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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 235 records · Page 13
All sourcesNASA NTRSDOE OSTI
NASA NTRS2014

Microbiology and Crew Medical Events on the International Space Station

The closed environment of the International Space Station (ISS) creates an ideal environment for microbial growth. Previous studies have identified the ubiquitous nature of microorganisms throughout the space station environment. To ensure safety of the crew, microbial monitoring of air and surface within ISS began in December 2000 and continues to be monitored on a quarterly basis. Water monitoring began in 2009 when the potable water dispenser was installed on ISS. However, it is unknown if high microbial counts are associated with inflight medical events. The microbial counts are determined for the air, surface, and water samples collected during flight operations and samples are returned to the Microbiology laboratory at the Johnson Space Center for identification. Instances of microbial counts above the established microbial limit requirements were noted and compared inflight medical events (any non-injury event such as illness, rashes, etc.) that were reported during the same calendar-quarter. Data were analyzed using repeated measures logistic regression for the forty-one US astronauts flew on ISS between 2000 and 2012. In that time frame, instances of microbial counts being above established limits were found for 10 times for air samples, 22 times for surface samples and twice for water. Seventy-eight inflight medical events were reported among the astronauts. A three times greater risk of a medical event was found when microbial samples were found to be high (OR = 3.01; p =.007). Engineering controls, crew training, and strict microbial limits have been established to mitigate the crew medical events and environmental risks. Due to the timing issues of sampling and the samples return to earth, identification of particular microorganisms causing a particular inflight medical event is difficult. Further analyses are underway.

Oubre, Cherie M.↗
NASA NTRSDate not supplied

Culture-Independent Microbial Air Profiling using a Spaceflight-Compatible Nanopore Sequencing Method

Microbial monitoring of spacecraft air is critical toward assessing the efficacy of microbial controls within the environmental control and life support systems to protect the crew and vehicle environment. Currently, onboard the International Space Station (ISS), the air is monitored every quarter using an impaction air sampler. With this method, microbial cells and spores are pulled onto plates containing a growth medium. Following onboard incubation, the crew reports approximate microbial levels to the ground, but sample return is required for identification. Upon return of the plates, the isolates present are identified for crew health risk assessments. As NASA moves beyond low-Earth orbit, sample return will be impractical, and a near real-time monitoring capability is essential. Significant strides have been made in recent years to utilize a molecular-based method for microbial profiling of ISS surfaces. The developed method is independent of microbial culture, thus removing the bias toward detecting only culturable organisms, eliminating the need for sample return, and reducing the risk to crew health from exposure to high microbial levels. The work described here details the evaluation of three different air sampling platforms whose product is amenable to downstream molecular processing. The three samplers were compared in terms of mass and power requirements, ease of use, and the resulting data. For the two highest-ranking samplers, a basic concept of operations was developed to transfer the sample into the already established preparation and sequencing process. Using these concepts of operations, an in-depth comparison of the molecular data generated was compared to the historical culture-based method. Data from both methods detailed similar microbial profiles, while the molecular method detailed microbial identifications that were lacking from the culture data. The developed method will enable the generation of near real-time microbial profiles of the spacecraft atmosphere.

Brandon Dunbar↗
DOE OSTI2023

How reliable is distribution of relaxation times (DRT) analysis? A dual regression-classification perspective on DRT estimation, interpretation, and accuracy

