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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 505 records · Page 28
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

SGD-OD: investigating the potential oxygen demand of submarine groundwater discharge in coastal systems

Submarine groundwater discharge (SGD) supplies nutrients, carbon, metals, and radionuclide tracers to estuarine and coastal waters. One aspect of SGD that is poorly recognized is its direct effect on dissolved oxygen (DO) demand in receiving waters, denoted here as SGD-OD. Sulfate-mediated oxidation of organic matter in salty coastal aquifers produces numerous reduced byproducts including sulfide, ammonia, dissolved organic carbon and nitrogen, methane, and reduced metals. When these byproducts are introduced to estuarine and coastal systems by SGD and are oxidized, they may substantially reduce the DO concentration in receiving waters and impact organisms living there. We consider six estuarine and coastal sites where SGD derived fluxes of reduced byproducts are well documented. Using data from these sites we present a semiquantitative model to estimate the effect of these byproducts on DO in the receiving waters. Without continued aeration with atmospheric oxygen, the study sites would have experienced periodic hypoxic conditions due to SGD-OD. The presence of H2S supplied by SGD could also impact organisms. This process is likely prevalent in other systems worldwide.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Decentralised demand response market model based on reinforcement learning

A new decentralised demand response (DR) model relying on bi‐directional communications is developed in this study. In this model, each user is considered as an agent that submits its bids according to the consumption urgency and a set of parameters defined by a reinforcement learning algorithm called Q‐learning. The bids are sent to a local DR market, which is responsible for communicating all bids to the wholesale market and the system operator (SO), reporting to the customers after determining the local DR market clearing price. From local markets’ viewpoint, the goal is to maximise social welfare. Four DR levels are considered to evaluate the effect of different DR portions in the cost of the electricity purchase. The outcomes are compared with the ones achieved from a centralised approach (aggregation‐based model) as well as an uncontrolled method. Numerical studies prove that the proposed decentralised model remarkably drops the electricity cost compare to the uncontrolled method, being nearly as optimal as a centralised approach.

Shafie‐Khah, Miadreza↗
DOE OSTI2025

On-Demand Column Joining for High Energy Physics

As the Large Hadron Collider (LHC) transitions into the High-Luminosity LHC (HL-LHC) era, the volume of data to be processed is expected to increase significantly. The CMS Experiment currently utilizes various data formats, including AOD, MiniAOD, and NanoAOD, each with different levels of detail and storage requirements. This paper addresses the challenges of data duplication and storage inefficiencies in high-energy physics (HEP) analyses by proposing an on-demand column-joining solution. This approach aims to reduce data duplication by enabling the dynamic combination of NanoAOD data with auxiliary information from larger data tiers, such as MiniAOD. The proposed solution leverages Trino, a high-performance distributed SQL query engine, to perform efficient and scalable data joins. Benchmarks using CMS OpenData demonstrate the feasibility of this approach, showing that it can handle large datasets with low latency. Integration with the scikit-hep ecosystem and the coffea analysis framework is also discussed, highlighting the potential for seamless end-to-end data processing and analysis. Ongoing and future work focuses on expanding benchmarks, integrating ServiceX for data transformation, and exploring the use of native object storage solutions.

Manganelli, Nicholas [Northeastern U.]↗
DOE OSTI2025

ATLAS HL-LHC Demonstrators with Data Carousel: Dataon-Demand and Tape Smart Writing

The High Luminosity upgrade to the LHC (HL-LHC) is expected to deliver scientific data at the multi-exabyte scale. To tackle this unprecedented data storage challenge, the ATLAS experiment initiated the Data Carousel project in 2018. Data Carousel is a tape-driven workflow in which bulk production campaigns with input data resident on tape are executed by staging and promptly processing a sliding window to disk buffer such that only a small fraction of inputs are pinned on disk at any one time. Put in ATLAS production before Run3, Data Carousel continues to be our focus for seeking new opportunities in disk space savings, and enhancing tape usage throughout the ATLAS Distributed Computing (ADC) environment. These efforts are highlighted by two recent ATLAS HL-LHC demonstrator projects: data-on-demand and tape smart writing. In this paper, we will discuss the recent studies and outcomes from these projects. The research was conducted together with site experts at CERN and Tier-1 centers.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2020

Novel PBX formulations containing thermally-expandable microspheres for on-demand control of explosive behavior

