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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 379 records · Page 21
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Intelligent Monitoring Systems and Advanced Well Integrity and Mitigation

Long-term seismic monitoring of carbon capture and storage projects is needed to verify that the injected gas is safely stored in the subsurface until permanence can be assured. Conventional surface seismic monitoring techniques are usually expensive, require highly invasive surface operations, and need significant time investments on the part of personnel for both the field effort and processing the acquired data. For these reasons, permanent reservoir monitoring technologies are preferred, as they can offer a cost-effective solution for long-term monitoring. As part of the monitoring program of the Archer Daniels Midland’s large-scale injection of CO 2 in Decatur, Illinois, USA, a continuous seismic monitoring array was installed using a combination of surface orbital vibrator (SOV) sources and fiber-optic cables for distributed acoustic sensing (DAS) acquisition with the objective to build a continuous monitoring array. The aim of the presented project was to build a monitoring array and platform that integrates real-time seismic data with conventional data streams and provides continuous data analysis using dynamic computational models to deliver a comprehensive real-time assessment of subsurface conditions. It is in this context that the Intelligent Monitoring Systems and Advanced Well Integrity and Mitigation project was proposed with the objective to develop an integrated architecture that utilizes a permanent seismic monitoring network, combines the real-time geophysical and process data with reservoir flow and geomechanical models to create a comprehensive monitoring, visualization, and control system that delivers critical information for process surveillance and optimization.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1975

Air pollution source identification

The techniques available for source identification are reviewed: remote sensing, injected tracers, and pollutants themselves as tracers. The use of the large number of trace elements in the ambient airborne particulate matter as a practical means of identifying sources is discussed. Trace constituents are determined by sensitive, inexpensive, nondestructive, multielement analytical methods such as instrumental neutron activation and charged particle X-ray fluorescence. The application to a large data set of pairwise correlation, the more advanced pattern recognition-cluster analysis approach with and without training sets, enrichment factors, and pollutant concentration rose displays for each element is described. It is shown that elemental constituents are related to specific source types: earth crustal, automotive, metallurgical, and more specific industries. A field-ready source identification system based on time and wind direction resolved sampling is described.

Fordyce, J. S.↗
NASA NTRS1978

Combustion of hydrogen in a two-dimensional duct with step fuel injectors

An investigation of the combustion of hydrogen perpendicularly injected from step fuel injectors into a Mach 2.72, 2100 K vitiated test gas was conducted. The model simulated the flow between the center and side struts of an integrated scramjet module at Mach 7 flight and an altitude of 29 km. Parametric variation included equivalence ratio, fuel dynamic pressure ratio, and area distribution of the model. The overall area ratio of the model was held constant at 2.87. The data analysis indicated that no measurable improvement in mixing or combustion efficiency was obtained by varying the fuel dynamic pressure ratio from 0.79 to 2.45. Computations indicated approximately 80 percent of the fuel was mixed so that it could react; however, only approximately 50 percent of the mixed fuel actually reacted in two test configurations, and 74 percent in later tests where less area expansion of the flow occurred.

Eggers, J. M.↗
NASA NTRS2013

Investigating Titan's Atmospheric Chemistry at Low Temperature in Support of the NASA Cassini Mission

Titan's atmosphere, composed mainly of N2 and CH4, is the siege of a complex chemistry induced by solar UV radiation and electron bombardment from Saturn's magnetosphere. This organic chemistry occurs at temperatures lower than 200 K and leads to the production of heavy molecules and subsequently solid aerosols that form the orange haze surrounding Titan. The Titan Haze Simulation (THS) experiment has been developed on the COSMIC simulation chamber at NASA Ames in order to study the different steps of Titan's atmospheric chemistry at low temperature and to provide laboratory data in support for Cassini data analysis. The chemistry is simulated by plasma in the stream of a supersonic expansion. With this unique design, the gas mixture is adiabatically cooled to Titan-like temperature (approx. 150 K) before inducing the chemistry by plasma discharge. Different gas mixtures containing N2, CH4, and the first products of the N2,-CH4 chemistry (C2H2, C2H4, C6H6...) but also heavier molecules such as PAHs or nitrogen containing PAHs can be injected. Both the gas phase and solid phase products resulting from the plasma-induced chemistry can be monitored and analyzed. Here we present the results of recent gas phase and solid phase studies that highlight the chemical growth evolution when injecting heavier hydrocarbon trace elements in the initial N2-CH4 mixture. Due to the short residence time of the gas in the plasma discharge, only the first steps of the chemistry have time to occur in a N2-CH4 discharge. However by adding acetylene and benzene to the initial N2-CH4 mixture, we can study the intermediate steps of Titan's atmospheric chemistry as well as specific chemical pathways. These results show the uniqueness of the THS experiment to help understand the first and intermediate steps of Titan fs atmospheric chemistry as well as specific chemical pathways leading to Titan fs haze formation.

