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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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All sourcesNASA NTRSDOE OSTI
NASA NTRS2009

Pulmonary Toxicity Studies of Lunar Dusts in Rodents

NASA will build an outpost on the lunar surface for long-duration human habitation and research. The surface of the Moon is covered by a layer of fine, reactive dust, and the living quarters in the lunar outpost are expected to be contaminated by lunar dust. Because the toxicity of lunar dust is not known, NASA has tasked its toxicology laboratory to evaluate the risk of exposure to the dust and to establish safe exposure limits for astronauts working in the lunar habitat. Studies of the pulmonary toxicity of a dust are generally done first in rodents by intratracheal/intrapharyngeal instillation. This toxicity screening test is then followed by an inhalation study, which requires much more of the test dust and is labor intensive. Preliminary results obtained by examining lung lavage fluid from dust-treated mice show that lunar dust was somewhat toxic (more toxic than TiO2, but less than quartz dust). More extensive studies are in progress to further examine lung lavage fluid for biomarkers of toxicity and lung tissues for histopathological lesions in rodents exposed to aged and activated (ground) lunar dust samples. In these studies, reference dusts (TiO2 and quartz) of known toxicities and have industrial exposure limits will be studied in parallel so the relative toxicity of lunar dust can be determined. The results from the instillation studies will be useful for choosing exposure concentrations for the animal inhalation study. The animal inhalation exposure will be conducted with lunar dust simulant prior to the study with the lunar dust. The experiment with the simulate will ensure that the study techniques used with actual lunar dust will be successful. The results of instillation and inhalation studies will reveal the toxicological risk of exposures and are essential for setting exposure limits on lunar dust for astronauts living in the lunar habitat.

Lam, Chiu-wing↗
NASA NTRS2014

Human Factor Investigation of Waste Processing System During the HI-SEAS 4-month Mars Analog Mission in Support of NASA's Logistic Reduction and Repurposing Project: Trash to Gas

NASA's Logistics Reduction and Repurposing (LRR) project is a collaborative effort in which NASA is tasked with reducing total logistical mass through reduction, reuse and recycling of various wastes and components of long duration space missions and habitats. Trash to Gas (TtG) is a sub task to LRR with efforts focused on development of a technology that converts wastes generated during long duration space missions into high-value products such as methane, water for life support, raw material production feedstocks, and other energy sources. The reuse of discarded materials is a critical component to reducing overall mission mass. The 120 day Hawaii Space Exploration and Analog Simulation provides a unique opportunity to answer questions regarding crew interface and system analysis for designing and developing future flight-like versions of a TtG system. This paper will discuss the human factors that would affect the design of a TtG or other waste processing systems. An overview of the habitat, utility usage, and waste storage and generation is given. Crew time spent preparing trash for TtG processing was recorded. Gas concentrations were measured near the waste storage locations and at other locations in the habitat. In parallel with the analog mission, experimental processing of waste materials in a TtG reactor was performed in order to evaluate performance with realistic waste materials.

waste management↗
NASA NTRS2014

Human Factor Investigation of Waste Processing System During the HI-SEAS 4 Month Mars Analog Mission in Support of NASA's Logistic Reduction and Repurposing Project: Trash to Gas

NASAs Logistics Reduction and Repurposing (LRR) project is a collaborative effort in which NASA is tasked with reducing total logistical mass through reduction, reuse and recycling of various wastes and components of long duration space missions and habitats. Trash to Gas (TtG) is a sub task to LRR with efforts focused on development of a technology that converts wastes generated during long duration space missions into high-value products such as methane, water for life support, raw material production feedstocks, and other energy sources. The reuse of discarded materials is a critical component to reducing overall mission mass. The 120 day Hawaii Space Exploration and Analog Simulation provides a unique opportunity to answer questions regarding crew interface and system analysis for designing and developing future flight-like versions of a TtG system. This paper will discuss the human factors that would affect the design of a TtG or other waste processing systems. An overview of the habitat, utility usage, and waste storage and generation is given. Crew time spent preparing trash for TtG processing was recorded. Gas concentrations were measured near the waste storage locations and at other locations in the habitat. In parallel with the analog mission, experimental processing of waste materials in a TtG reactor was performed in order to evaluate performance with realistic waste materials.

