anisotropic composite human skull model and skull fracture validation against temporo-parietal skull...

$: Anisotropic composite human skull model and skull fracture validation against temporo-parietal skull fracture$
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Research Paper

Anisotropic composite human skull model and skullfracture validation against temporo-parietalskull fracture

Debasis Sahooa, Caroline Decka, Narayan Yoganandanb, Remy Willingera,n

aUniversité de Strasbourg ICube, UNISTRA-CNRS, 2 rue Boussingault, 67000 Alsace, Strasbourg, FrancebDepartment of Neurosurgery, Medical College of Wisconsin, 9200 West Wisconsin Avenue, Milwaukee, WI 53226, USA

a r t i c l e i n f o

Article history:

Received 22 March 2013

Received in revised form

15 July 2013

Accepted 4 August 2013

Available online 22 August 2013

Keywords:

Temporo-parietal impact

experiments

Finite element head modeling

Skull fracture tolerance limit

nt matter & 2013 Elsevie1016/j.jmbbm.2013.08.010

[email protected]

a b s t r a c t

A composite material model for skull, taking into account damage is implemented in the

Strasbourg University finite element head model (SUFEHM) in order to enhance the existing

skull mechanical constitutive law. The skull behavior is validated in terms of fracture

patterns and contact forces by reconstructing 15 experimental cases. The new SUFEHM

skull model is capable of reproducing skull fracture precisely. The composite skull model

is validated not only for maximum forces, but also for lateral impact against actual force

time curves from PMHS for the first time. Skull strain energy is found to be a pertinent

parameter to predict the skull fracture and based on statistical (binary logistical regression)

analysis it is observed that 50% risk of skull fracture occurred at skull strain energy of

544.0 mJ.

& 2013 Elsevier Ltd. All rights reserved.

1. Introduction

Skull fracture is the mostly occurred head injury in all kindsof fatalities over last decades. Among all the head injuries,skull fracture accounts for 32% (Fredriksson et al., 2001).Motor vehicle crashes and pedestrian accidents are the majorsource of the increasing head trauma. Occupants sustainsevere and complex brain injuries (DAI) during side impactvehicle collision and around 95% of all DAI cases are asso-ciated with head contact to the interior surface of the vehiclewhich leads to skull fracture in most of the cases as reportedin literature (Yoganandan et al., 2009). Pedestrians accountfor about 12% of all road fatalities in the US, 15% in WesternEurope (IRTAD, 2009; NHTSA, 2008). Head injuries result froman application of the impact force to the cranium. Fractures

r Ltd. All rights reserved.

(R. Willinger).

occur when the dynamic input exceeds the tolerance of theskull. The variation in contact surface can significantly affectthe impact loading and the severity of sustained head injury.A better understanding of the mechanism of skull fracturerequires adequate relevant experimental data, through inves-tigation of the effect of material properties of contact surfaceand an appropriate material model for skull of finite elementhead model (FEHM) which is capable of predicting accurateskull fracture at different impact loading conditions.

In the context of head trauma biomechanics, computa-tional modeling of the head is considered as an efficient andvery promising tool to study. FE modeling technique rendersthe advantage of being able to describe the intricate geometryof head in detail and multiple material compositions fordifferent parts of head model (Raul et al., 2008). The injuries

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sustained by different parts of the head in various impactscenarios can be accurately accessed with the help of FE headmodel by computing strain, stress and other pertinent para-meters at different locations to establish a robust injurytolerance limit. FE human head models have been theprincipal focus of research and several FE head models havebeen reported in the literature in the last decades. In most ofthese models, an isotropic linear elastic material model isimplemented for the skull model and few considered skullmodel (SIMon) as rigid (Kang et al., 1997; Zhang et al., 2001;Kleiven, 2007; Iwamoto et al., 2007; Takhounts et al., 2008).The models are unable to predict skull fracture due to thelack of composite fracture material model. These simplifiedhypotheses are not acceptable as long as skull fracturecriteria and skull fracture pattern are important. Moreoverfully-validated human FE head model for lateral impacts donot exist. In most of these, the skull models are validatedagainst maximum force during frontal impact and few(including Strasbourg University finite element head model(SUFEHM)) are validated for force–deflection curve till thefracture point during vertex impact (Deck and Willinger,2008a, b), but not actual force time curves from post-mortem human surrogates (PMHS) during lateral impact.

Controlled laboratory experiments using appropriate modelof head injury are of great importance in order to investigatethe biomechanical aspects of skull injury mechanism, developtolerance criteria, provide fundamental data to mathematicalanalogue for validation, conduct parametric studies and designanthropometric test devices. Human cadaver experiments offeran unique opportunity to understand certain aspects of headtrauma, despite the postmortem characteristics of the tissue(Yoganandan et al., 1995). The FE head model should bevalidated by comparing and correlating the simulation resultsagainst the experimental data in order to better predict theaccuracy and fidelity of the model. Limited experimental dataare available in literature for skull fracture, which are basedon dynamic experiments (Yoganandan et al., 1994, 1995;Yoganandan, Pintar, 2004, Delye et al., 2007; Verschureerenet al., 2007). Most of the studies have focused on frontal impactto skull because frontal crashes received principal attentionduring the early year of biomechanical research. Lateral impactto the head, in contrast to the frontal loading has been

Table 1 – Detailed SUFEHM model with mechanical properties

Density [kg/m3] 2500 1000 1040Young′s modulus [MPa]

5000 16.7 Viscoe

Poisson′s ratio 0.23 0.42Element type Shell Brick BrickShell thickness [m] 1� 10�2 – –

investigated less frequently in laboratory research leading topaucity of data for this region of human body. Injury criteriaderived for frontal impacts may exceed its limits during sideimpacts, mostly occurred in vehicle crashes Yoganandan andPintar (2004). Further research in this field can ameliorate theinjury prediction and render a better path for FE modelvalidation and simulation.