Sciamma-O'Brien, Ella↗
NASA NTRS1991

Photometric analysis of a space shuttle water venting

Presented here is a preliminary interpretation of a recent experiment conducted on Space Shuttle Discovery (Mission STS 29) in which a stream of liquid supply water was vented into space at twilight. The data consist of video images of the sunlight-scattering water/ice particle cloud that formed, taken by visible light-sensitive intensified cameras both onboard the spacecraft and at the AMOS ground station near the trajectory's nadir. This experiment was undertaken to study the phenomenology of water columns injected into the low-Earth orbital environment, and to provide information about the lifetime of ice particles that may recontact Space Shuttle orbits later. The findings about the composition of the cloud have relevance to ionospheric plasma depletion experiments and to the dynamics of the interaction of orbiting spacecraft with the environment.

Viereck, R. A.↗
DOE OSTI2022

Quality Analysis of Baseline Time-Lapse CSEM Data CarbonSAFE Project, North Dakota

Conference presentation at International Meeting for Applied Geoscience & Energy (IMAGE), Houston, TX, August 28 – September 2, 2022. When a series of time-lapse CSEM surveys are designed to measure the often-small variations in signal seen in CCUS projects, the primary concern must be collecting the highest-quality data and reducing as much noise as possible. This includes optimization during planning and feasibility, careful and consistent quality checks in the field, and transparent and repeatable postprocessing steps. We apply this practice to a baseline (prior to CO 2 injection) CSEM data set collected for a time-lapse survey in Center, North Dakota, as a part of the North Dakota CarbonSAFE project, and describe the rigorous quality control and assessment methods used, including noise removal and data validation with 1D and 3D inversion to tie results to borehole logs. The final result is an accurate and representative CSEM data set and information that stakeholders can use to inform future time-lapse survey costs and designs.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2022

Phenomenological Model of Nonlinear Dynamics and Deterministic Chaotic Gas Migration in Bentonite: Experimental Evidence and Diagnostic Parameters

Understanding gas migration in compacted clay materials, e.g., bentonite and claystone, is important for the design and performance assessment of an engineered barrier system of a radioactive waste repository system, as well as many practical applications. Existing field and laboratory data on gas migration processes in low-permeability clay materials demonstrate the complexity of flow and transport processes, including various types of instabilities, caused by nonlinear dynamics of coupled processes of liquid–gas exchange, dilation, fracturing, fracture healing, etc., which cannot be described by classical models of fluid dynamics in porous media. We here show that the complexity of gas migration processes can be explained using a phenomenological concept of nonlinear dynamics and deterministic chaos theory. To do so, we analyzed gas pressure and gas influx (i.e., input) and outflux (i.e., output), recorded during the gas injection experiment in the compact Mx80-D bentonite sample, and calculated a set of the diagnostic parameters of nonlinear dynamics and chaos, such a global embedding dimension, a correlation dimension, an information dimension, and a spectrum of Lyapunov exponents, as well as plotted 2D and 3D pseudo-phase-space strange attractors, based on the univariate influx and outflux time series data. These results indicate the presence of phenomena of low-dimensional deterministic chaotic behavior of gas migration in bentonite. In particular, during the onset of gas influx in the bentonite core, before the breakthrough, the development of gas flow pathways is characterized by the process of chaotic gas diffusion. After the breakthrough, with inlet-to-outlet movement of gas, the prevailing process is chaotic advection. During the final phase of the experiment, with no influx to the sample, the relaxation pattern of gas outflux is resumed back to a process of chaotic diffusion. The types of data analysis and a proposed phenomenological model can be used to establish the basic principles of experimental data-gathering, modeling predictions, and a research design.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Investigation of acoustic waves under subsurface conditions to improve the predictions of rock mechanical properties and natural fracture characteristics

