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At least 631 records · Page 35
All sourcesNASA NTRSDOE OSTI
DOE OSTI2013

Reinterpreting the development of extensive air showers initiated by nuclei and photons

Ultra-high energy cosmic rays (UHECRs) interacting with the atmosphere generate extensive air showers (EAS) of secondary particles. The depth corresponding to the maximum development of the shower, X{sub max}, is a well-known observable for determining the nature of the primary cosmic ray which initiated the cascade process. In this paper, we present an empirical model to describe the distribution of X{sub max} for EAS initiated by nuclei, in the energy range from 10{sup 17} eV up to 10{sup 21} eV, and by photons, in the energy range from 10{sup 17} eV up to 10{sup 19.6} eV. Our model adopts the generalized Gumbel distribution motivated by the relationship between the generalized Gumbel statistics and the distribution of the sum of non-identically distributed variables in dissipative stochastic systems. We provide an analytical expression for describing the X{sub max} distribution for photons and for nuclei, and for their first two statistical moments, namely (X{sub max}) and σ{sup 2}(X{sub max}). The impact of the hadronic interaction model is investigated in detail, even in the case of the most up-to-date models accounting for LHC observations. We also briefly discuss the differences with a more classical approach and an application to the experimental data based on information theory.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2017

A moment projection method for population balance dynamics with a shrinkage term

A new method of moments for solving the population balance equation is developed and presented. The moment projection method (MPM) is numerically simple and easy to implement and attempts to address the challenge of particle shrinkage due to processes such as oxidation, evaporation or dissolution. It directly solves the moment transport equation for the moments and tracks the number of the smallest particles using the algorithm by Blumstein and Wheeler (1973) . The performance of the new method is measured against the method of moments (MOM) and the hybrid method of moments (HMOM). The results suggest that MPM performs much better than MOM and HMOM where shrinkage is dominant. The new method predicts mean quantities which are almost as accurate as a high-precision stochastic method calculated using the established direct simulation algorithm (DSA).

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2016

Noise-induced multistability in the regulation of cancer by genes and pseudogenes

We extend a previously introduced model of stochastic gene regulation of cancer to a nonlinear case having both gene and pseudogene messenger RNAs (mRNAs) self-regulated. The model consists of stochastic Boolean genetic elements and possesses noise-induced multistability (multimodality). We obtain analytical expressions for probabilities for the case of constant but finite number of microRNA molecules which act as a noise source for the competing gene and pseudogene mRNAs. The probability distribution functions display both the global bistability regime as well as even-odd number oscillations for a certain range of model parameters. Statistical characteristics of the mRNA’s level fluctuations are evaluated. The obtained results of the extended model advance our understanding of the process of stochastic gene and pseudogene expressions that is crucial in regulation of cancer.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2013

PROBING DYNAMICS OF ELECTRON ACCELERATION WITH RADIO AND X-RAY SPECTROSCOPY, IMAGING, AND TIMING IN THE 2002 APRIL 11 SOLAR FLARE

Based on detailed analysis of radio and X-ray observations of a flare on 2002 April 11 augmented by realistic three-dimensional modeling, we have identified a radio emission component produced directly at the flare acceleration region. This acceleration region radio component has distinctly different (1) spectrum, (2) light curves, (3) spatial location, and, thus, (4) physical parameters from those of the separately identified trapped or precipitating electron components. To derive evolution of physical parameters of the radio sources we apply forward fitting of the radio spectrum time sequence with the gyrosynchrotron source function with five to six free parameters. At the stage when the contribution from the acceleration region dominates the radio spectrum, the X-ray- and radio-derived electron energy spectral indices agree well with each other. During this time the maximum energy of the accelerated electron spectrum displays a monotonic increase with time from {approx}300 keV to {approx}2 MeV over roughly one minute duration indicative of an acceleration process in the form of growth of the power-law tail; the fast electron residence time in the acceleration region is about 2-4 s, which is much longer than the time of flight and so requires a strong diffusion mode there to inhibit free-streaming propagation. The acceleration region has a relatively strong magnetic field, B {approx} 120 G, and a low thermal density, n{sub e} {approx}< 2 Multiplication-Sign 10{sup 9} cm{sup -3}. These acceleration region properties are consistent with a stochastic acceleration mechanism.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2019

