Search Results (3,311)

Buried pipelines in permafrost areas are affected by harsh environments, especially those with defects and damages, which are prone to failure or even leakage accidents. However, current research is limited to single-factor analysis and fails to comprehensively consider the interaction relationships among temperature fields, moisture fields, and stress fields. Therefore, based on the thermodynamic equilibrium equation and the ice–water phase transition theory, this paper constructs the temperature field equation including the latent heat of phase transition, the water field equation considering the migration of unfrozen water, and the elastoplastic stress field equation. A numerical model of the heat–water–force three-field coupling is established to systematically study the influence laws of key parameters such as burial depth, water content, pipe diameter, and wall thickness on the strain distribution of pipelines with defects. The numerical simulation results show that the moisture content has the most significant influence on the stress of pipelines. Pipelines with defects are more prone to damage under the action of freeze–thaw cycles. Based on data analysis, the safety criteria for pipelines were designed, the strain response surface function of pipelines was constructed, and the simulation was verified through experiments. It was concluded that the response surface function has good predictability, with a prediction accuracy of over 90%. Full article

To overcome the production bottleneck induced by the high viscosity of extra-heavy oil and resolve the issues of limited efficiency in traditional thermal oil recovery methods (including cyclic steam stimulation (CSS), steam flooding, and steam-assisted gravity drainage (SAGD)) as well as the fragmentation of existing viscosity reducer evaluation systems, this study establishes a multi-dimensional evaluation system for the effectiveness of viscosity reducers, with stage-averaged remaining oil saturation as the core benchmarks. A “1D static → 2D dynamic → 3D synergistic” progressive sequential experimental design was adopted. In the 1D static experiments, multi-gradient concentration tests were conducted to analyze the variation law of the viscosity reduction rate of viscosity reducers, thereby screening out the optimal adapted concentration for subsequent experiments. For the 2D dynamic experiments, sand-packed tubes were used as the experimental carrier to compare the oil recovery efficiencies of ultimate steam flooding, viscosity reducer flooding with different concentrations, and the composite process of “steam flooding → viscosity reducer flooding → secondary steam flooding”, which clarified the functional value of viscosity reducers in dynamic displacement. In the 3D synergistic experiments, slab cores were employed to simulate the SAGD development process after multiple rounds of cyclic steam stimulation, aiming to explore the regulatory effect of viscosity reducers on residual oil distribution and oil recovery factor. This novel evaluation system clearly elaborates the synergistic mechanism of viscosity reducers, i.e., “chemical empowerment (emulsification and viscosity reduction, wettability alteration) + thermal amplification (steam carrying and displacement, steam chamber expansion)”. It fills the gap in the existing evaluation chain, which previously lacked a connection from static performance to dynamic displacement and further to multi-process synergistic adaptation. Moreover, it provides quantifiable and implementable evaluation criteria for steam–chemical composite flooding of extra-heavy oil, effectively releasing the efficiency-enhancing potential of viscosity reducers. This study holds critical supporting significance for promoting the efficient and economical development of extra-heavy oil resources. Full article

Benford’s law states that in many real-world datasets, the probability that the leading digit is d equals ${log}_{10}((d+1)/d)$ for all $1\le d\le 9$. We call this weak Benford behavior. A dataset is said to follow strong Benford behavior if the probability that its significand (i.e., the significant digits in scientific notation) is at most s equals ${log}_{10}\left(s\right)$ for all $s\in [1,10)$. We investigate Benford behavior in a multi-proportion stick fragmentation model, where a stick is split into m substicks according to fixed proportions at each stage. This generalizes previous work on the single proportion stick fragmentation model, where each stick is split into two substicks using one fixed proportion. We provide a necessary and sufficient condition under which the lengths of the stick fragments converge to strong Benford behavior in the multi-proportion model. Full article

