THE POSSIBILITY OF USING JERK PARAMETERS AS SEISMIC INTENSITY MEASURE
It is a common procedure to use a single parameter because of its simplicity to represent the seismic
action in a particular region and describe its complex nature. This single parameter generally is known as
ground motion intensity measure IM. The time derivative of acceleration, commonly known as jerk, is met
in a limited number of such studies and specifically in earthquake engineering. For that purpose, this
paper presents a study on the performance of using seismic jerk as ground motion IM. Several typical RC
frame buildings of different numbers of stories were selected. The nonlinear time-history analysis is
performed while the buildings are exposed to twenty-seven natural earthquake records using ETABS
software. The maximum displacement at the top of the building is selected as the structural response
parameter. Several widely used IMs were defined in addition to the jerk and its based parameters. After
performing a large number of nonlinear analyses and applying machine learning, best feature subsets that
present relation between response parameter and considered intensity measures were obtained. For
structures with low nonlinearity in behavior, jerk- based parameters were shown to be effective.
Seismic evaluation and retrofit of existing
buildings, Standard ASCE/SEI 41-17. Reston,
VA.: American Society of Civil
Engineers/Structural Engineering Institute.
American Society of Civil Engineers (ASCE). (2007).
Seismic rehabilitation of existing buildings,
ASCE/SEI 41-06. Reston, VA.: American
Society of Civil Engineers/Structural
An YH, Jo HK, Spencer FB, &Ou JP. (2014) A
damage localization method based on the „jerk
energy‟. Smart Materials and Structures,
23(2). Applied Technology Council (ATC). (2011). ATC-58,
Guidelines for Seismic Performance
Assessment of Buildings, 75% Draft.
Redwood City, CA
Arias, A. (1970). A Measure of Earthquake Intensity.
In R. Hansen(Ed.), Seismic Design for
Nuclear Power Plants (pp. 438-483).
Cambridge Massachusetts: MIT Press.
Buratti, N. (2012). A comparison of the performances
of various ground–motion intensity measures.
Paper presented at the Proceedings of the 15th
world conference on earthquake engineering,
Caruana, R., &Freitag, D. (1994). Greedy attribute
selection. In Machine Learning: Proceedings
of the Eleventh International Conference.
CEN (2003). Eurocode 8 - Design of Structures for
Earthquake Resistance, Part 1: General rules,
seismic action, and rules for buildings
(Report). Brussels: European Union, European
Committee for Standardization.
Computers and Structures, Inc. (2016), ETABS.
Elenas, A. (2013). Intensity Parameters as Damage
Potential Descriptors of Earthquakes. In M.
Papadrakakis, G. Stefanou, & V.
Papadopoulos(Eds.), Computational Methods
in Stochastic Dynamics (pp. 327-334).
He, H., Li, R., & Chen, K. (2015). Characteristics of
Jerk Response Spectra for Elastic and Inelastic
Systems. Shock and Vibration, pp. 1–12.
He, H.X., Yan, W.M.,Chen, Y.J.(2011). Study on
concept and characteristics of seismic jerk
response spectra. Engineering Mechanics,
Holmes, G., Donkin, A., & Witten, I.H. (1994). Weka:
A machine learning workbench. In
Proceedings of the Second Australia and New
Zealand Conference on Intelligent Information
Housner, G. W. (1952). Spectrum Intensities of
Strong-Motion Earthquakes. Paper presented
at the Proceedings of the Symposium on
Earthquake and Blast Effectrs on Structures,
Housner, G. W., & Jennings, P. C. (1964). Generation
of artificial earthquakes. Journal of the
Engineering Mechanics Division, EM1, pp.
Hrovat, D., & Hubbard, M. (1987). A comparison
between jerk optimal and acceleration optimal
vibration isolation. Journal of Sound and
Vibration, 112(2), pp. 201–210.
John, G. H., & Langley, P. (1996). Static versus
dynamic sampling for data mining. In
Proceedings of the Second International
Conference on Knowledge Discovery and
Data Mining. AAAI Press.
John, G. H., Kohavi, R., &Pfleger, P. (1994).
Irrelevant features and the subset selection
problem. In Machine Learning: Proceedings of
the Eleventh International Conference.
Kohavi, R. (1995). Wrappers for performance
enhancement and oblivious decision graphs.
PhD thesis, Stanford University.
Kohavi, R., & John, G. (1996). Wrappers for feature
subset selection. Artificial Intelligence, special
issue on relevance, 97(1–2), pp.273–324.
Kramer, S. L. (1996). Geotechnical Earthquake
Engineering. New Jersey: Prentice-Hall.
Langley, P., & Simon, H. A. (1995). Applications of
machine learning and rule induction.
Communications of the ACM, 38(11), pp. 55–
Liu, C., Gazis, D. C., & Kennedy, T. W. (1999).
Human judgment and analytical derivation of
ride quality. Transportation Science, 33(3), pp.
Nanos, N. (2011). A study on the importance of
seismic parameter selection for the
vulnerability assessment of mid-rise reinforced
concrete structures. PhD Thesis, University of
Qiao, YF. (1990). GIBBS–APPELL‟S equations of
variable mass nonlinear non holonomic
mechanical systems. Applied Mathematics and
Riddell, R. (2006). Correlation between Ground
Motion Intensity Indices and Structural
Response to Earthquakes. In J.J. Perez Gavilan
(ed.), Earthquake Engineering Challenges and
Trends (pp. 521-536). Mexico: Instituto de
Schot, S. H. (1978). Jerk: the time rate of change of
acceleration. The American Journal of Physics,
11(46), p. 1090.
SeismoSoft, (2018).SeismoSignal: A computer
program for signal processing of strong-
motion data. S Antoniou, R Pinho. Technical
Report 4.0. 0. Pavia, Italy.
Shome, N., Cornell, C. A., Bazzurro, P., & Carballo,
J. E. (1998). Earthquakes, records, and
nonlinear responses. Earthquake Spectra,
14(3), pp. 469-500.
Sofronie, R. (2017). On the Seismic Jerk. Journal of
Geological Resource and Engineering, 5(4).
Tong, M., Wang, G.-Q., & Lee, G. C. (2005). Time
derivative of earthquake acceleration.
Earthquake Engineering and Engineering
Vibration, 4(1), 1–16.
Toshiyuki, A., Yutaka, S., &Tomokazu, I. (2009).
Cycle slip detection in kinematic GPS with a
jerk model for land vehicles, International
Journal of Innovative Computing Information
and Control, 21(4), pp. 153–166.
Yaseen, A. A., (2015). Seismic fragility assessment of
masonry buildings in the Kurdistan region.
PhD thesis, University of Portsmouth, UK
It is the policy of the Journal of Duhok University to own the copyright of the technical contributions. It publishes and facilitates the appropriate re-utilize of the published materials by others. Photocopying is permitted with credit and referring to the source for individuals use.
Copyright © 2017. All Rights Reserved.