Search Results (6,809)

Under China’s “dual-carbon” strategic goals and the advancement of smart city development, the rapid adoption of electric vehicles (EVs) has deepened the spatiotemporal coupling between transportation networks and distribution grids, posing new challenges for integrated energy systems. To address this, we propose a collaborative optimization framework for power–transportation coupled networks that integrates multi-modal data with physical priors. The framework constructs a joint feature space from traffic flow, pedestrian density, charging behavior, and grid operating states, and employs hypergraph modeling—guided by power flow balance and traffic flow conservation principles—to capture high-order cross-domain coupling. For prediction, spatiotemporal graph convolution combined with physics-informed attention significantly improves the accuracy of EV charging load forecasting. For optimization, a hierarchical multi-agent strategy integrating federated learning and the Alternating Direction Method of Multipliers (ADMM) enables privacy-preserving, distributed charging load scheduling. Case studies conducted on a 69-node distribution network using real traffic and charging data demonstrate that the proposed method reduces the grid’s peak–valley difference by 20.16%, reduces system operating costs by approximately 25%, and outperforms mainstream baseline models in prediction accuracy, algorithm convergence speed, and long-term operational stability. This work provides a practical and scalable technical pathway for the deep integration of energy and transportation systems in future smart cities. Full article

Background/Objectives: Mathematical modelling provides a quantitative way to describe the fate and action of drugs in the oral cavity, where transport processes are shaped by salivary flow, pellicle formation, biofilm structure and the wash-out effect of gingival crevicular fluid (GCF). Local pharmacokinetics in the mouth differ substantially from systemic models, and therefore a dedicated framework is required. The aim of this work was to present a structured, physiologically based concept that links in vitro release testing with local pharmacokinetics and pharmacodynamics. Methods: A narrative review with elements of systematic search was conducted in PubMed, Scopus and Web of Science (1980–2025) for publications describing drug release, local PBPK, and PK/PD modelling in the oral cavity. Mathematical formulations were grouped into release kinetics, mini-PBPK transport and local PK/PD relations. Classical models (Higuchi, Korsmeyer–Peppas, Peppas–Sahlin) were integrated with a mini-PBPK structure describing saliva–mucosa–biofilm–pocket interactions. Results: The combined model captures adsorption to pellicle, diffusion within biofilm and wash-out by GCF. It allows simulation of variable clinical conditions, such as inflammation-related changes in Q_GCF, and links local exposure to pharmacodynamic outcomes. Case studies with PerioChip^®, Arestin^®, and Atridox^® demonstrate how mechanistic models explain observed therapeutic duration and low-systemic exposure. Conclusions: The proposed mini-PBPK framework bridges empirical release data and physiological transport in the oral cavity. It supports rational formulation design, optimisation of local dosage, and personalised prediction of drug retention in gingival pockets. This modelling approach can become a practical tool for the development of dental biomaterials and subgingival therapies. Full article

Short-term traffic prediction is vital for intelligent transportation systems, enabling adaptive congestion control, real-time signal management, and dynamic route planning for autonomous vehicles (AVs). This study introduces a custom Transformer-based deep learning framework for joint forecasting of traffic flow and vehicle speed, leveraging handcrafted positional encoding and stacked multi-head attention layers to model multivariate traffic patterns. Evaluated against baselines including Long Short-Term Memory (LSTM), Support Vector Machine (SVM), Random Tree, and Random Forest on the Next-Generation Simulation (NGSIM) dataset, the model achieves 94.2% accuracy (Root Mean Squared Error (RMSE) 0.16) for flow and 92.1% accuracy for speed, outperforming traditional and deep learning approaches. A hybrid evaluation metric, integrating RMSE and threshold-based accuracy tailored to AV operational needs, enhances its practical relevance. With its parallel processing capability, this framework offers a scalable, real-time solution, advancing AV ecosystems and smart mobility infrastructure. Full article

River ice is a common natural phenomenon in cold regions during winter, and it is also one of the key factors that must be considered in the development and utilization of water resources in these areas. In this paper, based on a two-dimensional hydrodynamic model and ice dynamics model coupled with a linear thermodynamic process, this study simulates and validates the formation, decay, transport, and accumulation of river ice at the Toudaoguai reach of the Yellow River in Inner Mongolia during the winters of 2019–2020 and 2020–2021. The influence of different parameters on backwater level variations caused by ice jams is further investigated using a modified Morris sensitivity analysis method. The results show that (1) the coupled thermal-dynamic model can accurately simulate the formation, transport, and accumulation process of river ice in natural river, as well as the freeze-up patterns and corresponding hydraulic characteristics. (2) Due to the influence of river topography, flow rate, and flow density, the freeze-up form is slightly different in different years, and the low discharge process favor a more stable freeze-up. (3) According to the modified Morris screening method, discharge (Q) and ice concentration (N) are the most sensitive to the change in the backwater water level after the ice jam, and the sensitivity is more than 50%. The next most sensitive factor is the ice-cover roughness (n_i), whereas ice porosity (e_f) exhibits a negative sensitivity to the water level after ice jam. Thus, this study provides effective tools to reproduce the process of river ice transport and accumulation in the reach of the Yellow River (Inner Mongolia section) and offers technical support and insights for ice-flood prevention and mitigation in this section. Full article

