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At least 1,099 records · Page 61
All sourcesNASA NTRSDOE OSTI
NASA NTRS2016

Hybrid Reynolds-Averaged/Large Eddy Simulation of the Flow in a Model SCRamjet Cavity Flameholder

Steady-state and scale-resolving simulations have been performed for flow in and around a model scramjet combustor flameholder. Experimental data available for this configuration include velocity statistics obtained from particle image velocimetry. Several turbulence models were used for the steady-state Reynolds-averaged simulations which included both linear and non-linear eddy viscosity models. The scale-resolving simulations used a hybrid Reynolds-averaged/large eddy simulation strategy that is designed to be a large eddy simulation everywhere except in the inner portion (log layer and below) of the boundary layer. Hence, this formulation can be regarded as a wall-modeled large eddy simulation. This e ort was undertaken to not only assess the performance of the hybrid Reynolds-averaged / large eddy simulation modeling approach in a flowfield of interest to the scramjet research community, but to also begin to understand how this capability can best be used to augment standard Reynolds-averaged simulations. The numerical errors were quantified for the steady-state simulations, and at least qualitatively assessed for the scale-resolving simulations prior to making any claims of predictive accuracy relative to the measurements. The steady-state Reynolds-averaged results displayed a high degree of variability when comparing the flameholder fuel distributions obtained from each turbulence model. This prompted the consideration of applying the higher-fidelity scale-resolving simulations as a surrogate "truth" model to calibrate the Reynolds-averaged closures in a non-reacting setting prior to their use for the combusting simulations. In general, the Reynolds-averaged velocity profile predictions at the lowest fueling level matched the particle imaging measurements almost as well as was observed for the non-reacting condition. However, the velocity field predictions proved to be more sensitive to the flameholder fueling rate than was indicated in the measurements.

Baurle, R. A.↗
DOE OSTI2013

An Optical Streak Diagnostic for Observing Anode-Cathode Plasmas for Radiographic Source Development

National Security Technologies, LLC, and Sandia National Laboratories are collaborating in the development of pulsed power–driven flash x-ray radiographic sources that utilize high-intensity electron beam diodes. The RITS 6 (Radiographic Integrated Test Stand) accelerator at Sandia is used to drive a self magnetic pinch diode to produce a Bremsstrahlung x-ray source. The high electric fields and current densities associated with these short A-K gap pinch beam diodes present many challenges in diode development. Plasmas generated at both the anode and cathode affect the diode performance, which is manifested in varying spot (source) sizes, total dose output, and impedance profiles. Understanding the nature of these plasmas including closure rates and densities is important in modeling their behavior and providing insight into their mitigation. In this paper we describe a streak camera–based optical diagnostic that is capable of observing and measuring plasma evolution within the A-K gap. By imaging a region of interest onto the input slit of a streak camera, we are able to produce a time-resolved one-dimensional image of the evolving plasma. Typical data are presented.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2016

Continuum Gyrokinetic Edge New Technology

COGENT is a simulation code that models the plasma evolution in the edge region of a tokamak fusion reactor, from the open field line scrape-off layer, across the separatrix, and into the core. The model is based on the 4D gyrokinetic closure of the kinetic equations for a plasma coupled to an electrostatic potential field. The background magnetic field is prescribed either analytically or generated from experimental data, and the grid is aligned with magnetic flux surfaces. Multiple collision operator options are provided, from Krook to fully nonlinear Fokker-Planck.

Dorr, M. R.↗
DOE OSTI2016

Flexible Computer Science Infrastructure (FleCSI)

FleCSI is a compile-time configurable framework designed to support multi-physics application development. As such, FleCSI attempts to provide a very general set of infrastructure design patterns that can be specialized and extended to suit the needs of a broad variety of solver and data requirements. Current support includes multi-dimensional mesh topology, mesh geometry, and mesh adjacency information, n-dimensional hashed-tree data structures, graph partitioning interfaces, and dependency closures. FleCSI also introduces a functional programming model with control, execution, and data abstractions that are consistent with both MPI and state-of-the-art task-based runtimes such as Legion and Charm++. The FleCSI abstraction layer provides the developer with insulation from the underlying runtime, while allowing support for multiple runtime systems, including conventional models like asynchronous MPI. The intent is to give developers a concrete set of user-friendly programming tools that can be used now, while allowing flexibility in choosing runtime implementations and optimizations that can be applied to architectures and runtimes that arise in the future. The control and execution models in FleCSI also provide formal nomenclature for describing poorly understood concepts like kernels and tasks.

