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At least 1,009 records · Page 56
All sourcesNASA NTRSDOE OSTI
NASA NTRS2021

Application of Radon Transform to Multi-Angle Measurements Made by the Research Scanning Polarimeter: A New Approach to Cloud Tomography. Part I: Theory and Tests on Simulated Data.

The Research Scanning Polarimeter (RSP) is an airborne along-track scanner measuring the polarized and total reflectances in 9 spectral channels. The RSP was a prototype for the Aerosol Polarimetry Sensor (APS) launched on-board the NASA Glory satellite. Currently the retrieval algorithms developed for the RSP are being adopted for the measurements of the space-borne polarimeters on the upcoming NASA’s Plankton, Aerosol, Cloud Ocean Ecosystem (PACE)satellite mission. The RSP’s uniquely high angular resolution coupled with the high frequency of measurements allows for characterization of liquid water cloud droplet sizes using the polarized rainbow structure. It also provides geometric constraints on the cumulus cloud’s 2D cross section yielding the cloud’s geometric shape estimates. In this study we further build on the latter technique to develop a new tomographic approach to retrieval of cloud internal structure from remote sensing measurements. While tomography in the strict definition is a technique based on active measurements yielding a tomogram (directional optical thickness as a function of angle and offset of the view ray), we developed a “semi-tomographic” approach in which tomogram of the cloud is estimated from passive observations instead of being measured directly. This tomogram is then converted into 2D spatial distribution of the extinction coefficient using inverse Radon transform (filtered back projection) which is the standard tomographic procedure used e.g., in medical CT scans. This algorithm is computationally inexpensive compared to techniques relying on highly-multi-dimensional least-square fitting; it does not require iterative 3D RT simulations. The resulting extinction distribution is defined up to an unknown constant factor, so we discuss the ways to calibrate it using additional independent measurements. In the next step we use the profile of the droplet size distribution parameters from the cloud’s side (derived by fitting the polarized rainbows) to convert the 2D extinction distribution into that of the droplet number concentration. We illustrate and validate the proposed technique using 3D-RT-simulatedRSP observations of a LES-generated Cu cloud. Quantitative comparisons between the retrieved and the original optical and microphysical parameters are presented.

clouds↗
DOE OSTI2019

Seismoacoustic Analysis of Chemical Explosions at the Nevada National Security Site

In recent years, two sets of chemical explosions have been conducted at the Nevada National Security Site (NNSS): 6 explosions from Phase I of the Source Physics Experiment (SPE) and 4 explosions from the Forensics Surface Events (FSE). We have estimated the explosive yield and depth-of-burial/height-of-burst of both from the synthesis of seismic and low-frequency acoustic data. Analysis of the seismic signal is performed using a waveform envelope technique. Using seismic data only, however, there is a tradeoff between the yield and depth or height of the explosion, which becomes especially acute for near-surface events. This tradeoff between yield and depth/height can be broken by including complementary analysis of the acoustic signal using the acoustic waveform inversion method. The acoustic signal also has a strong tradeoff between a yield and depth/height, but the slope is opposite that of the seismic for near-surface events. We use a likelihood function to combine the seismic and acoustic analysis and improve our estimates of yield and depth/height for these sets of explosions. The results are generally consistent with the known parameters, but can be improved upon by higher-frequency seismic analysis and improved acoustic impulse scaling for large scaled depths-of-burial. These events serve as prime examples of data fusion from multiple data streams. The challenge will be to apply the method to events at longer regional distances where the seismic signals will include phases traveling in the upper mantle, and the acoustic signals will be recorded as infrasound signals, which are subject to atmospheric variability.

58 GEOSCIENCES↗
DOE OSTI2024

Dynamical edge modes and entanglement in Maxwell theory

Abstract Previous work on black hole partition functions and entanglement entropy suggests the existence of “edge” degrees of freedom living on the (stretched) horizon. We identify a local and “shrinkable” boundary condition on the stretched horizon that gives rise to such degrees of freedom. They can be interpreted as the Goldstone bosons of gauge transformations supported on the boundary, with the electric field component normal to the boundary as their symplectic conjugate. Applying the covariant phase space formalism for manifolds with boundary, we show that both the symplectic form and Hamiltonian exhibit a bulk-edge split. We then show that the thermal edge partition function is that of a codimension-two ghost compact scalar living on the horizon. In the context of a de Sitter static patch, this agrees with the edge partition functions found by Anninos et al. in arbitrary dimensions. It also yields a 4D entanglement entropy consistent with the conformal anomaly. Generalizing to Proca theory, we find that the prescription of Donnelly and Wall reproduces existing results for its edge partition function, while its classical phase space does not exhibit a bulk-edge split.

