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TOWARDS SEISMIC RESILIENCE OF INDUSTRIAL FACILITIES:
THE CASE STUDY OF AN OIL REFINERY
Vasileios E. MELISSIANOS
1
,4, Nikolaos D. KARAFERIS
2
, Athanasia K.
KAZANTZI3,4, Konstantinos BAKALIS5 & Dimitrios VAMVATSIKOS6
Abstract: Crude oil refineries are high-importance infrastructure that play a key role in the energy
supply chain. Securing the operational and structural integrity of refineries in the aftermath of an
earthquake is crucial for avoiding the undesirable consequences of a Natural-Technological
(NaTech) incident, such as injuries, environmental pollution, business interruption, and monetary
losses. Refineries are designed, constructed, maintained, and operated under a strict framework
of standards and regulations. Still, seismic-related NaTech incidents are occurring. Thus, to
assess with more confidence and consequently improve, if needed, their seismic resilience, a
coherent performance-based framework needs to be utilised, that accounts for the refinery as an
integrated system comprising a variety of structural typologies, such as buildings, tanks, and high-
rise stacks. These structures have very diverse dynamic properties and hence seismic responses.
Towards this objective, a virtual crude oil refinery is examined herein as a case study. The aim is
to showcase the steps of a seismic risk assessment framework when applied to such
infrastructures, focusing on the evaluation of the seismic hazard, the development of the exposure
model, the numerical analysis of the structures, and the preliminary damage assessment of the
facility using different earthquake scenarios.
Introduction
Crude oil refineries are among the most important energy infrastructure since they are located in
the core of the energy supply chain. Crude oil extracted at oil rigs, is transported to refineries
(upstream part), then processed to produce liquid and gaseous fuels (midstream part), which are
then delivered to costumers (downstream part). The large amount of oil and oil products being
circulated in a refinery, which are flammable, hazardous, and potentially explosive materials,
dictates the need to secure the operational and structural integrity of the facility in the aftermath
of an earthquake event. In fact, a potential failure may result in undesirable events, spanning from
business disruption to uncontrolled leakage and/ or major fire incidents, as well as injuries and
event casualties (Cruz and Steinberg 2005). The devastating consequences of such seismic-
triggered NaTech events have been reported, among others, in the aftermath of the 1999 Izmit
earthquake in Turkey, the 2003 Tokachi-Oki and the 2011 Tohoku earthquakes in Japan.
The standard practice is the refinery operators to work closely with regulatory authorities to
improve the existing as well as to develop more reliable frameworks for the seismic risk
assessment of refineries in order to cope with the consequences of earthquakes and ensure
continuous operation in case of a NaTech event (Camila et al. 2019). Still, most existing
frameworks are qualitative tools based on risk analysis (Girgin et al. 2019), risk evaluation
(Theocharidou and Giannopoulos, 2015), and risk rating (Krausmann et al. 2011). These tools
are in fact very useful for the development of preliminary mitigation strategies, as well as for
developing emergency response plans and mitigation actions on account of predefined scenarios.
Yet, they cannot offer a reliable computation of the actual expected seismic loss and consequently
contribute to the improvement of the seismic resilience of the facility. It is, thus, necessary to
develop a comprehensive framework for the seismic risk assessment of such facilities by
considering the aleatory and epistemic uncertainties stemming from the seismic hazard, the
1
Research Associate, National Technical University of Athens, Athens, Greece, melissia@mail.ntua.gr
2
PhD Candidate, National Technical University of Athens, Athens, Greece
3 Adjunct Lecturer, Department of Civil Engineering, International Hellenic University, Serres, Greece
4 Member, Societal Resilience & Climate Change (SoReCC) Center of Excellence, Diegem, Belgium
5 Postdoctoral Researcher, Institute of Structural Engineering IBK, Swiss Federal Institute of Technology
ETH Zürich, Zürich, Switzerland
6 Associate Professor, National Technical University of Athens, Athens, Greece
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structures’ modelling approaches, the structures’ seismic performance, etc. via exploiting the
Performance-Based Earthquake Engineering framework (Cornell and Krawinkler 2000).
