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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 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Effect of natural fractures on determining closure pressure

Abstract In Utah FORGE reservoir, eight pressure transient tests (microhydraulic fracturing and DFIT™) show natural fracture/pressure-dependent leakoff. This behavior may lead to misinterpretation of the closure pressure (proxy for minimum principal stress). The closure pressures obtained from DFIT™ (or microhydraulic fracturing) testing may reflect shear failure along natural fractures or discontinuities rather than tensile failure and lead to inaccurate estimates of the minimum principal stress. In pressure tests conducted at the Utah FORGE site showed that reactivation or opening of natural fractures intersecting the wellbore and were suggested by multiple closure events in DFIT™ tests. In addition, comparisons between the pre- and post-well-tests FMI logs show that there are populations of induced fracture and reactivated natural fractures which are mostly vertical and sub-vertical. In this study, DFIT™ (or microhydraulic fracturing) test analysis and numerical simulations were used to suggest that hydraulic shearing of critically stressed natural fractures can contribute to multiple closure signatures and possibly lead to incorrect determination of the minimum principal stress. As other authors have previously advocated, the DFIT™ test analyses and numerical simulations suggest that better estimations of minimum principal stress may be derived by injecting at relatively high rate and pressure and insuring that tensile breakdown is reached. In addition, extended shut-in period is required to determine accurate reservoir characteristics and fluid flow regime.

Nadimi, S.↗
DOE OSTI2021

Direct observations and characterization of crack closure during microstructurally small fatigue crack growth via in-situ high-energy X-ray characterization

This study provides direct observation of the crack closure mechanism of a naturally occurring, tortuous, 3D microstructurally small fatigue crack (SFC) in additively manufactured Inconel 718. In-situ non-destructive characterization is performed using high-energy X-ray diffraction techniques to capture the evolution of the 3D microstructure and micromechanical response in the vicinity of the crack front. Based on the stress state of twelve grains analyzed at the crack tip, the crack closure events of the SFC front was found to be spatially heterogeneous with respect to loading progression governed by the local stress state of the grains (specifically the stress reversal from compression to tension). From this analysis, three grains that displayed different degrees of crack closure were further investigated, based on the orientation of the crack relative to the grains and the associated modality of crack growth. The stress normal to the crack plane and the associated degree of Mode I crack behavior were correlated with events of the crack opening earlier during the loading cycle. This was further corroborated by diffraction spot spreading analysis that quantified the crystallographic lattice distortion caused by the opening crack. Additionally, the detailed characterization of the opening behavior of the grains located at the crack tip and their associated states of stress elucidates the mechanism governing crack closure and will inform future modeling efforts of this phenomenon.

36 MATERIALS SCIENCE↗
DOE OSTI2023

A multifidelity deep operator network approach to closure for multiscale systems

Projection-based reduced order models (PROMs) have shown promise in representing the behavior of multiscale systems using a small set of generalized (or latent) variables. Despite their success, PROMs can be susceptible to inaccuracies, even instabilities, due to the improper accounting of the interaction between the resolved and unresolved scales of the multiscale system (known as the closure problem). In the current work, we interpret closure as a multifidelity problem and use a multifidelity deep operator network (DeepONet) framework to address it. In addition, to enhance the stability and/or accuracy of the multifidelity-based closure, we employ the recently developed ``in-the-loop" training approach from the literature on coupling physics and machine learning models. The resulting approach is tested on shock advection for the one-dimensional viscous Burgers equation and vortex merging for the two-dimensional Navier-Stokes equations. Furthermore, the numerical experiments show significant improvement of the predictive ability of the closure-corrected PROM over the un-corrected one both in the interpolative and the extrapolative regimes.

