Receptivity of a super-sonic acoustic mode through a normal shock
Presentation to go with previous IR Request ID: 1780436 for AIAA Aviation 2025 presentation by the same title
Harris, Shaun Ransom [Sandia National Laboratories↗
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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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Motion video from isochrome transit rate
companion presentation to recently approved SPIE conference paper of same title having Request ID 1781903
Sandusky, John [Sandia National Laboratories (SNL-↗
Intelligent Experiments Through Real-time AI: Fast Data Processing and Autonomous Detector Control for sPHENIX and Future EIC Detectors (Final Report)
The overall vision of this project was to integrate real-time artificial intelligence (AI) directly into the data acquisition and detector-control systems of nuclear physics experiments, including both fast online event selection and an autonomous detector-control feedback loop. The work carried out under the award focused on the fast online event-selection half of that vision: the efficient recording of low-momentum heavy-flavor (HF) hadron decays in proton-proton collisions at the sPHENIX experiment at the Relativistic Heavy Ion Collider (RHIC)—an observable that requires fast tracking and topological trigger selection not previously demonstrated at RHIC, and that is essential for QCD studies at future facilities such as the Electron-Ion Collider (EIC). The autonomous detector-control (GPU-based feedback) component named in the project title remained a design concept and was not implemented under this award. The Massachusetts Institute of Technology (MIT) group led the offline simulation and data processing needed to train the machine-learning (ML) models, the translation of trained models to Field-Programmable Gate Array (FPGA) firmware using the hls4ml framework, and the physics validation of heavy-flavor reconstruction. Over the award period, the team developed and hardware-tested the principal components of an AI-based heavy-flavor trigger on simulated and recorded sPHENIX tracker data: a software Bipartite Graph Attention Network (BiGAT) trigger model reaching > 95% signal efficiency at 99% background rejection; an FPGA-native hit clusterizer matching the offline clustering; smaller networks synthesized to FPGA within the required sub-10 µs latency; and an assembled decoder–clusterizer–inference firmware chain exercised on the FELIX readout board. A complete, fully integrated hardware demonstrator was not finished within the award period. This report documents the project goals, the MIT group’s contributions, the technical accomplishments, and the outlook toward applications at the future EIC ePIC detector.
73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
Computational Analysis of Hydraulic Efficiency of Michigan DOT Covers J and K
Drainage structures are used in urban street and highway systems to capture stormwater runoff. These structures typically consist of catch basins fitted with grates, inlets, or combination grate/inlet configurations that collect runoff and convey it through buried drainage systems. They are strategically placed within curb-and-gutter systems to enhance public safety by efficiently removing water from roadways and thereby reducing the risk of hydroplaning. The performance of drainage structures is commonly evaluated in terms of hydraulic efficiency, defined as the percentage of flow captured by the basin relative to the total flow reaching the structure. Understanding the hydraulic performance of these structures allows designers to properly space inlets, resulting in cost-effective designs that also help ensure the safety of the traveling public. MDOT uses a variety of drainage structures for runoff capture, as documented in Michigan Department of Transportation (MDOT) Drainage Manual. Many of these structures incorporate sinusoidal-type grates that are not addressed in HEC-22. Because physical modeling of these structures has been limited, further analysis is needed to verify their capture efficiency. Under current MDOT practice, the capture efficiency of these grates is estimated by assuming performance similar to that of a comparably sized reticuline grate described in HEC22. The first phase of this effort, titled Computational Analysis of Hydraulic Efficiency of Michigan DOT Cover C, focused on evaluating the hydraulic performance of MDOT’s Cover C grate. Cover C was selected as the initial test candidate because its sinusoidal pattern is representative of other MDOT grates, while it is typically used in high-volume, higher-speed applications. A similar version, Cover CX, is used on interstate highways but does not include transverse bars for bicycle safety. The current second phase of the study expands this work to evaluate MDOT’s Covers J and K. These grates were selected for additional analysis to further assess the hydraulic performance of MDOT drainage structures that are not directly represented by grate configurations in HEC-22. The results of this phase will build on the findings from the Cover C analysis and support improved understanding of the capture efficiency of MDOT’s standard drainage grates. This report is intended to serve as a companion document to the earlier study, Computational Analysis of Hydraulic Efficiency of Michigan DOT Cover C [3]. The present work applies the same overall CFD-based evaluation approach to MDOT Covers J and K and compares the resulting performance trends with those previously identified for Cover C. In particular, both studies assess on-grade interception efficiency, sag-location hydraulic capacity, and the effects of partial obstruction relative to HEC-22-based design estimates.