Lignin valorization process control under feedstock uncertainty through a dynamic stochastic programming approach

The randomness introduced by reactants is an issue when processing renewable bioresources. In this paper, we apply tools from dynamic stochastic programming theory to the biochemical process. Instead of introducing extra preprocessing units, we consider the inherent randomness of the process and optimize in expectation the performance of the system. In a general setting, this is a multistage stochastic optimization problem and we investigate its approximate solution via two approaches, namely stochastic dual dynamic programming (SDDP) and the finite state, finite action Markov decision process (MDP) framework. These two methods are implemented to a case study of lignin valorization that is crucial to a cost-effective biorefinery process using biomass as the feedstock.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2011

Coupled-Channels Density-Matrix Approach to Low-Energy Nuclear Reaction Dynamics

Atomic nuclei are complex, quantum many-body systems whose structure manifests itself through intrinsic quantum states associated with different excitation modes or degrees of freedom. Collective modes (vibration and/or rotation) dominate at low energy (near the ground-state). The associated states are usually employed, within a truncated model space, as a basis in (coherent) coupled channels approaches to low-energy reaction dynamics. However, excluded states can be essential, and their effects on the open (nuclear) system dynamics are usually treated through complex potentials. Is this a complete description of open system dynamics? Does it include effects of quantum decoherence? Can decoherence be manifested in reaction observables? In this contribution, I discuss these issues and the main ideas of a coupled-channels density-matrix approach that makes it possible to quantify the role and importance of quantum decoherence in low-energy nuclear reaction dynamics. Topical applications, which refer to understanding the astrophysically important collision {sup 12}C+{sup 12}C and achieving a unified quantum dynamical description of relevant reaction processes of weakly-bound nuclei, are highlighted.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2014

Thermal X-ray spectral tools. I. Parameterizing impulsive X-ray heating with a cumulative initial temperature (CIT) distribution

In collisional ionization equilibrium, the X-ray spectrum from a plasma depends on the differential emission measure (DEM), distributed over temperature. Due to the well-known ill conditioning problem, no precisely resolved DEM can be inverted directly from the spectrum, so often only a gross parameterization of the DEM is used to approximate the data, in hopes that the parameterization can provide useful model-independent constraints on the heating process. However, ill conditioning also introduces ambiguity into the various different parameterizations that could approximate the data, which may spoil the perceived advantages of model independence. Thus, this paper instead suggests a single parameterization for both the heating mechanism and the X-ray sources, based on a model of impulsive heating followed by radiative cooling. This approach is similar to a 'cooling flow' approach but allows injection at multiple initial temperatures and applies even when the steady state is a distribution of different shock strengths, as for a standing shock with a range of obliquities, or for embedded stochastic shocks that are only steady in a statistical sense. This produces an alternative parameterization for X-ray spectra that is especially streamlined for higher density plasmas with efficient radiative cooling and minimal thermal conduction and mixing. The method also provides some internal consistency checks on the validity of its assumptions. A heuristic general version is then applied over a wide range of astrophysical applications to schematically explore potential alternative models for these phenomena.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2018

Soil pH mediates the balance between stochastic and deterministic assembly of bacteria

Little is known about the factors affecting the relative influence of stochastic and deterministic processes that governs the assembly of microbial communities in successional soils. Here, we conducted a meta-analysis of bacterial communities using six different successional soils data sets, scattered across different regions, with different pH conditions in early and late successional soils. We found that soil pH was the best predictor of bacterial community assembly and the relative importance of stochastic and deterministic processes along successional soils. Extreme acidic or alkaline pH conditions lead to assembly of phylogenetically more clustered bacterial communities through deterministic processes, whereas pH conditions close to neutral lead to phylogenetically less clustered bacterial communities with more stochasticity. We suggest that the influence of pH, rather than successional age, is the main driving force in producing trends in phylogenetic assembly of bacteria, and that pH also influences the relative balance of stochastic and deterministic processes along successional soils. Given that pH had a much stronger association with community assembly than did successional age, we evaluated whether the inferred influence of pH was maintained when studying globally-distributed samples collected without regard for successional age. This dataset confirmed the strong influence of pH, suggesting that the influence of soil pH on community assembly processes occurs globally. Extreme pH conditions likely exert more stringent limits on survival and fitness, imposing strong selective pressures through ecological and evolutionary time. Taken together, these findings suggest that the degree to which stochastic vs. deterministic processes shape soil bacterial community assembly is a consequence of soil pH rather than successional age.

