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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 253 records · Page 14
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

OSU/NETL/Sandia/LBNL IDAES (CRADA Final Report)

The objective of this CRADA is to facilitate the cooperation among the Ohio State Univesity and the collaborators for the Institute for the Design of Advanced Energy Systems (IDAES). The goal is to develop, validate, and use a suite of process models based on the Ohio State's Fe-based coal direct chemical looping (CDCL) combustion process. This collaboration will provide Ohio State with a greater fundamental understanding of their chemical looping process, will help to improve the process efficiency, and will thus enable a greater probability of developing a commercial success. This collaboration will provide the IDAES team with detailed real-world process data to validate and demonstrate the effectiveness of its toolset.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2023

Numerical Investigation of the characteristics of pressurized biomass-oxy-combustion

As a second generation of oxy-fuel combustion technologies, pressurized oxy-combustion has a potential to improve the process efficiency and economy. With the modern decarbonization needs, biomass combustion is considered to be nearly CO2 neutral, and thus co-firing biomass with coal in an oxy-combustion process can achieve a negative CO2 balance. The size of the biomass fuel particles is a key parameter in an entrained flow combustor because large biomass particles, exceeding some threshold size, may only partially be burnt due to the restrictions on the heat transport, thereby diminishing the combustion efficiency. While such a threshold particle size has been scrutinized at an atmospheric pressure, the present study extends the analysis to elevated pressures. Specifically, two scenarios were set up, for experimental-scale and full-scale pressurized oxy-combustors, with the threshold sizes of biomass particles appearing 0.5 mm and 5 mm, respectively, without temperature gradient in biomass particles. With temperature gradient, the parametric study included the particles in the range from 0.15 mm to 5 mm. It is shown that the thermal-thin model is applicable to spherical biomass particles not exceeding 0.15 mm. The impact of the heating rate on biomass particle devolatilization was also investigated and the biomass devolatilization could happen in less than 1 second; the same amount of heat energy could induce different volatile release rates.

Li, Lei↗
DOE OSTI2013

Chemical annotation of small and peptide-like molecules at the Protein Data Bank

Over the past decade, the number of polymers and their complexes with small molecules in the Protein Data Bank archive (PDB) has continued to increase significantly. To support scientific advancements and ensure the best quality and completeness of the data files over the next 10 years and beyond, the Worldwide PDB partnership that manages the PDB archive is developing a new deposition and annotation system. This system focuses on efficient data capture across all supported experimental methods. The new deposition and annotation system is composed of four major modules that together support all of the processing requirements for a PDB entry. In this article, we describe one such module called the Chemical Component Annotation Tool. This tool uses information from both the Chemical Component Dictionary and Biologically Interesting molecule Reference Dictionary to aid in annotation. Benchmark studies have shown that the Chemical Component Annotation Tool provides significant improvements in processing efficiency and data quality.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Kinetic and Mechanistic Understanding of Boron-Containing Catalysts for the Production of Light Olefins through Selective Oxidation

In recent years, an abundance of natural gas obtained from shale deposits has created opportunities for the US chemical industry to establish new and more efficient processes for the production of chemical intermediates and polymers. For example, the replacement of petroleum-derived naphtha as a to shale-derived ethane as feedstocks has made the production of ethylene/polyethylene less costly. However, this shift in feedstock has led to lower production of propylene from steam crackers, and new “on-purpose” light olefin production technologies have been implemented to bridge the gap between propylene supply and demand. The most important of these processes is direct propane dehydrogenation (PDH), but catalyst deactivation and high temperatures lead to high capital and operating costs. Oxidative dehydrogenation of propane (ODHP) is an efficient alternative to PDH, but high selectivity to CO2 from previous metal oxide catalyst prevents implementation. Hexagonal boron nitride (hBN) and other boron-containing materials have been recently developed as highly selective catalysts for both ODHP and oxidative cracking, surpassing previous systems. Much is still unknown in regard to the mechanism and the dynamic surface changes that occur under reaction conditions. This research project aims to combine in situ/operando spectroscopic investigation and kinetic studies to elucidate the interplay between the proposed gas-phase mechanism and the surface structures on the working catalyst. These insights will be leveraged to create a framework for optimizing reaction conditions and material synthesis for the next generation of boron-containing selective oxidation catalysts.