42 ENGINEERING↗
Idaho National Laboratory CY 2025 National Emission Standards for Hazardous Air Pollutants Analysis, Methodology, and Results for Radionuclides
This report details calculations of potential dose—at public receptor locations surrounding the Idaho National Laboratory (INL) Site boundary and INL in-town facilities—from radionuclides reported to be in use and potentially emitted from INL facilities during calendar year (CY) 2025. All calculations were performed in accordance with the requirements of Code of Federal Regulations (CFR), Title 40, “Protection of the Environment,” Part 61, “National Emission Standards for Hazardous Air Pollutants (NESHAPs),” Subpart H, “National Emission Standards for Emissions of Radionuclides Other than Radon from Department of Energy Facilities” (40 CFR 61, Subpart H). Modeling methodology, model-input parameters, and contribution to dose by facility, source, and radionuclide at the maximally exposed individual (MEI) location are also discussed. The information in this report supports the “National Emission Standards for Hazardous Air Pollutants—Calendar Year 2025 INL Report for Radionuclides” (DOE-ID 2026). During CY 2025, the estimated annual potential dose at the INL Site MEI location was 2.45E-02 mrem/yr, up from the previous year, but remaining far less than the regulatory standard of 10 mrem/yr (CFR 40 Part 61, Subpart H). Approximately 92% of the total dose to the INL Site MEI originated from Materials and Fuels Complex sources. Emissions from INL in-town facilities resulted in an estimated annual potential dose of 4.50E-03 mrem/yr to the MEI, down slightly from the CY 2024 estimated dose. Year-to-year variations in estimated annual dose can be attributed to adjustments in laboratory operations, changes to facility infrastructure, and variation in meteorological conditions.
42 - ENGINEERING↗
Low-cost, Highly Efficient and Fast Thermally Pressed Scalable Carbon-based Planar Perovskite Solar Cells
This Final Technical Report summarizes work completed under Award Number DEEE0009833, titled "Low-cost, Highly Efficient and Fast Thermally Pressed Scalable Carbon-based Planar Perovskite Solar Cells." The project addressed the central technical problem that carbon-electrode perovskite solar cells (C-PSCs) can reduce electrode costs and improve environmental durability, but they have historically lagged noble-metalcontact devices due to poor carbon/perovskite contact, high carbon-electrode resistance, imperfect hole extraction, and insufficient operational stability. The Statement of Project Objectives (SOPO), therefore, required systematic engineering of thermally pressed carbon-based planar perovskite solar cells by improving the carbon/perovskite interface quality, improving carbon-electrode conductivity, and further increasing device stability. The work advanced understanding of carbon-based perovskite photovoltaics by connecting device performance to three coupled mechanisms: interfacial recombination at the perovskite/hole-transport-layer/carbon stack; lateral and vertical transport losses in carbon contacts; and instability driven by moisture, heat, illumination, ion migration, and slow/variable manufacturing steps.
14 SOLAR ENERGY↗
Evaluation of Sandia NCS Benchmark Suite Updates
Description of impacts to Sandia NCS benchmark suite following implementation of ENDF/B-VIII.0 nuclear data library. Presentation accompaniment to paper and abstract submission with the same titles.
Morell-Pacheco, Andres Guillermo [Sandia National ↗
SupplementalFilesCPTAC_ProteogenomicOvarianPaper_2020_02_27
Interactive plots (in HTML/javascript) as supplemental files for the paper titled: Proteogenomic Characterization of Ovarian High-Grade Serous Cancer Implicates Mitotic Kinases, Replication Stress in Observed Chromosomal Instability. The plots represent the differential expression of proteins (File 1) and phosphopeptides (File 2) comparing tumor to normal tissue.
