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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 361 records · Page 20
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Understanding atom probe’s analytical performance for iron oxides using correlation histograms and ab initio calculations

Abstract Field evaporation from ionic or covalently bonded materials often leads to the emission of molecular ions. The metastability of these molecular ions, particularly under the influence of the intense electrostatic field (10 10 Vm −1 ), makes them prone to dissociation with or without an exchange of energy amongst them. These processes can affect the analytical performance of atom probe tomography (APT). For instance, neutral molecules formed through dissociation may not be detected at all or with a time of flight no longer related to their mass, causing their loss from the analysis. Here, we evaluated the changes in the measured composition of FeO, Fe 2 O 3 and Fe 3 O 4 across a wide range of analysis conditions. Possible dissociation reactions are predicted by density-functional theory calculations considering the spin states of the molecules. The energetically favoured reactions are traced on to the multi-hit ion correlation histograms, to confirm their existence within experiments, using an automated Python-based routine. The detected reactions are carefully analyzed to reflect upon the influence of these neutrals from dissociation reactions on the performance of APT for analysing iron oxides.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2021

Measuring Nd(III) Solution Concentration in the Presence of Interfering Er(III) and Cu(II) Ions: A Partial Least Squares Analysis of Ultraviolet–Visible Spectra

Optical spectroscopy is a powerful characterization tool with applications ranging from fundamental studies to real-time process monitoring. However, it can be difficult to apply to complex samples that contain interfering analytes which are common in processing streams. Multivariate (chemometric) analysis has been examined for providing selectivity and accuracy to the analysis of optical spectra and expanding its potential applications. Here we will discuss chemometric modeling with an in-depth comparison to more simplistic analysis approaches and outline how chemometric modeling works while exploring the limits on modeling accuracy. Understanding the limitations of the chemometric model can provide better analytical assessment regarding the accuracy and precision of the analytical result. This will be explored in the context of UV–Vis absorbance of neodymium (Nd 3+ ) in the presence of interferents, erbium (Er 3+ ) and copper (Cu 2+ ) under conditions simulating the liquid–liquid extraction approach used to recycle plutonium (Pu) and uranium (U) in used nuclear fuel worldwide. Finally, the selected chemometric model, partial least squares regression, accurately quantifies Nd 3+ with a low percentage error in the presence of interfering analytes and even under conditions that the training set does not describe.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS2004

Compensating for Effects of Humidity on Electronic Noses

A method of compensating for the effects of humidity on the readouts of electronic noses has been devised and tested. The method is especially appropriate for use in environments in which humidity is not or cannot be controlled for example, in the vicinity of a chemical spill, which can be accompanied by large local changes in humidity. Heretofore, it has been common practice to treat water vapor as merely another analyte, the concentration of which is determined, along with that of the other analytes, in a computational process based on deconvolution. This practice works well, but leaves room for improvement: changes in humidity can give rise to large changes in electronic-nose responses. If corrections for humidity are not made, the large humidity-induced responses may swamp smaller responses associated with low concentrations of analytes. The present method offers an improvement. The underlying concept is simple: One augments an electronic nose with a separate humidity and a separate temperature sensor. The outputs of the humidity and temperature sensors are used to generate values that are subtracted from the readings of the other sensors in an electronic nose to correct for the temperature-dependent contributions of humidity to those readings. Hence, in principle, what remains after corrections are the contributions of the analytes only. Laboratory experiments on a first-generation electronic nose have shown that this method is effective and improves the success rate of identification of analyte/ water mixtures. Work on a second-generation device was in progress at the time of reporting the information for this article.

Homer, Margie↗
NASA NTRS2014

An Analysis of Earth Science Data Analytics Use Cases

The increase in the number and volume, and sources, of globally available Earth science data measurements and datasets have afforded Earth scientists and applications researchers unprecedented opportunities to study our Earth in ever more sophisticated ways. In fact, the NASA Earth Observing System Data Information System (EOSDIS) archives have doubled from 2007 to 2014, to 9.1 PB (Ramapriyan, 2009; and https:earthdata.nasa.govaboutsystem-- performance). In addition, other US agency, international programs, field experiments, ground stations, and citizen scientists provide a plethora of additional sources for studying Earth. Co--analyzing huge amounts of heterogeneous data to glean out unobvious information is a daunting task. Earth science data analytics (ESDA) is the process of examining large amounts of data of a variety of types to uncover hidden patterns, unknown correlations and other useful information. It can include Data Preparation, Data Reduction, and Data Analysis. Through work associated with the Earth Science Information Partners (ESIP) Federation, a collection of Earth science data analytics use cases have been collected and analyzed for the purpose of extracting the types of Earth science data analytics employed, and requirements for data analytics tools and techniques yet to be implemented, based on use case needs. ESIP generated use case template, ESDA use cases, use case types, and preliminary use case analysis (this is a work in progress) will be presented.

