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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 1,279 records · Page 71
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

Preliminary Evaluation of the DUSTRAN Modeling Suite for Modeling Atmospheric Chloride Transport

This study investigates the potential of DUSTRAN, a dust dispersion modeling system developed by Pacific Northwest National Laboratory, to model the transport of sea salt aerosols (SSA). Results from DUSTRAN simulations run with historical meteorological data were compared against privately-measured chloride data at the near coastal Maine Yankee Nuclear Power Plant (NPP) and the Environmental Protection Agency-measured CASTNET data from Acadia National Park (NP). The comparisons have provided both encouragement as to the practical value of DUSTRAN’s CALPUFF model and suggestions for further software development opportunities. All modeled concentrations were within one order of magnitude of those measured and a few test cases showed excellent agreement between modeled and measured concentrations. However, there is a lack of consistency in discrepancy which may be due to inaccurate extrapolation of meteorological data, underlying model physics, and the source term. Future research will refine the software to better capture physical phenomena. Overall, results indicate that with parameter refinement, DUSTRAN has the potential to simulate atmospheric chloride transport from known sources to inland sites for the purpose of determining the corrosion susceptibility of various structures, systems, and components at the site.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Strong-coupling expansion of multi-band interacting models: Mapping onto the transverse-field J 1 - J 2 Ising model

We investigate a class of two-dimensional two-band microscopic models in which the inter-band repulsive interactions play the dominant role. We first demonstrate three different schemes of constraining the ratios between the three types of inter-band interactions – density-density, spin exchange, and pair-hopping – that render the model free of the fermionic sign-problem for any filling and, consequently, amenable to efficient Quantum Monte Carlo simulations. We then study the behavior of these sign-problem-free models in the strong-coupling regime. In the cases where spin-rotational invariance is preserved or lowered to a planar symmetry, the strong-coupling ground state is a quantum paramagnet. However, in the case where there is only a residual Ising symmetry, the strong-coupling expansion maps onto the transverse-field J 1 - J 2 Ising model, whose pseudospins are associated with local inter-band magnetic order. We show that by varying the band structure parameters within a reasonable range of values, a variety of ground states and quantum critical points can be accessed in the strong-coupling regime, some of which are not realized in the weak-coupling regime. Here, we compare these results with the case of the single-band Hubbard model, where only intra-band repulsion is present, and whose strong-coupling behavior is captured by a simple Heisenberg model.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

Modeling and Evaluation of Cyber-Attacks on Grid-Interactive Efficient Buildings

Grid-interactive efficient buildings (GEBs) are not only exposed to passive threats (e.g., physical faults) but also active threats such as cyber-attacks launched on the network-based control systems. The impact of cyber-attacks on GEB operation are not yet fully understood, especially as regards the performance of grid services. To quantify the consequences of cyber-attacks on GEBs, this paper proposes a modeling and simulation framework that includes different cyber-attack models and key performance indexes to quantify the performance of GEB operation under cyber-attacks. The framework is numerically demonstrated to model and evaluate cyber-attacks such as data intrusion attacks and Denial-of-Service attacks on a typical medium-sized office building that uses the BACnet/IP protocol for communication networks. Simulation results show that, while different types of attacks could compromise the building systems to different extents, attacks via the remote control of a chiller yield the most significant consequences on a building system’s operation, including both the building service and the grid service. It is also noted that a cyber-attack impacts the building systems during the attack period as well as the post-attack period, which suggests that both periods should be considered to fully evaluate the consequences of a cyber-attack.

Fu, Yanyang↗
DOE OSTI2025

Coupled THM modeling of bentonite heating and hydration in tank tests with a new temperature-dependent water retention model

This study presents a coupled thermo-hydro-mechanical (THM) model for simulating the heating and hydration behavior of bentonite, a buffer material in deep geological repositories (DGRs). The model incorporates a new temperature-dependent soil water retention curve which captures the thermal-induced shift in water retention behavior. It also distinguishes between liquid and gas permeability, modeling intrinsic gas permeability as a function of accessible porosity to improve vapor transport and desaturation predictions. The model was validated against two large-scale tank tests, demonstrating good agreement with measured temperature, relative humidity, and water inflow data. It revealed a complex porosity evolution driven by thermal expansion, vapor movement, vapor condensation, and hydration-induced swelling during heating and hydration processes. The simulation results also suggest that the permeability of the hydration layer plays a critical role in controlling water intake. Clogging of this layer can significantly reduce the volume of water inflow during the hydration phase. Furthermore, while the model effectively captures key THM behavior, further development of the mechanical constitutive law is required to account for possible thermo-elasto-plastic volume changes and microstructural effects. Overall, the model provides a robust tool for evaluating the evolution of bentonite-based barrier material in DGRs.

