Application of Stochastic Fracture Network with Numerical Fluid Flow Simulations to Groundwater Flow Modeling in Fractured Rocks

The continuum approach in fluid flow modeling is generally applied to porous geological media, but has limited applicability to fractured rocks. With the presence of a discrete fracture network relatively sparsely distributed in the matrix, it may be difficult or erroneous to use a porous medium fluid flow model with continuum assumptions to describe the fluid flow in fractured rocks at small or even large field scales. A discrete fracture fluid flow approach incorporating a stochastic fracture network with numerical fluid flow simulations could have the capability of capturing fluid flow behaviors such as inhomogeneity and anisotropy while reflecting the changes of hydraulic features at different scales. Moreover, this approach can be implemented to estimate the size of the representative elementary volume (REV) in order to find out the scales at which a porous medium flow model could be applied, and then to determine the hydraulic conductivity tensor for fractured rocks. The following topics are focused on in this study: (a) conceptual discrete fracture fluid flow modeling incorporating a stochastic fracture network with numerical flow simulations; (b) estimation of REV and hydraulic conductivity tensor for fractured rocks utilizing a stochastic fracture network with numerical fluid flow simulations; (c) investigation of the effect of fracture orientation and density on the hydraulic conductivity and REV by implementing a stochastic fracture network with numerical fluid flow simulations, and (d) fluid flow conceptual models accounting for major and minor fractures in the 2 D or 3 D flow fields incorporating a stochastic fracture network with numerical fluid flow simulations.

Physics-informed neural network-based petroleum reservoir simulation with sparse data using domain decomposition

Recent advances in deep learning have expanded new possibilities for fluid flow simulation in petroleum reservoirs.However,the predominant approach in existing research is to train neural networks using high-fidelity numerical simulation data.This presents a significant challenge because the sole source of authentic wellbore production data for training is sparse.In response to this challenge,this work introduces a novel architecture called physics-informed neural network based on domain decomposition(PINN-DD),aiming to effectively utilize the sparse production data of wells for reservoir simulation with large-scale systems.To harness the capabilities of physics-informed neural networks(PINNs)in handling small-scale spatial-temporal domain while addressing the challenges of large-scale systems with sparse labeled data,the computational domain is divided into two distinct sub-domains:the well-containing and the well-free sub-domain.Moreover,the two sub-domains and the interface are rigorously constrained by the governing equations,data matching,and boundary conditions.The accuracy of the proposed method is evaluated on two problems,and its performance is compared against state-of-the-art PINNs through numerical analysis as a benchmark.The results demonstrate the superiority of PINN-DD in handling large-scale reservoir simulation with limited data and show its potential to outperform conventional PINNs in such scenarios.

Uniformity evaluation and optimization of fluid flow characteristics in a seven-strand tundish

The effect of flow control devices（FCDs） on the uniformity of flow characteristics in a seven-strand symmetrical trapezoidal tundish was studied using both an experimental 1：2.5 hydraulic model and a numerical simulation of a 1：1 geometric model.The variation coefficient（CV） was defined to evaluate the flow uniformity of the seven-strand tundish.An optimized FCD configuration was proposed on the basis of the evaluation of experimental results.It is concluded that a turbulence inhibitor（TI） and U-type dam are essential to improve the uniformity of fluid flow in the seven-strand tundish.In addition,the configuration of inclination T-type dams with a height of 200 mm between the second and third strands and with a height of 300 mm between the third and fourth strands can minimize the proportion of dead zone.After optimizing the configuration of FCDs,the variation coefficient reduces below 20%of the mean value,and the average proportion of dead zone is just 14.6%;in addition,the temperature fluctuation between the strands could be controlled within 0.6 K.In summary,the uniformity of flow and temperature in the seven-strand tundish is greatly improved.

Modeling transient fluid flow and heat transfer phenothena in stationary pulsed current TIG weld pool

A mathematical model is presented to describe transient behavior of heat transfer and fluid flow in stationary pulsed current tungsten inert gas (PC-TIG) weld pool, which considers three kinds of driving, forces for weld pool convection, i,e. buoyancyforce, electromagnetic force and surface tension force. furthermore. the effect of vaporization heat flux at the free surface of weld pool and the temperature coefficient of surface tenston which is a function of temperatuer and composition are considered in the model In order to accelerate the convergence of iteration the AST(additive source term)method which concerns with the thermal energv boundary conditions is extended successfully to deal with the momentum boundary conditions by which the transient momentum equation and energy equation are mutually coupled. At the same time. ADI (Alternating direction implicit) method and DBC (double blocks correction) technque are employed to solve the finite difference equations. The results of numerical simulation demonstrate the transient behavior of PC-TIG weld pool, as well as the periodic variation of fluid flow and heat transfer with the periodic variation of welding current in stationary PC-TIG weld pool. The theoretical predictions based on this model are, shown to be in good accordance with the experimental measurements.

Hydrodynamics and Heat Transfer Analysis of Airflow in a Sinusoidally Curved Channel

For heat transfer enhancement in heat exchangers,different types of channels are often tested.The performance of heat exchangers can be made better by considering geometry composed of sinusoidally curved walls.This research studies the modeling and simulation of airflow through a 2πunits long sinusoidally curved wavy channel.For the purpose,two-dimensional Navier Stokes equations along with heat equations are under consideration.To simulate the fluid flow problem,the finite element-based software COMSOL Multiphysics 5.4 is used.The parametric study for Reynolds number from Re=100 to Re=1000 and the period of vibration P from 0 to 5 are observed.The surface plots,streamline patterns,contours,and graphs are presented for the velocity field magnitude,temperature,and pressure against the Reynolds number as well as period of vibration.The results are compared with various literature.It is found that due to the creation of periodic contraction regions the velocity magnitude of the flow is continuously increasing with the increase of Reynolds number,on the contrary the pressure is decreasing from inlet to outlet of the channel.Also,a periodic variation in the pressure distribution along the vibrating boundaries has been found with an average increase of 500%for the high Reynolds number.A novel work was done by expressing the rotation rate per second in terms of local Reynolds number for the recirculating regions found due to the periodic oscillation of the boundaries.The average temperature near the outlet where a fixed temperature is imposed initially is decreasing with an increase in Reynolds number.The convection process is weakened due to an increase of periodic vibration of boundaries.

