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At least 1,099 records · Page 61

Mathematical Analysis and Optimization of Infiltration Processes

A variety of infiltration techniques can be used to fabricate solid materials, particularly composites. In general these processes can be described with at least one time dependent partial differential equation describing the evolution of the solid phase, coupled to one or more partial differential equations describing mass transport through a porous structure. This paper presents a detailed mathematical analysis of a relatively simple set of equations which is used to describe chemical vapor infiltration. The results demonstrate that the process is controlled by only two parameters, alpha and beta. The optimization problem associated with minimizing the infiltration time is also considered. Allowing alpha and beta to vary with time leads to significant reductions in the infiltration time, compared with the conventional case where alpha and beta are treated as constants.

Chang, H.-C.↗

Microchannel reactive distillation for the conversion of aqueous ethanol to ethylene

Here we demonstrate the proof-of-concept for microchannel reactive distillation for alcohol-to-jet application: combining ethanol/water separation and ethanol dehydration in one unit operation. Ethanol is first distilled into the vapor phase, converted to ethylene and water, and then the water co-product is condensed to shift the reaction equilibrium. Process intensification is achieved through rapid mass transfer—ethanol stripping from thin wicks using novel microchannel architectures—leading to lower residence time and improved separation efficiency. Energy savings are realized with integration of unit operations. For example, heat of condensing water can offset vaporizing ethanol. Furthermore, the dehydration reaction equilibrium shifts towards completion by immediate removal of the water byproduct upon formation while maintaining aqueous feedstock in the condensed phase. For aqueous ethanol feedstock (40% w ), 71% ethanol conversion with 91% selectivity to ethylene was demonstrated at 220 °C, 600 psig, and 0.28 h -1 wt hour space velocity. 2.7 stages of separation were also demonstrated, under these conditions, using a device length of 8.3 cm. This provides a height equivalent of a theoretical plate (HETP), a measure of separation efficiency, of ~3.3 cm. By comparison, conventional distillation packing provides an HETP of ~30 cm. Thus, 9.1× reduction in HETP was demonstrated over conventional technology, providing a means for significant energy savings and an example of process intensification. Finally, preliminary process economic analysis indicates that by using microchannel reactive distillation technology, the operating and capital costs for the ethanol separation and dehydration portion of an envisioned alcohol-to-jet process could be reduced by at least 35% and 55%, respectively, relative to the incumbent technology, provided future improvements to microchannel reactive distillation design and operability are made.

10 SYNTHETIC FUELS↗

Silicon production process evaluations

The chemical engineering analysis of the preliminary process design of a process for producing solar cell grade silicon from dichlorosilane is presented. A plant to produce 1,000 MT/yr of silicon is analyzed. Progress and status for the plant design are reported for the primary activities of base case conditions (60 percent), reaction chemistry (50 percent), process flow diagram (35 percent), energy balance (10 percent), property data (10 percent) and equipment design (5 percent).

Source record↗

Orbit Determination Toolbox

The Orbit Determination Toolbox is an orbit determination (OD) analysis tool based on MATLAB and Java that provides a flexible way to do early mission analysis. The toolbox is primarily intended for advanced mission analysis such as might be performed in concept exploration, proposal, early design phase, or rapid design center environments. The emphasis is on flexibility, but it has enough fidelity to produce credible results. Insight into all flight dynamics source code is provided. MATLAB is the primary user interface and is used for piecing together measurement and dynamic models. The Java Astrodynamics Toolbox is used as an engine for things that might be slow or inefficient in MATLAB, such as high-fidelity trajectory propagation, lunar and planetary ephemeris look-ups, precession, nutation, polar motion calculations, ephemeris file parsing, and the like. The primary analysis functions are sequential filter/smoother and batch least-squares commands that incorporate Monte-Carlo data simulation, linear covariance analysis, measurement processing, and plotting capabilities at the generic level. These functions have a user interface that is based on that of the MATLAB ODE suite. To perform a specific analysis, users write MATLAB functions that implement truth and design system models. The user provides his or her models as inputs to the filter commands. The software provides a capability to publish and subscribe to a software bus that is compliant with the NASA Goddard Mission Services Evolution Center (GMSEC) standards, to exchange data with other flight dynamics tools to simplify the flight dynamics design cycle. Using the publish and subscribe approach allows for analysts in a rapid design center environment to seamlessly incorporate changes in spacecraft and mission design into navigation analysis and vice versa.

