DISCRETE ELEMENT SIMULATIONS OF WATER FLOW THROUGH GRANULAR SOILS

Similar documents
Fluid-soil multiphase flow simulation by an SPH-DEM coupled method

Studies on flow through and around a porous permeable sphere: II. Heat Transfer

Discrete particle analysis of 2D pulsating fluidized bed. T. Kawaguchi, A. Miyoshi, T. Tanaka, Y. Tsuji

DEM-PFV analysis of solid-fluid transition in granular sediments under the action of waves

dynamics of f luids in porous media

Micro-scale modelling of internally

Prof. B V S Viswanadham, Department of Civil Engineering, IIT Bombay

Chapter 7 Permeability and Seepage

An Immersed Boundary Method for Computing Anisotropic Permeability of Structured Porous Media

DEVELOPMENT OF A NUMERICAL APPROACH FOR SIMULATION OF SAND BLOWING AND CORE FORMATION

Hydraulic conductivity of granular materials

In all of the following equations, is the coefficient of permeability in the x direction, and is the hydraulic head.

A Baseline Drag Force Correlation for CFD Simulations of Gas-Solid Systems

Table of Contents. Preface... xiii

1 Modeling Immiscible Fluid Flow in Porous Media

Study on Estimation of Hydraulic Conductivity of Porous Media Using Drag Force Model Jashandeep Kaur, M. A. Alam

DYNAMICS OF LIQUEFIED SEDIMENT FLOW. Advances in Natural and Technological Hazards Research Vol. 19

Water in Soil Sections in Craig

EMPIRICAL ESTIMATION OF DOUBLE-LAYER REPULSIVE FORCE BETWEEN TWO INCLINED CLAY PARTICLES OF FINITE LENGTH

JAEA-Research m 2) 6

*** ***! " " ) * % )!( & ' % # $. 0 1 %./ +, - 7 : %8% 9 ) 7 / ( * 7 : %8% 9 < ;14. " > /' ;-,=. / ١

Evaluation of undrained response from drained triaxial shear tests: DEM simulations and Experiments

The Derivation of a Drag Coefficient Formula from Velocity-Voidage Correlations

Permeability in Soils

Instructor : Dr. Jehad Hamad. Chapter (7)

NUMERICAL MODELING OF FLOW THROUGH DOMAINS WITH SIMPLE VEGETATION-LIKE OBSTACLES

Time Rate of Consolidation Settlement

Permeability of Dual-Structured Porous Media

Darcy's Law. Laboratory 2 HWR 531/431

RATE OF FLUID FLOW THROUGH POROUS MEDIA

CENTRIFUGE MODELING OF PILE FOUNDATIONS SUBJECTED TO LIQUEFACTION-INDUCED LATERAL SPREADING IN SILTY SAND

Distinct Element Modeling of Coupled Chemo-Mechanical Compaction of Rock Salt

A discrete element analysis of elastic properties of granular materials

Simulation of Particulate Solids Processing Using Discrete Element Method Oleh Baran

6.2 Governing Equations for Natural Convection

Convective flow of two immiscible viscous fluids using Brinkman model

DEM 6 6 th International Conference on Discrete Element Methods and Related Techniques

Liquefaction is the sudden loss of shear strength of a saturated sediment due to earthquake shaking. Nisqually earthquake 02/28/2001: Olympia, WA

COMPUTATIONAL STUDY OF PARTICLE/LIQUID FLOWS IN CURVED/COILED MEMBRANE SYSTEMS

SIMULATION OF FLOW IN A RADIAL FLOW FIXED BED REACTOR (RFBR)

Surta, Osaka 565 (Japan)

Chapter 3 Permeability

ENTROPY GENERATION IN HEAT AND MASS TRANSFER IN POROUS CAVITY SUBJECTED TO A MAGNETIC FIELD

Simulation of Cyclic Direct Simple Shear Loading Response of Soils Using Discrete Element Modeling


