Path Evolution Research Articles

Study on Human Factor Reliability under the Dynamic Evolution of Intelligent Lifting Construction Accidents

This research explores human factors involved in intelligent lifting construction operations risks to prevent errors and manage processes affecting risk evolution. The study employs the human factors analysis and classification system with text mining to identify risk-inducing factors from accident reports. An initial hierarchy is created from the data using the ISM technique, which is further developed into a Bayesian network diagram based on Fuzzy Dynamic Bayesian Networks. Using the approach of the fuzzy set and the developed similarity aggregation method, probabilities before or under the conditions of the network nodes are also estimated. The model’s performance is carefully verified through forward reasoning based on specific indicators, through an analysis which traces the evolution of the various paths through time, and again through sensitivity analysis. They used the FDBN-based human factor reliability risk model; the results show that the constructed risk prediction and control mechanisms help determine the significant evolutionary risk paths, optimising the management strategies for intelligent lifting construction. It presents new findings regarding outcomes of human reliability engineering applied to intelligent construction systems and presents a set of practical recommendations on safety and operations improvement.

Spatio-temporal Evolution of Carbon Emissions and Emission Reduction Paths in the Northern Farming-pastoral Ecotone

The farming-pastoral ecotone has an important strategic place in the energy supply and ecological layout of China. Thus, exploring the spatial and temporal variation characteristics of carbon emissions in this region will help to deeply understand the information on the historical carbon emissions in China's energy production bases and provide data references for the formulation of differentiated emission reduction policies and the promotion of regional energy-saving and carbon-reducing measures, which is of great significance for the realization of low-carbon economic development. This study constructed a spatialization model of carbon emissions based on land use, night lighting, and provincial energy consumption data； explored the spatiotemporal changes and aggregation characteristics of carbon emissions in the farming-pastoral ecotone from 1995 to 2020 using the global Moran's index and hotspot analysis； and then combined it with the slack-based measure model to calculate the carbon emission efficiency and emission reduction potential of each city from 2010 to 2020 and classify cities to propose a differentiated emission reduction path. The results showed that, firstly, the estimated results at the prefectural city level of the carbon emission spatialization model constructed in this study with multi-source data could reach an R2 of 0.92 for a linear fit. Secondly, the total carbon emissions in the farming-pastoral ecotone increased from 176.29 million tons in 1995 to 1 014.51 million tons in 2020. However, the carbon emission intensity and growth rate both decreased, which was related to adjusting the energy structure and improving energy efficiency. Regarding spatial distribution, the cities with high carbon emissions over time were Datong, Baotou, and Yulin in order. Thirdly, the carbon emissions in the study area showed a significant global spatial positive correlation at the county level, with the hot spots mainly located at the junction of Shanxi, Shaanxi, and Inner Mongolia, while the cold spots were extended from Yanan City to Qingyang and Guyuan City after 2010. Finally, based on the differences in carbon emission efficiency and reduction potential, cities could be classified into four types： "high-efficiency and high potential," "low-efficiency and high potential," "high-efficiency and low potential," and "low-efficiency and low potential" to implement targeted emission reduction strategies.

Green technology innovation or pollution substitution? an evolutionary game for high-Energy-consuming enterprises’ strategy from a consideration of energy-consuming trading rights

ABSTRACT The energy-consuming rights trading (ECRT) environmental regulatory policy starting from demand side reform has a significant influence on the enterprises’ production strategies. However, there is still a lack of research on dynamic mechanisms from a micro perspective. Referencing ECRT policy implementation, this paper incorporates government, the public, and high-energy-consuming enterprises into a unified framework, and constructs a tripartite evolutionary game model to explore the enterprises’ production strategy under the reward and punishment accountability mechanism. Then, a case study is addressed to examine the role of government. The results show that: (1) The steady-state conditions of the three parties depend on their own cost–benefit circumstances. Enterprises’ production strategy is driven by the coordination of the government and the public. (2) Achieving ideal equilibrium path evolution requires that the expected benefits of green technology innovation more strongly than the expected benefits of ‘pollution substitution’ practices. (3) A strict accountability system that includes penalties and rewards can enhance public supervision and accelerate the transformation of government active regulatory supervision strategies, stimulating the internal driving forces that motivate enterprises’ green technology innovation. The findings provide references for promoting the implementation of ECRT and helping to achieve the strategy of ecological civilisation construction.