The distribution of relaxation times (DRT) has gained increasing attention and adoption in recent years as a versatile method for analyzing electrochemical impedance spectroscopy (EIS) data obtained from complex devices like fuel cells, electrolyzers, and batteries. The DRT deconvolutes the impedance without a priori specification of a generative model, which is especially useful for interpretation and model selection when the governing principles of the system under study are not fully understood. However, DRT estimation is an ill-posed inversion problem that must be addressed with a subjective choice of regularization and tuning, which leaves substantial risk of misleading interpretations of EIS data. In this work, we suggest a new classification view of the DRT inversion to clarify DRT estimation and interpretation. We introduce a dual regression-classification framework that unifies the classification and regression views of the DRT inversion with wide-reaching implications for DRT analysis. The dual framework is employed to demonstrate a new kind of DRT inversion algorithm and develop novel evaluation metrics that capture previously ignored aspects of DRT accuracy. These approaches are applied to both synthetic data and experimental spectra collected from a protonic ceramic fuel cell and a lithium-ion battery to illustrate their broad utility. The dual inversion algorithm shows promising performance for accurate DRT estimation and autonomous model identification, while the dual evaluation approach produces metrics that meaningfully assess the strengths and risks of DRT algorithms. Here this work provides valuable insight for both practical application of the DRT to experimental data and further development of EIS analysis methods.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Application of Modified Meshgraphnets for Subsurface Prediction during CO2 Sequestration

In the face of the increasingly dire consequences of anthropogenic climate change, capturing and storing carbon dioxide is paramount. However, several impediments exist to the safe and effective subsurface storage of CO2, such as cost of transport, identification of suitable sites for subsurface storage, and assessment of long-term risk from storage in subsurface aquifers. Accurate subsurface modeling is necessary to ensure that CO2 storage is both safe and effective. Still, such modeling has traditionally required either substantial time and computational power (numerical simulation) or a substantial amount of pre-existing data for training (machine learning models). Additionally, these models lack flexibility in dealing with both changes in discretization of the input data and generalizability beyond the data on which they are trained. In order to address these issues, this research applies graph neural networks (GNNs) to predict subsurface saturation and pressure during CO₂ injection in a model of the Illinois Basin-Decatur Project (IBDP). GNNs provide a flexible, intuitive method for representing and manipulating complex unstructured data, which is often found in many practical domain problems such as fluid flow and subsurface characterization. These unstructured grids are easily represented in GNNs by representing spatially-localized features such as permeability, porosity, saturation, and pressure as nodes in a graph and relationships between these properties as edges connecting these nodes. This research applies a specific GNN model called MeshGraphNets (MGN) to model the change in CO2 saturation and pressure over a 50-month time period (36 months of injection, 14 months post-injection). The MGN model leverages a message passing process that allows the network to learn both the spatial and temporal dynamics of this system simultaneously. Additionally, training on a limited dataset (64 realizations, 20 time points each) resulted in a high degree of accuracy in saturation prediction both within the same timeframe as the training (20 months, 0.039 average RMSE) and when projecting out to the end of injection (36 months, 0.053 average RMSE). Temporal predictions such as those generated by MGNs and other similar models are prone to accumulated error over time; in order to address this, a multi-step rollout (MSR) training process was applied to calculate training loss. This method mimics the forward prediction during inference by “rolling out” multiple time points in a single training step using the previous prediction as input to the MGN model. By calculating the loss several time steps forward from the current prediction, the model is forced to find a more stable state over time. Application of MSR to the MGN model resulted in an average 15% reduction in inference error over time during forward prediction. This study showcases the immense potential of GNNs as a game-changing methodology for predicting pressure and saturation evolution in CCS projects, ultimately paving the way for more sustainable and effective carbon storage solutions. Presentation prepared for the 2024 AiChE Annual Meeting, October 27 to November 1 2024, San Diego, CA.

Holcomb, Paul↗
NASA NTRS1979

Millimeter wave satellite concepts. Volume 2: Technical report

Identification of technologies for millimeter satellite communication systems, and assessment of the relative risks of these technologies, were accomplished through subsystem modeling and link optimization for both point-to-point and broadcast applications. The results, in terms of annual cost per channel to the user from a commercial view point, are described.

