Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “stochastic processes”

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.

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

At least 1,117 records · Page 62
All sourcesNASA NTRSDOE OSTI
DOE OSTI2014

Reversible order-disorder related band gap changes in Cu{sub 2}ZnSn(S,Se){sub 4} via post-annealing of solar cells measured by electroreflectance

We report on order–disorder related band gap changes in Cu{sub 2}ZnSn(S,Se){sub 4} solar cells which are induced by post-annealing. The band gap changes of the absorber are detected utilizing electroreflectance and analyzed by comparison with predictions of the stochastic Vineyard model. This yields a critical temperature of T{sub C}=195 °C above which the Cu{sub 2}ZnSn(S,Se){sub 4} absorber layer is entirely disordered within the Cu–Zn layers of the kesterite unit cell. The temporal evolution of the band gap during annealing shows that the equilibrium value is reached on a timescale in the order of hours, depending on the annealing temperature. In contrast to other experimental techniques, electroreflectance precisely measures the band gap and is not influenced by defect-mediated radiative recombination.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2015

Fixed-node diffusion Monte Carlo potential energy curve of the fluorine molecule F{sub 2} using selected configuration interaction trial wavefunctions

The potential energy curve of the F{sub 2} molecule is calculated with Fixed-Node Diffusion Monte Carlo (FN-DMC) using Configuration Interaction (CI)-type trial wavefunctions. To keep the number of determinants reasonable and thus make FN-DMC calculations feasible in practice, the CI expansion is restricted to those determinants that contribute the most to the total energy. The selection of the determinants is made using the CIPSI approach (Configuration Interaction using a Perturbative Selection made Iteratively). The trial wavefunction used in FN-DMC is directly issued from the deterministic CI program; no Jastrow factor is used and no preliminary multi-parameter stochastic optimization of the trial wavefunction is performed. The nodes of CIPSI wavefunctions are found to reduce significantly the fixed-node error and to be systematically improved upon increasing the number of selected determinants. To reduce the non-parallelism error of the potential energy curve, a scheme based on the use of a R-dependent number of determinants is introduced. Using Dunning’s cc-pVDZ basis set, the FN-DMC energy curve of F{sub 2} is found to be of a quality similar to that obtained with full configuration interaction/cc-pVQZ.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2015

Model for temperature-dependent magnetization of nanocrystalline materials

A magnetization model of nanocrystalline materials incorporating intragrain anisotropies, intergrain interactions, and texture effects has been extended to include the thermal fluctuations. The method relies on the stochastic Landau–Lifshitz–Gilbert theory of magnetization dynamics and permits to study the magnetic properties of nanocrystalline materials at arbitrary temperature below the Currie temperature. The model has been used to determine the intergrain exchange constant and grain boundary anisotropy constant of nanocrystalline Ni at 100 K and 298 K. It is found that the thermal fluctuations suppress the strength of the intergrain exchange coupling and also reduce the grain boundary anisotropy. In comparison with its value at 2 K, the interparticle exchange constant decreases by 16% and 42% and the grain boundary anisotropy constant decreases by 28% and 40% at 100 K and 298 K, respectively. An application of the model to study the grain size-dependent magnetization indicates that when the thermal activation energy is comparable to the free energy of grains, the decrease in the grain size leads to the decrease in the magnetic permeability and saturation magnetization. The mechanism by which the grain size influences the magnetic properties of nc–Ni is discussed.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2015

Sublinear scaling for time-dependent stochastic density functional theory

A stochastic approach to time-dependent density functional theory is developed for computing the absorption cross section and the random phase approximation (RPA) correlation energy. The core idea of the approach involves time-propagation of a small set of stochastic orbitals which are first projected on the occupied space and then propagated in time according to the time-dependent Kohn-Sham equations. The evolving electron density is exactly represented when the number of random orbitals is infinite, but even a small number (≈16) of such orbitals is enough to obtain meaningful results for absorption spectrum and the RPA correlation energy per electron. We implement the approach for silicon nanocrystals using real-space grids and find that the overall scaling of the algorithm is sublinear with computational time and memory.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2015

