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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 631 records · Page 35
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

A mechanistic modeling framework for gas-phase adsorption kinetics and fixed-bed transport

Adsorption is a complex physicochemical process involving interparticle transport, interphase mass-transfer, intraparticle diffusion, and surface reactions. Although the exact description of the adsorption process will inevitably vary from system to system, it will always be governed by those primary mechanisms. Thus, by devising a model framework that can inherently include those mechanisms, it would be possible to create a modeling platform on which many different adsorption problems could be solved numerically. In order to accomplish this task, a generalized 1-D conservation law model was created to include the necessary mechanisms of adsorption on several different geometrical domains. Specific model applications for adsorption were developed under that framework and validated using experimental data available in literature or obtained in this work. This modeling platform makes it easier to model various adsorption problems and develop new adsorption models because of the common treatment of the mathematics governing the physical processes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2018

Application of Bound-to-Bound Data Collaboration approach for development and uncertainty quantification of a reduced char combustion model

The development of efficient industrial oxy-coal boilers can be significantly aided by Computational Fluid Dynamics (CFD) tools, as far as fidelity in modeling coal combustion is also complemented by feasible computational costs. Reduced and predictive models are the most suitable for this application scale. Reduced models feature predictivity when they are validated against a broad range of experiments and targeted by Uncertainty Quantification (UQ) procedures. This work proposes a numerical procedure that uses Bound-to-Bound Data Collaboration (B2B-DC) to derive a reduced char combustion model describing transport phenomena and reactions between char carbon and O 2 , CO 2 and H 2 O, in both conventional and oxy-conditions. The approach determines the consistency between a numerical model and an experimental dataset. The latter is made up of the experiments carried out in an optically accessible laminar entrained flow reactor, operated by Sandia National Laboratories. The procedure follows five steps towards predictive modeling capability, namely: quantification of the uncertainty in the experiments, via instrument verification and modeling; development of a physics model and continuous improvement of its fidelity, via model-form uncertainty; identification of the uncertain and most sensitive parameters and of their prior bounds; sampling of the initial uncertain parameter space and training of a surrogate model; validation of the physics model via inference from the data. The last step, also known as inverse problem, is performed by applying the Bound-to-Bound Data Collaboration approach. A char combustion model is found consistent with the experimental data and its validity stands for conventional and oxy-combustion conditions. It accounts for heterogeneous reactions at the particle surface, mass transport of species in the particle boundary layer, pore diffusion and surface area changes. The consistent reduced model overcomes the differences in mass transport and kinetics observed in the experimental campaign. In conclusion, a reduction of the initial degree of uncertainty in both model and experiments is achieved.

42 ENGINEERING↗
DOE OSTI2018

Effect of ball milling conditions on microstructure and lithium storage properties of LiNi0.5Mn1.5O4 as cathode for lithium-ion batteries

Highlights: • Precursors of LNM respectively synthesized by dry and wet ball-milling. • Under wet ball-milling raw materials form slurry and mix well in microscale. • LNM-w12 sample presents proper stoichiometric composition and the highest D{sub Li}{sup +}. • At 0.1 C rate LNM-w12 delivers 133 mAh g{sup −1} at 100 cycle close to theoretical value. • LNM-w12 delivers 97 mAh g{sup −1} at 10 C rate and remains 78% after 1000 cycles. - Abstract: In this work, the precursors of LiMn{sub 1.5}Ni{sub 0.5}O{sub 4} (LNM) are respectively synthesized by dry and wet ball-milling. Under wet ball-milling, the problem of sticky residue in dry ball-milling is effectively resolved, the three raw materials form homogeneous slurry and mix well in micrometers level. LNM-w12 sample synthesized by using precursor added 12 mL milling medium gains the atomic composition closed to the theoretical value, ordered crystal structure and the highest lithium diffusion coefficient. At 0.1 C rate, LNM-w12 delivers the capacity of 136 mAh g{sup −1} at the first cycle, and 133 mAh g{sup −1} at the 100th cycle. Moreover, LNM-w12 delivers the initial capacity of 97 mAh g{sup −1} at 10 C rate, and remains 78% after 1000 cycles. The great rate capability of LNM-w12 can be attributed to the well-formed crystal structure, ordered and stable surface structure, which is conducive to the diffusion of lithium ions and prevents the dissolution of the material at high voltage.