42 ENGINEERING↗
DOE OSTI2019

A regularized deconvolution method for turbulent closure modeling in implicitly filtered large-eddy simulation

Turbulence closure models that are based on a regularized deconvolution method (RDM) are proposed for application to implicitly filtered Large-Eddy Simulation (LES). This method reconstructs sub-grid scale contributions by approximately recovering filtered quantities through an optimization approach. Physical principles on the boundedness and conservation of reconstructed quantities are preserved by constraining the optimization problem. Further, to account for effects of scales that are not resolved in implicitly filtered LES, a reconstruction method is proposed that combines sub-grid projection and energy-similarity to enrich unresolved scales. With this method, closure models are developed for turbulent scalar fluxes and turbulence–chemistry interaction that are intrinsically consistent with the LES formulation. These closure models are evaluated in application to a piloted turbulent jet flame with inhomogeneous inlet composition, in which combustion is represented by a two-scalar manifold model. The RDM-formulation is benchmarked against simulations obtained using a presumed PDF method and eddy diffusivity closure model. In partially-premixed flame regions, it is observed that RDM improves the prediction of turbulent mixing, and faster grid convergence is observed for results with RDM compared to simulations employing a presumed PDF method.

42 ENGINEERING↗
DOE OSTI2020

Deep learning interfacial momentum closures in coarse-mesh CFD two-phase flow simulation using validation data

Multiphase flow phenomena have been widely observed in the industrial applications while it remains a challenging yet unsolved problems. Three-dimensional computational fluid dynamics (CFD) approaches resolve the flow fields on a finer special and temporal scales which can complement the dedicated experimental study. However, closures have to be introduced to reflect the underlying physics in multiphase flow. Among them, the interfacial forces, including drag, lift, turbulent dispersion and wall lubrication forces, play in important role on the bubble’s distribution and migration in liquid-vapor two-phase flow. Development of those closures traditionally rely on the experimental data and analytical derivation with simplified assumptions which usually cannot deliver a universal solution across wide range of flow conditions. In this paper, a data-driven approach, named as Feature Similarity Measurement (FSM), is developed and applied to improve the simulation capability of two-phase flow with coarse-mesh CFD approach. Interfacial momentum transfer in adiabatic bubbly flow serves as the focus of the present study. Both a mature and a simplified set of interfacial closures are taken as the low fidelity data. Experimental data and fine mesh CFD simulations results are adopted as high-fidelity data. Qualitative and quantitative analysis are performed in this paper which reveals that FSM can substantially improve the prediction of coarse mesh CFD model regardless of the choice of interfacial closures and it provides scalability and consistency across discontinuous flow regimes. Furthermore, it demonstrates that data-driven method can aid the multiphase flow modeling by exploring the connections between local physical features and simulation errors.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Unified Entrainment and Detrainment Closures for Extended Eddy-Diffusivity Mass-Flux Schemes

The extended Eddy Diffusivity Mass Flux (EDMF) scheme is used as a unied parameterization that simulates subgrid-scale dynamics across a range of regimes.This work presents unied entrainment and detrainment closures that allow this scheme to simulate the dry convective boundary layer, shallow convection and deep convection , while adjacent works present other necessary closures for this unied scheme and test its performance for stable, stratocumulus topped and convective boundary layers. Entrainment and detrainment are modeled as a combination of turbulent and dynamical processes. The turbulent component is taken as downgradient diffusion between subdomains. The dynamical component is based on a ratio of buoyancy and vertical velocity that ensures consistent treatment of the ratio of mass-flux at vanishing area fraction. Dynamical detrainment is controlled by the difference in relative humidity between subdomains when liquid water is present. These closures are rst evaluated with entrainment and detrainment diagnosed from Large Eddy Simulations where decaying tracers are used to identify the different subdomains and mass exchanges between them. When implemented in a single column model (SCM), these closures are tested in simulations of several observationally motivated cases of dry convective boundary layer, shallow convection and deep convection. Results show good agreement between the SCM and Large Eddy Simulations in key properties for climate models and profiles of first, second and third moments. The development of diurnal cycles and the onset of and precipitation (with simplified microphysics) are well predicted by the SCM.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2015

