1. SCHOOL OF INFORMATION UNIVERSITY OF MICHIGAN The NEESgrid Experience: 2000 - 2003 Tom Finholt School of Information University of Michigan This work was supported primarily by the George E. Brown, Jr. Network for Earthquake Engineering Simulation (NEES) program of the National Science Foundation under award number CMS-0117853. Support was also provided by the National Science Foundation through the ITR program under award number IIS-0085951.

2. SCHOOL OF INFORMATION UNIVERSITY OF MICHIGAN Outline n The earthquake engineering community n The George E. Brown, Jr. Network for Earthquake Engineering Simulation n NEESgrid – the collaboratory element of NEES n Challenges & Successes n The field of dreams

3. SCHOOL OF INFORMATION UNIVERSITY OF MICHIGAN The earthquake engineering community n Research –University-based –Funded by NSF and industry –Focus on simulation Physical models (e.g., reduced scale specimens) Numerical models (e.g., finite element analysis) n Practice –Professional firms –Structural engineering (e.g., earthquake remediation) –Formulation of uniform building codes –Lifelines (e.g., ensure survival of roads, gaslines, power distribution)

4. SCHOOL OF INFORMATION UNIVERSITY OF MICHIGAN Bhuj, India. One of the towers of this apartment complex totally collapsed,and the central stairway leaned on another building of the complex. Photo courtesy of Dr. J.P. Bardet, University of Southern California http://geoinfo.usc.edu/gees/RecentEQ/India_Gujarat/Report/Damage/Bhuj/Bardet_Feb18.html

5. SCHOOL OF INFORMATION UNIVERSITY OF MICHIGAN Instruments n Structural –reaction walls –shake tables –field test n Geotechnical –centrifuges –field test n Tsunami –wave basins

6. SCHOOL OF INFORMATION UNIVERSITY OF MICHIGAN Shake table: Nevada, Reno

7. SCHOOL OF INFORMATION UNIVERSITY OF MICHIGAN Reaction wall: Minnesota

8. SCHOOL OF INFORMATION UNIVERSITY OF MICHIGAN Centrifuge: UC Davis

9. SCHOOL OF INFORMATION UNIVERSITY OF MICHIGAN Wave basin: Oregon State

10. SCHOOL OF INFORMATION UNIVERSITY OF MICHIGAN Survey methods n Technical surveys –Response from fourteen of fifteen sites n Practice survey (2002) –Administered to 444 engineers –187 responses (42%) 11% non-NEES equipment sites 9% women 56% students 39% from Year 1 (26% repeat response rate)

11. SCHOOL OF INFORMATION UNIVERSITY OF MICHIGAN Practice survey: Data use

12. SCHOOL OF INFORMATION UNIVERSITY OF MICHIGAN Practice survey: Collaboration 20012002 Item MeanSDMeanSD Number of collaborations you are currently involved with 2.56.12.34.7 Number of collaborations with remote participants 1.43.21.33.6 Number of collaborators on your primary collaboration 5.77.16.17.3 Number of collaborators from prior collaborations in primary collaboration 1.63.11.73.0

13. SCHOOL OF INFORMATION UNIVERSITY OF MICHIGAN George E. Brown, Jr. Network for Earthquake Engineering Simulation n NSF Major Research Equipment and Facility Construction award (MRE) n $82 million, 2001-04 –$10 million for system integration (NCSA, ANL, USC-ISI, Michigan, Oklahoma) –$2 million for consortium development (CUREE) –$60 million for new equipment sites 3 shake tables (Buffalo, Nevada-Reno, UCSD) 2 centrifuges (RPI, UC Davis) 5 reaction walls (Berkeley, Buffalo, Colorado, Illinois, Lehigh, Minnesota) 3 field test (Texas, UCSB/USC/BYU, UCLA) 1 lifeline (Cornell) 1 tsunami (Oregon State)

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15. SCHOOL OF INFORMATION UNIVERSITY OF MICHIGAN NEES expectations n Community survey (2002) Stratified on region (six regions – CA, NW, SW, MW, SE, NE) and sub-field (e.g., structural, geotechnical etc.) EERI membership roll and key tsunami mailing lists as sampling frame n = 361 (99 responses; 27%) n Workshop survey (2002) Registered participants in nineteen of the twenty regional workshops –The survey administration was not ready for the first workshop held in Charleston, SC n = 287 (260 responses; 91%)

