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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. However, 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. A theoretical model is developed for power law tailing of breakthrough curves influenced by matrix diffusion and heterogeneous advectionA threshold decay rate for the advective travel time distribution is identified,below which matrix diffusion produces tail decay rates >−3/2Matrix diffusion is implemented in high‐fidelity three‐dimensioal discrete fracture network simulations to confirm theoretical predictions

We model flow and transport in fracture networks with varying degrees of fracture‐to‐fracture aperture heterogeneity and network intensity to show how changes in these properties can cause the emergence of anomalous flow and transport behavior. If fracture‐to‐fracture aperture heterogeneity is increased in sparse networks, velocity fluctuations inhibit high flow rates and solute transport can be delayed. Surprisingly, transport can be slowed even in cases where hydraulic aperture is monotonically increased. As the intensity of the networks is increased, more connected pathways allow for particles to bypass these effects. There exists transition behavior where with relatively few connected pathways in a network, first arrival times of particles are not heavily affected by fracture‐to‐fracture aperture heterogeneity, but the scaling behavior of the tails is strongly influenced. These results reinforce the importance of considering multi‐scale effects in fractured systems and can inform flow and transport processes in both natural and engineered fractured systems. Fractured rocks are important to study to understand subsurface geology, hydrology, and engineered systems. Individual fractures often form connected networks with other fractures, which complicates the prediction of flow and transport behavior. In this work, we study how changes in fracture network properties such as the variability of fracture apertures and the number of fractures in a network, affect flow and transport observables, such as the amount of actively flowing network structure, as well as the arrival times of solutes. Our results point to rich behavior where there is a close link between how much variability exists between individual fracture apertures, the network intensity, and the behavior of the solute transport. When fracture networks have relatively few fractures, increases in the magnitude of the fracture apertures and the variability between individual apertures can cause unusual changes in the flow and transport, causing delays in solute transport times. However, these effects are gradually lost as the number of fractures in the network is increased. Our results can inform both natural hydrological processes, as well as engineered systems, such as enhanced geothermal systems and hydraulic fracturing because these systems often create high aperture fractures that connect to natural fractures with lower aperture. We investigate the influence of multi‐scale heterogeneity in fracture networks on flow and transport using discrete fracture network modelsHigh aperture heterogeneity across a sparse fracture network results in counter‐intuitive flow and transport behaviorEffects of fracture‐to‐fracture aperture heterogeneity are limited at high network intensities We investigate the influence of multi‐scale heterogeneity in fracture networks on flow and transport using discrete fracture network models High aperture heterogeneity across a sparse fracture network results in counter‐intuitive flow and transport behavior Effects of fracture‐to‐fracture aperture heterogeneity are limited at high network intensities

Fractured reservoirs are complex and multi‐scale systems composed of matrix and fractures. Accordingly, modeling flow in such geological media has been a great challenge. In this study, we investigated the effect of scale as well as matrix and fracture network characteristics on the effective permeability (keff) in matrix‐fracture systems under fully saturated conditions. We generated fracture networks, embedded within a matrix of permeability of 10−18m2, with fracture lengths followed a truncated power‐law distribution with exponent α= 1.5, 2.0, and 2.5. We set fracture permeability equal to 10−16, 10−14, and 10−12m2and numerically simulated fluid flow to determine the keffat six fracture densities for 36 fractured reservoirs. Results showed that the effect of αand scale on the keffbecame more significant as the contrast between matrix and fracture permeabilities increased. We also fit the percolation‐based effective‐medium approximation (P‐EMA) to the simulations and optimized its two parameters critical fracture density and scaling exponent. Results exhibited that both P‐EMA model parameters were scale‐dependent. Through linear regression analysis, we found that the critical fracture density and scaling exponent were highly correlated to other matrix‐fracture system properties and proposed two regression‐based models evaluated using a new six sets of simulations. Comparing the estimated keffvalues with the simulated ones demonstrated the reliability and predictability of the P‐EMA. The matrix‐fracture systems studied here were finite in size. We also showed that one may extend results to infinitely large reservoirs using the P‐EMA framework. Scale‐dependent effective permeability in matrix‐fracture systems is investigated using numerical simulations and theoretical modelingCritical fracture density and scaling exponent are linked to reservoir properties and its size, and results are extended to large systemsTheoretical estimations of effective permeability in six unseen fractured reservoirs agree with numerical simulations well Scale‐dependent effective permeability in matrix‐fracture systems is investigated using numerical simulations and theoretical modeling Critical fracture density and scaling exponent are linked to reservoir properties and its size, and results are extended to large systems Theoretical estimations of effective permeability in six unseen fractured reservoirs agree with numerical simulations well

