Welcome!
The Austin Chapter of SIAM is a society for all those interested in mathematics and its applications. We sponsor guest speakers, career discussions on industry and academia, studentfaculty social events, and visits to annual SIAM meetings. We welcome new members from all majors and all University of Texas at Austin members, whether undergraduate, graduate, faculty, or other.
Spring 2016 SIAM Coffee Breaks
We will once again have Biweekly Coffee Breaks this semester, starting February 10 at 11:30 A.M. at POB 6.102. We hope you will join us!
Career tools
Although not exhaustive by any means, here are some useful tools for improving your job search:
 SIAM Career Center
 Profiles of nonacademic applied mathematicians from the American Mathematical Society
 UT Career Exploration Center
 Handouts on resume writing, interviewing, and more.
 Columbia University Career Tools Handouts
 Graduate Student Instructor Program Workshops
 A Mathematician's Survival Guide: Graduate School and Early Career Development
Graduate fellowships
There are many fellowships to help fund graduate school. Pearl Flath has compiled a few places to begin looking for yours:
 UT Graduate School Funding Resources
 NASA Graduate Student Researchers Program
 National Physical Sciences Consortium Fellowship
 National Science Foundation Funding Opportunities
 DOE Computational Science Graduate Fellowship
 DOE High Performance Computer Science Fellowship
 DOE NNSA Stewardship Science Graduate Fellowship
 American Indian Graduate Center
 Jack Kent Cooke Foundation Scholarships
 Ford Foundation Fellowships
 AT&T Labs Fellowship Program
 Gates Cambridge Scholarships
 Marshall Scholarships
 National Defense Science and Engineering Fellowship
 Hertz Foundation Applied Science Fellowships
 IBM Ph.D. Fellowship Awards
 Department of Homeland Security Scholarship Program
 Texas Space Grant Consortium Scholarships
Related campus organizations
 Saturday Morning Math Group
 "The Saturday Morning Math Group is a UT sponsored outreach program aimed at junior high and high school students, their teachers, and their parents."
 Undergraduate Mathematics Research Group
 "[The group] is open to all students interested in mathematics, and especially caters to the UTAustin pure and applied mathematics communities. Our goal is to enhance the undergraduate math experience by exposing students to beautiful mathematics, interesting research, and helpful information every week."
Related campus departments
 Aerospace Engineering & Engineering Mechanics Department
 Computer Science Department
 UT Graduate School
 Institute for Computational Engineering and Sciences
 Mathematics Department
 Physics Department
Other SIAM chapters in Texas
 Rice University
 Texas Tech Univeristy
 Trinity University
 A complete SIAM chapter list is available.
Related societies
LaTeX Help
Latex is a typesetting language widely used in the sciences for writing articles, textbooks, and just about anything with equations in it.
Distributions
You'll need an installed LaTeX distribution to typeset your work. Several popular distributions are:
If you're using a Linux system (especially on campus), the odds are good that the software you need is already installed.
Tutorials
If you're completely new to LaTeX, here are some good places to get started:
 The Not So Short Introduction to LaTeX2e by Oetiker et al.
 Getting Started With Latex, 2nd Edition by David Wilkins
 The LaTeX Wikibook
 Math into LaTeX, 1st Edition by George Grätzer
 Getting to grips with LaTeX by Andrew Roberts
Finally, with Beamer, LaTeX can be used to make great presentations. A Beamer Quickstart shows how it's done.
References
Here are some great places to look when you can't quite figure out how to do what you need:
 The Comprehensive TeX Archive Network (CTAN)
 The Comprehensive LaTeX Symbol List
 A 2sided LaTeX Cheat Sheet
 UT Dissertation LaTeX Package
 Short Math Guide for LaTeX
Useful Packages
Lastly, here are some LaTeX packages that can make your life easier:
 amsmath
 This package is the principal package in the AMSLaTeX distribution. It adapts for use in LaTeX most of the mathematical features found in AMSTeX; it is a nearindispensable adjunct to serious mathematical typesetting in LaTeX.
 cancel
 A package to draw diagonal lines (“cancelling” a term) and arrows with limits (cancelling a term “to a value”) through parts of maths formulas.
 enumerate
 The enumerate package adds an optional argument to the enumerate environment which determines the style in which the counter is printed.
 fancyhdr
 The package provides extensive facilities, both for constructing headers and footers, and for controlling their use (for example, at times when LaTeX would automatically change the heading style in use).
 fullpage
 This package sets all 4 margins to be either 1 inch or 1.5 cm, and specifies the page style.
 mathtools
 Mathtools provides many useful tools for mathematical typesetting.
 pstricks
 An extensive collection of PostScript macros that is compatible with most TeX macro formats, including Plain TeX, LaTeX, AMSTeX, and AMSLaTeX. Included are macros for colour, graphics, pie charts, rotation, trees and overlays.
 setspace
 Provides support for setting the spacing between lines in a document. Package options include singlespacing, onehalfspacing, and doublespacing.
CTAN is also a good place to look for specific functionality.
Mathematics help
Here's a collection of classic and notsoclassic references to help you look up an unfamiliar term, find an analytic solution, or refresh you on a high school trig identity:
 Wikipedia: Mathematics Portal
 PlanetMath
 mathoverflow
 Wolfram MathWorld
 Equation World
 Handbook of Mathematical Functions by Abramowitz and Stegun
 Numerical Recipes, 3rd Edition (Free on campus)
 Numerical Recipes, 2nd Edition (Free)
 Wikibooks: Engineering Bookshelf
Programming help
Everyone comes at programming from a different background. Hopefully one of these sites speaks to yours:
 Texas Advanced Computing Center Training Classes
 "TACC offers various training classes in high performance computing (HPC), scientific visualization (SciVis), distributed and grid computing (DGC), and computational cluster management. TACC training classes teach the programming principles and techniques in HPC and SciVis as well as how to use TACC's highend systems most effectively."
 Software Carpentry
 "Many scientists and engineers spend much of their lives programming, but only a handful have ever been taught how to do this well. ... This course is an intensive introduction to basic software development practices for scientists and engineers that can reduce the time they spend programming by 2025%."
 Blaise Barney's Introduction to Parallel Computing
