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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 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Visualisation and outlier detection for probability density function ensembles

Abstract Exploratory data analysis (EDA) for functional data—data objects where observations are entire functions—is a difficult problem that has seen significant attention in recent literature. This surge in interest is motivated by the ubiquitous nature of functional data, which are prevalent in applications across fields such as meteorology, biology, medicine and engineering. Empirical probability density functions (PDFs) can be viewed as constrained functional data objects that must integrate to one and be nonnegative. They show up in contexts such as yearly income distributions, zooplankton size structure in oceanography and in connectivity patterns in the brain, among others. While PDF data are certainly common in modern research, little attention has been given to EDA specifically for PDFs. In this paper, we extend several methods for EDA on functional data for PDFs and compare them on simulated data that exhibit different types of variation, designed to mimic that seen in real‐world applications. We then use our new methods to perform EDA on the breakthrough curves observed in gas transport simulations for underground fracture networks.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

Regional-scale analysis of karst underground flow deduced from tracing experiments: examples from carbonate aquifers in Malaga province, southern Spain

Tracer concentration data from field experiments conducted in several carbonate aquifers (Malaga province, southern Spain) were analyzed following a dual approach based on the graphical evaluation method (GEM) and solute transport modeling to decipher flow mechanisms in karst systems at regional scale. The results show that conduit system geometry and flow conditions are the principal factors influencing tracer migration through the examined karst flow routes. Solute transport is mainly controlled by longitudinal advection and dispersion throughout the conduit length, but also by flow partitioning between mobile and immobile fluid phases, while the matrix diffusion process appears to be less relevant. The simulation of tracer breakthrough curves (BTCs) suggests that diffuse and concentrated flow through the unsaturated zone can have equivalent transport properties under extreme recharge, with high flow velocities and efficient mixing due to the high hydraulic gradients generated. Tracer mobilization within the saturated zone under low flow conditions mainly depends on the hydrodynamics (rather than on the karst conduit development), which promote a lower longitudinal advection and retardation in the tracer migration, resulting in a marked tailing effect of BTCs. The analytical advection-dispersion equation better approximates the effective flow velocity and longitudinal dispersion estimations provided by the GEM, while the non-equilibrium transport model achieves a better adjustment of most asymmetric and long-tailed BTCs. The assessment of karst underground flow properties from tracing tests at regional scale can aid design of groundwater management and protection strategies, particularly in large hydrogeological systems (i.e. transboundary carbonate aquifers) and/or in poorly investigated ones.

58 GEOSCIENCES↗
DOE OSTI2018

Machine learning for graph-based representations of three-dimensional discrete fracture networks

Structural and topological information play a key role in modeling flow and transport through fractured rock in the subsurface. Discrete fracture network (DFN) computational suites such as dfnWorks (Hyman et al. Comput. Geosci. 84, 10–19 2015) are designed to simulate flow and transport in such porous media. Flow and transport calculations reveal that a small backbone of fractures exists, where most flow and transport occurs. Restricting the flowing fracture network to this backbone provides a significant reduction in the network’s effective size. However, the particle-tracking simulations needed to determine this reduction are computationally intensive. Such methods may be impractical for large systems or for robust uncertainty quantification of fracture networks, where thousands of forward simulations are needed to bound system behavior. In this paper, we develop an alternative network reduction approach to characterizing transport in DFNs, by combining graph theoretical and machine learning methods. We consider a graph representation where nodes signify fractures and edges denote their intersections. Using random forest and support vector machines, we rapidly identify a subnetwork that captures the flow patterns of the full DFN, based primarily on node centrality features in the graph. Our supervised learning techniques train on particle-tracking backbone paths found by dfnWorks, but run in negligible time compared to those simulations. In conclusion, we find that our predictions can reduce the network to approximately 20% of its original size, while still generating breakthrough curves consistent with those of the original network.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Model reduction for fractured porous media: a machine learning approach for identifying main flow pathways

