Search Results (156)

Empirical research on the impact of the digital economy on sustainable development is hampered by severe methodological challenges. Discrepancies in the theoretical foundations and construction logic of measurement frameworks have led to diverse and often conflicting conclusions, hindering the systematic accumulation of knowledge. This study aims to address this critical gap by proposing a new, logically consistent measurement framework. To overcome the existing limitations, we construct a functional deconstruction framework grounded in General-Purpose Technology (GPT) theory and a “stock–flow” perspective. This framework deconstructs the digital economy into a neutral “digital infrastructure” (stock platform) and two forces reflecting its inherent duality: a “consumption force” (digital industrialization) and an “empowerment force” (industrial digitalization). Based on this, we develop a measurement system adhering to the principle of “logical purity” and apply a “two-step entropy weighting method with annual standardization” to assess 30 provinces in China from 2012 to 2023. Our analysis reveals a multi-scalar evolution. At the micro level, we identified four distinct provincial development models and three evolutionary paths. At the macro level, we found that the overall inter-provincial disparity followed an inverted U-shaped trajectory, with the core contradiction shifting from an “access gap” to a more profound “application gap.” Furthermore, the primary driver of this disparity has transitioned from being “empowerment-led” to a new phase of a “dual-force rebalancing.” The main contribution of this study is the provision of a new analytical tool that enables a paradigm shift from “aggregate assessment” to “structural diagnosis.” By deconstructing the digital economy, our framework allows for the identification of internal structural imbalances and provides a more robust and nuanced foundation for future causal inference studies and evidence-based policymaking in the field of digital sustainability Full article

This study explores the dynamic behavior of a vertical pipe conveying gas-liquid two-phase flow with rotationally restrained boundaries, employing the generalized integral transform technique (GITT). The rotationally restrained boundary conditions are more realistic for practical engineering applications in comparison to the classical simply-supported and clamped boundary conditions, which can be viewed as limiting scenarios of the rotationally restrained boundary conditions when rotational stiffness approaches zero and infinity, respectively. Utilizing the small-deflection Euler-Bernoulli beam theory, the governing equation of motion for the deflection of the pipe is transformed into an infinite set of coupled ordinary differential equations, which is then numerically solved following truncation at a finite order $NW$. The proposed integral transform solution was initially validated against extant literature results. Numerical findings demonstrate that as the gas volume fraction increases, there is a reduction in both the first-order critical flow velocity and the vibration frequency of the pipe conveying two-phase flow. Conversely, as the rotational stiffness factor enhances, both the first-order critical velocity and vibration frequency increase, resulting in improved stability of the pipe. The impact of the bottom-end rotational stiffness factor $r_2$ on the dynamic stability of the pipe is more pronounced compared to the top-end rotational factor $r_1$. The variation in two-phase flow parameters is closely associated with the damping and stiffness matrices. Modifying the gas volume fraction in the two-phase flow alters the distribution of centrifugal and Coriolis forces within the pipeline system, thereby affecting the pipeline’s natural frequency. The results illustrate that an increase in the gas volume fraction leads to a decrease in both the pipeline’s critical velocity and vibration frequency, culminating in reduced stability. The findings suggest that both the gas volume fraction and boundary rotational stiffness exert a significant influence on the dynamic behavior and stability of the pipe conveying gas-liquid two-phase flow. Full article