Proppant crushing seriously affects the efficiency and effectiveness of oil and gas production. In conventional studies, multi-particle crushing research often adopts the particle replacement method; however, this method results in a relatively rough and discontinuous crushing simulation process, making energy conservation difficult to maintain before and after crushing, neglects complex mechanical behaviors such as internal stress distribution and crack propagation of particles, and thus lacks mechanical authenticity. Thus, this study employs the bonded crushing method and establishes a calibration method for mesoscopic parameters. By constructing a particle flow numerical model, the force and crushing processes of proppants under different mesoscopic parameter conditions for both single-particle clusters and multi-particle clusters are simulated, enabling comprehensive monitoring of internal crack propagation within particle clusters. The study systematically analyzes and investigates the influence of key mesoscopic parameters including the tensile strength of parallel bonds (pb-ten), cohesion of parallel bonds (pb-coh), effective modulus (emod), and stiffness ratio (kratio) on the maximum force required for particle crushing. Additionally, orthogonal experiment analysis is used to study the influence of different mesoscopic parameters on the proppant crushing rate. The results show that the larger the pb-ten and pb-coh, the less likely the proppant particle clusters are to crush; conversely, the higher the emod, the more likely the particle clusters are to crush. Within a certain range, pb-ten has the most significant impact on the proppant crushing rate, followed by pb-coh and emod, while kratio has a smaller impact. Based on the research results regarding the influence of laws of different mesoscopic parameters on proppant crushing performance, the mesoscopic parameters of the proppant were calibrated using the post-experiment proppant crushing rate as the fitting index. The simulation results were then compared with the experimental results, verifying the accuracy of the model. The findings of this study clarify the influence of laws of mesoscopic parameters on proppant crushing performance, providing a basis for the subsequent calibration of mesoscopic parameters for numerical proppants and helping to accurately characterize the macroscopic crushing performance of numerical proppants. Full article

Exploring homogeneous dense groups is one of the important issues in social network structure measurement. k-core decomposition and core member filtering are common methods to uncover homogeneous dense groups in a network. However, existing methods of k-core decomposition struggle to support in-depth exploration of homogeneous dense groups. To address this issue, we store social networks in a graph database, taking advantage of its characteristics such as property indexes and batch queries. Based on this storage, we propose a k-core decomposition algorithm to improve the efficiency of homogeneous dense group detection. Subsequently, we introduce a core member filtering algorithm for identifying core members, a key exploration goal of this study. In experiments, we verify the efficiency of the k-core decomposition algorithm. Finally, we conduct an in-depth analysis of the characteristics of k-cores and their core members, yielding several important conclusions. For example, the relationship between the core number and the number of nodes obeys the power law distribution. In addition, we find that despite the strong connection of the core members, they do not play an important role in the information spreading of social networks. Full article

Gluons within the proton may accumulate near a critical momentum due to nonlinear QCD effects, leading to a gluon condensation. Surprisingly, the pion distribution predicted by this gluon distribution could answer two puzzles in astronomy and high-energy physics. During ultra-high-energy cosmic ray collisions, gluon condensation may abruptly produce a large number of low-momentum pions, whose electromagnetic decays have the typical broken power law. On the other hand, the Large Hadron Collider (LHC) shows weak but recognizable signs of gluon condensation, which had been mistaken for BEC pions. Symmetry is one of the fundamental laws in natural phenomena. Conservation of energy stems from time symmetry, which is one of the most central principles in nature. In this study, we reveal that the connection between the above two apparently unrelated phenomena can be fundamentally explained from the fundamental principle of conservation of energy, highlighting the deep connection and unifying role symmetry plays in physical processes. Full article

Modern energy systems are undergoing a profound transformation characterized by the active replacement of conventional fossil-fuel-based power plants with renewable energy sources. This transition aims to reduce the carbon emissions associated with electricity generation while enhancing the economic performance of electric power market players. However, alongside these benefits come several challenges, including reduced overall inertia within energy systems, heightened stochastic variability in grid operation regimes, and stricter demands on the rapid response capabilities and adaptability of emergency controls. This paper presents a novel methodology for selecting effective control laws for low-inertia energy systems, ensuring their dynamic stability during post-emergency operational conditions. The proposed approach integrates advanced techniques, including feature selection via decision tree algorithms, classification using Random Forest models, and result visualization through the Mean Shift clustering method applied to a two-dimensional representation derived from the t-distributed Stochastic Neighbor Embedding technique. A modified version of the IEEE39 benchmark model served as the testbed for numerical experiments, achieving a classification accuracy of 98.3%, accompanied by a control law synthesis delay of just 0.047 milliseconds. In conclusion, this work summarizes the key findings and outlines potential enhancements to refine the presented methodology further. Full article