The preliminary framework for the seismic risk assessment of a crude oil refinery that is developed
in this study, consists of (1) the seismic hazard calculation, (2) the development of the exposure
model, (3) the analysis of the structures via simplified and surrogate numerical models, and (4)
the damage assessment. A virtual typical mid-size refinery located in a highly seismic active area
in Greece is considered as a case study, in order to showcase the process and present scenario-
based results, as a first step towards identifying the most critical assets at risk.
Seismic hazard
The case-study refinery is located within a major industrial area in the west of Athens, Greece.
The open-source platform OpenQuake (Pagani et al. 2014), developed by the Global Earthquake
Model Foundation, was employed to compute the seismic hazard for the area of interest. The
seismic hazard calculations were based on the results of the Eu-funded SHARE Project
(Woessner et al. 2015) area source model and the Ground Motion Prediction Equation of Boore
and Atkinson (2008).
The geometry and dynamic properties of the structures encountered in an oil refinery are
essentially very different. A variety of Engineering Demand Parameters (EDPs) is therefore
required to assess the structural performance of such assets. Thus, the selected Intensity
Measure (IM) for the analysis should be a reliable and sufficient predictor for “all” EDPs of interest
(Kohrangi et al. 2017). The mean of the log spectral acceleration at a set of periods (), that
is in fact an asset-aware IM, is selected herein as the appropriate IM considering for its evaluation
a range of periods that span between 0.1sec to 1.0sec. The seismic hazard curve for the site of
interest is presented in Figure 1. Additionally, the typical asset-agnostic is also adopted as
an IM.
A set of 30 hazard-consistent natural ground motion records was selected for undertaking the
time-history analyses of the assets. The non-pulse-like and non-long-duration records were
selected from the NGA-West2 database (Ancheta et al. 2013) using the Conditional Spectrum-
base method of Kohrangi et al. (2017). More details on the selected ground motion records are
presented by Bakalis et al. (2018) and Karaferis et al. (2022).
Figure 1. Seismic hazard curve for the case-study refinery site.
Exposure model
The examined facility is a typical mid-size crude oil refinery in terms of functionality, covering an
area of 1850m x 1250m. The plan view of the refinery is shown in Figure 2. The identified critical
assets at risk are (1) the atmospheric liquid storage tanks (crude oil, naphtha, diesel, marine oil,
jet oil, gasoline, slops, asphalt), (2) the spherical pressure vessels for storing gases (propane,
butane), (3) the flare for burning gaseous wastes, (4) the main refinery flare, and (5) the refining
areas, where process towers, chimneys, and equipment-supporting building-type structures are
located.
Crude oil is imported in the refinery via pipelines from marine or land terminals and stored in crude
oil tanks. Then, it is transported to the refining areas for processing. Intermediate and final
products (liquid and gaseous fuels) are stored in tanks. Fuels and gases are circulated within the
refinery via a dense piping network, consisting of buried, on-ground, and rack-supported pipes.
An overview of the entire refining process can be found in Ancheyta (2011).
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Figure 2. Exposure model: Plan view of the case-study crude oil refinery.
Fragility analysis
A comprehensive description of the considered structures and the corresponding numerical
models is offered in Table 1.
Structure
Description
Model
Reference
Liquid
storage
tanks
Anchored and unanchored
tanks with diameter raging
from 11.6m to 85.4m
Surrogate model
Bakalis et
al. (2017)
Steel
buildings
1 and 2 story steel open-
frame buildings with
rectangular plan
Elastic nonlinear models with
diaphragms modelling slabs
Kazantzi et
al. (2022)
RC
buildings
1, 2, and 4 story RC open-
frame buildings with
rectangular plan
Elastic nonlinear models with
diaphragms modelling slabs
Kazantzi et
al. (2022)
Process
towers
Pressurized steel tower
with height 33m
Multi degree-of-freedom nonlinear
model with elastic beam-column
elements
Karaferis et
al. (2022)
RC
chimney
Reinforced Concrete
chimney with height 87m
Multi degree-of-freedom nonlinear
model with fibre elements
Karaferis et
al. (2022)
Steel
chimney
Steel chimneys with height
30m and 80m
Multi degree-of-freedom nonlinear
model with elastic beam-column
elements
Karaferis et
al. (2022)
Flare
Steel lattice tower with
height 68m and
rectangular plan
Nonlinear 3D model with elastic
beam-column elements
Karaferis et
al. (2022)
Spherical
pressure
vessels
Spherical pressure
vessels (tanks) with
diameter 20.22m,
supported by braced legs
Spherical shell represented by a
concentrated mass, legs modelled
with elastoplastic beam-column
elements, and braces modelled with
tension-only elements
Table 1. Refinery structures analysed: Brief description and numerical models.