Steam reformer↗
NASA NTRS2000

Towards Flange-to-Flange Turbopump Simulations for Liquid Rocket Engines

The primary objective of this research is to support the design of liquid rocket systems for the Advanced Space Transportation System. Since the space launch systems in the near future are likely to rely on liquid rocket engines, increasing the efficiency and reliability of the engine components is an important task. One of the major problems in the liquid rocket engine is to understand fluid dynamics of fuel and oxidizer flows from the fuel tank to plume. Understanding the flow through the entire turbopump geometry through numerical simulation will be of significant value toward design. This will help to improve safety of future space missions. One of the milestones of this effort is to develop, apply and demonstrate the capability and accuracy of 3D CFD methods as efficient design analysis tools on high performance computer platforms. The development of the MPI and MLP versions of the INS3D code is currently underway. The serial version of INS3D code is a multidimensional incompressible Navier-Stokes solver based on overset grid technology. INS3D-MPI is based on the explicit massage-passing interface across processors and is primarily suited for distributed memory systems. INS3D-MLP is based on multi-level parallel method and is suitable for distributed-shared memory systems. For the entire turbopump simulations, moving boundary capability and an efficient time-accurate integration methods are build in the flow solver. To handle the geometric complexity and moving boundary problems, overset grid scheme is incorporated with the solver that new connectivity data will be obtained at each time step. The Chimera overlapped grid scheme allows subdomains move relative to each other, and provides a great flexibility when the boundary movement creates large displacements. The performance of the two time integration schemes for time-accurate computations is investigated. For an unsteady flow which requires small physical time step, the pressure projection method was found to be computationally efficient since it does not require any subiterations procedure. It was observed that the artificial compressibility method requires a fast convergence scheme at each physical time step in order to satisfy incompressibility condition. This was obtained by using a GMRES-ILU(0) solver in our computations. When a line-relaxation scheme was used, the time accuracy was degraded and time-accurate computations became very expensive. The current geometry for the LOX boost turbopump has various rotating and stationary components, such as inducer, stators, kicker, hydrolic turbine, where the flow is extremely unsteady. Figure 1 shows the geometry and computed surface pressure of the inducer. The inducer and the hydrolic turbine rotate in different rotational speed.

Kiris, Cetin↗
DOE OSTI2019

DXT: Darshan eXtended Tracing

As modern supercomputers evolve to exascale, their I/O subsystems are becoming increasingly complex, making optimization of I/O for scientific applications a daunting task. Although I/O profiling tools facilitate the process of optimizing application I/O performance, legacy profiling tools lack flexibility in their level of detail and ability to correlate traces with other sources of data. Additionally, a lack of robust trace analysis tools makes it difficult to derive actionable insights from large-scale I/O traces. Darshan is an HPC I/O characterization tool that records statistics in a lightweight manner that makes it appropriate for full-time production deployment. However, Darshan’s default characterization mechanism records information at a fixed granularity. We augment Darshan by proposing Darshan eXtended Tracing (DXT) for more detailed profiling of I/O software stacks. DXT enables users and administrators to vary the level of fidelity captured by Darshan at run time without modifying or recompiling applications. This capability facilitates systematic analysis on the I/O behavior of applications and can provide useful application kernel I/O traces to help advance parallel I/O research. We have demonstrated the power of DXT by obtaining a wide range of useful statistics for multiple case studies, and we further show that DXT is able to do so same with negligible overhead.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1994

Extended cooperative control synthesis

This paper reports on research for extending the Cooperative Control Synthesis methodology to include a more accurate modeling of the pilot's controller dynamics. Cooperative Control Synthesis (CCS) is a methodology that addresses the problem of how to design control laws for piloted, high-order, multivariate systems and/or non-conventional dynamic configurations in the absence of flying qualities specifications. This is accomplished by emphasizing the parallel structure inherent in any pilot-controlled, augmented vehicle. The original CCS methodology is extended to include the Modified Optimal Control Model (MOCM), which is based upon the optimal control model of the human operator developed by Kleinman, Baron, and Levison in 1970. This model provides a modeling of the pilot's compensation dynamics that is more accurate than the simplified pilot dynamic representation currently in the CCS methodology. Inclusion of the MOCM into the CCS also enables the modeling of pilot-observation perception thresholds and pilot-observation attention allocation affects. This Extended Cooperative Control Synthesis (ECCS) allows for the direct calculation of pilot and system open- and closed-loop transfer functions in pole/zero form and is readily implemented in current software capable of analysis and design for dynamic systems. Example results based upon synthesizing an augmentation control law for an acceleration command system in a compensatory tracking task using the ECCS are compared with a similar synthesis performed by using the original CCS methodology. The ECCS is shown to provide augmentation control laws that yield more favorable, predicted closed-loop flying qualities and tracking performance than those synthesized using the original CCS methodology.