Mechanical properties and natural fracture characteristics are critical to investigate for subsurface engineering applications, including carbon storage, well drilling, and stimulation, as they govern rock stability, fluid flow, and mechanical behavior under stress. This dissertation integrates experimental and machine learning approaches to enhance the prediction and understanding of these properties by analyzing acoustic wave behavior under varied subsurface conditions. First, the influence of temperature, pore pressure, and supercritical CO2 (scCO2) saturation on poroelastic properties is examined using Gray Berea sandstone samples. The results show that temperature and pore pressure significantly affect the bulk modulus and Biot’s coefficient, while scCO2 saturation impacts rock compressibility, informing strategies for effective geological carbon storage. The study extends this understanding by experimentally evaluating the impact of reservoir depletion on the dynamic mechanical properties of the emerging Caney shale in South Oklahoma with the employment of unsupervised machine learning to predict static mechanical properties across the Caney shale. Integrating petrophysical data and chemostratigraphy, the workflow—featuring K-means clustering, principal component analysis (PCA), and inverse distance weighting (IDW)—improves stratigraphic characterization and the estimation of static-to-dynamic modulus ratios, which is vital for optimizing drilling and stimulation strategies. Finally, the work explores how natural fracture characteristics in shale influence acoustic waveforms and shear wave splitting (SWS) analysis. Experimental data on fractured samples under different stress and temperature conditions, combined with machine learning models such as K-nearest neighbors (KNN) and extreme gradient boosting (XGBoost), reveal key fracture properties impacting SWS and wave propagation. Together, these studies provide a comprehensive framework for linking acoustic wave behavior with rock properties, advancing the methods for monitoring and predicting geomechanical changes. The insights offered valuable implications for safer, more efficient CO2 injection, hydrocarbon extraction, and subsurface management.

Elkholy, Sherif↗
NASA NTRS1981

A study of stratospheric aerosol maturity

A sampling and analysis technique that uses the binomial distribution to characterize stratospheric aerosol populations at the 95% level of confidence is described. Particle samples obtained over Alaska during July 15-19, 1979, are used; the results show the presence of more small particles at lower altitude than at high altitudes. Calculations of the surface area and volume distributions for all aerosol samples collected are given. Evidence from these data suggests either that Aitken nuclei are injected or diffused across the tropopause and rise into the stratosphere, where they mature into larger particles, or nuclei form in the lower stratosphere and become mature aerosols at high altitude. Samples obtained at another site give the same results, supporting the view that the process of injection or nucleation and maturing of aerosols with altitude may be global and need not occur only in locations exhibiting unique meteorologic features.

Oberbeck, V. R.↗
DOE OSTI2020

Quantitative Long-Term Monitoring of the Circulating Gases in the KATRIN Experiment Using Raman Spectroscopy

The Karlsruhe Tritium Neutrino (KATRIN) experiment aims at measuring the effective electron neutrino mass with a sensitivity of 0.2 eV/c2, i.e., improving on previous measurements by an order of magnitude. Neutrino mass data taking with KATRIN commenced in early 2019, and after only a few weeks of data recording, analysis of these data showed the success of KATRIN, improving on the known neutrino mass limit by a factor of about two. This success very much could be ascribed to the fact that most of the system components met, or even surpassed, the required specifications during long-term operation. Here, we report on the performance of the laser Raman (LARA) monitoring system which provides continuous high-precision information on the gas composition injected into the experiment’s windowless gaseous tritium source (WGTS), specifically on its isotopic purity of tritium—one of the key parameters required in the derivation of the electron neutrino mass. The concentrations cx for all six hydrogen isotopologues were monitored simultaneously, with a measurement precision for individual components of the order 10−3 or better throughout the complete KATRIN data taking campaigns to date. From these, the tritium purity, εT, is derived with precision of <10−3 and trueness of <3 × 10−3, being within and surpassing the actual requirements for KATRIN, respectively.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

Accurate and Timely Forecasts of Geologic Carbon Storage using Machine Learning Methods

Carbon capture and storage is one strategy to reduce greenhouse gas emissions. One approach to storing the captured CO2 is to inject it into deep saline aquifers. However, dynamics of the injected CO2 plume is uncertain and the potential for leakage back to the atmosphere must be assessed. Thus, accurate and timely forecasts of CO2 storage via real-time measurements integration becomes very crucial. This study proposes a learning-based, inverse-free prediction method that can accurately and rapidly forecast CO2 movement and distribution with uncertainty quantification based on limited simulation and observation data. The machine learning techniques include dimension reduction, multivariate data analysis, and Bayesian learning. The outcome is expected to provide CO2 storage site operators with an effective tool for real-time decision making.