59 BASIC BIOLOGICAL SCIENCES↗
Warming Permafrost Model Intercomparision Project (WrPMIP): Pan-Arctic Perturbation Warming Simulations
Title: Warming Permafrost Model Intercomparision Project (WrPMIP): Pan-Arctic Perturbation Warming Simulations Description: WrPMIP Pan-Arctic simulations including historial baseline and two warming simulations. Models were perturbed similarly to known experimental warming trials that have been implemented across the Pan-Arctic over the last several decades. More information about the dataset can be found at the following links: https://warmingpermafrost.nau.edu/ The dataset is available at: https://esgf-node.ornl.gov/search/project=WrPMIP&mip_era=CMIP6&activity_id=WrPMIP
54 ENVIRONMENTAL SCIENCES↗
Low-Income Energy Affordability Data - LEAD Tool - 2018 Update
The Low-Income Energy Affordability Data (LEAD) Tool was created by the Better Building's Clean Energy for Low Income Communities Accelerator (CELICA) to help state and local partners understand housing and energy characteristics for the low- and moderate-income (LMI) communities they serve. The LEAD Tool provides estimated LMI household energy data based on income, energy expenditures, fuel type, housing type, and geography, which stakeholders can use to make data-driven decisions when planning for their energy goals. From the LEAD Tool website, users can also create and download customized heat-maps and charts for various geographies, housing, and energy characteristics. Datasets are available for 50 states plus Puerto Rico and Washington D.C., along with their cities, counties, and census tracts. The file below, "1. Description of Files," provides a list of all files included in this dataset. A description of the abbreviations and units used in the LEAD Tool data can be found in the file below titled "2. Data Dictionary 2018". The Low-Income Energy Affordability Data comes primarily from the 2018 U.S. Census American Community Survey 5-Year Public Use Microdata Samples and is calibrated to 2018 U.S. Energy Information Administration electric utility (Survey Form-861) and natural gas utility (Survey Form-176) data. The methodology for the LEAD Tool can viewed below (3. Methodology Document). For more information, and to access the interactive LEAD Tool platform, please visit: https://www.energy.gov/eere/slsc/low-income-energy-affordability-data-lead-tool For more information on the Better Building's Clean Energy for Low Income Communities Accelerator (CELICA), visit: https://betterbuildingsinitiative.energy.gov/accelerators/clean-energy-low-income-communities
affordability↗
Low-Income Energy Affordability Data - LEAD Tool - 2022 Update
The Low-Income Energy Affordability Data (LEAD) Tool was created by the Better Building's Clean Energy for Low Income Communities Accelerator (CELICA) to help state and local partners understand housing and energy characteristics for the low- and moderate-income (LMI) communities they serve. The LEAD Tool provides estimated LMI household energy data based on income, energy expenditures, fuel type, housing type, and geography, which stakeholders can use to make data-driven decisions when planning for their energy goals. From the LEAD Tool website, users can also create and download customized heat-maps and charts for various geographies, housing, energy characteristics, and population demographics and educational attainment. Datasets are available for 50 states plus Puerto Rico and Washington D.C., along with their cities, counties, and census tracts, as well as tribal areas. The file below, "01. Description of Files," provides a list of all files included in this dataset. A description of the abbreviations and units used in the LEAD Tool data can be found in the file below titled "02. Data Dictionary 2022". A list of geographic regions used in the LEAD Tool can be found in files 04-11. The Low-Income Energy Affordability Data comes primarily from the 2022 U.S. Census American Community Survey 5-Year Public Use Microdata Samples and is calibrated to 2022 U.S. Energy Information Administration electric utility (Survey Form-861) and natural gas utility (Survey Form-176) data. The methodology for the LEAD Tool can viewed below (3. Methodology Document). For more information, and to access the interactive LEAD Tool platform, please visit the "10. LEAD Tool Platform" resource link below. For more information on the Better Building's Clean Energy for Low Income Communities Accelerator (CELICA), please visit the "11. CELICA Website" resource below.
AMI↗
Comparing micro climate weather conditions from the weather research and forecasting (wrf) model with typical meteorological year (tmy) data for building energy simulations
Conference paper titled, Comparing microclimate weather conditions from the weather research and forecasting (WRF) model with typical meteorological year (TMY) data for building energy simulations accepted for Building Simulation 2025 Conference in Brisbane, Australia in Aug 2025.
Li, Hang↗
Aculeaxanthones A–E, new xanthones from the marine-derived fungus Aspergillus aculeatinus WHUF0198
Introduction Dimeric natural products are widespread in plants and microorganisms, which usually have complex structures and exhibit greater bioactivities than their corresponding monomers. In this study, we report five new dimeric tetrahydroxanthones, aculeaxanthones A−E ( 4−8 ), along with the homodimeric tetrahydroxanthone secalonic acid D ( 1 ), chrysoxanthones B and C ( 2 and 3 ), and 4−4’-secalonic acid D ( 9 ), from different fermentation batches of the title fungus. Methods A part of the culture was added to a total of 60 flasks containing 300 ml each of number II fungus liquid medium and culture 4 weeks in a static state at 28˚C. The liquid phase (18 L) and mycelia was separated from the fungal culture by filtering. A crude extract was obtained from the mycelia by ultrasound using acetone. To obtain a dry extract (18 g), the liquid phase combined with the crude extract were further extracted by EtOAc and concentrated in vacuo. The MIC of anaerobic bacteria was examined by a broth microdilution assay. To obtain MICs for aerobic bacteria, the agar dilution streak method recommended in Clinical and Laboratory Standards Institute document (CLSI) M07-A10 was used. Compounds 1−9 was tested against the Bel-7402, A-549 and HCT-116 cell lines according to MTT assay. Results and Discussion The structures of these compounds were elucidated on the base of 1D and 2D NMR and HR-ESIMS data, and the absolute configurations of the new xanthones 4−8 were determined by conformational analysis and time-dependent density functional theory-electronic circular dichroism (TDDFT-ECD) calculations. Compounds 1–9 were tested for cytotoxicity against the Bel-7402, A549, and HCT-116 cancer cell lines. Of the dimeric tetrahydroxanthone derivatives, only compound 6 provided cytotoxicity effect against Bel-7402 cell line (IC50, 1.96 µM). Additionally, antimicrobial activity was evaluated for all dimeric tetrahydroxanthones, including four Gram-positive bacteria including Enterococcus faecium ATCC 19434, Bacillus subtilis 168, Staphylococcus aureus ATCC 25923 and MRSA USA300; four Gram-negative bacteria, including Helicobacter pylori 129, G27, as well as 26,695, and multi drug-resistant strain H. pylori 159, and one Mycobacterium M. smegmatis ATCC 607. However, only compound 1 performed activities against H. pylori G27, H. pylori 26695, H. pylori 129, H. pylori 159, S. aureus USA300, and B. subtilis 168 with MIC values of 4.0, 4.0, 2.0, 2.0, 2.0 and 1.0 μg/mL, respectively.