flare
naphtha tanks
marine oil tanks
crude oil tanks
gasoline tanks
gasoline tanks
crude oil tanks
kerosene tanks
slop
oil
tanks
water
tanks fuel oil
tanks asphalt
tanks
lubricants
tanks
refining
unit
area 2
refining
unit
area 4
refining
unit
area 1
refining
unit
area 3
spherical
pressure
vessels
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The numerical models were developed using the open-source software OpenSees (McKenna
and Fenves 2000). The seismic demand of the refinery structures was evaluated by means of
Incremental Dynamic Analysis (Vamvatsikos and Cornell 2002) for the selected set of 30 records.
Both aleatory and epistemic uncertainties were considered. The former stem from the record-to-
record variability, while the latter from the analysis assumptions.
Fragility curves are employed to quantify the structure’s susceptibility to damage. The fragility for
the considered structures is computed as:
(1)
where is the fragility at a given IM level, is the probability of its arguments, is the
structural demand, and is the capacity.
The structure-specific damages states (DSs) are homogenized in order to formulate a set of
global DS for the refinery system as per ATC-20 (1989), namely DS0: No damage, DS1: Low
damage, DS2: Medium damage, DS3: Extensive damage, and DS4: Near collapse. The failure
modes of each refinery structure with reference to the global DSs are presented in Table 2.
Structure
DS0
DS1
DS2
DS3
DS4
Liquid
storage
tanks
─
Sloshing
Sloshing, base
plate rotation
Elephants’ foot
buckling, base
plate rotation
Steel/RC
buildings
─
Structural
elements:
low intestory
drift
Structural
elements: medium
intestory drift
Structural
elements: high
intestory drift
Components:
failure of low
importance
Components:
failure of medium
importance
Components:
failure of high
importance
Process
towers
─
Top
displacement
Shell local
buckling
RC
chimney
─
Top
displacement
Cross-section
yielding
Cross-
section
failure
Steel
chimney
─
Top
displacement
Interstory drift
Shell local
buckling
Flare
─
Top
displacement
Interstory drift
Buckling
of
structural
members
Spherical
pressure
vessels
─
First yielding
of braces
Most braces have
yielded
Brace fracture
Table 2. Refinery structures analysed: Brief description and numerical models.
The computed fragility curves of two liquid storage tanks are shown in Figure 3, while the
corresponding ones for two typical steel high-rise stacks, namely a 30m high chimney and a
process tower are presented in Figure 4.
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(a)
(b)
Figure 3. Fragility curves: (a) crude oil tank and (b) gasoline tank [LS2: sloshing base plate
rotation, LS3: elephants’ foot buckling, base plate rotation].
(a)
(b)
Figure 4. Fragility curves: (a) 30m high steel chimney and (b) a process tower [LS1: top
displacement, LS2: Interstory drift, LS4: shell local buckling].
Preliminary results
Stakeholders and policy makers are typically more familiar with scenario-based results, compared
to time-based ones, because the former provide a “straightforward” answer on the expected
structural damages given that a specific earthquake scenario has occurred. These results are
usually included in risk assessment studies and are used for post-disaster emergency planning
and risk mitigation strategies designing, using the colour tagging of ATC-20: DS0 “green”, DS1
“yellow”, DS2 “orange”, DS3 “red”, and DS4 “black”. In such results, apparently, the likelihood of
the earthquake scenario in a given time period and consequently the distribution of the most
probable damage throughout the facility is not provided.