25 ENERGY STORAGE↗
DOE OSTI2023

Bound-preserving finite element approximations of the Keller–Segel equations

We report this paper aims to develop numerical approximations of the Keller–Segel equations that mimic at the discrete level the lower bounds and the energy law of the continuous problem. We solve these equations for two unknowns: the organism (or cell) density, which is a positive variable, and the chemoattractant density, which is a non-negative variable. We propose two algorithms, which combine a stabilized finite element method and a semi-implicit time integration. The stabilization consists of a nonlinear artificial diffusion that employs a graph-Laplacian operator and a shock detector that localizes local extrema. As a result, both algorithms turn out to be nonlinear and can generate cell and chemoattractant numerical densities fulfilling lower bounds. However, the first algorithm requires a suitable constraint between the space and time discrete parameters, whereas the second one does not. We design the latter to attain a discrete energy law on acute meshes. We report some numerical experiments to validate the theoretical results on blowup and nonblowup phenomena. In the blowup setting, we identify a locking phenomenon that relates the L ∞ (Ω)-norm to the L 1 (Ω)-norm limiting the growth of the singularity when supported on a macroelement.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Conditional Karhunen-Loève expansion for uncertainty quantification and active learning in partial differential equation models

We use a conditional Karhunen-Lo` eve (KL) model to quantify and reduce uncertainty in a stochastic partial differential equation (SPDE) problem with partially-known space-dependent coefficient, Y (x). We assume that a small number of Y (x) measurements are available and model Y (x) with a KL expansion. We achieve reduction in uncertainty by conditioning the KL expansion coefficients on measurements. We consider two approaches for conditioning the KL expansion: In Approach 1, we condition the KL model first and then truncate it. In Approach 2, we first truncate the KL expansion and then condition it. We employ the conditional KL expansion together with Monte Carlo and sparse grid collocation methods to compute the moments of the solution of the SPDE problem. Uncertainty of the problem is further reduced by adaptively selecting additional observation locations using two active learning methods. Method 1 minimizes the variance of the PDE coefficient, while Method 2 minimizes the variance of the solution of the PDE. We demonstrate that conditioning leads to dimension reduction of the KL representation of Y (x). For a linear diffusion SPDE with uncertain log-normal coefficient, we show that Approach 1 provides a more accurate approximation of the conditional log-normal coefficient and solution of the SPDE than Approach 2 for the same number of random dimensions in a conditional KL expansion. Furthermore, Approach 2 provides a good estimate for the number of terms of the truncated KL expansion of the conditional field of Approach 1. Finally, we demonstrate that active learning based on Method 2 is more efficient for uncertainty reduction in the SPDE’s states (i.e., it leads to a larger reduction of the variance) than active learning using Method 2.

Conditioned Karhunen-Lo` eve expanion, machine lea↗
DOE OSTI2017

Facile fabrication of micro-floriated AgBr/Bi{sub 2}O{sub 3} as highly efficient visible-light photocatalyst

Highlights: • We successfully fabricate micro-floriated AgBr/Bi{sub 2}O{sub 3} composites by one simple hydrothermal react with precusor BiOBr. This micro-floriated Bi{sub 2}O{sub 3} heterojunction composite is rarely reported by others. • Heterojunction AgBr/Bi{sub 2}O{sub 3} composite exhibits highly efficient photocatalytic activity to decompose pollutant. • The enhanced photocatalytic activity was attributed to the improved visible light harvesting ability and higher separation efficiency of photogenerated electron–hole pairs by the introduction of AgBr. • This composite is beneficial to industrial applications to eliminate the organic pollutants from waste water. - Abstract: Semiconductor with photocatalytic property is the potential solution to solve the problem about water pollution. Novel floriated AgBr/Bi{sub 2}O{sub 3} fabricated through a facile simple two-step hydrothermal method is an efficient photocatalyst. The eminent performance for degradation of methyl orange (MO) was evaluated under visible light irradiation. Many characterization methods, including XPS, XRD, FT-IR, SEM, TEM and UV–vis diffuse reflection spectroscopy, were used to investigate the structure, elemental composition, morphology and catalytic activity. Broad contact between AgBr and Bi{sub 2}O{sub 3} interface enabled hybrid materials possess superior efficiency for the decomposition of MO under visible light irradiation. The optimum photocatalytic activity of samples was approximately 11.7 times higher than pure Bi{sub 2}O{sub 3}. In addition, the photo-generated reactive species were identified based on free radicals trapping experiments, which revealed that superoxide radical is the key factor to the photocatalytic process.