data analytics↗
NASA NTRS1993

Extrusion process optimization for toughness in balloon films

An experimental optimization process for blown film extrusion is described and examined in terms of the effects of the technique on the toughness of balloon films. The optimization technique by Cantor (1990) is employed which involves the identification of key process variables including screw speed, nip speed, bubble diameter, and frost-line height for analysis to optimize the merit function. The procedure is employed in the extrusion of a low-density polyethylene polymer, and the resulting optimized materials are toughness- and puncture-tested. Balloon toughness is optimized in the analytical relationship, and the process parameters are modified to attain optimal toughness. The film produced is shown to have an average toughness of 24.5 MPa which is a good value for this key property of balloon materials for high-altitude flights.

Cantor, K. M.↗
NASA NTRS1976

Considerations on data compression of synthetic aperture radar images

This paper describes some analytical results relative to the effectiveness of applying data compression techniques for efficient transmission of synthetic aperture radar (SAR) signals and images. A Rayleigh target model is assumed in the analysis. It is also assumed that all surface reflectivity information is of interest and needs to be transmitted. Spectral characteristics of radar echo signals and processed images are analyzed. Analytical results generally indicate that due to the lack of high spatial correlation in the Rayleigh distributed radar surface reflectivity, application of data compression to SAR signals and images under the square difference fidelity criterion may be less effective than its application to images obtained using incoherent illumination. On the other hand, if certain random variations in radar images are considered as undesirable, substantial compression ratio may be achieved by removing such variations.

Wu, C.↗
NASA NTRS2006

Characterization and Analyses of Valves, Feed Lines and Tanks used in Propellant Delivery Systems at NASA SSC

Accurate modeling of liquid rocket engine test processes involves assessing critical fluid mechanic and heat and mass transfer mechanisms within a cryogenic environment, and accurately modeling fluid properties such as vapor pressure and liquid and gas densities as a function of pressure and temperature. The Engineering and Science Directorate at the NASA John C. Stennis Space Center has developed and implemented such analytic models and analysis processes that have been used over a broad range of thermodynamic systems and resulted in substantial improvements in rocket propulsion testing services. In this paper, we offer an overview of the analyses techniques used to simulate pressurization and propellant fluid systems associated with the test stands at the NASA John C. Stennis Space Center. More specifically, examples of the global performance (one-dimensional) of a propellant system are provided as predicted using the Rocket Propulsion Test Analysis (RPTA) model. Computational fluid dynamic (CFD) analyses utilizing multi-element, unstructured, moving grid capability of complex cryogenic feed ducts, transient valve operation, and pressurization and mixing in propellant tanks are provided as well.

Ryan, Harry M.↗
NASA NTRS1984

Error detection process - Model, design, and its impact on computer performance

An analytical model is developed for computer error detection processes and applied to estimate their influence on system performance. Faults in the hardware, not in the design, are assumed to be the potential cause of transition to erroneous states during normal operations. The classification properties and associated recovery methods of error detection are discussed. The probability of obtaining an unreliable result is evaluated, along with the resulting computational loss. Error detection during design is considered and a feasible design space is outlined. Extension of the methods to account for the effects of extant multiple faults is indicated.

Shin, K. G.↗
DOE OSTI2022

Evaluation of Heat Exchanger Technology for Integrated Energy System: Methodology and Preliminary Application

This report proposes a novel heat exchanger evaluation method, based on integrated QFD-AHP technique, to support strategic optimal selection of heat exchanger (HX) technology for integrated energy systems. The term “optimal selection” is defined as selecting a product (i.e., HX) that best meets various aspects of end user demand, including both technical and economic requirements. Compared to previous HX evaluation methods, the proposed approach allows decision makers to explicitly take into account the practical demand of customers (i.e., HX end users) which may vary depending on the HX application target. In addition, the proposed evaluation method can be used not only for high-level decisions to select HX type, but also for low-level decisions such as the selection of the key components including HX material or heat transfer fluid. The focus of this study is to describe the new HX evaluation method and to illustrate the overall HX evaluation and selection processes using the three nuclear heat application cases that represent the thermal integration between advanced nuclear reactors and industrial processes. As a preliminary study, three different types of HX, i.e., shell-and-tube heat exchanger, printed circuit heat exchanger, and heat pipe heat exchanger, were compared.