In the present study a composite material model whichtakes in account for the fracture is implemented for the skullof human FE head model. The principal objective of the studyis to validate SUFEHM skull fracture against new cadaverexperimental data. The impact scenarios are mainly based ontemporo-parietal impacts to human cadaver. This study leadsto a better understanding of skull fracture mechanism andbetter parameters for injury tolerance limit.

2. Materials and methods

2.1. Skull finite element modeling

Strasbourg University finite element head model (SUFEHM),which is a 50th percentile FE model of the adult human head,developed under Radioss software (Kang et al., 1997) andtransferred to LS-DYNA (Deck and Willinger, 2008a, b), wastaken into account in this present study. The main anatomi-cal features includes the scalp, the brain, the brainstem andthe cerebrospinal fluid (CSF) represented by brick elementsand the skull, the face and two membranes (the falx and thetentorium) modeled with shell elements as shown in Table 1.The SUFEHM presents a continuous mesh that is made upwith 13,208 elements, including 1797 shell elements utilizedto compose the skull. The total mass of the head model is4.7 kg which is equivalent to the mass of a 50th percentileadult human head. The geometry of the inner and outersurfaces of the skull was digitized from a human adult maleskull to ensure anatomical accuracy. Isotropic, homogeneousand elastic mechanical constitutive material model wereapplied to each of the SUFEHM parts except for the brain,for which viscoelasticity was assumed. In the present studythe skull was modeled by a three layered composite shell.

(Kang et al., 1997 and Deck and Willinger, 2008a).

1040 1040 1140lastic 0.012 31.5

0.49 0.45Brick Brick Shell– – Falx¼1� 10-3

Tentorium¼2�10�3

Table 2 – Skull mechanical parameters under LS-DYNA code for the SUFEHM.

Parameters Cortical bone Diploe bone

Mass density (kg/m3) 1900 1500Young′s modulus (MPa) 15000 4665Poisson′s ratio 0.21 0.05Longitudinal and transverse compressive strength (MPa) 132 24.8Longitudinal and transverse tensile strength (MPa) 90 34.8


The mechanical properties of all parts of SUFEHM head modelexcept the skull are reported in Table 1.

All the parameters for the brain material model wereidentified from the experimental in vitro data on human braintissue proposed by Shuck and Advani (1972) as well as recentin vivo based values from magnetic resonance elastography(MRE) published by Kruse et al. (2007), with the following values:G0¼49�103 Pa, G1¼1.62�104 Pa, β¼145 s�1. Validation ofSUFEHM against intracranial pressure data from Nahum et al.(1977) and Trosseille et al. (1992) was proposed by Kang et al.(1997), Willinger and Baumgartner (2003), Deck et al. (2004) underRadioss code and by Deck and Willinger (2008a, b) under LS-Dyna code. Extensive real world head trauma simulations wereconducted to derive head tolerance limits to specific head injurymechanisms by Deck and Willinger (2008a, b) and Chatelin et al.(2011). The brain behavior was validated recently against Hardyet al. (2001, 2007) by Sahoo et al. (in press). There exists very fewvalidation of this model to reveal the skull fracture mechanismin the literature proposed by Deck and Willinger (2008a, b) forthe experiments carried out by Yoganandan (1994).

Currently the skull was modeled by a three layered com-posite shell representing the inner table, the diploe andthe external table of human cranial bone. Under LS-DYNAplatform INTEGRATION_SHELL card has been implementedin order to define the three skull layers (cortical bone anddiploe) as layers thicknesses (2 mm for cortical layers and3 mm for diploe layer). The material model 55 which isavailable in LS-DYNA named as MAT_ENHANCED COMPOSI-TE_DAMAGE was used to represent the material behaviour ofskull bones. The material model 55 has three failure criterionfor four different types of inplane damage mechanism basedon Tsai and Wu (1971) criterion which is an operationallysimple strength criterion for anisotropic materials developedfrom a scalar function of two strength tensors.

The basic assumption of this criterion is that there exists afailure in the stress-space in the following scalar form:

f skð Þ ¼ Fisi þ FijsisjZ1 failed;

o1 elastic

�ð1Þ

where i,j,k¼1,2,3…6, and F′s are strength tensors. In theexpansion of Eq. (1) the higher order terms in the strengthcriterion are ignored due to operational standpoint. Theequation reduced to:

f ðsÞ ¼ F1s1 þ F2s2 þ F11s21 þ F22s22 þ F66s26 þ 2F12s1s2 ð2Þ

The linear term in si takes into account internal stresswhich can describe the difference between positive andnegative stress induced failures. The quadratic terms si sjdefine an ellipsoid in the stress space. For uniaxial ply in

failure Eq. (2) becomes:

F1s1 þ F11s21 ¼ 1 ð3Þ

when s1¼Xt then Eq. (3) is

F1Xt þ F11X2t ¼ 1 ð4Þ

and when s1¼�Xc then Eq. (3) is

F11X2c�F1Xc ¼ 1 ð5Þ

where Xt and Xc are longitudinal tensile and compressivestrengths respectively. Upon solving Eqs. (4) and (5) we get

F1 ¼1Xt

� 1Xc

and F11 ¼1

XtXcð6Þ

Similarly applying transverse tensile strength (Yt), trans-verse compressive strength (Yc) and shear strength (Sc) weget:

F2 ¼1Yt

� 1Yc

and F22 ¼1

YtYcð7Þ

F66 ¼1

StScand F12 ¼

1

2P21�P

1Xt

� 1Xc

þ 1Yt

� 1Yc

� ��

�P21

XtXcþ 1

YtYc

� ��ð8Þ

where P is defined by the solution of P2ðF11 þ F22 þ 2F12ÞþPðF1 þ F2Þ ¼ 1.

