Search Results (281)

Deepwater oil–gas–water three-phase flow is widely regarded as a multiphase system. Intense interfacial interactions cause significant nonuniform fluid distributions in the wellbore, giving rise to complex nonlinear dynamics. In this study, a distributed conductance sensor (DCS) was developed to capture local flow information from a horizontal oil–gas–water simulation well. To quantify the complexity of nonlinear time series, phase permutation entropy (PPE) was first validated using artificial data, including the Tent map, Hénon map, and Lorenz system. PPE demonstrates superior capability in detecting abnormal dynamical changes compared with permutation entropy (PE). Subsequently, PPE is combined with the multiscale approach, i.e., multiscale phase permutation entropy (MPPE), to analyze the DCS signals and uncover the complexity of horizontal oil–gas–water flows. The results show that the MPPE analysis can reveal the spatial distribution characteristics of elongated gas bubbles, gas paths, dispersed bubbles and oil droplets. Full article

The use of liquid hydrogen (LH₂) as an energy carrier is gaining traction across sectors such as aerospace, maritime, and large-scale energy storage due to its high gravimetric energy density and low environmental impact. However, the cryogenic nature of LH₂, with storage temperatures near 20 K, poses significant thermodynamic and safety challenges. This review consolidates the current state of modelling approaches used to simulate LH₂ behaviour during storage and transfer operations, with a focus on improving operational efficiency and safety. The review categorizes the literature into two primary domains: (1) thermodynamic behaviour within storage tanks and (2) multi-phase flow dynamics in storage and transfer systems. Within these domains, it covers a variety of phenomena. Particular attention is given to the role of heat ingress in driving self-pressurization and boil-off gas (BoG) formation, which significantly influence storage performance and safety mechanisms. Eighty-one studies published over six decades were analyzed, encompassing a diverse range of modelling approaches. The reviewed literature revealed significant methodological variety, including general analytical models, lumped-parameter models (0D/1D), empirical and semi-empirical models, computational fluid dynamics (CFD) models (2D/3D), machine learning (ML) and artificial neural network (ANN) models, and numerical multidisciplinary simulation models. The review evaluates the validation status of each model and identifies persistent research gaps. By mapping current modelling efforts and their limitations, this review highlights opportunities for enhancing the accuracy and applicability of LH₂ simulations. Improved modelling tools are essential to support the design of inherently safe, reliable, and efficient hydrogen infrastructure in a decarbonized energy landscape. Full article

Gas–liquid discharge shows great promise for enhancing the efficiency of diverse energy conversion systems; however, its inherent stochasticity and instability hinder precise process control. Here, we use femtosecond laser-induced discharge combined with space–time resolution spectroscopy to achieve stable and tunable plasma generation at the gas–liquid interface. Experimental results show that the interface reduces the breakdown electric-field threshold by about 25%, shortens the breakdown delay by about 80 ns, and markedly suppresses timing jitter compared with air and the formation of high-density, low-temperature plasma, indicating that liquid-derived species participate in and reshape the ionization pathways. This work provides a controllable platform for the study of gas–liquid discharge and new insights for the design of efficient plasma auxiliary systems for multiphase flow energy conversion. Full article

Accurate modeling of multiphase flow in porous media remains challenging due to the nonlinear transport and sharp displacement fronts described by the Buckley–Leverett (B-L) equation. Although Fourier Neural Operators (FNOs) have recently emerged as powerful surrogates for parametric partial differential equations, they exhibit limited robustness when extrapolating beyond the training regime, particularly for shock-dominated fractional flows. This study aims to enhance the extrapolative performance of FNOs for one-dimensional B-L displacement. Analytical solutions were generated using Welge’s graphical method, and datasets were constructed across a range of mobility ratios. A baseline FNO was trained to predict water saturation profiles and evaluated under both interpolation and extrapolation conditions. While the standard FNO accurately reconstructs saturation profiles within the training window, it misestimates shock positions and saturation jumps when extended to longer times or higher mobility ratios. To address these limitations, we develop Physics-Informed FNOs (PI-FNOs), which embed PDE residuals and boundary constraints, and Transfer-Learned FNOs (TL-FNOs), which adapt pretrained operators to new regimes using limited data. Comparative analyses show that both approaches markedly improve extrapolation accuracy, with PI-FNOs achieving the most consistent and physically reliable performance. These findings demonstrate the potential of combining physics constraints and knowledge transfer for robust operator learning in multiphase flow systems. Full article