Carpenter, James R.↗

On-Orbit Solar Dynamics Observatory (SDO) Star Tracker Warm Pixel Analysis

This paper describes the process of identification and analysis of warm pixels in two autonomous star trackers on the Solar Dynamics Observatory (SDO) mission. A brief description of the mission orbit and attitude regimes is discussed and pertinent star tracker hardware specifications are given. Warm pixels are defined and the Quality Index parameter is introduced, which can be explained qualitatively as a manifestation of a possible warm pixel event. A description of the algorithm used to identify warm pixel candidates is given. Finally, analysis of dumps of on-orbit star tracker charge coupled devices (CCD) images is presented and an operational plan going forward is discussed. SDO, launched on February 11, 2010, is operated from the NASA Goddard Space Flight Center (GSFC). SDO is in a geosynchronous orbit with a 28.5 inclination. The nominal mission attitude points the spacecraft X-axis at the Sun, with the spacecraft Z-axis roughly aligned with the Solar North Pole. The spacecraft Y-axis completes the triad. In attitude, SDO moves approximately 0.04 per hour, mostly about the spacecraft Z-axis. The SDO star trackers, manufactured by Galileo Avionica, project the images of stars in their 16.4deg x 16.4deg fields-of-view onto CCD detectors consisting of 512 x 512 pixels. The trackers autonomously identify the star patterns and provide an attitude estimate. Each unit is able to track up to 9 stars. Additionally, each tracker calculates a parameter called the Quality Index, which is a measure of the quality of the attitude solution. Each pixel in the CCD measures the intensity of light and a warns pixel is defined as having a measurement consistently and significantly higher than the mean background intensity level. A warns pixel should also have lower intensity than a pixel containing a star image and will not move across the field of view as the attitude changes (as would a dim star image). It should be noted that the maximum error introduced in the star tracker attitude solution during suspected warm pixel corruptions is within the specified 36 attitude error budget requirement of [35, 70, 70] arcseconds. Thus, the star trackers provided attitude accuracy within the specification for SDO. The star tracker images are intentionally defocused so each star image is detected in more than one CCD pixel. The position of each star is calculated as an intensity-weighted average of the illuminated pixels. The exact method of finding the positions is proprietary to the tracker manufacturer. When a warm pixel happens to be in the vicinity of a star, it can corrupt the calculation of the position of that particular star, thereby corrupting the estimate of the attitude.

Felikson, Denis↗

Evaluation of AI-enabled Digital Documented Safety Analysis

The National Reactor Innovation Center (NRIC) is leading a transformative initiative to accelerate advanced reactor deployment by fundamentally reimagining how nuclear safety basis documentation is developed, reviewed, and maintained. Traditional Documented Safety Analysis (DSA) processes for DOE-authorized facilities rely on static, document-centric workflows that consume significant time and resources, exemplified by recent major licensing efforts requiring hundreds of thousands of staff hours and millions of pages of documentation review. These conventional approaches create barriers to the rapid, cost-effective deployment of advanced reactors that America's future energy needs demand. NRIC's DOE Authorization Digital Transformation Project addresses these challenges through an innovative framework that integrates artificial intelligence (AI), digital engineering, and systems-based data management into a cohesive digital ecosystem. This white paper presents NRIC's methodology for evaluating AI-enabled document generation capabilities within this broader digital infrastructure, using the Demonstration of Microreactor Experiments (DOME) facility as a pilot case study. The evaluation will assess an AI tool's ability to generate a Preliminary Documented Safety Analysis (PDSA) through progressive integration stages—from standalone document processing to full digital thread connectivity—while maintaining rigorous verification, validation, and regulatory acceptance standards. By establishing dynamic, traceable connections between design data and safety documentation, NRIC's approach has the potential to reduce both document development time and regulatory review cycles by as much as 50%, while simultaneously improving accuracy, consistency, and traceability. This initiative represents a critical step toward establishing reusable digital infrastructure that reactor developers can leverage to accelerate their path from concept to commercial operation, directly supporting NRIC's mission to demonstrate and deploy advanced nuclear energy technologies.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗

A standardized quantitative analysis strategy for stable isotope probing metagenomics

ABSTRACT Stable isotope probing (SIP) facilitates culture-independent identification of active microbial populations within complex ecosystems through isotopic enrichment of nucleic acids. Many DNA-SIP studies rely on 16S rRNA gene sequences to identify active taxa, but connecting these sequences to specific bacterial genomes is often challenging. Here, we describe a standardized laboratory and analysis framework to quantify isotopic enrichment on a per-genome basis using shotgun metagenomics instead of 16S rRNA gene sequencing. To develop this framework, we explored various sample processing and analysis approaches using a designed microbiome where the identity of labeled genomes and their level of isotopic enrichment were experimentally controlled. With this ground truth dataset, we empirically assessed the accuracy of different analytical models for identifying active taxa and examined how sequencing depth impacts the detection of isotopically labeled genomes. We also demonstrate that using synthetic DNA internal standards to measure absolute genome abundances in SIP density fractions improves estimates of isotopic enrichment. In addition, our study illustrates the utility of internal standards to reveal anomalies in sample handling that could negatively impact SIP metagenomic analyses if left undetected. Finally, we present SIPmg , an R package to facilitate the estimation of absolute abundances and perform statistical analyses for identifying labeled genomes within SIP metagenomic data. This experimentally validated analysis framework strengthens the foundation of DNA-SIP metagenomics as a tool for accurately measuring the in situ activity of environmental microbial populations and assessing their genomic potential. IMPORTANCE Answering the questions, “who is eating what?” and “who is active?” within complex microbial communities is paramount for our ability to model, predict, and modulate microbiomes for improved human and planetary health. These questions can be pursued using stable isotope probing to track the incorporation of labeled compounds into cellular DNA during microbial growth. However, with traditional stable isotope methods, it is challenging to establish links between an active microorganism’s taxonomic identity and genome composition while providing quantitative estimates of the microorganism’s isotope incorporation rate. Here, we report an experimental and analytical workflow that lays the foundation for improved detection of metabolically active microorganisms and better quantitative estimates of genome-resolved isotope incorporation, which can be used to further refine ecosystem-scale models for carbon and nutrient fluxes within microbiomes.

54 ENVIRONMENTAL SCIENCES↗

Multi-Angle Implementation of Atmospheric Correction (MAIAC) Algorithm

Multi-Angle Implementation of Atmospheric Correction (MAIAC) is a new algorithm developed for MODIS. MAIAC uses a time series analysis and processing of groups of pixels to perform simultaneous retrievals of aerosol properties and surface bidirectional reflectance without typical assumptions about the surface. It is a generic algorithm which works over both dark and bright land surfaces, including deserts. MAIAC has an internal Cloud Mask, a dynamic land-water-snow classification and a surface change mask which allows it to flexibly choose processing path over different surfaces. A distinct feature of MAIAC is a high 1 km resolution of aerosol retrievals which is required in different applications including the air quality analysis. The novel features of MAIAC include the high quality cloud mask, discrimination of aerosol type, including biomass burning smoke and dust, and detection of surface change - all required for high quality aerosol retrievals. An overview of the algorithm, results of AERONET validation, and examples of comparison with MODIS Collection 5 aerosol product and Deep Blue algorithm for different parts of the world, will be presented.