Gradient flow of the stochastic relaxation on a generic exponential family

We study the natural gradient flow of the expected value E{sub p} [f] of an objective function f for p in an exponential family. We parameterize the exponential family with the expectation parameters and we show that the dynamical system associated to the natural gradient flow can be extended outside the marginal polytope.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2015

Energy in density gradient

Inhomogeneous plasmas and fluids contain energy stored in inhomogeneity and they naturally tend to relax into lower energy states by developing instabilities or by diffusion. But the actual amount of energy in such inhomogeneities has remained unknown. In the present work, the amount of energy stored in a density gradient is calculated for several specific density profiles in a cylindrical configuration. This is of practical importance for drift wave instability in various plasmas, and, in particular, in its application in models dealing with the heating of solar corona because the instability is accompanied with stochastic heating, so the energy contained in inhomogeneity is effectively transformed into heat. It is shown that even for a rather moderate increase of the density at the axis in magnetic structures in the corona by a factor 1.5 or 3, the amount of excess energy per unit volume stored in such a density gradient becomes several orders of magnitude greater than the amount of total energy losses per unit volume (per second) in quiet regions in the corona. Consequently, within the life-time of a magnetic structure such energy losses can easily be compensated by the stochastic drift wave heating.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2015

Theoretical analysis of selectivity mechanisms in molecular transport through channels and nanopores

Selectivity is one of the most fundamental concepts in natural sciences, and it is also critically important in various technological, industrial, and medical applications. Although there are many experimental methods that allow to separate molecules, frequently they are expensive and not efficient. Recently, a new method of separation of chemical mixtures based on utilization of channels and nanopores has been proposed and successfully tested in several systems. However, mechanisms of selectivity in the molecular transport during the translocation are still not well understood. Here, we develop a simple theoretical approach to explain the origin of selectivity in molecular fluxes through channels. Our method utilizes discrete-state stochastic models that take into account all relevant chemical transitions and can be solved analytically. More specifically, we analyze channels with one and two binding sites employed for separating mixtures of two types of molecules. The effects of the symmetry and the strength of the molecular-pore interactions are examined. It is found that for one-site binding channels, the differences in the strength of interactions for two species drive the separation. At the same time, in more realistic two-site systems, the symmetry of interaction potential becomes also important. The most efficient separation is predicted when the specific binding site is located near the entrance to the nanopore. In addition, the selectivity is higher for large entrance rates into the channel. It is also found that the molecular transport is more selective for repulsive interactions than for attractive interactions. The physical-chemical origin of the observed phenomena is discussed.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2015

Effects of forcing time scale on the simulated turbulent flows and turbulent collision statistics of inertial particles

In this paper, we study systematically the effects of forcing time scale in the large-scale stochastic forcing scheme of Eswaran and Pope [“An examination of forcing in direct numerical simulations of turbulence,” Comput. Fluids 16, 257 (1988)] on the simulated flow structures and statistics of forced turbulence. Using direct numerical simulations, we find that the forcing time scale affects the flow dissipation rate and flow Reynolds number. Other flow statistics can be predicted using the altered flow dissipation rate and flow Reynolds number, except when the forcing time scale is made unrealistically large to yield a Taylor microscale flow Reynolds number of 30 and less. We then study the effects of forcing time scale on the kinematic collision statistics of inertial particles. We show that the radial distribution function and the radial relative velocity may depend on the forcing time scale when it becomes comparable to the eddy turnover time. This dependence, however, can be largely explained in terms of altered flow Reynolds number and the changing range of flow length scales present in the turbulent flow. We argue that removing this dependence is important when studying the Reynolds number dependence of the turbulent collision statistics. The results are also compared to those based on a deterministic forcing scheme to better understand the role of large-scale forcing, relative to that of the small-scale turbulence, on turbulent collision of inertial particles. To further elucidate the correlation between the altered flow structures and dynamics of inertial particles, a conditional analysis has been performed, showing that the regions of higher collision rate of inertial particles are well correlated with the regions of lower vorticity. Regions of higher concentration of pairs at contact are found to be highly correlated with the region of high energy dissipation rate.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2015

