Post E vent Data Collection Case Studies Andre R. Barbosa, Ph.D. - - PowerPoint PPT Presentation

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Post E vent Data Collection Case Studies Andre R. Barbosa, Ph.D. - - PowerPoint PPT Presentation

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Post E vent Data Collection Case Studies Andre R. Barbosa, Ph.D. Assistant Professor of Structural Engineering EERI & DOGAMI: Post-Earthquake Reconnaissance Workshop Portland, Oregon, April 9, 2018 Nepal 2015 Italy 2015 Napa 2014 China

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Post E vent Data Collection Case Studies

Andre R. Barbosa, Ph.D. Assistant Professor of Structural Engineering

EERI & DOGAMI: Post-Earthquake Reconnaissance Workshop Portland, Oregon, April 9, 2018

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Andre Barbosa

  • Structures
  • Critical facilities
  • Resilience

Michael Olsen

  • Geomatics
  • Hazard Mapping

Chile 2010 MO NZ 2011, NZ 2017 MO Napa 2014 AB,EF, MO Italy 2015 EF Japan 2011 MO China 2014 HW Nepal 2015 AB, MO Mexico 2017 AB,EF, HW Haizhong Wang

  • Transportation
  • Mobility

Erica Fischer

  • Structures
  • Utility Networks
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Geomatics

Michael Olsen Michael.Olsen@oregonstate.edu

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Geomatics Tech + Applications

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3D Laser Scanning – Web viewer

2016 Kaikoura E arthquake

Geotechnical Coastal Structural Transportation Michael Olsen

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Seeing the full picture

  • Unprecedented quantity

and quality of data

  • High-resolution, systematic data

collection (reduce biases; increase certainty)

  • Shift from 2D to 3D\ 4D; leads to

new analysis and scientific approaches that consider the 3D\ 4D nature of these hazards and the systems affected by them

  • Broad range of spatial and

temporal scales

  • Collection and integration of

engineering, and natural and social science data sets

  • Greatly expanded

community of reconnaissance investigators

Damaged Train Culvert, New Zealand, GEER 2016

Michael Olsen

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UAS and TLS APPLICATIONS

Geotechnical Structural

  • Liquefaction\Lateral

spreading

  • Landslide\slope stability
  • Coastal erosion
  • Settlement
  • Scour (depth distribution and

volume)

  • Surface rupture
  • Quay, retaining & sea wall

failures

  • Topographic analysis
  • Sediment accretion
  • Subsidence
  • Geomorphic change

detection

  • Structural deformations\

displacements\ deflections\ rotations

  • Shear and other crack

analysis (orientation, location, distribution, width (larger cracks), etc.)

  • Bridge collapse analysis
  • Spalled concrete

quantification

  • Concrete wall blow-out/in

failure analysis

  • Permanent soil structure

interactions

  • Fatigue analysis
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  • TLS preserves the data virtually, so you can explore anytime, anywhere

without safety concerns and logistics -> Virtual Time Capsule

  • TLS provides data to generate, validate, and/or calibrate numerical models
  • For structural analysis, TLS provides more information than can typically be

used in current models

  • TLS records vital information regarding surrounding terrain and objects
  • > helps place the interpretation of the data in context
  • TLS maps the location, distribution, and patterns of deformations compared

to relatively few traditional measurements and observations

UAS and SFM in RE CON

Michael Olsen

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Structures

Andre Barbosa Andre.Barbosa@oregonstate.edu Erica Fischer erica.fischer@oregonstate.edu

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Building E valuations

GREEN: 10,140 YELLOW: 3,814 RED: 3,229 PINK: 1,109

https://plataforma.cdmx.gob.mx/

  • Green:

– “Low Risk”: No Restriction

  • Yellow:

– “Serious Damage”/”Uncertain Risk”: Restricted access

  • Red:

– “High Risk”: No access

Credit: N. Trujillo Reid Middleton

Mexico City, 2017 Erica Fischer and Erik Bishop

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Damage Assessment Urban Centers

https://doi.org/10.1193/010817EQS009M Nepal, 2015

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Damage Assessment Urban Centers

1 4 7 9 3 2 5 3 9 19 15 9 6 11 13 19 15 10 2 6 6 3 5 1 D0 D1 D2 D3 D4 D5

Number of Biuildings Damage Level

2-story 3-story 4-story 5-story Barbosa and Olsen https://doi.org/10.1193/010817EQS009M

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Damage Assessment Urban Centers

 UAV flight plan for damage assessment

Nepal, 2015 Dan Gillins, Michael Olsen, Andre Barbosa

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 Correlation of UAV based damage assessment with visual damage assessment

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 1600 overlapping photos were taken with Sony A5000 and Go-Pro Hero cameras

mounted on multi-rotor UAVs. The photos were processed in Structure-from- Motion software to output 3D models and ortho-rectified aerial imagery. These

  • utputs were geo-referenced to real-world coordinates by establishing ground

control points in the study area by a static differential GPS survey (Dan Gillins)

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Impact of Retrofits Cripple Walls

Napa, 2014

Cripple wall collapse Cripple wall, and porch roof collapsed (Photo: B. Mathieson and J. Maffei)

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Impact of Retrofits Cripple Walls

Napa, 2014

Retrofit Success: Cripple wall and sliding failures are preventable with inexpensive retrofits (Photos: S. Pryor)

  • Yellow house: cripple wall failure.
  • Blue house: Retrofitted taller house with taller

cripple wall did not fail

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Impact of Policy Change Unreinforced Masonry

  • Failures were typically observed where walls lack ties

to roof and/or walls, but also some instances where some ties were present. Minimal retrofit with wall-to-floor ties Brick masonry, no retrofit

Napa, 2014

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Photo: Marko Schotanus

Clearly retrofitted.