Bergen, Ben↗
DOE OSTI2013

Variance estimates for transport in stochastic media by means of the master equation

The master equation has been used to examine properties of transport in stochastic media. It has been shown previously that not only may the Levermore-Pomraning (LP) model be derived from the master equation for a description of ensemble-averaged transport quantities, but also that equations describing higher-order statistical moments may be obtained. We examine in greater detail the equations governing the second moments of the distribution of the angular fluxes, from which variances may be computed. We introduce a simple closure for these equations, as well as several models for estimating the variances of derived transport quantities. We revisit previous benchmarks for transport in stochastic media in order to examine the error of these new variance models. We find, not surprisingly, that the errors in these variance estimates are at least as large as the corresponding estimates of the average, and sometimes much larger. We also identify patterns in these variance estimates that may help guide the construction of more accurate models. (authors)

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1995

Galactic cosmic-ray mediation of a spherical solar wind flow. 1: The steady state cold gas hydrodynamical approximation

Realistic models of the outer heliosphere should consider that the interstellar cosmic-ray pressure becomes comparable to pressures in the solar wind at distances more than 100 AU from the Sun. The cosmic-ray pressure dynamically affects solar wind flow through deceleration. This effect, which occurs over a scale length of the order of the effective diffusion length at large radial distances, has important implications for cosmic-ray modulation and acceleration. As a first step toward solution of this nonlinear problem, a steady state numerical model was developed for a relatively cold spherical solar wind flow which encounters the confining isotropic pressure of the surrounding Galactic medium. This pressure is assumed to be dominated by energetic particles (Galactic cosmic rays). The system of equations, which are solved self-consistently, includes the relevant hydrodynamical equations for the solar wind flow and the spherical cosmic-ray transport equation. To avoid the closure parameter problem of the two-fluid model, the latter equation is solved for the energy-dependent cosmic-ray distribution function.

Le Roux, J. A.↗
DOE OSTI2013

Advanced simulation capability for environmental management - current status and future applications

The U.S. Department of Energy (US DOE) Office of Environmental Management (EM), Office of Soil and Groundwater (EM-12), is supporting development of the Advanced Simulation Capability for Environmental Management (ASCEM). ASCEM is a state-of-the-art scientific tool and approach that is currently aimed at understanding and predicting contaminant fate and transport in natural and engineered systems. ASCEM is a modular and open source high-performance computing tool. It will be used to facilitate integrated approaches to modeling and site characterization, and provide robust and standardized assessments of performance and risk for EM cleanup and closure activities. The ASCEM project continues to make significant progress in development of capabilities, with current emphasis on integration of capabilities in FY12. Capability development is occurring for both the Platform and Integrated Tool-sets and High-Performance Computing (HPC) multi-process simulator. The Platform capabilities provide the user interface and tools for end-to-end model development, starting with definition of the conceptual model, management of data for model input, model calibration and uncertainty analysis, and processing of model output, including visualization. The HPC capabilities target increased functionality of process model representations, tool-sets for interaction with Platform, and verification and model confidence testing. The integration of the Platform and HPC capabilities were tested and evaluated for EM applications in a set of demonstrations as part of Site Applications Thrust Area activities in 2012. The current maturity of the ASCEM computational and analysis capabilities has afforded the opportunity for collaborative efforts to develop decision analysis tools to support and optimize radioactive waste disposal. Recent advances in computerized decision analysis frameworks provide the perfect opportunity to bring this capability into ASCEM. This will allow radioactive waste disposal to be evaluated based on decision needs, such as disposal, closure, and maintenance. Decision models will be used in ASCEM to identify information/data needs, and model refinements that might be necessary to effectively reduce uncertainty in waste disposal decisions. Decision analysis models start with tools for framing the problem, and continue with modeling both the science side of the problem (for example, inventories, source terms, fate and transport, receptors, risk, etc.), and the cost side of the problem, which could include costs of implementation of any action that is chosen (e.g., for disposal or closure), and the values associated with those actions. The cost side of the decision problem covers economic, environmental and societal costs, which correspond to the three pillars of sustainability (economic, social, and environmental). These tools will facilitate stakeholder driven decision analysis to support optimal sustainable solutions in ASCEM. In this paper the current state of ASCEM is first described, followed by a description of the approach that will be taken to augment ASCEM for simulating fate and transport with tools that facilitate a top-down or systems level view of finding optimal, sustainable solutions to difficult environmental (including radioactive waste) problems. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2022

