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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 NTRS1997

Effects of Bioreactor Retention Time on Aerobic Microbial Decomposition of CELSS Crop Residues

The focus of resource recovery research at the KSC-CELSS Breadboard Project has been the evaluation of microbiologically mediated biodegradation of crop residues by manipulation of bioreactor process and environmental variables. We will present results from over 3 years of studies that used laboratory- and breadboard-scale (8 and 120 L working volumes, respectively) aerobic, fed-batch, continuous stirred tank reactors (CSTR) for recovery of carbon and minerals from breadboard grown wheat and white potato residues. The paper will focus on the effects of a key process variable, bioreactor retention time, on response variables indicative of bioreactor performance. The goal is to determine the shortest retention time that is feasible for processing CELSS crop residues, thereby reducing bioreactor volume and weight requirements. Pushing the lower limits of bioreactor retention times will provide useful data for engineers who need to compare biological and physicochemical components. Bioreactor retention times were manipulated to range between 0.25 and 48 days. Results indicate that increases in retention time lead to a 4-fold increase in crop residue biodegradation, as measured by both dry weight losses and CO2 production. A similar overall trend was also observed for crop residue fiber (cellulose and hemicellulose), with a noticeable jump in cellulose degradation between the 5.3 day and 10.7 day retention times. Water-soluble organic compounds (measured as soluble TOC) were appreciably reduced by more than 4-fold at all retention times tested. Results from a study of even shorter retention times (down to 0.25 days), in progress, will also be presented.

Strayer, R. F.↗
DOE OSTI2025

Advancing continuous enzymatic hydrolysis for improved biomass saccharification

Background: A deployable, continuous enzymatic hydrolysis (CEH) process can address cost and commercialization risks associated with second-generation (Gen2) biorefinery sugar/lignin/ethanol production while contributing to energy supply and security. Developments in commercial enzymatic hydrolysis formulations targeting Gen2 pretreated biomass such as deacetylated mechanically refined (DMR) biomass necessitate a reassessment of the existing hybrid simultaneous saccharification and fermentation (SSF) approach. Notably, the practice of "finishing hydrolysis" in SSF has become problematic with the introduction of oxidative enzymes, such as lytic polysaccharide monooxygenases (LPMOs), into commercial cellulase formulations as these require specific redox conditions and cofactor. Moreover, continuous SSF has not been demonstrated at commercial scale, limiting deployment and the associated economic benefits to farmers, producers, and support industries. Results: Continuous enzymatic hydrolysis (CEH) was demonstrated at bench scale to enable optimal saccharification performance of deacetylated mechanically refined (DMR) pretreated biomass. Diafiltration was demonstrated to retain pretreated biomass solids and enzymes for continuous reaction while removing solubilized product sugars in situ. A significant breakthrough afforded by the CEH process is its ability to achieve equivalent endpoint conversions with approximately 50% lower enzyme loading. Yields of glucose and xylose were increased ~ 15% and ~ 4%, respectively, over batch hydrolysis. Unlike SSF using yeast or Zymomonas, CEH allows precise optimization of pH, temperature, oxygen tension, LPMO mediator concentration, and removal of end-product inhibitors. Conclusions: Advanced CEH holds promise as a transformational, process-intensified, and cost-effective method for producing soluble clarified biomass sugars and insoluble lignin-rich streams. Enhancing saccharification performance, optimizing operating parameters, and employing membrane filtration will help overcome existing challenges and enable the efficient production of valuable biomaterials from lignocellulosic biomass.

09 BIOMASS FUELS↗
NASA NTRS1989

Automation of orbit determination functions for National Aeronautics and Space Administration (NASA)-supported satellite missions

The Flight Dynamics Facility (FDF) at Goddard Space Flight Center (GSFC) provides spacecraft trajectory determination for a wide variety of National Aeronautics and Space Administration (NASA)-supported satellite missions, using the Tracking Data Relay Satellite System (TDRSS) and Ground Spaceflight and Tracking Data Network (GSTDN). To take advantage of computerized decision making processes that can be used in spacecraft navigation, the Orbit Determination Automation System (ODAS) was designed, developed, and implemented as a prototype system to automate orbit determination (OD) and orbit quality assurance (QA) functions performed by orbit operations. Based on a machine-resident generic schedule and predetermined mission-dependent QA criteria, ODAS autonomously activates an interface with the existing trajectory determination system using a batch least-squares differential correction algorithm to perform the basic OD functions. The computational parameters determined during the OD are processed to make computerized decisions regarding QA, and a controlled recovery process isactivated when the criteria are not satisfied. The complete cycle is autonomous and continuous. ODAS was extensively tested for performance under conditions resembling actual operational conditions and found to be effective and reliable for extended autonomous OD. Details of the system structure and function are discussed, and test results are presented.