42 ENGINEERING↗
DOE OSTI2024

Crossing beyond scattering amplitudes

We find that different asymptotic measurements in quantum field theory can be related to one another through new versions of crossing symmetry. Assuming analyticity, we conjecture generalized crossing relations for multi-particle processes and the corresponding paths of analytic continuation. We prove them to all multiplicity at tree-level in quantum field theory and string theory. We illustrate how to practically perform analytic continuations on loop-level examples using different methods, including unitarity cuts and differential equations. We study the extent to which anomalous thresholds away from the usual physical region can cause an analytic obstruction to crossing when massless particles are involved. In an appendix, we review and streamline historical proofs of four-particle crossing symmetry in gapped theories.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

Using Best Basis Inventory Data to Direct Strategies for Real-Time Monitoring of Hanford High Level Waste

The proposed Direct Feed High Level Waste (DFHLW) approach for processing high-level tank waste at Hanford is intended to reduce processing time by bypassing the Pretreatment Facility and transferring waste directly from the tank farm to the WTP HLW vitrification facility. This processing strategy could reduce or eliminate the washing and leaching steps that would have occurred in the Pretreatment facility. Operation of the vitrification facility is subject to chemical and radiological limits protecting safety (e.g. Waste Acceptance Criteria, or WACs) and process quality (e.g. Process Control Limits, or PCLs). Without washing and leaching, there is a greater risk of exceeding the WACs and PCLs. Hanford process engineers have devised blending strategies based on known chemical and radiological composition, volumes, and solids loadings of individual layers within each waste tank. These blending campaigns succeed in predicting a processing strategy that does not exceed the WACs and PCLs. However, the calculations do not ascribe uncertainties to the tank analysis data, quantities of material taken from the tanks to make the blend, or potential for mixing of layers within tanks. In order to confirm that a process strategy is working, it would be advantageous to have inline or at-line analytical instrumentation installed in the processing facilities that deliver measurement results in real time.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
NASA NTRS2010

Maximum Likelihood Time-of-Arrival Estimation of Optical Pulses via Photon-Counting Photodetectors

Many optical imaging, ranging, and communications systems rely on the estimation of the arrival time of an optical pulse. Recently, such systems have been increasingly employing photon-counting photodetector technology, which changes the statistics of the observed photocurrent. This requires time-of-arrival estimators to be developed and their performances characterized. The statistics of the output of an ideal photodetector, which are well modeled as a Poisson point process, were considered. An analytical model was developed for the mean-square error of the maximum likelihood (ML) estimator, demonstrating two phenomena that cause deviations from the minimum achievable error at low signal power. An approximation was derived to the threshold at which the ML estimator essentially fails to provide better than a random guess of the pulse arrival time. Comparing the analytic model performance predictions to those obtained via simulations, it was verified that the model accurately predicts the ML performance over all regimes considered. There is little prior art that attempts to understand the fundamental limitations to time-of-arrival estimation from Poisson statistics. This work establishes both a simple mathematical description of the error behavior, and the associated physical processes that yield this behavior. Previous work on mean-square error characterization for ML estimators has predominantly focused on additive Gaussian noise. This work demonstrates that the discrete nature of the Poisson noise process leads to a distinctly different error behavior.

Erkmen, Baris I.↗
NASA NTRS1988

Thermodynamic modeling of the no-vent fill methodology for transferring cryogens in low gravity

The filling of tanks with cryogens in the low-gravity environment of space poses many technical challenges. Chief among these is the inability to vent only vapor from the tank as the filling proceeds. As a potential solution to this problem, the NASA Lewis Research Center is researching a technique known as No-Vent Fill. This technology potentially has broad application. The focus is the fueling of space based Orbital Transfer Vehicles. The fundamental thermodynamics of the No-Vent Fill process to develop an analytical model of No-Vent Fill is described. The model is then used to conduct a parametric investigation of the key parameters: initial tank wall temperature, liquid-vapor interface heat transfer rate, liquid inflow rate, and inflowing liquid temperatures. Liquid inflowing temperature and the liquid-vapor interface heat transfer rate seem to be the most significant since they influence the entire fill process. The initial tank wall temperature must be sufficiently low to prevent a rapid pressure rise during the initial liquid flashing stage, but then becomes less significant.