Fuel electro-hydraulic servo valves are core components in the fuel control system of aero-engines, and their performance directly affects thrust regulation and power output precision. Due to the combustibility of the working medium in fuel systems and the lack of effective circulation filtration, the retention of micron-sized particles within the valve gap can lead to valve spool jamming, which is a critical reliability issue. This study, based on fractal theory and the liquid–solid two-phase flow model, proposes a parametric model for non-ideal surface valve gaps and analyzes the dynamics of particles subjected to drag, lift, and buoyant forces on rough surfaces. By numerically analyzing flow field models with different roughness levels and comparing them with an ideal smooth gap model, the migration characteristics of particles were studied. To verify the accuracy of the model, an upscaled experimental setup was built based on similarity theory, and PIV experiments were conducted for validation. Experimental results show that the particle release position and valve surface roughness significantly affect particle migration time. The weight of the release position on particle migration time is 63%, while the impact of valve surface roughness is 37%. In models with different roughness levels, the particle migration time increases more rapidly for roughness values greater than Ra0.4, while for values less than Ra0.4, the increase in migration time is slower. Furthermore, the study reveals that particle migration trajectories are independent of flow velocity, with velocity only affecting particle migration time. This research provides theoretical support for enhancing the reliability of fuel electro-hydraulic servo valves and offers a new perspective for the design of highly reliable hydraulic components. Full article

To investigate the impact of sand-laden flow on energy loss in Francis turbines, this study integrates entropy generation theory with numerical simulations conducted using ANSYS CFX. The mixture multiphase flow model and the SST k-ω turbulence model are employed to simulate the solid–liquid two-phase flow throughout the entire flow passage of the turbine at the Gengda Hydropower Station (Minjiang River Basin section, 103°17′ E and 31°06′ N). The energy loss characteristics under different off-design conditions are analyzed on the basis of the average sediment concentration during the flood season (2.9 kg/m³) and a median particle diameter of 0.058 mm. The results indicate that indirect entropy generation and wall entropy generation are the primary contributors to total energy loss, while direct entropy generation accounts for less than 1%. As the guide vane opening increases, the proportion of wall entropy generation initially rises and then decreases, while the total indirect entropy generation exhibits a non-monotonic trend dominated by the flow pattern in the draft tube. Entropy generation on the runner walls increases steadily with larger openings, whereas entropy generation on the draft tube walls first decreases and then increases. The variation in entropy generation on the guide vanes remains relatively small. These findings provide technical support for the optimal design and operation of turbines in sediment-rich rivers. Full article

We consider the macroscopic motion of the normal component of superfluid ³He-A in global thermodynamic equilibrium within the context of the Zubarev statistical operator method. We formulate the corresponding effective theory in the language of the functional integral. The effective Lagrangian comprising macroscopic motion of fermionic excitations is calculated explicitly for the emergent relativistic fermions of the superfluid ³He-A phase immersed in a non-trivial bosonic background due to a space- and time-dependent matrix-valued vierbein featuring nonzero torsion as well as the Nieh–Yan anomaly. We do not consider the dynamics of the superfluid component itself and thereby its backreaction effects due to normal component macroscopic flow. It is treated as an external background within which the emergent relativistic fermions of the normal component move. The matrix-valued vierbein formulation comprises an additional two-dimensional internal spin space for the two axially charged Weyl fermions living at the Fermi points, which may be replaced by one featuring a Dirac fermion doublet with a real-valued vierbein, an axial Abelian gauge field, and a spin connection gauge field mixing the Dirac and internal spin spaces. We carry out this change of description in detail and determine the constraints on the superfluid background as well as the the normal component motion as determined from the Zubarev statistical operator formalism in global thermodynamic equilibrium. As an application of the developed theory, we consider macroscopic rotation around the axis of pure integer mass vortices. The corresponding thermodynamic quantities of the normal component are analyzed. Our formulation incorporates both superfluid background flow and macroscopic motion flow of the normal component and thereby enables an analysis of their interrelation. Full article

