SEARCH · Engineering Papers

Results for “POPULATION COUNT”

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.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 109 records · Page 6

All sources NASA NTRS DOE OSTI

DOE OSTI2021

Uniformly Ordered Binary Decision Algorithm for Benchmark Experiment Correlations in Whisper Validation

When performing a validation exercise for determining the upper subcritical limit of a nuclear criticality safety application, an analyst should select and perform a statistical analysis on a population of benchmark experiments that are neutronically similar to the application. The size of this population should be sufficiently large such that the statistical analysis has a high degree of confidence that the bias plus bias uncertainty (calculational margin) has been accurately quantified. A complication arises because many benchmark experiments share common components, leading to correlations in their measured effective multiplication factors. Correlations between benchmark experiments within the population reduces its predictive power. This motivates the need for methods that consider benchmark experiment correlations and ensure adequate statistical significance of results. The Whisper code is a statistical analysis pack- age that incorporates nuclear data sensitivity coefficients from MCNP to assess benchmark experiment similarity and then performs an extreme-value analysis to estimate the bias plus bias uncertainty. The original methodology in Whisper does not consider the effect of benchmark experiment correlations when making this estimation, and this summary proposes the uniformly ordered binary decision algorithm to address this shortcoming. The original methodology in Whisper computes similarity coefficients ck for an application compared to all benchmark experiments in its library and develops weighting factors for a selected population proportional to the ck values. The methodology can be interpreted as statistically emulating a validation exercise for a particular application where the weighting factors may be viewed as the likelihood that an analyst would include a particular benchmark experiment within the population. The effective sample size of the population is the expected or mean number of benchmark experiments in the population. The uniformly ordered binary decision algorithm identifies clusters of correlated benchmark experiments within the population and then computes adjusted weighting factors based on the magnitude of the correlation coefficients within the cluster to compute a reduced effective sample size accounting for the lower information content because of correlations. Benchmark experiments within the cluster are ordered randomly with equal probability and probabilistic decisions are made as to whether a benchmark. experiment within the cluster should treated as redundant with a previous one; if two redundant benchmark experiments are included, then the conservative worst case bias plus bias uncertainty is used and the pair is counted as a single benchmark experiment in the population. Results are provided for HEU solutions in a research version of the Whisper software using benchmark experiment correlations provided by DICE, the Database for the International Criticality Safety Benchmark Evaluation Project (ICSBEP). These show that there can be a significant increase in the bias plus bias uncertainty because the effective sample size is reduced, and therefore the algorithm, needing to meet sample size requirements, expands the benchmark experiment population by accepting less similar benchmark experiments that would have otherwise not been included.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

NASA NTRS2003

Genetic models in applied physiology: selected contribution: effects of spaceflight on immunity in the C57BL/6 mouse. I. Immune population distributions

There are several aspects of the spaceflight environment that may lead to changes in immunity: mission-related psychological stress, radiation, and changes in gravity. On December 5, 2001, the space shuttle Endeavor launched for a 12-day mission to examine these effects on C57BL/6 mice for the first time. On their return, assays were performed on the spleen, blood, and bone marrow. In response to flight, there were no significant differences in the general circulating leukocyte proportions. In contrast, there was an increase in splenic lymphocyte percentages, with a corresponding decrease in granulocytes. There was an overall shift in splenic lymphocytes away from T cells toward B cells, and a decrease in the CD4-to-CD8 ratios due to a decrease in T helpers. In contrast, there were proportional increases in bone marrow T cells, with decreases in B cells. Although the blast percentage and count were decreased in flight mice, the CD34(+) population was increased. The data were more consistent with a shift in bone marrow populations rather than a response to changes in the periphery. Many of the results are similar to those using other models. Clearly, spaceflight can influence immune parameters ranging from hematopoiesis to mature leukocyte mechanisms.

