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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 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Analytical Methods of Approximating the Fisher Information Matrix for the Lognormal Distribution

Modelling the matter density in the universe through time has become one of the most important open problems in cosmology. One distribution that works particularly well is the lognormal distribution, where if Y follows a lognormal distribution, ln Y follows a normal distribution. In many cases, we want to know how much information a variable carries about some unknown parameter; this can be accomplished by calculating the Fisher information matrix. However, for the lognormal distribution, the Fisher matrix is much more complicated to evaluate in closed form. In this paper, we will look at some analytical methods to evaluate the Fisher matrix.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

The Effect Of Ionization Variance On Nuclear-recoil Dark Matter Searches

Direct detection dark matter experiments are increasingly interested in the low-mass dark matter parameter space, but zero-background low-mass searches require event separation between the electron and nuclear recoil bands, which requires a proper understanding of detector energy reconstruction. Previous simulations have shown that we do not entirely understand the ionization efficiency (yield) for electron and nuclear recoils, as the assumption that the distribution for the yield is normally distributed for a true recoil energy is violated. Since the yield distribution may directly affect dark matter low-mass limits, it is crucial we understand how the yield is distributed. A component to understanding the yield distribution is the variance in the number of electron-hole pairs produced or ionization variance. This effect has been studied relatively infrequently as experiments have been interested in large energy deposits (10 - 100 keV) and could accurately separate electron and nuclear recoil events. For electron recoils, the ionization variance is described by a “Fano” factor. For nuclear recoils the effect can be parameterized by an “effective” Fano factor, which has similar definition but a different physical origin. The nuclear recoil “effective” Fano factor is shown to be much larger than the electron-recoil version above around 10 keV deposited energy.

Matheny, Mitchell Douglas↗
DOE OSTI2015

STOCHASTIC MODEL OF THE SPIN DISTRIBUTION OF DARK MATTER HALOS

We employ a stochastic approach to probing the origin of the log-normal distributions of halo spin in N-body simulations. After analyzing spin evolution in halo merging trees, it was found that a spin change can be characterized by a stochastic random walk of angular momentum. Also, spin distributions generated by random walks are fairly consistent with those directly obtained from N-body simulations. We derived a stochastic differential equation from a widely used spin definition and measured the probability distributions of the derived angular momentum change from a massive set of halo merging trees. The roles of major merging and accretion are also statistically analyzed in evolving spin distributions. Several factors (local environment, halo mass, merging mass ratio, and redshift) are found to influence the angular momentum change. The spin distributions generated in the mean-field or void regions tend to shift slightly to a higher spin value compared with simulated spin distributions, which seems to be caused by the correlated random walks. We verified the assumption of randomness in the angular momentum change observed in the N-body simulation and detected several degrees of correlation between walks, which may provide a clue for the discrepancies between the simulated and generated spin distributions in the voids. However, the generated spin distributions in the group and cluster regions successfully match the simulated spin distribution. We also demonstrated that the log-normality of the spin distribution is a natural consequence of the stochastic differential equation of the halo spin, which is well described by the Geometric Brownian Motion model.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Seawater sea-sand engineered/strain-hardening cementitious composites (ECC/SHCC): Assessment and modeling of crack characteristics

Highlights: • A probabilistic model was proposed to model the crack width evolution of SS-ECC at different strain levels. • The Weibull distribution fit the crack width distribution better than the log-normal distribution. • A 5-D representation was proposed to assess the SS-ECC by considering both cracking and mechanical performance. • Larger sea-sand size and lower fiber dosage led to larger crack widths in SS-ECC under the same tensile strain. • 18-mm PE fiber led to larger crack widths in SS-ECC at strain >2%, due to a large fraction of fiber rupture. Seawater sea-sand Engineered Cementitious Composites (SS-ECC) is a new version of ECC for marine constructions facing the scarcity of freshwater and river/manufactured sand. This study aims to assess and model the crack characteristics of SS-ECC, which are critical for its applications with non-corrosive reinforcements. The influence of sea-sand size, fiber length and fiber dosage on the crack characteristics of SS-ECC was explored. A five-dimensional representation was proposed to assess the overall performance of SS-ECC, by comprehensively considering both the crack characteristics (i.e., crack width and its variation) and the mechanical properties (i.e., compressive and tensile properties). A probabilistic model was also proposed to describe the stochastic nature and evolution of crack width, and it can be used to estimate the critical tensile strain on SS-ECC for a given crack-width limit and cumulative probability. The findings and proposed methods can facilitate the design of SS-ECC in marine and coastal structures.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Clutter Distributions for Tomographic Image Standardization in Ground-Penetrating Radar

