On the benefits of using shorter rise-time current pulses to drive MagLIF implosions
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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 provides an analysis of the financial, operational, and strategic advantages of incorporating Security-by-Design (SeBD) early in the lifecycle of nuclear power plant projects. By framing security as a foundational design element rather than a late-stage add-on, owners, vendors, and operators can reduce budget overruns, strengthen regulatory compliance, and increase revenue opportunities. The report details key lifecycle phases, highlighting the strategic imperative for organizations (including project developers, investors, vendors, and regulators) to adopt SeBD. Drawing on industry estimates, real-world case studies, and comparative cost analyses, the findings underscore that even a modest upfront investment in SeBD can yield substantial long-term returns by preventing costly retrofit activities, minimizing regulatory delays, and positioning nuclear vendors for the ability to adapt in the evolving security market. By avoiding excessive retrofit expenses and positioning security as a built-in feature rather than an afterthought, nuclear projects can protect their financial performance, enhance public trust, and secure a competitive edge in an increasingly complex global energy market. The authors advocate for SeBD’s strategic implementation, supported by established quality management methodologies, thereby promoting continuous improvement and defect avoidance. Ultimately, early SeBD integration represents a strategic investment, yielding significant returns by preventing costly retrofits and positioning nuclear projects for enhanced competitiveness and public trust.
Conference presentation at International Fuel and Ethanol Workshop and Expo (FEW), Omaha, Nebraska, June 13, 2023. An overview of the Plains CO 2 Reduction (PCOR) Partnership Initiative and active commercial carbon capture, utilization, and storage (CCUS) activity in the region. Includes solutions for CCUS deployment challenges.
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We pursued a data science driven machine learning (ML) approach that blended molecular scale attributes informed from molecular dynamics (MD) simulation and materials properties to the selectivity and energy efficiency in targeted ionic separations using electric fields. The model mixtures investigated for ionic separations are pH sensitive and include organic acids, silica and boron, transition metals, such as copper and chromium. There were two major research thrusts of this project. Firstly, we investigated surrogate models and deep learning that relate material chemistries and structures to selective transport of ionic species under applied electric fields. Secondly we investigated how the bipolar junction interfacial design and water dissociation catalyst in bipolar membranes affect reverse bias polarization behavior and pH modulation in deionization platforms as a function of the platform operating parameters (e.g., cell voltage, residence time, and salt feed concentration). As a result of this work, we also were able to start a new direction, namely ML models for molecular design of surfactants.
Phase modifiers are low molecular weight molecules added to solvent extraction separations to improve the physical performance of the separation system, for example by increasing the concentration of metal ions that can be separated or improving the compatibility of the two solvents.
The purpose of the project was to observe and quantify temporal variation in snow albedo and snow characteristics across the Arctic coastal landscape as winter transitioned into spring and snowmelt occurred, both on tundra and sea ice. This transition is bounded by fully snow-covered landscapes with broadband albedos of approximately 0.8 and snow-free landscapes with albedos of 0.15 (tundra or ponded sea ice). For these landscapes, we monitored the spring surface characteristics and radiative properties nearly daily at three locations on or near the Department of Energy ARM North Slope of Alaska (NSA) User Facility in Utqiagvik, Alaska: the central NSA Facility (hereafter called ARM), one near NSA-E12 (BEO), and one on the sea ice of Elson Lagoon (ICE) during three melt seasons (2019, 2022, and 2024). The field campaign component of this award was named SALVO ( S now AL bedo E VO lution). Typical field seasons began in mid-April and lasted until mid-June. Main measurements included snow depth (at 1-m intervals), broadband albedo (at 5-m intervals), spectral albedo (at 5- m intervals), and multiple digital images. Orthomosaics were converted into binary images to determine the snow-covered fraction over time across various landscapes. Additional measurements included basic weather data and snow-ground (or ice) interface temperatures. Sky conditions were observed and photographed to help assess albedo values.
The presentation is aimed to teach participants about achieving affordable energy through utility program design. Learning objectives include: identify key utility program characteristics that support affordability and consumer choice; apply best practices in outreach, eligibility, and evaluation to improve program design; and evaluate strategies for aligning program design with customer needs and regulatory goals.
The primary objective of the proposed research is to use observational data to examine how PBL aerosol and low cloud microphysical properties are coupled for differing turbulent dynamics in the PBL.
The presentation summarizes part of our work on the PrOMMiS project. It describes a systematic benchmarking activity of data-driven optimization algorithms.
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The goal of the project is to develop a platform for the OMEGA-60 laser facility to study MHD effects in cylindrical implosions at regimes of large magnetic pressure and magnetization.
Abstract not provided.
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