The relation of cool flames and auto-ignition phenomena to process safety at elevated pressure and temperature.
The cool-flame phenomenon can occur in fuel-oxygen (air) mixtures within the flammable range and outside the flammable range, at fuel-rich compositions, at temperatures below the auto-ignition temperature (AIT). It is caused by chemical reactions occurring spontaneously at relatively low temperatures and is favoured by elevated pressure. The hazards that cool flames generate are described. These vary from spoiling a product specification through contamination and explosive decomposition of condensed peroxides to the appearance of unexpected normal (hot) flame (two-stage ignition).
Pressure dependence of the auto-ignition temperature of methane/air mixtures
Abstract The results of experiments conducted to determine the auto-ignition temperature (AIT) and the cool flame temperature (CFT) of methane/air mixtures at elevated pressures (200–4700 kPa) and for concentrations from 30 up to 83 vol.% are reported. The experiments were performed in a closed spherical vessel with a volume of 8 dm 3 . It is shown that methane/air mixtures can react spontaneously for methane concentrations far outside the flammability limits. Cool flames are observed for methane concentrations higher than 40 vol.%. The AIT and CFT are strongly pressure-dependent and decrease with increasing pressures. A Semenov correlation is developed for the CFT as a function of the pressure. The upper explosion limit (UEL) of methane/air mixtures at elevated pressure and temperature is linked with the CFT. It is shown that for certain conditions of pressure and temperature, the flammability range increases considerably even for a small temperature rise.
An intelligent control system for ventilators.
This study reports on a ventilator system that consists of several intelligent modules for controlling ventilator operation. These modules are software programs in two controllers. One controller is a personal computer used for diagnoses, determining settings and checking the effects of settings. The other controller is a single-chip microprocessor in a ventilator that controls the ventilator's settings in accordance with the computer settings. After setting up the system, an artificial lung model simulating a patient's lung is used to test the system. The result of test run indicated that it always responds to a patient's lung condition in a stable manner. Thus, the proposed system with its intelligent modules may assist clinicians in caring for patients and managing ventilator operation.