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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 271 records · Page 15
All sourcesNASA NTRSDOE OSTI
NASA NTRS2015

Particle Image Velocimetry Applications Using Fluorescent Dye-Doped Particles

Polystyrene latex sphere particles are widely used to seed flows for velocimetry techniques such as Particle Image Velocimetry (PIV) and Laser Doppler Velocimetry (LDV). These particles may be doped with fluorescent dyes such that signals spectrally shifted from the incident laser wavelength may be detected via Laser Induced Fluorescence (LIF). An attractive application of the LIF signal is achieving velocimetry in the presence of strong interference from laser scatter, opening up new research possibilities very near solid surfaces or at liquid/gas interfaces. Additionally, LIF signals can be used to tag different fluid streams to study mixing. While fluorescence-based PIV has been performed by many researchers for particles dispersed in water flows, the current work is among the first in applying the technique to micron-scale particles dispersed in a gas. A key requirement for such an application is addressing potential health hazards from fluorescent dyes; successful doping of Kiton Red 620 (KR620) has enabled the use of this relatively safe dye for fluorescence PIV for the first time. In this paper, basic applications proving the concept of PIV using the LIF signal from KR620-doped particles are exhibited for a free jet and a twophase flow apparatus. Results indicate that while the fluorescence PIV techniques are roughly 2 orders of magnitude weaker than Mie scattering, they provide a viable method for obtaining data in flow regions previously inaccessible via standard PIV. These techniques have the potential to also complement Mie scattering signals, for example in multi-stream and/or multi-phase experiments.

Petrosky, Brian J.↗
DOE OSTI2021

Pozzolanic reactivity of natural pozzolans, ground glasses and coal bottom ashes and implication of their incorporation on the chloride permeability of concrete

It is well understood that the partial replacement of portland cement with pozzolans in sufficient proportions results in improved long-term performance of concrete. However, dwindling availability of the most widely used pozzolan in the construction industry, fly ash, is forecast due to the termination of coal-fired electricity power stations around the world, necessitating the exploration of alternative pozzolans. Experimental investigations are conducted to study the performance of traditional pozzolans such as fly ash, silica fume and natural pozzolans (metakaolin, pumice, perlite and lassenite) together with novel pozzolans, including ground glasses (high-alkali and low-alkali), and ground bottom ash. Twenty-one concrete mixtures are examined for compressive strength, electrical conductivity, electrical resistivity, chloride permeability, and chloride migration coefficient. The reactivity of pozzolans studied is also determined in terms of compressive strength in lime-pozzolan mortar using a modified lime-reactivity test method. Many of the materials tested demonstrate the potential to be used in place of fly ash. However, a wide variation in the performance of these materials is evident which highlights the need for a reliable test to determine the level of reactivity of a pozzolan. The results indicate that the 7-day strength in the modified lime-reactivity test provides a good indication of the pozzolanic reactivity of the material and of how the material can be expected to contribute to the strength and permeability of concrete. The use of electrical resistivity as an indicator of the performance of pozzolans in terms of strength development and chloride penetration resistance when used to partially replace portland cement in concrete is also discussed.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Precise Timing Based on Pulsar Observation for Grid Synchronization

While Global Positioning System signals are widely used as the synchronized timing Sources for wide-area measurement systems for power grid monitoring and control, they are vulnerable to failures and malicious attacks. To address this Problem, an alternative kind of timing sources, the millisecond pulsars, were proposed to serve the power grid as they are more precise and physically indestructible. Millisecond pulsars are a kind of neutron stars that emit radio pulse signals that have extremely stable periods of milliseconds. However, the observed pulse Signals from pulsars cannot be directly used for timing because of their low signal-to-noise ratio and the dispersion effects of interstellar medium. In this paper, the precise timing method based on pulsar observation data is proposed to interpret the pulsar observation data and therefrom to generate precise timing signal for the power grid synchronization. In our proposed method,. incoherent de-dispersion is used on the observation data to mitigate the effect of interstellar medium. dispersion. Then spectrum analysis and segment folding are used to precisely estimate the local pulsar period. Finally the standard pulse per second signal is generated from. the estimated pulsar period and its precision. is analyzed. Experiments with the observation data of the pulsar based timing signal can be more accurate compared to GPS timing signals.