High-pressure, high-volume fracturing in unconventional reservoirs often induces perforation erosion damage, endangering operational safety. This paper employs fluid–solid coupling theory to analyze the flow characteristics of fracturing fluid inside the casing during fracturing. Combined with strength theory, the stress distribution and variation law are investigated, revealing the mechanical mechanism of casing perforation erosion damage. The results indicate that the structural discontinuity at the entrance of the perforation tunnel causes an increase in fracturing-fluid velocity, and this is where the most severe erosion happens. The stress around the perforation is symmetrically distributed along the perforation axis. The casing inner wall experiences a combined tensile–compressive stress state, while non-perforated regions are under pure tensile stress, with the maximum amplitudes occurring in the 90° and 270° directions. Although the tensile and compressive stress do not exceed the material’s allowable stress, the shear stress exceeds the allowable shear stress, indicating that shear stress failure is likely to initiate at the perforation, inducing erosion. Moreover, under the impact of fracturing fluid, the contact forces at the first and second interfaces of the casing are unevenly distributed, reducing cement bonding capability and compromising casing integrity. The findings provide a theoretical basis for optimizing casing selection. Full article

Growing global supply chain uncertainties significantly threaten China’s forage import security. The evolving characteristics of the global forage trade network directly impact the stability of China’s supply. This study constructs a directed, weighted trade network based on global forage products trade data (2000–2024). Using complex network analysis methods, it systematically analyzes the network’s topological structure and evolutionary patterns, with a focus on their impact on China’s import security. The study addresses the following questions: What evolutionary patterns does the global forage trade network exhibit in terms of its topological structure? How does the evolution of this network impact the import security of forage products in China, specifically regarding supply chain stability and risk resilience? The research findings indicate the following: (1) From 2000 to 2024, the total volume of global forage products trade increased by 48.17%, primarily driven by forage products excluding alfalfa meal and pellets, which accounted for an average of 82.04% of volume annually. Additionally, the number of participating countries grew by 21.95%. (2) The global forage products trade network follows a power–law distribution, characterized by increasing network density, a clustering coefficient that initially declines and then rises, and a shortening of the average path length. (3) The core structure of the global forage products trade network shows an evolutionary trend of diffusion from core nodes in North America, Oceania, and Asia to multiple core nodes, including those in North America, Oceania, Europe, Africa, and Asia. (4) China’s forage products trade network displays distinct phase characteristics; however, imports face significant risks from high supply chain dependency and exposure to international price fluctuations. Based on these conclusions, it is recommended that China actively expands trade relations with potential product-exporting countries in Africa, encouraging enterprises to “go global.” Additionally, China should establish a three-dimensional supply chain security system, comprising maritime, land, and storage components, to enhance risk resistance and import safety. Full article

Objectives: To systematically review and analyze electronic systems in competitive motorcycles (2020–2025), examining their technical specifications, performance impacts, and technological evolution across MotoGP, World Superbike (WSBK), MotoE, British Superbike (BSB), and Spanish Championship (ESBK) categories. Eligibility criteria: Included studies reporting technical specifications or performance data of electronic systems in professional motorcycle racing, published between January 2020 and December 2025 in English, Spanish, Italian, or Japanese. Excluded: opinion pieces, amateur racing, and studies without quantitative data. Information sources: IEEE Xplore, SAE Technical Papers, Web of Science, Scopus, and specialized motorsport databases were searched through 15 December 2025. Risk of bias: Modified Cochrane Risk of Bias tool for experimental studies and Newcastle-Ottawa Scale for observational studies. Synthesis of results: Synthesis of results: Random-effects meta-analysis using DerSimonian-Laird method for homogeneous outcomes; narrative synthesis for heterogeneous data. Included studies: 87 studies met inclusion criteria (52 experimental, 38 simulation, 23 technical descriptions, 14 comparative analyses). Electronic systems were categorized into six domains: Engine Control Units (ECU, 28 studies, 22%), Vehicle Dynamics (23 studies, 18%), Traction Control (19 studies, 15%), Data Acquisition (21 studies, 17%), Braking Systems (18 studies, 14%), and Emerging Technologies (18 studies, 14%). Note that studies could address multiple domains. Limitations of evidence: Proprietary restrictions limited access to 31% of technical details; 43% lacked cross-category comparisons. Interpretation: Electronic systems are primary performance differentiators, with computational power following Moore’s Law. Future developments point toward distributed architectures and 5G telemetry. Full article

