Search Results (5,399)

Wellbore instability in clay-rich intervals remains a major drilling challenge, even when the selected fluid density satisfies the conventional pressure window. This study evaluates delayed instability during exposure to a low-salinity water-based drilling fluid using outcrop-derived Aleg and El Haria materials as analogs for clay-rich Tunisian drilling intervals. Mineralogical, chemical, geotechnical, and shear strength data were integrated with a coupled stability analysis to link fluid exposure, pore pressure redistribution, effective stress modification, and hydration-induced strength degradation. The two materials exhibited contrasting hydro-mechanical behavior. El Haria is clay-rich, with 80% total clay mineral content, including 41% smectite and 47% illite/smectite mixed layers, and has a swelling pressure of 2112 kPa. Aleg is more carbonate-influenced, with 66% total clay mineral content, 28% calcite, and a lower swelling pressure of 576 kPa. Freshwater hydration strongly reduced the shear strength envelope; between approximately 15% and 45% water content, cohesion decreased by approximately 91% in Aleg and 70% in El Haria. The stability profiles show that El Haria reached r_c/a = 1.10 after 0.3 h and the critical threshold of r_c/a = 1.30 after 21.7 h, whereas Aleg remained close to r_c/a = 1.03. This defines a practical temporal stability window for planning open-hole exposure during logging, casing, and cementing operations. Full article

This study investigates residual stress development in double-lap T-joints fabricated from medium- and heavy-gauge steel plates. A three-dimensional thermo-mechanically coupled finite element model was developed in Abaqus and validated against blind-hole drilling measurements. Four distinct welding sequence schemes were systematically implemented to quantify their influence on the spatial distribution, peak magnitudes, and evolution trajectories of individual residual stress components (σ_x, σ_γ, σ_z). Results demonstrate that the inherent structural rigidity of medium-to-thick plate assemblies strongly constrains global distortion but does not eliminate sensitivity to sequencing at the local stress level. Although equivalent residual stress peaks remain largely insensitive to welding sequence, the distributions of principal stress components exhibit pronounced sequence-dependent heterogeneity. Specifically, single-side continuous unidirectional welding leverages interpass residual heat accumulation to suppress longitudinal tensile stress, achieving a peak value of 449.9 MPa, the lowest among all configurations. In contrast, double-sided alternating reverse welding promotes thermal dispersion across the joint, thereby reducing both transverse tensile stress magnitude and stress concentration in the distal heat-affected zone. Collectively, these findings establish that optimizing welding sequences for double-lap T-joints in medium-to-heavy plates centers not on minimizing global equivalent stress, but on deliberately tailoring the spatial partitioning and balance of individual stress components, a principle that directly informs robust, performance-driven weld path selection in structural fabrication. Full article

To reveal the damage–seepage coupling mechanism of delayed floor water inrush induced by small fault activation under mining-induced stress, a cubic cement mortar specimen containing a persistent small fault was prepared based on similarity theory. Systematic triaxial loading–seepage tests were conducted under different fault fracture zone particle gradations, fracture zone widths, and fault angles, with simultaneous monitoring of stress–strain behavior, acoustic emission (AE) characteristics, and seepage flow evolution. The results show that: ① The peak strength decreases with increasing fracture zone width, but increases with increasing Talbot gradation coefficient (a fractal grading method) and fault angle. The failure mode transitions from shear-dominated to tension–shear composite failure. The spatial localization of AE events corresponds well with macroscopic fracture surfaces, and the AE source amplitude is positively correlated with compressive strength. ② The seepage flow exhibits a nonlinear evolution pattern of “compaction stabilization—stepwise rise—plateau stabilization” during loading. In the early loading stage, compaction of the fracture zone causes a slight decrease in flow. Approaching peak strength, the initiation and propagation of through-going fractures create interconnected seepage channels, leading to a stepwise jump in flow. In the post-peak stage, accompanied by fine particle erosion and framework reconfiguration, the flow tends to stabilize. A larger fracture zone width, smaller gradation coefficient, and smaller fault angle result in a more significant post-peak seepage surge, with the maximum flow rate reaching 3.6 times that of the specimen with a 2 mm wide fracture zone. ③ Grey relational analysis indicates that the fault angle is the most sensitive factor affecting the risk of delayed water inrush (correlation degree 0.788), followed by particle gradation and fracture zone width. The study demonstrates that under monotonic loading conditions, the damage evolution and seepage response of small faults are jointly controlled by their geometric parameters and internal structure, with the fractal grading method effectively quantifying the role of particle gradation. The findings provide a theoretical basis for risk assessment of delayed water inrush from small faults in working faces above confined aquifers. Full article