Luo, Xiqian↗
DOE OSTI2021

Advances in Processing, Manufacturing, and Applications of Magnetic Materials

Magnetic materials are increasingly important for many green energy technologies. Probably, the best known of these are permanent magnets. They are used to supply a magnetic field and are widely used in actuators, motors, generators, data storage, and sensors. These are “hard magnets,” meaning that they retain a large permanent magnetization (difficult to be demagnetized), which is what makes them so useful in motors where an opposing magnetic field can be used to push against them. A coercivity (resistance to demagnetization) of ~400 Oe (32,000 A/m) or more is typically the threshold value for a hard magnet and is typical of isotropic sintered ferrite (SrFe 12 O 19 ) such as found in many “refrigerator magnets.” Comparably important soft magnets are useful for directing magnetic fields and can be very easily (de)magnetized. As such, they typically have a coercivity < 12.5 Oe (1000 A/m), and specialized very soft magnets can have coercivities < 0.00125 Oe (1 A/m). Some common applications include coil cores, transformer cores, and magnetic shielding. Additionally, they are important for many AC electrical applications such as inductors, filters, and resonators, particularly at high frequencies up to and including microwaves.

36 MATERIALS SCIENCE↗
DOE OSTI2020

A review of SWAT applications, performance and future needs for simulation of hydro-climatic extremes

Hydro-climatic extremes, such as droughts and floods, have most likely increased due to climatic change and could lead to severe impacts on socio-economic, structural and environmental sectors. With nearly 4000 publications, the Soil and Water Assessment Tool (SWAT) is clearly one of the most extensively used ecohydrological models worldwide. The model has been widely used for projecting the impacts of future hydro-climatic changes, but application for extreme streamflow conditions is still rarely reported. To date, SWAT application reviews have focused on compilations of SWAT studies for specific or relatively new applications such as eco-hydrological modelling, ecosystem services, sub-daily simulations, and pesticide fate and transport simulations. However, no existing SWAT review studies have focused on simulation of hydro-climatic extremes. Furthermore, this research aims to bridge this gap by compiling and reviewing the findings of studies reporting SWAT hydro-climatic extremes including highlighting the performance and future research needs. A total of 111 articles have been identified since 1999; most of these studies were conducted in the United States and China. These articles can be divided into extreme flow assessments, drought studies, flood studies, drought and flood studies, SWAT coupling with other models, and SWAT improvements. Most of the extreme performance assessment studies reported “satisfactory ”performance, with a particular emphasis on peak flow comparisons. Future research needs regarding this topic include: (1) a unified SWAT extreme performance assessment framework; (2) SWAT improvements that result in improved replication of peak and low flows; (3) reliability assessment of global and satellite products for SWAT extreme simulations; (4) bias correction of CMIP6 and regional climate projections; (5) comparison of SWAT + and SWAT for extreme flow simulations in different types of basins; (6) development of an extreme flow module within an overall SWAT modelling system; and (7) integration of artificial intelligence within SWAT modelling.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Pro‐ L * ‐ A Probabilistic L * Mapping Tool for Ground Observations

