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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 199 records · Page 11
All sourcesNASA NTRSDOE OSTI
NASA NTRS1996

Statistical Process Control for KSC Processing

The 1996 Summer Faculty Fellowship Program and Kennedy Space Center (KSC) served as the basis for a research effort into statistical process control for KSC processing. The effort entailed several tasks and goals. The first was to develop a customized statistical process control (SPC) course for the Safety and Mission Assurance Trends Analysis Group. The actual teaching of this course took place over several weeks. In addition, an Internet version of the same course complete with animation and video excerpts from the course when it was taught at KSC was developed. The application of SPC to shuttle processing took up the rest of the summer research project. This effort entailed the evaluation of SPC use at KSC, both present and potential, due to the change in roles for NASA and the Single Flight Operations Contractor (SFOC). Individual consulting on SPC use was accomplished as well as an evaluation of SPC software for KSC use in the future. A final accomplishment of the orientation of the author to NASA changes, terminology, data format, and new NASA task definitions will allow future consultation when the needs arise.

Ford, Roger G.↗
NASA NTRS1996

Efficient Process Migration for Parallel Processing on Non-Dedicated Networks of Workstations

This paper presents the design and preliminary implementation of MpPVM, a software system that supports process migration for PVM application programs in a non-dedicated heterogeneous computing environment. New concepts of migration point as well as migration point analysis and necessary data analysis are introduced. In MpPVM, process migrations occur only at previously inserted migration points. Migration point analysis determines appropriate locations to insert migration points; whereas, necessary data analysis provides a minimum set of variables to be transferred at each migration pint. A new methodology to perform reliable point-to-point data communications in a migration environment is also discussed. Finally, a preliminary implementation of MpPVM and its experimental results are presented, showing the correctness and promising performance of our process migration mechanism in a scalable non-dedicated heterogeneous computing environment. While MpPVM is developed on top of PVM, the process migration methodology introduced in this study is general and can be applied to any distributed software environment.

Chanchio, Kasidit↗
NASA NTRS2001

Composites: Processing and Fabrication Methodologies of Nonoxide Ceramic Composites. Processing HfB2 Composites for Use in Extreme Environments

HfB2 and ZrB2 composites containing SiC are known to have good thermal shock and configurational stability at elevated temperatures. These are promising ultra-high temperature ceramics (UHTCs) for use on the sharp leading edges of next generation space vehicles. Sharp leading edges on these vehicles will need to: withstand repeated exposures to temperatures > 2200 C in oxidizing environments; have good thermal shock and ablation resistance; and withstand the mechanical stress of launch and reentry. The HfB2/SiC composite is currently undergoing processing improvements in an effort to better the performance of a material that has been studied for approx. 35 years. The potential for HfB2/SiC composites to meet the requirements of hypersonic flight depends on controlling processing techniques. This presentation will focus on understanding processing steps now being undertaken to optimize the material properties of HfB2/SiC composites at NASA Ames Research Center. Correlation between processing techniques and microstructure will be shown. Preliminary oxidation studies will also be discussed.

Gusman, Michael I.↗
DOE OSTI2018

A Workshop on the History of Plutonium Processing at Hanford Washington as the Foundation for Modern-day Plutonium Process Science

Numerous national laboratories in the United States have roots related to the Manhattan Project that contributed to the end of World War II. The pioneering science and engineering that took place over the decades that followed continues to influence modern-day actinide-related research at those institutions, leading to unique strengths and cutting-edge ideas and perspectives. These same national laboratories also face a challenge: figuring out how to capture the expertise of a retiring workforce who had first-hand experience in these pioneering nuclear efforts. Recently, at PNNL a “Train-the-Trainer” approach has been piloted where mentors and mentees are paired together to develop and deliver interactive workshops on historical topics that relate to modern-day research, such as Plutonium Processing or Environmental Management of Legacy Nuclear Waste. This approach was used to develop a workshop that beings with the Historic Hanford process plutonium chemistry and engineering, describes its influence on current plutonium separation and process science, and then details the chemistry of plutonium as it progresses from a minor constituent in irradiated fuel to purified solid product. This workshop is targeted to the practitioner of applied science and technology wishing to gain a better understanding of the history and process-related chemistry of element 94 so that they may better direct the tools of their specific craft toward the present and future needs of plutonium science.

