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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
NASA NTRS2016

Performance Assessment of Different Pulse Reconstruction Algorithms for the ATHENA X-Ray Integral Field Unit

The X-ray Integral Field Unit (X-IFU) microcalorimeter, on-board Athena, with its focal plane comprising 3840 Transition Edge Sensors (TESs) operating at 90 mK, will provide unprecedented spectral-imaging capability in the 0.2-12 keV energy range. It will rely on the on-board digital processing of current pulses induced by the heat deposited in the TES absorber, as to recover the energy of each individual events. Assessing the capabilities of the pulse reconstruction is required to understand the overall scientific performance of the X-IFU, notably in terms of energy resolution degradation with both increasing energies and count rates. Using synthetic data streams generated by the X-IFU End-to-End simulator, we present here a comprehensive benchmark of various pulse reconstruction techniques, ranging from standard optimal filtering to more advanced algorithms based on noise covariance matrices. Beside deriving the spectral resolution achieved by the different algorithms, a first assessment of the computing power and ground calibration needs is presented. Overall, all methods show similar performances, with the reconstruction based on noise covariance matrices showing the best improvement with respect to the standard optimal filtering technique. Due to prohibitive calibration needs, this method might however not be applicable to the X-IFU and the best compromise currently appears to be the so-called resistance space analysis which also features very promising high count rate capabilities.

microcalorimeters↗
NASA NTRS1977

Multi-attribute subjective evaluations of manual tracking tasks vs. objective performance of the human operator

A computational method to deal with the multidimensional nature of tracking and/or monitoring tasks is developed. Operator centered variables, including the operator's perception of the task, are considered. Matrix ratings are defined based on multidimensional scaling techniques and multivariate analysis. The method consists of two distinct steps: (1) to determine the mathematical space of subjective judgements of a certain individual (or group of evaluators) for a given set of tasks and experimental conditionings; and (2) to relate this space with respect to both the task variables and the objective performance criteria used. Results for a variety of second-order trackings with smoothed noise-driven inputs indicate that: (1) many of the internally perceived task variables form a nonorthogonal set; and (2) the structure of the subjective space varies among groups of individuals according to the degree of familiarity they have with such tasks.

Siapkaras, A.↗
DOE OSTI2019

Development of a Stochastic Infiltration Model for PPA Implementation - 19293

Performance Assessment models often require inputs representing specific hydrologic processes and properties such as infiltration, water content, groundwater flow rate, streamflow, and sediment flux. This paper details the development of a process-level infiltration model and its use in a Probabilistic Performance Assessment (PPA) model for the West Valley Site in western New York. Additionally, this paper demonstrates a method for obtaining distributions of the long-term average hydrologic processes and properties for a PA model. For this PPA, an infiltration model was developed using HELP (Hydrologic Evaluation of Landfill Performance) to evaluate the rates of infiltration, percolation, and drainage through several site soil and proposed decommissioning cover systems, as well as the volumetric water contents of each of the unsaturated layers in a modeled soil column. A particular challenge of probabilistic modeling over long periods of time is scaling parameters appropriately so that outcomes are not grossly over- or underestimated. For these models, distributions of climatic parameters such as average precipitation rate, temperature, wind speed, humidity, and solar radiation were scaled to 1000-year averages and were used to force steady-state models that predict 1000-year average infiltration rates, drainage rates, and water contents. For the HELP model, distributions were developed for the physical and hydrologic properties of each material in a given soil column or cover system, and these properties were allowed to vary stochastically along with climatic inputs. The HELP model was run 5000 times for each of seven different soil and cover systems representing various existing and proposed conditions (i.e. native soil, backfill, existing covers, and a proposed close-in-place cover). The results of the HELP model provide ranges of 1000-year average infiltration rates, drainage rates, and water contents through and within the various layers of each of the different soil and cover conditions. The model outcomes also demonstrate the effectiveness of a proposed close-in-place cover, which essentially eliminates infiltration during its operational lifetime. Following model simulation, a sensitivity analysis was performed to establish the relative importance of each stochastic input with respect to each output. The outcomes of the model simulations and the sensitivity analysis were implemented into a system-level GoldSim model via a novel sensitivity-informed nearest neighbor approach. These infiltration rates, drainage rates, and water contents are used to parameterize mixing cells within the GoldSim Contaminant Transport module, which is the primary system-level model used in the PPA. The infiltration rates are also used as boundary conditions for a stochastic groundwater flow model that is also utilized in the PPA, but not discussed in this paper. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2024

