Network


Latest external collaboration on country level. Dive into details by clicking on the dots.

Hotspot


Dive into the research topics where Ehsan Arzaghi is active.

Publication


Featured researches published by Ehsan Arzaghi.


Process Safety Progress | 2016

Dynamic risk-based maintenance for offshore processing facility

Jyoti Bhandari; Ehsan Arzaghi; Rouzbeh Abbassi; Vikram Garaniya; Faisal Khan

Processing facilities in a marine environment may not remain safe and available if they are not well maintained. Dynamic risk‐based maintenance (RBM) methodology is a tool for maintenance planning and decision making, used to enhance the safety and availability of the equipment. It also assists in identifying and prioritizing the maintenance of equipment based on the level of risk. This article discusses an advanced methodology for the design of an optimum maintenance program integrating a dynamic risk‐based approach with a maintenance optimization technique. In this study, Bayesian Network (BN) is employed to develop a new dynamic RBM methodology that is capable of using accident precursor information in order to revise the risk profile. The use of this methodology is based on its failure prediction capability which optimizes the cost of maintenance. The developed methodology is applied to a case study involving a failure of a separator system in the offshore oil and gas production platform considering marine environments. The result shows it is essential that the valve system in the separator needs to be planned for maintenance once every 25 days; however, the cooler system can be planned for repairs once only biennially. A sensitivity analysis is also conducted to study the criticality of the operating system.


Journal of Hazardous Materials | 2019

Multi-level optimization of maintenance plan for natural gas system exposed to deterioration process

Ahmad BahooToroody; Mohammad Mahdi Abaei; Ehsan Arzaghi; Farshad BahooToroody; Filippo De Carlo; Rouzbeh Abbassi

In this paper, a risk-based optimization methodology for a maintenance schedule considering Process Variables (PVs), is developed within the framework of asset integrity assessment. To this end, an integration of Dynamic Bayesian Network, Damage Modelling and sensitivity analysis are implemented to clarify the behaviour of failure probability, considering the exogenous undisciplinable perturbations. Discrete time case is considered through measuring or observing the PVs. Decision configurations and utility nodes are defined inside the network to represent maintenance activities and their associated costs. The regression analysis is considered to model the impact of perturbations on PVs for future applications. The developed methodology is applied to a case study of Chemical Plant (Natural Gas Regulating and Metering Stations). To demonstrate the applicability of the methodology, three cases of seasonal observations of specific PV (pressure) are considered. The proposed methodology could either analyse the failure based on precursor data of PVs or obtain the optimum maintenance schedule based on actual condition of the systems.


Marine Pollution Bulletin | 2018

An ecological risk assessment model for Arctic oil spills from a subsea pipeline

Ehsan Arzaghi; Rouzbeh Abbassi; Vikram Garaniya; Jonathan Binns; Faisal Khan

There is significant risk associated with increased oil and gas exploration activities in the Arctic Ocean. This paper presents a probabilistic methodology for Ecological Risk Assessment (ERA) of accidental oil spills in this region. A fugacity approach is adopted to model the fate and transport of released oil, taking into account the uncertainty of input variables. This assists in predicting the 95th percentile Predicted Exposure Concentration (PEC95%) of pollutants in different media. The 5th percentile Predicted No Effect Concentration (PNEC5%) is obtained from toxicity data for 19 species. A model based on Dynamic Bayesian Network (DBN) is developed to assess the ecological risk posed to the aquatic community. The model enables accounting for the occurrence likelihood of input parameters, as well as analyzing the time-variable risk profile caused by seasonal changes. It is observed through the results that previous probabilistic methods developed for ERA can be overestimating the risk level.


Renewable Energy | 2017

Developing a novel risk-based methodology for multi-criteria decision making in marine renewable energy applications

Mohammad Mahdi Abaei; Ehsan Arzaghi; Rouzbeh Abbassi; Vikram Garaniya; I Penesis


Engineering Failure Analysis | 2017

Risk-based maintenance planning of subsea pipelines through fatigue crack growth monitoring

Ehsan Arzaghi; Mohammad Mahdi Abaei; Rouzbeh Abbassi; Vikram Garaniya; Christopher Chin; Faisal Khan


Journal of Petroleum Science and Engineering | 2017

Risk-based maintenance of offshore Managed Pressure Drilling (MPD) operation

Gallant Pui; Jyoti Bhandari; Ehsan Arzaghi; Rouzbeh Abbassi; Vikram Garaniya


Ocean Engineering | 2018

A robust risk assessment methodology for safety analysis of marine structures under storm conditions

Mohammad Mahdi Abaei; Ehsan Arzaghi; Rouzbeh Abbassi; Vikram Garaniya; Shuhong Chai; Faisal Khan


Process Safety and Environmental Protection | 2018

A hierarchical Bayesian approach to modelling fate and transport of oil released from subsea pipelines

Ehsan Arzaghi; Mohammad Mahdi Abaei; Rouzbeh Abbassi; Vikram Garaniya; Jonathan Binns; Christopher Chin; Faisal Khan


Ocean Engineering | 2018

Dynamic reliability assessment of ship grounding using Bayesian Inference

Mohammad Mahdi Abaei; Ehsan Arzaghi; Rouzbeh Abbassi; Vikram Garaniya; M Javanmardi; Shuhong Chai


Ocean Engineering | 2017

Developing a dynamic model for pitting and corrosion-fatigue damage of subsea pipelines

Ehsan Arzaghi; Rouzbeh Abbassi; Vikram Garaniya; Jonathan Binns; Christopher Chin; Nima Khakzad; Genserik Reniers

Collaboration


Dive into the Ehsan Arzaghi's collaboration.

Top Co-Authors

Avatar
Top Co-Authors

Avatar

Vikram Garaniya

Australian Maritime College

View shared research outputs
Top Co-Authors

Avatar
Top Co-Authors

Avatar

Faisal Khan

Memorial University of Newfoundland

View shared research outputs
Top Co-Authors

Avatar

Jonathan Binns

Australian Maritime College

View shared research outputs
Top Co-Authors

Avatar

Christopher Chin

Australian Maritime College

View shared research outputs
Top Co-Authors

Avatar

Shuhong Chai

Australian Maritime College

View shared research outputs
Top Co-Authors

Avatar

Garaniya

Australian Maritime College

View shared research outputs
Top Co-Authors

Avatar

Jyoti Bhandari

Australian Maritime College

View shared research outputs
Top Co-Authors

Avatar

Genserik Reniers

Delft University of Technology

View shared research outputs
Researchain Logo
Decentralizing Knowledge