MA 664 Fall 2007

MA 664 University Handbook Description

Seminar in Applied Mathematics. Problems, methods and recent developments in applied mathematics. This course may be taken five times for credit as content varies.

Prerequisites: Approval of instructor.

Specific Course Description for this Term

Dynamic Data-Driven Application Systems (DDDAS) is a paradigm whereby applications (or simulations) and measurements become a symbiotic feedback control system. DDDAS entails the ability to dynamically incorporate additional data into an executing application, and in reverse, the ability of an application to dynamically steer the measurement process. Such capabilities promise more accurate analysis and prediction, more precise controls, and more reliable outcomes. The ability of an application to control and guide the measurement process and determine when, where, and how it is best to gather additional data has itself the potential of enabling more effective measurement methodologies.

In this course, we will study several successful DDDAS applications that are extensively documented through the DDDAS community web site, http://www.dddas.org. DDDAS is already in use in Lexington, KY and Taipei, Taiwan: the entire traffic light system in either city is run using a single computer cluster, a dynamic data-driven commodity transportation application, and a large number of sensors under many strategic streets.

No prior knowledge of DDDAS is assumed nor knowledge of high level mathematics or computational sciences. This will be a self contained class.

Goals and Friendly Advice

The goal at the end of this course is that you will know why using dynamic data and models is more useful than the traditional take some random data and run a computer into the ground until it gives one, and only one, prediction for some phenomena. Then keep repeating with another random data set until the computer eventually fails or is replaced with a faster one (then the data sets can get bigger). Repeat all until you retire or change jobs.

The friendly advice is as follows:

1. Always come to class unless you are sick (in which case, do not come to class).
2. Raise your hand and participate in class discussions often.
3. Interrupt lectures if you do not understand or agree with something.
4. Do your work on time (i.e., do not tell me your flowering pine tree ate your homework).

Office Hours and Contact Information

My office hours will be on Tuesdays 11:00-12:00 and Wednesdays 10:00-11:00 (and subject to cancellation occasionally).

My office is 608G Blocker My office telephone number is 845-3336-2438 and my eFAX is +1-203-547-6273. Feel free to telephone my office as late as 7:00pm. In a pinch, I can be reached at home on Friday evenings and weekends only at +1-203-625-9449 (this is in Connecticut, not Kentucky). Please do not call me at home before 8:00 am or after 8:00 pm (central time). I respond to e-mail fairly quickly (always include a phone number where I can call you back and MA664 in the subject). If you are stuck on something, please do not hesitate to contact me. Please be utterly brazen.

Homework and Grading

Your grade will be based entirely on the homework.

General readings for everone:

• SBES Report
• 2006 NSF DDDAS Workshop Report

Specific to a student readings:

• Linfeng Bi
  1. John Michopoulos et al
  2. Mahinthakumar et al
  3. Manish Parashar et al
• Lijian Jiang
  1. Leona Golubchik et al
  2. Adrian Sandu et al
  3. Theodore B. Trafalis et al
• Yan Li
  1. V. Akcelik, G. Biros, A. Draganescu, O. Ghattas. et al
  2. Jonathan How et al
  3. Charbel Farhat and John Michopoulos et al
• Dukjin Nam
  1. Dimitris Metaxas et al
  2. Sai Ravela and John Marshall et al
  3. L.H. Tsoukalas et al
• Mei Yang
  1. D.S. Bernstein et al
  2. Greg Madey et al
  3. Catriona Kennedy and Georgios Theodoropoulos et al

 

Cheers,
Craig C. Douglas

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