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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 595 records · Page 33
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Generative Ensemble Regression: Learning Particle Dynamics from Observations of Ensembles with Physics-informed Deep Generative Models

Here, we propose a new method for inferring the governing stochastic ordinary differential equations (SODEs) by observing particle ensembles at discrete and sparse time instants, i.e., multiple “snapshots.” Particle coordinates at a single time instant, possibly noisy or truncated, are recorded in each snapshot but are unpaired across the snapshots. By training a physics-informed generative model that generates “fake” sample paths, we aim to fit the observed particle ensemble distributions with a curve in the probability measure space, which is induced from the inferred particle dynamics. We employ different metrics to quantify the differences between distributions, e.g., the sliced Wasserstein distances and the adversarial losses in generative adversarial networks. We refer to this method as generative “ensemble-regression” (GER), in analogy to the classic “point-regression,” where we infer the dynamics by performing regression in the Euclidean space. We illustrate the GER by learning the drift and diffusion terms of particle ensembles governed by SODEs with Brownian motions and Lévy processes up to 100 dimensions. We also discuss how to treat cases with noisy or truncated observations. Apart from systems consisting of independent particles, we also tackle nonlocal interacting particle systems with unknown interaction potential parameters by constructing a physics-informed loss function. Finally, we investigate scenarios of paired observations and discuss how to reduce the dimensionality in such cases by proving a convergence theorem that provides theoretical support.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Collisional broadening of nonlinear resonant wave-particle interactions

A general procedure for understanding plasma behavior when resonant wave-particle interactions are the sole destabilizing and transport mechanism or only heating and/or current drive source is highlighted without recourse to involved numerical or analytical treatments. These phenomena are characterized by transport that appears to be collisionless even though collisions play a central role in narrow collisional boundary layers. The order of magnitude estimates, which include nonlinear effects, are shown to provide expressions in agreement with the principle results of recent toroidal Alfvén eigenmode (TAE), toroidal magnetic field ripple, and heating and current drive treatments. More importantly, the retention of nonlinearities leads to new estimates of the alpha particle energy diffusivity at saturation for TAE modes, and the ripple threshold at which superbanana plateau evaluations of alpha particle transport are modified by nonlinear radial drift effects. In addition, the estimates indicate when quasilinear descriptions for heating and current drive will begin to fail. The phenomenological procedure demonstrates that in magnetic fusion relevant plasmas narrow collisional boundary layers must be retained for resonant wave-particle interactions as they enhance the role of collisions, and make stochastic particle motion unlikely to be more important than other nonlinear process.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2016

Capture zone area distributions for nucleation and growth of islands during submonolayer deposition

A fundamental evolution equation is developed to describe the distribution of areas of capture zones (CZs) associated with islands formed by homogeneous nucleation and growth during submonolayer deposition on perfect flat surfaces. This equation involves various quantities which characterize subtle spatial aspects of the nucleation process. These quantities in turn depend on the complex stochastic geometry of the CZ tessellation of the surface, and their detailed form determines the CZ area distribution (CZD) including its asymptotic features. For small CZ areas, behavior of the CZD reflects the critical island size, i. For large CZ areas, it may reflect the probability for nucleation near such large CZs. Predictions are compared with kinetic Monte Carlo simulation data for models with two-dimensional compact islands with i = 1 (irreversible island formation by diffusing adatom pairs) and i = 0 (adatoms spontaneously convert to stable nuclei, e.g., by exchange with the substrate).

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Production of neutron-rich isotopes for 𝑍 ≥ 98 in the 238 U + 248 Cm reaction

Multinucleon transfer (MNT) reactions in actinide systems are a promising method to synthesize transuranium neutron-rich elements. Appropriate theoretical approaches are needed to understand the mechanisms behind MNT. We employ a microscopic approach to calculate neutron-rich isotope production in the reaction 238 U + 248 Cm system. Here, the stochastic mean-field (SMF) approach is used to calculate the primary cross sections in MNT reactions based on the quasifission and inverse quasifission processes, and a statistical de-excitation model with GEMINI ++ code to calculate the secondary fragment cross sections. The calculated cross sections using SMF and GEMINI ++ explain available experimental results for the 238 U + 248 Cm system at 𝐸 c.m. = 898.7 MeV energy. This shows the effectiveness and applicability of the quantal diffusion approach, based on the SMF theory, in heavy-ion collisions. Production of transuranium neutron-rich elements with a proton number up to 𝑍=101 is obtained with sizable cross sections. Theoretical results calculated for the 𝑍=102–105 region, for which there are no experimental data, show that the cross-section values would be lower than the microbarn level. SMF theory does not contain any adjustable parameters other than the standard parameters of the energy density functional used in the TDHF theory and is an important approach for the microscopic understanding of reaction mechanisms.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
NASA NTRS1979