Mardirossian, H.↗
NASA NTRS1990

Automation of orbit determination functions for National Aeronautics and Space Administration (NASA)-supported satellite missions

The Flight Dynamics Facility (FDF) at Goddard Space Flight Center (GSFC) provides spacecraft trajectory determination for a wide variety of National Aeronautics and Space Administration (NASA)-supported satellite missions, using the Tracking Data Relay Satellite System (TDRSS) and Ground Spaceflight and Tracking Data Network (GSTDN). To take advantage of computerized decision making processes that can be used in spacecraft navigation, the Orbit Determination Automation System (ODAS) was designed, developed, and implemented as a prototype system to automate orbit determination (OD) and orbit quality assurance (QA) functions performed by orbit operations. Based on a machine-resident generic schedule and predetermined mission-dependent QA criteria, ODAS autonomously activates an interface with the existing trajectory determination system using a batch least-squares differential correction algorithm to perform the basic OD functions. The computational parameters determined during the OD are processed to make computerized decisions regarding QA, and a controlled recovery process is activated when the criteria are not satisfied. The complete cycle is autonomous and continuous. ODAS was extensively tested for performance under conditions resembling actual operational conditions and found to be effective and reliable for extended autonomous OD. Details of the system structure and function are discussed, and test results are presented.

Mardirossian, H.↗
DOE OSTI2025

In‐situ Analysis of Paste Properties in Resonant Acoustic Mixers for Quality Monitoring

Formulation control is key to achieving consistent target properties of energetic materials, as feedstock variations and slight deviations in the ratios of different ingredients can have major effects on final product properties, particularly in dense pastes with high particle loading >65 vol.%. In large‐scale operations, it is imperative to either correct or remove batches of material that perform outside baseline property specifications as early as possible to avoid unnecessary processing of suboptimal material. Quality monitoring is the practice of measuring material properties during processing using process analytical technologies as opposed to only testing the properties of the final product; it is a key principle in the quality‐by‐design frameworks used for designing formulations and manufacturing processes. Herein, a process analytical technology method for correlating material properties of dense pastes directly after mixing in a Resonant Acoustic Mixer to motor data is developed and used to detect differences in the particle content of dense paste formulations. This method was also capable of detecting variations in powder feedstock properties, such as particle packing efficiency, and is sensitive enough to detect changes of 2 wt.% in the total solids content of the formulation. The techniques presented herein show excellent promise for use as a process analytical technology capable of quantifying formulation effects on material movement modes during resonant acoustic mixing.

Materials science↗
DOE OSTI2024

Software For Automated Leak Detection Using Infrared Camera

This code can read in videos or images in either a batch or real-time format. Videos are broken up into frames, and the frames are processed using an optical flow algorithm to decipher movement between adjacent frames. This adherent movement is ran through a convolutional neural network that automatically classifies the contents of the video. Additional content inside the code aids with noisy images and removal of nuisance movement.

Walker, CodyM. [Idaho National Laboratory (INL), I↗
DOE OSTI2024

Uranium Solubility and Supernate Enrichment Testing for Accelerated Basin De-Inventory Discards to Concentration, Storage, and Transfer Facilities

After future Accelerated Basin De-inventory (ABD) enriched uranium discards into sludge batches (SB), portions of supernate decants during SB preparation will be blended into salt batches (StB) and the resulting feeds must meet the nuclear safety requirements for the Salt Waste Processing Facility (SWPF). During previous SB10 sampling and testing, which involved H-Canyon material containing enriched uranium being mixed with Tank 51 sludge shortly after the H-Canyon stream was neutralized, it was identified that the uranium isotopic enrichment in the supernate deviated from the uranium isotopic enrichment in the slurry. The higher uranium isotopic enrichment in the supernate introduced the risk of challenging the feed requirements of SWPF. The ABD material added to SB11 was isotopically diluted with depleted uranium, mitigating any downstream impacts. However, H-Canyon desires to eliminate or minimize future depleted uranium additions in order to meet the mission schedule.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
NASA NTRS1980

Basic cluster compression algorithm

Feature extraction and data compression of LANDSAT data is accomplished by BCCA program which reduces costs associated with transmitting, storing, distributing, and interpreting multispectral image data. Algorithm uses spatially local clustering to extract features from image data to describe spectral characteristics of data set. Approach requires only simple repetitive computations, and parallel processing can be used for very high data rates. Program is written in FORTRAN IV for batch execution and has been implemented on SEL 32/55.

