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Results for “information measures”

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At least 127 records · Page 7

All sources NASA NTRS DOE OSTI

NASA NTRS2004

DSMC Simulations of Hypersonic Flows With Shock Interactions and Validation With Experiments

The capabilities of a relatively new direct simulation Monte Carlo (DSMC) code are examined for the problem of hypersonic laminar shock/shock and shock/boundary layer interactions, where boundary layer separation is an important feature of the flow. Flow about two model configurations is considered, where both configurations (a biconic and a hollow cylinder-flare) have recent published experimental measurements. The computations are made by using the DS2V code of Bird, a general two-dimensional/axisymmetric time accurate code that incorporates many of the advances in DSMC over the past decade. The current focus is on flows produced in ground-based facilities at Mach 12 and 16 test conditions with nitrogen as the test gas and the test models at zero incidence. Results presented highlight the sensitivity of the calculations to grid resolution, sensitivity to physical modeling parameters, and comparison with experimental measurements. Information is provided concerning the flow structure and surface results for the extent of separation, heating, pressure, and skin friction.

Moss, James N.↗

NASA NTRS2004

DSMC Simulations of Hypersonic Flows With Shock Interactions and Validation With Experiments

The capabilities of a relatively new direct simulation Monte Carlo (DSMC) code are examined for the problem of hypersonic laminar shock/shock and shock/boundary layer interactions, where boundary layer separation is an important feature of the flow. Flow about two model configurations is considered, where both configurations (a biconic and a hollow cylinder-flare) have recent published experimental measurements. The computations are made by using the DS2V code of Bird, a general two-dimensional/axisymmetric time accurate code that incorporates many of the advances in DSMC over the past decade. The current focus is on flows produced in ground-based facilities at Mach 12 and 16 test conditions with nitrogen as the test gas and the test models at zero incidence. Results presented highlight the sensitivity of the calculations to grid resolutions, sensitivity to physical modeling parameters, and comparison with experimental measurements. Information is provided concerning the flow structure and surface results for the extent of separation, heating, pressure, and skin friction.

Moss, James N.↗

NASA NTRS2001

Optimal firing rate estimation

We define a measure for evaluating the quality of a predictive model of the behavior of a spiking neuron. This measure, information gain per spike (Is), indicates how much more information is provided by the model than if the prediction were made by specifying the neuron's average firing rate over the same time period. We apply a maximum Is criterion to optimize the performance of Gaussian smoothing filters for estimating neural firing rates. With data from bullfrog vestibular semicircular canal neurons and data from simulated integrate-and-fire neurons, the optimal bandwidth for firing rate estimation is typically similar to the average firing rate. Precise timing and average rate models are limiting cases that perform poorly. We estimate that bullfrog semicircular canal sensory neurons transmit in the order of 1 bit of stimulus-related information per spike.

NASA Discipline Neuroscience↗

NASA NTRS1994

Weld analysis and control system

The invention is a Weld Analysis and Control System developed for active weld system control through real time weld data acquisition. Closed-loop control is based on analysis of weld system parameters and weld geometry. The system is adapted for use with automated welding apparatus having a weld controller which is capable of active electronic control of all aspects of a welding operation. Enhanced graphics and data displays are provided for post-weld analysis. The system provides parameter acquisition, including seam location which is acquired for active torch cross-seam positioning. Torch stand-off is also monitored for control. Weld bead and parent surface geometrical parameters are acquired as an indication of weld quality. These parameters include mismatch, peaking, undercut, underfill, crown height, weld width, puddle diameter, and other measurable information about the weld puddle regions, such as puddle symmetry, etc. These parameters provide a basis for active control as well as post-weld quality analysis and verification. Weld system parameters, such as voltage, current and wire feed rate, are also monitored and archived for correlation with quality parameters.

