Seismic Site Response: Case Histories, Research Issue and Best Practice

A special issue of Geosciences (ISSN 2076-3263).

Deadline for manuscript submissions: closed (31 July 2023) | Viewed by 2642

Special Issue Editors


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Guest Editor
Dipartimento di Ingegneria Civile, Ambientale, del Territorio, Edile e di Chimica, Politecnico di Bari, Bari, Italy
Interests: geotechnical earthquake engineering; seismic site response; seismic risk reduction; emergency system management; numerical modelling; sub-soil modelling; earthquake-induced permanent deformation; cyclic behaviour of soils; slope stability; soil-structure interaction; stochastic analysis of site conditions; three-dimensional geotechnical model

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Guest Editor
Dipartimento di Ingegneria Civile, Ambientale e del Territorio, Edile e di Chimica, Politecnico di Bari, Bari, Italy
Interests: geotechnical earthquake engineering; dynamic soil-structure interaction; seismic site response; FE numerical modelling; cyclic behaviour of soils; geotechnical modelling; slope stability analysis; weather-induced landslide; slope-vegetation-atmosphere interaction

Special Issue Information

Dear Colleagues,

The paramount role of the seismic site effects in the distribution and damages associated with a seismic event is widely recognized. Thus, the alteration of the earthquake characteristics during the propagation from the bedrock to the surface due to local site conditions is of great interest for the earthquake engineering community. Forecasting the seismic site response could be a very hard and highly relevant challenge due to different issues, related to the local geomorphology, the geological and lithostratigraphic spatial variability, and the mechanical properties of the soils. Real site conditions, in general, are quite different from the ideal simplified settings assumed for prediction purposes, as for example, the assumptions of the horizontal ground surface, of horizontally layered sub-soil deposit, of initial shear wave profiles, or of nonlinear dynamic features. Indeed, the characterisation of the dynamic response of geo-materials is typically affected by different sources of uncertainty, due to the reproducibility of in situ investigations and laboratory tests and to the complexity of the subsoil conditions, for example related to spatial heterogeneity. Different approaches are available for the investigation of the seismic site response, as well presented in the literature:

- Simplified analytical approaches, based on closed form solutions, which have represented the kick-off strategy in understanding and investigating the dynamic site response, providing the basic benchmark for the verification and validation of more complex approaches;

- Numerical approaches, based on mono-, bi-, and tri-dimensional schemes, which provide a more realistic methodology for predicting the seismic ground response, depending on whether simplified or advanced constitutive models are implemented. In this case, the higher the complexity of either the geometrical scheme or the soil constitutive assumptions, the higher the level of detail of the required input data, the higher the computational effort;

- Machine learning procedure, which has the advantage to handle a lot of input data in a short time-span, also allowing the near-real time forecasting of ground shaking;

- Laboratory apparatuses, such as shaking table and centrifuge test, providing a tool for both the physical interpretation of the phenomena of interest and the calibration of the above-mentioned approaches.

Bearing in mind that the paradigm should be shifted from managing disasters to managing the risk, the type of analysis should be selected depending on the available input data (e.g., soft data or well detailed data), on the extension of the area of interest (from local to large areas) and on the expected goals (e.g., planning or design).

As Guest Editors for the theme “Seismic site response: case histories, research issue and best practice”, we cordially invite you to submit your manuscripts about your recent projects, experimental research, or case studies, detailing the key-points above listed including, but not limited to:

  • Numerical approaches for seismic site response;
  • Site response forecasting based on in situ investigations;
  • Directionality of ground motion induced by sub-soil setting and/or topography;
  • Parametric analyses, comparing results from different approaches or different codes;
  • Charts to provide amplification phenomena over large areas;
  • Best practice;
  • Permanent ground deformation (liquefaction, soil compressibility, slope stability) induced by earthquakes;
  • Constitutive modelling of non-linear behaviour of geo-materials for local seismic site response;
  • Seismic risk management;
  • Dynamic soil-structure interaction effects;
  • Constitutive and numerical models for dynamic analyses;
  • Physical modelling, shaking table and centrifuge tests;
  • Seismic hazard, ground motion records and prediction;
  • Case histories and instrumented test sites;
  • Lessons learned from recent and past earthquakes.

In this Special Issue, original research articles, technical notes, communications, and reviews are welcome.

We would even like to encourage you to send a brief abstract outlining the purpose of your research and the key results obtained, in order to verify at an early stage that your manuscript falls within the objectives of the Special Issue.

We look forward to receiving your contributions.

Dr. Gaetano Falcone
Dr. Annamaria di Lernia
Guest Editors

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Keywords

  • local seismic site response
  • numerical analysis
  • machine learning procedures
  • ground motion prediction maps
  • site effects
  • earthquake induced permanent ground deformation
  • dynamic soil-structure interaction
  • dynamic response of geomaterials
  • dynamic laboratory tests
  • seismic microzonation
  • seismic risk mitigation

Published Papers (1 paper)

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Research

19 pages, 3649 KiB  
Article
The Influence of Input Motion Scaling Strategies on Nonlinear Ground Response Analyses of Soft Soil Deposits
by Yusuf Guzel, Gaetano Elia, Mohamed Rouainia and Gaetano Falcone
Geosciences 2023, 13(1), 17; https://doi.org/10.3390/geosciences13010017 - 6 Jan 2023
Cited by 3 | Viewed by 1719
Abstract
A key issue for the estimation of ground shaking is the proper selection of input motions at the seismic bedrock. At the same time, the effect of the input motion scaling strategy on structural response is typically studied disregarding the presence of the [...] Read more.
A key issue for the estimation of ground shaking is the proper selection of input motions at the seismic bedrock. At the same time, the effect of the input motion scaling strategy on structural response is typically studied disregarding the presence of the soil deposit. In this work, different soft soil deposits are selected by varying the shear wave velocity profiles and the depth to the seismic bedrock, modelling the soil behaviour through a nonlinear constitutive model implemented into a fully coupled FE code. Seven input motions are retrieved for several selection strategies in conjunction with two seismic intensity levels. Hence, more than 300 one-dimensional ground response analyses are performed. The results of the analysed cases, which are presented in terms of spectral response at ground surface and amplification factors, indicate that: (i) the use of an advanced elasto-plastic soil constitutive model accounts for nonlinear ground response effects, including higher site amplification in the mid-period range and deamplification of the peak ground accelerations; (ii) the different scaling strategies lead to comparable mean values of the amplification factors, and (iii) the variability of the amplification factors is significantly reduced when the scaling strategy seeks the compatibility with the target spectrum over a specified period range. The research will aid the prediction of local seismic site response over large areas, particularly in the absence of the fundamental period of a structure and facilitate its use in general recommendation for quantifying and reducing uncertainty. Full article
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