36 MATERIALS SCIENCE↗
DOE OSTI2019

A configurational force for adaptive re-meshing of gradient-enhanced poromechanics problems with history-dependent variables

Here, we introduce a mesh-adaption framework that employs a multi-physical configurational force and Lie algebra to capture multiphysical responses of fluid-infiltrating geological materials while maintaining the efficiency of the computational models. To resolve sharp gradients of both displacement and pore pressure, we introduce an energy-estimate-free re-meshing criterion by extending the configurational force theory to consider the energy dissipation due to the fluid diffusion and the gradient-dependent plastic flow. To establish new equilibria after remeshing, the local tensorial history-dependent variables at the integration points are first decomposed into spectral forms. Then, the principal values and directions are projected onto smooth fields interpolated by the basis function of the finite element space via the Lie-algebra mapping. Our numerical results indicate that this Lie algebra operator in general leads to a new trial state closer to the equilibrium than the ones obtained from the tensor component mapping approach. A new configurational force for dissipative fluid-infiltrating porous materials that exhibit gradient-dependent plastic flow is introduced such that the remeshing may accommodate the need to resolve the sharp pressure gradient as well as the strain localization. The predicted responses are found to be not influenced by the mesh size due to the micromorphic regularization, while the adaptive meshing enables us to capture the width of deformation bands without the necessity of employing fine mesh everywhere in the domain.

42 ENGINEERING↗
DOE OSTI2019

An efficient three-dimensional rhizosphere modeling capability to study the effect of root system architecture on soil water and reactive transport

This research was to develop a rhizosphere modeling capability for plant-soil interactions by integrating water and ion uptake and release from three dimensional (3D) root systems and 3D variably saturated flow and multicomponent reactive transport in soil. We combined open source software for simulating plant and soil interactions with parallel processing computational technologies to address highly-resolved root system architecture and soil hydrobiogeochemical processes. Simulation capability was demonstrated on Brachypodium distachyon . Our demonstration problem showed that availability of water and plant nutrients is controlled by the interplay between 1) transpiration-driven cycles of water uptake, root zone saturation and desaturation; 2) sorption and desorption via competitive ion exchange; 3) buildup of ions not taken up during kinetic uptake of nutrients/ions from pore water; and 4) advection, dispersion, and diffusion of ions in the soil. The uptake of water and ions by individual roots leads to dynamic, local gradients in ion concentrations. The resulting higher solution ionic strength can lead to increasing sorption of K+ and NH4+ on the soil exchange sites, despite their preferential absorption by roots. The modeling framework makes it possible to explore alternative conceptual models and improve the understanding of the biogeochemical and physical environment within the rhizosphere.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2017

Convective mixing in vertically-layered porous media: The linear regime and the onset of convection

In this paper, we study the effect of permeability heterogeneity on the stability of gravitationally unstable, transient, diffusive boundary layers in porous media. Permeability is taken to vary periodically in the horizontal plane normal to the direction of gravity. In contrast to the situation for vertical permeability variation, the horizontal perturbation structures are multimodal. We therefore use a two-dimensional quasi-steady eigenvalue analysis as well as a complementary initial value problem to investigate the stability behavior in the linear regime, until the onset of convection. We find that thick permeability layers enhance instability compared with thin layers when heterogeneity is increased. On the contrary, for thin layers the instability is weakened progressively with increasing heterogeneity to the extent that the corresponding homogeneous case is more unstable. For high levels of heterogeneity, we find that a small change in the permeability field results in large variations in the onset time of convection, similar to the instability event in the linear regime. However, this trend does not persist unconditionally because of the reorientation of vorticity pairs due to the interaction of evolving perturbation structures with heterogeneity. Consequently, an earlier onset of instability does not necessarily imply an earlier onset of convection. A resonant amplification of instability is observed within the linear regime when the dominant perturbation mode is equal to half the wavenumber of permeability variation. On the other hand, a substantial damping occurs when the perturbation mode is equal to the harmonic and sub-harmonic components of the permeability wavenumber. Finally, the phenomenon of such harmonic interactions influences both the onset of instability as well as the onset of convection.