To describe failure in matrix mode, it is assumed to failbased on the stress perpendicular to the fiber direction s2 andthe shear stress. Also the shear strength is presumed tobehave the same in compressive and tensile loading. There-fore the s1 in Eq. (2) is set to zero which gives the failuresurface as:

f ðsÞ ¼ e2md ¼s22

YcYtþ s12

Sc

� �2

þ ðYc�YtÞs12YcYt

�1Z0 failed;

o0 elastic

�ð9Þ

For both the fiber modes (tensile and compressive) thefailure criterion is similar as Chang and Chang (1987) criterionas described by Eq. (10) and Eq. (11).

For tensile fiber mode

s1140 then e2f ¼s11Xt

� �2

þ βs12Sc

� ��1

Z0 failed;

o0 elastic

�ð10Þ

where β is weighting factor for shear term.For compressive fiber mode

s11o0 then e2c ¼s11Xc

� �2

�1Z0 failed;

o0 elastic

�ð11Þ

Each of them predicts failure of one or more plies in alaminate. The expressions accommodate four in plane failuremodes.


The parameters for the composite material model for theskull are identified from various in vitro experimental datareported in literature. For the elastic material properties likeYoung′s modulus and Poisson′s ratio, parameters remainsame as the previous model (Deck and Willinger 2008a, b).The different strength tensors like longitudinal/transversetensile and compressive strength and shear strengths, arange of values are acquired from in vitro experimental testsconducted by Wood et al. (1971) and McElhaney et al. (1970).The skull mechanical parameters implemented underLS-DYNA are represented in Table 2.

2.2. Experimental data for skull validation

The study was conducted after obtaining the approval of thelocal Institutional Review Board for testing PMHS speci-mens. Unembalmed PMHS were procured and medicalrecords were evaluated and screened for HIV, and hepatitisA, B and C, before conducting experiments. All specimenswere checked for the absence of pre-existing skull fracturesto ensure full applicability to the test protocol. X-ray and CTscans were obtained to ensure the intactness of the skullbones in all specimens. The specimens were sealed indouble plastic bags and stored at �40 deg until furtheruse, a method used in previous biomechanical studies withPMHS (Yoganandan et al., 1988). Seventeen specimens wereisolated at the level of the occipital condyles. The scalp wasincluded in the preparation. The specimens included thehead with intracranial contents (for some specimens syl-gard gel was used as brain substitute). The instrumentationfor biomechanical data acquisition were consisted of triax-ial accelerometers at the vertex, anterior and posteriorregions of cranium, and a-nine accelerometer package(pyramid-shaped PNAP) was attached to the skull at the

Fig. 1 – (a) Specimen prep

Table 3 – Test matrix.

IMPACTOR 40D flat (50 mm thick)

No of specimen tested 9Total tests per impactor 54Mean age 56.8Mean tests per specimen 6Velocity range 3.46 m/s to 8.08 m/s

contra-lateral site of impact using screws as shown inFig. 1a, (Yoganandan et al., 2006).

Locations of the accelerometers were digitized usinga faroarm (Faro Tech. Inc, St Mary, FL) with respect to theanatomical co-ordinate system with the origin at the centreof gravity of the head. The entire assembly was inspectedafter each impact to ensure the absence of loosening. A sixaxis load cell was placed on the impacting platform to recordthe force time histories. The dynamic mode of loading wasaccomplished using free-fall (drop) techniques. No halo ringwas secured to the skull using screws which may affect theintegrity of the skull bones. In other words, the preparedspecimen was completely unconstrained and the skull bonewas intact prior to the drop test. This methodology thusprovided the biomechanical response of the intact skull bonesincluding the basilar skull. The test matrix consisted of repeatedtests on the same specimen with successively increasing inputenergies until fracture or the impact force was closer to therated limit of the load cell. This coincided impacting thespecimen at increasing drop heights associated with impactvelocities ranging from 2.44m/s to 8.08m/s. X-rays wereobtained before and following each impact, i.e., between eachdrop test, and skull fracture identification was made from theseimages. Three impacting boundary conditions, also termed astargets, were used: flat 40- and 90-durometer paddings (50mmthickness), and cylindrical 90-durometer (50mm diameter)padding. The mid-sagittal plane of the specimen was alignedat an angle of approximately 10-deg with respect to thehorizontal plane such that the impact occurred to the lefttemporo-parietal region as illustrated in Fig. 1b.

The test matrix consists of total 86 drop tests from17 PMHS specimens. The mean age, number of specimentested, mean tests per specimen and velocity ranges areshown in Table 3. Repeated drop tests were conducted on

aration; (b) test setup.

90D flat (50 mm thick) 90D cylindrical (50 mm diameter)

4 416 1674.5 654 42.44 m/s to 5.99 m/s 2.44 m/s to 5.99 m/s

Fig. 2 – Peak velocities for each specimen, for different impactors.

Table 4 – Details of experimental data.

