June 6, 2003

Breakout group 2 -- Analysis, Modeling, and Simulation

Tom Impelluso <impellus@engineering.sdsu.edu>

Jennie Si <si@asu.edu>

Ted Belytschko <tedbelytschko@northwestern.edu>

David Bernstein <bernstdh@jmu.edu>

Shiyi Chen <syc@pegasus.me.jhu.edu>

John Doyle <doyle@cds.caltech.edu>

Greg Fenves <fenves@ce.berkeley.edu>

Jose Fortes <fortes@ufl.edu>

Thomas Harris <thomas.r.harris@vanderbilt.edu>

Marianthi Ierapetritou <marianth@soemail.rutgers.edu>

Grace Lin <gracelin@us.ibm.com>

Andrei Reinhorn <reinhorn@buffalo.edu>

Maria Burka <mburka@nsf.gov>

Delcie Durham <ddurham@nsf.gov>

Miriam Heller <mheller@nsf.gov>

Vittal Rao <vrao@nsf.gov>

 

Jennie Si scribed the first three questions; Tom Impelluso scribed the
last three.

Q1. How will investments in cyberinfrastructure spur major advances in
engineering research and education?

Cyberinfrastructure should not be a progression from the existing
systems since they have not proven themselves robust and reliable (For
example, the high end internet congestion and reliability problems).
Infusion of systematic thinking is important before we invest in
connectivity. The operating system and the Internet are engineering
design problems. However, the current practice emphasizes more on "rapid
prototyping" by sacrificing reliability. The middleware (TCP/IP) issue
is important and should be addressed first. Controls and systems
theorists in the past have contributed to the fundamental groundwork in
distributed computing and networking. They should be an important
partner to get things done right from the ground up.

In the context of cyberinfrastructure, the engineering field should not
only be an end user that provides domain specific applications and
specifies needs from cyberinfrastructure. Cyberinfrastructure should be
an infusion of engineering thinking. Engineers should play an important
and integral role, together with key infrastructure providers and
application end users, to address the cyberinfrastructure issue
systematically. The need for cyberinfrastructure is not just buying more
hardware; it embraces many important aspects of engineering approaches
to deal with congestion control, scheduling, stability, security,
service, performance, simulations and many other important features of a
seamless cyberinfrastrucutre environment. Cyberinfrastructure requires a
robust, reliable, and reconfigurable middleware.

There is a natural and critical need in cyberinfrastructure for network
management designs for two reasons: (1) the cyberinfrastructure is
itself a complex network; (2) a crucial function of cyberinfrastructure
is to assist in the management of other large networks, such as electric
power networks, transportation networks, supply chain, communication
networks, financial networks, major disaster relief system, knowledge
networks, software replication, simulation, and data acquisition of
traditional infrastructures (e.g., bridge and building monitoring,
digital medicine such as surgical simulations) and many more.
Historically, ad hoc domain-specific tools have been used to provide at
least adequate management of such networks, but there are limits to what
can be accomplished with ad hoc tools. There is a need to go beyond the
current operating system and the current TCP/IP. More flexible,
adaptable, and reconfigurable algorithms, software tools, systematic
development of the middleware are needed.

Cyberinfrastructure is naturally an interdisciplinary effort. In regards
to analysis and modeling tools, Cyberinfrastructure should help us
identify common transcending issues, unifying tools and methodologies by
bridging the gap between engineering theory and experiments. By making
experiments and simulations available to theorists, much could be
learned about uncertainties of and sensitivities to measurements vs.
uncertainties of and sensitivities to modeling errors. **Under
cyberinfrastrcture, theorists and experimentalists would be brought
together and one might expect major developments in both modeling and
experimental techniques.**

Cyberinfrastructure will also enable a broad use of research and
teaching tools in an integrated fashion. Integration of models across
domains and/or scales may result in better renditions of complex
systems. Alternatively, simple interfacing (connecting data flow) across
models may prove inadequate and demonstrate the need for more tightly
coupled, new models to capture real system complexities, which more
closely reflect the real world in terms of emergent behaviors.

Cyberinfrastructure can potentially provide a venue to bring diversity
in opinions, especially critical engineering information, into
decision-making. The earthquake community is a great example for
developing and reinforcing building code and systematic procedures.
Cyberinfrastructure can be an enabling paradigm to develop preventive
measures in addition to disaster relief in addressing critical national
security needs. In addition, CI can allow for simulations for disaster
relief planning. In this regard, engineering approach is natural to
several problem domains such as pattern recognition and data mining.

Q2. For what type of research and education activities (provide
examples) will cyberinfrastructure be critical, and what characteristics
will be required of the cyberinfrastructure? Where are the major
challenges?

