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

An unorthodox X-Class Long-Duration Confined Flare

We report the observation of an X-class long-duration flare which is clearly confined. It appears as a compact-loop flare in the traditional EUV passbands (171 and 195 Å), but in the passbands sensitive to flare plasmas (94 and 131 Å), it exhibits a cusp-shaped structure above an arcade of loops like other long-duration events. Inspecting images in a running difference approach, we find that the seemingly diffuse, quasi-static cusp-shaped structure consists of multiple nested loops that repeatedly rise upward and disappear approaching the cusp edge. Over the gradual phase, we detect numerous episodes of loop rising, each lasting minutes. A differential emission measure analysis reveals that the temperature is highest at the top of the arcade and becomes cooler at higher altitudes within the cusp-shaped structure, contrary to typical long-duration flares. With a nonlinear force-free model, our analysis shows that the event mainly involves two adjacent sheared arcades separated by a T-type hyperbolic flux tube (HFT). One of the arcades harbors a magnetic flux rope, which is identified with a filament that survives the flare owing to the strong confining field. We conclude that a new emergence of magnetic flux in the other arcade triggers the flare, while the preexisting HFT and flux rope dictate the structure and dynamics of the flare loops and ribbons during the long-lasting decay phase, and that a quasi-separatrix layer high above the HFT could account for the cusp-shaped structure.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2016

Asymmetric collapse by dissolution or melting in a uniform flow

An advection-diffusion-limited dissolution model of an object being eroded by a two-dimensional potential flow is presented. By taking advantage of the conformal invariance of the model, a numerical method is introduced that tracks the evolution of the object boundary in terms of a time-dependent Laurent series. Simulations of a variety of dissolving objects are shown, which shrink and collapse to a single point in finite time. The simulations reveal a surprising exact relationship, whereby the collapse point is the root of a non-Analytic function given in terms of the flow velocity and the Laurent series coefficients describing the initial shape. This result is subsequently derived using residue calculus. The structure of the non-Analytic function is examined for three different test cases, and a practical approach to determine the collapse point using a generalized Newton-Raphson root-finding algorithm is outlined. These examples also illustrate the possibility that the model breaks down in finite time prior to complete collapse, due to a topological singularity, as the dissolving boundary overlaps itself rather than breaking up into multiple domains (analogous to droplet pinch-off in fluid mechanics). In conclusion, the model raises fundamental mathematical questions about broken symmetries in finite-Time singularities of both continuous and stochastic dynamical systems.

42 ENGINEERING↗
DOE OSTI2018

Real-Time Control of an Ensemble of Heterogeneous Resources

This paper focuses on the problem of controlling an ensemble of heterogeneous resources connected to an electrical grid at the same point of common coupling (PCC). The controller receives an aggregate power setpoint for the ensemble in real time and tracks this setpoint by issuing individual optimal setpoints to the resources. The resources can have continuous or discrete nature (e.g., heating systems consisting of a finite number of heaters that each can be either switched on or off) and/or can be highly uncertain (e.g., photovoltaic (PV) systems or residential loads). A naive approach would lead to a stochastic mixed-integer optimization problem to be solved at the controller at each time step, which might be infeasible in real time. Instead, we allow the controller to solve a continuous convex optimization problem and compensate for the errors at the resource level by using a variant of the well-known error diffusion algorithm. We give conditions guaranteeing that our algorithm tracks the power setpoint at the PCC on average while issuing optimal setpoints to individual resources. We illustrate the approach numerically by controlling a collection of batteries, PV systems, and discrete loads.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2019

Low-Rank Solution Methods for Stochastic Eigenvalue Problems

In this report, we study efficient solution methods for stochastic eigenvalue problems arising from discretization of self-adjoint partial differential equations with random data, where the underlying operators depend linearly on the random parameters. With the stochastic Galerkin approach, the solutions are represented as generalized polynomial chaos expansions. When these solutions can be approximated well by low-rank objects, we introduce a low-rank variant of the inverse subspace iteration algorithm for computing one or several minimal eigenvalues and corresponding eigenvectors of parameter-dependent matrices. In the algorithm, the iterates are approximated by low-rank matrices, which leads to significant cost savings. Furthermore, the algorithm is tested on two benchmark problems, a stochastic diffusion problem with some poorly separated eigenvalues, and an operator derived from a discrete stochastic Stokes problem whose minimal eigenvalue is related to the inf-sup stability constant. Numerical experiments show that the low-rank algorithm produces accurate solutions compared to the Monte Carlo method, and it uses much less computational time than the original algorithm without low-rank approximation.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Instability of steady-state mixed-state symmetry-protected topological order to strong-to-weak spontaneous symmetry breaking

