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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 811 records · Page 45
All sourcesNASA NTRSDOE OSTI
NASA NTRS2024

Final Technical Report for CMSC 838L

This paper describes Rahul Vishnoi’s final project supporting in his Graduate School curriculum CMSC 838L, Advanced Topics in Programming Languages and Computer Architecture. This project was selected to intersect with his work as a Pathways Intern supporting Code 583, the Ground Software Systems Branch, at NASA’s Goddard Space Flight Center (GSFC). In this project, Field Programmable Gate Array (FPGA) hardware from Xilinx is used to replace and offload processor and memory-intensive computations from a microcontroller/Processing System (PS) to the FPGA Programmable Logic (PL). An interface between the PL and PS in the form of a C library allows for this bridging of capability.

Microcontroller, FPGA, Embedded Development, Xilin↗
DOE OSTI2025

Expanding the physics reach of DUNE in the near and far detectors

The Deep Underground Neutrino Experiment (DUNE) is a next-generation long-baseline neutrino oscillation experiment. Its primary goal is the determination of the neutrino mass hierarchy and the CP-violating phase. The DUNE physics programme also includes the detection of astrophysical neutrinos and the search for beyond the Standard Model (BSM) phenomena. DUNE will consist of a near detector (ND) complex placed at Fermilab, and a modular Liquid Argon Time Projection Chamber (LArTPC) far detector (FD) to be built in the Sanford Underground Research Facility (SURF), approximately 1300 km away from the neutrino production point. This thesis describes three different projects within DUNE. First, a novel strategy to improve the triggering capabilities of the DUNE FD is proposed. It uses matched filters to enhance the production of online hits across all charge collection planes. Next, the possibility of detecting neutrinos coming from dark matter (DM) annihilations in the Sun with the FD is explored. The complementarity of DUNE to this kind of DM searches is shown. Finally, the simulation and reconstruction framework of ND-GAr, the gas argon ND proposed for Phase II of DUNE, is presented. A number of additions to this are described, particularly focused on the development of the particle identification (PID) capabilities of the detector. These are then used to perform the first event selection studies with an end-to-end simulation in ND-GAr, in particular the selection of pion exclusive samples in $\nu_{\mu}$ CC interactions. All three of these projects share the common goal of enhancing the physics programme of DUNE.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
NASA NTRSDate not supplied

Surface Radiation Budget (SRB) Release 2 Shortwave Monthly Data in Native Format (SRB_REL2_SW_MONTHLY)

The SRB data include the average upward and downward fluxes, photosynthetically active radiative flux, aerosol and cloud optical depth, cloud fraction, and solar zenith angle at three hourly intervals for each day for the entire globe between 07/01/1983 and 10/31/1995. These parameters were derived with the Shortwave algorithm of the NASA World Climate Research Programme /Global Energy and Water-Cycle Experiment (WCRP/GEWEX) Surface Radiation Budget (SRB) Project. [Location=GLOBAL] [Temporal_Coverage: Start_Date=1983-07-01; Stop_Date=1998-07-26] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=180] [Data_Resolution: Latitude_Resolution=1 degree; Longitude_Resolution=Ranges from 1 degree in the tropics to 120 degrees at the poles.; Temporal_Resolution=monthly; Temporal_Resolution_Range=monthly].

DIRECT/DIFFUSE SOLAR RADIATION↗
NASA NTRSDate not supplied

Surface Radiation Budget (SRB) Release 2.5 QC Shortwave Monthly Data in Native Format (SRB_REL2.5_QCSW_MONTHLY)

These surface radiation budget data include both surface and top of the atmosphere insolation fluxes as well as cloud fraction/amount for the entire globe between 07/01/1983 and 06/30/2005. These parameters were derived with the Quality-Check SW (QCSW) algorithm of the NASA World Climate Research Programme /Global Energy and Water-Cycle Experiment (WCRP/GEWEX) Surface Radiation Budget (SRB) Project. [Location=GLOBAL] [Temporal_Coverage: Start_Date=1998-01-01; Stop_Date=2005-06-30] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=180] [Data_Resolution: Latitude_Resolution=1 degree; Longitude_Resolution=Ranges from 1 degree (tropics and subtropics) to 120 degrees (the poles).; Temporal_Resolution=monthly; Temporal_Resolution_Range=monthly].

SHORTWAVE FLUX↗
NASA NTRSDate not supplied

Surface Radiation Budget (SRB) Release 2.5 QC Longwave 3 Hourly Monthly Data in Native Format(SRB_REL2.5_QCLW_3HRLY_MONTHLY)

These surface radiation budget data sets include downward fluxes and cloud radiative properties for the entire globe between 07/01/1983 and 06/30/2005. These parameters were parameters derived with the Quality-Check LW (QCLW) algorithm of the NASA World Climate Research Programme /Global Energy and Water-Cycle Experiment (WCRP/GEWEX) Surface Radiation Budget (SRB) Project. [Location=GLOBAL] [Temporal_Coverage: Start_Date=1998-01-01; Stop_Date=2004-12-31] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=180] [Data_Resolution: Latitude_Resolution=1 degree; Longitude_Resolution=Ranges from 1 degree in the tropics to 120 degrees at the poles; Temporal_Resolution=3 hourly averaged monthly].