Cyberinfrastructure will be critical in the following engineering
research and educational activities: sharing data among different
platforms and/or for different applications, and creating new
collaboration paradigms. Toward this end, there is a strong need to
advance from the current solutions to obtain easily reconfigurable
tools, standardized protocols, easily accessible databases and toolsets.
Current solutions are too domain specific, not application or user
centric. Models of different scale and purpose under cyberinfrastructure
should be able to talk to each other and inter-operable. Each domain
tool should work with every other tool. All these issues are much easier
to deal with at the infrastructure stages.

For example, cyberinfrastructure could advance turbulence modeling,
which usually entails Terabytes of data, in the following 3 ways:

-   Different models within the same domain could be integrated and/or
    compared

-   Models within different domains could be interfaces/integrated

-   Models could be used in conjunction with experimental facilities or
    real world data.

Cyberinfrastructure would be an enabler in modeling efforts such that
models can be compared, integrated and/or validated over:

-   Types

    -   Deterministic vs. stochastic

    -   Simulation vs. analytic

    -   Descriptive, predictive, vs. prescriptive

    -   Mechanistic/Physical/Kinetic/etc. vs. Statistical

    -   Purpose: policy issue vs. measurement issue

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-   Domains

    -   e.g., air quality models, traveler behavior models,
        transportation models

-   Geographic Scale

    -   e.g., fate and transport of contaminants over a whole water shed

-   Multi-Scale

    -   Computational Fluid Dynamics / Turbulence

-   Cyberinfrastructure would bring modeling capability to those without
    modeling capabilities. It will foster inclusiveness by connecting
    and facilitating use of new software models by

    -   smaller, less computer/software rich universities

    -   primarily undergraduate or underrepresented institutions

    -   disciplines with more limited resources and capabilities (note
        that the early adopters of Cyberinfrastructure are disciplinary:
        NEES, NEON, etc.)

    -   general public

    -   decision-makers in the public and private sector

Models complement data. Cyberinfrastructure is not complete without
model. Visualization, database management, or basic components of such
are available for domain specific applications (e.g., supply chain
networks). However, there is a need for standard protocol,
heterogeneity, and scalable tools.

Many engineering fields have developed similar tools for domain specific
applications. There is a need to identify the fundamental problem with
abstraction and create tools to address diverse fields with flexibility
and scalability. There is also a need to break down disciplinary
jargons.

There is a need for a software architecture to integrate existing
mechanical models to provide a foundation for integrated physics based
simulations.

Q3. How can effective partnership between computer science and
engineering researchers and educators be developed to best provide the
needed cyberinfrastructure?

We as engineers need to articulate engineering challenges well to make
them specific enough to our engineering peers, but can still be
understood by computer scientists. Better abstraction of engineering
problems for computer scientists is critical and characteristic in
cyberinfrastructure. Rapid prototyping tools and visualization, for
example, are commonly used in computer science community, which are
examples for engineers to learn to communicate with a larger community
outside our own engineering field. Engineers need to work with computer
scientists to develop computer tools across disciplines with increased
ease and flexibility. This collaboration would also reduce and prevent
redundant work, enable more sharing of results. We as engineers need to
be open minded; don't shoot ourselves in the foot.

Engineers and computer scientists have complementary skills.
Cyberinfrastructure enhances intellectual diversity and working with
other communities. It takes time, tool, capability, and discipline to
develop strong ties to other fields. However, **an interdisciplinary
approach is key to the success of cyberinfrastructure**.

It takes a strong partnership of several communities, with engineering
and computer science playing important roles, to address research
problems in multiscale chemistry, composite materials, turbulence, civil
infrastructure, driver behavior, air quality, simulations and many other
engineering problems. Cyberinfrastructure is an opportunity for
researchers working together to address very large problems that could
not have been dealt with without simultaneous access to heterogeneous
computing resources, experimental facilities, and flexible and scalable
analysis and modeling tools.

The exposure of different disciplines to other frameworks could cause
the kind of paradigm shift described by Thomas Kuhn.

Q4. Develop a general road map for future investments in
cyberinfrastructure. What investments need to come first and why? What
payoffs can be expected? Provide input on cost estimates to implement
the road map.

# 

Some engineers focus on \"the model\", other engineers focus on \"the
data\". Cyberinfrastructure should be the vehicle through which models
and data are integrated in a collaborative. **It is the integration of
model and data that should be a focus of cyberinfrastructure research
and funding**.

Traditionally, there has been a bottleneck as far as engineering is
concerned.

Traditionally, there has been a need for \"application\" and
\"hardware\" to communicate

(this can be considered as a communication between theory and
experiment).

And, traditionally, it has been \"the network\" that has facilitated
this communication.

Thus, \"middleware\" is critical and funding must be spent on ensuring a
robust platform to facilitate communication between these two critical
aspects of study for engineers: theory and experiment (modeling, and
data acquisition).

