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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 1,009 records · Page 56
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

A User-Friendly GUI Tool for Automated Microstructural Analysis of Fiber-Reinforced Composites and Porous Structures

Understanding and quantifying microstructural features such as fiber orientation and porosity is critical for predicting the mechanical behavior and performance of fiber-reinforced polymer composites. Traditional manual analysis is time-consuming, subjective, and unsuitable for high-throughput datasets. We present a graphical user interface (GUI) application that automates the analysis of microscopy images to extract key microstructural metrics, including fiber orientation tensors, fiber orientation distribution, porosity and pore size distribution. The app integrates multiple image segmentation techniques including global and local thresholding, clustering, and region-based approaches, offering flexibility for different types of image qualities and features. Users can load microstructural images, select regions of interest and segmentation techniques tailored to their image dataset. It also addresses a critical challenge in fiber orientation analysis: the ambiguities caused by touching, overlapping, or partially cut fibers. It supports autorun examples for standardized workflows, enabling reproducible analysis and facilitating training and benchmarking. This tool significantly reduces manual intervention, enhances consistency, and accelerates data generation for structure–property modeling, process optimization, and digital materials research. The tool is intended for use by materials scientists, engineers, and researchers engaged in composite characterization, quality control, and machine learning-based microstructural studies.

Chawla, Komal [ORNL] (ORCID:0000000190327565)↗
DOE OSTI2023

Auto Stop-Start Fuel Consumption Benefits

With increasingly stringent regulations mandating the improvement of vehicle fuel economy, automotive manufacturers face growing pressure to develop and implement technologies that improve overall system efficiency. One such technology is an automatic (auto) stop-start feature. Auto stop-start reduces idle time and reduces fuel use by temporarily shutting the engine off when the vehicle comes to a stop and automatically re-starting it when the brake is released, or the accelerator is pressed. As mandated by the U.S. Congress, the U.S. Environmental Protection Agency (EPA) is required to keep the public informed about fuel saving practices. This is done, in partnership with the U.S. Department of Energy (DOE), through the fueleconomy.gov website. The “Fuel-Saving Technologies” and “Gas Mileage Tips” sections of the website are focused on helping the public make informed purchasing decisions and encouraging fuel-saving driving habits. Here, in order to provide users with accurate information about the auto stop-start feature, experiments were conducted to determine its fuel economy effect. Four vehicles were tested both with and without the feature enabled under three test cycles: the Federal Test Procedure (FTP) city fuel economy test, the US06 high acceleration aggressive driving schedule that is often identified as the “Supplemental FTP” driving schedule, and the EPA New York City Cycle (NYCC). The results were compared to measure the fuel economy and consumption effects of using the auto stop-start feature. It was found that the fuel economy improvement varied significantly between drive cycles depending on the amount and percentage of idle time during the test. The largest fuel economy improvements were 7.27% and 26.4% for the FTP and NYCC, respectively.

33 ADVANCED PROPULSION SYSTEMS↗
NASA NTRS1989

Relativistic neutrons in active galactic nuclei

The acceleration of protons to relativistic energies in active galactic nuclei leads to the creation of relativistic neutrons which escape from the central engine. The neutrons decay at distances of up to 1-100 pc, depositing their energies and momenta in situ. Energy deposition by decaying neutrons may inhibit spherical accretion and drive a wind, which could be responsible for the velocity fields in emission-line regions and the outflow of broad absorption line systems. Enhanced pressure in the neutron decay region may also help to confine emission line clouds. A fraction of the relativistic proton energy is radiated in gamma-rays with energies which may be as large as about 100,000 GeV.

Sikora, Marek↗
NASA NTRS1993

The Space Station Freedom microgravity environment

The SSF microgravity environment is discussed focusing on requirements derived from initial specifications proposed by the NASA Office of Space Science and Applications and on microgravity assessment methods including quasi-steady, structural dynamic, and vibroacoustic methods. Preliminary results indicate that the flight dynamics of the vehicle meet the requirements for both scientific and engineering communities, but that a number of vibroacoustic disturbance sources violate the criteria. The assessment updates along with planned on-orbit acceleration measurements and crew disturbance characterizations are being carried out to clearly define and understand the acceleration environment.