Kennedy, Larry Z.↗

NASA NTRS2010

Cytogenetic Biodosimetry Using the Blood Lymphocytes of Astronauts

Cytogenetic analysis of blood lymphocytes remains the most sensitive and reliable method available for in vivo assessment of the biological effects of exposure to radiation and provides the most informative measurement of radiation induced health risks. To date chromosome damage has been assessed in lymphocytes from more than 30 astronauts before and after they participated in long-duration space missions of three months or more on board the International Space Station. For all individuals, the frequency of chromosome damage measured within a month of return from space was higher than their prefight yield and biodosimetry estimates lie within the range expected from physical dosimetry. Biodosimetry data provides a direct measurement of space radiation damage, which takes into account individual radiosensitivity in the presence of confounding factors such as microgravity and other stress conditions. In contrast to physical measurements, which are external to body and require multiple devices to detect all radiation types all of which have poor sensitivity to neutrons, biodosimetry is internal and includes the effects of shielding provided by the body itself plus chromosome damage shows excellent sensitivity to protons, heavy ions, and neutrons. In addition, chromosome damage is reflective of cancer risk and biodosimetry values can therefore be used to validate and develop risk assessment models that can be used to characterize excess health risk incurred by crewmembers. A review of astronaut biodosimetry data will be presented along with recent findings on the persistence of space radiation induced chromosome damage and the cytogenetic effects of repeat long duration missions

George, Kerry↗

NASA NTRS2018

Further Examinations of Bimodal SLD Ice Accretion in the NASA Icing Research Tunnel

An ice shape database has been created to document ice accretions on a 72-inch chord NACA 23012 airfoil model resulting from an exposure to a Supercooled Large Drop (SLD) icing cloud with a bimodal drop size distribution. The ice shapes created were documented with photographs, laser scanned surface measurements over a section of the model span, and measurement of the ice mass over the same section of each accretion. The icing conditions used in the test matrix were based upon previously measured ice shapes on the same model to connect the current database to previously measured information. Ice shapes resulting from the bimodal distribution as well as from equivalent mono-modal drop size distributions were obtained and compared. Results indicate that the ice shapes resulting from the bimodal drop size distributions had higher mass and volume values than their mono-modal distribution equivalents as well as having icing limits that extended further back on the chord of the model.

Aircraft↗

NASA NTRS2017

Bimodal SLD Ice Accretion on a NACA 0012 Airfoil Model

An initial ice shape database has been created to document ice accretions on a 21-inch chord NACA 0012 airfoil model resulting from an exposure to a Supercooled Large Droplet (SLD) icing cloud with a bimodal droplet distribution. The ice shapes created were documented with photographs, laser scanned surface measurements over a section of the model span, and measurement of the ice mass over the same section of each accretion. The icing conditions used in the test matrix were based upon previously measured ice shapes on the same model to connect the current database to previously measured information. Ice shapes resulting from the bimodal distribution as well as from equivalent standard droplet distributions were obtained and compared. Results indicate that the ice shapes resulting from the bimodal droplet distributions had higher mass and volume values than their standard distribution equivalents as well as having icing limits that extended further back on the chord of the model.

aircraft icing↗

NASA NTRSDate not supplied

Algorithmic Detection of Elemental Biosignatures

Machine learning models that classify a sample as indicative or non-indicative of life could play an important role in life-detection missions. Their predictions result from agnostic algorithms and thereby add redundancy to judgements resulting from human expertise. Additionally, their important features can reveal the most informative measurements within the operational constraints of a life-detection mission. The Ladder of Life Detection (Neveu 2018) identifies the need for an understanding of how combinations of multiple biosignatures affect overall confidence. The present work provides a starting point to answer this need, and future work will expand the data types to obtain even more predictive combinations of features. Elemental abundance was chosen as a starting set of features due to its availability in diverse sample types, which are needed to train a generalizable model. A standardized dataset was collected, including 35 non-indicative, e.g., lunar rock, basalt; 19 indicative mixed, e.g., seawater, agricultural soil; 46 indicative non-alive, e.g., coal, chalk; and 10 indicative alive, e.g., biofilm, bacteria. This dataset could be valuable for complementary biosignature research. The samples were standardized to the same limit of detection of a simulated mission scenario. Four classification models were used: k-nearest neighbors (KNN), logistic regression (LR), linear support vector machines (SVM), and Gaussian naïve Bayes (GNB). To obtain feature importances, KNN was run on three principal components of the training data and LR and SVM were run with L1 and L2 regularization. The performances and feature importances of the six model variants on 40:60 train to validation ratios were assessed with Monte Carlo simulations. ROC AUC and mean accuracy scores ranged between 82% - 94%, with sensitivity greater than specificity. For indicative of life predictors, all models had C and Ca as strong and Cl as medium; a majority of models had N, K, and P as medium. For non-indicative of life predictors, all models had Si as strong, and a majority of models had Mg, Al, and Ti as medium. Varied elements were Fe (slightly non-indicative), H (slightly indicative), O (widely varied), Na, Mn, and S. These results serve as a proof of concept and suggest important elemental signals beyond merely the CHNOPS of Earth-based life.

