Abstract

We performed a characterization of the shock wave loading on the response of the specimen representing a simplified head model. A polycarbonate cylinder (2-in. outer diameter, wall thickness: 0.06 or 0.12 in.) was filled with two fluids: pure de-ionized water and 40% glycerol in water, which differ only slightly in their constitutive material properties. These two fluids were selected to represent the cerebrospinal fluid and cerebral blood, using their high strain rate viscosity as a primary selection criterion. The model specimen was exposed to a single shock wave with two nominal intensities: 70 and 130kPa overpressure. The response of the model was measured using three strain gauges and three pressure sensors, one mounted on the front face of the cylinder and two embedded in the cylinder to measure the pressure inside of the fluid. We noted several discriminant characteristics in the collected data, which indicate that the type of fluid is strongly influencing the response. The vibrations of the cylinder walls are strongly correlated with the fluid kind. The similarity analysis via the Pearson coefficient indicated that the pressure waveforms in the fluid are only moderately correlated, and these results were further corroborated by Euclidean distance analysis. Continuous wavelet transform of pressure waveforms revealed that the frequency response is strongly correlated with the properties of the fluid. The observed differences in strain and pressure modalities stem from relatively small differences in the properties of the fluids used in this study.

References

1.
Gupta
,
R. K.
, and
Przekwas
,
A.
,
2013
, “
Mathematical Models of Blast-Induced TBI: Current Status, Challenges, and Prospects
,”
Front. Neurol.
,
4
, p.
59
.10.3389/fneur.2013.00059
2.
Warden
,
D.
,
2006
, “
Military TBI During the Iraq and Afghanistan Wars
,”
J. Head Trauma Rehabil.
,
21
(
5
), pp.
398
402
.10.1097/00001199-200609000-00004
3.
Leonardi
,
A. D.
,
Bir
,
C. A.
,
Ritzel
,
D. V.
, and
VandeVord
,
P. J.
,
2011
, “
Intracranial Pressure Increases During Exposure to a Shock Wave
,”
J Neurotrauma
,
28
(
1
), pp.
85
94
. Epub 2010/11/26. PubMed PMID: 21091267.10.1089/neu.2010.1324
4.
Bolander
,
R.
,
Mathie
,
B.
,
Bir
,
C.
,
Ritzel
,
D.
, and
VandeVord
,
P.
,
2011
, “
Skull Flexure as a Contributing Factor in the Mechanism of Injury in the Rat When Exposed to a Shock Wave
,”
Ann. Biomed. Eng.
,
39
(
10
), pp.
2550
2559
.10.1007/s10439-011-0343-0
5.
Skotak
,
M.
,
Wang
,
F.
,
Alai
,
A.
,
Holmberg
,
A.
,
Harris
,
S.
,
Switzer
,
R. C.
, and
Chandra
,
N.
,.
2013
, “
Rat Injury Model Under Controlled Field-Relevant Primary Blast Conditions: Acute Response to a Wide Range of Peak Overpressures
,”
J. Neurotrauma
,
30
(
13
), pp.
1147
1160
.10.1089/neu.2012.2652
6.
Zhu
,
F.
,
Wagner
,
C.
,
Dal Cengio Leonardi
,
A.
,
Jin
,
X.
,
VandeVord
,
P.
,
Chou
,
C.
,
Yang
,
K. H.
, and
King
,
A. I.
,
2012
, “
Using a Gel/Plastic Surrogate to Study the Biomechanical Response of the Head Under Air Shock Loading: A Combined Experimental and Numerical Investigation
,”
Biomech. Model. Mechanobiol.
,
11
(
3–4
), pp.
341
353
.10.1007/s10237-011-0314-2
7.
Hua
,
Y.
,
Kumar Akula
,
P.
,
Gu
,
L.
,
Berg
,
J.
, and
Nelson
,
C. A.
,
2014
, “
Experimental and Numerical Investigation of the Mechanism of Blast Wave Transmission Through a Surrogate Head
,”
ASME J. Comput. Nonlinear Dynam.
, 9(3), p.
031010
.10.1115/1.4026156
8.
Mediavilla Varas
,
J.
,
Philippens
,
M.
,
Meijer
,
S. R.
,
van den Berg
,
A. C.
,
Sibma
,
P. C.
,
van Bree
,
J. L. M. J.
, and
de Vries
,
D. V. W. M.
,.
2011
, “
Physics of IED Blast Shock Tube Simulations for mTBI Research
,”
Front. Neurol.
,
2
(
58
), pp.
1
–14.10.3389/fneur.2011.00058
9.
Ganpule
,
S.
,
Salzar
,
R.
,
Perry
,
B.
, and
Chandra
,
N.
,
2016
, “
Role of Helmets in Blast Mitigation: Insights From Experiments on PMHS Surrogate
,”
Int. J. Exp. Comput. Biomech.
