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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 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Aeroacoustic Measurements from the Aerodynamic and Acoustic Rotorprop Test (AART) in the National Full-Scale Aerodynamics Complex (NFAC) 40- by 80-Foot Wind Tunnel

Unmanned Aerial Vehicle (UAV) designs typically have aerodynamic configurations that result in complex aerodynamic and acoustic conditions, such as wing and propeller interaction. In response, the Aerodynamic and Acoustic Rotorprop Test (AART) Program was implemented, a primary objective of which was to determine the aerodynamics and acoustics related to an auxiliary propulsor mounted behind an isolated wing in the National Full-Scale Aerodynamics Complex (NFAC) 40-by 80-Foot Wind Tunnel. Three configurations (no wing, half wing, and full wing) were tested, with conditions including variation of the propeller speed, wind tunnel Mach number, and Yaw. The acoustic set up, processing, and analysis are discussed along with the known issues for this complex data set. The interaction of upstream bodies and the resulting substantial increase in acoustic emissions are discussed in detail.

Propeller↗
NASA NTRS2001

Optimization of Training Sets for Neural-Net Processing of Characteristic Patterns from Vibrating Solids

Artificial neural networks have been used for a number of years to process holography-generated characteristic patterns of vibrating structures. This technology depends critically on the selection and the conditioning of the training sets. A scaling operation called folding is discussed for conditioning training sets optimally for training feed-forward neural networks to process characteristic fringe patterns. Folding allows feed-forward nets to be trained easily to detect damage-induced vibration-displacement-distribution changes as small as 10 nm. A specific application to aerospace of neural-net processing of characteristic patterns is presented to motivate the conditioning and optimization effort.

Decker, Arthur J.↗
NASA NTRS2006

Optimization of Training Sets For Neural-Net Processing of Characteristic Patterns From Vibrating Solids

An artificial neural network is disclosed that processes holography generated characteristic pattern of vibrating structures along with finite-element models. The present invention provides for a folding operation for conditioning training sets for optimally training forward-neural networks to process characteristic fringe pattern. The folding pattern increases the sensitivity of the feed-forward network for detecting changes in the characteristic pattern The folding routine manipulates input pixels so as to be scaled according to the location in an intensity range rather than the position in the characteristic pattern.

Decker, Arthur J.↗
DOE OSTI2025

A quality-agnostic combinatoric cost estimation model for large-format directed energy deposition metal additive manufacturing

Directed energy deposition (DED) additive manufacturing (AM) processes are amenable to synergistic combination into multi-process AM systems due to similar requirements for automation and energy sources. This work analyzes the economic performance of such DED AM systems from a quality-agnostic combinatoric standpoint with a model that calculates lowest-cost system combinations based on part geometry and process performance metrics. Common DED AM systems research focuses on a single process and does not consider the process, system, and application in the context of all possible system combinations (e.g., the combined set of process selection(s), motion system(s), and process hardware), leading to limited applicability of the resulting DED AM systems to cost-sensitive components such as those found in energy generation applications. The model developed herein incorporates the capital, material, and energy costs associated with DED AM system combinations into a predictive tool for estimating part and system cost, the output of which is intended to guide deployment of finite research and development resources towards DED AM system combinations with the lowest costs and greatest likelihood of economic impact. The DED AM systems identified by this framework may enable domestic production of the large conventionally cast and forged components necessary for energy generation.

Shanafield, Alexandra [ORNL]↗
DOE OSTI2022

Scaled Vecchia Approximation for Fast Computer-Model Emulation

Many scientific phenomena are studied using computer experiments consisting of multiple runs of a computer model while varying the input settings. Gaussian processes (GPs) are a popular tool for the analysis of computer experiments, enabling interpolation between input settings, but direct GP inference is computationally infeasible for large datasets. We adapt and extend a powerful class of GP methods from spatial statistics to enable the scalable analysis and emulation of large computer experiments. Specifically, we apply Vecchia’s ordered conditional approximation in a transformed input space, with each input scaled according to how strongly it relates to the computer-model response. The scaling is learned from the data by estimating parameters in the GP covariance function using Fisher scoring. Our methods are highly scalable, enabling estimation, joint prediction, and simulation in near-linear time in the number of model runs. In several numerical examples, our approach substantially outperformed existing methods.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Lightweight Metal Stamping Optimization Enabled by Artificial Intelligence

