Knowledge (XXG)

Hybrid rocket fuel regression

Source ๐Ÿ“

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power function. Initially, methods for fitting the power function were often left ambiguous in publications due to variation in the possible calculations for average mass flux, making it difficult to compare findings. A now commonly-referenced study by Karabeyoglu indicates that the easiest measurement, the port diameter average, also provides the most accurate results.
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Because of the lack of accurate prediction methods, each system should generally be tested in full configuration to accurately determine the regression rate before flight. Typically, data points for several identical grains tested under different flux conditions are fitted to the space-time averaged
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In fact, the process is even slightly more complicated because corners protruding into the combustion chamber will regress more quickly than their circular counterparts, since they are exposed to heat on both sides. To model the problem, Bath developed a technique of iteratively blurring pixels and
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Using non-circular port cross sections increases the area exposed to the oxidizer to be gasified, especially at the start of the burn. However, as the fuel continues to regress it will begin to round out the shape because regression generally occurs normal to the fuelโ€™s surface, and corners tend to
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Many alternative equations for regression rate have been derived, usually constructed by reconsidering the assumptions made by Marxman but using the same diffusion-limited calculation approach. A model published by Karabeyoglu, for example, provides a more accurate approach by considering variation
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or complex port designs that result in excess mass. Regression rate has also proven quite difficult to predict, with advanced models still providing significant error when applied at various scales and with differing fuels. Recent research has centered around the development of more accurate models
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In contrast to solid rocket motors, hybrids exhibit significant dependence on the size of the port and low dependence on chamber pressure under normal conditions. Because they are dominated by thermodynamic forces, models typically emerge via a heat transfer calculation. Marxman provided the first
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The simplest technique for increasing the regression rate is to use a different fuel. Solids with lower molecular masses tend to have lower viscosities, a quality which generally correlates with a decrease in the required energy for gasification. Taken to the extreme, a new phenomenon actually
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and Orbital Technologies Corporation (ORBITEC) tested several cryogenic fuels in an effort to increase specific impulse. Using solidified pentane, they found regression rates vastly increased over traditional hybrid fuels. Several tests with paraffin also foreshadowed modern liquifying rocket
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Unfortunately, most models still require an empirical factor that depends on variations in fuel and oxidizer flow paths for different port geometries. In the case of the image blurring model, predictions of regression are also dependent on the settings used in the image processing program.
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Some of the first attempts at complex geometries were wagon wheel designs developed by the United Technology Center. Though they massively increase fuel flow, wagon wheels require that a significant portion of fuel is left behind, or the structure could break apart.
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emerges, where a melt layer at the surface of the fuel allows droplets to be entrained as oxidizer flows past. At the flux levels commonly seen in hybrid rocketry, this entrainment actually accounts for the largest portion of regression (dominating vaporization).
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being burned is important for the effectiveness of combustion in the engine, the regression rate plays a fundamental role in the design and firing of a hybrid engine. Unfortunately, hybrid fuel grains tend to have extremely slow regression, requiring very long