Lyapustin, A.↗

Improved Single-Cell Proteome Coverage Using Narrow-Bore Packed NanoLC Columns and Ultrasensitive Mass Spectrometry

Single-cell proteomics can provide unique insights into biological processes by resolving heterogeneity that is obscured by bulk measurements. Gains in the overall sensitivity and proteome coverage through improvements in sample processing and analysis increase the information content obtained from each cell, particularly for less abundant proteins. Here we report on improved single-cell proteome coverage through the combination of the previously developed Nanodroplet Processing in One Pot for Trace Samples (nanoPOTS) platform with further miniaturization of liquid chromatography (LC) separations and implementation of an ultrasensitive latest-generation mass spectrometry (MS) instrument. Following nanoPOTS sample preparation, protein digest from single cells were separated using a 20-µm-i.d. in-house-packed nanoLC column. Separated peptides were ionized using an etched fused silica emitter capable of stable ionization at the ~20 nL/min flow rate provided by the LC separation. Ultrasensitive LC-MS analysis was achieved using the Orbitrap Eclipse Tribrid mass spectrometer. An average of 362 protein groups were identified by MS/MS from single HeLa cells, and 874 protein groups were identified using the Match Between Runs (MBR) feature of MaxQuant. This represents a >70% increase in label-free proteome coverage for single cells relative to previous efforts using larger-bore (30-µm-i.d.) LC columns coupled to a previous-generation MS (Orbitrap Fusion Lumos).

Cong, Yongzheng↗

An empirical analysis of the distribution of overshoots in a stationary Gaussian stochastic process

The frequency distribution of overshoots in a stationary Gaussian stochastic process is analyzed. The primary processes involved in this analysis are computer simulation and statistical estimation. Computer simulation is used to simulate stationary Gaussian stochastic processes that have selected autocorrelation functions. An analysis of the simulation results reveals a frequency distribution for overshoots with a functional dependence on the mean and variance of the process. Statistical estimation is then used to estimate the mean and variance of a process. It is shown that for an autocorrelation function, the mean and the variance for the number of overshoots, a frequency distribution for overshoots can be estimated.

Carter, M. C.↗

Single‐Step Deformation Processing of Ultrathin Lithium Foil and Strip

Abstract Next‐generation, high‐efficiency energy storage and conversion systems require development of lithium metal batteries. But the high cost of production and constraints on thickness of lithium (anode) foils continue to limit adoption for integration into battery cell architectures. Here, a novel lithium anode manufacturing solution is demonstrated – single‐step production of ultrathin gauge foil formats directly from solid ingot. Hybrid cutting‐based deformation processes, involving large plastic strains and strain rates, produce foil to sub‐10 µm thickness, with surface quality even superior to present Li anode processing routes. Energy analysis shows the single‐stage processing is ≈50% more efficient than conventional processing by extrusion‐rolling. Through in situ force measurements and high‐speed imaging of the cutting it also characterize – for the first time – the flow stress of Li to strain rates of 800 sec −1 , revealing a power‐law relationship. The results present a paradigm shift in manufacturing and integration of solid lithium anodes for energy applications.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Laser annealing of amorphous/poly: Silicon solar cell material flight experiment

The preliminary design proposed for the microelectronics materials processing equipment is presented. An overall mission profile, description of all processing steps, analysis methods and measurement techniques, data acquisition and storage, and a preview of the experimental hardware are included. The goal of the project is to investigate the viability of material processing of semiconductor microelectronics materials in a micro-gravity environment. The two key processes are examined: (1) Rapid Thermal Annealing (RTA) of semiconductor thin films and damaged solar cells, and (2) thin film deposition using a filament evaporator. The RTA process will be used to obtain higher quality crystalline properties from amorphous/poly-silicon films. RTA methods can also be used to repair radiation-damaged solar cells. On earth this technique is commonly used to anneal semiconductor films after ion-implantation. The damage to the crystal lattice is similar to the defects found in solar cells which have been exposed to high-energy particle bombardment.

Cole, Eric E.↗

Some practicable applications of quadtree data structures/representation in astronomy

Development of quadtree as hierarchical data structuring technique for representing spatial data (like points, regions, surfaces, lines, curves, volumes, etc.) has been motivated to a large extent by storage requirements of images, maps, and other multidimensional (spatially structured) data. For many spatial algorithms, time-efficiency of quadtrees in terms of execution may be as important as their space-efficiency concerning storage conditions. Briefly, the quadtree is a class of hierarchical data structures which is based on the recursive partition of a square region into quadrants and sub-quadrants until a predefined limit. Beyond the wide applicability of quadtrees in image processing, spatial information analysis, and building digital databases (processes becoming ordinary for the astronomical community), there may be numerous further applications in astronomy. Some of these practicable applications based on quadtree representation of astronomical data are presented and suggested for further considerations. Examples are shown for use of point as well as region quadtrees. Statistics of different leaf and non-leaf nodes (homogeneous and heterogeneous sub-quadrants respectively) at different levels may provide useful information on spatial structure of astronomical data in question. By altering the principle guiding the decomposition process, different types of spatial data may be focused on. Finally, a sampling method based on quadtree representation of an image is proposed which may prove to be efficient in the elaboration of sampling strategy in a region where observations were carried out previously either with different resolution or/and in different bands.