Defining Detection Limits for Continuous Monitoring Systems for Methane Emissions at Oil and Gas Facilities

Networks of fixed-point continuous monitoring systems are becoming widely used in the detection and quantification of methane emissions from oil and gas facilities in the United States. Regulatory agencies and operators are developing performance metrics for these systems, such as minimum detection limits. Performance characteristics, such as minimum detection limits, would ideally be expressed in emission rate units; however, performance parameters such as detection limits for a continuous monitoring system (CMS) will depend on meteorological conditions, the characteristics of emissions at the site where the CMS is deployed, the positioning of CMS devices in relation to the emission sources, and the amount of time allowed for the CMS to detect an emission source. This means that certifying the performance of a CMS will require test protocols with well-defined emission rates and durations; initial protocols are now being used in field tests. Field testing results will vary, however, depending on meteorological conditions and the time allowed for detection. This work demonstrates methods for evaluating CMS performance characteristics using dispersion modeling and defines an approach for normalizing test results to standard meteorological conditions using dispersion modeling.

Chen, Qining (ORCID:0000000316908091)↗
DOE OSTI2025

An Internal Digital Image Correlation Technique for High-Strain Rate Dynamic Experiments

Full-field, quantitative visualization techniques, such as digital image correlation (DIC), have unlocked vast opportunities for experimental mechanics. However, DIC has traditionally been a surface measurement technique, and has not been extended to perform measurements on the interior of specimens for dynamic, full-scale laboratory experiments. This limitation restricts the scope of physics which can be investigated through DIC measurements, especially in the context of heterogeneous materials. The focus of this study is to develop a method for performing internal DIC measurements in dynamic experiments. The aim is to demonstrate its feasibility and accuracy across a range of stresses (up to 650 MPa), strain rates (10 3 - 10 6 s -1 ), and high-strain rate loading conditions (e.g., ramped and shock wave loading). Internal DIC is developed based on the concept of applying a speckle pattern at an inner-plane of a transparent specimen. The high-speed imaging configuration is coupled to the traditional dynamic experimental setups, and is focused on the internal speckle pattern. During the experiment, while the sample deforms dynamically, in-plane, two-dimensional deformations are measured via correlation of the internal speckle pattern. In this study, the viability and accuracy of the internal DIC technique is demonstrated for split-Hopkinson (Kolsky) pressure bar (SHPB) and plate impact experiments. The internal DIC experimental technique is successfully demonstrated in both the SHPB and plate impact experiments. In the SHPB setting, the accuracy of the technique is excellent throughout the deformation regime, with measurement noise of approximately 0.2% strain. In the case of plate impact experiments, the technique performs well, with error and measurement noise of 1% strain. The internal DIC technique has been developed and demonstrated to work well for full-scale dynamic high-strain rate and shock laboratory experiments, and the accuracy is quantified. Here, the technique can aid in investigating the physics and mechanics of the dynamic behavior of materials, including local deformation fields around dynamically loaded material heterogeneities.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Assessing liver function: diagnostic efficacy of parenchymal enhancement and liver volume ratio of Gd-EOB-DTPA-enhanced MRI study during interstitial and hepatobiliary phase

Aim: To assess the efficacy of signal intensity in interstitial and hepatobiliary phase normalized for liver volume, on gadolinium-ethoxybenzyl-diethylenetriaminepentaacetic acid (Gd-EOB-DTPA)-enhanced magnetic resonance imaging (MRI) study, for the evaluation of liver function through the comparison with Child–Pugh (CP), model for end-stage liver disease (MELD), and biochemical tests. Methods: All dynamic Gd-EOB-DTPA MRI studies performed in patients with suspected liver lesions were retrospectively reviewed. The rate of liver-to-muscle ratio on T1 sequence 70 s (interstitial phase) and 20 min (hepatobiliary phase) after injection of Gd-EOB-DTPA was calculated for each MRI study and then normalized for liver volume (irINTnorm and irHEPnorm). Pearson correlation coefficient was computed to assess the correlation among these values and CP and MELD scores, and biochemical tests. Results: A total of 303 MRI studies, performed on 221 patients, were included. Mean age was 63.8 years ± 12.9 with a majority of male patients (186; 61.4%). A total of 186 out of 303 (61.4%) were cirrhotic patients. The irHEPnorm was significantly lower in cirrhotic than non-cirrhotic patients (0.0004 ± 0.0002 to 0.0005 ± 0.0003, p = 0.010). This value had a moderate, significant correlation with Child–Pugh and MELD scores (R = − 0.292, p < 0.0001 and R = − 0.192, p = 0.010, respectively). In particular, irHEPnorm progressively decreased from Child–Pugh A to C (0.0004–0.0002, p < 0.0001) and from MELD ≤ 10 to 19–24 (0.0004–0.0003, p = 0.018). Among biochemical parameters, total bilirubin, GOT, and albumin had the strongest correlation with irHEPnorm (R = − 0.258, − 0.291, and 0.262, p < 0.0001, respectively). No correlations were found between irINTnorm and CP and MELD scores. Conclusion: irHEPnorm value derived from Gd-EOB-DTPA-enhanced MRI is a reliable, non-invasive, useful tool to quantify liver function and to assess the degree of cirrhosis, offering a strict relationship with clinical scores and biochemical parameters. This could help surgeons in clinical decision-making, allowing them to choose the more suitable surgical approach for cirrhotic patients.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2024

