Microbubbles oxygen transfer to water was simulated based on experimental results obtained from the bubbles generation operated under varying liquid supply velocity to the multi-step orifices of the generator. It had been known that liquid supply velocity and bubble size are inversely related. In the oxygen transfer, a non-steady state was assumed and the pseudo stagnation caused the slow movement of bubbles from the bottom to the water surface. Two parameters were considered for the simulation: They represent a factor to correct the pseudo stagnation state and a scale which represented the amount of bubbles in supply versus time. The sum of absolute error determined by fitting regression to the experimental results was comparable to that of the American Society of Civil Engineers (ASCE) model, which is based on concentration differential as the driving force. Hence, considering the bubbles formation factors, the simulation process has the potential to be easily used for applications by introducing two parameters in the assumptions. Compared with the ASCE model, the simulation method reproduced the experimental results well by detailed conditions.

In steady-state simulation the output data of the transient phase often cause a bias in the estimation of the steady-state results. A common method is to cut off this transient phase. This paper presents a new heuristic used to detect the warm-up period in steady-state simulation output. An evaluation procedure is used to compare the presented rule, called EVR, with the method MSER-m known as the most sensitive rule in detecting bias and most consistent rule in mitigating its effects. The rules are applied to the output generated by M/M/1 queuing process and the performance of the methods is tested at 4 different levels of utilizations. Various measures of goodness are used to assess the effectiveness, consistency and confidence of the methods.