Pasztor, L.↗

Remote Sensing Information Science Research

This document is the final report summarizing research conducted by the Remote Sensing Research Unit, Department of Geography, University of California, Santa Barbara under National Aeronautics and Space Administration Research Grant NAG5-10457. This document describes work performed during the period of 1 March 2001 thorough 30 September 2002. This report includes a survey of research proposed and performed within RSRU and the UCSB Geography Department during the past 25 years. A broad suite of RSRU research conducted under NAG5-10457 is also described under themes of Applied Research Activities and Information Science Research. This research includes: 1. NASA ESA Research Grant Performance Metrics Reporting. 2. Global Data Set Thematic Accuracy Analysis. 3. ISCGM/Global Map Project Support. 4. Cooperative International Activities. 5. User Model Study of Global Environmental Data Sets. 6. Global Spatial Data Infrastructure. 7. CIESIN Collaboration. 8. On the Value of Coordinating Landsat Operations. 10. The California Marine Protected Areas Database: Compilation and Accuracy Issues. 11. Assessing Landslide Hazard Over a 130-Year Period for La Conchita, California Remote Sensing and Spatial Metrics for Applied Urban Area Analysis, including: (1) IKONOS Data Processing for Urban Analysis. (2) Image Segmentation and Object Oriented Classification. (3) Spectral Properties of Urban Materials. (4) Spatial Scale in Urban Mapping. (5) Variable Scale Spatial and Temporal Urban Growth Signatures. (6) Interpretation and Verification of SLEUTH Modeling Results. (7) Spatial Land Cover Pattern Analysis for Representing Urban Land Use and Socioeconomic Structures. 12. Colorado River Flood Plain Remote Sensing Study Support. 13. African Rainfall Modeling and Assessment. 14. Remote Sensing and GIS Integration.

Clarke, Keith C.↗

The International DORIS Service contribution to ITRF2020

For the realization of the 2020 International Terrestrial Reference Frame (ITRF2020), the International DORIS Service delivered to the International Earth Rotation and Reference Systems Service (IERS) a set of 1456 weekly solution files from 1993.0 to 2021.0 including station coordinates and Earth orientation parameters (EOPs). The data come from fourteen DORIS satellites: TOPEX/Poseidon, SPOT-2, SPOT-3, SPOT-4, SPOT-5, Envisat, Jason-1, Jason-2, Cryosat-2, Saral, HY-2A, Jason-3, Sentinel-3A and Sentinel-3B. In their processing, the four analysis centers which contributed to the DORIS combined solution used the latest time variable gravity models, the new mean pole and diurnal-subdiurnal tidal EOP models recommended by IERS. In addition, all the analysis centers included in their processing precise SPOT-5 solar panel angle values and quaternions for, at least, the Jason satellites. Furthermore, a new Alcatel phase center variation model was implemented for the ITRF2020 processing. The main objective of this study is to present the combination process and to analyze the impact of the new modeling on the performance of the new combined solution. Comparisons with the IDS contribution to ITRF2014 show that i) the application of the new phase center variations for the Alcatel DORIS ground antennas in the data processing combined with the gradual replacement over time of the Alcatel by Starec antennas implies a scale drift from 1993.0 to 2002.5 and ii) thanks to a better modeling of the surface forces on the satellites, the new combined solution shows smaller annual and 118-day signals in the geocenter. A new DORIS terrestrial reference frame was computed to evaluate the intrinsic quality of the new combined solution. That evaluation shows that over almost the full time span the intrinsic IDS scale values lie in a range of ±5 mm. After mid-2008, the new DORIS reference frame has an internal position consistency in North-East-Up better than 7.5 mm.