CMPLE: Correlation Modeling to Decode Photosynthesis Using the Minorize–Maximize Algorithm

In plant genomic experiments, correlations among various biological traits (phenotypes) give new insights into how genetic diversity may have tuned biological processes to enhance fitness under diverse conditions. Consequently, knowing how the correlations are affected by genetic (G) and environmental (E) factors helps develop climate-resilient plants. However, the current literature lacks any method for assessing the effect of predictors on pairwise correlations among multiple phenotypes together with easily interpretable model parameters. To address this need, we propose to model pairwise correlations directly in terms of G and E and develop a computationally efficient inference procedure. Two major novelties in our methodology are (1) the use of a composite pairwise likelihood method to avoid the positive definiteness restriction on the correlation matrix and (2) the use of a novel Minorize–Maximize (MM) algorithm for the efficient estimation of a large number of parameters. The proposed method shows excellent numerical performance on synthetic datasets. Here, the analysis of the motivating data on cowpea reveals that the rates of solar energy storage by photosynthesis (the aggregate trait) are differentially affected by different genetic loci through two distinct processes: “photoinhibition” which results from photodamage caused by excess light, and “photoprotection” which protects plants from photodamage but also results in energy loss.

Correlation modeling↗
DOE OSTI2025

Near-zero photon bioimaging by fusing deep learning and ultralow-light microscopy

Enhancing the reliability and reproducibility of optical microscopy by reducing specimen irradiance continues to be an important biotechnology target. As irradiance levels are reduced, however, the particle nature of light is heightened, giving rise to Poisson noise, or photon sparsity that restricts only a few (0.5%) image pixels to comprise a photon. Photon sparsity can be addressed by collecting approximately 200 photons per pixel; this, however, requires long acquisitions and, as such, suboptimal imaging rates. Here, we introduce near-zero photon bioimaging, a method that operates at kHz rates and 10,000-fold lower irradiance than standard microscopy. To achieve this level of performance, we uniquely combined a judiciously designed epifluorescence microscope enabling ultralow background levels and AI that learns to reconstruct biological images from as low as 0.01 photons per pixel. We demonstrate that near-zero photon bioimaging captures the structure of multicellular and subcellular features with high fidelity, including features represented by nearly zero photons. Beyond optical microscopy, the near-zero photon bioimaging paradigm can be applied in remote sensing, covert applications, and biomedical imaging that utilize damaging or quantum light.

AI↗
DOE OSTI2023

Anomalous cross-field transport in a Hall thruster inferred from direct measurement of instability growth rates

The contribution of the electron drift instability to anomalous electron transport is experimentally assessed in a Hall effect discharge. The transport is represented by an anomalous collision frequency, which is related through quasilinear theory to the energy and growth rate of the instability. The wave energy is measured directly with ion saturation probes, while estimates of the growth rate are employed based on both linearized theory and direct measurement. The latter measurement is performed with a bispectral analysis method. The wave-driven collision frequency is compared to measurements of the actual collision frequency inferred from a method based on laser- induced fluorescence. It is found that estimates for transport using linearized theory for the growth differ by over an order of magnitude from the actual anomalous collision frequency in the plasma. The wave-driven anomalous collision frequency with measured growth, however, is shown to agree with the electron collision frequency in magnitude and capture aspects of the trends in spatial variation. This result demonstrates experimentally that wave-driven effects ultimately can explain the observed cross-field transport in these devices. As a result, the implications of this finding are discussed in the context of the key lengthscales that drive the transport as well as the implications identifying reduced fidelity models that could be used to predict anomalous collision frequency.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Upcycling Polyethylene Waste to Advanced Carbon Materials for Energy Storage Applications

