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Results for “Breakthrough Curves”

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 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Direct Breakthrough Curve Prediction From Statistics of Heterogeneous Conductivity Fields

In this paper, we present a methodology to predict the shape of solute breakthrough curves in heterogeneous aquifers at early times and/or under high degrees of heterogeneity, both cases in which the classical macrodispersion theory may not be applicable. The methodology relies on the observation that breakthrough curves in heterogeneous media are generally well described by lognormal distributions, and mean breakthrough times can be predicted analytically. The log-variance of solute arrival is thus sufficient to completely specify the breakthrough curves, and this is calibrated as a function of aquifer heterogeneity and dimensionless distance from a source plane by means of Monte Carlo analysis and statistical regression. Using the ensemble of simulated groundwater flow and solute transport realizations employed to calibrate the predictive regression, reliability estimates for the prediction are also developed. Additional theoretical contributions include heuristics for the time until an effective macrodispersion coefficient becomes applicable, and also an expression for its magnitude that applies in highly heterogeneous systems. Finally, it is seen that the results here represent a way to derive continuous time random walk transition distributions from physical considerations rather than from empirical field calibration.

58 GEOSCIENCES↗
DOE OSTI2019

Matrix Diffusion in Fractured Media: New Insights Into Power Law Scaling of Breakthrough Curves

Here, we develop a theoretical model for power law tailing behavior of transport in fractured rock based on the relative dominance of the decay rate of the advective travel time distribution, modeled using a Pareto distribution (with tail decaying as ~ time -(1+α) ), versus matrix diffusion, modeled using a Lévy distribution. The theory predicts that when the advective travel time distribution decays sufficiently slowly (α<1), the late-time decay rate of the breakthrough curve is -(1+α/2) rather than the classical -3/2. Yet, if α>1, the -3/2 decay rate is recovered. For weak matrix diffusion or short advective first breakthrough times, we identify an early-time regime where the breakthrough curve follows the Pareto distribution, before transitioning to the late-time decay rate. The theoretical predictions are validated against particle tracking simulations in the three-dimensional discrete fracture network simulator dfnWorks, where matrix diffusion is incorporated using a time domain random walk.

58 GEOSCIENCES↗
DOE OSTI2022

Machine-Learning of Nonlocal Kernels for Anomalous Subsurface Transport from Breakthrough Curves

Anomalous behavior is ubiquitous in subsurface solute transport due to the presence of high degrees of heterogeneity at different scales in the media. Although fractional models have been extensively used to describe the anomalous transport in various subsurface applications, their application is hindered by computational challenges. Simpler nonlocal models characterized by integrable kernels and finite interaction length represent a computationally feasible alternative to fractional models; yet, the informed choice of their kernel functions still remains an open problem. We propose a general data-driven framework for the discovery of optimal kernels on the basis of very small and sparse data sets in the context of anomalous subsurface transport. Using spatially sparse breakthrough curves recovered from fine-scale particle-density simulations, we learn the best coarse-scale nonlocal model using a nonlocal operator regression technique. Predictions of the breakthrough curves obtained using the optimal nonlocal model show good agreement with fine-scale simulation results even at locations and time intervals different from the ones used to train the kernel, confirming the excellent generalization properties of the proposed algorithm. A comparison with trained classical models and with black-box deep neural networks confirms the superiority of the predictive capability of the proposed model.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