Abstract Both ground and space observations are used extensively in the modeling of space weather processes within the Earth’s magnetosphere. In radiation belt physics modeling, one of the key phase‐space coordinates is L *, which indicates the location of the drift paths of energetic electrons. Global magnetic field models allow a subset of locations on the ground (mainly subauroral) to be mapped along field lines to a location in space and transformed into L *, provided that the initial ground location maps to a closed drift path. This allows observations from ground, or low‐altitude space‐based platforms to be mapped into space in order to inform radiation belt modeling. Many data‐based magnetic field models exist; however, these models can significantly disagree on mapped L * values for a single point on the ground, during both quiet times and storms. We present a state of the art probabilistic L * mapping tool, Pro‐ L *, which produces probability distributions for L * corresponding to a given ground location. Pro‐ L * has been calculated for a high resolution magnetic latitude by magnetic local time grid in the Earth’s Northern Hemisphere. We have developed the probabilistic model using 11 years of L * calculations for seven widely used magnetic field models. Usage of the tool is highlighted for both event studies and statistical models, and we demonstrate a number of potential applications.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

The Impulse Approximation Scattering Function and Its Use in Monte Carlo Photon Transport Simulations

The viability of using the impulse approximation scattering function in Monte Carlo photon transport simulations is explored. This scattering function can be constructed from the double differential incoherent scattering cross section developed by Ribberfors and Berggren. A commonly used method for modeling photon Doppler broadening, which is referred to as the hybrid Doppler broadening method, can also be derived from this cross section. A new photon Doppler broadening method, called the consistent Doppler broadening method, is derived and discussed. This method eliminates some of the commonly employed approximations in the hybrid Doppler broadening method, in part, by using the impulse approximation scattering function. Integrated incoherent cross sections generated using the impulse approximation scattering function and the widely used Waller-Hartree scattering function are in good agreement above 20 keV. Below 20 keV, differences as high as 70% are observed, which differs from the roughly 5% differences observed by Ribberfors for some of the materials. Integral and spectral quantities for two problems are also generated using the Monte Carlo photon transport capabilities of the Framework for REsearch in Nuclear ScIence and Engineering (FRENSIE). Due to the small, relative result differences observed when using the impulse approximation scattering function, it is considered a viable alternative to the Waller-Hartree scattering function. In addition, some small, but expected, differences in spectral fluxes at low energies can be avoided by adopting the consistent Doppler broadening method.

42 ENGINEERING↗
DOE OSTI2024

Auxiliary field Quantum Monte Carlo for dilute neutrons on the lattice

We employ constrained path Auxiliary Field Quantum Monte Carlo (AFQMC) in the pursuit of studying physical nuclear systems using a lattice formalism. Since AFQMC has been widely used in the study of condensed-matter systems such as the Hubbard model, we benchmark our method against published results for both one- and two-dimensional Hubbard model calculations. We then turn our attention to cold atomic and nuclear systems. We use an onsite contact interaction that can be tuned in order to reproduce the known scattering length and effective range of a given interaction. Developing this machinery allows us to extend our calculations to study nuclear systems within a lattice formalism. In conclusion, we perform initial calculations for a range of nuclear systems from two- to few-body neutron systems.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2020

New method for fitting coefficients in standard model effective theory

We present an alternative method for carrying out a principal-component analysis of Wilson coefficients in standard model effective field theory (SMEFT). The method is based on singular-value decomposition (SVD). The SVD method provides information about the sensitivity of experimental observables to physics beyond the standard model that is not accessible in the Fisher-information method. In principle, the SVD method can also have computational advantages over diagonalization of the Fisher information matrix. We demonstrate the SVD method by applying it to the dimension-6 coefficients for the process of top-quark decay to a b quark and a W boson and use this example to illustrate some pitfalls in widely used fitting procedures. We also outline an iterative procedure for applying the SVD method to dimension-8 SMEFT coefficients.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

Monte Carlo Simulation and Reconstruction: Assessment of Myocardial Perfusion Imaging of Tracer Dynamics With Cardiac Motion Due to Deformation and Respiration Using Gamma Camera With Continuous Acquisition