Successfully manufacturing an automotive body structure made via the sheet metal stamping process depends upon simultaneous consideration of component design, tooling design, stamping process control, and material properties. In many cases, introducing lightweight sheet materials (e.g., aluminum alloys, magnesium alloys, advanced high strength steels) holds the potential to significantly reduce vehicle weight, but challenges the stamping process by introducing materials with inherently less ductility. Successful and repeatable applications require co-developing the stamping process controls with the varying material properties, including formability. During the stamping process, as soon as the forming limit of the sheet is exceeded, the material shows localized necking which quickly leads to splits. Controlling process variability to avoid these material splits will enable deployment of less formable, lighter, and stronger materials for stamped automotive components. A typical optimization procedure for manufacturing requires an iterative process involving parameter setting, execution of computational simulations, and modifying the parameters. The entire process demands substantial computational time, making it impractical for real-time feedback towards rapid corrective actions required for in-line control for running production processes. To overcome this challenge, artificial intelligence (AI) can be leveraged to determine optimal manufacturing parameters within a single manufacturing cycle time. This research proposes an in-line optimization framework incorporating a trained AI model to predict kidney-shaped die forming. Preliminary results indicate that the AI framework can accurately predict draw-in values based on a given parameter set, a process referred to as forward prediction. Furthermore, the AI framework can also predict the optimal parameter set that leads to the desired draw-in values, referred to as inverse optimization (or backward prediction). This research has been performed in collaborations with USCAR (US Council for Automotive Research) and AutoForm. The members of USCAR are Ford, GM, and Stellantis.

36 MATERIALS SCIENCE↗
NASA NTRS1993

Predesign of diamond turned refractive/diffractive elements for IR objectives

Diffractive lenses have arrived. Literally hundreds of papers have been published and technology impact reports have been written about the exciting addition of a new tool for the lens designer. Sophisticated computer programs have been developed to aid in the optimization of these diffractive phase profiles for a wide variety of applications. Now, several fabrication methods are being pursued to produce these diffractive elements economically. The best known process is the etching of a multi-level relief grating, known as binary optics. This process uses sets of computer generated lithographic masks. Another, more recently developed method is Dry Photopolymer Embossing (DPE). This replication process uses master holograms. And now, diamond turning is being applied for the machining of these elements. Diamond turning is especially well suited for infrared optics. As any process has advantages and limitations, so has diamond turning. These advantages and limitations are discussed and general guidelines are presented to aid the designer and systems engineer in the project predesign stage.

Riedl, Max J.↗
NASA NTRS2005

A CSP-Based Agent Modeling Framework for the Cougaar Agent-Based Architecture

Cognitive Agent Architecture (Cougaar) is a Java-based architecture for large-scale distributed agent-based applications. A Cougaar agent is an autonomous software entity with behaviors that represent a real-world entity (e.g., a business process). A Cougaar-based Model Driven Architecture approach, currently under development, uses a description of system's functionality (requirements) to automatically implement the system in Cougaar. The Communicating Sequential Processes (CSP) formalism is used for the formal validation of the generated system. Two main agent components, a blackboard and a plugin, are modeled as CSP processes. A set of channels represents communications between the blackboard and individual plugins. The blackboard is represented as a CSP process that communicates with every agent in the collection. The developed CSP-based Cougaar modeling framework provides a starting point for a more complete formal verification of the automatically generated Cougaar code. Currently it is used to verify the behavior of an individual agent in terms of CSP properties and to analyze the corresponding Cougaar society.

Gracanin, Denis↗
NASA NTRS2005

Liquid Nitrogen Removal of Critical Aerospace Materials

Identification of innovative solutions to unique materials problems is an every-day quest for members of the aerospace community. Finding a technique that will minimize costs, maximize throughput, and generate quality results is always the target. United Space Alliance Materials Engineers recently conducted such a search in their drive to return the Space Shuttle fleet to operational status. The removal of high performance thermal coatings from solid rocket motors represents a formidable task during post flight disassembly on reusable expended hardware. The removal of these coatings from unfired motors increases the complexity and safety requirements while reducing the available facilities and approved processes. A temporary solution to this problem was identified, tested and approved during the Solid Rocket Booster (SRB) return to flight activities. Utilization of ultra high-pressure liquid nitrogen (LN2) to strip the protective coating from assembled space shuttle hardware marked the first such use of the technology in the aerospace industry. This process provides a configurable stream of liquid nitrogen (LN2) at pressures of up to 55,000 psig. The performance of a one-time certification for the removal of thermal ablatives from SRB hardware involved extensive testing to ensure adequate material removal without causing undesirable damage to the residual materials or aluminum substrates. Testing to establish appropriate process parameters such as flow, temperature and pressures of the liquid nitrogen stream provided an initial benchmark for process testing. Equipped with these initial parameters engineers were then able to establish more detailed test criteria that set the process limits. Quantifying the potential for aluminum hardware damage represented the greatest hurdle for satisfying engineers as to the safety of this process. Extensive testing for aluminum erosion, surface profiling, and substrate weight loss was performed. This successful project clearly demonstrated that the liquid nitrogen jet possesses unique strengths that align remarkably well with the unusual challenges that space hardware and missile manufacturers face on a regular basis. Performance of this task within the confines of a critical manufacturing facility marks a milestone in advanced processing.