Improved Method for Estimating Reaction Rates During Push‐Pull Tests

Abstract The breakthrough curve obtained from a single‐well push‐pull test can be adjusted to account for dilution of the injection fluid in the aquifer fluid. The dilution‐adjusted breakthrough curve can be analyzed to estimate the reaction rate of a solute. The conventional dilution‐adjusted method assumes that the ratios of the concentrations of the nonreactive and reactive solutes in the injection fluid vs. the aquifer fluid are equal. If this assumption is invalid, the conventional method will generate inaccurate breakthrough curves and may lead to erroneous conclusions regarding the reactivity of a solute. In this study, a new method that generates a dilution‐adjusted breakthrough curve was theoretically developed to account for any possible combination of nonreactive and reactive solute concentrations in the injection and aquifer fluids. The newly developed method was applied to a field‐based data set and was shown to generate more accurate dilution‐adjusted breakthrough curves. The improved dilution‐adjusted method presented here is simple, makes no assumptions regarding the concentrations of the nonreactive and reactive solutes in the injection and aquifer fluids, and easily allows for estimating reaction rates during push‐pull tests.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Chromatographic Modeling of 1-Foot Detritiation Test Column Results for the Optimization of Regeneration Time

This report documents the methods and results of a modeling study on a series of data generated by 1-foot test columns for the Water Detritiation project. In order to compliment modeling work already in progress on this project, a purely empirical curve-fitting approach is used in this study to determine chromatographic performance indicators such as retention time, curve width, and the number of chromatographic stages. The data used in this study comes from four sets of chromatographic test separations performed in March through May of 2017 using 1-foot columns. All are using the same flow rates and temperature (room temperature, nominally 25 C°). The first set of data (referred to in this report as the Column 1 data) is a series of twelve breakthrough curve measurements. Prior to each of these twelve runs, the column was regenerated by flowing hydrogen gas through the column, for increasing amounts of time, ranging from 2 hours to 25 hours. The second set of data (referred to as the Column 2 data) is comprised of five measurements of breakthrough curves measured in similar fashion as the Column 1 data, across a range of regeneration times from 2 to 21 hours. The third set of data (referred to as the Purge data) is of three breakthrough curves, measured after a regeneration time of 8 hours, which takes place after a nitrogen purge of 15, 30, or 45 minutes. The fourth data set is a series of five breakthrough curve measurements using a 2 nd batch of stationary phase, taken after regeneration times ranging from 2 to 20 hours. The overall modeling approach is as follows. First, the data is pre-processed for formatting, artifact removal, and is normalized. The data is then fit by integrated versions of four common chromatographic models. The best model is chosen based on the predictive performance of the model, and chromatographic performance values are calculated based on the best model’s fit parameters. Each of these processes are detailed below.

42 ENGINEERING↗
DOE OSTI2023

Numerical evaluation of photosensitive tracers as a strategy for separating surface and subsurface transient storage in streams

For this work, we numerically evaluated photosensitive tracers as a potential strategy for separating the effects of surface and hyporheic storage zones (SSZs and HSZs, respectively) on stream corridor transport. Correctly separating HSZ and SSZ effects is critical to estimating the hydro-biogeochemical function of a stream because HSZs and SSZs expose solutes to significantly different biogeochemical conditions, like sunlight exposure, microbial processes, and oxygen availability. Our numerical experiments used a multiscale river-corridor transport model implemented in the ATS code, which accommodates multiple storage zones with distinct travel time distributions and biogeochemical reactions. For parameter inferences, we used Bayesian inverse modeling. We found that breakthrough curves for photo-decaying tracers from day and night injection can delineate surface and hyporheic transient storage contributions, but only when interpreted jointly through a two-storage zone model. Numerical experiments that used only daytime injection or interpreted breakthrough curves with a single storage zone model yielded good fit to breakthrough curves, but parameter estimates were biased and controlling processes misattributed, examples of good model fits for the wrong reasons. Using those biased parameter estimates in reactive transport simulations resulted in significantly different projections of denitrification, which underscores the potential for stream function to be mischaracterized if tracer tests are interpreted through an inappropriately simplified model for transient storage. More generally, this study highlights the role of modeling in evaluating the experimental design and identifying the potential of system mischaracterization and its implications.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