Summary of biomechanical data

Velocity Peak force (N) Pulse width(ms)

Skullfracture

m/s Mean SD Mean SD (Y/N)

40-D flat impacting boundary condition3.46 3985 7655 9.51 71.49 N4.24 5650 7650 8.66 70.84 N4.89 6630 71240 8.51 70.89 N5.46 7635 71650 8.76 71.36 N5.99 8285 71135 8.75 70.55 N6.47 8695 71275 9.65 71.35 Y90-D flat impacting boundary condition2.44 4545 7615 7.6 70.6 N3.46 6890 71220 7.1 71.0 N4.24 8430 71670 8.1 71.9 Y4.89 9215 71985 9.1 71.1 Y5.46 9765 72935 8.1 71.4 Y90-D cylindrical impacting boundary condition2.44 4050 7430 7.15 70.95 N3.46 6315 71075 8.05 70.05 N4.24 7110 7580 6.65 71.45 N4.89 7280 72220 7.66 70.66 Y

Table 5 – Impactors mechanical parameters used underLS-DYNA code.

Parameters 40Dflat

90Dflat

90Dcylindrical

Mass density (kg/m3) 4230 4930 4930Young′s modulus(Mpa)

9 12 12

Poisson′s ratio 0.43 0.43 0.43


the same specimen with successively increasing input ener-gies (increasing drop heights) to the specimen until fracture.

Acceleration- and force–time signals were collected usinga digital data acquisition system (TDAS Pro, DTS Technolo-gies, Seal Beach, CA) according to SAE J 211 specifications at asampling frequency of 12.5 kHz. Signals were processed usingSAE Class 1000 filter. Peak resultant forces and center ofgravity linear and angular accelerations were obtained foreach test, using the dynamic equations of equilibrium. As themethods for the computations are described elsewhere, theyare not repeated here (Yoganandan et al., 2006). Fig. 2 showsthe peak velocity of all the specimens for different impactingsurfaces. The black columns indicate the fracture pointvelocity and the white columns indicate where there is nofracture occurred to the skull until this velocity limit. Table 4shows the experimental data of means and standard devia-tions of the force and time variables and the presence orabsence of skull fracture at all velocities for all the three

impacting boundary conditions: flat 40- and 90-durometerpaddings (50 mm thickness), and cylindrical 90-durometer(50 mm diameter) padding. The pulse width is measured asthe time duration between the force reading starts increasingfrom zero and till the force reading reaches a value zero.

2.3. Simulation BCs and data quantification

The SUFEHM model with new constitutive law for skull boneis used to reproduce the similar impact of head as in cadavertests. The impact surface called as pad is modeled as solidelement with MAT 63 CRUSHABLE_FOAM of thickness 50 mmand rested on the top of a rigid platform. The materialparameters are reported in Table 5. To include the strain ratedependency in the foam material a load curve (Yield stress–volumetric strain) is incorporated in the material modelunder LS-DYNA. The slopes of the load curve play veryimportant role to reproduce the contact force between headmodel and pad. The load curve for the impactor and thestrength parameters for the skull are properly chosen in orderto reproduce the best match for impact force time history andfracture pattern for all velocity ranges and different impac-tors. The rigid platform is constrained at its bottom in alldirection to replicate the boundary conditions. The CONTAC-T_AUTOMATIC_SURFACE TO_SURFACE interface is usedbetween FE head model and impactor with static frictioncoefficient 0.7. The mid sagittal plane of the head FE modelis aligned at an angle of 10 deg with respect to horizontalplane as described in the experiment such that the impactoccurred to the left temporo-parietal region. A schematicfor the simulation configuration in LS-DYNA is illustrated inFig. 3. The velocity just before the impact in experiment is

Fig. 3 – Illustration of SUFEHM model orientation andboundary conditions used for simulation under LS-DYNA.

Fig. 4 – Peak strain energy extraction for a case with 90D flatimpactor with impact velocity 5.46 m/s.


applied to the FE head model in initial velocity card. Thematerial for pad is varied according to the durometer numberreported in experiment. The LS-DYNA solver currently usedfor the simulation is ls971_d_R5.1.1_win32_p. The simulationsfor all the tests reported in Table 3 are conducted and thecontact force time history between skull and pad is calculatedin order to validate simulations in regards to experiments.

Variations between the FEM predicted and experimentalcorridors are quantified by calculating the percentage ofdifference between simulation and experimental peak con-tact forces. Then the correlation value “r” (also knownas sample Pearson correlation coefficient) is calculated formean experimental and simulation contact force–time plots.It measures the linear dependence between two arrays ofdata. It is defined as covariance of the two samples divided bythe product of their standard deviation. The correlation valueof range 0.1–0.3 indicates a poor correlation and 0.5 to 1indicates strong correlation between the curves. Moreoverthe peak strain energy of skull is extracted for each caseas well as skull fracture pattern observation in order toidentify a potential candidate capable to predict skull fracturenumerically. The strain energy plots for all the simulationswere obtained as the result of simulation in LS-DYNA plat-form. Then the strain energy–time curve is plotted againstcontact force–time curve as shown in Fig. 4. The skull internalenergy is extracted at time corresponds to the peak impactforce in all the cases, which is normally the peak strainenergy for each simulation.

A statistical analysis is performed in order to assess theaccuracy of peak strain energy of skull as a variable capableto predict skull fractures. Binary logistical regression wascarried out using the version 14.0 release of the proprietarystatistical software package SPSS. This logistical regressionmethod provided the best statistical assessment for data(Deck and Willinger, 2008a) and no underlying assumptionsare made regarding the outcome of the analysis. This methodinvolved fitting a regression model between a number ofpossible skull injury metrics (x¼peak strain energy valuescalculated in our study) and the probability of injury (skullfracture) is defined as follows:

PðxÞ ¼ eaþbx=1þ eaþbx with a and b two parameters calcu-lated by the regression.

