The role of pore fluids in supershear earthquake ruptures.

The intensity and damage potential of earthquakes are linked to the speed at which rupture propagates along sliding crustal faults. Most earthquakes are sub-Rayleigh, with ruptures that are slower than the surface Rayleigh waves. In supershear earthquakes, ruptures are faster than the shear waves, leading to sharp pressure concentrations and larger intensities compared with the more common sub-Rayleigh ones. Despite significant theoretical and experimental advances over the past two decades, the geological and geomechanical controls on rupture speed transitions remain poorly understood. Here we propose that pore fluids play an important role in explaining earthquake rupture speed: the pore pressure may increase sharply at the compressional front during rupture propagation, promoting shear failure ahead of the rupture front and accelerating its propagation into the supershear range. We characterize the transition from sub-Rayleigh to supershear rupture in fluid-saturated rock, and show that the proposed poroelastic weakening mechanism may be a controlling factor for intersonic earthquake ruptures.

Physics-informed attention-based neural network for hyperbolic partial differential equations: application to the Buckley-Leverett problem.

Physics-informed neural networks (PINNs) have enabled significant improvements in modelling physical processes described by partial differential equations (PDEs) and are in principle capable of modeling a large variety of differential equations. PINNs are based on simple architectures, and learn the behavior of complex physical systems by optimizing the network parameters to minimize the residual of the underlying PDE. Current network architectures share some of the limitations of classical numerical discretization schemes when applied to non-linear differential equations in continuum mechanics. A paradigmatic example is the solution of hyperbolic conservation laws that develop highly localized nonlinear shock waves. Learning solutions of PDEs with dominant hyperbolic character is a challenge for current PINN approaches, which rely, like most grid-based numerical schemes, on adding artificial dissipation. Here, we address the fundamental question of which network architectures are best suited to learn the complex behavior of non-linear PDEs. We focus on network architecture rather than on residual regularization. Our new methodology, called physics-informed attention-based neural networks (PIANNs), is a combination of recurrent neural networks and attention mechanisms. The attention mechanism adapts the behavior of the deep neural network to the non-linear features of the solution, and break the current limitations of PINNs. We find that PIANNs effectively capture the shock front in a hyperbolic model problem, and are capable of providing high-quality solutions inside the convex hull of the training set.

Crustal fingering facilitates free-gas methane migration through the hydrate stability zone.

Widespread seafloor methane venting has been reported in many regions of the world oceans in the past decade. Identifying and quantifying where and how much methane is being released into the ocean remains a major challenge and a critical gap in assessing the global carbon budget and predicting future climate [C. Ruppel, J. D. Kessler. Rev. Geophys. 55, 126-168 (2017)]. Methane hydrate ([Formula: see text]) is an ice-like solid that forms from methane-water mixture under elevated-pressure and low-temperature conditions typical of the deep marine settings (>600-m depth), often referred to as the hydrate stability zone (HSZ). Wide-ranging field evidence indicates that methane seepage often coexists with hydrate-bearing sediments within the HSZ, suggesting that hydrate formation may play an important role during the gas-migration process. At a depth that is too shallow for hydrate formation, existing theories suggest that gas migration occurs via capillary invasion and/or initiation and propagation of fractures (Fig. 1). Within the HSZ, however, a theoretical mechanism that addresses the way in which hydrate formation participates in the gas-percolation process is missing. Here, we study, experimentally and computationally, the mechanics of gas percolation under hydrate-forming conditions. We uncover a phenomenon-crustal fingering-and demonstrate how it may control methane-gas migration in ocean sediments within the HSZ.

Hand-Hygiene Mitigation Strategies Against Global Disease Spreading through the Air Transportation Network.

The risk for a global transmission of flu-type viruses is strengthened by the physical contact between humans and accelerated through individual mobility patterns. The Air Transportation System plays a critical role in such transmissions because it is responsible for fast and long-range human travel, while its building components-the airports-are crowded, confined areas with usually poor hygiene. Centers for Disease Control and Prevention (CDC) and World Health Organization (WHO) consider hand hygiene as the most efficient and cost-effective way to limit disease propagation. Results from clinical studies reveal the effect of hand washing on individual transmissibility of infectious diseases. However, its potential as a mitigation strategy against the global risk for a pandemic has not been fully explored. Here, we use epidemiological modeling and data-driven simulations to elucidate the role of individual engagement with hand hygiene inside airports in conjunction with human travel on the global spread of epidemics. We find that, by increasing travelers engagement with hand hygiene at all airports, a potential pandemic can be inhibited by 24% to 69%. In addition, we identify 10 airports at the core of a cost-optimal deployment of the hand-washing mitigation strategy. Increasing hand-washing rate at only those 10 influential locations, the risk of a pandemic could potentially drop by up to 37%. Our results provide evidence for the effectiveness of hand hygiene in airports on the global spread of infections that could shape the way public-health policy is implemented with respect to the overall objective of mitigating potential population health crises.