Physics↗
DOE OSTI2015

USING KAPPA FUNCTIONS TO CHARACTERIZE OUTER HELIOSPHERE PROTON DISTRIBUTIONS IN THE PRESENCE OF CHARGE-EXCHANGE

Kappa functions have long been used in the analysis and modeling of suprathermal particles in various space plasmas. In situ observations of the supersonic solar wind show its distribution contains a cold ion core and power-law tail, which is well-represented by a kappa function. In situ plasma observations by Voyager, as well as observations of energetic neutral atom (ENA) spectra by the Interstellar Boundary Explorer (IBEX), showed that the compressed and heated inner heliosheath (IHS) plasma beyond the termination shock can also be represented by a kappa function. IBEX exposes the IHS plasma properties through the detection of ENAs generated by charge-exchange in the IHS. However, charge-exchange modifies the plasma as it flows through the IHS, and makes it difficult to ascertain the parent proton distribution. In this paper we investigate the evolution of proton distributions, initially represented by a kappa function, that experience losses due to charge-exchange in the IHS. In the absence of other processes, it is no longer representable by a single kappa function due to the energy-dependent, charge-exchange process. While one can still fit a kappa function to the evolving proton distribution over limited energy ranges, this yields fitting parameters (pseudo-density, pseudo-temperature, pseudo-kappa index) that depend on the energy range of the fit. We discuss the effects of fitting a kappa function to the IHS proton distribution over limited energy ranges, its dependence on the initial proton distribution properties at the termination shock, and implications for understanding the observations.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1978

Ride quality flight testing

The ride quality experienced by passengers is a function of airframe rigid-body, elastic dynamic responses, autopilot, and stability augmentation system control inputs. A frequency response method has been developed to select sinusoidal elevator input time histories yielding vertical load factor distributions, within a given limit, as a function of fuselage station. The numerical technique is illustrated by applying two-degree-of-freedom short-period and first symmetric mode equations of motion to a B-1 aircraft at Mach 0.85 during sea level flight conditions.

Swaim, R. L.↗
NASA NTRS2010

Ares Launch Vehicle Transonic Buffet Testing and Analysis Techniques

It is necessary to define the launch vehicle buffet loads to ensure that structural components and vehicle subsystems possess adequate strength, stress, and fatigue margins when the vehicle structural dynamic response to buffet forcing functions are considered. In order to obtain these forcing functions, the accepted method is to perform wind-tunnel testing of a rigid model instrumented with hundreds of unsteady pressure transducers designed to measure the buffet environment across the desired frequency range. The buffet wind-tunnel test program for the Ares Crew Launch Vehicle employed 3.5 percent scale rigid models of the Ares I and Ares I-X launch vehicles instrumented with 256 unsteady pressure transducers each. These models were tested at transonic conditions at the Transonic Dynamics Tunnel at NASA Langley Research Center. The ultimate deliverable of the Ares buffet test program are buffet forcing functions (BFFs) derived from integrating the measured fluctuating pressures on the rigid wind-tunnel models. These BFFs are then used as input to a multi-mode structural analysis to determine the vehicle response to buffet and the resulting buffet loads and accelerations. This paper discusses the development of the Ares I and I-X rigid buffet model test programs from the standpoint of model design, instrumentation system design, test implementation, data analysis techniques to yield final products, and presents normalized sectional buffet forcing function root-mean-squared levels.

Piatak, David J.↗
DOE OSTI2025

Rapid Bayesian High Entropy Alloy Designs Fabricated via Wire Arc Additive Manufacturing