Hilsen, N. B.↗
NASA NTRS2000

Hyper-X Research Vehicle (HXRV) Experimental Aerodynamics Test Program Overview

This paper provides an overview of the experimental aerodynamics test program to ensure mission success for the autonomous flight of the Hyper-X Research Vehicle (HXRV). The HXRV is a 12-ft long, 2700 lb lifting body technology demonstrator designed to flight demonstrate for the first time a fully airframe integrated scramjet propulsion system. Three flights are currently planned, two at Mach 7 and one at Mach 10, beginning in the fall of 2000. The research vehicles will be boosted to the prescribed scramjet engine test point where they will separate from the booster, stabilize. and initiate engine test. Following 5+ seconds of powered flight and 15 seconds of cowl-open tares, the cowl will close and the vehicle will fly a controlled deceleration trajectory which includes numerous control doublets for in-flight aerodynamic parameter identification. This paper reviews the preflight testing activities, wind tunnel models, test rationale. risk reduction activities, and sample results from wind tunnel tests supporting the flight trajectory of the HXRV from hypersonic engine test point through subsonic flight termination.

Holland, Scott D.↗
NASA NTRS2000

Hyper-X Research Vehicle (HXRV) Experimental Aerodynamics Test Program Overview

This paper provides an overview of the experimental aerodynamics test program to ensure mission success for the autonomous flight of the Hyper-X Research Vehicle (HXRV). The HXRV is a 12-ft long, 2700 lb lifting body technology demonstrator designed to flight demonstrate for the first time a fully airframe integrated scramjet propulsion system. Three flights are currently planned, two at Mach 7 and one at Mach 10, beginning in the fall of 2000. The research vehicles will be boosted to the prescribed scramjet engine test point where they will separate from the booster, stabilize, and initiate engine test. Following 5+ seconds of powered flight and 15 seconds of cow-open tares, the cowl will close and the vehicle will fly a controlled deceleration trajectory which includes numerous control doublets for in-flight aerodynamic parameter identification. This paper reviews the preflight testing activities, wind tunnel models, test rationale, risk reduction activities, and sample results from wind tunnel tests supporting the flight trajectory of the HXRV from hypersonic engine test point through subsonic flight termination.

Holland, Scott D.↗
NASA NTRS2014

Rapid Electrochemical Detection and Identification of Microbiological and Chemical Contaminants for Manned Spaceflight Project

Microbial control in the spacecraft environment is a daunting task, especially in the presence of human crew members. Currently, assessing the potential crew health risk associated with a microbial contamination event requires return of representative environmental samples that are analyzed in a ground-based laboratory. It is therefore not currently possible to quickly identify microbes during spaceflight. This project addresses the unmet need for spaceflight-compatible microbial identification technology. The electrochemical detection and identification platform is expected to provide a sensitive, specific, and rapid sample-to-answer capability for in-flight microbial monitoring that can distinguish between related microorganisms (pathogens and non-pathogens) as well as chemical contaminants. This will dramatically enhance our ability to monitor the spacecraft environment and the health risk to the crew. Further, the project is expected to eliminate the need for sample return while significantly reducing crew time required for detection of multiple targets. Initial work will focus on the optimization of bacterial detection and identification. The platform is designed to release nucleic acids (DNA and RNA) from microorganisms without the use of harmful chemicals. Bacterial DNA or RNA is captured by bacteria-specific probe molecules that are bound to a microelectrode, and that capture event can generate a small change in the electrical current (Lam, et al. 2012. Anal. Chem. 84(1): 21-5.). This current is measured, and a determination is made whether a given microbe is present in the sample analyzed. Chemical detection can be accomplished by directly applying a sample to the microelectrode and measuring the resulting current change. This rapid microbial and chemical detection device is designed to be a low-cost, low-power platform anticipated to be operated independently of an external power source, characteristics optimal for manned spaceflight and areas where power and computing resources are scarce.

