Vinyl Acetate Emission Rates and Explosions in Tank Farms in Dilovasi and Yumurtalik, Turkey: A Case Study

The emission estimations for vinyl acetate from storage tanks located in Dilovasi and Yumurtalik, Turkey, were completed by using the US EPA standard regulatory storage tanks emission model (TANKS 4.9b). Total annual emission was determined to be 7,603.15 kg/year for Yumurtalik and 6,057.06 kg/year for Dilovasi. In addition, ALOHA software was used in order to define emergency responses required in the case of vinyl acetate leakage based on different scenarios. According to ALOHA program modelling results, the threat regions occurred were 113 and 236 m for the red threat region, 299 and 663 m for the orange threat region, and 790 m and 2.0 km for the yellow threat region for vinyl acetate toxic vapour in Dilovasi and Yumurtalik, respectively. The threat regions determined were 10 and 15 m for the red threat region, 9.14 m for orange threat region, and 20 and 49 m for the yellow threat region for modelling of flammable area for the vapour cloud of vinyl acetate in Dilovasi and Yumurtalik, respectively. The amount of thermal radiation was determined to be 10 kW/m2 at a distance of 9.96 m from the tanks in both Dilovasi and Yumurtalik during a jet fire.

Experimental Aircraft Fuel Tank Vapour/Air Explosions Using Jet A and Jet A / Gasoline Blend Fuels

The potential of a fuel tank explosion is a well-known hazard in the aircraft industry. In this study, an investigation of a lab scale aircraft fuel tank in a flight situation at varying initial pressures of 400 - 1,000 mbar (equivalent to altitudes of 0 - 22,300 ft) and at variable temperatures was conducted in a 100-litre cylindrical test rig. A standard Jet A fuel and with a type Jet B fuel (which in this case was a Jet A with 10% of gasoline by mass) were used. Their flashpoints were measured to be 45oC (Jet A) and 20 oC (Jet B). In the simulated fuel tank explosions ignition occurred when the fuel liquid temperature was much higher than the flash point - 71 – 107 oC depending on initial pressure (altitude) for Jet A and 57 – 95 oC for the more volatile Jet B. The resulting maximum explosion overpressures were high, ranging from 0.7 to 5.8 bar, much higher than typical design strengths of aircraft fuel tanks, and much stronger than anticipated overpressures on the basis of ignition at or close to the lower flammability limit (LFL). It is postulated that these pressures are due to the distance between the liquid fuel surface and the ignition point and the formation of a vapour cloud with decreasing concentration with height above the fuel (being at LFL at the ignition point) and hence an overall concentration much higher than LFL. This demonstrated that severe explosions are fuel tanks are likely and the assumption that the explosion will be a near lean limit event is not safe. The work also provided explosion severity index data which can be used in design of suppression and venting systems for the mitigation of aircraft fuel tank explosions and provided other quantitative data to help manage this explosion risk appropriately.

Investigating Vapour Cloud Explosion Dynamic Fatality Risk on Offshore Platforms by Using a Grid-Based Framework

The reliability of petroleum offshore platform systems affects human safety and well-being; hence, it should be considered in plant design and operation in order to determine its effect on human fatality risk. Methane Vapour Cloud Explosions (VCE) in offshore platforms are known to be one of the fatal potential accidents that can be attributed to failure in plant safety systems. Traditional Quantitative Risk Analysis (QRA) lacks in providing microlevel risk assessment studies and are unable to update risk with the passage of time. This study proposes a grid-based dynamic risk analysis framework for analysing the effect of VCEs on the risk of human fatality in an offshore platform. Flame Acceleration Simulator (FLACS), which is a Computational Fluid Dynamics (CFD) software, is used to model VCEs, taking into account different wind and leakage conditions. To estimate the dynamic risk, Bayesian Inference (BI) is utilised using Accident Sequence Precursor (ASP) data. The proposed framework offers the advantage of facilitating microlevel risk analysis by utilising a grid-based approach and providing grid-by-grid risk mapping. Increasing the wind speed (from 3 to 7 m/s) resulted in maximum increase of 21% in risk values. Furthermore, the integration of BI with FLACS in the grid-based framework effectively estimates risk as a function of time and space; the dynamic risk analysis revealed up to 68% increase in human fatality risk recorded from year one to year five.