Fracture shear can induce flow channeling within the fracture plane, enhancing flow perpendicular to the fracture shear direction. The resulting flow anisotropy is crucial for determining optimal well locations at geothermal sites, where efficient heat extraction relies on productive fluid circulation. This research examines the impact of shear on flow anisotropy under variable conditions of normal stress, shear displacement, and fracture size. The research comprises three main stages: (1) simulating fracture shear incorporating asperity degradation, (2) modeling preferential fluid flow within a sheared fracture, and (3) upscaling the laboratory-scale results to the reservoir scale of a hundred-meter. Two fracture surfaces with dimensions of 10 × 10 cm and one fracture surface with a dimension of 1× 1m are used for analysis. A numerical shear model based on elastic-plastic contact mechanics is employed to simulate asperity degradation during shear. Flow simulation on a sheared surface reveal significantly increased permeability anisotropy ratio defined as the ratio of permeability perpendicular to parallel to the shear direction. This permeability anisotropy ratio still prevailed and even increased with higher normal stress, emphasizing the importance of considering flow anisotropy under high-stress conditions. The effect of fracture sizes is investigated using square fractures with side length from 10 cm to 60 cm, extracted from the 1× 1m fracture. While increasing fracture size led to higher permeability and reduced variation in flow anisotropy across the fractures, anisotropy remained evident and significant. To investigate the effect of anisotropy in reservoir scale, a hundred-meter scale reservoir model with an upscaled sheared fracture was constructed. Injection tests showed that higher flow rates were observed when injection and production wells were positioned perpendicular to shear. The results demonstrate that perpendicular flow is enhanced both at the laboratory and reservoir scale, highlighting the importance of considering the influence of fracture shear on flow anisotropy for optimizing well locations.

Thermal stress can trigger slip in rock fractures. Understanding this thermally induced slip behavior of fractures in crystalline rock is crucial for the design and operation of enhanced geothermal systems, and deep geological repository. The present study aims to investigate mechanism and mechanical response of thermal-induced slip in a single fracture. We develop a FEM-based model to simulate the thermally induced slip in fractures with different surface roughness, and under different boundary conditions. The model is validated against a unique set of thermally induced slip test data in laboratory. The results show that thermal stress can cause a decrease in normal stress on the fracture surface, accompanied by an increase in shear stress. The mechanical boundary conditions and fracture roughness can significantly influence the fracture aperture evolution during the slip process. Specifically, results show that increasing the vertical stress can induce a transition from fracture closure to dilation (3.8% closure at z= 1 MPa versus 23.7% aperture increase at z= 50 MPa), while a higher normal stiffness suppresses slip and limits aperture changes. Additionally, rougher fractures exhibit greater closure (the roughest fracture exhibits 3.8% closure vs 1.0% for the smoothest), and neglecting fracture surface plasticity leads to an underestimation of fracture closure in the slip process.

Socio-psychological studies have identified a common phenomenon where an individual's public actions do not necessarily coincide with their private opinions, yet most existing models fail to capture the dynamic interplay between these two aspects. To bridge this gap, we propose a novel agent-based modeling framework that integrates opinion dynamics with a decision-making mechanism. More precisely, our framework generalizes the classical Hegselmann-Krause (HK) model by combining it with a utility maximization problem. Preliminary results from our model demonstrate that the degree of opinion-action divergence within a population can be effectively controlled by adjusting two key parameters that reflect agents' personality traits, while the presence of social network amplifies the divergence. In addition, we study the social diffusion process by introducing a small number of committed agents into the model, and identify three key outcomes: adoption of innovation, rejection of innovation, and the enforcement of unpopular norms, consistent with findings in socio-psychological literature. The strong relevance of the results to real-world phenomena highlights our framework's potential for future applications in understanding and predicting complex social behaviors.

Cement grouting is widely used in rock tunnelling to control groundwater inflow by sealing rock fractures. Accurately predicting grout propagation in rock fractures is crucial for the design, execution, and monitoring of rock grouting in engineering applications. Current methods rely on theoretical models, such as the real-time grouting control (RTGC) method, which is derived based on simplified fracture geometries like smooth parallel plates/disks. However, real rock fractures consist of rough surfaces with variable apertures. In this study, we present a computational model for theoretically predicting the propagation of non-Newtonian cement grout in variable fracture apertures. This model is validated with laboratory test data on grout propagation in a one-dimensional varying aperture long slot (VALS). We also analysed the impact of varying aperture on cement grout propagation processes. Our findings demonstrate that the presented computational model predicts the grout propagation process in this geometry with good accuracy. Moreover, we observed that varying aperture significantly affects the grout propagation process in fractures. The insights provided by our model and analysis results are potentially useful in rock tunnelling projects, specifically for the theoretical analysis of cement grout propagation in rock fractures.

Understanding the shear strength characteristics of rock fractures is crucial for a wide range of rock engineering applications. The strength of rock fractures is significantly dependent on fracture geometry that can be altered during historical shearing process. This study presents a brief analysis of repeated direct shear of a mated fracture. We conducted five repeated shear test simulations under constant normal load conditions using a predictive shear model presented in our previous work. The fracture surface used in the first round of shear simulation is scanned from a natural granite fracture surface. After shearing, the fracture surfaces are repeatedly used for the next rounds of shear simulations. The results generally show that the repeated shear induces irreversible surface degradation, which reduces the shear strength and normal displacement. The findings of this study are helpful for understanding the shear behavior of rock fractures.