 "This tutorial covers the very basics of parallel computing, and is intended for someone who is just becoming acquainted with the subject. It begins with a brief overview, including concepts and terminology associated with parallel computing. The topics of parallel memory architectures and programming models are then explored. These topics are followed by a discussion on a number of issues related to designing parallel programs. The tutorial concludes with several examples of how to parallelize simple serial programs."
 Texas Advanced Computing Center Academic Courses
 "TACC scientists are teaching ... undergraduate and graduate level courses at The University of Texas at Austin, in the Division of Statistics and Scientific Computation. The courses are designed to enable students to apply scientific computing in research and development for both academic and industry careers."
Software help
This is a small collection of symbolic manipulation, number crunching, and plotting software that will make your life easier:
Chapter officers
 Officers
 President: Brendan Keith
 VicePresident: Gopal Yalla
 Treasurer: Tom O'LearyRoseberry
 Industry liason: Tim Smith
 Communications director: Max Bremer
 Administrative director: Josh Chen
 Advisors
 Dr. Clint Dawson
 Dr. Todd Arbogast
 Past President and Founder
 Pearl Flath
Our mission
 To promote interactions between members of the applied mathematics community at UT Austin, across departments and across professional ranks
 To provide a forum for the discussion of applied and computational mathematics research and pedagogy at UT Austin.
 To help Longhorns understand the breadth of career possibilities in applied and computational mathematics.
 To promote publications, conferences, prizes, and other opportunities offered by SIAM.
Organization resources
Chapter officers
 Officers
 Brendan Keith
 Prapti Neupane
 Chenglong Zhang
 Advisors
 Dr. Clint Dawson
 Dr. Todd Arbogast
 Past President and Founder
 Pearl Flath
Our mission
 To promote interactions between members of the applied mathematics community at UT Austin, across departments and across professional ranks
 To provide a forum for the discussion of applied and computational mathematics research and pedagogy at UT Austin.
 To help Longhorns understand the breadth of career possibilities in applied and computational mathematics.
 To promote publications, conferences, prizes, and other opportunities offered by SIAM.
Organization resources
Presentation tips
Giving a good presentation requires careful preparation. Here's a quick, handy list of presentation tips compiled by Pearl Flath:
 Have an outline of the talk on the title page or the first slide so the audience knows where you're going.
 Have a short topic header at the top of each slide.
 Don't use complete sentences on the slide.
 Don't put too much on a slide.
 If you have animations, make sure the talk can proceed even if they don't work.
 Make sure the font size is large enough to read. Make sure it has enough contrast to read it  light text on dark background or dark text on light background. Don't use strange fonts.
 Use graphics and pictures in your slides.
 For a graph, have a title and labels for the axes with units.
 Don't try to cover too much  a one term course cannot be covered in an hour.
 Don't introduce too much jargon.
 Don't do a long derivation.
 If you do a derivation or a proof, make sure you first write what you are trying to derive or prove. That way, when people get lost, they can look at the top of the board and see where they are trying to go to and where from.
 When you have an important equation, try to have a physical or conceptual explanation of it too.
 Don't introduce too many new variables.
 Practice the talk by yourself and in front of others. Have them give you suggestions for improvement.
 During the presentation, look at the audience and make eye contact with a number of people.
 Speak loud enough for people to hear you.
 Avoid saying fluff words, such as "uh" and "basically."
 If you stumble verbally, do not apologize but continue.
 Do not rush the presentation.
 Look at the computer screen or a printout of your slides, not the screen behind you.
 Do not read your slides or have your presentation memorized wordforword, but speak about your work from the bullets on the slide or from notes.
 Smile.
 Stop talking periodically and ask questions to make sure everyone is keeping up with you. In your practice, time the presentation to allow for a few minutes of questions at the end. At the last, ask the question "Are there any questions?"
 You should spend at least 75% of your time looking at your audience and at most 25% of your time looking at the blackboard. Firsttime speakers often spend 100% of their time looking at the blackboard
 Plan a closing line. Even if you give a great talk, ending it with "Um, I guess that's all I've got" or "I think that's the last slide" will do nothing for your cause. Say something like "That concludes my presentationthank you for your attention" or "I'll be happy to take questions nowthanks for coming " or simply "Thank you."
Sources
 Dr. Wiggins
 Krell Institute : Computational Science Opportunities for Undergraduates : Presenting Your Work
 Richard Felder's Tips on Talks
 Presentation Dos and Don'ts, (section 3 linked from PRB Library)
 Virginia Montecino's Powerpoint tips
Rules of procedure
This Rules of Procedure (hereinafter called "Rules") apply to the SIAM student chapter called “UT Austin Chapter of SIAM".
The Chapter to which these Rules apply is formed by the Society for Industrial and Applied Mathematics and shall operate within the Bylaws of the parent organization. The SIAM bylaws specify how Chapters are formed; see the SIAM bylaws for details. The Chapter shall not affiliate with any other organization without first obtaining the written approval of SIAM. Provisions for SIAM Student (University) Chapters are contained in the SIAM Bylaws and are included in these Rules. No provisions of these rules shall be construed so as to contradict the Bylaws of SIAM.
Article I: Purpose
The objectives of SIAM, as established in the Certificate of Incorporation, are:
 To further the application of mathematics to industry and science.
 To promote basic research in mathematics leading to new methods and techniques useful to industry and science.
 To provide media for the exchange of information and ideas between mathematicians and other technical and scientific personnel.
The objectives of the UT Austin Student Chapter of SIAM are:
 To promote interactions between members of the applied mathematics community at UT Austin, across departments, institutes, and professional ranks;
 To provide a forum for the discussion of applied and computational mathematics research and pedagogy;
 To help members prepare for future careers in applied and computational mathematics;
 To promote publications, conferences, prizes, and other opportunities offered by SIAM;
Article II: Activities