Algorithmic↗

NASA NTRSDate not supplied

PyroCbs from Australia Fires and its Impact Using Satellite Observations from CrIS and TROPOMI and Reanalysis Data

Pyrocumulonimbus (pyroCb) clouds are thunder clouds created by intense heat from the Earth’s surface. They are formed similarly to cumulonimbus clouds, but the intense heat that results in the vigorous updraft comes from fire, either large wildfires or volcanic eruptions. Australia’s unprecedented fire disasters at the end of 2019 to early 2020 emitted huge amounts of carbon monoxide (CO) and fire aerosol particles to the atmosphere, particularly during the pyroCb outbreak that occurred in southeast Australia between 29 December 2019 and 4 January 2020. It was estimated that at least 18 pyroCbs were generated during this episode, and some of them injected ice, smoke, and biomass burning gases above the local tropopause. An unprecedented abundance of H2O and CO in the stratosphere, and the displacement of background ozone (O3) and N2O from rapid ascent of air from the troposphere and lower stratosphere were found from satellite observations. Some other studies also found that the fire emissions and their long-range transport resulted in stratospheric aerosol, temperature, and O3 anomalies after the 2020 Australian bushfires and altered the Antarctic ozone and vortex, posing great impact to local air quality and climate change. Further study on the atmospheric thermodynamic status of atmosphere associated with these pyroCbs, and the change of the cloud properties and trace gases during this unprecedented Australia fires will be made using a new single Field of View (SFOV) Sounder Atmospheric Products (SiFSAP). SiFSAP was developed by NASA using the Cross-track Infrared Sounder (CrIS) and Advanced Technology Microwave Sounder (ATMS) onboard SNPP and JPSS-1, and will soon be available to the public at NASA DAAC. Since this product has a spatial resolution of 15 km at nadir, which is better than most global weather and climate models and other current operational sounding products, a process-oriented analysis of the dynamic transport of CO and fire plumes during this unprecedented fire disasters will be made in this study. Based on a Principal Component Radiative Transfer Model (PCRTM) and an optimized estimation retrieval algorithm, a simultaneously retrieval is made using the whole spectral information measured by CrIS, and the derived SiFSAP include temperature, water vapor, trace gases (such as O3, CO2, CO, CH4 and N2O), cloud properties and surface properties. Use of ATMS together with CrIS allows SiFSAP to get accurate retrieval products under thick pyroCb conditions, and an algorithm to detect pyroCb based on the hyperspectral infrared sounder spectrum from CrIS will be developed and verified. In addition to SiFSAP sounding products, other products like CO, O3, NO2 from TROPOMI, O3 from OMPS will be used for retrospective analysis. The wind fields from the NASA’s Modern-Era Retrospective Analysis for Research and Applications Version-2 (MERRA-2) and ERA5 will be used to characterize the transport, and the SiFSAP temperature and water vapor profiles within and around pyroCbs will be compared with MERRA-2 and ERA5 products.

Xiaozhen (Shawn) Xiong↗

NASA NTRSDate not supplied

Hyperspectral Sounder Spectral Fingerprinting: Using Machine Learning Techniques to Enhance Model-Based Physical Inversion

Different retrieval algorithms have been developed to process top-of-atmosphere (TOA) spectral radiance data provided by hyperspectral infrared sounder missions. Those algorithms are either optimal estimation method (OEM) based schemes with radiative transfer calculation involved in the retrieval process, or machine learning based methods that allow ultra-efficient data procession but lack of radiometric consistency validation based on the directly measured information. Combining both approaches leverages their respective technical advantages, leading to more accurate results. This study introduces a hyperspectral sounder fingerprinting algorithm to explore this hybrid approach. This approach involves the use of a spectral information-based classification method to identify an reference geophysical state and the corresponding radiative kernel. This enables the efficient retrieval of geophysical variables of interest through a radiative kernel-based linear inversion procedure. The fingerprinting method has been applied to analyze a decade-long hyperspectral sounder data record.

