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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 1,225 records · Page 68
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Evaluating the Efficacy of Conditional Variational Autoencoders in Generating Synthetic Single Nuclei RNA-Seq Data for Space Biology Research

Astronauts are subject to unique stressors during spaceflight, leading to changes in their cellular function. However, neither astronauts nor model organisms respond the same to spaceflight, and research implicates a contribution of omics components in differential responses. Understanding how gene expression affects astronaut health is critical for the success of long-term space missions, prompting interest in developing personalized predictive models leveraging artificial intelligence (AI) and machine learning (ML) techniques. Developing such models requires extensive data, which is challenging to obtain and share. This study explores the use of conditional variational autoencoders (CVAEs) to synthetically generate single-nuclei RNA-seq (snRNA-seq) data. CVAEs build on standard variational autoencoders (VAEs) by conditioning data generation on covariates like sample identity and mission parameters, enhancing the relevance of generated data for specific contexts. For our work, we built two CVAEs with varying degrees of sparsity to optimize both interpretability and generative power. We train and validate models on existing snRNA-seq data collected from the brain tissue of mice subjected to spaceflight conditions and their ground control counterparts. We evaluate model performance using statistical tests and visualizations to compare synthetic data to real data. We aim to demonstrate that these prototype CVAE architectures could be used in future space biology work and that this is a method worth further exploring.

Sarah Golts↗
NASA NTRSDate not supplied

Numerical Investigation of Heat Transfer and Fluid Flow within Electrochemical Hydrogen Peroxide Generation Unit

Long-term manned space missions require the onboard production of disinfectants essential for maintaining crew health and supporting life systems. Currently, disinfection aboard the International Space Station (ISS) relies on disposable wetted wipes, which are regularly resupplied from Earth. This approach imposes a significant burden on resupply logistics, storage, and waste management. To address these challenges and support future missions, efforts are underway to develop an in-situ solution that electrochemically generates hydrogen peroxide disinfectant using onboard resources. In collaboration with NASA, Faraday Technology, Inc. has advanced this concept through a series of Small Business Innovation Research (SBIR) projects, resulting in the development of a Peroxide Generation Unit (PGU). The PGU can produce up to 3 wt.% hydrogen peroxide on-demand at a rate of 1 liter per day, providing a sustainable alternative to Earth-dependent supplies. The resulting aqueous hydrogen peroxide (H₂O₂) is an effective disinfectant, safe for crew use, compatible with spacecraft systems, and free from volatiles, off-gassing, or residues. This innovation offers a reliable, efficient solution for onboard disinfection, reducing dependence on Earth-based resupply while ensuring the health and safety of space crews. Generating hydrogen peroxide at the required rate needs high voltages and currents, exceeding 20V and 2A respectively, which leads to significant heat generation from Joule heating. This temperature rise poses a risk to sensitive system components, especially critical and expensive membranes that can degrade under thermal stress. To mitigate this risk, the thermal, fluid, and electrical flows within the system are modeled computationally using the commercial software COMSOL. The numerical simulations are validated against experimental data from both sub-scale and alpha-scale systems. Once verified, the model is employed to identify thermal hotspots, investigate their underlying causes, and explore solutions to prevent them.

Life Support Systems (LSS)↗
NASA NTRSDate not supplied

Americium-Fuelled Radioisotope Stirling Generator Elegant Breadboard

High power solutions for spacecraft are becoming increasingly sought after in the new era of space exploration, with energy intensive in-situ lunar surface exploration becoming a key part of the roadmap for major space agencies, as well as commercial companies. Nuclear power provides the most feasible solution to achieve continued operation through the long lunar night, and in extended periods in Permanently Shadowed Regions (PSRs). Americium-241 (241Am) is used as the fuel of choice in European Radioisotope Power Systems (RPS). The University of Leicester have developed a number of systems using this fuel type, including a 200 Wth heat source. Building on existing international partnerships, the University of Leicester is continuing to work with NASA Glenn Research Center (GRC) to maximise the electrical output that can be generated from the heat source by progressing the radioisotope-Stirling generator concept to elegant breadboard level, building on the long heritage of dynamic power conversion developments at NASA Glenn. Presented in the following conference paper is the next iteration of the Americium-fuelled Radioisotope Stirling Generator (Am-RSG) Elegant Breadboard, following on from a successful technology demonstration design conducted at NASA Glenn in early 2025. The design laid-out in this paper is a more flight-like version of the technology demonstrator, and is intended to pair with the next generation of Stirling convertor technology, the SunPower Robust Stirling Converter (SRSC). The SRSC is able to operate more efficiently at lower thermal power levels than the previous Advanced Stirling Convertor (ASC), making it more suitable for the 241Am system.