Surface water-groundwater interaction zones are critical ecohydrological interfaces in arid regions, yet quantitative spatiotemporal patterns and soil-vegetation responses under coupled water-salt-heat gradients remain poorly documented. Based on a one-year monitoring period (August 2024–August 2025) at four sites along a river-to-desert transect (LW3: 25 m, LW2: 200 m, LW1: 300 m, LW4: 400 m from the Niya River) in the hyper-arid Tarim Basin, this study reveals the following quantitative patterns. Groundwater depth increased with distance from the river and followed an annual decrease-increase trend, with an anomalous shallow peak in March 2025 (−20 cm) linked to precipitation recharge. Soil temperature stability increased with depth: the 20 cm layer recorded the widest annual fluctuation (e.g., −1.5 °C to 24 °C at LW1), whereas the 80 cm layer varied only between approximately −0.2 °C and 28 °C. Proximity to the river dampened thermal extremes. Shallow soil moisture was highly dynamic (with a coefficient of variation [CV] reaching 40–50% at LW1 and LW4), while deeper layers remained stable; LW3 near the river stayed saturated year-round (CV = 0). Soil electrical conductivity (EC) decreased with distance from the river: LW3 exhibited the highest surface values (5000–16,000 μS cm⁻¹), whereas LW1 recorded the lowest (1000–2700 μS cm⁻¹). Vegetation performance was governed by coupled water-salt conditions rather than moisture alone: P. australis at LW1 achieved the tallest growth (>200 cm) and highest photosynthetic rates (20.25–37.38 μmol m⁻² s⁻¹), outperforming LW3 (104 cm, winter photosynthesis dropping to 2.01) and LW4 (~100 cm). Correlation analysis further showed strong vertical temperature coupling (r > 0.96 across all depths) and depth-stratified water-salt relationships (e.g., EC-volumetric water content r = 0.95 at 20 cm in LW4), reflecting spatial differentiation driven by freeze-thaw cycles, evaporative enrichment, and homogeneous silt-textured soils (54–96% fine fraction). These quantitative findings provide a detailed observational baseline for riparian ecohydrology in hyper-arid inland rivers and underscore that sustainable vegetation management requires balancing water availability against salinity stress. Full article

Natural fractures can significantly affect fluid seepage behavior and development performance in tight formations. However, the optimal configurations and performance of oriented horizontal wells under various natural fracture scenarios remain insufficiently understood. Numerical simulation models for a fractured horizontal well in a five-spot well pattern were established based on the embedded discrete fracture model (EDFM) to consider the coupled effects of hydraulic fractures and natural fractures. Optimization analyses were performed under different natural fracture conditions, with cumulative oil production used as the main evaluation criterion. The results indicate that natural fractures play a significant role in determining the optimal horizontal well orientation. For reservoirs without natural fractures and those with low- to medium-density single-set natural fractures, the optimal horizontal well orientation is perpendicular to the maximum horizontal stress direction. In contrast, for high-density single-set natural fracture systems, a slight rotation of the horizontal wellbore improves cumulative oil production, with an optimal orientation angle of approximately 15° identified in this work. For conjugate fracture networks, the influence of well orientation becomes more significant, and the optimal orientation angle varies with fracture density, ranging from 15° to 45°. This study indicates that the horizontal wellbore trajectory design may highly rely on the characteristics of natural fractures. Therefore, thorough and accurate characterization of natural fractures should be conducted before optimizing the orientation of fractured horizontal wells. The findings of this work provide theoretical guidance for the placement of fractured horizontal wellbores in naturally fractured tight formations. Full article

Evaluating resource and environmental carrying capacity (RECC) serves as a fundamental approach for assessing regional environmental baselines and is widely applied in territorial spatial planning. Focusing on Daye City—a characteristic resource-exhausted city in Hubei Province—this study developed a comprehensive RECC evaluation system. By integrating the obstacle degree model, hotspot analysis, and Geodetector, we investigated the spatial differentiation mechanisms of RECC and the resulting production–living–ecological (PLE) spatial conflicts, ultimately proposing targeted optimization pathways. The core findings are as follows: (1) The RECC of Daye City exhibits pronounced spatial polarization and a distinct north–south gradient. (2) The spatial stress of industrial/mining land emerges as the primary obstacle (36.47%). Together with geological hazard risk and soil erosion sensitivity, it forms a core constraint chain. The highly significant hotspots of these factors strongly overlap in the north-central mining districts. (3) Geodetector analysis reveals robust bivariate and nonlinear enhancement effects among these core obstacle factors. This indicates that the cascading vicious cycle of mining disturbance, ecological degradation, and declining carrying capacity fundamentally underlies the constrained RECC in mining regions. (4) PLE spatial conflicts across the study area are dominated by production–ecological conflicts (47.73%), presenting a spatial pattern that heavily couples with the polarized obstacle zones. Based on these findings, this study proposes differentiated regulation strategies centered on mitigating mining-induced stress and interrupting the cascading transmission of disaster risks. These strategies aim to restructure and optimize the territorial spatial pattern, providing robust quantitative decision support for the sustainable transformation of similar resource-exhausted cities. Full article

