Fuel tank safety has been an issue associated with the design and operation of aircraft fuel systems for decades. Research in this area has undergone transition from the early stage of the use of polyurethane reticulated foam installed within the fuel tanks, to the present day On Board Inert Gas Generating System (OBIGGS). Recent patents related to the topic have been discussed. This paper presents the safety assessment of an OBIGGS using genetic algorithm. Functional Hazard Assessment (FHA), Preliminary System Safety Assessment (PSSA), Fault Tree Analysis (FTA) and Failure Mode and Effect Critical Analysis (FMECA) were all used in the study. Genetic algorithm was used to optimize the Cyclic Flow Multiplying Factor (CFMF), using MatLab programming language. Decoding model was developed for this problem. Point mask and binary window crossover techniques were implemented. The calculated failure rate of the Air Separation Module (ASM) for reliability prediction purposes is 9.125E-08. The budgeted ASM failure rate for a 10hours flight was well greater than the calculated failure rate as shown in the Failure Mode and Effect Summary (FMES).
Safety Assessment, Board Inert Gas, Board Inert Gas Generating System, Air separation module, genetic algorithm and failure rate, optimization, FMEA, Effect Critical Analysis, MatLab, Genetic algorithm, Functional Hazard Assessment, Cyclic Flow Multiplying Factor, Inert Gas, Viscosity, Aircraft Inerting Systems, Air separation module (ASM), safety
College of Civil Aviation, Nanjing University of Aeronautics and Astronautics, Nanjing, Jiangsu Province, China.