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concluded that regression rates generally increased by at least a factor of two, up to even a factor of four. In general, helical regression rate is modeled by several multiplicative adjustments to the skin friction coefficient and to the blowing coefficient.
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removing those that fall below a certain threshold of brightness. Using the image processing to generate a table of surface area outputs for a given volume, it can easily be implemented into a model for regression of the fuel grain over time.
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by effectively combining most of the terms into one coefficient that is assumed constant throughout the burn. It was typically simplified into a basic equation by considering the average regression over time for a test, fitting coefficients
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of fuel is usually given by the regression rate multiplied by the burn area. Depending on the complexity of the grain geometry, it can also be quite difficult to calculate. At its simplest form, a tube-shaped fuel grain has a burn area of
436:, the strong dependence on flux was a key finding. Unfortunately, many components of the equation are extremely difficult to determine, so most engineers focused on developing models based on testing, fitting the regression rate to a 895:
Models of burn area based on 2D cross sections lose another component of accuracy because they assume regression in the radial direction. For a helical grain, for example, the burn area predicted by Bath's model would be incorrect.
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Similar concepts can be seen in an extension by Whitmore, where the Prandtl number is approximated as 0.8 and the skin friction coefficient is recalculated to consider blowing and the flow development along the grain length.
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designs have been used to create a centripetal component of flow, reducing blowing and providing greater friction between the oxidizer and fuel in order to increase convection. Analysis at the
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and leaving the engine. Indeed, paraffin has a tendency to even slough off large fragments, greatly reduces combustion efficiency and potentially contributing to combustion instability.
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The burn area refers to the surface exposed to the heat of the combustion chamber, and it is just as pivotal to the regression of the rocket as the regression rate itself, since the
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is converted from a solid to a gas that is combusted. It encompasses the regression rate, the distance that the fuel surface recedes over a given time, as well as the burn area, the
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Although it is much harder to predict, complex grain geometries offer another technique for increasing regression rate and burn area in order to greatly increase fuel flow.
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T. R. Brown, M. C. Lydon, Testing of Paraffin-Based Hybrid Rocket Fuel using Hydrogen Peroxide Oxidizer, AIAA Region Student Conference, Wichita, KS, USA, April 6โ€“8, 2005
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or other geometric software to determine the surface area, particularly as the surface area regresses along the normals, often creating highly irregular geometry.
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Bath, Andrew, "Performance Characterization of Complex Fuel Port Geometries for Hybrid Rocket Fuel Grains" (2012). All Graduate Theses and Dissertations. 1381.
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An Investigation of Injectors for Use with High Vapor Pressure Propellants with Applications to Hybrid Rockets. BS Waxman. Stanford University, 2014.
1642: 1600: 1198: 425:{\displaystyle {\dot {r}}={\frac {0.036G}{\rho _{f}}}{({\frac {Gx}{\mu }})}^{-0.2}{({\frac {u_{e}}{u_{c}}}{\frac {\Delta h}{h_{v}}})}^{0.23}} 883:
Bath's regression algorithm begins with a cross section of the port, blurs it, then converts back to black and white based on a threshold.
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attempt at an a priori model of hybrid regression, basing the rate on a heat transfer equilibrium calculation and assuming unity for the
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Where G is the mass flux of propellant and x is the distance along the fuel grain. Though Marxman's initial math indicates that
