Presentation at ,28th International Symposium on SpaceTechnology and Science, June 2011. American Astronautical Society Awardを受賞！

1. 1
The 28th International Symposium on Space Technology and Science
Chemical Propulsion 2011-a-35s
Multi-Stage Hybrid Rocket Design for
Micro Satellites
Micro-Satellites Launch using Genetic Algorithm
Yosuke Kitagawa
Tokyo Metropolitan University

2. 2
Contents
1. Background
2. Objectives
3. Design methods
g
4. Design problem
5.
5 Results
6. Conclusions

3. 3
Background
 Advantage of hybrid rocket engine (HRE)
・ Safety ・ Cost ・ Environment
L
Launch Vehicle (LV) development with HRE
h V hi l d l ih
• HRE is employed in plan of private space travel using SpaceShipTwo
by Virgin Galactic in America.
America
• Copenhagen Suborbitals develops small manned spacecraft using
HRE, TychoBrahe
SpaceShipTwo
S Shi T Tycho Brahe
Tycho Brahe
www.scaled.com www.copenhagensuborbitals.com

4. 4
Background
 Disadvantage of HRE
• Regression rate of solid fuel is slow.
• LOX tank is required in the engine construction.
construction
• There is severe trade-off between flight altitude and gross weight.
 Thrust and weight are affected by
Pressurized tank
・Pressure
Nozzle
LOX tank Chamber
・Expansion ratio
Expansion
・Mass flow of oxidizer ・Pressure
・Pressure Solid fuel
・Length
・Port radius
It is helpful for design of LV with HRE to apply multi disciplinary
multi-disciplinary
optimization (MDO) and knowledge discovery techniques.

5. 5
Objectives
MDO of three-stage LV with HRE for delivering
micro-satellites
micro satellites using genetic algorithm (GA)
• Evaluation method of multi-stage LV with HRE
multi stage
• Exploration of global solutions by genetic algorithm
• Design knowledge discovery by data mining

6. 6
Flowchart of Evaluation
Grain sizing INPUT
Grain length Oxidizer mass flow
Port radius Initial O/F
Fuel mass flow Coefficient of regression rate
O/F Initial oxidizer mass flux
O/F Combustion time
Initial pressure of chamber
Pressure and NASA CEA
NASA-CEA Initial pressure of pressurized tank
p p
velocity at Isp Expansion ratio of nozzle
nozzle exit C*
Thrust
Th t Mass
M
Thrust Gross mass
Trajectory
Kosugi, K., et al. "Multidisciplinary and Multi-objective Design
g, , p y j g
OUTPUT Exploration Methodology for Conceptual Design of a Hybrid Rocket,"
Infotech@aerospace, AIAA 2011-1634, 2011.
Flight path, Rocket length and diameter etc.

7. 7
Grain Configuration
 Initial radius of grain port L fuel
moxii

rport 0 
Go 0 r (t )

m fuel

moxi

rport (t )
(
Design
D i variables
i bl
 Grain length Grain
moxi

m fuel 0  

O F 0  moxi : Oxidizer mass flow

m fuel : Fuel mass flow
f
m fuel 0
 rport : Radius of grain port
L fuel 
2rp 0  r 0   fuel
port
 f r : Regression rate

Go : Oxidizer mass flux
r 0  a  Gon 0
 L fuel : Grain length
Design variables  fuel : Grain density

8. 8
O/F and Chamber Pressure Calculation
L fuel
 Definition of O/F
O moxi

(t )  r (t )