16. SCHOOL OF INFORMATION UNIVERSITY OF MICHIGAN Summary of survey results n Workshop and community respondents share consensus about NEES expectations –…but level of agreement is much higher among workshop respondents n Access to experimental data is paramount –…and is more important than access to experimental facilities for both workshop and community respondents n Producing standard data formats is a critical goal n Workshop respondents skewed toward academic, structural earthquake engineers

17. SCHOOL OF INFORMATION UNIVERSITY OF MICHIGAN Why is NEES exciting? n Funding –scientists recruited through the NEES equipment site program and through the NEES grand challenge program n Recognition –innovative system –highly visible to earthquake engineering and computer science communities (e.g., SC 2002 demo) n Novel capabilities –first operational use of Globus/OGSA technology –“hybrid” operations -- combining numerical and physical simulations

18. SCHOOL OF INFORMATION UNIVERSITY OF MICHIGAN NEESgrid – the collaboratory element of NEES n Primary –Shared instrument –Community data system n Secondary –Distributed research center –Virtual community of practice

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20. SCHOOL OF INFORMATION UNIVERSITY OF MICHIGAN Technology involved n Globus/OGSA (USC ISI and ANL) –GSI and Gridftp n CHEF (Michigan) n Telepresence systems (ANL) n Data repository (NCSA) n Deployment, operations, and support (NCSA)

21. SCHOOL OF INFORMATION UNIVERSITY OF MICHIGAN What’s A Grid? http:// Web: Uniform access to documents Grid: Flexible, high- performance access to resources for distributed communities Sensors and instruments Data archives Computers Software catalogs Colleagues Source: Harvey Newman, Caltech

22. SCHOOL OF INFORMATION UNIVERSITY OF MICHIGAN NEESgrid High-Level Architecture n Capabilities –data, simulation, collaboration, visualization, telepresence validated and improved via EA demonstration scenarios and delivered via –APIs and tools for users –services and interfaces at equipment and resource sites –management services for operation System Resources: Compute, Network, Data Storage, Testing Sites Grid Resource Management Middleware APIs Supporting Higher Level Information Services Collaboration Services Data & Information Services Telepresence Services Simulation & Analysis Services Portal, Web and 3 rd Party End User Interfaces APIs, Tools and Libraries Supporting End User Interfaces

23. SCHOOL OF INFORMATION UNIVERSITY OF MICHIGAN NEESgrid interface

24. SCHOOL OF INFORMATION UNIVERSITY OF MICHIGAN System evolution n Scoping study –NCSA, ISI, ANL, UM n Alpha 1.0 –demonstrated at UNR, November 2002 –released February 2003 n Alpha 1.1 –released June 2003 n MOST experiment –real-time control of reaction wall from numerical simulation –UIUC and Colorado, July 2003

25. SCHOOL OF INFORMATION UNIVERSITY OF MICHIGAN Multi-Site, On-Line Simulation Test (MOST) July 2003 UIUC Experimental Model f1f1 m1m1 NCSA Computational Model m1m1 f1f1 f2f2 f2f2 Colorado Experimental Model SAC Consortium Benchmark Structure

26. SCHOOL OF INFORMATION UNIVERSITY OF MICHIGAN Multi-Site, On-Line Simulation Test (MOST) Colorado Experimental Model f2f2 m 1,  1 F2F2 F1F1 e = f 1, x 1 UIUC Experimental Model m1m1 f1f1 f2f2 NCSA Computational Model SIMULATIONCOORDINATOR NEESpop UIUC MUST-SIM Dan Abrams Amr Elnashai Dan Kuchma Bill Spencer and others Colorado FHT Benson Shing and others

27. SCHOOL OF INFORMATION UNIVERSITY OF MICHIGAN MOST Column Test Specimens Illinois Test Specimen Colorado Test Specimen

28. SCHOOL OF INFORMATION UNIVERSITY OF MICHIGAN Challenges n Confused lines of authority n Cultural differences –Different jargon –Different world views

29. SCHOOL OF INFORMATION UNIVERSITY OF MICHIGAN Confused lines of authority n NEES program (2000-2004) –NEESgrid, system integration –NEES Consortium Development –15 equipment sites n NEES Consortium (2003-2014) –Board and Executive Committee –Standing Committees

30. BYU/UCSB/USC Les Youd

33. SCHOOL OF INFORMATION UNIVERSITY OF MICHIGAN Earthquake engineers – in Hofstede’s scheme n Power distance –Hierarchical –Bias toward seniority n Individualist –“My lab is my empire” –Solo PI model n Masculine –Adversarial –Competitive n Uncertainty avoidance –Highly skeptical of new technologies –Extremely risk adverse

