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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 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Nitrogen derived from Combined Algal Processing supports algae cultivation for biofuels

Algae biomass, a biofuel feedstock with potential to reduce global CO 2 emissions, is currently too expensive Nitrogen, a significant input and life cycle cost, requires research on recycling and additional sources to reduce costs. Integral to nitrogen recycling is the knowledge of actual nitrogen requirements in outdoor ponds, thus data from the Unified Field Studies of the Algae Testbed Public-Private Partnership was analyzed. The data showed that Nannochloropsis oceanica used 14–24 mg/L NH 4 + per harvest cycle for robust growth. Nitrogen recycled directly from the algae conversion process will likely be the primary source of nitrogen for algae cultivation. Harvested algae can be fractionated via Combined Algal Processing (CAP), where algae are pretreated, fermented, and the fuel feedstocks (e. g. ethanol, lipids) are removed leaving a nitrogen rich slurry. Chlorella vulgaris grew robustly in nitrogen-free media supplemented with CAP residues through 4 harvest cycles with no inhibition. The amount of nitrogen as free ammonium available for recycling directly without further processing was insufficient (~4% of total needed), thus the nitrogen fixing bacteria, Azotobacter vinelandii, was investigated as a means for increasing ammonium concentration in CAP residues. This organism was shown to be proficient at growth on sugars liberated from algae biomass during pretreatment and sustained algae growth using A. vinelandii supernatants was also demonstrated. Using Azotobacter to increase ammonium concentrations on-site using an inexpensive biological process to generate the necessary ammonium for outdoor algae cultivation improves sustainability of algae biofuels by avoiding the energy intensive steps of typical ammonium production and transport. Furthermore, these results show that byproducts of algae conversion begin to close nitrogen demand and, with further supplementation by diazotrophic bacteria or protein hydrolysis, may completely replace current energyintensive and costly industrial nitrogen sources offering a path to increased economic feasibility and improved life cycle analysis of algae-based biofuels.

09 BIOMASS FUELS↗
DOE OSTI2021

Modeling heat transport processes in enhanced geothermal systems: Validation study from EGS Collab Experiment 1

Heat recovery from enhanced geothermal systems (EGS) is a complex process involving heat transport in both fracture networks and rock formations. A comprehensive understanding of and the ability to model the underlying heat transport mechanisms is important for the success of EGS but remains challenging in practice due to the generally insufficient characterization of EGS reservoirs. In the present study, we analyze an extensively monitored intermediate-scale EGS field experiment performed in a well-characterized testbed. The high-resolution, high-quality measurements from the field experiment enable the development of a high-fidelity model incorporating a well-constrained fracture network. Based on the field experiment, we investigate the complex heat transport processes in an EGS-relevant environment and validate the capability of a numerical approach in simulating these inherently coupled heat transport processes. A series of numerical simulations were performed to study the effects of different heat transport mechanisms, including thermal convection with fracture flow, thermal conduction in rock formations, and the Joule-Thomson effect. The agreement of thermal responses between field measurements and simulation results indicates that our numerical approach can appropriately model the heat transport processes pertaining to heat recovery from EGS reservoirs.

Wu, Hui↗
DOE OSTI2023

Mass measurements show slowdown of rapid proton capture process at waiting-point nucleus 64Ge

Abstract X-ray bursts are among the brightest stellar objects frequently observed in the sky by space-based telescopes. A type-I X-ray burst is understood as a violent thermonuclear explosion on the surface of a neutron star, accreting matter from a companion star in a binary system. The bursts are powered by a nuclear reaction sequence known as the rapid proton capture process (rp process), which involves hundreds of exotic neutron-deficient nuclides. At so-called waiting-point nuclides, the process stalls until a slower β + decay enables a bypass. One of the handful of rp process waiting-point nuclides is 64 Ge, which plays a decisive role in matter flow and therefore the produced X-ray flux. Here we report precision measurements of the masses of 63 Ge, 64,65 As and 66,67 Se—the relevant nuclear masses around the waiting-point 64 Ge—and use them as inputs for X-ray burst model calculations. We obtain the X-ray burst light curve to constrain the neutron-star compactness, and suggest that the distance to the X-ray burster GS 1826–24 needs to be increased by about 6.5% to match astronomical observations. The nucleosynthesis results affect the thermal structure of accreting neutron stars, which will subsequently modify the calculations of associated observables.