,
4
(
1
), pp.
13
31
.10.1504/IJECB.2016.081745
10.
Tan
,
X. G.
,
Przekwas
,
A. J.
, and
Long
,
J. B.
,
2013
, “
Validations of Virtual Animal Model for Investigation of Shock/Blast Wave TBI
,”
ASME Paper No. IMECE2013-64587
.10.1115/IMECE2013-64587
11.
Shridharani
,
J. K.
,
Wood
,
G. W.
,
Panzer
,
M. B.
,
Capehart
,
B. P.
,
Nyein
,
M. K.
,
Radovitzky
,
R. A.
, and Bass, C. R. D.,
2012
, “
Porcine Head Response to Blast
,”
Front. Neurol.
,
3
(
70
), pp.
1
12
.10.3389/fneur.2012.00070
12.
Zhu
,
F.
,
Skelton
,
P.
,
Chou
,
C. C.
,
Mao
,
H.
,
Yang
,
K. H.
, and
King
,
A. I.
,
2013
, “
Biomechanical Responses of a Pig Head Under Blast Loading: A Computational Simulation
,”
Int. J. Numer. Methods Biomed. Eng.
,
29
(
3
), pp.
392
407
.10.1002/cnm.2518
13.
Moss
,
W. C.
,
King
,
M. J.
, and
Blackman
,
E. G.
,
2009
, “
Skull Flexure From Blast Waves: A Mechanism for Brain Injury With Implications for Helmet Design
,”
Phys. Rev. Lett.
,
103
(
10
), p.
108702
.10.1103/PhysRevLett.103.108702
14.
Tan
,
X. G.
,
Przekwas
,
A. J.
, and
Gupta
,
R. K.
,
2017
, “
Computational Modeling of Blast Wave Interaction With a Human Body and Assessment of Traumatic Brain Injury
,”
Shock Waves
,
27
(
6
), pp.
889
904
.10.1007/s00193-017-0740-x
15.
Goeller
,
J.
,
Wardlaw
,
A.
,
Treichler
,
D.
,
O'Bruba
,
J.
, and
Weiss
,
G.
,
2012
, “
Investigation of Cavitation as a Possible Damage Mechanism in Blast-Induced Traumatic Brain Injury
,”
J. Neurotrauma
,
29
(
10
), pp.
1970
1981
.10.1089/neu.2011.2224
16.
Panzer
,
M. B.
,
Myers
,
B. S.
,
Capehart
,
B. P.
, and
Bass
,
C. R.
,
2012
, “
Development of a Finite Element Model for Blast Brain Injury and the Effects of CSF Cavitation
,”
Ann. Biomed. Eng.
,
40
(
7
), pp.
1530
1544
.10.1007/s10439-012-0519-2
17.
Zhang
,
L.
,
Makwana
,
R.
, and
Sharma
,
S.
,
2013
, “
Brain Response to Primary Blast Wave Using Validated Finite Element Models of Human Head and Advanced Combat Helmet
,”
Front. Neurol.
,
4
(
80
), pp.
1
12
.10.3389/fneur.2013.00088
18.
Petr
,
K.
,
Bondi
,
M. W.
,
Ward
,
S. R.
, and
Frank
,
L. R.
,
2012
, “
On Sources of Error in Finite Element Simulations of Blast Effects in the Human Brain
,”
ASME J. Comput. Nonlinear Dyn.
,
7
(
3
), p.
031008
.10.1115/1.4006143
19.
Singh
,
D.
,
Cronin
,
D. S.
, and
Haladuick
,
T. N.
,
2014
, “
Head and Brain Response to Blast Using Sagittal and Transverse Finite Element Models
,”
Int. J. Numer. Methods Biomed. Eng.
,
30
(
4
), pp.
470
489
.10.1002/cnm.2612
20.
Meaney
,
D. F.
,
Morrison
,
B.
, and
Dale Bass
,
C.
,
2014
, “
The Mechanics of Traumatic Brain Injury: A Review of What We Know and What We Need to Know for Reducing Its Societal Burden
,”
ASME J. Biomech. Eng.
, 136(2), p.
021008
.10.1115/1.4026364
21.
Townsend
,
M. T.
,
Alay
,
E.
,
Skotak
,
M.
, and
Chandra
,
N.
,
2019
, “
Effect of Tissue Material Properties in Blast Loading: Coupled Experimentation and Finite Element Simulation
,”
Ann. Biomed. Eng.
,
47
(
9
), pp.
2019
2032
.10.1007/s10439-018-02178-w
22.
Zhu
,
F.
,
Mao
,
H.
,
Leonardi
,
A. D. C.
,
Wagner
,
C.
,
Chou
,
C. C.
, and
Jin
,
X.