In natural gas gathering and transportation projects, efficient gas-liquid separation equipment is crucial to ensuring the stable operation of subsequent processes. Conventional separation units often have problems such as low efficiency, high energy consumption and poor resistance to load fluctuations when dealing with foam-containing gas-liquid mixtures. For this purpose, numerical simulation and structural optimization of multi-stage foam separation units were carried out in this study. Based on FLUENT software fluid analysis software, a three-dimensional, multi-physics coupled model incorporating cyclonic defoaming components and axial-flow separation tubes was developed. The volume of fluid (VOF) multiphase flow model was used to capture the dynamic characteristics of the gas-liquid interface, and the population balance model was used to simulate the coalescence and fragmentation of the foam. The results show that in the non-working fluid stage, the optimal operating pressure is 5.0–5.5 MPa, and the droplet concentration should be maintained below 50 × 10⁻⁵. The system performance during the working fluid stage is significantly influenced by foam size. The efficiency of millimeter-sized foams is stable above 88% in the 5.0–6.0 MPa range, while the efficiency of micrometer-sized foams is optimal in the 5.3–5.7 MPa range. It is recommended to control the foam proportion below 35% and add a pre-defoaming unit to improve overall performance. Full article

This review paper investigates the use of air lubrication to reduce ship hull skin frictional drag, a technology whose fundamental drag-reduction mechanisms and impact on seakeeping are increasingly being studied through Computational Fluid Dynamics (CFD). Simulating this process is challenging, as the air phase often manifests as dispersed bubbles rather than a continuous film, necessitating high-fidelity models. Traditional simulations treating air and water as distinct phases fall short, and while Direct Numerical Simulation (DNS) captures bubble behaviour, its computational cost is prohibitive for practical application. This paper, therefore, reviews numerical simulation methods for air lubrication systems, evaluating their capabilities and limitations in capturing the system’s hydrodynamics and structural interaction, in contrast to traditional towing tank testing. The evaluation reveals a critical trade-off: methods with high computational feasibility (e.g., standard LES with VOF) provide an adequate estimation of overall drag reduction but consistently fail to accurately model the detailed bubble breakup and coalescence dynamics crucial for predicting system performance across different vessel speeds and pressures. Specifically, the review establishes that current mainstream CFD approaches underestimate the pressure-induced stability effects on bubbles. The paper concludes that accurate and practical simulation requires the integration of advanced techniques, such as Population Balance Models or Lagrangian Particle Tracking, to account for these distinct, flow-dependent phenomena, thereby highlighting the path forward for validated numerical models in marine air lubrication. Full article

We present a new finite element framework for modeling compressible, turbulent multiphase flows with heat transfer. For two-fluid systems with a free surface, the Volume of Fluid (VOF) method is implemented without the need for interface reconstruction, while turbulence is resolved using a dynamic Vreman large eddy simulation (LES) model. Unlike most two-phase VOF studies, which neglect heat transfer, the present approach incorporates energy transport equations within the VOF formulation to account for heat exchange, an effect particularly important in turbulent flows. Conjugate heat transfer is often challenging in finite volume methods, which require explicit specification of heat fluxes at the solid–fluid interface, limiting accuracy and predictive capability. By contrast, the finite element formulation does not require heat flux inputs, allowing more accurate and robust simulation of heat transfer between solids and fluids. The method is demonstrated through three representative cases. First, a two-fluid instability with a single-mode perturbation is simulated and validated against analytical growth rates. Second, conjugate heat transfer is examined in a high-temperature flow over a cold metal cylinder, with validation performed both quantitatively—via pressure coefficient comparisons with experimental data—and qualitatively using vector field topology. Finally, compressible spray injection and breakup are modeled, demonstrating the ability of the framework to capture interfacial dynamics and atomization under turbulent, high-speed conditions. In the compressible spray injection and breakup case, the results indicate that the finite element formulation achieved higher predictive accuracy and robustness than the finite-volume method. With the same mesh resolution, the FEM reduced the root mean square error (RMSE) and mean absolute percentage error (MAPE) from 6.96 mm and 26.0% (for the FVM) to 4.85 mm and 12.7%, respectively, demonstrating improved accuracy and robustness in capturing interfacial dynamics and heat transfer. The study also introduced vector field topology to visualize and interpret coherent flow structures and instabilities, offering insights beyond conventional scalar-field analyses. Full article

The development of large-scale, flexible, and safe hydrogen storage is critical for enabling a low-carbon energy system. Deep saline aquifers (DSAs) offer substantial theoretical capacity and broad geographic distribution, making them attractive options for underground hydrogen storage. However, hydrogen storage in DSAs presents complex technical, geochemical, microbial, geomechanical, and economic challenges that must be addressed to ensure efficiency, safety, and recoverability. This study synthesizes current knowledge on hydrogen behavior in DSAs, focusing on multiphase flow dynamics, capillary trapping, fingering phenomena, geochemical reactions, microbial consumption, cushion gas requirements, and operational constraints. Advanced numerical simulations and experimental observations highlight the role of reservoir heterogeneity, relative permeability hysteresis, buoyancy-driven migration, and redox-driven hydrogen loss in shaping storage performance. Economic analysis emphasizes the significant influence of cushion gas volumes and hydrogen recovery efficiency on the levelized cost of storage, while pilot studies reveal strategies for mitigating operational and geochemical risks. The findings underscore the importance of integrated, coupled-process modeling and comprehensive site characterization to optimize hydrogen storage design and operation. This work provides a roadmap for developing scalable, safe, and economically viable hydrogen storage in DSAs, bridging the gap between laboratory research, pilot demonstration, and commercial deployment. Full article

