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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 1,693 records · Page 94
All sourcesNASA NTRSDOE OSTI
NASA NTRS1985

Fast laser-induced aerosol formation for visualization of gas flows

A technique for aerosol seeding of gas flows by laser-induced particle formation is demonstrated using a pulsed Nd:YAG laser (1.06 microns) for optical breakdown of a mixture of SF6 and H2 in an inert carrier gas. It is noted that, contrary to the smoke-wire approach, the laser-induced particles form first in zones of high turbulence, since mixing enhances coagulation. The method also allows seeding to be performed in locations hardly accessible otherwise and is mechanically nonintrusive. Finally, a study of the mixture and the breakdown effects indicates that for H2:SF6 ratios between 3:1 and 15:1 the particle formation is only limited by the physics of the gas/particle conversion.

Hassa, C.↗
NASA NTRS1985

What are the best radar wavelengths, incidence angles and polarizations for geologic applications? A statistical approach

Linear discriminant analysis of multifrequency and multipolarization radar scatterometer data of lava flows and sedimentary rocks indicates that the lava flows can be separated by age and the sedimentary rocks can be discriminated from one another. The optimum wavelengths, polarizations and incidence angles among those available for these problems was determined by the discriminant analysis program. For separation of the lava flows, shorter wavelengths, smaller incidence angles and horizontal polarization are best. A SIR-C radar configuration could provide nearly complete discrimination of these lava flows. Conversely, the longer wavelengths, larger incidence angles and vertical polarization was preferred for sedimentary rocks, perhaps due to the slight vegetation cover. Satisfactory classification of sedimentary rocks requires more radar data than for the lavas. These results are potentially useful both for radar system configuration and for geological applications. The method developed here may provide a rationale for user specification of imaging system parameters.

Blom, R.↗
NASA NTRS1992

Lidar conversion parameters derived from SAGE II extinction measurements

SAGE II multiwavelength aerosol extinction measurements are used to estimate mass- and extinction-to-backscatter conversion parameters. The basis of the analysis is the principal component analysis of the SAGE II extinction kernels to estimate both total aerosol mass and aerosol backscatter at a variety of wavelengths. Comparisons of coincident SAGE II extinction profiles with 0.694-micron aerosol backscatter profiles demonstrate the validity of the method.

Thomason, L. W.↗
NASA NTRS1999

Robotic Rock Classification

This report describes a three-month research program undertook jointly by the Robotics Institute at Carnegie Mellon University and Ames Research Center as part of the Ames' Joint Research Initiative (JRI.) The work was conducted at the Ames Research Center by Mr. Liam Pedersen, a graduate student in the CMU Ph.D. program in Robotics under the supervision Dr. Ted Roush at the Space Science Division of the Ames Research Center from May 15 1999 to August 15, 1999. Dr. Martial Hebert is Mr. Pedersen's research adviser at CMU and is Principal Investigator of this Grant. The goal of this project is to investigate and implement methods suitable for a robotic rover to autonomously identify rocks and minerals in its vicinity, and to statistically characterize the local geological environment. Although primary sensors for these tasks are a reflection spectrometer and color camera, the goal is to create a framework under which data from multiple sensors, and multiple readings on the same object, can be combined in a principled manner. Furthermore, it is envisioned that knowledge of the local area, either a priori or gathered by the robot, will be used to improve classification accuracy. The key results obtained during this project are: The continuation of the development of a rock classifier; development of theoretical statistical methods; development of methods for evaluating and selecting sensors; and experimentation with data mining techniques on the Ames spectral library. The results of this work are being applied at CMU, in particular in the context of the Winter 99 Antarctica expedition in which the classification techniques will be used on the Nomad robot. Conversely, the software developed based on those techniques will continue to be made available to NASA Ames and the data collected from the Nomad experiments will also be made available.