Understanding mechanistic causes of non‐Fickian transport in fractured media is important for many hydrogeologic processes and subsurface applications. This study elucidates the effects of dead‐end fractures on non‐Fickian transport in three‐dimensional (3D) fracture networks. Although dead‐end fractures have been identified as low‐velocity regions that could delay solute transport, the direct relation between dead‐end fractures and non‐Fickian transport has been elusive. We systematically generate a large number of 3D discrete fracture networks with different fracture length distributions and fracture densities. We then identify dead‐end fractures using a novel graph‐based method. The effect of dead‐end fractures on solute residence time maximizes at the critical fracture density of the percolation threshold, leading to strong late‐time tailing. As fracture density increases beyond the percolation threshold, the network connectivity increases, and dead‐end fractures diminish. Consequently, the increase in network connectivity leads to a reduction in the degree of late‐time tailing. We also show that dead‐end fractures can inform about main transport paths, such as the mean tortuosity of particle trajectories. This study advances our mechanistic understanding of solute transport in 3D fracture networks. A critical phenomenon often observed in fractured rocks is an anomalously slow decay of solute concentration, which is often called solute tailing. Long retention of solute contaminants poses severe threats to human health, and predicting solute tailing is critical for remediation purposes. However, solute tailing is challenging to predict, and understanding the mechanisms inducing solute tailing is important for improving our predictive capability. Recent studies showed that dead‐end fractures form slow‐flow regions that could cause solute tailing. However, no study has explicitly quantified the effects of dead‐end fractures on solute tailing. By simulating flow and transport in three‐dimensional fracture networks over more than 200 realizations, we find that the relationship between fracture density and dead‐end fracture formation is non‐monotonic. Specifically, we observe that there exists a critical level of fracture density where the presence of dead‐end fractures is maximized. At the optimum level, solute particles' residence time in dead‐end fractures significantly increases, leading to strong solute tailing. As fracture density increases beyond the optimum, dead‐end fractures diminish due to the improved network connectivity, reducing solute tailing. This study improves our mechanistic understanding of how dead‐end fractures control solute tailing in fracture networks. A new graph‐based measure that identifies dead‐end fractures is proposedLate‐time solute tailing is maximized at the percolation thresholdThe density of dead‐end fractures is a good predictor of non‐Fickian transport A new graph‐based measure that identifies dead‐end fractures is proposed Late‐time solute tailing is maximized at the percolation threshold The density of dead‐end fractures is a good predictor of non‐Fickian transport

The Indiana Supreme Court recently delivered a landmark public trust decision, Gunderson v. State, ruling that the state acquired and still owns Indiana's bed of Lake Michigan below the ordinary high water mark, including exposed shores, and that it holds that bed in an inalienable trust for public uses. This is a unique decision for the Great Lakes region. This Article examines the legal background for the case, the conflicts and contradictory rulings that emerged as it travelled upward through the court system, and the ultimate resolution by Indiana's high court. The Article also places the decision in the larger context of environmental conservation and public trust advocacy. [ABSTRACT FROM AUTHOR]

We recreate three‐phase reservoir conditions (high‐pressure/temperature) using a microfluidics system and show that the use of scCO2for restimulation operations, such as hydraulic fracturing, can enhance mixing and production. The results inform hydrocarbon extraction from deep shale formations, which has recently generated an energy boom that has lowered hydrocarbon costs. However, production decreases rapidly and methods to increase efficiency or allow restimulation of wells are needed. In our experiments, the presence of residual brine from initial production creates spatiotemporal variability in the system that causes the injected scCO2to more effectively interact‐mix with trapped hydrocarbon, thereby increasing recovery. We apply volume‐averaging techniques to upscale brine saturation, which allows us to analyze the complex three‐phase system in the framework of well characterized two‐phase systems. The upscaled three‐phase system behaves like a two‐phase system: greater mixing with larger non‐wetting content and higher heterogeneity. The results are contrary to previous observations in water‐wet systems. Mixing in three‐phase systemsResidual brine enhances mixing between scCO2and hydrocarbons in oil‐wet rocksRestimulation operations in hydraulic fracturing: Alternatives to water

