Fluid Flow Processes Research Articles

Coal seam penetration enhancement technology integrating hydraulic fracturing fracture development theory

The development process of fractures in coal beds is influenced by many factors, and its development mechanism is complicated and difficult to be predicted accurately. The research addresses the problem of penetration enhancement technology in the process of coal bed methane mining, and designs a method that incorporates the theory of hydraulic fracturing fracture development. In the process, the coal seam structure was studied, the coal rock was cracked using water injection, the fracture development process during hydraulic fracturing was analysed, the numerical simulation model was constructed using the expanded finite element method, and the fluid flow process in the unit was designed. The experimental results show that when the research method is tested for the time-consuming generation of numerical simulation results, the maximum time-consuming generation of is only 92 ms when the fracture length is 10 m, which is shorter than that of other methods; when analysing the results of fracture initiation pressure calculations, the error between the calculation results generated by the research method and the actual measured results in a total of 14 sample points of the two mines is maintained at less than 0.5 MPa; in the analysis of the relationship between the fluid flow rate and the fluid flow rate, the error is kept at less than 0.5 MPa in the case of fluid flow rate exceeding 0.5 ms; the fracture length and the longest fracture radius decreased significantly with the increase of the injection flow rate after the injection flow rate exceeded 0.005 m3/s. It shows that the research method can effectively carry out coal seam penetration enhancement with good computational efficiency and higher accuracy.

Numerical Method for the Variable-Order Fractional Filtration Equation in Heterogeneous Media

This paper presents a study of the application of the finite element method for solving a fractional differential filtration problem in heterogeneous fractured porous media with variable orders of fractional derivatives. A numerical method for the initial-boundary value problem was constructed, and a theoretical study of the stability and convergence of the method was carried out using the method of a priori estimates. The results were confirmed through a comparative analysis of the empirical and theoretical orders of convergence based on computational experiments. Furthermore, we analyzed the effect of variable-order functions of fractional derivatives on the process of fluid flow in a heterogeneous medium, presenting new practical results in the field of modeling the fluid flow in complex media. This work is an important contribution to the numerical modeling of filtration in porous media with variable orders of fractional derivatives and may be useful for specialists in the field of hydrogeology, the oil and gas industry, and other related fields.

Comprehensive Investigation of Factors Affecting Acid Fracture Propagation with Natural Fracture

Acid fracturing is a crucial stimulation technique to enhance hydrocarbon recovery in carbonate reservoirs. However, the interaction between acid fractures and natural fractures remains complex due to the combined effects of mechanical, chemical, and fluid flow processes. This study extends a previously developed hydro-mechano-reactive flow coupled model to analyze these interactions, focusing on the influence of acid dissolution. The model incorporates reservoir heterogeneity and simulates various scenarios, including different stress differences, approaching angles, injection rates, and acid concentrations. Numerical simulations reveal distinct propagation modes for acid and hydraulic fractures, highlighting the significant influence of acid dissolution on fracture behavior. Results show that hydraulic fractures are more likely to cross natural fractures, whereas acid fractures tend to be arrested due to wormhole formation. Increasing stress differences and approaching angles promote fracture crossing, while lower angles favor diversion into natural fractures. Higher injection rates facilitate fracture crossing by increasing pressure accumulation, but excessive acid concentrations hinder fracture initiation due to enhanced wormhole formation. The study demonstrates the importance of tailoring fracturing treatments to specific reservoir conditions, optimizing parameters to enhance fracture propagation and reservoir stimulation. These findings contribute to a deeper understanding of fracture mechanics in heterogeneous reservoirs and offer practical implications for improving the efficiency of hydraulic fracturing operations in unconventional reservoirs.

