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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 343 records · Page 19
All sourcesNASA NTRSDOE OSTI
NASA NTRS1983

Solid waste treatment processes for space station

The purpose of this study was to evaluate the state-of-the-art of solid waste(s) treatment processes applicable to a Space Station. From the review of available information a source term model for solid wastes was determined. An overall system is proposed to treat solid wastes under constraints of zero-gravity and zero-leakage. This study contains discussion of more promising potential treatment processes, including supercritical water oxidation, wet air (oxygen) oxidation, and chemical oxidation. A low pressure, batch-type treament process is recommended. Processes needed for pretreatment and post-treatment are hardware already developed for space operations. The overall solid waste management system should minimize transfer of wastes from their collection point to treatment vessel.

Marrero, T. R.↗
DOE OSTI2021

Analysis of Defense Waste Processing Facility Sample: Recycle Collection Tank Sample Batch 4945

The Savannah River National Laboratory (SRNL) was requested by Savannah River Remediation (now Savannah River Mission Completion (SRMC)), through a Technical Task Request, to characterization the “as-received” Recycle Collection Tank (RCT) Sample identified as sample batch 4945 [Sludge Receipt and Adjustment Tank (SRAT) batch 796)], which was delivered to SRNL Shielded Cells on January 28, 2021. The RCT characterization data will be used as input to the Defense Waste Processing Facility (DWPF) Recycle Diversion Project. This RCT report is the first of three sample characterization reports that will be used for this DWPF Project. The other DWPF reports will involve the characterization of the Off-Gas Condensate Tank (OGCT) and the Slurry Mix Evaporator Condensate Tank (SMECT) samples.

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DOE OSTI2022

Analysis of Defense Waste Processing Facility Sample: Recycle Collection Tank Sample Batch 4945

The Savannah River National Laboratory (SRNL) was requested by Savannah River Remediation (now Savannah River Mission Completion (SRMC)), through a Technical Task Request, to characterization the “as-received” Recycle Collection Tank (RCT) Sample identified as sample batch 4945 [Sludge Receipt and Adjustment Tank (SRAT) batch 796)], which was delivered to SRNL Shielded Cells on January 28, 2021. The RCT characterization data will be used as input to the Defense Waste Processing Facility (DWPF) Recycle Diversion Project. This RCT report is the first of three sample characterization reports that will be used for this DWPF Project. The other DWPF reports will involve the characterization of the Off-Gas Condensate Tank (OGCT) and the Slurry Mix Evaporator Condensate Tank (SMECT) samples.

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DOE OSTI2022

Characterization of Tank 11H Samples from Tank Closure Cesium Removal 1A (TCCR 1A) Batch 1

Savannah River Mission Completion (SRMC) is currently operating the Tank Closure Cesium Removal 1A (TCCR 1A) process to remove 137 Cs from tank waste supernate using an ion exchange process. The TCCR 1A unit processes dissolved salt fed from Tank 10H through a series of ion exchange columns containing crystalline silicotitanate (CST, IONSIV TM R9120-B, 30x60) and the effluent is then discharged to Tank 11H. In support of the TCCR 1A program, SRNL analyzed samples taken from Tank 11H (without tank mixing) before, during, and at the completion of TCCR 1A Batch 1 processing. Tank 11H serves as the receipt tank for the filtered and cesium removed product from the TCCR 1A system. Processing of Batch 1 commenced on January 13, 2022 and completed on February 17, 2022, after processing approximately 70,100 gallons. A pre-production sample was collected from the heel remaining in Tank 11H just before Batch 1 processing began. In addition, five interim surface samples were collected from Tank 11H during processing, and both a surface and a variable depth sample (VDS, ~7” from tank bottom) were collected just after processing completed. Analysis of all samples included density and gamma spectroscopy, in addition to a more comprehensive suite of analytes for the pre- and post-production samples. The density of the pre-production sample was the highest of all samples measured and was then observed to decrease for the first two interim samples, followed by becoming fairly consistent for the remainder of the samples (~1.3 g/mL). The density of 1.3 g/mL is similar to the density measured for one of the three Tank 10H qualification samples (HTF-10-21-126). The 137 Cs activity was found to decrease as additional decontaminated effluent from the TCCR columns was added to Tank 11H during processing; however, an increase in activity was observed during periods of no processing which can be attributed to leaching of 137 Cs from the known solids in Tank 11H. The Cs isotope concentrations in the Tank 11H postproduction surface sample were determined to be 99.7-99.8% lower than the concentrations measured in the Tank 10H feed as measured by mass spectrometry.