CLOUD FORCING↗
DOE OSTI2024

Lax-Oleinik-Type Formulas and Efficient Algorithms for Certain High-Dimensional Optimal Control Problems

Two of the main challenges in optimal control are solving problems with state-dependent running costs and developing efficient numerical solvers that are computationally tractable in high dimension. In this paper, we provide analytical solutions to certain optimal control problems whose running cost depends on the state variable and with constraints on the control. We also provide Lax-Oleinik-type representation formulas for the corresponding Hamilton-Jacobi partial differential equations with state-dependent Hamiltonians. Additionally, we present an efficient, grid-free numerical solver based on our representation formulas, which is shown to scale linearly with the state dimension, and thus, to overcome the curse of dimensionality. Using existing optimization methods and the min-plus technique, we extend our numerical solvers to address more general classes of convex and nonconvex initial costs. We demonstrate the capabilities of our numerical solvers using implementations on a central processing unit (CPU) and a field-programmable gate array (FPGA). In several cases, our FPGA implementation obtains over a 10 times speedup compared to the CPU, which demonstrates the promising performance boosts FPGAs can achieve. Furthermore, our numerical results show that our solvers have the potential to serve as a building block for solving broader classes of high-dimensional optimal control problems in real-time.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Ion Transport in Self-Assembled Peptoid Membranes with Carbon Nanotube Porin Channels

Artificial membranes that combine high ionic selectivity with mechanical robustness remain a key challenge for next-generation separation technologies. Here, we report ion transport measurements in biomimetic membranes composed of crystalline peptoid nanosheets co-assembled with carbon nanotube porins (CNTPs). Pure peptoid sheets formed defect-free, ion-impermeable membranes, which were then suspended over small SiN x nanopore apertures for ion transport measurements. Incorporation of CNTPs into the peptoid sheet matrix made these membranes ion permeable, with ion conductance values consistent with ion transport through individual and multiple carbon nanotube channels. In conclusion, the modularity and molecular order of peptoid membranes, combined with the exceptional conductance properties of CNTPs, position this platform as a versatile framework for assembling programmable, selective, and robust nanofluidic membranes that can bridge the performance gap between biological and synthetic membrane materials.

Biotechnology↗
DOE OSTI2024

Catalytic Resonance Theory: Turnover Efficiency and the Resonance Frequency

Programmable catalysts exhibiting forced oscillation in the free energy of reacting surface species were simulated to understand the general mechanisms leading to efficient use of the input energy. Catalytic ratchets with either positive or negative adsorbate scaling exhibited oscillation conditions of both high and low turnover efficiency, yielding catalytic turnover frequencies either close to or significantly lower than the applied catalyst oscillation frequency, respectively. The “effective rate”, defined as the product of the catalytic turnover frequency and the turnover efficiency (ηTOE), was limited via two catalytic mechanisms: a leaky catalytic ratchet existed when molecules repeatedly traversed backward through the catalytic transition state upon catalyst oscillation, while a catalytic ratchet with low surface participation exhibited reduced formation of a gas-phase final product due to low surface product coverage. Furthermore, a single applied frequency yielding a maximum effective catalytic rate defined as the “resonance frequency” provided maximum combined benefit for catalytic rate and efficiency.

25 ENERGY STORAGE↗
DOE OSTI2025

End-to-End Workflow for Machine-Learning-Based Qubit Readout With QICK and hls4ml

In this article, we present an end-to-end workflow for superconducting qubit readout that embeds codesigned neural networks into the quantum instrumentation control kit (QICK). Capitalizing on the custom firmware and software of the QICK platform, which is built on Xilinx radiofrequency system-on-chip field-programmable gate arrays (FPGAs), we aim to leverage machine learning (ML) to address critical challenges in qubit readout accuracy and scalability. The workflow utilizes the hls4ml package and employs quantization-aware training to translate ML models into hardware-efficient FPGA implementations via user-friendly Python application programming interfaces. We experimentally demonstrate the design, optimization, and integration of an ML algorithm for single transmon qubit readout, achieving 96% single-shot fidelity with a latency of 32.25 ns and less than 16% FPGA lookup table resource utilization. Our results offer the community an accessible workflow to advance ML-driven readout and adaptive control in quantum information processing applications.

42 ENGINEERING↗
DOE OSTI2024

End-to-end codesign of Hessian-aware quantized neural networks for FPGAs

Here, we develop an end-to-end workflow for the training and implementation of co-designed neural networks (NNs) for efficient field-programmable gate array (FPGA) hardware. Our approach leverages Hessian-aware quantization of NNs, the Quantized Open Neural Network Exchange intermediate representation, and the hls4ml tool flow for transpiling NNs into FPGA firmware. This makes efficient NN implementations in hardware accessible to nonexperts in a single open sourced workflow that can be deployed for real-time machine-learning applications in a wide range of scientific and industrial settings. We demonstrate the workflow in a particle physics application involving trigger decisions that must operate at the 40-MHz collision rate of the CERN Large Hadron Collider (LHC). Given the high collision rate, all data processing must be implemented on FPGA hardware within the strict area and latency requirements. Based on these constraints, we implement an optimized mixed-precision NN classifier for high-momentum particle jets in simulated LHC proton-proton collisions.

