APSSRA Shinozuka Memorial session

Memories of Prof. M. Shinozuka - Stochastic FEM, Lifelines, and Remote Sensing -

October 7, 2020

Fumio Yamazaki Research Fellow, NIED, . Professor Emeritus, Chiba University, Japan.

1 History of Prof. M. Shinozuka Year Prof. Masanobu Shinozuka Affiliation Research topics

1930 1930.12.23 born in Tokyo

1940 1950 1953 BS, Kyoto University Kyoto reliability theory 1955 MS, Kyoto University Columbia 1960 1960 PhD, Columbia Monte Carlo simulation 1969 Professor 1970 Columbia system identification/control, stochastic dynamics

1980 Columbia lifeline 1988 Princeton stochastic FEM 1990 1990 Director, NCEER Princeton earthquake engineering 1995 USC USC advanced technologies (including remote sensing and GIS) 2000 2001 UC Irvine USC risk management UC Irvine monitoring of infrastructures 2010 2010. 12.23 80th Birthday Columbia 2018 2018. 11. 5 passed away 2 Masanobu Shinozuka After Google Scholar Citation: 30,043 Professor of Civil Engineering and Engineering Mechanics, Columbia University h Index: 77 Continuum mechanics, stochastic processes, structural dynamics and control, earthquake and wind engineering i10 Index: 323 Title Citation Year A framework to quantitatively assess and enhance the seismic resilience of communities M Bruneau, SE Chang, RT Eguchi, GC Lee, TD O’Rourke, AM 2909 2003 Reinhorn, ...Earthquake spectra 19 (4), 733-752 Digital simulation of random processes and its applications M Shinozuka, CM Jan Journal of sound and vibration 25 (1), 111-128 1845 1972 Statistical analysis of fragility curves M Shinozuka, MQ Feng, J Lee, T Naganuma Journal of engineering mechanics 126 (12), 1224-1231 1299 2000 Simulation of stochastic processes by spectral representation M Shinozuka, G Deodatis 1233 1991 Simulation of multivariate and multidimensional random processes M Shinozuka The Journal of the Acoustical Society of America 49 (1B), 357-368 737 1971 Basic analysis of structural safety M Shinozuka Journal of Structural Engineering 109 (3), 721-740 638 1983 Monte Carlo solution of structural dynamics M Shinozuka Computers & Structures 2 (5-6), 855-874 618 1972 Neumann expansion for stochastic finite element analysis F Yamazaki, M Shinozuka, G Dasgupta Journal of engineering mechanics 114 (8), 1335-1354 610 1988

Measuring improvements in the disaster resilience of communities SE Chang, M Shinozuka Earthquake spectra 20 (3), 739-755 528 2004 Nonlinear static procedure for fragility curve development M Shinozuka, MQ Feng, HK Kim, SH Kim Journal of engineering mechanics 126 (12), 1287-1295 477 2000 Simulation of multi-dimensional Gaussian stochastic fields by spectral representation M Shinozuka, G Deodatis 451 1996 Simulation of nonstationary random process M Shinozuka, Y Sato Journal of the Engineering Mechanics Division 93 (1), 11-40 429 1967 The analysis of structural safety .AM Freudenthal, JM Garrelts, M Shinozuka Columbia Univ New York Inst For The Study Of Fatigue And Reliability 415 1964

Digital generation of non-Gaussian stochastic fields F Yamazaki, M Shinozuka Journal of Engineering Mechanics 114 (7), 1183-1197 373 1988 Random fields and stochastic finite elements E Vanmarcke, M Shinozuka, S Nakagiri, GI Schueller, M Grigoriu Structural safety 3 (3-4), 143-166 369 1986 A vision-based system for remote sensing of bridge displacement JJ Lee, M Shinozuka Ndt & E International 39 (5), 425-431 354 2006 Structural-system identification. I: Theory R Ghanem, M Shinozuka Journal of Engineering Mechanics 121 (2), 255-264 345 1995 Response variability of stochastic finite element systems M Shinozuka, G Deodatis Journal of Engineering Mechanics 114 (3), 499-519 319 1988 Real-time displacement measurement of a flexible bridge using digital image processing techniques JJ Lee, M Shinozuka Experimental mechanics 46 (1), 276 2006 105-114 3 1984-1986 Columbia University Picnic