Lu, Dan↗
NASA NTRS2019

Numerical Investigation and Optimization of a Flushwall Injector for Scramjet Applications at Hypervelocity Flow Conditions

An investigation utilizing Reynolds-averaged simulations (RAS) was performed in order to find optimal designs for an interdigitated flushwall injector suitable for scramjet applications at hypervelocity conditions. The flight Mach number, duct height, spanwise width, and injection angle were the design variables selected to maximize two objective functions: the thrust potential and combustion efficiency. A Latin hypercube sampling design-of-experiments method was used to select design points for RAS. A methodology was developed that automated building geometries and generating grids for each design. The ensuing RAS analysis generated the performance database from which the two objective functions of interest were computed using a one-dimensional performance utility. The data were fitted using four surrogate models: an artificial neural network (ANN) model, a cubic polynomial, a quadratic polynomial, and a Kriging model. Variance-based decomposition showed that both objective functions were primarily driven by changes in the duct height. Multiobjective design optimization was performed for all four surrogate models via a genetic algorithm method. Optimal solutions were obtained at the upper and lower bounds of the flight Mach number range. The Kriging model obtained an optimal solution set that predicted high values for both objective functions. Additionally, three challenge points were selected to assess the designs on the Pareto fronts. Further sampling among the designs of the Pareto fronts are required in order to lower the errors and perform more accurate surrogate-based optimization. sed optimization.

Shenoy, Rajiv R.↗
DOE OSTI2021

Information Leakage Analysis using a Co-design-Based Fault Injection Technique on a RISC-V Microprocessor

The RISC-V instruction set architecture open licensing policy has spawned a hive of development activity, making a range of implementations publicly available. The environments in which RISC-V operates have expanded correspondingly, driving the need for a generalized approach to evaluating the reliability of RISC-V implementations under adverse operating conditions or after normal wear-out periods. Fault injection (FI) refers to the process of changing the state of registers or wires, either permanently or momentarily, and then observing execution behavior. The analysis provides insight into the development of countermeasures that protect against the leakage or corruption of sensitive information which might occur because of unexpected execution behavior. In this paper, we develop a hardware-software co-design architecture that enables fast, configurable fault emulation and utilize it for information leakage and data corruption analysis. Modern System-on-chip FPGAs enable building an evaluation platform where control elements run on a processor(s) (PS) simultaneously with the target design running in the programmable logic (PL). Software components of the FI system introduce faults and report execution behavior. A pair of RISC-V FI-instrumented implementations are created and configured to execute the Advanced Encryption Standard and Twister algorithms. Key and plaintext information leakage and degraded pseudo-random sequences are both observed in the output for a subset of the emulated faults.

42 ENGINEERING↗
DOE OSTI2024

Rapid Monitoring and Defense Approach for Resilience Improvement of Grid Cyber Security

Cyber-physical systems and electric utilities significantly depend on the reliability and efficiency of information and operational technology. However, false data injection attacks based on synchrophasor measurement data pose a serious threat to the safe and reliable operation of modern power systems. Here, to mitigate this problem, a rapid monitoring and defense approach is proposed to defend against cyber attacks. Initially, the Time and Frequency based Convolutional neural Network (TFCN) is proposed to detect different types of attacks. Within the TFCN, the advances are that both time and frequency domain information can be fused without extra spectrum analysis methods, and can save detection time to speed the calculation efficiency using the developed time-frequency block. Next, a comprehensive defense strategy is developed for multiple cyber attacks to ensure the stability and resilience of the power system according to the feedback detection results. The advances of this strategy are that different control strategies can be automatically selected to recover the stability to the greatest extent according to the detected attacks. To verify the effectiveness of the proposed approach, the high-speed frequency measurements collected from the wide-area monitoring system are used. The results demonstrate that the cyber attack detection performance can reach 95.57% accuracy, outperforming both traditional and some advanced neural networks. Importantly, the defense strategy is conducted and verified in a modified IEEE 39 bus system as well, which illustrates profound performance in faster stability restoration.