Lunar↗
DOE OSTI2019

Generating clock signals for a cycle accurate, cycle reproducible FPGA based hardware accelerator

A method, system and computer program product are disclosed for generating clock signals for a cycle accurate FPGA based hardware accelerator used to simulate operations of a device-under-test (DUT). In one embodiment, the DUT includes multiple device clocks generating multiple device clock signals at multiple frequencies and at a defined frequency ratio; and the FPG hardware accelerator includes multiple accelerator clocks generating multiple accelerator clock signals to operate the FPGA hardware accelerator to simulate the operations of the DUT. In one embodiment, operations of the DUT are mapped to the FPGA hardware accelerator, and the accelerator clock signals are generated at multiple frequencies and at the defined frequency ratio of the frequencies of the multiple device clocks, to maintain cycle accuracy between the DUT and the FPGA hardware accelerator. In an embodiment, the FPGA hardware accelerator may be used to control the frequencies of the multiple device clocks.

Asaad, Sameh W.↗
DOE OSTI2018

Methods and systems for generating a continuous helical tool path for parts having multiple central axes

A computer-implemented method for generating a continuous helical tool path for forming a part having a plurality of central axes is provided. The method includes performing a tool path algorithm modeling and a tool path algorithm execution using a computer system. The tool path algorithm modeling includes defining a starting point location within a computer-generated three-dimensional part geometry model, defining a vector, defining a helix, defining a sweeping surface three-dimensional geometry element, and generating an intersection curve from tracing a continuous curved line of an intersection between the sweeping surface geometry element and the part geometry model. The tool path algorithm execution includes defining data for a forming tool stylus, selecting the intersection curve as a guiding element for the forming tool stylus, and generating the continuous helical tool path for the forming tool stylus. The continuous helical tool path includes a forming tool stylus centerline path in graphical space.

42 ENGINEERING↗
DOE OSTI2019

Bulk Power System Dynamics with Varying Levels of Synchronous Generators and Grid-Forming Power Inverters: Preprint

Inverters using phase-locked loops for control depend on voltages generated by synchronous machines to operate. This might be problematic if much of the conventional generation fleet is displaced by inverters. To solve this problem, grid-forming control for inverters has been proposed as being capable of autonomously regulating grid voltages and frequency. Presently, the performance of bulk power systems with massive penetrations of grid-forming inverters has not been thoroughly studied to elucidate benefits. Hence, this paper presents inverter models with two grid-forming strategies: virtual oscillator control and droop control. The two models are specifically developed to be used in positive-sequence simulation packages and have been implemented in PSLF. The implementations are used to study the performance of bulk power grids incorporating inverters with grid-forming capability. Specifically, simulations are conducted on a modified IEEE 39-bus test system and the micro-WECC test system with varying levels of synchronous and inverter-based generation. The dynamic performance of the tested systems with grid-forming inverters during contingency events is better than cases with only synchronous generation.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2019

Detecting faults in turbine generators

Turbine generator faults can be detected by receiving a current signal from the turbine generator, and synchronously sampling the current signal to obtain a set of current signal samples that are evenly spaced in the phase domain, in which phase differences between adjacent current signal samples in the set of current signal samples are substantially the same. The process includes generating a frequency spectrum of the current signal samples, identifying one or more excitations in the frequency spectrum, and detecting a fault in the turbine generator based on the one or more excitations in the frequency spectrum.

Qiao, Wei↗
DOE OSTI2019

Apparatus and methods for probing a material as a function of depth using depth-dependent second harmonic generation

A method for non-invasively probing at least one physics property of a solid material. In one embodiment, the method has the steps of splitting a photon beam into a first photon beam and a second photon beam, exposing the solid material to the first photon beam to generate a coherent acoustic phonon wave in the solid material at time t, and exposing the solid material to the second photon beam at a time t+Δt, where t+Δt≥t, to generate corresponding second harmonic generation signals, where from the corresponding second harmonic generation signals, the at least one physics property of the solid material is determinable.

Garnett, Joy↗
DOE OSTI2019

Charge generating devices and methods of making and use thereof

Provided herein are charge generating devices and methods of making and use thereof. The charge generating devices comprise a substrate having a top surface; a plurality of spaced-apart three-dimensional elements disposed on the top surface of the substrate; and a plurality of cavities formed by the plurality of spaced-apart three-dimensional elements, the plurality of cavities being the area between the plurality of spaced-apart three-dimensional elements. The charge generating devices can further comprise a radioactive layer disposed on at least a portion of the plurality of spaced-apart three-dimensional elements and the top surface such that the plurality of cavities and the top surface are substantially coated by the radioactive layer. In some examples, the charge generating devices can comprise a radiation material and/or a scintillating material disposed within at least a portion of the plurality of cavities.

