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At least 91 records · Page 5

Origin and evolution of the Saturn system

As was the case for Jupiter, Saturn formed either as a result of a gas instability within the solar nebula or the accretion of a solid core that induced an instability within the surrounding solar nebula. In either case, the proto-planet's history is divided into three major stages: early, quasi-hydrostatic evolution (stage 1); hydrodynamical collapse (stage 2); and late, quasi-hydrostatic contraction (stage 3). During stage 1, Saturn had a radius of several hundred times that of its present radius, R(s), while stage 3 began when Saturn had a radius of 3.5 R(s). Stages 1 and 2 lasted one-million to 10-million years and one year, respectively, while stage 3 is continuing through the present epoch. During the early history of the Saturn system, giant impact events may have catastrophically disrupted most of the original satellites of Saturn. Such disruption, followed by reaccretion, may be responsible, in part for the occurrence of Trojans and co-orbital moons in the Saturn system, the apparent presence of a stochastic component in the trend of satellite density with radial distance, and the present population of ring particles.

Pollack, J. B.↗

Modeling of asteroidal dust production rates

The production rate of dust associated with the prominent Hirayama asteroid families and the background asteroidal population are modeled with the intent of using the families as a calibrator of mainbelt dust production. However, the dust production rates of asteroid families may be highly stochastic; there is probably more than an order of magnitude variation in the total area of dust associated with a family. Over 4.5 x 10(exp 9) years of collisional evolution, the volume (mass) of a family is ground down by an order of magnitude, suggesting a similar loss from the entire mainbelt population. Our collisional models show that the number of meteoroids deliverable to Earth also varies stochastically, but only by a factor of 2 to 3.

Durda, Daniel D.↗

Investigating the effects of electron bounce-cyclotron resonance on plasma dynamics in capacitive discharges operated in the presence of a weak transverse magnetic field

Recently, Patil et al. [Phys. Rev. Res. 4, 013059 (2022)] have reported the existence of an enhanced operating regime when a low-pressure (5 mTorr) capacitively coupled discharge (CCP) is driven by a very high radio frequency (60 MHz) source in the presence of a weak external magnetic field applied parallel to its electrodes. Their particle-in-cell simulations show that a significantly higher bulk plasma density and ion flux can be achieved at the electrode when the electron cyclotron frequency equals half of the applied radio frequency for a given fixed voltage. In the present work, we take a detailed look at this phenomenon and further delineate the effect of this “electron bounce-cyclotron resonance (EBCR)” on the electron and ion dynamics of the system. We find that the ionization collision rate and stochastic heating are maximum under resonance condition. The electron energy distribution function also indicates that the population of tail-end electrons is highest for the case where EBCR is maximum. Formation of electric field transients in the bulk plasma region is also seen at lower values of applied magnetic field. Finally, we demonstrate that the EBCR-induced effect is a low-pressure phenomenon and weakens as the neutral gas pressure increases. The potential utility of this effect to advance the operational performance of CCP devices for industrial purposes is discussed in this report.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Validation of Hygrothermal Simulations with Wall Performance Experiments in an Environmental Chamber

Oak Ridge National Laboratory is developing a web tool, built on a rule-based expert system, that aids stakeholders in designing energy-efficient moisture-durable walls. Currently, the tool’s expert system database is mostly populated with expert opinion, but work is being done to incorporate durability assessment based on stochastic hygrothermal modeling. Chamber experiments have been conducted to validate the hygrothermal models. The measured temperature and humidity have been compared with those predicted by the hygrothermal model. Experiments and comparison to one-dimensional hygrothermal modeling results were completed with two walls, a Structural Insulated Panel (SIP) based wall and a Concrete Masonry Unit (CMU) based wall. The two walls were succumbed to typical Chicago weather in ORNL’s Heat, Air and Moisture chamber. The walls were sequentially exposed to different scenarios, including diffusion, wetting, air leakage and solar radiation. For the most part, the hygrothermal simulations can be successfully used to predict the performance of these wall systems for the moisture transport phenomenon. Errors between measured and simulated values decreased as measurements got closer to the interior side of the wall. The root mean square error was larger for relative humidity (up to 17.5%-RH for CMU) than for temperature (up to 4.5°C for CMU wall). The errors were larger for the CMU wall than the wood frame wall. The phenomenon, including liquid water, caused large discrepancies between measurement and simulation results, and simulated results showed slower drying of materials than measured results. The one-dimensional nature of the simulation model made simulating air leaks difficult but not impossible.