02 PETROLEUM↗
NASA NTRS1984

A SAR correlation algorithm which accommodates large-range migration

This paper presents an algorithm for azimuth correlation of synthetic aperture radar (SAR) data with extraordinarily large-range migration which cannot be accommodated by the existing frequency domain interpolation approach used in current Seasat SAR processing. A mathematical model is provided for the SAR range-correlated point-target response both in the spatial and frequency domains. A simple and efficient processing algorithm derived from the exact two-dimensional correlation algorithm is given. This algorithm enables azimuth correlation by two cascaded one-dimensional correlation steps. The first step is to transform the range-correlated SAR data into the frequency domain in azimuth, followed by a newly developed range convolution filter to correct the range-dispersed spectrum of the range-correlated point-target response (RCPTR). The second step is the frequency-domain range migration correction approach for the azimuth compression. Simulation results provided here indicate that this processing algorithm yields a satisfactory compressed impulse response for SAR data with large-range migration whereas previous methods were subject to a broadening of the impulse response along range.

Jin, M. Y.↗
DOE OSTI2017

Trace: a high-throughput tomographic reconstruction engine for large-scale datasets

Abstract Background Modern synchrotron light sources and detectors produce data at such scale and complexity that large-scale computation is required to unleash their full power. One of the widely used imaging techniques that generates data at tens of gigabytes per second is computed tomography (CT). Although CT experiments result in rapid data generation, the analysis and reconstruction of the collected data may require hours or even days of computation time with a medium-sized workstation, which hinders the scientific progress that relies on the results of analysis. Methods We present Trace, a data-intensive computing engine that we have developed to enable high-performance implementation of iterative tomographic reconstruction algorithms for parallel computers. Trace provides fine-grained reconstruction of tomography datasets using both (thread-level) shared memory and (process-level) distributed memory parallelization. Trace utilizes a special data structure called replicated reconstruction object to maximize application performance. We also present the optimizations that we apply to the replicated reconstruction objects and evaluate them using tomography datasets collected at the Advanced Photon Source. Results Our experimental evaluations show that our optimizations and parallelization techniques can provide 158× speedup using 32 compute nodes (384 cores) over a single-core configuration and decrease the end-to-end processing time of a large sinogram (with 4501 × 1 × 22,400 dimensions) from 12.5 h to <5 min per iteration. Conclusion The proposed tomographic reconstruction engine can efficiently process large-scale tomographic data using many compute nodes and minimize reconstruction times.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
NASA NTRS1983

SAR correlation technique - An algorithm for processing data with large range walk

This paper presents an algorithm for synthetic aperture radar (SAR) azimuth correlation with extraneously large range migration effect which can not be accommodated by the existing frequency domain interpolation approach used in current SEASAT SAR processing. A mathematical model is first provided for the SAR point-target response in both the space (or time) and the frequency domain. A simple and efficient processing algorithm derived from the hybrid algorithm is then given. This processing algorithm enables azimuth correlation by two steps. The first step is a secondary range compression to handle the dispersion of the spectra of the azimuth response along range. The second step is the well-known frequency domain range migration correction approach for the azimuth compression. This secondary range compression can be processed simultaneously with range pulse compression. Simulation results provided here indicate that this processing algorithm yields a satisfactory compressed impulse response for SAR data with large range migration.

Jin, M.↗
NASA NTRS2007

High Performance Processors for Space Environments: A Subproject of the NASA Exploration Missions Systems Directorate "Radiation Hardened Electronics for Space Environments" Technology Development Program

Implementation of challenging Exploration Systems Missions Directorate objectives and strategies can be constrained by onboard computing capabilities and power efficiencies. The Radiation Hardened Electronics for Space Environments (RHESE) High Performance Processors for Space Environments project will address this challenge by significantly advancing the sustained throughput and processing efficiency of high-per$ormance radiation-hardened processors, targeting delivery of products by the end of FY12.