Pierson, Duane↗
DOE OSTI2026

Assessing shellfish water exposure to fecal bacteria pollution in Salish Sea: three-dimensional modeling and implications for monitoring

Fecal bacteria (FB) contamination poses significant risks to shellfish safety and management in coastal and estuarine waters. Despite extensive pollution identification and correction efforts, FB contamination in shellfish-growing areas persists in the Salish Sea, highlighting the need to identify overlooked sources and better understand FB transport from riverine and shoreline inputs to shellfish beds. To address this, a high-resolution three-dimensional hydrodynamic model coupled with FB kinetics was developed and applied to a case study site in Salish Sea—Portage Bay—to simulate freshwater plume circulation, flushing dynamics, and bacterial transport. Daily FB loading from the major freshwater inflow—Nooksack River was generated by both linear interpolation and integrating a machine learning approach (XGBoost), trained on historical hydrological and meteorological data. The model successfully reproduced both the magnitude and seasonal variation of FB concentrations in Portage Bay for the year of 2021, demonstrating that simplified FB kinetics with first-order decay due to mortality was effective in this dynamic coastal environment with short flushing time. Model results identified the Nooksack River as the dominant far-field FB source, while scenario simulations showed that near-field coastal stormwater outfalls elevated local FB levels following rainfall, particularly under low-flow conditions. The XGBoost prediction provided comparable or superior accuracy to linear interpolation, particularly during periods of missing observational data, by capturing short-term variability and event-driven loading more effectively. Integrating data-driven riverine FB inputs with mechanistic coastal numerical modeling provides a robust framework for operational forecasting of shellfish bed exposure risk and supports adaptive monitoring and management of shellfish growing areas in the Salish Sea and similar coastal systems.

Salish Sea↗
DOE OSTI2025

An interregional optimization approach for time series aggregation in continent-scale electricity system models

Modeling electric power systems with high shares of weather-dependent resources requires tradeoffs between temporal, spatial, and operational resolution. Many studies perform time series aggregation using clustering algorithms to reduce the temporal dimension, but when modeling continent-scale electricity systems that are large enough to contain multiple independent weather systems, this approach requires large numbers of representative periods to minimize errors in regional wind and solar capacity factors. Here, a new optimization-based approach for representative period selection and weighting is introduced that minimizes regional errors in average renewable capacity factors and electricity demand. The method delivers higher regional fidelity with fewer representative periods than alternative clustering methods when applied to wind, solar, and demand profiles for the contiguous United States. When representative periods are selected from multiple weather years, the optimized method reproduces regional averages with lower error than a complete 365-day time series from any single weather year. The method identifies only representative (as opposed to outlying) periods but can be combined with an iterative "stress period" identification approach to guide efficient decision-making considering both average and high-risk weather conditions.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

Automatic identification of edge localized modes in the DIII-D tokamak

Fusion power production in tokamaks uses discharge configurations that risk producing strong type I edge localized modes. The largest of these modes will likely increase impurities in the plasma and potentially damage plasma facing components, such as the protective heat and particle divertor. Machine learning-based prediction and control may provide for the automatic detection and mitigation of these damaging modes before they grow too large to suppress. To that end, large labeled datasets are required for the supervised training of machine learning models. We present an algorithm that achieves 97.7% precision when automatically labeling edge localized modes in the large DIII-D tokamak discharge database. The algorithm has no user controlled parameters and is largely robust to tokamak and plasma configuration changes. This automatically labeled database of events can subsequently feed future training of machine learning models aimed at autonomous edge localized mode control and suppression.

O’Shea, Finn H. (ORCID:0000000323987381)↗
NASA NTRS1977

Preliminary candidate advanced avionics system for general aviation

An integrated avionics system design was carried out to the level which indicates subsystem function, and the methods of overall system integration. Sufficient detail was included to allow identification of possible system component technologies, and to perform reliability, modularity, maintainability, cost, and risk analysis upon the system design. Retrofit to older aircraft, availability of this system to the single engine two place aircraft, was considered.