Although hydraulic fracturing has been used for natural gas production for the past couple of decades, there are significant uncertainties about the underlying mechanisms behind the production curves that are seen in the field. A discrete fracture network‐based reservoir‐scale work flow is used to identify the relative effect of flow of gas in fractures and matrix diffusion on the production curve. With realistic three‐dimensional representations of fracture network geometry and aperture variability, simulated production decline curves qualitatively resemble observed production decline curves. The high initial peak of the production curve is controlled by advective fracture flow of free gas within the network and is sensitive to the fracture aperture variability. Matrix diffusion does not significantly affect the production decline curve in the first few years, but contributes to production after approximately 10 years. These results suggest that the initial flushing of gas‐filled background fractures combined with highly heterogeneous flow paths to the production well are sufficient to explain observed initial production decline. These results also suggest that matrix diffusion may support reduced production over longer time frames. Initial fast decline in gas production is due to flushing of gas from fracturesProduction curve is insensitive to local aperture variability within a fractureMatrix diffusion can improve gas production at later times

Field measurements of apparent geochemical weathering reaction rates in subsurface fractured porous media are known to deviate from laboratory measurements by multiple orders of magnitude. To date, there is no geologically based explanation for this discrepancy that can be used to predict reaction rates in field systems. Proposed correction factors are typically based on ad hoc characterizations related to geochemical kinetic models. Through a series of high‐fidelity reactive transport simulations of mineral dissolution within explicit 3D discrete fracture networks, we are able to link the geo‐structural attributes with reactive transport observations. We develop a correction factor to linear transition state theory for the prediction of the apparent dissolution rate based on measurable geological properties. The modified rate law shows excellent agreement with numerical simulations, indicating that geological structure could be a primary reason for the discrepancy between laboratory and field observations of apparent dissolution rates in fractured media. Fractures are the principal conduits for fluid flow through low permeability rock in the Earth's subsurface. In many of these systems, fluids passing through the fractures are out of equilibrium with the resident minerals, and various reactions, such as dissolution and precipitation, occur. These geochemical processes change the fracture permeability and drive fracture propagation, thereby dynamically changing flows. Field measurements of apparent geochemical weathering reaction rates are lower than laboratory measurements by multiple orders of magnitude, which makes predictions of geochemical reaction rates highly uncertain. These slow apparent dissolution rates are particularly pronounced in fracture networks where geo‐structural attributes, for example, the network connectivity and fracture geometry, determine the flow field structure and dictate transport. Through a series of high‐fidelity reactive transport simulations of mineral dissolution in fractured media, we uncovered a new link between the geo‐structural attributes of the underlying fracture network with reactive transport observations. Guided by this information, we develop a correction factor to linear transition state theory to predict the apparent dissolution rate that is based on these geological attributes. The excellent agreement of the proposed model with our numerical simulations indicates that geological structure could be one of the reasons for the commonly observed discrepancy. Observations of apparent reaction rates in fractured media are orders of magnitude lower than those measured in laboratory conditionsReactive transport simulations are used to characterize the influence of 3D fracture network structure on apparent dissolution ratesA geo‐structurally based modification to linear transition state theory for the prediction of the apparent dissolution rate is presented Observations of apparent reaction rates in fractured media are orders of magnitude lower than those measured in laboratory conditions Reactive transport simulations are used to characterize the influence of 3D fracture network structure on apparent dissolution rates A geo‐structurally based modification to linear transition state theory for the prediction of the apparent dissolution rate is presented

Bisphenol A (BPA) and other related chemical compounds may be components used in the manufacturing process of resin-based composite dental restorative material. The purpose of the authors#study was to assess salivary and urinary concentrations of BPA and other compounds before and after placement of resin-based composite dental restorations.

Bisphenol A (BPA) and other related chemical compounds may be components used in the manufacturing process of resin-based composite dental restorative material. The purpose of the authors#study was to assess salivary and urinary concentrations of BPA and other compounds before and after placement of resin-based composite dental restorations.