Background/Aims: While pathogenic germline variants play a critical role in pediatric cancer susceptibility, traditional clinical genetics primarily focuses on single-gene interpretations. Transitioning to a systems-level analysis of inherited variation can uncover shared biological vulnerabilities, informing genetic counseling, surveillance, and targeted therapeutics. This study aims to implement an unsupervised machine learning framework to identify and characterize Germline Mutation Signatures (GMS) across diverse pediatric malignancies, elucidating latent genomic patterns that reveal shared oncogenic mechanisms. Methods: We analyzed germline whole-exome and whole-genome sequencing (WES/WGS) data from a retrospective cohort of 420 pediatric cancer patients and matched non-cancer controls. Variants were deeply annotated to capture multi-dimensional features, including predicted pathogenicity, splice-site disruption, regulatory impact, population frequency, and sequence context. To enable robust modeling, we integrated an augmented feature set encompassing evolutionary constraint, loss-of-function intolerance, and compositionally normalized substitution spectra. These high-dimensional annotations were processed using a deep autoencoder for non-linear representation learning, followed by Gaussian Mixture Modeling (GMM) of the latent space. Results: The framework delineated 13 signatures (GMS1–GMS13), yielding an optimal Davies–Bouldin index of 1.051. These signatures map to fundamental biological processes, including DNA repair deficiencies, transcription-coupled damage, replication stress, and aberrant RNA regulation. Crucially, these GMSs transcend traditional tissue-of-origin classifications, manifesting across multiple distinct cancer types. This observation indicates convergent germline etiologies and suggests potential shared susceptibilities to pathway-directed therapies. Conclusions: The discovery of these cross-cancer signatures provides a scalable, biologically interpretable framework for decoding inherited pediatric cancer risk. While the therapeutic mapping networks identified are currently exploratory and serve as a hypothesis-generating foundation, this deep learning-driven paradigm establishes a robust basis for stratified precision medicine. Pending prospective clinical validation, this approach holds significant translational potential to move beyond single-gene paradigms toward unified, systems-level precision oncology strategies. Full article

Fractures are widely developed in deep coal-mine surrounding rocks. They weaken the load-bearing capacity and energy-storage capacity of rock specimens, which may induce surrounding-rock deformation, roof collapse, and other hazards. Current studies on fractured rock masses mainly focus on a single parameter, such as fracture number or fracture dip angle. However, their coupled effects remain unclear. Integrated analyses of mechanical behavior, crack propagation, and energy evolution are also limited. In this study, uniaxial compression simulations of intact sandstone, single-fracture sandstone, and double-fracture sandstone were conducted using PFC^2D. The effects of fracture number and fracture dip angle on mechanical properties and failure characteristics were investigated. The results show that fractures reduced the peak stress and modulus of elasticity. A stronger weakening effect was observed with increasing fracture number. With increasing fracture dip angle, both peak stress and modulus of elasticity showed a V-shaped trend. The minimum peak stress occurred at 15°, while the minimum modulus of elasticity occurred at 45°. Sandstone failure was mainly dominated by tensile cracks. At 15°, the total crack number was the lowest, with 932 and 818 cracks for single-fracture and double-fracture specimens, respectively. Energy analysis showed that increasing fracture number reduced elastic strain energy and promoted dissipated energy. The weakest energy-storage capacity was observed at 30°. Overall, fracture number and fracture dip angle jointly controlled strength degradation, crack propagation, and energy evolution. This study provides a reference for fracture–damage assessment and disaster prevention in deep coal-bearing sandstone. Full article