INL Intern Poster Session

Characterization of off-gas constituents from nuclear fuel reprocessing can be measured using a residual gas analyzer. Characterization of this off-gas is important in a closed fuel cycle, where gasses such as Nox, Kr, I, and C-14 need to be removed from reprocessing plants to meet regulatory requirements. Both Kr and Xe have low chemical reactivity, making capture and separation difficult. Solid sorbents can be used to capture these gases as an alternative to cryogenic distillation, which is energy intensive and hazardous. AgZ-PAN and HZ-PAN are two solid sorbents that have demonstrated selective capture of Xe and Kr. A residual gas analyzer can be used to obtain breakthrough curves that demonstrate how well this adsorption and separation occur. The breakthrough curve is dependent on packing density, column size, and flow rate. Data obtained from the RGA was verified with a gas chromatographer.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2018

Transport of perfluorocarbon tracers in the Cranfield Geological Carbon Sequestration Project

A field–scale carbon dioxide (CO 2 ) injection pilot project was conducted by the Southeast Regional Carbon Sequestration Partnership (SECARB) at Cranfield, Mississippi. Two associated campaigns in 2009 and 2010 were carried out to co–inject perfluorocarbon tracers (PFTs) and sulfur hexafluoride (SF 6 ) with CO 2 . Tracers in gas samples from two observation wells were analyzed to construct breakthrough curves. In this work, we present the field data and numerical modeling of the flow and transport of CO 2 , brine, and tracers. A high–resolution static model of the formation geology in the detailed area study (DAS) was used to capture the impact of connected flow pathways created by fluvial channels on breakthrough curves and breakthrough times of PFTs and SF6 tracers. We use the cubic–plus–association (CPA) equation of state, which takes into account the polar nature of water molecules, to describe the phase behavior of CO 2 –brine–tracer mixtures. Our simulated results show good agreement for the 2009 tracer campaign in Cranfield, while a larger discrepancy emerges by 2010. Here, the combination of multiple tracer injection pulses with detailed numerical simulations proves to be a powerful tool in constraining both formation properties and how complex flow paths develop over time.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Field experiments of surface water to groundwater recharge to characterize the mobility of uranium and vanadium at a former mill tailing site

Characterizing the mobility of uranium and vanadium in groundwater with a hydraulic connection to surface water is important to inform the best management practices of former mill tailing sites. In this study, the recharge of river water to the unsaturated and saturated zones of a uranium-contaminated alluvial aquifer was simulated in a series of forced-gradient single- and multi-well injection-extraction tests. The injection fluid (river water) was traced with natural and artificial tracers that included halides, fluorobenzoates, lithium, and naphthalene sulfonate to characterize the potential mass transport mechanisms of uranium and vanadium. The extraction fluid (river water/groundwater mixture) was analyzed for the tracers, uranium, and vanadium. The results from the tracers indicated that matrix diffusion was likely negligible over the spatiotemporal scales of the tests as evident by nearly identical breakthrough curves of the halides and fluorobenzoates. In contrast, the breakthrough curves of lithium and naphthalene sulfonate indicated that sorption by cation exchange and sorption to organic matter, respectively, were potential mass transport mechanisms of uranium and vanadium. Uranium was mobilized in the saturated zone containing gypsum (gypsum-rich zone), the vadose zone (vadose-rich zone), and the saturated zone containing organic carbon (organic-rich zone) whereas vanadium was mobilized only in the saturated gypsum-rich zone. The mechanisms responsible for the mobilization of uranium and vanadium were likely dissolution of uranium- and vanadium-bearing minerals and/or desorption from the gypsum-rich zone, flushing of uranium from the vadose-rich zone, and desorption of uranium from the organic-rich zone due to the natural contrast in the geochemistry between the river water and groundwater. The experimental design of this study was unique in that it employed the use of multiple natural and artificial tracers coupled with a direct injection of native river water to groundwater. Here, these results demonstrated that natural recharge and flooding events at former mill tailing sites can mobilize uranium, and possibly vanadium, and contribute to persistent levels of groundwater contamination.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Using the Diffusion Equation to Predict CST Resin Breakthroughs - 19051