Tripathi, Binu M.↗
NASA NTRS1995

Visualizing turbulent mixing of gases and particles

A physical model and interactive computer graphics techniques have been developed for the visualization of the basic physical process of stochastic dispersion and mixing from steady-state CFD calculations. The mixing of massless particles and inertial particles is visualized by transforming the vector field from a traditionally Eulerian reference frame into a Lagrangian reference frame. Groups of particles are traced through the vector field for the mean path as well as their statistical dispersion about the mean position by using added scalar information about the root mean square value of the vector field and its Lagrangian time scale. In this way, clouds of particles in a turbulent environment are traced, not just mean paths. In combustion simulations of many industrial processes, good mixing is required to achieve a sufficient degree of combustion efficiency. The ability to visualize this multiphase mixing can not only help identify poor mixing but also explain the mechanism for poor mixing. The information gained from the visualization can be used to improve the overall combustion efficiency in utility boilers or propulsion devices. We have used this technique to visualize steady-state simulations of the combustion performance in several furnace designs.

Ma, Kwan-Liu↗
DOE OSTI2020

Dynamic Performance Enhancement for Nonlinear Stochastic Systems Using RBF Driven Nonlinear Compensation with Extended Kalman Filter

In this paper, a novel hybrid control method is proposed to enhance the control performance of the PI based control system for a class of nonlinear and non-Gaussian stochastic dynamic processes with unmeasurable states. Firstly, to enhance the tracking performance of the PI controller where the PI parameters are fixed in many actual control systems, the compensative signal is formed using the extended Kalman filter(EKF) based state estimator and driven by the radial basis function (RBF) neural network based compensator. In addition, the weights of RBF is trained to minimize the entropy criterion of tracking error as the process is subjected to non-Gaussian disturbances. Meanwhile, since the precise statistical property of noises is hard to obtain for many industrial processes, the kernel density estimation (KDE) technique is employed in this paper to estimate the entropy. The convergence of RBF network is discussed and the stability of the resulted closed-loop hybrid control system is analyzed in mean square sense. Finally, a numerical example and a practical system testing are given to illustrate the effectiveness of the proposed control method.

stochastic systems, PI Controller, Entropy, Extend↗
NASA NTRS2021

Introduction to the Physics of Ionic Conduction in Narrow Biological and Artificial Channels

The permeation of ions through narrow water-filled channels is essential to life and of rapidly-growing importance in technology. Reaching an understanding of the mechanisms underlying the permeation process requires an interdisciplinary approach, where ideas drawn from physics are of particular importance and have brought encouraging progress in recent years. This Introduction sets into context the several ground-breaking papers presented in the Entropy Special Issue on "The Physics of Ionic Conduction in Narrow Biological and Artificial Channels''.

ion channel↗
DOE OSTI2026

X-ray tomography of damage dynamics in advanced materials using a laser wakefield accelerator

Additively manufactured (AM) metals offer the potential for customizable, cost-effective components, but qualification and certification are crucial. Key to this process is understanding pore dynamics under stress, typically analyzed using micro-computed tomography. This study introduces laboratory-scale “betatron” x-rays from laser wakefield acceleration as a high-throughput alternative for x-ray tomography of advanced materials, such as AM AlSi10Mg alloys. Coupled with 3D finite element modeling, this method provides detailed insights into stress-porosity interactions. The approach delivers high-resolution scans, revealing that pore shape and local triaxiality significantly influence fracture dynamics, supporting advanced material characterization. This work also demonstrates the potential and versatility of laser-betatron x-ray μCT for generating large datasets to accelerate our understanding of the stochastic, process-specific nature of pore formation in AM alloys.