We incorporate observations of real fracture aperture variability observed in laboratory experiments into an ensemble of three‐dimensional discrete fracture network (DFN) simulations to characterize how variations of this micro‐scale feature can influence flow and transport behavior at the network scale. A shear fracture is created within a Marcellus shale sample, and the fracture aperture is measured using a triaxial direct‐shear device coupled with real‐time X‐ray imaging at in‐situ stress conditions. We construct an ensemble of fracture networks based on natural fractures in Marcellus shale and project regions of the experimental aperture field onto each fracture in the networks. Our calculations demonstrate that the degree of flow channelization, a network‐scale flow field structure, is dramatically increased by local changes in the aperture field that in turn affects flow and transport properties. Fluid flow and solute transport through subsurface fractured media are inherently multi‐scale phenomena. Individual fractures connect to form complicated networks where relevant length scales span multiple orders of magnitude. In this letter, we address a long‐standing question in this research area regarding the relative impact of micro‐scale heterogeneity of fracture roughness, that is, internal aperture variability, on flow and transport at the network macro‐scale. To do so, we developed a methodology to incorporate real apertures obtained from in‐situ observations of dynamically fractured laboratory specimens into three‐dimensional discrete fracture network simulations for the first time. This methodology allows us to characterize how variations in fracture aperture can lead to increased flow channelization at the network scale, a phenomenon that we refer to as scale‐bridging. Our results show that this natural aperture variability not only modifies the local flow field within a single fracture but can re‐structure the global flow field of the entire network. In turn, the distribution of solute transport behavior is drastically modified, the networks' active surface area is drastically decreased, and the degree of flow channelization is markedly increased compared to reference networks that use equivalent smooth fractures. We incorporate X‐ray imaged fracture apertures, obtained at high‐stress in‐situ conditions, into 3D DFN flow and transport simulationsWe observe the effects of incorporating real aperture data for fractures on network‐scale flow and transport properties for the first timeInclusion of aperture variability leads to scale‐bridging, where this small‐scale feature reorganizes the flow field at the network scale We incorporate X‐ray imaged fracture apertures, obtained at high‐stress in‐situ conditions, into 3D DFN flow and transport simulations We observe the effects of incorporating real aperture data for fractures on network‐scale flow and transport properties for the first time Inclusion of aperture variability leads to scale‐bridging, where this small‐scale feature reorganizes the flow field at the network scale

Many studies investigating the relationship between periodontal disease and systemic diseases have been reported; the majority of these have been epidemiologic (or observational) studies. The purpose of this article is to help readers understand the strengths and limitations of epidemiology for the purpose of being better able to interpret these studies.

Healthy People (HP) 2010 is a national health promotion and disease prevention initiative of the U.S. Department of Health and Human Services. The HP 2010 report highlighted a range of racial/ethnic disparities in dental health. A substantial portion of these disparities appear to be explained by differences in access to care. Members of the U.S. military have universal access to care that also has a compulsory component. The authors conducted a study to investigate the extent to which disparities in progress toward achievement of HP 2010 objectives were lower among the military population and to compare the oral health of the military population with that of the civilian population.

Background:Cigarette smoking is a significant risk factor for both chronic obstructive pulmonary disease (COPD) and periodontal disease. The goal of this study was to better understand the role of smoking in a possible relationship between periodontal disease and COPD. Methods:The study population consisted of 7,625 participants in the Third National Health and Nutrition Examination Survey (NHANES III) during 1988‐1994 who were aged 30 years or older when examined and who received a spirometric examination. The data analysis employed logistic regression models and accounted for the complex sampling design used in NHANES III. Results:After adjustment for potential confounders, there was no statistically significant association between periodontal disease and COPD among former or non‐smokers. Current smokers with ≥4 mm mean loss of attachment had an odds ratio of 3.71 (95% confidence interval: 1.74, 7.89). Conclusions:These results suggest that cigarette smoking may be a cofactor in the relationship between periodontal disease and chronic obstructive pulmonary disease. The key role played by smoking in the etiology of both periodontal disease and chronic obstructive pulmonary disease suggests that much of the observed increase in risk may actually reflect the exposure to smoking. Additional research into smoking‐related effect modification is needed to clarify the role of periodontal disease in the etiology of smoking‐related systemic diseases. J Periodontol 2004;75:9‐15.