Chato, David J.↗
NASA NTRS2019

A Segmentation Algorithm for Characterizing Rise and Fall Segments in Seasonal Cycles: An Application to XCO2 to Estimate Benchmarks and Assess Model Bias

There is more useful information in the time series of satellite-derived column-averaged carbon dioxide (XCO2) than is typically characterized. Often, the entire time series is treated at once without considering detailed features at shorter timescales, such as nonstationary changes in signal characteristics – amplitude, period and phase. In many instances, signals are visually and analytically differentiable from other portions in a time series. Each rise (increasing) and fall (decreasing) segment in the seasonal cycle is visually discernable in a graph of the time series. The rise and fall segments largely result from seasonal differences in terrestrial ecosystem production, which means that the segment's signal characteristics can be used to establish observational benchmarks because the signal characteristics are driven by similar underlying processes. We developed an analytical segmentation algorithm to characterize the rise and fall segments in XCO2 seasonal cycles. We present the algorithm for general application of the segmentation analysis and emphasize here that the segmentation analysis is more generally applicable to cyclic time series. We demonstrate the utility of the algorithm with specific results related to the comparison between satellite- and model-derived XCO2 seasonal cycles (2009–2012) for large bioregions across the globe. We found a seasonal amplitude gradient of 0.74–0.77 ppm for every 10∘ of latitude in the satellite data, with similar gradients for rise and fall segments. This translates to a south–north seasonal amplitude gradient of 8 ppm for XCO2, about half the gradient in seasonal amplitude based on surface site in situ CO2 data (∼19 ppm). The latitudinal gradients in the period of the satellite-derived seasonal cycles were of opposing sign and magnitude (−9 d per 10∘ latitude for fall segments and 10 d per 10∘ latitude for rise segments) and suggest that a specific latitude (∼2∘ N) exists that defines an inversion point for the period asymmetry. Before (after) the point of asymmetry inversion, the periods of rise segments are lesser (greater) than the periods of fall segments; only a single model could reproduce this emergent pattern. The asymmetry in amplitude and the period between rise and fall segments introduces a novel pattern in seasonal cycle analyses, but, while we show these emergent patterns exist in the data, we are still breaking ground in applying the information for science applications. Maybe the most useful application is that the segmentation analysis allowed us to decompose the model biases into their correlated parts of biases in amplitude, period and phase independently for rise and fall segments. We offer an extended discussion on how such information about model biases and the emergent patterns in satellite-derived seasonal cycles can be used to guide future inquiry and model development.

Calle, Leonardo↗
NASA NTRS2019

A Segmentation Algorithm for Characterizing Rise and Fall Segments in Seasonal Cycles: an Application to Xco2 to Estimate Benchmarks and Assess Model Bias

There is more useful information in the time series of satellite-derived column-averaged carbon dioxide (XCO2) than is typically characterized. Often, the entire time series is treated at once without considering detailed features at shorter timescales, such as nonstationary changes in signal characteristics – amplitude, period and phase. In many instances, signals are visually and analytically differentiable from other portions in a time series. Each rise (increasing) and fall (decreasing) segment in the seasonal cycle is visually discernable in a graph of the time series. The rise and fall segments largely result from seasonal differences in terrestrial ecosystem production, which means that the segment's signal characteristics can be used to establish observational benchmarks because the signal characteristics are driven by similar underlying processes. We developed an analytical segmentation algorithm to characterize the rise and fall segments in XCO2 seasonal cycles. We present the algorithm for general application of the segmentation analysis and emphasize here that the segmentation analysis is more generally applicable to cyclic time series. We demonstrate the utility of the algorithm with specific results related to the comparison between satellite- and model-derived XCO2 seasonal cycles (2009–2012) for large bioregions across the globe. We found a seasonal amplitude gradient of 0.74–0.77 ppm for every 10∘ of latitude in the satellite data, with similar gradients for rise and fall segments. This translates to a south–north seasonal amplitude gradient of 8 ppm for XCO2, about half the gradient in seasonal amplitude based on surface site in situ CO2 data (∼19 ppm). The latitudinal gradients in the period of the satellite-derived seasonal cycles were of opposing sign and magnitude (−9 d per 10∘ latitude for fall segments and 10 d per 10∘ latitude for rise segments) and suggest that a specific latitude (∼2∘ N) exists that defines an inversion point for the period asymmetry. Before (after) the point of asymmetry inversion, the periods of rise segments are lesser (greater) than the periods of fall segments; only a single model could reproduce this emergent pattern. The asymmetry in amplitude and the period between rise and fall segments introduces a novel pattern in seasonal cycle analyses, but, while we show these emergent patterns exist in the data, we are still breaking ground in applying the information for science applications. Maybe the most useful application is that the segmentation analysis allowed us to decompose the model biases into their correlated parts of biases in amplitude, period and phase independently for rise and fall segments. We offer an extended discussion on how such information about model biases and the emergent patterns in satellite-derived seasonal cycles can be used to guide future inquiry and model development.