An 'adding' algorithm for the Markov chain formalism for radiation transfer

An adding algorithm is presented, that extends the Markov chain method and considers a preceding calculation as a single state of a new Markov chain. This method takes advantage of the description of the radiation transport as a stochastic process. Successive application of this procedure makes calculation possible for any optical depth without increasing the size of the linear system used. It is determined that the time required for the algorithm is comparable to that for a doubling calculation for homogeneous atmospheres. For an inhomogeneous atmosphere the new method is considerably faster than the standard adding routine. It is concluded that the algorithm is efficient, accurate, and suitable for smaller computers in calculating the diffuse intensity scattered by an inhomogeneous planetary atmosphere.

Esposito, L. W.↗
NASA NTRS1986

Unimolecular diffusion-mediated reactions with a nonrandom time-modulated absorbing barrier

A diffusion-reaction model with time-dependent reactivity is formulated and applied to unimolecular reactions. The model is solved exactly numerically and approximately analytically for the unreacted fraction as a function of time. It is shown that the approximate analytical solution is valid even when the system is far from equilibrium, and when the reactivity probability is more complicated than a square-wave function of time. A discussion is also given of an approach to problems of this type using a stochastically fluctuating reactivity, and the first-passage time for a particular example is derived.

Bashford, D.↗
DOE OSTI2013

Hydrogeologic Modeling at the Sylvania Corning FUSRAP Site - 13419

A comparative groundwater hydrogeologic modeling analysis is presented herein to simulate potential contaminant migration pathways in a sole source aquifer in Nassau County, Long Island, New York. The source of contamination is related to historical operations at the Sylvania Corning Plant ('Site'), a 9.49- acre facility located at 70, 100 and 140 Cantiague Rock Road, Town of Oyster Bay in the westernmost portion of Hicksville, Long Island. The Site had historically been utilized as a nuclear materials manufacturing facility (e.g., cores, slug, and fuel elements) for reactors used in both research and electric power generation in early 1950's until late 1960's. The Site is contaminated with various volatile organic and inorganic compounds, as well as radionuclides. The major contaminants of concern at the Site are tetrachloroethene (PCE), trichloroethene (TCE), nickel, uranium, and thorium. These compounds are present in soil and groundwater underlying the Site and have migrated off-site. The Site is currently being investigated as part of the Formerly Utilized Sites Remedial Action Program (FUSRAP). The main objective of the current study is to simulate the complex hydrogeologic features in the region, such as numerous current and historic production well fields; large, localized recharge basins; and, multiple aquifers, and to assess potential contaminant migration pathways originating from the Site. For this purpose, the focus of attention was given to the underlying Magothy formation, which has been impacted by the contaminants of concern. This aquifer provides more than 90% of potable water supply in the region. Nassau and Suffolk Counties jointly developed a three-dimensional regional groundwater flow model to help understand the factors affecting groundwater flow regime in the region, to determine adequate water supply for public consumption, to investigate salt water intrusion in localized areas, to evaluate the impacts of regional pumping activity, and to better understand the contaminant transport and fate mechanisms through the underlying aquifers. This regional model, developed for the N.Y. State Department of Environmental Conservation (NYSDEC) by Camp Dresser and McKee (CDM), uses the finite element model DYNFLOW developed by CDM, Cambridge, Massachusetts. The coarseness of the regional model, however, could not adequately capture the hydrogeologic heterogeneity of the aquifer. Specifically, the regional model did not adequately capture the interbedded nature of the Magothy aquifer and, as such, simulated particles tended to track down-gradient from the Site in relatively straight lines while the movement of groundwater in such a heterogeneous aquifer is expected to proceed along a more tortuous path. This paper presents a qualitative comparison of site-specific groundwater flow modeling results with results obtained from the regional model. In order to assess the potential contaminant migration pathways, a particle tracking method was employed. Available site-specific and regional hydraulic conductivity data measured in-situ with respect to depth and location were incorporated into the T-PROG module in GMS model to define statistical variation to better represent the actual stratigraphy and layer heterogeneity. The groundwater flow characteristics in the Magothy aquifer were simulated with the stochastic hydraulic conductivity variation as opposed to constant values as employed in the regional model. Contaminant sources and their exact locations have been fully delineated at the Site during the Remedial Investigation (RI) phase of the project. Contaminant migration pathways originating from these source locations at the Site are qualitatively traced within the sole source aquifer utilizing particles introduced at source locations. Contaminant transport mechanism modeled in the current study is based on pure advection (i.e., plug flow) and mechanical dispersion while molecular diffusion effects are neglected due to relatively high groundwater velocities encountered in the aquifer. In addition, fate of contaminants is ignored hereby to simulate the worst-case scenario, which considers the contaminants of concern as tracer-like compounds for modeling purposes. The results of the modeling analysis are qualitatively compared with the County's regional model, and patterns of contaminant migration in the region are presented. (authors)

