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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 793 records · Page 44
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NASA NTRS1953

Investigation of acceleration characteristics of a single-spool turbojet engine

Operation of a single-spool turbojet engine with constant exhaust-nozzle area was investigated at one flight condition. Data were obtained by subjecting the engine to approximate-step changes in fuel flow, and the information necessary to show the relations of acceleration to the sensed engine variables was obtained. These data show that maximum acceleration occurred prior to stall and surge. In the low end of the engine-speed range the margin was appreciable; in the high-speed end the margin was smaller but had not been completely defined by these data. Data involving acceleration as a function of speed, fuel flow, turbine-discharge temperature, compressor-discharge pressure, and thrust have been presented and an effort has been made to show how a basic control system could be improved by addition of an override in which the acceleration characteristic is used not only to prevent the engine from entering the surge region but also to obtain acceleration along the maximum acceleration line during throttle bursts.

Oppenheimer, Frank L↗
DOE OSTI2024

Carbon Transport and Storage Planning and Viability Support Tools

The EDX disCO2ver Carbon Transport and Storage Planning and Viability Support Tools are made up of the Carbon Storage Planning Inquiry Tool (CS PlanIT, Justman et al. 2024) and the Carbon Storage Technical Viability Approach Support Tool (CS TVA). Together, these tools support data access to support understanding data availability to support planning efforts for carbon transport and storage. The Carbon Storage Planning Inquiry Tool (CS PlanIT) is an online web mapping application designed to help users explore, query, and evaluate multiple data layers to support and accelerate carbon storage resource and feasibility assessments and planning efforts. CS PlanIT currently contains a range of datasets associated with geologic, technical, and infrastructure factors. The data sets can be filtered geographically for an area of interest to update statistics and charts within the dashboard. The dashboard is divided into different sections called widgets, relating to different steps in the carbon storage planning process. The resources in this submission include a link to PlanIT, as well as a data catalog and link to user documentation. The original citation for the CS PlanIT tool, which has now been integrated into the toolset here, was: - Devin Justman, Scott Pantaleone, Maneesh Sharma, Lucy Romeo, Paige Morkner, CS PlanIT (Carbon Storage Planning Inquiry Tool) , 6/28/2024, https://edx.netl.doe.gov/dataset/cs-planit-carbon-storage-planning-inquiry-tool, DOI: 10.18141/2377953 The Carbon Storage Technical Viability Approach Support (CS TVA) Tool displays spatial data availability for the many components of Geologic Carbon Storage (GCS) technical viability assessment (Creason al 2025). Identifying sites suitable for GCS requires evaluating the intersection of myriad factors, including reservoir conditions, subsurface and surface hazards, infrastructure requirements, and energy community metrics. The technical viability of a site can only be confirmed for instances where all these factors have data available, and where those data support viability. Additional Resources related to the Technical Viability Assessment Tool: - Julia Mulhern, Casey White, Araceli Lara, Neyda Cordero Rodriguez, Zachary Jackson, Jacob Shay, Gabriel Creason, MacKenzie Mark-Moser, Paige Morkner, Kelly Rose, Carbon Storage Technical Viability Approach (CS TVA) Database, 3/26/2025, https://edx.netl.doe.gov/dataset/edx4ccs-carbon-storage-technical-viability-approach-database , DOI:10.18141/1984655 - Julia Mulhern, MacKenzie Mark-Moser, Gabriel Creason, Casey White, Araceli Lara, Neyda Cordero Rodriguez, Zach Jackson, Paige Morkner, Kelly Rose, Carbon Storage Technical Viability Approach (CS TVA) Matrix, 3/27/2025, https://edx.netl.doe.gov/dataset/carbon-storage-technical-viability-approach-cs-tva-matrix , DOI: 10.18141/2539979 - Gabriel Creason, Zach Jackson, Neyda Cordero Rodriguez, Julia Mulhern, Casey White, Araceli Lara, MacKenzie Mark-Moser, Paige Morkner, Kelly Rose, Carbon Storage Technical Viability Approach (CS TVA) Data Availability Results Database, 3/27/2025, https://edx.netl.doe.gov/dataset/carbon-storage-technical-viability-approach-cs-tva-data-availability-results-database, DOI:10.18141/2538557

