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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

Turning statistical physics models into materials design engines

Despite the success statistical physics has enjoyed at predicting the properties of materials for given parameters, the inverse problem, identifying which material parameters produce given, desired properties, is only beginning to be addressed. Recently, several methods have emerged across disciplines that draw upon optimization and simulation to create computer programs that tailor material responses to specified behaviors. However, so far the methods developed either involve black-box techniques, in which the optimizer operates without explicit knowledge of the material's configuration space, or require carefully tuned algorithms with applicability limited to a narrow subclass of materials. Here we introduce a formalism that can generate optimizers automatically by extending statistical mechanics into the realm of design. The strength of this approach lies in its capability to transform statistical models that describe materials into optimizers to tailor them. Here, by comparing against standard black-box optimization methods, we demonstrate how optimizers generated by this formalism can be faster and more effective, while remaining straightforward to implement. The scope of our approach includes possibilities for solving a variety of complex optimization and design problems concerning materials both in and out of equilibrium.

36 MATERIALS SCIENCE↗
DOE OSTI2016

Statistical physics of multicomponent alloys using KKR-CPA

We apply variational principles from statistical physics and the Landau theory of phase transitions to multicomponent alloys using the multiple-scattering theory of Korringa-Kohn-Rostoker (KKR) and the coherent potential approximation (CPA). This theory is a multicomponent generalization of the S( 2 ) theory of binary alloys developed by G. M. Stocks, J. B. Staunton, D. D. Johnson and others. It is highly relevant to the chemical phase stability of high-entropy alloys as it predicts the kind and size of finite-temperature chemical fluctuations. In doing so it includes effects of rearranging charge and other electronics due to changing site occupancies. When chemical fluctuations grow without bound an absolute instability occurs and a second-order order-disorder phase transition may be inferred. The S( 2 ) theory is predicated on the fluctuation-dissipation theorem; thus we derive the linear response of the CPA medium to perturbations in site-dependent chemical potentials in great detail. The theory lends itself to a natural interpretation in terms of competing effects: entropy driving disorder and favorable pair interactions driving atomic ordering. Moreover, to further clarify interpretation we present results for representative ternary alloys CuAgAu, NiPdPt, RhPdAg, and CoNiCu within a frozen charge (or band-only) approximation. These results include the so-called Onsager mean field correction that extends the temperature range for which the theory is valid.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Stochastic Spatial Models in Ecology: A Statistical Physics Approach

Ecosystems display a complex spatial organization. Ecologists have long tried to characterize them by looking at how different measures of biodiversity change across spatial scales. Ecological neutral theory has provided simple predictions accounting for general empirical patterns in communities of competing species. However, while neutral theory in well-mixed ecosystems is mathematically well understood, spatial models still present several open problems, limiting the quantitative understanding of spatial biodiversity. In this review, we discuss the state of the art in spatial neutral theory. We emphasize the connection between spatial ecological models and the physics of non-equilibrium phase transitions and how concepts developed in statistical physics translate in population dynamics, and vice versa. We focus on non-trivial scaling laws arising at the critical dimension D=2 of spatial neutral models, and their relevance for biological populations inhabiting two-dimensional environments. We conclude by discussing models incorporating non-neutral effects in the form of spatial and temporal disorder, and analyze how their predictions deviate from those of purely neutral theories.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

A Bayesian Approach for Statistical–Physical Bulk Parameterization of Rain Microphysics. Part I: Scheme Description