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Structuring, stochastic behavior, and charge storage capacity of redox-active microemulsions formulated with mixtures of toluene and ionic liquid as oil phase

Oil/water microemulsions (µEs) are promising electrolytes for redox flow batteries (RFBs) as they simultaneously improve charge capacity and ionic conductivity. Here, we report the successful formulation of bicontinuous µEs where the oil phase is a solution of trihexyltetradecylphosphonium bis(trifluoromethylsulfonyl)amide ionic liquid in toluene with redox-active ferrocene. We examined the effect of supporting electrolyte anion (NO 3 – , Cl – , ClO 4 – ) on the structure, reactivity, transport, and electrolytic performance of redox-active µEs. Neutron scattering and nuclear magnetic resonance showed that the domain size increased as Cl – > NO 3 – > ClO 4 – while the ferrocene diffusion coefficient increased as NO 3 – > Cl – > ClO 4 – . Scanning electrochemical microscopy indicated anion-dependent current fluctuations during electrolysis, with ClO 4 – exhibiting the least high-frequency oscillations, which correlate to the highest charge and discharge capacity and reversibility. All ionic liquid containing systems improved the performance of toluene-based µEs, highlighting new design principles for these electrolytes.

diffusion↗
DOE OSTI2020

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↗
DOE OSTI2026

Monitored Fluctuating Hydrodynamics

We introduce a hydrodynamic framework for describing monitored classical stochastic processes. We study the conditional ensembles for these monitored processes—i.e., we compute spacetime correlation functions conditioned on a fixed, typical measurement record. In the presence of global symmetries we show that these conditional ensembles can undergo measurement-induced “sharpening” phase transitions as a function of the monitoring rate; moreover, even weak monitoring can give rise to novel critical phases, derived entirely from a classical perspective. We give a simple hydrodynamic derivation of the known “charge-fuzzy phase” for weakly monitored diffusive many-body quantum systems. We show that although the unmonitored symmetric and asymmetric exclusion processes are in different universality classes of transport, the fluctuations in their conditional ensembles flow to the same fixed point with emergent relativistic invariance under monitoring. On the other hand, weakly monitored systems with non-Abelian symmetries enter a novel strongly coupled fixed point with nontrivial dynamical exponent, which we characterize. Our formalism naturally accounts for monitoring general observables, such as currents or density gradients, and allows for a direct calculation of information-theoretic diagnostics of sharpening transitions, including the Shannon entropy of the measurement record.

classical statistical mechanics↗
DOE OSTI2014

Relativistic electron precipitation events driven by electromagnetic ion-cyclotron waves

We adopt a canonical approach to describe the stochastic motion of relativistic belt electrons and their scattering into the loss cone by nonlinear EMIC waves. The estimated rate of scattering is sufficient to account for the rate and intensity of bursty electron precipitation. This interaction is shown to result in particle scattering into the loss cone, forming ∼10 s microbursts of precipitating electrons. These dynamics can account for the statistical correlations between processes of energization, pitch angle scattering, and relativistic electron precipitation events, that are manifested on large temporal scales of the order of the diffusion time ∼tens of minutes.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Stochastic Price Generation for Evaluating Wholesale Electricity Market Bidding Strategies