34. SCHOOL OF INFORMATION UNIVERSITY OF MICHIGAN Grid specialists – in Hofstede’s scheme n Power distance –Egalitarian at development level –Bias toward talent n Collectivist –Use the Internet to create worldwide communities –Project model n Masculine –Adversarial –Competitive n Uncertainty avoidance –Extremely open to new technologies –Extremely risk seeking

35. SCHOOL OF INFORMATION UNIVERSITY OF MICHIGAN Agreeing on terms

36. SCHOOL OF INFORMATION UNIVERSITY OF MICHIGAN How earthquake engineers think Customer Need Customer Requirements Requirements Analysis Structure Design Structure Construction Structure Acceptance Structure Operations Customer Needs Assessment Design, Engineering, and Development Deployment and Operations Progress Feedback

37. SCHOOL OF INFORMATION UNIVERSITY OF MICHIGAN Prelim Analysis START Prelim Design Prototyping Proto EvaluationSystem AnalysisSystem DesignEvaluation Implementation More Iterations How grid specialists think

38. SCHOOL OF INFORMATION UNIVERSITY OF MICHIGAN Successes n Scientific –First teleobservation of shake table (November 2002) –First data saved to repository (November 2002) n Community –NEES Consortium incorporated (January 2003) –First NEES Consortium meeting (May 2003) –Use of prototype tools n Future –MOST experiment, July 2003 –Operational collaboratory October 1, 2004

39. SCHOOL OF INFORMATION UNIVERSITY OF MICHIGAN NEESgrid November 2002 Demonstration n Earthquake simulation at UNR early adopter site –biaxial shake table with cameras and instrumentation –40% scale model of a two span bridge concrete slab over steel girders n Bridge model instrumented with sensors –strain gauges, load cells, displacement, acceleration

40. SCHOOL OF INFORMATION UNIVERSITY OF MICHIGAN NEESgrid November 2002 Demonstration n CHEF-based collaborative framework n Electronic notebook for data recording n Experiment management tools –data and metadata n Streaming data and video –teleobservation of experiment –data channels from sensors n Data analysis and visualization SAP2000  model Tele-observation

41. SCHOOL OF INFORMATION UNIVERSITY OF MICHIGAN Prototype tool use n H.323 videoconferencing n Worktools n Placeware

42. SCHOOL OF INFORMATION UNIVERSITY OF MICHIGAN Use of H.323 videoconferencing UNR Demo b cd a = initial ES-TF meeting; b = ES-TF meeting time changed; c = succession to new ES-TF chair; d = change to biweekly ES-TF meetings a NSF LAN meetings

43. SCHOOL OF INFORMATION UNIVERSITY OF MICHIGAN Use of H.323 videoconferencing

44. SCHOOL OF INFORMATION UNIVERSITY OF MICHIGAN Use of H.323 videoconferencing

45. SCHOOL OF INFORMATION UNIVERSITY OF MICHIGAN Use of Worktools

46. SCHOOL OF INFORMATION UNIVERSITY OF MICHIGAN Use of Worktools

47. SCHOOL OF INFORMATION UNIVERSITY OF MICHIGAN Use of Worktools

48. SCHOOL OF INFORMATION UNIVERSITY OF MICHIGAN Use of Worktools

49. SCHOOL OF INFORMATION UNIVERSITY OF MICHIGAN The field of dreams I was sitting on the verandah of my farm house in eastern Iowa when a voice clearly said to me, “If you build it, he will come.” – Ray Kinsella in Shoeless Joe, by W.P. Kinsella Image source: http://www.fieldofdreamsmoviesite.com/

50. SCHOOL OF INFORMATION UNIVERSITY OF MICHIGAN Building it so they will come… n Balance contributions (pp. 50-51 in the Atkins report) –Weight domain science too heavily? Overemphasize procurement of existing technologies Computer scientists become viewed as “merely” consultants and implementers –Weight computer science too heavily? End user needs insufficiently addressed Emphasis on novelty at the expense of usability and stability Source: Atkins report --http://www.communitytechnology.org/nsf_ci_report/

51. SCHOOL OF INFORMATION UNIVERSITY OF MICHIGAN Innovation Extrapolatio n Social &Technological Forces digital libraries computational grids video conferencing electronic journals distance learning electronic commerce collaboratories community networks e-science Innovation vs. extrapolation

52. SCHOOL OF INFORMATION UNIVERSITY OF MICHIGAN Building it so they will come… n Give users objects to think with (scenarios, mock-ups, prototypes) n Be patient…let users convince themselves n Know where you’ve been (collect baseline data) and what’s changed (collect data as you go along)

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