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Sutton, George P, and Oscar Biblarz. Rocket Propulsion Elements. New York: John Wiley & Sons, 2001.
1333: 193: 1388: 1230: 836: 796: 1540:"Radiation Heating Effects on Oxidizer-to-Fuel Ratio of Additively Manufactured Hybrid Rocket Fuels" 1384:
Experimental Review of Methods for Performance Enhancement of Paraffin Fueled Hybrid Rocket Motors
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Doran, Eric; Dyer, Jonny; Lohner, Kevin; Dunn, Zach; Cantwell, Brian; Zilliac, Greg (2007),
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regress faster. Generally, this will cause the O/F ratio to shift away from stoichiometric.
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technology, with the Peregrine rocket among others leading the way for further development.
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added to the area on both ends. However, a star-shaped fuel grain could require the use of
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Whitmore, Stephen A.; Walker, Sean D.; Merkley, Daniel P.; Sobbi, Mansour (2015-11-01).
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The alternative regression method does supply some other issues, mainly a reduction in
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Piscitelli, F.; Saccone, G.; Gianvito, A.; Cosentino, G.; Mazzola, L. (2018-09-01).
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Though the model showed large errors when used to predict regression rate for an
1581:"Analytical and Experimental Comparisons of HTPB and ABS as Hybrid Rocket Fuels" 190:
for the velocity ratio between gas in the main stream and gas at the flame, and
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The concept was originally discovered during a brief research period in which
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Both improved formulas appear to show a better relationship with tested data.
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for the ratio considering the enthalpy difference from flame to fuel surface (
1523: 1479: 1425:"High Regression Rate Hybrid Rocket Fuel Grains with Helical Port Structures" 1359: 1250: 1424: 1455: 1218: 1127: 1411: 1268: 1623:"Nitrous Oxide Hybrid Rocket Motor Fuel Regression Rate Characterization" 1634: 1592: 1190: 1300:"From Pedicures to the Peregrine Rocket, Paraffin Wax Proves Its Worth" 125: 1126:
Karabeyoglu, M. Arif; Cantwell, Brian J.; Zilliac, Greg (2007-07-01).
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coupled with research into techniques for increasing regression rate.
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Karabeyoglu, M. Arif; Cantwell, Brian J.; Zilliac, Greg (July 2007).
1440: 1269:"Combustion of Liquefying Hybrid Propellants: Part 1, General Theory" 1471: 1242: 1143: 1539: 1284: 878: 819: 433: 1627:
43rd AIAA/ASME/SAE/ASEE Joint Propulsion Conference & Exhibit
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47th AIAA/ASME/SAE/ASEE Joint Propulsion Conference & Exhibit
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42nd AIAA/ASME/SAE/ASEE Joint Propulsion Conference & Exhibit
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Whitmore, Stephen; Peterson, Zachary; Eilers, Shannon (2011),
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Karabeyoglu, M. A.; Altman, D.; Cantwell, B. J. (2002-05-01).
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in the Prandtl number, accounting for entrance effects in the
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Advanced Hybrid Rocket Motor Propulsion Unit For CubeSats
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Eilers, Shannon D.; Whitmore, Stephen A. (2008-09-01).
1629:, American Institute of Aeronautics and Astronautics, 1587:, American Institute of Aeronautics and Astronautics, 1179:"Hybrid Rocket Fuel Regression Rate Data and Modeling" 946: 925: 846: 706: 686: 680:, the flux of oxidizer, for the flux term instead of 659: 639: 619: 590: 564: 507: 487: 467: 447: 290: 263: 236: 196: 154: 134: 103: 83: 63: 633:
and usually shows less dependence than predicted on
