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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 541 records · Page 30
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Process Engineering to Increase the Layered Phase Concentration in the Immediate Products of Flame Spray Pyrolysis

Flame-spray-pyrolysis (FSP) is a robust and scalable process to synthesize particles at the commodity-scale. FSP has been used to produce the precursor powders which were converted to the layered structure $(R\bar{3m} \text { phase})$ by a postannealing step in making nickel-rich cathode materials (NCMs). Theoretically, the high flame temperature (normally >1500 K) in FSP can provide adequate energy for the phase conversion from rock-salt to layered structures and potentially enables one-step synthesis. However, the high flame temperature is a critical issue to cause lithium loss and structural degradation, preventing the formation of the layered phase. Here, guided by the gaseous nucleation theory, we implemented several FSP processes with different solution recipes. The layered phase concentration in the as-burned products can be increased with the solution enthalpies. By adding a rapid quench step to suppress the lithium loss and phase degradation, the layered phase can be further increased. This work contributes new ideas to innovating process regarding the process efficiency and throughput of manufacturing cathode materials at a large scale.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS2011

Fixed Eigenvector Analysis of Thermographic NDE Data

Principal Component Analysis (PCA) has been shown effective for reducing thermographic NDE data. This paper will discuss an alternative method of analysis that has been developed where a predetermined set of eigenvectors is used to process the thermal data from both reinforced carbon-carbon (RCC) and graphiteepoxy honeycomb materials. These eigenvectors can be generated either from an analytic model of the thermal response of the material system under examination, or from a large set of experimental data. This paper provides the details of the analytic model, an overview of the PCA process, as well as a quantitative signal-to-noise comparison of the results of performing both conventional PCA and fixed eigenvector analysis on thermographic data from two specimens, one Reinforced Carbon-Carbon with flat bottom holes and the second a sandwich construction with graphite-epoxy face sheets and aluminum honeycomb core.

Cramer, K. Elliott↗
DOE OSTI2021

Techno-Economic Analysis and Life Cycle Assessment of Waste Lignin Fractionation and Valorization Using the ALPHA Process

Techno-Economic Analysis (TEA) and Life Cycle Assessment (LCA) were performed on the Aqueous Lignin Purification with Hot Agents (ALPHA) process, which is being investigated for the fractionation and purification of raw, bulk lignins recovered from cellulosic ethanol biorefineries or Kraft pulp mills. Here, ALPHA is proposed for the isolation of lignin from a corn stover-to-ethanol plant into purified low, medium, and high molecular weight (MW) fractions for producing polyurethane foam, activated carbon, and carbon fiber, respectively. A scenario analysis was conducted to determine the effect of ALPHA solvent choice on process economics and environmental performance. Solvent choice was found to have a significant impact on ALPHA, with a minimum selling price of 838/tonne with use of acetic acid vs 463/tonne with ethanol. Conversion of the lignin, processed with ethanol solvent, to high-value products yields 151 million/year in profit, which over 30 years results in a total net present value of 533 million. A life cycle assessment was conducted to determine the “gate-to-gate” greenhouse gas emissions and energy consumption of the lignin-based products compared to fossil-based equivalents. In conclusion, a value allocation scenario was conducted and it was determined that products generated using the ALPHA process with ethanol have similar or lower greenhouse gas emissions than the same products from fossil feedstocks.

09 BIOMASS FUELS↗
DOE OSTI2023

Machine Learning Enabled Sensor Fusion for In-Situ Defect Detection in Laser Powder Bed Fusion

Laser Powder Bed Fusion (L-PBF) Additive Manufacturing (AM) is among the metal 3D printing technologies most broadly adopted by the manufacturing industry. The current industry qualification paradigm for critical-application L-PBF parts relies heavily on expensive non-destructive inspection techniques such as X-Ray Computed Tomography (XCT), which significantly limits the use-cases of L-PBF. In situ monitoring of the process promises a less expensive alternative to ex situ testing, but existing sensor technologies and data analysis techniques struggle to detect sub-surface flaws (e.g., porosity and cracking) on production-scale L-PBF printers. RTX Technologies Research Center (RTRC) has licensed ORNL’s Peregrine software package – a printer- and camera-agnostic data analytics tool designed specifically for detecting process anomalies using in situ data collected during powder bed printing. The goal of this project was to feed temporally rich, multi-modal sensor data, including visible light, integrated near infrared (NIR), and spatially mapped co-axial melt pool thermal emission data into Peregrine to enable detection of subsurface flaws. XCT data was used as ground truth training data to allow Peregrine’s deep learning algorithms to recognize anomalies in these complex data streams in both test artifacts and industrially relevant geometries. Completion of this program has seen the successful implementation of multi-modal, multi-layer sensor data footprints for training of machine learning models in Peregrine. Flaws detected in XCT data have been successfully detected directly from this in situ data footprint, and initial analyses of the in situ probability-of-detection has been conducted, showing performance levels commensurate with traditional non-destructive evaluation (NDE) methods. The in situ monitoring methodology was then applied to an industrially relevant component that was using post-build NDE, highlighting the utility of the proposed method for hard-to-inspect AM components. As a direct result of this program, two journal manuscripts [1], [2] have been published in Additive Manufacturing, with additional manuscripts planned following program completion.