Up till now, these NSF reports have been investing in \"application \".
Decisions have been made that middleware gets the \$ and it is time we,
as engineers, embrace this and infuse it with thinking critical to our
mission.

Middleware is not only a CISE problem but is an engineering problem.

The roadmap cannot be CS first and then engineering.

The roadmap, for us, must be engineering first. We must define what we
need. And then we must Go to CISE and tell them what we need.

We, as engineers need a distributed dynamic middle ware that is not
reducible to anything currently existing in practice. We need a
middleware that is dedicated to the internet transmission of both
engineering models (processes), and data, and, the integration of data
and modeling through visualization and data mining.

NSF should use cyberinfrastructure funds to foster communication between
engineering and computer science

Q5. What organizational structure is needed to provide long-term support
for cyberinfrastructure development?

## NSF needs to fund the following under the CI initiative

1.  Middleware needs funding. Data Analysis Software needs funding.

2.  Organizational

    -   There should be a small number of interdisciplinary engineering
        centers.

    -   These engineering centers should abstract classes of problems
        regarding how CI relates to specific disciplines.

    -   Then comp.sci should get involved to assist engineers in step 2
        above.

3.  An interdisciplinary start point is good.

4.  We, as engineers, have good data and data sets...We, as engineers,
    have good models. NSF should spend funds to distribute models and
    data using "collaboratives". Exactly how these models and data are
    exchanged is an engineering design problem. For engineers must
    embrace network technology and construct the data frame transmission
    protocols to transmit engineering data and models in the same way
    the seismic community has done.

5.  Network congestion and algorithm control becomes unstable at high
    transmission speeds needed by engineers. Research in this area needs
    to be conducted.

6.  We should establish the engineering needs not being met by Comp.Sci.
    And when things break down, we should bring in the comp.sci to
    discuss and advise us.

7.  We seem to be struggling (as engineers) with how to transform
    engineering and engineers from being users to partners.

8.  The computer science community is not the problem. We as engineers
    are the problem. It is engineers who have not risen to the challenge
    and we need workshops to assist us in this. We, as engineers must
    learn to prototype systems not just components of systems.

9.  Fault tolerance is an issue for engineers.

10. Where is the boundary between middleware and application? NSF should
    fund research into the different levels of abstraction at this vague
    intersection.

Q6. What should be the path forward regarding future workshops and other
activities? What information is needed to address outstanding questions
and knowledge gaps important for decisionmaking about NSF's
cyberinfrastructure investments?

We need funds for equipment and deployment. We need funds to interface
to the general community.

We propose that NSF funds 5-6 CyberInfrastructure Engineering Centers
(see below for examples). We propose that we need 10 million for each
center per year for a minimum of five years.

We should request funds to enable the center to communicate with each
other: 2 million per year for this alone. The centers should be focused
on specific engineering problems.

We need a mechanism for the center results to filter down to the general
community. How should a small school hook in? What mechanisms should
there be for this? There should be funds for outreach partners to get
separate funding to hook in. We need a mechanism am for K12 to connect
to such centers. Might we need to allocate funds to work with
industry... what mechanisms?

We need funds for collaboration.

We might give examples of modeling examples that could be the focus of
such CI engineering centers:

1.  Snapshot data. Send data for analysis. Ship data back for
    predictions

2.  Surgical planning

3.  Using CI to assist in Multi-scale models should be the focus of some
    of the centers.

4.  Social aspects of engineering problems as evinced by CI.

5.  Simulations of hardware infrastructure (modeling of bridge and
    building health); simulations to train for disaster prepardness.

6.  integrated physical (experimental/data) and computational
    models/simulation.

7.  How can data be infused into the models? And v.v.

8.  We embed in data with interpretations of data. We should do the same
    with models.

9.  Nanotechnology

Total: 80 million. Per year for five years is needed to ensure that the
engineering modeling community embraces, exploits, and even assists in
defining what CI is.

We need to fund NOT ONLY centers, but also workshops

Here are some possible workshop activities....

1.  We need a workshop on how the current infrastructure is breaking,
    with respect to security, real-time processing...We need a workshop
    to show how the current network system inhibits us as engineers

2.  There should be a workshop on sensing technologies (yes, NSF has
    done this) but now, with specific attention to cyberinfrastructure.

3.  We need workshops to discuss policy issues for engineering and the
    Cyberinfrastructure.

4.  We need a workshop to discuss the next step in the use of models:
    not just to simulate, but to predict. We have exceeded the limits of
    simulation to address scaleable models and analysis for complex
    problems

5.  We need workshops on Human computer interaction.

6.  We need workshops on how to integrate modeling, data and
    visualization. This could be the role of group 3: the
    collaboratives.