The vortex splitting process from interaction between a mesoscale vortex and two islands

Mesoscale vortices are major carriers of oceanic material and energy transfer, transporting large amounts of high-energy, temperature-anomalous water bodies during their movement. This significantly impacts both the ocean and the atmosphere. Based on the distribution of the North Brazil Curren rings and the Lesser Antilles in the eastern Caribbean Sea, we use the Regional Ocean Model System ocean circulation model to construct an idealized vortex. Simulations are conducted by varying the distances between the two islands and the scales of the islands to analyze how different parameters affect the vortex path and structural evolution. Using theoretical derivation and numerical simulation results, we construct a dimensionless parameter involving vortex diameter, island diameter, and the distance between the islands to determine the conditions under which vortex splitting occurs. The reliability of this dimensionless parameter is verified using experimental data and satellite data from St. Vincent and Barbados from April 6 to May 6, 2000.

Under double shadows: how U.S.–China trade relations and path dependence shape China's IP preliminary injunction system

ABSTRACT The current IP preliminary injunction system in China is an awkward mixture that has developed under two shadows: U.S.–China trade relations, and path dependence. This article traces the historical moments when China amended its rules on IP preliminary injunctions. It finds that, while U.S.–China trade relations facilitated the transplantation of equitable standards into the regime, the basic procedural framework, rooted in the civil law tradition, remains largely intact. These double shadows have introduced pressing problems into the system. However, most of these issues can be attributed to China's retention of its basic procedural framework, which is shared with and originates from the property preservation system. Path dependence theory aptly explains this developmental trajectory and offers normative guidance for future reforms. It may not be feasible to conduct a full cost–benefit analysis on establishing a standalone framework for IP preliminary injunctions in China, which would represent a radical alteration of the system. However, the developmental-evolution model of path dependence theory can still provide valuable insights, even if the system currently exhibits a semi-strong form of path dependence. Chinese legislators could design future incremental reforms with path evolution in mind, aiming for a gradual recombination that ultimately pulls the IP preliminary injunction system out of its original procedural framework. Once sufficient incremental reforms have accumulated, decision-makers can seize critical junctures (such as future escalations in U.S.–China trade conflicts) as opportunities to establish a new, standalone framework for IP preliminary injunctions, thereby breaking the lock-in loop.

Evolution of Unmanned Surface Vehicle Path Planning: A Comprehensive Review of Basic, Responsive, and Advanced Strategic Pathfinders

Unmanned Surface Vehicles (USVs) are rapidly becoming mission-indispensable for a variety of naval operations, from search and rescue to environmental monitoring and surveillance. Path planning lies at the heart of the operational effectiveness of USVs, since it represents the key technology required to enable the vehicle to transit the unpredictable dynamics of the marine environment in an efficient and safe way. The paper develops a critical review of the most recent advances in USV path planning and a novel classification of algorithms according to operational complexity: Basic Pathfinders, Responsive Pathfinders, and Advanced Strategic Pathfinders. Each category can adapt to different requirements, from environmental predictability to the desired degree of human intervention, and from stable and controlled environments to highly dynamic and unpredictable conditions. The review includes current methodologies and points out the state-of-the-art algorithmic approaches in their experimental validations and real-time applications. Particular attention is paid to the description of experimental setups and navigational scenarios showing the realistic impact of these technologies. Moreover, this paper goes through the key, open challenges in the field and hints at the research direction to leverage in order to enhance the robustness and adaptability of path planning algorithms. This paper, by offering a critical analysis of the current state-of-the-art, lays down the foundation of future USV path planning algorithms.