Mccalla, T. M.↗
NASA NTRS1979

Alsep data processing: How we processed Apollo Lunar Seismic Data

The Apollo lunar seismic station network gathered data continuously at a rate of 3 x 10 to the 8th power bits per day for nearly eight years until the termination in September, 1977. The data were processed and analyzed using a PDP-15 minicomputer. On the average, 1500 long-period seismic events were detected yearly. Automatic event detection and identification schemes proved unsuccessful because of occasional high noise levels and, above all, the risk of overlooking unusual natural events. The processing procedures finally settled on consist of first plotting all the data on a compressed time scale, visually picking events from the plots, transferring event data to separate sets of tapes and performing detailed analyses using the latter. Many problems remain especially for automatically processing extraterrestrial seismic signals.

Latham, G. V.↗
NASA NTRS1980

How we processed Apollo lunar seismic data

The Apollo lunar seismic station network gathered data continuously at a rate of 3 x 10 to the 8th bits per day for nearly eight years until termination in September, 1977. The data were processed and analyzed using a PDP-15 minicomputer. On average, 1500 long-period seismic events were detected yearly. Automatic event detection and identification schemes proved unsuccessful because of occasional high noise levels and, above all, the risk of overlooking unusual natural events. The processing procedures which were finally chosen consist of plotting all the data on a compressed time scale, visually picking events from the plots, transferring event data to separate sets of tapes and performing detailed analyses using the latter. Many problems remain, especially in the automatic processing of extraterrestrial seismic signals.

Nakamura, Y.↗
NASA NTRS2006

NASA Langley Research Center Systems Analysis & Concepts Directorate Participation in the Exploration Systems Architecture Study

The NASA Langley Research Center (LaRC) Systems Analysis & Concepts Directorate (SACD) began studying human exploration missions beyond low Earth orbit (LEO) in the year 1999. This included participation in NASA s Decadal Planning Team (DPT), the NASA Exploration Team (NExT), Space Architect studies and Revolutionary Aerospace Systems Concepts (RASC) architecture studies that were used in formulating the new Vision for Space Exploration. In May of 2005, NASA initiated the Exploration Systems Architecture Study (ESAS). The primary outputs of the ESAS activity were concepts and functional requirements for the Crewed Exploration Vehicle (CEV), its supporting launch vehicle infrastructure and identification of supporting technology requirements and investments. An exploration systems analysis capability has evolved to support these functions in the past and continues to evolve to support anticipated future needs. SACD had significant roles in supporting the ESAS study team. SACD personnel performed the liaison function between the ESAS team and the Shuttle/Station Configuration Options Team (S/SCOT), an agency-wide team charged with using the Space Shuttle to complete the International Space Station (ISS) by the end of Fiscal Year (FY) 2010. The most significant of the identified issues involved the ability of the Space Shuttle system to achieve the desired number of flights in the proposed time frame. SACD with support from the Kennedy Space Center performed analysis showing that, without significant investments in improving the shuttle processing flow, that there was almost no possibility of completing the 28-flight sequence by the end of 2010. SACD performed numerous Lunar Surface Access Module (LSAM) trades to define top level element requirements and establish architecture propellant needs. Configuration trades were conducted to determine the impact of varying degrees of segmentation of the living capabilities of the combined descent stage, ascent stage, and other elements. The technology assessment process was developed and implemented by SACD as the ESAS architecture was refined. SACD implemented a rigorous and objective process which included (a) establishing architectural functional needs, (b) collection, synthesis and mapping of technology data, and (c) performing an objective decision analysis resulting in technology development investment recommendations. The investment recommendation provided budget, schedule, and center/program allocations to develop required technologies for the exploration architecture, as well as the identification of other investment opportunities to maximize performance and flexibility while minimizing cost and risk. A summary of the trades performed and methods utilized by SACD for the Exploration Systems Mission Directorate (ESAS) activity is presented along with how SACD is currently supporting the implementation of the Vision for Space Exploration.

