Facial reconstruction

Search LJMU Research Online

Browse Repository | Browse E-Theses


Dantsoho, AM (2015) RISK-BASED FRAMEWORK FOR SAFETY MANAGEMENT OF ONSHORE TANK FARM OPERATIONS. Doctoral thesis, Liverpool John Moores University.

[img] Text
158204_PhD Thesis of Abubakar Mahmud Dantsoho.pdf - Published Version

Download (2MB)


AbstractThe onshore tank farm operations has become more useful and handy, as a result of increased international sea-borne trade, particularly, the unprecedented higher volume of petroleum products and hazardous chemicals traffic globally. The onshore tank farm is a facility used for safe discharge, loading and storage of petroleum products and other hazardous chemicals at the ports. It has become an important element in the supply chain system because of the increased universal energy demand and the fact that large number of modern tanker vessel is busy and efficiently moving cargo to different destinations around the world. The tank farm serves as a back-up facility to the ports. However, it has high degree of system-wide challenges of potential major incidents/accidents, as evidenced in various tank farm recorded accidents, which occurred at different times with estimated losses valued in millions of US dollars. The accidents could be catastrophic, leading to deaths, extensive damages and adverse impact on environment. To eliminate or minimize the risk of major incident/accidents, as well as minimize the magnitude and severity, it is acutely urgent to uncover and assess all potential hazards, with a view to adopt the best preventive/mitigative policy direction in the management of this strategic facility.This thesis presents multiple safety/risk assessment approaches, uncertainties treatments and decision making techniques that are capable of finding optimal solutions that will ensure safety of tank farm operations. The standard tools of analysis employed in this tank farm operational risk assessment are Failure Mode Effect Analysis (FMEA), Faulty Tree Analysis (FTA), fuzzy logic, Analytic Hierarchy Process (AHP) and Technique for Order Preference by Similarity to the Ideal Solution (TOPSIS). Firstly, the FMEA-Fuzzy Rule Based (FRB) is applied in Hazard Identification (HAZID) and risk evaluation of tank farm operations. The methodology is utilized to discover five possible causes of catastrophic accidents in tank farm operations. The causes/hazards are described as the automatic shut-down oil safety valve failure, pipe corrosion protection system failure, automatic tank gauge system failure, leak detection device system failure, and secondary containment monitoring system failure. In the risk assessment conducted, the leak detection system failure was identified as the riskiest hazard using the Expected Utility Theory.Consequent upon the need for further investigation, another technique, Fuzzy Fault Tree (FFT), as novel model is used successfully to investigate and understand the causes of the leak detection system failure. The main aim of these two exercises is to assess risks and facilitate proper manage of these risks in tank farm operations, in order to forestall accidents that could cause damage to the facility, workers and the port environment. Nevertheless, the tank farm operations need to be optimized by ensuring the efficiency and safety of all systems and sub-systems through the adoption of best safety management decisions, which is achieved by employing AHP-TOPSIS model. This method is used to solve a complex multi-criteria decision-making problem such as selection of best Safety Control Design (SCD) among various SCDs identified. Finally, the results produced from the developed models and frameworks are summarized and other areas where they can effectively make impacts in HAZID, risk assessment and safety improvement are defined.

Item Type: Thesis (Doctoral)
Subjects: T Technology > TC Hydraulic engineering. Ocean engineering
T Technology > TJ Mechanical engineering and machinery
Divisions: Maritime & Mechanical Engineering (merged with Engineering 10 Aug 20)
Date Deposited: 04 Nov 2016 16:32
Last Modified: 03 Sep 2021 23:26
DOI or ID number: 10.24377/LJMU.t.00004496
Supervisors: Wal, Alan, Ren, Jun and Riahi, Ramin
URI: https://researchonline.ljmu.ac.uk/id/eprint/4496
View Item View Item