Salonvaara, Mikael↗

Model data for Flood Frequency Analysis using Stochastic Storm Transposition and an Integrated Surface-Subsurface Hydrological Model

This archived provides scripts and input files used for the implementation of a novel approach to conduct process-based Flood Frequency Analysis using a Stochastic Storm Transposition (SST) and an Integrated Surface-Subsurface Hydrological Model (ISSHM). As a proof-of-concept, this study uses the ISSHM, Advanced Terrestrial Simulator (Amanzi-ATS) model, and the SST model, RainyDay, to conduct flood frequency analysis by simulating the flood response to 5,000 annual synthetic storm events in a ~2000 km2 Southeast Texas watershed.The Watershed Workflow package is implemented in Python3. The Jupyter notebooks can be executed through multiple open-source tools, for example, Anaconda Jupyter Lab, VS Studio Code, etc. Other data files include TXT, CSV, DAT, SBATCH, SHP, TIF, NetCDF, and HDF5 files, which can be read through Python scripts. The input files for the ATS model and RainyDay model have .XML and .SST extensions, respectively, and can be edited in any commonly used text editors.This archive contains:* Scripts and data files essential for generating the ATS model input. It uses the Watershed Workflow package to produce both mesh and ATS input files. * Jupyter notebooks designated for the ATS model evaluation, covering both long-term simulations and 40 rainfall-runoff events.* Input files required to simulate SST storm events using RainyDay.

54 ENVIRONMENTAL SCIENCES↗

Stochastic journeys of cell progenies through compartments and the role of self-renewal, symmetric and asymmetric division

Abstract Division and differentiation events by which cell populations with specific functions are generated often take place as part of a developmental programme, which can be represented by a sequence of compartments. A compartment is the set of cells with common characteristics; sharing, for instance, a spatial location or a phenotype. Differentiation events are transitions from one compartment to the next. Cells may also die or divide. We consider three different types of division events: (i) where both daughter cells inherit the mother’s phenotype (self-renewal), (ii) where only one of the daughters changes phenotype (asymmetric division), and (iii) where both daughters change phenotype (symmetric division). The self-renewal probability in each compartment determines whether the progeny of a single cell, moving through the sequence of compartments, is finite or grows without bound. We analyse the progeny stochastic dynamics with probability generating functions. In the case of self-renewal, by following one of the daughters after any division event, we may construct lifelines containing only one cell at any time. We analyse the number of divisions along such lines, and the compartment where lines terminate with a death event. Analysis and numerical simulations are applied to a five-compartment model of the gradual differentiation of hematopoietic stem cells and to a model of thymocyte development: from pre-double positive to single positive (SP) cells with a bifurcation to either SP4 or SP8 in the last compartment of the sequence.

Science & Technology - Other Topics↗

Improved Measurements of Galaxy Star Formation Stochasticity from the Intrinsic Scatter of Burst Indicators