Background:Cigarette smoking is a significant risk factor for both coronary heart disease and periodontal disease. The goal of this study was to better understand the role of smoking in the relationship between periodontal disease and heart attack history. Methods:The study population consisted of 5,285 participants in the Third National Health and Nutrition Examination Survey (NHANES) during 1988‐1994 and who were age 40 years or older when examined. The data analysis employed logistic regression models and accounted for the complex sampling design used in NHANES. Results:After adjustment for potential confounders, we only found significant associations between periodontal loss of attachment (LOA) and heart attack history for smokers, with odds ratios and 95% confidence interval (CI) of 2.64 (1.48 to 4.71), 3.84 (1.22 to 12.10) and 5.87 (1.91 to 18.00) for those with 2.0 to 2.99, 3.0 to 3.99, and 4 mm or more mean LOA, respectively. When the analysis was stratified by smoking status and tertile of age at heart attack, the statistically significant associations were limited to smokers who had a heart attack between the ages of 25 and 50 years, with odds ratios and 95% CI associated with increasing mean LOA for this group of 3.29 (1.35 to 8.04), 7.32 (1.60 to 33.51), and 8.04 (1.91 to 18.00), respectively. Conclusions:These results suggest that cigarette smoking is a necessary cofactor in the relationship between periodontal disease and coronary heart disease, and the increase in risk appears to be age dependent. However, the key role played by smoking in the etiology of both periodontal and heart diseases makes it difficult to determine how much of the observed association resulted from periodontal disease. J Periodontol 2002;73:988‐994.

Focuses on the accountability of retailers over customer injury due to falling merchandise in the United States. Characteristics of falling-merchandise incidents; Presentation of several court cases of falling merchandise; Application of 'res ipsa loquitor' doctrine; Excuses of merchants.

Reports on the ruling of the Sixth Circuit court that refuses to accord deference to the United States Internal Revenue Service's position denying a 10-year carryback in the consolidated return context in the case involving Intermet Corp. Definition of a specified liability loss; Question of applicability of the doctrine; Broader implications of the ruling.

The purpose of the present studies was to determine whether the diagnostic criteria of the antisocial personality disorder on Axis II of DSM-III-R overdiagnose conduct disorders in normal adults. In the first study 232 college students took a 12-question, self-report, true-false inventory based on the 12 criteria in the B section (evidence of a conduct disorder before the age of 15) of the antisocial personality disorder (APD). Of the males 39% met the criterion (at least 3 of 12 statements answered as true) for a conduct disorder and 10% of the females met criterion. A second study of 363 purportedly normal adults revealed that 5% of the males and 1% of the females met the criterion for an APD, while the early history criteria again appeared to overdiagnose conduct disorders. The results may raise some empirical and theoretical questions about the early history section of the APD.

We study how the interplay between fracture aperture heterogeneity and tracer injection mode controls fluid flow and tracer transport in three‐dimensional (3D) discrete fracture networks (DFNs). The direct 3‐D DFN simulations show that tracer injection mode has substantial effects on tracer spreading across all levels of aperture heterogeneity. The key controlling factor for effective transport is the initial Lagrangian velocity distribution, which is determined by the interplay between injection mode and aperture heterogeneity. The fundamental difference between initial Lagrangian velocity distribution and domain‐scale Eulerian velocity distribution plays a vital role in determining anomalous transport. We effectively capture the observed anomalous transport using an upscaled transport model that incorporates initial velocity distribution, stationary velocity distribution, velocity correlation length, and average advective tortuosity. With the upscaled transport model, we accurately capture the evolution of Lagrangian velocity distribution and predict longitudinal spreading in 3‐D DFN. Tracer injection mode has strong impact on transport in 3‐D DFNs across all levels of aperture heterogeneityInitial Lagrangian velocity distribution determines the late‐time power‐law scaling of a breakthrough curveA Bernoulli CTRW model effectively captures anomalous transport in 3‐D DFNs