TALLINN UNIVERSITY OF TECHNOLOGY, DIVISION OF PHYSICS 13. STOKES METHOD

Micro-macro Modeling of Particle Crushing Based on Branch Lengths. Esmaeel Bakhtiary 1, and Chloé Arson 2

Three-Dimensional Discrete Element Simulations of Direct Shear Tests

Numerical and Analytical Study of Exhaust Gases Flow in Porous Media with Applications to Diesel Particulate Filters

16 Rainfall on a Slope

The performance of drag models on flow behaviour in the CFD simulation of a fluidized bed

EXPERIMENTAL AND NUMERICAL STUDIES ON INERTIAL EFFECT IN POROUS MEDIA FLOW

EXAMINING THE BEHAVIORS OF SANDY AND SILTY SEABED UNDER WAVE ACTIONS

FLUID MECHANICS PROF. DR. METİN GÜNER COMPILER

Paper No. : 04 Paper Title: Unit Operations in Food Processing Module- 18: Circulation of fluids through porous bed

Effects of Viscous Dissipation on Unsteady Free Convection in a Fluid past a Vertical Plate Immersed in a Porous Medium

Wall Effects in Convective Heat Transfer from a Sphere to Power Law Fluids in Tubes

Seepage flow analysis in gravity and in variable acceleration fields

A correlation for the lift-off of many particles in plane Poiseuille flows of Newtonian fluids

This document is downloaded from DR-NTU, Nanyang Technological University Library, Singapore.

INVESTIGATION ON THE DRAG COEFFICIENT OF SUPERCRITICAL WATER FLOW PAST SPHERE-PARTICLE AT LOW REYNOLDS NUMBERS

GATE PSU. Chemical Engineering. Fluid Mechanics. For. The Gate Coach 28, Jia Sarai, Near IIT Hauzkhas, New Delhi 16 (+91) ,

Basic concepts in viscous flow

SIMULATION OF THERMAL CHARACTERISTICS OF RADIATORS USING A POROUS MODEL. YETSAN Auto Radiator Co. Inc Çorum, Turkey NOMENCLATURE

Fundamentals of Fluid Dynamics: Elementary Viscous Flow

Prediction Of Minimum Fluidization Velocity And Bed Pressure Drop In Non-circular Gas-solid Fluidized Bed

Forced Convection Heat Transfer Enhancement by Porous Pin Fins in Rectangular Channels

Fluid Particle Interactions Basics

ISMS Paper No Modelling the impact of particle flow on rigid structures: experimental and numerical investigations

Chemical and Biomolecular Engineering 150A Transport Processes Spring Semester 2017

STEADY SOLUTE DISPERSION IN COMPOSITE POROUS MEDIUM BETWEEN TWO PARALLEL PLATES

150A Review Session 2/13/2014 Fluid Statics. Pressure acts in all directions, normal to the surrounding surfaces

4 Undrained Cylindrical Cavity Expansion in a Cam-Clay Medium

NON-DARCY POROUS MEDIA FLOW IN NO-SLIP AND SLIP REGIMES

Permeability of Sandy Soil CIVE 2341 Section 2 Soil Mechanics Laboratory Experiment #5, Laboratory #6 SPRING 2015 Group #3

Particle flow simulation of sand under biaxial test

Fundamentals of Fluid Mechanics

1 FLUIDS AND THEIR PROPERTIES

This report shows the capabilities of Tdyn for modelling the fluid flow through porous media.

M98-P2 (formerly C98-P1) Non-Newtonian Fluid Flow through Fabrics Matthew W. Dunn Philadelphia University

Particle Dynamic Simulation of Free Surface Granular Flows

Numerical Modeling of Porous Flow in Fractured Rock and Its Applications in Geothermal Energy Extraction

Module 2 Lecture 9 Permeability and Seepage -5 Topics

Differential relations for fluid flow

NUMERICAL AND EXPERIMENTAL ANALYSIS OF SEEPAGE BENEATH A MODEL OF A GRAVITY DAM

Flow Distribution inside an Electrostatic Precipitator: Effects of Uniform and Variable Porosity of Perforated Plate