Comprehensive comparison of pore-scale models for multiphase flow in porous media.

Multiphase flows in porous media are important in many natural and industrial processes. Pore-scale models for multiphase flows have seen rapid development in recent years and are becoming increasingly useful as predictive tools in both academic and industrial applications. However, quantitative comparisons between different pore-scale models, and between these models and experimental data, are lacking. Here, we perform an objective comparison of a variety of state-of-the-art pore-scale models, including lattice Boltzmann, stochastic rotation dynamics, volume-of-fluid, level-set, phase-field, and pore-network models. As the basis for this comparison, we use a dataset from recent microfluidic experiments with precisely controlled pore geometry and wettability conditions, which offers an unprecedented benchmarking opportunity. We compare the results of the 14 participating teams both qualitatively and quantitatively using several standard metrics, such as fractal dimension, finger width, and displacement efficiency. We find that no single method excels across all conditions and that thin films and corner flow present substantial modeling and computational challenges.

Nonequilibrium Thermodynamics of Hydrate Growth on a Gas-Liquid Interface.

We develop a continuum-scale phase-field model to study gas-liquid-hydrate systems far from thermodynamic equilibrium. We design a Gibbs free energy functional for methane-water mixtures that recovers the isobaric temperature-composition phase diagram under thermodynamic equilibrium conditions. The proposed free energy is incorporated into a phase-field model to study the dynamics of hydrate formation on a gas-liquid interface. We elucidate the role of initial aqueous concentration in determining the direction of hydrate growth at the interface, in agreement with experimental observations. Our model also reveals two stages of hydrate growth at an interface-controlled by a crossover in how methane is supplied from the gas and liquid phases-which could explain the persistence of gas conduits in hydrate-bearing sediments and other nonequilibrium phenomena commonly observed in natural methane hydrate systems.

Forced Wetting Transition and Bubble Pinch-Off in a Capillary Tube.

Immiscible fluid-fluid displacement in partial wetting continues to challenge our microscopic and macroscopic descriptions. Here, we study the displacement of a viscous fluid by a less viscous fluid in a circular capillary tube in the partial wetting regime. In contrast with the classic results for complete wetting, we show that the presence of a moving contact line induces a wetting transition at a critical capillary number that is contact angle dependent. At small displacement rates, the fluid-fluid interface deforms slightly from its equilibrium state and moves downstream at a constant velocity, without changing its shape. As the displacement rate increases, however, a wetting transition occurs: the interface becomes unstable and forms a finger that advances along the axis of the tube, leaving the contact line behind, separated from the meniscus by a macroscopic film of the viscous fluid on the tube wall. We describe the dewetting of the entrained film, and show that it universally leads to bubble pinch-off, therefore demonstrating that the hydrodynamics of contact line motion generate bubbles in microfluidic devices, even in the absence of geometric constraints.

Fluid-driven fracture propagation in heterogeneous media: Probability distributions of fracture trajectories.

Hydraulic fracture trajectories in rocks and other materials are highly affected by spatial heterogeneity in their mechanical properties. Understanding the complexity and structure of fluid-driven fractures and their deviation from the predictions of homogenized theories is a practical problem in engineering and geoscience. We conduct a Monte Carlo simulation study to characterize the influence of heterogeneous mechanical properties on the trajectories of hydraulic fractures propagating in elastic media. We generate a large number of random fields of mechanical properties and simulate pressure-driven fracture propagation using a phase-field model. We model the mechanical response of the material as that of an elastic isotropic material with heterogeneous Young modulus and Griffith energy release rate, assuming that fractures propagate in the toughness-dominated regime. Our study shows that the variance and the spatial covariance of the mechanical properties are controlling factors in the tortuousness of the fracture paths. We characterize the deviation of fracture paths from the homogenous case statistically, and conclude that the maximum deviation grows linearly with the distance from the injection point. Additionally, fracture path deviations seem to be normally distributed, suggesting that fracture propagation in the toughness-dominated regime may be described as a random walk.