Hebert, Martial↗
DOE OSTI2023

Metal complexes and methods of making the same

Disclosed herein are embodiments of metal complexes and methods of making the same. The disclosed method embodiments provide a one-step approach to making metal complexes, such as complexes comprising lanthanide metals, rare earth metals, transition metals, main group metals, and/or actinide metals that can be used various applications, such as in separations technology, catalysis (e.g., catalysts for pharmaceutical synthesis and/or catalysts for biomass conversion), nuclear chemistry, LED phosphors, scintillator materials, magnetic materials, and nuclear fuels.

Kiplinger, Jaqueline↗
DOE OSTI2024

Key Experimental Considerations When Evaluating Functional Ionic Liquids for Combined Capture and Electrochemical Conversion of CO 2

Ionic liquids (ILs) are considered functional electrolytes for the electrocatalytic reduction of CO 2 (ECO 2 R) due to their role in the double-layer structure formation and increased CO 2 availability at the electrode surface, which reduces the voltage requirement. However, not all ILs are the same, considering the purity and degree of the functionality of the IL. Further, there are critical experimental factors that impact the evaluation of ILs for ECO 2 R including the reference electrode, working electrode construction, cosolvent selection, cell geometry, and whether the electrochemical cell is a single compartment or a divided cell. Here, we describe improved synthesis methods of imidazolium cyanopyrrolide IL for electrochemical studies in consideration of precursor composition and reaction time. We explored how IL with cosolvents (i.e. acetonitrile, dimethylformamide, dimethyl sulfoxide, propylene carbonate, and n-methyl-2-pyrrolidone) affects conductivity, CO 2 mass transport, and ECO 2 R activation overpotential together with the effects of electrode materials (Sn, Ag, Au, and glassy carbon). Acetonitrile was found to be the best solvent for lowering the onset potential and increasing the catalytic current density for the production of CO owing to the enhanced ion mobility in combination with the silver electrode. Further, the ECO 2 R activity of molecular catalysts Ni(cyclam)Cl 2 and iron tetraphenylsulfonato porphyrin (FeTPPS) on the carbon cloth electrode maintained high Faradaic efficiencies for CO in the presence of the IL. This study presents best practices for examining nontraditional multifunctional electrolytes amenable to integrated CO 2 capture and conversion technologies for homogeneous and heterogeneous ECO 2 R.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Thermochemical Conversion of Sugarcane Bagasse: A Comprehensive Analysis of Ignition and Burnout Temperatures

The Brazilian sugarcane industry generates a significant amount of waste each year, which should be properly analyzed and studied to allow an adequate recovery and application supported by the best understanding of its properties. The present work reports the ignition and burnout temperatures of sugarcane bagasse (SCB) obtained after performing a thermal analysis using four different heating rates. The intersection method (IM) and deviation method (DM) were employed to approach the ignition and burnout temperatures of the sugarcane bagasse. The ignition temperatures of the SCB measured from IM are between 250 and 263 °C, and their burnout temperatures are between 357 and 377 °C. The ignition temperature was in the range of 205 °C to 236 °C for the DM. IM is recommended for determining the ignition and burnout temperatures. In TGA, the heating rates in the range of 10 °C·min−1 and 15 °C·min−1 are suggested due to their accuracy and the contribution to timesaving in the analysis.

Morais, Leandro C. de (ORCID:0000000314685453)↗
DOE OSTI2024

Development of algorithms for augmenting and replacing conventional process control using reinforcement learning

Here, this work seeks to allow for the online operation and training of model-free reinforcement learning (RL) agents but limit the risk to system equipment and personnel. The parallel implementation of RL alongside more conventional process control (CPC) allows for the RL algorithm to learn from CPC. The past performance of both methods are assessed on a continuous basis allowing for a transition from CPC to RL and, if needed, transitioning back to CPC from RL. This allows for the RL algorithm to slowly and safely assume control of the process without significant degradation in control performance. It is shown that the RL can derive a near optimal policy even when coupled with a suboptimal CPC. It is also demonstrated that the coupled RL-CPC algorithm learns at a faster rate than traditional RL methods of exploration while the algorithm’s performance does not deteriorate below CPC, even when exposed to an unknown operating condition.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2023

Towards deep computer vision for in-line defect detection in polymer electrolyte membrane fuel cell materials

