Document Type dissertation Author Name Ierardi, James Arthur Email Address ierardi at alum.wpi.edu URN etd-051105-160327 Title Characterizing the Entry Resistance of Smoke Detectors Degree PhD Department Fire Protection Engineering Advisors Prof. Jonathan R. Barnett, Advisor Prof. Nicholas A. Dembsey, P.E., Co-Advisor Keywords smoke detector response modeling entry resistance resistance factor Date of Presentation/Defense 2005-05-11 Availability unrestricted
Entry resistance in smoke detectors was investigated using experimental and analytical approaches. The experimental work consisted of measuring velocity inside the sensing chamber of smoke detectors with a two-component Laser Doppler Velocimeter and exposing addressable smoke detectors to four different aerosol sources. The velocity measurements and exposure tests were performed in NIST’s Fire Emulator / Detector Evaluator under steady state flow conditions in the range of 0.08 to 0.52 m/s. The addressable detectors were a photoelectric and an ionization detector. A specially constructed rectangular detector model was also used for the interior velocity measurements in order to have geometry compatible with numerical approaches, such as computational fluid dynamics modeling or a two-dimensional analytical solution. The experimental data was used to investigate the fluid mechanics and mass transport processes in the entry resistance problem.
An inlet velocity boundary condition was developed for the smoke detectors evaluated in this study by relating the external velocity and detector geometry to the internal velocity by way of a resistance factor. Data from the exposure tests was then used to characterize the nature of aerosol entry lag and sensor response. The time to alarm for specific alarm points was determined in addition to performing an exponential curve fit to obtain a characteristic response time. A mass transport model for smoke detector response was developed and solved numerically. The mass transport model was used to simulate the response time data collected in the experimental portion of this study and was found, in general, to underestimate the measured response time by up to 20 seconds. However, in the context of wastebasket fire scenario the amount of underprediction in the model is 5 seconds or less which is within the typically polling interval time of 5 to 10 seconds for an addressable system. Therefore, the mass transport model results developed using this proposed engineering framework show promise and are within the expected uncertainty of practical fire protection engineering design situations.
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