Purpose: This project seeks to demonstrate a new high-throughput (rapid) alloy design technique applied to creating new high entropy alloys (HEAs) for extreme environments. High entropy alloys shift the design paradigm from being focused on a single principal element (e.g. nickel-based alloys) to target alloys that include high atomic fractions (X >10%) of multiple elements. These HEA materials can exhibit sluggish diffusion and enhanced corrosion resistance, ideal for potential applications in advanced ultra supercritical (A-USC) steam cycles for power generation. Scope: The addition of multiple elements in high atomic fractions creates an enormous design space that cannot easily be investigated by traditional material design strategies such as designed of experiments (DOE). This project utilizes a Bayesian machine learning algorithm that has been modified to work with calculation of phase diagrams (CALPHAD) software. This Bayesian algorithm reduces manual inputs and increase the likelihood of achieving an optimal solution. Compositional inputs to this algorithm will be assessed using existing material property models for high temperature strength and corrosion resistance. The target for alloy performance will be a 15% (~100 ⁰C) increase in allowable service temperature beyond heat-resistant stainless steels while maintaining or improving alloy cost and corrosion resistance. Haynes 230 was selected as a baseline, which is 57 wt% Ni with 22 wt% Cr 14 wt% W, and 2 wt% Mo as solid solution strengtheners. In addition to rapid design via Bayesian machine learning, the alloys were rapidly fabricated using a multi-wire arc additive manufacturing (mWAAM) technique which allows for precise control of alloy composition and assessing of alloy design “windows” to study composition effects. Build speeds for wire-arc additive processes are among the highest for additive technologies enabling rapid and reliable sample fabrication when compared to conventional methods such as arc button melting. The mWAAM samples will be rapidly characterized via instrumented indentation for room temperature modulus and strength and for elevated temperature strength via hot hardness tests. After being screened with hardness testing, potential alloys will be further evaluated with conventional microscopy techniques including scanning electron microscopy (SEM) and transmission electron microscopy (TEM) to assess agreement with modeling results. The most promising compositions will also be evaluated by printing full sized tensile specimens for mechanical behavior tests at elevated temperatures. Results: Bayesian machine learning of a single performance function was initially used to optimize five performance metrics: 1) single phase stability, 2) yield strength, 3) creep resistance (low diffusion coefficient), 4) freezing range (weldability), and 5) material cost. The single performance function was suboptimal as assumptions had to be made about the results while formulating the optimization. A goal-oriented Bayesian optimization strategy (Hanaoka, 2021) was implemented with CALPHAD for use with the five metrics above. This multi-objective Bayesian optimization (MOBO) enabled the design of NiCrCoFe alloys with V and W additions. A base composition of NiCoCr was selected as Ni provides a stable FCC matrix, Cr aids corrosion/oxidation resistance, and Co is a solid-solutions strengthener that also improves creep by increasing the activation energy. Fe helps reduce diffusion coefficients and cost. Finally, V and W were selected for their reasonable solubility and high atomic misfit to aid in solid solution strengthening. Cracking of the mWAAM specimens was an early issue, and the Easton solidification cracking model (Easton et al., 2014a) was selected for addition to the MOBO function. High performing alloys fabricated by mWAAM included Ni 28 Cr 25 Co 26 Fe 15 V 8 and Ni 62 Cr 18 Co 1 Fe 3 W 15 . It was observed that even after adapting the mWAAM process for W, the W did not fully dissolve. To fully evaluate the Ni 62 Cr 18 Co 1 Fe 3 W 15 composition, a cored wire (80-20 NiCr sheath/powder core) was manufactured and printed via WAAM, and HIP’ing was utilized to homogenize and densify the printed alloy. The V and W alloys produced met metrics 1 (solid solution), 4 (solidification cracking), and 5 (cost). However, an unmodeled mechanism of thermal stress cracking was identified in the WAAM produced materials, perhaps exacerbated by the lack of grain boundary strengthening elements (B, C). Conclusions & Recommendations: A high-throughput (rapid) alloy design technique was applied to designing and manufacturing new high entropy alloys (HEAs) for extreme environments utilizing MOBO and mWAAM. The developed process was rapid and effective in addressing the mechanisms included in the model. The lack of grain boundary strengthening element additions (e.g., B, C) was a simplification that likely produced thermal stress cracking that turned into a large part of the investigation. Additions on the order of 0.005 wt% B and 0.05 wt% C likely would have minimized thermal stress grain boundary cracking. Overall, the high throughput design strategy is promising for rapid design of metrics-driven alloys for advanced ultra supercritical (A-USC) steam cycles for power generation. The MOBO and mWAAM process could be commercialized to accelerate metrics-driven alloy design. In addition, the cored-wire process utilized for scale-up is a promising high-volume process for WAAM alloy development and scale-up.

