Barnhardt, Michael D.

Borner, Arnaud

Ferguson, Joseph C.

Mansour, Nagi N.

Panerai, Francesco

Wright, Michael

NASA Technical Reports Server

X-ray	micro-tomography	for	
advanced	material	technologies:
a	NASA	perspective	
Space	Tech	Expo,	2017
Pasadena,	CA
Joseph	C.	Ferguson	1
Francesco	Panerai 2
Arnaud	Borner 1
Nagi N.	Mansour	3
Michael	Barnhardt 3
Michael	Wright	3
1.	STC	at	NASA	Ames	Research	Center
2.	AMA	at	NASA	Ames	Research	Center
3.	NASA	Ames	Research	Center
https://ntrs.nasa.gov/search.jsp?R=20170011262 2019-08-31T01:23:07+00:00Z
Thermal	Protection	Systems
NASA TM 101055, 1989
=+
Carbon	fibers Resin PICA
Ablative Thermal Protection Systems
Stackpoole et al., AIAA 2008-1202 www.spacex.com
Stardust	Capsule Dragon	V1	&	V2 Mars	Science	Laboratory
Material Design and Modeling
Virgin	
material
Pyrolysis	zone
Ablation	zone
≈	400	K
≈	1200	K
≈	1400	K
Coking	zone
≈	3000	K
Boundary	 layer
Shock	 layer
≈	6000	K
Bondline
C6H6 + H2O
C6 + 3 H2
3 C2H2
O
C(s) + Oà CO
coking
Radiation
He
at
	tr
an
sf
er
Phenolic
polymer
H2   +
Shear
stresses
Pl
as
m
a
M
at
er
ia
l
Lachaud and Mansour, JTHT 2013
Lawson et. al. 2010
X-ray micro-tomography
• Advanced	Light	Source	(ALS)	at	the	Lawrence	
Berkeley	Natl.	Laboratory
• Synchrotron	electron	accelerator	used	to	
produce	14Kev	X-rays
• Used	for	many	research	areas,	including	
optics,	chemical	reaction	dynamics,	biological	
imaging,	and	X-ray	micro-tomography.
Berkeley	Labs,	Flickr
http://www2.lbl.gov/MicroWorlds/ALSTool
X-ray micro-tomography
Collect	X-ray	images	of	the	sample	as	you	rotate	
it	through	180°
Use	this	series	of	images	to	
“reconstruct”	the	3D	object
Multiple	anglesPenetrating	power
6
Courtesy of D. Parkinson (ALS)
X-ray micro-tomography
X – Ray Projections
Reconstruction 
Software
Reconstructed Image Stack

Determine	effective	material	
properties	and	response
Material	design	from	
micro-structure
• Determination	of	material	
properties	and	response	based	on	
micro-structure
• Porosity,	specific	surface	area,	
thermal	conductivity,	permeability,	
tortuosity
• Generation	of	artificial	micro-
structures
• Goal	of	fine-tuning	material	
characteristics	to	meet	design	
requirements
Characterize	material	micro-
structure
• Use	of	x-ray	micro-tomography	to	
characterize	material	micro-
structure
• Determination	of	physical	
properties	such	as	pore	size,	fiber	
diameter
Porous Materials Analysis (PuMA) Technical	Specifications
• Written	in	C++
• GUI	built	on	QT
• Visualization	module	based	on	
OpenGL
• Parallelized	using	OpenMP for	
shared	memory	systems
Effective Material Properties
Porosity
Specific	Surface	Area
• Based	on	the	Marching	
Cubes	algorithm	
• Overall	surface	area	
computed	as	a	sum	of	
individual	triangle	areas
• Based	on	the	grayscale
threshold
• Sum	of	all	void	voxels	over	
the	total	volume
Effective Thermal Conducitivity
• Computes	effective	thermal	conductivity	using	a	
finite	difference	method	[Weigmann,	2006]
• BicGStab iterative	method	and	FFTW	used	to	
solve	linear	system	of	equations	[Sleijpen,	1993]
• Parallelized	based	on	OpenMP
• Verified	against	complex	analytical	solutions
12-ply,	dry
12-ply,	infused	
(fully	dense)
Diffusivity / Tortuoosity
Continuum
Transitional/Rarified
• Solves	for	effective	
diffusivity	using	a	finite	
difference	method
• Solves	effective	diffusivity	
through	a	random	walk	
method	
• Knudsen	number	is	varied	
by	changing	molecular	
mean	free	path
Permeability using DSMC
Borner et al., Int J Heat Mass Transfer (2016), in press
a) b) 
80 µm  µm 120 0 60 
x
y
z
• Direct	Simulation	Monte	Carlo	(DSMC):	probabilistic	
simulation	method	to	solve	the	Boltzmann	equation	
for	finite	Kn
• Simulates	fluid	flow	using	a	particle-based	approach	
with	particle-particle	and	particle-surface	interactions
• Ability	to	solve	chemically	reacting	flows	at	high	
Knudsen	numbers	(where	typical	CFD	is	no	longer	
valid)
• DSMC	code:	SPARTA	(Sandia)

Micro-Scale Oxidation Simulations
16
• Particle-based oxidation method
• Diffusion simulated through random walks
• Collision detection with linear interpolation method
• Sticking probability method for material recession
• Verified against analytical solutions for single fiber
Ferguson et al., Carbon 96 (2016), 57-65

Micro-Scale Oxidation Simulations
Ferguson et al., Carbon 96 
(2016), 57-65
Material Generation
Random	Fiber	Structures Packed	Sphere	Beds Periodic	Foams
Conclusion and Outlook
• Micro-tomography	and	simulations
• Help	us	developing	TPS	response	modes
• Enable	predictive	materials	modeling
• Support	cheaper	and	faster	material	development
• Impact	not	only	Entry	Descent	Landing,	but	also	other	NASA’s	grand	challenges:
600	µm
10	m
12-ply,	dry12-ply,	infused	
(fully	dense)
Acknowledgements
• This work was supported by the Entry System Modeling project (M.J. Wright project manager) of the 
NASA Game Changing Development program.
• T. Sandstrom, C. Henze, D. Ellsworth, and B. Nelson for useful discussions during the development of 
PuMA and the parallelization of the oxidation model. 
• A.A. MacDowell and D.Y. Parkinson are acknowledged for their assistance with tomography 
measurements. 
• The Advanced Light Source is supported by the Director, Office of Science, Office of Basic Energy 
Sciences, of the U.S. Department of Energy under Contract No. DE-AC02-05CH11231.


X-Ray Micro-Tomography for Advanced Material Technologies: A NASA Perspective

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