Endogenous field feedback promotes the detectability for exogenous electric signal in the hybrid coupled population

This paper presents the endogenous electric field in chemical or electrical synaptic coupled networks, aiming to study the role of endogenous field feedback in the signal propagation in neural systems. It shows that the feedback of endogenous fields to network activities can reduce the required energy of the noise and enhance the transmission of input signals in hybrid coupled populations. As a common and important nonsynaptic interactive method among neurons, particularly, the endogenous filed feedback can not only promote the detectability of exogenous weak signal in hybrid coupled neural population but also enhance the robustness of the detectability against noise. Furthermore, with the increasing of field coupling strengths, the endogenous field feedback is conductive to the stochastic resonance by facilitating the transition of cluster activities from the no spiking to spiking regions. Distinct from synaptic coupling, the endogenous field feedback can play a role as internal driving force to boost the population activities, which is similar to the noise. Thus, it can help to transmit exogenous weak signals within the network in the absence of noise drive via the stochastic-like resonance.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2015

The Sharma-Parthasarathy stochastic two-body problem

We study the Sharma-Parthasarathy stochastic two-body problem introduced by Sharma and Parthasarathy in [“Dynamics of a stochastically perturbed two-body problem,” Proc. R. Soc. A 463, 979-1003 (2007)]. In particular, we focus on the preservation of some fundamental features of the classical two-body problem like the Hamiltonian structure and first integrals in the stochastic case. Numerical simulations are performed which illustrate the dynamical behaviour of the osculating elements as the semi-major axis, the eccentricity, and the pericenter. We also derive a stochastic version of Gauss’s equations in the planar case.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2015

Noise-induced bifurcations in magnetization dynamics of uniaxial nanomagnets

Stochastic magnetization dynamics in uniformly magnetized nanomagnets is considered. The system is assumed to have rotational symmetry as the anisotropy axis, the applied field, and the spin polarization are all aligned along an axis of symmetry. By appropriate integration of the Fokker-Planck equation associated to the problem, the stochastic differential equation governing the evolution of the angle between the magnetization orientation and the symmetry axis is derived. The drift terms present in this equation contain a noise-induced drift term, which, in combination with drift terms of deterministic origin, can be written as the derivative of an effective potential. Superparamagnetic-like transitions are studied in connections with the bifurcations of the effective potential as temperature and excitation conditions are varied.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2015

Stochastic linear multistep methods for the simulation of chemical kinetics

In this paper, we introduce the Stochastic Adams-Bashforth (SAB) and Stochastic Adams-Moulton (SAM) methods as an extension of the τ-leaping framework to past information. Using the Θ-trapezoidal τ-leap method of weak order two as a starting procedure, we show that the k-step SAB method with k ≥ 3 is order three in the mean and correlation, while a predictor-corrector implementation of the SAM method is weak order three in the mean but only order one in the correlation. These convergence results have been derived analytically for linear problems and successfully tested numerically for both linear and non-linear systems. A series of additional examples have been implemented in order to demonstrate the efficacy of this approach.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2015

Tipping point analysis of atmospheric oxygen concentration

We apply tipping point analysis to nine observational oxygen concentration records around the globe, analyse their dynamics and perform projections under possible future scenarios, leading to oxygen deficiency in the atmosphere. The analysis is based on statistical physics framework with stochastic modelling, where we represent the observed data as a composition of deterministic and stochastic components estimated from the observed data using Bayesian and wavelet techniques.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2014