Davidson, John B.↗
DOE OSTI2022

Dictionary Learning with Accumulator Neurons

The Locally Competitive Algorithm (LCA) uses local competition between non-spiking leaky integrator neurons to infer sparse representations, allowing for potentially real-time execution on massively parallel neuromorphic architectures such as Intel's Loihi processor. Here, we focus on the problem of inferring sparse representations from streaming video using dictionaries of spatiotemporal features optimized in an unsupervised manner for sparse reconstruction. Non-spiking LCA has previously been used to achieve unsupervised learning of spatiotemporal dictionaries composed of convolutional kernels from raw, unlabeled video. We demonstrate how unsupervised dictionary learning with spiking LCA (\hbox{S-LCA}) can be efficiently implemented using accumulator neurons, which combine a conventional leaky-integrate-and-fire (\hbox{LIF}) spike generator with an additional state variable that is used to minimize the difference between the integrated input and the spiking output. We demonstrate dictionary learning across a wide range of dynamical regimes, from graded to intermittent spiking, for inferring sparse representations of both static images drawn from the CIFAR database as well as video frames captured from a DVS camera. On a classification task that requires identification of the suite from a deck of cards being rapidly flipped through as viewed by a DVS camera, we find essentially no degradation in performance as the LCA model used to infer sparse spatiotemporal representations migrates from graded to spiking. We conclude that accumulator neurons are likely to provide a powerful enabling component of future neuromorphic hardware for implementing online unsupervised learning of spatiotemporal dictionaries optimized for sparse reconstruction of streaming video from event based DVS cameras.

artificial intelligence↗
NASA NTRS2004

A Survey of Formal Methods for Intelligent Swarms

Swarms of intelligent autonomous spacecraft, involving complex behaviors and interactions, are being proposed for future space exploration missions. Such missions provide greater flexibility and offer the possibility of gathering more science data than traditional single spacecraft missions. The emergent properties of swarms make these missions powerful, but simultaneously far more difficult to design, and to assure that the proper behaviors will emerge. These missions are also considerably more complex than previous types of missions, and NASA, like other organizations, has little experience in developing or in verifying and validating these types of missions. A significant challenge when verifying and validating swarms of intelligent interacting agents is how to determine that the possible exponential interactions and emergent behaviors are producing the desired results. Assuring correct behavior and interactions of swarms will be critical to mission success. The Autonomous Nano Technology Swarm (ANTS) mission is an example of one of the swarm types of missions NASA is considering. The ANTS mission will use a swarm of picospacecraft that will fly from Earth orbit to the Asteroid Belt. Using an insect colony analogy, ANTS will be composed of specialized workers for asteroid exploration. Exploration would consist of cataloguing the mass, density, morphology, and chemical composition of the asteroids, including any anomalous concentrations of specific minerals. To perform this task, ANTS would carry miniaturized instruments, such as imagers, spectrometers, and detectors. Since ANTS and other similar missions are going to consist of autonomous spacecraft that may be out of contact with the earth for extended periods of time, and have low bandwidths due to weight constraints, it will be difficult to observe improper behavior and to correct any errors after launch. Providing V&V (verification and validation) for this type of mission is new to NASA, and represents the cutting edge in system correctness, and requires higher levels of assurance than other (traditional) missions that use a single or small number of spacecraft that are deterministic in nature and have near continuous communication access. One of the highest possible levels of assurance comes from the application of formal methods. Formal methods are mathematics-based tools and techniques for specifying and verifying (software and hardware) systems. They are particularly useful for specifying complex parallel systems, such as exemplified by the ANTS mission, where the entire system is difficult for a single person to fully understand, a problem that is multiplied with multiple developers. Once written, a formal specification can be used to prove properties of a system (e.g., the underlying system will go from one state to another or not into a specific state) and check for particular types of errors (e.g., race or livelock conditions). A formal specification can also be used as input to a model checker for further validation. This report gives the results of a survey of formal methods techniques for verification and validation of space missions that use swarm technology. Multiple formal methods were evaluated to determine their effectiveness in modeling and assuring the behavior of swarms of spacecraft using the ANTS mission as an example system. This report is the first result of the project to determine formal approaches that are promising for formally specifying swarm-based systems. From this survey, the most promising approaches were selected and are discussed relative to their possible application to the ANTS mission. Future work will include the application of an integrated approach, based on the selected approaches identified in this report, to the formal specification of the ANTS mission.