Multistatic ground-penetrating radar (GPR) signals can be imaged tomographically to produce 3-D distributions of image intensities. In the absence of objects of interest, these intensities can be considered to be estimates of clutter. These clutter intensities spatially vary over several orders of magnitude and vary across different arrays, which makes a direct comparison of these raw intensities difficult. However, by gathering statistics on these intensities and their spatial variation, a variety of metrics can be determined. In this study, the clutter distribution is found to fit better to a two-parameter Weibull distribution than Gaussian or log-normal distributions. Based on the spatial variation of the two Weibull parameters, scale and shape, more information may be gleaned from these data. How well the GPR array is illuminating various parts of the ground, in depth and cross track, may be determined from the spatial variation of the Weibull scale parameter, which may in turn be used to estimate an effective attenuation coefficient in the soil. The transition in depth from clutter- to noise-limited conditions (which is one possible definition of GPR penetration depth) can be estimated from the spatial variation of the Weibull shape parameter. Lastly, the underlying clutter distributions also provide an opportunity to standardize image intensities to determine when a statistically significant deviation from background (clutter) has occurred, which is convenient for buried threat detection algorithm development that needs to be robust across multiple different arrays.

42 ENGINEERING↗
DOE OSTI2015

SU-E-J-243: Reproducibility of Radiomics Features Through Different Voxel Discretization Levels in F18-FDG PET Images of Cervical Cancer

Purpose: Site-specific investigations of the role of Radiomics in cancer diagnosis and therapy are needed. We report of the reproducibility of quantitative image features over different discrete voxel levels in PET/CT images of cervical cancer. Methods: Our dataset consisted of the pretreatment PET/CT scans from a cohort of 76 patients diagnosed with cervical cancer, FIGO stage IB-IVA, age range 31–76 years, treated with external beam radiation therapy to a dose range between 45–50.4 Gy (median dose: 45 Gy), concurrent cisplatin chemotherapy and MRI-based Brachytherapy to a dose of 20–30 Gy (median total dose: 28 Gy). Two board certified radiation oncologists delineated Metabolic Tumor volume (MTV) for each patient. Radiomics features were extracted based on 32, 64, 128 and 256 discretization levels (DL). The 64 level was chosen to be the reference DL. Features were calculated based on Co-occurrence (COM), Gray Level Size Zone (GLSZM) and Run-Length (RLM) matrices. Mean Percentage Differences (Δ) of features for discrete levels were determined. Normality distribution of Δ was tested using Kolomogorov - Smirnov test. Bland-Altman test was used to investigate differences between feature values measured on different DL. The mean, standard deviation and upper/lower value limits for each pair of DL were calculated. Interclass Correlation Coefficient (ICC) analysis was performed to examine the reliability of repeated measures within the context of the test re-test format. Results: 3 global and 5 regional features out of 48 features showed distribution not significantly different from a normal one. The reproducible features passed the normality test. Only 5 reproducible results were reliable, ICC range 0.7 – 0.99. Conclusion: Most of the radiomics features tested showed sensitivity to voxel level discretization between (32 – 256). Only 4 GLSZM, 3 COM and 1 RLM showed insensitivity towards mentioned discrete levels.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

Predicting the mineral composition of dust aerosols – Part 1: Representing key processes

Soil dust aerosols created by wind erosion are typically assigned globally uniform physical and chemical properties within Earth system models, despite known regional variations in the mineral content of the parent soil. Mineral composition of the aerosol particles is important to their interaction with climate, including shortwave absorption and radiative forcing, nucleation of cloud droplets and ice crystals, heterogeneous formation of sulfates and nitrates, and atmospheric processing of iron into bioavailable forms that increase the productivity of marine phytoplankton. Here, aerosol mineral composition is derived by extending a method that provides the composition of a wet-sieved soil. The extension accounts for measurements showing significant differences between the mineral fractions of the wet-sieved soil and the emitted aerosol concentration. For example, some phyllosilicate aerosols are more prevalent at silt sizes, even though they are nearly absent at these diameters in a soil whose aggregates are dispersed by wet sieving. We calculate the emitted mass of each mineral with respect to size by accounting for the disintegration of soil aggregates during wet sieving. These aggregates are emitted during mobilization and fragmentation of the original undispersed soil that is subject to wind erosion. The emitted aggregates are carried far downwind from their parent soil. The soil mineral fractions used to calculate the aggregates also include larger particles that are suspended only in the vicinity of the source. We calculate the emitted size distribution of these particles using a normalized distribution derived from aerosol measurements. In addition, a method is proposed for mixing minerals with small impurities composed of iron oxides. These mixtures are important for transporting iron far from the dust source, because pure iron oxides are more dense and vulnerable to gravitational removal than most minerals comprising dust aerosols. Finally, a limited comparison to measurements from North Africa shows that the model extensions result in better agreement, consistent with a more extensive comparison to global observations as well as measurements of elemental composition downwind of the Sahara, as described in companion articles.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Distributions of the Mean for Lognormally Distributed Data - 19427