A test of the overall model fit for the model was performedusing Chi-squared test with 5% significance level. The qualityof fit for the skull injury metric is determined by using theNagelkerke R2 statistic (the limits for the measure are 0 for apoor fit and 1 for ideal fit).

3. Results

The resultant contact force between SUFEHM and pad inthe simulations for all the cadaver tests was extracted andplotted with the experimental resultant force curves. Theresults are filtered at SAE 1000 Hz as per the experiments.Fig. 5 shows the comparison of simulation contact force withmean experimental contact force (obtained by averaging theupper and lower corridor) for 40D flat padding. There aretotal six simulations conducted for six different velocities.The velocity ranges from 6.47 m/s to 3.46 m/s in accordancewith the experimental data. The curves attain peak valuebetween 3 ms and 4 ms as in experimental data. The devia-tion of peak value of simulation curve from peak of meanexperimental curve is calculated for all cases. The averagediscrepancy in peak values is 2.42%. The correlation coeffi-cient between simulation and mean experimental curve isalso calculated for all cases. The average value is 0.9906.

Fig. 6 shows the comparison of simulation contact forcewith mean experimental contact force (obtained by averagingthe upper and lower corridor) for 90D flat padding. There aretotal five simulations conducted for five different velocities.The velocity ranges from 5.46 m/s to 2.44 m/s in accordancewith the experimental data. The curves attain peak valuebefore 2 ms in all experimental data as well as in simulationresults. The deviation of peak value of simulation curve frompeak of mean experimental curve is calculated for all cases.The average discrepancy in peak values is 4.75%. The corre-lation coefficient between simulation and mean experimentalcurve is also calculated for all cases. The average value is0.9553.

Fig. 7 shows the comparison of simulation contact forcewith mean experimental contact force (obtained by averagingthe upper and lower corridor) for 90D cylindrical padding.There are total four simulations conducted for four diffe-rent velocities. The velocity ranges from 4.89 m/s to 2.44 m/sin accordance with the experimental data. The curvesattain peak value before 3 ms as in experimental data. The

Upper /Lower Corridor Mean Experimental Simu on

r=0.991 r=0.994

r=0.993r=0.987

r=0.989r=0.987

Fig. 5 – Simulation contact force in comparison with experimental for 40D flat pad for six different head impact velocities.


deviation of peak value of simulation curve from peakof mean experimental curve is calculated for all cases. Theaverage discrepancy in peak values is 2.58%. The correlationcoefficient between simulation and mean experimentalcurve is also calculated for all cases. The average value is0.9086.

The strain energy curve was extracted in all the simula-tions and the peak values of all the cases are compared asillustrated in Fig. 8. All the simulations are labeled as Case A,Case B and Case C and are representing SUFEHM impactsimulations on 40D flat, 90D flat and 90D cylindrical paddingrespectively. Results have been separated in two groups,cases with skull fracture in black color and cases withoutfracture in white color. A statistical analysis is performed forall the 15 cases that are reconstructed, based on binarylogistical regression. The Nagelkerke R2 value for the S curve

shown in Fig. 9 for this statistical analysis is calculated as0.714. The other parameters in the probabilistic function area¼�7.073 and b¼0.013. It is observed that the 50% risk ofskull fracture occurred at skull strain energy 544.0 mJ asrepresented by the dashed line in Fig. 9.

The skull fracture patterns for all the simulations wereobtained by marking the fracture initiation when the skullelement failure begins and accounts all the element failurestill the end of the simulation. For 40D flat pad test simula-tions the fracture is initiated at 6.47 m/s and before that thereis no fracture as illustrated in Fig. 10. There are total sixsimulations conducted for six different velocities. The velo-city ranges from 6.47 m/s to 3.46 m/s in accordance with theexperimental data. The skull fracture is represented in blackcolor. Similarly for 90D flat and 90D cylindrical pad fracture isinitiated at 4.24 m/s and 4.89 m/s respectively as shown in

Upper /Lower Corridor Mean Experimental Simu on

r=0.941

r=0.971 r=0.972

r=0.942 r=0.952

Fig. 6 – Simulation contact force in comparison with experimental for 90D flat pad for five different head impact velocities.


Figs. 11 and 12. For 90D flat impactor there are total fivesimulations conducted and the velocity ranges from 5.46 m/sto 2.44 m/s. For 90D cylindrical impactor there are total foursimulations conducted for four different velocities. The velo-city ranges from 4.89 m/s to 2.44 m/s.

4. Discussion

As stated in the introductory paragraphs of the paper, theobjective of the study was to present a composite materialmodel which takes in account the skull fracture in the humanFE head model and validate against temporo-parietal impactsto PMHS. The objective was achieved by using appropriatematerial properties for the outer and inner tables of the skull

bone, incorporating the damage model in LS-DYNA software,and comparing the predicted responses from PMHS tests atdifferent velocities and different impacting conditions usedin the experiments. The software used in the study is wellknown in impact biomechanics literatures (Roberts et al.,2012; Dewit and Cronin, 2012; Ito et al., 2010). The computa-tional model development has also been accepted (Deck andWillinger, 2008a, b; Chatelin et al., 2011). The previous versionof the finite element head model under LS-DYNA code (Deckand Willinger, 2008a, b) used isotropic linear elastic materialfor skull. The linear definition was in-line with the needs ofthe then-used modeling process. However, with the advance-ment of biomechanical research and enhanced efficiencyin computational aspects, the skull was modeled in thecurrent study as anisotropic composite material law with

Upper /LowerCorridor Mean Experimental Simu on

r=0.905 r=0.886

r=0.921 r=0.923

Fig. 7 – Simulation contact forces in comparison with experimental for 90D cylindrical pad for four different head impactvelocities.