The thermomechanical deformation behavior of high-entropy alloys (HEAs) is governed by complex interactions among strain, strain rate, and deformation temperature, necessitating robust constitutive models for accurate flow stress prediction and process optimization. In this study, a novel Zerilli–Armstrong (NZA) constitutive model was developed to characterize the hot deformation behavior of FeCoCrNi HEA. The proposed NZA model incorporates enhanced descriptions of strain hardening and deformation-temperature coupling to improve prediction accuracy. The predictability of the proposed NZA model was systematically evaluated and compared with that of the original Zerilli–Armstrong (ZA) and modified Zerilli–Armstrong (MZA) models using key statistical indicators, including the correlation coefficient (R), average absolute relative error (AARE), and root mean square error (RMSE). The findings demonstrate that the NZA model exhibits superior predictive performance, achieving an excellent correlation coefficient (R) of 0.997, a low AARE of 4.22%, and an RMSE of 5.82 MPa. These results confirm the reliability and effectiveness of the proposed constitutive framework in accurately describing the thermomechanical flow behavior of FeCoCrNi HEA over a wide range of deformation conditions. The proposed NZA model provides a robust framework for optimizing hot-forming processes and improving the manufacturing performance of HEA-based components while promoting sustainable manufacturing through reduced material consumption, enhanced energy efficiency, and support for SDGs 9 and 12. Full article

Global container liner shipping networks (GCLSNs) underpin world trade, yet their organization is increasingly reshaped by geopolitical fragmentation. Existing studies often model GCLSNs as single-layer networks, overlooking how carriers’ geopolitical affiliations structure both connectivity and disruption risk. This study constructs a weighted carrier–geopolitical multiplex network in which layers are defined by carriers’ geopolitical affiliations and coupled through shared port calls. Structural analysis reveals pronounced asymmetry in layer size, cohesion, and inter-layer dependence, with overlap concentrated in a limited set of shared hubs. Using the Red Sea crisis as an empirical stress-test scenario, we develop a load–capacity propagation model, incorporating intra-layer load redistribution, rerouting to substitute shared hubs, and inter-layer resource squeeze at same-port layer copies. Results show that direct losses concentrate in corridor-exposed layers, while indirect losses propagate selectively through bridge hubs, especially Singapore, Shanghai, Shenzhen, and Port Klang. Sensitivity analysis indicates nonlinear amplification when low tolerance, strong inter-layer squeeze, and elevated rerouting pressure coincide. These findings show that multiplexity does not imply resilience by itself; cross-layer connectivity buffers disruption only when spare capacity is distributed but amplifies vulnerability when it converges on a narrow set of shared hubs. The paper contributes a carrier–geopolitical perspective to shipping network analysis and a dynamic framework for studying disruption propagation in complex logistics systems. Full article

In modern multistory buildings, integrating beam web openings adjacent to beam–column connections (BCCs) is frequently required to accommodate utility ducts and piping. While this optimizes clear story height, it drastically alters the stress distribution within the BCCs under seismic loading. Consequently, this study evaluates the seismic performance of twenty-one exterior BCCs, with particular emphasis on the coupled effects of opening configuration (size and location) and concrete type: normal strength concrete (NSC, f_c′ = 25 MPa), high-strength concrete (HSC, f_c′ = 80 MPa), and ultra-high-strength concrete (UHPC, f_c′ = 120 MPa). For BCC specimens without openings, upgrading from NSC to HSC and UHPC increased the failure load (P_f) by about 66.67% and 111.11%, and the ultimate capacity (P_u) by 61.54% and 100.0%, respectively. Conversely, web openings reduced the (P_u) of HSC specimens by 14–34%, and UHPC specimens by 12–31%, respectively, when compared to the reference specimens without openings. Furthermore, the presence of web openings compromised cumulative energy dissipation capacity by 16–36% for (NSC), 13–31% for (HSC), and 12–28% for (UHPC), compared with the corresponding reference specimens without openings. Although HSC and UHPC provided superior absolute energy performance, they did not eliminate the structural deficiencies associated with openings positioned adjacent to the joint core. Consequently, a critical threshold value of S/D ≥ 0.5 (where S represents the distance from the column face to the edge of the opening, and D denotes the beam depth), is recommended for HSC and UHPC. In contrast, conventional NSC strictly requires a more conservative limit of S/D ≥ 1.0 to prevent severe cyclic shear degradation near the high-stress region. Full article

