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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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At least 307 records · Page 17
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Platform for Integrated Land use And Transportation Experiments and Simulation (PILATES) v1.0

PILATES allows for flexibly and at-scale coupling of multiple models to allow for multi-scale and multi-resolution simulation of regional-scale transport networks. In particular, it couples the MATSim-derived transportation modeling framework for Behavior, Energy, Autonomy and Mobility (BEAM) with other models operating at different time scales. Rather than tightly coupling supply and demand models using shared agents and memory within the same software process, PILATES orchestrates different model runs in a containerized framework. This structure requires passing information from the demand models to BEAM in the format of a synthetic population and agent plans, and from BEAM to the demand models in terms or origin/destination tables (also known as "skims"). This allows it to take advantage of the behavioral sophistication of existing activity-based models as well as the reinforcement learning structure of MATSim replanning and adopted by BEAM, in a way that requires minimal changes to existing models. It also takes advantage of the computational performance of BEAM, which allows for simulations with millions of agents to complete in reasonable time as well as allowing for detailed mechanistic simulation of the operation of on-demand modes.

Needell, Zachary↗
DOE OSTI2024

RhizoMAP: a comprehensive, nondestructive, and sensitive platform for metabolic imaging of the rhizosphere

Elucidating the intricate structural organization and spatial gradients of biomolecular composition within the rhizosphere is critical to understanding important biogeochemical processes, which include the mechanisms of root-microbe interactions for maintaining sustainable plant ecosystem services. While various analytical methods have been developed to assess the spatial heterogeneity within the rhizosphere, a comprehensive view of the fine distribution of metabolites within the root-soil interface has remained a significant challenge. This is primarily due to the difficulty of maintaining the original spatial organization during sample preparation without compromising its molecular content.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Pooled PPIseq: Screening the SARS-CoV-2 and human interface with a scalable multiplexed protein-protein interaction assay platform

Protein-Protein Interactions (PPIs) are a key interface between virus and host, and these interactions are important to both viral reprogramming of the host and to host restriction of viral infection. In particular, viral-host PPI networks can be used to further our understanding of the molecular mechanisms of tissue specificity, host range, and virulence. At higher scales, viral-host PPI screening could also be used to screen for small-molecule antivirals that interfere with essential viral-host interactions, or to explore how the PPI networks between interacting viral and host genomes co-evolve. Current high-throughput PPI assays have screened entire viral-host PPI networks. However, these studies are time consuming, often require specialized equipment, and are difficult to further scale. Here, we develop methods that make larger-scale viral-host PPI screening more accessible. This approach combines the mDHFR split-tag reporter with the iSeq2 interaction-barcoding system to permit massively-multiplexed PPI quantification by simple pooled engineering of barcoded constructs, integration of these constructs into budding yeast, and fitness measurements by pooled cell competitions and barcode-sequencing. We applied this method to screen for PPIs between SARS-CoV-2 proteins and human proteins, screening in triplicate >180,000 ORF-ORF combinations represented by >1,000,000 barcoded lineages. Our results complement previous screens by identifying 74 putative PPIs, including interactions between ORF7A with the taste receptors TAS2R41 and TAS2R7, and between NSP4 with the transmembrane KDELR2 and KDELR3. We show that this PPI screening method is highly scalable, enabling larger studies aimed at generating a broad understanding of how viral effector proteins converge on cellular targets to effect replication.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

The MOSAiC Distributed Network: Observing the coupled Arctic system with multidisciplinary, coordinated platforms