Senthilkumaran, Vigneshvar↗
DOE OSTI2013

PULSAR STATE SWITCHING FROM MARKOV TRANSITIONS AND STOCHASTIC RESONANCE

Markov processes are shown to be consistent with metastable states seen in pulsar phenomena, including intensity nulling, pulse-shape mode changes, subpulse drift rates, spin-down rates, and X-ray emission, based on the typically broad and monotonic distributions of state lifetimes. Markovianity implies a nonlinear magnetospheric system in which state changes occur stochastically, corresponding to transitions between local minima in an effective potential. State durations (though not transition times) are thus largely decoupled from the characteristic timescales of various magnetospheric processes. Dyadic states are common but some objects show at least four states with some transitions forbidden. Another case is the long-term intermittent pulsar B1931+24 that has binary radio-emission and torque states with wide, but non-monotonic duration distributions. It also shows a quasi-period of 38 ± 5 days in a 13 yr time sequence, suggesting stochastic resonance in a Markov system with a forcing function that could be strictly periodic or quasi-periodic. Nonlinear phenomena are associated with time-dependent activity in the acceleration region near each magnetic polar cap. The polar-cap diode is altered by feedback from the outer magnetosphere and by return currents from the equatorial region outside the light cylinder that may also cause the neutron star to episodically charge and discharge. Orbital perturbations of a disk or current sheet provide a natural periodicity for the forcing function in the stochastic-resonance interpretation of B1931+24. Disk dynamics may introduce additional timescales in observed phenomena. Future work can test the Markov interpretation, identify which pulsar types have a propensity for state changes, and clarify the role of selection effects.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2015

Ensemble-type numerical uncertainty information from single model integrations

We suggest an algorithm that quantifies the discretization error of time-dependent physical quantities of interest (goals) for numerical models of geophysical fluid dynamics. The goal discretization error is estimated using a sum of weighted local discretization errors. The key feature of our algorithm is that these local discretization errors are interpreted as realizations of a random process. The random process is determined by the model and the flow state. From a class of local error random processes we select a suitable specific random process by integrating the model over a short time interval at different resolutions. The weights of the influences of the local discretization errors on the goal are modeled as goal sensitivities, which are calculated via automatic differentiation. The integration of the weighted realizations of local error random processes yields a posterior ensemble of goal approximations from a single run of the numerical model. From the posterior ensemble we derive the uncertainty information of the goal discretization error. This algorithm bypasses the requirement of detailed knowledge about the models discretization to generate numerical error estimates. The algorithm is evaluated for the spherical shallow-water equations. For two standard test cases we successfully estimate the error of regional potential energy, track its evolution, and compare it to standard ensemble techniques. The posterior ensemble shares linear-error-growth properties with ensembles of multiple model integrations when comparably perturbed. The posterior ensemble numerical error estimates are of comparable size as those of a stochastic physics ensemble.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

A hierarchical stochastic modeling approach for representing point bar geometries and petrophysical property variations

The flow of fluids in point bars is affected by the existence of heterogeneities like shale drapes that are found on the surfaces of inclined heterolithic stratifications. In fact, these shale drapes can act as fluid flow baffles; therefore, developing a framework for modeling point bars and their associated heterogeneities is vital. In this study, a stochastic process-based modeling approach is presented for capturing the main point bar heterogeneities: accretion surfaces (i.e., the aerial heterogeneity) and inclined heterolithic stratifications (i.e., the vertical heterogeneity). The former was modeled using a sine-generation function and the latter, with a sigmoidal function after which they were combined into a 3D point bar model. To ensure proper modeling of petrophysical properties, we developed a more representative gridding scheme which generates curvilinear grids representative of the point bar geometry. This grid was then transformed into a rectilinear grid to allow for geostatistical simulation after which all petrophysical properties were mapped back into the original curvilinear grid. An essential element of this modeling approach is the stochastic representation of shale drapes at the interface between successive accretion surfaces. The workflow was tested using a real field dataset for the Cranfield field, Mississippi. The constructed model was then subjected to a flow simulation study mimicking a CO 2 storage scenario. Various sensitivities were simulated to evaluate the effect of heterogeneities on CO 2 flow within the point-bar. Results demonstrate the importance of representing point-bar related heterogeneity and the spatial distribution of shale drapes on CO 2 plume migration and storage.