Analysis of pore-fluid pressure gradient and effective vertical-stress gradient distribution in layered hydrodynamic systems

Shear dynamics simulations of high-disperse cohesive powder

Darcy s Law. Darcy s Law

Towards hydrodynamic simulations of wet particle systems

Glacier Hydrology II: Theory and Modeling

DEM modeling of penetration test in static and dynamic conditions

The role of a movable sandy-bed in modelling open-channel flow

Minimum fluidization velocity, bubble behaviour and pressure drop in fluidized beds with a range of particle sizes

Supporting Information. Technique for real-time measurements of endothelial permeability in a

Discrete Element Modelling of a Reinforced Concrete Structure

Review of Fluid Mechanics

The Use of Lattice Boltzmann Numerical Scheme for Contaminant Removal from a Heated Cavity in Horizontal Channel

Available online at ScienceDirect. Procedia Engineering 103 (2015 )

Lecture 30 Review of Fluid Flow and Heat Transfer

Transcription:

15th ASCE Engineering Mechanics Conference June 2-5, 2002, Columbia University, New York, NY EM 2002 DISCRETE ELEMENT SIMULATIONS OF WATER FLOW THROUGH GRANULAR SOILS Usama El Shamy 1, Student Member, ASCE, Mourad Zeghal 2, Member, ASCE, Mark Shephard 3, Member, ASCE, Ricardo Dobry 4, Member, ASCE, Jacob Fish 5, Member, ASCE, and Tarek Abdoun 6, Member, ASCE ABSTRACT This paper presents a coupled micro-mechanical technique to model pore water flow and solid phase deformation of granular soils. The fluid motion is idealized using averaged Navier-Stokes equations, and the discrete element method (DEM) is employed to model the assemblage of granular particles. The fluid-particle interactions are provided by established semi-empirical relationships. The developed model is used to simulate a range of seepage conditions through idealized granular samples. The conducted simulations are validated using published experimental results. Keywords: Discrete elements, pore water flow, fluid dynamics, granular soils. INTRODUCTION The dynamic flow of water and other viscous fluids through granular soils is commonly modeled using Darcy s law with time-independent permeability coefficients. Experimental studies show that this law is not valid for large nonlaminar fluid velocities which may develop under high hydraulic gradients (e.g., Burmister 1954). Furthermore, particle rearrangements leading to substantial variations in porosity are prevalent during soil liquefaction and other extreme flow driven phenomena, such as piping. These variations in porosity affect significantly the soil hydraulic conductivity and stiffness characteristics. Experimental investigations furnish only macroscopic phenomenological characterization of these complex response mechanism. 1 Civ. and Env. Engrg. Dept., School of Engrg., Rensselaer Polytechnic Institute,110 8th St., Troy, NY 12180. E-mail: elshau@rpi.edu. 2 Civ. and Env. Engrg. Dept., School of Engrg., Rensselaer Polytechnic Institute,110 8th St., Troy, NY 12180. E-mail: zeghal@rpi.edu 3 Civ. and Env. Engrg. Dept., School of Engrg., School of Engrg., Rensselaer Polytechnic Institute,110 8th St., Troy, NY 12180. E-mail: shepard@scorec.rpi.edu. 4 Civ. and Env. Engrg. Dept., School of Engrg., School of Engrg., Rensselaer Polytechnic Institute,110 8th St., Troy, NY 12180. E-mail: dobryr@rpi.edu. 5 Civ. and Env. Engrg. Dept., School of Engrg., School of Engrg., Rensselaer Polytechnic Institute,110 8th St., Troy, NY 12180. E-mail: fishj@rpi.edu. 6 Civ. and Env. Engrg. Dept., School of Engrg., School of Engrg., Rensselaer Polytechnic Institute,110 8th St., Troy, NY 12180. E-mail: abdout@rpi.edu.