The mechanism of proppant transport dynamic propagation in rough fracture for supercritical CO2 fracturing

Supercritical CO2 fracturing technology has shown great potential for enhancing production in unconventional reservoirs. It is essential to clarify the transport mechanism of proppant under the dynamic propagation conditions within rough fractures. A realistic rough fracture model is reconstructed, and Computational Fluid Dynamics simulations are conducted to track proppant movement during fracture propagation. The typical transport characteristics of proppant within rough fractures are revealed, and the effects of fracture propagation rate, proppant density, mass flow rate, particle size, sand ratio, and temperature on the support effect are discussed. The results show that the flow channels formed by sand carrying fluid in rough fractures are complex, with fracture propagation changing some flow channels. The proppant forms an irregular sand bed interspersed with unfilled areas, and complex flow characteristics are generated. The increase in fractal dimension increases the resistance in the fluid flow process and affects the movement of the proppant, which tends to create unfilled areas. Low density and size of proppant can improve the proppant placement length. In a certain temperature range, high temperature injection of sand carrying fluid can improve the proppant placement effect. In addition, the low sand ratio and high mass flow rate pumping can be used to form the dominant channel, followed by pumping with a high sand ratio and low mass flow rate for effective support.

Effect of infusion direction on convection-enhanced drug delivery to anisotropic tissue.

Convection-enhanced delivery (CED) can effectively overcome the blood-brain barrier by infusing drugs directly into diseased sites in the brain using a catheter, but its clinical performance still needs to be improved. This is strongly related to the highly anisotropic characteristics of brain white matter, which results in difficulties in controlling drug transport and distribution in space. In this study, the potential to improve the delivery of six drugs by adjusting the placement of the infusion catheter is examined using a mathematical model and accurate numerical simulations that account simultaneously for the interstitial fluid (ISF) flow and drug transport processes in CED. The results demonstrate the ability of this direct infusion to enhance ISF flow and therefore facilitate drug transport. However, this enhancement is highly anisotropic, subject to the orientation of local axon bundles and is limited within a small region close to the infusion site. Drugs respond in different ways to infusion direction: the results of our simulations show that while some drugs are almost insensitive to infusion direction, this strongly affects other compounds in terms of isotropy of drug distribution from the catheter. These findings can serve as a reference for planning treatments using CED.

Geometrical characterization of fracture systems using point clouds and SELF-Software: example of the Añisclo anticline carbonate platform, Central Pyrenees

Natural fracture systems contribute significantly to rock mass anisotropies. Characterizing these systems is essential for understanding processes of fluid flow, energy exploration and storage, slope stability or tectonic processes that can affect the permeability or compaction of the material, as well as reflect its temporal evolution. This work presents a set of automatic and supervised algorithms integrated into the open-access software solution SEFL, designed to characterize fracture systems using remote sensing data sets. The software implements various strategies to quantify geometrical parameters with deterministic or stochastic descriptions, facilitating a detailed characterization of the fracture system for numerical simulations. Geological outcrops provide direct access to the rock masses and discontinuities, offering analogies with materials that are otherwise inaccessible for its direct study. The digital acquisition of the terrain using high-resolution techniques, such as Terrestrial Laser Scanner (TLS) or photogrammetry to obtain point clouds, enabled post-field studies, particularly for fracture systems that are complex, inaccessible, or large in scale. Additionally, SEFL offers a tool based on the concept of fracture stratigraphy to identify mechanical units, which are essential frameworks for measuring and calculating fracture properties. This new methodology has been applied to study the fractured Eocene limestone outcrop at the hinge of the Añisclo anticline (South-Central Pyrenees, NE Iberia) which has been digitally acquired and characterized. SEFL output data interpretations revealed an outcrop characterized by over two thousand modelled fractures, five fracture sets, fourteen fracture stratigraphic units, and 1-2 fractures/m.

Numerical investigation of the effects of variable fluid properties on cilia-driven flow of tangent hyperbolic fluid in a channel with heat and mass transfer: A new approach to microfluidic pumps