Discrete fracture networks (DFN) are often used to model flow and transport in fractured porous media. The accurate resolution of flow and transport behavior on a large DFN involving thousands of fractures is computationally expensive. This makes uncertainty quantification studies of quantities of interest such as travel time through the network computationally intractable, since hundreds to thousands of runs of the DFN model are required to get bounds on the uncertainty of the predictions. Prior works on the subject demonstrated that the complexity of a DFN could be reduced by considering a sub-network of it (often termed a “backbone” sub-network), one whose flow and transport properties were then shown to be similar to that of the full network. The technique is tantamount to partitioning the complete set of fractures of a network into two disjoint sets, one of which is the backbone sub-network while the other its complement. It is in this context that we present a system-reduction technique for DFNs using supervised machine learning via a Random Forest Classifier that selects a backbone sub-network from the full set of fractures. The in-sample errors (in terms of precision and recall scores) of the trained classifier are found to be very accurate indicators of the out-of-sample errors, thus exhibiting that the classifier generalizes well to test data. Moreover, this system-reduction technique yields sub-networks as small as 12% of the full DFN that still recover transport characteristics of the full network such as the peak dosage and tailing behavior for late times. Most importantly, the sub-networks remain connected, and their size can be controlled by a single dimensionless parameter. Furthermore, measures of KL-divergence and KS-statistic for the breakthrough curves of the sub-networks with respect to the full network show physically realistic trends in that the measures decrease monotonically as the size of the sub-networks increase. In conclusion, the computational efficiency gained by this technique depends on the size of the sub-network, but large reductions in computational time can be expected for small sub-networks, yielding as much as 90% computational savings for sub-networks that are as small as 10-12% of the full network.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Markovian transport processes in a heterogeneous, variably saturated watershed: A multi-domain spatial Markov model

Transport processes in watersheds remain challenging to describe accurately with upscaled models because of their intricate complexities at multiple scales that can lead to multi-modal, non-Fickian breakthrough curves. One of the recent advances in solute transport modeling has been the Lagrangian spatial Markov model (SMM), which describes transport using velocity increments and models the correlated transitions between them. The method has been applied previously to saturated porous media and fractured media, but these successful applications suggest it may be useful for describing watershed scale processes as well. An existing, 3-D, heterogeneous variably saturated model of a headwaters catchment and classical random walk particle tracking were used to generate a forward simulation and the resulting transport was analyzed with a spatial Markov framework. Existing SMM methods were used to analyze the transport paths through the complex, unconfined domain and we found that the vadose zone plays an important role in the correlation structure. As such, a new kind of SMM is proposed, termed a multi-domain SMM (MD-SMM), that uses separate correlation models for auto-transitions in the vadose zone and the saturated zone, and for the cross-transitions between them. The MD-SMM improves representation of transport relative to the single domain model and can naturally delineate times when a particle is in the vadose zone or the saturated zone, adding an additional degree of realism to the upscaled model. Lastly, we show that the transition probability matrix for transport in the saturated portion of this unconfined system is approximately Markovian, which is an important validation of the proposed framework.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Nonparametric, data-based kernel interpolation for particle-tracking simulations and kernel density estimation

Traditional interpolation techniques for particle tracking include binning and convolutional formulas that use pre-determined (i.e., closed-form, parameteric) kernels. In many instances, the particles are introduced as point sources in time and space, so the cloud of particles (either in space or time) is a discrete representation of the Green’s function of an underlying PDE. As such, each particle is a sample from the Green’s function; therefore, each particle should be distributed according to the Green’s function. In short, the kernel of a convolutional interpolation of the particle sample “cloud” should be a replica of the cloud itself. This idea gives rise to an iterative method by which the form of the kernel may be discerned in the process of interpolating the Green’s function. When the Green’s function is a density, this method is broadly applicable to interpolating a kernel density estimate based on random data drawn from a single distribution. We formulate and construct the algorithm and demonstrate its ability to perform kernel density estimation of skewed and/or heavy-tailed data including breakthrough curves.