,
2010
, “
Development of an FE Model of the Rat Head Subjected to Air Shock Loading
,”
SAE Paper No. 2010-22-0011
.10.4271/2010-22-0011
23.
Elkin
,
B. S.
,
Ilankovan
,
A.
, and
Morrison
,
B.
,
2010
, “
Age-Dependent Regional Mechanical Properties of the Rat Hippocampus and Cortex
,”
ASME J. Biomech. Eng.
,
132
(
1
), p.
011010
.10.1115/1.4000164
24.
Mendis
,
K.
,
Stalnaker
,
R.
, and
Advani
,
S.
,
1995
, “
A Constitutive Relationship for Large Deformation Finite Element Modeling of Brain Tissue
,”
ASME J. Biomech. Eng.
,
117
(
3
), pp.
279
285
.10.1115/1.2794182
25.
Chandra
,
N.
,
Ganpule
,
S.
,
Kleinschmit
,
N. N.
,
Feng
,
R.
,
Holmberg
,
A. D.
,
Sundaramurthy
,
A.
,
Selvan
,
V.
, and
Alai
,
A.
,
2012
, “
Evolution of Blast Wave Profiles in Simulated Air Blasts: Experiment and Computational Modeling
,”
Shock Waves
,
22
(
5
), pp.
403
415
.10.1007/s00193-012-0399-2
26.
Ganpule
,
S.
,
Alai
,
A.
,
Plougonven
,
E.
, and
Chandra
,
N.
,
2013
, “
Mechanics of Blast Loading on the Head Models in the Study of Traumatic Brain Injury Using Experimental and Computational Approaches
,”
Biomech. Model. Mechanobiol.
,
12
(
3
), pp.
511
531
.10.1007/s10237-012-0421-8
27.
Kuriakose
,
M.
,
Skotak
,
M.
,
Misistia
,
A.
,
Kahali
,
S.
,
Sundaramurthy
,
A.
, and
Chandra
,
N.
,
2016
, “
Tailoring the Blast Exposure Conditions in the Shock Tube for Generating Pure, Primary Shock Waves: The End Plate Facilitates Elimination of Secondary Loading of the Specimen
,”
PLoS One
,
11
(
9
), p.
e0161597
.10.1371/journal.pone.0161597
28.
Sundaramurthy
,
A.
,
Alai
,
A.
,
Ganpule
,
S.
,
Holmberg
,
A.
,
Plougonven
,
E.
, and
Chandra
,
N.
,
2012
, “
Blast-Induced Biomechanical Loading of the Rat: An Experimental and Anatomically Accurate Computational Blast Injury Model
,”
J. Neurotrauma
,
29
(
13
), pp.
2352
2364
.10.1089/neu.2012.2413
29.
Selvan
,
V.
,
Ganpule
,
S.
,
Kleinschmit
,
N.
, and
Chandra
,
N.
,
2013
, “
Blast Wave Loading Pathways in Heterogeneous Material Systems–Experimental and Numerical Approaches
,”
ASME J. Biomech. Eng.
,
135
(
6
), pp.
061002
061014
.10.1115/1.4024132
30.
Skotak
,
M.
,
Alay
,
E.
, and
Chandra
,
N.
,
2018
, “
On the Accurate Determination of Shock Wave Time-Pressure Profile in the Experimental Models of Blast-Induced Neurotrauma
,”
Front. Neurol.
,
9
(
52
), pp.
1
11
.10.3389/fneur.2018.00052
31.
Palaniappan
,
L.
, and
Velusamy
,
V.
,
2004
, “
Ultrasonic Study of Human Cerebrospinal Fluid
,”
Indian J. Pure Appl. Phys.
, 42(8), pp.
591
594
.https://www.researchgate.net/publication/277146081_Ultrasonic_study_of_human_cerebrospinal_fluid
32.
Baumgartner
,
R. W.
,
2006
,
Handbook on Neurovascular Ultrasound
,
Karger Medical and Scientific Publishers
,
Zürich, Switzerland
. 10.1159/isbn.978-3-318-01284-2
33.
Kim
,
M.-S.
,
Kim
,
J.-Y.
,
Noh
,
S.-C.
, and
Choi
,
H.-H.
,
2017
, “
Thermal Characteristics of Non-Biological Vessel Phantoms for Treatment of Varicose Veins Using High-Intensity Focused Ultrasound
,”
PloS One
,
12
(
4
), p.
e0174922
.10.1371/journal.pone.0174922
34.
Miner
,
C. S.
, and
Dalton
,
N. N.
,
1967
, “
Physical Properties of Glycerine and Its Solutions
,”
Hydrocarbon Process.
, pp.
1
7
.http://www.aciscience.org/docs/physical_properties_of_glycerine_and_its_solutions.pdf
35.
Pichardo
,
S.
,
Sin
,
V. W.
, and
Hynynen
,
K.