36 MATERIALS SCIENCE↗
DOE OSTI2018

A remarkable case of basis set dependence: the false convergence patterns of the methyl anion

Here, the gas phase methyl anion, CH 3 ¯, has been difficult to study experimentally, and the extreme basis set dependence of its molecular properties has presented a comparable challenge to theoreticians. Reliable predictions for the electronic structure of CH 3 ¯ require the use of basis sets capable of describing both the diffuse and valence characteristics of the system. The present study examines the basis set dependence of the equilibrium geometry and harmonic vibrational frequencies of CH 3 ¯. Both Hartree–Fock and CCSD(T) levels of theories are used with cc-pVXZ (, T, Q, 5, 6) basis sets with up to triple augmentation to describe the diffuse nature of the electron distribution. We find that non-augmented basis sets systematically yield vibrational frequencies that are too high for the umbrella mode and too low for the C–H symmetric and antisymmetric stretch even when extrapolated to the complete basis set limit, displaying false convergence patterns. The inclusion of one set of augmented functions significantly improves the convergence of these properties, but again yields false convergence patterns. Only with the doubly augmented basis set do we approach the basis set limit for the CH 3 ¯ vibrational frequencies.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2017

Near-threshold J/ψ-meson photoproduction on nuclei

On the basis of the first-collision model that relies on the nuclear spectral function and which includes incoherent processes involving charmonium production in proton–nucleon collisions, the photoproduction of J/ψ mesons on nuclei is considered at energies close to the threshold for their production on a nucleon. The absorption of final J/ψ mesons, their formation length, and the binding and Fermi motion of target nucleons are taken into account in this model along with the effect of the nuclear potential on these processes. The A dependences of the absolute and relative charmonium yields are calculated together with absolute and relative excitation functions under various assumptions on the magnitude of the cross section for J/ψN absorption, the J/ψ-meson formation length, and their inmedium modification. It is shown that, at energies above the threshold, these features are virtually independent of the formation length and the change in the J/ψ-meson mass in nuclear matter but are rather highly sensitive to the cross section for J/ψN interaction. The calculations performed in the present study can be used to determine the unknown cross section for J/ψ-meson absorption in nuclei from a comparison of their results with data expected from experiments in the Hall C of the CEBAF (USA) facility upgraded to the energy of 12 GeV. It is also shown that the absolute and relative excitation functions for J/ψ mesons in photon–nucleus reactions at subthreshold energies are sensitive to the change in the meson mass and, hence, carry information about the properties of charmonium in nuclear matter.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2019

Amine Functionalized Electrospun Cellulose Nanofibers for Fluoride Adsorption from Drinking Water

In this study, we synthesized amine functionalized cellulose nanofiber based adsorbent for effective removal of dissolved fluoride ions from groundwater samples. Cellulose acetate was electrospun into nanofibers followed by deacetylation to yield cellulose nanofibers which were then treated with ethylenediamine to prepare amine functionalized cellulose fabric to be used as an adsorbent. As- synthesized adsorbent was first characterized by scanning electron microscopy and Fourier transform infrared spectroscopy for physiochemical characteristics. Fluoride adsorption studies were then carried out under batch mode to study the influence of various parameters on adsorption process. Amine functionalized cellulose nanofibrous mat was found to be effective with high adsorption efficiency for removal of fluoride ions from aqueous solution, even at low fluoride concentrations (< 5 mg L{sup −1}). Adsorption mechanism of fluoride onto prepared cellulose nanofibers based adsorbent was explained from the studies of isotherms, kinetic and thermodynamic parameters. Field studies conducted using this amine functionalized cellulose nanofibrous mat revealed the suitability and effectiveness of adsorbent for fluoride removal from contaminated groundwater.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2026

Effects of Recovery Conditions and Aggregation Mechanisms on the Chemical and Physical Properties of Hybrid Poplar and Corn Stover Lignins

Heterogeneity in the physical properties and processing behavior of lignins recovered from biorefining process streams can hinder their effective utilization and industrial valorization. This work investigates lignin recovery by acidification from alkaline pretreatment liquors of varying sources (corn stover and hybrid poplar), compositions, solid contents, and incubation temperatures prior to filtration. Recovered lignins were characterized for filtration performance, mass yield, chemical composition, particle size and morphology, and color. A transition temperature was identified corresponding to marked shifts in lignin physical properties and was a function of the solid content and liquor source. Filtration below this temperature yielded slow-filtering, dark, brittle lignins with smoother particle surfaces, whereas precipitation above this threshold yielded fast-filtering, lighter, powdery lignins with rougher particle surfaces. The impact of temperature and concentration on universal cluster aggregation mechanisms was proposed to explain the differences between lignin particle properties and filtration behavior.