Smith, Frances N.↗
NASA NTRS2018

Hyperspectral Data Processing: an Opportunity for End-To-End Processing

The evolution and improvements in hyperspectral instrumentation are being matched by information technology improvements in science data processing and analysis. Research has improved techniques in both onboard and ground-based processing to support other high data volume instruments. Algorithms and hardware have evolved, permitting faster access to the observations. Cloud computing is taking the algorithms to the data. Technologies are being specifically designed to address high volume data sets and are an investment in the improvement of hyperspectral data processing.

science data processing↗
DOE OSTI2025

Highly crystalline, low-ash, graphite from coal using an Fe 2 O 3 -based catalytic process with recovery and reuse of catalyst and process acid

This study presents a sustainable process for producing highly crystalline, low-ash graphite from sub-bituminous coal using an Fe 2 O 3 -based catalytic method. The process integrates coal mineral removal, catalyst regeneration, and reagent recycling into a closed-loop system. Acid-soluble Fe-residue and mineral impurities are eliminated from the solid graphite through HCl treatment, followed by hydrolytic distillation to regenerate Fe 2 O 3 and recover HCl for reuse. Coal-derived silica is removed with a KOH rinse, yielding low-ash graphite suitable for high-performance applications. The closed-loop catalytic graphitization, where the recovered Fe 2 O 3 and HCl are used in subsequent graphitization runs, produces graphite with a degree of graphitization exceeding 95%. The L a and L c crystallite sizes reach 65–78 nm and 44–48 nm, respectively, with BET surface areas of 4–10 m 2 /g and an ash content below 0.1 wt.%. Lithium-ion battery testing reveals that anodes fabricated with this graphite deliver an initial discharge capacity between 384.5 and 421.2 mAh/g, averaging 395.0 ± 19.1 mAh/g, along with initial coulombic efficiencies of 85.0–89.1%. After 100 discharge–charge cycles at 0.25C, reversible capacities remain between 358.8 and 369.7 mAh/g, while coulombic efficiency stays above 99.9%. The findings highlight that coal can serve as a viable precursor for high-quality graphite production under relatively mild conditions, avoiding the need for extreme temperatures or aggressive reagents such as hydrofluoric acid, commonly employed in conventional processes. This work demonstrates both technical feasibility and environmental benefits, emphasizing its potential to support large-scale, sustainable graphite production for applications such as lithium-ion batteries.

Catalytic graphitization↗
DOE OSTI2024

A Gaussian Process-Based extended Goldak heat source model for finite element simulation of laser powder bed fusion additive manufacturing process

In this study, laser powder bed fusion (L-PBF) additive manufacturing (AM) is a key enabling technology to manufacture highly complex and integrated metallic structures. In L-PBF AM process, the melting of the metal powders and the layers underneath can be governed by either “conduction mode” or “keyhole mode”, with the keyhole mode reportedly leading to porosity and decreased strength and ductility by many studies. In part scale simulations, finite element (FE) model is often used to study the temperature distribution during printing and to predict the residual stress, where a volumetric heat flux with a Gaussian or a double ellipsoidal (Goldak) distribution is often applied as the laser heat source. However, the above heat source models can only capture the melt pool shape in the conduction mode, and fail to capture the transition to keyhole melting mode when the process parameters change. To overcome this inaccuracy, an extended Goldak heat source model is proposed by introducing a laser penetration term as a function of laser parameters obtained from a Gaussian-Process (GP) model. The model is validated by “2D pad” AlSi10Mg L-PBF experiments under a wide range of laser power, scan speed, and laser focus offset, and the results show the model successfully captures the measured melt pool shape in all conditions.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Investigation of the benefits of diabatic microreactors for process intensification of the water-gas shift reaction within the steam reforming process

Presently, the steam reforming process is the largest industrial source of hydrogen. Improving its efficiency can help to reduce associated carbon emissions and hydrogen production costs. Intensifying the water-gas shift reaction using microreactors with integrated cooling is one way of achieving this. In this study, a 2-D computational model of one of these microreactors is developed, validated with experimental data, and then used to demonstrate how microreactors can enhance the conversion of the water-gas shift reaction beyond what can be achieved using conventional packed bed reactors. These results are then generalized into a full system model of the steam reforming process to demonstrate how microreactors can reduce hydrogen production costs. The results suggest that microreactors can significantly reduce the required reactor volume and catalyst loading for the water-gas shift reaction and can similarly reduce the hydrogen production costs associated with the steam reforming process.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2018

Geometric Analysis Based Double Closed-loop Iterative Learning Control of Output PDF Shaping of Fiber Length Distribution in Refining Process

In order to improve the pulp quality and to reduce the energy consumption, the fiber length distribution (FLD) is generally employed as one of the important technological indexes in the refining process. Considering that the traditional mean and variance of fiber length are unable to adequately characterize the non-Gaussian distribution properties, this paper proposes a novel geometric analysis based double closed-loop iterative learning control (ILC) method for probability density function (PDF) shaping of output FLD in the refining process. Primarily, a RBF neural network (NN) with Gaussian-type is utilized to approximate the square root PDF in the inner loop, where the RBF basis function parameters (center and width) are tuned between any two adjacent batches by using an ILC law, and the subspace identification method can be applied to establish the state-space model of weight vector. Then, for the sake of accelerating the convergence rate of the closed-loop sysyem, a geometric analysis based ILC method is adopted in the outer loop. Lastly, both simulation and experiments demonstrate the effectiveness and practicability of the proposed approach.

