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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 presentation covers motivation and Introduction, experimental Data Considered in the Analysis, R-Matrix Analysis and Model Details and Selection of Critical Benchmark Experiments.
To advance the development of accident-tolerant fuel cladding for light-water reactors, the Advanced Fuels Campaign actively addresses the R&D gap between the specialized technological progress in SiC-based composite materials, led by industrial partners, and the fundamental scientific understanding of material behavior under reactor operating conditions. The laboratory activities are systematically organized based on the Development Strategy document, which outlines critical barriers to the use of SiC composites in nuclear energy applications for the coming decade and beyond. To complement the strategy, this execution plan specifies a detailed year-by-year work package and establishes key milestones for assessing progress in technological advancement. This plan has been formulated in collaboration with principal investigators at national laboratories, stakeholders, and industry partners with the goal of closing technology gaps and readying SiC-based cladding technologies for full-scale commercial testing. The research conducted at the national laboratories is categorized into three primary subjects: (1) addressing challenges associated with the performance of SiC cladding under normal operating environments, (2) identifying the failure limits of SiC cladding under accident conditions, and (3) modeling fuel performance for SiC cladding systems. Comprehensive laboratory activities integrate the development of advanced modeling tools for SiC-based cladding systems with experimental validation via integrated testing of multiphysics phenomena. This document lays out the laboratory plan to support the development of SiC-based technologies, which have the potential for significant operational and safety benefits for the U.S. nuclear industry. This plan aligns with industry developer needs, relevant Nuclear Energy University Programs, and Nuclear Energy Advanced Modeling and Simulation Programs to ensure SiC cladding technologies are matured as efficiently as possible and will be maintained and updated to accommodate the dynamically evolving progress of development, capability needs, and resource availability.
One of the primary objectives of the Energy Storage effort is the development of durable and affordable advanced batteries (and ultracapacitors) for use in a full range of vehicle applications, from start/stop to full-power HEVs, EVs, and PHEVs. The battery technology development activity spans three areas: system development of full battery systems; benchmark testing of emerging technologies in order to remain abreast of the latest industry developments; and Small Business Innovative Research (SBIR) to fund early-stage R&D for small businesses/entrepreneurs.
This presentation described the state of the art in cavity string assembly for the LCLS-II, HE, and PIP-II projects, as well as cavity performance statistics. The presentation also described the knowledge gap, opportunities for improvement, and future R&D recommendations.
This presentation described the state of the art in cavity string assembly for the LCLS-II, HE, and PIP-II projects, as well as cavity performance statistics. The presentation also described the knowledge gap, opportunities for improvement, and future R&D recommendations.
Renewable natural gas (RNG) produced from animal manure can significantly reduce greenhouse gas (GHG) emissions from the transportation sector, but accurate life cycle assessment (LCA) of this fuel depends on precise modeling of emissions from business-as-usual (BAU) manure manage ment. This report documents updates to the Research & Development version of the Greenhouse Gases, Regulated Emissions, and Energy Use in Technologies (R&D GREET) model that attempt to improve that precision.
The Greenhouse Gases, Regulated Emissions and Energy Use in Technologies model (R&D GREET) evaluates the life cycle impacts of renewable fuels and materials, including renewable natural gas (RNG) produced from wastewater (WW) sludge. In the sludge-to-RNG pathway, the assumed anaerobic digestion (AD) technology impacts results, such as energy use, greenhouse gases (GHG), and air pollutant emissions. Prior versions assumed sludge was fed through a thermal hydrolysis stage preceding the mesophilic AD (Thermohydrolysis). Such a process is expected to yield biosolids with sufficiently reduced pathogens to qualify for U.S Environmental Protection Agency (EPA) Class A designation. Other technologies, such as mesophilic AD without any advanced pretreatments, typically produce lower quality Class B biosolids but requires a lower energy burden and infrastructure investment. Table 1 displays the available AD technologies and the assumed resulting EPA biosolids class type from each technology. Full descriptions of each technology and their performance differences can be found in previous work.
This report details the responsibilities, outcomes, and project details of a summer R&D internship at Los Alamos National Laboratory (LANL). LANL is a multidisciplinary laboratory that focuses on current cutting-edge research in many fields such as national security, engineering, materials science, computational modeling, and advanced manufacturing. The goal of the internship project was to work with lab engineers and resources to develop an energy absorbing structure for high-velocity impact applications. The successful development of this technology and methodology would not only positively impact future project funding but also contribute to the laboratory's commitment to solve national security challenges through simultaneous excellence. Such devices would also support efforts surrounding the research and development of energy absorbing structures and would provide new vital information backed by experimentation. Different computational and modeling methods were used to design these structures, in addition to qualitative background information provided by past literature. The resultant designs were successfully tested, and the test results were successfully quantified. From these results, new computational methods were developed through python programming and modeling to predict ideal materialistic properties for these structures given a sufficiently defined application.