47 OTHER INSTRUMENTATION↗
DOE OSTI2025

Synchronous Machine Governor Upgrade

Conventional generation sources play a critical role in the stability and reliability of the electrical grid, particularly as we transition towards more renewable energy sources. To understand and accurately emulate their behavior for optimizing grid operations and ensuring seamless integration with renewable technologies, it is essential to better emulate the grid- and plant-level impacts of conventional generation sources, such as natural gas (NG) driven heat recovery steam generators (HRSGs) and combustion turbines (CTs). Therefore, a governor model is developed in a programmable logic controller (PLC) to investigate the performance of the conventional generator under various dynamic operating conditions and to identify the impact on grid stability in a controlled environment. The governor model aims to enable the hardware-in-the-loop (HIL) based emulation of these conventional generation sources using the existing 2 MVA synchronous machine/generator that is driven by a flexible 2.5 MW variable speed drive. This setup will allow us to replicate the dynamic characteristics and response behaviors of NG-driven HRSGs and CTs. The controls for the emulated conventional plants follow the industry standard and are adjustable, ensuring they accurately reflect the operational capabilities and limitations of real-world systems. These controls include load-following capabilities, ramp rates, startup and shutdown sequences, and emissions characteristics. By incorporating these adjustable controls, we aim to capture the nuanced impacts of conventional generation, such as their ability to provide ancillary services like frequency regulation, voltage support, and spinning reserve. In this report, we simulate two types of dynamic operations: grid-connected and islanding. For each dynamic operation, representative starting sequences are tested, including turbine purge, ignition, speed ramping up, generator excitation and synchronizing, and breaker close. The HIL based tests provides insights for field deployment, specifically the high-fidelity governor model provides results to predict the potential stability and reliability risk and suggest possible integration measures (e.g., generation and load balancing, tuning of governor control parameters). Ultimately, this enhanced emulation capability will be integrated into our Advanced Research on Integrated Energy Systems (ARIES), enabling us to conduct comprehensive studies on the interactions between conventional and renewable energy sources. By better understanding these interactions, we can develop strategies to optimize the overall performance and reliability of the grid. This will support the deployment of advanced grid management techniques, such as demand response, grid-forming inverters, and energy storage systems. The main contributions are summarized as follows: (1) This report introduces a PLC-based governor model for gas turbines. This model accurately simulates the dynamic behavior of conventional generation sources under various operational scenarios; (2) The model is integrated with an HIL testbed that includes a 2.5 MW variable speed drive and a 2 MVA synchronous machine. This setup enables realistic, real-time emulation of conventional power plants, particularly NG driven HRSGs and CTs; (3) The developed model is adaptable to various gas turbine configurations and allows for precise control over parameters such as MW ramp rates. This flexibility makes it a valuable tool for future research and industry collaboration; and (4) By incorporating the model into the National Renewable Energy Laboratory's Advanced Research on Integrated Energy Systems, the report lays the groundwork for future studies on interactions between conventional and renewable energy sources, enhancing the ability to develop advanced grid management strategies.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2026

Modeling and Power-Hardware-in-the-Loop Validation of Synchronous Machine Governor

This paper introduces the development of a high-fidelity gas turbine governor model using a programmable logic controller for power-hardware-in-the-loop (PHIL) validation. The governor model is integrated with the National Renewable Energy Laboratory's (NREL) PHIL test bed, featuring a 2-MVA synchronous machine and a 2.5-MW variable-speed drive, to emulate NG-driven HRSGs and CTs under various operational scenarios. The primary objective of this research is to study the grid-connected and islanding operations of conventional generation sources, with representative startup sequences including turbine purge, ignition, speed ramp-up, synchronization, and breaker closure. Preliminary results of the generator governor model on NREL PHIL platform, particularly using the 2.5-MW dynamometer system, offered significant insights into the modeling techniques, hardware integration, scaling, and real-world simulation dynamics.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS1997

Variable Dynamic Testbed Vehicle: Dynamics Analysis

The Variable Dynamic Testbed Vehicle (VDTV) concept has been proposed as a tool to evaluate collision avoidance systems and to perform driving-related human factors research. The goal of this study is to analytically investigate to what extent a VDTV with adjustable front and rear anti-roll bar stiffnesses, programmable damping rates, and four-wheel-steering can emulate the lateral dynamics of a broad range of passenger vehicles.

Variable Dynamic Testbed Vehicle VDTV collision av↗
NASA NTRS2005

FPGA development for high altitude subsonic parachute testing

This paper describes a rapid, top down requirements-driven design of a Field Programmable Gate Array (FPGA) used in an Earth qualification test program for a new Mars subsonic parachute. The FPGA is used to process and control storage of telemetry data from multiple sensors throughout launch, ascent, deployment and descent phases of the subsonic parachute test.

Field Programmable Gate Array (FPGA)↗