Del Basso, Steve↗
NASA NTRS2001

Training to Enhance Design Team Performance: A Cure for Tunnel Vision

Design Team performance is a function of the quality and degree of academic training and the cumulative, learned experience of the individual members of the team. Teamwork, leadership, and communications certainly are factors that affect the measure of the performance of the team, but they are not addressed here. This paper focuses on accelerating the learned experience of team members and describes an organizational approach that can significantly increase the effective experience level for any engineering design team. The performance measure of the whole team can be increased by increasing the engineering disciplines' cross awareness of each other and by familiarizing them with their affect at the system level. Discipline engineers know their own discipline well, but typically are not intimately familiar with their technical interaction with and dependencies on all the other disciplines of engineering. These dependencies are design integration functions and are worked out well by the discipline engineers as long as they are involved in the design of types of systems that they have experience with.

Parker, James W.↗
NASA NTRS2007

Computational Modeling Develops Ultra-Hard Steel

Glenn Research Center's Mechanical Components Branch developed a spiral bevel or face gear test rig for testing thermal behavior, surface fatigue, strain, vibration, and noise; a full-scale, 500-horsepower helicopter main-rotor transmission testing stand; a gear rig that allows fundamental studies of the dynamic behavior of gear systems and gear noise; and a high-speed helical gear test for analyzing thermal behavior for rotorcraft. The test rig provides accelerated fatigue life testing for standard spur gears at speeds of up to 10,000 rotations per minute. The test rig enables engineers to investigate the effects of materials, heat treat, shot peen, lubricants, and other factors on the gear's performance. QuesTek Innovations LLC, based in Evanston, Illinois, recently developed a carburized, martensitic gear steel with an ultra-hard case using its computational design methodology, but needed to verify surface fatigue, lifecycle performance, and overall reliability. The Battelle Memorial Institute introduced the company to researchers at Glenn's Mechanical Components Branch and facilitated a partnership allowing researchers at the NASA Center to conduct spur gear fatigue testing for the company. Testing revealed that QuesTek's gear steel outperforms the current state-of-the-art alloys used for aviation gears in contact fatigue by almost 300 percent. With the confidence and credibility provided by the NASA testing, QuesTek is commercializing two new steel alloys. Uses for this new class of steel are limitless in areas that demand exceptional strength for high throughput applications.

Source record↗
NASA NTRS2010

JANNAF Lessons Learned Panel: Selected Saturn V History

Pogo occurs when the natural frequency of a propellant feed line comes close to a readily excited rocket longitudinal structural vibration natural frequency. Maximum Pogo response corresponds to close tuning of the structural and hydraulic frequencies. On Saturn V, accelerations up to 17 g's (Zero To Peak) at the Launch Vehicle/Payload Interface and up to 34 g's at an Engine have been observed. Nicknamed Pogo because it causes the Rocket to stretch and compress like a Pogo stick. First recognized with the Titan II in 1962, Pogo remains a prime consideration in design of launch vehicles today

Urquhart, Skip↗
DOE OSTI2018

Application of Geant4 Monte Carlo simulation in dose calculations for small radiosurgical fields