Central Arctic properties and processes are important to the regional and global coupled climate system. The Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) Distributed Network (DN) of autonomous ice-tethered systems aimed to bridge gaps in our understanding of temporal and spatial scales, in particular with respect to the resolution of Earth system models. By characterizing variability around local measurements made at a Central Observatory, the DN covers both the coupled system interactions involving the ocean-ice-atmosphere interfaces as well as three-dimensional processes in the ocean, sea ice, and atmosphere. The more than 200 autonomous instruments (“buoys”) were of varying complexity and set up at different sites mostly within 50 km of the Central Observatory. During an exemplary midwinter month, the DN observations captured the spatial variability of atmospheric processes on sub-monthly time scales, but less so for monthly means. They show significant variability in snow depth and ice thickness, and provide a temporally and spatially resolved characterization of ice motion and deformation, showing coherency at the DN scale but less at smaller spatial scales. Ocean data show the background gradient across the DN as well as spatially dependent time variability due to local mixed layer sub-mesoscale and mesoscale processes, influenced by a variable ice cover. The second case (May–June 2020) illustrates the utility of the DN during the absence of manually obtained data by providing continuity of physical and biological observations during this key transitional period. We show examples of synergies between the extensive MOSAiC remote sensing observations and numerical modeling, such as estimating the skill of ice drift forecasts and evaluating coupled system modeling. The MOSAiC DN has been proven to enable analysis of local to mesoscale processes in the coupled atmosphere-ice-ocean system and has the potential to improve model parameterizations of important, unresolved processes in the future.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Portable Optical Particle Spectrometer aboard an Airborne Platform (POPS_AIR) Instrument Handbook

The U.S. Department of Energy Atmospheric Radiation Measurement (ARM) user facility portable optical particle spectrometer (POPS) is a lightweight particle spectrometer designed for aerosol particle size distribution measurement. Several POPS of different versions have been procured to serve as routine instruments for the ARM Aerial Facility (AAF) unmanned aerial systems (UAS) and tethered balloon system (TBS) deployment since 2018. POPS measures the aerosol particle size distribution approximately between 0.13 and 3 μm.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

WDM-SP-25A: Development of a stopping power platform using secondary nuclear reactions in Warm Dense Matter (Director’s Post-Doc Shot Request) [Slides]

Motivation: Recent theoretical modeling at LANL has demonstrated that the ignition criteria is a strong function of the temperature of the DT ice that surrounds the hot spot [Daughton et al. PoP 2023]. Alpha heating of the DT shell can raise the ignition threshold. Critical to modeling the alpha-particle deposition in the shell is understanding charged particle stopping in warm dense matter.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

Developing and Evaluating a Smart Curtailment Strategy Integrated with a Wind Turbine Manufacturer Platform

The Renewable Energy Wildlife Institute lead a team of scientists, wind developers, and turbine manufacturers in a study to develop and test a “smart curtailment” system intended to help reduce bat collisions with wind turbines. The Vestas Bat Protection System (VBPS) is a newly developed software module within the Supervisory Control and Data Acquisition (SCADA) system of Vestas turbines. The VBPS combines data from commercially available environmental sensors and the turbine’s built-in sensors with the Vestas SCADA system. VBPS is designed to receive environmental data from sensors on the turbine such as temperature, wind speed, wind direction, time of day, and time of year, relays that information to the SCADA system to determine whether to execute turbine curtailments at any given time. The goals of this study were to 1) develop a bat fatality risk model based on bat activity data and environmental data collected in year 1, and to 2) evaluate the VBPS, using the bat fatality risk model to implement curtailment, in comparison to “blanket curtailment” (turbines curtailed when wind speed is below 5.0 meters per second (m/s)) and “control” (normally operating, feathered below 3.0 m/s) turbines in year 2. The field study took place at a wind energy facility in Iowa during the fall bat migration seasons (July – October) in 2021 and 2022. For VBPS to succeed as a viable strategy for the minimization of bat fatalities, it should meet or exceed the performance of blanket curtailment. Specifically, the VBPS should meet the following performance targets to demonstrate whether it an effective, practical risk reduction measure: (1) Turbines operating VBPS should have equal or fewer bat fatalities compared to turbines operating with blanket curtailment, and significantly fewer bat fatalities compared to control turbines; and (2) Turbines operating VBPS should have greater power production compared to turbines operating with blanket curtailment. The study was completed in accordance with the Statement of Project Objectives and within the terms of the Budget Justification. This Final Report describes the progress, challenges, and outcomes of the study.