Polymer Electrolyte Membrane (PEM) fuel cells are a promising source of alternative energy. However, their production is limited by a lack of well-established methods for quality control of their constituent materials like the membrane-electrode assembly during roll-to-roll manufacturing. One potential solution is the implementation of deep learning methods to detect unwanted defects through their detection in scanned images. Here we explore the detection of defects like scratches, pinholes, and scuffs in a sample dataset of PEM optical images using two deep learning algorithms: Patch Distribution Modeling (PaDiM) for unsupervised anomaly detection and Faster-RCNN for supervised object detection. Both methods achieve scores on performance metrics (ROC-AUC and PRO-AUC for PaDiM and AP for Faster-RCNN) that are comparable to their scores on benchmark datasets. These methods also have the potential to detect a wider range of defects compared to IR thermography and previous optical inspection methods. Overall, deep learning shows promise at detecting relevant defects of interest and has the potential to achieve real-time defect detection.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2021

Comparison of powder bed fusion and directed energy deposition for tailoring mechanical properties of traditionally brittle alloys

The mechanical performance of an Fe-Co intermetallic alloy processed by laser powder bed fusion (L-PBF) and laser directed energy deposition (L-DED) additive manufacturing is compared. L-PBF material was characterized by high strength (500–550 MPa) and high ductility (35%) in tension, corresponding to a ~250% increase in strength and an order-of-magnitude improvement in ductility relative to conventional material. Conversely, L-DED material exhibited similarly poor tensile properties to the conventional wrought alloy, with low strength (200–300 MPa) and low ductility (0–2.7%). Finally, the disparity in properties between L-PBF and L-DED material is discussed in the context of the fundamental differences between manufacturing methods.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Laser-assisted high-energy proton pulse extraction for feasibility study of co-located muon source at the SNS

Here, we have experimentally demonstrated the first non-intrusive 1-GeV proton beam extraction for the generation of muons with a temporal structure optimized for Muon Spin Relaxation/Rotation/Resonance (μSR) applications. The proton pulses are extracted based on the laser neutralization of 1 GeV hydrogen ion (H - ) beam in the high energy beam transport of the Spallation Neutron Source (SNS) accelerator. The maximum flux of the extracted proton beam based on laser neutralization causes only 0.2% reduction of the total proton beam used for neutron production, a marked difference from the 20% reduction at other co-located muon and neutron facilities, and thus the proposed method will result in negligible impact on the SNS operation. This paper describes the development of a fiber/solid-state hybrid laser system that has high flexibility of pulse structure and output power, initial experiments on laser neutralization of beam and separation of H 0 beam from the existing SNS accelerator beam line, conversion of H 0 to proton at the SNS linac dump, and measurement results of 30 ns/50 kHz proton pulses. This system conclusively demonstrates the feasibility of laser-based proton beam extraction to power a world-leading μSR facility at the SNS.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2023

Recent advances in biomass pretreatment using biphasic solvent systems

The complexity and recalcitrance of lignocellulosic biomass seriously hinder its subsequent conversion to liquid fuels. To achieve high-value utilization of lignocellulosic biomass, the physical–chemical barrier should be overcome through appropriate pretreatment techniques to improve the accessibility of cellulose for efficient enzymatic hydrolysis. With the rapid emergence of novel pretreatment solvents, biphasic solvent pretreatments represent a nascent and green pretreatment method that has shown outstanding advantages and broad application prospects in the biorefinery of lignocellulosic substrates due to its ability to provide economically viable biomass upgrading, the separation process for products in the solvent phase, and the reutilization of solvents. Herein, different types of biphasic solvents (e.g., 2-methyltetrahydrofuran, methyl isobutyl ketone, 1-butanol, phenoxyethanol, ionic liquids, and deep eutectic solvents) were reviewed systematically, including the fundamental designs of biphasic solvents for biomass pretreatment, their effect on the fractionation of individual biomass components (e.g., carbohydrate and lignin) and the enzymatic hydrolysis performance, and the coproduction of furan and hydroxymethylfurfural. Finally, the main pros and cons of these different biphasic solvent systems are summarized, and the future development direction is also proposed. Finally, this review can provide a reference for designing and selecting effective biphasic pretreatment methods for various types of lignocellulosic biomass.

