Modeling Variability in Seismic Analysis of Concrete Gravity Dams: A Parametric Analysis of Koyna and Pine Flat Dams
Autor(en): |
Bikram Kesharee Patra
(Department of Building, Civil & Environmental Engineering, Concordia University, Montreal, QC H3G 1M8, Canada)
Rocio L. Segura (Department of Civil, Environmental, and Sustainable Engineering, Santa Clara University, Santa Clara, CA 95053, USA) Ashutosh Bagchi (Department of Building, Civil & Environmental Engineering, Concordia University, Montreal, QC H3G 1M8, Canada) |
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Medium: | Fachartikel |
Sprache(n): | Englisch |
Veröffentlicht in: | Infrastructures, 20 Dezember 2023, n. 1, v. 9 |
Seite(n): | 10 |
DOI: | 10.3390/infrastructures9010010 |
Abstrakt: |
This study addresses the vital issue of the variability associated with modeling decisions in dam seismic analysis. Traditionally, structural modeling and simulations employ a progressive approach, where more complex models are gradually incorporated. For example, if previous levels indicate insufficient seismic safety margins, a more advanced analysis is then undertaken. Recognizing the constraints and evaluating the influence of various methods is essential for improving the comprehension and effectiveness of dam safety assessments. To this end, an extensive parametric study is carried out to evaluate the seismic response variability of the Koyna and Pine Flat dams using various solution approaches and model complexities. Numerical simulations are conducted in a 2D framework across three software programs, encompassing different dam system configurations. Additional complexity is introduced by simulating reservoir dynamics with Westergaard-added mass or acoustic elements. Linear and nonlinear analyses are performed, incorporating pertinent material properties, employing the concrete damage plasticity model in the latter. Modal parameters and crest displacement time histories are used to highlight variability among the selected solution procedures and model complexities. Finally, recommendations are made regarding the adequacy and robustness of each method, specifying the scenarios in which they are most effectively applied. |
Copyright: | © 2023 the Authors. Licensee MDPI, Basel, Switzerland. |
Lizenz: | Dieses Werk wurde unter der Creative-Commons-Lizenz Namensnennung 4.0 International (CC-BY 4.0) veröffentlicht und darf unter den Lizenzbedinungen vervielfältigt, verbreitet, öffentlich zugänglich gemacht, sowie abgewandelt und bearbeitet werden. Dabei muss der Urheber bzw. Rechteinhaber genannt und die Lizenzbedingungen eingehalten werden. |
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