Thermodynamic coarsening arrested by viscous fingering in partially miscible binary mixtures.

We study the evolution of binary mixtures far from equilibrium, and show that the interplay between phase separation and hydrodynamic instability can arrest the Ostwald ripening process characteristic of nonflowing mixtures. We describe a model binary system in a Hele-Shaw cell using a phase-field approach with explicit dependence of both phase fraction and mass concentration. When the viscosity contrast between phases is large (as is the case for gas and liquid phases), an imposed background flow leads to viscous fingering, phase branching, and pinch off. This dynamic flow disorder limits phase growth and arrests thermodynamic coarsening. As a result, the system reaches a regime of statistical steady state in which the binary mixture is permanently driven away from equilibrium.

Self-organization of network dynamics into local quantized states.

Self-organization and pattern formation in network-organized systems emerges from the collective activation and interaction of many interconnected units. A striking feature of these non-equilibrium structures is that they are often localized and robust: only a small subset of the nodes, or cell assembly, is activated. Understanding the role of cell assemblies as basic functional units in neural networks and socio-technical systems emerges as a fundamental challenge in network theory. A key open question is how these elementary building blocks emerge, and how they operate, linking structure and function in complex networks. Here we show that a network analogue of the Swift-Hohenberg continuum model-a minimal-ingredients model of nodal activation and interaction within a complex network-is able to produce a complex suite of localized patterns. Hence, the spontaneous formation of robust operational cell assemblies in complex networks can be explained as the result of self-organization, even in the absence of synaptic reinforcements.

Thin Films in Partial Wetting: Internal Selection of Contact-Line Dynamics.

When a liquid touches a solid surface, it spreads to minimize the system's energy. The classic thin-film model describes the spreading as an interplay between gravity, capillarity, and viscous forces, but it cannot see an end to this process as it does not account for the nonhydrodynamic liquid-solid interactions. While these interactions are important only close to the contact line, where the liquid, solid, and gas meet, they have macroscopic implications: in the partial-wetting regime, a liquid puddle ultimately stops spreading. We show that by incorporating these intermolecular interactions, the free energy of the system at equilibrium can be cast in a Cahn-Hilliard framework with a height-dependent interfacial tension. Using this free energy, we derive a mesoscopic thin-film model that describes the statics and dynamics of liquid spreading in the partial-wetting regime. The height dependence of the interfacial tension introduces a localized apparent slip in the contact-line region and leads to compactly supported spreading states. In our model, the contact-line dynamics emerge naturally as part of the solution and are therefore nonlocally coupled to the bulk flow. Surprisingly, we find that even in the gravity-dominated regime, the dynamic contact angle follows the Cox-Voinov law.

Regime shifts in bistable water-stressed ecosystems due to amplification of stochastic rainfall patterns.

We develop a framework that casts the point water-vegetation dynamics under stochastic rainfall forcing as a continuous-time random walk (CTRW), which yields an evolution equation for the joint probability density function (PDF) of soil-moisture and biomass. We find regime shifts in the steady-state PDF as a consequence of changes in the rainfall structure, which flips the relative strengths of the system attractors, even for the same mean precipitation. Through an effective potential, we quantify the impact of rainfall variability on ecosystem resilience and conclude that amplified rainfall regimes reduce the resilience of water-stressed ecosystems, even if the mean annual precipitation remains constant.

Pattern formation and coarsening dynamics in three-dimensional convective mixing in porous media.

Geological carbon dioxide (CO2) sequestration entails capturing and injecting CO2 into deep saline aquifers for long-term storage. The injected CO2 partially dissolves in groundwater to form a mixture that is denser than the initial groundwater. The local increase in density triggers a gravitational instability at the boundary layer that further develops into columnar plumes of CO2-rich brine, a process that greatly accelerates solubility trapping of the CO2. Here, we investigate the pattern-formation aspects of convective mixing during geological CO2 sequestration by means of high-resolution three-dimensional simulation. We find that the CO2 concentration field self-organizes as a cellular network structure in the diffusive boundary layer at the top boundary. By studying the statistics of the cellular network, we identify various regimes of finger coarsening over time, the existence of a non-equilibrium stationary state, and a universal scaling of three-dimensional convective mixing.

Synergetic fluid mixing from viscous fingering and alternating injection.