Microscopic numerical analyses provide effective alternative tools to assess the hydraulic and deformation characteristics of granular soils in a coupled fashion. Pore-scale models of fluid flow through porous media (e.g., Zhu et al. 1999) generally provide useful microscopic details such as drag forces and actual flow pattern, but present a significant computational challenge. Herein, pore water flow is idealized using averaged Navier- Stokes equations which are coupled with a discrete element model of the solid phase, or soil particulate matrix (Tsuji et al. 1993). Such coupled formulation is computationally tractable and provides adequate level of information on pore water flow. This paper presents preliminary results on an ongoing research effort to simulate the micro-mechanical fluid-particle response under deformation and extreme flow conditions such as liquefaction and piping. MICRO-MECHANICAL MODEL OF SATURATED GRANULAR SOILS Fluid Phase The pore fluid motion is modeled using averaged Navier-Stokes equations (Anderson and Jackson 1967). For an inviscid incompressible fluid, this model consists of: Continuity Equation: @n @t + @(nu i) =0 (1) @x i Momentum Equations: @(nu i ) @t + @(nu iu j ) @x j = n ρ @p @x i + nρg i + d i (2) where x i (i = 1; 2; 3) are Cartesian coordinates, n is porosity, u i is fluid velocity, ρ is fluid density, p is fluid pressure, and g i is gravitational force per unit mass. The terms d i (i =1; 2; 3) represent the resultant of the drag forces exerted by the fluid on the particles. Semi-empirical relationships are commonly used to quantify these interaction terms. The equations proposed by Ergun (1952), and Wen and Yu (1966) are used in this study. The averaged Navier-Stokes equations (Eqs. 1 and 2) are discretized using a finite volume technique on a staggard grid to ensure stability (Patankar 1980). Solid Phase Granular soils consist of an assemblage of discontinuous particles which can be modeled effectively using the discrete element method, DEM (Cundall and Strack 1979). In DEM models the particles are rigid but can overlap. The interaction forces between any two particles are dictated by contact laws and are direct functions of the overlap and the relative movement at the contact. Details of the employed PFC3D DEM code and associated contact law model are given in Itasca (1999). Coupled Response An explicit time-advancing scheme is used to evaluate the coupled fluid-particle response. The flow domain is discretized into parallelepiped cells and averaged Navier-Stokes equations are solved using a finite volume technique (as mentioned above). Average drag forces are evaluated for each individual cell based on mean values of porosity, as well as of particle velocities and sizes within this cell. These drag forces are then applied to individual particles proportionally to their volumes. Deformation of the solid phase subjected to the drag forces along with any external loads is subsequently computed using the DEM technique. 2

Porous stone Free surface boundary Impermeable wall Porous stone Increase in base water pressure ( p) Increase in base water pressure ( p) (a) (b) FIG. 1. Idealized soil samples NUMERICAL SIMULATIONS Basic flow problems are used to assess the capabilities of the employed model. Several numerical simulations were performed to investigate the range of validity of Darcy s law. First, the flow of water through a confined soil sample under constant hydraulic gradient is analyzed in a setup similar to laboratory constant-head permeability tests (Fig. 1a). Second, a numerical simulation is conducted on a soil sample with a free surface and subjected to an upward flow (Fig. 1b). In these analyses, water is assumed to have a viscosity of 0.001 Pa.sec, and a density of 1000 kg/m 3. Validity of Darcy s Law The discrete element code PFC3D is used to generate arrays of spherical uniformly-sized particles having different porosities (ranging between the limiting values of 26.0% and 47.6%, Lambe and Whitman 1969). Figure 2 shows the discharge velocities calculated for a range of hydraulic gradients of practical interest. For relatively small particles sizes (less than 1 mm in diameter) Darcy s law remains valid up to at least a hydraulic gradient of 1. For larger particles (1 mm and 2 mm in diameter in Fig. 2), deviation from Darcy s law is observed for hydraulic gradients less than 1. This deviation becomes more pronounced in high porosity arrays and consistently occurred for Reynolds number ranging between about 1 to 4. This behavior is in agreement with experimental observations of Scheidegger (1969) and Lindquist (1933). Upward Flow through a Sand Bed An upward flow simulation is conducted using a soil sample composed of 10,664 randomly distributed spherical particles with diameters ranging from 0.6 mm to 1.4 mm. The sample is subjected first to a hydrostatic water pressure (to account for buoyancy) and then to an upward hydraulic gradient of 0.1. Figure 3 shows the time history of the average vertical effective 3