A coupled CFD-DEM model was adopted to investigate the floating ice accumulation mechanism and its disturbance to the flow field in the pump house of coastal nuclear power plants in cold regions. Based on numerical simulations, the motion, accumulation, and flow interaction characteristics of floating ice under various release positions and heights were analyzed. The results indicate that the release height significantly governs the accumulation morphology and hydraulic response. The release height critically determines ice accumulation patterns and hydraulic responses. For inlet scenarios, lower heights induce a dense, wedge-shaped accumulation at the coarse trash rack, increasing thickness by 57.69% and shifting the accumulation 38.16% inlet-ward compared to higher releases. Conversely, higher releases enhance dispersion, expanding disturbances to the central pump house and intensifying flow heterogeneity. In bottom release cases, lower heights form wall-adhering accumulations, while higher releases cause ice to rise into mid-upper layers, thereby markedly intensifying local vortices (peak intensity 79.68, approximately 300% higher). Spatial release locations induce 2.7–4.8-fold variations in flow disturbance intensity across monitoring points. These findings clarify the combined impact of the release height and location on the ice accumulation and flow field dynamics, offering critical insights for the anti-ice design and flow safety assessment of pump houses. Full article

Cyclone separators are widely used for gas–solid separation due to their robustness and low operating cost. This study focuses on the experimental validation of a single cyclone configuration and the development of a MATLAB-based numerical framework. The model employs a Euler–Lagrange approach to capture centrifugal, drag, and gravitational forces acting on spherical polyethylene particles (D = 5 mm). Laboratory-scale measurements of airflow, pressure drop, and separation efficiency showed strong agreement with the numerical model (deviation < 6%), confirming its reliability for the single cyclone case. Beyond this validated framework, exploratory simulations were carried out for series and parallel cyclone configurations to provide predictive insights into possible design trade-offs. Unlike high-fidelity CFD–DEM models, which are computationally intensive and allow detailed turbulence and particle–particle interactions, the present MATLAB model is simplified but transparent and fast to implement. Its originality lies in demonstrating a low-cost, experimentally calibrated tool that can support preliminary design decisions. The multi-cyclone results should be interpreted as predictive trends, as no direct experimental validation was possible within the present setup. These findings offer preliminary guidance for balancing efficiency, energy demand, and throughput in applied mechanics of multiphase flow systems. Full article

The shallow-water delta-front reservoir in Member II of the Oligocene Dongying Formation (Ed2), located in an oilfield within the Bohai Bay Basin, is a large-scale composite sedimentary system dominated by subaqueous distributary channels and mouth bars. Within this system, reservoir sand bodies exhibit significant thickness, complex internal architecture, poor injection–production correspondence during development, and an ambiguous understanding of remaining oil distribution. To enhance late-stage development efficiency, it is imperative to deepen the understanding of the genesis and evolution of the subaqueous distributary channel–mouth bar system, analyze the internal reservoir architecture, and clarify sand body connectivity relationships. Based on sedimentary physical modeling experiments, integrated with core, well logging, and seismic data, this study systematically reveals the architectural characteristics and spatial stacking patterns of the mouth bar reservoirs using Miall’s architectural element analysis method. The results indicate that the study area is dominated by sand-rich, shallow-water delta front deposits, which display a predominantly coarsening-upward character. The main reservoir units are mouth bar sand bodies (accounting for 30%), with a vertical stacking thickness ranging from 3 to 20 m, and they exhibit lobate distribution patterns in plan view. Sedimentary physical modeling reveals the formation mechanism and stacking patterns of these sand-rich, thick sand bodies. Upon entering the lake, the main distributary channel unloads its sediment, forming accretionary bodies. The main channel then bifurcates, and a new main channel forms in the subsequent unit, which transports sediment away and initiates a new phase of deposition. Multi-phase deposition ultimately builds large-scale lobate complexes composed of channel–mouth bar assemblages. These complexes exhibit internal architectural styles, including channel–channel splicing, channel–bar splicing, and bar–bar splicing. Reservoir architecture analysis demonstrates that an individual distributary channel governs the formation of an individual lobe, whereas multiple distributary channels control the development of composite lobes. These lobes are laterally spliced and vertically superimposed, exhibiting a multi-phase progradational stacking pattern. Dynamic production data analysis validates the reliability of this reservoir architecture classification. This research elucidates the genetic mechanisms of thick sand bodies in delta fronts and establishes a region-specific reservoir architecture model. This study clarifies the spatial distribution of mudstone interlayers and preferential flow pathways within the composite sand bodies. It provides a geological basis for optimizing injection–production strategies and targeting residual oil during the ultra-high water-cut stage. The findings offer critical guidance for the efficient development of shallow-water delta front reservoirs. Full article