The Geant4 toolkit was used to develop a Monte Carlo (MC)-based engine for accurate dose calculations in small radiation field sizes. The Geant4 toolkit (version 10.1.p02) was used to simulate 6-MV photon beam of a Varian2100C linear accelerator that is being used for stereotactic radiosurgery (SRS) treatment with small radiation fields. Geometric models of 3 in-house designed radiosurgical divergent cones, with the diameters of their projections at the isocenter being 10, 20, and 30 mm, were simulated. The accuracy of the MC simulation technique was examined by reproducing several different simulated dosimetric parameters of the primary beams with the experimental data. The dose distributions are first checked for single beams for each cone, then standard multiple field (SMF) techniques are applied. A sample set of DICOM files from computed tomography (CT) scan imaging of a patient's head was converted to the Geant4 geometry format to implement MC-based engine for a clinical test. To validate the accuracy of the MC-based calculations for SMF arrangements, the isodose lines from MC simulation in water phantom were compared with the measured isodose lines using EBT3 Gafchromic film in Solid Water phantoms. Agreements between measured and simulated depth dose values and beam profiles for SRS cones were generally within 2%/2 mm. For output factors, the largest discrepancy was observed for 10 mm SRS cone, which was 1.7%. For SMF techniques, in SRS cones, the MC simulation and EBT3 Gafchromic film dosimetry were in acceptable agreement (5%/5 mm). Excellent agreement between the results of the MC-based and measured dose values for both single and SMF techniques in SRS cones indicates the ability of the Geant4 toolkit to be applied as the platform for treatment planning of advanced radiotherapy techniques.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2021

Comparing total cost of ownership of battery electric vehicles and internal combustion engine vehicles

The technological advance of electrochemical energy storage and the electric powertrain has led to rapid growth in the deployment of electric vehicles. The high cost and the added weight of the batteries have limited the size (energy storage capacity) and, therefore, the driving range of these vehicles. However, consumers are steadily purchasing these vehicles because of the fast acceleration, quiet ride, and high energy efficiency. The higher pack-to-wheel efficiency and the lower energy cost per mile, as well as the lower expense for maintenance and repair, translate to operating savings over conventional vehicles. Here we compare battery electric vehicles with internal combustion engine vehicles based on the total cost of ownership. It is seen that the higher initial cost of electric vehicles can be recovered in as little as 5 years. This is especially true for electric vehicles with shorter driving ranges. Specifically, a vehicle with an electric driving range under 200 miles may achieve cost parity with an equivalent internal combustion engine vehicle in 8 years or less.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2025

Report on the Integration of Experimental and Modeling Data for Initial Equivalence Study of Mechanical Performance in Irradiated LPBF 316 Stainless Steel

To ensure the rapid development, deployment, and use of advanced nuclear technologies, faster qualification approaches are needed. Typically, the primary pathway uses traditional data packages consistent with the American Society of Mechanical Engineers Boiler and Pressure Vessel Code, which does not consider the environmental effects the material will experience such as corrosion and radiation damage. Examining radiation effects requires a significant amount of space in US facilities at the Advanced Test Reactor and the High Flux Isotope Reactor (HFIR) and suffers from natural gradients in temperature and neutron flux profiles. Ion irradiation may enable rapid assessment of radiation-induced damage to a material and is proposed as part of an accelerated materials qualification framework through the Advanced Materials and Manufacturing Technologies program. To enhance the utility of ion irradiation as an examination tool, this report provides the initial assessment of engineering-relevant properties of microstructures produced from ion irradiation in the near-surface volume. Nanoindentation, Vickers hardness, and known tensile properties were brought together with simple mathematical models and experimental data for an initial equivalence study of the mechanical performance of irradiated laser powder bed fusion (LPBF) 316 stainless steels across length scales. Direct observation of the calculated ion irradiation yield stress and measured neutron irradiation yield stress at 2 dpa showed that both datasets exhibit the same trend with irradiation temperature and overlap within an acceptable band of stress values. Ion irradiations at 10 dpa serve as a prediction of properties to compare to postirradiation examination of HFIR-irradiated LPBF 316H further in the program. This work is a significant demonstration of the Licensing Approach with Ions and Neutrons, which uses ion irradiations to generate mechanical property information more rapidly than through neutron irradiations.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Deep reinforcement learning for dynamic control of fuel injection timing in multi-pulse compression ignition engines