Keyes, Jennifer↗
DOE OSTI2022

Utilization of the LMP Methodology in Support of the VTR Conceptual Safety Design Report

The Versatile Test Reactor (VTR) is a fast spectrum test reactor currently being developed in the United States under the direction of the US Department of Energy (DOE), Office of Nuclear Energy. The VTR is utilizing a risk-informed performance-based (RIPB) approach for design support and authorization by the DOE, derived from recent efforts by the US industry led Licensing Modernization Project (LMP). This document contains an overview of the implementation of the LMP approach in support of the VTR Conceptual Safety Design Report (CSDR). The work reported here is the result of studies supporting a VTR conceptual design, cost, and schedule estimate for DOE-NE to make a decision on procurement. As such, it is preliminary. The VTR RIPB authorization approach utilizes information from the probabilistic risk assessment (PRA), coupled with deterministic analyses, to aid in decision-making regarding the identification and categorization of safety basis events (SBEs), the classification of structures, systems, and components (SSCs), and the evaluation of defense-in-depth (DID) adequacy. As part of initial reactor design efforts, a VTR conceptual design PRA was developed to support the RIPB process, which focused on at-power internal events, with scoping analyses for seismic and sodium fire hazards. In addition to supporting numerous design studies, preliminary results from the RIPB approach and the VTR conceptual design PRA were utilized as the basis of the VTR CSDR. The initial identification and categorization of SBEs, SSC classification, and DID evaluation were contained within the CSDR, which was submitted to DOE in 2019 as part of the CD-1 submittal package. Following review, DOE approved the CSDR in April 2020 and the CD-1 package in late 2020. Valuable experience was gained through the implementation of the RIPB approach for design and authorization during the VTR conceptual design phase, which is summarized in this document. To the extent possible, this experience has been shared with the advanced reactor industry, through publications and participation in licensing tabletops, in addition to informing DOE:NE advanced reactor regulatory development efforts. Furthermore, the approval of the CSDR by the DOE as part of CD-1 represents a significant milestone in the use of RIPB approaches for advanced reactor licensing.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
NASA NTRS2006

Database of Properties of Meteors

A database of properties of meteors, and software that provides access to the database, are being developed as a contribution to continuing efforts to model the characteristics of meteors with increasing accuracy. Such modeling is necessary for evaluation of the risk of penetration of spacecraft by meteors. For each meteor in the database, the record will include an identification, date and time, radiant properties, ballistic coefficient, radar cross section, size, density, and orbital elements. The property of primary interest in the present case is density, and one of the primary goals in this case is to derive densities of meteors from their atmospheric decelerations. The database and software are expected to be valid anywhere in the solar system. The database will incorporate new data plus results of meteoroid analyses that, heretofore, have not been readily available to the aerospace community. Taken together, the database and software constitute a model that is expected to provide improved estimates of densities and to result in improved risk analyses for interplanetary spacecraft. It is planned to distribute the database and software on a compact disk.

Suggs, Rob↗
DOE OSTI2021

Towards Resolving the Risk of Turbine Collision on Fish: FY21-22 Seedling Report Phase I

The most important concern for permitting tidal and river turbines is the collision risk of marine animals with the turbine blades. Our understanding of the risk to individual fish from colliding with turbine blades is poor; if these collisions were to occur, it is unknown whether fish will sustain recoverable injuries or be killed. Equally unknown is the impact these collisions might have on populations, particularly for threatened, endangered, or commercially managed fish species. In addition to observations of interactions of fish with turbines, numerical models need to be developed or expanded to predict impacts on fish populations. These models could replace expensive and technically challenging monitoring programs in high energy, often murky, tidal or river waters. In this project, a multi-pronged approach was taken to understand the state of knowledge for collision risk of fish with turbines and build a pathway forward. This approach included a workshop with experts, a literature review of modeling and empirical studies, the development of a research framework, and the identification of case studies to address through future work. This project is a first step towards the future development of effective and robust numerical models for assessing the collision risk of fish around turbines. This will achieve a balanced and improved estimate of the severity of collision risk to fish at the population scale.

Garavelli, Lysel↗