Hilbert, E. E.↗
NASA NTRS1979

Automated Array Assembly Task In-depth Study of Silicon Wafer Surface Texturizing

Several aspects of silicon wafer surface texturizing were studied. A low cost cleaning method that utilizes recycled Freon in an ultrasonic vapor degreaser to remove organic and inorganic contaminants from the surface of silicon wafers as received from silicon suppliers was investigated. The use of clean dry air and high throughout wafer batch drying techniques was shown to lower the cost of wafer drying. A two stage texturizing process was examined for suitability in large scale production. Also, an in-depth gettering study with the two stage texturizing process was performed for the enhancement of solar cell efficiency, minimization of current versus voltage curve dispersion, and improvement in process reproducibility. The 10% efficiency improvement goal was exceeded for the near term implementation of flat plate photovoltaic cost reduction.

Jones, G. T.↗
NASA NTRS1991

Controls for agility research in the NASA High-Alpha Technology Program

The research process being used to develop control law design methodologies and guidelines in the NASA High-Alpha Technology Program are discussed. This step-by-step process consists of four basic elements: (1) control law architecture definition and linear synthesis, (2) nonlinear batch simulation, (3) piloted simulation evaluation, and (4) flight test validation. This paper discusses the research tools being used in this effort and provides a status report on design methodologies and guidelines being developed for each of these elements.

Foster, John V.↗
NASA NTRS2010

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.↗
NASA NTRS2005

Improved Method of Manufacturing SiC Devices

The phrase, "common-layered architecture for semiconductor silicon carbide" ("CLASSiC") denotes a method of batch fabrication of microelectromechanical and semiconductor devices from bulk silicon carbide. CLASSiC is the latest in a series of related methods developed in recent years in continuing efforts to standardize SiC-fabrication processes. CLASSiC encompasses both institutional and technological innovations that can be exploited separately or in combination to make the manufacture of SiC devices more economical. Examples of such devices are piezoresistive pressure sensors, strain gauges, vibration sensors, and turbulence-intensity sensors for use in harsh environments (e.g., high-temperature, high-pressure, corrosive atmospheres). The institutional innovation is to manufacture devices for different customers (individuals, companies, and/or other entities) simultaneously in the same batch. This innovation is based on utilization of the capability for fabrication, on the same substrate, of multiple SiC devices having different functionalities (see figure). Multiple customers can purchase shares of the area on the same substrate, each customer s share being apportioned according to the customer s production-volume requirement. This makes it possible for multiple customers to share costs in a common foundry, so that the capital equipment cost per customer in the inherently low-volume SiC-product market can be reduced significantly. One of the technological innovations is a five-mask process that is based on an established set of process design rules. The rules provide for standardization of the fabrication process, yet are flexible enough to enable multiple customers to lay out masks for their portions of the SiC substrate to provide for simultaneous batch fabrication of their various devices. In a related prior method, denoted multi-user fabrication in silicon carbide (MUSiC), the fabrication process is based largely on surface micromachining of poly SiC. However, in MUSiC one cannot exploit the superior sensing, thermomechanical, and electrical properties of single-crystal 6H-SiC or 4H-SiC. As a complement to MUSiC, the CLASSiC five-mask process can be utilized to fabricate multiple devices in bulk single-crystal SiC of any polytype. The five-mask process makes fabrication less complex because it eliminates the need for large-area deposition and removal of sacrificial material. Other innovations in CLASSiC pertain to selective etching of indium tin oxide and aluminum in connection with multilayer metallization. One major characteristic of bulk micromachined microelectromechanical devices is the presence of three-dimensional (3D) structures. Any 3D recesses that already exist at a given step in a fabrication process usually make it difficult to apply a planar coat of photoresist for metallization and other subsequent process steps. To overcome this difficulty, the CLASSiC process includes a reversal of part of the conventional flow: Metallization is performed before the recesses are etched.