Infrared spectroscopic analysis of palygorskite clay from the Dashkovskoye and Borshchevskoye deposits yielded key insights into the sedimentation conditions prevailing in the study area. In this paper, the composition, structure, and adsorption properties of smectite–palygorskite clays from the Steshevian sub-stage of the Lower Carboniferous (Russia) are investigated. The study applied X-ray diffraction, infrared spectroscopy, scanning electron microscopy, assessment of cation exchange capacity by adsorption of [Cu(trien)²⁺], assessment of Cs sorption, and particle size analysis. It is demonstrated that the Al–palygorskite of the Dashkovskoye deposit was formed by sedimentation from suspended matter in a shallow-water basin in the Steshevian sub-age, despite a different genesis (chemogenic in the case of the palygorskites, clastic/redeposited in the case of the smectites). The palygorskites of the Borschovskoye deposit have a complex terrigenous genesis and were formed from redeposited chemogenic Al–palygorskites transported into the basin from the surrounding region of the Dashkovskoye deposit. With increasing depth of the basin in the Steshevian sub-age, the volume of incoming palygorskite material decreases, and the proportion of smectite material increases. The Fe–palygorskites entered the Borschovskoye deposit due to the redeposition of sediments from soils upstream of water flows. All the studied clays have considerable adsorption properties (32–49 mg-eq/100 g) and can be used in various industries. Full article

In this study, we developed a novel water quality model that integrated hydrodynamic, solute transport, and geochemical reactions processes. This model was built upon the open-source ELCIRC hydrodynamic model, the TVD-format solute transport model, and the PhreeqcRM geochemical reaction engine. The accuracy of the model was rigorously validated using a 2D chain decay analytical solution, demonstrating its capability to accurately simulate water flow, solute transport, and chemical reactions. To evaluate the practical applicability of the model, case studies involving the 2012 Huaihe River benzene leakage accident and the acetic acid leakage accident in the Gulei sea area were simulated. Findings indicate that the model effectively captures the diffusion and attenuation dynamics of the benzene contamination plume. Furthermore, it accurately depicts the reaction–diffusion interaction with seawater following acetic acid release. Notably, the versatility and flexibility of the model were further demonstrated by its ability to simulate a wide range of pollutants and their associated biochemical processes. This addresses the limitations of existing water quality models and provides a powerful tool for environmental monitoring and assessment. The results of this study offer valuable insights for improving water quality management and emergency response strategies in the face of environmental pollution incidents. Full article

The “Double High—Double Extra High” stage of offshore oilfields, where large pumps lift liquids, leads to a rapid rise in water concentration, which triggers a decrease in rock strength and exacerbates the risk of sand production; this leads to a blockage of the reservoir, thus restricting the release of production capacity. In this paper, for the typical weak cementation strength of unconsolidated sandstone of a Class I reservoir in the P oilfield, numerical simulation and indoor experimental methods are utilized to explore the plugging mechanism and law of the water-contenting conditions, with micro-sand and mud conditions, on the screen. Considering the combined effects of reservoir particulate transport plugging and near-well sand control media plugging, the additional pressure drop and skin factor calculation model is constructed, and a dynamic capacity prediction model for sand control wells is formed. By matching the physical properties of the target reservoir and optimizing the sand control method, the production capacity prediction model and the sand control optimization design method for the high water-content period of the unconsolidated sandstone reservoir are finally obtained. The results show that the median sand size of well A1 in the P oilfield Class I reservoir is 220 μm, the sand transportation diameter is about 15–20 m, the serious plugging area near the well is distributed in 2–2.5 m, and the predicted loss of production capacity is about 18%. The use of a foam metal screen can significantly reduce the plugging pressure and increase the flow of crude oil, which is 2.2 and 1.2 times higher than that of the precision mesh and pre-filled screen, respectively. These research results can provide technical support and theoretical guidance for the sustained, efficient, and stable production of sand reservoirs in the Bohai Oilfield. Full article