A novel framework is proposed for the bulk parameterization of rain microphysics: the Bayesian Observationally Constrained Statistical–Physical Scheme (BOSS). It is designed to facilitate direct constraint by observations using Bayesian inference. BOSS combines existing process-level microphysical knowledge with flexible process rate formulations and parameters constrained by observations within a Bayesian framework. Furthermore, using a raindrop size distribution (DSD) normalization method that relates DSD moments to one another via generalized power series, generalized multivariate power expressions are derived for the microphysical process rates as functions of a set of prognostic DSD moments. The scheme is flexible and can utilize any number and combination of prognostic moments and any number of terms in the process rate formulations. This means that both uncertainty in parameter values and structural uncertainty associated with the process rate formulations can be investigated systematically, which is not possible using traditional schemes. In this paper, BOSS is compared to two- and three-moment versions of a traditional bulk rain microphysics scheme (denoted as MORR). It is demonstrated that some process formulations in MORR are analytically equivalent to the generalized power expressions in BOSS using one or two terms, while others are not. BOSS is able to replicate the behavior of MORR in idealized one-dimensional rainshaft tests, but with a much more flexible and systematic design. Part II of this study describes the application of BOSS to derive rain microphysical process rates and posterior parameter distributions in Bayesian experiments using Markov chain Monte Carlo sampling constrained by synthetic observations.

58 GEOSCIENCES↗
DOE OSTI2020

A Bayesian Approach for Statistical–Physical Bulk Parameterization of Rain Microphysics. Part II: Idealized Markov Chain Monte Carlo Experiments

Observationally informed development of a new framework for bulk rain microphysics, the Bayesian Observationally Constrained Statistical–Physical Scheme (BOSS; described in Part I of this study), is demonstrated. This scheme’s development is motivated by large uncertainties in cloud and weather simulations associated with approximations and assumptions in existing microphysics schemes. Here, a proof-of-concept study is introduced using a Markov chain Monte Carlo sampling algorithm with BOSS to probabilistically estimate microphysical process rates and parameters directly from a set of synthetically generated rain observations. The framework utilized is an idealized steady-state one-dimensional column rainshaft model with specified column-top rain properties and a fixed thermodynamical profile. Different configurations of BOSS—flexibility being a key feature of this approach—are constrained via synthetic observations generated from a traditional three-moment bulk microphysics scheme. The ability to retrieve correct parameter values when the true parameter values are known is illustrated. For cases when there is no set of true parameter values, the accuracy of configurations of BOSS that have different levels of complexity is compared. It is found that addition of the sixth moment as a prognostic variable improves prediction of the third moment (proportional to bulk rain mass) and rain rate. In contrast, increasing process rate formulation complexity by adding more power terms has little benefit—a result that is explained using further-idealized experiments. BOSS rainshaft simulations are shown to well estimate the true process rates from constraint by bulk rain observations, with the further benefit of rigorously quantified uncertainty of these estimates.

58 GEOSCIENCES↗
DOE OSTI2017

Ensemble of Thermostatically Controlled Loads: Statistical Physics Approach

Thermostatically Controlled Loads (TCL), e.g. air-conditioners and heaters, are by far the most wide-spread consumers of electricity. Normally the devices are calibrated to provide the so-called bang-bang control of temperature - changing from on to off , and vice versa, depending on temperature. Aggregation of a large group of similar devices into a statistical ensemble is considered, where the devices operate following the same dynamics subject to stochastic perturbations and randomized, Poisson on/off switching policy. We analyze, using theoretical and computational tools of statistical physics, how the ensemble relaxes to a stationary distribution and establish relation between the re- laxation and statistics of the probability flux, associated with devices' cycling in the mixed (discrete, switch on/off , and continuous, temperature) phase space. This allowed us to derive and analyze spec- trum of the non-equilibrium (detailed balance broken) statistical system. and uncover how switching policy affects oscillatory trend and speed of the relaxation. Relaxation of the ensemble is of a practical interest because it describes how the ensemble recovers from significant perturbations, e.g. forceful temporary switching o aimed at utilizing flexibility of the ensemble in providing "demand response" services relieving consumption temporarily to balance larger power grid. We discuss how the statistical analysis can guide further development of the emerging demand response technology.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2017