Cao, Lei↗
DOE OSTI2018

Generation Forecasting for Small Run-of-the-River Hydroelectric Systems Using Statistical Learning Models

With an increasing interest in constructing new run-of-the-river (ROR) hydroelectric generation over the more traditional reservoir-based hydroelectric systems, there is an increasing operational challenge due to the volatility of stream flow. The Snohomish County Public Utilities District (SnoPUD) has recently invested in the construction and operation of 3 new run-of-the-river projects in Northwestern Washington along Calligan Creek, Hancock Creek, and Youngs Creek. In order to effectively plan generation dispatch, SnoPUD has expressed interest in the development of an accurate forecasting tool to predict the generation capacity for these ROR systems. The following research project aims to use statistical learning models, namely Hidden Markov Models (HMMs), to predict day-ahead generation capacities for the aforementioned ROR systems. These models are constructed using 12 years of historical stream flow data collected at the intake sites and precipitation data recorded at the National Oceanic and Atmospheric Administration (NOAA) Alpine Meadows station. Four methods of constructing the models are studied for their forecast accuracies, and are compared with the persistence model. Despite using only one set of observable variables, the HMMs are shown to have slight improvements in accuracy over the persistence model approach, which shows great optimism for future work.

13 HYDRO ENERGY↗
DOE OSTI2019

Correlated Synthetic Time Series Generation using Fourier and ARMA

As the contribution of renewable energy grows in electricity markets, the complexity nuclear’s place within the energy mix increases, and likewise the need for robust simulation techniques. While decades of wind, solar, and demand pro- files can sometimes be obtained, this is too few samples to provide a statistically meaningful analysis of a system with baseload, peaker, and renewable generation. Synthetic time series generation presents itself as a suitable methodology to meet this need. One approach for synthetic series generation is training a model using Fourier series decomposition for seasonal patterns and Auto-Regressive Moving Average models (ARMA) to describe time-correlated statistical noise about the seasonal patterns. When combined, the Fourier plus ARMA (FARMA) model has been shown to provide an infinite set of independent, identically-distributed sample time series with the same statistical properties as the original data [1]. When considering an energy mix with renewable electricity production, several time series of energy, grid, and weather measurements are needed for each synthetic year modeled to statistically comprehend the efficiency of any given energy mix. These cannot be considered independent series in a given synthetic year. To capture and reproduce the correlations that might exist in the measured histories, the ARMA can further be extended as a Vector ARMA (VARMA). In the VARMA algorithm, covariance in statistical noise is captured both within a history as part of the autoregressive moving average, and with respect to the other variables in the time series. In this work the implementation of the Fourier VARMA in the RAVEN uncertainty quantification and risk analysis software framework [2] is presented, along with examples of correlated synthetic history generation.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Apprentice for Event Generator Tuning

Apprentice is a tool developed for event generator tuning. It contains a range of conceptual improvements and extensions over the tuning tool Professor. Its core functionality remains the construction of a multivariate analytic surrogate model to computationally expensive Monte-Carlo event generator predictions. The surrogate model is used for numerical optimization in chi-square minimization and likelihood evaluation. Apprentice also introduces algorithms to automate the selection of observable weights to minimize the effect of mis-modeling in the event generators. We illustrate our improvements for the task of MC-generator tuning and limit setting.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

Generating clock signals for a cycle accurate, cycle reproducible FPGA based hardware accelerator

A method, system and computer program product are disclosed for generating clock signals for a cycle accurate FPGA based hardware accelerator used to simulate operations of a device-under-test (DUT). In one embodiment, the DUT includes multiple device clocks generating multiple device clock signals at multiple frequencies and at a defined frequency ratio; and the FPG hardware accelerator includes multiple accelerator clocks generating multiple accelerator clock signals to operate the FPGA hardware accelerator to simulate the operations of the DUT. In one embodiment, operations of the DUT are mapped to the FPGA hardware accelerator, and the accelerator clock signals are generated at multiple frequencies and at the defined frequency ratio of the frequencies of the multiple device clocks, to maintain cycle accuracy between the DUT and the FPGA hardware accelerator. In an embodiment, the FPGA hardware accelerator may be used to control the frequencies of the multiple device clocks.