In recent years, underground hydrogen storage (UHS) has become a hot topic in the field of deep energy storage. Green hydrogen, produced using surplus electricity during peak production, can be injected and stored in underground reservoirs and extracted during periods of high demand. A profound understanding of the mechanisms of the gas–water two-phase flow at the pore scale is of great significance for evaluating the sealing integrity of UHS reservoirs and optimizing injection, as well as the storage space. The pore structure of rocks, as the storage space and flow channels for fluids, has a significant impact on fluid injection, production, and storage processes. This paper systematically summarizes the methods for characterizing the micro-pore structure of reservoir rocks. The applicability of different techniques was evaluated and compared. A detailed comparative analysis was made of the advantages and disadvantages of various numerical simulation methods in tracking two-phase flow interfaces, along with an assessment of their suitability. Subsequently, the microscopic visualization seepage experimental techniques, including microfluidics, NMR-based, and CT scanning-based methods, were reviewed and discussed in terms of the microscopic dynamic mechanisms of complex fluid transport behaviors. Due to the high resolution, non-contact, and non-destructive, as well as the scalable in situ high-temperature and high-pressure experimental conditions, CT scanning-based visualization technology has received increasing attention. The research presented in this paper can provide theoretical guidance for further understanding the characterization of the micro-pore structure of reservoir rocks and the mechanisms of two-phase flow at the pore scale. Full article

The fluid properties of low-saturation reservoirs (LSRs) produced after fracturing are complex and diverse, which makes it difficult to predict the post-fracturing productivity of oil–water two-phase flow and results in a low prediction accuracy. Therefore, based on elliptical seepage theory and nonlinear steady-state seepage formula, a new method for predicting the post-fracturing productivity (PFP) of oil–water two-phase flow in vertical wells in LSRs after fracturing is proposed in this paper. The Li Kewen model is preferred for accurately calculating oil–water relative permeability. Based on the elliptical fracture morphology, a quantitative prediction model for the PFP of oil–water two-phase flow is established. This model incorporates a starting pressure gradient (SPG) to depict the non-Darcy flow seepage law in low-permeability reservoirs. Hydraulic fracturing fracture length, width and permeability are obtained using logging curves and fracturing data, and this model can be applied to the quantitative prediction of PFP of oil–water two-phase flow in LSRs. The research results show that the conformity rate of oil production is 77.5%, and that of water production is 73.2%, with an improvement of over 15% in the interpretation conformity rate. Compared with actual well test productivity, the mean absolute error of the oil productivity prediction is 3.51 t/d, and the mean absolute error of the water productivity prediction is 12.37 t/d, which meet the requirements of field productivity quantitative evaluation, indicating the effectiveness of this quantitative prediction method for predicting the PFP of oil–water two-phase flow. Full article

The widespread adoption of background music in workplaces contrasts with the inconsistent empirical evidence regarding its cognitive effects, particularly concerning how music types influence the sequential pathway from flow states to work engagement and task performance. While prior research identifies flow and engagement as potential mediators, theoretical conflicts persist regarding their temporal dynamics and susceptibility to auditory habituation. This study tested three hypotheses: (1) music type indirectly affects performance through flow–engagement mediation, (2) high-arousal music impairs while structured compositions (e.g., Mozart’s K448) enhance this pathway, and (3) repeated exposure diminishes music’s efficacy. A two-phase longitudinal experiment with 428 Chinese undergraduates employed structural equation modeling (SEM) to analyze data from randomized groups (control, high-arousal, low-arousal, and Mozart K448), completing Backward Digit Span tasks under controlled auditory conditions. The results confirmed Mozart K448’s superior immediate mediation effect (β = 0.118, 95% CI [0.072, 0.181]) compared to high-arousal music’s detrimental impact (β = −0.112, 95% CI [−0.182, −0.056]), with flow fully mediating engagement’s influence on performance. A longitudinal analysis revealed a 53% attenuation in Mozart’s flow-enhancing effect after a 30-day familiarization (B = 0.150 vs. baseline 0.321), though residual benefits persisted. These findings reconcile the cognitive tuning and arousal–mood hypotheses by proposing a hybrid model where music initially operates through a novelty-driven dopamine release before transitioning to schema-based cognitive priming. Practically, the results advocate tiered auditory strategies: deploying structured music during skill acquisition phases while rotating selections to counter habituation. The study highlights the cultural specificity in auditory processing, challenging universal prescriptions and underscoring the need for localized music policies. By integrating flow theory with neurocognitive habituation models, this research advances evidence-based guidelines for optimizing workplace auditory environments. Full article