Purpose: Myocardial perfusion imaging (MPI) with single photon emission computed tomography (SPECT) is routinely used for stress testing in nuclear medicine. Recently, our group extended its potential going from 3D visual qualitative image analysis to 4D spatiotemporal reconstruction of dynamically acquired data to capture the time variation of the radiotracer concentration and the estimated myocardial blood flow (MBF) and coronary flow reserve (CFR). However, the quality of reconstructed image is compromised due to cardiac deformation and respiration. The work presented here develops an algorithm that reconstructs the dynamic sequence of separate respiratory and cardiac phases and evaluates the algorithm with data simulated with a Monte Carlo simulation for the continuous image acquisition and processing with a slowly rotating SPECT camera. Methods: A clinically realistic Monte Carlo (MC) simulation is developed using the 4D Extended Cardiac Torso (XCAT) digital phantom with respiratory and cardiac motion to model continuous data acquisition of dynamic cardiac SPECT with slowly rotating gamma cameras by incorporating deformation and displacement of the myocardium due to cardiac and respiratory motion. We extended our previously developed 4D maximum-likelihood expectation-maximization (MLEM) reconstruction algorithm for a data set binned from a continuous list mode (LM) simulation with cardiac and respiratory information. Our spatiotemporal image reconstruction uses splines to explicitly model the temporal change of the tracer for each cardiac and respiratory gate that delineates the myocardial spatial position as the tracer washes in and out. Unlike in a fully list-mode data acquisition and reconstruction the accumulated photons are binned over a specific but very short time interval corresponding to each cardiac and respiratory gate. Reconstruction results are presented showing the dynamics of the tracer in the myocardium as it continuously deforms. These results are then compared with the conventional 4D spatiotemporal reconstruction method that models only the temporal changes of the tracer activity. Mean Stabilized Activity (MSA), signal to noise ratio (SNR) and Bias for the myocardium activities for three different target-to-background ratios (TBRs) are evaluated. Dynamic quantitative indices such as wash-in (K1) and wash-out (k2) rates at each gate were also estimated. Results: The MSA and SNR are higher with higher TBRs while biases were improved with higher TBRs to less than 10%. The correlation between exhalation-inhalation sequence with the ground truth during respiratory cycle was excellent. Our reconstruction method showed better resolved myocardial walls during diastole to systole as compared to the ungated 4D image. Estimated values of K1 and k2 were also consistent with the ground truth. Conclusion: The continuous image acquisition for dynamic scan using conventional two-head gamma cameras can provide valuable information for MPI. Our study demonstrated the viability of using a continuous image acquisition method on a widely used clinical two-head SPECT system. Our reconstruction method showed better resolved myocardial walls during diastole to systole as compared to the ungated 4D image. Precise implementation of reconstruction algorithms, better segmentation techniques by generating images of different tissue types and background activity would improve the feasibility of the method in real clinical environment.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Evaluation of Deep Learning Model Architectures for Point-of-Care Ultrasound Diagnostics

Point-of-care ultrasound imaging is a critical tool for patient triage during trauma for diagnosing injuries and prioritizing limited medical evacuation resources. Specifically, an eFAST exam evaluates if there are free fluids in the chest or abdomen but this is only possible if ultrasound scans can be accurately interpreted, a challenge in the pre-hospital setting. In this effort, we evaluated the use of artificial intelligent eFAST image interpretation models. Widely used deep learning model architectures were evaluated as well as Bayesian models optimized for six different diagnostic models: pneumothorax (i) B- or (ii) M-mode, hemothorax (iii) B- or (iv) M-mode, (v) pelvic or bladder abdominal hemorrhage and (vi) right upper quadrant abdominal hemorrhage. Models were trained using images captured in 27 swine. Using a leave-one-subject-out training approach, the MobileNetV2 and DarkNet53 models surpassed 85% accuracy for each M-mode scan site. The different B-mode models performed worse with accuracies between 68% and 74% except for the pelvic hemorrhage model, which only reached 62% accuracy for all model architectures. These results highlight which eFAST scan sites can be easily automated with image interpretation models, while other scan sites, such as the bladder hemorrhage model, will require more robust model development or data augmentation to improve performance. With these additional improvements, the skill threshold for ultrasound-based triage can be reduced, thus expanding its utility in the pre-hospital setting.