Heat, mass transfer, and non-Newtonian fluid flow processes have gained significant interest in various industrial applications due to their substantial significance in the fields of technology, engineering, and science. The aforementioned processes hold significance in the context of polymer solutions, porous industrial materials, ceramic processing, oil recovery, and fluid beds. This study aims to investigate the impact of temperature-dependent viscosity and thermal conductivity on the cilia-driven flow of tangent hyperbolic fluid with mass and heat transfer. The objectives include analyzing how these variable properties affect the velocity, temperature, and concentration profiles within the fluid flow, thereby providing insights into potential applications in bioenergy systems and enhancing the understanding of non-Newtonian fluid dynamics. Viscous dissipation has been taken into consideration. Firstly, governing nonlinear coupled equations are solved in a fixed frame, and then the results are tracked in the wave frame. MATHEMATICA's NDSolve command is utilized to graphically discuss the findings for several different flow parameters. Analytically stated, solving a problem with such a coupled and nonlinear system is tough. The effect of new parameters is discussed on velocity and temperature profile and graphically shown. It has been observed that the thermal conductivity is improved at moderately low temperatures, whereas the opposite pattern is seen at comparatively high temperatures. On the other hand, the temperature distribution demonstrates a behaviour consistent with lowering as the number of heat Bolus increases. The findings that were provided offer beneficial insight into bioenergy systems and serve as a helpful benchmark for both experimental and extra-progressive computational Multiphysics models.

Tidal triggering of seismic swarm associated with hydrothermal circulation at Blanco ridge transform fault zone, Northeast Pacific

Seismicity associated with hydrothermal systems (e.g., submarine volcanoes, mid-oceanic ridges, oceanic transform faults, etc.) share a complex relationship with the tidal forcing and induced fluid flow process under different tectonic settings. The hydrothermal circulation drives the deformation at the brittle-ductile transition zone within a permeable brittle crust. Although the tidal loading amplitudes are too small to generate a brittle deformation, the incremental pressure exerted by the tidal loading can modulate the flow of hydrothermal fluid circulation and trigger the critically stressed faults or fracture zones. We present a compelling case of tidal modulation in seismicity along the Blanco Ridge Transform Fault Zone (BRTFZ), in the northeast Pacific. The strong diurnal and fortnightly periodicity has been observed in the deeper seismic swarm (7–15 km), whereas the shallow seismic swarm (0–7 km) does not exhibit any such tidal periodicity. The dominance of diurnal and fortnightly periodicity in the deeper seismic swarm is explained by the high amplitude tidal cycles providing additional stress on the fluid circulation at the crust-mantle boundary. Moreover, our robust statistical correlation of seismicity with tidal stress and resonance destabilization model under rate-and-state friction formalism suggests that the fault segments are conditionally unstable and more sensitive to periodic tidal stress perturbation.

Wetting mechanism and alteration of nano-sized shale pores: Insights from contrast variation small angle neutron scattering

Wettability of tight shale is crucial for fluid flow and mass transport process in energy geosciences. However, understanding the interfacial chemistry and wetting mechanisms at sub-nano-pore scales remains a formidable challenge. In this study, the Contrast Variation technique of Small Angle Neutron Scattering (CV-SANS) is employed to investigate shale’s interfacial chemistry using reagents that possess a range of different polarities, including water, n-decane, toluene, and dimethyl methanamide. Through five different experimental strategies, we have demonstrated a successful modification of shale wettability, ranging from enhancement, weakening, to reversal. Delving into the mechanisms, we illustrated the crucial role of pre-existing liquid films in these changes, where the uniquely co-existing polar and non-polar functional groups in dimethyl methanamide acted as a conduit for interfacial chemistry adjustments. Furthermore, a solvent immersion led to matrix dilation as well as liberation of residual oil-occupied pores, resulting in altered pore size distributions, with hydrogen bonding playing a significant role in the polar groups. Interestingly, despite shale exhibiting a stronger affinity for oil over water, hydrophilic solvents induced more substantial dilation than lipophilic ones. Collectively, this work elucidates the dynamic change of interfacial chemistry via the configuration of polarity using chemical reagents, and the CV-SANS technique underscores its invaluable utilities in decoding the interfacial wettability traits in nanopore space of shale.