Non-NASA Center↗

NASA NTRS1986

Star counts and galactic structure

Star counts are discussed as an aid in studies of galactic structure. Iterative computations using a method-of-color-bins to match numerical models with observational data are described. The star counts provide bounds for the luminosity function and the color-magnitude diagram and allow spheroid normalization in a copycat Galaxy model which posits a galaxy with a Population I disk and a Population II spheroid. Good agreement has been obtained between star counts predicted by the model and observed distributions, including color and magnitude ranges and direction. Modifications being considered for the model include consideration of the halo, a galactic bulge and a thick disk. Several galactic structural features which have yet to be modeled and which may be tractable to the copycat model corrected with star counts are identified.

Bahcall, John N.↗

DOE OSTI2019

Road exposure and the detectability of birds in field surveys

Road ecology, the study of the impacts of roads and their traffic on wildlife, including birds, is a rapidly growing field, with research showing effects on local avian population densities up to several kilometres from a road. However, in most studies, the effects of roads on the detectability of birds by surveyors are not accounted for. This could be a significant source of error in estimates of the impacts of roads on birds and could also affect other studies of bird populations. Using road density, traffic volume and bird count data from across Great Britain, we assess the relationships between roads and detectability of a range of bird species. Of 51 species analysed, the detectability of 36 was significantly associated with road exposure, in most cases inversely. Across the range of road exposure recorded for each species, the mean positive change in detectability was 52% and the mean negative change was 36%, with the strongest negative associations found in smaller‐bodied species and those for which aural cues are more important in detection. These associations between road exposure and detectability could be caused by a reduction in surveyors’ abilities to hear birds or by changes in birds’ behaviour, making them harder or easier to detect. We suggest that future studies of the impacts of roads on populations of birds or other taxa, and other studies using survey data from road‐exposed areas, should account for the potential impacts of roads on detectability.

Cooke, Sophia C.↗

DOE OSTI2013

A HYBRID MODEL FOR THE EVOLUTION OF GALAXIES AND ACTIVE GALACTIC NUCLEI IN THE INFRARED

We present a comprehensive investigation of the cosmological evolution of the luminosity function of galaxies and active galactic nuclei (AGNs) in the infrared (IR). Based on the observed dichotomy in the ages of stellar populations of early-type galaxies on one side and late-type galaxies on the other, the model interprets the epoch-dependent luminosity functions at z {>=} 1.5 using a physical approach for the evolution of proto-spheroidal galaxies and of the associated AGNs, while IR galaxies at z < 1.5 are interpreted as being mostly late-type ''cold'' (normal) and ''warm'' (starburst) galaxies. As for proto-spheroids, in addition to the epoch-dependent luminosity functions of stellar and AGN components separately, we have worked out, for the first time, the evolving luminosity functions of these objects as a whole (stellar plus AGN component), taking into account in a self-consistent way the variation with galactic age of the global spectral energy distribution. The model provides a physical explanation for the observed positive evolution of both galaxies and AGNs up to z {approx_equal} 2.5 and for the negative evolution at higher redshifts, for the sharp transition from Euclidean to extremely steep counts at (sub-)millimeter wavelengths, as well as the (sub-)millimeter counts of strongly lensed galaxies that are hard to account for by alternative, physical or phenomenological, approaches. The evolution of late-type galaxies and z < 1.5 AGNs is described using a parametric phenomenological approach. The modeled AGN contributions to the counts and to the cosmic infrared background (CIB) are always sub-dominant. They are maximal at mid-IR wavelengths: the contribution to the 15 and 24 {mu}m counts reaches 20% above 10 and 2 mJy, respectively, while the contributions to the CIB are of 8.6% and of 8.1% at 15 {mu}m and 24 {mu}m, respectively. The model provides a good fit to the multi-wavelength (from the mid-IR to millimeter waves) data on luminosity functions at different redshifts and on number counts (both global and per redshift slices). A prediction of the present model, useful to test it, is a systematic variation with wavelength of the populations dominating the counts and the contributions to the CIB intensity. This implies a specific trend for cross-wavelength CIB power spectra, which is found to be in good agreement with the data.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2022

Counting generations in birth and death processes with competing Erlang and exponential waiting times