Noah, Donald E.↗
DOE OSTI2026

Use of friction stir processing to synthesize nanocrystalline, grain boundary segregating Fe-Ti alloys

Grain boundary segregating alloys, a class of alloys designed such that nanocrystalline grain sizes are thermodynamically stabilized by the presence of high segregation energy solutes at the grain boundaries, are typically produced through geometrically limited processing techniques such as equal channel angular extrusion or thin film sputtering. Here, this study explores the use of friction stir processing (FSP) as a novel means of studying and producing these alloys using a test system of Fe-6at%Ti. Spot FSPs with a range of processing parameter sets were produced on bulk, coarse grained bars of material and optimal parameters were identified. Microscopy identified a range of processed materials which achieved nanocrystalline grains on the order of 100 nm, delineating a critical window of processing parameters which limit heat input while inducing sufficient plastic deformation for grain refinement. The finest grained nanocrystalline Fe-Ti achieved a hardness of 7.68 GPa, a significant increase in hardness over pure Fe with a similar microstructure due to increased dislocation density from FSP as well as several strengthening mechanisms produced through the presence and segregation of Ti. These results demonstrated the feasibility of using FSP to produce nanocrystalline grain boundary segregating alloys.

Fe alloys↗
DOE OSTI2025

Modeling diffusion and depletion in high-aspect-ratio atomic layer deposition processes: Process parameters and manufacturing impacts

Atomic layer deposition (ALD) is a powerful technique for modifying the surface chemistry and properties of substrates with complex and nonplanar topologies. However, achieving uniform and conformal deposition on ultrahigh-aspect-ratio substrates remains challenging, typically requiring large quantities of precursors and long exposure times. Furthermore, process optimization is often performed empirically and involves substantial trial and error. In this work, we perform a combined experimental and computational study of ALD Al 2 O 3 infiltration into silica aerogel monoliths (aspect ratio >10 5 ). A reaction-diffusion model is used to explore the effects of key processing parameters, namely, exposure time per dose, precursor source temperature, number of aerogels in the reactor, and reactor volume. The model is based on quasi-static mode ALD, where the dosed precursor is held in the chamber for a fixed period of time before purging. We analyze the trade-offs between process throughput and precursor utilization for each of these parameters. Furthermore, we investigate the co-optimization and interactions between multiple process parameters, demonstrating the potential for further improvements. Furthermore, this physics-based model can be used to identify a set of process parameters for high-aspect-ratio ALD that meet specific manufacturing objective functions, including throughput, cost, and sustainability.

Aerogel↗
DOE OSTI2021

GMS Station SOH Monitoring Configuration Guide (V.1.2)

The GMS Station State-of-Health (SOH) monitoring capability provides the system controller the ability to view current SOH values and calculated statistics for stations and channels, view trend plots of SOH values, be notified when station SOH status changes, and acknowledge or quiet notifications while the station issues are being investigated. The SOH monitoring capability includes components to acquire CD 1.1 protocol station data, extract SOH information from the raw data packets, process the raw SOH information for display, store the SOH information, and display the SOH information in an interactive display. All these components use system and processing configuration to provide the system controller mission-relevant information about station health. This document is a guide to setting the processing configuration for GMS SOH monitoring.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Contactless Ultrasonic Wavefield Imaging to Visualize Near-Surface Damage in Concrete Elements

We present work to detect and visualize near-surface damage in concrete using contactless ultrasonic wavefield imaging technology. A fully contactless ultrasonic scanning system that utilizes a micro-electro-mechanical systems (MEMS) ultrasonic microphone array is used to collect ultrasonic surface wave data from a concrete sample. The obtained wavefield data sets are processed with a frequency-wavenumber (f-k) domain wavefield filtering approach to extract non-propagating oscillatory fields set up by near-surface concrete cracking damage. The experimental results demonstrate that near-surface concrete damage can be detected and visualized using the proposed ultrasonic wavefield imaging approach.

Song, Homin (ORCID:0000000269141579)↗
NASA NTRS1997

Response Modality Modulator PRP Interference, Even When Task 1 is a no-go trial

In a Psychological Refractory Period paradigm where the first task requires one of several possible responses on some trials (the go trials), but no response on other (no-go) trials, response modality modulates the amount of interference on Task 2 processing. This is true even when Task 1 is no-go trial. Differences in the cost of switching response sets between processing for Task 1 and Task 2 may provide an account of this surprising phenomenon.