Carbon storage↗
NASA NTRS1995

Correlation of electron and proton irradiation-induced damage in InP solar cells

When determining the best solar cell technology for a particular space flight mission, accurate prediction of solar cell performance in a space radiation environment is essential. The current methodology used to make such predictions requires extensive experimental data measured under both electron and proton irradiation. Due to the rising cost of accelerators and irradiation facilities, such extensive data sets are expensive to obtain. Moreover, with the rapid development of novel cell designs, the necessary data are often not available. Therefore, a method for predicting cell degradation based on limited data is needed. Such a method has been developed at the Naval Research Laboratory based on damage correlation using 'displacement damage dose' which is the product of the non-ionizing energy loss (NIEL) and the particle fluence. Displacement damage dose is a direct analog of the ionization dose used to correlate the effects of ionizing radiations. In this method, the performance of a solar cell in a complex radiation environment can be predicted from data on a single proton energy and two electron energies, or one proton energy, one electron energy, and Co(exp 60) gammas. This method has been used to accurately predict the extensive data set measured by Anspaugh on GaAs/Ge solar cells under a wide range of electron and proton energies. In this paper, the method is applied to InP solar cells using data measured under 1 MeV electron and 3 MeV proton irradiations, and the calculations are shown to agree well with the measured data. In addition to providing accurate damage predictions, this method also provides a basis for quantitative comparisons of the performance of different cell technologies. The performance of the present InP cells is compared to that published for GaAs/Ge cells. The results show InP to be inherently more resistant to displacement energy deposition than GaAs/Ge.

Walters, Robert J.↗
DOE OSTI2025

Using "AI Poincare" to analyze non-linear integrable optics

This study dives into the applicability of using automated discovery of conserved quantities in dynamical systems relevant to accelerator physics. Specifically, we explore the performance of AI Poincaré in analyzing numerical trajectory data obtained using the McMillan system of non-linear integrable optics. A comprehensive evaluation of the algorithm's performance is conducted through diverse methodologies. These include the analysis of the estimated number of conserved quantities embedded in a dataset and the deviation of interpolated points on the inferred manifold with respect to points in actually in the dataset. the investigation identifies an optimal range of perturbation distances where the underlying manifold extraction algorithm inside AI Poincaré exhibits optimal performance. Additionally, an improved neural network architecture is proposed based on the observed results. Finally, we apply the algorithm to preliminary experimental data from the Integrable Optics Test Accelerator at Fermilab to successfully infer the number of conserved quantities even in the presence of fast decoherence of the measured signal.

Osmanov, Lazare [Free U. Tbilisi]↗
NASA NTRS1986

Time-dependent coronal shock acceleration of energetic solar flare particles

A global time-dependent model is presented for the coronal and interplanetary shock acceleration and propagation of energetic solar flare particles. The calculations are carried out to help prove that coronal shock acceleration of solar flare particles is responsible for energetic solar flare event data gathered in interplanetary space. The model is based on the theory of diffusive shock acceleration, and requires particle speeds to be much greater than bulk velocities. Also, sufficient scattering must occur upstream and downstream of the shock for the particle scattering mean free path to be smaller than the characteristic scale lengths, which causes the same particles to encounter the shock repeatedly. A spherically symmetric shock wave is assumed, which leads to the same emission configuration for impulsively and monoenergetically emitted particles. Consideration is given to acceleration by compression at the shock front, adiabatic deceleration in the divergent downstream flow, the temporal evolution of the shock and the three-dimensional geometry of the corona. The model is used to generate normalized proton omnidirectional distributions at 1 AU and at the shock front. The spectral exhibit trends similar to those in observational data, especially proton acceleration times and the proton distribution profiles at 1 AU.

Lee, M. A.↗
DOE OSTI2021

PACT Data Management Plan (V.1.0)

The Perovskite PV Accelerator for Commercial Technology (PACT) is an independent validation center for the evaluation of perovskite PV technologies and their bankability. The center is led by Sandia National Laboratories and the National Renewable Energy Laboratory (NREL) and includes as part of its team Los Alamos National Laboratory (LANL), CFV Labs, Black and Veatch (B&V), and the Electric Power Research Institute (EPRI). The goals of the center are to: Develop and improve indoor and outdoor performance characterization methods, Develop and validate accelerated qualification testing for early failures (5-10 years), Research degradation and failure modes, Validate outdoor performance, and Provide bankability services to US perovskite PV (PSC) industry. The importance of data and data management to the success and outcomes of the PACT center is paramount. This report describes how data will be managed and protected by PACT and identifies important data management principles that will guide our approach.