DORIS↗

Uncertainty Budget for Detector-Based Absolute Radiometric Calibration With GLAMR

The accuracy of the absolute radiometric calibration (RadCal) for remote sensing instruments is essential to their wide range of applications. The uncertainty associated to the traditional source-based RadCal method is assessed at a 2% (k=1) or higher level for radiance measurement. To further improve the accuracy to meet the demands of climate studies, a detector-based approach using tunable lasers as a light source has been devised. The Goddard Laser for Absolute Measurement of Radiance, known as the GLAMR system, is a notable example of the incorporation of such technology. Using transfer radiometers calibrated at NIST as calibration standards, the absolute spectral response (ASR) function of a remote sensing instrument is measured with its uncertainty traceable to the International System of Units. This paper presents a comprehensive uncertainty analysis of the detector-based absolute RadCal using the GLAMR system. It identifies and examines uncertainty sources during the GLAMR RadCal test, including those from the GLAMR system, the testing configuration, and data processing methodologies. Analysis is carried out to quantify the contribution of each source and emphasize the most influential factors. It is shown that the calibration uncertainty of GLAMR RadCal can be better than 0.3% (k=1) in the wavelength range of 350-950 nm and 0.6% (k=1) between 950-2300 nm, with the exception of regions with strong water absorption. In addition, recommendations are made to refine the calibration process to further reduce the uncertainty.

Zhipeng Wang↗

Radiation Monitoring for Volatilized Zinc Contamination Using Gamma-Ray Imaging and Spectroscopy

Gamma-ray imaging is a tool that has grown in importance in the applications of non-destructive assay (NDA) for radioactive survey and analysis of nuclear facilities. Imaging techniques have shown great promise in providing valuable information involving radioactive waste management and contamination prevention. For the application studied in this work, 65 Zn has been identified as a radioactive contaminant during tritium extraction. Due to the volatile nature of 65 Zn under the pressure and temperature changes during extraction operations, 65 Zn can easily travel through components of the extraction system as vapor, making it difficult to trap. Previous research involving the development of a filtration system showed that the 65 Zn can be trapped, mitigating product contamination. However, during the extraction process, direct analysis of the equipment to confirm that zinc contamination is trapped in the filter and has not spread to other components is impractical. Here, in this situation, the need to assay the location of the contamination with little-to-no interference with operations is vital. In this work, we demonstrate the use of a commercialized 3D position-sensitive CdZnTe (CZT) gamma-ray imaging spectrometer to provide analysis of the 65 Zn contamination. Onsite measurements during an extraction process are studied to assess the location and migration of the 65 Zn. The results obtained from real-time glovebox monitoring demonstrate the feasibility of gamma-ray imaging for localizing the contamination and providing a preliminary qualitative assessment that is intended to be used in future work quantifying the contamination build-up and activity over time.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Process Considerations for the Production of Hydrogen via Steam Reforming of Oxygenated Gases from Biomass Pyrolysis and Other Conversion Processes

Abstract In 2021, average CO 2 emissions was 9.7 g CO 2 /g H 2 produced, primarily based on steam methane reforming (SMR) technology that currently dominates hydrogen production. The substitution of natural gas (NG) and other fossil feedstocks in SMRs with renewable gases may be considered as an option for reducing greenhouse gas emissions. This analysis explores process impacts and constraints associated with the potential introduction of biogenic gases into SMRs. The results indicate that replacing NG in the fuel train of the SMR, followed by partial replacement of NG in the feed train may be a feasible approach. For the CO‐ and CO 2 ‐rich gas compositions assumed in this analysis the results indicate that feed train may accommodate up to 25 mole % of biogenic gases using allowances in existing designs and/or with small modifications, while maintaining similar hydrogen output. NG substitution in higher proportions require more major changes because of increased flow rates and heat exchange requirements in the system. Biogenic gases with lower CO 2 and higher calorific values are advantageous for NG substitution, and dry reforming using the CO 2 present in the feed gas can reduce steam consumption and increase process efficiency within limits where coking does not become a new constraint.

08 HYDROGEN↗