To avoid predators, benthic fish will stir up the sediment on the seabed by flapping their pectoral fins, thus burying themselves. This self-burial concealment strategy can offer bionic enlightenment for the benthic residence method of Unmanned Underwater Vehicles (UUVs). In this paper, based on the observation results of the self-burial behavior of benthic fish, a two-dimensional fluid-particle numerical model was developed to simulate the processes of sediment transport induced by pectoral fin flapping. In addition, an orthogonal experimental design was employed to analyze the effects of body length, flapping amplitude, flapping number, flapping frequency, and particle size on burial ratio, input power, and burial efficiency. The results reveal that rapid pectoral fin flapping enables benthic fish to fluidize sediments and achieve self-burial. Among the influencing factors, body size has the most significant impact on coverage ratio and input power, as larger fish generate stronger tip vortices and fluid disturbances, making local flow velocities more likely to exceed the critical starting velocity. In contrast, particle size has the weakest effect on burial performance, while kinematic parameters exert a far greater impact on self-burial than environmental parameters. The research results can offer references for the biomimetic design of self-burying UUVs. Full article

The flexible micro-structured surface found in biological skins exhibits remarkable drag reduction properties, inspiring applications in the aerospace industry, underwater exploration, and pipeline transportation. To address the challenge of efficiently replicating such structures, this study presents a composite flexible polymer film with a bio-inspired micro-dimple array, fabricated via an integrated process of precision milling, polishing, and micro-injection molding using thermoplastic polyurethane (TPU). We systematically investigated the influence of key injection parameters on the shape accuracy and surface quality of the film. The experimental results show that polishing technology can significantly reduce mold core surface roughness, thereby enhancing film replication accuracy. Among the parameters, melt temperature and holding time exerted the most significant effects on shape precision PV and bottom roughness R_a, while injection speed showed the least influence. Under optimized conditions of a melt temperature of 180 °C, injection speed of 60 mm/s, holding pressure of 7 MPa, and holding time of 13 s, the film achieved a micro-structure shape accuracy of 13.502 μm and bottom roughness of 0.033 μm. Numerical simulation predicted a maximum drag reduction rate of 10.26%, attributable to vortex cushion effects within the dimples. This performance was experimentally validated in a flow velocity range of 0.6–2 m/s, with the discrepancy between simulated and measured drag reduction kept within 5%, demonstrating the efficacy of the proposed manufacturing route for flexible bio-inspired drag reduction film. Full article

The uncoordinated water–sediment relationship, fragile eco-environment and unbalanced economic development in the Wei River Basin (WRB) pose serious challenges to its high-quality development. Most existing studies focus on static structures or single elements, making it difficult to systematically reveal the complex interrelationships among ecosystem services (ESs) supply, transmission and demand. To address this issue, this paper innovatively combines the “system perspective” with the “flow network model”. From the perspective of flood-sediment transport, eco-environmental and socio-economic (FES) subsystems, we take the WRB as its research object and systematically analyzes the supply–demand relationship of ESs, the pathways of the ESs flows and ecological compensation (EC) strategies at multiple scales. By constructing a supply–demand assessment model for six types of ESs combined with the water-related flows model, the enhanced two-step floating catchment area method and the gravity model, this paper simulates the ESs flows driven by different transmission media (water, road and atmosphere). The results showed the following: (1) a significant spatial mismatch was observed between the high-supply areas at the northern foothills of the Qinling Mountains and the high-demand areas in the Guanzhong Plains. Furthermore, the degree of this mismatch increased with decreasing scale. (2) The pathways of different ESs flows were influenced by their respective transmission media. The water-related flows passed through areas along the Wei River and the Jing River. The carbon sequestration flows were identified in the upper reaches of the Luo River and between the core urban agglomerations of the Guanzhong Plains. The crop production flows were significantly influenced by the scale of urban crop demand, radiating outward from Xi’an City. (3) At the county and watershed scales, The EC fund pools of 7.5 billion yuan and 2.6 billion yuan were formed, respectively. These EC funds covered over 90% of the areas. These findings verify the applicability of the “FES subsystems” framework for multi-scale EC and provide a theoretical basis for developing an integrated EC mechanism across the entire basin. Full article