F m fuel (t )
 m fuel

moxi

moxii
 rport (t )
(

2rport (t ) L fuel  fuel r (t )
 Grain
n
 moxi 

r t   a  G t   a 
 n  
 rport t  
o  2 
p
Pch Chamber pressure
：
m prop Propellant mass flow
p ： p
 Ch b pressure
Chamber 
C：Characteristic velocity
m prop (t )  C  (t )  C 
  C： Efficiency of characteristic velocity
Pch (t ) 

t)
Ath Ath Area of nozzle throat
：

9. 9
Mass Estimation
 Structural mass Design variables
・Chamber M ch  PchVch 17 .3  10 4 same as motor case as solid
・Pressurized tank M pre  Ppre V pre 17 .3  10 4 rocket, M V
rocket M-V (CFRP)
・Oxidizer tank M res  PresV res 4 .4  10 4 CFRP with aluminum liner
2 1
 M prop   
3 4
・Nozzle* M noz  125 
   
 Empirical expression
 5400  4
Structure* M st  1 . 3 M ch  M res  M pre  M noz   M He
 Propellant mass Design variables
tburn
M prop  M oxi  M fuel  moxi  tburn  
 m fuel (t )dt

0
 Gross mass
M tot  M prop  M st  M pay M pay : Payload mass
* Ronald Humble, “Space Propulsion Analysis and Design”

10. 10
Trajectory Evaluation
 Thrust
T t    CF  C* [ m prop u e  ( Pe  Pa )  Ae ]

•  C * ：thrust loss by incomplete combustion
•  CF ：thrust loss by friction at nozzle wall
 Drag 1.0
During combustion
Estimation using flight data of solid rocket, S-520 0.8
After combustion
CD,S-520
• Friction drag coefficient 0.6
0.455 1 0.4
C D f , Design  
2.58

log10 Re  1  0.144M 2 0.655  0.2
02
0.0
• Pressure drag coefficient
S wet , S 520 0.0 2.0 4.0 6.0 8.0 10.0
C D p , S 520  C D , S 520  C D f , S 520  Mach number
S ref , S 520
• Drag of designed rocket
S wet Rocket wet area
：
1

D  V 2 S ref , DesignC D p , S 520  S wet , DesignC D f , Design
2
S ref Rocket reference area
：
The effect of the longitude and diameter can be separately evaluated.

11. 11
Optimization Methods
Multi-objective Genetic Algorithm (MOGA)
 Searching global non-dominated solutions
hi l b l d i d l i
based on global explorations
 E l i and selection (P
Evaluation d l i (Pareto ranking method)
ki h d)
• When a solution #xi is dominated by #ni solutions,
rank(xi)=1+ ni.
• Penalty method
When a solution xi don’t meet constraints,
rank(xi)= rank(xi)+p (p>0). Optimum direction

12. 12
Optimization Method
 Crossover（BLX-α）
• Children are generated based on interpolation
or extrapolation based on selected two parents.
• In BLX-α, children are generated between the
range which is extended equally on both sides
determined by a parameter, α.
Children2 Children1
 Mutation x1 x2 x3 x4 x5
• Mutation generate children that cannot be
Parent
generated from the present population.
• Children are generated by a uniform
Child
random number.

13. 13
Data Mining Method
Parallel Coordinate Plot (PCP)
• One of statistical visualization techniques from high dimensional
high-dimensional
data into two dimensional graph.
• Normalized design variables and objective functions are set
parallel in the normalized axis.
• Global trends of design variables can be visualized using PCP.
g g
1.0
0.8
0.6
0.4
0.2
0.0
dv1
d 1 dv2
d 2 dv3
d 3 dv4
d 4 dv5
d 5 H W L/D

14. 14
Design Problem
 Design target: Design of three-stage rocket which can deliver micro-satellites
to the Sun-synchronous orbit (SSO) (perigee is 250km, apogee is 800km)
 Obj ti f
Objective functions
ti
• maximize Payload mass/Gross mass (Mpay/Mtot)
• minimize Gross mass (Mttott)
 Constraints
• After combustion of third stage,
 Height > 250km
 Angular momentum > 52413.5km2/s
 -0.5deg. < Fli ht path angle < 0.5deg.
0 5d Flight th l 0 5d
• Rocket aspect ratio < 20
• Radius of nozzle exit < Radius of rocket
• Area of grain port > 2・(Area of nozzle throat)
 Combustion type
• Swirling oxidizer type engine
• Oxidizer：LOX, Fuel：WAX (FT-0070)