47 OTHER INSTRUMENTATION↗
NASA NTRS1989

Interpretation and modeling of the averaged equations for a fluid-solid flow

A self-consistent derivation of the conservation laws is given for flows of a fluid-solid mixture. A unified analytical framework for obtaining constitutive relations is provided. This analysis uses a control volume/control surface approach that is widely used in fluid mechanics. All terms in the governing equations and the constitutive relations are written in terms of the mass-weighted averages except solid concentration. It is believed that the mass-weighted average is the natural bridge between micromechanics and constitutive relations. The derived momentum equations contain terms that differ from all existing models except that of Prosperetti and Jones (1984). However, their assumptions are not needed here. Special attention is given to the solid phase pressure. The physical basis of the previously assumed form for this pressure (Givler 1987) becomes clear. A number of related phenomena are also discussed. These include the anti-diffusion and anisotropic normal stresses. The energy equations are also different from existing models.

Shen, Hayley H.↗
NASA NTRS1994

Performance of customized DCT quantization tables on scientific data

We show that it is desirable to use data-specific or customized quantization tables for scaling the spatial frequency coefficients obtained using the Discrete Cosine Transform (DCT). DCT is widely used for image and video compression (MP89, PM93) but applications typically use default quantization matrices. Using actual scientific data gathered from divers sources such as spacecrafts and electron-microscopes, we show that the default compression/quality tradeoffs can be significantly improved upon by using customized tables. We also show that significant improvements are possible for the standard test images Lena and Baboon. This work is part of an effort to develop a practical scheme for optimizing quantization matrices for any given image or video stream, under any given quality or compression constraints.

Ratnakar, Viresh↗
NASA NTRS2002

Optimal Fitting of Non-linear Detector Pulses with Nonstationary Noise

Optimal extraction of pulses of constant known shape from a time series with stationary noise is well understood and widely used in detection applications. Applications where high resolution is required over a wide range of input signal amplitudes use much of the dynamic range of the sensor. The noise will in general vary over this signal range, and the response may be a nonlinear function of the energy input. We present an optimal least squares procedure for inferring input energy in such a detector with nonstationary noise and nonlinear energy response.

Fixsen, D. J.↗
NASA NTRS2010

Comparison of Two Methodologies for Calibrating Satellite Instruments in the Visible and Near Infrared

Traditionally, satellite instruments that measure Earth-reflected solar radiation in the visible and near infrared wavelength regions have been calibrated for radiance response in a two-step method. In the first step, the spectral response of the instrument is determined using a nearly monochromatic light source, such a lamp-illuminated monochromator. Such sources only provide a relative spectral response (RSR) for the instrument, since they do not act as calibrated sources of light nor do they typically fill the field-of-view of the instrument. In the second step, the instrument views a calibrated source of broadband light, such as lamp-illuminated integrating sphere. In the traditional method, the RSR and the sphere spectral radiance are combined and, with the instrument's response, determine the absolute spectral radiance responsivity of the instrument. More recently, an absolute calibration system using widely tunable monochromatic laser systems has been developed, Using these sources, the absolute spectral responsivity (ASR) of an instrument can be determined on a wavelength-hy-wavelength basis. From these monochromatic ASRs. the responses of the instrument bands to broadband radiance sources can be calculated directly, eliminating the need for calibrated broadband light sources such as integrating spheres. Here we describe the laser-based calibration and the traditional broad-band source-based calibration of the NPP VIIRS sensor, and compare the derived calibration coefficients for the instrument. Finally, we evaluate the impact of the new calibration approach on the on-orbit performance of the sensor.

