Performance Based Engineering Application

Adam Zsarnoczay , Frank McKenna , Charles Wang , Stevan Gavrilovic , Michael Gardner , Sang-ri Yi , Aakash Bangalore Satish , Wael Elhaddad , & Peter Mackenzie-Helnwein

The Performance Based Engineering Application (PBE app) is an open-source desktop application designed to support the assessment of building performance under natural hazard events. The application quantifies performance in a probabilistic approach. Users can consider uncertainties in event intensity, structural behavior, component quantities and their limit state capacities, as well as the consequences of exceeding component limit states (i.e., experiencing damage). The PBE app provides a convenient user interface and uses the settings provided by the user to prepare a simulation workflow description in a JSON file. This workflow description is used to run a simulation workflow on SimCenter’s backend engine using sWHALE. The structural response estimation part of the workflow can run on the TACC high-performance computing cluster made available through DesignSafe. The performance assessment part runs locally using SimCenter’s PELICUN performance assessment engine.

This document covers the features and capabilities of Version 4.1 of the tool. Users are encouraged to comment on what additional features and capabilities they would like to see in future versions of the application through the github discussion page.

Developer Manual

Contact

Adam Zsarnóczay, NHERI SimCenter, Stanford University, adamzs@stanford.edu

References

AS00

Ronald. D. Andrus and Kenneth H Stokoe. Liquefaction resistance of soils from shear wave velocity. Journal of Geotechnical and Geoenvironmental Engineering, 126(11):1015–1025, 2000.

BZ15

RW Boulanger and K Ziotopoulou. Pm4sand (version 3): a sand plasticity model for earthquake engineering applications. Center for Geotechnical Modeling Report No. UCD/CGM-15/01, Department of Civil and Environmental Engineering, University of California, Davis, Calif, 2015.

CTH+04

K. Onder Cetin, Kohji Tokimatsu, Leslie F. Harder, Robert E. S. Moss, Robert E. Kayen, Armen Der Kiureghian, and Raymond B. Seed. Standard penetration test-based probabilistic and deterministic assessment of seismic soil liquefaction potential. Journal of Geotechnical and Geoenvironmental Engineering, 130(12):1314–1340, 2004. doi:10.1061/(asce)1090-0241(2004)130:12(1314).

CA20

Long Chen and Pedro Arduino. Implementation, verification, and validation of PM4Sand model in OpenSees”. PEER Report - Submitted, under review, 2020.

DDK17

Mayssa Dabaghi and Armen Der Kiureghian. Stochastic model for simulation of near-fault ground motions. Earthquake Engineering & Structural Dynamics, 46(6):963–984, 2017. URL: https://onlinelibrary.wiley.com/doi/abs/10.1002/eqe.2839, arXiv:https://onlinelibrary.wiley.com/doi/pdf/10.1002/eqe.2839, doi:10.1002/eqe.2839.

DDK18

Mayssa Dabaghi and Armen Der Kiureghian. Simulation of orthogonal horizontal components of near-fault ground motion for specified earthquake source and site characteristics. Earthquake Engineering & Structural Dynamics, 47(6):1369–1393, 2018. URL: https://onlinelibrary.wiley.com/doi/abs/10.1002/eqe.3021, arXiv:https://onlinelibrary.wiley.com/doi/pdf/10.1002/eqe.3021, doi:10.1002/eqe.3021.

DK14

Mayssa Dabaghi and Armen Der Kiureghian. Stochastic Modeling and Simulation of Near-Fault Ground Motions for Performance-Based Earthquake Engineering. Technical Report, Pacific Earthquake Engineering Research Center, 2014.

GBS20

Xingquan Guan, Henry Burton, and Thomas Sabol. Python-based computational platform to automate seismic design, nonlinear structural model construction and analysis of steel moment resisting frames. Engineering Structures, 224:111199, 2020.

IB08

I. M. Idriss and R. W. Boulanger. Soil liquefaction during earthquakes. MNO-12. Earthquake Engineering Research Institute, Oakland, Calif., 2008. ISBN 9781932884364.

Ish93

K. Ishihara. Liquefaction and flow failure during earthquakes. Géotechnique, 43(3):351–451, 1993. doi:10.1680/geot.1993.43.3.351.

KELL18

Arash Khosravifar, Ahmed Elgamal, Jinchi Lu, and John Li. A 3D model for earthquake-induced liquefaction triggering and post-liquefaction response. Soil Dynamics and Earthquake Engineering, 110:43–52, 2018. URL: http://www.sciencedirect.com/science/article/pii/S0267726117308722, doi:https://doi.org/10.1016/j.soildyn.2018.04.008.

PK99

Kok Kwang Phoon and Fred H. Kulhawy. Characterization of geotechnical variability. Canadian Geotechnical Journal, 36(4):612–624, 1999. doi:10.1139/t99-038.

Shi07

HyungSuk Shin. Numerical modeling of a bridge system & its application for performance-based earthquake engineering. PhD thesis, University of Washington, Seattle, WA, 2007.

SSGA97

Paul G. Somerville, Nancy F. Smith, Robert W. Graves, and Norman A. Abrahamson. Modification of Empirical Strong Ground Motion Attenuation Relations to Include the Amplitude and Duration Effects of Rupture Directivity. Seismological Research Letters, 68(1):199–222, 01 1997. URL: https://doi.org/10.1785/gssrl.68.1.199, arXiv:https://pubs.geoscienceworld.org/srl/article-pdf/68/1/199/2753665/srl068001\_0199.pdf, doi:10.1785/gssrl.68.1.199.

VPD18

Christos Vlachos, Konstantinos G. Papakonstantinou, and George Deodatis. Predictive model for site specific simulation of ground motions based on earthquake scenarios. Earthquake Engineering & Structural Dynamics, 47(1):195–218, 2018. URL: https://onlinelibrary.wiley.com/doi/abs/10.1002/eqe.2948, doi:10.1002/eqe.2948.

YS88

Fumio Yamazaki and Masanobu Shinozuka. Digital generation of Non-Gaussian stochastic fields. Journal of Engineering Mechanics, 114(7):1183–1197, 1988. doi:10.1061/(asce)0733-9399(1988)114:7(1183).

YI01

T. L. Youd and I. M. Idriss. Liquefaction resistance of soils: summary report from the 1996 nceer and 1998 nceer/nsf workshops on evaluation of liquefaction resistance of soils. Journal of Geotechnical and Geoenvironmental Engineering, 127(4):297–313, 2001. doi:10.1061/(asce)1090-0241(2001)127:4(297).