42 ENGINEERING↗
DOE OSTI2025

Catalytic hydrogenation of HMF to BHMF over copper catalysts

2,5-Bis(hydroxymethyl)furan (BHMF) is a bio-derived building block for polyester production, obtained via the hydrogenation of 5-hydroxymethylfurfural (HMF). First-principles thermodynamic equilibrium calculations indicate that this reaction is not thermodynamically limited under relevant conditions (e.g., 100 °C and high H 2 partial pressure). In this work, crude HMF was employed as the feedstock for BHMF synthesis. Initially, acidic impurities and humins were removed from unrefined HMF through filtration using a packed bed of γ-alumina. A comprehensive study of the filtration process is presented, including filtration kinetics, breakthrough curve analysis, and mathematical modeling. The purified HMF was subsequently hydrogenated over a 10 wt% CuZrO 2 catalyst, using ethanol as the reaction solvent. Batch reactions were first performed for collection of kinetic data to guide the transition to continuous flow operation. Kinetic data was collected in a fixed bed reactor at varying contact time, time on stream, temperature, and HMF concentration. This data was used to develop a kinetic model for HMF hydrogenation. Maximum BHMF production rates were achieved at 130 °C, accompanied by minor formation of byproducts from BHMF ring-opening reactions. The BHMF selectivity was 100 % at 100 °C although with lower reaction rates. Furthermore, catalyst stability tests revealed a loss of up to 50 % in catalytic activity within the first 24 h, likely due to the adsorption of HMF-derived oligomers that are not easily removed by filtration.

Crude HMF filtration↗
DOE OSTI2021

Encapsulation of highly viscous CO 2 capture solvents for enhanced capture kinetics: Modeling investigation of mass transfer mechanisms

The encapsulation of highly viscous liquid-like Nanoparticle Organic Hybrid Materials (NOHMs) inside a gas permeable polymer to form SIPs (Solvent Impregnated Polymers) significantly enhanced the CO 2 capture kinetics of NOHMs, leading to a remarkable 50-fold increase in CO 2 flux compared to the neat NOHMs. To understand the mechanism for enhanced CO 2 mass transfer within these hybrid materials, kinetic modeling of CO 2 uptake into SIPs containing polyethylenimine functionalized NOHMs, denoted NPEI-SIP, was conducted. CO 2 mass transfer into NPEI-SIP films was found to conform, both qualitatively and quantitatively, with a diffusion-controlled moving front model. The diffusion-controlled model was also used to simulate CO 2 uptake within a fixed bed containing polydisperse NPEI-SIP particles, and this model accurately predicted experimentally measured breakthrough curves at 25 °C and 50 °C. The 50-fold increase in gas flux was shown to be a consequence of the very large CO 2 permeability within the polymer–solvent composite. Furthermore, the increase in gas flux is also dependent on the diffusion–reaction regime in which the chemical solvent operates, and the largest improvement will occur when immobilizing solvents, such as NOHMs, which operate in the instantaneous-reaction regime. The CO 2 capacity (~3 mol CO 2 /kg) and saturation time (~5 min) of 430 μm SIP particles were comparable to popular CO 2 chemisorption materials such as amine grafted silicates, in spite of the slow kinetics of NOHM-I-PEI in liquid form (CO 2 saturation time ~24 h for a 1 mm thin film).

36 MATERIALS SCIENCE↗
DOE OSTI2021

Dimensionality effects on multicomponent ionic transport and surface complexation in porous media

Coulombic interactions between charged species in pore water and at surface/solution interfaces are of pivotal importance for multicomponent reactive transport in porous media. In this study, we investigate the impact of domain dimensionality on electrostatically coupled dispersion and surface-solution reactions during transport of acidic plumes and major ions in porous media. Column and quasi two-dimensional flow-through experiments were performed, with identical silica porous media and under the same advection-dominated conditions. Equal mass fluxes of different electrolyte solutions (i.e., HCl - pH ~ 2.8, NaBr - 100 mM, HCl - pH ~ 2.8 plus NaBr - 100 mM) were continuously injected in the 1-D and 2-D experiments and breakthrough curves of pH and major ions were measured at the outlet of the domains. The presence of pronounced ionic strength gradients in the transverse direction in the 2-D setup caused distinct retardation and transport behaviors of protons and major ions which were not observed in the one-dimensional column experiments. Furthermore, in the cases of salt electrolytes injection, considerably enhanced release of H + (>61%) from the quartz surface was observed in the multidimensional system compared to the one-dimensional setup. Reactive transport modeling was performed to reproduce the experimental outcomes and to analyse the coupling between transport processes, based on the Nernst-Planck formulation of diffusive/dispersive fluxes and on surface complexation reactions at the solid-solution interface. Electrostatic interactions between Na + , B – , and H + , and deprotonation of the quartz surface upon the formation of sodium outer-sphere complexes, are the primary controllers of the spatial and temporal features displayed by the pH and major ions measurements. The reactive transport simulations allowed us to interpret the experimental observations, to visualize the distribution and spatio-temporal evolution of dissolved and solid species, to identify a spatially heterogeneous zonation of Coulombic interactions with distinct behavior at the fringe and core of the injected plumes in the multidimensional setup, and to quantify the different components of the Nerst-Planck fluxes of the charged solutes. This study demonstrates that the domain dimensionality directly affects electrostatic interactions between charged aqueous species in the pore water and surface complexation reactions at the solid-solution interface. The non-trivial effects of dimensionality on multicomponent ionic transport result in a significantly different behavior in 1-D and 2-D systems.