36 MATERIALS SCIENCE↗
DOE OSTI2017

Ray tracing and Hubble diagrams in post-Newtonian cosmology

On small scales the observable Universe is highly inhomogeneous, with galaxies and clusters forming a complex web of voids and filaments. The optical properties of such configurations can be quite different from the perfectly smooth Friedmann-Lemaȋtre-Robertson-Walker (FLRW) solutions that are frequently used in cosmology, and must be well understood if we are to make precise inferences about fundamental physics from cosmological observations. We investigate this problem by calculating redshifts and luminosity distances within a class of cosmological models that are constructed explicitly in order to allow for large density contrasts on small scales. Our study of optics is then achieved by propagating one hundred thousand null geodesics through such space-times, with matter arranged in either compact opaque objects or diffuse transparent haloes. We find that in the absence of opaque objects, the mean of our ray tracing results faithfully reproduces the expectations from FLRW cosmology. When opaque objects with sizes similar to those of galactic bulges are introduced, however, we find that the mean of distance measures can be shifted up from FLRW predictions by as much as 10%. This bias is due to the viable photon trajectories being restricted by the presence of the opaque objects, which means that they cannot probe the regions of space-time with the highest curvature. It corresponds to a positive bias of order 10% in the estimation of Ω{sub Λ} and highlights the important consequences that astronomical selection effects can have on cosmological observables.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2018

Atomistic simulation methods for long-time dynamics in materials for nuclear energy systems

Many important processes in materials systems are intrinsically atomistic in nature but involve time scales that span many orders of magnitude, thus exceeding what can be directly simulated using molecular dynamics. This is especially true for materials in nuclear energy applications, in which defects created by collision cascades on the femtosecond-picosecond time scale cause microstructural changes that continue to evolve for years, in many cases leading to failure of the material. In this chapter, we review atomistic methods for reaching long time scales in systems like these. These accelerated molecular dynamics and adaptive kinetic Monte Carlo methods exploit the infrequent-event nature of the diffusive events that comprise this long-time evolution. In favorable cases, these methods can predict state-to-state evolution that approximates what would result from an extremely long molecular dynamics simulation, and the most accurate of the methods can do this to arbitrary accuracy. We present some examples of applications of these methods to problems relevant to nuclear energy materials, the subject of this volume. We then discuss situations that are difficult for the methods, causing them to be less efficient, and we conclude with a short list of the most pressing issues in the further development of these approaches to make them as powerful and predictive as possible for realistic problems.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Dark Field Proton Radiography (Los Alamos LDRD Report)

Proton radiography at LANL (pRad) takes advantage of the high flux, high proton energy, and flexible timing structure of LANSCE's 800-MeV proton beam to visualize dense, dynamic systems under extreme strain. With recent needs identified for the development of the W93, the pRad team has been actively searching for ways to increase the facility's radiographic capabilities. Recently, we discovered that utilizing two magnetic lenses (one upstream and one downstream of the object), and specific combinations of collimator choices within the two lenses, that the signal-to-noise ratio was improved by more than a factor of two. However, we did not fully understand the mechanism, and found that results did not match forward modeling predictions. This work specifically sought to implement an engineering solution to solve this problem, through the development of an actuated collimator that reduced the time required to swap collimator settings from a typical 4-8 hours, to less than 30 seconds. This allowed, in combination with a unique multi-material, multi-resolution stepwedge, to acquire an unprecedently enormous dataset, with in total 24 collimation combinations, and multiple diffuser settings and pulse patterns, equivalent to almost a full run cycle's worth of data in a few days. This massive dataset is currently being harnessed to make a fully-predictive, ultra-fast Python-based model of the system, to dial in specific settings for any future experiments that fully optimize that radiographic sensitivity to the material of interest.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

Approximate Bayesian Computation applied to the Diffuse Gamma-Ray Sky

ABSTRACT Many sources contribute to the diffuse gamma-ray background (DGRB), including star forming galaxies, active galactic nuclei, and cosmic ray interactions in the Milky Way. Exotic sources, such as dark matter annihilation, may also make some contribution. The photon counts-in-pixels distribution is a powerful tool for analysing the DGRB and determining the relative contributions of different sources. However, including photon energy information in a likelihood analysis of the counts-in-pixels distribution quickly becomes computationally intractable as the number of source types and energy bins increase. Here, we apply the likelihood-free method of approximate Bayesian computation (ABC) to the problem. We consider a mock analysis that includes contributions from dark matter annihilation in Galactic subhaloes as well as astrophysical backgrounds. We show that our results using ABC are consistent with the exact likelihood when energy information is discarded, and that significantly tighter parameter constraints can be obtained with ABC when energy information is included. ABC presents a powerful tool for analysing the DGRB and understanding its varied origins.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Data-Driven Reduced-Order Modeling of Convective Heat Transfer in Porous Media