GDSA - Modeling and Integration – ORNL: PFLOTRAN modeling

This report summarizes work done at Oak Ridge National Laboratory (ORNL) related to post-closure criticality consequence analysis of dual-purpose canister (DPC) direct disposal in unsaturated alluvium. PFLOTRAN software was used to model the behavior of a breached DPC with low water infiltration rates and unsaturated conditions in alluvial deposits such that a low-power criticality event occurs with a focus on thermal hydrological constraints on criticality timing and power output. This summary describes initial exploration of those thermal hydrological processes and of the long-term average power output from a criticality event that could be sustained without driving water out of the DPC package and thereby terminating the criticality event. The objectives are (1) to identify, for different groundwater infiltration rates, the time at which the DPC fills with water sufficiently to potentially initiate criticality; (2) to bound the power output that could be produced by a criticality event that would thermally drive water out of the package at various percolation rates; and (3) provide an estimate of how the size of a package breach affects the water infiltration and therefore the possibility timing of criticality.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2022

Post-closure Nuclear Criticality Safety Evaluations for Disposition of Criticality Control Overpacks at the Waste Isolation Pilot Plant

The Waste Isolation Pilot Plant (WIPP) is a geological repository in southern New Mexico that provides for disposal of transuranic (TRU) wastes from atomic energy defense activities. The Sandia National Laboratories (Sandia) Report, Consideration of Nuclear Criticality When Disposing of Transuranic Waste at the Waste Isolation Pilot Plant, addresses nuclear criticality safety based on the projected inventory characteristics for the initial compliance certification application of WIPP in 1996. As the inventory, waste forms, and disposal package designs change, revised or new analyses are necessary to demonstrate acceptability for these configurations within the WIPP safety basis and compliance with 10,000-year post-closure standards of the US Environmental Protection Agency (EPA). Saylor and Scaglione evaluated criticality control overpacks (CCOs) in 2017 based on conservative assumptions for post-closure repository structural conditions with resulting effects on containers and container spacing, The Saylor and Scaglione evaluation of CCOs addressed a single waste configuration that represents the Surplus Plutonium Disposition Program’s dilute and dispose waste form and composition. This initial CCO study demonstrated that 50 grams of boron carbide (B 4 C) per CCO is sufficient to ensure post-closure criticality safety based on a well-mixed waste composition, and Oak Ridge National Laboratory (ORNL) subsequently determined that this amount of B 4 C does not require constraints on moisture or plastic present as moderator. The Saylor and Scaglione analysis conservatively assumes repository room closure that eliminates all space between fissile gram equivalent (FGE) 239 Pu masses. The close-packed array was selected based on limited availability of repository salt creep modeling results at that time. In 2019, Brickner provided additional evaluations for pipe overpack containers (POCs), building on the conservative basis provided by Saylor and Scaglione. Brickner’s 2019 analysis made use of new geomechanical data for post-closure spacing that rely on advances in repository modeling as documented in the work by Reedlunn and Bean. This current CCO evaluation for generic waste materials expands on earlier work performed at ORNL and includes evaluation of CCOs across a much broader range of possible waste compositions and geometries. This evaluation is intended to provide input for the required feature, event and process (FEP) screening to determine if post-closure criticality must be included as an event in the 10,000-year regulatory evaluation. As such, the approach to modeling post-closure criticality presented in this report has been coordinated with the Sandia team responsible for FEP screening. The resulting analysis supports disposition of fissile materials in the CCO containing up to 380 FGE 239 Pu and expands conditions acceptable for disposal of fissile material in CCOs. This evaluation builds on the methodology of Saylor and Scaglione and Brickner, using the most recently available geomechanical data for CCO spacing under salt creep compaction scenarios provided by Reedlunn and Bean. The broad range of fissile material configurations analyzed in this report are intended to account for configurations that may occur during the post-closure disposal time period, and it also includes waste configurations that are not physically possible to support analysis of conditions that influence neutron fluence.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2021

“Scrutinizing entrainment and mass flux closures in shallow cumulus parameterizations using cloud-radar observations and large-eddy simulation” (Final report for DOE grant)

Warm, shallow clouds are responsible for a substantial portion of Earth System Model (ESM) uncertainty and divergence among model climate projections. A substantial amount of this uncertainty is tied to the representation of convection in ESMs, in particular assumptions underlying the convective parameterizations. This study focuses on entrainment and entrainment closures in ESM parameterizations. The completed project was a joint observational and modeling study to observationally derive estimates of entrainment and to use high-resolution modeling to scrutinize entrainment and mass flux closures in shallow convection parameterizations.