Multivariate moment closure techniques for stochastic kinetic models

Stochastic effects dominate many chemical and biochemical processes. Their analysis, however, can be computationally prohibitively expensive and a range of approximation schemes have been proposed to lighten the computational burden. These, notably the increasingly popular linear noise approximation and the more general moment expansion methods, perform well for many dynamical regimes, especially linear systems. At higher levels of nonlinearity, it comes to an interplay between the nonlinearities and the stochastic dynamics, which is much harder to capture correctly by such approximations to the true stochastic processes. Moment-closure approaches promise to address this problem by capturing higher-order terms of the temporally evolving probability distribution. Here, we develop a set of multivariate moment-closures that allows us to describe the stochastic dynamics of nonlinear systems. Multivariate closure captures the way that correlations between different molecular species, induced by the reaction dynamics, interact with stochastic effects. We use multivariate Gaussian, gamma, and lognormal closure and illustrate their use in the context of two models that have proved challenging to the previous attempts at approximating stochastic dynamics: oscillations in p53 and Hes1. In addition, we consider a larger system, Erk-mediated mitogen-activated protein kinases signalling, where conventional stochastic simulation approaches incur unacceptably high computational costs.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2018

Electron parallel closures for the 3 + 1 fluid model

Linear closures are obtained for arbitrary collisionality for the 3 + 1 fluid model which includes the evolution of density, flow velocity, and pressure both parallel and perpendicular to a preferred direction, usually a magnetic field. A large set of 6400 moment equations is solved to provide closures that are accurate in the collisional regime and well into the collisionless regime. The closures in the collisionless limit are determined by solving the kinetic equation with a model collision operator. Simple fits for the kernel functions that define the closures are obtained for arbitrary collisionality in wave number space. The results are linearly accurate to within 3% across the entire range of collisionality.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Neural network representability of fully ionized plasma fluid model closures

The closure problem in fluid modeling is a well-known challenge to modelers aiming to accurately describe their systems of interest. Over many years, analytic formulations in a wide range of regimes have been presented but a practical, generalized fluid closure for magnetized plasmas remains an elusive goal. Here, as a first step toward constructing a novel data-based approach to this problem, we apply ever-maturing machine learning methods to assess the capability of neural network architectures to reproduce crucial physics inherent in known magnetized plasma closures. We find encouraging results, indicating the applicability of neural networks to closure physics, but also arrive at recommendations on how one should choose appropriate network architectures for the given locality properties dictated by the underlying physics of the plasma.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Supervised machine learning-based multivariate regression of parallel closures for a high-collisionality deuterium-carbon plasma

Many plasmas of interest in laboratory experiments and space consist of multiple ion species. In tokamak edge plasmas, for instance, ionized impurities expelled from the vessel wall influence plasma transport. When describing multi-species plasmas using fluid equations, we need accurate closure relations to close the set of fluid equations. In this study, we introduce the development of fitting formulas for parallel closures using supervised machine learning, in conjunction with the recent closure theory, considering multi-ion collisions and arbitrary ion temperatures. We apply this approach to a high-collisionality deuterium-carbon plasma and demonstrate its effectiveness. As a result, the machine learning-based method for developing practical and accurate closures can be extended to a wider range of plasmas.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Ethical considerations in infectious disease modelling for public health policy: the case of school closures

Mathematical models of infectious diseases are frequently used as a tool to support public health policy and decisions around the implementation of interventions such as school closures. However, most publications on policy-relevant modelling lack an ethical framework and do not explicitly consider the ethical implications of the work. This creates a risk that the unintended consequences of interventions are overlooked or that models are used to justify decisions that are inconsistent with public health ethics. In this article, we focus on the case study of school closures as a commonly modelled intervention against pandemic influenza, COVID-19 and other infectious disease threats. We briefly review some of the key concepts in public health ethics and describe approaches to modelling the effects of school closures. We then identify a series of ethical considerations involved in modelling school closures. These include accounting for population heterogeneity and inequalities; including a diversity of viewpoints and expertise in model design; considering the distribution of benefits and harms; and model transparency and contextualization. Furthermore, we conclude with some recommendations to ensure that policy-relevant modelling is consistent with some key ethics values.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