Abstract Measurements of short-timescale star formation variations (i.e., “burstiness” or star formation stochasticity) are integral to our understanding of star formation feedback mechanisms and the assembly of stellar populations in galaxies. We expand upon the work of Broussard et al. by introducing a new analysis of galaxy star formation burstiness that accounts for variations in the Q sg = E B − V stars / E B − V gas distribution, a major confounding factor. We use Balmer decrements from the MOSFIRE Deep Evolution Field (MOSDEF) survey to measure Q sg , which we use to construct mock catalogs from the Santa Cruz Semi-Analytic Models and Mufasa cosmological hydrodynamical simulation based on 3D-HST, Fiber Multi-Object Spectrograph (FMOS)-COSMOS, and MOSDEF galaxies with H α detections. The results of the mock catalogs are compared against observations using the burst indicator η = log 10 ( SFR H α / SFR NUV ) , with the standard deviation of the η distribution indicating burstiness. We find decent agreement between mock and observed η distribution shapes; however, the FMOS-COSMOS and MOSDEF mocks show a systematically low median and scatter in η in comparison to the observations. This work also presents the novel approach of analytically deriving the relationship between the intrinsic scatter in η , scatter added by measurement uncertainties, and observed scatter, resulting in an intrinsic burstiness measurement of 0.06–0.16 dex.

79 ASTRONOMY AND ASTROPHYSICS↗

A Stochastic Approach to Reconstruct Gamma-Ray-burst Light Curves

Gamma-ray bursts (GRBs), as they are observed at high redshift ( z = 9.4), are vital to cosmological studies and investigating Population III stars. To tackle these studies, we need correlations among relevant GRB variables with the requirement of small uncertainties on their variables. Thus, we must have good coverage of GRB light curves (LCs). However, gaps in the LC hinder the precise determination of GRB properties and are often unavoidable. Therefore, extensive categorization of GRB LCs remains a hurdle. We address LC gaps using a stochastic reconstruction, wherein we fit two preexisting models (the Willingale model; W07; and a broken power law; BPL) to the observed LC, then use the distribution of flux residuals from the original data to generate data to fill in the temporal gaps. We also demonstrate a model-independent LC reconstruction via Gaussian processes. At 10% noise, the uncertainty of the end time of the plateau, its correspondent flux, and the temporal decay index after the plateau decreases by 33.3%, 35.03%, and 43.32% on average for the W07, and by 33.3%, 30.78%, 43.9% for the BPL, respectively. The uncertainty of the slope of the plateau decreases by 14.76% in the BPL. After using the Gaussian process technique, we see similar trends of a decrease in uncertainty for all model parameters for both the W07 and BPL models. These improvements are essential for the application of GRBs as standard candles in cosmology, for the investigation of theoretical models, and for inferring the redshift of GRBs with future machine-learning analyses.

79 ASTRONOMY AND ASTROPHYSICS↗

Energization of ionospheric ions by electrostatic hydrogen cyclotron waves

Interactions between ionospheric ions and electrostatic hydrogen cyclotron waves are studied numerically in an investigation of a possible mechanism for the energization of the low-energy ionospheric ions flowing along geomagnetic field lines to high altitudes. Ion equations of motion are solved numerically for a given number of O(+), He(+) and He(2+) ions initially in a Maxwellian distribution. All the ions considered are found capable of undergoing stochastic acceleration by a coherent electrostatic hydrogen cyclotron wave with parameters typical of the auroral plasma above 1 earth radius. The fraction of the initial ion population undergoing heating depends strongly on the mass, charge and initial temperature of the ion species, with O(+) ions only heated when their initial temperature is approximately greater than the hydrogen temperature and the lighter ions able to be heated even when cold, due to cyclotron resonant stochastic heating.

Singh, N.↗

Semi-Analytical Hierarchical Bayesian Inference of Nonlinear Model Structure in Stochastic Dynamics: Applied to Compartmental Models of Infectious Diseases

