INTERACTIVE CONTROL OF INTERACTIVE CONTROL OF LARGE-SCALE SIMULATIONSLARGE-SCALE SIMULATIONS

Richard E. EwingInstitute for Scientific Computation

Texas A&M University

Robert C. SharpleyIndustrial Mathematics Institute

University of South Carolina

LEAKY UNDERGROUND LEAKY UNDERGROUND STORAGE TANKSSTORAGE TANKS

NEED TO DEVELOP MONITORINGAND CLEAN UP METHODS

UNSATURATED ZONE

SATURATED ZONE

AQUIFER

BIOREMEDIATION STRATEGIESBIOREMEDIATION STRATEGIES

MMACROSCALEACROSCALE

MMESOSCALEESOSCALE

INJECTION RECOVERY

FLOW

MMICROSCALEICROSCALE

GROWTH MECHANISMS

AttachmentDetachmentReproductionAdsorptionDesorptionFiltrationInteraction

INPUTSubstrateSuspended CellsOxygen

PETROLEUM APPLICATIONS PETROLEUM APPLICATIONS

GAS

OIL

WATERFAULT

SALT

DOME

MODELING PROCESSMODELING PROCESS

PHYSICALPHYSICALPROCESSPROCESS

PHYSICALPHYSICALMODELMODEL

MATHEMATICALMATHEMATICALMODELMODEL

OUTPUTOUTPUTVISUALIZATIONVISUALIZATION

DISCRETEDISCRETEMODELMODEL

NUMERICALNUMERICALMODELMODEL

NEED FOR SIMULATIONNEED FOR SIMULATION

DDEVELOP EVELOP B BETTER ETTER UUNDERSTANDING OF NDERSTANDING OF NNONLINEAR ONLINEAR BBEHAVIOREHAVIOR

– CCOMPUTATIONAL OMPUTATIONAL LLABORATORY ABORATORY EEXPERIMENTSXPERIMENTS

– UUNDERSTAND NDERSTAND SSENSITIVITIES OF ENSITIVITIES OF PPARAMETERSARAMETERS

– IISOLATE SOLATE PPHENOMENA THEN HENOMENA THEN CCOMBINEOMBINE

SSCALECALE UUP P IINFORMATION AND NFORMATION AND UUNDERSTANDINGNDERSTANDING

– PPORE ORE LLABORATORY ABORATORY FFIELDIELD

OOBTAIN BTAIN BBOUNDING OUNDING CCALCULATIONSALCULATIONS DDEVELOP EVELOP PPREDICTIVE REDICTIVE CCAPABILITIESAPABILITIES

– OOPTIMIZATION AND PTIMIZATION AND CCONTROLONTROL

TRANSPORT IN POROUS MEDIATRANSPORT IN POROUS MEDIA

PPHYSICAL HYSICAL RRELATIONS:ELATIONS:

CCONSTITUTIVE ONSTITUTIVE LLAW (AW (DD’ ARCY)’ ARCY)

CCONSERVATION OF ONSERVATION OF MMASSASS

CCOMPONENT OMPONENT BBALANCESALANCES

EEQUATIONS OF QUATIONS OF SSTATETATE

TTHERMAL HERMAL BBALANCEALANCE

u T

div ut

S q

t

f c div u f c D c q c1 2

TRANSPORT IN POROUS MEDIATRANSPORT IN POROUS MEDIA(CONTINUED)(CONTINUED)

AARE RE UUSUALLY SUALLY UUNKNOWNNKNOWN

– PPARAMETER ARAMETER EESTIMATION / STIMATION / IINVERSE NVERSE PPROBLEMSROBLEMS

PPARAMETERS ARAMETERS AARE RE HHETEROGENEOUS AT ETEROGENEOUS AT VVARIOUS ARIOUS LLENGTHSENGTHS

– NNEED EED EEFFECTIVE FFECTIVE PPARAMETERS / ARAMETERS / EEQUATIONSQUATIONS

NNEED EED AACCURATE CCURATE FFLUID LUID VVELOCITIESELOCITIES

– MMIXED IXED FFINITE INITE EELEMENT LEMENT MMETHODSETHODS

IIMPORTANCE OF MPORTANCE OF TTRANSPORTRANSPORT

– EEULERIAN ULERIAN LLAGRANGIAN AGRANGIAN MMETHODSETHODS

CCOUPLED OUPLED NNONLINEAR ONLINEAR SSYSTEMSYSTEMS

– EEFFECTIVE FFECTIVE LLINEARIZATION / INEARIZATION / SSOLUTION OLUTION MMETHODSETHODS

, , , , ,T S f f D1 2

TWO-PHASE FLOWTWO-PHASE FLOW

DD’ARCY’S ’ARCY’S LLAW:AW:

MMASS ASS BBALANCE:ALANCE:

1SS , ppp

nw,i , quSt

nw,i , zgpk

u

wnwnc

iiiiii

iii

rii

wn,

K

wPcn w,

Sw

n

Sw

k rn

k rw

w = Wetting Phase n = Nonwetting Phase

PPHYSICALHYSICAL

PPROCESSROCESS

IDENTIFICATION (INVERSE) PROBLEMIDENTIFICATION (INVERSE) PROBLEM

DDETERMINE ETERMINE SSUITABLE UITABLE MMATHEMATICAL ATHEMATICAL MMODELODEL

EESTIMATE STIMATE PPARAMETERS ARAMETERS WWITHIN ITHIN MMATHEMATICAL ATHEMATICAL MMODELODEL

IINPUTSNPUTS OOUTPUTSUTPUTS

OOUTPUTSUTPUTSIINPUTSNPUTS

MMEASUREMENTSEASUREMENTS

MMATHEMATICALATHEMATICAL

MMODELODEL

PPHYSICALHYSICAL

PPROCESSROCESS

IDENTIFICATION (INVERSE) PROBLEMIDENTIFICATION (INVERSE) PROBLEM

DDETERMINE ETERMINE SSUITABLE UITABLE MMATHEMATICAL ATHEMATICAL MMODELODEL

EESTIMATE STIMATE PPARAMETERS ARAMETERS WWITHIN ITHIN MMATHEMATICAL ATHEMATICAL MMODELODEL

IINPUTSNPUTS OOUTPUTSUTPUTS

OOUTPUTSUTPUTSIINPUTSNPUTS

MMEASUREMENTSEASUREMENTS

MMATHEMATICALATHEMATICAL

MMODELODEL

LARGE SCALE INTERACTIVE LARGE SCALE INTERACTIVE APPLICATIONS ON REMOTE APPLICATIONS ON REMOTE

SUPERCOMPUTERSSUPERCOMPUTERS

Model Development and FormulationModel Development and Formulation Coupled Flow and Transport Codes with Complex Coupled Flow and Transport Codes with Complex

Boundary ConditionsBoundary Conditions Numerical Discretization and Parallel Algorithm Numerical Discretization and Parallel Algorithm

DevelopmentDevelopment MPP Code DevelopmentMPP Code Development Field Testing and Production RunsField Testing and Production Runs User Environments and Visualization ToolsUser Environments and Visualization Tools

Need for Interactive tracking and steeringNeed for Interactive tracking and steering

PRIMARY RESEARCH TEAMPRIMARY RESEARCH TEAM

Texas A&MTexas A&M

– Richard EwingRichard Ewing– Steve JohnsonSteve Johnson– Hao LuHao Lu– Joseph PasciakJoseph Pasciak

South CarolinaSouth Carolina

– Robert Sharpley– Ronald DeVore– L. Scott Johnson

SAVANNAH RIVER SITESAVANNAH RIVER SITE

Difficult topography Highly Heterogeneous

Soils Saturated and

Unsaturated Flows Reactions with disparate

time scale Transient/Mixed

Boundary Conditions

Software Engineering– Motif with OpenGL / MESA rendering areas– Self-Interrupting Work Stack

3D Pre-processing– Data set construction – GIS Import of Field Data– Data Verification

Post-processing– Data Verification– Model and Algorithm Verification

Controller library coupling

G3D - GRAPHICS FRONT-ENDG3D - GRAPHICS FRONT-END

GRAPHICS PRE-PROCESSINGGRAPHICS PRE-PROCESSING

3D grid creation and editing

Material properties

Initial conditions

Time dependent boundary conditions

Multiple views

GRAPHICS POST-PROCESSINGGRAPHICS POST-PROCESSING

Multiple vector/scalar fields

Time animation

Multiple slices/Iso-surfaces

Stereo rendering, lighting models

Overlay images for orientation

Volume rendering

Hierarchical Representations

CONTROLLER LIBRARYCONTROLLER LIBRARY

User callable Client - Server– server MPP - client workstations

Non-interrupt approach Controller - “Graphics” Node– processes client requests and performs scale analysis/compression

MPI Message passing Remote procedure calls

COMPRESSION MODULE FOR COMPRESSION MODULE FOR ENCODED TRANSMISSION OVER ENCODED TRANSMISSION OVER

CONGESTED NETWORKSCONGESTED NETWORKS Wavelet based processing

– Fast decomposition/reconstruct– Nonlinear approximation in various metrics– Compression– Feature identification at various scales– Scale up/scale down

Progressive transmission – Lossy to lossless – Adaptive local spatial resolution

Scattered data assimilation and denoising

INTERACTIVE CONTROL OF INTERACTIVE CONTROL OF LARGE-SCALE SIMULATIONSLARGE-SCALE SIMULATIONS

Richard E. EwingInstitute for Scientific Computation

Texas A&M University

Robert C. SharpleyIndustrial Mathematics Institute

University of South Carolina