The random utility model (RUM) is a fundamental notion in studies of human decision-making. However, RUM relies on the calibration of its choice function's weight parameter, usually interpreted as a rationality parameter, resulting in a case-dependence that undermines both interpretability and predictability of choices across experimental settings. We addressed this limitation by normalizing utilities in RUM and deriving a new choice parameter β, independent of case-specific prospects. Drawing from a novel interpretation of β in terms of the lowest perceived probability of unlikely events, we conducted an experimental survey in Swedish universities to infer β distributions, capturing the variability of probability perception among decision-makers. We tested these statistical models for β on two independent datasets exploring the framing effect. The results showed that the predictions align with the observed experimental data (Pearson's correlation greater than 94%), thereby indicating that the novel characterization of the choice parameter strengthens the predictive capabilities of RUM.

This study investigates the impact of multiscale surface roughness on shear behaviors of crystalline rock fractures. Employing wavelet decomposition, we analyze the multiscale features of 3D fracture surface roughness and characterize each roughness level using statistical parameters. Using a validated shear simulation model, we simulate the direct shear processes of mated fractures with a realistic fracture surface digitalized from the scanning of a granite sample under various normal stresses and decomposed surface roughness levels. The shear behaviors, including the peak and residual shear strengths, shear-induced normal displacement (shear dilation) and surface degradation of the decomposed fractures are analyzed. The results reveal a significant correlation between shear strengths and the multiple levels of surface roughness. For the first time, we demonstrate the crucial role of 3D multiscale surface roughness in determining fracture shear strengths and find that the surface unevenness notably affects the peak shear strength of unfilled and mated fractures, while the surface waviness controls the residual shear strength. The unevenness also can enhance the fracture dilation and surface degradation within a relatively short shear distance (∼1 mm). The findings offer valuable insights for a better understanding and estimation of the shear behaviors of unfilled and mated crystalline rock fractures in engineering practice.

The energy consumption of a building is significantly influenced by occupant behaviour. This paper presents an agent-based model that accounts for social interactions among occupants and quantitatively portrays the evolution process of their energy use patterns due to social norms. Several important factors influencing occupants' total energy consumption have been identified and examined within the model, including individual's energy use intensity (EUI) distribution and the introduction of energy-saving ambassadors into a scale-free social network. Results indicate that up to 40% of energy savings can be achieved through specific strategies, providing valuable insights for promoting sustainable practices among occupants in real world.

Polyurethane grouting is an important technical solution used for seepage prevention and mechanical reinforcement of fractured rock. Various components of polyurethane grout significantly affect the grout properties and propagation behavior. The present study focuses on the crucial role of component parameters in controlling the propagation process and designing grouting parameters for foaming polyurethane grout. A coupled modeling approach combining chemical reactions and flow field analysis is developed to investigate the polyurethane foaming process. The proposed modeling approach is validated by comparing simulation results with experimental data from the literature. The influence of key component parameters: isocyanate index, initial water concentration and physical blowing agent, on the propagation characteristics (including propagation distance, maximum pressure, final density, reaction time and maximum temperature) of foaming polyurethane grout in rock fractures are further analyzed. The results reveal two distinct types of effects caused by the components, i.e., a monotonic relationship and a parabolic trend. Critical values are identified for the impact of isocyanate index on maximum propagation distance, final density and characteristic time, as well as for the influence of physical blowing agent on maximum propagation distance, final density and maximum pressure. Other parameters demonstrated a monotonic relationship. Additionally, a quantitative assessment is conducted to evaluate the impact of multiple components on propagation characteristics. The finding indicates that the initial water concentration has a significant effect on all properties, while isocyanate index exerts a more pronounced impact on reaction time and maximum temperature. The effect of the physical blowing agent is relatively minor compared to other factors. This study is helpful for material selection and proportioning of polyurethane grout in practical engineering applications.

Understanding the influence of shear displacement on heat transport in rock fractures is important for evaluating and optimizing heat extraction in enhanced geothermal systems. This study presents quantitative characterization of the heat transfer evolution in single fractures subject to shear displacement, aiming to demonstrate the impact of shear displacement on heat transport in natural rock fractures. The direct shear of rock fractures is directly simulated using the finite element method and the Mohr-Coulomb yield criterion. The shear simulation method is validated against laboratory shear test data from the literature. Shear simulations under different mechanical conditions, including different normal stresses and shear displacements, are conducted. The sheared fractures are then used to simulate fluid flow and heat transfer processes by directly solving the Navier-Stokes equations and the heat transport equation. The results show that shear displacements can cause significant changes in fracture aperture and subsequently enhance the heterogeneity of flow fields and temperature fields in the fracture. The heat transfer coefficient increases with the increasing of normal stress and Peclet number, while it decreases with the increase of shear displacement. The plastic deformation of fracture surfaces can significantly affect the heat transfer rate. The findings can help understand the heat transfer characteristics in natural rock fractures.