This work presents a data-driven Reduced-Order Model (ROM) for parametric convective heat transfer problems in porous media. The intrusive Proper Orthogonal Decomposition aided Reduced-Basis (POD-RB) technique is employed to reduce the porous medium formulation of the incompressible Reynolds-Averaged Navier–Stokes (RANS) equations coupled with heat transfer. Instead of resolving the exact flow configuration with high fidelity, the porous medium formulation solves a homogenized flow in which the fluid-structure interactions are captured via volumetric flow resistances with nonlinear, semi-empirical friction correlations. A supremizer approach is implemented for the stabilization of the reduced fluid dynamics equations. The reduced nonlinear flow resistances are treated using the Discrete Empirical Interpolation Method (DEIM), while the turbulent eddy viscosity and diffusivity are approximated by adopting a Radial Basis Function (RBF) interpolation-based approach. The proposed method is tested using a 2D numerical model of the Molten Salt Fast Reactor (MSFR), which involves the simulation of both clean and porous medium regions in the same domain. For the steady-state example, five model parameters are considered to be uncertain: the magnitude of the pumping force, the external coolant temperature, the heat transfer coefficient, the thermal expansion coefficient, and the Prandtl number. For transient scenarios, on the other hand, the coastdown-time of the pump is the only uncertain parameter. The results indicate that the POD-RB-ROMs are suitable for the reduction of similar problems. The relative L2 errors are below 3.34% for every field of interest for all cases analyzed, while the speedup factors vary between 54 (transient) and 40,000 (steady-state).

German, Péter (ORCID:0000000307285283)↗
DOE OSTI2018

A Weighted Least-Squares Transport Equation Compatible with Source Iteration and Voids

We present that second-order forms of the transport equation allow the use of continuous finite elements (CFEMs). This can be desired in multiphysics calculations where other physics require CFEM discretizations. Second-order transport operators are generally self-adjoint, yielding symmetric positive-definite (SPD) matrices, which allow the use of efficient linear algebra solvers with an enormous advantage in memory usage. Least-squares (LS) forms of the transport equation can circumvent the void problems of other second-order forms but are almost always nonconservative. Additionally, the standard LS form is not compatible with discrete ordinates method (SN) iterative solution techniques such as source iteration. A new form of the LS transport equation has recently been developed that is compatible with voids and standard SN iterative solution techniques. Performing nonlinear diffusion acceleration (NDA) using an independently differenced low-order equation enforces conservation for the whole system and makes this equation suitable for reactor physics calculations. In this context, “independent” means that both the transport and low-order solutions converge to the same scalar flux and current as the spatial mesh is refined, but for a given mesh, the solutions are not necessarily equal. In this paper we show that introducing a weight function into this LS equation improves issues with causality and can render our equation equal to the self-adjoint angular flux (SAAF) equation. Causality is a principle of the transport equation that states that information travels only downstream along characteristics. This principle can be violated numerically. We show how to limit the weight function in voids and demonstrate the effect of this limit on accuracy. Using the C5G7 benchmark, we compare our method to the SAAF formulation with a void treatment (SAAFτ) that is not self-adjoint and has a nonsymmetric coefficient matrix. Finallyl, we show that the weighted LS equation with NDA gives acceptable accuracy relative to the SAAFτ equation while maintaining a SPD system matrix.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Transcritical diffuse-interface hydrodynamics of propellants in high-pressure combustors of chemical propulsion systems