VanSelst, Mark↗
NASA NTRS2003

Results of the Workshop on Impact Cratering: Bridging the Gap Between Modeling and Observations

On February 7-9,2003, approximately 60 scientists gathered at the Lunar and Planetary Institute in Houston, Texas, for a workshop devoted to improving knowledge of the impact cratering process. We (co-conveners Elisabetta Pierazzo and Robert Herrick) both focus research efforts on studying the impact cratering process, but the former specializes in numerical modeling while the latter draws inferences from observations of planetary craters. Significant work has been done in several key areas of impact studies over the past several years, but in many respects there seem to be a disconnect between the groups employing different approaches, in particular modeling versus observations. The goal in convening this workshop was to bring together these disparate groups to have an open dialogue for the purposes of answering outstanding questions about the impact process and setting future research directions. We were successful in getting participation from most of the major research groups studying the impact process. Participants gathered from five continents with research specialties ranging from numerical modeling to field geology, and from small-scale experimentation and geochemical sample analysis to seismology and remote sensing.With the assistance of the scientific advisory committee (Bevan French, Kevin Housen, Bill McKinnon, Jay Melosh, and Mike Zolensky), the workshop was divided into a series of sessions devoted to different aspects of the cratering process. Each session was opened by two invited t a b , one given by a specialist in numerical or experimental modeling approaches, and the other by a specialist in geological, geophysical, or geochemical observations. Shorter invited and contributed talks filled out the sessions, which were then concluded with an open discussion time. All modelers were requested to address the question of what observations would better constrain their models, and all observationists were requested to discuss how their observations can constrain modeling efforts.

Herrick, Robert↗
NASA NTRS1992

Monthly mean global satellite data sets available in CCM history tape format

Satellite data for climate monitoring have become increasingly important over the past decade, especially with increasing concern for inadvertent antropogenic climate change. Although most satellite based data are of short record, satellites can provide the global coverage that traditional meteorological observations network lack. In addition, satellite data are invaluable for the validation of climate models, and they are useful for many diagnostic studies. Herein, several satellite data sets were processed and transposed into 'history tape' format for use with the Community Climate Model (CCM) modular processor. Only a few of the most widely used and best documented data sets were selected at this point, although future work will expand the number of data sets examined as well as update the archived data sets. An attempt was made to include data of longer record and only monthly averaged data were processed. For studies using satellite data over an extended period, it is important to recognize the impact of changes in instrumentation, drift in instrument calibration, errors introduced by retrieval algorithms and other sources of errors such as those resulting from insufficient space and/or time sampling.

Hurrell, James W.↗
DOE OSTI2022

Printability and Mechanical Properties of Polyethylene and Polyethylene/Nylon Blend Parts Made by Selective Laser Sintering

Improving the printability of polyethylene powder in selective laser sintering is of keen interest for the additive manufacturing community. Work to increase the variety of available feedstocks still must be done, as Nylon powder still constitutes a huge majority of all feedstocks used for selective laser sintering. Polyethylene is particularly of interest because it is a cheap, commodity polymer. Although some commercially available polyethylene powders exist, choosing one of these means the user is restricted to the specific polymer properties that those powders possess. Developing a reproducible processing parameter regime for polyethylene that exhibits other useful properties, such as very high densities or molecular weights, requires a uniquely tailored set of processing parameters. Particular emphasis will be placed on processing parameters that result in improved mechanical properties, as well as the possibility of successfully making SLS parts from polyethylene blends, e.g. polyethylene/Nylon blends.

36 MATERIALS SCIENCE↗
NASA NTRS1985

Autoclave processing for composite material fabrication. 1: An analysis of resin flows and fiber compactions for thin laminate

High quality long fiber reinforced composites, such as those used in aerospace and industrial applications, are commonly processed in autoclaves. An adequate resin flow model for the entire system (laminate/bleeder/breather), which provides a description of the time-dependent laminate consolidation process, is useful in predicting the loss of resin, heat transfer characteristics, fiber volume fraction and part dimension, etc., under a specified set of processing conditions. This could be accomplished by properly analyzing the flow patterns and pressure profiles inside the laminate during processing. A newly formulated resin flow model for composite prepreg lamination process is reported. This model considers viscous resin flows in both directions perpendicular and parallel to the composite plane. In the horizontal direction, a squeezing flow between two nonporous parallel plates is analyzed, while in the vertical direction, a poiseuille type pressure flow through porous media is assumed. Proper force and mass balances have been made and solved for the whole system. The effects of fiber-fiber interactions during lamination are included as well. The unique features of this analysis are: (1) the pressure gradient inside the laminate is assumed to be generated from squeezing action between two adjacent approaching fiber layers, and (2) the behavior of fiber bundles is simulated by a Finitely Extendable Nonlinear Elastic (FENE) spring.

Hou, T. H.↗