Flow channelization is a commonly observed phenomenon in fractured subsurface media where the flow of fluids is restricted primarily to highly transmissive fracture networks surrounded by a low‐permeability rock matrix. The multiscale structural heterogeneity of these networks results in multiscale flow channelization where preferential flow paths form at length scales ranging from the entire system down to the subfracture size. We present an analysis of how one of the largest scales in fractured media, the network density, influences the degree of flow channeling that occurs using an ensemble of semigeneric three‐dimensional discrete fracture network (DFN) simulations. We construct 10 DFNs, whose fracture lengths follow a power law distribution, at four densities for a total of 40 networks. We characterize their structure in terms of the network topology and geometry. Eulerian and Lagrangian observations of the steady‐state flow fields obtained within the networks are used to quantify the degree of flow channelization at the network scale. We introduce a measure for the importance‐ranking/hierarchy of different flow paths in the network using graph‐based analysis of Lagrangian transport by which the degree of flow channeling between networks is compared. These flow observations are then linked to the structural properties of the networks. In general, network‐scale flow channeling decreases as the network density increases. However, at low densities, there is more uniform flow within the entire connected network than in high‐density networks. We also demonstrate how standard transport observables can be used to infer the degree of flow channelization occurring within a fracture network. Flow and transport through an ensemble of networks with varying densities are simulatedNovel measurements of flow channeling degree are introducedAs the network connectivity increases, the degree of network‐scale flow channeling decreases

Multiphase flow is ubiquitous in subsurface energy applications and natural processes, such as oil recovery, CO2sequestration, and water flow in soils. Despite its importance, we still lack a thorough understanding of the coupling of multiphase flow and reaction of transported fluids with the confining media, including rock dissolution and mineral precipitation. Through the use of geomaterial microfluidic flow experiments and high‐performance computer simulations, we identify key pore‐scale mechanisms that control this coupling. We compare the reactivity of fractured limestone with CO2‐saturated brine (single phase) and a mixture of supercritical (sc) CO2and CO2‐saturated brine (multiphase). We find that the presence of scCO2bubbles significantly changes both the flow dynamics and the resulting reaction patterns from a single‐phase system, spatially homogenizing the rock dissolution. In addition, bubbles redirect oversaturated fluid into low‐velocity regions, thereby enhancing carbonate precipitation occurs. The impact of pore‐scale multiphase flow on fluid‐solid reactions is poorly understood because direct observations of reactive multiphase fluids in real rock materials are not widely available and the necessary computing is intractable. Using high‐pressure/temperature geomaterial microfluidic experiments complemented by high‐performance computer direct numerical simulation of multiphase flow in those geometries, we elucidate the pore‐scale mechanisms that lead to homogenization of rock dissolution and enhancement of mineral precipitation. This study contributes to our ability to predict soil weathering and to optimize CO2sequestration and hydrocarbon extraction. Multiphase flow leads to homogenization of rock dissolution and enhancement of mineral precipitationThe identified pore‐scale mechanisms have fundamental implications for soil weathering and subsurface applicationsThe results provide a foundation for engineering design and predictive tools

The topology of natural fracture networks is inherently linked to the structure of the fluid velocity field and transport therein. Here we study the impact of network density on flow and transport behaviors. We stochastically generate fracture networks of varying density and simulate flow and transport with a discrete fracture network model, which fully resolves network topology at the fracture scale. We study conservative solute trajectories with Lagrangian particle tracking and find that as fracture density decreases, solute channelization to large local fractures increases, thereby reducing plume spreading. Furthermore, in sparse networks mean particle travel distance increases and local network features, such as velocity zones where flow is counter to the primary pressure gradient, become increasingly important for transport. As the network density increases, network statistics homogenize and such local features have a reduced impact. We quantify local topological influence on transport behavior with an effective tortuosity parameter, which measures the ratio of total advective distance to linear distance at the fracture scale; large tortuosity values are correlated to slow‐velocity regions. These large tortuosity, slow‐velocity regions delay downstream transport and enhance tailing on particle breakthrough curves. Finally, we predict transport with an upscaled, Bernoulli spatial Markov random walk model and parameterize local topological influences with a novel tortuosity parameter. Bernoulli model predictions improve when sampling from a tortuosity distribution, as opposed to a fixed value as has previously been done, suggesting that local network topological features must be carefully considered in upscaled modeling efforts of fracture network systems. We investigate the impact of fracture density on transport in three‐dimensional fracture networksNegative velocity zones influence network scale transport behaviorA tortuosity dependent Bernoulli CTRW model is used to upscale topological heterogeneity