In this work, we present the formulation and analysis of inert Plastic-Bonded eXplosive (PBX)-surrogates loaded with thermally expandable microspheres (TEMs). TEMs consist of a thermoplastic acrylonitrile shell (10-50 µm diameter) encapsulating an inert low boiling hydrocarbon. Upon heating, the TEMs expand as the shell softens while the hydrocarbon gasifies, increasing the internal pressure and expanding the particle by as much as 120 vol%. We hypothesize that TEM expansion within a PBX will introduce tunable changes in local density and porosity, and ultimately the shock sensitivity. This paper focuses on microstructural analysis of surrogate PBX-TEM formulations, both before and after thermally- induced TEM expansion. The formulations were analyzed by scanning electron microscopy (SEM), ultra-small angle neutron scattering (USANS), and X-ray Computed Tomography (x-ray CT) under various thermal conditions. Evidence suggests that TEM expansion within a PBX is a viable method to impart microstructural changes that are predicted to have a measurable, on-demand effect on the initiation sensitivity. Future work includes development of PBX-TEM formulations with HMX and shock initiation experiments.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2020

A combined numerical and experimental study to elucidate primary breakup dynamics in liquid metal droplet-on-demand printing

Droplet-on-demand liquid metal jetting is emerging as a powerful technology for the additive manufacturing of metallic parts. The success of this method hinges on overcoming several technological challenges. Additionally, the principal one among these challenges is the controlled repeatable ejection of single uniform droplets. Due to the high density and surface tension of liquid metals, the droplet ejection process occurs near the minimal extremes of the printability phase diagram, defined by acceptable ranges for the Weber (We) and Ohnesorge (Oh) numbers. In this work, we experimentally demonstrate the satellite-free ejection of pneumatically actuated molten tin droplets in this extreme corner of printability and use a combination of high-speed video analysis and volume-of-fluid modeling to elucidate the droplet dynamics. While the simulations at low Oh and We can correctly describe several aspects of the breakup process, such as an increasing tail and pinch-point near the nozzle, no single parameter set can completely capture the droplet shape at breakup. Instead, the experimental droplet dynamics appear to include features from both high and low Oh breakup. This disagreement is ascribed to the incomplete description of the droplet ejection process including wetting and exit effects near the nozzle opening and surface effects such as transient cooling and oxide formation.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Millimeter-wave electromagnetic monitoring for liquid metal droplet-on-demand printing

As new printing approaches emerge, in situ diagnostics to monitor the print quality in real-time become essential for long-term monitoring and feedback control. In this article, we present a millimeter-wave electromagnetic monitoring approach for liquid metal droplet-on-demand printing to support the high-speed and real-time evaluation of droplet ejection. An open-ended rectangular waveguide is placed perpendicular to a jetted droplet stream and operated at a continuous-wave frequency of 40 GHz. Liquid metal droplets with diameters as low as 1.2 mm are characterized, and droplet jetting events on the order of 500 μm are detected at ejection rates up to 80 Hz. The measured results demonstrate that trends at the macro-level (large-scale print variation and anomalies at the nozzle tip) as well as micro-level (droplet size, position, and dynamics) can be detected using this technique.

42 ENGINEERING↗
DOE OSTI2024

On-demand fabrication of piezoelectric sensors for in-space structural health monitoring

Abstract Inflatable structures, promising for future deep space exploration missions, are vulnerable to damage from micrometeoroid and orbital debris impacts. Polyvinylidene fluoride-trifluoroethylene (PVDF-trFE) is a flexible, biocompatible, and chemical-resistant material capable of detecting impact forces due to its piezoelectric properties. This study used a state-of-the-art material extrusion system that has been validated for in-space manufacturing, to facilitate fast-prototyping of consistent and uniform PVDF-trFE films. By systematically investigating ink synthesis, printer settings, and post-processing conditions, this research established a comprehensive understanding of the process-structure-property relationship of printed PVDF-trFE. Consequently, this study consistently achieved the printing of PVDF-trFE films with a thickness of around 40 µ m, accompanied by an impressive piezoelectric coefficient of up to 25 pC N −1 . Additionally, an all-printed dynamic force sensor, featuring a sensitivity of 1.18 V N −1 , was produced by mix printing commercial electrically-conductive silver inks with the customized PVDF-trFE inks. This pioneering on-demand fabrication technique for PVDF-trFE films empowers future astronauts to design and manufacture piezoelectric sensors while in space, thereby significantly enhancing the affordability and sustainability of deep space exploration missions.