Recent experimental progress in controlling open quantum systems enables the pursuit of mixed-state nonequilibrium quantum phases. We investigate whether open quantum systems hosting mixed-state symmetry-protected topological states as steady states retain this property under symmetric perturbations. Focusing on the decohered cluster state – a mixed-state symmetry-protected topological state protected by a combined strong and weak symmetry – we construct a parent Lindbladian that hosts it as a steady state. This Lindbladian can be mapped onto exactly solvable reaction-diffusion dynamics, even in the presence of certain perturbations, allowing us to solve the parent Lindbladian in detail and reveal previously-unknown steady states. Using both analytical and numerical methods, we find that typical symmetric perturbations cause strong-to-weak spontaneous symmetry breaking at arbitrarily small perturbations, destabilize the steady-state mixed-state symmetry-protected topological order. However, when perturbations introduce only weak symmetry defects, the steady-state mixed-state symmetry-protected topological order remains stable. Additionally, we construct a quantum channel which replicates the essential physics of the Lindbladian and can be efficiently simulated using only Clifford gates, Pauli measurements, and feedback.

Shah, Jeet [University of Maryland, College Park, ↗
DOE OSTI2019

Chemical explosive mode analysis of lean blowout in a gas turbine combustor

In this study, stabilization and lean blowout (LBO) mechanisms in a gas turbine combustor are numerically studied based on large eddy simulation (LES) data and the chemical explosive mode analysis (CEMA). Three CEMA-based local combustion modes, that is, auto-ignition, diffusion-assisted ignition, and extinction, are employed to quantify interactions between local diffusion and chemical processes in complex turbulent fields. The capability of CEMA-based local modes in extinction detection is first demonstrated in a one-dimensional non-premixed flamelet undergoing transient extinction. Flame structure and dynamics in the gas turbine combustor are then examined in detail using CEMA and the local combustion modes for both the stably burning and lean blowout conditions. Local structure comprised of all the three modes are identified, and each mode is found to play an important role in determining the overall burning rate. The heat release rate attributed to each local mode remains nearly constant at the stably burning condition. In contrast, the flame during LBO shows a two-stage extinction behavior: at the initial stage, the extinction mode is largely enhanced and becomes dominant over the assisted-ignition model; at the second stage, all three modes are suppressed, signifying global extinction. It is therefore suggested that the excessive local extinction mode, due to an increased amount of heat and radical losses through diffusion, finally leads to lean flame blowout.

chemical explosive mode↗
DOE OSTI2019

Estimation of conductivity for nanoporous materials

Methods and systems for estimating conductivity of clay mineral systems, and for applying the estimates in larger-scale analysis. Conductivity of the clay may be estimated by constructing a molecular model of an anhydrous charge-neutral clay, and then assigning a charge density by substitution of ions in the model of the clay structure. Counterions are inserted for charge neutrality, and water molecules are added to the model to reflect a selected level of hydration. Following assignment of force-field coefficients, molecular dynamics simulation provides data from which diffusion coefficients can be estimated. Application of the Nernst-Einstein relationship to the diffusion coefficients of the counterions provides the ion conductivity of the clay system. This conductivity can be used to derive a formation factor, and can be applied in direct numerical simulation analysis.

58 GEOSCIENCES↗
DOE OSTI2025

Prediction and Analysis of Utah FORGE Injection Activities using a Coupled Thermo-hydro-mechanical and Earthquake (THM+E) Modeling Workflow