09 BIOMASS FUELS↗
DOE OSTI2018

Bioenergy Research Centers

Multiple societal benefits underlie U.S. Department of Energy (DOE) research efforts to support a viable and sustainable domestic biofuel and bioproducts industry from nonfood lignocellulosic plant biomass. These benefits include ensuring future energy security, lowering greenhouse gases to mitigate climate impacts, diversifying the range of available biobased products, producing fewer toxic chemicals and byproducts, creating jobs in rural areas, and improving the trade balance. Cellulose—the most abundant biological material on Earth—is contained within plant cell walls in the form of long, tightly bound chains of sugars (polysaccharides) that can be converted into biofuels and bioproducts by microbes. Physically accessing these sugars, however, is difficult because the cellulose is embedded within a matrix of other polymers including hemicellulose and lignin, making it resistant to degradation. This resistance, called recalcitrance, along with a lack of efficient methods to convert lignocellulose to useful products are major impediments to the cost-effective production of biofuels and bioproducts from plant biomass. Innovation stemming from advanced biotechnology-based research is key to accelerating needed improvements in the sustainable production of lignocellulosic biomass, its deconstruction into sugars and lignin, and conversion.

09 BIOMASS FUELS↗
DOE OSTI2022

Feedstock-Conversion Interface Consortium: Failure Mode and Effects Analysis Summary Report (FY2022)

This report provides an overview of the development of failure modes and effects analysis (FMEA) and its implementation as a systematic criticality and risk assessment tool supporting a quality by design (QbD) approach for FCIC research. This report also provides a high-level overview of the results for the FMEA evaluation of two feedstock preprocessing system configurations: (1) generation of pine residue materials for high-temperature pyrolysis conversion and (2) generation of corn stover materials for low-temperature conversion using deacetylation and disc mechanical refining pretreatment for fermentation to hydrocarbons. For the results presented in this report, our FMEA interviews included two approaches. The first approach was to perform FMEA interviews for the entire system of unit operations giving a wholistic system level view. The second approach consisted of detailed interviews for each individual unit operation within the system allowing for a “deep dive” into the specific failures for the individual components within the configuration. These two approaches provide different resolutions of information. The FMEA results of this report were focused on failures associated with meeting critical quality attributes (CQAs) identified for the target conversion processes for each processed feedstock type. The information gathered through the FMEA interviews include estimations of risk scores for meeting each given CQA specification, identification of the impacts for not meeting a CQA specification, capturing causes associated with material attributes and process parameters for each failure, identification of current detection methods, and speculation of potential mitigation strategies for decreasing a failure’s risk score. The complete results of all FMEA interviews are provided in the Appendices of this report.

09 BIOMASS FUELS↗
NASA NTRS2000

Biological Moleculars: Have Most of Our Problems Already Been Solved?

Evolution has resulted in biological machinery that engineers have great reason to envy and at present can only poorly mimic. This is not just a curiosity as biological systems perform many functions that are desired industrial processes. Examples include photosynthesis, chemosynthesis, energy storage, low temperature chemical conversion, reproducible manufacture of chemical compounds, etc. The bases of biological machinery are the proteins and nucleic acids that comprise living organisms. Each molecule functions as a part of a biological machine. In many cases the molecule can be properly regarded as a stand alone machine of its own. Concepts and methods for harnessing the power of biological molecules exist but are often overlooked in the industrial world. Some are old and appear crude but are quite effective, e.g. the fermentation of grains and fruits. Currently, there is a revolution in progress regarding the harnessing biological processes. These include techniques such as genetic manipulation via polymerase chain reaction, forced evolution also known as evolution in a test tube, determination of molecular structure, and combinatorial chemistry. The following is a brief discussion on how these processes are performed and how they may relate to industrial and aerospace processes.

Downey, James P.↗