Efficient cutting transport is crucial in challenging drilling environments such as ultra-short-radius horizontal wells. Flexible drill pipes, designed for complex wellbore geometries, offer a potential solution. However, the cutting transport behavior within them remains poorly understood. To improve wellbore cleaning and drilling efficiency, this study investigates the underlying transport mechanisms. The investigation employs a coupled CFD-DEM approach to model cutting transport in flexible drill pipes. This method combines fluid dynamics and particle motion simulations to analyze the interaction between drilling fluid and cuttings, evaluating the impact of factors such as rotational speed, flow rate, and fluid properties on cleaning efficiency. The results indicate that increasing the flow rate at a constant rotational speed significantly reduces the cutting concentration. Nevertheless, beyond a critical flow rate of 1.5 m/s, further increases yield diminishing returns in cleaning efficiency due to transport capacity saturation. In contrast, increasing the rotational speed at a fixed flow rate of 1.42 m/s has a less pronounced effect on cutting transport and increases frictional torque, thereby reducing energy efficiency. Higher rotational speeds primarily enhance the suspension of fine cuttings, with minimal impact on larger particles. Additionally, the rheological properties of the drilling fluid play a key role. A higher flow behavior index increases viscosity near the wellbore, improving transport performance. Conversely, a higher consistency index enhances the fluid’s carrying capacity but increases annular pressure drop, which imposes greater demands on pump capacity. Thus, optimal drilling performance requires balancing pressure losses and cleaning efficiency through comprehensive parameter optimization. Full article

Neutron radiography has been used to assess water content and transport in porous media like cement paste, mortar and concrete. This paper presents a methodology to evaluate water content profiles from neutron radiographs of axisymmetric cylindrical samples along the radial direction. Three examples are proposed as potential applications of this methodology: a drying mortar specimen, a sample of fluid cement paste during high-shear flow, and a steel-reinforced mortar specimen with a gap at the steel–mortar interface. In each case, a simulated neutron image is generated to represent experimental data. The proposed methodology is used to back-calculate the water content distribution of the original sample. The proposed approach can accurately quantify the distribution of water in all three theoretical cylindrical samples. For neutron radiographs created using a random distribution of neutron cross-section values for each constituent, emulating the experimental variability of the imaging process, the proposed method was able to quantify the distribution of water along the radial direction with an average error less than 1.5% for the drying mortar specimen, 3% for the cement paste sample during high-shear flow, and 4% for the reinforced sample with a gap at the steel–mortar interface. Full article

The study underpins the geothermal energy potential of Cambrian reservoirs in Lithuania, which utilizes the use of reactive transport modelling to examine how different reinjection temperatures and flow rates affect mineral changes. The results are then applied to design field development plans, using petroleum engineering methods such as horizontal wells and induced fracturing. The research study indicates that there are some changes in porosity and permeability over time due to mineral dissolution and precipitation because of injection rates, but no adverse effect of re-injection temperature was observed. Hence, a reinjection temperature of 40 °C is geochemically stable and suitable for long-term operation, with no significant effect on mineral behavior. Moreover, application of horizontal wells proves that there is a significant increase in water production and power (thermal) output due to improved reservoir exposure. Hydraulic fracturing further enhanced the performance and flow rates, concluding that, among all the sites studied, Nausodis demonstrated the highest thermal output, while Genciai showed the lowest potential due to limited reservoir temperature and productivity. Thus, research aims to improve power output by studying how well design, reinjection methods, and chemical reactions affect the reservoir, and it shows that using horizontal wells, fracturing, and proper reinjection temperature can help increase geothermal energy recovery in Lithuania. Full article

This study investigates the energy performance and preliminary turbomachinery design of post-combustion CO₂ compression systems integrated into an ultra-supercritical coal-fired power plant with carbon capture and storage (CCS). To enable pipeline transport, CO₂ must be delivered at 150 bar and 15 °C, i.e., in liquid phase. Unlike conventional configurations that compress CO₂ entirely in the gaseous/supercritical phase before final cooling, two alternative layouts are proposed, introducing an intermediate liquefaction step prior to liquid-phase compression. Each layout uses a chiller system that operates at CO₂ condensation temperatures of 10 °C and 20 °C. The energy performance and the system layout architecture are evaluated and compared with the conventional gaseous-phase compression configuration. An in-depth sensitivity analysis, which varies the flow coefficient, the working coefficient, and the degree of reaction, confirms that the turbomachinery preliminary design, based on input parameters related to the specific speed, is a high-efficiency design. The results indicate that the 10 °C liquefaction layout requires the least compression power (60 MW), followed by the 20 °C layout (62.5 MW) and the conventional system (67 MW). Including the consumption of the chiller, the proposed systems require an additional power of 11–12 MW, compared to just over 1 MW for the conventional layout with simple CO₂ cooling. These results highlight the significant influence of the integration of the chiller on the overall power requirement of the system. Although the proposed configurations result in a larger equipment footprint, the integrated capture and compression/liquefaction system allows for very low CO₂ emissions, making the power plant more sustainable. Full article