17 WIND ENERGY↗
DOE OSTI2024

Virtual Environment Platform for OT/IT Training Enhancement

TRADITIONAL TECHNIQUES OT/IT Concepts Operational Technology (OT) and Information Technology (IT) concepts can often be difficult to visualize Teaching Methods Traditional teaching methods lack the intuitive & immersive aspects of hands-on activities Caveat: Unless taught by Team B! Physical Limitations Digital Twins require existing systems/hardware to mirror UPDATED TECHNIQUES Virtual Environment By making use of a virtual environment, we can represent abstract concepts in a more approachable and digestible way Increased Engagement Students are more engaged with the activities and are more likely to retain the information they are given. New/Emerging Technologies As the system is currently growing and developing, the technologies in use, as well as those represented by the system, stay up-to-date.

Deroller, Nicholas F.↗
DOE OSTI2024

Cryogenic Platforms at Fermilab: Recent Results and Outlook

The Cosmic Quantum group at Fermilab operates three cryogenic facilities dedicated to the development and calibration of superconducting low-threshold detectors and qubits. One of which (LOUD) is located at the surface, while the other two (NEXUS and QUIET) are located 100 m underground enabling low-background device characterization and rare event searches. Recently, we have demonstrated world-leading resolution in the quasiparticle channel for kinetic inductance phonon-mediated detectors as well as the lowest rate of spatially- and temporally- correlated errors ( charge jumps ) in superconducting qubit chips. We have additionally made significant progress in expanding the suite of tools for simulating signal production and readout of these devices. In this talk, I will review these recent results, discuss some nascent projects focused on enhancing sensitivity of these detectors to sub-GeV dark matter, and highlight activities in these facilities over the next year.

Temples, Dylan J.↗
DOE OSTI2024

Manufacturing of Fabric Electrodes using a High-Throughput Screening Platform for Redox Flow Batteries

The objective of this project is to establish a new manufacturing methodology with machine learning- based high-throughput screening for the design and development of hierarchical structured, high-performance fabric electrodes for redox flow batteries (RFBs). The end goal of the project is to design and manufacture fabric electrodes for RFB applications that can provide 250 mA/cm2 current density operation for 100-cycles with 80% average energy efficiency. This was accomplished by first examining the structure-performance-property linkages of the electrodes provided by our partner, AvCarb. The electrodes’ microstructure was characterized by determining their pore size distribution, tortuosity, specific surface area, and porosity. The ohmic, charge transfer and mass transfer resistances were then calculated using electrochemical impedance spectroscopy. Carbon cloth electrodes showed the greatest resistance, which was dominated by charge transfer resistance, which we believe is related to the surface functionalization. Full cell cycling was used in order to determine the area specific resistance and energy efficiency of the cells. All of this experimental data and the results of the mathematical model (to increase the amount of inputs with parametric sweeping) were used to develop a machine learning-based model for the design of high-performance fabric electrodes. Using the results from the machine learning tool, optimized electrodes were fabricated by AvCarb. The ohmic, charge transfer and mass transfer resistances for these new electrodes were measured, and both performed better than any of the initial samples which had been provided by AvCarb.

25 ENERGY STORAGE↗
DOE OSTI2024

Mercury Detection Utilizing an Aquatic Animal as a Remote-Sensing Platform

Mercury species in open water, especially the accumulated methylmercury ion, pose a threat to fish and environment. Therefore, it is important to develop a small sensor package that can be integrated into a biotelemetry sensor carried by an aquatic animal, enhancing the ability to detect mercury contamination in large water areas. A quartz crystal microbalance (QCM) sensor using metal-organic framework (MOF) as sensing material was developed to detect mercury and methylmercury ions in real time based on acoustic wave perturbation. Thiol groups were introduced into the MOF UiO-66 through the organic linker to prepare the UiO-66-SH which was confirmed by infrared spectroscopy results. Batch adsorption experiments were conducted for the Hg 2+ , CH 3 Hg + , and Ca 2+ ions adsorption in the UiO-66-SH. The adsorption capacities of the mercury ions were more than an order of magnitude higher than those of the competing Ca 2+ ions at the same concentration. The frequency changes of the QCM sensor with the UiO-66-SH sensing film were an order of magnitude higher than those of the controlled baseline QCM sensor without a sensing film. Additionally, the frequency change can be tailored by adjusting the thickness of the MOF film and the adsorption properties of the sensing material. The sensor frequency change correlates well with ion adsorption capacities.

47 OTHER INSTRUMENTATION↗