Observation of a periodic array of flux-closure quadrants in strained ferroelectric PbTiO 3 films

Nanoscale ferroelectrics are expected to exhibit various exotic domain configurations, such as the full flux-closure pattern that is well known in ferromagnetic materials. Here we observe not only the atomic morphology of the flux-closure quadrant but also a periodic array of flux closures in ferroelectric PbTiO 3 films, mediated by tensile strain on a GdScO 3 substrate. Using aberration-corrected scanning transmission electron microscopy, we directly visualize an alternating array of clockwise and counterclockwise flux closures, whose periodicity depends on the PbTiO 3 film thickness. In the vicinity of the core, the strain is sufficient to rupture the lattice, with strain gradients up to 10 9 per meter. We found engineering strain at the nanoscale may facilitate the development of nanoscale ferroelectric devices.

36 MATERIALS SCIENCE↗
DOE OSTI2019

An Improved Double-Gaussian Closure for the Subgrid Vertical Velocity Probability Distribution Function

Abstract The vertical velocity probability distribution function (PDF) is analyzed throughout the depth of the lower atmosphere, including the subcloud and cloud layers, in four large-eddy simulation (LES) cases of shallow cumulus and stratocumulus. Double-Gaussian PDF closures are examined to test their ability to represent a wide range of turbulence statistics, from stratocumulus cloud layers characterized by Gaussian turbulence to shallow cumulus cloud layers displaying strongly non-Gaussian turbulence statistics. While the majority of the model closures are found to perform well in the former case, the latter presents a considerable challenge. A new model closure is suggested that accounts for high skewness and kurtosis seen in shallow cumulus cloud layers. The well-established parabolic relationship between skewness and kurtosis is examined, with results in agreement with previous studies for the subcloud layer. In cumulus cloud layers, however, a modified relationship is necessary to improve performance. The new closure significantly improves the estimation of the vertical velocity PDF for shallow cumulus cloud layers, in addition to performing well for stratocumulus. In particular, the long updraft tail representing the bulk of cloudy points is much better represented and higher-order moments diagnosed from the PDF are also greatly improved. However, some deficiencies remain owing to fundamental limitations of representing highly non-Gaussian turbulence statistics with a double-Gaussian PDF.

Fitch, A. C.↗
DOE OSTI2013

Post-Closure Inspection and Monitoring Report for Corrective Action Unit 417: Central Nevada Test Area Surface, Hot Creek Valley, Nevada

This report presents results of data collected during the annual post-closure site inspections conducted at the Central Nevada Test Area surface Corrective Action Unit (CAU) 417 in May 2011 and July 2012. The annual post-closure site inspections included inspections of the UC-1, UC-3, and UC-4 sites in accordance with the Post-Closure Monitoring Plan provided in the CAU 417 Closure Report (NNSA/NV 2001). The annual inspections conducted at the UC-1 Central Mud Pit (CMP) indicated that the site and soil cover were in good condition. No new fractures or extension of existing fractures were observed and no issues with the fence or gate were identified. The vegetation on the cover continues to look healthy, but the biennial vegetation survey conducted during the 2012 inspection indicated that the total foliar cover was slightly higher in 2009 than in 2012. This may be indicative of a decrease in precipitation observed during the 2-year monitoring period. The precipitation totaled 9.9 inches from July 1, 2010, through June 30, 2011, and 5 inches from July 1, 2011, through June 30, 2012. This decrease in precipitation is also evident in the soil moisture data obtained from the time domain reflectometry sensors. Soil moisture content data show that the UC-1 cover is performing as designed, and evapotranspiration is effectively removing water from the cover.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Corrective Action Management Unit Report of Post-Closure Care Activities Calendar Year 2017.