Characteristics and generation of elastic turbulence in a three-dimensional parallel plate channel using direct numerical simulation

Direct numerical simulations（DNSs） of purely elastic turbulence in rectilinear shear flows in a three-dimensional（3D） parallel plate channel were carried out,by which numerical databases were established.Based on the numerical databases,the present paper analyzed the structural and statistical characteristics of the elastic turbulence including flow patterns,the wall effect on the turbulent kinetic energy spectrum,and the local relationship between the flow motion and the microstructures＇ behavior.Moreover,to address the underlying physical mechanism of elastic turbulence,its generation was presented in terms of the global energy budget.The results showed that the flow structures in elastic turbulence were 3D with spatial scales on the order of the geometrical characteristic length,and vortex tubes were more likely to be embedded in the regions where the polymers were strongly stretched.In addition,the patterns of microstructures＇ elongation behave like a filament.From the results of the turbulent kinetic energy budget,it was found that the continuous energy releasing from the polymers into the main flow was the main source of the generation and maintenance of the elastic turbulent status.

Lattice Boltzmann simulation of fluid flow through coal reservoir's fractal pore structure

The influences of fractal pore structure in coal reservoir on coalbed methane(CBM) migration were analyzed in detail by coupling theoretical models and numerical methods.Different types of fractals were generated based on the construction thought of the standard Menger Sponge to model the 3D nonlinear coal pore structures.Then a correlation model between the permeability of fractal porous medium and its pore-size-distribution characteristics was derived using the parallel and serial modes and verified by Lattice Boltzmann Method(LBM).Based on the coupled method,porosity(ф),fractal dimension of pore structure(Db),pore size range(rmin,rmax) and other parameters were systematically analyzed for their influences on the permeability(ф) of fractal porous medium.The results indicate that:① the channels connected by pores with the maximum size(rmax) dominate the permeability,approximating in the quadratic law;② the greater the ratio of r max and r min is,the higher is;③ the relationship between D b and follows a negative power law model,and breaks into two segments at the position where Db ≌2.5.Based on the results above,a predicting model of fractal porous medium permeability was proposed,formulated as k=cfrnmax,where C and n(approximately equal to 2) are constants and f is an expression only containing parameters of fractal pore structure.In addition,the equivalence of the new proposed model for porous medium and the Kozeny-Carman model k=Crn was verified at Db =2.0.

Modeling and Generating Realistic Background Traffic by Hybrid Approach

One of the key challenges in largescale network simulation is the huge computation demand in fine-grained traffic simulation.Apart from using high-performance computing facilities and parallelism techniques,an alternative is to replace the background traffic by simplified abstract models such as fluid flows.This paper suggests a hybrid modeling approach for background traffic,which combines ON/OFF model with TCP activities.The ON/OFF model is to characterize the application activities,and the ordinary differential equations(ODEs) based on fluid flows is to describe the TCP congestion avoidance functionality.The apparent merits of this approach are(1) to accurately capture the traffic self-similarity at source level,(2) properly reflect the network dynamics,and(3) efficiently decrease the computational complexity.The experimental results show that the approach perfectly makes a proper trade-off between accuracy and complexity in background traffic simulation.

Modeling and simulation of chemically reacting flows in gas-solid catalytic and non-catalytic processes

This paper gives an overview of the recent development of modeling and simulation of chemically react- ing flows in gas-solid catalytic and non-catalytic processes. General methodology has been focused on the Eulerian-Lagrangian description of particulate flows, where the particles behave as the catalysts or the reactant materials. For the strong interaction between the transport phenomena （i.e., momentum, heat and mass transfer） and the chemical reactions at the particle scale, a cross-scale modeling approach, i.e., CFD-DEM or CFD-DPM, is established for describing a wide variety of complex reacting flows in multiphase reactors, Representative processes, including fluid catalytic cracking （FCC）, catalytic conversion of syngas to methane, and coal pyrolysis to acetylene in thermal plasma, are chosen as case studies to demonstrate the unique advantages of the theoretical scheme based on the integrated particle-scale information with clear physical meanings, This type of modeling approach provides a solid basis for understanding the multiphase reacting flow problems in general.

Numerical estimation of bank-propeller-hull interaction effect on ship manoeu-vring using CFD method

This paper presents a numerical investigation of ship manoeuvring under the combined effect of bank and propeller. The incompressible turbulent flow with free surface around the self-propelled hull form is simulated using a commercial CFD software （ANSYS-FLUENT）. In order to estimate the influence of the bank-propeller effect on the hydrodynamic forces acting on the ship, volume forces representing the propeller are added to Navier-Stokes equations. The numerical simulations are carried out using the equivalent of experiment conditions. The validation of the CFD model is performed by comparing the numerical results to the availa- ble experimental data. For this investigation, the impact of Ship-Bank distance and ship speed on the bank effect are tested with and without propeller. An additional parameter concerning the advance ratio of the propeller is also tested.