Guo, Guanlong [Lawrence Berkeley National Laborato↗
DOE OSTI2012

COMPARING MODEL RESULTS TO NATIONAL CLIMATE POLICY GOALS: RESULTS FROM THE ASIA MODELING EXERCISE

While the world has yet to adopt a single unified policy to limit climate change, many countries and regions have adopted energy and climate policies that have implications for global emissions. In this paper, we discuss a few key policies and how they are included in a set of 24 energy and integrated assessment models that participated in the Asia Modeling Exercise. We also compare results from these models for a small set of stylized scenarios to the pledges made as part of the Copenhagen Accord and the goals stated by the Major Economies Forum. We find that the targets outlined by the United States, the European Union, Japan, and Korea require significant policy action in most of the models analyzed. For most of the models in the study, however, the goals outlined by India are met without any climate policy. The stringency of climate policy required to meet China’s Copenhagen pledges varies across models and accounting methodologies.

Calvin, Katherine V↗
DOE OSTI2013

Volume-translated cubic EoS and PC-SAFT density models and a free volume-based viscosity model for hydrocarbons at extreme temperature and pressure conditions

This research focuses on providing the petroleum reservoir engineering community with robust models of hydrocarbon density and viscosity at the extreme temperature and pressure conditions (up to 533 K and 276 MPa, respectively) characteristic of ultra-deep reservoirs, such as those associated with the deepwater wells in the Gulf of Mexico. Our strategy is to base the volume-translated (VT) Peng–Robinson (PR) and Soave–Redlich–Kwong (SRK) cubic equations of state (EoSs) and perturbed-chain, statistical associating fluid theory (PC-SAFT) on an extensive data base of high temperature (278–533 K), high pressure (6.9–276 MPa) density rather than fitting the models to low pressure saturated liquid density data. This high-temperature, high-pressure (HTHP) data base consists of literature data for hydrocarbons ranging from methane to C{sub 40}. The three new models developed in this work, HTHP VT-PR EoS, HTHP VT-SRK EoS, and hybrid PC-SAFT, yield mean absolute percent deviation values (MAPD) for HTHP hydrocarbon density of ~2.0%, ~1.5%, and <1.0%, respectively. An effort was also made to provide accurate hydrocarbon viscosity models based on literature data. Viscosity values are estimated with the frictional theory (f-theory) and free volume (FV) theory of viscosity. The best results were obtained when the PC-SAFT equation was used to obtain both the attractive and repulsive pressure inputs to f-theory, and the density input to FV theory. Both viscosity models provide accurate results at pressures to 100 MPa but experimental and model results can deviate by more than 25% at pressures above 200 MPa.

02 PETROLEUM↗
DOE OSTI2021

Modeling heat transport processes in enhanced geothermal systems: Validation study from EGS Collab Experiment 1

Heat recovery from enhanced geothermal systems (EGS) is a complex process involving heat transport in both fracture networks and rock formations. A comprehensive understanding of and the ability to model the underlying heat transport mechanisms is important for the success of EGS but remains challenging in practice due to the generally insufficient characterization of EGS reservoirs. In the present study, we analyze an extensively monitored intermediate-scale EGS field experiment performed in a well-characterized testbed. The high-resolution, high-quality measurements from the field experiment enable the development of a high-fidelity model incorporating a well-constrained fracture network. Based on the field experiment, we investigate the complex heat transport processes in an EGS-relevant environment and validate the capability of a numerical approach in simulating these inherently coupled heat transport processes. A series of numerical simulations were performed to study the effects of different heat transport mechanisms, including thermal convection with fracture flow, thermal conduction in rock formations, and the Joule-Thomson effect. The agreement of thermal responses between field measurements and simulation results indicates that our numerical approach can appropriately model the heat transport processes pertaining to heat recovery from EGS reservoirs.