Inclusive education is a central pillar of contemporary educational policy worldwide, aiming to ensure equity, participation, and success for all learners. Understanding how inclusive policies are implemented in everyday school contexts is essential to identify both enabling factors and persistent barriers. In Portugal, this process has been shaped by a progressive legislative framework, notably Decree-Law 54/2018 and its regional adaptation in the Autonomous Region of Madeira (RAM) through Regional Legislative Decree 11/2020/M. This case study combined qualitative documentary analysis with a questionnaire applied to coordinators of the Multidisciplinary Teams to Support Inclusive Education (EMAEI) from 11 of the 14 secondary schools in the RAM (79% of the total). The questionnaire covered five domains: inclusive principles, leadership, professional development, resources, and diagnosis of learning barriers. Descriptive statistics and content analysis were used to interpret the data. Results show that coordinators share a strong ethical commitment to inclusion and recognize EMAEI as a strategic organizational structure. However, they point to irregular and insufficient training, delays and mismatches in resource allocation, and limited institutionalization of co-teaching and joint planning. Leadership emerges as a decisive enabler of collaborative cultures. The study concludes that ambitious legislation must be complemented by agile resource management, sustained context-based training, and distributed leadership for inclusive schooling to become everyday practice. Full article

The accuracy of numerical model outputs strongly depends on the quality of the initial wind field, yet ground observation data are typically sparse and provide incomplete spatial coverage. More importantly, many current mainstream correction models rely on reanalysis grid datasets like ERA5 as the true value, which relies on interpolation calculation, which directly affects the accuracy of the correction results. To address these issues, we propose a new deep learning model, PPWNet. The model directly uses sparse and discretely distributed observation data as the true value, which integrates observation point positions and a physical consistency term to achieve a high-precision corrected wind field. The model design is inspired by biological intelligence. First, observation point positions are encoded as input and observation values are included in the loss function. Second, a parallel dual-branch DenseInception network is employed to extract multi-scale grid features, simulating the hierarchical processing of the biological visual system. Meanwhile, PPWNet references the PointNet architecture and introduces an attention mechanism to efficiently extract features from sparse and irregular observation positions. This mechanism reflects the selective focus of cognitive functions. Furthermore, this paper incorporates physical knowledge into the model optimization process by adding a learned physical consistency term to the loss function, ensuring that the corrected results not only approximate the observations but also adhere to physical laws. Finally, hyperparameters are automatically tuned using the Bayesian TPE algorithm. Experiments demonstrate that PPWNet outperforms both traditional and existing deep learning methods. It reduces the MAE by 38.65% and the RMSE by 28.93%. The corrected wind field shows better agreement with observations in both wind speed and direction, confirming the effectiveness of incorporating position information and a physics-informed approach into deep learning-based wind field correction. Full article