This work presents a novel method for generating electricity price scenarios from statistical properties of past electricity prices using a hybrid statistical and reduced-form stochastic model. Previous work in applying stochastic differential equations (SDE) to model electricity prices has focused on daily average prices. To extend stochastic price generation methods to hourly or sub-hourly pricing, we address several weaknesses in the state-of-the-art: (1) we replace the mean-reversion component of the SDE with an ARIMA process that is better able to characterize the daily and weekly trends; (2) we extend the price-spike, or jump process to account for conditional probabilities of price spikes occurring in consecutive time steps by replacing the traditional Poisson process for modeling jumps with a generalized point process model inspired by brain neuron models; and (3) we replace the traditional method of estimating spike intensity with empirical variance with a Markov process based on observed price spike intensity transitions. The method is demonstrated with electricity prices from the US ERCOT market and a use-case example is provided for bidding an energy storage unit into the day-ahead and real-time energy markets of ERCOT using stochastic optimization methods. Results show that the the synthetic price model out performs a (naive) persistence forecast model by resulting in 24% to 47% more in profits over 168 simulated days.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2013

Exact PDF equations and closure approximations for advective-reactive transport

Mathematical models of advection–reaction phenomena rely on advective flow velocity and (bio) chemical reaction rates that are notoriously random. By using functional integral methods, we derive exact evolution equations for the probability density function (PDF) of the state variables of the advection–reaction system in the presence of random transport velocity and random reaction rates with rather arbitrary distributions. These PDF equations are solved analytically for transport with deterministic flow velocity and a linear reaction rate represented mathematically by a heterog eneous and strongly-correlated random field. Our analytical solution is then used to investigate the accuracy and robustness of the recently proposed large-eddy diffusivity (LED) closure approximation [1]. We find that the solution to the LED-based PDF equation, which is exact for uncorrelated reaction rates, is accurate even in the presence of strong correlations and it provides an upper bound of predictive uncertainty.

PDF methods, Uncertainty quantification, Heterogen↗
DOE OSTI2017

Three-dimensional spontaneous magnetic reconnection

Magnetic reconnection is best known from observations of the Sun where it causes solar flares. Observations estimate the reconnection rate as a small, but non-negligible fraction of the Alfvén speed, so-called fast reconnection. Until recently, the prevailing pictures of reconnection were either of resistivity or plasma microscopic effects, which was contradictory to the observed rates. Alternative pictures were either of reconnection due to the stochasticity of magnetic field lines in turbulence or the tearing instability of the thin current sheet. In this paper we simulate long-term three-dimensional nonlinear evolution of a thin, planar current sheet subject to a fast oblique tearing instability using direct numerical simulations of resistive-viscous magnetohydrodynamics. The late-time evolution resembles generic turbulence with a −5/3 power spectrum and scale-dependent anisotropy, so we conclude that the tearing-driven reconnection becomes turbulent reconnection. The turbulence is local in scale, so microscopic diffusivity should not affect large-scale quantities. This is confirmed by convergence of the reconnection rate toward ∼0.015v{sub A} with increasing Lundquist number. In this spontaneous reconnection, with mean field and without driving, the dissipation rate per unit area also converges to ∼0.006ρv{sub A}{sup 3}, and the dimensionless constants 0.015 and 0.006 are governed only by self-driven nonlinear dynamics of the sheared magnetic field. Remarkably, this also means that a thin current sheet has a universal fluid resistance depending only on its length to width ratio and to v{sub A}/c.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Discrete Fracture Network Modeling to Estimate Upscaled Parameters for the Topopah Spring, Lava Flow, and Tiva Canyon Aquifers at Pahute Mesa, Nevada National Security Site