Truszkowski, Walt↗
NASA NTRS1994

Arc electrode interaction study

The project consisted of two parts: (1) the cathode interaction studies which were a continuation of previous work and had the objective of increasing our understanding of the microscopic phenomena controlling cathode erosion in arc jet thrusters, and (2) the studies of the anode attachment in arc jet thrusters. The cathode interaction studies consisted of (1) a continuation of some modeling work in which the previously derived model for the cathode heating was applied to some specific gases and electrode materials, and (2) experimental work in which various diagnostics was applied to the cathode. The specific diagnostics used were observation of the cathode tip during arcing using a Laser Strobe Video system in conjunction with a tele-microscope, a monochromator with an optical multichannel analyzer for the determination of the cathode temperature distribution, and various ex situ materials analysis methods. The emphasis of our effort was shifted to the cathode materials analysis because a parallel project was in place during the second half of 1993 with a visiting scientist pursuing arc electrode materials studies. As a consequence, the diagnostic investigations of the arc in front of the cathode had to be postponed to the first half of 1994, and we are presently preparing these measurements. The results of last year's study showed some unexpected effects influencing the cathode erosion behavior, such as increased erosion away from the cathode tip, and our understanding of these effects should improve our ability to control cathode erosion. The arc jet anode attachment studies concentrated on diagnostics of the instabilities in subsonic anode attachment arc jet thrusters, and were supplemental measurements to work which was performed by one of the authors who spent the summer as an intern at NASA Lewis Research Center. A summary of the results obtained during the internship are included because they formed an integral part of the study. Two tasks for 1994, the diagnostics of the anode closure phenomenon, and the use of arc jet thrusters for the deposition of c-BN, are being prepared.

Zhou, X.↗
DOE OSTI2019

Development and refinement of an in situ ‘molecular microscope’ utilizing ultrahigh resolution mass spectrometry

The ability to elucidate complex metabolic behavior of living organisms in situ and with cellular resolution is a bioanalytical grand challenge that is yet to be realized. Mass spectrometry imaging (MSI) using laser ablation electrospray ionization mass spectrometry (LAESI) has recently been demonstrated, and holds promise for direct spatially resolved molecular profiling in a variety of living systems of DOE relevance (e.g., plant leaf, stem, and root tissue). The LAESI MSI approach has revealed cell-to-cell heterogeneity of metabolites within living plant tissue, in a multiplexed fashion and without the need for labeling. Cellular resolution by in situ, ambient pressure MSI methods are far from routine, however, and have inadequate spatial resolution for many biological questions of interest. We propose to develop next-generation LAESI approaches, using advanced fiber optics and transmission-based geometries, in efforts to attain dynamic bioanalysis of living systems at better than 20 µm lateral resolution. In parallel with LAESI innovations, attendant increases in sensitivity and dynamic range of the mass spectrometer system will also be necessary for detection of the limited amount of material being ionized. To respond to this need, a new, high magnetic field (21 Tesla) Fourier Transform Ion Cyclotron Resonance (FTICR) MS at the EMSL/PNNL will be coupled with the newly developed LAESI source. This mass spectrometer, currently being assembled, will be one of only two such systems in the world, and the only one in a DOE laboratory or user facility. Fundamentally, all key figures of merits of FTICR MS performance improve with increased magnetic field strength, providing the ability to achieve unparalleled molecular specificity (near unequivocal molecular constituent identification) at the highest possible mass resolving power and sensitivity. The work proposed here will greatly increase the utility of this FTICR MS instrument, providing unique capabilities to support BER-relevant science. The research plan is comprised of three tasks, two of which are directed by the academic leads (University of Missouri and George Washington University), and one of which will be performed in conjunction with the BER user facility at EMSL/PNNL. In task 1, advancements of the LAESI technology will be achieved, with oversight and leadership of Professor Akos Vertes of George Washington University. In task 2, incorporation of this ion source with EMSL’s new 21T FTICR MS system will be undertaken, supplemented by global omics measurements and calibrated against more conventional MSI platforms also available at EMSL (Drs. Pasa-Tolic, Anderton, and Koppenaal team). In the final task, the resultant innovations and advancements will be tested and validated by addressing important BER relevant science questions on model systems of interest under the direction of Professor Gary Stacey of the University of Missouri. This research follows on key recommendations of the recent BER “Research in Sustainable Bioenergy” report that, for example, stressed that “The design of sustainable biofuel systems requires knowledge about key plant-microbe-environment interactions that provide a range of ecosystem services.” This task will focus on validation of the instrumentation developed through this proposal, advertising this capability to the community through demonstration and, finally, discovering new biology relevant to the BER mission. This final objective will make use of Setaria viridis, a model C4 grass species, as well as switchgrass and sorghum, two promising biofuel crops. Specifically, we will demonstrate applicability to plant-microbe rhizosphere interactions focusing on the biological nitrogen fixation by monitoring metabolic changes in real-time with nutrient, growth condition, and other perturbations.