Rocket engines and high-power new generations of gas-turbine jet engines and diesel engines oftentimes involve the injection of one or more reactants at subcritical temperatures into combustor environments at high pressures, and more particularly at pressures higher than those corresponding to the critical points of the individual components of the mixture, which typically range from 13 to 50 bars for most propellants. This class of trajectories in the thermodynamic space has been traditionally referred to as transcritical. However, the fundamental understanding of fuel atomization, vaporization, mixing, and combustion processes at such high pressures remains elusive. In particular, whereas fuel sprays are relatively well characterized at normal pressures, analyses of dispersion of fuel in high-pressure combustors are hindered by the limited experimental diagnostics and theoretical formulations available. The description of the thermodynamics of hydrocarbon-fueled mixtures employed in chemical propulsion systems is complex and involves mixing-induced phenomena, including an elevation of the critical point whereby the coexistence region of the mixture extends up to pressures much larger than the critical pressures of the individual components. As a result, interfaces subject to surface-tension forces may persist in multicomponent systems despite the high pressures, and may give rise to unexpected spray-like atomization dynamics that are otherwise absent in monocomponent systems above their critical point. In this article, the current understanding of this phenomenon is reviewed within the context of propulsion systems fueled by heavy hydrocarbons. Emphasis is made on analytical descriptions at mesoscopic scales of interest for computational fluid dynamics. In particular, a set of modifications of the constitutive laws in the Navier–Stokes equations for multicomponent flows, supplemented with a high-pressure equation of state and appropriate redefinitions of the thermodynamic potentials, are introduced in this work based on an extended version of the diffuse-interface theory of van der Waals. The resulting formulation involves revisited forms of the stress tensor and transport fluxes of heat and species, and enables a description of the mesoscopic volumetric effects induced by transcritical interfaces consistently with the thermodynamic phase diagram of the mixture at high pressures. Additionally, applications of the theory are illustrated in canonical problems, including dodecane/nitrogen transcritical interfaces in non-isothermal systems. The results indicate that a transcritical interface is formed between the propellant streams that persists downstream of the injection orifice over distances of the same order as the characteristic thermal-entrance length of the fuel stream. The transcritical interface vanishes at an edge that gives rise to a fully supercritical mixing layer.

02 PETROLEUM↗
DOE OSTI2023

Reacceleration of Galactic Cosmic Rays beyond the Knee at the Termination Shock of a Cosmic-Ray-driven Galactic Wind

The origin of cosmic rays (CRs) above the knee in the spectrum is an unsolved problem. We present a wind model in which interstellar gas flows along a nonrotating, expanding flux tube with a changing speed and cross-sectional area. CRs from Galactic sources, such as supernova remnants, which are coupled to the plasma via Alfvén waves, provide the main pressure source for driving this outflow. These CRs are then subject to diffusive shock reacceleration at the Galactic wind termination shock, which is located at a distance ~200 kpc. Some of the highest-energy reaccelerated particles propagate upstream against the wind and can contribute to the petaelectronvolt to exaelectronvolt range of the spectrum. We analyze the conditions under which efficient reacceleration can occur and find that rigidities ~10–40 PV can be obtained and that the termination shock may account for between 10% and 50% of the proton spectrum measured in IceCube/IceTop experiment. In our model, the termination shock is unable to fully explain the CR spectrum in the petaelectronvolt to exaelectronvolt range. The highest-energy particles that escape downstream from our termination shock, and similar shocks surrounding most galaxies, can be further accelerated by intergalactic shock fronts.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2017

Pore-network model of evaporation-induced salt precipitation in porous media: The effect of correlations and heterogeneity

Salt transport and precipitation in porous media constitute a set of complex and fascinating phenomena that are of considerable interest to several important problems, ranging from storage of CO 2 in geological formations, to soil fertility, and protection of pavements and roads, as well as historical monuments. The phenomena occur at the pore scale and are greatly influenced by the heterogeneity of the pore space morphology. In this paper, we present a pore-network (PN) model to study the phenomena. Vapor diffusion, capillary effect at the brine-vapor interface, flow of brine, and transport of salt and its precipitation in the pores that plug the pores partially or completely are all accounted for. The drying process is modeled by the invasion percolation, while transport of salt in brine is accounted for by the convective-diffusion equation. We demonstrate that the drying patterns, the clustering and connectivity of the pore throats in which salt precipitation occurs, the saturation distribution, and the drying rate are all strongly dependent upon the pore-size distribution, the correlations among the pore sizes, and the anisotropy of the pore space caused by stratification that most natural porous media contain. In particular, if the strata are more or less parallel to the direction of injection of the gas that dries out the pore space (air, for example) and/or causes salt precipitation (CO 2 , for example), the drying rate increases significantly. Moreover, salt tends to precipitate in clusters of neighboring pores that are parallel to the open surface of the porous medium.

42 ENGINEERING↗