Large eddy simulation of various EMBr effects on the fluid flow, heat transfer and solidification process in an ultra-high speed thin slab casting mould with multi-port SEN

Effective control of intense turbulence is a crucial challenge for achieving steady production with ultra-high casting speed in thin slab continuous casting. In thin slab casting process, specially designed multi-port submerged entry nozzle (SEN) with four outlets is utilised to ensure an ample supply of molten steel, necessitating the selection and optimisation of suitable Electromagnetic Braking (EMBr) equipment for steel jet control. This study established a comprehensive three-dimensional model of a funnel-type mould, employing a combined experimental-numerical approach to validate and investigate the flow, heat transfer, solidification and electromagnetic behaviour in the mould. The steel grade studied in the simulation is Q235B, and its physical properties were calculated based on its composition with a temperature range of 1450–1826 K. To analyse the influence of high casting speed on the flow and solidification behaviour in the mould, three casting speeds were selected for the study, which were 6, 7 and 8 m/min. The results indicate that the novel Bowl EMBr significantly suppressed the penetration of steel jet and thus enhanced the thickness and uniformity of the solidified shell. As the casting speed increases from 6 to 8 m/min, the solidified shell thickness at the mould exit decreases from 7.91 to 5.94 mm, with the stagnant growth region approaching the mould exit. This highlights the requirement to correspondingly increase EMBr strength under ultra-high casting speed condition to avoid remelting of the shell and the risk of molten steel leakage. The coupled mathematical model established in this study provides guidance for optimising EMBr structures and casting speed under special multi-port SEN conditions, offering recommendations for the rational control of flow, heat transfer and solidification process in the mould.

Double‐sided queues and their applications to vaccine inventory management

AbstractWe consider a double‐sided queueing model with batch Markovian arrival processes (BMAPs) and finite discrete abandonment times, which arises in various stochastic systems such as perishable inventory systems and financial markets. Customers arrive at the system with a batch of orders to be matched by counterparts. While waiting to be matched, customers become impatient and may abandon the system without service. The abandonment time of a customer depends on its batch size and its position in the queue. First, we propose an approach to obtain the stationary joint distribution of age processes via the stationary analysis of a multi‐layer Markov modulated fluid flow process. Second, using the stationary joint distribution of the age processes, we derive a number of queueing quantities related to matching rates, fill rates, sojourn times and queue length for both sides of the system. Last, we apply our model to analyze a vaccine inventory system and gain insight into the effect of uncertainty in supply and demand processes on the performance of the inventory system. It is observed that BMAPs are better choices for modeling the supply/demand process in systems with high uncertainty for more accurate performance quantities.

Development of Methodologies and Software for Design, Simulation and Optimization of Oil Hydraulic Cylinders of Large Dimensions and Power

As part of the research carried out in the field of processing systems and the production process of oil-hydraulic cylinders of large dimensions and power, the specifics of fluid power transmission, in the functioning of hydropower facilities, were analyzed. The research also includes the optimization of the physical–mathematical model of non-stationary processes, which take place inside the chamber of a large hydrocylinder. In parallel with the definition of the optimization model, the work parameters that affect the process of fluid flow and piston movement were determined. The operating and technological construction parameters of the hydraulic cylinder, which most significantly affect the operation of the hydraulic cylinder, were defined, and the observed parameters were optimized, based on which a prototype with improved characteristics compared to existing solutions was realized.

Efficient Numerical Implementation of the Time-Fractional Stochastic Stokes–Darcy Model

This paper presents an efficient numerical method for the fractional-order generalization of the stochastic Stokes–Darcy model, which finds application in various engineering, biomedical and environmental problems involving interaction between free fluid flow and flows in porous media. Unlike the classical model, this model allows taking into account the hereditary properties of the process under uncertainty conditions. The proposed numerical method is based on the combined use of the sparse grid stochastic collocation method, finite element/finite difference discretization, a fast numerical algorithm for computing the Caputo fractional derivative, and a cost-effective ensemble strategy. The hydraulic conductivity tensor is assumed to be uncertain in this problem, which is modeled by the reduced Karhunen–Loève expansion. The stability and convergence of the deterministic numerical method have been rigorously proved and validated by numerical tests. Utilizing the ensemble strategy allowed us to solve the deterministic problem once for all samples of the hydraulic conductivity tensor, rather than solving it separately for each sample. The use of the algorithm for computing the fractional derivatives significantly reduced both computational cost and memory usage. This study also analyzes the influence of fractional derivatives on the fluid flow process within the fractional-order Stokes–Darcy model under uncertainty conditions.