Fig. 8 – Peak skull strain energy calculated for allsimulations.

Fig. 9 – S curve obtained after binary logistical regressionanalysis for the peak skull strain energy data.


damage. This is considered as advancement to the previousmodel. Further, the present model, as described in the earliersections, has been validated with new experimental datawith different impacting structural (durometer differences),at different velocities and with different surface properties(flat and curved shapes) of the impacting materials. Theevaluation of the current model with these widely varyingconditions provided more confidence for future applicationsin impact biomechanics of head injuries and mitigationefforts.

The orientation of the specimens used in the experimentswas simulated by properly orienting the model to achievethe desired temporo-parietal impact region. The chosenparameter for the validation exercise was the entire force–time history although it is customary to use the maximumforce as a validating parameter in computational modeling(Deck and Willinger, 2008a, b). The use of the peak force while

Velocity=8.08 m/s Velocity=6.47 m/s



Velocity=3.46 m/s

Fig. 10 – Fracture pattern for 40D flat impactors.


acceptable, any model validation that takes into account theentire force–time history is superior as the progression in thedevelopment of the peak force is considered. From thisperspective, the present modeling effort is more accurate todepict the full range of the biomechanical responses of thehead. There are several widely recognized FE head modelsthat have reasonable skull models reported in literature.

A comparison of their skull model in terms of software used,mesh and number of elements, material laws used and theirvalidations is reported in Table 6. Detail descriptions of oldermodels are reported in Voo et al. (1996).

As shown in the results section, a good accordance betweenexperimental and numerical results has been obtained. This isappreciated both in terms of the time histories and very strong



Velocity=2.44 m/s

Fig. 11 – Fracture pattern for 90D flat impactors.


statistical measures (Pearson correlation coefficients rangingfrom 0.987 to 0.993 for the 40D flat, 0.941 to 0.972 for the 90Dflat, and 0.0.886 to 0.923 for the 90D cylindrical pads). The likelyvariations, albeit small, may be due to the experimental designwhich included factors such as age and sample size differencesbetween the three padding (Table 3) conditions. These findingsclearly indicate that the present model is validated for forcesin the entire time domain at different velocities and for diffe-rent boundary conditions. Thus, the model can be used withconfidence in future modeling wherein automotive interiorsurfaces and occupant velocities are simulated to depict real-world scenarios, as it is known that head contact loading withinterior surfaces in non-ejected occupants is a source of headinjury in motor vehicle crashes (Grant et al., 2007; Yoganandanet al., 2009).

In addition to the force history, patterns of fracture distribu-tions at different velocities for different boundary conditionswere in agreement with experimental data, i.e., lower velocitytests not producing skull fractures while higher impacts resulting

in fractures depending on the boundary condition. Thesefurther add to the confidence in the validation process of themodel in the fracture-producing domain and confirm the appro-priateness in the use of the modeling and analysis approachesused in the present study. However, to further reinforce thegrowth of the local fracture patterns, it would be important todesign advanced fracture detection experiments, perhaps usingnewer technologies and sensors. This is considered as a futurestudy.

Another variable used in the validation process was theinternal energy of the skull. This parameter was extractedat the time of peak impact force in all cases. Based on thisapproach, as a first step, the strain energy of 544mJ canbe used as the threshold for 50% of risk for human skullbone fracture. Additional experimental studies at other velocitiesand boundary conditions are needed to improve the quality ofthe risk curve. This is also considered as a future research topic.

The limitations of the model include incorporations ofthe exact mass and orientations of each cadaver head.



Fig. 12 – Fracture pattern for 90D cylindrical impactors.

Table 6 – Comparison of human FE skull models and validation.

FEHM Solvingsoftware

No. of elements Skull model

Materialproperty

Validation

Ruan et al. (1993)and Ruan andPrasad (1994)

PAM-CRASH

Total 7351elements, 2800elements for skull

Elastic–plastic Not performed

Dimasi et al.(1995)

LS-DYNA Total 5900 elements Rigid Not performed

WSUBIM (Zhanget al., 2001)

PAM-CRASH

Total 314500elements

Elastic-plasticwith failure

Validation against force–penetrationcurve for facial impacttests (Zhang et al. 2001)

UCDBTM (Horganand Gilchrist,2003)

ABAQUS Element densitiesvaries from 9000–50000 elements

Isotropic Elasticmaterial

Not performed

THUMS (Iwamotoet al., 2007)

LS-DYNA Total 49700elements

Elastic-plasticwith failure

Not performed

KTH (Kleiven,2007)


Isotropic Elasticmaterial withfailure

Validation against force–deflection curve for parietalimpact and one case study (Kleiven, 2006)

SIMon(Takhounts et al.,2008)


Rigid Not performed

Author′s model RADIOSSand LS-DYNA

Total 13208elements, 1797 shellelements for skull

Anisotropiccompositematerial withfailure

Validation against force–deflection curve for verteximpact (Deck and Willinger, 2008b). Validation againstforce–time curve for temporo-parietal impact andfracture pattern for 15 cases from experiments on PMHS


The precise three-dimensional orientation of the head at theinstant of impact with the padding surface was not knownfrom the experimental data. While these parameters may

influence the outputs, the close agreements in the entire timedomain for all the forces at all velocities and for allthe three boundary conditions together with the fracture


patterns indicate that the model has accurately reproducedthe experimental conditions and stress analysis outputs arereliable.