Physics↗
DOE OSTI2024

Performance Analysis of Data Processing in Distributed File Systems with Near Data Processing

In the era of big data, the escalating volume and velocity of data generation pose significant challenges in data processing. Traditional systems like Spark and Hadoop manage the increasing amount and velocity of data by improving data placement and processing speeds. However, they face inherent limitations due to the essential data movement required for processing. In this paper, we explore the Skyhook framework, a novel extension of the Ceph distributed system, which significantly reduces the need for data movement. We present an extensive case study using the Skyhook framework, applying it with the TPC-H and K-means clustering algorithms. More specifically, we leverage the TPC-H benchmark to distinguish between CPU-intensive and I/O-intensive tasks. We explore the integration of K-means clustering into SQL, coupled with a near-data processing system to offload the computational burden of the K-means clustering algorithm to storage nodes. We conduct a comprehensive performance evaluation of distributed data processing applications across three processing approaches: traditional layout (baseline), optimized layout, and near-data processing. Additionally, we introduce the use of the FIO tool to simulate real-world system workloads, enabling the measurement of performance metrics such as average latency and CPU utilization. Our research is a significant advance in understanding how to optimize data processing systems to meet the demands of the modern data landscape.

Hou, Shiyue↗
DOE OSTI2021

Monitoring Radiochemical Processing Streams for the 238 Pu Supply Program with Process Pulse II

Oak Ridge National Laboratory (ORNL) is developing advanced spectroscopic and real-time monitoring capabilities to improve the timeliness of analytical measurements and process decisions for the 238Pu Supply Program. Reducing the time, resources, and costs associated with each production campaign is critical because overlapping campaigns will be required to meet the production goals of the National Aeronautics and Space Administration. Real-time, in situ analytical measurements in the heavily shielded hot cells at the Radiochemical Engineering Development Center (REDC) will allow for rapid process information feedback and operational benefits that help the 238Pu supply program scale-up production efforts. Noteworthy steps were taken during Campaign 5 to establish the ability to monitor processing streams in real time with spectrophotometry and a commercially available online monitoring software called The Unscrambler X Process Pulse II (PP) multivariate statistical process monitoring system by Camo Analytics (version 5.60). PP automates univariate-type calculations within the software itself and executes multivariate models built using The Unscrambler X (version 10.4 or newer). The Unscrambler is a commercially available data analysis software made by the same company. PP is composed of easy-to-use-tools for all personnel, including data scientists and technicians. The software can be used to plot analyte concentration profiles, spectral data, and other process variables in real time. All process data are represented in a single view with interactive charts useful for viewing how a process evolves over time.

07 ISOTOPE AND RADIATION SOURCES↗
DOE OSTI2021

Modifications to LEU-Modified Cintichem Process to Allow Processing of Fission-Produced 99 Mo from Up to 750 g of Irradiated Uranium Targets

Eden Radioisotopes, LLC is developing a TRIGA* -sized, 2 MW all-target reactor system licensed from Sandia National Laboratories. This all-target reactor uses up to 60 Argonne-designed annular LEU-foil targets to produce fission-produced 99 Mo. The Eden low-enriched uranium (LEU) target contains ~137 g of uranium and will be irradiated at up to 30 kW, with a target burnup determined by the number of targets processed each week. The annular target utilizes metallic uranium foils 400 mm long by 72 mm wide by 250±25 -µm-thick covered by a thin (10 µm on each face) nickel fission barrier. The foil is placed between two 35 mil aluminum tubes that form the outer and inner walls of the cladding cylinder, which is hydroformed to provide high thermal conductivity within the target. Eden expects to process between three and five targets per process batch, to maintain the process batch 99 Mo inventory at or below 5000 curies to maintain high 99 Mo recovery, within a few hours of discharge from the reactor. Eden expects to meet full U.S. demand by processing 30 targets per week, with each target operated for two weeks at 30 kW. To meet less than full U.S. demand, both the target power and the number of targets processed weekly will be adjusted. With increased 99 Mo production and given the size of U targets processed in a single batch (up to ~750g-U), it is important to identify whether any modifications are needed to the LEU-modified Cintichem process.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2019

Molybdenum Isotopes in Presolar Silicon Carbide Grains: Details of s -process Nucleosynthesis in Parent Stars and Implications for r - and p -processes