The crystalline silicotitanate, CST, resin manufactured by UOP Honeywell is well-suited for single-use decontamination of caustic liquid wastes at Hanford and Savannah River Sites. There are many measurements of column loading and breakthrough for CST resin decontamination of Cs-137 in various Hanford and SRS waste simulants. Such measurements provide a very good basis for estimating CST resin demand and these more refined predictions make the CST column loading as efficient as possible given the very expensive CST resin. Although there are a variety of tools for predicting chromatographic resin column performance, [1-4], there is a particularly useful method that is suitable as a simple spreadsheet model [4]. This spreadsheet model is an analytical error function for the mass transfer zone (mtz) diffusion width in resin columns and is well-suited for resin breakthrough and column loading. This paper describes just such an error function spreadsheet model and how well the error function agrees with more traditional models and fits the observed small scale breakthrough curves for CST that can then better predict large scale column loading efficiency. The very high sorption of Cs onto CST tends to be slower than that of other lower sorption resins and as a result of the slow CST kinetics, there is also a marked asymmetry in many CST breakthrough curves. The CST breakthrough asymmetry is largely due to the distribution of CST particle sizes because smaller particles sorb much faster than larger particles. It is then the smaller particles that determine the leading mtz at a decontamination factor of 1,000 breakthrough and therefore the decontamination efficiency for a given loading. The larger CST particles correspondingly determine the tailing mtz width and therefore the overall loading efficiency and it is important to model both leading and tailing mtz widths to best optimize CST for a particular Cs-137 decontamination application. (authors)

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

Fracture Network Influence on Rock Damage and Gas Transport following an Underground Explosion

Simulations of rock damage and gas transport following underground explosions that omit preexisting fracture networks in the subsurface cannot fully characterize the influence of geo-structural variability on gas transport. Previous studies do not consider the impact that fracture network structure and variability have on gas seepage. In this study, we develop a sequentially coupled, axi-symmetric model to look at the damage pattern and resulting gas breakthrough curves following an underground explosion given different fracture network realizations. We simulate 0.327 and 0.164 kT chemical explosives with burial depths of 100 m for 90 stochastically generated fracture networks. Gases quickly reach the surface in 30% of the higher yield simulations and 5% of the lower yield simulations. The fast breakthrough can be attributed to the formation of connected pathways between fractures to the surface. The formation of a connected damage pathway to the surface is not clearly correlated with the fracture intensity (P32) in our simulations. Breakthrough curves with slower transport are highly variable depending on the fracture network sample. The variability in the breakthrough behavior indicates that ignoring the influence of fracture networks on rock damage, which strongly influences the hydraulic properties following an underground explosion, will likely lead to a large underestimation of the uncertainty in the gas transport to the surface. This work highlights the need for incorporation of fracture networks into models for accurately predicting gas seepage following underground explosions.

58 GEOSCIENCES↗
DOE OSTI2020

Adaptive Multirate Mass Transfer (aMMT) Model: A New Approach to Upscale Regional‐Scale Transport Under Transient Flow Conditions

Abstract The long‐term evaluation of regional‐scale groundwater quality needs efficient upscaling methods for transient flow. Upscaling techniques, such as the Multirate Mass Transfer (MRMT) method with constant upscaling parameters, have been used for transport with steady‐state flow, yet the upscaling parameters (i.e., rate coefficients) may be time dependent. This study proposed and validated an adaptive MRMT (aMMT) method by allowing the mass transfer coefficients in MRMT to change with the flow field. Advective‐dispersive contaminant transport simulated in a 3‐D heterogeneous medium was used as a reference solution. Equivalent transport under homogeneous flow conditions was evaluated by applying the MRMT and aMMT models for upscaling. The relationship between mass transfer coefficients and flow rates was fitted under steady‐state flow driven by various hydraulic gradients. A power law relationship was obtained, which was then used to update the mass transfer coefficients in each stress period under transient flow conditions in the aMMT method. Results indicated that for advection‐dominated transport, both the MRMT and aMMT methods can upscale the anomalous transport dynamics affected by subgrid heterogeneity under transient flow conditions. Whereas for diffusion‐dominated systems, the MRMT model failed to capture the tails of tracer breakthrough curves after the boundary condition changed, but the results from the aMMT model were significantly improved. However, if the overall flow direction changed, both MRMT and aMMT failed to represent the breakthrough curve tail generated by the heterogeneous system. The results point toward a promising path for upscaling transport in complex aquifers with transient flow.