1984/ 09/22 1986/ 08/01 ASCE congress @San Francisco

1984/ 10/06 1984/ 10/05 4 1984-1986 My research work at Columbia University Yamazaki, F. and Shinozuka, M., Digital Simulation of Non-Gaussian Stochastic Fields, Journal of Engineering Mechanics, ASCE, Vol. 114, No. 7, 1988. Citation by SCOPUS: 229 Google Scholar: 373

2D Power Spectral Density Function

Simulated sample function 5 1984 - 1986 My Research work at Columbia University Citation by SCOPUS: 389 Yamazaki, F., Shinozuka, M., and Dasgupta, G., Neumann Expansion for Stochastic Google Scholar: 610 Finite Element Analysis, Journal of Engineering Mechanics, ASCE, Vol. 114, No. 8, 1988.

6 1st International Conference on Computational Stochastic Mechanics Celebration of Shono’s 60-years Birthday Corfu, Greece, 1991.8

7 February 1999, Taipei, Taiwan 8 Lifeline and Prof. Shinozuka Seismic Performance Analysis of Electric Power Systems APEC Seminar on Earthquake Disaster Management of Energy Supply Systems Chinese Taipei September 5 and 6, 2001 M. Shinozuka University of , Irvine Fragility Curves for Transformers

% # CasticG # Sylmar # Victorvlle Rinaldi Adelanto 1 # LADWP Service Areas Valley Northridge # 0.9 #

0.8 Tarzana Toluca # # Glendale # Part of Western 0.7 Atwater # Systems Coordinating Hollywood 0.6 # St. John # Fairfax River Council’s (WSCC’s) Olympic # # 0.5 # Velasco Case1 # network covering 14 Santa Monica Bay Case2 0.4 Airport US western states, TriNet # Century USGS # # Probability of Failure Probability 0.3 Scattergood Gramercy 1 7 # 2 Canadian provinces 2 8 $ ScattergoodG 0.2 4 11 Sub_station.shp and northern part of # Receiving Station Halldale 7 $ Generating Station(Thermal) # % Power Plant(Hydro) Baja California 0.1 8 Line.shp Wilmington HynessG Area.shp 11 # $ 1 Harbor 0 2 # HarborG Ocean.shp $ 0 0.2 0.4 0.6 0.8 1 1.2 1.4 Land.shp Seal Long Beach PGA (g) Beach

9 Effect of earthquake ground motions on fragility curves of highway bridge piers based on numerical simulation Karim and Yamazaki (2001) EESD

I. Ground Motion II. Dynamic Response Analysis W=5163 kN Google Scholar: 248

cc hP=8.5 m Acceleration Time History 4 m

III. Damage Criteria Analytical Model Restoring-Force Rules A. Damage Classification Fragility curves for a 1964 pier B. Damage Indices (DI) Park and with respect to PGV Ang, 1985  C  IV. Fragility Curves DI  d  . h 1.0 u 0.8 B 1.0 A 0.8 0.6 As

0.6 P roba0.4 bility 0.4 Probability 0.2 0.2 0.0 0.0 0 200 400 600 800 1000 0 50 100 150 200 PGA (cm/s2) 10 PGV (cm/s) Prof. Shinozuka visited E-Defense construction site in Miki, Hyogo, Japan 2000. 7.13 Many US-Japan projects after 1994 Northridge and 1995 Kobe EQs

11 U.S.-Japan Cooperative Research in Urban Earthquake Disaster Mitigation 15-16 August 2001, Seattle, Washington Many US-Japan projects after 1994 Northridge and 1995 Kobe EQs

12 Remote Sensing and Prof. Shinozuka

SAR Simulation of Urban Areas Shinozuka et al. 2000 Resolution 2m by 2m 2000 MCEER-EDM Workshop @ Newport Beach

USC-DRB & KAP buildings USC-DRB building before introducing damage after introducing damage

2003 1st Remote Sensing WS @UCI 13 Extraction of Damage Areas in 1995 Kobe EQ using ERS/SAR  Difference of backscattering Matsuoka and Yamazaki (2004) EQS coefficient (1995/5/23 – 1994/6/3)  Correlation coefficient Google Scholar: 265