Conventional compression-ignition (CI) engines have long offered high thermal efficiencies and torque across a wide range of loads, but often require extensive exhaust gas treatment that decreases efficiency to meet ever-increasing emissions regulations. One strategy to decrease emissions is to split the fuel injection into a series of smaller injections. In this paper, we explore a new way of discovering optimal control strategies for the next generation of CI engines using deep reinforcement learning (DRL). We outline a DRL procedure to maximize the weighted reward of engine work while minimizing end-of-cycle NO x emissions. Through the procedure outlined in this paper, we show that the DRL agent is able to reduce NO x emissions threefold while only decreasing network by 2%. We demonstrate the use of transfer learning (TL) across hierarchies of physical models to accelerate the learning process, making this approach feasible for a range of control problems within this space. This paper presents a framework and demonstration for using DRL to design control systems in technology areas such as multi-pulse engine control where a hierarchy of models combined with multi-objective rewards are used for optimal operation.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2023

Neural message-passing for objective-based uncertainty quantification and optimal experimental design

Various real-world scientific applications involve the mathematical modeling of complex uncertain systems with numerous unknown parameters. Accurate parameter estimation is often practically infeasible in such systems, as the available training data may be insufficient and the cost of acquiring additional data may be high. In such cases, based on a Bayesian paradigm, we can design robust operators retaining the best overall performance across all possible models and design optimal experiments that can effectively reduce uncertainty to enhance the performance of such operators maximally. While objective-based uncertainty quantification (objective-UQ) based on MOCU (mean objective cost of uncertainty) provides an effective means for quantifying uncertainty in complex systems, the high computational cost of estimating MOCU has been a challenge in applying it to real-world scientific/engineering problems. In this work, we propose a novel scheme to reduce the computational cost for objective-UQ via MOCU based on a data-driven approach. We adopt a neural message-passing model for surrogate modeling, incorporating a novel axiomatic constraint loss that penalizes an increase in the estimated system uncertainty. As an illustrative example, we consider the optimal experimental design (OED) problem for uncertain Kuramoto models, where the goal is to predict the experiments that can most effectively enhance robust synchronization performance through uncertainty reduction. We show that our proposed approach can accelerate MOCU-based OED by four to five orders of magnitude, without any visible performance loss compared to the state-of-the-art. The proposed approach applies to general OED tasks, beyond the Kuramoto model.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

An MLIR-based Compiler Flow for System-Level Design and Hardware Acceleration

The generation of custom hardware accelerators for applications implemented within high-level productive programming frameworks requires considerable manual effort. To automate this process, we introduce \sodaopt, a compiler tool that extends the MLIR infrastructure. \sodaopt automatically searches, outlines, tiles, and pre-optimizes relevant code regions to generate high-quality accelerators through high-level synthesis. \sodaopt can support any high-level programming framework and domain-specific language that interface with the MLIR infrastructure. By leveraging MLIR, \sodaopt solves compiler optimization problems with specialized abstractions. Backend synthesis tools connect to \sodaopt through progressive intermediate representation lowerings. \sodaopt interfaces to a design space exploration engine to identify the combination of compiler optimization passes and options that provides high-performance generated designs for different backends and targets. We demonstrate the practical applicability of the compilation flow by exploring the automatic generation of accelerators for deep neural networks operators outlined at arbitrary granularity and by combining outlining with tiling on large convolution layers. Experimental results with kernels from the PolyBench benchmark show that \sodaopt high-level optimizations improve execution delays of synthesized accelerators up to 60x. We also show that for the selected kernels, our solution outperforms the current of state-of-the art in more than 70% of the benchmarks and provides better average speedup in 55% of them.

Bohm Agostini, Nicolas↗
DOE OSTI2024

Self-similar Reynolds-averaged mechanical–scalar turbulence models for Rayleigh–Taylor mixing induced by power-law accelerations in the small Atwood number limit