In environmental sciences, a distribution of the mean is often needed for right-skewed data. For example, risk assessments are often based on distributions of the mean to obtain upper confidence limits (UCLs) for analyte concentrations, and, in probabilistic performance assessment (PPA) models, parameters are given distributions rather than deterministic values, and they are usually given distributions of their mean rather than the population distributions to account for the large spatial and temporal domains to which they are applied. How this distribution of the mean is developed depends on the characteristics of the parameter's full distribution and how the parameter relates to its use. In this presentation, I will discuss the implications of a right skew in distribution development. Parameters may vary over orders of magnitude and/or may be right-skewed. The material property of saturated hydraulic conductivity, Ks, is a prime example of such a parameter. Right-skewed parameters are often assumed to follow lognormal distributions. If X follows a lognormal distribution, then log(X) follows a normal distribution. For some right-skewed parameters, practitioners go back and forth between the two forms of the data depending on their needs. For example, it may be preferred to use the untransformed version of X in a model or equation, but it is easier to visualize the parameter values on a logarithmic scale. However, distribution development for the average value of the parameter will differ depending on whether X or log(X) is modeled. This difference is due to Jensen's Inequality, a theorem which states that the expected value of a concave function of a variable is less than or equal to the same function of the expected value of the variable; a logarithm is a concave function. In other words, the mean of log(X) is always less than or equal to the log of the mean of X and therefore the mean estimated from a distribution based on log(X) is less than or equal to the mean estimated from a distribution based on X. If a parameter is naturally considered on a log scale by subject matter experts, then distributions developed for the mean of log(X) may be more consistent with the use of the parameters in the literature than distributions developed for X. The statistical decisions of distribution development will be discussed within the context of right-skewed, lognormal data. These issues include method-of-moments versus maximum likelihood estimation of the distribution parameters and the use of bootstrapping to aid in the visualization of a distribution of the mean. The details surrounding Jensen's Inequality will be explained and visualized within the context of distribution development of a right-skewed parameter such as saturated hydraulic conductivity. (authors)

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

A Further Study of the t{sub Burst} of GRBs: Rest-frame Properties, External Plateau Contributions, and Multiple Parameter Analysis

Zhang et al. propose to redefine the true γ-ray burst (GRB) central engine activity duration, t{sub burst}, by considering the contributions from the prompt γ-ray emission, X-ray flare, and internal plateau features. With a comprehensive study of a large sample of Swift GRBs, it is shown that the t{sub burst} distribution in the observer frame consists of a bimodal feature, suggesting the existence of a new population of ultra-long GRBs. In this work, we make a series of further studies on t{sub burst}: we update the Swift GRB sample up to 2016 June; we investigate the properties of t{sub burst} distribution in the rest frame; we redefine t{sub burst} by involving external plateau contributions; and we make a multiple parameter analysis to investigate whether the bursts within the ultra-long population are statistically different in the sense of other features besides the duration distribution. We find that for all situations, the distribution of t{sub burst} requires two normal distributions in logarithmic space to provide a good fit both in the observer frame and in the rest frame. Considering the observational gap effect would not completely erase the bimodal distribution feature. However, the bursts within the ultra-long population may have no statistical difference in the sense of other features besides the duration term. We thus suggest that if the ultra-long population of GRBs indeed exists, their central engine and radiation mechanisms should be similar to those of the normal population, but they have a longer central engine activity timescale.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2016

WE-H-207A-03: The Universality of the Lognormal Behavior of [F-18]FLT PET SUV Measurements