1 Filtering Window: 21 x 21 Calculation Window: 13 x 13 95/05-94/10 95/05-94/06 95/05-93/08 95/05-92/11 Severe 0.5 damage area

N N N

NIa i Ibi  Iai Ibi r  i 1 i 1 i 1 Very severe  N  N 2   N  N 2  0 NIa2  Ia NIb2  Ib  damage area   i  i     i  i    i 1 i 1    i 1 i 1   Correlation Coefficient of Intensity Images -3 -2 -1 0 1 2 Red: Very severe damage area 14 Difference of Backscattering Coefficient [dB] Yellow: Severe damage area 3rd International Workshop on Remote Sensing for Post-Disaster Response September 12th, 2005 Chiba University, Japan Keynote Lecture by M. Shnozuka “Application of Remote Sensing Technology in Natural Hazard Assessment”

Keynote Speaker and Karaoke Singer

15 MCEER’s Remote Sensing Program Masanobu Shinozuka University of California, Irvine Year 8 Accomplishments

1. Post-disaster damage & situation assessment

2. Field reconnaissance - damage data collection & visualization

Lat Long, Dist, status, etc.. 3. Building inventory for loss estimation

3rd International Workshop on Remote Sensing and Disaster Response, Chiba, Japan, September 12-13, 2005 MULTIDISCIPLINARY CENTER FOR EARTHQUAKE ENGINEERING RESEARCH International Symposium on Stochastic Analyses for Risk Management (SARM2010) Tokyo Forum, December 23, 2010 80th Birthday of Prof. Shinozuka

17 Emergence of Computational Stochastic Systems Response Monitoring for System Modeling and Calibration

3 Displ. Transducer 2.5 2 1.5 1 0.5

Displacement [mm] Displacement 0 15 tons 30 tons 40 tons 0 10 20 30 40 50 60 70 Time [sec]

3 Laser Vibrometer Masanobu Shinozuka 2.5 2 1.5 1

University of California, Irvine 0.5 15 tons 30 tons 40 tons

Displacement [mm] Displacement 0 0 10 20 30 40 50 60 70 Time [sec]

3 Image Processing 2.5 International Symposium on Stochastic Analysis for Risk Management (SARM 1 2010) 2 1.5 1 40 tons Tokyo International Forum, Tokyo, Japan, December 23, 2010 0.5 15 tons 30 tons

Displacement [mm] Displacement 0 18 0 10 20 30 40 50 60 70 Time [sec] 18 Detection of collapsed bridges from TerraSAR-X images

Orbit Dir. : Desc. F. Yamazaki, K. Inoue, W. Liu (2016) SM & MS Look Dir. : Right Imaging Mode : StripMap Pixel Res. : 1.25m/pix Polarization : HH Product Level : EEC

21. Oct. 2010 m m 0 100 13. Mar. 2011 0 100 0.9 Difference 20 Correlation Coefficient Jogawa Bridge Correlation coefficient, (126.0m) Difference,

d TSX data provided r by PASCO Co. -20 -0.9 9x9 window 9x9 window 19 Extraction of collapsed bridges based on the relationship between the difference and correlation coefficient from SAR images

F. Yamazaki, K. Inoue, W. Liu (2016) SM& MS 1.0 1.00 Survived 0.90

r 0.8 Collapsed

Collapsed 0.80 Collapsed 0.6 0.70 0.47 0.60 Probability Coefficient,

0.4 0.50 Difference 0.40 Survived 0.2 0.30 Cumulative

Correlation 0.0 0.20 0.10 0.47 ‐0.2 0.00 ‐14.0 ‐12.0 ‐10.0 ‐8.0 ‐6.0 ‐4.0 ‐2.0 0.0 2.0 4.0 ‐0.2‐0.1 0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0 Diff. of the Backscattering Coefficients, d (dB) Correlation Coefficient, r Correlation Coefficent (a) (b)

F. Yamazaki, K. Inoue, W. Liu, Damage assessment of bridges using spatial characteristics of high-resolution satellite SAR intensity images, Stochastic Mechanics SM&MS 2016, vol. VI, No. 1, Capri, Italy, 2016. 20 Last Reunion with Prof. Shinozuka ICOSSAR 2013 @

21 21 Prof. Shinozuka: We appreciate all your supports to guide us to academia. You are my great mentor over 30 years. We pray your soul may rest in peace.

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