Nation-state influence on tourism path creation in Southern Africa

ABSTRACT This paper explores the role of agency in the emergence and evolution of tourism paths in the post-colonial states of Southern Africa. Building on the Trinity of Change Agency concept, we emphasise the critical role of the nation-state by spotlighting the multi-scalarity of institutional entrepreneurship and the impact of triggering events. These elements are essential for understanding the decisive forms of agency that can redirect tourism economic paths at pivotal moments. This approach is adapted to explain the uneven evolution of tourism paths across the border regions of Chobe, Victoria Falls and Zambezi. Our findings suggest that the interplay between regional actors and a responsive nation-state during periods of change plays a crucial role in shaping the development of tourism paths.

Comprehensive evaluation of “Three Waters” carrying capacity and path evolution study: A case of the Yellow River Basin

Research focusing solely on the carrying capacity of a single aspect of water resources, water environment, or water ecology is no longer sufficient to support the sustainable development and management of basin water systems. The study of basin carrying capacity should expand towards a comprehensive and holistic direction. Therefore, this study constructed an evaluation index system for carrying capacity based on water resources, water environment, and water ecology (“Three Waters”). Utilizing the entropy weight-TOPSIS method, System Comprehensive Index Evaluation, and ArcGIS tools, the comprehensive evaluation index of the “Three Waters” System Carrying Capacity (TWSCC) in the Yellow River Basin (YRB) from 2005 to 2020 was calculated. The evaluation index analyzed the spatiotemporal variation characteristics of subsystem carrying capacity and performed early warning identification and analysis of TWSCC. Four differentiated developmental pathways were designed based on the current status of basin carrying capacity. Leveraging System Dynamics (SD) modeling, the dynamic simulation, and emulation of carrying capacity trends in the YRB from 2020 to 2035 were conducted. The research findings indicate that from 2005 to 2020, the TWSCC levels across the nine provinces in the YRB consistently exhibited varying degrees of overload. The alert levels mostly remained in “Heavy warning” or “Medium warning” states. By 2035, TWSCC under the four development paths improved from 2020 levels, with the Green Environmental Protection-Oriented scheme reaching a safe carrying capacity. In summary, this paper offers theoretical and methodological support for developing basin-carrying capacity and the integrated governance of “Three Waters.”

My money—My problem: How fear‐of‐missing‐out appeals can hinder sustainable investment decisions

AbstractCryptocurrencies (cryptos) have detrimental environmental effects due to their massive energy consumption. While several green crypto coins have been launched, the mainstream—environmentally unfriendly coins—still lead the market. In this study, we explore if influencer marketing, specifically fear‐of‐missing‐out (FOMO) appeals, can contribute to promoting green crypto coin purchases to encourage sustainable investments. The results of five studies (two lab experiments using neurobiological sensors, two online experiments, and a discrete choice experiment) show that social media postings conveying FOMO appeals decrease (increase) green crypto (normal crypto) coin investments. The results further show that message congruence and emotional value perceptions mediate this effect. Finally, we demonstrate that the observed results hold when adding governance and regulatory crypto support as well as the crypto price path evolution to the choice. The results provide notable theoretical contributions and implications for policymakers concerned with fostering more sustainable consumption behavior in the crypto context.

The Lyman-limit photon mean free path at the end of late reionization in the Sherwood–Relics simulations