Johnson, M.↗
DOE OSTI2016

Application of a theory and simulation-based convective boundary mixing model for AGB star evolution and nucleosynthesis

The s-process nucleosynthesis in Asymptotic giant branch (AGB) stars depends on the modeling of convective boundaries. We present models and s-process simulations that adopt a treatment of convective boundaries based on the results of hydrodynamic simulations and on the theory of mixing due to gravity waves in the vicinity of convective boundaries. Hydrodynamics simulations suggest the presence of convective boundary mixing (CBM) at the bottom of the thermal pulse-driven convective zone. Similarly, convection-induced mixing processes are proposed for the mixing below the convective envelope during third dredge-up (TDU), where the {sup 13}C pocket for the s process in AGB stars forms. In this work, we apply a CBM model motivated by simulations and theory to models with initial mass M = 2 and M=3 M{sub ⊙}, and with initial metal content Z = 0.01 and Z = 0.02. As reported previously, the He-intershell abundances of {sup 12}C and {sup 16}O are increased by CBM at the bottom of the pulse-driven convection zone. This mixing is affecting the {sup 22}Ne(α, n){sup 25}Mg activation and the s-process efficiency in the {sup 13}C-pocket. In our model, CBM at the bottom of the convective envelope during the TDU represents gravity wave mixing. Furthermore, we take into account the fact that hydrodynamic simulations indicate a declining mixing efficiency that is already about a pressure scale height from the convective boundaries, compared to mixing-length theory. We obtain the formation of the {sup 13}C-pocket with a mass of ≈10{sup −4} M{sub ⊙}. The final s-process abundances are characterized by 0.36<[s/Fe]<0.78 and the heavy-to-light s-process ratio is −0.23<[hs/ls]<0.45. Finally, we compare our results with stellar observations, presolar grain measurements and previous work.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2011

A rare terminal dinitrogen complex of chromium

Cis and trans-Cr–N₂ complexes supported by the diphosphine ligand P{sup Ph}₂N{sup Bn}₂ have been prepared. Positioned pendant amines in the second coordination sphere influence the thermodynamically preferred geometric isomer. Electronic structure calculations indicate negligible Cr–N₂ back-bonding; rather, electronic polarization of N₂ ligand is thought to stabilize Cr–N₂ binding.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

LTE-P-8 Gas permeability

A procedure for the measurement of gas permeability of an anion exchange membrane (AEM). During the course of the electrochemical reaction, low gas permeation of hydrogen and oxygen through the membrane is crucial to run the process efficiently. The gas permeation rate can be measured using (A) pressure permeation cell, (B) electrochemical monitoring cell, (C) microelectrode and (D) in-situ measurement in MEA. The process relies on a chronoamperometric technique to accurately measure the gas permeation rate across the membrane.

08 HYDROGEN↗
DOE OSTI2015

Equipment Loan for Concentrated PV Cavity Converter (PVCC) Research: (CRADA CRD-08-285 Final Report)