58 GEOSCIENCES↗
NASA NTRS1989

Nonlinear fracture of concrete and ceramics

The nonlinear fracture process zones in an impacted unnotched concrete bend specimen, a prenotched ceramic bend specimen, and an unnotched ceramic/ceramic composite bend specimen were estimated through hybrid experimental numerical analysis. Aggregate bridging in concrete, particulate bridging in ceramics, and fiber bridging in ceramic/ceramic composite are modeled by Barenblatt-type cohesive zones which are incorporated into the finite-element models of the bend specimens. Both generation and propagation analyses are used to estimate the distribution of crack closure stresses in the nonlinear fracture process zones. The finite-element models are then used to simulate fracture tests consisting of rapid crack propagation in an impacted concrete bend specimen, and stable crack growth and strain softening in a ceramic and ceramic/ceramic composite bend specimens.

Kobayashi, Albert S.↗
DOE OSTI2020

Reynolds-Averaged Turbulence Modeling Using Deep Learning with Local Flow Features: An Empirical Approach

Reynolds-Averaged Navier-Stoke (RANS) models offer an alternative avenue in predicting flow characteristics when the corresponding experiments are difficult to achieve due to geometry complexity, limited budget, or knowledge. RANS models require the knowledge of subgrid scale physics to solve conservation equations for mass, energy, and momentum. Mechanistic turbulence models, such as k-epsilon, are generally evaluated and calibrated for specific flow conditions with various degrees of uncertainty. These models have limited capability to assimilate a substantial amount of data due to model form constraints. Meanwhile, deep learning (DL) has been proven to be universal approximators with the potential to assimilate available, relevant, and adequately evaluated data. Moreover, deep neural networks (DNNs) can create surrogate models without knowing function forms. Such a data-driven approach can be used in updating fluid models based on observations as opposed to hard-wiring models with precalibrated correlations. The paper presents progress in applying DNNs to model Reynolds stress using two machine learning (ML) frameworks. A novel flow feature coverage mapping is proposed to quantify the physics coverage of DL-based closures. It can be used to examine the sufficiency of training data and input flow features for data-driven turbulence models. The case of a backward-facing step is formulated to demonstrate that not only can DNNs discover underlying correlation behind fluid data but also they can be implemented in RANS to predict flow characteristics without numerical stability issues. Finally, the presented research is a crucial stepping-stone toward the data-driven turbulence modeling, which potentially benefits the design of data-driven experiments that can be used to validate fluid models with ML-based fluid closures.

42 ENGINEERING↗
DOE OSTI2014

Physics of forced magnetic reconnection in coaxial helicity injection experiments in National Spherical Torus Experiment

We numerically examine the physics of fast flux closure in transient coaxial helicity injection (CHI) experiments in National Spherical Torus Experiment (NSTX). By performing resistive Magnetohydrodynamics (MHD) simulations with poloidal injector coil currents held constant in time, we find that closed flux surfaces are formed through forced magnetic reconnection. Through a local Sweet-Parker type reconnection with an elongated current sheet in the injector region, closed flux surfaces expand in the NSTX global domain. Simulations demonstrate outflows approaching poloidally Alfvénic flows and reconnection times consistent with the Sweet-Parker model. Critical requirements for magnetic reconnection and flux closure are studied in detail. These primary effects, which are magnetic diffusivity, injector flux, injector flux footprint width, and rate of injector voltage reduction, are simulated for transient CHI experiments. The relevant time scales for effective reconnection are τ{sub V}<τ{sub rec}≈τ{sub A}√(S)(1+Pm){sup 1/4}<τ{sub R}, where τ{sub V} is the time for the injector voltage reduction, τ{sub A} is the poloidal Alfvén transit time, τ{sub R} is the global resistive diffusion time, and Pm and S are Prandtl and Lundquist numbers.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
NASA NTRS1985

On the divergence of the Hall current in the westward traveling surge

Recent observations suggest that the Hall current tends to be highly divergence-free in the westward traveling surge. It is shown in a model calculation that the blockage of the Hall current from closure along field lines leads to a significant reduction of the divergence of the Hall current, but is not divergence-free. The westward electrojet in this models is found to rotate counterclock wise around the leading edge of the surge and merge into the eastward electrojet. The difference in strength between the two electrojets at the head of the surge goes into the upward field-aligned current. It is also shown that the conductivity enhanced by the discrete auroral precipitation does not contribute to the divergence of the Hall current, provided that the electric fields are coplanar along a field line. The above results strongly suggest that the Hall current tends to be highly divergence-free in regions of bright auroral forms, especially in the westward traveling surge.

