Multiple Tank Explosions in an Edible-Oil Refinery Plant: A Case Study

2013 ◽  
Vol 36 (7) ◽  
pp. 1131-1137 ◽  
Author(s):  
L. Marmo ◽  
N. Piccinini ◽  
G. Russo ◽  
P. Russo ◽  
L. Munaro
Keyword(s):  
Edible Oil ◽  
Oil Refinery ◽  
Refinery Plant

scholarly journals Various risks and safety analysis to reduce fire in oil refinery plant

2021 ◽  
Vol 1078 (1) ◽  
pp. 012028
Author(s):  
Md Zahangir Alam ◽  
Md Nazmus Sakib ◽  
Minarul Islam ◽  
Mohammad Jalal Uddin
Keyword(s):  
Safety Analysis ◽  
Oil Refinery ◽  
Refinery Plant

Decision Support Model for Fire Insurance Risk Analysis in a Petrochemical Case Study

2015 ◽  
pp. 990-1004
Author(s):  
Hadis Z. Nejad ◽  
Reza Samizadeh
Keyword(s):  
Decision Support ◽  
Risk Analysis ◽  
Oil And Gas ◽  
Oil Refinery ◽  
Decision Support Model ◽  
Analysis Methodology ◽  
Damage Costs ◽  
Fire Insurance ◽  
Margin Of Error

A decision support system was researched and applied to a case study in the petrochemical industry. The participants were an insurance company underwriting the policies of oil and gas refineries located in a major oil producing nation. The Chemical Process Quantitative Risk Analysis methodology was applied as a framework to implement uncertainty quantification and risk analysis using a specialized commercial DSS software product. A gas vapor explosion was simulated at an oil refinery, to predict the fire and radiation damage. Costs and risks were entered into the model based on historical data. Loss estimates were generated for equipment and buildings located various distances (pressures) from the explosion origin. Overall, the DSS model predicted an expected loss of over $14,000,000 USD for equipment located in the 50 meter explosion radius, which represented a loss ratio of almost 52%. The losses predicted from the DSS model were comparable to the literature and to experiences of the case study company. The margin of error from the DSS model was less than ±5% which made it very reliable according to benchmarks.

scholarly journals Production of glycolipid biosurfactant during crude oil degradation by the novel indigenous isolated Achromobacter kerstersii LMG3441

2020 ◽  
Vol 82 (10) ◽  
pp. 2134-2147
Author(s):  
Somayeh Kazemzadeh ◽  
Nafiseh Sadat Naghavi ◽  
Zarrindokht Emami-Karvani ◽  
Giti Emtiazi ◽  
Masoud Fouladgar
Keyword(s):  
Crude Oil ◽  
High Surface ◽  
Oil Refinery ◽  
Gas Chromatography Mass Spectrometry ◽  
Klebsiella Pneumonia ◽  
Glycolipid Biosurfactant ◽  
Rdna Sequencing ◽  
Degrading Bacteria ◽  
High Resolution Gas Chromatography ◽  
Refinery Plant

Abstract This study aimed to find biosurfactant producing and crude oil-degrading bacteria able to decontaminate crude oil from wastewater. The bacteria that were isolated from contaminated sites in an oil refinery plant in Isfahan, Iran, were identified by 16S rDNA sequencing as Achromobacter kerstersii strain LMG3441, Klebsiella pneumonia strain SKBA6, and Klebsiella variicola strain SKV2. According to the results obtained from different tests for the production of biosurfactant among three strains, only Achromobacter kerstersii strain LMG3441 was selected for further study. The pattern of residual hydrocarbons was analyzed by high-resolution gas chromatography-mass spectrometry (GC-MS). This novel and indigenous strain was capable of producing the highest amount of a glycolipid biosurfactant (7.81 g/L) in MSM (mineral salt medium) with 1% (v/v) crude oil as the only source of carbon and energy. The compound showed high surface activation capacity with reduction of surface tension from 40 mN m–1 in the control to 23.3 mN m–1 by the bacterium. The results of GC-MS for assessment of residual hydrocarbons in the MSM and comparison with crude oil as a control showed that 53% of the hydrocarbons in the crude oil were consumed by this novel strain.

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