42 ENGINEERING↗
NASA NTRS2025

Gaussian Process for Flight Delay Prediction: Learning a Stochastic Process

This paper presents a machine-learning approach to predict flight delays. Whereas neural networks are extensively studied for predictive capabilities, they involve non-intuitive design and extensive analysis, particularly in training and optimization processes. Instead, the proposed framework employs Gaussian Processes as a supervised learning technique for flight delay prediction. This data-driven approach trains the model using prior information, specifically the mean and covariance tied to existing data. The proposed Gaussian Process Regression (GPR) model employs the day of flight as a pivotal feature for delay forecasting. We analyze flights from various routes and gauge the accuracy of the presented learning technique by comparing the predicted delays with the actual ones. Given the inherent challenges in precisely forecasting delays, we predict the delays with a 95 % confidence interval. Also, an error propagation analysis in the prediction horizon is carried out to determine the optimal time frame for prediction. The proposed method for flight delay prediction is important as airlines can strategize flight operations and issue timely advisories.

stochastic↗
DOE OSTI2020

One–Step Fabrication of Nanocrystalline Nanonetwork SnO 2 Gas Sensors by Integrated Multilaser Processing

An integrated multilaser process is developed to fabricate nanocrystalline nanonetwork SnO 2 gas sensors in one integrated procedure, which combines electrodes fabrication, nanomaterials deposition, and postannealing. Interdigit electrodes are fabricated on an Au-coated fused silica substrate using a picosecond (ps) laser, which ablates the Au coating from the back of the substrate to pattern the electrodes. A novel transmitted Ps laser deposition (TPLD) process is designed to deposit SnO 2 nanonetwork on the interdigit electrodes with precise deposition area control under a close target-to-substrate distance. The obtained SnO 2 nanonetwork is in situ postannealed by a CO 2 laser to improve the crystallinity, while the nano morphology and grain size keep intact. To investigate the morphology and formation process of the nanonetwork, the microstructure of the laser-deposited SnO 2 layer is characterized. As a result, the crystallization control of CO 2 laser annealing is investigated through analyzing the Raman spectrum, X-ray diffraction (XRD) patterns, and lattice structures of the samples. By exposed to H 2 atmosphere, the fabricated gas sensor is demonstrated for H 2 monitoring.

08 HYDROGEN↗
DOE OSTI2018

Study of a Single-Power Two-Circuit ESR Process with Current-Carrying Mold: Mathematical Simulation of the Process and Experimental Verification

A novel single-power two-circuit ESR process (ESR-STCCM) with current-carrying mold has been investigated via numerical simulation and experimental research in this paper. A 2D quasi-steady-state mathematical model is developed to describe ESR-STCCM. The electromagnetic field, flow field, slag pool temperature distribution, and the shape of a molten steel pool in ESR-STCCM have been investigated by FLUENT software as well as user-defined functions (UDF). The results indicate that ESR-STCCM is different from the conventional ESR process. The maximum electromagnetic force, current density, Joule heat, and slag pool flow velocity are located in the lower part of the conductor in the ESR-STCCM process. The direction of the maximum electromagnetic force inclines upward. There are two distinct vortices in the slag pool. The larger swirl rotates counterclockwise near the conductor, with a value of 0.0263 m s{sup −1} due to the interaction of the electromagnetic force and gravity. The maximum temperature of the slag pool is 2070 K (1797 °C) and is located in the center of the swirl with a filling ratio of 0.6 and a 20 mm electrode immersion depth. The depth of a molten steel pool is shallower, which is conducive to improving solidification quality. In addition, the filling ratio of 0.6 is conducive to controlling steel solidification quality. Some experiments have been done, and the numerical model is confirmed by experimental results.