Lymphocyte populations, stimulated in vitro or in vivo, grow as cells divide. Stochastic models are appropriate because some cells undergo multiple rounds of division, some die, and others of the same type in the same conditions do not divide at all. If individual cells behave independently, then each cell can be imagined as sampling from a probability density of times to division and death. The exponential density is the most mathematically and computationally convenient choice. It has the advantage of satisfying the memoryless property, consistent with a Markov process, but it overestimates the probability of short division times. With the aim of preserving the advantages of a Markovian framework while improving the representation of experimentally-observed division times, we consider a multi-stage model of cellular division and death. We use Erlang-distributed (or, more generally, phase-type distributed) times to division, and exponentially distributed times to death. We classify cells into generations, using the rule that the daughters of cells in generation n are in generation n + 1. In some circumstances, our representation is equivalent to established models of lymphocyte dynamics. We find the growth rate of the cell population by calculating the proportions of cells by stage and generation. The exponent describing the late-time cell population growth, and the criterion for extinction of the population, differs from what would be expected if N steps with rate λ were equivalent to a single step of rate λ/N. We link with a published experimental dataset, where cell counts were reported after T cells were transferred to lymphopenic mice, using Approximate Bayesian Computation. In the comparison, the death rate is assumed to be proportional to the generation and the Erlang time to division for generation 0 is allowed to differ from that of subsequent generations. The multi-stage representation is preferred to a simple exponential in posterior distributions, and the mean time to first division is estimated to be longer than the mean time to subsequent divisions.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2026

Pb-Apatite Framework as a Generator of Novel Flat-Band CuO-Based Physics

Based upon density functional theory (DFT) calculations, we present the basic electronic structure of CuPb 9 (PO 4 ) 6 O (Cu-doped lead apatite, aka LK-99), in two scenarios: (1) where the structure is constrained to the P3 symmetry and (2) where no symmetry is imposed. At the DFT level, the former is predicted to be metallic while the latter is found to be a charge-transfer insulator. In both cases the filling of these states is nominally d 9 , consistent with the standard Cu 2+ valence state, and Cu with a local magnetic moment of order 0.7 μ B . In the metallic case we find these states to be unusually flat (∼0.2 eV dispersion), giving a very high density of electronic states (DOS) at the Fermi level that we argue can be a host for novel electronic physics. The flatness of the bands is the likely origin of symmetry-lowering gapping possibilities that would remove the spectral weight from E F . Motivated by some initial experimental observations of metallic or semiconducting behavior, we propose that disorder (likely structural) is responsible for closing the gap. Here, we consider a variety of possibilities that could possibly close the charge-transfer gap but limit consideration to kinds of disorder that preserve electron count. Of the possible kinds we considered (spin disorder, O populating vacancy sites, and Cu on less energetically favorable Pb sites), the local Cu moment, and consequently the charge-transfer gap, remains robust. We conclude that disorder responsible for metallic behavior entails some kind of doping where the electron count changes. Further, we claim that the emergence of the flat bands should be due to weak wave function overlap between the orbitals on Cu and O sites, owing to the directional character of the constituent orbitals. Therefore, finding an appropriate host structure for minimizing hybridization between Cu and O while allowing them to still weakly interact should be a promising route for generating flat bands at E F which can lead to interesting electronic phenomena, regardless of whether LK-99 is a superconductor.

36 MATERIALS SCIENCE↗

NASA NTRSDate not supplied

Application of Support Vector Regression to Derive Crater Depth/Diameter From Satellite Images

Through the study of impact crater shapes, one can draw important conclusions about the nature and evolution of planetary surfaces [e.g., 1-4].In particular, studying the depth (d) to diameter (D)ratio (d/D) of a population of impact craters, in combination with crater count statistics, can yield valuable insights regarding rates of erosion and burial[5]. Motivated by the great abundance of available planetary surface image data, the goal of this project is to develop an efficient way to estimate d/D from satellite images of impact craters for which stereo information is not available [6]. We set out to develop and train a machine learning algorithm to extract d/D from a dataset of synthetic impact crater images for which model d/D is known. The applications of machine learning to planetary science are numerous and diverse [7], including automatic planetary surface mapping [8] and the detection of impact craters [9]. Our algorithm makes use of Support Vector Regression (SVR), which is a type of Support Vector Machine (SVM) [10, 11].SVMs are a branch of supervised machine learning valued for their straightforward implementation and versatility in solving both classification and regression problems. In regression analysis, an SVR algorithm produces a hyperplane function to fit the training data points, as well as an ε-tube that surrounds the hyperplane. Tunable hyperparameters include the width of the ε-tube (ε) and the amount an algorithm is penalized for points which fall outside the ε-tube.