We have analyzed molybdenum isotopes, together with strontium and barium isotopes, in 18 presolar silicon carbide grains using the Chicago Instrument for Laser Ionization (CHILI), a resonance ionization mass spectrometer. All observed isotope ratios can be explained by mixtures of pure s-process matter with isotopically solar material. Grain residues were subsequently analyzed for carbon, nitrogen, silicon, and sulfur isotopes, as well as a subset for 26 Al– 26 Mg systematics using the NanoSIMS. These analyses showed that all but one grain are mainstream grains, most probably coming from low-mass asymptotic giant branch (AGB) stars. One grain is of the AB type, for which the origin is still a matter of debate. The high precision of molybdenum isotope measurements with CHILI provides the best estimate to date for s -process molybdenum made in low-mass AGB stars. The average molybdenum isotopic abundances produced by the s -process found in the analyzed mainstream SiC grains are 0% 92 Mo, 0.73% 94 Mo, 13.30% 95 Mo, 36.34% 96 Mo, 9.78% 97 Mo, 39.42% 98 Mo, and 0.43% 100 Mo. Solar molybdenum can be explained as a combination of 45.9% s -process, 30.6% r -process, and 23.5% p -process contributions. Moreover, the observed variability in the individual grain data provides insights into the variability of conditions (neutron density, temperature, and timescale) during s -process nucleosynthesis in the grains' parent stars, as they have subtle effects on specific molybdenum isotope ratios. Lastly, the results indicate that the ratio between p - and r -process molybdenum in presolar SiC from many different types of parent stars is Mo p /Mo r = 0.767, the value inferred for the solar system and consistent with what has been found in bulk samples and leachates of primitive meteorites.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1982

s-process studies in the light of new experimental cross sections - Distribution of neutron fluences and r-process residuals

A best set of neutron-capture cross sections has been evaluated for the most important s-process isotopes. With this data base, s-process studies have been carried out using the traditional model which assumes a steady neutron flux and an exponential distribution of neutron irradiations. The calculated sigma-N curve is in excellent agreement with the empirical sigma-N-values of pure s-process nuclei. Simultaneously, good agreement is found between the difference of solar and s-process abundances and the abundances of pure r-process nuclei. The abundance pattern of the iron group elements where s-process results complement the abundances obtained from explosive nuclear burning is discussed. The results obtained from the traditional s-process model such as seed abundances, mean neutron irradiations, or neutron densities are compared to recent stellar model calculations which assume the He-burning shells of red giant stars as the site for the s-process.

Kaeppeler, F.↗
DOE OSTI2018

An overview of process systems engineering approaches for process intensification: State of the art

Process intensification offers the potential to drastically reduce the energy consumption and cost of producing chemicals from both bulk and distributed feedstocks. This review article aims to offer an extensive survey on state-of-the-art process systems engineering (PSE) approaches for process intensification. From both academic and industrial perspectives, this paper provides an overview of the development of various process intensification technologies, specifically those under the categories of separation, reaction, hybrid reaction/separation, and alternative energy sources. A current status analysis in the areas of modeling and simulation is then provided. An indicative list of PSE publications specialized on process intensification is presented to illustrate the progresses made so far towards the deployment of novel process intensification technologies. We also highlight some recent advances for the modeling, design, and synthesis of intensified systems, as well as for the assessment of their controllability/operability/safety performance. As a result, key open questions in these areas include: (i) how to systematically derive intensified designs, and (ii) how to ensure the operability and optimality of the derived intensified structures while delivering their expected functionality.

42 ENGINEERING↗
DOE OSTI2022

Two-stage membrane-based process utilizing highly CO 2 -selective membranes for cost and energy efficient carbon capture from coal flue gas: A process simulation study