Guo, Zhilin↗
DOE OSTI2021

Contributions of biofilm-induced flow heterogeneities to solute retention and anomalous transport features in porous media

We report that microbial biofilms are ubiquitous within porous media and the dynamics of their growth influence surface and subsurface flow patterns which impacts the physical properties of porous media and large-scale transport of solutes. Here, a two-dimensional pore-scale numerical model was used to evaluate the impact of biofilm-induced flow heterogeneities on conservative transport. Our study integrates experimental biofilm images of Paenibacillus 300A strain in a microfluidic device packed with cylindrical grains in a hexagonal distribution, with mathematical modeling. Biofilm is represented as a synthetic porous structure with locally varying physical properties that honors the impact of biofilm on the porous medium. We find that biofilm plays a major role in shaping the observed conservative transport dynamics by enhancing anomalous characteristics. More specifically, when biofilm is present, the pore structure in our geometry becomes more spatially correlated. We observe intermittent behavior in the Lagrangian velocities that switches between fast transport periods and long trapping events. Our results suggest that intermittency enhances solute spreading in breakthrough curves which exhibit extreme anomalous slope at intermediate times and very marked late solute arrival due to solute retention. The efficiency of solute retention by the biofilm is controlled by a transport regime which can extend the tailing in the concentration breakthrough curves. These results indicate that solute retention by the biofilm exerts a strong control on conservative solute transport at pore-scale, a role that to date has not received enough attention.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Linking structural and transport properties in three-dimensional fracture networks

Here, we investigate large scale particle motion and solute breakthrough in sparse three-dimensional discrete fracture networks (DFN) characterized by power-law distributed fracture lengths. The three networks we consider have the same fracture intensity values but exhibit different percolation densities, geometric properties and topological structures. We considered two different average transport models to predict solute breakthrough, a streamtube model and a Bernoulli CTRW model, both of which provide insights into the flow fields within the networks. The streamtube model provides acceptable predictions at short distances in two of the networks, but fails in all cases to predict breakthrough times at the outlet plane, which indicates that particle motion in such fracture networks cannot be characterized by a constant velocity between the inlet and control plane at which the breakthrough curve is detected. Rather the structure of the network requires that frequent velocity transitions be made as particles move through the system. Despite the relatively broad distribution of fracture radii and relatively small number of independent velocity transitions, the CTRW approach conditioned on the initial velocity distribution provides reasonable predictions for the breakthrough curves at different distances from the inlet. The application of these averaged transport models provides a richer understanding of the link from the fracture network structure to ow and transport properties.

58 GEOSCIENCES↗
DOE OSTI2023

Harnessing Uncertainty through Functional Data Analysis in Gas Breakthrough Data

Detecting subsurface explosions from radionuclide gas migration through rock fractures is an effective way to identify nuclear activity. Los Alamos National Laboratory (LANL) has developed simulation methods, based on data from the 1962 Hardhat underground nuclear test, to predict gas breakthrough times at the surface. However, these methods rely on an imperfect understanding of the relationship between rock damage and fracture permeability. Our clinic project studies methods for predicting breakthrough curves that characterize total mass produced as a function of time, as well as quantifying the uncertainty associated with these predictions. The model that is currently employed to relate damage to permeability uses an empirically motivated power-law expression, with a range of parameter values that are compatible with the experimental Hardhat data. We develop emulators, built from functional data analysis techniques and trained on simulation data, that rapidly predict the gas breakthrough curve given a damage field and given the parameter values of the power-law equation. Using Bayesian regression, we address the problem of uncertainty quantification in our emulators. Finally, in order to test the robustness of the model, we further validate it on a damage field representing different physical conditions.