Okojie, Robert S.↗
NASA NTRS1976

Evaluation of Inorganic/Organic Separators

Thirty-six (36) experimental 40AH sealed silver-zinc cells were constructed during phase I of this two (2) phase program. These cells were divided into six (6) groups of six (6) cells each. Each group of six (6) cells was evenly divided into two batches of three (3) cells each. Groups 1 through 4 each featured a different inorganic filler material in the slurry used to coat the separator substrate. Groups 5 and 6 featured an alternate method of separator bag construction. With the exception of the various separator materials, the parts and processes used to produce these thirty-six (36) cells were the same as those used to make the HR40-7 cell. The two (2) batches of cells in each cell group differed only in the lots of solutions and other separator slurry components used. Each cell was given two formation charge/discharge cycles prior to being shipped to NASA Lewis Research Center. Phase II of the program consisted of constructing another thirty-six (36) 40AH experimental cells in six (6) groups of six (6) cells each. Each group was distinguished by the type of precoated separator material used to fabricate separator bags. A new method of separator bag construction was used in this phase of the program. These cells were given two (2) formation cycles and shipped to NASA Lewis Research Center.

Donnel, C. P., III↗
DOE OSTI2024

Enhanced prediction of Cs removal by CST from Hanford tank waste with K accountability

Abstract The treatment of Hanford tank waste is one of the most challenging environmental cleanup activities to date. To expedite the processing of liquid waste stored in underground tanks in Washington State it is necessary to remove the significant dose contributor, 137 Cs. Crystalline silicotitanate ion exchanger is currently used to remove 137 Cs from the aqueous phase of Hanford tank wastes in preparation for vitrification at the Waste Treatment and Immobilization Plant (WTP). Improving the understanding of potassium impacts on ion exchange behavior of Cs will help in the operation of a critical component of one of the most complex treatment processes in the world today. Optimization of this process can result in significant cost savings and less waste production. Toward this effort, a series of batch contact tests varied in potassium concentration were conducted to look at the impact of potassium concentration on Cs distribution. Experimental distribution ratios ( K d ) were compared to the distribution ratios predicted using the ZAM model. A significant underprediction of Cs capacity in the presence of potassium was seen with the existing model. A revision of the equilibrium constants was determined and provided a statistically better fit for determining the Cs K d values in tank waste matrices.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
NASA NTRS2016

The Matsu Wheel: A Cloud-Based Framework for Efficient Analysis and Reanalysis of Earth Satellite Imagery

Project Matsu is a collaboration between the Open Commons Consortium and NASA focused on developing open source technology for cloud-based processing of Earth satellite imagery with practical applications to aid in natural disaster detection and relief. Project Matsu has developed an open source cloud-based infrastructure to process, analyze, and reanalyze large collections of hyperspectral satellite image data using OpenStack, Hadoop, MapReduce and related technologies. We describe a framework for efficient analysis of large amounts of data called the Matsu "Wheel." The Matsu Wheel is currently used to process incoming hyperspectral satellite data produced daily by NASA's Earth Observing-1 (EO-1) satellite. The framework allows batches of analytics, scanning for new data, to be applied to data as it flows in. In the Matsu Wheel, the data only need to be accessed and preprocessed once, regardless of the number or types of analytics, which can easily be slotted into the existing framework. The Matsu Wheel system provides a significantly more efficient use of computational resources over alternative methods when the data are large, have high-volume throughput, may require heavy preprocessing, and are typically used for many types of analysis. We also describe our preliminary Wheel analytics, including an anomaly detector for rare spectral signatures or thermal anomalies in hyperspectral data and a land cover classifier that can be used for water and flood detection. Each of these analytics can generate visual reports accessible via the web for the public and interested decision makers. The result products of the analytics are also made accessible through an Open Geospatial Compliant (OGC)-compliant Web Map Service (WMS) for further distribution. The Matsu Wheel allows many shared data services to be performed together to efficiently use resources for processing hyperspectral satellite image data and other, e.g., large environmental datasets that may be analyzed for many purposes.

0↗
NASA NTRS1976

Models and error analyses in urban air quality estimation

Estimation theory has been applied to a wide range of aerospace problems. Application of this expertise outside the aerospace field has been extremely limited, however. This paper describes the use of covariance error analysis techniques in evaluating the accuracy of pollution estimates obtained from a variety of concentration measuring devices. It is shown how existing software developed for aerospace applications can be applied to the estimation of pollution through the processing of measurement types involving a range of spatial and temporal responses. The modeling of pollutant concentration by meandering Gaussian plumes is described in some detail. Time averaged measurements are associated with a model of the average plume, using some of the same state parameters and thus avoiding the problem of state memory. The covariance analysis has been implemented using existing batch estimation software. This usually involves problems in handling dynamic noise; however, the white dynamic noise has been replaced by a band-limited process which can be easily accommodated by the software.