Wu, Hui↗
DOE OSTI2020

Time-Lapse Gravity Monitoring of CO2 Migration Based on Numerical Modeling of a Faulted Storage Complex

In this study, the performance of both surface and borehole time-lapse gravity monitoring to detect CO2 leakage from a carbon storage site is evaluated. Several hypothetical scenarios of CO2 migration in a leaky fault, and thief zones at different depths at the Kimberlina site (California, USA) constitute the basis of the approach. The CO2 displacement is simulated using the TOUGH2 simulator applied to a detailed geological model of the site. The gravity responses to these CO2 plumes are simulated using forward modeling with sensors at ground surface and in vertical boreholes. Results of inversion on one scenario are also presented. The surface-based gravity responses obtained for the different leakage scenarios demonstrate that leakage can be detected at the surface in all the scenarios but the time to detection is highly variable (10 to 40 years) and dependent on the detection threshold considered. Borehole measurements of the vertical component of gravity provide excellent constrains in depth when they are located in proximity of the density anomaly associated with the presence of CO2, thus discriminating multiple leaks in different thief zones. Joint inversion of surface and borehole data can bring valuable information of the occurrence of leakages and their importance by providing a reasonable estimate of mass of displaced fluids. This study demonstrates the importance of combining multiphase flow simulations with gravity modeling in order to define if and when gravity monitoring would be applicable at a given storage site.

Time-lapse gravity monitoring, leak detection, CCS↗
DOE OSTI2025

Modeling aerosol bolus inhalations in the human lung with the multiple path particle deposition model: Comparison with experimental data

Existing one-dimensional (1D) models of aerosol dosimetry often ignore mixing mechanisms of inhaled aerosols during their transport in the lung. This mixing or aerosol dispersion results from different physical mechanisms in different regions of the lung. It is a higher order effect, which cannot be directly captured in 1D modeling approaches, and thus is sometimes modeled as a diffusive process. Here, in this study, we improved our recently developed alveolar mixing module incorporated in the multiple path particle dosimetry model (MPPD) to account for flow irreversibility and particle trapping in the alveolar spaces, as well as mixing occurring in the tracheobronchial region. This new version of MPPD was coupled with CFPD-based predictions of aerosol bolus dispersion in the oral airway. The model was used to predict the deposition, dispersion, and mode shift of aerosol bolus inhaled at different penetration depths within the lung for breathing patterns and particle size matching those used in a previous experimental study (Darquenne et al., 2016). Even though a quite simplified approach was used, the computations appear to describe subject-specific and test-specific experimental data reasonably well. The proposed combined dispersion-deposition model can be a useful tool for targeted drug delivery and also for exposure health risk assessment.

MPPD↗
DOE OSTI2017

Modelling the sulfate capacity of simulated radioactive waste borosilicate glasses

The capacity of simulated high-level radioactive waste borosilicate glasses to incorporate sulfate has been studied as a function of glass composition. Combined Raman, 57 Fe Mössbauer and literature evidence supports the attribution of coordination numbers and oxidation states of constituent cations for the purposes of modelling, and results confirm the validity of correlating sulfate incorporation in multicomponent borosilicate radioactive waste glasses with different models. A strong compositional dependency is observed and this can be described by an inverse linear relationship between incorporated sulfate (mol% SO 4 2- ) and total cation field strength index of the glass, Σ(z/a 2 ), with a high goodness-of-fit (R 2 ≈ 0.950). Similar relationships are also obtained if theoretical optical basicity, Λ th (R 2 ≈ 0.930) or non-bridging oxygen per tetrahedron ratio, NBO/T (R 2 ≈ 0.919), are used. Results support the application of these models, and in particular Σ(z/a 2 ), as predictive tools to aid the development of new glass compositions with enhanced sulfate capacities.