ABSTRACT Recent evidence supporting reionization ending at redshift $z \lesssim 6$ includes the rapid redshift evolution of the mean free path, $\lambda _{\rm mfp}$, for Lyman-limit photons through the intergalactic medium (IGM) at $5\lt z\lt 6$. Here, we investigate $\lambda _{\rm mfp}$ predicted by the Sherwood–Relics suite of hybrid radiation hydrodynamical simulations. Simulations with comoving volumes of $40^{3}\, h^{-3}\rm \, cMpc^{3}$ ($160^{3}\, h^{-3}\rm \, cMpc^{3}$), calibrated to match the observed Ly $\alpha$ forest transmission with a late end to reionization at $z\lt 6$, are consistent with recent $\lambda _{\rm mfp}$ measurements at $z\lt 5.9$, and are $1.2\sigma$ ($1.8\sigma$) above the highest redshift $\lambda _{\rm mfp}$ measurement at $z=5.93$. The majority of the Lyman-limit opacity at the end of reionization is attributable to highly ionized Ly $\alpha$ forest absorbers with neutral hydrogen column densities $N_{\rm HI} \leq 10^{16}$–$10^{17}\rm \, cm^{-2}$. Resolving these systems is critical for capturing the redshift evolution of $\lambda _{\rm mfp}$ during the final stages of reionization. After reionization completes, overdense gas will reduce $\lambda _{\rm mfp}$ by up to 20 per cent around haloes with masses $M_{\rm h}\sim 10^{9}$–$10^{11}h^{-1}\, {\rm M}_{\odot }$, but during reionization ionized bubbles will instead boost $\lambda _{\rm mfp}$ around haloes by up to an order of magnitude when the IGM is as much as 90 per cent neutral by volume. This effect will play an important role in the visibility of Ly $\alpha$ emitting galaxies at $z\gtrsim 10$ discovered with JWST.

Fluvial channel path evolution – Documenting decades of change along the Little Wabash River, East Central Illinois, USA

Fluvial channel path evolution – Documenting decades of change along the Little Wabash River, East Central Illinois, USA

Visualizing preferential flow paths using dye tracer and species diversity theory methods to explore their correlation to soil properties with random forest algorithm

The preferential flow path development is potentially the result of spatial variations in soil properties with soil depth. However, visualizing the evolution of the preferential flow path with soil depth remains a challenge. This paper presents dye tracer and species diversity theory methods for characterizing preferential flow paths. Field dye tracer experiments were performed at three sites (tree, bush, and grass) in the Yellow River Delta wetland and dye distribution diversity indices (Simpson index (Ds), Shannon-Wiener index (H), Margalef index (Dm), and Pielou index (E)) were applied to verify their availability for preferential flow assessment. The results showed that the uniformity of the shallow-infiltrated dye at the tree site, non-uniformity of the shallow-infiltrated dye at the bush site, and deep dye infiltration at the grass site were the three typical infiltration types. The average proportion of dye-stained areas (PDA) gradually decreased with increasing soil depth. The quantitative effects of soil properties on PDA changes were profound, indicating that soil clay content at 0–10 cm depth, soil sand content at 10–20 cm depth, soil drainage capacity at 20–30 cm depth, and soil bulk density at 30–40 cm depth were the most predictive factors controlling PDA changes. Our results also showed that dye-stained patches with extremely high and high dye concentrations were the most distributed; Ds, H, Dm, and E were the highest at the tree site and E was the diversity index with the greatest importance for PDA change. The findings reveal the soil properties controlling the formation of preferential flow paths, which will improve our understanding of water resource management in the vadose zones of coastal wetlands.

Mastering the complex time-scale interaction during Stress Corrosion Cracking phenomena through an advanced coupling scheme

Stress corrosion cracking (SCC) failure is a multi-physics phenomena and is usually modelled at the microstructural level, which includes mechanical, chemical, and electrochemical contributions. In aggressive corrosive environments, materials prone to localized corrosion, can suffer heavy pitting corrosion. Subsequently, pit-to-crack transition events might be initiated. Respective mechanical assisted pitting corrosion propagation processes are determined by mechanical, chemical, and electrochemical properties as well as transport properties of ions at grain boundaries. Variations in the electrolyte exposure conditions (including the kinetics at the solid–liquid interface), different mechanical loading scenarios, grain-specific crystal anisotropies, and other local factors combine to produce a highly complex SCC-type interaction scenario at various time and length scales. Since corrosion is a slow process whereas brittle fracture is a rapid failure mechanism, the individual domain discretization-based solvers need to use distinct time steps and appropriate solver settings to become capable to accurately simulate such coupled events. In order to address the issues that arise while accounting for scaling effects in both time and space, and retaining coupled mechanistic interplay and including the aspects specified earlier, a sophisticated modelling method is necessary for the analysis of structural failure by SCC. In this work, a partitioned multi-physics computational approach is presented, using two separate single physics solvers coupled by the open-source coupling library preCICE. In the proposed computational setup, two separate software environments are used, with dedicated solver settings and different time steps, to simulate the mechanical fracture and dissolution-driven pitting corrosion for various loading and corrosion conditions, while also taking into account the effects of microstructural anisotropy. For a 2D polycrystalline model representing face-centered-cubic (fcc) material systems, selected numerical experiments are conducted that predict the evolution of fracture and crack path resulting from SCC. The framework has been further extended to simulate 3D problems as well. The corresponding results are evaluated to show the applicability of the proposed methodology.