Ensemble of Thermostatically Controlled Loads: Statistical Physics Approach

Thermostatically controlled loads, e.g., air conditioners and heaters, are by far the most widespread consumers of electricity. Normally the devices are calibrated to provide the so-called bang-bang control – changing from on to off, and vice versa, depending on temperature. We considered aggregation of a large group of similar devices into a statistical ensemble, where the devices operate following the same dynamics, subject to stochastic perturbations and randomized, Poisson on/off switching policy. Using theoretical and computational tools of statistical physics, we analyzed how the ensemble relaxes to a stationary distribution and established a relationship between the relaxation and the statistics of the probability flux associated with devices’ cycling in the mixed (discrete, switch on/off, and continuous temperature) phase space. This allowed us to derive the spectrum of the non-equilibrium (detailed balance broken) statistical system and uncover how switching policy affects oscillatory trends and the speed of the relaxation. Relaxation of the ensemble is of practical interest because it describes how the ensemble recovers from significant perturbations, e.g., forced temporary switching off aimed at utilizing the flexibility of the ensemble to provide “demand response” services to change consumption temporarily to balance a larger power grid. We discuss how the statistical analysis can guide further development of the emerging demand response technology.

Science & Technology - Other Topics↗
DOE OSTI2018

Statistical Physics Approach to Thermophoresis of Colloids

Brownian colloidal particles dispersed in a fluid with a temperature gradient experience a driving force which produces a large biased steady density profile. This phenomenon, named thermophoresis, is quantified by the Soret coefficient S{sub T}. This problem is studied here within the Fokker–Planck formalism. Using the experimental observation of S{sub T} it is possible to extract relevant analytical information about a temperature dependent nonequilibrium effective potential which can produce the thermophoresis force. It will be presented here a statistical physics derivation of this effective potential in terms of some physical parameters. Experimental data are analyzed within this theoretical scenario.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2016

GPU Acceleration of the Locally Selfconsistent Multiple Scattering Code for First Principles Calculation of the Ground State and Statistical Physics of Materials

The Locally Self-consistent Multiple Scattering (LSMS) code solves the first principles Density Functional theory Kohn-Sham equation for a wide range of materials with a special focus on metals, alloys and metallic nano-structures. It has traditionally exhibited near perfect scalability on massively parallel high performance computer architectures. We present our efforts to exploit GPUs to accelerate the LSMS code to enable first principles calculations of O(100,000) atoms and statistical physics sampling of finite temperature properties. Using the Cray XK7 system Titan at the Oak Ridge Leadership Computing Facility we achieve a sustained performance of 14.5PFlop/s and a speedup of 8.6 compared to the CPU only code.

Eisenbach, Markus↗
DOE OSTI2016

GPU acceleration of the Locally Selfconsistent Multiple Scattering code for first principles calculation of the ground state and statistical physics of materials

The Locally Self-consistent Multiple Scattering (LSMS) code solves the first principles Density Functional theory Kohn–Sham equation for a wide range of materials with a special focus on metals, alloys and metallic nano-structures. It has traditionally exhibited near perfect scalability on massively parallel high performance computer architectures. In this paper, we present our efforts to exploit GPUs to accelerate the LSMS code to enable first principles calculations of O(100,000) atoms and statistical physics sampling of finite temperature properties. We reimplement the scattering matrix calculation for GPUs with a block matrix inversion algorithm that only uses accelerator memory. Finally, using the Cray XK7 system Titan at the Oak Ridge Leadership Computing Facility we achieve a sustained performance of 14.5PFlop/s and a speedup of 8.6 compared to the CPU only code.

36 MATERIALS SCIENCE↗
DOE OSTI2015

Resistive switching phenomena: A review of statistical physics approaches

Here we report that resistive switching (RS) phenomena are reversible changes in the metastable resistance state induced by external electric fields. After discovery ~50 years ago, RS phenomena have attracted great attention due to their potential application in next-generation electrical devices. Considerable research has been performed to understand the physical mechanisms of RS and explore the feasibility and limits of such devices. There have also been several reviews on RS that attempt to explain the microscopic origins of how regions that were originally insulators can change into conductors. However, little attention has been paid to the most important factor in determining resistance: how conducting local regions are interconnected. Here, we provide an overview of the underlying physics behind connectivity changes in highly conductive regions under an electric field. We first classify RS phenomena according to their characteristic current–voltage curves: unipolar, bipolar, and threshold switchings. Second, we outline the microscopic origins of RS in oxides, focusing on the roles of oxygen vacancies: the effect of concentration, the mechanisms of channel formation and rupture, and the driving forces of oxygen vacancies. Third, we review RS studies from the perspective of statistical physics to understand connectivity change in RS phenomena. We discuss percolation model approaches and the theory for the scaling behaviors of numerous transport properties observed in RS. Fourth, we review various switching-type conversion phenomena in RS: bipolar-unipolar, memory-threshold, figure-of-eight, and counter-figure-of-eight conversions. Finally, we review several related technological issues, such as improvement in high resistance fluctuations, sneak-path problems, and multilevel switching problems.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Memristive networks: From graph theory to statistical physics