This report describes the results of Discrete Fracture Network (DFN) simulations for the Topopah Spring Aquifer (TSA), Lava Flow Aquifer, and Tiva Canyon Aquifer (TCA), at Pahute Mesa on the Nevada National Security Site (NNSS), formerly the Nevada Test Site. The research focuses on calculating upscaled groundwater flow and contaminant transport parameters using DFNs generated according to fracture characteristics observed in the TSA, LFA and TCA at Pahute Mesa. The highly fractured and heterogeneous nature of these aquifers makes them candidates for stochastic DFN modeling of radionuclide transport on a small scale with subsequent upscaling. One hundred independent DFN realizations are generated for each aquifer, and the upscaled parameters for continuum simulations of subsurface flow and transport in fractured media at Pahute Mesa are calculated. Our goal is to implement a modeling approach that can translate parameters to larger-scale models that account for local-scale flow and transport processes, such as channelization of flow and transport along a few well connected, large fractures. Additionally, to simulate advective and advective-diffusive transport through the fracture networks, the Time Domain Random Walk (TDRW) approach is applied to account for matrix diffusion into a finite half-space. Moreover, a novel approach to calculate dynamic (active) fracture surface area to reflect flow channeling is implemented. This work will improve the representation of radionuclide transport processes in largescale, regulatory-focused models by providing estimates of hard-to-measure flow and contaminant transport parameters at large scales. In this report, we (1) show recent results of flow and transport simulations on multiple DFN realizations of the TSA, LFA, TCA; (2) discuss the resulting distributions of estimated upscaled parameters; (3) describe the estimation of upscaled parameters for an equivalent parallel-plate continuum model and (4) present a comparison between simulated transport from the equivalent continuum model and an actual DFN.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

From Latent Dynamics to Meaningful Representations

While representation learning has been central to the rise of machine learning and artificial intelligence, a key problem remains in making the learnt representations meaningful. For this the typical approach is to regularize the learned representation through prior probability distributions. However such priors are usually unavailable or are ad hoc. To deal with this, recent efforts have shifted towards leveraging the insights from physical principles to guide the learning process. In this spirit, we propose a purely dynamics-constrained representation learning framework. Instead of relying on predefined probabilities, we restrict the latent representation to follow overdamped Langevin dynamics with a learnable transition density — a prior driven by statistical mechanics. We show this is a more natural constraint for representation learning in stochastic dynamical systems, with the crucial ability to uniquely identify the ground truth representation. We validate our framework for different systems including a real-world fluorescent DNA movie dataset. Here, we show that our algorithm can uniquely identify orthogonal, isometric and meaningful latent representations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2016

Data-driven probability concentration and sampling on manifold

A new methodology is proposed for generating realizations of a random vector with values in a finite-dimensional Euclidean space that are statistically consistent with a dataset of observations of this vector. The probability distribution of this random vector, while a priori not known, is presumed to be concentrated on an unknown subset of the Euclidean space. A random matrix is introduced whose columns are independent copies of the random vector and for which the number of columns is the number of data points in the dataset. The approach is based on the use of (i) the multidimensional kernel-density estimation method for estimating the probability distribution of the random matrix, (ii) a MCMC method for generating realizations for the random matrix, (iii) the diffusion-maps approach for discovering and characterizing the geometry and the structure of the dataset, and (iv) a reduced-order representation of the random matrix, which is constructed using the diffusion-maps vectors associated with the first eigenvalues of the transition matrix relative to the given dataset. The convergence aspects of the proposed methodology are analyzed and a numerical validation is explored through three applications of increasing complexity. The proposed method is found to be robust to noise levels and data complexity as well as to the intrinsic dimension of data and the size of experimental datasets. Both the methodology and the underlying mathematical framework presented in this paper contribute new capabilities and perspectives at the interface of uncertainty quantification, statistical data analysis, stochastic modeling and associated statistical inverse problems.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2016

Efficient molecular dynamics using geodesic integration and solvent–solute splitting

We present an approach to Langevin dynamics in the presence of holonomic constraints based on decomposition of the system into components representing geodesic flow, constrained impulse and constrained diffusion. We show that a particular ordering of the components results in an integrator that is an order of magnitude more accurate for configurational averages than existing alternatives. Moreover, by combining the geodesic integration method with a solvent–solute force splitting, we demonstrate that stepsizes of at least 8 fs can be used for solvated biomolecules with high sampling accuracy and without substantially altering diffusion rates, approximately increasing by a factor of two the efficiency of molecular dynamics sampling for such systems. The methods described in this article are easily implemented using the standard apparatus of modern simulation codes.

97 MATHEMATICS AND COMPUTING↗