s interface and management capabilities with other open and closed source tools in the field, illustrating its practicality in managing complex data and computation tasks. Our manuscript underlines the benefits of Foldy as a day-to-day tool for life science researchers, and shows how Foldy can make modern tools more accessible and efficient.
The dataset contains simulation-based charging infrastructure outputs that are visualized on the EVI-RoadTrip webtool. The outputs are aggregated to lower spatial resolution (e.g., state-level, corridor-level).
The dataset contains EVI-RoadTrip outputs, minute-by-minute load profiles in kW for each station in the simulation based on assumed utilization and network density. The load profiles are aggregated to lower spatial resolution (e.g., state-level, corridor-level) by summation of all station loads associated with the respective geography. This results in a load profile for each scenario that summarizes the corridor's, state's, or county's load profile in minute-level resolution.
Infrastructure is relied upon to support many basic functions of society. This summary provides information about Los Alamos National Laboratory's role to help counter natural and human-caused catastrophes on infrastructure.
Abstract not provided.
The first presentation discuses moving distribution of nuclear data to an online platform which allows ore frequent nuclear data updates, greater ease of acquiring nuclear data, and user flexibility in what nuclear data to download. The second presentation illustrates uncertainties without correlation, uncertainties without correlation with negative samples, uncertainties with correlation, uncertainties with a χ-like constraint, uncertainties with a Σ tot -like constraint, sampling using different distributions, and dealing with negative eigenvalues in a covariance matrix.
NREL will work with the EGI FORGE team to design and develop data visualizations and pathways from the existing Utah FORGE website (https://utahforge.com/) to the FORGE DMS, to showcase and disseminate data generated by the EGI FORGE project.
Abstract not provided.
The overall aim of the CyclusJS project has been to design novel approaches that support fuel cycle simulations and empower decision-makers and researchers with better tools to compare and contrast results from multiple simulations to understand the landscape of potential outcomes better. In particular, nuclear fuel cycle simulations focus on modeling the nuclear industry and ecosystem at a macroscopic level, and the analysis tools connect such simulations with decision support systems. As a demonstration of the novelty and effectiveness of the proposed approach, we study scenarios for transitioning from one technology, Light Water Reactors (LWR), to a newer Sodium-cooled Fast breeder Reactor (SFR) technology.
Abstract not provided.