Polyethylene is notoriously difficult to upcycle because it decomposes into light gases at approximately 350-400 °C which prevents processing it at higher temperatures to convert it into high-value carbon materials, such as graphene or graphite. We address this challenge by using an air-based, thermo-oxidation process, which heats polyethylene (PE) just below the decomposition point to initiate oxidation and cross-linking of PE alkyl chains. These molecular transformations allow PE to be further graphenized or graphitized at higher temperatures without decomposing. The PE-derived graphene has a specific surface area up to 1,800 m 2/g and Raman ID/IG ratio of 0.85, which enables it to be used as an electrode material for a symmetric supercapacitor with the 1 M H2SO4 electrolyte. The PE-derived graphene material has a comparable electrochemical capacitive performance, such as power density, specific capacitance, and long cycle stability, to the commercial state of art porous carbon electrode. The stabilized PE could also be converted into highly crystalline flake graphite via low-temperature catalytic graphitization. The PE-derived graphite is used for the lithium-ion battery anode, which showed comparable electrochemical battery performance, such as reversible rate performance and long-term cyclic stability, to the current use battery-grade graphite, thus providing a scalable method to upcycle PE plastic waste into high-value carbon material.

Gao, Yuan↗
NASA NTRS1978

Calculated rate constants for the reaction ClO + O yields Cl + O2 between 220 and 1000 deg K

Classical trajectory calculations are presented for the reaction ClO + O yields Cl + O2, a reaction which is an important step in the chlorine-catalyzed destruction of ozone which is thought to occur in the 220 and 1000 K. The calculated rate constant is 4.36 x 10 to the minus 11th power exp (-191/T)cu cm molecule (-1)s(-1) and its value at 300 K is 2.3 plus or minus 10 to the 11th power cu cm molecule (-1)s(-1), about a factor of 2 lower than recent experimental data. The empirical potential energy surface used in the calculations was constructed to fit experimental data for ClO, O2 and ClOO molecules. Other important features of this potential surface, such as the barrier to reaction, were varied systematically and calculations were performed for a range of conditions to determine the best theoretical rate constants. Results demonstrate the utility of classical trajectory methods for determining activation energies and other kinetic data for important atmospheric reactions.

Jaffee, R. L.↗
NASA NTRS1980

Estimation procedures to measure and monitor failure rates of components during thermal-vacuum testing

Estimation procedures are described for measuring component failure rates, for comparing the failure rates of two different groups of components, and for formulating confidence intervals for testing hypotheses (based on failure rates) that the two groups perform similarly or differently. Appendix A contains an example of an analysis in which these methods are applied to investigate the characteristics of two groups of spacecraft components. The estimation procedures are adaptable to system level testing and to monitoring failure characteristics in orbit.

Williams, R. E.↗
NASA NTRS1983

Integrated pilot - Optimal augmentation synthesis for complex flight vehicles: Experimental validation

The purpose of this work is to present an experimental validation via fixed-base simulation of analytical methods for predicting handling qualities of flight vehicles. Different augmented dynamics are considered and analytical predictions of performance and pilot rating obtained. A flight simulation is then performed and comparison between experiment and theoretical data is shown.

Innocenti, M.↗
NASA NTRS1987

Relaxation schemes for spectral multigrid methods

The effectiveness of relaxation schemes for solving the systems of algebraic equations which arise from spectral discretizations of elliptic equations is examined. Iterative methods are an attractive alternative to direct methods because Fourier transform techniques enable the discrete matrix-vector products to be computed almost as efficiently as for corresponding but sparse finite difference discretizations. Preconditioning is found to be essential for acceptable rates of convergence. Preconditioners based on second-order finite difference methods are used. A comparison is made of the performance of different relaxation methods on model problems with a variety of conditions specified around the boundary. The investigations show that iterations based on incomplete LU decompositions provide the most efficient methods for solving these algebraic systems.