Under low-temperature and humid conditions, icing on airfoil surfaces, such as wind turbine blades, deteriorates the aerodynamic performance and decreases the power generation efficiency. To shorten the de-icing time and reduce the de-icing energy consumption, an ultrasonic de-icing method was used by coupling the longitudinal vibration of a piezoelectric transducer and the bending deformation of an iced plate. The simulation method was used to investigate the distributions and the variations of the stresses at the bond interface. An experimental system for ultrasonic de-icing tests was developed and built, and the de-icing experiments were carried out. The experimental results showed that the present ultrasonic de-icing method had a short de-icing time and low de-icing energy consumption, and the de-icing processes agreed with the simulation results. In the present research, the ice layer with a diameter of 20 mm was removed in the shortest de-icing time and the lowest energy consumption because its diameter was close to that of the transducer, which resulted in the highest shear stress at the bond interface. The present study provides theoretical and experimental foundations for deep research on the surface anti- and de-icing method with ultrasonic techniques. Full article

The feasibility of employing the dynamic substructure approach for seismic response analysis of complex structures has been widely recognized. However, the analytical accuracy of this method is affected by several factors, including the element type, the structural configuration, and the analysis method. To address these issues, four types of reticulated shell structures were designed and analyzed using the mode superposition response spectrum method (MSRSM) and the time history analysis method (THAM). The displacements of the key nodes and all member stresses were extracted to compare the simplified finite element models with the original models. The relative errors of nodal displacements calculated by the models with reduced degree of freedom (DOF) were within 1.62%. For the member stresses of the single-layer reticulated shells, the relative errors of the simplified models were within 14.35%. In the simplified models of double-layer reticulated shells, several members exhibited a relative error greater than 30%; however, these members were mainly located near the substructure boundaries and accounted for less than 0.62% of the entire structure. Three strategies are proposed to mitigate the influence of the member stress errors on the structural analysis conclusions for double-layer reticulated shell structures. In addition, the dynamic substructure method was extended to the coupled system of large-span spatial structures and point-supported glass facades. The seismic response results confirmed that this method effectively reduces computational costs while maintaining satisfactory accuracy, indicating that it is a useful tool for simplifying large-span spatial structures in extensive numerical analyses. Full article

Anxiety disorders pose an increasing challenge to the mental health of individuals, particularly in regions with limited healthcare access. This study investigated the potential of integrating a brain–computer interface for processing electroencephalography (EEG) data with deep learning models to accurately classify anxious and non-anxious states. In the first phase, a convolutional neural network (CNN) was developed and validated on the public GAMEEMO dataset, achieving a classification accuracy of 95.72%. In the second phase, we conducted a separate experimental validation with seven participants (aged 18–60 years) using a within-subjects design. The protocol comprised a custom Stroop test to elicit acute cognitive stress and anxiety-related arousal, followed by a guided 4–7–8 breathing exercise to induce relaxation. EEG data from this experiment were used to classify anxious versus non-anxious states with the same CNN architecture after domain adaptation. On this self-collected dataset, the CNN achieved an accuracy of 86.58%. These results demonstrate proof-of-concept transferability while highlighting the performance gap between controlled benchmark data and real-world, small-sample recordings. The deep learning model can subsequently be coupled with neurofeedback techniques to manage anxiety levels. Overall, the findings support the potential of the developed automated system for detecting stress-induced anxious states, with possible future integration into neurofeedback-based management systems. Full article

The design of intravascular ultrasound (IVUS) catheters involves inherently coupled acoustic, hemodynamic, and structural requirements. Existing design strategies, which often rely on empirical geometric refinement or single-physics optimization, are limited in their ability to simultaneously ensure acoustic transmission efficiency, flow compatibility, and mechanical reliability. A multiphysics topology optimization method for the integrated design of IVUS catheters under acoustic–fluid–structure interactions is proposed in this paper. A density-based design variable is introduced to characterize the material distribution within the design domain, and consistent interpolation schemes are employed to relate this variable to the effective acoustic properties in the Helmholtz equation, the Brinkman penalization coefficient in the incompressible Navier–Stokes equations, and the elastic stiffness tensor in the structural equilibrium equation. The optimization problem is formulated as a normalized multi-objective minimization of acoustic transmission loss, flow resistance, and structural compliance, subject to constraints on material volume, received acoustic energy, wall shear stress, and structural displacement. Density filtering and smooth Heaviside projection are incorporated to regularize the design field and promote well-defined material boundaries. An adjoint sensitivity formulation is further developed to enable efficient gradient evaluation for the coupled system. Compared with the initial design, the average acoustic transmission efficiency has increased by $59.01\%$, the shear stress has decreased by $53.87\%$, and the stiffness matching rate has reached $98.27\%$. The objective function converged after 35 iterations, demonstrating the numerical stability of the proposed acoustic–fluid–structure topology optimization framework. Full article