Two earthquake scenarios are considered in this study: (1) a M6.4 earthquake event at the
Loutraki fault, located 46km southwest of the considered refinery and (2) a M6.0 earthquake event
at the Ag. Theodoroi fault, located 32km west of the refinery. The accelerograms at the refinery
site were produced using the EXSIM (https://www.seismotoolbox.ca/) software taking into
consideration the effects of the source, the propagation path of the seismic waves, and the local
geotechnical conditions at the site of interest. The seismic sources are modelled by rectangular
planes that are divided into discrete sub-faults, which are then considered to be point sources.
The energy produced by these sub-faults propagates radially with a constant velocity and triggers
neighbouring sub-faults, leading to the rupture of the entire fault surface. The path effects are
represented by empirical attenuation relationships. The maximum acceleration at the refinery site
resulting from the event at the Loutraki fault is 0.37g, while from the event at the Ag. Theodoroi
fault is 0.621g. The consequences are depicted in Figure 5 for the scenario (1) and in Figure 6
for the scenario (2). In both cases, it is identified that the liquid storage tanks and the building in
the refining unit areas are the most vulnerable assets.
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Figure 5. M6.4 earthquake event at the Loutraki fault [scenario (1)]: Consequences in terms of
most probable DS.
Figure 6. M6.0 earthquake event at the Ag. Theodoroi fault [scenario (2)]: Consequences in
terms of most probable DS.
flare spherical pressure tanks
naphtha tanks
marine oil tanks
crude oil tanks
gasoline tanks
gasoline tanks
crude oil tanks
kerosene tanks
slop
oil
tanks
water
tanks fuel oil
tanks asphalt
tanks
lubricants
tanks
refining unit area 2
refining unit area 4
refining unit area 1
refining unit area 3
flare spherical pressure tanks
naphtha tanks
marine oil tanks
crude oil tanks
gasoline tanks
gasoline tanks
crude oil tanks
kerosene tanks
slop
oil
tanks
water
tanks fuel oil
tanks asphalt
tanks
lubricants
tanks
refining unit area 2
refining unit area 4
refining unit area 1
refining unit area 3
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Conclusions
The structural integrity and operational safety of crude oil refineries are critical, especially in the
event of an earthquake. To reliably achieve this dual objective, a comprehensive framework for
assessing the seismic risk of refineries is necessary. This study presents a preliminary seismic
risk assessment of a virtual mid-size oil refinery, which is examined as a case study. Initially, the
critical assets of the facility, namely liquid storage tanks, equipment-supporting building-type
structures, spherical pressure vessels, process towers, chimneys, and the flare, were identified
to formulate the exposure model. The seismic hazard at the site of interest was calculated using
the 2013 European Seismic Hazard Model. Reduced-order numerical models for the assets were
developed, and Incremental Dynamic Analysis was used to analyse the structures and compute
their seismic demands. The fragility curves of the assets were calculated by defining a set of
global damage states. Finally, the seismic consequences for two seismic scenarios were
evaluated, demonstrating that liquid storage tanks and equipment-supporting building-type
structures as the most vulnerable assets. While these results are typically used in risk assessment
studies to provide information to stakeholders and engineers for post-disaster emergency
planning and design, they may not be applicable for insurance purposes.
Acknowledgements
The authors would like to thank Dr. V. Karastathis, Research Director at the National Observatory
of Athens, Greece, for selecting the seismic scenarios and carrying out the analyses for producing
the accelerograms.
Funding
This research has been co-financed by the European Union through the HORIZON 2020 research
and innovation programme “METIS–Seismic Risk Assessment for Nuclear Safety” under Grant
Agreement No. 945121 and the HORIZON innovation action “PLOTO–Deployment and
Assessment of Predictive modelling, environmentally sustainable and emerging digital
technologies and tools for improving the resilience of IWW against Climate change and other
extremes” under Grant Agreement No. 101069941.
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