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Breakthrough Curve
The Experts below are selected from a list of 315 Experts worldwide ranked by ideXlab platform
B Jai S Prakash – 1st expert on this subject based on the ideXlab platform

interaction of chromate on surfactant modified montmorillonite Breakthrough Curve study in fixed bed columns
Industrial & Engineering Chemistry Research, 2008CoAuthors: N Mahadevaiah, B Venkataramani, B Jai S PrakashAbstract:Interactions between chromate and surfactant modified montmorillonite at room temperature (25 °C) and different pHs (17) in aqueous solution in fixed bed columns have been studied. A series of column tests were performed to determine the Breakthrough Curves at different initial surfactant loadings (0.53 CEC) of the bed. The interlayer spacing increased with the surfactant loading from 14.2 to 40.5 A. Experimental results of the column tests and the basal spacing of the column material showed that the adsorption of chromate onto the clay did not occur until the initial surfactant loading was beyond a critical concentration apparently enough to open the clay sheets for the entry of chromate species. The shapes of the Breakthrough Curves indicate that the chromate ions enter the interlamellar region only when the initial surfactant loadings are beyond 2 times the CEC of the clay. The amount of adsorbate increases proportionally with increasing bed depth. A simple twoparameter model originally introduced by Yoon and Nelson (Yoon, Y. H.; Nelson, J. H. Am. Ind. Hyg. Assoc. J. 1984, 45, 509) was used to calculate the Breakthrough time. Chromate could be recovered completely by washing with ammonium hydroxide, and the column material was found to regain its capacity to adsorb repeatedly after simple acid wash.

restrictive entry of aqueous molybdate species into surfactant modified montmorillonitea Breakthrough Curve study
Chemistry of Materials, 2007CoAuthors: N Mahadevaiah, B Venkataramani, B Jai S PrakashAbstract:Molybdenum sorption behavior and the nature of Breakthrough Curves have been studied in a fixedbed column containing montmorillonite clay modified by treatment with cationic surfactant hexadecyltrimethylammonium (HDTMA) bromide. Different amounts of the surfactant loaded into the interlayer region of the montmorillonite to increase the interlayer spacing is found to enhance molybdate sorption. The sorption was found to be at a maximum in acidic medium (pH <0) and was almost constant between pH 3 and 4. Beyond pH 4, adsorption decreased rapidly and was almost two to four times lower than that in the acid medium. It is known from the equilibria of aquo molybdate species that polymolybdate species Mo8O264 and Mo7O246 are prevalent in the highly acidic medium; the species H2MoO4 and HMoO4 are stable between pH 0 and 4, and MoO42 is predominantly present above pH 5. The variation in adsorption of Mo is interpreted on the basis of the type of species prevalent at different pHs. The sample loaded at 0.5 CEC...
Philip H Stauffer – 2nd expert on this subject based on the ideXlab platform

On estimating functional average Breakthrough Curve using time‐warping technique and perturbation approach
Water Resources Research, 2012CoAuthors: Zhiming Lu, Philip H StaufferAbstract:[1] Simulated contaminant Breakthrough Curves (BTC) are often used to predict mass arrival at compliance boundaries at waste storage sites. In numerical simulations that involve uncertainties on input parameters such as randomly heterogeneous rock properties, Monte Carlo simulations are commonly utilized and the mean Breakthrough Curve is often calculated from the arithmetic average of all realizations. The arithmetic mean Breakthrough Curve in general overestimates the mass flow rate at early and late time but underestimates the peak mass flow rate. The averaged Breakthrough Curve usually does not resemble any of individual Breakthrough Curves. The reason is that BTCs vary not only on amplitude but also on dynamics (time) and therefore it is not appropriate to take the arithmetic average directly. In this study, we consider each BTC as a random Curve, and use timewarping techniques to align all Curves in a timewarped space, compute the sample mean of the Curves in the timewarped space, and transform the means back to the original time space. We show that all BTCs are aligned based on the percentile of mass reaching the compliance boundary, and the functional average is the percentile average of all BTCs. The confidence interval of the sample mean Curve is estimated using the perturbation approach. The functional average provides an additional metric that can be used to characterize the Breakthrough behavior in addition to more traditional median and arithmetic average Curves. The method is illustrated using transport simulations at the Material Disposal Area G, Los Alamos National Laboratory (LANL) in New Mexico.

on estimating functional average Breakthrough Curve using time warping technique and perturbation approach
Water Resources Research, 2012CoAuthors: Zhiming Lu, Philip H StaufferAbstract:[1] Simulated contaminant Breakthrough Curves (BTC) are often used to predict mass arrival at compliance boundaries at waste storage sites. In numerical simulations that involve uncertainties on input parameters such as randomly heterogeneous rock properties, Monte Carlo simulations are commonly utilized and the mean Breakthrough Curve is often calculated from the arithmetic average of all realizations. The arithmetic mean Breakthrough Curve in general overestimates the mass flow rate at early and late time but underestimates the peak mass flow rate. The averaged Breakthrough Curve usually does not resemble any of individual Breakthrough Curves. The reason is that BTCs vary not only on amplitude but also on dynamics (time) and therefore it is not appropriate to take the arithmetic average directly. In this study, we consider each BTC as a random Curve, and use timewarping techniques to align all Curves in a timewarped space, compute the sample mean of the Curves in the timewarped space, and transform the means back to the original time space. We show that all BTCs are aligned based on the percentile of mass reaching the compliance boundary, and the functional average is the percentile average of all BTCs. The confidence interval of the sample mean Curve is estimated using the perturbation approach. The functional average provides an additional metric that can be used to characterize the Breakthrough behavior in addition to more traditional median and arithmetic average Curves. The method is illustrated using transport simulations at the Material Disposal Area G, Los Alamos National Laboratory (LANL) in New Mexico.
John L Hutson – 3rd expert on this subject based on the ideXlab platform