36 MATERIALS SCIENCE↗
NASA NTRS1973

Mars physical parameters as determined from Mariner 9 observations of the natural satellites

Derivation of values for the Mars gravity field, as well as the mass and spin axis direction, by processing combined radio and optical data taken with the Mariner 9 spacecraft. The optical data consists of 62 TV photographs of Phobos and Deimos taken during the Mars orbiting phase of Mariner 9. The radio data consists of apoapsis state vectors obtained from 195 one-revolution fits of the Doppler data. A first-order analytic theory is used to model both the satellites and the spacecraft's motion. However, the shallow resonance condition of Mariner 9's orbit necessitated development of a partial second-order theory to model the long-period perturbations which derive from Mars even-order tesseral harmonics. Use of an analytic theory allows rapid and inexpensive processing of both data types simultaneously. The results are in good agreement with those previously published from Mariner 9 Doppler and landmark data.

Born, G. H.↗
DOE OSTI2021

Optimizing Process Conditions during Catalytic Fast Pyrolysis of Pine with Pt/TiO 2 —Improving the Viability of a Multiple-Fixed-Bed Configuration

Catalytic fast pyrolysis (CFP) has been identified as a promising pathway for the production of renewable fuels and co-products. However, continued technology development is needed to increase process efficiency and reduce process costs. This report builds upon previous research in which a bifunctional metal–acid Pt/TiO 2 catalyst was utilized in a fixed-bed reactor operated with co-fed H 2 to improve product yield and reduce coke generation compared to conventional CFP methods. Here, we report further process optimization, in which we achieved similar CFP oil carbon efficiency (>35%) and CFP oil oxygen content (<20 wt %) to our previous report while reducing catalyst and equipment costs by increasing time-on-stream between regenerations by 40–95% and decreasing required regeneration time by more than a factor of 2. These process improvements were achieved by conducting parameter sweeps to determine optimum conditions for CFP and regeneration with key variables including pyrolysis temperature, catalytic upgrading temperature, hydrogen partial pressure, and regeneration oxygen concentration. Coupled with comprehensive oil analyses, these data provide foundational insight into the deoxygenation and coking chemistries for CFP under realistic process conditions while also advancing the technology through applied engineering.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Utilization of machine learning to accelerate colloidal synthesis and discovery

Machine learning techniques are seeing increased usage for predicting new materials with targeted properties. However, widespread adoption of these techniques is hindered by the relatively greater experimental efforts required to test the predictions. Furthermore, because failed synthesis pathways are rarely communicated, it is difficult to find prior datasets that are sufficient for modeling. This work presents a closed-loop machine learning-based strategy for colloidal synthesis of nanoparticles, assuming no prior knowledge of the synthetic process, in order to show that synthetic discovery can be accelerated despite limited data availability.

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

Equivalent GPS measurements for efficient estimation process

Dual-frequency pseudorange and carrier phase data streams can be analytically combined into a single equivalent data stream, reducing the data volume and computing time in the filtering process for parameter estimation by a factor of 2 to 4. The resulting single data stream is that of carrier phase measurements with both data noise and bias uncertainty strictly defined. Based on these analytical formulas the equivalent GPS measurements can be formed by simple and efficient numerical calculations without any degradation in data strength. Formulation for the equivalent GPS measurements and their covariances are given in closed form; and a numerical simulation is performed to demonstrate the validity and effectiveness of the equivalent measurements.