15. 15
Design Problem (design space)
1st stage 2nd stage 3rd stage
Design variables
Min Max Min Max Min Max
Oxidizer
O idi mass flow [k / ]
fl [kg/s] moxi,1st moxi,1st moxi,2nd moxi,2nd
50 150
(moxi) ×1/10 ×1/3 ×1/10 ×1/3
Initial O/F [-] 2 3 2 3 2 3
Coefficient of regression rate
6.224 15.61 6.224 15.61 6.224 15.61
equation, a* [×10-3]
Initial oxidizer mass flux
200 800 200 800 100 800
[kg/m2s]
Combustion time [s] (tburn) 40 80 tburn,1st+0 tburn,1st+50 tburn,2nd+0 tburn,2nd+50
Initial pressure of
0.5 5.0 0.5 5.0 0.5 5.0
chamber [MPa]
Initial pressure of
10 47 10 47 10 47
pressurized tank [MPa]
Expansion ratio of nozzle [-] 2 15 15 60 50 100
Coasting time [s] 0 300
The range of the a for each stage is empirically decided*. ( r t   a  Gon t  )

* Hikone,S., et al, “Regression Rate Characteristics and Combustion Mechanism of Some Hybrid Rocket Fuels ,”Asian Joint Conference on
Propulsion and Power 2010.

16. 16
Results

17. 17
MOGA Results
Optimum direction
O ti di ti
Epsilon
rocket
Mpay/Mto [%]
Mpay [kg]
ot
[
Mtot [ton] Mtot [ton]
• There is trade-off between Mtot and Mpay/Mtot.
• Maximum Mpay/Mtot is 1.30% (Mpay is 232kg, Mtot is 17.8ton).
• Maximum Mpay/Mtot of solid rocket, Epsilon* is about 1.3%.
⇒ LV with HRE considered here have enough capability compared
with the solid rocket.
ih h lid k
• Mpay is approximately proportional to Mtot (Mtot=0.0619Mpay+3.427).
⇒When Mpay increases by 1kg, Mtot must increase by 61.9kg.
*Epsilon rocket: Next generation solid rocket developed by JAXA and IA.

18. 18
PCP Visualization
 Non-dominated solutions
Picking up solutions (150kg payload)

19. 19
PCP Visualization (to deliver 150kg payload)
 Effect of combustion process a：Coefficient of regression
rate equation
Go：Oxidizer mass flux
1：1st stage
2：2nd stage
3：3rd stage
Max Min Average Required regression rate
a1 [×10-3]
[ 0 1.44
. 1.34
.3 1.37
.37
14.6mm/s
14 6 /
Go1 [kg/m2s]
r t   a  Gon t 
488 357 428

a2 [×10-3] 1.16 1.13 1.09
9.1mm/s
9 1mm/s
Go2 [kg/m2s] 211 208 209
a3 [×10-3] 1.34 1.29 1.31
8.8mm/s
Go3
G 3 [k / 2s]
[kg/m ] 141 126 130

20. 20
PCP Visualization (to deliver 150kg payload)
 Effect of internal pressure of chamber/ pressurized tanks Pc：Chamber pressure
Pp：Pressure of pressurized
tank
Max Min Average Structural mass/Gross mass
Pc1 [MPa]
[ ] 2.90
.90 2.27
. 7 2.63
.63
20.7%
20 7%
Pp1 [MPa] 43.5 37.9 41.0
Pressure：Large
Pc2 [MPa] 1.00 0.98 0.99 ⇒Thickness： Increase
11.9%
11 9% ⇒ Structural mass：Increase
Pp2 [MPa] 21.8 19.6 21.3
Pc3 [MPa] 0.80 0.72 0.75
14.5%
Pp3 [MPa]
P 3 [MP ] 12.8
12 8 10.9
10 9 11.9
11 9