36 MATERIALS SCIENCE↗
DOE OSTI2019

The SCALE/AMPX multigroup cross section processing for fast reactor analysis

The SCALE/AMPX multigroup (MG) cross section processing procedure has been updated to minimize reactivity differences for fast reactor designs and boiling water reactors (BWRs) with very high void fractions to provide excellent agreement with continuous-energy reference calculations. SCALE MG calculations are widely applied to thermal spectrum light-water reactor (LWR) systems as well as fast spectrum metallic systems of interest to National Nuclear Security Administration. With growing interest from industry and regulators in applying SCALE for the design of fast spectrum reactors, both sodium and molten salt, and in the licensing of power up rates for BWRs, it is desirable to review the SCALE/AMPX procedure for unresolved resonance self-shielded data and high energy neutron spectra. The data were improved by generating MG unresolved resonance data based on the analytic probability table method with the narrow resonance approximation as well as the use of a very fine group structure typically used in fast system analysis. This study focused on verifying the probability table and the SCALE/AMPX MG cross section processing procedure by performing reaction rate analysis and benchmark calculations for various fast reactor and high void BWR systems. Here, results indicate that the improved SCALE/AMPX MG cross section processing provides excellent results for the fast reactor analysis.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2022

CO 2 utilization potential of a novel calcium ferrite based looping process fueled with coal: Experimental evaluation of various coal feedstocks and thermodynamic integrated process analysis

Here, conversion of CO 2 to CO was performed at 800-850C via reduction of calcium ferrite (CaFe 2 O 4 ) with coal followed by oxidation of reduced CaFe 2 O 4 with CO 2 to produce CO and partially oxidized Ca ferrite. The process was evaluated with several types of coals which included lignite, sub-bituminous, bituminous, anthracite and pet-coke. Reduction of CaFe 2 O 4 with sub-bituminous coal and lignite coal was more favorable than that with higher rank coals. Stable reactivity performance was demonstrated for 35-cycle test conducted with lignite coal/CaFe 2 O 4 at 800°C and with high conversion of CO 2 to CO. The rate of conversion of CO 2 to CO with reduced CaFe 2 O 4 was found to be 1st order with respect to CO 2 and had a low activation energy of 7.4 kJ/mol. Thermodynamic integrated process assessments suggest that two and three reactor process concepts can be realized and net CO 2 utilization achievable. The two reactor configuration shows the highest potential for CO 2 utilization while generating a value-added CO rich syngas stream.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

Integrated Two-Stage Alkaline–Oxidative Pretreatment of Hybrid Poplar. Part 2: Impact of Cu-Catalyzed Alkaline Hydrogen Peroxide Pretreatment Conditions on Process Performance and Economics

Two-stage alkaline/copper 2,2'-bipyridine-catalyzed alkaline hydrogen peroxide (Cu-AHP) pretreatment is an effective strategy for improving the enzymatic digestibility of hybrid poplar. To reduce the chemical inputs and processing costs associated with this process, we investigated the effect of increasing the temperature for both the alkaline pre-extraction and the Cu-AHP pretreatment stages. The results indicate that increasing the alkaline pre-extraction and the Cu-AHP pretreatment temperatures from 30 to 120 and 80 °C, respectively, allowed us to reduce both the pretreatment time of the Cu-AHP stage and the chemical loadings. Incubating alkaline pre-extracted hybrid poplar for 12 h with 10% NaOH (w/w biomass), 8% hydrogen peroxide (w/w biomass), and a Cu 2+ and 2,2'-bipyridine (bpy) concentration of 1 mM yielded monomeric sugar yields of approximately 77% glucose and 66% xylose (based on the initial sugar composition) following enzymatic hydrolysis. Technoeconomic analysis (TEA) indicates that these changes to the two-stage alkaline/Cu-AHP pretreatment process could potentially reduce the minimum fuel selling price (MFSP) by more than $\$1.00$ per gallon of biofuel compared to the reference case where both stages were conducted at 30 °C with higher chemical inputs.

09 BIOMASS FUELS↗
DOE OSTI2021

Vertical variation of turbulent entrainment mixing processes in marine stratocumulus clouds using high-resolution digital holography

Marine stratocumulus clouds contribute signi?cantly to the Earth’s radiation budget due to their extensive coverage and high albedo. Yet, subgrid variability in cloud properties such as aerosol concentration, droplet number and precipitation rates lead to considerable errors in global climate models. While these clouds usually have small vertical ex-tent, turbulent entrainment-mixing and precipitation can generate signi?cant variations in droplet number, size and relative dispersion with altitude. In this paper, we analyze turbulent entrainment-mixing processes and the variability in cloud microphysical properties as a function of height within a warm marine stratocumulus cloud layer over the Eastern North Atlantic. We use high resolution airborne holographic measurements and compare them with local turbulence measurements. We ?nd that entrainment-mixing is primarily inhomogeneous near cloud top leading to larger droplet sizes and homogeneous near cloud base leading to smaller droplet sizes. Further analysis of Damk¨ohler number measurements are able to explain the mixing mechanisms at di?erent cloud heights, reinforcing the importance of turbulent mixing and microphysical time scales in deter-mining cloud microphysics.

Desai, Neel↗