Wan Wu↗

NASA NTRS2024

Sonic Boom Analyses in Support of Improved X-59 Community Noise Testing

informing measurement planning and analysis of quiet supersonic aircraft community testing. The report is divided into three main sections: (1) investigations on the impacts of contaminating noise on sonic boom community noise metrics; (2) investigations into sonic boom variability, including turbulence effects on metrics of interest and development of a data-driven boom variability analysis framework; (3) other studies that support developing improved methodologies for community testing and analysis.

community noise↗

NASA NTRS2024

Harnessing Collaborative Learning Automata to Guide Multi-objective Optimization based Inverse Analysis for Structural Damage Identification

Structural damage identification based on physical models is often transformed into an optimization problem that minimizes the difference between measurement information of structure being monitored and the model prediction in the parametric space. However, the objective function in this context often exhibits multimodality, involving high-dimensional variables due to the reliance on finite element models for damage identification. These features pose challenges to optimization algorithms, where entrapment in local solutions can lead to false positives and false negatives in damage identification. In this research, we propose a reinforcement learning based multi-swarm optimizer to tackle such challenges in pursuit of a small yet diverse solution set that can capture the true damage scenario as one of the solutions. The proposed method leverages the flexibility of the particle swarm optimizer and incorporates novel strategies of metaheuristics to realize targeted improvement. To enable the particle swarm to adaptively select the appropriate search strategy based on the current environment, we adopt the learning automata technique, which sidesteps the need for reward strategy selection that is usually ad hoc at each step of the search. The integration harnesses the automatic learning and self-adaptation capabilities of learning automata, enabling the particles to navigate based on environmental signals. This leads to accumulated probabilities tied to advantageous movements, fostering an adaptive exploration of particles in the search space. The proposed approach is first validated through implementing into benchmark test cases with comparisons. It is then applied to structural damage identification with piezoelectric admittance experimental signals. `The results highlight the capability of the algorithm to identify a small solution set with high accuracy to match the actual damage scenario.

Yang Zhang↗

DOE OSTI2021

A Robust Approach to Sequential Information Theoretic Planning

In many sequential planning applications a natural approach to generating high quality plans is to maximize an information reward such as mutual information (MI). Unfortunately, MI lacks a closed form in all but trivial models, and so must be estimated. In applications where the cost of plan execution is expensive, one desires planning estimates which admit theoretical guarantees. Through the use of robust M-estimators we obtain bounds on absolute deviation of estimated MI. Moreover, we propose a sequential algorithm which integrates inference and planning by maximally reusing particles in each stage. We validate the utility of using robust estimators in the sequential approach on a Gaussian Markov Random Field wherein information measures have a closed form. Lastly, we demonstrate the benefits of our integrated approach in the context of sequential experiment design for inferring causal regulatory networks from gene expression levels. Here, our method shows improvements over a recent method which selects intervention experiments based on the same MI objective.

Zheng, Sue↗

DOE OSTI2021

Preventing stent failure using adaptive shear responsive endovascular implant

A stent apparatus, system, and method that senses wall shear stress by measuring fluid flow at localized areas within the stent, that processes measured information through an integrated circuit, and selectively sends power to mechanically controllable stent surfaces which results in localized geometric changes. In various embodiments the stent apparatus, system, and method sends data to outside the body in real time.

Mukerjee, Erik V.↗

DOE OSTI2024

Preventing stent failure using adaptive shear responsive endovascular implant

Mukerjee, Erik V.↗

DOE OSTI2023

Stable isotopes contain substantial additive information about terrestrial carbon and water cycling

Abstract Stable isotope ratios of H ( δ 2 H ), O ( δ 18 O), and C ( δ 13 C) are linked to key biogeochemical processes of the water and carbon cycles; however, the degree to which isotope-associated processes are reflected in macroscale ecosystem flux observations remains unquantified. Here through formal information assessment, new measurements of δ 13 C of net ecosystem exchange ( NEE ) as well as δ 2 H and δ 18 O of latent heat ( LH ) fluxes across the United States National Ecological Observation Network (NEON) are used to determine conditions under which isotope measurements are informative of environmental exchanges. We find all three isotopic datasets individually contain comparable amounts of information about NEE and LH fluxes as wind speed observations. Such information from isotope measurements, however, is largely unique. Generally, δ 13 C provides more information about LH as aridity increases or mean annual precipitation decreases. δ 2 H provides more information about LH as temperatures or mean annual precipitation decreases, and also provides more information about NEE as temperatures decrease. Overall, we show that the stable isotope datasets collected by NEON contribute non-trivial amounts of new information about bulk environmental fluxes useful for interpreting biogeochemical and ecohydrological processes at landscape scales. However, the utility of this new information varies with environmental conditions at continental scales. This study provides an approach for quantifying the value adding non-traditional sensing approaches to environmental monitoring sites and the patterns identified here are expected to aid in modeling and data interpretation efforts focused on constraining carbon and water cycles’ mechanisms.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS2000