Membrane technology for CO 2 capture has become an attractive strategy due to its cost and energy efficiency and low materials costs. In the past decade, membrane-based process designs for post-combustion power plant CO 2 capture have been developed, utilizing existing highly CO 2 -permeable membranes with relatively low CO 2 /N 2 selectivity (<50), and have obtained reasonably economic carbon capture. However, few membrane-based process designs were proposed for moderate to highly CO 2 -selective membranes (CO 2 /N 2 selectivity of 50–300, and >300, respectively), which have vastly emerged in recent years, such as various facilitated transport membranes (FTMs). Herein, we proposed a two-stage membrane-base process design targeting economic carbon capture from coal-fired flue gas. This process design features the utilization of highly CO 2 -selective membranes for one-stage CO 2 enrichment to 95% dry-base purity in the first stage and recycle of the remaining CO 2 by a highly CO 2 -permeable membrane in the second stage, in order to achieve economic CO 2 capture with 90% capture rate and >95% CO 2 product purity. Through an integration-iteration membrane model and the Aspen Plus process simulation, a sensitivity study of operating pressures (feed and permeate pressures) and membrane properties (CO 2 permeance and CO 2 /N 2 selectivity) was conducted. Critical CO 2 /N 2 selectivity of 300–400 was found for the highly CO 2 -selctive membranes to meet the demand for cost and energy efficient results. The lowest possible membrane area of 4.8 × 10 5 m 2 and fractional energy of 19.3% were obtained, which is comparable to or even more attractive than reported membrane-based process designs. Here, this work provides a new membrane process design option for highly CO 2 -selective membranes and gives insights on the influence of membrane performance and operation condition.

42 ENGINEERING↗
NASA NTRS2024

Correlations of Additive Manufacturing Model-Based Process Metrics With Spatter-Induced Porosity in the Powder Bed Fusion-Laser Beam/Metallic Process

Components fabricated using the powder bed fusion laser beam metallic (PBF-LB/M) additive manufacturing (AM) process comprise a multitude of sequential weld passes. Qualifying materials for components in critical applications requires a thorough understanding of pertinent processing-microstructure-property relationships. Porosity defects have a strong adverse effect on the mechanical properties of a material. The morphology of porosity defects created by lack of fusion in PBF-LB/M often exhibit high aspect ratios that can act as stress concentrators and become crack initiation sites. The occurrence of spatter induced porosity is studied using synchronized AM model-based process metrics and porosity measured by high-resolution X-ray computed tomography. A novel AM process metric is introduced to quantify the relative exposure to spatter ejecta impacts and incorporation throughout the sequence of the PBF-LB/M process. Further characterization using optical metallography and scanning electron microscopy indicated that both keyhole and lack of fusion porosity correlated statistically with the spatter ejecta impact field of the PBF-LB/M process. Both keyhole and lack of fusion porosity can be predicted by the spatter exposure process metric, which can be exploited to control the fusion sequence.

Additive Manufacturing↗
DOE OSTI2018

Process development of 99.95% pure copper processed via selective electron beam melting and its mechanical and physical properties

Highlights: • Additively manufactured dense copper samples (>99.5%) • Measured electrical conductivity >58 MS/m (>100% IACS) • Equiaxed grain structure • 177 N/mm{sup 2} tensile strength, 87 N/mm{sup 2} yield strength, 59% elongation at fracture - Abstract: Additive manufacturing by selective electron beam melting (SEBM) was used to fabricate pure copper specimens. A process window at process temperature of 530 °C, gives the required beam powers and deflection speeds for manufacturing dense specimens (>99.5%). The microstructure of SEBM specimens was analyzed by using optical and scanning electron microscopy (SEM). Electrical conductivity, thermal conductivity, hardness, and mechanical performance were investigated by using eddy current, laser flash analysis, Vickers hardness and tensile tests, respectively. It was found that the variation of beam power and scan speed results in different microstructures from columnar to nearly equiaxed grain. The electrical conductivity of SEBM-processed specimens was above 58 MS/m (>100 IACS) while their hardness was around 55 HV0.05 and 46 HV5 without any dependency on processing parameters within the process window. The tensile tests revealed how vertical cracks affect the mechanical strength under tensile loading condition. The results of this study not only show a reliable process window but also introduce the links between processing parameters, defect formations, conductivity and mechanical strength of pure copper specimens manufactured by SEBM.