It is demonstrated that the general representation of a dynamic multiphase wellbore flow model may be identified from the available physical measurements. The proposed approach is based on the techniques of numerical optimization and also requires the availability of solvers for the general type of partial differential equations describing two-phase gas–oil flow. A solution is obtained both for the case of the homogeneous no-slip model and the drift-flux model with velocity slip. The feasibility of the proposed approach for system identification and parameter estimation has been demonstrated using simulated flow data. Two distinct scenarios have been considered: firstly, when the well is fully instrumented with multiple pressure sensors and a multiphase flow meter, and secondly, when only a single downhole pressure gauge is available. Full article

The phenomenon known as non-wetting phase (nwp) entrapment, and the multiphase fluid flow within porous media that gives rise to it, is important in several areas such as contaminant transport and subsequent remediation, subsurface energy storage, oil recovery, carbon dioxide sequestration, and pore structural characterisation. The aim of this review was to survey the various different modelling and simulation approaches used to predict the pore-scale processes involved in the entrapment of nwp in disordered porous media, and the impact of pore structural features on the level of entrapment. The various modelling and simulation approaches considered included empirical models, pore network models (PNMs), percolation models, models derived directly from imaging data, and thermodynamic and statistical mechanical techniques. Dynamic flow simulations within models derived from images have validated the quasi-static idealisation for low capillary number, often used with PNMs. Modelling using this approximation has demonstrated the importance of pore connectivity and macroscopic heterogeneities in the spatial distribution of pore sizes in determining entrapment. Dynamic simulations in image-derived models have also shown the need for proper representation of menisci configurations in the complex void spaces of mixed-wetting systems in order to accurately predict entrapment, something that is not always currently possible. Full article

During natural gas extraction, understanding multiphase flow in fractured reservoirs remains a critical challenge due to the heterogeneous distribution of pores and fractures and the multi-scale nature of seepage mechanisms. These complexities introduce randomness in fluid distribution and tortuosity in seepage channels, limiting accurate characterization of gas-water flow. To address this issue, a dual-medium gas-water two-phase relative permeability model is developed by incorporating the fractal dimension of fracture surfaces, the tortuosity of the rock matrix, and the stress sensitivity of fracture networks. The model integrates essential microstructural parameters to capture the nonlinear flow behavior in dual-porosity systems. A systematic sensitivity analysis is conducted to evaluate the effects of fracture and matrix properties on the relative permeability curve. Results indicate that the fracture surface fractal dimension exerts a dominant influence in the two-phase flow region (fracture fractal dimensions in the range of 1.6–2.8), while near single-phase flow, fracture fractal dimensions in the range of 2.4–2.8 strongly affect flow behavior. Overall, the findings demonstrate that fracture-related parameters play a greater role than matrix properties in governing permeability evolution. This study provides predictive capability for two-phase flow in stress-sensitive fractured carbonates. Full article

Horizontal annular flow channels are widely applied in various fields, including thermal engineering, drilling engineering, and food engineering. Investigating their internal flow patterns is crucial for optimizing pipeline design, selecting appropriate equipment, and understanding the sedimentation and migration modes of multiphase flows within annular geometries. In practical engineering applications, the operational conditions of annular flow channels during gas drilling are the most complex, involving parameters such as eccentricity, rotation, surface roughness, and multiphase flow interactions. This study focuses on the flow characteristics of horizontal annular channels under real-world engineering conditions, examining variations in operational parameters. The pressure drop in annular pipelines is influenced by factors such as flow velocity, eccentricity, and rotational speed, exhibiting complex variation patterns. However, previous studies have not fully considered the impact of rough wellbore walls and the interactions among various factors. Employing experimental methods, this research analyzes the pressure drop characteristics within annular geometries. The results reveal that surface roughness significantly affects pressure drop, with the inner pipe’s roughness having a greater impact when the outer pipe surface is rough compared to when it is smooth. An increase in eccentricity substantially reduces pressure drop, with both positive and negative eccentricities demonstrating symmetric pressure drop patterns. Moreover, a significant positive correlation exists between the total rough area of the annular channel and pressure drop. Furthermore, this study establishes a predictive model through dimensional analysis. Unlike existing models, this new model incorporates the influences of both roughness and eccentricity, achieving a prediction accuracy of over 99%. This research confirms the critical role of roughness in annular flow systems and provides practical implications for selecting more reliable pump power equipment in engineering fields. Full article