Quadratic partial eigenvalue assignment in large-scale stochastic dynamic systems for resilient and economic design

Failure of structural systems under dynamic loading can be prevented via active vibration control which shifts the damped natural frequencies of the systems away from the dominant range of loading spectrum. The damped natural frequencies and the dynamic load typically show significant variations in practice. A computationally efficient methodology based on quadratic partial eigenvalue assignment technique and optimization under uncertainty has been formulated in the present work that will rigorously account for these variations and result in an economic and resilient design of structures. A novel scheme based on hierarchical clustering and importance sampling is also developed in this work for accurate and efficient estimation of probability of failure to guarantee the desired resilience level of the designed system. Numerical examples are presented to illustrate the proposed methodology.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2015

Stochastic generation of hourly rainstorm events in Johor

Engineers and researchers in water-related studies are often faced with the problem of having insufficient and long rainfall record. Practical and effective methods must be developed to generate unavailable data from limited available data. Therefore, this paper presents a Monte-Carlo based stochastic hourly rainfall generation model to complement the unavailable data. The Monte Carlo simulation used in this study is based on the best fit of storm characteristics. Hence, by using the Maximum Likelihood Estimation (MLE) and Anderson Darling goodness-of-fit test, lognormal appeared to be the best rainfall distribution. Therefore, the Monte Carlo simulation based on lognormal distribution was used in the study. The proposed model was verified by comparing the statistical moments of rainstorm characteristics from the combination of the observed rainstorm events under 10 years and simulated rainstorm events under 30 years of rainfall records with those under the entire 40 years of observed rainfall data based on the hourly rainfall data at the station J1 in Johor over the period of 1972–2011. The absolute percentage error of the duration-depth, duration-inter-event time and depth-inter-event time will be used as the accuracy test. The results showed the first four product-moments of the observed rainstorm characteristics were close with the simulated rainstorm characteristics. The proposed model can be used as a basis to derive rainfall intensity-duration frequency in Johor.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2015

Stochastic modeling for river pollution of Sungai Perlis

River pollution has been recognized as a contributor to a wide range of health problems and disorders in human. It can pose health dangers to humans who come into contact with it, either directly or indirectly. Therefore, it is most important to measure the concentration of Biochemical Oxygen Demand (BOD) as a water quality parameter since the parameter has long been the basic means for determining the degree of water pollution in rivers. In this study, BOD is used as a parameter to estimate the water quality at Sungai Perlis. It has been observed that Sungai Perlis is polluted due to lack of management and improper use of resources. Therefore, it is of importance to model the Sungai Perlis water quality in order to describe and predict the water quality systems. The BOD concentration secondary data set is used which was extracted from the Drainage and Irrigation Department Perlis State website. The first order differential equation from Streeter – Phelps model was utilized as a deterministic model. Then, the model was developed into a stochastic model. Results from this study shows that the stochastic model is more adequate to describe and predict the BOD concentration and the water quality systems in Sungai Perlis by having smaller value of mean squared error (MSE)

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2015

Gompertzian stochastic model with delay effect to cervical cancer growth

In this paper, a Gompertzian stochastic model with time delay is introduced to describe the cervical cancer growth. The parameters values of the mathematical model are estimated via Levenberg-Marquardt optimization method of non-linear least squares. We apply Milstein scheme for solving the stochastic model numerically. The efficiency of mathematical model is measured by comparing the simulated result and the clinical data of cervical cancer growth. Low values of Mean-Square Error (MSE) of Gompertzian stochastic model with delay effect indicate good fits.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

Geometric quadratic stochastic operator on countable infinite set

In this paper we construct the family of Geometric quadratic stochastic operators defined on the countable sample space of nonnegative integers and investigate their trajectory behavior. Such operators can be reinterpreted in terms of of evolutionary operator of free population. We show that Geometric quadratic stochastic operators are regular transformations.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