Interest in High Concentration Photovoltaics (HCPV) for terrestrial applications has significantly grown in recent years. A major driver behind this growth trend is the availability of high efficiency multi-junction (MJ) cells that promise reliable operation under high concentrations (500 to 1000 suns). The primary impact of HCPV on the solar electricity cost is the dramatic reduction in cell cost. For terrestrial HCPV systems, operating at concentrations >/=500 suns, the expensive MJ cells are marginally affordable. Most recently, triple-junction test cells have achieved a conversion efficiency of over 40% under concentrated sunlight. Photovoltaic Cavity Converter (PVCC) is a multi-bandgap, high concentration PV device developed by United Innovations, Inc., under subcontract to NREL. The lateral- (2- dimensional) structure of PVCC, as opposed to vertical multi-junction (MJ) structure, helps to circumvent most of the developmental challenges MJ technology has yet to overcome. This CRADA will allow the continued development of this technology by United Innovations. cost. For terrestrial HCPV systems, operating at concentrations >/=500 suns, the expensive MJ cells are marginally affordable. Most recently, triple-junction test cells have achieved a conversion efficiency of over 40% under concentrated sunlight. Photovoltaic Cavity Converter (PVCC) is a multi-bandgap, high concentration PV device developed by United Innovations, Inc., under subcontract to NREL. The lateral- (2- dimensional) structure of PVCC, as opposed to vertical multi-junction (MJ) structure, helps to circumvent most of the developmental challenges MJ technology has yet to overcome. This CRADA will allow the continued development of this technology by United Innovations. cost. For terrestrial HCPV systems, operating at concentrations >/=500 suns, the expensive MJ cells are marginally affordable. Most recently, triple-junction test cells have achieved a conversion efficiency of over 40% under concentrated sunlight. Photovoltaic Cavity Converter (PVCC) is a multi-bandgap, high concentration PV device developed by United Innovations, Inc., under subcontract to NREL. The lateral- (2- dimensional) structure of PVCC, as opposed to vertical multi-junction (MJ) structure, helps to circumvent most of the developmental challenges MJ technology has yet to overcome. This CRADA will allow the continued development of this technology by United Innovations. cost. For terrestrial HCPV systems, operating at concentrations >/=500 suns, the expensive MJ cells are marginally affordable. Most recently, triple-junction test cells have achieved a conversion efficiency of over 40% under concentrated sunlight. Photovoltaic Cavity Converter (PVCC) is a multi-bandgap, high concentration PV device developed by United Innovations, Inc., under subcontract to NREL. The lateral- (2- dimensional) structure of PVCC, as opposed to vertical multi-junction (MJ) structure, helps to circumvent most of the developmental challenges MJ technology has yet to overcome. This CRADA will allow the continued development of this technology by United Innovations.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2012

H Canyon Processing in Correlation With FH Analytical Labs

Management of radioactive chemical waste can be a complicated business. H Canyon and F/H Analytical Labs are two facilities present at the Savannah River Site in Aiken, SC that are at the forefront. In fact H Canyon is the only large-scale radiochemical processing facility in the United States and this processing is only enhanced by the aid given from F/H Analytical Labs. As H Canyon processes incoming materials, F/H Labs provide support through a variety of chemical analyses. Necessary checks of the chemical makeup, processing, and accountability of the samples taken from H Canyon process tanks are performed at the labs along with further checks on waste leaving the canyon after processing. Used nuclear material taken in by the canyon is actually not waste. Only a small portion of the radioactive material itself is actually consumed in nuclear reactors. As a result various radioactive elements such as Uranium, Plutonium and Neptunium are commonly found in waste and may be useful to recover. Specific processing is needed to allow for separation of these products from the waste. This is H Canyon's specialty. Furthermore, H Canyon has the capacity to initiate the process for weapons-grade nuclear material to be converted into nuclear fuel. This is one of the main campaigns being set up for the fall of 2012. Once usable material is separated and purified of impurities such as fission products, it can be converted to an oxide and ultimately turned into commercial fuel. The processing of weapons-grade material for commercial fuel is important in the necessary disposition of plutonium. Another processing campaign to start in the fall in H Canyon involves the reprocessing of used nuclear fuel for disposal in improved containment units. The importance of this campaign involves the proper disposal of nuclear waste in order to ensure the safety and well-being of future generations and the environment. As processing proceeds in the fall, H Canyon will have a substantial number of samples being sent to F/H Labs. All analyses of these samples are imperative to safe and efficient processing. The important campaigns to occur would be impossible without feedback from analyses such as chemical makeup of solutions, concentrations of dissolution acids and nuclear material, as well as nuclear isotopic data. The necessity of analysis for radiochemical processing is evident. Processing devoid of F/H Lab's feedback would go against the ideals of a safety-conscious and highly accomplished processing facility such as H Canyon.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2023