The Deep Underground Neutrino Experiment (DUNE) is a next generation long-baseline neutrino experiment that will send an intense beam of neutrinos through two detector complexes: a near detector complex located at Fermilab (Chicago), and a far detector complex located $\sim$ 1.5 km underground at Sanford Underground Research Facility (SURF) in South Dakota. One of the DUNE Far Detector (FD) modules will employ the Vertical Drift (VD) Technology, which will vertically drift the ionized electrons from the cathode plane suspended at the mid-height of the active volume of the cryostat. The Photon Detection System (PDS) will be installed along the cathode and behind the field cage to increase the photon detection coverage. Due to the high voltage ($\sim$300 kV) present at the cathode, conventional copper cables cannot be used to power the photon detectors. Therefore, Power-over-Fiber (PoF) technology will be deployed to power the PDS based on optical power transmission over optical fibers. This poster presents the R$&$D campaign on different PoF components under harsh environments and its novel application in the DUNE PDS.
Particle accelerators are arguably the most effective tools for the particle physics research. The physics needs continuously push us to invent novel ways to increase energy and improve performance of accelerators, reduce their cost and make them more power efficient. Here we briefly overview three main families of modern and future accelerators for HEP – high intensity accelerators for neutrino research, particle factories for the electro-weak physics and Higgs studies, and post-LHC energy frontier colliders – and discuss corresponding ongoing or planned accelerator R&D topics and objectives.
Inner-shell photodetachment of Na – near the L-edge threshold was investigated using the R-matrix method. Significant structure was found in the cross section, and this structure is shown to be related to the complicated correlated electron dynamics endemic in negative ions. Comparison with experiment suggests that the absolute values of the measured cross section might be too small by a factor of two.
R Coronae Borealis (RCB) stars are rare hydrogen-deficient carbon-rich variable supergiants thought to be the result of dynamically unstable white dwarf mergers. In this article, we attempt to model RCB stars through all the relevant timescales by simulating a merger event in Octo-tiger, a 3D adaptive mesh refinement (AMR) hydrodynamics code, and mapping the post-merger object into MESA, a 1D stellar evolution code. We then post-process the nucleosynthesis on a much larger nuclear reaction network to study the enhancement of s-process elements. We present models that match observations or previous studies in most surface abundances, isotopic ratios, early evolution, and lifetimes. We also observe similar mixing behavior to previous modeling attempts that result in the partial He-burning products visible on the surface in observations. However, we do note that our subsolar models lack any enhancement in s-process elements, which we attribute to a lack of hydrogen in the envelope. We also find that the 16 O/ 18 O isotopic ratio is very sensitive to initial hydrogen abundance and increases outside of the acceptable range with a hydrogen mass fraction greater than 10 -4 .
The fortedata R package is an open data notebook from the Forest Resilience Threshold Experiment (FoRTE) – a modeling and manipulative field experiment that tests the effects of disturbance severity and disturbance type on carbon cycling dynamics in a temperate forest. Package data consist of measurements of carbon pools and fluxes and ancillary measurements to help analyze and interpret carbon cycling over time. Currently the package includes data and metadata from the first three FoRTE field seasons, serves as a central, updatable resource for the FoRTE project team, and is intended as a resource for external users over the course of the experiment and in perpetuity. Further, it supports all associated FoRTE publications, analyses, and modeling efforts. This increases efficiency, consistency, compatibility, and productivity while minimizing duplicated effort and error propagation that can arise as a function of a large, distributed and collaborative effort. More broadly, fortedata represents an innovative, collaborative way of approaching science that unites and expedites the delivery of complementary datasets to the broader scientific community, increasing transparency and reproducibility of taxpayer-funded science. The fortedata package is available via GitHub: https://github.com/FoRTExperiment/fortedata (last access: 19 February 2021), and detailed documentation on the access, used, and applications of fortedata are available at https://fortexperiment.github.io/fortedata/ (last access: 19 February 2021). The first public release, version 1.0.1 is also archived at https://doi.org/10.5281/zenodo.4399601 (Atkins et al., 2020b). All data products are also available outside of the package as .csv files: https://doi.org/10.6084/m9.figshare.13499148.v1 (Atkins et al., 2020c).
Abstract. Hydrological modeling is a crucial component in hydrology research, particularly for projecting future scenarios. However, achieving reproducibility and automation in distributed hydrological modeling research for modeling, simulation, and analysis is challenging. This paper introduces rSHUD v2.0, an innovative, open-source toolkit developed in the R environment to enhance the deployment and analysis of the Simulator for Hydrologic Unstructured Domains (SHUD). The SHUD is an integrated surface–subsurface hydrological model that employs a finite-volume method to simulate hydrological processes at various scales. The rSHUD toolkit includes pre- and post-processing tools, facilitating reproducibility and automation in hydrological modeling. The utility of rSHUD is demonstrated through case studies of the Shale Hills Critical Zone Observatory in the USA and the Waerma watershed in China. The rSHUD toolkit's ability to quickly and automatically deploy models while ensuring reproducibility has facilitated the implementation of the Global Hydrological Data Cloud (https://ghdc.ac.cn, last access: 1 September 2023), a platform for automatic data processing and model deployment. This work represents a significant advancement in hydrological modeling, with implications for future scenario projections and spatial analysis.
This zipped archive of a GitHub repository includes the experimental data (csv files) collected for the reduction of NO to N2O by purified Paracoccus denitrificans cytochrome c nitric oxide reductase (cNOR) and the R code (qmd files) used to analyze these data. A link to the corresponding GitHub repository is also provided.
Statistical analysis - R chart control limit based on small number of subgroups
Vaporization analysis of liquid uranium, metal, and carbon systems at 9000 and 10000 deg R
Program management study on effects of PERT on industries with large R&D organizations