Predicting Smoke Detector Responce Using a Quantitative Salt-Water Modeling Technique

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dc.contributor.advisorMarshall, Andreen_US
dc.contributor.advisorRoby, Richarden_US
dc.contributor.authorjankiewicz, seanen_US
dc.contributor.departmentFire Protection Engineeringen_US
dc.contributor.publisherDigital Repository at the University of Marylanden_US
dc.contributor.publisherUniversity of Maryland (College Park, Md.)en_US
dc.date.accessioned2004-08-27T05:17:58Z
dc.date.available2004-08-27T05:17:58Z
dc.date.issued2004-06-16en_US
dc.description.abstractThis investigation provides a detailed analysis of the hydraulic analogue technique used as a predictive tool for understanding smoke detector response within a complex enclosure. There currently exists no collectively accepted method for predicting the response of smoke detectors; one of the most important elements in life safety. A quantitative technique has been developed using salt-water modeling and planar laser induced fluorescence (PLIF) diagnostics. The non-intrusive diagnostic technique is used to temporally and spatially characterize the dispersion of a buoyant plume within a 1/7th scale room-corridor-room enclosure. This configuration is geometrically similar to a full-scale fire test facility, where local conditions were characterized near five ionization type smoke detectors placed throughout the enclosure. An evaluation of the scaled local conditions and dispersive event times for both systems was used to formulate a preliminary predictive detector response model for use with the hydraulic analogue.en_US
dc.format.extent5005392 bytes
dc.format.mimetypeapplication/pdf
dc.identifier.urihttp://hdl.handle.net/1903/1709
dc.language.isoen_US
dc.subject.pqcontrolledEngineering, Generalen_US
dc.subject.pquncontrolledfireen_US
dc.subject.pquncontrolledsalt wateren_US
dc.subject.pquncontrolledPLIFen_US
dc.subject.pquncontrolledmodelingen_US
dc.subject.pquncontrolledsmoke detectoren_US
dc.subject.pquncontrolleddispersionen_US
dc.titlePredicting Smoke Detector Responce Using a Quantitative Salt-Water Modeling Techniqueen_US
dc.typeThesisen_US

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