58 GEOSCIENCES↗
DOE OSTI2015

PROGNOSIS OF GLEs OF RELATIVISTIC SOLAR PROTONS

Ground level enhancements (GLEs) are relativistic solar particles measured at ground level by the worldwide network of cosmic ray detectors. These sporadic events are associated with solar flares and are assumed to be of a quasi-random nature. Studying them gives information about their source and propagation processes, the maximum capacity of the Sun as a particle accelerator engine, the magnetic structure of the medium traversed, etc. Space vehicles, as well as electric transformers and gas pipes at high latitudes may be damaged by this kind of radiation. As a result, their prediction has turned out to be very important, but because of their random occurrence, up to now few efforts toward this goal have been made. The results of these efforts have been limited to possible warnings in real time, just before a GLE occurrence, but no specific dates have been predicted well enough in advance to prevent possible hazards. In this study we show that, in spite of the quasi-stochastic nature of GLEs, it is possible to predict them with relative precision, even for future solar cycles. Additionally, a previous study establishing synchronization among some periodicities of several layers of solar atmosphere argues against the full randomness of the phenomenon of relativistic particle production. Therefore, by means of wavelet spectral analysis combined with fuzzy logic tools, we reproduce previous known GLE events and present results for future events. The next GLE is expected to occur in the first semester of 2016.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1994

Statistical mechanics in biology: how ubiquitous are long-range correlations?

The purpose of this opening talk is to describe examples of recent progress in applying statistical mechanics to biological systems. We first briefly review several biological systems, and then focus on the fractal features characterized by the long-range correlations found recently in DNA sequences containing non-coding material. We discuss the evidence supporting the finding that for sequences containing only coding regions, there are no long-range correlations. We also discuss the recent finding that the exponent alpha characterizing the long-range correlations increases with evolution, and we discuss two related models, the insertion model and the insertion-deletion model, that may account for the presence of long-range correlations. Finally, we summarize the analysis of long-term data on human heartbeats (up to 10(4) heart beats) that supports the possibility that the successive increments in the cardiac beat-to-beat intervals of healthy subjects display scale-invariant, long-range "anti-correlations" (a tendency to beat faster is balanced by a tendency to beat slower later on). In contrast, for a group of subjects with severe heart disease, long-range correlations vanish. This finding suggests that the classical theory of homeostasis, according to which stable physiological processes seek to maintain "constancy," should be extended to account for this type of dynamical, far from equilibrium, behavior.

Non-NASA Center↗
DOE OSTI2012

INTERCHANGE RECONNECTION IN A TURBULENT CORONA

Magnetic reconnection at the interface between coronal holes and loops, the so-called interchange reconnection, can release the hotter, denser plasma from magnetically confined regions into the heliosphere, contributing to the formation of the highly variable slow solar wind. The interchange process is often thought to develop at the apex of streamers or pseudo-streamers, near Y- and X-type neutral points, but slow streams with loop composition have been recently observed along fanlike open field lines adjacent to closed regions, far from the apex. However, coronal heating models, with magnetic field lines shuffled by convective motions, show that reconnection can occur continuously in unipolar magnetic field regions with no neutral points: photospheric motions induce a magnetohydrodynamic turbulent cascade in the coronal field that creates the necessary small scales, where a sheared magnetic field component orthogonal to the strong axial field is created locally and can reconnect. We propose that a similar mechanism operates near and around boundaries between open and closed regions inducing a continual stochastic rearrangement of connectivity. We examine a reduced magnetohydrodynamic model of a simplified interface region between open and closed corona threaded by a strong unipolar magnetic field. This boundary is not stationary, becomes fractal, and field lines change connectivity continuously, becoming alternatively open and closed. This model suggests that slow wind may originate everywhere along loop-coronal-hole boundary regions and can account naturally and simply for outflows at and adjacent to such boundaries and for the observed diffusion of slow wind around the heliospheric current sheet.

79 ASTRONOMY AND ASTROPHYSICS↗