Purpose: Log transforming [F-18]FDG PET standardized uptake values (SUVs) has been shown to lead to normal SUV distributions, which allows utilization of powerful parametric statistical models. This study identified the optimal transformation leading to normally distributed [F-18]FLT PET SUVs from solid tumors and offers an example of how normal distributions permits analysis of non-independent/correlated measurements. Methods: Forty patients with various metastatic diseases underwent up to six FLT PET/CT scans during treatment. Tumors were identified by nuclear medicine physician and manually segmented. Average uptake was extracted for each patient giving a global SUVmean (gSUVmean) for each scan. The Shapiro-Wilk test was used to test distribution normality. One parameter Box-Cox transformations were applied to each of the six gSUVmean distributions and the optimal transformation was found by selecting the parameter that maximized the Shapiro-Wilk test statistic. The relationship between gSUVmean and a serum biomarker (VEGF) collected at imaging timepoints was determined using a linear mixed effects model (LMEM), which accounted for correlated/non-independent measurements from the same individual. Results: Untransformed gSUVmean distributions were found to be significantly non-normal (p<0.05). The optimal transformation parameter had a value of 0.3 (95%CI: −0.4 to 1.6). Given the optimal parameter was close to zero (which corresponds to log transformation), the data were subsequently log transformed. All log transformed gSUVmean distributions were normally distributed (p>0.10 for all timepoints). Log transformed data were incorporated into the LMEM. VEGF serum levels significantly correlated with gSUVmean (p<0.001), revealing log-linear relationship between SUVs and underlying biology. Conclusion: Failure to account for correlated/non-independent measurements can lead to invalid conclusions and motivated transformation to normally distributed SUVs. The log transformation was found to be close to optimal and sufficient for obtaining normally distributed FLT PET SUVs. These transformations allow utilization of powerful LMEMs when analyzing quantitative imaging metrics.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

Development of an empirical model relating permeability and specific stiffness for rough fractures from numerical deformation experiments: Fracture Permeability and Stiffness

The coupling between hydraulic and mechanical properties of porous and fractured geologic media are critical for many geophysical processes and practical applications. Thus, the prediction of this linkage between these properties is broadly important. Here we present a potentially predictive model that links fracture permeability and specific stiffness with empirical coefficients dependent on fracture roughness, correlation length of aperture field, and rock mechanical properties. The equation was developed empirically from results of modeling the deformation and flow through synthetic fractures with aperture fields that follow a normal distribution. The fractures were subjected to increasing normal stress and deformed following an elastic model. Specific stiffness was directly quantified from these numerical deformation experiments. Permeability was estimated through calculation of the local flow field while considering effects of local fracture roughness and tortuosity. The empirical model roughly captures the transition from effective medium to percolation flow regimes with increasing specific stiffness.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

Theoretical estimate of the effect of thermal agitation on ribosome motion generated by stochastic microswimming

The effect of thermal agitation on ribosome motion is evaluated through the Péclet number, assuming that the ribosome is self-propelled along the mRNA during protein synthesis by a swimming stroke consisting of a cycle of stochastically-generated ribosome configurations involving its two subunits. The ribosome velocity probability distribution function is obtained, giving an approximately normal distribution. Its mean and variance together with an estimate of the in vivo free diffusion coefficient of the ribosome and using only configuration changes of small size, give a Péclet number similar to motor proteins and microorganisms. These results suggest the feasibility of the stochastic microswimming hypothesis to explain ribosome motion. - Highlights: • Hypothesis: the ribosome swims along the mRNA during protein synthesis. • How can withstand the thermal agitation of the particles in the surrounding fluid? • The Péclet number Pe is calculated estimating the in vivo diffusion coefficient. • With small size deformations the ribosome has speeds similar to motor proteins. • Similar Pe values for the ribosome and the motor proteins mean feasible hypothesis.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2017

Release Fractions from Airborne Fluid and Slurry Spills

Release fractions are commonly used to make conservative estimates of emissions from processes and are applied to characterize industrial operations to safeguard workers and public. Release fractions cannot be derived theoretically; they must be measured. Appropriate measurements are limited. This paper describes tests that were conducted to provide large-scale release fraction data for estimating releases from three operations proposed for waste remediation at the Hanford Site in Richland, Washington. Experiments were conducted to measure release fractions of three processes: 1) pipe discharge of liquid and slurry in free fall into a liquid or slurry, 2) jet transfer of contents to the other side of the tank either impacting the tank wall or falling into the fluid pool, and 3) high pressure fan jet striking a steel plate or simulated waste from a small stand-off distance. The tests were conducted without forced ventilation in an enclosed prototypic ¼-scale model of a 3785 m^3 (1 million gallon) tank in use at the Hanford Site for storage of radioactive waste. Aerosol releases were characterized based on filter samples of aerosol collected near the process stream, tank wall, and tank top to determine release fraction at engineering scale. Particle size distribution measurements were analyzed to determine whether the particles were in the respirable range. The release fractions for the top of the unventilated tank ranged from 9x10-7 to 6x10-4 depending on the process simulated. The particle size distribution was determined to be log-normally distributed with geometric mean diameters ranging from 3 to 8 µm. Thus, all particles are conservatively considered to be “respirable.”