The effect of overlying rock fracture and stress path evolution in steeply dipping and large mining height stope

To study the fracture instability characteristics and fracture mechanism of overlying strata in steeply dipping and large mining height stope, through the combination of physical simulation experiment, numerical calculation, theoretical analysis and field measurement, the correlation between the evolution of mining stress field and the fracture of overlying strata in large mining height stope under the effect of dip angle is analyzed, and the stress transfer path and the fracture mechanism of overlying strata are revealed. Finally, the influence mechanism of key strata on the evolution of the mining stress field of overlying strata is explained. The research shows that under the influence of gravity dip angle effect and mining height increase, the mining stress is non-equilibrium transferred and evolved in space, and the principal stress field presents the characteristics of partition evolution. The fracture trajectory of rock strata is multi-step and “八” shaped, and the inclined masonry structure and multi-step key strata form a cooperative bearing structure. The key layer of the ladder is the stress transmission structure between the caving zone and the stress arch, and the high stress in the overhanging area under the main roof is transmitted to the advanced roof. With the increase of dip angle, the height of the caving zone decreases, and the fracture range of ladder and principal stress arch decreases. The cracks in the middle and upper broken rock blocks increase, and the instability of the “high ladder rock layer” is easy to induce the simultaneous fracture of the “inclined masonry structure”, resulting in regional unbalanced instability and impact. The research results can provide some reference and guiding significance for the stability control of surrounding rock in longwall stope with steeply dipping.

An enhanced deep learning approach for vascular wall fracture analysis

This work outlines an efficient deep learning approach for analyzing vascular wall fractures using experimental data with openly accessible source codes (https://doi.org/10.25835/weuhha72) for reproduction. Vascular disease remains the primary cause of death globally to this day. Tissue damage in these vascular disorders is closely tied to how the diseases develop, which requires careful study. Therefore, the scientific community has dedicated significant efforts to capture the properties of vessel wall fractures. The symmetry-constrained compact tension (symconCT) test combined with digital image correlation (DIC) enabled the study of tissue fracture in various aorta specimens under different conditions. Main purpose of the experiments was to investigate the displacement and strain field ahead of the crack tip. These experimental data were to support the development and verification of computational models. The FEM model used the DIC information for the material parameters identification. Traditionally, the analysis of fracture processes in biological tissues involves extensive computational and experimental efforts due to the complex nature of tissue behavior under stress. These high costs have posed significant challenges, demanding efficient solutions to accelerate research progress and reduce embedded costs. Deep learning techniques have shown promise in overcoming these challenges by learning to indicate patterns and relationships between the input and label data. In this study, we integrate deep learning methodologies with the attention residual U-Net architecture to predict fracture responses in porcine aorta specimens, enhanced with a Monte Carlo dropout technique. By training the network on a sufficient amount of data, the model learns to capture the features influencing fracture progression. These parameterized datasets consist of pictures describing the evolution of tissue fracture path along with the DIC measurements. The integration of deep learning should not only enhance the predictive accuracy, but also significantly reduce the computational and experimental burden, thereby enabling a more efficient analysis of fracture response.