36 MATERIALS SCIENCE↗
DOE OSTI2021

High-speed synchrotron X-ray imaging of directed energy deposition of titanium: effects of processing parameters on the formation of entrapped-gas pores

Laser based directed energy deposition (DED) is a competitive method for repairing and remanufacturing metallic parts used in numerous industries including aerospace and biomedical. However, the numerous dynamic phenomena associated with the DED process often result in defects such as entrapped-gas pores, lack of fusion, and undesirable anisotropic properties. The entrapped-gas pore, being one of the most common issues, not only influences melt-pool dynamics but also reduces the fabrication quality and mechanical properties of parts fabricated by the DED process. To reduce and further understand this issue, the real-time observation of the pore formation process needs to be studied first. To directly observe the phenomena in the melt pool, high-speed techniques are needed because rapid solidification leads to rapid pore formation and movement. In-situ high-speed X-ray has been proven to be an effective method in investigating the melt pool dynamics and pore formation mechanisms in the laser powder bed fusion process, in which the fabrication process is quite different from that in DED. Here, the high-speed X-ray method is extended to study the formation of entrapped-gas pores. The real-time formation and quantitative analysis of pores under each set of processing parameters (particle velocity, laser power, and spot welding dwelling time of stationary laser) in the DED process are investigated. We found that the DED with a higher particle velocity (3.19 m/s) produced a smaller average pore size of 27.8 µm and a lower pore area fraction of 0.52%. The DED under lower laser power (156 W) generated a smaller average pore size of 20.3 µm and a lower pore area fraction of 1.94%. The shorter dwelling time (10 ms) benefited the decrease of both average pore size and pore area fraction.

Defect↗
DOE OSTI2020

Data-driven predictive probability density function control of fiber length stochastic distribution shaping in refining process

Pulp is the most important raw material in paper in paper industries, whose Fiber Length Stochastic Distribution (FLSD) shaping directly determines the energy consumption and paper quality of the subsequent papermaking processes. However, the mean and variance are insufficient to describe the output FLSD shaping, which display non-Gaussian distribution properties. Therefore, the traditional control, method based on the mean and variance of fiber length is difficult to control the FLSD shaping effectively. In this paper, a novel data-driven predictive probability density function (PDF) control method is proposed for output FLSD shaping in refining process. Primarily, in order to improve the approximation accuracy of the PDF employing RBF neural network, the parameters (center value and width) of each RBF basis functions are tuned via utilizing iterative learning control (ILC) law, and the corresponding estimations of weights law can be obtained. Secondly, considering that the conventional linear model of weights vector has drawbacks of low accuracy and weak generalization ability, random vector functional link networks (RVFLNs) based data driven nonlinear modelling method is employed to characterize the prediction model between the input variables and weights vector. Finally, in order to reduce the randomness of the output FLSD, a minimum entropy control method under mean constraint is employed to design the predictive PDF controller for the output FLSD shaping with the help of the established nonlinear stochastic distribution model. Both simulations and experiments are given to illustrate the effectiveness and practicability of the proposed method.

Probability debsity function, Fiber length distrib↗
DOE OSTI2016

Defense Waste Processing Facility (DWPF) Viscosity Model: Revisions for Processing High TiO 2 Containing Glasses

Radioactive high-level waste (HLW) at the Savannah River Site (SRS) has successfully been vitrified into borosilicate glass in the Defense Waste Processing Facility (DWPF) since 1996. Vitrification requires stringent product/process (P/P) constraints since the glass cannot be reworked once it is poured into ten foot tall by two foot diameter canisters. A unique “feed forward” statistical process control (SPC) was developed for this control rather than statistical quality control (SQC). In SPC, the feed composition to the DWPF melter is controlled prior to vitrification. In SQC, the glass product would be sampled after it is vitrified. Individual glass property-composition models form the basis for the “feed forward” SPC. The models transform constraints on the melt and glass properties into constraints on the feed composition going to the melter in order to guarantee, at the 95% confidence level, that the feed will be processable and that the durability of the resulting waste form will be acceptable to a geologic repository. The DWPF SPC system is known as the Product Composition Control System (PCCS). The DWPF will soon be receiving wastes from the Salt Waste Processing Facility (SWPF) containing increased concentrations of TiO 2 , Na 2 O, and Cs 2 O . The SWPF is being built to pretreat the high-curie fraction of the salt waste to be removed from the HLW tanks in the F- and H-Area Tank Farms at the SRS. In order to process TiO 2 concentrations >2.0 wt% in the DWPF, new viscosity data were developed over the range of 1.90 to 6.09 wt% TiO 2 and evaluated against the 2005 viscosity model. An alternate viscosity model is also derived for potential future use, should the DWPF ever need to process other titanate-containing ion exchange materials. The ultimate limit on the amount of TiO 2 that can be accommodated from SWPF will be determined by the three PCCS models, the waste composition of a given sludge batch, the waste loading of the sludge batch, and the frit used for vitrification.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