There are currently numerous types of water-flooding characteristic curves, most of which are derived from fundamental theories such as material balance, relative permeability, along with experimental results. A single exponential or power function expression cannot accurately characterize the complex flow characteristics of different types of reservoirs, and the equivalent relationships corresponding to production wells and entire oilfields remain unclear. Consequently, practical applications often encounter issues such as curve tailing, difficulty in determining linear segments, inability to identify anomalous points, and inaccuracies in dynamic fitting and prediction. This paper derives a novel water-flooding characteristic curve expression based on fractal theory, incorporating the fractal characteristics of two-phase oil–water flow in reservoirs, as well as the micro-level pore–throat flow features and macro-level dynamic laws of water flooding. The approach is analyzed and validated with real oilfield cases. This study indicates that fitting with the novel water-flooding characteristic curve yields high correlation coefficients and excellent fitting results, demonstrating strong applicability across various types of oilfields and water cut stages. It can more accurately describe the water-flooding characteristics under different reservoir conditions and rapidly predict recoverable reserves, offering significant application value in the dynamic analysis of oilfields and the formulation of development strategies. Full article

This study presents a comprehensive investigation into multi-directional fatigue damage characteristics of fixed offshore wind turbine tower roots through comparative analysis using FAST (3.5.0) and Bladed (4.3) software platforms. The research methodology encompasses three principal phases: First, a stochastic wind field model was developed through statistical analysis of historical wind speed measurements, achieving superior correlation (R² = 0.983) in goodness-of-fit tests. Subsequently, the rain flow counting technique was employed to characterize equivalent cyclic load spectra. Building upon these foundations, an integrated predictive fatigue life evaluation framework was formulated by synergistically combining S–N curve principles with Palmgren–Miner’s linear cumulative damage theory. The methodology was further validated through cross-platform verification with Bladed software, revealing only a 7.4% deviation in predicted fatigue lives between the two computational models, confirming the technical feasibility of the proposed simplified model. Full article

The Indian Ocean Rim (IOR) is a crucial hub for global commerce, possessing key maritime corridors and competitive markets for China and the United States. Assessing the evolving positions of China and the United States in regional trade provides critical insights into their economic competition. This study quantitatively investigated their changing positions in the IOR trade networks from 1992 to 2020 through an interdisciplinary approach combining the Fisher optimal segmentation, chord-diagram visualization, and five weighted centrality indicators, including two advanced metrics derived from physical current flow theory. The results reveal a significant shift in their trade positions in the IOR trade networks across four phases (1992–2002, 2003–2008, 2009–2014, and 2015–2020); in particular, the United States occupied a dominant position in the IOR trade networks until 2008, after which China rose to the central trading position, as reflected in its top ranking across four weighted indicators (excluding weighted authority centrality). In machinery and transport equipment (SITC7), China also surpassed the United States in 2008 and further consolidated its supremacy, driven by its strong manufacturing capabilities and the growing demand from the IOR countries. Meanwhile, the United States experienced a noticeable decline but maintained substantial influence as a key importer. This research develops a quantitative framework that integrates the temporal segmentation with weighted centrality indicators to provide insights into the dynamics and structural changes of trade networks across sectors and regions. Full article

It has been demonstrated that when a low-molecular-weight salt solution flows through a polyelectrolyte gel, an electromotive force is generated, and its polarity depends on the sign of the polyelectrolyte network’s charge. A mathematical model proving the possibility of developing a device for separating a solution of low-molecular salt into enriched and depleted phases under the influence of gravitational forces has been developed. Such a device contains a system of parallel columns filled with different kinds of cross-linked polyelectrolyte networks. The proposed mathematical model is grounded in the theory of double electrical layers forming at the hydrogel/solution interface; these layers deform under non-equilibrium conditions, specifically during the flow of the solution through the cross-linked polyelectrolyte network. An analogous model is proposed describing the case of an analogous device based on an electric current passing through two oppositely charged contacting networks, which provides the possibility of separating the initial solution into enriched and the depleted phases too. The practical applications of the found effect are discussed. In particular, it is demonstrated that a wide number of measurement electronic devices can be created on such a base, including devices to be used within the investigation of polyelectrolyte hydrogels of different types. Full article