5. Conclusions

Although FE head models have been developed in the litera-ture, fully validated models in the time domain for temporo-parietal impacts using companion experimental PMHS dataare not available. The present study validated a three-dimensional FE model of the human head for such impactsusing PMHS data. The composite material model which takesin account the skull fracture was used to simulate testsconducted at various velocities for three different boundaryconditions using different specimens. The skull was modeledby a three layered composite shell representing the innertable, the diploe and the external table of human cranial bone.Force–time histories instead of peak forces were obtained fromtests for each case and used for the validation process. Resultsindicate that the FE model force outputs in the time domainmatched very well with all tests and all conditions. In addition,fracture patterns predicted by the FE model were also inagreement with experimental outcomes. The strain energymagnitude of 544 mJ at the time of peak impact force can beused as the threshold for 50% of risk for human skull bonefracture. The present validation efforts in the time domainusing various testing parameters and fracture patterns usingPMHS data adds confidence in the future use of the currentFE model for simulating real-world impact scenarios andunderstanding of human head injuries and injurybiomechanics.

Acknowledgements

The authors acknowledge research support to this work fromthe MAIF Foundation and VA Medical Research.

r e f e r e n c e s

Chang, F.K., Chang, K.Y., 1987. A progressive damage model forlaminated composites containing stress concentration.Journal of Composite Materials 21, 834–855.

Chatelin, S., Deck, C., Renard, F., Kremer, S., Heinrich, C.,Armspach, J.-P., Willinger, R., 2011. Computation of axonalelongation in head trauma finite element simulation. Journalof the Mechanical Behavior of Biomedical Materials 1751–6161(10), 1016.

Deck, C., Nicolle, S.,Willinger, R., 2004. Human head FE modelling:improvement of skull geometry and brain constitutivelaws. In: Proceedings on the IRCOBI Conference, 2004 Graz,pp. 79–92.

Deck, C., Willinger, R., 2008a. Improved head injury criteria basedon head FE model. International Journal of Crashworthiness13 (6), 667–678.

Deck, C., Willinger, R., 2008b. Head injury prediction tool forpredictive systems optimization. In: Seventh EuropeanLS-DYNA Conference.

Delye, H., Verschueren, P., Depreitere, B., Verpoest, I., Berckmans,D., Sloten, J.S., Perre, G.V., Goffin, J., 2007. Biomechanics of

frontal skull fracture. Journal of Neurotrauma 24 (10),1576–1586.

Dewit, J.A., Cronin, D.S., 2012. Cervical spine segment finite elementmodel for traumatic injury prediction. Journal of the MechanicalBehavior of Biomedical Materials 10, 138–150.

DiMasi, F.P., Eppinger, R.H., Bandak, F.A., 1995, Computationalanalysis of head impact response under car crash loadings. In:Proceedings of the 39th Stapp Car Crash Conference, SAE952718, San Diego, CA, USA.

Fredriksson, R., Haland, Y., Yang J. 2001. Evaluation of a newpedestrian head injury protection system with a sensorin the bumper and lifting of the bonnet′s rear part. In:Proceedings of the 17th International Technical Conferenceon the Enhanced Safety of Vehicles(ESV), Paper no 131-0Amsterdam, Netherlands.

Grant, J.R., Rhee, J.S., Pintar, F.A., Yoganandan, N., 2007. Modelingmechanisms of skull base injury for drivers in motor vehiclecollisions. Otolaryngology—Head and Neck Surgery: OfficialJournal of American Academy of Otolaryngology-Head andNeck Surgery 137, 195–200.

Hardy, W.N., Foster, C.D., Mason, M.J., Yang, K.H., King, A.I.,Tashman, S., 2001. Investigation of head injury mechanismsusing neutral density technology and high-speed biplanarX-ray. Stapp Car Crash Journal 45, 337–368.

Hardy, W.N., Mason, M.J., Foster, C.D., Shah, C.S., Kopacz, J.M.,Yang, K.H., King, A.I., Bishop, J., Bey, M., Anderst, W.,Tashman, S., 2007. A study of the response of the humancadaver head to impactStapp Car Crash Journal 51.

Horgan, T.J., Gilchrist, M.D., 2003. The creation of three-dimensional finite element models for simulating headimpact biomechanics. International Journal ofCrashworthiness 8 (4), 353–366.

IRTAD (2009) Annual Report 2009. International Traffic SafetyData and Analysis Group. Accessed 2010-12-28 at: ⟨http://www.irfnet.ch/filesupload/knowledges/IRTAD-ANNUAL-REPORT_2009.pdf⟩.

Ito, D., Tanaka, E., Yamamotto, S., 2010. A novel constitutivemodel of skeletal muscle taking into account anisotropicdamage. Journal of mechanical behavior of biomedicalmaterial 3 (1), 85–93.

Iwamoto, M., Nakahira, Y., Tamura, A., Kimpara, H., Watanabe, I.,Miki, K., 2007. Development of advanced human models inTHUMS. In: Proceedings of the Sixth European LS-DYNA Users′Conference, pp. 47–56.

Kang, H.S., Willinger, R., Diaw, B.M., Chinn, B., 1997. Validationof a 3D human head model and replication of headimpact in motorcycle accident by finite element modeling.In: Proceedings of the 41th Stapp Car Crash Conference,Society of Automotive Engineers, Lake Buena Vista, USA,pp. 329–338.

Kleiven, S., 2006. Biomechanics as a forensic science tool—reconstruction of a traumatic head injury using the finiteelement method. Scandinavian Journal of Forensic Sciences 2,73–78.