,
2011
, “
Multi-Frequency Characterization of the Speed of Sound and Attenuation Coefficient for Longitudinal Transmission of Freshly Excised Human Skulls
,”
Phys. Med. Biol.
,
56
(
1
), pp.
219
250
.10.1088/0031-9155/56/1/014
36.
Segur
,
J. B.
, and
Oberstar
,
H. E.
,
1951
, “
Viscosity of Glycerol and Its Aqueous Solutions
,”
Ind. Eng. Chem.
,
43
(
9
), pp.
2117
2120
.10.1021/ie50501a040
37.
Windberger
,
U.
,
Bartholovitsch
,
A.
,
Plasenzotti
,
R.
,
Korak
,
K.
, and
Heinze
,
G.
,
2003
, “
Whole Blood Viscosity, Plasma Viscosity and Erythrocyte Aggregation in Nine Mammalian Species: Reference Values and Comparison of Data
,”
Exp. Physiol.
,
88
(
3
), pp.
431
440
.10.1113/eph8802496
38.
Valant
,
A. Z.
,
Žiberna
,
L.
,
Papaharilaou
,
Y.
,
Anayiotos
,
A.
, and
Georgiou
,
G. C.
,
2011
, “
The Influence of Temperature on Rheological Properties of Blood Mixtures With Different Volume Expanders—Implications in Numerical Arterial Hemodynamics Simulations
,”
Rheol. Acta
,
50
(
4
), pp.
389
402
.10.1007/s00397-010-0518-x
39.
Rosebrock
,
A.
,
2014
, “
How-To: 3 Ways to Compare Histograms Using OpenCV and Python
,” PyImageSearch, accessed Apr. 25, 2019, https://www.pyimagesearch.com/2014/07/14/3-ways-compare-histograms-using-opencv- python/
40.
Rosebrock
,
A.
,
2014
, “
How-To: Python Compare Two Images
,” PyImageSearch, accessed Apr. 25, 2019, https://www.pyimagesearch.com/2014/09/15/python-compare-two-images/
41.
Feng
,
K.
,
Zhang
,
L.
,
Jin
,
X.
,
Chen
,
C.
,
Kallakuri
,
S.
,
Saif
,
T.
,
Cavanaugh
,
J.
, and
King
,
A.
,.
2016
, “
Biomechanical Responses of the Brain in Swine Subject to Free-Field Blasts
,”
Front Neurol.
,
7
(
179
), pp.
1
–12.10.3389/fneur.2016.00179
42.
Skotak
,
M.
,
Alay
,
E.
,
Zheng
,
J. Q.
,
Halls
,
V.
, and
Chandra
,
N.
,
2018
, “
Effective Testing of Personal Protective Equipment in Blast Loading Conditions in Shock Tube: Comparison of Three Different Testing Locations
,”
PLoS One
,
13
(
6
), p.
e0198968
.10.1371/journal.pone.0198968
43.
Fukunaga
,
K.
,
1990
,
Introduction to Statistical Pattern Recognition
, 2nd ed.,
Academic Press Professional, Inc
.,
Englewood Cliffs, NJ
, pp.
131
–152.
44.
Jain
,
A. K.
, and
Dubes
,
R. C.
,
1988
,
Algorithms for Clustering Data
,
Prentice Hall, Inc
., San Diego, CA, pp.
223
–240.
45.
Palubinskas
,
G.
,
2017
, “
Image Similarity/Distance Measures: What is Really Behind MSE and SSIM?
Int. J. Image Data Fusion
,
8
(
1
), pp.
32
53
.10.1080/19479832.2016.1273259
46.
Carmelo
,
C.
,
Placido
,
M.
,
Marco
,
A.
,
Andrea
,
C.
, and
Alfredo
,
P.
,
2012
, “
Similarity Measures and Dimensionality Reduction Techniques for Time Series Data Mining
,”
Advances in Data Mining Knowledge Discovery and Applications
, A. Karahoca, ed., IntechOpen, Rijeka, Croatia, pp.
72
96
.10.5772/49941
47.
Berthold
,
M. R.
, and
Höppner
,
F.
,
2016
, “
On Clustering Time Series Using Euclidean Distance and Pearson Correlation
,”
Cornell University
,
Ithaca, NY
, accessed Jan. 1, 2016, https://arxiv.org/abs/1601.02213
48.
Murtagh
,
F.
, and
Starck
,
J. -L.
,
2002
, “
Wavelets and Multiscale Transform in Astronomical Image Processing
,”
Handbook of Massive Data Sets
,
J.
Abello
,
P. M.
Pardalos
, and
M. G. C.
Resende
, eds.,
Springer US
,
Boston, MA
, pp.
473
500
.10.1007/978-1-4615-0005-6_13
You do not currently have access to this content.