Activities anticipated for the chapter include:
 Regular informal brown bag lunch discussions with local and visiting speakers;
 Career discussions on applied mathematics in academia and industry;
 Student chapter representation at SIAM annual meetings;
 Development and maintenance of a UT Austin Chapter of SIAM website;
 Annual elections for Chapter officers, beginning in November 2005, for calendaryear terms of service;
Article III: Institution Served
Members shall be recruited from The University of Texas at Austin.
Article IV: Membership
 Section 1
 Any person engaged or interested in mathematics or computing and their applications shall be eligible for membership in this Chapter. Chapter membership may be interdisciplinary, with members from multiple departments.
 Section 2
 There are no dues.
 Section 3
 Chapter members shall have the privileges of SIAM membership only if they are regular or student members of SIAM.
 Section 4
 All members of the chapter who are students enrolled in the sponsoring institution(s) are eligible for free student memberships in SIAM. The chapter is responsible for providing a list of its student members to SIAM so that complimentary student membership in SIAM can be processed.
 Section 5
 Termination of student membership will take place upon graduation or withdrawal from the university.
Article V: Sponsorship
 Section 1
 The Sponsor is UT Austin.
 Section 2
 The Sponsor of the Chapter shall appoint two Faculty Advisors for the Chapter. One of these must be affiliated with the UT Austin Mathematics Department. One of these must be affiliated with the Institute for Computational Engineering and Sciences (ICES). In the event either Advisor relinquishes his/her position, the Sponsor shall appoint a new Advisor. The responsibilities, rights and duties of the Faculty Advisor shall be those normally assigned to the Faculty Advisor of student organizations of the Sponsor, but in addition, the Faculty Advisor is expected to take leading role in the development of the Chapter activities consistent with the objectives of SIAM.
Article VI: Officers
 Section 1
 The Chapter shall have a President, a VicePresident, and a SecretaryTreasurer. Officers shall be Student Members in good standing with SIAM, and shall be chosen from Student Members of the Chapter.
 Section 2
 The President shall preside at the meetings of the Chapter (and the Chapter Executive Committee, see Article VII below). The president must be a graduate student at UT Austin. In the absence of the President, the VicePresident shall assume the duties of the President. In the absence of the latter, the SecretaryTreasurer shall assume said duties.
 Section 3
 The SecretaryTreasurer shall keep a record of the affairs of the Chapter, handle correspondence, and submit an annual report of Chapter activities to the Secretary of SIAM, which report shall be suitable for publication in SIAM News or its equivalent. The SecretaryTreasurer shall receive and take custody of Chapter funds, and shall submit an annual Treasurer's Report and other financial reports, as requested, to the Treasurer of SIAM. The annual Treasurer's Report shall be prepared as of the end of the academic year and shall be transmitted to the Treasurer of SIAM by no later than 30 days following the end of the academic year.
 Section 5
 Elections will be held yearly near the end of the Fall semester. Elections may be held earlier in the Fall of 2005 in order to fill the positions of VicePresident and SecretaryTreasurer.
Article VII: Executive Committee
 Section 1
 The Executive Committee will consist of the President, Vice President, and SecretaryTreasurer. The President is the Committee chair. The Executive Committee is responsible for planning meetings, organizing elections, and maintaining a website. It should have at least quarterly meetings to discuss plans for the chapter.
 Section 2
 In the event of a vacancy, members shall be notified (by email) and elections held two weeks later.
Article VIII: Other Committees
 Section 1
 Nominations for officers should be sent to the member of the Executive Committee specified in the announcement of the election.
Article X: Meetings
 Section 1
 There shall be at least three chapter meetings per year. Meetings will be scheduled and planned by the Executive Committee.
 Section 2
 The Chapter shall conduct a business meeting once per year during the month of September. Other business meetings may be called by the President or the Treasurer on two weeks notice.
Article XI: Chapter Funds
 Section 1
 The Chapter shall deposit all unused funds to which it has legal title in excess of $200 in an insured savings account, unless current operating commitments are in excess of that amount or unless the Chapter Treasurer obtains a written authorization from the SIAM Treasurer.
 Section 2
 The Treasurer shall maintain books of account that show income and expense items for all activities and balances for all accounts of the Chapter.
 Section 3
 The Chapter may request a grant or loan from the Treasurer of SIAM under the provision of Article XII, Chapter 8 of the Bylaws of SIAM. Such requests shall be made by submission of “Request for Funding” form to SIAM and include a current financial statement for the Chapter and a proposed budget for the requested funds.
 Section 4
 Other than seeking funds from the sponsoring institutions of the chapter, no officers or member of the Chapter may apply for a grant to support the Chapter activities or enter into any contract to support such activities or provide services, without approval of the President and the Treasurer of SIAM or the Executive Director acting on behalf of the Treasurer.
Article XII: Amendments
 Section 1
 These Rules may be altered or amended with the approval of the SIAM Board of Trustees. Submission to the board of proposal alterations or amendments shall be made only after approval by majority vote of members of the Chapter present (or represented by proxy) at a scheduled meeting. Before the scheduled meeting, a notice of the upcoming vote shall be sent (by email) to all members at least 1 week in advance.
Article XIII: Termination of the Chapter
 Section 1
 A Chapter may terminate itself by the unanimous vote of the members of the Chapter present (or represented by proxy) at a scheduled meeting, provided that notice of the proposed termination and the meeting at which it is to be considered has been given to all Chapter members at least 30 days in advance.
 Section 2
 A Chapter may be terminated by the board if there has been no Chapter activity for one year.
 Section 3
 In the event a Chapter terminates, the funds to which it has legal title shall revert to the account of SIAM.
History
 Approved, SIAM Board of Trustees, December 3, 1977
 Revised, SIAM Board of Trustees, June 21, 2003
 Adopted with minor customization, UT Austin Chapter of SIAM, September 29, 2005