Damage characteristics of sandstone subjected to freeze–thaw cycles under different stress paths

The damage characteristics and failure modes of rock specimens subjected to different freeze–thaw (FT) cycles are vital to rock engineering in cold regions. Hence, in this study, the physical and mechanical parameters of sandstone specimens under different FT cycles were measured, and their deterioration laws were analyzed. The damage features of the rocks in different FT states under loading along various stress paths, including the main-frequency variation and crack propagation path evolution, were statistically analyzed. Two damage variables, one related to the acoustic emission (AE) and the other related to the rock strength, were combined to reveal the AE characteristics and damage evolution laws in the different damage states. The results showed that FT cycling led to a decrease in the peak stress, an increase in the number of microcracks, an increase in the AE activity, a shift in the main-frequency distribution toward the low-frequency range, and a shift in the damage mode from shear damage to a mixed damage dominated by tensile damage. The degree of strength deterioration in the rock specimens was affected by FT cycling under the different stress paths in the following influence order: conventional uniaxial loading > equal-amplitude cyclic loading> multistage cyclic loading; cyclic loading was more likely to induce tensile rupture than conventional uniaxial loading. The AE characteristic parameters were consistent with the stress–strain curve variations, which could reflect the damage evolution process of the rock specimens. The main frequencies showed a band-like evolution trend with the loading process and could be divided into three bands: a low-frequency interval (0–50 kHz), a medium-frequency interval (50–150 kHz), and a high-frequency interval (150–300 kHz); the main frequencies were concentrated in the low-frequency interval. With the increase in the number of FT cycles, the main frequency in the high-frequency interval and the number of corresponding microcracks gradually decreased.

Expanding Karst Groundwater Tracing Techniques: Incorporating Population Genetic and Isotopic Data to Enhance Flow-Path Characterization

Karst aquifers are unique among groundwater systems because of variable permeability and flow-path organization changes resulting from dissolution processes. Over time, changes in flow-path connectivity complicate interpretations of conduit network evolution in karst hydrogeology. Natural and artificial tracer techniques have long provided critical information for protecting karst aquifers and understanding the potential impacts on ecosystems and human populations. Conventional tracer methods are useful in karst hydrogeologic studies for delineating flow paths and defining recharge, storage, and discharge properties. However, these methods only provide snapshots of the current conditions and do not provide sufficient information to understand the changes in interconnection or larger-scale evolution of flow paths in the aquifer over time. With advances in population genetics, it is possible to assess population connectivity, which may provide greater insights into complex groundwater flow paths. To assess this potential, we combined the more traditional approaches collected in this and associated studies, including artificial (dye) and natural (geochemistry, isotopes, and discharge) tracers, with the population genetic data of a groundwater crustacean to determine whether these data can provide insights into seasonal or longer changes in connections between conduits. The data collected included dye trace, hydrographs, geochemistry, and asellid isopod (Caecidotea bicrenenta) population genetics in Fern Cave, AL, USA, a 25 km-long cave system. Combined, these data show the connections between two separate flow paths during flood events as the downstream populations of isopods belonging to the same subpopulation were measured in both systems. Additionally, the sub-populations found in higher elevations of the cave suggest a highly interconnected unsaturated zone that allows for genetic movement in the vadose zone. Although upstream populations show some similarities in genetics, hydrologic barriers, in the form of large waterfalls, likely separate populations within the same stream.

Phase field model for electric-thermal coupled discharge breakdown of polyimide nanocomposites under high frequency electrical stress

In contrast to conventional transformers, power electronic transformers, as an integral component of new energy power system, are often subjected to high-frequency and transient electrical stresses, leading to heightened concerns regarding insulation failures. Meanwhile, the underlying mechanism behind discharge breakdown failure and nanofiller enhancement under high-frequency electrical stress remains unclear. An electric-thermal coupled discharge breakdown phase field model was constructed to study the evolution of the breakdown path in polyimide nanocomposite insulation subjected to high-frequency stress. The investigation focused on analyzing the effect of various factors, including frequency, temperature, and nanofiller shape, on the breakdown path of Polyimide (PI) composites. Additionally, it elucidated the enhancement mechanism of nano-modified composite insulation at the mesoscopic scale. The results indicated that with increasing frequency and temperature, the discharge breakdown path demonstrates accelerated development, accompanied by a gradual dominance of Joule heat energy. This enhancement is attributed to the dispersed electric field distribution and the hindering effect of the nanosheets. The research findings offer a theoretical foundation and methodological framework to inform the optimal design and performance management of new insulating materials utilized in high-frequency power equipment.