A Breakthrough Curve analysis of unstable density‐driven flow and transport in homogeneous porous media
Water Resources Research, 2004CoAuthors: M Wood, Craig T Simmons, John L HutsonAbstract:[1] In certain hydrogeological situations, density variations occur because of changes in solute concentration, temperature, and pressure of the fluid. These include seawater intrusion, highlevel radioactive waste disposal, groundwater contamination, and geothermal energy production. Under certain conditions, when the density of the invading fluid is greater than that of the ambient one, gravitational instabilities or fingers may lead to transport over larger spatial scales and significantly shorter timescales than compared with diffusion alone. This study has two key objectives: (1) to explore how the nature of a Breakthrough Curve changes as the density of the invading fluid changes and there is a subsequent transition from stable to unstable behavior and (2) to examine the feasibility of using 1D advectiondispersion fitting models to fit the experimental data as the density of the invading fluid increases. Thirtysix Breakthrough Curve experiments were carried out in fully saturated, homogeneous sand columns. Results show that an increase in the density of the source solutions leads to Breakthrough Curves with lower peak concentrations at Breakthrough, earlier peak Breakthrough pore volume and time, and an increase in positive skewness of the Breakthrough Curve. Visual experiments conducted in transparent columns confirm that a transition from stable to unstable behavior occurs as the density of the injectant increases and that backward convective reflux in the highdensity cases leads to dilution of the trailing edge of the pulse as evidenced by positively skewed Breakthrough Curves. These mixed convective systems (controlled by both forced and free convection) are characterized by a mixed convective ratio. Parameter estimation using a 1D advectiondispersion fitting model suggests that unstable plume migration can be fitted with an apparent pore flow velocity and dispersivity at lowdensity gradients. However, as the density of the injectant increases, it becomes progressively difficult to estimate parameters that fit the experimental Curves with a model that does not explicitly account for density effects. Significantly poorer matches are obtained when the invading solution concentration is equal to, or exceeds, the solution concentration denoted by ML (the medium to lowdensity solution), i.e., invading solutions greater than approximately 13,000 mg/L in this study. Care must therefore be taken in applying standard advectiondispersion models to Breakthrough Curve analyses where even modest density differences are encountered.

a Breakthrough Curve analysis of unstable density driven flow and transport in homogeneous porous media
Water Resources Research, 2004CoAuthors: M Wood, Craig T Simmons, John L HutsonAbstract:[1] In certain hydrogeological situations, density variations occur because of changes in solute concentration, temperature, and pressure of the fluid. These include seawater intrusion, highlevel radioactive waste disposal, groundwater contamination, and geothermal energy production. Under certain conditions, when the density of the invading fluid is greater than that of the ambient one, gravitational instabilities or fingers may lead to transport over larger spatial scales and significantly shorter timescales than compared with diffusion alone. This study has two key objectives: (1) to explore how the nature of a Breakthrough Curve changes as the density of the invading fluid changes and there is a subsequent transition from stable to unstable behavior and (2) to examine the feasibility of using 1D advectiondispersion fitting models to fit the experimental data as the density of the invading fluid increases. Thirtysix Breakthrough Curve experiments were carried out in fully saturated, homogeneous sand columns. Results show that an increase in the density of the source solutions leads to Breakthrough Curves with lower peak concentrations at Breakthrough, earlier peak Breakthrough pore volume and time, and an increase in positive skewness of the Breakthrough Curve. Visual experiments conducted in transparent columns confirm that a transition from stable to unstable behavior occurs as the density of the injectant increases and that backward convective reflux in the highdensity cases leads to dilution of the trailing edge of the pulse as evidenced by positively skewed Breakthrough Curves. These mixed convective systems (controlled by both forced and free convection) are characterized by a mixed convective ratio. Parameter estimation using a 1D advectiondispersion fitting model suggests that unstable plume migration can be fitted with an apparent pore flow velocity and dispersivity at lowdensity gradients. However, as the density of the injectant increases, it becomes progressively difficult to estimate parameters that fit the experimental Curves with a model that does not explicitly account for density effects. Significantly poorer matches are obtained when the invading solution concentration is equal to, or exceeds, the solution concentration denoted by ML (the medium to lowdensity solution), i.e., invading solutions greater than approximately 13,000 mg/L in this study. Care must therefore be taken in applying standard advectiondispersion models to Breakthrough Curve analyses where even modest density differences are encountered.