58 GEOSCIENCES↗
DOE OSTI2019

Climate change impact on residual contaminants under sustainable remediation

This study investigates the potential impact of climate change on residual contaminants in vadose zones and groundwater. We assume that the effect of climate changes can be represented by perturbations in the natural recharge through the aquifer system. We perform numerical modeling of unsaturated/saturated flow and transport and consider different performance metrics: contaminant concentrations at observation wells and contaminant export at the site's boundary. We evaluate the effect of increasing and decreasing recharge as well as the impact of potential failure of surface capping structures employed to immobilize vadose zone contaminants. Our approach is demonstrated in a real case study by simulating transport of non-reactive radioactive tritium at the U.S. Department of Energy's Savannah River Site. Results show that recharge changes significantly affect well concentrations: after an initial slight dilution we identify a significant concentration increase at different observation wells some years after the recharge increase and/or the cap failure, as a consequence of contaminants' mobilization. This effect is generally emphasized and occurs earlier as the recharge increases. Under decreased aquifers' recharge the concentration could slightly increase for some years, due to a decrease of dilution, depending on the magnitude of the negative recharge shift. We identify trigger levels of recharge above which the concentration/export breakthrough curves and the time of exceedance of the Maximum Contaminant Level for tritium are remarkably affected. Moreover, we observe that the contaminant export at the control plane, identified as the risk pathway to the downgradient population, may only be minimally affected by shifts in the natural recharge regime, except for some extreme cases. We conclude that more frequent sampling and in-situ monitoring near the source zone should be adopted to better explain concentrations' anomalies under changing climatic conditions. Moreover, the maintenance of the cap is critical not only to sequester residual contaminants in the vadose zone, but also to reduce the uncertainty associated with future precipitation changes. Finally, realistic flow and transport simulations achieved through proper calibration processes, rather than conservative modeling, should be adopted to identify non-trivial trade-offs which enable better allocation of resources towards reducing uncertainty in decision making.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

A comparative study of discrete fracture network and equivalent continuum models for simulating flow and transport in the far field of a hypothetical nuclear waste repository in crystalline host rock

One of the major challenges of simulating flow and transport in the far field of a geologic repository in crystalline host rock is related to reproducing the properties of the fracture network over the large volume of rock with sparse fracture characterization data. Various approaches have been developed to simulate flow and transport through the fractured rock. The approaches can be broadly divided into Discrete Fracture Network (DFN) and Equivalent Continuum Model (ECM). The DFN explicitly represents individual fractures, while the ECM uses fracture properties to determine equivalent continuum parameters. In this paper, we compare DFN and ECM in terms of upscaled observed transport properties through generic fracture networks. The major effort was directed on making the DFN and ECM approaches similar in their conceptual representations. This allows for separating differences related to the interpretation of the test conditions and parameters from the differences between the DFN and ECM approaches. The two models are compared using a benchmark test problem that is constructed to represent the far field (1 × 1 × 1 km 3 ) of a hypothetical repository in fractured crystalline rock. The test problem setting uses generic fracture properties that can be expected in crystalline rocks. The models are compared in terms of the: 1) effective permeability of the domain, and 2) nonreactive solute breakthrough curves through the domain. The principal differences between the models are mesh size, network connectivity, matrix diffusion and anisotropy. We demonstrate how these differences affect the flow and transport. Finally, we identify the factors that should be taken in consideration when selecting an approach most suitable for the site-specific conditions.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2024

Mechanistic definition and prediction of the mass exchange coefficient between rivers and hyporheic zones: The $α$ of two $Ω$s