Impact of alteration corridors on karst reservoir organisation and evolution of groundwater flow path: An example from the southern border of the Larzac Causse, southern France

All the features of karstic reservoirs result from the chemical and/or mechanical erosion of an initial rock volume, which modifies the initial petrophysical properties (i.e., porosity and permeability). The spatial distribution and organisation of the karst system in a carbonate massif are often overlooked in studies on karst hydrological functioning. However, these parameters are key to understand and accurately model dynamic flow. This contribution aims at characterising the nature and impact of alteration corridors on the organisation and evolution of the karstic reservoir and its present-day functioning. We focus on characterising the specific impact of the late onset of pocket valley regressive erosion on the organisation of the present-day drainage system. We used a 3D approach to correlate field observations on the surface and in caves, with remote sensing. The expression of alteration corridors is analysed in a 40 km2 area on the southern border of the Larzac Causse. This Jurassic carbonate massif is affected over its entire thickness by a network of vertically elongated alteration corridors containing dissolution-collapse breccia, mainly oriented in a N-S direction. Ghost-rock karstification played a significant part in the karstic reservoir structure and evolution. Alteration corridors result from the in-situ dissolution of the bedrock along an initial jointing pattern. The dissolution-collapse breccia corridors correspond to ghost-rock corridors selectively emptied of their alterite, under the effect of a hydraulic gradient. The vertically elongated structure of alteration corridors that cross-cut the Jurassic sequence enables fluid circulation from an upper to a lower aquifer, which were initially separated by a Toarcian marly seal unit. The subsequent initiation of pocket valleys led to the rapid evacuation of the residual alterite contained in ghost-rock corridors, under the influence of gravity. These alteration corridors determine the position of present-day pocket valley springs and enhance the regressive erosion dynamics, that progressively capture a north-east flowing watershed (Vis River). Finally, residual alterites are evacuated below the overflow spring altitude during high-flow events by flooding/dewatering of galleries. Such mechanisms of alterite evacuation provide insight into i) the part of the karstic reservoir that is connected to the spring, and ii) the dynamics of the associated flows. This study suggests that corridor networks constitute a substantial volume of porous and permeable materials that plays a major role in the present-day groundwater flow path. Such features should be considered valuable drilling targets for water exploration when located below the piezometric level.

Cyclic shear behavior of en-echelon joints under constant normal stiffness conditions

To reveal the mechanism of shear failure of en-echelon joints under cyclic loading, such as during earthquakes, we conducted a series of cyclic shear tests of en-echelon joints under constant normal stiffness (CNS) conditions. We analyzed the evolution of shear stress, normal stress, stress path, dilatancy characteristics, and friction coefficient and revealed the failure mechanisms of en-echelon joints at different angles. The results show that the cyclic shear behavior of the en-echelon joints is closely related to the joint angle, with the shear strength at a positive angle exceeding that at a negative angle during shear cycles. As the number of cycles increases, the shear strength decreases rapidly, and the difference between the varying angles gradually decreases. Dilation occurs in the early shear cycles (1 and 2), while contraction is the main feature in later cycles (3−10). The friction coefficient decreases with the number of cycles and exhibits a more significant sensitivity to joint angles than shear cycles. The joint angle determines the asperities on the rupture surfaces and the block size, and thus determines the subsequent shear failure mode (block crushing and asperity degradation). At positive angles, block size is more greater and asperities on the rupture surface are smaller than at nonpositive angles. Therefore, the cyclic shear behavior is controlled by block crushing at positive angles and asperity degradation at negative angles.