To optimize the location optimization of the coalbed methane (CBM) extraction target area in abandoned mines, based on the background of the Songzao mining area in Chongqing, theoretical analysis and numerical simulation research methods were comprehensively used to systematically evaluate the potential of residual CBM resources in the goaf of the Songzao mining area. The stress-fracture evolution law and permeability enhancement characteristics of overlying strata under repeated mining of inclined multi-coal seams were deeply revealed, and the location optimization of the residual CBM extraction borehole target area was carried out. The results show that the amount of CBM resources in Songzao Coal Mine is 5.248 × 10⁷ m³, accounting for 26.57% of the total resources, which is suitable for the extraction of CBM left in goaf. The maximum height of the overburden fracture zone caused by repeated mining of K2b, K1, and K3b coal seams in Songzao Coal Mine is 72.3 m, which is basically consistent with the results of the numerical simulation (69.76 m). The fracture development of overlying strata is in the distribution form of a symmetrical trapezoid and inclined asymmetrical trapezoid, and its development height increases with an increase in coal seam mining times, and finally forms a three-dimensional ‘O’-ring fracture area, which provides a channel and enrichment area for the effective migration of CBM. The significant permeability-increasing zone of overburden rock is stable in the range of 10~40 m above the roof of the K3b coal seam and is nearly trapezoidal. According to the calculation of the height prediction model of the fracture zone in the abandoned goaf, the fracture height of the long-term compaction of the Songzao Coal Mine is reduced to 63.74 m. Based on the stress-fracture evolution characteristics of the overburden rock, combined with the permeability-increasing characteristics of the overburden rock and the migration law of the remaining CBM, it is determined that the preferred position of the remaining CBM extraction target area of the Songzao Coal Mine should be in the upper corner of the fracture development area within the range of 10~32.47 m above the K36 coal seam. Full article

Basalt fiber reinforced polymer (BFRP) is one of the new materials that can be used for making photovoltaic scaffolds, which can effectively solve the problem of the rapid deterioration of complex environmental performance and high maintenance cost of traditional scaffold materials. This paper focuses on the BFRP photovoltaic support in the cold and arid irrigation area of northwest China, carries out the durability test under the action of chloride salt, freeze-thaw cycle, and chloride salt freeze-thaw environment coupling, and it compares and analyzes the degradation law of the mechanical properties of BFRP sheets under different environmental effects. The performance degradation mechanism of BFRP materials under different environmental effects was revealed by SEM scanning electron microscopy and EDS energy spectrum analysis. The main conclusions are as follows: (1) Under the action of chloride salt, the tensile strength, elastic modulus and elongation at break of the specimen decreased by 11.46%, 7.02%, and 10.27%, respectively. Under the freeze-thaw cycle, the tensile strength and elongation at break of the specimen decreased by 9.62% and 6.85%, while the elastic modulus first increased and then decreased, with a maximum decrease of 12.95%. The degradation of mechanical properties is the most serious under the coupling effect of chloride salt and the freeze-thaw environment. The tensile strength, elastic modulus, and elongation at break of the specimens decreased by 25.73%, 9.55%, and 24.81%, respectively. (2) In the chloride environment, the distribution of elements on the surface of the specimen changed, the metal ions of the fibers precipitated, and ‘black spots‘ and corrosion pits appeared. The resin matrix forms ‘sponge-like‘ pores; under the freeze-thaw cycle, the fiber–resin interface cracks and fiber shedding intensifies; under the coupling effect of chloride freeze-thaw, ‘black spots‘, pits, resin holes, and interface cracks increased, and chloride penetration corrosion accelerated. Full article

To quantitatively analyze the macroscopic diffusion process of chloride ions in existing concrete members, the Peridynamic Differential Operator (PDDO) was introduced to formulate a discrete format for Fick’s second law, and a simulation model was established and validated. Subsequently, the influence of specific or randomly distributed defects in the concrete is reflected by adjusting the coefficients in the model’s global matrix. Moreover, the complex geometry of concrete members is captured by employing a point set-based spatial discretization approach. The model also accommodates for the complex corrosion conditions encountered in practice by imposing different boundary conditions. These features allowed for the simulation and validation of chloride ion diffusion experiments on concrete under natural environmental conditions. The study further analyzed how factors such as defects, diffusion coefficients, boundary conditions, and the geometric shape of members influence the macroscopic diffusion process. The findings indicate that the numerical model based on the PDDO can effectively quantify the macroscopic diffusion of chloride ions in existing concrete members. It provides fundamental data for the durability maintenance of concrete infrastructures and potentially reduces their carbon footprint by preventing unnecessary rehabilitation or reconstruction. Full article