Alien Registration- Bolster, Albert D. (Wade, Aroostook County)

https://digitalmaine.com/alien_docs/32628/thumbnail.jp

Recent advances in anomalous transport models for predicting contaminants in natural groundwater systems

High degrees of spatial heterogeneity in hydrologic systems pose a major barrier for their protection and remediation. Dissolved and particulate contaminants are mixed and retained over timescales ranging from seconds to years due to their interactions with these structural heterogeneities. Over the last two decades, a new class of models has demonstrated its capacity to describe observed ‘anomalous transport’ behavior that is ubiquitous to nearly all flowing waters. The promise of these models lies in their potential for predicting transport using minimal parameters, while remaining faithful to the underlying complexity of the system. In this review, we highlight recent experimental studies that have improved our understanding of the structural controls of anomalous transport, as well as modeling studies that use these new insights to better predict contaminant fate

Filtered deterministic waves and analysis of the fractal dimension of the components of the wind velocity

The difficulty in developing models for waves in turbulent flows is a key problem in the analysis of the complexity of turbulence. We present a method to find and filter perturbations that are generated by the flow of deterministic waves from the power spectrum in the atmospheric boundary layer (ABL). The perturbation model proposed assumes that the amplitude and frequency of such waves decay with time exponentially. For illustrative purposes, we apply the technique to three time series of wind velocities obtained with a sonic anemometer. This analytical procedure allows us to filter waves of the proposed structure with a 99% significance level in the power spectrum. We have applied the same method to 540 such wind series, all painting similar results. We then compare the fractal dimension of the original series to those from which the waves have been removed. We find that the fractal dimension of the filtered waves is slightly less than that of the original series. Finally, we consider the fractal dimension of the studied series as a function of the length-scales and dissipation rate of kinetic energy per unit mass. Our results suggest an increase of fractal dimension with both length-scale and dissipation rate of kinetic energy

Apparent directional mass-transfer capacity coefficients in three-dimensional anisotropic heterogeneous aquifers under radial convergent transport

        Aquifer hydraulic properties such as hydraulic conductivity (K) are ubiquitously heterogeneous and typically only a statistical characterization can be sought. Additionally, statistical anisotropy at typical characterization scales is the rule. Thus, regardless of the processes governing solute transport at the local (pore) scale, transport becomes non‐Fickian. Mass‐transfer models provide an efficient tool that reproduces observed anomalous transport; in some cases though, these models lack predictability as model parameters cannot readily be connected to the physical properties of aquifers. In this study, we focus on a multirate mass‐transfer model (MRMT), and in particular the apparent capacity coefficient (β), which is a strong indicator of the potential of immobile zones to capture moving solute. We aim to find if the choice of an apparent β can be phenomenologically related to measures of statistical anisotropy. We analyzed an ensemble of random simulations of three‐dimensional log‐transformed multi‐Gaussian permeability fields with stationary anisotropic correlation under convergent flow conditions. It was found that apparent β also displays an anisotropic behavior, physically controlled by the aquifer directional connectivity, which in turn is controlled by the anisotropic correlation model. A high hydraulic connectivity results in large β values. These results provide new insights into the practical use of mass‐transfer models for predictive purposes. &nbsp

Probabilistic risk analysis of groundwater remediation strategies

Heterogeneity of subsurface environments and insufficient site characterization are some of the reasons why decisions about groundwater exploitation and remediation have to be made under uncertainty. A typical decision maker chooses between several alternative remediation strategies by balancing their respective costs with the probability of their success or failure. We conduct a probabilistic risk assessment (PRA) to determine the likelihood of the success of a permeable reactive barrier, one of the leading approaches to groundwater remediation. While PRA is used extensively in many engineering fields, its applications in hydrogeology are scarce. This is because rigorous PRA requires one to quantify structural and parametric uncertainties inherent in predictions of subsurface flow and transport. We demonstrate how PRA can facilitate a comprehensive uncertainty quantification for complex subsurface phenomena by identifying key transport processes contributing to a barrier's failure, each of which is amenable to uncertainty analysis. Probability of failure of a remediation strategy is computed by combining independent and conditional probabilities of failure of each process. Individual probabilities can be evaluated either analytically or numerically or, barring both, can be inferred from expert opinio

Effect of spatial concentration fluctuations on effective kinetics in diffusion-reaction systems

International audienceThe effect of spatial concentration fluctuations on the reaction of two solutes, A þ B* C, is considered. In the absence of fluctuations, the concentration of solutes decays as Adet ¼ Bdet t 1. Contrary to this, experimental and numerical studies suggest that concentrations decay significantly slower. Existing theory suggests a t d/4 scaling in the asymptotic regime (d is the dimensionality of the problem). Here we study the effect of fluctuations using the classical diffusion-reaction equation with random initial conditions. Initial concentrations of the reactants are treated as correlated random fields.We use the method of moment equations to solve the resulting stochastic diffusion-reaction equation and obtain a solution for the average concentrations that deviates from t 1 to t d/4 behavior at characteristic transition time t . We also derive analytical expressions for t as a function of Damköhler number and the coefficient of variation of the initial concentration

Association of Pain Centralization and Patient‐Reported Pain in Active Rheumatoid Arthritis

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/156205/2/acr23994_am.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/156205/1/acr23994.pd