Kan, J. R.↗
DOE OSTI2018

A Hybrid Approach for Model Order Reduction of Barotropic Quasi-Geostrophic Turbulence

We put forth a robust reduced-order modeling approach for near real-time prediction of mesoscale flows. In our hybrid-modeling framework, we combine physics-based projection methods with neural network closures to account for truncated modes. We introduce a weighting parameter between the Galerkin projection and extreme learning machine models and explore its effectiveness, accuracy and generalizability. To illustrate the success of the proposed modeling paradigm, we predict both the mean flow pattern and the time series response of a single-layer quasi-geostrophic ocean model, which is a simplified prototype for wind-driven general circulation models. We demonstrate that our approach yields significant improvements over both the standard Galerkin projection and fully non-intrusive neural network methods with a negligible computational overhead.

42 ENGINEERING↗
DOE OSTI2017

Increasing atmospheric humidity and CO 2 concentration alleviate forest mortality risk

Climate-induced forest mortality is being increasingly observed throughout the globe. Alarmingly, it is expected to exacerbate under climate change due to shifting precipitation patterns and rising air temperature. However, the impact of concomitant changes in atmospheric humidity and CO 2 concentration through their influence on stomatal kinetics remains a subject of debate and inquiry. By using a dynamic soil–plant–atmosphere model, mortality risks associated with hydraulic failure and stomatal closure for 13 temperate and tropical forest biomes across the globe are analyzed. The mortality risk is evaluated in response to both individual and combined changes in precipitation amounts and their seasonal distribution, mean air temperature, specific humidity, and atmospheric CO 2 concentration. Model results show that the risk is predicted to significantly increase due to changes in precipitation and air temperature regime for the period 2050–2069. However, this increase may largely get alleviated by concurrent increases in atmospheric specific humidity and CO 2 concentration. The increase in mortality risk is expected to be higher for needleleaf forests than for broadleaf forests, as a result of disparity in hydraulic traits. These findings will further facilitate decisions about intervention and management of different forest types under changing climate.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Ice‐Nucleating Particles That Impact Clouds and Climate: Observational and Modeling Research Needs

Abstract Atmospheric ice‐nucleating particles (INPs) play a critical role in cloud freezing processes, with important implications for precipitation formation and cloud radiative properties, and thus for weather and climate. Additionally, INP emissions respond to changes in the Earth System and climate, for example, desertification, agricultural practices, and fires, and therefore may introduce climate feedbacks that are still poorly understood. As knowledge of the nature and origins of INPs has advanced, regional and global weather, climate, and Earth system models have increasingly begun to link cloud ice processes to model‐simulated aerosol abundance and types. While these recent advances are exciting, coupling cloud processes to simulated aerosol also makes cloud physics simulations increasingly susceptible to uncertainties in simulation of INPs, which are still poorly constrained by observations. Advancing the predictability of INP abundance with reasonable spatiotemporal resolution will require an increased focus on research that bridges the measurement and modeling communities. This review summarizes the current state of knowledge and identifies critical knowledge gaps from both observational and modeling perspectives. In particular, we emphasize needs in two key areas: (a) observational closure between aerosol and INP quantities and (b) skillful simulation of INPs within existing weather and climate models. We discuss the state of knowledge on various INP particle types and briefly discuss the challenges faced in understanding the cloud impacts of INPs with present‐day models. Finally, we identify priority research directions for both observations and models to improve understanding of INPs and their interactions with the Earth System.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Large-Eddy Simulations of Idealized Atmospheric Boundary Layers Using Nalu-Wind

Accurate prediction of wind-plant performance relies, in part, on properly characterizing the turbulent atmospheric boundary layer (ABL) flow in which wind turbines operate. Large-eddy simulation (LES) is a powerful tool for simulating ABLs because it resolves the largest, most energetic scales of three-dimensional turbulent motions. Yet LES predictions are well known to depend on modeling choices such as grid resolution, numerical discretization schemes, and closures for unresolved scales of turbulence. Here, we evaluate how these choices influence predictions of ABL winds using Nalu-Wind, a wind-specific fork of the open-source, generalized, unstructured, massively parallel flow solver NaluCFD/Nalu.

17 WIND ENERGY↗