PhytoOracle: Scalable, modular phenomics data processing pipelines

As phenomics data volume and dimensionality increase due to advancements in sensor technology, there is an urgent need to develop and implement scalable data processing pipelines. Current phenomics data processing pipelines lack modularity, extensibility, and processing distribution across sensor modalities and phenotyping platforms. To address these challenges, we developed PhytoOracle (PO), a suite of modular, scalable pipelines for processing large volumes of field phenomics RGB, thermal, PSII chlorophyll fluorescence 2D images, and 3D point clouds. PhytoOracle aims to ( i ) improve data processing efficiency; ( ii ) provide an extensible, reproducible computing framework; and ( iii ) enable data fusion of multi-modal phenomics data. PhytoOracle integrates open-source distributed computing frameworks for parallel processing on high-performance computing, cloud, and local computing environments. Each pipeline component is available as a standalone container, providing transferability, extensibility, and reproducibility. The PO pipeline extracts and associates individual plant traits across sensor modalities and collection time points, representing a unique multi-system approach to addressing the genotype-phenotype gap. To date, PO supports lettuce and sorghum phenotypic trait extraction, with a goal of widening the range of supported species in the future. At the maximum number of cores tested in this study (1,024 cores), PO processing times were: 235 minutes for 9,270 RGB images (140.7 GB), 235 minutes for 9,270 thermal images (5.4 GB), and 13 minutes for 39,678 PSII images (86.2 GB). These processing times represent end-to-end processing, from raw data to fully processed numerical phenotypic trait data. Repeatability values of 0.39-0.95 (bounding area), 0.81-0.95 (axis-aligned bounding volume), 0.79-0.94 (oriented bounding volume), 0.83-0.95 (plant height), and 0.81-0.95 (number of points) were observed in Field Scanalyzer data. We also show the ability of PO to process drone data with a repeatability of 0.55-0.95 (bounding area).

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Life cycle assessment of a novel gas switching reforming for sustainable hydrogen production with CO2 capture

Gas switching reforming for hydrogen production (GSR-H2) presents an efficient, low-carbon hydrogen production method that incorporates integrated carbon capture, offering efficiency gains over traditional methods such as proton exchange membrane (PEM) electrolysis, steam methane reforming (SMR) and the newer method of chemical looping reforming (CLR). GSR-H2 has been demonstrated in lab scale which operates as an exothermic process that eliminates the need for additional natural gas combustion, using its own waste heat to generate process steam and partially offset energy usage through electricity production. Beyond its thermal self-sufficiency, GSR-H2 advances upon CLR by integrating all reaction stages within a single reactor cluster, eliminating the complexities of solid circulation, reducing capital costs, and enhancing overall process efficiency. This streamlined design simplifies scale-up and enables inherent CO2 separation with minimal energy penalty, making GSR-H2 a highly competitive pathway for low-carbon hydrogen production. This study presents the first life cycle assessment (LCA) of GSR-H2, offering a novel evaluation of this new process’s environmental impacts across diverse energy scenarios. Key findings reveal that in the renewables-powered scenario, GSR-H2 achieves a GWP of 2.77 kg CO2 eq per kg H2, a substantial improvement over SMR’s 10.4 kg CO2 eq and close to the low emissions of CLR (1.84 kg CO2 eq) and PEM electrolysis (1.85 kg CO2 eq). These results demonstrate GSR-H2’s competitive advantage as a lower-emission alternative, combining design simplicity and efficiency gains, especially in renewable-integrated systems. These results establish GSR-H2 as a competitive, scalable option for hydrogen production, particularly in decarbonization efforts.