A Bayesian computational framework for parsimonious inference in stochastic nonlinear dynamical systems is presented. This framework enables the concurrent estimation of system states, time-varying parameters, time-invariant parameters, and the optimal sparsity structure of the model parameters. Because differential equation-based models are often simplified mechanistic or phenomenological representations, robust inference from noisy measurement data requires explicit treatment of model error and uncertainty. Model error and time-varying parameters can be represented as random processes, enabling inference while making minimal assumptions about the underlying sources of discrepancy and variability. Adopting stochastic differential equation representations affords the model significant flexibility, but can also render it susceptible to overfitting during statistical inversion, where the inferred model may track noise rather than the underlying signal. To alleviate the effects of overfitting and to enable the discovery of the optimal sparse representation of the time-invariant parameters, a Bayesian sparse learning algorithm is embedded within the framework. This sparse learning framework adopts an approximate hierarchical Bayesian setting defined by a series of semi-analytical expressions. The model structure inference framework is validated using a stochastic compartmental model for tracking and forecasting active cases of an infectious disease. Compartmental models describe population-level infectious disease dynamics through interactions among population fractions grouped by disease state. Mathematically, such models consist of a system of coupled ordinary differential equations. This example adopts an expressive compartmental model that includes multiple possible interactions between disease states, motivated by early uncertainty surrounding COVID-19 reinfection dynamics and their implications for long-term epidemic forecasting. The sparse learning exercise permits the inference of a priori unknown epidemiological dynamics from simulated public health data, discovering the nested compartmental model that optimizes the trade-off between average data-fit and model complexity. It is shown that inducing sparsity among the model parameters eliminates redundant interactions between compartments, equivalently revealing the optimal coupling structure between differential equations.

97 MATHEMATICS AND COMPUTING↗

Snowmass2021 Cosmic Frontier White Paper: Future Gravitational-Wave Detector Facilities

The next generation of gravitational-wave observatories can explore a wide range of fundamental physics phenomena throughout the history of the universe. These phenomena include access to the universe's binary black hole population throughout cosmic time, to the universe's expansion history independent of the cosmic distance ladders, to stochastic gravitational-waves from early-universe phase transitions, to warped space-time in the strong-field and high-velocity limit, to the equation of state of nuclear matter at neutron star and post-merger densities, and to dark matter candidates through their interaction in extreme astrophysical environments or their interaction with the detector itself. We present the gravitational-wave detector concepts than can drive the future of gravitational-wave astrophysics. We summarize the status of the necessary technology, and the research needed to be able to build these observatories in the 2030s.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

A Comprehensive Assessment of Biologicals Contained Within Commercial Airliner Cabin Air

Both culture-based and culture-independent, biomarker-targeted microbial enumeration and identification technologies were employed to estimate total microbial and viral burden and diversity within the cabin air of commercial airliners. Samples from each of twenty flights spanning three commercial carriers were collected via air-impingement. When the total viable microbial population was estimated by assaying relative concentrations of the universal energy carrier ATP, values ranged from below detection limits (BDL) to 4.1 x 106 cells/cubic m of air. The total viable microbial population was extremely low in both of Airline A (approximately 10% samples) and C (approximately 18% samples) compared to the samples collected aboard flights on Airline A and B (approximately 70% samples). When samples were collected as a function of time over the course of flights, a gradual accumulation of microbes was observed from the time of passenger boarding through mid-flight, followed by a sharp decline in microbial abundance and viability from the initiation of descent through landing. It is concluded in this study that only 10% of the viable microbes of the cabin air were cultivable and suggested a need to employ state-of-the art molecular assay that measures both cultivable and viable-but-non-cultivable microbes. Among the cultivable bacteria, colonies of Acinetobacter sp. were by far the most profuse in Phase I, and Gram-positive bacteria of the genera Staphylococcus and Bacillus were the most abundant during Phase II. The isolation of the human pathogens Acinetobacter johnsonii, A. calcoaceticus, Janibacter melonis, Microbacterium trichotecenolyticum, Massilia timonae, Staphylococcus saprophyticus, Corynebacterium lipophiloflavum is concerning, as these bacteria can cause meningitis, septicemia, and a handful of sometimes fatal diseases and infections. Molecular microbial community analyses exhibited presence of the alpha-, beta-, gamma-, and delta- proteobacteria, as well as Gram-positive bacteria, Fusobacteria, Cyanobacteria, Deinococci, Bacterioidetes, Spirochetes, and Planctomyces in varying abundance. Neisseria meningitidis rDNA sequences were retrieved in great abundance from Airline A followed by Streptococcus oralis/mitis sequences. Pseudomonas synxantha sequences dominated Airline B clone libraries, followed by those of N. meningitidis and S. oralis/mitis. In Phase II, Airline C, sequences representative of more than 113 species, enveloping 12 classes of bacteria, were retrieved. Proteobacterial sequences were retrieved in greatest frequency (58% of all clone sequences), followed in short order by those stemming from Gram-positives bacteria (31% of all clone sequences). As for overall phylogenetic breadth, Gram-positive and alpha-proteobacteria seem to have a higher affinity for international flights, whereas beta-and gamma-proteobacteria are far more common about domestic cabin air parcels in Airline C samples. Ultimately, the majority of microbial species circulating throughout the cabin airs of commercial airliners are commensal, infrequently pathogenic normal flora of the human nasopharynx and respiratory system. Many of these microbes likely originate from the oral and nasal cavities, and lungs of passengers and flight crew and are disseminated unknowingly via routine conversation, coughing, sneezing, and stochastic passing of fomites. The data documented in this study will be useful to generate a baseline microbial population database and can be utilized to develop biosensor instrumentation for monitoring microbial quality of cabin or urban air.