Instruments & Instrumentation↗
DOE OSTI2025

Active tungsten expulsion in ELM-absent H-mode plasmas via on-demand ELM triggering with lithium granule injection

Lithium granules gravitationally injected into the upper X-point region demonstrated on-demand edge-localized modes (ELM) triggering in otherwise ELM-suppressed H-mode plasmas on the Experimental Advanced Superconducting Tokamak. Sub-mm lithium granules dropped into enhanced D-alpha H-mode plasmas achieved a high triggering efficiency, while enabling ELM frequencies from several to hundreds of hertz. Core radiation from heavy impurities, dominated by W, was reduced by up to 60%, and the normalized energy confinement increased by up to 30%. At low injection frequencies, ELMs of substantially reduced size compared to spontaneous type-I ELMs were observed. At high injection frequencies, a transition to a mixed ELM phase occurred, characterized by intermittent larger ELMs and suppression of the quasi-coherent mode, achieving the most significant W reduction and energy confinement improvement. These results highlight a promising pathway for active W control via controlled, small ELMs in long-pulse, high-performance scenarios.

EDA H-mode↗
DOE OSTI2023

Acquisition of host-derived carbon in biomass of the ectomycorrhizal fungus Pisolithus microcarpus is correlated to fungal carbon demand and plant defences

Abstract Ectomycorrhizal (ECM) fungi are key players in forest carbon (C) sequestration, receiving a substantial proportion of photosynthetic C from their forest tree hosts in exchange for plant growth-limiting soil nutrients. However, it remains unknown whether the fungus or plant controls the quantum of C in this exchange, nor what mechanisms are involved. Here, we aimed to identify physiological and genetic properties of both partners that influence ECM C transfer. Using a microcosm system, stable isotope tracing, and transcriptomics, we quantified plant-to-fungus C transfer between the host plant Eucalyptus grandis and nine isolates of the ECM fungus Pisolithus microcarpus that range in their mycorrhization potential and investigated fungal growth characteristics and plant and fungal genes that correlated with C acquisition. We found that C acquisition by P. microcarpus correlated positively with both fungal biomass production and the expression of a subset of fungal C metabolism genes. In the plant, C transfer was not positively correlated to the number of colonized root tips, but rather to the expression of defence- and stress-related genes. These findings suggest that C acquisition by ECM fungi involves individual fungal demand for C and defence responses of the host against C drain.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Leakage Reduces Device Coherence Demands for Pulse-Level Molecular Simulations

Quantum simulation on noisy intermediate-scale quantum devices is severely limited by short qubit coherence times. A variational pulse-shaping algorithm known as ctrl-VQE was recently proposed to address this issue by eliminating the need for parameterized quantum circuits, which lead to long state preparation times. Here, in this study, we find the fastest possible pulses that prepare target molecular wave functions for a given device Hamiltonian describing coupled transmon qubits using simulations. We find that the resulting time-optimal pulses develop a bang-bang form consistent with Pontryagin’s maximum principle. We further investigate how the minimal state preparation time is impacted by the number of energy levels active in the transmon simulations. We find that leakage outside the computational subspace (something that is usually considered problematic) speeds up the state preparation, further reducing device coherence-time demands. Our analysis reveals that this speedup is due to both an enlarged solution space of target wave functions and the appearance of additional channels connecting initial and target states.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2025

On-demand magnon resonance isolation in cavity magnonics

Cavity magnonics is a promising field focusing on the interaction between spin waves (magnons) and other types of signal. In cavity magnonics, isolation of magnons from the cavity to allow signal storage and processing fully in the magnonic domain is highly desired, but its realization is often hindered by the lack of necessary tunability of the interaction. This work shows that by using the collective mode of two yttrium iron garnet spheres and applying Floquet engineering, magnonic signals can be switched on demand to a magnon dark mode that is protected from the environment, enabling a variety of manipulation over the magnon dynamics. Furthermore, our demonstration can be scaled up to systems with an array of magnonic resonators, paving the way for large-scale programmable hybrid magnonic circuits.