Impacts of Stefan Blowing on Thermophoretic Particle Deposition in Sisko Nanofluid Flow Over a Riga Plate with Soret and Dufour Effects

The proposed framework considers the thermosolutal Marangoni convective flow of Sisko [Formula: see text] nanofluid over a Riga surface with the effects of Stefan blowing and thermophoretic particle deposition. The phenomena of mass and heat are discussed in relation to Soret and Dufour impacts. Electrodes and magnets are arranged on a plate to make up the Riga plate. Since the fluid conducts electricity, the Lorentz force upsurges exponentially in the vertical direction. There are numerous possible uses for this study in different disciplines. The design and production of thin films, coatings, and nanostructured materials can be enhanced by knowledge of how nanoparticles settle onto surfaces under various fluid flow conditions. By optimizing fluid flow and particle deposition processes, engineering insights from this work can guide the development of more efficient heat transfer systems, such as heat exchangers and cooling technologies. The nonlinear governing PDEs are converted into nonlinear ODEs using appropriate transformations. The resultant system of highly nonlinear equations can be solved analytically by using the homotopy analysis method (HAM). The significance of factors on the flow, thermal, and concentration fields are thoroughly explained with the use of tables and figures. Higher Marangoni convection parameter in more effective heat and mass transport within the liquid as well as higher induced flows when the Marangoni convection parameter is increased. A more uniform distribution of these properties throughout the liquid is the result of decreasing temperature and concentration profiles.

Deep learning-based prediction of velocity and temperature distributions in metal foam with hierarchical pore structure

Constrained by the substantial computational time required for numerical simulation, a deep learning technique is applied to investigate fluid flow and heat transfer processes in metal foam with a hierarchical pore structure. This work adopted a 3D convolutional neural network (CNN) combining U-Net architecture to predict velocity and temperature distributions, alongside corresponding permeability and overall heat transfer coefficient. This approach demonstrates excellent capability in intricate image segmentation. The training sets were acquired by lattice Boltzmann method (LBM) simulations. The CNN model, trained on a substantial amount of data, demonstrates remarkable precision, exhibiting mean relative errors of 0.57% for permeability prediction and 2.27% for overall heat transfer coefficient prediction. Moreover, in CNN prediction, a broader range of structure parameters and boundary conditions beyond those in the training set was used to evaluate the practicability of the trained CNN model. In contrast to numerical simulation, the CNN model economizes approximately 95.41% and 99.57% of computational time for velocity and temperature distribution prediction, respectively, providing a novel approach for exploring transport processes in metal foam with hierarchical pore structure.

The impact of the correlation coefficient of interarrival and service times on queueing performance: The [formula omitted] case

This paper is concerned on an M/M/1 queue with correlated interarrival and service times. In particular, we assume that the interarrival time and service time of a customer have a bivariate exponential distribution. By utilizing a Markov modulated fluid flow (MMFF) process associated with the age process of the customer in service, we obtain a number of queueing quantities in closed form. Using the solutions, the impact of the correlation coefficient of the interarrival and service times on a variety of queueing quantities is explored quantitatively and qualitatively. Specifically, we establish a monotonic relationship between the decay rates of queueing quantities and the correlation coefficient of the interarrival and service times. We also show that the decay rates are increasing in the correlation coefficient. In addition, queues with the maximum/minimum correlation coefficient are analyzed. Two examples are presented to demonstrate the importance of using the correlation coefficient in queueing performance/economic analysis.

Online Flow Measurement of Liquid Metal Solutions Based on Impact Force Sequences: Modeling Analysis, Simulation, and Validation of Experimental Results.

Aiming at the existing high-temperature liquid metal flow online accurate measurement by the metal melt characteristics, installation space, and high-temperature environment adaptability limitations, this paper innovatively puts forward a soft measurement method based on the impact force generated in the fluid flow process as an observational variable series. Fluid mechanics theory and simulation software are used to analyze and verify the feasibility of the impact force as an observable variable to measure the flow rate, followed by the construction of the CNN-LSTM-CNN-Double (CLCD) flow measurement model of impact force and flow rate based on the parameters of the learning rate and the number of training times, and finally the construction of a test platform for the flow measurement, and the validity of the method is verified through actual operation.