SIAM prizes for students
Among many other awards, SIAM sponsors the following prizes for students:
 SIAM Student Paper Prize
 "The SIAM Student Paper Prizes are awarded every year to the student author(s) of the most outstanding paper(s) submitted to the SIAM Student Paper Competition. This award is based solely on the merit and content of the student's contribution to the submitted paper. The purpose of the Student Paper Prizes is to recognize outstanding scholarship by students in applied mathematics or computing."
 SIAM Award in the Mathematical Contest in Modeling
 "The SIAM Award in the Mathematical Contest in Modeling (MCM), established in 1988, is awarded to two of the teams judged 'Outstanding' in the Mathematical Contest in Modeling (MCM), administered annually by the Consortium for Mathematics and Its Applications (COMAP). One winning team is chosen for each of the two problems (continuous and discrete) posed in the MCM."
 Frank and Brennie Morgan Prize for Outstanding Research in Mathematics by an Undergraduate Student
 "The Morgan Prize was established in 1995 and is awarded annually to an undergraduate student (or students having submitted joint work) for outstanding research in mathematics. It is entirely endowed by a gift from Mrs. Frank (Brennie) Morgan. Any student who is an undergraduate in a college or university in Canada, Mexico, the United States or its possessions is eligible to be considered for the prize. The award is made jointly by the American Mathematical Society, the Mathematical Association of America, and the Society for Industrial and Applied Mathematics."
 SIAM Student Travel Awards
 "SIAM offers travel support for students through SIAM Student Travel Awards. The awards are made from the SIAM Student Travel Fund, created in 1991 and maintained through book royalties donated by generous SIAM authors and by donations from SIAM members. The awards for selected conferences are also supported by donations from industry. Any fulltime student in good standing is eligible to receive an award plus gratis meeting registration."
SIAM Resources
The following is a condensed list of SIAM resources. Please see www.siam.org for a complete list of member resources.
 Activity Groups
 "SIAM Activity Groups (SIAGs) provide a more focused forum for SIAM members interested in exploring one of the areas of applied mathematics, computational science, or applications."
 Books
 "The mission of SIAM's book program is to make relevant research results accessible to industry and science and to promote the interaction between mathematics and other disciplines such as engineering, science, and computing."
 Careers & Jobs
 "Whether you are a student considering a career in mathematics, or an established mathematician, you will find the jobsearch and career information resources in this section invaluable."
 Conferences
 "SIAM conferences focus on timely topics in applied and computational mathematics and applications and provide a place for members to exchange ideas and to expand their network of colleagues in both academia and industry."
 Journals
 "SIAM publishes 14 peerreviewed research journals. . . . The full text of SIAM journals is now available electronically on a subscription basis."
 Membership List
 "Search directory information for members of AMS, MAA, SIAM, AMATYC, AWM, & CMS/SMC."
 Prizes
 "SIAM conducts an extensive prize program to recognize outstanding applied mathematicians and computational scientists."
 Proceedings
 "SIAM publishes selected proceedings from its yearly meetings and conferences."
 Students
 "Students are the future of applied mathematics and computational science. SIAM welcomes students with opportunities to participate in SIAM, as well as online resources on education and careers."
SIAM student travel awards
SIAM offers travel support for students through SIAM Student Travel Awards.
Any fulltime student in good standing is eligible to receive an award plus gratis meeting registration. Top priority will be given to students presenting papers at the meeting, with second priority to students who are coauthors of papers to be presented at the meetings. Only students traveling more than 100 miles to the meetings are eligible for the awards.
An application for a travel award must include:
 A letter from the student describing his/her academic standing and interests, his/her expected graduation date and degree, advisor's name, and, if available, a URL for a working Web page.
 A onepage vita that includes the student's research interests, projects, and papers published.
 A detailed letter from the student's faculty advisor indicating why the student is deserving of receiving a travel award and any special circumstances.
 If applicable, the title(s) of the paper(s) to be presented (coauthored) by the student at the meeting.
In most cases, the deadline for complete applications is approximately seven months before the first day of the conference for which support is requested, and awardees will be notified by email five months before the first day of the meeting.
More information, including the online application submission system, is available at SIAM's Student Travel Awards page.
UT graduate student professional development awards
"Professional Development Awards provide support for students to attend major professional meetings at which they present an original paper based on their research. The Graduate School allocates travel funds to each department or program. The graduate adviser and graduate coordinator can nominate students for these awards which are approved and administered by the Graduate School."
CSE Success Stories: Storm Surge
Fig. 4  Time history of water surface elevation for simulated severe storm impacting Houston Galveston region.
At the forefront of scientific research, Computational Science and Engineering plays a critical role in analyzing and predicting the behavior of complex physical systems. A significant application is the modeling of hurricane storm surge, a natural phenomena which wreaks major damage on coastal communities every year. Long known for its damaging effects, storm surge is difficult to predict and has been responsible for the loss of thousands of lives and billions of dollars in damages along the Texas and Louisiana Gulf coasts in particular.
The ability to accurately model and subsequently communicate results effectively is crucial to decision makers both during the emergency phase of an impacting storm, and off season during which structural and nonstructural mitigation strategies are planned. Sea walls and levees have been built in an attempt to protect lives and communities from the onslaught of this powerful force, and additional solutions are consistently proposed. The National Oceanic and Atmospheric Administration, U.S. Army Corp of Engineers, as well as academic researchers, all use CS&E modeling to help make informed decisions. Clearly the impact of hurricane storm surge modeling is large scale, directly influencing current decision making and the planning of future strategies to reduce the impact of these natural disasters.