Wu, Jun↗
Editorial: Future perspectives on separation technologies
Sustainable separation process development is crucial in promoting economic and environmental sustainability. Separation processes can be energy-intensive, and early-stage or emerging separation technologies can also be costly. For instance, separations in biomass-based fuels and chemicals production can account for up to 50% of the production cost, while industrial separations can consume up to 15% of the total energy used in the United States. Separations are essential to many industrial processes and play a crucial role in helping industry achieve several United Nations sustainable development goals (SDG), such as clean energy, responsible production, and climate change mitigation. Therefore, it is imperative to have a comprehensive discussion within the scientific community to identify innovative approaches for sustainable separation processes. This editorial highlights the key insights and research findings presented in this research topic titled "Future Perspectives on Separation Technologies."
42 ENGINEERING↗
Data for "Observation of Nonaxisymmetric Standard Magnetorotational Instability Induced by a Free-Shear Layer"
This repository provides the data plotted in the figures of the article titled "Observation of Nonaxisymmetric Standard Magnetorotational Instability Induced by a Free-Shear Layer", published in the Physical Review Letters, 2025.
magnetorotational instability; MHD; laboratory ast↗
Data for: "Wall conditioning effects of boron powder injection in KSTAR with a tungsten divertor"
This data set consists of the data used to generate the figures in the paper titled "Wall conditioning effects of boron powder injection in KSTAR with a tungsten divertor" in the journal Nuclear Fusion, 2025.
boron powder injection↗
Data for "Thermal Response of a Lithium Vapor Divertor to Cyclical Operation"
This repository provides the data which is plotted in the figures of the article titled "Thermal Response of a Lithium Vapor Divertor to Cyclical Operation", published in the Journal of Fusion Energy, 2025.
divertor↗
An overview of the Western United States Dynamically Downscaled Dataset (WUS-D3)
Abstract. Predicting future climate change over a region of complex terrain, such as the western United States (US), remains challenging due to the low resolution of global climate models (GCMs). Yet the climate extremes of recent years in this region, such as floods, wildfires, and drought, are likely to intensify further as climate warms, underscoring the need for high-quality and high-resolution predictions. Here, we present an ensemble of dynamically downscaled simulations over the western US from 1980–2100 at 9 km grid spacing, driven by 16 latest-generation GCMs. This dataset is titled the Western US Dynamically Downscaled Dataset (WUS-D3). We describe the challenges of producing WUS-D3, including GCM selection and technical issues, and we evaluate the simulations' realism by comparing historical results to temperature and precipitation observations. The future downscaled climate change signals are shaped in physically credible ways by the regional model's more realistic coastlines and topography. (1) The mean warming signals are heavily influenced by more realistic snowpack. (2) Mean precipitation changes are often consistent with wetting on the windward side of mountain complexes, as warmer, moister air masses are uplifted orographically during precipitation events. (3) There are large fractional precipitation increases on the lee side of mountain complexes, leading to potentially significant changes in water resources and ecology in these arid landscapes. (4) Increases in precipitation extremes are generally larger than in the GCMs, driven by locally intensified atmospheric updrafts tied to sharper, more realistic gradients in topography. (5) Changes in temperature extremes are different from what is expected by a shift in mean temperature and are shaped by local atmospheric dynamics and land surface feedbacks. Because of its high resolution, comprehensiveness, and representation of relevant physical processes, this dataset presents a unique opportunity to evaluate societally relevant future changes in western US climate.
Rahimi, Stefan (ORCID:0000000331884462)↗