Trustworthy and Scalable Data-Driven Closure Models
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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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This report details the development and implementation of ATEAM4Py, a Python-based simulation model that projects demand for battery electric vehicle (BEV) charging based on adoption trends and consumer behavior. With Exelon’s support, Argonne National Laboratory converted the original Java-based Agent-based Transportation Energy Analysis Model (ATEAM) into Python, resulting in a faster and more efficient tool for forecasting the timing, location, and scale of charging demand growth. ATEAM4Py tackles key challenges in simulation efficiency and runtime, supporting the strategic development of cost-effective grid capacity expansion strategies and ensuring reliable service for stakeholders.
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This project focused on investigating two acoustic-based processing methods: a nozzle-based printhead and a chamber that map to two different battery electrode architectures: (1) a line-pattern electrode and (2) a grid-pattern electrode. These two parallel manufacturing and electrode geometry explorations were proposed for the project to understand the process space of acoustic-based manufacturing methods to fabricate patterned battery electrodes. This two-path exploration also allowed us to de-risk the overall project and not rely on a single process for creating patterned electrodes. This project consisted of six high-level tasks aimed at transitioning the concept of acoustic focusing for battery electrodes from a technology readiness level (TRL) of 1 to 3 by project conclusion. Overall, we believe we have developed a practical and high-impact processing method that is chemistry agnostic and suitable for large-area fabrication of both 3D LIBs and other functional material systems where structuring on the scale of tens of microns has the potential to break conventional bulk material trade-offs in performance. In the case of batteries for electric vehicles, structuring 3D LIBs with our acoustic process breaks traditional energy and power trade-offs observed with conventional flat battery packs.
This project extends the state of the art in formal verification modeling with modules and automatically checkable data-sharing patterns such that component modules can retain their assurance case when composed within a larger system. For users, smaller models make reasoning easier and help to ensure they accurately reflect text specifications. For automated methods, smaller models give exponential benefits for verification algorithm execution time.
This project developed a publicly available, high-fidelity dataset about the interactions among humans, homes, and heat pumps supporting grid interactive efficient buildings to balance demand on the grid with comfort for occupants. Laboratory measurements and simulations of the hardware capture the second-scale electric power dynamics of heat pumps providing grid services like load shifting and load shedding. Field measurements, behavior tracking, and qualitative surveys of people in their homes over multiple years—including experimentally adjusting the heating and cooling system to provide grid services—to capture the reciprocal effect of human behavior on grid services, and grid services on human comfort. Taken together, these data capture the complete Hardware and Human in the loop system for residential heat pumps, reducing large uncertainties in simulation for design, and models for control of heat pumps, and grid-interactive buildings.
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As part of the Scientific Discovery through Advanced Computing (SciDAC) program, the Quantum Chromodynamics Nuclear Tomography (QuantOM) project aims to analyze data from Deep Inelastic Scattering (DIS) experiments conducted at Thomas Jefferson National Accelerator Facility and the upcoming Electron Ion Collider. The DIS data analysis is performed on an event level by taking into leveraging nuclear theory models and accounting for experimental conditions. In order to efficiently run multiple analyses under varying conditions, a composable workflow was designed where each section (theory, experiment, objective minimization, etc.) has its own dedicated module. This presentation gives an overview over of the current status of this workflow, highlights present and future challenges, and highlights possible extensions to other projects with similar requirements.
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High Performance Computing (HPC) centers, such as the Oak Ridge Leadership Computing Facility (OLCF), provide advanced infrastructure that enables scientific research at extreme scale. These centers operate with unique hardware configurations, specialized software environments, and elevated security re quirements that differ substantially from what most users encounter on their local systems. As a result, users often develop customized digital artifacts that are tightly coupled to the specific configuration of a given HPC center. Although necessary, this practice can lead to significant duplication of effort as multiple users independently create similar solutions to common problems.
The goals of the project included the identification and evaluation of a voltage source converter multiterminal high-voltage direct current (VSC-MTdc) system architecture suitable for a high amount of power transfer through long transmission lines.
The goals of the project included the development of characterization methods and tools to evaluate reliability, transient stability, and economics of large-scale dc architectures in ac grids.
Imaging opportunities (viewable conjunctions) of Resident Space Objects (RSOs) by satellites are not continuously discovered. We propose to continuously produce and report viewable conjunctions among objects in orbit. Viewable conjunctions are events in space and time when a satellite may favorably view a Resident Space Object (RSO). Favorability is defined by a set of constraints, e.g., solar illumination, distance between observer and target, orbital location for viewable event. Computing viewable conjunctions requires calculation of orbital propagation while considering constraints based on the state vectors of position, velocity, with covariance for both satellite and RSO. We propose two parallel lanes of effort: acceleration and research. The objective of acceleration is to avoid missed opportunities and reduce latency for satellite maneuver requests through continuous prediction and reporting of viewable conjunctions. The effort will begin by deploying currently available software on dedicated systems and continue with optimizing the code for high performance computing hardware. The research lane aims to expand RSO inspection and modeling capabilities. Among our current research ideas are spectral characterization of RSO materials and planning multiple observations to recover RSO 3D form. Computing resources at Oak Ridge National Laboratory (ORNL) are available for the acceleration work. Laika, Maxar conjunction prediction dashboard software, and Bluesim, Maxar orbital propagation software, are expected to be the first software in the acceleration lane. Laike and Bluesim are to be provided by the sponsor, and output will be made accessible through its dashboard. Deliverables will follow a gated schedule to the sponsor. ORNL will provide progressively more robust viewable conjunction assessments from both modelled and actual ephemerides.
This work describes the improved workflow for evaluating open-source large language models (LLMs) for trustworthiness. The workflow facilitates the acquisition of LLMs, the generation of LLM responses, and the evaluation of the responses for their trustworthiness. As a use case, the workflow is employed to evaluate dense, quantized, and pruned Meta Llama3.1 LLMs for their truthfulness. The outcome of the project could set the stage for understanding and developing trustworthy models in the future projects.
Presentation for U.S. Department of Energy/NETL Closeout Meeting, virtual, December 4, 2020.
Final Technical Report for Award SC0020286.
In partnership with Bergey Windpower, this project explored the use of recyclable and recycled materials in small- to medium-wind turbine blades (WTBs). A recyclable epoxy resin and infusible thermoplastic resin were investigated using identical fiber reinforcements and manufacturing practices used as Bergey, and the substitution of continuous virgin glass fiber (GF) layers with recycled nonwoven GF (rGF, NW) mats was trialed. The alternative resins both showed very promising performance in terms of static tensile and flexural behavior as well as thermal properties and fatigue behavior in comparison with that of the incumbent materials used at Bergey. The NW rGF materials, however, were found to be a poor substitute for the continuous GF materials for two primary reasons. Firstly, the NW mats took up significantly more resin than their continuous counterparts, which would increase both the weight and the cost of the WTBs. Additionally, an unexpected reaction occurred between the rGF and epoxy materials that resulted in a highly porous, foamed structure. The foaming phenomenon was not observed with the rGF NW and infusible thermoplastic material, but the resin uptake was still prohibitively high. Based on the results of this study, recyclable infusible resins could be viable candidate materials for Bergey in the future. The foaming reaction with the rGF NW mats could prove highly useful in other applications requiring structural foams and has been used to produce demonstrative sandwich panels.