14 SOLAR ENERGY↗
DOE OSTI2020

Concurrent Relaxation through Accelerated Deep Learning

CRADL captures performance metrics of machine learning algorithms operating on mesh data from multiphysics codes This proxy application is a tool to explore scalability of inference on HPC platforms, and also gather performance metrics for inference on new machine learning specific hardware. CRADL is designed to give users as fine a control as possible over an inference simulation. Users may select the number of cycles, amount of data, and batch size to pass to the accelerator of choice. Additionally the user may select a number of performance optimization libraries and flags. CRADL comes packaged with a repository of anonymized multi-physics simulation data, as well as a pretrained model for inference. The code allows a user to load their own pre-trained model and data if they wish. The code can operate in multiple parallelization schemes, with performance enhancing options such as half-precision libraries, PyTorch benchmarking, and pinned memory with non-blocking data transfers.

Zieb, KristoferJ.↗
DOE OSTI2023

Carbon Storage Planning Framework Dashboard

The Carbon Storage Planning Framework dashboard (beta version) provides easy access to explore, query, and evaluate multiple data layers to support and accelerate carbon storage resource and feasibility assessments and planning efforts. The interactive dashboard currently contains a range of authoritative datasets associated with geologic, technical, social, and environmental factors. The data sets can be filtered geographically for an area of interest to update statistics and charts within the dashboard. Terms of Use: NETL is sharing this beta/prototype tool with the request that users will provide feedback to NETL about the function and content of the dashboard, alerting NETL to any bugs or providing suggestions for additional resources to help mature the platform.

CCS,EDX4CCS,carbon storage,dashboard↗
DOE OSTI2023

Nb3Sn Coating of Twin Axis Cavity and Other Complex SRF Cavity Structures

In the field of Accelerator Science, for the low cost and increased quality factor, thin films coated niobium cavities are used in the modern SRF research. Within the potential substances, Nb3Sn has shown higher critical temperature than niobium. Here the tin vapor diffusion method is used as the preferred technique to coat niobium cavities. So far, only elliptical cavities have been coated with Nb3Sn and this technique has not yet been applied to cavities with complex geometries, which are also helpful in the accelerator science field. The Half-wave resonator could provide us data across frequencies of interest for particle accelerators world wide. Similarly the Twin axis cavity proposed for Energy Recovary Linac (ERL) applications could benefit from Nb3Sn coating. But with their advanced geometries, increased area, more number of ports and hard to reach areas, a different coating approach is needed to provide a uniform coating of Nb3Sn. We used twin axis cavity to optimize the coating technique and followed a low temperature annealing to further improvement of the thin film quality by low temperature annealing as a post coating method. With these we could expand the current coating system at JLab to coat complex cavity models

Tiskumara, Jayendrika↗
DOE OSTI2022

On the integration of molecular dynamics, data science, and experiments for studying solvent effects on catalysis

Computational workflows that combine molecular dynamics (MD) simulations and emerging data-centric (DC) methods can accelerate the screening and analysis of solvent systems experimentally and computationally. Here, MD simulations provide atomic positions and velocities of reactant, solvent, and catalyst materials that can be manipulated into data representations that in turn can be used by DC techniques to conduct predictive modeling, feature extraction, and experimental design. For liquid-phase catalytic applications, emerging DC techniques such as Convolutional and Graph Neural Networks (CNN/GNN), Topological Data Analysis (TDA), and Active Learning (AL) can leverage MD and experimental data to quickly predict solvent effects on reaction outcomes. For instance, in recent studies, 3D solvent environments obtained with MD have been exploited by CNNs to predict experimental reaction rates for homogeneous acid-catalyzed lignocellulosic processes. In this perspective, we discuss basic principles of DC methods and how these can be combined with MD to enable high-throughput screening of solvent selection for diverse catalysis applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1992

Multispectral observations of the Jovian aurora

This paper presents and analyzes images of the Jovian aurora gathered by the Hubble Space Telescope Faint Object Camera (FOC) and the ROSAT Position Sensitive Proportional Counter (PSPC) to determine the function of energetic heavy ion precipitation in the inner magnetosphere and electron acceleration in the outer magnetosphere. Hubble data includes hydrogen auroral spectra and reduced images of Jupiter's north and south poles. One important result is that acceleration of electrons may be largely responsible for the discrete auroral emission features seen in the data set. ROSAT PSPC data presented includes a photon energy spectrum. A two line emission model is shown to produce the best fit to the data. The production of these emission lines occurs as a result of recombination lines that are produced from the slowing of the energetic ion beam as it enters the Jupiter upper atmosphere. It is noted that the observed energetic ion precipitation does not contain sufficient power to explain the observed ultraviolet aurora; it is therefore concluded that both electrons and ions play a role in the Jupiter auroral emissions, but that the bulk of the ultraviolet emissions comes from electron processes.