segmentation algorithm↗
DOE OSTI2020

Overcoming Oxidation State-Dependent Spectral Interferences: Online Monitoring of U(VI) Reduction to U(IV) via Raman and UV–vis Spectroscopy

Analytical characterization of chemical processes is an essential component of both industrial processes and fundamental studies. Applicable techniques abound, but optical spectroscopy has the unique combination of being easily incorporated into on-line (in-situ) monitoring probes and can also provide abundant chemical information (concentration, oxidation state, speciation). However, this abundance of chemical information can make applying optical spectroscopy to complex chemical processes challenging. This is particularly evident in the bulk electrolysis of U(VI) to U(IV), an essential preparatory step in some nuclear fuel recycling schemes. Starting and product materials have interfering spectral signatures in both electronic and vibrational spectroscopies, making accurate and real-time analysis difficult to achieve. In this paper, we discuss the application of optical spectroscopy to the on-line monitoring of a bulk electrolysis process and the methods utilized to analyze data as well as characterize the efficiency and mechanism of U(IV) generation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS2001

Integration Process for Payloads in the Fluids and Combustion Facility

The Fluids and Combustion Facility (FCF) is an ISS research facility located in the United States Laboratory (US Lab), Destiny. The FCF is a multi-discipline facility that performs microgravity research primarily in fluids physics science and combustion science. This facility remains on-orbit and provides accommodations to multi-user and Principal investigator (PI) unique hardware. The FCF is designed to accommodate 15 PI's per year. In order to allow for this number of payloads per year, the FCF has developed an end-to-end analytical and physical integration process. The process includes provision of integration tools, products and interface management throughout the life of the payload. The payload is provided with a single point of contact from the facility and works with that interface from PI selection through post flight processing. The process utilizes electronic tools for creation of interface documents/agreements, storage of payload data and rollup for facility submittals to ISS. Additionally, the process provides integration to and testing with flight-like simulators prior to payload delivery to KSC. These simulators allow the payload to test in the flight configuration and perform final facility interface and science verifications. The process also provides for support to the payload from the FCF through the Payload Safety Review Panel (PSRP). Finally, the process includes support in the development of operational products and the operation of the payload on-orbit.

Free, James M.↗
DOE OSTI2026

An analytic approximation to the covariance between pre- and post-reconstruction galaxy two-point statistics

We present a simple analytic approximation for the covariance between pre-reconstruction galaxy power spectrum measurements and post-reconstruction two-point correlation functions. This cross-covariance is essential for joint analyses that combine full-shape clustering information with baryon acoustic oscillation (BAO) measurements, as commonly performed in modern spectroscopic surveys. Our model builds on the disconnected contribution to the covariance and accounts for the damping of correlations due to the BAO reconstruction process. We validate our analytic prescription against numerical simulations from the Dark Energy Spectroscopic Instrument (DESI), testing both idealized cubic geometries and realistic survey configurations including complex footprints and fiber assignment effects. Despite neglecting survey window functions in the analytic calculation, we find excellent agreement with simulation-based covariances and demonstrate that cosmological parameter constraints are virtually unchanged when using our approximation. Our results show that the pre-post cross-covariance is sufficiently small that even approximate treatments are adequate for cosmological inference, opening a pathway toward fully analytic covariance matrices for next-generation galaxy surveys.

baryon acoustic oscillations↗