03 NATURAL GAS↗
DOE OSTI2023

Thermochemical processes for CO 2 hydrogenation to fuels and chemicals: Challenges and opportunities

This manuscript discusses the potential use of CO 2 as a carbon and oxygen carrier to return it to the carbon life cycle in the form of fuels or chemicals via thermochemical catalytic pathways. Theoretically, CO 2 hydrogenation can form a variety of fuels and chemicals. Practically, however, the selectivity, conversion, operating range, and kinetic limitations and operational cost determine the end product. Because of their high value and versatility as a chemical or fuel, small olefins (i.e., C 2 H 4 ) and methanol are often considered as target species. Whether alcohol or olefin formation, CH 4 and CO are the nature’s primary choices of CO 2 conversion. They can be formed over a wide operating temperature, pressure, and CO 2 :H 2 ratios. They are often competitive carbon species in olefin or methanol formation steps. Although they are less valuable as end products, they can be used as intermediate species. Secondary processes of CO and CH 4 to form chemicals and fuels can increase the overall CO 2 hydrogenation yield. Independent of the choice of end product, CO 2 hydrogenation requires hydrogen. Pure hydrogen derived mostly from fossil fuels adds to the overall process cost and also increases the CO 2 emissions. Hydrogen produced from water electrolysis is a renewable green pathway but is limited by the process efficiency and cost. As an alternative to pure hydrogen, low-value, small chain paraffins are suggested as the hydrogen carriers. Carbon dioxide–assisted oxidative dehydrogenation of paraffins to olefins process is a direct pathway to olefin formation. The paper discusses these potential pathways for CO 2 utilization based on theoretical analysis and recent advances in academia and industry.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Wireless Interrogation of High Temperature Surface Acoustic Wave Dynamic Strain Sensor

Dynamic strain sensing is necessary for high-temperature harsh-environment applications, including powerplants, oil wells, aerospace, and metal manufacturing. Monitoring dynamic strain is important for structural health monitoring and condition-based maintenance in order to guarantee safety, increase process efficiency, and reduce operation and maintenance costs. Sensing in high-temperature (HT), harsh-environments (HE) comes with challenges including mounting and packaging, sensor stability, and data acquisition and processing. Wireless sensor operation at HT is desirable because it reduces the complexity of the sensor connection, increases reliability, and reduces costs. Surface acoustic wave resonators (SAWRs) are compact, can operate wirelessly and battery-free, and have been shown to operate above 1000°C, making them a potential option for HT HE dynamic strain sensing. This paper presents wirelessly interrogated SAWR dynamic strain sensors operating around 288.8MHz at room temperature and tested up to 400°C. The SAWRs were calibrated with a high-temperature wired commercial strain gauge. The sensors were mounted onto a tapered-type Inconel constant stress beam and the assembly was tested inside a box furnace. The SAWR sensitivity to dynamic strain excitation at 25°C, 100°C, and 400°C was .439 μV/με, 0.363μV/με, and .136 μV/με, respectively. Furthermore, the experimental outcomes verified that inductive coupled wirelessly interrogated SAWRs can be successfully used for dynamic strain sensing up to 400°C.

47 OTHER INSTRUMENTATION↗
DOE OSTI2024

Transitioning from Simulation to Reality: Applying Chatter Detection Models to Real-World Machining Data

Chatter, a self-excited vibration phenomenon, is a critical challenge in high-speed machining operations, affecting tool life, product surface quality, and overall process efficiency. While machine learning models trained on simulated data have shown promise in detecting chatter, their real-world applicability remains uncertain due to discrepancies between simulated and actual machining environments. The primary goal of this study is to bridge the gap between simulation-based machine learning models and real-world applications by developing and validating a Random Forest-based chatter detection system. This research focuses on improving manufacturing efficiency through reliable chatter detection by integrating Operational Modal Analysis (OMA), Receptance Coupling Substructure Analysis (RCSA), and Transfer Learning (TL). The study applies a Random Forest classification model trained on over 140,000 simulated machining datasets, incorporating techniques like Operational Modal Analysis (OMA), Receptance Coupling Substructure Analysis (RCSA), and Transfer Learning (TL) to adapt the model for real-world operational data. The model is validated against 1600 real-world machining datasets, achieving an accuracy of 86.1%, with strong precision and recall scores. The results demonstrate the model’s robustness and potential for practical implementation in industrial settings, highlighting challenges such as sensor noise and variability in machining conditions. This work advances the use of predictive analytics in machining processes, offering a data-driven solution to improve manufacturing efficiency through more reliable chatter detection.

42 ENGINEERING↗