Comprehensive defense strategy↗
NASA NTRS1983

EXOS-B/Siple station VLF wave-particle interaction experiments. II - Transmitter signals and associated emissions

New observations in the magnetosphere of coherent VLF waves from the Siple Station, Antarctica, transmitter and associated VLF emissions triggered by the transmitter signals are reported. The data analyzed were acquired on the EXOS-B high-altitude satellite during the period July 15-September 7, 1979, during joint VLF wave-injection experiments involving scientists from Kyoto, Tokyo, and Stanford universities. The experiments were carried out to gain a deeper understanding of the interactions between coherent VLF waves and energetic particles in the magnetosphere, in particular, the whistler-mode instability through which both natural and stimulated VLF emissions are produced. Analysis of the emission-triggering events provides strong evidence that the triggering took place inside whistler-mode ducts and that the emissions reached the satellite only after being scattered at one end of the ducts by ionospheric irregularities. It is concluded that in the noon sector of the magnetosphere, the amplitude of nonducted signals from the Siple transmitter is generally less than the threshold level necessary for triggering in the nonducted mode.

Bell, T. F.↗
NASA NTRS1997

Lunar Prospector Mission Design

The National Aeronautics and Space Administration (NASA) has selected Lunar Prospector as one of the discovery missions to conduct solar system exploration science investigations. The mission is NASA's first lunar voyage to investigate key science objectives since Apollo and will be launched in September 1997. In keeping with discovery program requirements to reduce total mission cost and utilize new technology, Lunar Prospector's mission design and control will focus on the use of innovative and proven trajectory analysis programs. As part of this effort, the Ames Research Center and the Goddard Space Flight Center have become partners in the Lunar Prospector trajectory team to provide the trajectory analysis and orbit determination support. The mission design of Lunar Prospector is characterized by a direct minimum energy transfer trajectory to the moon with an injection into a circular 100 km altitude polar mapping orbit. The mission design will incorporate the optimization of the reference trajectory for a new launch vehicle. An extended mission includes a periselene altitude approaching 10 km. As part of the navigation, a new lunar potential model will be used that incorporates data from the recent Clementine mission. This paper provides understanding of the design of the Lunar Prospector mission and the optimization process of the nominal trajectory, orbit determination, launch windows, and lunar orbit targets, and discusses the feasibility of meeting the mission goals.

Folta, David↗
NASA NTRS2009

Loss Factor Estimation Using the Impulse Response Decay Method on a Stiffened Structure

High-frequency vibroacoustic modeling is typically performed using energy-based techniques such as Statistical Energy Analysis (SEA). Energy models require an estimate of the internal damping loss factor. Unfortunately, the loss factor is difficult to estimate analytically, and experimental methods such as the power injection method can require extensive measurements over the structure of interest. This paper discusses the implications of estimating damping loss factors using the impulse response decay method (IRDM) from a limited set of response measurements. An automated procedure for implementing IRDM is described and then evaluated using data from a finite element model of a stiffened, curved panel. Estimated loss factors are compared with loss factors computed using a power injection method and a manual curve fit. The paper discusses the sensitivity of the IRDM loss factor estimates to damping of connected subsystems and the number and location of points in the measurement ensemble.

Cabell, Randolph↗
NASA NTRS2014

Search for Cosmic-Ray-Induced Gamma-Ray Emission in Galaxy Clusters

Current theories predict relativistic hadronic particle populations in clusters of galaxies in addition to the already observed relativistic leptons. In these scenarios hadronic interactions give rise to neutral pions which decay into gamma rays that are potentially observable with the Large Area Telescope (LAT) on board the Fermi space telescope. We present a joint likelihood analysis searching for spatially extended gamma-ray emission at the locations of 50 galaxy clusters in four years of Fermi-LAT data under the assumption of the universal cosmic-ray (CR) model proposed by Pinzke & Pfrommer. We find an excess at a significance of 2.7 delta, which upon closer inspection, however, is correlated to individual excess emission toward three galaxy clusters: A400, A1367, and A3112. We discuss these cases in detail and conservatively attribute the emission to unmodeled background systems (for example, radio galaxies within the clusters).Through the combined analysis of 50 clusters, we exclude hadronic injection efficiencies in simple hadronic models above 21% and establish limits on the CR to thermal pressure ratio within the virial radius, R(sub 200), to be below 1.25%-1.4% depending on the morphological classification. In addition, we derive new limits on the gamma-ray flux from individual clusters in our sample.

Online-only material: color figures↗