Solute transport in interconnected rivers and hyporheic zones is typically modeled through dual-domain models where first-order solute mass transfer between the two domains, Ω R and Ω HZ , is represented by a coefficient α. The transient storage model (TSM) is an example of such an approach. In practice, α is determined by fitting the tails of solute tracer breakthrough curves using a TSM. This approach has led to ambiguity regarding α’s physical meaning and transferability. Here, in this work, we investigated the physical basis for α and tested it with virtual experiments through the fully coupled multiphysics model hyporheicFoam for the Ω R – Ω HZ system. hyporheicFoam explicitly simulated coupled flow and solute transport over a kilometer with centimeter-scale resolution. Model results were analyzed to calculate α following its theoretical definition directly. Using the determined α within a TSM enables accurate reproduction of solute transport, underscoring α’s physical relevance and precision.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Characterizing the impact of finite matrix block size on conservative particle transport through three-dimensional fracture networks

Mass transfer of solutes between fractures and the surrounding rock matrix exerts a noticeable signature on the tail of travel time distributions. When the width of the matrix is assumed to be infinite and advective transport through the fracture is sufficiently fast, the tails of the travel time distributions exhibit a classically expected slope of ψ(t) ∝ t -3/2 . However, studies have yet to characterize how solute transfer between fractures via diffusion through finite matrix blocks influences the tail’s slope in three-dimensional fractured media. Here, in this study, we assess the impact of finite matrix block size on breakthrough curve shape at different spatio-temporal scales by con ducting particle tracking simulations in three-dimensional discrete fracture networks. We consider a variety of hydrodynamic and geostructural proper ties to determine their relative impact on the resulting travel time distributions. We observe that the impact of matrix diffusion through a finite block on travel time distributions is similar to that of an infinite matrix block when the fracture spacing is sufficiently large, matrix diffusion is relatively weak, or transport is considered at an early control plane distance. We observe that the converse of these conditions, results in deviations from the classical ψ(t) ∝ t -3/2 scaling. These results provide a first step toward developing a metric to assess when finite block size effects are expected to significantly influence transport.

58 GEOSCIENCES↗
DOE OSTI2018

Rate analysis of sorption of Ce 3+ , Sm 3+ , and Yb 3+ ions from aqueous solution using Dowex 50W-X8 as a sorbent in a continuous flow reactor

Kinetic analysis of removal of three rare earth elements metals, Ce 3+ , Sm 3+ , and Yb 3+ ions from aqueous solutions in a continuous flow fixed bed reactor using Dowex 50W-X8 ion-exchange resin was conducted here. The performance of the fixed bed sorption was evaluated using the concept of the sorption breakthrough process. Parameters characteristic of a fixed bed sorption such as breakthrough times, saturation times, critical reactor lengths, and lengths of mass transfer zone were inferred from the metal ion concentration breakthrough curves. The sorption capacity of Dowex 50W-X8 ion-exchange resin for Ce 3+ , Sm 3+ , and Yb 3+ are 191, 252, and 294 mg/g, respectively. The sorption kinetics were evaluated using a zero-order, first-order and second-order reaction models. The kinetics of the sorption process follows a zero-order model which has not been reported before. The rate constants of sorption using the zero-order kinetic model are obtained. Two different analysis were conducted to identify whether the diffusion is intraparticle or film diffusion. Finally, both analysis confirms that the film diffusion is the controlling mechanism in reactor bed.

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

Mussel-inspired surface modification of untreated wasted husks with stable polydopamine/polyethylenimine for efficient continuous Cr(VI) removal

Highlights: • Functional rice husks with abundant amino groups was firstly modified with PDA/PEI for Cr(VI) removal. • Potentiality of monolithic samples for dynamic continuous adsorption. • Expectable higher adsorption capacity than most of reported similar bio-sorbents. • Excellent mechanical stability, reusability and convenient separation. - Abstract: A cost-effective and chemically modified biological adsorbent based on agricultural wasted husks for heavy metal removal was fabricated by coating with Polydopamine–Polyethylenimine via the mussel inspired chemistry. Batch and fixed bed column adsorption experiments were carried out to explore the sorption capacity and potency of industrial application. The batch results indicated that the maximum adsorption capacity reached 42.8 mg/g which is much larger than most adsorbents based on bioresource and agricultural wastes for Cr(VI) removal in aqueous solution simultaneously with excellent recycling performance. In column adsorption experiments, it exhibited high mechanical stability and applied potential. The equilibrium time was 9130 min under the flow rate of 1 ml/min, and reached the equilibrium adsorption capacity of 47.14 mg/g. The breakthrough curves ploted by the data of fixed bed experiments under different flow rates (1 ml/min & 2 ml/min) fitted the Thomas model with R{sup 2} of 0.9510 and 0.9437 respectively.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2015