21. 21
Selected Design from Non-dominated Solutions
Non-
Design variables 1st 2nd 3rd
Oxidizer mass flow [kg/s] 100.3 28.3 4.3
O/F [-] 2.47 2.88 2.87
Coefficient of regression rate [×10-3] 1.34 1.16 1.32
I iti l oxidizer mass flux [k / 2s]
Initial idi fl [kg/m ] 445 209 128
Combustion time [s] 43.0 90.2 96.0
Initial pressure of chamber [MPa] 2.90
2 90 0.98
0 98 0.73
0 73
Initial pressure of pressurized tank [MPa] 43.5 21.7 12.8
Nozzle expansion ratio [-]
p [] 6.3 22.1 72.4
Mpay/Mtot [%]
Mtot [ton]

22. 22
Selected Design from Non-dominated Solutions
Non-
 Engine parameter of selected rocket
1st t
1 t stage 2nd t
2 d stage 3rd t
3 d stage
Thrust
(after ignition ⇒ [kN] 342 ⇒ 415 95 2 ⇒ 123
95.2 17 8 ⇒ 20 1
17.8 20.1
after combustion)
Isp [s] 248 ⇒ 284 256 ⇒ 316 334 ⇒ 344
Regression rate [mm/s] 14.5 ⇒ 7.08 9.33 ⇒ 3.70 8.75 ⇒ 2.64
Length of grain [m] 2.18 1.06 0.35
Inside diameter of grain [m] 0.54 0.42 0.21
Outside diameter of grain [m] 1.34 1.35 0.96
To realize space transportation using HRE with existent fuel,
engine of thrust 400kN must be developed.
developed

23. 23
Selected Design from Non-dominated Solutions
Non-
 Selected rocket size
Length of rocket [m] 20.8
Diameter of rocket [m] 1.46
1 46
Aspect ratio of rocket [-] 14.3
Gross mass [ton] 13.0
Payload mass [kg] 152
Payload mass/Gross mass [%] 1.17
1st stage 2nd stage 3rd stage
Length [m] 8.22 6.57 6.06
Diameter [m] 1.45 1.46 1.07
Gross mass [ton] 8.07 4.09 0.70
Structural mass [ton] 1.78 0.49 0.10
Structural mass ratio [%] 22.1 11.9 14.5
20.8
8.22 6.57 6.06
1.35 1.36 0.97
1.46
1.21 2.18 3.21 1.61 2.29 1.06 2.11 1.11 2.06 0.35 0.99 0.64 2.02

24. 24
Flight History
Start of combustion
in 2nd stage
Start of coasting
Start f
St t of combustion
b ti
in 3rd stage
• Maximum acceleration is 9G less than 10G.
• Load to satellites is lower than that of solid
rocket.
(M-V ： About 12G in 3rd stage)

25. 25
Conclusions
MDO of LV using HRE for space transportation
• Development of performance evaluation method
• The design of three-stage rocket for delivering micro-satellites
to SSO
 maximize
i i Payload
P l d mass/Gross mass
/G
 minimize Gross mass
• Exploration of global non-dominated solutions using MOGA
non dominated
 There is trade-off between Mtot and Mpay/Mtot.
 Maximum Mpay/Mtot is 1.30%.
• Design knowledge discovery using PCP
 Maximum regression rate should be about 15mm/s in first stage.
 In first stage, pressure of chamber, LOX tank and pressurized tank
should be large.
 In second stage and third stage press re of chamber LOX tank and
stage, pressure chamber,
pressurized tank should be low.

26. 26
Acknowledgement
This presentation was supported by hybrid rocket research
working group (HRrWG), ISAS/JAXA.
gg p( ),
I thank members of HRrWG in ISAS/JAXA for giving their
experimental data and their valuable advices.
p

27. 27
Thank you for your attention.