Major initiatives are currently underway by the Computational Hydraulics Group (CHG) at The University of Texas at Austin and collaborators to research and design the next generation of highly accurate computational storm surge modeling and analysis. We highlight here two such areas of current research underway.
In collaboration with Rice University’s Severe Storm Prediction Education and Evacuation from Disasters (SSPEED) Center, researchers are developing a comprehensive strategy to prepare and protect the HoustonGalveston region from hurricanes. Computational modeling is a critical tool to predict the severity of storms and to evaluate the effectiveness of proposed surge reduction ideas prior to implementation. Where and what is chosen to construct may have far reaching effects, either increasing or decreasing potential damage. Planners and policy makers can better understand which mitigation designs function well as barriers to the sea and subsequently limit development in these areas.
Results of CHG research yield a Houston Galveston Area Protection System (HGAPS), which includes the “Coastal Spline”— a proposed multibilliondollar seawall that would enhance the existing wall and expand it to run the length of Galveston Island and Bolivar Peninsula. Alternatively, a “Centennial Gate” would close off the upper portion of the shipping channel to protect the greater Houston region (Figure 2). To evaluate the effectiveness of these structures, computational modelers simulate a severe storm directly impacting the most vulnerable region of greater Houston and Galveston (Figure 1 and 2).
To efficiently generate data regarding potential outcomes, the use of high performance computers is essential due to the complexity of the hydrological model. The National Science Foundation recently funded CHG’s STORM project, an initiative designed to enhance the current performance of computational storm surge model functionality.
Driven by increased performance, computational hardware is becoming more powerful and diverse in terms of components. For a predictive model to achieve optimal performance across systems, scientific computing must keep up with stateoftheart invention. The High Performance ParallelX (HPX) code currently under development in the STORM project is a completely new foundation that is designed to be flexible and easily integrable with other architectures. By utilizing HPX, the software enables scientific computations to run more efficiently on modern supercomputing systems. Moreover, it is well equipped to handle the inevitable future of hardware development.
Research Group
CHG Researchers:
 Clint Dawson, The University of Texas at Austin
 Craig Michowski, The University of Texas at Austin
 Jennifer Proft, The University of Texas at Austin
Collaborators:
 Hartmut Kaiser, Lousiana State University
 Joannes Westerink, The University of Notre Dame
 Richard A. Luettich, The University of North Carolina at Chapel Hill
 Jim Blackburn, SSPEED Center, Rice University
 Phil Bedient, SSPEED Center, Rice University
 Larry Dunbar, SSPEED Center, Rice University
Funding sources:
 National Science Foundation grant NSF ACI 1339801.
 Houston Endowment, SSPEED Center grant.
Related Links:
 Prepping for the STORM: Clint Dawson Receives $3M NSF Grant to Overhaul Storm Surge Code
 Rice wins $3.1M to develop storm strategy for HoustonGalveston
Acknowledgements:
This webpage was designed in part by Lindley Graham, NSF GRFP doctoral fellow.
CSE Success Stories: Storm Surge
Time history of water elevation for Mega Hurricane Ike, storm track 7.
At the forefront of scientific research, Computational Science and Engineering plays a critical role in analyzing and predicting the behavior of complex physical systems. A significant application is the modeling of hurricane storm surge, a natural phenomena which wreaks major damage on coastal communities every year. Long known for its damaging effects, storm surge is difficult to predict and has been responsible for the loss of thousands of lives and billions of dollars in damages along the Texas and Louisiana Gulf coasts in particular.
The ability to accurately model and subsequently communicate results effectively is crucial to decision makers both during the emergency phase of an impacting storm, and off season during which structural and nonstructural mitigation strategies are planned. Sea walls and levees have been built in an attempt to protect lives and communities from the onslaught of this powerful force, and additional solutions are consistently proposed. The National Oceanic and Atmospheric Administration, U.S. Army Corp of Engineers, as well as academic researchers, all use CS&E modeling to help make informed decisions. Clearly the impact of hurricane storm surge modeling is large scale, directly influencing current decision making and the planning of future strategies to reduce the impact of these natural disasters.
Major initiatives are currently underway by the Computational Hydraulics Group (CHG) at The University of Texas at Austin and collaborators to research and design the next generation of highly accurate computational storm surge modeling and analysis. We highlight here two such areas of current research underway.
In collaboration with Rice University’s Severe Storm Prediction Education and Evacuation from Disasters (SSPEED) Center, researchers are developing a comprehensive strategy to prepare and protect the HoustonGalveston region from hurricanes. Computational modeling is a critical tool to predict the severity of storms and to evaluate the effectiveness of proposed surge reduction ideas prior to implementation. Where and what is chosen to construct may have far reaching effects, either increasing or decreasing potential damage. Planners and policy makes can better understand which mitigation developments function well as barriers to the sea and limit development in these areas.
Results of CHG work yield a Houston Galveston Area Protection System (HGAPS), which includes the “Coastal Spline”— a proposed multibilliondollar seawall that would enhance the existing wall and expand it to run the length of Galveston Island and Bolivar Peninsula. Alternatively, a “Centennial Gate” would close off the upper portion of the shipping channel to protect the greater Houston region (Figure 2). To evaluate the effectiveness of these structures, computational modelers simulate a severe storm directly impacting the most vulnerable region of greater Houston and Galveston (Figure 1 and 2).