Aggregation↗
DOE OSTI2023

Predicting Biomass Yields of Advanced Switchgrass Cultivars for Bioenergy and Ecosystem Services Using Machine Learning

The production of advanced perennial bioenergy crops within marginal areas of the agricultural landscape is gaining interest due to its potential to sustainably produce feedstocks for biofuels and bioproducts while also improving the sustainability and resilience of commodity crop production. However, predicting the biomass yields of this production system is challenging because marginal areas are often relatively small and spread around agricultural fields and are typically associated with various abiotic conditions that limit crop production. Machine learning (ML) offers a viable solution as a biomass yield prediction tool because it is suited to predicting relationships with complex functional associations. The objectives of this study were to (1) evaluate the accuracy of commonly applied ML algorithms in agricultural applications for predicting the biomass yields of advanced switchgrass cultivars for bioenergy and ecosystem services and (2) determine the most important biomass yield predictors. Datasets on biomass yield, weather, land marginality, soil properties, and agronomic management were generated from three field study sites in two U.S. Midwest states (Illinois and Iowa) over three growing seasons. The ML algorithms evaluated in the study included random forests (RFs), gradient boosting machines (GBMs), artificial neural networks (ANNs), K-neighbors regressor (KNR), AdaBoost regressor (ABR), and partial least squares regression (PLSR). Coefficient of determination (R 2 ) and mean absolute error (MAE) were used to evaluate the predictive accuracy of the tested algorithms. Results showed that the ensemble methods, RF (R 2 = 0.86, MAE = 0.62 Mg/ha), GBM (R 2 = 0.88, MAE = 0.57 Mg/ha), and GBM (R 2 = 0.78, MAE = 0.66 Mg/ha), were the most accurate in predicting biomass yields of the Independence, Liberty, and Shawnee switchgrass cultivars, respectively. This is in agreement with similar studies that apply ML to multi-feature problems where traditional statistical methods are less applicable and datasets used were considered to be relatively small for ANNs. Consistent with previous studies on switchgrass, the most important predictors of biomass yield included average annual temperature, average growing season temperature, sum of the growing season precipitation, field slope, and elevation. This study helps pave the way for applying ML as a management tool for alternative bioenergy landscapes where understanding agronomic and environmental performance of a multifunctional cropping system seasonally and interannually at the sub-field scale is critical.

09 BIOMASS FUELS↗
NASA NTRS2004

Reduced Order Methods for Prediction of Thermal-Acoustic Fatigue

The goal of this investigation is to assess the quality of high-cycle-fatigue life estimation via a reduced order method, for structures undergoing random nonlinear vibrations in a presence of thermal loading. Modal reduction is performed with several different suites of basis functions. After numerically solving the reduced order system equations of motion, the physical displacement time history is obtained by an inverse transformation and stresses are recovered. Stress ranges obtained through the rainflow counting procedure are used in a linear damage accumulation method to yield fatigue estimates. Fatigue life estimates obtained using various basis functions in the reduced order method are compared with those obtained from numerical simulation in physical degrees-of-freedom.

Przekop, A.↗
NASA NTRS2006

A Nonlinear Reduced Order Method for Prediction of Acoustic Fatigue

The goal of this investigation is to assess the quality of high-cycle-fatigue life estimation via a reduced order method, for structures undergoing geometrically nonlinear random vibrations. Modal reduction is performed with several different suites of basis functions. After numerically solving the reduced order system equations of motion, the physical displacement time history is obtained by an inverse transformation and stresses are recovered. Stress ranges obtained through the rainflow counting procedure are used in a linear damage accumulation method to yield fatigue estimates. Fatigue life estimates obtained using various basis functions in the reduced order method are compared with those obtained from numerical simulation in physical degrees-of-freedom.

Przekop, Adam↗
NASA NTRS2015

Calibration of Predictor Models Using Multiple Validation Experiments

This paper presents a framework for calibrating computational models using data from several and possibly dissimilar validation experiments. The offset between model predictions and observations, which might be caused by measurement noise, model-form uncertainty, and numerical error, drives the process by which uncertainty in the models parameters is characterized. The resulting description of uncertainty along with the computational model constitute a predictor model. Two types of predictor models are studied: Interval Predictor Models (IPMs) and Random Predictor Models (RPMs). IPMs use sets to characterize uncertainty, whereas RPMs use random vectors. The propagation of a set through a model makes the response an interval valued function of the state, whereas the propagation of a random vector yields a random process. Optimization-based strategies for calculating both types of predictor models are proposed. Whereas the formulations used to calculate IPMs target solutions leading to the interval value function of minimal spread containing all observations, those for RPMs seek to maximize the models' ability to reproduce the distribution of observations. Regarding RPMs, we choose a structure for the random vector (i.e., the assignment of probability to points in the parameter space) solely dependent on the prediction error. As such, the probabilistic description of uncertainty is not a subjective assignment of belief, nor is it expected to asymptotically converge to a fixed value, but instead it casts the model's ability to reproduce the experimental data. This framework enables evaluating the spread and distribution of the predicted response of target applications depending on the same parameters beyond the validation domain.