Analytical self-similar solutions to two-, three-, and four-equation Reynolds-averaged mechanical–scalar turbulence models describing turbulent Rayleigh–Taylor mixing driven by a temporal power-law acceleration are derived in the small Atwood number (Boussinesq) limit. The solutions generalize those previously derived for constant acceleration Rayleigh–Taylor mixing for models based on the turbulent kinetic energy K and its dissipation rate ε, together with the scalar variance S and its dissipation rate χ [O. Schilling, “Self-similar Reynolds-averaged mechanical–scalar turbulence models for Rayleigh–Taylor, Richtmyer–Meshkov, and Kelvin–Helmholtz instability-induced mixing in the small Atwood number limit,” Phys. Fluids 33, 085129 (2021)]. The turbulent fields are expressed in terms of the model coefficients and power-law exponent, with their temporal power-law scalings obtained by requiring that the self-similar equations are explicitly time-independent. Mixing layer growth parameters and other physical observables are obtained explicitly as functions of the model coefficients and parameterized by the exponent of the power-law acceleration. Values for physical observables in the constant acceleration case are used to calibrate the two-, three-, and four-equation models, such that the self-similar solutions are consistent with experimental and numerical simulation data corresponding to a canonical (i.e., constant acceleration) Rayleigh–Taylor turbulent flow. The calibrated four-equation model is then used to numerically reconstruct the mean and turbulent fields, and turbulent equation budgets across the mixing layer for several values of the power-law exponent. Finally, the reference solutions derived here can be used to understand the model predictions for strongly accelerated or decelerated Rayleigh–Taylor mixing in the large Reynolds number limit.

42 ENGINEERING↗
DOE OSTI2020

Fabricated ecosystem workshop: bridging laboratory to field science. Workshop report.

Lawrence Berkeley National Laboratory (Berkeley Lab) scientists held a workshop at the DOE BER Genomic Sciences PI meeting on the use of Fabricated Ecosystems in Washington D.C. on February 25th, 2020. Ecosystem fabrication is an approach to creating controlled microbial, soil and plant ecologies within a laboratory setting that enable discovery and dissection of environmental variables, activities, and interactions. At Berkeley Lab, we are developing two systems which span spatial and temporal scales — the EcoFAB and the EcoPOD. The participants of the workshop discussed the potential applications and challenges of using fabricated ecosystems as tools to tackle BER-relevant scientific questions. Specifically, they identified (1) research challenges that would benefit from ready access to this infrastructure (2) identified and prioritized technical challenges that currently limit these systems and (3) discussed how to use them to bridge the gap between lab and field research. To ensure that the fabricated ecosystems , in particular the larger-scale EcoPODs, are of use to as much of the BER community as possible, the workshop participants made the following recommendations: 1. Produce publicly available datasets for a set of control variables. Use for benchmarking, and assessing reproducibility between systems. 2. Implement data standards. 3. Develop/leverage nano/micro sensors and in situ root imaging. 4. Encourage the development of interdisciplinary teams to develop EcoPOD experiments. 5. Develop fabricated ecosystems with size and complexity that sits between the EcoFAB and EcoPOD to accelerate use and access.

42 ENGINEERING↗
NASA NTRS1963

THE ELECTRON-BOMBARDMENT ION ROCKET

Proposed electron bombardment ion rocket, discussing ion chamber, magnetic field, cathode, accelerator and neutralizer in terms of spacecraft power requirements

PROPULSION CONFIGURATION↗
NASA NTRS1950

Free-flight Performance of 16-inch-diameter Supersonic Ram-jet Units II : Five Units Designed for Combustion-chamber-inlet Mach Number of 0.16 at Free-stream Mach Number of 1.60 (units B-1, B-2, B-3, B-4, and B-5) /c Wesley E. Messing and Scott H. S

Free-flight performance of five 16-inch-diameter ram-jet units was determined over range of free-stream Mach numbers of 0.50 to 1.86 and gas total-temperature ratios between 1.0 and 6.1 Time histories of performance data are presented for each unit. Correlations illustrate effect of free-stream Mach number and gas total-temperature ratio on diffuser total-pressure recovery, net-thrust coefficient, and external drag coefficient. One unit had smooth steady burning throughout the entire flight and encountered a maximum free-stream Mach number of 1.86 with a net acceleration of approximately 4.2 g's.

COMBUSTION - RAM-JET ENGINES↗