To efficiently generate data regarding potential outcomes, the use of high performance computers is essential due to the complexity of the hydrological model. The National Science Foundation recently funded CHG’s STORM project, an initiative designed to enhance the current performance of computational storm surge model functionality.
Driven by increased performance, computational hardware is becoming more powerful and diverse in terms of components. For a predictive model to achieve optimal performance across systems, scientific computing must keep up with stateoftheart invention. The High Performance ParallelX (HPX) code currently under development in the STORM project is a completely new foundation that is designed to be flexible and easily integrable with other architectures. By utilizing HPX, the software enables computations to run more efficiently on modern supercomputing systems. Moreover, it is well equipped to handle the inevitable future of hardware development.
Research Group
CHG Researchers:
 Clint Dawson, The University of Texas at Austin
 Craig Michowski, The University of Texas at Austin
 Jennifer Proft, The University of Texas at Austin
Collaborators:
 Hartmut Kaiser, Lousiana State University
 Joannes Westerink, The University of Notre Dame
 Richard A. Luettich, The University of North Carolina at Chapel Hill
 Jim Blackburn, SSPEED Center, Rice University
 Phil Bedient, SSPEED Center, Rice University
 Larry Dunbar, SSPEED Center, Rice University
Funding sources:
 National Science Foundation grant NSF ACI 1339801.
 Houston Endowment, SSPEED Center grant.
Related Links:
 Prepping for the STORM: Clint Dawson Receives $3M NSF Grant to Overhaul Storm Surge Code
 Rice wins $3.1M to develop storm strategy for HoustonGalveston
Acknowledgements:
This webpage was designed in part by Lindley Graham, NSF GRFP doctoral fellow.
CSE Success Stories: Storm Surge UNDER CONSTRUCTION
Time history of water elevation for Mega Hurricane Ike, storm track 7.
At the forefront of scientific research, Computational Science and Engineering plays a critical role in analyzing and predicting the behavior of complex physical systems. A significant application is the modeling of hurricane storm surge, a natural phenomena which wreaks major damage on coastal communities every year. Long known for its damaging effects, storm surge is difficult to predict and has been responsible for the loss of thousands of lives and billions of dollars in damages along the Texas and Louisiana Gulf coasts in particular.
The ability to accurately model and subsequently communicate results effectively is crucial to decision makers both during the emergency phase of an impacting storm, and off season during which structural and nonstructural mitigation strategies are planned. Sea walls and levees have been built in an attempt to protect lives and communities from the onslaught of this powerful force, and additional solutions are consistently proposed. The National Oceanic and Atmospheric Administration, U.S. Army Corp of Engineers, as well as academic researchers, all use CS&E modeling to help make informed decisions. Clearly the impact of hurricane storm surge modeling is large scale, directly influencing current decision making and the planning of future strategies to reduce the impact of these natural disasters.
Major initiatives are currently underway by the Computational Hydraulics Group (CHG) at The University of Texas at Austin and collaborators to research and design the next generation of highly accurate computational storm surge modeling and analysis. We highlight here two such areas of current research underway.
In collaboration with Rice University’s Severe Storm Prediction Education and Evacuation from Disasters (SSPEED) Center, researchers are developing a comprehensive strategy to prepare and protect the HoustonGalveston region from hurricanes. Computational modeling is a critical tool to predict the severity of storms and to evaluate the effectiveness of proposed surge reduction ideas prior to implementation. Where and what is chosen to construct may have far reaching effects, either increasing or decreasing potential damage. Planners and policy makes can better understand which mitigation developments function well as barriers to the sea and limit development in these areas.
Results of CHG work yield a Houston Galveston Area Protection System (HGAPS), which includes the “Coastal Spline”— a proposed multibilliondollar seawall that would enhance the existing wall and expand it to run the length of Galveston Island and Bolivar Peninsula. Alternatively, a “Centennial Gate” would close off the upper portion of the shipping channel to protect the greater Houston region (Figure 2). To evaluate the effectiveness of these structures, computational modelers simulate a severe storm directly impacting the most vulnerable region of greater Houston and Galveston (Figure 1 and 2).
To efficiently generate data regarding potential outcomes, the use of high performance computers is essential due to the complexity of the hydrological model. The National Science Foundation recently funded CHG’s STORM project, an initiative designed to enhance the current performance of computational storm surge model functionality.
Driven by increased performance, computational hardware is becoming more powerful and diverse in terms of components. For a predictive model to achieve optimal performance across systems, scientific computing must keep up with stateoftheart invention. The High Performance ParallelX (HPX) code currently under development in the STORM project is a completely new foundation that is designed to be flexible and easily integrable with other architectures. By utilizing HPX, the software enables computations to run more efficiently on modern supercomputing systems. Moreover, it is well equipped to handle the inevitable future of hardware development.
Research Group
CHG Researchers:
 Clint Dawson, The University of Texas at Austin
 Craig Michowski, The University of Texas at Austin
 Jennifer Proft, The University of Texas at Austin
Collaborators:
 Hartmut Kaiser, Lousiana State University
 Joannes Westerink, The University of Notre Dame
 Richard A. Luettich, The University of North Carolina at Chapel Hill
 Jim Blackburn, SSPEED Center, Rice University
 Phil Bedient, SSPEED Center, Rice University
 Larry Dunbar, SSPEED Center, Rice University
Funding sources:
 National Science Foundation grant NSF ACI 1339801.
 Houston Endowment, SSPEED Center grant.
Related Links:
 Prepping for the STORM: Clint Dawson Receives $3M NSF Grant to Overhaul Storm Surge Code
 Rice wins $3.1M to develop storm strategy for HoustonGalveston
Acknowledgements:
This webpage was designed in part by Lindley Graham, NSF GRFP doctoral fellow.
Contact
For any questions regarding the 2009 TAMMS conference, please contact:
 Name
 Rhys Ulerich
 siam@ices.utexas.edu
 Phone
 5126637669
 Post