L R Chin↗

DOE OSTI2018

Fission Induced Electromagnetic Response

The FIER (Fission Induced Electromagnetic Response) code is a C++ program designed to predict delayed gamma-ray spectra following fission. Given a fissioning isotope and irradiation scheme, FIER will determine the decay chains for each fission fragment and their daughters. Each product’s time-dependent population is calculated using an analytical solution to the Bateman equations that guide decay transmutation. These populations are then used to calculate the number of gamma-ray emissions for a given counting scheme. A Monte Carlo method is also available to determine the uncertainty of the fission product populations and delayed gamma-ray intensities based on the uncertainties on the input nuclear data.

Matthews, EricFrancis [University of California - ↗

DOE OSTI2024

Screening Tool for Equitable Adoption and Deployment of Solar (STEADy Solar)

The Screening Tool for Equitable Adoption and DeploYment of Solar (STEADy Solar) is a database and mapping tool designed to promoting clean energy investments for low-income communities across the United States. The tool indicates locations that may be eligible for the Investment Tax Credit bonus adders defined in the 2022 Inflation Reduction Act (IRA) and combines this information with demographics, social vulnerability, solar technical potential, solar economics (modeled net present value), and building counts by use-type. It can be used by states, municipalities, community-based organizations, developers, and researchers to identify sites where solar projects may be economical and where federal incentives may be available to support equitable adoption of solar. Specific values include: Areas eligible for the Energy Communities Tax Credit Bonus Program (including brownfield site counts) Areas eligible for the Low Income Communities Bonus Credit Program (including Tribal Lands, and covered affordable housing project counts) Areas categorized as disadvantaged by Justice40 Commercial and Residential Solar economics characterized by the Net Present Value and Simple Payback Period Total Population, Race, and Ethnicity Median Household Income, Poverty rate, Household Tenure Social Vulnerability Count of buildings, developable rooftop solar capacity (in kWdc) and estimated annual generation potential (in kWh) on four building types: Government General Services, Government Emergency Response, Grade Schools, and Colleges/Universities. The linked report describes the STEADy dataset metadata and presents high level insights from the data. The downloadable and formatted excel dataset makes it easy for users to gain insights for their locations. Supporting .csv and shapefiles provide users with the full data to run their own analyses on equitable solar siting.

14 SOLAR ENERGY↗

DOE OSTI2015

Time Evolving Fission Chain Theory and Fast Neutron and Gamma-Ray Counting Distributions

Here, we solve a simple theoretical model of time evolving fission chains due to Feynman that generalizes and asymptotically approaches the point model theory. The point model theory has been used to analyze thermal neutron counting data. This extension of the theory underlies fast counting data for both neutrons and gamma rays from metal systems. Fast neutron and gamma-ray counting is now possible using liquid scintillator arrays with nanosecond time resolution. For individual fission chains, the differential equations describing three correlated probability distributions are solved: the time-dependent internal neutron population, accumulation of fissions in time, and accumulation of leaked neutrons in time. Explicit analytic formulas are given for correlated moments of the time evolving chain populations. The equations for random time gate fast neutron and gamma-ray counting distributions, due to randomly initiated chains, are presented. Correlated moment equations are given for both random time gate and triggered time gate counting. There are explicit formulas for all correlated moments are given up to triple order, for all combinations of correlated fast neutrons and gamma rays. The nonlinear differential equations for probabilities for time dependent fission chain populations have a remarkably simple Monte Carlo realization. A Monte Carlo code was developed for this theory and is shown to statistically realize the solutions to the fission chain theory probability distributions. Combined with random initiation of chains and detection of external quanta, the Monte Carlo code generates time tagged data for neutron and gamma-ray counting and from these data the counting distributions.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