57:. He eventually developed the below equation, using 19:refers to the process by which the fuel grain of a 952: 931: 864: 746: 692: 672: 645: 625: 605: 576: 550: 493: 473: 453: 424: 276: 245: 222: 182: 140: 116: 89: 69: 1177:Zilliac, Gregory; Karabeyoglu, M. (2006-07-09). 8: 909:Space-Time Averaged Regression Coefficients 613:, data typically ranges from 0.5 to 0.8 for 148:for viscosity of the main-stream gas flow, 907: 1555: 1522: 1349: 945: 924: 845: 738: 731: 726: 708: 707: 705: 685: 664: 658: 638: 618: 589: 563: 542: 532: 527: 509: 508: 506: 486: 466: 446: 416: 404: 390: 382: 372: 366: 362: 352: 333: 329: 320: 306: 292: 291: 289: 268: 262: 235: 213: 208: 203: 195: 174: 165: 159: 153: 133: 108: 102: 82: 62: 551:{\displaystyle {\dot {r}}=a{G}^{n}x^{m}} 27:that is being eroded at a given moment. 1412:https://digitalcommons.usu.edu/etd/1381 1118: 747:{\displaystyle {\dot {r}}=a{G_{o}}^{n}} 1538:Whitmore, S. A.; Merkley, S. (2019). 1491: 1489: 1406: 1404: 1402: 7: 1262: 1260: 1212: 1210: 1172: 1170: 1168: 1166: 1164: 1162: 77:for instantaneous local mass flux, 393: 237: 197: 14: 1223:Journal of Spacecraft and Rockets 253:) in comparison to the effective 1667:. Pennsylvania State University. 1505:Whitmore, Stephen (2020-04-12). 223:{\displaystyle \Delta h/{h_{v}}} 97:as distance along the port, rho 1544:Journal of Propulsion and Power 1460:Journal of Propulsion and Power 1429:Journal of Propulsion and Power 1381:Clay, Reed McRae (2019-01-01). 1273:Journal of Propulsion and Power 1132:Journal of Propulsion and Power 700:for flux of oxidizer and fuel). 412: 363: 348: 330: 1: 1338:Propulsion and Power Research 1298:Tabor, Abigail (2017-04-18). 17:Hybrid rocket fuel regression 501:based on regression testing. 183:{\displaystyle u_{e}/u_{c}} 1706: 1663:McKnight, Brendan (2015). 1351:10.1016/j.jppr.2018.07.007 1685:Hybrid-propellant rockets 117:{\displaystyle \rho _{f}} 1524:10.3390/aerospace7040043 865:{\displaystyle \pi *D*l} 246:{\displaystyle \Delta h} 30:Because the quantity of 21:hybrid-propellant rocket 770:Regression enhancements 1387:(Thesis). p. 37. 954: 933: 884: 866: 748: 694: 674: 647: 627: 607: 606:{\displaystyle m=-0.2} 578: 552: 495: 475: 455: 426: 278: 247: 224: 184: 142: 118: 91: 71: 955: 934: 882: 867: 793:combustion efficiency 749: 695: 675: 673:{\displaystyle G_{o}} 648: 628: 608: 579: 577:{\displaystyle n=0.8} 553: 496: 476: 456: 427: 279: 277:{\displaystyle h_{v}} 248: 225: 185: 143: 119: 92: 72: 944: 923: 844: 704: 684: 657: 637: 617: 588: 562: 505: 485: 465: 445: 288: 261: 255:heat of vaporization 234: 194: 152: 141:{\displaystyle \mu } 132: 101: 81: 61: 1635:10.2514/6.2007-5352 1593:10.2514/6.2011-5909 1393:2019MsT.........37C 1235:2008JSpRo..45.1010E 1191:10.2514/6.2006-4504 910: 37:combustion chambers 950: 929: 908: 900:Regression testing 885: 862: 824:University of Utah 744: 690: 670: 643: 623: 603: 574: 548: 491: 471: 451: 422: 274: 243: 220: 180: 138: 114: 87: 67: 1644:978-1-62410-011-6 1602:978-1-60086-949-5 1200:978-1-62410-038-3 1110: 1109: 953:{\displaystyle n} 932:{\displaystyle a} 716: 693:{\displaystyle G} 646:{\displaystyle x} 626:{\displaystyle n} 517: 494:{\displaystyle m} 474:{\displaystyle n} 454:{\displaystyle a} 410: 388: 346: 326: 300: 90:{\displaystyle x} 70:{\displaystyle G} 1697: 1669: 1668: 1660: 1654: 1653: 1652: 1651: 1618: 1612: 1611: 1610: 1609: 1576: 1570: 1569: 1559: 1557:10.2514/1.B37037 1535: 1529: 1528: 1526: 1502: 1496: 1493: 1484: 1483: 1451: 1445: 1444: 1441:10.2514/1.B35615 1435:(6): 1727โ€“1738. 1420: 1414: 1408: 1397: 1396: 1378: 1372: 1371: 1353: 1329: 1323: 1320: 1314: 1313: 1311: 1310: 1295: 1289: 1288: 1264: 1255: 1254: 1229:(5): 1010โ€“1020. 1214: 1205: 1204: 1174: 1157: 1154: 1148: 1147: 1123: 959: 957: 956: 951: 938: 936: 935: 930: 911: 871: 869: 868: 863: 837:volume flow rate 803:Complex geometry 775:Liquifying fuels 753: 751: 750: 745: 743: 742: 737: 736: 735: 718: 717: 709: 699: 697: 696: 691: 679: 677: 676: 671: 669: 668: 652: 650: 649: 644: 632: 630: 629: 624: 612: 610: 609: 604: 583: 581: 580: 575: 557: 555: 554: 549: 547: 546: 537: 536: 531: 519: 518: 510: 500: 498: 497: 492: 480: 478: 477: 472: 460: 458: 457: 452: 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379: 373: 369: 356: 353: 343: 339: 336: 321: 317: 312: 309: 303: 297: 294: 269: 265: 256: 240: 214: 210: 204: 200: 175: 171: 166: 160: 156: 135: 128:of the fuel, 127: 109: 105: 84: 64: 56: 55:Lewis numbers 52: 43: 41: 38: 33: 28: 26: 22: 18: 1664: 1658: 1648:, retrieved 1626: 1616: 1606:, retrieved 1584: 1574: 1547: 1543: 1533: 1514: 1510: 1500: 1463: 1459: 1449: 1432: 1428: 1418: 1383: 1376: 1341: 1337: 1327: 1318: 1307:. 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Index

hybrid-propellant rocket
surface area
fuel
combustion chambers
Prandtl
Lewis numbers
density
heat of vaporization
annular port
power function
Reynolds number
AFRL
combustion efficiency
nozzle
helical
University of Utah
volume flow rate
CAD

"Development of Scalable Space-Time Averaged Regression Rate Expressions for Hybrid Rockets"
doi
10.2514/1.19226






"Hybrid Rocket Fuel Regression Rate Data and Modeling"
doi

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