Shale gas extraction is hindered by the complex geological conditions of shale reservoirs, such as deep burial, low permeability, and multi-zone characteristics. Therefore, horizontal well hydraulic fracturing is essential for improving reservoir permeability. However, fracture interference and fracturing fluid retention can lead to gas–water co-production. Existing models for predicting the productivity of fractured horizontal wells typically focus on single-phase flow or do not fully account for fracture interactions and dynamic water saturation changes. In contrast, this study introduces a novel fast prediction model for the steady-state productivity of fractured horizontal wells under a gas–water two-phase flow. The model extends single-phase fluid seepage theory by incorporating a gas–water two-phase pseudo-pressure function, while also accounting for fracture interference using potential theory and the superposition principle. Furthermore, it dynamically integrates formation pressure and water saturation variations, offering a more accurate prediction of productivity. The result demonstrates that fracture interference significantly affects the distribution of productivity, with end fractures producing up to 5.6 × 10⁴ m³ while intermediate fractures maintain a relatively uniform production of around 0.9 × 10⁴ m³. The sensitivity analysis reveals that productivity increases with an increase in formation pressure, fracture number, fracture half-length, and fracture angle, while an increcase in water saturation and skin factor reduce it. These results highlight the importance of optimizing fracture design and production strategies. This work provides a more comprehensive and efficient method for predicting and optimizing the gas–water two-phase productivity of fractured horizontal wells. Full article

In recent years, there has been significant interest in the development of self-compacting concrete (SCC). This study views SCC as a two-phase composite material and introduces a new aggregate spacing coefficient model based on the concept of Fullman’s mean free path and stereological theory. The validity of the aggregate spacing coefficient model was verified. The relationship between the fine and coarse aggregate coefficients and the properties of SCC are revealed. The results show that the slump and slump flow of SCC increase as the fine and coarse aggregate coefficients increase. The coarse aggregate spacing coefficient has a significant influence on the compressive strength and drying shrinkage of SCC. A significant linear relationship between the coarse aggregate spacing coefficient and SCC dry shrinkage properties is revealed. Compared to the conditional mixing proportion method, which considers the aggregate volume as a control factor, the aggregate spacing coefficient takes into account the aggregate volume and gradation, which can more accurately reflect the characteristics of the aggregate. Meanwhile, this new perspective on the macroscopic composition of SCC provides insights into the controlling factors of its performance. Full article

The numerical solution of flow and temperature fields in and around a hot metal component being immersed into a cooling fluid offers powerful insights into investigating industrial quenching processes. The calculation requires a simultaneous solution of the Navier Stokes and the according energy equation. Difficulties arise at the boundaries where high heat transfer rates are forced from the solid surface to the fluid due to high metal temperatures. Heat transfer rates are determined based on the similarity theory, but reliable heat transfer equations valid for the high temperature typical of quenching processes are rare. This paper presents a two-fluid VOF (volume-of-fluid method) approach, giving an insight into the transient heat transfer and its oscillations. Unlike our previous publications, this paper uses the lumped heat conduction model to obtain the heat transfer coefficient in the film boiling heat transfer mode. Its application leads to an estimation of an average heat transfer coefficient. Furthermore, the unsteady distribution of the heat transfer coefficient values, shown in our previous paper, is now supplemented with the corresponding flow behavior obtained using the numerical simulation. In our approach, the vapor bubble formation during the film boiling phase is tracked directly (DNS of interface motion, not turbulence), and the unsteady heat transfer coefficient distribution is obeyed. Full article