aerosol generation, release fraction, water spill,↗
DOE OSTI2020

Creep Deformation and Dynamic Grain Growth in an Interstitial-Free Steel

Dynamic grain growth is demonstrated to be much faster than static grain growth in a body-centered-cubic, interstitial-free steel sheet material at 850°C. Dynamic grain growth occurs during concurrent plastic deformation at elevated temperature, whereas static grain growth occurs during static annealing. Grain growth during steady-state plastic flow in tension at 850°C to a true strain of 0.2 at a true-strain rate of 10 -4 s -1 doubled grain size, while static annealing for the same time produced no increase in grain size. This is described as dynamic normal grain growth (DNGG) because no abnormally large grains were observed. The recrystallized microstructure of the steel demonstrated a log-normal distribution of grain sizes. DNGG produced bimodal grain size distributions that deviate from the theoretical expectation of a simple shift to larger sizes during normal growth. The bimodal distributions contained a remnant of small grains that were not consumed during grain growth. DNGG produced a crystallographic texture that is unique from both the recrystallized material and that produced by lattice rotation alone. DNGG strengthened the {111}&lang;110&rang; and {111}&lang;112&rang; components of the strong γ-fiber component in the original recrystallization texture. Lattice rotation from tensile deformation, by contrast, strengthened the α-fiber components that intersect the original γ-fiber.

36 MATERIALS SCIENCE↗
DOE OSTI2020

The role of the spatial heterogeneity and correlation length of surface wettability on two-phase flow in a CO 2 -water-rock system

This study characterized and modeled heterogeneous surface wettability in sandstone and investigated the role of spatial heterogeneity and correlation length of surface wettability on relative permeability in a supercritical CO 2 (scCO 2 )-brine-rock system. Understanding the role of wettability heterogeneity on relative permeability is essential to geological CO 2 sequestration, oil and gas recovery, and contaminated groundwater remediation. Although numerous studies have attempted to understand the influences of surface wettability, capillary number (Ca), and viscosity ratio, the role of the spatial variation and correlation length of surface wettability on two-phase flow in three-dimensional (3D) porous media has not been unraveled due to the challenges in the measurement and representation of realistic rock surface wettability. In this work, we conducted in-situ measurements of surface contact angle (CA) in a Bentheimer sandstone after CO 2 flooding using micro-computed tomography (micro-CT), and found that the pore-scale CA distribution on rock surfaces followed a log-normal distribution associated with a spatial correlation length. Based on the statistical information from CT scanning, a Gaussian random field was used to model CA distributions that had desired standard deviations and spatial correlation lengths, which were then adjusted within a certain range of values for sensitivity analyses to study their combined effects on the two-phase flow in the porous medium using the lattice Boltzmann (LB) method. The LB two-phase flow simulation was accelerated using hybrid, multicore parallel computing to overcome the challenges in simulating multiphase flow in a large 3D domain having 800 × 800 × 600 nodes. The simulation results showed that the surface wettability heterogeneity (i.e., standard deviation of CA) had a lesser effect on the relative permeability of the wetting fluid (water) but a more significant impact on the relative permeability of the non-wetting fluid (scCO 2 ). The Corey model was used to fit the LB-simulated relative permeability curves of water and scCO 2 and showed that the variations in the relative permeability curves for both water and scCO 2 increased as the standard deviation and spatial correlation length of CA increased. This study illustrated that the assumption of homogeneous surface wettability may cause errors in multiphase flow simulations. Furthermore, the impacts of both the standard deviation and spatial correlation length of CAs should be accounted for. This is the first study that explored the spatial correlation lengths associated with CA distributions on sandstone surfaces and comprehensively investigated the roles of both spatial variation and correlation length of CA on two-phase flow properties in 3D porous media. The optimized LB multiphase flow model was proved a powerful tool to study the interplays and combined effects of these statistical parameters, which had critical applications in numerous natural and engineering processes that involved multiphase flow in porous media.