09 BIOMASS FUELS↗
DOE OSTI2025

Introduction: Neuromorphic Materials

The explosive growth in data collection and the need to process it efficiently, as well as the desire to automate increasingly complex tasks in transportation, medical care, manufacturing, security and many other fields have motivated a growing interest in neuromorphic computing. Unlike the binary, transistorbased ON/OFF logic gates and separate logic and memory functionalities employed in digital computing, neuromorphic computing is inspired by animal brains that use interconnected synapses and neurons to perform processing, storage and transmission of information at the same location, while only consuming ~20 W or less of power. Motivated by the brain’s efficiency, adaptability, self-learning and resiliency qualities, neuromorphic computing can be broadly defined as an approach to processing and storing information using hardware and algorithms inspired by models of biological neural systems. Present research in neuromorphic computing encompasses approaches that vary significantly in their degree of neuro-inspiration, from systems that only incorporate features such as asynchronous, event-driven operation or use crossbar arrays of non-volatile memory (NVM) elements to accelerate deep neural networks (DNNs), to designs that embrace the extreme parallelism, sparsity, reconfigurability, adaptability, complexity and stochasticity observed in nervous systems. The term ‘neuromorphic’ computing is often credited to Carver Mead, who in the 1980s investigated Si-based analog electronics to replicate functions of the animal retina. Earlier important advances in this field include the work of Frank Rosenblatt, who proposed the concept of the perceptron, Bernard Widrow, who used this concept to build one of the first analog neural networks, the Adaline and many other researchers (see ref. 6 for an historical perspective on neuromorphic computing). With the recent increase in the use of artificial intelligence and large language models, and rising concerns over the associated energy costs, interest in neuromorphic hardware has expanded rapidly. According to some estimates, driven largely by the drastic growth in the training use of artificial intelligence (AI) models using the current computing architectures, the energy cost of computing is projected to reach the energy supply worldwide by 2045. Furthermore, while this is not a realistic outcome, it means that, if more efficient computing technologies are not developed -- soon -- the world will soon become one where demand for energy and market constraints limit the continued increase of societal access to AI and cloud services from data centers. Data centers used for training and use of these models consume hundreds of terawatt hours of electricity, already past 4% of the US electricity demand.

Circuits↗
NASA NTRS2018

Automated Impact Assessment: A New Approach to ISS Payload Operations Anomaly Response

The International Space Station (ISS) Payload Operations and Integration Center (POIC) is undergoing rapid growth as the space station program focuses on science and commercial activities. The ISS is expanding its onboard capabilities to support additional science activities. In parallel, the POIC is expanding the capabilities of our operations tools to support the higher pace of payload activities being executed each week. An effect of these changes is that anomaly resolution has become more challenging. In the event of a real-time system fault, operators are responsible for analyzing telemetry displays, anomaly monitoring tools, documentation, and system models in order to produce failure impacts and recovery strategies. This approach to operations relies on the operator to ingest, process, and analyze information from an array of deterministic sources to provide actionable data on impacted systems and activities. Changing the existing approach of anomaly response is necessary if the ISS community is to succeed in the age of science and commercialization of space. The creation of a tool that captures deterministic technical systems knowledge and integrates existing telemetry, documentation, and planning information will allow the burden of impact assessment to be automated, thereby allowing the operator to focus on non-deterministic tasks, such as recovering failed systems and restoring critical payload operations.

Hall, R. Mason↗
DOE OSTI2021

Phasor-Measurement-Unit-Based Data Analytics Using Digital Twin and PhasorAnalytics Software

A major objective of this project was to apply GE’s commercial machine learning and data analytics toolsets to large-scale, real-world, anonymized Phasor Measurement Unit (PMU) datasets in order to extract signatures, correlated and/or causal factors, and precursor patterns associated with significant power system phenomena. The project had a particular emphasis on extraction of insights relevant to asset health monitoring, real-time load modeling and cybersecurity monitoring. Additionally, the team was directed to undertake a comprehensive data quality analysis for the provided datasets and encouraged to estimate the ‘machine-learning readiness’ of the datasets by documenting any major obstacles to the application of commercial machine learning algorithms. To accomplish the aforementioned objectives, the project team’s work centered around the identification of key event signatures and application of the identified event signatures for event detection and event classification. The industry-validated, semi-supervised machine learning strategy employed for event signature identification involved several major tasks, including data-preprocessing, generation of an overabundance of features, normal data identification, normality modeling, and event signature identification through a methodical, quantitative ranking of features in order of relevance to each studied event type. Throughout the project, data quality issues and mitigation techniques were investigated. In this report, insights are provided regarding the readiness of the provided synchrophasor datasets for application of machine learning and data analytics. The methodologies employed for this technical strategy are summarized in this report. With regards to data preprocessing and feature generation, the provided Training and Test Datasets were ingested into GE’s big data environment. Subsequently, the team applied bad data cleansing and data imputation scripts, event detection scripts, and application programming interfaces (APIs) to the datasets for convenient data access. The project team completed development and validation of dozens of physics-based, statistics-based and transformation-based feature functions used for the extraction of over 60 synchrophasor features. Using a new parallel feature generation technology developed on this project, over 60 features have been rapidly generated for the full two years’ worth of Training and Test Dataset data associated with both the Eastern and Western interconnects. Even accommodating for temporal down-sampling inherent to the feature extraction procedure, this parallel feature generation activity resulted in a massive feature set with a storage requirement approximately equal to that of the raw training dataset itself. With regards to normal data identification and normality modeling, a normality model was built using the feature data extracted from the Training Dataset and iteratively refined subsequent to incremental adjustments and expansions of the Training Dataset feature data. With respect to event characterization and signature identification, an event signature identification pipeline was developed and used in conjunction with the normality model to identify over 15 event signatures for key event categories within the Training Dataset. The identified event signatures were used to characterize hundreds of key events in terms of relative severity, duration, and location of the event. An investigation was undertaken to identify correlated and causal factors involved in transformer events. A separate investigation into temporal trends in ring-down analysis results was undertaken to determine possible associations between system dynamics and various other factors such as loading, season or year. To validate the identified event signatures, additional work was undertaken to develop signature-based anomaly detection and classification tools suitable for convenient application to the synchrophasor datasets. The anomaly detection and classification tools, suitable for online application, were then applied to the entirety of the Eastern Interconnect Training and Test Datasets. Performance of the event detection and classification tools was evaluated upon receipt of the Test Dataset event logs (i.e., the labels for events contained in the Test Dataset), and promising results were obtained despite several challenges (documented herein) associated with application of supervised or semi-supervised machine learning methods to large-scale, anonymized datasets. Finally, the detection and classification tools were used to detect, classify, and characterize thousands of new events not included in the original event logs provided by the DOE within both the Training and Test Datasets.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS2007