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DOE OSTI2024

Analysis of the Sludge Batch 9 (Macrobatch 11) DWPF Pour Stream Glass Sample Collected During the Nitric-Glycolic Acid Flowsheet Transition

A pour stream (PS) sample taken near the end of processing of Sludge Batch 9 (SB9, Macrobatch 11) during the transition to the nitric-glycolic acid (NGA) flowsheet was analyzed by the Savannah River National Laboratory (SRNL). The SB9 NGA PS sample was taken on 12/18/2022 during Melter Feed Batch 823 associated with glass canister S04773 and was transferred to SRNL in Primary Container PC0139 in February 2023.

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DOE OSTI2020

NREL's Biochemical Conversion Pilot Plant Capabilities

NREL's biochemical conversion plant is a flexible pilot plant for testing a wide range of bio-based technologies for producing renewable fuels and byproducts. The biochemical conversion pilot plant is housed in the Integrated Biorefinery Research Facility located on the National Renewable Energy Laboratory's (NREL's) main campus. The facility provides industry partners the opportunity to test and develop their own biorefining technology using NREL equipment or rental equipment that can be brought into the plant. The pilot plant can process materials up to one dry ton per day in an integrated fashion using a variety of operating modes including batch, fed-batch, and continuous processing.

biochemical↗
DOE OSTI2020

Real‐Time Optical Process Monitoring for Structure and Property Control of Aerosol Jet Printed Functional Materials

Abstract Aerosol jet printing is a popular digital additive manufacturing method for flexible and hybrid electronics, but it lacks sophisticated real‐time process control schemes that would enable more widespread adoption in manufacturing environments. Here, an optical measurement system is introduced to track the aerosol density upstream of the printhead. The measured optical extinction, combined with the aerosol flow rate, is directly related to deposition rate and accurately predicts functional materials properties such as the electrical resistance of printed graphene films. This real‐time system offers a compelling solution for process drift and batch‐to‐batch variability, rendering it a valuable tool for both real‐time control of aerosol jet printing and fundamental studies of the underlying process science.

Tafoya, Rebecca R.↗
DOE OSTI2022

Dante

SAND2022-12905 O Dante is a physical security simulation package used in evaluating protective staffing and physical security elements against adversarial threats. Dante simulates force-on-force scenarios in a batch Monte Carlo process. Analysts use the included Scenario Editor to define the scenarios for their site and then execute and analyze the results using the Batch Manager tool. Dante provides insight into how well a security system performs against threats and lets analysts mine the results for key indicators of system performance. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Hart, Brian↗
NASA NTRS1993

Investigation for improving Global Positioning System (GPS) orbits using a discrete sequential estimator and stochastic models of selected physical processes