Effect of complex void structures on flow channeling and heterogeneous heat transfer in fractured rocks

Natural or hydraulic fractures in enhanced geothermal systems (EGS) typically have complex void structures due to the presence of surface contact. In this study, fluid flow and heat transfer processes in three-dimensional rough fractures with different contact ratios are investigated. Stronger flow channeling and heterogeneous heat transfer are observed in fracture voids with increasing surface contacts, and the fluid flow exhibits nonlinear characteristics due to the complex fracture void structures. Parts of fracture voids with large apertures and void areas contribute negligibly to the overall flow due to their weak connectivity to the main flow channels. Removing the low-flow regions does not significantly impact the flow channeling and heterogeneous heat transfer in the fracture voids. However, the heat exchange in the low-flow regions results in differences in the overall heat transfer coefficient and heat extraction rate between the reconstructed and original fractures. An empirical model is proposed to describe the overall heat transfer coefficient in fractures with complex void structures. Furthermore, the flow and heat transfer processes in the highly contacted fractures are not significantly affected by the change in flow direction, indicating that the anisotropic degree of the fracture void structures decreases as the contact areas increases. This study may further deepen the understanding of fluid flow and heat transfer in realistic fractured rocks at high temperatures, which is critical for geothermal energy extraction.

Computational Fluid Dynamics in Wind Energy: Modeling and Optimization for Turbine Design

Renewable energy sources are hard to come by, but wind power has become one of the most popular options because it can make a lot of clean electricity. For wind energy to be used properly, however, turbines need to be designed in a way that takes into account the surrounding environment. To model and improve wind turbine systems, computational fluid dynamics (CFD) has become very important. It lets engineers simulate complicated fluid flow processes and improve turbine performance. When it comes to wind energy, this study mainly talks about how CFD can be used to model and improve rotor designs. Experts can learn more about the complicated fluid dynamics around wind turbines by using CFD models. For example, they can learn how the rotor blades interact with the wind flow moving in. Calculative fluid dynamics (CFD) makes it easier to guess things like power output, efficiency, and structure loads for wind turbines by accurately modeling turbulence, boundary layers, and other airflow effects. An important other topic this paper covers is how to make wind machine designs work better. To find the best setups for capturing energy while using the least amount of materials and spending the least amount of money on upkeep, engineers can combine computational fluid dynamics (CFD) with optimization methods. Blade shape, tower height, turning angle, and rotor speed are just some of the design factors that this optimization process looks at. We can make very efficient and cost-effective wind turbine systems that are perfect for each spot by using CFD-driven optimization methods and running models and analyses over and over again. For better confidence and accuracy in turbine design predictions, this study talks about how to combine CFD models with actual confirmation. Engineers can make sure that CFD models work in a wide range of situations by comparing modeling results with readings taken in the real world. It also helps to improve the models. This paper emphasizes how important CFD is to the progress of wind energy technology by giving a thorough look at its uses in designing turbines and their optimization, proof, and development. Potential for improving the efficiency and long-term viability of wind power generation stays high as long as more study and new ideas are put into CFD-driven methods.

A turbulent mass diffusivity model for analyzing the mixing characteristics in an impinging stream-rotating packed bed

In this study, the fluid flow and mixing process in an impinging stream-rotating packed bed (IS-RPB) is simulated by using a new three-dimensional computational fluid dynamics model. Specifically, the gas–liquid flow is simulated by the Euler–Euler model, the hydrodynamics of the reactor is predicted by the RNG k–ε method, and the high gravity environment is simulated by the sliding mesh model. The turbulent mass transfer process is characterized by the concentration variance and its dissipation rate εc formulations, and therefore the turbulent mass diffusivity can be directly obtained. The simulated segregation index Xs are in agreement with our previous experimental results. The simulated results reveal that the fringe effect of IS can be offset by the end effect at the inner radius of RPB, so the investigation for the coupling mechanism between IS and RPB is critical to intensify the mixing process in IS-RPB.