NASA NTRS1993

Deep galaxy count predictions in the radio, infrared, and X-ray spectral bands

The existence of a dominant population of strongly evolving starburst sources at moderate redshift is a plausible explanation for the excess number of faint blue galaxies detected in deep sky surveys. Multiwavelength observations at faint magnitudes would allow the existence of such a population to be confirmed. We use observed luminosity correlations and physical properties of known starburst galaxies to predict their contribution to the deep radio, infrared, and X-ray counts, as well as to the diffuse extragalactic background radiation in these various spectral bands.

Treyer, Marie-Agnes↗

DOE OSTI2020

The enigmatic Galactic Center excess: Spurious point sources and signal mismodeling

The Galactic Center GeV excess (GCE) has garnered great interest as a possible signal of either dark matter annihilation or some novel astrophysical phenomenon, such as a new population of gamma-ray emitting pulsars. In a companion paper, we showed that in a 10° radius region of interest (ROI) surrounding the Galactic Center, apparent evidence for GCE point sources (PSs) from non-Poissonian template fitting (NPTF) is actually an artifact of unmodeled north-south asymmetry of the GCE. In this work, we develop a simplified analytic description of how signal mismodeling can drive an apparent preference for a PS population, and demonstrate how the behavior pointed out in the companion paper also appears in simpler simulated datasets that contain no PS signals at all. We explore the generality of this behavior in the real gamma-ray data, and discuss the implications for past and future studies using NPTF techniques. While the drop in PS preference once north-south asymmetry is included is not ubiquitous in larger ROIs, we show that any overly-rigid signal model is expected to yield a spurious PS signal that can appear very convincing: as well as apparent significance comparable to what one would expect from a true PS population, the signal can exhibit stability against a range of variations in the analysis, and a source count function that is very consistent with previous apparent NPTF-based detections of a GCE PS population. This contrasts with previously studied forms of systematic mismodeling which are unlikely to mimic a PS population in the same way. Finally, in the light of this observation, and its explicit realization in the region where the GCE is brightest, we argue that a dominantly smooth origin for the GCE is not in tension with existing NPTF analyses.

79 ASTRONOMY AND ASTROPHYSICS↗

NASA NTRS2015

Microfluidic Device

Described herein are particular embodiments relating to a microfluidic device that may be utilized for cell sensing, counting, and/or sorting. Particular aspects relate to a microfabricated device that is capable of differentiating single cell types from dense cell populations. One particular embodiment relates a device and methods of using the same for sensing, counting, and/or sorting leukocytes from whole, undiluted blood samples.

Tai, Yu-Chong↗

NASA NTRS2016

Microfluidic Device

Tai, Yu-Chong↗

NASA NTRS2017

Microfluidic Device

Tai, Yu-Chong↗

NASA NTRS2017

Microfluidic Device

Tai, Yu-Chong↗

DOE OSTI2020

Learning to Count Grave Sites for Cemetery Observation Models With Satellite Imagery

Understanding how people occupy open spaces is important for research in support of population modeling, policy, national security, emergency response, and sustainability. For the past decade, there has been an increase in research toward capturing and reporting population dynamics and patterns of life at the building level and in some open public spaces such as cemeteries and parks. This is done through observation models developed from local sociocultural information acquired at various spatiotemporal scales to inform night, day, and episodic population occupancy estimates (people/1000 sq ft). Sociocultural information for cemeteries and parks is scarcely available and often collected manually. The process is not only marred by inconsistencies but is laborious and time consuming. In this study, we leverage convolutional neural networks (CNNs) and satellite imagery to derive grave site counts as proxy variables to support scalable and accurate sociocultural data required in a population observation model. Through a hybrid workflow (weak localization plus regression model), we characterize a large scale automation process to counting of grave sites. We evaluate and demonstrate the efficacy of proposed workflow using out-of-data set large satellite imagery and establish its broader impact on cemetery observation models.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