36 MATERIALS SCIENCE↗
DOE OSTI2014

A staggered-grid finite-difference scheme optimized in the time–space domain for modeling scalar-wave propagation in geophysical problems

For modeling scalar-wave propagation in geophysical problems using finite-difference schemes, optimizing the coefficients of the finite-difference operators can reduce numerical dispersion. Most optimized finite-difference schemes for modeling seismic-wave propagation suppress only spatial but not temporal dispersion errors. We develop a novel optimized finite-difference scheme for numerical scalar-wave modeling to control dispersion errors not only in space but also in time. Our optimized scheme is based on a new stencil that contains a few more grid points than the standard stencil. We design an objective function for minimizing relative errors of phase velocities of waves propagating in all directions within a given range of wavenumbers. Dispersion analysis and numerical examples demonstrate that our optimized finite-difference scheme is computationally up to 2.5 times faster than the optimized schemes using the standard stencil to achieve the similar modeling accuracy for a given 2D or 3D problem. Compared with the high-order finite-difference scheme using the same new stencil, our optimized scheme reduces 50 percent of the computational cost to achieve the similar modeling accuracy. This new optimized finite-difference scheme is particularly useful for large-scale 3D scalar-wave modeling and inversion.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2015

A Bayesian framework for adaptive selection, calibration, and validation of coarse-grained models of atomistic systems

A general adaptive modeling algorithm for selection and validation of coarse-grained models of atomistic systems is presented. A Bayesian framework is developed to address uncertainties in parameters, data, and model selection. Algorithms for computing output sensitivities to parameter variances, model evidence and posterior model plausibilities for given data, and for computing what are referred to as Occam Categories in reference to a rough measure of model simplicity, make up components of the overall approach. Computational results are provided for representative applications.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2018

Active learning of constitutive relation from mesoscopic dynamics for macroscopic modeling of non-Newtonian flows

We simulate complex fluids by means of an on-the-fly coupling of the bulk rheology to the underlying microstructure dynamics. In particular, a continuum model of polymeric fluids is constructed without a pre-specified constitutive relation, but instead it is actively learned from mesoscopic simulations where the dynamics of polymer chains is explicitly computed. To couple the bulk rheology of polymeric fluids and the microscale dynamics of polymer chains, the continuum approach (based on the finite volume method) provides the transient flow field as inputs for the (mesoscopic) dissipative particle dynamics (DPD), and in turn DPD returns an effective constitutive relation to close the continuum equations. In this multiscale modeling procedure, we employ an active learning strategy based on Gaussian process regression (GPR) to minimize the number of expensive DPD simulations, where adaptively selected DPD simulations are performed only as necessary. Numerical experiments are carried out for flow past a circular cylinder of a non-Newtonian fluid, modeled at the mesoscopic level by bead-spring chains. The results show that only five DPD simulations are required to achieve an effective closure of the continuum equations at Reynolds number RE = 10. Furthermore, when Re is increased to 100, only one additional DPD simulation is required for constructing an extended GPR-informed model closure. Compared to traditional message-passing multiscale approaches, applying an active learning scheme to multiscale modeling of non-Newtonian fluids can significantly increase the computational efficiency. Although the method demonstrated here obtains only a local viscosity from the polymer dynamics, it can be extended to other multiscale models of complex fluids whose macro-rheology is unknown.

Computer Science↗
DOE OSTI2020

Defect cluster and nonequilibrium gas bubble associated growth in irradiated UMo fuels – a cluster dynamics and phase field model

Irradiation examination shows that gas bubble swelling kinetics is much faster after irradiation-induced recrystallization than that prior recrystallization in UMo fuels. It implies that gas bubbles in coarse grains and small recrystallized grains have different growth behavior. In this work, a phase-field model of gas bubble evolution integrating microstructure dependent cluster dynamics has been developed, for the first time, to study the gas bubble swelling behavior in the recrystallization zone of UMo fuels. Generation, diffusion, reaction, sink, emission and clustering of vacancies and interstitials are described by the cluster dynamics model while a phase-field model is used to describe the evolution of non-equilibrium gas bubbles including nucleation and growth. With the coupled model, the effect of defect generation rate, clustering rate, interstitial emission and sink rates on grain boundaries on the gas bubble evolution are systematically simulated. A set of model parameters (defect generation rate, clustering rate, interstitial emission and sink rates) is determined by comparing measured and simulated gas bubble swelling kinetics. The results demonstrate that interstitial clustering is one of the important physical mechanisms which results in a fast gas bubble swelling kinetics in the recrystallization zone. The developed model can also be extended to study the associated growth of defect and second phase precipitates often observed in irradiated materials.

Hu, Shenyang↗