Multiple-tracer tests for contaminant transport process identification in saturated municipal solid waste

Highlights: • Multiple tracers were applied to saturated MSW to test dual-porosity properties. • Lithium demonstrated to be non-conservative as a tracer. • 260 mm diameter column too small to test transport properties of MSW. • The classical advection-dispersion mode was rejected due to high dispersivity. • Characteristic diffusion times did not vary with the tracer. - Abstract: Two column tests were performed in conditions emulating vertical flow beneath the leachate table in a biologically active landfill to determine dominant transport mechanisms occurring in landfills. An improved understanding of contaminant transport process in wastes is required for developing better predictions about potential length of the long term aftercare of landfills, currently measured in timescales of centuries. Three tracers (lithium, bromide and deuterium) were used. Lithium did not behave conservatively. Given that lithium has been used extensively for tracing in landfill wastes, the tracer itself and the findings of previous tests which assume that it has behaved conservatively may need revisiting. The smaller column test could not be fitted with continuum models, probably because the volume of waste was below a representative elemental volume. Modelling compared advection-dispersion (AD), dual porosity (DP) and hybrid AD–DP models. Of these models, the DP model was found to be the most suitable. Although there is good evidence to suggest that diffusion is an important transport mechanism, the breakthrough curves of the different tracers did not differ from each other as would be predicted based on the free-water diffusion coefficients. This suggested that solute diffusion in wastes requires further study.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2020

Understanding How Ligand Functionalization Influences CO2 and N2 Adsorption in a Sodalite Metal–Organic Framework

In this work, a detailed study is conducted to understand how ligand substitution influences the CO2 and N2 adsorption properties of two highly crystalline sodalite metal–organic frameworks (MOFs) known as Cu–BTT (BTT–3 = 1,3,5-benzenetristetrazolate) and Cu–BTTri (BTTri–3 = 1,3,5-benzenetristriazolate). The enthalpy of adsorption and observed adsorption capacities at a given pressure are significantly lower for Cu–BTTri compared to its tetrazole counterpart, Cu–BTT. In situ X-ray and neutron diffraction, which allow visualization of the CO2 and N2 binding sites on the internal surface of Cu–BTTri, provide insights into understanding the subtle differences. As expected, slightly elongated distances between the open Cu2+ sites and surface-bound CO2 in Cu–BTTri can be explained by the fact that the triazolate ligand is a better electron donor than the tetrazolate. The more pronounced Jahn–Teller effect in Cu–BTTri leads to weaker guest binding. The results of the aforementioned structural analysis were complemented by the prediction of the binding energies at each CO2 and N2 adsorption site by density functional theory calculations. In addition, variable temperature in situ diffraction measurements shed light on the fine structural changes of the framework and CO2 occupancies at different adsorption sites as a function of temperature. Finally, simulated breakthrough curves obtained for both sodalite MOFs demonstrate the materials’ potential performance in dry postcombustion CO2 capture. The simulation, which considers both framework uptake capacity and selectivity, predicts better separation performance for Cu–BTT. The information obtained in this work highlights how ligand substitution can influence adsorption properties and hence provides further insights into the material optimization for important separations.

adsorption capacities↗
DOE OSTI2018

Transport and Retention of Concentrated Oil-in-Water Emulsions in Porous Media

Oil-in-water emulsions are routinely used in subsurface remediation. In these applications, high oil loadings present a challenge to remedial design as mechanistic insights into transport and retention of concentrated emulsions is limited. In this paper, column experiments were designed to examine emulsion transport and retention over a range of input concentrations (1.3–23% wt). Droplet breakthrough and retention data from low concentration experiments were successfully described by existing particle transport models. These models, however, failed to capture droplet transport in more concentrated systems. At high oil fraction, breakthrough curves exhibited an early fall at the end of the emulsion pulse and extending tailing. Irrespective of input concentration, all retention profiles displayed hyper-exponential behavior. Here, we extended existing model formulations to include the additional mixing processes occurring when at high oil concentrations—with focus on the influence of deposited mass and viscous instabilities. The resulting model was parametrized with low concentration data and can successfully predict concentrated emulsion transport and retention. Finally, the role of retained mass and viscous instabilities on mixing conditions can also be applied more broadly to systems with temporal or spatially variant water saturation or when viscosity contrasts exist between fluids.

54 ENVIRONMENTAL SCIENCES↗