GEODYNII is a conventional batch least-squares differential corrector computer program with deterministic models of the physical environment. Conventional algorithms were used to process differenced phase and pseudorange data to determine eight-day Global Positioning system (GPS) orbits with several meter accuracy. However, random physical processes drive the errors whose magnitudes prevent improving the GPS orbit accuracy. To improve the orbit accuracy, these random processes should be modeled stochastically. The conventional batch least-squares algorithm cannot accommodate stochastic models, only a stochastic estimation algorithm is suitable, such as a sequential filter/smoother. Also, GEODYNII cannot currently model the correlation among data values. Differenced pseudorange, and especially differenced phase, are precise data types that can be used to improve the GPS orbit precision. To overcome these limitations and improve the accuracy of GPS orbits computed using GEODYNII, we proposed to develop a sequential stochastic filter/smoother processor by using GEODYNII as a type of trajectory preprocessor. Our proposed processor is now completed. It contains a correlated double difference range processing capability, first order Gauss Markov models for the solar radiation pressure scale coefficient and y-bias acceleration, and a random walk model for the tropospheric refraction correction. The development approach was to interface the standard GEODYNII output files (measurement partials and variationals) with software modules containing the stochastic estimator, the stochastic models, and a double differenced phase range processing routine. Thus, no modifications to the original GEODYNII software were required. A schematic of the development is shown. The observational data are edited in the preprocessor and the data are passed to GEODYNII as one of its standard data types. A reference orbit is determined using GEODYNII as a batch least-squares processor and the GEODYNII measurement partial (FTN90) and variational (FTN80, V-matrix) files are generated. These two files along with a control statement file and a satellite identification and mass file are passed to the filter/smoother to estimate time-varying parameter states at each epoch, improved satellite initial elements, and improved estimates of constant parameters.

Goad, Clyde C.↗
NASA NTRS1985

Processing Digital Imagery Data

Earth Resources Laboratory Applications Software (ELAS) is geobased information system designed for analyzing and processing digital imagery data. ELAS offers user of remotely sensed data wide range of easy to use capabilities in areas of land cover analysis. ELAS system written in FORTRAN and Assembler for batch or interactive processing.

Conner, P. K.↗
DOE OSTI2015

Results Of Initial Analyses Of The Salt (Macro) Batch 9 Tank 21H Qualification Samples

Savannah River National Laboratory (SRNL) analyzed samples from Tank 21H in support of qualification of Interim Salt Disposition Project (ISDP) Salt (Macro) Batch 9 for processing through the Actinide Removal Process (ARP) and the Modular Caustic-Side Solvent Extraction Unit (MCU). This document reports the initial results of the analyses of samples of Tank 21H. Analysis of the Tank 21H Salt (Macro) Batch 9 composite sample indicates that the material does not display any unusual characteristics. Further results on the chemistry and other tests will be issued in the future.

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DOE OSTI2015

Results of initial analyses of the salt (macro) batch 9 tank 21H qualification samples

Savannah River National Laboratory (SRNL) analyzed samples from Tank 21H in support of qualification of Interim Salt Disposition Project (ISDP) Salt (Macro) Batch 9 for processing through the Actinide Removal Process (ARP) and the Modular Caustic-Side Solvent Extraction Unit (MCU). This document reports the initial results of the analyses of samples of Tank 21H. Analysis of the Tank 21H Salt (Macro) Batch 9 composite sample indicates that the material does not display any unusual characteristics or observations, such as floating solids, the presence of large amount of solids, or unusual colors. Further results on the chemistry and other tests will be issued in the future.

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DOE OSTI2017

Results of initial analyses of the salt (macro) batch 10 tank 21H qualification samples

Savannah River National Laboratory (SRNL) analyzed samples from Tank 21H in support of qualification of Interim Salt Disposition Project (ISDP) Salt (Macro) Batch 10 for processing through the Actinide Removal Process (ARP) and the Modular Caustic-Side Solvent Extraction Unit (MCU). This document reports the initial results of the analyses of samples of Tank 21H. Analysis of the Tank 21H Salt (Macro) Batch 10 composite sample indicates that the material does not display any unusual characteristics or observations, such as floating solids, the presence of large amount of solids, or unusual colors. Further sample results will be reported in a future document. This memo satisfies part of Deliverable 3 of the Technical Task Request (TTR).