A coupled thermo-hydro-mechanical (THM) numerical workflow that is capable of modeling seismic slip is critical for the successful development of enhanced geothermal systems (EGS). By integrating key physical processes, this workflow enables accurate simulation of temperature and pressure diffusions, stress changes, and induced seismicity. As a result, it serves as a vital tool for predicting induced seismicity and optimizing reservoir stimulation strategies. The Utah FORGE (Frontier Observatory for Research in Geothermal Energy) project, located near Milford, Utah, is a U.S. Department of Energy initiative aimed at advancing EGS technology. In April 2024, eight new stimulation stages (Stages 3R-10) were conducted in well 16A (injection well) subsequent to the first series of stimulation (Stages 1-3) performed in April, 2022. To monitor the induced seismicity, geophones were deployed in wells 58-32, 56-32, and 78B-32, while fiber optic cables were also installed in wells 16B, 78-32, and 78B-32 to collect microseismic data and detect frac hits Preliminary analyses of microseismic catalogs and fiber optic data suggest that the stimulated fractures in Stages 3R–6 closely align with that generated during Stage 3, indicating that the new stimulations were likely reactivating the previously stimulated fracture. To better understand the underlying process, a comprehensive modeling approach that can accurately capture thermal, hydrological, mechanical, and seismic responses is essential. In this work, we propose and utilize a coupled thermo-hydro-mechanical and earthquake (THM+E) simulation workflow to numerically investigate the stimulation activities on well 16A. The specific objective is to confirm whether the new stimulation stages (Stages 3R–6) reactivated fractures previously stimulated during Stage 3. For this purpose, we perform THM+E simulations individually for Stages 3, 3R, 4, and 5, incorporating the discrete fracture networks (DFNs) created by the plane-fitting technique based on the microseismic catalogs. The simulation workflow consists of two separate models: a THM model and an earthquake model, coupled in a one-way manner. Detailed descriptions of the workflow are provided in Section 3. Simulation results are presented in terms of injection pressure, permeability evolution, and predicted seismic catalogs, which are then compared with field data for further analyses. This report is structured as follows. In Section 2, we present detailed analyses of the field data and propose the hypothesis that the new stimulation stages (Stages 3R–6) were probably reactivating the previously stimulated fractures in Stage 3. In Section 3, we introduce the coupled THM+E workflow and the problem setup to validate our hypothesis, followed by the simulation results for each stage in Section 4. Meanwhile, discussions are included to analyze the model predictions and their comparison with field data. Lastly, we conclude the report and outline future plans in Section 5.

15 GEOTHERMAL ENERGY↗
DOE OSTI2015

Experimental and numerical analysis of parallel reactant flow and transverse mixing with mineral precipitation in homogeneous and heterogeneous porous media

Formation of mineral precipitates in the mixing interface between two reactant solutions flowing in parallel in porous media is governed by reactant mixing by diffusion and dispersion and is coupled to changes in porosity/permeability due to precipitation. The spatial and temporal distribution of mixing-dependent precipitation of barium sulfate in porous media was investigated with side-by-side injection of barium chloride and sodium sulfate solutions in thin rectangular flow cells packed with quartz sand. The results for homogeneous sand beds were compared to beds with higher or lower permeability inclusions positioned in the path of the mixing zone. In the homogeneous and high permeability inclusion experiments, BaSO 4 precipitate (barite) formed in a narrow deposit along the length and in the center of the solution–solution mixing zone even though dispersion was enhanced within, and downstream of, the high permeability inclusion. In the low permeability inclusion experiment, the deflected BaSO 4 precipitation zone broadened around one side and downstream of the inclusion and was observed to migrate laterally toward the sulfate solution. A continuum-scale fully coupled reactive transport model that simultaneously solves the nonlinear governing equations for fluid flow, transport of reactants and geochemical reactions was used to simulate the experiments and provide insight into mechanisms underlying the experimental observations. Lastly, migration of the precipitation zone in the low permeability inclusion experiment could be explained by the coupling effects among fluid flow, reactant transport and localized mineral precipitation reaction.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

WellPINN: Accurate Well Representation for Transient Fluid Pressure Diffusion in Subsurface Reservoirs With Physics‐Informed Neural Networks

Accurate representation of pumping wells is essential for reliable reservoir characterization and simulation of operational scenarios in subsurface flow models. Physics-informed neural networks (PINNs) are emerging as a promising alternative to numerical models for reservoir modeling, offering seamless integration of monitoring data and governing physical equations. However, existing PINN-based studies face major challenges in capturing fluid pressure near wells when using a source/sink term, particularly during the early stages after pumping begins. We address this problem by introducing WellPINN, a workflow in which an initially trained PINN infers fluid pressure across the entire reservoir domain using a large equivalent well radius. This initial PINN solution is then locally refined around the well by a set of subdomain PINNs that are trained for smaller equivalent well radii. Continuity across these subdomain interfaces as well as at the initial condition is ensured by hard-constraining each PINN on its subdomain boundary. Our results demonstrate WellPINN as the first workflow of its kind to focus on accurate inference of fluid pressure from pumping rates throughout the entire injection period, significantly advancing the potential of PINNs for inverse modeling and operational scenario simulations. All data and code for this paper are openly available at https://doi.org/10.20350/DIGITALCSIC/17260.