Englar, T., Jr.↗
DOE OSTI2026

Project Development of an Electrochemical Denitration and Caustic Generation System for HLW Pretreatment at Hanford - 26350

An engineering-scale electrochemical processing skid is proposed to perform the denitration of Hanford tank waste, which would help to mitigate a key process concern with the direct feed processing of the Hanford Tank Waste Treatment and Immobilization Plant (WTP). The reduction of nitrates and organic compounds in the waste feed will directly reduce hazardous NOx and ammonia gases generated during the vitrification process, which in turn will aid in addressing potential regulatory and safety challenges associated with processing large volumes of tank waste. This paper highlights the past legacy work, project layout, accomplishments from Phase 1 and research and development envisioned for Phase 2. An innovative electrochemical denitration and caustic generation (EDCGe) process was demonstrated for the pretreatment of tank waste at the Savannah River Site (SRS) in the early 2000s. The denitration electrolyzer, off-gas abatement system, and caustic generator electrolyzer are being developed with the intent that the denitration electrolyzer will convert nitrate and nitrite anions to nitrogen gas while also yielding other gaseous byproducts, which may include N2O, NH3, VOCs, and H2. The gaseous byproducts will be managed via a tandem off-gas catalyst-bed treatment system. The caustic generation electrolyzer will recycle NaOH from the feed to produce a clean caustic stream for use within the batching tanks at Hanford, aiding in the preparation of waste for WTP. The reduction in hazardous emissions and improved waste treatment processes provides a robust solution for nuclear waste management, contributing to environmental safety and regulatory compliance. The EDCGe technology is being adapted, modified, and updated for the preparation of the Direct Feed-High Level Waste (DF-HLW) flowsheet at Hanford. Phase 1 demonstrated a bench-scale proof-of-concept for reactions involving the denitration electrolyzer and gas phase abatement of ammonia. The electrochemical technology is drawing on the scientific outcomes that were reported in the legacy work. The results from Phase 1 demonstrated the viability of the EDCGe system in reducing the nitrogen species of simple non-radioactive waste simulants. Commercially available alloys used as electrode materials and membranes are being studied for the denitration and caustic generation electrolyzers. The continuation of this project holds promise for broader applications, such as energy-efficient ammonia production, and contributes significant advancements in nuclear waste management. Additional material discovery has been investigated into ceramic Na super ion conductive (NaSICON) materials and off-gas abatement catalyst discovery. NaSICON is of interest for selective transport of Na within the electrolyzers to make a clean caustic stream. Future integration and optimization efforts, informed by Phase 1 results and ongoing research, will continue to drive advancements in nuclear waste management technology. The technology developed for the EDCGe treatment of tank waste will also have broader potential to inform other fields, such as energy-efficient ammonia production, as well as ammonia abatement catalysis through the lessons learned in electrochemical nitrate reduction. The applications and benefits of this research extend beyond Hanford and the Savannah River Site, supported by a collaborative team of scientists and engineers from national labs, academia, and industry, ensuring a comprehensive approach to solving complex waste treatment challenges. The team is leveraging advanced electrochemical technologies, machine learning, novel catalysts tailored for gaseous nitrogen species, and cutting-edge reactor systems to enhance the process efficiency and effectiveness of the denitration process.

Rodene, Dylan [Savannah River National Laboratory ↗
NASA NTRS2014

Generalized Linear Covariance Analysis

This talk presents a comprehensive approach to filter modeling for generalized covariance analysis of both batch least-squares and sequential estimators. We review and extend in two directions the results of prior work that allowed for partitioning of the state space into solve-for'' and consider'' parameters, accounted for differences between the formal values and the true values of the measurement noise, process noise, and textita priori solve-for and consider covariances, and explicitly partitioned the errors into subspaces containing only the influence of the measurement noise, process noise, and solve-for and consider covariances. In this work, we explicitly add sensitivity analysis to this prior work, and relax an implicit assumption that the batch estimator's epoch time occurs prior to the definitive span. We also apply the method to an integrated orbit and attitude problem, in which gyro and accelerometer errors, though not estimated, influence the orbit determination performance. We illustrate our results using two graphical presentations, which we call the variance sandpile'' and the sensitivity mosaic,'' and we compare the linear covariance results to confidence intervals associated with ensemble statistics from a Monte Carlo analysis.

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