"Cloud Slicing" : A New Technique to Derive Tropospheric Ozone Profile Information from Satellite Measurements

A new technique denoted cloud slicing has been developed for estimating tropospheric ozone profile information. All previous methods using satellite data were only capable of estimating the total column of ozone in the troposphere. Cloud slicing takes advantage of the opaque property of water vapor clouds to ultraviolet wavelength radiation. Measurements of above-cloud column ozone from the Nimbus 7 total ozone mapping spectrometer (TOMS) instrument are combined together with Nimbus 7 temperature humidity and infrared radiometer (THIR) cloud-top pressure data to derive ozone column amounts in the upper troposphere. In this study tropical TOMS and THIR data for the period 1979-1984 are analyzed. By combining total tropospheric column ozone (denoted TCO) measurements from the convective cloud differential (CCD) method with 100-400 hPa upper tropospheric column ozone amounts from cloud slicing, it is possible to estimate 400-1000 hPa lower tropospheric column ozone and evaluate its spatial and temporal variability. Results for both the upper and lower tropical troposphere show a year-round zonal wavenumber 1 pattern in column ozone with largest amounts in the Atlantic region (up to approx. 15 DU in the 100-400 hPa pressure band and approx. 25-30 DU in the 400-1000 hPa pressure band). Upper tropospheric ozone derived from cloud slicing shows maximum column amounts in the Atlantic region in the June-August and September-November seasons which is similar to the seasonal variability of CCD derived TCO in the region. For the lower troposphere, largest column amounts occur in the September-November season over Brazil in South America and also southern Africa. Localized increases in the tropics in lower tropospheric ozone are found over the northern region of South America around August and off the west coast of equatorial Africa in the March-May season. Time series analysis for several regions in South America and Africa show an anomalous increase in ozone in the lower troposphere around the month of March which is not observed in the upper troposphere. The eastern Pacific indicates weak seasonal variability of upper, lower, and total tropospheric ozone compared to the western Pacific which shows largest TCO amounts in both hemispheres around spring months. Ozone variability in the western Pacific is expected to have greater variability caused by strong convection, pollution and biomass burning, land/sea contrast and monsoon developments.

Ziemke, J. R.↗

NASA NTRS1994

Constraints on Neural Mechanisms Underlying the Spatial Integration of Speed Information

We measured human ability to integrate speed information presented simultaneously at multiple locations in the visual field. Observers did a two-interval forced-choice speed discrimination task with n grating patches in each interval at 4' eccentricity from fixation. In the first (integration) paradigm, all gratings in each interval moved at the same speed and observers were asked to pick the interval containing the faster gratings. Speed discrimination improved as the number of gratings in each interval increased. The observed decrease in threshold is not due simply to an increase in the effective area because performance with a single grating two, four, or six times the area of the original grating showed no such improvement. Furthermore, the improvement with n was still observed even when the speeds of the individual gratings in each interval were independent samples from a Gaussian distribution and the grating directions were balanced (i.e. equal numbers of gratings moved to the left and right). These results indicate that the neural mechanisms responsible for the integration of speed information act as if each patch provides an independent sample of speed, independent of grating direction. The results are not consistent with simple summation across space by a directionally selective mechanism with a large receptive field. In the second (search) paradigm, only one of the gratings in an interval moved faster and observers were asked to pick this interval. In this case, thresholds increased with the number of distractor gratings. The decrease in performance with increased n is common in search tasks and is often attributed to a bottleneck in the information that observers can process simultaneously. However, the results in the integration paradigm show that subjects indeed have access to and can use additional information with increasing n, at least up to 4 patches. Finally, simple detection models predict the trends in both the search and integration paradigms without invoking an input bottleneck.

Verghese, Preeti↗