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DOE OSTI2017

Results of initial analyses of the salt (macro) batch 11 Tank 21H qualification samples

Savannah River National Laboratory (SRNL) analyzed samples from Tank 21H in support of qualification of Interim Salt Disposition Project (ISDP) Salt (Macro) Batch 11 for processing through the Actinide Removal Process (ARP) and the Modular Caustic-Side Solvent Extraction Unit (MCU). This document reports the initial results of the analyses of samples of Tank 21H. Analysis of the Tank 21H Salt (Macro) Batch 11 composite sample indicates that the material does not display any unusual characteristics or observations, such as floating solids, the presence of large amounts of solids, or unusual colors. Further sample results will be reported in a future document. This memo satisfies part of Deliverable 3 of the Technical Task Request (TTR).

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DOE OSTI2025

Geometric GNNs for charged particle tracking at GlueX

Nuclear physics experiments are aimed at uncovering the fundamental building blocks of matter. The experiments involve high-energy collisions that produce complex events with many particle trajectories. Tracking charged particles resulting from collisions in the presence of a strong magnetic field is critical to enable the reconstruction of particle trajectories and precise determination of interactions. It is traditionally achieved through combinatorial approaches that scale worse than linearly as the number of hits grows. Since particle hit data naturally form a point cloud and can be structured as graphs, graph neural networks (GNNs) emerge as an intuitive and effective choice for this task. In this study, we evaluate the GNN model for track finding on the data from the GlueX experiment at Jefferson Lab. We use simulation data to train the model and test on both simulation and real GlueX measurements. We demonstrate that GNN-based track finding outperforms the currently used traditional method at GlueX in terms of segment-based efficiency at a fixed purity while providing faster inferences. We show that the GNN model can achieve significant speedup by processing multiple events in batches, which exploits the parallel computation capability of graphical processing units (GPUs). Finally, we compare the GNN implementation on GPU and field-programmable gate array and describe the trade-off.

batched GNN pipeline↗
DOE OSTI2023

Evaluation Of Glass Density to Support the Estimation of Fissile Mass Loadings in Sludge Batch 10 Glasses

Per a directive from the Department of Energy Savannah River Operations Office (DOE-SR) in 2008, the fissile mass loading concentration must remain below 897 g/m 3 in each high-level waste (HLW) glass canister produced by the Defense Waste Processing Facility (DWPF). To support Sludge Batch 5 (SB5) processing, the Savannah River National Laboratory (SRNL) developed a technical basis that facilitates the evaluation of fissile mass loading of the glass product. The calculation is based on the iron (Fe) concentration in the glass as determined by measurements from the Slurry Mix Evaporator acceptability analysis as well as the glass density. In April 2022, a subsequent DOE-SR directive increased the fissile mass loading limit to 2500 g/m 3 beginning with Sludge Batch 11. Thus, the 897 g/m 3 limit still applies to Sludge Batch 10 (SB10) processing. For SB5 through initial Sludge Batch 9 (SB9) processing prior to coupled operation with the Salt Waste Processing Facility (SWPF), SRNL provided DWPF a bounding glass density value that was based on a statistical evaluation of density measurements. To eliminate the need for experimental work, a composition-based density model for HLW glasses was developed at SRNL in 2019. The objective of this report is to present the bounding glass density determined with the composition-based density model for SB10 sludge-only (SO) and coupled processing.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
NASA NTRS1975

Image Data Processing System (IDAPS) user manual, S-056 experiment. Volume 1: System description. Volume 2: Batch IDAPS. Volume 3: Interactive IDAPS

Image data processing system (IDAPS) developed to satisfy the image processing requirements of the Skylab S-056 experiment is described. The S-056 experiment was designed to obtain high-resolution photographs of the sun in the far ultraviolet, or soft X-ray, portion of the electromagnetic spectrum. Thirty-five thousand photographs were obtained by the three flights of the program; and, faced with such a massive volume of imagery, the designers of the experiment decided to develop a computer-based system which would reduce the image processing workload. The purpose of the IDAPS User Manual is to give the IDAPS user the necessary information and instructions to effectively utilize the system.

Source record↗