microbial diversity↗

Stochastic parametric skeletal dosimetry model for humans: Pediatric and adult computational skeleton phantoms for internal bone marrow dosimetry

Currently, computational phantoms that simulate skeletal tissues are used in active red bone marrow (AM) internal dosimetry. Up-to-date reference computational phantoms recommended by the ICRP are based on the analysis of CT-images of cadavers. Such phantoms have significant disadvantages. One disadvantage is that the assessment of uncertainty due to the population variability of skeleton dimensions and microstructure results from the limited availability of autopsy material. Another disadvantage is the simplified modelling of cortical layer and bone microarchitecture. A method of stochastic parametric skeletal dosimetry modelling of the bone structures – SPSD modelling – has been developed as an alternative to the ICRP reference phantoms. In the framework of this approach, skeletal phantom parameters are evaluated based on extensively reviewed results of published measurements of real bones. The SPSD approach allows for the assessment of both population-average values and their variability. SPSD-phantoms of the skeleton are modelled in voxel representation. They consist of smaller phantoms of the bone sites – segments – described by simple geometric shapes with uniform microarchitecture parameters. Such segmentation makes it possible to account for non-homogeneous skeletal microarchitecture and to model the bone structure with the required voxel resolution to elaborate suitable skeletal phantoms. The current study presents the parameters of the SPSD skeletal phantoms for the following age-groups: newborn, 1-year-old, 5-year-old, 10-year-old, 15-year-old (male and female), and adult (male and female). This skeletal phantom can be used for dosimetry as an alternative to available reference phantoms for bone-seeking radionuclides. The above-mentioned age- and sex-specific skeletal phantoms are comprised of 289 unique segments. The characteristics of the SPSD phantoms do not contradict published data and are in good agreement with the measurement results of real bones.

Science & Technology - Other Topics↗

Stochastic stability and instability of model ecosystems

In this work, we initiate a stability study of multispecies communities in stochastic environment by using Ito's differential equations as community models. By applying the direct method of Liapunov, we obtain sufficient conditions for stability and instability in the mean of the equilibrium populations. The conditions are expressed in terms of the dominant diagonal property of community matrices, which is a suitable mechanism for resolving the central problem of 'complexity vs stability' in model ecosystems. As a by-product of this analysis we exhibit important structural properties of the stochastic density-dependent models, and establish tolerance of community stability to a broad class of nonlinear time-varying perturbations.

