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UID:0-321@aerospace.technion.ac.il

DTSTART;TZID=Asia/Jerusalem:20191104T163000

DTEND;TZID=Asia/Jerusalem:20191104T173000

DTSTAMP:20230527T132149Z

URL:https://aerospace.technion.ac.il/events/investigation-of-the-influence
 -of-graphite-additives-on-the-fuel-regression-rate-in-hybrid-propulsion/

SUMMARY:Investigation of the Influence of Graphite Additives on the Fuel Re
 gression Rate in Hybrid Propulsion
DESCRIPTION:Lecturer:Silky Elanjickal\n Faculty:Department of Aerospace Eng
 ineering\n Institute:Technion – Israel Institute of Technology\n Locatio
 n:Classroom 165\, ground floor\, Library\, Aerospace Eng.\n Zoom: \n Abstr
 act: \n Details: \n Hybrid propulsion can be a good alternative to the sol
 id and liquid propellant systems\; recently it has been the preferred choi
 ce for space tourism missions. In comparison to the solid and liquid prope
 llant systems\, hybrid rockets have improved safety and controllability. H
 owever\, one of the major drawbacks of hybrid motors is its slow regressio
 n rate leading to a low thrust. The main objective of this research is to 
 experimentally and theoretically investigate the influence of an additive 
 called expandable graphite (EG) on the fuel regression rate.\nExpandable g
 raphite (EG) has a unique property of forming accordion-like strings which
  are several times longer than the original particle size\, when heated to
  high temperatures. EG is known to have a high thermal conductivity. When 
 mixed with a fuel matrix\, these strings can increase the heat transfer in
 to the fuel through conduction\, thus increasing the regression rate. Stat
 ic firing tests were conducted employing polymeric and liquefying fuels\, 
 with and without EG\, using gaseous oxygen as the oxidizer. The experiment
 al results revealed an increase of 30%-200% in the fuel regression rate du
 e to the addition of EG into the fuel matrix. A larger relative effect was
  observed for the polymeric fuel in comparison to the liquefying fuel. The
 oretical model predictions showed good agreement with the experimental res
 ults\, within approximately ± 10%.
CATEGORIES:Seminars
LOCATION:Classroom 165\, ground floor\, Library\, Aerospace Eng.

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DTSTART:20191027T010000

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