We study mixing of two fluids of different viscosity in a microfluidic channel or porous medium. We show that the synergetic action of alternating injection and viscous fingering leads to a dramatic increase in mixing efficiency at high Péclet numbers. Based on observations from high-resolution simulations, we develop a theoretical model of mixing efficiency that combines a hyperbolic mixing model of the channelized region ahead and a mixing-dissipation model of the pseudosteady region behind. Our macroscopic model quantitatively reproduces the evolution of the average degree of mixing along the flow direction and can be used as a design tool to optimize mixing from viscous fingering in a microfluidic channel.

The price of anarchy in mobility-driven contagion dynamics.

Public policy and individual incentives determine the patterns of human mobility through transportation networks. In the event of a health emergency, the pursuit of maximum social or individual utility may lead to conflicting objectives in the routing strategies of network users. Individuals tend to avoid exposure so as to minimize the risk of contagion, whereas policymakers aim at coordinated behaviour that maximizes the social welfare. Here, we study agent-driven contagion dynamics through transportation networks, coupled to the adoption of either selfish- or policy-driven rerouting strategies. In analogy with the concept of price of anarchy in transportation networks subject to congestion, we show that maximizing individual utility leads to a loss of welfare for the social group, measured here by the total population infected after an epidemic outbreak.

Pattern formation and coarsening dynamics in three-dimensional convective mixing in porous media.

Geological carbon dioxide (CO2) sequestration entails capturing and injecting CO2 into deep saline aquifers for long-term storage. The injected CO2 partially dissolves in groundwater to form a mixture that is denser than the initial groundwater. The local increase in density triggers a gravitational instability at the boundary layer that further develops into columnar plumes of CO2-rich brine, a process that greatly accelerates solubility trapping of the CO2. Here, we investigate the pattern-formation aspects of convective mixing during geological CO2 sequestration by means of high-resolution three-dimensional simulation. We find that the CO2 concentration field self-organizes as a cellular network structure in the diffusive boundary layer at the top boundary. By studying the statistics of the cellular network, we identify various regimes of finger coarsening over time, the existence of a non-equilibrium stationary state, and a universal scaling of three-dimensional convective mixing.

A metric of influential spreading during contagion dynamics through the air transportation network.

The spread of infectious diseases at the global scale is mediated by long-range human travel. Our ability to predict the impact of an outbreak on human health requires understanding the spatiotemporal signature of early-time spreading from a specific location. Here, we show that network topology, geography, traffic structure and individual mobility patterns are all essential for accurate predictions of disease spreading. Specifically, we study contagion dynamics through the air transportation network by means of a stochastic agent-tracking model that accounts for the spatial distribution of airports, detailed air traffic and the correlated nature of mobility patterns and waiting-time distributions of individual agents. From the simulation results and the empirical air-travel data, we formulate a metric of influential spreading--the geographic spreading centrality--which accounts for spatial organization and the hierarchical structure of the network traffic, and provides an accurate measure of the early-time spreading power of individual nodes.

Macroscopic phase-field model of partial wetting: bubbles in a capillary tube.

Drops and bubbles are nonspreading, local, compactly supported features. They are also equilibrium configurations in partial wetting phenomena. Yet, current macroscopic theories of capillary-dominated flow are unable to describe these systems. We propose a framework to model multiphase flow in porous media with nonspreading equilibrium configurations. We illustrate our approach with a one-dimensional model of two-phase flow in a capillary tube. Our model allows for the presence of compactons: nonspreading steady-state solutions in the absence of external forces. We show that local rate dependency is not needed to explain globally rate-dependent displacement patterns, and we interpret dynamic wetting transitions as the route from equilibrium, capillary-dominated configurations, towards viscous-dominated flow. Mathematically, these transitions are possible due to nonclassical shock solutions and the role of bistability and higher-order terms in our model.

Scaling of convective mixing in porous media.

Convective mixing in porous media is triggered by a Rayleigh-Bénard-type hydrodynamic instability as a result of an unstable density stratification of fluids. While convective mixing has been studied extensively, the fundamental behavior of the dissolution flux and its dependence on the system parameters are not yet well understood. Here, we show that the dissolution flux and the rate of fluid mixing are determined by the mean scalar dissipation rate. We use this theoretical result to provide computational evidence that the classical model of convective mixing in porous media exhibits, in the regime of high Rayleigh number, a dissolution flux that is constant and independent of the Rayleigh number. Our findings support the universal character of convective mixing and point to the need for alternative explanations for nonlinear scalings of the dissolution flux with the Rayleigh number, recently observed experimentally.