Flow Separation Side Loads Excitation of Rocket Nozzle FEM

Modern rocket nozzles are designed to operate over a wide range of altitudes, and are also built with large aspect ratios to enable high efficiencies. Nozzles designed to operate over specific regions of a trajectory are being replaced in modern launch vehicles by those that are designed to operate from earth to orbit. This is happening in parallel with modern manufacturing and wall cooling techniques allowing for larger aspect ratio nozzles to be produced. Such nozzles, though operating over a large range of altitudes and ambient pressures, are typically designed for one specific altitude. Above that altitude the nozzle flow is 'underexpanded' and below that altitude, the nozzle flow is 'overexpanded'. In both conditions the nozzle produces less than the maximum possible thrust at that altitude. Usually the nozzle design altitude is well above sea level, leaving the nozzle flow in an overexpanded state for its start up as well as for its ground testing where, if it is a reusable nozzle such as the Space Shuttle Main Engine (SSME), the nozzle will operate for the majority of its life. Overexpansion in a rocket nozzle presents the critical, and sometimes design driving, problem of flow separation induced side loads. To increase their understanding of nozzle side loads, engineers at MSFC began an investigation in 2000 into the phenomenon through a task entitled "Characterization and Accurate Modeling of Rocket Engine Nozzle Side Loads", led by A. Brown. The stated objective of this study was to develop a methodology to accurately predict the character and magnitude of nozzle side loads. The study included further hot-fire testing of the MC-l engine, cold flow testing of subscale nozzles, CFD analyses of both hot-fire and cold flow nozzle testing, and finite element (fe.) analysis of the MC-1 engine and cold flow tested nozzles. A follow on task included an effort to formulate a simplified methodology for modeling a side load during a two nodal diameter fluid/structure interaction for a single moment in time.

Smalley, Kurt B.↗
NASA NTRS2010

Direct Relationship Between Perceptual and Motor Variability

The time that elapses between stimulus onset and the onset of a saccadic eye movement is longer and more variable than can be explained by neural transmission times and synaptic delays (Carpenter, 1981, in: Eye Movements: Cognition & Visual Perception, Earlbaum). In theory, noise underlying response-time (RT) variability could arise at any point along the sensorimotor cascade, from sensory noise arising Vvithin the early visual processing shared Vvith perception to noise in the motor criterion or commands necessary to trigger movements. These two loci for internal noise can be distinguished empirically; sensory internal noise predicts that response time Vvill correlate Vvith perceived stimulus magnitude whereas motor internal noise predicts no such correlation. Methods. We used the data described by Liston and Stone (2008, JNS 28:13866-13875), in which subjects performed a 2AFC saccadic brightness discrimination task and the perceived brightness of the chosen stimulus was then quantified in a second 21FC perceptual task. Results. We binned each subject's data into quartiles for both signal strength (from dimmest to brightest) and RT (from slowest to fastest) and analyzed the trends in perceived brightness. We found significant effects of both signal strength (as expected) and RT on normalized perceived brightness (both p less than 0.0001, 2-way ANOVA), without significant interaction (p = 0.95, 2-way ANOVA). A plot of normalized perceived brightness versus normalized RT show's that more than half of the variance was shared (r2 = 0.56, P less than 0.0001). To rule out any possibility that some signal-strength related artifact was generating this effect, we ran a control analysis on pairs of trials with repeated presentations of identical stimuli and found that stimuli are perceived to be brighter on trials with faster saccades (p less than 0.001, paired t-test across subjects). Conclusion. These data show that shared early visual internal noise jitters perceived brightness and the saccadic motor output in parallel. While the present correlation could theoretically result, either directly or indirectly, from some low-level brainstem or retinal mechanism (e.g., arousal, pupil size, photoreceptor noise) that influences both visual and oculomotor circuits, this is unlikely given the earlier fin ding that the variability in perceived motion direction and smooth-pursuit motor output is highly correlated (Stone and Krauzlis, 2003, JOV 3:725-736), suggesting that cortical circuits contribute to the shared internal noise.