Photo: David McCormick

Impact of Policy Change Unreinforced Masonry

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Unreinforced Masonry

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Detailed Damage Assessment

Nepal, 2015 Andre Barbosa, Michael Olsen

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Detailed Damage Assessment

Nepal, 2015 Post-earthquake Dynamic Characterization of Frequencies, Mode Shapes, and Damping

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Detailed Damage Assessment

Nepal, 2015

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Detailed Damage Assessment

Nepal, 2015 https://www.frontiersin.org/articles/10.3389/fbuil.2017.00011/full https://doi.org/10.1193/051017EQS087M

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Critical Facilities Lifelines and Interdependencies

Andre Barbosa Andre.Barbosa@oregonstate.edu Erica Fischer erica.fischer@oregonstate.edu Andre Barbosa Andre.Barbosa@oregonstate.edu Haizhong Wang Haizhong.Wang@oregonstate.edu Michael Olsen Andre.Barbosa@oregonstate.edu Erica Fischer erica.fischer@oregonstate.edu

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Lifelines Interdependencies

Performance of engineered lifeline infrastructure Business continuity after the earthquake Performance of community after the earthquake Performance

  • f critical

facilities after an earthquake Mexico, 2017

EERI Resilience Observatory Framework

Based on preliminary data (by Erica Fischer)

Erica Fischer and Andre Barbosa

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Highway Structures

Bridges Tunnels Culverts Walls Embankments Overhead Signs

NCHRP Report 833

  • Developed a process for assessing highway structures in emergency situations.
  • Developed guidelines for coding and marking.
  • Produced training and implementation material.
  • Prepared materials in a format that facilitates acceptance and adoption (e.g., AASHTO).
  • Improved coordination with other agencies who are involved in emergency response.

Michael Olsen (PI), Andre Barbosa; Marc Veletsos; Zhiqiang Chen; MPN Components; Advanced Infrastructure Design

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Data Collection

E xperiential E vacuation Drills

8/10 (Light Blue (NEW)) — HMSC-REU/OMSI After Dark 2 7/13 (Violet) — HMSC-REU After Dark 1 6/26 (Turquoise) — CCE SURF students 6/16 (Brown) — HMSC evacuation 5/11 (Orange) — OPRD, SBSP 2/18 (Magenta) — First try ABM (Yellow Triangle)

Haizhong Wang

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Use of Smartphone App to Track Individuals in Drills

Haizhong Wang

Data Collection

E xperiential E vacuation Drills

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Conclusion

  • Terrestrial Laser Scanning (TLS) can be extremely useful at the urban and

infrastructure element scale for post-event data collection since it: – Has multiple applications and allows for data to be preserved and visualized data virtually, so you can explore anytime, anywhere without safety concerns and logistics -> Virtual Time Capsule – Maps the location, distribution, and patterns of damage, compared to relatively few traditional measurements and observations – Provides more information than can typically be used in current analysis models

  • Unmanned Aerial Systems (UAS) can be extremely useful to characterize

damage at an Urban Scale, and also at the infrastructure element scale

  • Detailed damage assessments can rely on structural health monitoring tools

combined combined with TLS and UAS.

  • Restoration time and recovery data need to be collected (currently lacking)
  • Evacuation drills and apps allow for communication of the risk, and also to

train systems for data collection during/after the event

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Thank you!

andre.barbosa@oregonstate.edu

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Virtual E arthquake Reconnaissance Team (VE RT)

Email VERT Co-Chairs: Erica Fischer erica.fischer@oregonstate.edu Manny Hakhameneshi manny.hakha@gmail.com

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What is VE RT?

Team of EERI Mem bers that assist EERI virtually after an earthquake Blogging/ curating EERI Clearinghouse Interfacing with on-site EERI members Assisting EERI Learning from Earthquake team prepare for deployment Assisting reconnaissance team members post-process data Participating in potential research projects

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What has VE RT done so far?

Nepal (2015)  Virtual earthquake clearinghouse blogging  Post-processing photos and data from field Ecuador (2016)  Virtual earthquake clearinghouse blogging  Post-processing photos and data from field  Assisting Exponent in mini-research project Taiwan (2016)  Virtual earthquake clearinghouse blogging  Post-processing photos and data from field Italy (2016 & 2017)  Virtual earthquake clearinghouse blogging Mexico (Puebla-Morelos & Chiapas) (2017)  Virtual earthquake clearinghouse blogging Topics: Hospitals Schools Infrastructure Geotechnical issues Seismicity Emergency Response … and more!