Ladde, G. S.↗

Energetic electron transport in magnetic fields with island chains and stochastic regions

This paper investigates energetic electron transport in magnetized toroidal plasmas with magnetic fields characterized by island chains and regions of stochastic field lines produced by coil perturbations. We report on experiments performed in the DIII-D tokamak, which utilize electron cyclotron heating and current drive pulses to ‘tag’ electron populations within different locations across the discharge. The cross-field transport of these populations is then inferred from electron cyclotron emission measurements and gamma emission signals from scintillator detectors. Two types of energetic particles are distinguished and discussed: non-relativistic suprathermal electrons and relativistic runaway electrons. The magnetic field topology in each discharge is reconstructed with field-line tracing codes, which are also used to determine the location and scale of magnetic islands and stochastic regions. Comparison of simulations and experiments suggests that suprathermal transport is suppressed when the tagging is performed at a smaller radial location than the location of the $q = 1$ island chain and enhanced otherwise. Here q is the safety factor. We further demonstrate that increasing the width of the stochastic region within the edge plasma yields enhancement of the suprathermal electron transport.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Computation Molecular Kinetics Model of HZE Induced Cell Cycle Arrest

Cell culture models play an important role in understanding the biological effectiveness of space radiation. High energy and charge (HZE) ions produce prolonged cell cycle arrests at the G1/S and G2/M transition points in the cell cycle. A detailed description of these phenomena is needed to integrate knowledge of the expression of DNA damage in surviving cells, including the determination of relative effectiveness factors between different types of radiation that produce differential types of DNA damage and arrest durations. We have developed a hierarchical kinetics model that tracks the distribution of cells in various cell phase compartments (early G1, late G1, S, G2, and M), however with transition rates that are controlled by rate-limiting steps in the kinetics of cyclin-cdk's interactions with their families of transcription factors and inhibitor molecules. The coupling of damaged DNA molecules to the downstream cyclin-cdk inhibitors is achieved through a description of the DNA-PK and ATM signaling pathways. For HZE irradiations we describe preliminary results, which introduce simulation of the stochastic nature of the number of direct particle traversals per cell in the modulation of cyclin-cdk and cell cycle population kinetics. Comparison of the model to data for fibroblast cells irradiated photons or HZE ions are described.

Cucinotta, Francis A.↗

Acousto-ultrasonics

The theoretical development, methodology, and potential applications of acousto-ultrasonic nondestructive testing are set forth in an overview to assess the effectiveness of the technique. Stochastic wave propagation is utilized to isolate and describe defects in fiber-reinforced composites, particularly emphasizing the integrated effects of diffuse populations of subcritical flaws. The generation and nature of acousto-ultrasonic signals are described in detail, and stress-wave factor analysis of the signals is discussed. Applications of acousto-ultrasonics are listed including the prediction of failure sites, assessing fatique and impact damage, calculating ultimate tensile strength, and determining interlaminar bond strength. The method can identify subtle but important variations in fiber-reinforced composites, and development of the related instrumentation technology is emphasized.

Vary, Alex↗

In-Situ Process Monitoring Evaluation and Demonstration using Advanced Characterization with Laser Powder Bed Systems

Oak Ridge National Laboratory’s (ORNL) Manufacturing Demonstration Facility (MDF) worked with EOS Group to evaluate the current in-situ sensor capabilities of an EOS M290 Laser Powder Bed Fusion machine. The M290 was fitted with a 1 Mega-Pixel (MP) grayscale visible-light camera and a 5 MP temporally integrated (TI) near-infrared (NIR) camera. One print from stainless steel (SS) 316 and two from Inconel 625 (IN625) were performed where data including in-situ imaging and a machine log file were captured. These data were subsequently analyzed using a Dynamic Multi-Scale Segmentation Convolutional Neural Network (DMSCNN) trained on user defined classes and correlated to as-printed flaws, in the form of porosity, discovered in X-Ray Computed Tomography (XCT). In Phase I, two indications were detected in-situ and spatially correlated to stochastic lack-of-fusion flaws discovered using XCT. In Phase II, using these links from in-situ signatures to XCT flaw populations, a second neural network (NN) was trained to create a Voxelized Property Prediction Model (VPPM) to predict porosity percentages within the part using only features garnered from the in-situ data from two IN625 complex geometries. The VPPM was able to accurately predict porosity values for IN625 parts with an R 2 value of 0.764.

36 MATERIALS SCIENCE↗