Wu, S. C.↗
DOE OSTI2021

Applications of analytical electron microscopy to guide the design of boron carbide

Compositional analysis of boron carbide on nanometer length scales to examine or interpret atomic mechanisms, for example, solid-state amorphization or grain-boundary segregation, is challenging. This work reviews advancements in high-resolution microanalysis to characterize multiple generations of boron carbide. First, ζ-factor microanalysis will be introduced as a powerful (scanning) transmission electron microscopy ((S)TEM) analytical framework to accurately characterize boron carbide. Three case studies involving the application of ζ-factor microanalysis will then be presented: (1) accurate stoichiometry determination of B-doped boron carbide using ζ-factor microanalysis and electron energy loss spectroscopy, (2) normalized quantification of silicon grain-boundary segregation in Si-doped boron carbide, and (3) calibration of a scanning electron microscope X-ray energy-dispersive spectroscopy (XEDS) system to measure compositional homogeneity differences of B/Si-doped arc-melted boron carbides in the as-melted and annealed conditions. Overall, the improvement and application of advanced analytical tools have helped better understand processing–microstructure–property relationships and successfully manufacture high-performance ceramics.

36 MATERIALS SCIENCE↗
NASA NTRS2013

Mars Hand Lens Imager (MAHLI) Efforts and Observations at the Rocknest Eolian Sand Shadow in Curiosity's Gale Crater Field Site

The Mars Science Laboratory (MSL) mission is focused on assessing the past or present habitability of Mars, through interrogation of environment and environmental records at the Curiosity rover field site in Gale crater. The MSL team has two methods available to collect, process and deliver samples to onboard analytical laboratories, the Chemistry and Mineralogy instrument (CheMin) and the Sample Analysis at Mars (SAM) instrument suite. One approach obtains samples by drilling into a rock, the other uses a scoop to collect loose regolith fines. Scooping was planned to be first method performed on Mars because materials could be readily scooped multiple times and used to remove any remaining, minute terrestrial contaminants from the sample processing system, the Collection and Handling for In-Situ Martian Rock Analysis (CHIMRA). Because of this cleaning effort, the ideal first material to be scooped would consist of fine to very fine sand, like the interior of the Serpent Dune studied by the Mars Exploration Rover (MER) Spirit team in 2004 [1]. The MSL team selected a linear eolian deposit in the lee of a group of cobbles they named Rocknest (Fig. 1) as likely to be similar to Serpent Dune. Following the definitions in Chapter 13 of Bagnold [2], the deposit is termed a sand shadow. The scooping campaign occurred over approximately 6 weeks in October and November 2012. To support these activities, the Mars Hand Lens Imager (MAHLI) acquired images for engineering support/assessment and scientific inquiry.

Edgett, K. S.↗
NASA NTRS1980

Assessment of analytic methods for the prediction of aerodynamic characteristics of arbitrary bodies at supersonic speeds

Trends toward the automation of the design process for airplanes and missiles accentuate the need for analytic techniques for the prediction of aerodynamic characteristics. A number of computer codes have been developed or are under development which show promise of significantly improving the estimation of aerodynamic characteristics for arbitrarily-shaped bodies at supersonic speeds. The programs considered range in complexity from a simple linearized solution employing slender body theory to an exact finite difference solution of the Euler equations. The results from five computer codes are compared with experimental data to determine the accuracy, range of applicability, ease of use, and computer time and cost of the programs. The results provide a useful guide for selecting the appropriate method for treating bodies at the various levels of an automated design process.

Landrum, E. J.↗
DOE OSTI2020

Evolutionary reinforcement learning of dynamical large deviations

In this work, we show how to bound and calculate the likelihood of dynamical large deviations using evolutionary reinforcement learning. An agent, a stochastic model, propagates a continuous-time Monte Carlo trajectory and receives a reward conditioned upon the values of certain path-extensive quantities. Evolution produces progressively fitter agents, potentially allowing the calculation of a piece of a large-deviation rate function for a particular model and path-extensive quantity. For models with small state spaces, the evolutionary process acts directly on rates, and for models with large state spaces, the process acts on the weights of a neural network that parameterizes the model's rates. This approach shows how path-extensive physics problems can be considered within a framework widely used in machine learning.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1986

Structural dynamic measurement practices for turbomachinery at the NASA Lewis Research Center

Methods developed for measuring blade and rotor-shaft system response include optical systems, transient instruments, and special digital data processing equipment. Optical methods offer some distinct benefits for blade vibration measurement. Transient and steady state measurements of the response of rotor-shaft systems strongly affect analytical methods development. Digital computing systems allow processing of large volumes of high speed data from rotating blade sets. Also, digital systems develop useful vibration response signatures from randomly excited systems. Research facilities include the spin rig facility and the transient rotor response lab.