58 GEOSCIENCES↗
DOE OSTI2015

Quantitative study of particle size distribution in an in-situ grown Al–TiB{sub 2} composite by synchrotron X-ray diffraction and electron microscopy

Synchrotron X-ray diffraction and transmission electron microscopy (TEM) were applied to quantitatively characterize the average particle size and size distribution of free-standing TiB{sub 2} particles and TiB{sub 2} particles in an in-situ grown Al–TiB{sub 2} composite. The detailed evaluations were carried out by X-ray line profile analysis using the restricted moment method and multiple whole profile fitting procedure (MWP). Both numerical methods indicate that the formed TiB{sub 2} particles are well crystallized and free of crystal defects. The average particle size determined from different Bragg reflections by the restricted moment method ranges between 25 and 55 nm, where the smallest particle size is determined using the 110 reflection suggesting the highest lateral-growth velocity of (110) facets. The MWP method has shown that the in-situ grown TiB{sub 2} particles have a very low dislocation density (~ 10{sup 11} m{sup −} {sup 2}) and their size distribution can be described by a log-normal distribution. Good agreement was found between the results obtained from the restricted moment and MWP methods, which was further confirmed by TEM. - Highlights: • Accurate quantitative characterization of in-situ grown T{sub i}B{sub 2} particles has been achieved. • Particle size anisotropy was revealed indicating 110 facets being largest during T{sub i}B{sub 2} growth. • A wide size distribution was observed for T{sub i}B{sub 2} particles with a dominant size smaller than 100 nm.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Determining reference standard strength for neutron-irradiated reduced activation ferritic/martensitic steel F82H by Bayesian method

The deterministic approach widely adopted in the design of structural components relies on systematically defined design limits using empirically determined safety factors. However, this approach is not always appropriate because structures are subjected to a variety of loads in the practical environment, which may result in excessively conservative design limits. In recent years, a more rigorous probabilistic approach that incorporates material strength distributions has become an important solution. In the probabilistic approach, the probability density functions of material strength properties underpin the design criteria. Here, the objective of this study is to identify the density distribution functions that best describe tensile properties of irradiated F82H to define a reference strength for DEMO design. Due to the limited number of existing data, this study specifically employs a Bayesian prediction method based on Monte Carlo simulations to determine a material reference value with statistical reliability and to investigate its effectiveness. For example, the dependence of tensile properties of 300 °C irradiated materials on irradiation damage and the range predicted by 95% Bayesian estimation was evaluated. As a statistical model for the dose dependence of statistical parameters, the normal distribution exhibited a better fit for 0.2% proof strength and tensile strength, whereas the distribution of total elongation data gave comparable reference values for both the normal and Weibull distribution models. Both models gave comparable criteria for the distribution of total elongation data. The Weibull model also gave better results for uniform elongation. The function best describing the model was a logarithmic law for both 0.2% proof strength and tensile strength, while a power law for both total and uniform elongation, which allowed for more comprehensive data prediction of irradiation data with statistical accuracy for DEMO reactor design.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Influence of Viscosity on Dynamic Magnetization of Thermally Blocked Iron Oxide Nanoparticles Characterized by a Sensitive AC Magnetometer

In this work, we show that the viscosity of carrier liquid affects the dynamic magnetization of thermally blocked multi-core iron oxide nanoparticles. The core size of the nanoparticles was determined from the magnetization curve measured by a specially developed high-T{sub c} SQUID magnetometer and calculated to be 11.7 nm. Using an AC magnetometer developed based on induction coils, the dynamic magnetization of the multi-core iron oxide nanoparticle solution was measured from 3 Hz to 10.48 kHz. Later, we reconstructed of the hydrodynamic size distribution of the particles by assuming a log-normal distribution of particle size in an AC susceptibility model by Shliomis and Stepanov, which accounts for anisotropic directions of the easy axes of magnetic nanoparticles with respect to the excitation field direction. The reconstructed hydrodynamic sizes showed an average diameter of 130 nm and agreed with the size determined by dynamic light scattering method. In the case of increasing viscosity of the carrier liquids from 0.89 to 8.11 mPa s, the dynamic magnetization peaks of the imaginary component have shifted to a lower frequency region. We showed that the harmonics ratio and phase delay upon the magnetic field excitation at 30 Hz could also be used to determine the viscosity of carrier liquid independently.

77 NANOSCIENCE AND NANOTECHNOLOGY↗