The Corrective Action Management Unit (CAMU) at Sandia National Laboratories, New Mexico (SNL/NM) consists of a containment cell and ancillary systems that underwent regulatory closure in 2003 in accordance with the Closure Plan in Appendix D of the Class 3 Permit Modification (SNL/NM September 1997). The containment cell was closed with wastes in place. On January 27, 2015, the New Mexico Environment Department (NMED) issued the Hazardous Waste Facility Operating Permit (Permit) for Sandia National Laboratories (NMED January 2015). The Permit became effective February 26, 2015. The CAMU is undergoing post-closure care in accordance with the Permit, as revised and updated. This CAMU Report of Post-Closure Care Activities documents all activities and results for Calendar Year (CY) 2017 as required by the Permit. The CAMU containment cell consists of engineered barriers including a cover system, a bottom liner with a leachate collection and removal system (LCRS), and a vadose zone monitoring system (VZMS). The VZMS provides information on soil conditions under the cell for early leak detection. The VZMS consists of three monitoring subsystems, which include the primary subliner (PSL), a vertical sensor array (VSA), and the Chemical Waste Landfill (CWL) sanitary sewer (CSS) line. The PSL, VSA, and CSS monitoring subsystems are monitored quarterly for soil moisture concentration, the VSA is monitored quarterly for soil temperature, and the VSA and CSS monitoring subsystems are monitored annually for volatile organic compound (VOC) concentrations in the soil vapor at various depths. Baseline data for the soil moisture, soil temperature, and soil vapor were established between October 2003 and September 2004.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2018

Chemical Waste Landfill Annual Post-Closure Report Calendar Year 2017

The Chemical Waste Landfill (CWL) at SNL/New Mexico (SNL/NM) is a remediated hazardous waste landfill that underwent closure. The CWL Post-Closure Care Permit (PCCP), which became effective June 2, 2011 and as modified, defines all post-closure requirements. This sixth CWL Annual Post-Closure Care Report documents all activities and results as required by the PCCP Attachment 1, Section 1.12.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2019

Closure Report for Corrective Action Unit 424: Area 3 Landfill Complex, Tonopah Test Range, Nevada, Revision 0. with ROTC 1

This Closure Report provides the documentation for closure of the Area 3 Landfill Complex Corrective Action Unit (CAU) 424. The site is located on the Tonopah Test Range, approximately 225 kilometers (140 miles) northwest of Las Vegas, Nevada. The purpose of this CR is to: Document the closure activities and provide the information collected, as recommended in the CADD. (DOE, 1998a) and proposed in the CAP (DOE~ 1998b ); Provide a Post-Closure Inspection Plan; Obtain a Notice of Completion from the NDEP; Recommend the movement of CAU 424 from Appendix III to Appendix IV of the FFACO.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Corrective Action Management Unit Report of Post-Closure Care Activities Calendar Year 2019

The Corrective Action Management Unit (CAMU) at Sandia National Laboratories, New Mexico (SNL/NM) consists of a containment cell and ancillary systems that underwent closure in 2003 in accordance with the Closure Plan in Appendix D of the Class 3 Permit Modification (SNL/NM September 1997). The containment cell was closed with wastes in place. On January 27, 2015, the New Mexico Environment Department (NMED) issued the Hazardous Waste Facility Operating Permit (Permit) for Sandia National Laboratories (NMED January 2015) to the U.S. Department of Energy/National Nuclear Security Administration (DOE/NNSA) and its Management and Operating (M&O) contractor. The current M&O contractor is National Technology & Engineering Solutions of Sandia, LLC (NTESS). The Permit became effective February 26, 2015. The CAMU is undergoing post-closure care in accordance with the Permit, as revised and updated. This CAMU Report of Post-Closure Care Activities documents all activities and results for calendar year (CY) 2019, as required by the Permit.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