Crespo, Luis G.↗
NASA NTRS1995

Medium-resolution studies of extreme-ultraviolet emission from CO by electron impact

We report medium-resolution (0.025 nm full width at half maximum (FWHM)) electron impact-induced emission spectra of CO for 20, 100, and 200 eV impact energies. The emission spectra correspond to the extreme ultraviolet transitions from the B (sup 1)Sigma(sup +)(0), and E (sup 1)Pi(0) vibronic states to the X (sup 1)Sigma(sup +)(0) ground state. The present measurements are carried out at 20 times higher spectral resolution (to separate the many blended components) compared to our previous measurements, which were at a spectral resolution of 0.5 nm FWHM. The emission cross sections corresponding to the B (sup 1)Sigma(sup +)(0) yields X (sup 1)Sigma(sup +)(0), C (sup 1)Sigma(sup +)(0) yields X (sup 1)Sigma(sup +)(0), and E (sup 1)Pi(0) yields X (sup 1)Sigma(sup +)(0) resonance transitions were measured. In addition, excitation functions (0-1 keV) extending well into the Born region have been measured for the strong transitions (B (sup 1)Sigma(sup +)(0) yields X (sup 1)Sigma(sup +)(0) and C (sup 1)Sigma(sup +)(0)) and oscillator strengths have been determined, using a modified Born approximation analytic fit to the measured excitation function.

Kanik, Isik↗
DOE OSTI2018

Improved Lithium Iodide neutron scintillator with Eu 2 + activation II: Activator zoning and concentration effects in Bridgman-grown crystals

We have previously reported on the formation of Suzuki Phase precipitate particles as a result of the addition of the divalent activator ion Eu 2+ to the monovalent alkali halide host LiI. [Boatner et al. (2017)]. These precipitates form during Bridgman or other melt-growth processes, even at low Eu 2+ concentrations (e.g., 0.1% EuI 2 doping), and scatter the scintillation light reducing the optical transparency of the scintillator and adversely affecting its radiation-detection performance. In our prior work, we developed a two-stage thermal-treatment method for the post-growth removal of the Suzuki Phase particles and the realization of a significant improvement in the optical transparency and associated neutron-detection of LiI:Eu 2+ scintillators. These improvements resulted in neutron-detection performance that is superior to GS-20 glass and that allows for the application of pulse height gamma-ray discrimination over a wide range of gamma ray energies as opposed to pulse shape discrimination. Here in this paper, we apply the two-stage thermal-processing method for the removal of Suzuki phase precipitates and carry out an in-depth study, first, of the neutron scintillator performance versus the Eu 2+ activator-ion-concentration spatial variation as a result of zoning effects during the Bridgman growth of LiI:Eu and, second, of the effects of varying the initial Eu 2+ activator ion concentration prior to crystal growth. The Eu 2+ zoning variation results allow one to identify and select the most efficient location of the scintillation performance in a directionally solidified single-crystal boule. The present study of the initial activator concentration levels shows that there are, in fact, two distinct types of luminescence centers with varying performance properties — one that occurs only at low EuI 2 addition levels (e.g., 0.01 to 0.06 %EuI 2 ) and that is quickly replaced by a second luminescing center with increasing Eu content (e.g., at 0.1% EuI2). The light yield for the luminescing center formed using a Eu activator in LiI is a critical function of the Eu concentration in the range of 0.01 to 0.1 % EuI 2 , and a high light yield of 100,000 photons/neutron is observed at the 0.06 %EuIadditive level prior to thermal processing.

36 MATERIALS SCIENCE↗
NASA NTRS1974

Quantitative values of blood flow through the human forearm, hand, and finger as functions of temperature

A literature search was made to obtain values of human forearm, hand and finger blood flow as functions of environmental temperature. The sources used include both government and laboratory reports and the research presented in the open literature. An attempt was made to review many of the more quantitative noninvasive determinations and to collate the results in such a way as to yield blood flow values for each body segment as continuous functions of temperature. A brief review of the various ways used to measure blood flow is included along with an abstract of each work from which data was taken.

Montgomery, L. D.↗