Liston, Dorion B.↗
DOE OSTI2020

Distributed fiber sensing systems for 3D combustion temperature field monitoring in coal-fired boilers using optically generated acoustic waves (Final Report)

In this project, we have developed and tested three kinds of fiber optic sensing systems for real time monitoring of temperature variations within an industrial scale boiler furnace. The fiber optic sensing systems target spatial and temporal distributions of high temperature profiles in a boiler furnace in fossil power plants. The reconstructed temperature profile will provide critical input for the control mechanisms to optimize the combustion process. This temperature profile will address the essential problem for fossil power plants in achieving higher efficiency and fewer pollutant emissions. Acoustic pyrometer systems have been used to reconstruct temperature field of power plant boilers based on measuring TOF (times-of-flight) of sound waves along some straight paths in a 2D cross-section of the boiler. In this project, optically generated acoustic signals from a fiber optic sensing system have replaced the acoustic signals generated from an electrical transducer. A 3D reconstruction algorithm replaced the previous 2D model. In this project, three kinds of fiber optic sensing systems have been developed and tested. They are fiber optic sensing system I, fiber optic sensing system II (Distributed Sensing System I) and fiber optic sensing system III (Distributed Sensing System II). For fiber optic sensing system I, the fiber optic ultrasound generator acts as a signal generator. A microphone, hydrophone or other electronic devices serve as a signal receiver. In this system, there are one generator and one receiver. Distance test, water temperature test, air temperature test, air temperature reconstruction, and GE ISBF pilot test were performed by Fiber optic sensing system I. The fiber optic sensing system I successfully detected temperature in all these tests. We got 2D temperature reconstruction results by using the fiber optic sensing system I and it matched the reference data. The fiber optic sensing system I successfully survived in GE ISBF boiler environment (480 °F). For fiber optic sensing system II (Distributed Sensing System I), it is an all optical ultrasound system. The fiber optic ultrasound generator acts as a signal generator. Fiber Bragg Grating (FBG) and Fabry-Perot (FP) sensor act as a signal receiver. In this system, there is one generator and one receiver. Aluminum plate temperature test, furnace high temperature test, and GE ISBF pilot test were performed by the fiber optic sensing system II. Fiber optic sensing system II successfully detected the temperature in all these tests. The fiber optic sensing system II successfully survived at up to 700 °C furnace environment and 320 °C GE ISBF boiler environment. For fiber optic sensing system III (Distributed Sensing System II), it is also an all optical ultrasound system. The fiber optic ultrasound generator acts as a signal generator. Multiple FP fiber sensors act as signal receivers. In this system, there is one generator and three receivers. Three GE ISBF pilot tests were performed by fiber optic sensing system III. The fiber optic sensing system III survived in the cold flow tests in GE’s ISBF pilot test facility. However, we didn’t get high temperature data by using this system since the nanosecond laser issues. During the period of the project, test trials, data simulation and algorithm optimization was performed successfully. For real time temperature field construction, the sampling rate must be fast enough to capture the field variations. The technology of Code-division multiple access (CDMA) is well studied which could allow parallel multiplexing, even if signals overlap in time or frequencies. Moreover, it has been known that extending the length of signal significantly improves SNR. For acoustic signals, these multiplexing techniques have also been widely used, mainly for sonar and acoustic communications. The CDMA modulation technique has been proposed and studied to guarantee high network throughput, low channel access delay and low energy consumption. We have studied the temperature field reconstruction using Gaussian Radial Basis Functions (GRBF)-based approximation approach. Reconstruction of 3D temperature field using Neural Networks with measured TOF and known propagation paths is feasible. 2D and 3D temperature field reconstruction simulation results are achieved. The milestone status is shown in Table 1. We finished milestone 1-8 and milestone 10. For milestone 9, we did three pilot tests by using the fiber optic sensing system III (Distributed Sensing System II) at GE Power. However, due to the failure of the ns laser, we did not get the temperature results. We conducted some additional tasks that were not originally proposed: 1) We fabricated a fiber optic sensing system I and did a pilot test based on this system. 2) In the proposal, we proposed two pilot tests at GE Power. In reality, we finished at least seven pilot tests at GE Power. GE Power has made a lot of efforts for supporting the pilot tests. 3) We got a simulation results based on CDMA. In summary, most of the tasks have been accomplished. The outcome of this project removed a few barriers that hinder the achievement of the final product of the distributed sensing systems. With the successful accomplishment of this project, a prototype of the fiber optic sensing system can be fabricated to attract more interests from companies and other funding agencies.