Kiraly, L. J.↗
NASA NTRS2003

Navigating a Mobile Robot Across Terrain Using Fuzzy Logic

A strategy for autonomous navigation of a robotic vehicle across hazardous terrain involves the use of a measure of traversability of terrain within a fuzzy-logic conceptual framework. This navigation strategy requires no a priori information about the environment. Fuzzy logic was selected as a basic element of this strategy because it provides a formal methodology for representing and implementing a human driver s heuristic knowledge and operational experience. Within a fuzzy-logic framework, the attributes of human reasoning and decision- making can be formulated by simple IF (antecedent), THEN (consequent) rules coupled with easily understandable and natural linguistic representations. The linguistic values in the rule antecedents convey the imprecision associated with measurements taken by sensors onboard a mobile robot, while the linguistic values in the rule consequents represent the vagueness inherent in the reasoning processes to generate the control actions. The operational strategies of the human expert driver can be transferred, via fuzzy logic, to a robot-navigation strategy in the form of a set of simple conditional statements composed of linguistic variables. These linguistic variables are defined by fuzzy sets in accordance with user-defined membership functions. The main advantages of a fuzzy navigation strategy lie in the ability to extract heuristic rules from human experience and to obviate the need for an analytical model of the robot navigation process.

Seraji, Homayoun↗
DOE OSTI2023

Editorial: Separations for Energy and Environmental Applications

Climate change and global environmental impacts are challenging humanity as a whole, and particularly the scientific community, to rethink our approaches towards energy harvesting, storage, and utilization, and to formulate processes geared to restoring compromised environments. A large task in these efforts involves developing technologies that have low or no carbon footprint, enable the use of renewable energy sources, and minimize or eliminate contamination of water resources and generation of untreatable waste.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1973

Advanced study of video signal processing in low signal to noise environments

Conventional analytical techniques used to determine and optimize phase-lock loop (PLL) characteristics are most often based on a model which is valid only if the intermediate frequency (IF) filter bandwidth is large compared to the PLL bandwidth and the phase error is small. An improved model (called the quasi-linear model) is developed which takes into account small IF filter bandwidths and nonlinear effects associated with large phase errors. By comparison of theoretical and experimental results it is demonstrated that the quasi-linear model accurately predicts PLL characteristics. This is true even for small IF filter bandwidths and large phase errors where the conventional model is invalid. The theoretical and experimental results are used to draw conclusions concerning threshold, multiplier output variance, phase error variance, output signal-to-noise ratio, and signal distortion. The relationship between these characteristics and IF filter bandwidth, modulating signal spectrum, and rms deviation is also determined.

Carden, F.↗
NASA NTRSDate not supplied

Coupling a Computational Fluid Dynamics Model to a Spacecraft Thermal System Model for the DraMS Instrument Thermal Analysis

The Dragonfly Mass Spectrometer (DraMS) is an instrument on the Dragonfly mission, which will spend 7 years in deep space cruise before landing and operating on the surface of Titan. Vacuum thermal analyses are required for deep space cruise, and convection analyses are required for the Titan surface operations. Model exchanges across multiple thermal teams are needed for all phases of the mission. For DraMS, Thermal Desktop® (TD) has been the main thermal analytical tool of choice due to its capability in modeling complex thermal systems with relatively low computational power and for its availability across thermal teams. However, TD does not have computational fluid dynamics (CFD) capability and struggles to accurately capture complex convective behavior. DraMS has fans operating in tandem and gas flow behaviors are not easily predicted due to its complex flow paths. CFD software, such as Fluent, can model and predict such complex flow behaviors, but CFD models are computationally expensive, and its workflow processes are not tailored towards simulating large and complex systems. Therefore, a coupled modeling approach was chosen for DraMS: A TD model was used for simulating all the conductive, radiative, and source terms, while a Fluent CFD model was added on, as needed, to the TD model to provide the convective boundary conditions using the System Coupling software. The coupling software allows the TD and Fluent models to communicate data and arrive at a co-solved and co-converged solution. Furthermore, Thermal Iso-value Exchange (TIE) method was developed to facilitate and improve the TD-Fluent data exchange process. This paper will discuss the analytical studies that were done to verify the accuracy and usability of the coupled approach and the challenges associated, which lead to the development of the TIE approach. DraMS thermal design and co-solved analysis results will also be discussed.

Heat transfer↗