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Università degli studi di Trento

Seismic risk mitigation of "special risk" process plants through enhanced concepts and subplant hybrid simulation

Abstract

dc:description

This doctoral thesis focuses on the seismic risk mitigation of â special riskâ industrial facilities, like chemical, petrochemical and process industries. It is known that the impact of natural hazards, such as earthquakes, on this type of structures may cause significant accidents leading to severe consequences to both the environment and human lives; see, among others, Lanzano et al., (2015) and Krausmann et. al (2010). In particular, the most critical components in a petrochemical plant are fluid-filled storage tanks; they can experience severe damages and trigger cascading effects in neighbouring tanks due to large vibrations induced by strong earthquakes, indeed. In order to reduce these tank vibrations, an innovative type of foundation based on metamaterial concepts is investigated. Metamaterials are generally regarded as manmade structures that exhibit unusual responses not readily observed in natural materials. Due to their exceptional properties and advancements in recent years, metamaterials have entered the field of seismic engineering, and therefore, offer a novel approach to design seismic shields. As a result, an encouraging and practicable strategy for the seismic protection of liquid storage tanks is presented and validated. On the other hand, the outcomes of this research study also aim to improve seismic risk assessment of â special riskâ facilities mainly through experimental dynamic analysis. In view of performing a dynamic analysis of these complex components, necessary for the global seismic risk assessment procedure, online hybrid (numerical/physical) dynamic substructuring simulations have shown their potential in enabling realistic dynamic analysis of almost any type of nonlinear structural system. At the same time, owing to faster and more accurate testing equipment, a number of different offline experimental substructuring methods, operating both in time and frequency domains, have been employed in mechanical engineering to examine dynamic substructure coupling. The scope of the study is the exploitation of different Experimental Dynamic Substructuring (EDS) methods in a complementary way to expedite a hybrid experiment/numerical simulation and, consequently, the comprehensive dynamic analysis. From this perspective, after a comparative uncertainty propagation analysis of three EDS algorithms, a new Composite-EDS (C-EDS) method is proposed and numerically validated. To the best of the authorâ s knowledge, this research study presents the first algorithm used to fuse both online and offline algorithms into a unique simulator with significant advantages in terms of dynamic analysis and seismic risk assessment of industrial plants. Finally, the research activity is supported by the results from different experimental testing campaigns with the main purpose to investigate the complex behaviour of critical industrial components, such as Tee joints and Bolted Flanged Joints (BFJs), with particular regard to the leakage phenomena resistance. In this respect, a reliable an innovative model capable of predicting the leakage force for a generic BFJ, including the interaction between axial and shear load, is proposed and validated.

Degree

thesis:*
Grantor dc:publisher
Università degli studi di Trento
Year dc:date
2018

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • La Salandra, Vincenzo
Contributors dc:contributor
  • Bursi, Oreste Salvatore

Subjects

dc:subject × 1

Rights

dc:rights
Statement dc:rights
  • info:eu-repo/semantics/openAccess
  • license:Tutti i diritti riservati (All rights reserved)
  • license uri:iris.PRI01
Language dc:language
eng

Identifiers

dc:identifier.*
OAI identifier oai:identifier
oai:iris.unitn.it:11572/368567

Chain of custody

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Università degli Studi di Trento
Base URL
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Last updated
2026-07-24
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OAI-PMH GetRecord
citation

La Salandra, Vincenzo. Seismic risk mitigation of "special risk" process plants through enhanced concepts and subplant hybrid simulation. Università degli studi di Trento, 2018. https://hdl.handle.net/11572/368567