47 OTHER INSTRUMENTATION↗
DOE OSTI2024

Pretraining Billion-Scale Geospatial Foundational Models on Frontier

As AI workloads increase in scope, generalization capability becomes challenging for small task-specific models and their demand for large amounts of labeled training samples increases. On the contrary, Foundation Models (FMs) are trained with internet-scale unlabeled data via self-supervised learning and have been shown to adapt to various tasks with minimal fine-tuning. Although large FMs have demonstrated significant impact in natural language processing and computer vision, efforts toward FMs for geospatial applications have been restricted to smaller size models, as pretraining larger models requires very large computing resources equipped with state-of-the-art hardware accelerators. Current satellite constellations collect 100+TBs of data a day, resulting in images that are billions of pixels and multimodal in nature. Such geospatial data poses unique challenges opening up new opportunities to develop FMs. We investigate billion scale FMs and HPC training profiles for geospatial applications by pretraining on publicly available data. We studied from end-to-end the performance and impact in the solution by scaling the model size. Our larger 3B parameter size model achieves up to 30% improvement in top1 scene classification accuracy when comparing a 100M parameter model. Moreover, we detail performance experiments on the Frontier supercomputer, America's first exascale system, where we study different model and data parallel approaches using PyTorch's Fully Sharded Data Parallel library. Specifically, we study variants of the Vision Transformer architecture (ViT), conducting performance analysis for ViT models with size up to 15B parameters. By discussing throughput and performance bottlenecks under different parallelism configurations, we offer insights on how to leverage such leadership-class HPC resources when developing large models for geospatial imagery applications.

Tsaris, Aristeidis (aris)↗
DOE OSTI2019

Dismantling of the Spent Resins Hot Compaction Unit at Tihange NPP, Belgium - 19139

Design, construction and commissioning of the Spent Ion Exchange Resins Hot Compaction Unit at Tihange Nuclear Power Plant took place from 2005 till 2011. In this conditioning process, batches of radioactive resin beads were first dried to less than 4% moisture by a conical vacuum dryer. Resins were then poured in compactable 200-liter drums and super-compacted. Resulting pellets were emplaced in standard 400-liter drums, the packages qualified for final disposal in Belgium, and eventually grouted. The Belgian Waste Management Agency (ONDRAF/NIRAS) was consulted before initiating the project and issued a statement of no objection. The technology turned out to be used for the first time in the particular case of bead shaped resins (unlike powdered resins) and with a grouting requirement. Finally, commissioning tests ended in a safe and reproducible waste form, compliant with prevailing Waste Acceptance Criteria. Volume Reduction Factors of about 2 were recorded after drying and compaction. New tests were carried out to support the Qualification File of the process, which was submitted to ONDRAF/NIRAS. After performing many trials using inactive resins, the Operator dried two batches of radioactive resins and super-compacted four drums: this was a planned qualification step, aiming at the validation of process parameters. In the meantime, ONDRAF/NIRAS made parallel progress in the design of the future Near Surface Repository, where conditioned resins will be disposed of, and found some incompatibility between encapsulated dried resin beads and water intrusion hazards inside the repository. Based on the risk that dried resin beads will swell if they absorb water, causing mechanical stresses likely to compromise the integrity of the disposal site, ONDRAF/NIRAS informed Tihange NPP that the Hot Compaction Unit would not be qualified as spent resins conditioning process. Further to this irrevocable decision, the Operator undertook three actions: - The first one was the qualification and purchase of waste containers to provide additional temporary storage capacity on site for its operational spent resins; - The second one is the selection of a new spent resins conditioning process and the performance of the related qualification tests to demonstrate it meets the updated Waste Acceptance Criteria; - The last one is the dismantling of the Hot Compaction Unit to clear the space and enable the installation of new equipment. This latter task was carried out in 2018, involving decontamination and free release measurements of all the materials, a very limited fraction of it having to be further processed as radioactive waste. Nevertheless, Tihange NPP wishes to keep the super-compactor and its hydraulic unit for a possible resale or reuse for the treatment of mixed waste. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