58 GEOSCIENCES↗
DOE OSTI2014

Radiation and porosity effects on the magnetohydrodynamic flow near a vertical plate that applies shear stress to the fluid with mass diffusion

This article studies the radiation and porosity effects on the unsteady magnetohydrodynamic free convection flow of an incompressible viscous fluid past an infinite vertical plate that applies a shear stress f(t) to the fluid. Conjugate phenomenon of heat and mass transfer is considered. General solutions of the dimensionless governing equations along with imposed initial and boundary conditions are determined using Laplace transform technique. The solution of velocity is presented as a sum of mechanical and non mechanical parts. These solutions satisfy all imposed initial and boundary conditions and reduce to some known solutions from the literature as special cases. The results for embedded parameters are shown graphically. Numerical results for skin friction, Nusselt number and Sherwood number are computed and presented in tabular forms.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2020

Numerical investigation of microbial quorum sensing under various flow conditions

Microorganisms efficiently coordinate phenotype expressions through a decision-making process known as quorum sensing (QS). We investigated QS amongst distinct, spatially distributed microbial aggregates under various flow conditions using a process-driven numerical model. Model simulations assess the conditions suitable for QS induction and quantify the importance of advective transport of signaling molecules. In addition, advection dilutes signaling molecules so that faster flow conditions require higher microbial densities, faster signal production rates, or higher sensitivities to signaling molecules to induce QS. However, autoinduction of signal production can substantially increase the transport distance of signaling molecules in both upstream and downstream directions. We present empirical approximations to the solutions of the advection–diffusion–reaction equation that describe the concentration profiles of signaling molecules for a wide range of flow and reaction rates. These empirical relationships, which predict the distribution of dissolved solutes along pore channels, allow to quantitatively estimate the effective communication distances amongst multiple microbial aggregates without further numerical simulations.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2016

Analyzing diffuse scattering with supercomputers. Corrigendum

The study by Michels-Clark et al. (2013 [Michels-Clark, T. M., Lynch, V. E., Hoffmann, C. M., Hauser, J., Weber, T., Harrison, R. & Bürgi, H. B. (2013). J. Appl. Cryst. 46, 1616-1625.]) contains misleading errors which are corrected here. The numerical results reported in that paper and the conclusions given there are not affected and remain unchanged. The transition probabilities in Table 1 (rows 4, 5, 7, 8) and Fig. 2 (rows 1 and 2) of the original paper were different from those used in the numerical calculations. Corrected transition probabilities as used in the computations are given in Table 1 and Fig. 1 of this article. The Δ parameter in the stacking model expresses the preference for the fifth layer in a five-layer stack to be eclipsed with respect to the first layer. This statement corrects the original text on p. 1622, lines 4–7. In the original Fig. 2 the helicity of the layer stacks b L and b R in rows 3 and 4 had been given as opposite to those in rows 1, 2 and 5. Fig. 1 of this article shows rows 3 and 4 corrected to correspond to rows 1, 2 and 5.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Synthesizing realistic sand assemblies with denoising diffusion in latent space

Abstract The shapes and morphological features of grains in sand assemblies have far‐reaching implications in many engineering applications, such as geotechnical engineering, computer animations, petroleum engineering, and concentrated solar power. Yet, our understanding of the influence of grain geometries on macroscopic response is often only qualitative, due to the limited availability of high‐quality 3D grain geometry data. In this paper, we introduce a denoising diffusion algorithm that uses a set of point clouds collected from the surface of individual sand grains to generate grains in the latent space. By employing a point cloud autoencoder, the three‐dimensional point cloud structures of sand grains are first encoded into a lower‐dimensional latent space. A generative denoising diffusion probabilistic model is trained to produce synthetic sand that maximizes the log‐likelihood of the generated samples belonging to the original data distribution measured by a Kullback‐Leibler divergence. Numerical experiments suggest that the proposed method is capable of generating realistic grains with morphology, shapes and sizes consistent with the training data inferred from an F50 sand database. We then use a rigid contact dynamic simulator to pour the synthetic sand in a confined volume to form granular assemblies in a static equilibrium state with targeted distribution properties. To ensure third‐party validation, 50,000 synthetic sand grains and the 1542 real synchrotron microcomputed tomography (SMT) scans of the F50 sand, as well as the granular assemblies composed of synthetic sand grains are made available in an open‐source repository.

