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Field studies show that the internal screens in a gross pollutant trap (GPT) are often clogged with organic matter, due to infrequent cleaning. The hydrodynamic performance of a GPT with fully blocked screens was comprehensively investigated under a typical range of onsite operating conditions. Using an acoustic Doppler velocimeter (ADV), velocity profiles across three critical sections of the GPT were measured and integrated to examine the net fluid flow at each section. The data revealed that when the screens are fully blocked, the flow structure within the GPT radically changes. Consequently, the capture/retention performance of the device rapidly deteriorates. Good agreement was achieved between the experimental and the previous 2D computational fluid dynamics (CFD) velocity profiles for the lower GPT inlet flow conditions.

A statistical modeling method to accurately determine combustion chamber resonance is proposed and demonstrated. This method utilises Markov-chain Monte Carlo (MCMC) through the use of the Metropolis-Hastings (MH) algorithm to yield a probability density function for the combustion chamber frequency and find the best estimate of the resonant frequency, along with uncertainty. The accurate determination of combustion chamber resonance is then used to investigate various engine phenomena, with appropriate uncertainty, for a range of engine cycles. It is shown that, when operating on various ethanol/diesel fuel combinations, a 20% substitution yields the least amount of inter-cycle variability, in relation to combustion chamber resonance.

A technique was developed to investigate the capture/retention characteristic of a gross pollutant trap (GPT) with fully and partially blocked internal screens. Custom modified spheres of variable density filled with liquid were released into the GPT inlet and monitored at the outlet. The outlet data shows that the capture/retention performances of a GPT with fully blocked screens deteriorate rapidly. During higher flow rates, screen blockages below 68% approach maximum efficiency. At lower flow rates, the high performance trend is reversed and the variation in behaviour of pollutants with different densities becomes more noticeable. Additional experiments with a second upstream inlet configured GPT showed an improved capture/retention performance. It was also noted that the bypass allows the incoming pollutants to escape when the GPT is blocked. This useful feature prevents upstream blockages between cleaning intervals.