58 GEOSCIENCES↗
DOE OSTI2025

Direct Observations of Solute Dispersion in Rocks With Distinct Degree of Sub‐Micron Porosity

Abstract The transport of chemical species in rocks is affected by their structural heterogeneity to yield a wide spectrum of local solute concentrations. To quantify such imperfect mixing, advanced methodologies are needed that augment the traditional breakthrough curve analysis by probing solute concentration within the fluids locally. Here, we demonstrate the application of asynchronous, multimodality imaging by X‐ray computed tomography (XCT) and positron emission tomography (PET) to the study of passive tracer experiments in laboratory rock cores. The four‐dimensional concentration maps measured by PET reveal specific signatures of the transport process, which we have quantified using fundamental measures of mixing and spreading. We observe that the extent of solute spreading correlate strongly with the strength of subcore‐scale porosity heterogeneity measured by XCT, while dilution is enhanced in rocks containing substantial sub‐micron porosity. We observe that the analysis of different metrics is necessary, as they can differ in their sensitivity to the strength and forms of heterogeneity. The multimodality imaging approach is uniquely suited to probe the fundamental difference between spreading and mixing in heterogeneous media. We propose that when multi‐dimensional data is available, mixing and spreading can be independently quantified using the same metric. We also demonstrate that one‐dimensional transport models have limited predictive ability toward the internal evolution of the solute concentration, when the model is solely calibrated against the effluent breakthrough curves. The data set generated in this study can be used to build realistic digital rock models and to benchmark transport simulations that account deterministically for rock property heterogeneity.

Kurotori, Takeshi [Department of Chemical Engineer↗
DOE OSTI2024

Enhancing predictive understanding and accuracy in geological carbon dioxide storage monitoring: Simulation and history matching of tracer transport dynamics

Co-injection of conservative tracers with carbon dioxide (CO 2 ) is a viable tool for monitoring subsurface processes during geological CO 2 storage (GCS). This research investigates the simulation and history-matching of a gas tracer (sulfur hexafluoride, SF 6 ) during CO 2 flooding, employing a core flooding result in Berea sandstone. Four extensively used saturation functions are assessed for their efficacy in history matching of CO 2 /SF 6 injection at the core scale. The history-matching process incorporates particle swarm optimization (PSO) to fine-tune constitutive relationships parameters. Next, employing transport models at the aquifer scale, we interrogate the impact on tracer transport and mixing of saturation function uncertainties, arising from the non-uniqueness of constitutive relationships parameters and saturation function types. To assess the effects of geological heterogeneity on behavior of tracer breakthrough curves (BTCs), we employ two normalized parameters assessing the degree of mixing and SF 6 breakthrough time. The aquifer-scale investigation encompasses both homogeneous and heterogeneous systems with and without capillary heterogeneity effects. Our findings underscore the critical importance of addressing saturation function uncertainties, emphasizing the significance of auxiliary experiments and innovative methodologies to enhance predictive accuracy. The findings highlight significant disparities in arrival times, BTC peaks, tails, and mixing levels, even under optimal conditions. Heterogeneity, with or without capillary heterogeneity, plays a crucial role in shaping BTC variations, resulting in accelerated SF 6 breakthrough times and reduced BTC peaks. Evaluation of monitoring points distant from the injector reveals a dampening effect on the SF6 BTC peak, particularly in heterogeneous systems with capillary heterogeneity, where the peak is halved. These insights underscore the challenges associated with tracer monitoring and the necessity for enhanced methodologies to improve predictive accuracy in subsurface processes during GCS.

58 GEOSCIENCES↗