Cyber-enabledCyber-enabledDiscovery and Discovery and

Innovation (CDI)Innovation (CDI)Objective:

Enhance American competitiveness by enabling innovation through the use of computational

thinking

(concepts, methods, models, algorithms, tools)

CDI is Unique within NSFCDI is Unique within NSF

five-year initiativeall directorates, programmatic offices involvedto create revolutionary science and engineering research outcomes made possible by innovations and advances in computational thinkingemphasis on bold, multidisciplinary activitiesradical, paradigm-changing science and engineering outcomes through computational thinking

CDI PhilosophyCDI Philosophy

“Business as usual” need not apply “Projects that make straightforward use of

existing computational concepts, methods, models, algorithms and tools to significantly advance only one discipline should be submitted to an appropriate program in that field instead of to CDI.”  

No place for incremental research

Untraditional approaches and collaborations welcome

NSF Review CriteriaNSF Review Criteria

Intellectual MeritBroader ImpactsNew on Transformative Research: to what extent does the proposed activity suggest and explore creative, original, or potentially transformative concepts?

Additional CDI Review CriteriaAdditional CDI Review CriteriaThe proposal should define a bold multidisciplinary research agenda that, through computational thinking, promises paradigm-shifting outcomes in more than one field of science and engineering. The proposal should provide a clear and compelling rationale that describes how innovations in, and/or innovative use of, computational thinking will lead to the desired project outcomes.  The proposal should draw on productive intellectual partnerships that capitalize upon knowledge and expertise synergies in multiple fields or sub-fields in science or engineering and/or in multiple types of organizations. Potential for extraordinary outcomes, such as revolutionizing entire disciplines, creating entirely new fields, or disrupting accepted theories and perspectives

… as a result of taking a fresh, multi-disciplinary approach. 

Special emphasis will be placed on proposals that promise to enhance competitiveness, innovation, or safety and security in the United States.

Three CDI ThemesThree CDI Themes

CDI seeks transformative research in the following general themes, via innovations in, and/or innovative use of, computational thinking:

 

From Data to Knowledge: enhancing human cognition and generating new knowledge from a wealth of heterogeneous digital data; Understanding Complexity in Natural, Built, and Social Systems: deriving fundamental insights on systems comprising multiple interacting elements;  and Building Virtual Organizations: enhancing discovery and innovation by bringing people and resources together across institutional, geographical and cultural boundaries. 

From Data to KnowledgeFrom Data to Knowledge

Knowledge extraction, noise, statisticsModeling, data assimilation, inverse problemsValidation; model/cyber/domain feedbacksAlgorithms for analysis of large data sets, dimension reductionVisualization, pattern recognition

Understanding Complexity in Understanding Complexity in Natural, Built, and Social Natural, Built, and Social

SystemsSystemsIdentifying general principles and laws that

characterize complexity and capture the essence of complex systems

Attaining the breakthroughs, to overcome these challenges, requires transformative ideas in the following areas:Simulation and Computational ExperimentsMethods, Algorithms, and ToolsNonlinear couplings across multiple scales

Virtual Organizations (VOs)Virtual Organizations (VOs)

Design, development, and assessment of VOsBringing domain needs together with

algorithm development, systems operations, organizational studies, social computing, and interactive design

Flexible boundaries, memberships, and lifecycles, tailored to particular research problems, users and learner needs or tasks of any community, providing opportunities for:Remote accessCollaborationEducation and training

Types of ProjectsTypes of Projects

CDI defines research modalitiesProject size not measured by $$Projects classified by magnitude of effortThree types are defined: Types I (~2 PI, 2 GRA), II (~3 PI, 3 GRA, 1 post-doc), and III (center scale) Type III, center-scale efforts, will not be supported in the first year of CDI

Funding Projections and Profile of NSF-Wide FY2008 Funding Projections and Profile of NSF-Wide FY2008

CompetitionCompetition All NSF directorates and programmatic offices are participating in CDI

FY2008 FY2009 FY2010 FY2011 FY2012 (budgeted) (requested) ------------------ (projected) -----------------

NSF $47.9 M* $100 M $150 M $200 M $250 MMPS $10.4 M $19.05 M ? ? ?

*At least $26 M ($5.2 M MPS) of the $47.9 M ($10.4 M MPS) to be invested in the NSF-wide pooled solicitation for FY08

-----------------------------------------------------------------------------------------Type I (mainly small collaborations): 494 reviewed, 82 invited (16%)

Type II (comparable to focused research groups):743 reviewed, 122 invited (16%)

Full proposals due April 29, 2008; to be reviewed early June

Expect ≈ 30 awards (Type I + Type II) made in July 2008

Stochastic Modeling of Multiphase Transport in Subsurface Porous Media: Motivation and Some Formulations

Thomas F. Russell

National Science Foundation, Division of Mathematical Sciences

David Dean, Tissa Illangasekare, Kevin Barnhart

Multiscale Workshop, Oregon State University, June 25-29, 2007

Philosophy 1 Goal: (motivated, e.g., by DNAPL)

Macro-model of complex multiphase transport – pooling, fingering, etc. – amenable to efficient computation

Pore-scale physics very important, but won’t be seen in that form at macro-scale

Homogenization can yield important insights, but is too restricted

Philosophy 2 For practical purposes, heterogeneous

multiphase effects can’t be characterized deterministically

Micro-scale phenomena show traits of randomness when viewed through a coarser lens

Thus: Consider modeling with stochastic processes

Seek: Stochastic micro-model that yields macro capillary behavior (end effect, etc.), analogous to Einstein-Fokker-Planck

Outline Background on capillary end effect 2-phase stochastic transport equation

for position of nonwetting fluid particle, derived from Itô calculus

Numerical SPDE Capillary barrier effect Channeling / fingering Qualitatively capture experimental

behavior

Summary

• Propose The Use Of The Ito Calculus To Develop Stochastic Differential Equation (SDE) Descriptions Of Saturation Phases

• Test The Ability Of The SDE Model To Capture The Interface Effects Of Plume Development, Such As Pooling, Channeling And Fingering

• Extend This Work To A Nonlinear Up-scaling Methodology

• Develop A Macro-scale Stochastic Theory Of Multiphase Flow And Transport Accounting For Micro-scale Heterogeneities And Interfaces