Vlassis, Nikolaos N.↗
DOE OSTI2016

Direct discontinuous Galerkin method and its variations for second order elliptic equations

In this study, we study direct discontinuous Galerkin method (Liu and Yan in SIAM J Numer Anal 47(1):475–698, 2009) and its variations (Liu and Yan in Commun Comput Phys 8(3):541–564, 2010; Vidden and Yan in J Comput Math 31(6):638–662, 2013; Yan in J Sci Comput 54(2–3):663–683, 2013) for 2nd order elliptic problems. A priori error estimate under energy norm is established for all four methods. Optimal error estimate under L 2 norm is obtained for DDG method with interface correction (Liu and Yan in Commun Comput Phys 8(3):541–564, 2010) and symmetric DDG method (Vidden and Yan in J Comput Math 31(6):638–662, 2013). A series of numerical examples are carried out to illustrate the accuracy and capability of the schemes. Numerically we obtain optimal (k+1)th order convergence for DDG method with interface correction and symmetric DDG method on nonuniform and unstructured triangular meshes. An interface problem with discontinuous diffusion coefficients is investigated and optimal (k+1)th order accuracy is obtained. Peak solutions with sharp transitions are captured well. Highly oscillatory wave solutions of Helmholz equation are well resolved.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2017

DG-IMEX Stochastic Galerkin Schemes for Linear Transport Equation with Random Inputs and Diffusive Scalings

In this paper, we consider the linear transport equation under diffusive scaling and with random inputs. The method is based on the generalized polynomial chaos approach in the stochastic Galerkin framework. Several theoretical aspects will be addressed. Additionally, a uniform numerical stability with respect to the Knudsen number ϵ, and a uniform in ϵ error estimate is given. For temporal and spatial discretizations, we apply the implicit–explicit scheme under the micro–macro decomposition framework and the discontinuous Galerkin method, as proposed in Jang et al. (SIAM J Numer Anal 52:2048–2072, 2014) for deterministic problem. Lastly, we provide a rigorous proof of the stochastic asymptotic-preserving (sAP) property. Extensive numerical experiments that validate the accuracy and sAP of the method are conducted.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

Homogenizing Advanced Alloys: Thermodynamic and Kinetic Simulations Followed by Experimental Results

Segregation of solute elements occurs in nearly all metal alloys during solidification. The resultant elemental partitioning can severely degrade as-cast material properties and lead to difficulties during post-processing (e.g., hot shorts and incipient melting). Many cast articles are subjected to a homogenization heat treatment in order to minimize segregation and improve their performance. Traditionally, homogenization heat treatments are based upon past practice or time-consuming trial and error experiments. Through the use of thermodynamic and kinetic modeling software, NETL has designed a systematic method to optimize homogenization heat treatments. Use of the method allows engineers and researchers to homogenize casting chemistries to levels appropriate for a given application. The method also allows for the adjustment of heat treatment schedules to fit limitations on in-house equipment (capability, reliability, etc.) while maintaining clear numeric targets for segregation reduction. In this approach, the Scheil module within Thermo-Calc is used to predict the as-cast segregation present within an alloy, and then diffusion controlled transformations is used to model homogenization kinetics as a function of time and temperature. Examples of computationally designed heat treatments and verification of their effects on segregation and properties of real castings are presented.

36 MATERIALS SCIENCE↗
DOE OSTI2017

Diffusiophoresis in one-dimensional solute gradients

Here, the diffusiophoretic motion of suspended colloidal particles under one-dimensional solute gradients is solved using numerical and analytical techniques. Similarity solutions are developed for the injection and withdrawal dynamics of particles into semi-infinite pores. Furthermore, a method of characteristics formulation of the diffusion-free particle transport model is presented and integrated to realize particle trajectories. Analytical solutions are presented for the limit of small particle diffusiophoretic mobility Γ p relative to the solute diffusivity D s for particle motions in both semi-infinite and finite domains. Results confirm the build up of local maxima and minima in the propagating particle front dynamics. The method of characteristics is shown to successfully predict particle motions and the position of the particle front, although it fails to accurately predict suspended particle concentrations in the vicinity of sharp gradients, such as at the particle front peak seen in some injection cases, where particle diffusion inevitably plays an important role. Results inform the design of applications in which the use of applied solute gradients can greatly enhance particle injection into and withdrawal from pores.

36 MATERIALS SCIENCE↗