In this work, we provide an introduction to a very specific toy model of memristive networks, for which an exact differential equation for the internal memory which contains the Kirchhoff laws is known. In particular, we highlight how the circuit topology enters the dynamics via an analysis of directed graph. We try to highlight in particular the connection between the asymptotic states of memristors and the Ising model, and the relation to the dynamics and statics of disordered systems.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2013

Statistical physics of black holes as quantum-mechanical systems

Some basic features of black-hole statistical mechanics are investigated, assuming that black holes respect the principles of quantum mechanics. Care is needed in defining an entropy S bh corresponding to the number of microstates of a black hole, given that the black hole interacts with its surroundings. An open question is then the relationship between this entropy and the Bekenstein-Hawking entropy S BH . For a wide class of models with interactions needed to ensure unitary quantum evolution, these interactions produce extra energy flux beyond that predicted by Hawking. Arguments are then presented that this results in an entropy S bh that is smaller than S BH . Correspondingly, in such scenarios equilibrium properties of black holes are modified. In this work, we examine questions of consistency of such an inequality; if it is not consistent, that provides significant constraints on models for quantum-mechanical black hole evolution.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Cosmic Reionization on Computers: Statistics, Physical Properties, and Environments of Lyman Limit Systems at z ~ 6

Lyman limit systems (LLSs) are dense hydrogen clouds with high enough H i column densities to absorb Lyman continuum photons emitted from distant quasars. Their high column densities imply an origin in dense environments; however, the statistics and distribution of LLSs at high redshifts still remain uncertain. In this paper, we use self-consistent radiative transfer cosmological simulations from the Cosmic Reionization on Computers (CROC) project to study the physical properties of LLSs at the tail end of cosmic reionization at z ~ 6. We generate 3000 synthetic quasar sight lines to obtain a large number of LLS samples in the simulations. In addition, with the high physical fidelity and resolution of CROC, we are able to quantify the association between these LLS samples and nearby galaxies. Our results show that the fraction of LLSs spatially associated with nearby galaxies increases with H i column density. Moreover, we find that LLSs that are not near any galaxy typically reside in filamentary structures connecting neighboring galaxies in the intergalactic medium (IGM). This quantification of the distribution and association of LLSs to large-scale structure informs our understanding of the IGM–galaxy connection during the "Epoch of Reionization," and provides a theoretical basis for interpreting future observations.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2015

Collaborative Research. Damage and Burst Dynamics in Failure of Complex Geomaterials. A Statistical Physics Approach to Understanding the Complex Emergent Dynamics in Near Mean-Field Geological Materials

We have carried out research to determine the dynamics of failure in complex geomaterials, specifically focusing on the role of defects, damage and asperities in the catastrophic failure processes (now popularly termed “Black Swan events”). We have examined fracture branching and flow processes using models for invasion percolation, focusing particularly on the dynamics of bursts in the branching process. We have achieved a fundamental understanding of the dynamics of nucleation in complex geomaterials, specifically in the presence of inhomogeneous structures.

58 GEOSCIENCES↗
DOE OSTI2014

Exploring new frontiers in statistical physics with a new, parallel Wang-Landau framework

Combining traditional Wang Landau sampling for multiple replica systems with an exchange of densities of states between replicas we describe a general framework for simulations on massively parallel Petaflop supercomputers. The advantages and general applicability of the method for simulations of complex systems are demonstrated for the classical 2D Potts spin model featuring a strong first-order transition and the self-assembly of lipid bilayers in amphiphilic solutions in a continuous model.

Vogel, Thomas↗