Phillips, Timothy N.↗
NASA NTRS1994

QPPM receiver for free-space laser communications

A prototype receiver developed at NASA Lewis Research Center for direct detection and demodulation of quaternary pulse position modulated (QPPM) optical carriers is described. The receiver enables dual-channel communications at 325-Megabits per second (Mbps) per channel. The optical components of the prototype receiver are briefly described. The electronic components, comprising the analog signal conditioning, slot clock recovery, matched filter and maximum likelihood data recovery circuits are described in more detail. A novel digital symbol clock recovery technique is presented as an alternative to conventional analog methods. Simulated link degradations including noise and pointing-error induced amplitude variations are applied. The bit-error-rate performance of the electronic portion of the prototype receiver under varying optical signal-to-noise power ratios is found to be within 1.5-dB of theory. Implementation of the receiver as a hybrid of analog and digital application specific integrated circuits is planned.

Budinger, J. M.↗
NASA NTRS2000

Comparison of sympathetic nerve responses to neck and forearm isometric exercise

PURPOSE: Although the autonomic and cardiovascular responses to arm and leg exercise have been studied, the sympathetic adjustments to exercise of the neck have not. The purpose of the present study was twofold: 1) to determine sympathetic and cardiovascular responses to isometric contractions of the neck extensors and 2) to compare sympathetic and cardiovascular responses to isometric exercise of the neck and forearm. METHODS: Muscle sympathetic nerve activity (MSNA), mean arterial pressure (MAP), and heart rate were measured in nine healthy subjects while performing isometric neck extension (INE) and isometric handgrip (IHG) in the prone position. After a 3-min baseline period, subjects performed three intensities of INE for 2.5 min each: 1) unloaded (supporting head alone), 2) 10% maximal voluntary contraction (MVC), and 3) 30% MVC, then subjects performed two intensities (10% and 30% MVC) of IHG for 2.5 min. RESULTS: Supporting the head by itself did not significantly change any of the variables. During [NE, MAP significantly increased by 10 +/- 2 and 31 +/- 4 mm Hg and MSNA increased by 67 +/- 46 and 168 +/- 36 units/30 s for 10% and 30% MVC, respectively. IHG and INE evoked similar responses at 10% MVC, but IHG elicited higher peak MAP and MSNA at 30% MVC (37 +/- 7 mm Hg (P < 0.05) and 300 +/- 48 units/30 s (P < 0.01) for IHG, respectively). CONCLUSIONS: The data indicate that INE can elicit marked increases in MSNA and cardiovascular responses but that it evokes lower peak responses as compared to IHG. We speculate that possible differences in muscle fiber type composition, muscle mass, and/or muscle architecture of the neck and forearm are responsible for these differences in peak responses.

NASA Discipline Neuroscience↗
NASA NTRS2011

Collaborative Clustering for Sensor Networks

Traditionally, nodes in a sensor network simply collect data and then pass it on to a centralized node that archives, distributes, and possibly analyzes the data. However, analysis at the individual nodes could enable faster detection of anomalies or other interesting events, as well as faster responses such as sending out alerts or increasing the data collection rate. There is an additional opportunity for increased performance if individual nodes can communicate directly with their neighbors. Previously, a method was developed by which machine learning classification algorithms could collaborate to achieve high performance autonomously (without requiring human intervention). This method worked for supervised learning algorithms, in which labeled data is used to train models. The learners collaborated by exchanging labels describing the data. The new advance enables clustering algorithms, which do not use labeled data, to also collaborate. This is achieved by defining a new language for collaboration that uses pair-wise constraints to encode useful information for other learners. These constraints specify that two items must, or cannot, be placed into the same cluster. Previous work has shown that clustering with these constraints (in isolation) already improves performance. In the problem formulation, each learner resides at a different node in the sensor network and makes observations (collects data) independently of the other learners. Each learner clusters its data and then selects a pair of items about which it is uncertain and uses them to query its neighbors. The resulting feedback (a must and cannot constraint from each neighbor) is combined by the learner into a consensus constraint, and it then reclusters its data while incorporating the new constraint. A strategy was also proposed for cleaning the resulting constraint sets, which may contain conflicting constraints; this improves performance significantly. This approach has been applied to collaborative clustering of seismic and infrasonic data collected by the Mount Erebus Volcano Observatory in Antarctica. Previous approaches to distributed clustering cannot readily be applied in a sensor network setting, because they assume that each node has the same view of the data set. A view is the set of features used to represent each object. When a single data set is partitioned across several computational nodes, distributed clustering works; all objects have the same view. But when the data is collected from different locations, using different sensors, a more flexible approach is needed. This approach instead operates in situations where the data collected at each node has a different view (e.g., seismic vs. infrasonic sensors), but they observe the same events. This enables them to exchange information about the likely cluster membership relations between objects, even if they do not use the same features to represent the objects.

Wagstaff. Loro :/↗