Source record↗
NASA NTRS2011

Functional Data Analysis of Spaceflight-Induced Changes in Coordination and Phase in Head Pitch Acceleration During Treadmill Walking

Astronauts returning from spaceflight experience neurovestibular disturbances during head movements and attempt to mitigate them by limiting head motion. Analyses to date of the head movements made during walking have concentrated on amplitude and variability measures extracted from ensemble averages of individual gait cycles. Phase shifts within each gait cycle can be determined by functional data analysis through the computation of time-warping functions. Large, localized variations in the timing of peaks in head kinematics may indicate changes in coordination. The purpose of this study was to determine timing changes in head pitch acceleration of astronauts during treadmill walking before and after flight. Six astronauts (5M/1F; age = 43.5+/-6.4yr) participated in the study. Subjects walked at 1.8 m/sec (4 mph) on a motorized treadmill while reading optotypes displayed on a computer screen 4 m in front of their eyes. Three-dimensional motion of the subject s head was recorded with an Inertial Measurement Unit (IMU) device. Data were recorded twice before flight and four times after landing. The head pitch acceleration was calculated by taking the time derivative of the pitch velocity data from the IMU. Data for each session with each subject were time-normalized into gait cycles, then registered to align significant features and create a mean curve. The mean curves of each postflight session for each subject were re-registered based on their preflight mean curve to create time-warping functions. The root mean squares (RMS) of these warping functions were calculated to assess the deviation of head pitch acceleration mean curves in each postflight session from the preflight mean curve. After landing, most crewmembers exhibited localized shifts within their head pitch acceleration regimes, with the greatest deviations in RMS occurring on landing day or 1 day after landing. These results show that the alteration of head pitch coordination due to spaceflight may be assessed using an analysis of time-warping functions.

Miller, Christopher↗
NASA NTRSDate not supplied

GL4U: Training the next generation of bioinformaticians, one omics datatype at a time

Spaceflight modifies gene expression in every organism examined to date, including humans. Understanding how these gene expression changes affect physiology is crucial for the development of countermeasures to enable long-duration manned missions. NASA’s GeneLab project provides researchers open access to multi-omics data, including genetic and gene expression data, from spaceflight experiments that can be mined to understand the effects of spaceflight on biological systems. To ensure new knowledge generation through data re-use, it is important to maximize the number of scientists who utilize GeneLab data. Training students on the GeneLab platform is the best way to create long-term adopters of this NASA database and its tools. Turning students into future instructors and advocates will also accelerate the dissemination of these data and tools to the broader scientific community. Therefore, in collaboration with the GeneLab Educational Working Group (EWG), GeneLab has created GeneLab for Colleges and Universities (GL4U). GL4U provides space biology-relevant training in bioinformatics to the next generation of scientists through direct and indirect approaches. The GeneLab team plans to host two annual data processing bootcamps, one for college-level students (direct) and one for college educators (indirect – training of trainers), in which participants learn to analyze GeneLab’s space-relevant omics data. During the bootcamp, educators will receive materials and training to enable them to run the bootcamp at their home institutions or alternatively to adapt the content to implement within existing courses, thereby extending the reach of this initiative. The GL4U direct training pilot program was conducted in June 2021 in collaboration with USRA and San Jose State University (SJSU). During the pilot, SJSU students participated in a week-long bootcamp consisting of space biology-specific lectures and hands-on instruction using Jupyter Notebooks to analyze RNA sequence data. This pilot demonstrates the capacity of GL4U for training young scientists and encouraging data re-use.

Jonathan Matthew Galazka↗
DOE OSTI2021

Binary Complex Neural Network Acceleration on FPGA

Being able to learn from complex data with phase information is imperative for many signal processing applications. Today’s real-valued deep neural networks (DNNs) have shown efficiency in latent information analysis but fall short when applied to the complex domain. Deep complex networks (DCN) , in contrast, can learn from complex data, but have high computational costs; therefore, they cannot satisfy the instant decision making requirements of many deployable systems dealing with short observations or short signal bursts. Recent, Binarized Complex Neural Network (BCNN), which integrates DCNs with binarized neural networks (BNN), shows great potential in classifying complex data in real-time. In this paper, we propose a structural pruning based accelerator of BCNN, which is able to provide more than 5000 frames/s inference throughput on edge devices. The high performance comes from both the algorithm and hardware sides. On the algorithm side, we conduct structural pruning to the original BCNN models and obtain 20 × pruning rates with negligible accuracy loss; on the hardware side, we propose a novel 2D convolution operation accelerator for the binary complex neural network. Experimental results show that the proposed design works with over 90% utilization and is able to achieve the inference throughput of 5882 frames/s and 4938 frames/s for complex NIN-Net and ResNet-18 using CIFAR-10 dataset and Alveo U280 Board.