Kleiven, S., 2007. Predictors for traumatic brain injuries evaluatedthrough accident reconstruction. In: Proceedings of the 51thStapp Car Crash Conference, Society of Automotive EngineersPaper 2007-22-0003, pp. 81–114.

Kruse, S.A., Rose, G.H., Glaser, K.J., Manduca, A., Felmlee, J.P., JackJr., C.R., Ehman, R., 2007. Magnetic resonance elastography ofthe brain. NeuroImage 39, 231–237.

McElhaney, J.H., Fogle, J.L., Melvin, J.W., Haynes, R.R., Roberts, V.L.,Alem, N.M., 1970. Mechanical properties of cranial bone. Journalof Biomechanics 3, 495–511.

Nahum, A., Smith, R., Ward, C., 1977. Intracranial pressuredynamics during head impact. In: Proceedings of the 21stStapp Car Crash Conference, SAE Paper No. 770922.

http://refhub.elsevier.com/S1751-6161(13)00267-1/sbref1








http://refhub.elsevier.com/S1751-6161(13)00267-1/othref0005













































http://www.irfnet.ch/filesupload/knowledges/IRTAD-ANNUAL-REPORT_2009.pdf



































NHTSA 2008. Traffic Safety Facts: 2007 Data Pedestrians. NationalHighway Traffic Safety Administration, Washington DC, USA.

Raul, J.S., Deck, C., Willinger, R., Ludes, B., 2008. Finite elementmodels of the human head and their applications in forensicpractice. International Journal of Legal Medicine 122, 359–366.

Roberts, J.C., Harrigan, T.P., Ward, E.E., Taylor, T.M., Annett, M.S.,Merkle, A.C., 2012. Human head–neck computational modelfor assessing blast injury. Journal of Biomechanics 45 (16),2899–2906.

Ruan, J.S., Khalil, T., King, A.I., 1993, Finite element modeling ofdirect head impact. In: 37th Stapp Conference Proceedings,SAE 933114. San Antonio, TX.

Ruan, J.S., Prasad, P., 1994, Head injury potential assessment infrontal impacts by mathematical modeling. In: Proceedings ofthe 38th Stapp Car Crash Conference, SAE 942212. Ft.Lauderdale, Florida, USA.

Sahoo, D., Deck, D., Willinger, R., 2013. Development andvalidation of an advanced anisotropic visco-hyperelastichuman brain FE model, http://dx.doi.org/10.1016/j.jmbbm.2013.08.022, in press.

Shuck, L.Z., Advani, S.H., 1972. Rheological response of humanbrain tissue in shearing. ASME Journal of BiomechanicalEngineering, 905–911.

Takhounts, E.G., Hasija, V., Ridella, S.A., Tannous, R.E., Campbell,J.Q., Malone, D., Danelson, K., Stitzel, J., Rowson, S., Duma, S.,2008. Investigation of traumatic brain injuries using the nextgeneration of simulated injury monitor (SIMon) finite elementhead model. Stapp Car Crash Journal 52, 1–32.

Trosseille, X., Tarriere, C., Lavaste, F., Guillon F., Domont, A., 1992.Development of a F.E.M. of the human head according to aspecific test protocol. In: Proceedings of the 36th Stapp CarCrash Conference, SAE Paper No. 922527.

Tsai, S.W., Wu, E.M., 1971. A general theory of strength foranisotropic materials. Journal of Composite Materials, 58–80.

Verschueren, P., Delye, H., 2007. A new test set-up for skullfracture characterisation. Journal of Biomechanics 40 (15),3389–3396.

Voo, L., Kumaresan, S., Pintar, F.A., Yoganandan, N., Sances, A.,1996. Finite-element models of human head. Medical &Biological Engineering & Computing 34, 375–381.

Willinger, R., Baumgartner, D., 2003. Human head tolerance limitsto specific injury mechanisms. International Journal ofCrashworthiness 8 (6), 605–617.

Wood, J.L., 1971. Dynamic response of human cranial bone.Journal of Biomechanics 4, 1–12.

Yoganandan, N., Maiman, D.J., Pintar, F., Ray, G., Myklebust, J.B.,Sances, Jr., A., Larson, S.J., 1988. Microtrauma in the lumbarspine: a cause of low back pain. Neurosurgery 23, 162–168.

Yoganandan N. 1994. Biomechanics of skull fracture. In:Proceedings of Head Injury 94 Symposium, Washington DC.

Yoganandan, N., Pintar, F.A., Sances, A., Walsh, P.R., Ewing, C.L.,Thomas, D.L., Snyder, R.G., 1995. Biomechanics of skullfracture. Journal of Neurotrauma 12, 659–668.

Yoganandan, N., Pintar, F.A., 2004. Biomechanics of temporo-parietal fracture. Clinical Biomechanics 19, 225–239.

Yoganandan, N., Zhang, J., Pintar, F.A., King Liu, Y., 2006.Lightweight low-profile nine-accelerometer package to obtainhead angular accelerations in short-duration impacts. Journalof Biomechanics 39, 1347–1354.

Yoganandan, N., Gennarelli, T.A., Zhang, J., Pintar, F.A.,Takhounts, E., Ridella, S.A., 2009. Association of contactloading in diffuse axonal injuries from motor vehicle crashes.The Journal of Trauma 66, 309–315.

Zhang, L., Yang, K., Dwarampudi, R., Omori, K., Li, T., Chang, K.,Hardy, W., Kahlil, T., King, A., 2001. Recent advances in braininjury research: a new human head model development andvalidation. Stapp Car Crash Journal 45.





































































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