42 ENGINEERING↗
DOE OSTI2022

Real-time streaming tomographic reconstruction with on-demand data capturing and 3D zooming to regions of interest

Complex dynamic tomographic experiments at brilliant X-ray light sources require real-time feedback on the sample changes with respect to environmental conditions, selecting representative regions of interest for high-resolution scanning, and on-demand data saving mechanisms for storing only relevant projections acquired by fast area detectors and reducing data volumes. Here the implementation details of a 3D real-time imaging monitoring instrument, with zooming to a volume of interest with easy-to-use visualization via ImageJ , a tool familiar to most beamline users, is presented. The instrument relies on optimized data flow between the detector and processing machines and is implemented on commodity computers. The instrument has been developed at beamline 2-BM of the Advanced Photon Source, where the automatic lens changing mechanism for zooming is implemented with an Optique Peter microscope. Performance tests demonstrate the ability to process more than 3 GB of projection data per second and generate real-time 3D zooming with different magnification. These new capabilities are essential for new APS Upgrade instruments such as the projection microscope under development at beamline 32-ID. The efficacy of the proposed instrument was demonstrated during an in situ tomographic experiment on ice and gas hydrate formation in porous samples.

3D zooming↗
DOE OSTI2022

Demand Driven Energy Management for PIPO Auxiliary Power Supply Architecture

In this paper, a demand driven energy management (DDEM) technique is implemented on modular parallel input parallel output DC/DC auxiliary power supply (APS) structure. In this method, modules are brought in/out of the operation making them operate under high loading conditions, avoiding low efficiency under light load. Such a method finds its application in power conservative systems with variable load. Implementation of DDEM and the energy saved is shown using APS comprised of two 15W commercially off-the-shelf DC-DC modules, with 100–1000 VDC input and 24 V output voltage. Along with the DDEM, the lifetime of the power stage devices is controlled minimizing their junction temperature swing through control of cooling system. This control method uses digital twin as interface to virtualize the power devices loading operation/ health condition. Accordingly, no extra sensor or closed loop control required to measure the junction temperature of the devices or feedback the losses to the cooling flow.

Azadeh, Yalda↗
DOE OSTI2024

Preparing an on-Demand Cloud Processing Workflow for NISAR Ecosystems Science Products

In preparation for the NISAR launch and data collection in 2024, the NISAR Project Science Team is building workflows for each Science Team discipline (Ecosystems, Cryosphere, and Solid Earth). This abstract focuses on the Ecosystem disciplines and the development of on-demand cloud-processing workflows for wetlands inundation, forest biomass, agricultural active crop area, and forest disturbance. The workflow simulates NISAR data using UAVSAR or ALOS-2 Single Look Complex data, which are processed to Level 2 geocoded polarimetric covariance matrix products using InSAR Scientific Computing Environment 3.0 software and to Level 3 science products using the Algorithm Theoretical Basis Documents. In this presentation, we describe these workflows and efforts to improve efficiency and data accessibility by using a cloud processing system. We present preliminary sample products from each Ecosystem discipline: inundation, forest biomass, crop area, and forest disturbance.

Christensen, Alexandra↗
DOE OSTI2021

Inertia Emulation Control using Demand Response via 5G Communications

Building energy equipment is moving rapidly towards Internet of Things (IoT)-driven devices to provide consumer connectivity and device management. These device-level interfaces along with 5G communications will be leveraged to develop control architectures to engage a large number of monitoring and control devices and provide real-time and reliable energy services. Emerging 5G networks have high potential to provide the communication technology for demand response, with fast transfer speed, high reliability, and high number of connections. Guaranteed inertial response to limit frequency fluctuations is one of the main challenges in modern power systems due to the increased penetration of renewable generation, and it is largely affected by communication delays and packet losses. This paper analyzes inertial response and rate of change of frequency in a power system model with inverter-interfaced air conditioners. The control loop considers time delays and packet losses to show the need to switch to 5G networks in future smart grids.

Morovati, Samaneh↗
DOE OSTI2020

Time-of-Use and Demand Charge Battery Controller Using Stochastic Model Predictive Control

Stationary batteries in residential and commercial buildings are often used to smooth customer load profiles and to lower customer electricity bills. Controllers for these battery systems should account for customer energy consumption, rate structures, and high internal battery temperatures, which can lead to reduced performance over the battery lifetime. It is important to consider the uncertainty in forecasting energy consumption and temperature, especially for customers with highly variable and uncertain loads. We propose a novel battery controller using stochastic model predictive control that accounts for these uncertainties and can handle complex rate structures, including demand charges. We show that the controller performs better than standard model predictive control when there is significant uncertainty in the forecast. We also show improvements in the performance with more accurate forecasts and with a more aggressive control strategy.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