Rhys Ulerich
201 E. 24th St
ACE 4.102
1 University Station C0200
Austin, Texas 78712
TAMMS 2009 Group Photo
The individuals in the photo are, from left to right and front to back: Yan Li, Yulia Hristova, Pearl Flath, Dr. Raegan Higgins, Rhys Ulerich, Linh Nguyen, Christopher Mirabito, Robert Rosenbaum, Toby Isaac, Ryan Nong, Kaleb McKale, Moritz Allmaras, Dimitar Trenev, Sean Hardesty, Anthony Kellems, and Omar Al Hinai.
The photo was taken by Khoa Tran of U.T. Austin.
Hotels
There are a variety of hotels within a fifteen minute drive from the University of Texas. Prices vary widely. Downtown hotels are generally the most expensive. Two relatively reasonable options are:
 La Quinta Inn Austin Capitol

300 E. 11th St.
Austin, TX 78701
(512) 4761166
 Days Inn Austin/University/Downtown

3105 N I35
I35 & 32nd Street
Austin, TX 78722
5124781631
Keynote speaker: Dr. Raegan Higgins
TAMMS was proud to have Dr. Raegan Higgins give the keynote at our conference. She presented on Friday, March 27th in CPE 2.212 at 4:45 PM.
"An Introduction to the Time Scale Calculus"
A time scale T is just a closed nonempty subset of the real numbers. Time scales include the real numbers, the integers, and the Cantor set. Given a smooth function p(t) defined on a time scale and a point s in the time scale we will define a generalized exponential function e_{p}(t,s) which generalizes the exponential function e^{pt} studied in calculus.
Brief Biography
Raegan Higgins received a B.S. degree in mathematics from Xavier University of Louisiana in 2002 , and the degrees of M.S. (2004) and Ph.D. (2008) from the University of NebraskaLincoln. Her dissertation work was in the area of oscillation criteria for dynamic equations on time scales.
Dr. Higgins' current research is in time scales; her interests focus on oscillation criteria for certain linear and nonlinear second order dynamic equations. She is also interested in issues that affect preservice teachers ability to teach mathematics.
Location
On Friday, March 27th the conference was in the Chemical and Petroleum Engineering Building (CPE) room 2.212. On Saturday, March 28th the conference was in in Robert Lee Moore Hall (RLM) room 4.102. Both buildings are at the corner of Speedway & E Dean Keeton St in the Engineering Area of the University of Texas at Austin campus.
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Texas Applied Mathematics Meeting for Students
The Austin Chapter of SIAM was proud to host the 2009 Texas Applied Mathematics Meeting for Students (TAMMS) on March 27–28th. Attendees had an opportunity both to present their own research and to meet fellow SIAM student members from other Texas institutions.
 Date & time:
 Friday, March 27th from 2 PM—6 PM
 Saturday, March 28th from 8 AM—12:30 PM
 Location:
 CPE 2.212 on Friday
 RLM 4.102 on Saturday
 Activities:
 Student presentations
 Keynote: Dr. Raegan Higgins
 Group dinner on Friday night at Sao Paulo's
 Participating schools:
 U.T. Austin Chapter of SIAM
 Rice University
 Texas Tech University
 Texas A&M University
 University of Houston
Parking
We recommend that visitors to our campus park at either the Speedway Garage (SWG) or the 27th Street Garage (TSG). From the Speedway garage, it will take you seven minutes to walk to either CPE on Friday or RLM on Saturday. From the 27th street garage, it will take you ten minutes to walk to these two buildings.
Garage parking rates as well as a printable campus visitor map are available from Parking and Transportation Services.
Registration
To register for the 2009 Texas Applied Mathematics Meeting for Students, please email siam@ices.utexas.edu and include your
 Full name
 Position (undergraduate, graduate, faculty)
 Department
 Institution
At this time, all of our student speaking slots are full. Please indicate in your registration note if you would like to be waitlisted for a speaking opportunity.
The registration fee is $10 if you register in advance or at the door. Registration does not cover the cost of Friday night dinner.
Meeting Schedule
The following talks took place at the conference.
Friday, March 27th 2009 in CPE 2.212
 2:00–2:30 PM
 Arrival & registration
 2:30–2:45 PM
 Welcoming remarks
 2:45–3:15 PM

James MartinComputational and Applied MathematicsUT AustinA Stochastic Newton's Method for Bayesian Inverse Problems
We present a new MCMC method for sampling highdimensional, expensivetoevaluate probability density functions. We improve upon Langevin sampling by using local Hessian information to guide sampling, drastically improving acceptance probabilities and MCMC convergence rates. The resulting method resembles a stochastic variant of Newton's method. We demonstrate by solving a statistical inverse problem governed by 1D seismic wave propagation with up to 65 parameter dimensions, for which the new method is two orders of magnitude faster than conventional MCMC.
 3:15–3:45 PM

Yulia HristovaMathematicsTexas A&M UniversityTime reversal in thermoacoustic tomography  an error estimate
In thermoacoustic tomography an object is irradiated by a short electromagnetic pulse and the absorbed energy causes a thermoelastic expansion. This expansion leads to a pressure wave propagating through the object. The goal of thermoacoustic tomography is the recovery of the initial pressure inside the object from measurements of the pressure wave made on a surface surrounding the object. The time reversal method can be used for approximating the initial pressure when the sound speed inside the object is variable (nontrapping as well as trapping).
In this talk I will present error estimates for the time reversal method in the cases of variable, nontrapping sound speeds.
 3:45–4:15 PM

Jay RaolComputational and Applied MathematicsRice UniversityUsing Fast Activating Voltage Sensitive Calcium Channels as Voltage Sensors
Calcium plays an important role in neuroscience. Not only is it involved in the pathways that govern learning events in neurons, but it is increasingly being used as the primary means of accessing information about the neuron's state. Unfortunately, for most physiologists, calcium information is an incomplete picture of the neuron.
We developed an algorithm to convert fluorescent calcium data into voltage and conductance information. We simulate our algorithm on synthetic data to illustrate its usefulness.
 4:15–4:45 PM
 Coffee Break
 4:45–5:30 PM

Dr. Raegan HigginsMathematics and StatisticsTexas Tech UniversityAn Introduction to the Time Scale Calculus
A time scale T is just a closed nonempty subset of the real numbers. Time scales include the real numbers, the integers, and the Cantor set. Given a smooth function p(t) defined on a time scale and a point s in the time scale we will define a generalized exponential function e_{p}(t,s) which generalizes the exponential function e^{pt} studied in calculus.
 5:30–6:00 PM

Moritz AllmarasMathematicsTexas A&M UniversityUltrasound Modulated Optical Tomography: Reconstructions for a Differential Model
Ultrasound Modulated Optical Tomography attempts to improve the severe illposedness of the reconstruction problem arising in classical Optical Tomography by combining the advantages of Optical Tomography with those of ultrasound imaging. In this talk, a model is introduced that describes the effect of ultrasound modulation on the light intensity by two coupled diffusion equations, one for the original, unaffected photon intensity and one for a second, virtual intensity field modulated at ultrasound frequency.
In contrast to previous statisticsbased approaches, this model allows reconstruction of the absorption coefficient by using efficient, PDEbased solutions for the forward problem. A simple reconstruction algorithm is introduced to demonstrate the feasibility of this reconstruction for 2D problems and wellfocused ultrasound signals. For the more realistic case of nonfocused ultrasound signals, reconstruction techniques based on inversion of certain integral transforms are suggested. For both of these cases, numerical reconstruction results for artificial absorption phantoms are presented.
 6:45–???