0.05 Particle diameter=2 mm Particle diameter=1 mm Discharge velocity (m/s) 0.04 0.03 0.02 0.01 39% 33% 26% 39% 33% 26% 0 0 0.2 0.4 0.6 0.8 1 x 10 4 Particle diameter=0.1 mm 0.2 0.4 0.6 0.8 1 Particle diameter=0.06 mm Discharge velocity (m/s) 2 1 39% 33% 26% 0 0 0.2 0.4 0.6 0.8 1 39% 33% 26% 0.2 0.4 0.6 0.8 1 FIG. 2. Variation of discharge velocity with hydraulic gradient for idealized soil samples of different particle sizes stress evaluated from the inter-particle contact forces. As shown in this figure, and as expected, a significant decrease in vertical stresses is associated with buoyancy and applied upward flow. Analyses of soil response under critical flow conditions are underway and will be published elsewhere. CONCLUSION This paper presented a computational micro-mechanical model for coupled analysis of pore water flow and deformation of granular assemblies. The results of numerical simulations of water seepage through soils are found to be consistent with published experimental observations. Intersticial water flow deviates from Darcy s law when the Reynolds number exceeds a value ranging between about 1 to 4. Research is currently underway to investigate the complex fluid-particle response mechanism under extreme conditions such as liquefaction and piping. ACKNOWLEDGEMENT This research was supported by the National Science Foundation, grant number CMS- 4

0 z/h=0.08 Average vertical effective stress (Pa) 100 200 300 400 500 600 z/h=0.25 z/h=0.42 z/h=0.58 z/h=0.75 z/h=0.92 700 Application of hydrostatic pressure Application of hydraulic gradient of 0.10 800 0 1 2 3 Time (sec) 4 5 6 x 10 3 FIG. 3. Time-history of average vertical effective stresses (z is depth below soil surface and H is soil sample height). 0084591. This support is gratefully acknowledged. REFERENCES Anderson, T. and Jackson, R. (1967). A fluid mechanical description of fluidized beds. Ind. Eng. Chem. Fundam., 6(4), 527 539. Burmister, D. (1954). Principles of permeability testing of soils. Proc., Symp. Permeability of Soils, Fifty-seventh Annual Meeting, Chicago, IL. 3 20. Cundall, P. and Strack, O. (1979). A discrete numerical model for granular assemblies. Geotechnique, 29(1), 47 65. Ergun, S. (1952). Fluid flow through packed columns. Chem. Engr. Prog., 43(2), 89 94. Itasca (1999). Particle Flow Code, PFC3D, release 2.0. Itasca Consulting Group, Inc., Minneapolis, Minesota. Lambe, T. and Whitman, R. (1969). Soil Mechanics. John Wiley and Sons. Lindquist, E. (1933). On the flow of water through porous soil. Proc., 1er Congres des Grands Barrages, Commission internationale des grands barrages, Stockholm. 81 101. Patankar, S. (1980). Numerical Heat Transfer and Fluid Flow. Taylor and Francis. 5

Scheidegger, A. (1969). The physics of flow through porous media. University of toronto press, 3rd edition. Tsuji, Y., Kawaguchi, T., and Tanaka, T. (1993). Discrete prticle simulation of twodimensional fluidized bed. Powder Technology, 77, 79 87. Wen, C. and Yu, Y. (1966). Mechanics of fluidization. Chem. Engng. Prog. Symp. Ser., 62(62), 100. Zhu, Y., Fox, P., and Morris, J. (1999). A pore-scale numerical model for flow through porous media. Int. J. Numer. Anal. Meth. Geomech., 23, 881 904. 6