Asaad, Sameh W.↗
DOE OSTI2021

Apparatuses and methods for generating carbon particles and exhaust gas used by gas turbine systems

Apparatuses for generating carbon particles and exhaust gas used by gas turbine systems are disclosed. One apparatus may include a decarbonization component combusting or reacting a mixture of a fuel and a mixing gas to generate the carbon particles and the exhaust gas and an exhaust conduit to receive the exhaust gas generated by the decarbonization component. The apparatus may also include a mixing duct in fluid communication with the exhaust conduit and the gas turbine system. The mixing duct may receive the exhaust gas and provide the exhaust gas to the gas turbine system to be used to produce a working fluid within the gas turbine system. The apparatus may further include a carbon particle collection component for receiving and storing the generated carbon particles.

Berry, Jonathan Dwight↗
DOE OSTI2021

Stable Parallel Training of Wasserstein Conditional Generative Adversarial Neural Networks : *Full/Regular Research Paper submission for the symposium CSCI-ISAI: Artificial Intelligence

We use a stable parallel approach to train Wasserstein Conditional Generative Adversarial Neural Networks (W-CGANs). The parallel training reduces the risk of mode collapse and enhances scalability by using multiple generators that are concurrently trained, each one of them focusing on a single data label. The use of the Wasserstein metric reduces the risk of cycling by stabilizing the training of each generator. We apply the approach on the CIFAR10 and the CIFAR100 datasets, two standard benchmark datasets with images of the same resolution, but different number of classes. Performance is assessed using the inception score, the Fréchet inception distance, and image quality. An improvement in inception score and Fréchet inception distance is shown in comparison to previous results obtained by performing the parallel approach on deep convolutional conditional generative adversarial neural networks (DC-CGANs). Weak scaling is attained on both datasets using up to 100 NVIDIA V100 GPUs on the OLCF supercomputer Summit.

Lupo Pasini, Massimiliano↗
DOE OSTI2022

Ozone generator system

An ozone generator system utilizes an electrochemical cell to produce and control ozone concentrations within an enclosure or to supply ozone to a flow conduit. The enclosure may he coupled with a flow conduit that carries the produced ozone to a desired location. An enclosure may be a sterilization chamber and the concentration of ozone produced by the ozone generating system may be sufficient to sterilize articles within the enclosure. An oxygen control electrolyzer cell and/or humidity control electrolyzer cell may be coupled with the enclosure to further control the environment of the enclosure. A humidity control electrolyzer cell may be fluidly coupled with the ozone generator to supply humidity for reaction on the anode of the ozone generator.

Bahar, Bamdad↗
DOE OSTI2022

Reduced Order Models Generation for HTGRs Pebble Shuffling Procedure Optimization Studies

This report provides an initial study for producing reduced-order models (ROMs) of pebble-bed high temperature gas reactor (HTGR) models for the purposes of design optimization. As an initial study, this work is meant to be exploratory---identifying useful workflows and methods for ROM generation---and not meant to be a catch-all analysis of HTGR ROM generation and usage for optimization. This report summarizes three tasks performed in Fiscal Year 2022: 1) the creation of HTGR model, 2) the sensitivity analysis of model design parameters, and 3) an introduction to ROM generation techniques. The representative HTGR model created in this work is a multiphysics equilibrium-core using the BlueCRAB (comprehensive reactor analysis bundle) reactor analysis application, coupling four physical phenomena: neutronics, streamline depletion, porous flow thermal hydraulics, and pebble heat conduction. Part of the model creation was identifying some design parameters and quantities of interest that are relevant in an optimization analysis and adjustable in the model. The sensitivity analysis utilized a polynomial chaos expansion methodology to compute global sensitivity metrics. This analysis showed that thermal hydraulics parameters and quantities of interest had a relatively small impact on simulation results. Finally, the ROM generation work involved exploring three different ROM methodologies: polynomial regression, a Gaussian process, and artificial neural networks. Using a cross-validation technique to characterize ROM performance, the Gaussian process and single-layer artificial neural networks showed the most promising results. Overall, this study was insightful and the lessons learned will be invaluable for the eventual development of an HTGR design optimization workflow.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Programmable pseudo-random sequence generator for use with universal lidar and its associated method of operation

A pseudo-random sequence generator for use within a universal lidar system and its corresponding method of operation. The pseudo-random sequence generator uses synchronized shift registers that are in series Binary adders are provided. The signal output of each of the shift registers is tapped and directed to the binary adders. High-speed switches are provided between the shift registers and the binary adders. The switches are programmed to connect only two of the shift registers to the binary adders for each of the pseudo-random patterns being generated. The binary adders generate an output signal that is received by the first shift register. The signal propagates through all the shift registers to the last shift register. The last shift register outputs a pseudo-random sequence.

Datta, Shubhashish↗