Dinner at Sao Paulo's Brazilian Restaurante, 2809 San Jacinto Blvd.
Saturday, March 28th 2009 in RLM 4.102
 8:00–8:30 AM

Sean HardestyComputational and Applied MathematicsRice UniversityOptimization of Shell Structure Acoustics
Modeling of elastic shell structures coupled with acoustics in a way that is suitable for optimization poses a multitude of challenges. For the exterior problem, it is convenient to use shell elements in conjunction with boundary elements so that shape updates can be performed without modifying the mesh. In order to do so, the shell code must be free of the socalled locking phenomenon, and the boundary element code must be robust and reasonably fast. With the aim of making the implementation of the coupling and adjoint equations as simple as possible, we describe a scheme satisfying these criteria, and present some numerical results.
 8:30–9:00 AM

Anthony R. KellemsComputational and Applied MathematicsRice UniversityDimension Reduction Techniques that Capture Nonlinear Behavior of Morphologically Accurate Neuronal Models
Simulating active neurons with realistic morphologies and synaptic inputs requires the solution of large systems of nonlinear ordinary differential equations. Using model reduction techniques of proper orthogonal decomposition and an empirical interpolation method, we recover the complete neuronal voltage dynamics using a system of dimension nearly two orders of magnitude smaller than the original and that simulates one order of magnitude faster, without sacrificing the spatiallydistributed input structure.
 9:00–9:30 AM

Yan LiMathematicsTexas A&M UniversityLocalGlobal Upscaling of Flow and Transport in heterogeneous porous media
Flow and transport in subsurface formations are affected by geological variability over multiple length scales. We develop a localglobal twophase upscaling approach to generate upscaled transport functions. The upscaling of multiphase flow parameters is challenging due to their strong dependency on global flow effects. The localglobal twophase upscaling directly incorporates global coarsescale twophase solutions into local twophase upscaling calculations. It effectively captures the impact of global flow, while avoiding global twophase finescale simulations. The local boundary conditions are updated with timedependent coarsescale solutions. It therefore captures the global flow effects both spatially and temporally. The method is applied to permeability distributions with various correlation lengths. Numerical results show that it consistently improves existing twophase upscaling methods (e.g., upscaling with effective flux boundary conditions), and provides accurate coarsescale solutions for both flow and transport.
 9:30–10:00 AM

Ryan NongComputational and Applied MathematicsRice UniversityNumerical Solutions of Matrix Equations Arising in Model Order Reduction for LinearTimeInvariant Systems in the LargeScale Setting
Balanced truncation and positive real balancing techniques in dimension reduction for lineartimeinvariant dynamical systems require the solution of multiple largescale matrix equations. Current iterative solvers include the approximate power method (APM) and the alternating direction implicit (ADI) method. The former is parameter free and tends to be efficient in practice but there is little theoretical understanding of its convergence properties. The latter has a well understood convergence theory but relies heavily upon heuristic parameter selection for rapid convergence. In this talk, I will first introduce a novel algorithm that is based on a synthesis of the two aforementioned techniques. This parameter free ADIlike (PFADI) technique uses an APM iteration as a means to bypass the trouble in parameter selection of the ADI method but still preserves its convergence properties. I will then present new results in optimizing the performance of the PFADI method.
 10:00–10:30 PM
 Coffee Break
 10:30–11:00 AM

Dimitar TrenevMathematicsTexas A&M UniversityApproximating solutions of infinite domain Laplace and Helmholtz problems
In this talk I will discuss the main difficulties that arise when employing the finite element method to approximately solve PDEs posed on infinite domains. I will then present a simple way of overcoming them for the cases of exterior Laplace and Helmholtz problems. Additionally this talk will serve as an introduction to the Perfectly Matched Layer technique  the leading artificial boundary condition for acoustic and electromagnetic scattering problems.
 11:00–11:30 AM

Robert RosenbaumMathematicsUniversity of HoustonCorrelation Propagation in Networks of IntegrateandFire Neurons
Experimental results show that correlations between the spiking activity of neurons are used to encode information about some stimuli. However, experimental and theoretical results show that excess correlation can accumulate in feedforward networks and lead to pathological spiking behaviors. I will discuss some work on correlation transfer properties of analytically tractable neuron models and implications on the activity of feedforward networks.
 11:30–12:00 AM

Linh NguyenMathematicsTexas A&M UniversityOn inversion formula in Thermoacoustic Tomography
We present a family of inversion formulas in Thermoacoustic Tomography that contains as special cases most of previously known closed form reconstructions for acoustically homogeneous media.
 12:00–12:30 AM

Pearl FlathComputational and Applied MathematicsUT AustinFast algorithms for uncertainty estimation in large scale linear dynamical systems
We consider the problem of estimating and propagating the uncertainty in the initial condition field of a convectiondiffusion problem describing the transport of atmospheric contaminants. Estimation of the uncertainty is treated within a Bayesian framework. Standard Markov chain Monte Carlo approaches are intractable for such highdimensional problems. Even when the data and prior uncertainty are Gaussian, and as a result the posterior estimate is Gaussian with covariance given by the inverse of the Hessian matrix of the regularized least squares objective, the computation of the exact covariance matrix is intractable due to the large size and extreme cost of forming the inverse of the Hessian. In the case of linear illposed inverse problems, we show that fast algorithms can be constructed that provide accurate low rank Hessian approximations of the least squares data misfit, and as a result permit estimation and propagation of the uncertainty for largescale problems at a small multiple of the cost of solving the forward problem. Largescale examples demonstrate the main ideas.
 12:30–12:45 PM
 Concluding remarks
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