Barnes, Robert A.↗
NASA NTRS2011

Extension of Generalized Fluid System Simulation Program's Fluid Property Database

This internship focused on the development of additional capabilities for the General Fluid Systems Simulation Program (GFSSP). GFSSP is a thermo-fluid code used to evaluate system performance by a finite volume-based network analysis method. The program was developed primarily to analyze the complex internal flow of propulsion systems and is capable of solving many problems related to thermodynamics and fluid mechanics. GFSSP is integrated with thermodynamic programs that provide fluid properties for sub-cooled, superheated, and saturation states. For fluids that are not included in the thermodynamic property program, look-up property tables can be provided. The look-up property tables of the current release version can only handle sub-cooled and superheated states. The primary purpose of the internship was to extend the look-up tables to handle saturated states. This involves a) generation of a property table using REFPROP, a thermodynamic property program that is widely used, and b) modifications of the Fortran source code to read in an additional property table containing saturation data for both saturated liquid and saturated vapor states. Also, a method was implemented to calculate the thermodynamic properties of user-fluids within the saturation region, given values of pressure and enthalpy. These additions required new code to be written, and older code had to be adjusted to accommodate the new capabilities. Ultimately, the changes will lead to the incorporation of this new capability in future versions of GFSSP. This paper describes the development and validation of the new capability.

Patel, Kishan↗
NASA NTRS2013

Impact of Surface Roughness and Soil Texture on Mineral Dust Emission Fluxes Modeling

Dust production models (DPM) used to estimate vertical fluxes of mineral dust aerosols over arid regions need accurate data on soil and surface properties. The Laboratoire Inter-Universitaire des Systemes Atmospheriques (LISA) data set was developed for Northern Africa, the Middle East, and East Asia. This regional data set was built through dedicated field campaigns and include, among others, the aerodynamic roughness length, the smooth roughness length of the erodible fraction of the surface, and the dry (undisturbed) soil size distribution. Recently, satellite-derived roughness length and high-resolution soil texture data sets at the global scale have emerged and provide the opportunity for the use of advanced schemes in global models. This paper analyzes the behavior of the ERS satellite-derived global roughness length and the State Soil Geographic data base-Food and Agriculture Organization of the United Nations (STATSGO-FAO) soil texture data set (based on wet techniques) using an advanced DPM in comparison to the LISA data set over Northern Africa and the Middle East. We explore the sensitivity of the drag partition scheme (a critical component of the DPM) and of the dust vertical fluxes (intensity and spatial patterns) to the roughness length and soil texture data sets. We also compare the use of the drag partition scheme to a widely used preferential source approach in global models. Idealized experiments with prescribed wind speeds show that the ERS and STATSGO-FAO data sets provide realistic spatial patterns of dust emission and friction velocity thresholds in the region. Finally, we evaluate a dust transport model for the period of March to July 2011 with observed aerosol optical depths from Aerosol Robotic Network sites. Results show that ERS and STATSGO-FAO provide realistic simulations in the region.

textures↗
NASA NTRSDate not supplied

Sampling Functions from Gaussian Processes and Structured Covariance Gaussian Networks

When learning aerodynamic models from data, it is critical to incorporate estimates of model uncertainty. This motivates the design of probabilistic aerodynamic databases which can be sampled to generate physically and statistically plausible aerodynamic models. In this talk we discuss how to sample deterministic functions from two different kinds of probabilistic models and demonstrate their use. First, Gaussian Process Regressors (GPRs) are a widely used probabilistic kernel-based model which can be thought of as Gaussian distributions over functions. GPRs are generally trained by maximizing the marginal likelihood of seeing the training data over the kernel parameter space. Sample functions are easily generated by drawing points from the Gaussian distribution at desired input points. However, when the points are not known ahead of time, the classical sampling approach is not possible since successive function samples will generate different function realizations. We present an approach for sampling consistent function evaluations from a GPR over multiple samples. Second, we describe a neural network architecture which learns a conditional Gaussian distribution by maximizing the marginal likelihood at each point in the input space. We then discuss and compare several options for generating sample functions which match this distribution. Finally, we demonstrate the use of these probabilistic aerodynamic models in an atmospheric reentry simulation.

Gaussian process regression↗