Peng, Hongwu↗
NASA NTRS2025

Subsonic Ultra Green Aircraft Research: Phase V – Buffet Test Report

This test report summarizes work performed by the Boeing Subsonic Ultra-Green Aircraft Research (SUGAR) team in the Phase V Transonic Truss-Braced Wing contract task. The task was awarded in September 2020, and ended at the end of September 2022. As a part of the SUGAR Phase V contract task, Boeing developed a wind tunnel test plan, model requirements, then fabricated and conducted a dedicated transonic buffet wind tunnel test. The test focused on the investigation of buffet onset, and the ability to accurately predict buffet onset for the TTBW configuration. This report summarizes the results and post-test analysis of the 9% scale, semispan, Transonic Truss-Braced Wing (TTBW) transonic buffet model tested at the NASA Ames Research Center Unitary Plan Wind Tunnel (UPWT) 11-Foot Transonic Wind Tunnel (11-Ft TWT) facility located at Moffett Field, CA. It was tested from January 24, 2022, through February 18, 2022. The wind tunnel test was successful in capturing buffet onset at the model design dynamic pressure. Multiple configurations were tested starting in the wing-body-strut configuration and ending with the full configuration including wing-body-strut-nacelle/pylon, and flap hinge. The test also measured the effect of control surface deflections (ailerons and spoilers), as well as the effect of an outboard strut flap. Steady data collected during the test included standard force and moment measurements, as well as wing, strut, nacelle, and body (fuselage) static pressures. These data were collected in a standard pitch-pause mode. Unsteady data captured in the test, collected in continuous pitch mode, included wing and strut dynamic pressures, accelerations, and strains. According to test data, previous concerns regarding critical buffet onset on the strut (at low vehicle lift coefficient) and in the wing-strut channel have been mitigated. Buffet onset on the TTBW appears to follow conventional wing-induced buffet onset mechanisms. However, the critical station where buffet onset first occurs has moved inboard to the wing-strut juncture span location (55-60% span) from the typical ~70% span location. Test data obtained by unsteady pressure transducers provided a good match to expected buffet onset modes. An assessment of different tools and methodologies for predicting buffet onset was conducted. Reasonable agreement was found for buffet boundary predictions between most of the methods examined when using a forward trip location, with the greatest discrepancies from the pitching moment break and trailing edge pressure divergence methods. When an aft trip location was used the buffet boundary predictions diverged more significantly from unsteady pressure measurements. In addition, good agreement between the buffet onset trends were found when the Reynolds number, configuration, or spanload was changed.

strut↗
DOE OSTI2020

Accelerate M-TIP on GPUs and deploy to Summit and NERSC-9 (against simulated data) WBS 2.2.4.05 ExaFEL, Milestone ADSE13-199

We evaluated the orientation matching step in the M-TIP SPI workflow for potential offloading to accelerators. We ported the code to GPUs, benchmarked it, optimized and down-selected the best versions. The accelerated version of the orientation matching code that was developed at LANL (LANL GPU v3) is 34-55X faster than sequential, 2.4-4.9X faster than the fastest OpenMP open source version we found (FAISS OpenMP) and 1.5-4X faster than the fastest GPU open source version we found (FAISS GPU). Summit single-node GPU versions were somewhat faster than Cori GPU. Image size plays a role; mid-range image sizes take more time. The LANL CUDA multi-node, multi-GPU implementation shows mostly linear strong scaling. I/O also plays a large role; splitting data into parts improves read time and burst buffers dramatically improve read times. This work will be integrated into the M-TIP workflow as part of the next milestone ADSE13-193.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1985

Particle acceleration due to shocks in the interplanetary field: High time resolution data and simulation results

Data were examined from two experiments aboard the Explorer 50 (IMP 8) spacecraft. The Johns Hopkins University/Applied Lab Charged Particle Measurement Experiment (CPME) provides 10.12 second resolution ion and electron count rates as well as 5.5 minute or longer averages of the same, with data sampled in the ecliptic plane. The high time resolution of the data allows for an explicit, point by point, merging of the magnetic field and particle data and thus a close examination of the pre- and post-shock conditions and particle fluxes associated with large angle oblique shocks in the interplanetary field. A computer simulation has been developed wherein sample particle trajectories, taken from observed fluxes, are allowed to interact with a planar shock either forward or backward in time. One event, the 1974 Day 312 shock, is examined in detail.

Kessel, R. L.↗