Abstract
Under strong seismic excitation, a rigid block will uplift from its support and undergo rocking oscillations which may lead to (complete) overturning. Numerical and analytical solutions to this highly nonlinear vibration problem are first highlighted in the paper and then utilized to demonstrate how sensitive the overturning behavior is not only to the intensity and frequency content of the base motion, but also to the presence of strong pulses, to their detailed sequence, and even to their asymmetry. Five idealised pulses capable of representing “rupture-directivity” and “fling” affected ground motions near the fault, are utilized to this end: the one-cycle sinus, the one-cycle cosinus, the Ricker wavelet, the truncated (T)-Ricker wavelet, and the rectangular pulse “Overturning-Acceleration Amplification” and “Rotation” spectra are introduced and presented. Artificial neural network modeling is then developed as an alternative numerical solution. The neural network analysis leads to closed-form expressions for predicting the overturning failure or survival of a rigid block, as a function of its geometric properties and the characteristics of the excitation time history. The capability of the developed neural network modeling is validated through comparisons with the numerical solution. The derived analytical expressions could also serve as a tool for assessing the destructiveness of near-fault ground motions, for structures sensitive to rocking with foundation uplift.
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References
Abrahamson N (2001), “Incorporating Effects of Near Fault Tectonic Deformation into Design Ground Motions,” A presentation sponsored by the Multidisciplinary Center for Earthquake Engineering Research, SUNY at Buffalo.
Akbulut S, Hasiloglu AS and Pamukcu S (2004), “Data Generation for Shear Modulus and Damping Ratio in Reinforced Sands Using Adaptive Neuro-fuzzy Inference System,” Soil Dynamics and Earthquake Engineering, 24: 805–14.
Anderson C and Bertero V (1986), “Uncertainties in Establishing Design Earthquakes,” Journal of Structural Engineering, ASCE, 113: 1709–1724.
Anooshehpoor A, Heaton T, Shi B and Brune J (1999), “Estimates of the Ground Acceleration Point Reyes Station During the 1906 San Francisco Earthquake,” Bulletin of the Seismological Society of America, 89(4): 843–853.
Apostolou M, Anastasopoulos J and Gazetas G (2001), “Back-analysis of Sliding and Toppled Structures for the Estimation of Ground Motion During the Athens Earthquake (1999),” 2nd Greek Conference on Earthquake Engineering and Engineering Seismology, Thessaloniki, Greece.
Apostolou M and Gazetas G (2005), “Seismic Response of Slender Rigid Structures with Foundation Uplift,” Soil Dynamics and Earthquake Engineering (in press).
Baziar MH and Nilipour N (2003), “Evaluation of Liquefaction Potential Using Neural-networks Land CPT Results,” Soil Dynamics and Earthquake Engineering, 23: 631–636.
Burton SA, Makris N, Konstantopoulos IK, and Antsaklis PJ (1996), “Modeling the Response of an Electrorheological Fluid Damper: Constitutive Modelling and Neural Networks,” Intelligent Automation and Soft Computing, 2(4): 339–54.
Faccioli E, Paolucci R and Vanini M (1998), “3D Site Effects and Soil Foundation Interaction in Earthquake and Vibration Risk Evaluation,” TRISEE.
Ghaboussi J, Garret JH and Wu X (1991), “Knowledge Based Modeling of Material Bbehavior with Neural Networks,” J Engng Mech Div, ASCE, 117(2): 132–53.
Giacinto G, Paolucci R and Roli F (1997), “Application of Neural Networks and Statistical Pattern Recognition Algorithms to Earthquake Risk Evaluations,” Pattern Recognition Letters, 18: 1353–62.
Goh ATC (1994), “Seismic Liquefaction Potential Assessed by Neural Networks,” J Geotech Engng, ASCE, 120(9): 1467–80.
Habibagahi G. (1997), “Reservoir Induced Earthquakes Analyzed via Radial Basis Function Networks,” Soil Dynamics and Earthquake Engineering, 17: 53–56.
Hisada Y and Bielak J. (2003), “A Theoretical Method for Computing Near-fault Ground Motions in Layered Half-spaces Considering Static Offset due to Surface Faulting, with a Physical Interpretation of Fling Step and Rupture Directivity,” Bulletin of the Seismological Society of America, 93(3): 1154–1168.
Housner G (1963), “The Behavior of Inverted Pendulum Structures During Earthquakes,” Bulletin of the Seismological Society of America, 53(2): 404–417.
Huckelbridge AA and Clough RW (1978), “Seismic Response of Uplifting Building Frame,” Journal of Structural Engineering, ASCE, 104(8): 1211–1229.
Hurtado JE, Londono JM and Meza MA (2001), “On the Applicability of Neural Networks for Soil Dynamic Amplification Analysis,” Soil Dynamics and Earthquake Engineering, 21: 579–91.
Ishiyama Y (1982), “Motions of Rigid Bodies and Criteria for Overturning by Earthquake Excitations,” Earthquake Engineering and Structural Dynamics; 10: 635–650.
Kirkpatrick P (1927), “Seismic Measurements by the Overthrow of Columns,” Bulletin of the Seismological Society of America; 17(2): 95–109.
Makris N and Roussos YS (1998), “Rocking Response and Overturning of Equipment Under Horizontal Pulse-type Motions,” Technical Report 5, Pacific Earthquake Engineering Research Center.
Makris N and Roussos YS (2000), “Rocking Response of Rigid Blocks Under Near-source Ground Motions,” Geotechnique, 50(3): 243–262.
MATLAB (2000), “The Language of Technical Computing,” Copyright 1984–2000 The Math Works, Inc.
Milne J. and Omori F. (1893), “On the Overturning and Fracturing of Brick and Other Columns by Horizontally Applied Motion,” The Seismological Journal of Japan, 1: 59–86.
Shi B, Anooshehpoor A, Zeng Y and Brune J (1996), “Rocking and Overturning of Precariously Balanced Rocks by Earthquake,” Bulletin of the Seismological Society of America, 86(5): 1364–1371.
Somerville P and Graves R (1993), “Conditions that Give Rise to Unusually Large Long Period Ground Motions,” Structural Design of Tall Buildings; 2: 211–232.
Somerville P (2003), “Characterization of Near Fault Ground Motions for Design,” American Concrete Institute Conference, San Diego.
Spanos P and Koh A-S (1984), “Rocking of Rigid Blocks Due to Harmonic Shaking,” Journal of Engineering Mechanics ASCE; 110(11): 1627–1642.
Tung ATY, Wang YY and Wong FS (1993), “Assessment of Liquefaction Potential Using Neural Networks,” Soil Dynamics and Earthquake Engineering, 12: 325–35.
Wang J and Rahman MS (1999), “A Neural Network Model for Liquefaction-induced Horizontal Ground Displacement,” Soil Dynamics and Earthquake Engineering, 18: 555–68.
Wong C M and Tso W K (1989), “Steady-state Rocking Response of Rigid Blocks. Part 2: Experiment,” International Journal of Earthquake Engineering and Structural Dynamics, 18: 107–120.
Zhang J and Makris N (1999), “Rocking Response and Overturning of Anchored Equipment Under Seismic Excitations,” Technical Report 6, Pacific Earthquake Engineering Research Center.
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Gerolymos, N., Apostolou, M. & Gazetas, G. Neural network analysis of overturning response under near-fault type excitation. Earthq. Engin. Engin. Vib. 4, 213–228 (2005). https://doi.org/10.1007/s11803-005-0004-0
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DOI: https://doi.org/10.1007/s11803-005-0004-0