Modeling Human Volunteers in Multidirectional, Uni-axial Sled Tests Using a Finite Element Human Body Model

Abstract

A goal of the Human Research Program at National Aeronautics and Space Administration (NASA) is to analyze and mitigate the risk of occupant injury due to dynamic loads. Experimental tests of human subjects and biofidelic anthropomorphic test devices provide valuable kinematic and kinetic data related to injury risk exposure. However, these experiments are expensive and time consuming compared to computational simulations of similar impact events. This study aimed to simulate human volunteer biodynamic response to unidirectional accelerative loading. Data from seven experimental studies involving 212 volunteer tests performed at the Air Force Research Laboratory were used to reconstruct 13 unique loading conditions across four different loading directions using finite element human body model (HBM) simulations. Acceleration pulses and boundary conditions from the experimental tests were applied to the Global Human Body Models Consortium (GHBMC) simplified 50th percentile male occupant (M50-OS) using the LS-Dyna finite element solver. Head acceleration, chest acceleration, and seat belt force traces were compared between the experimental and matched simulation signals using correlation and analysis (CORA) software and averaged into a comprehensive response score ranging from 0 to 1 with 1 representing a perfect match. The mean comprehensive response scores were 0.689 ± 0.018 (mean ± 1 standard deviation) in two frontal simulations, 0.683 ± 0.060 in four rear simulations, 0.676 ± 0.043 in five lateral simulations, and 0.774 ± 0.013 in two vertical simulations. The CORA scores for head and chest accelerations in these simulations exceeded mean scores reported in the original development and validation of the GHBMC M50-OS model. Collectively, the CORA scores indicated that the HBM in these boundary conditions closely replicated the kinematics of the human volunteers across all loading directions.

Appendices

Appendix A: Human Volunteer Characteristics by Loading Condition

See Figs. A1 and A2.

Figure A1

Distribution of volunteer subject mass by loading test condition.

Figure A2

Distribution of volunteer subject heights by loading test condition.

Appendix B: Foam Material Properties for Head Rest and Side Guard Cushions

Expected Base Units: kg, mm, ms, kN

LS-Dyna Material Model: Low Density Foam

See Tables B1 and B2.

Table B1 Material properties for low density foam.

Table B2 Load curve ID 1, stress–strain behavior of low density foam.

Appendix C: Input Acceleration Pulses

See Figs. C1, C2, C3 and C4.

Figure C1

− G_x input sled pulses.

Figure C2

+ G_x input sled pulses.

Figure C3

G_Y input sled pulses.

Figure C4

+ G_Z input sled pulses.

Appendix D: CORA Score Generation Parameters

Parameters for CORA version 3.5.1.

Global settings to define the interval of evaluation

A_THRES	0.03	Threshold to set the start of the interval of evaluation [0,…,1]
B_THRES	0.075	Threshold to set the end of the interval of evaluation [0,…,1]
A_EVAL	0.01	Extension of the interval of evaluation [0,…,1]
B_DELTA_END	0.2	Additional parameter to shorten the interval of evaluation (width of the corridor: A_DELTA_END*Y_NORM) 0 = disabled
T_MIN	0	Manually defined start (time) and end (time) of the interval of evaluation (automatic = calculated for each channel)
T_MAX	200

Global settings of the corridor method

G_1	0.5	Weighting factor of the corridor method
K	2	Transition between ratings of 1 and 0 of the corridor method (1 = linear, 2 = quadratic …)

Global settings of the cross correlation method

G_2	0.5	Weighting factors of the cross correlation method
D_MIN	0.05	delta_min as share of the interval of evaluation [0,…,1]
D_MAX	0.15	delta_max as share of the interval of evaluation [0,…,1]
INT_MIN	0.8	Minimum overlap of the interval [0,…,1]
K_V	10	Transition between ratings of 1 and 0 of the progression rating (1 = linear, 2 = quadratic …)
K_G	1	Transition between ratings of 1 and 0 of the size rating (1 = linear, 2 = quadratic …)
K_P	1	Transition between ratings of 1 and 0 of the phase shift rating (1 = linear, 2 = quadratic …)
G_V	0.50	Weighting factors of the progression rating
G_G	0.25	Weighting factors of the size rating
G_P	0.25	Weighting factors of the phase shift rating

Appendix E: Graphical CORA Comparisons by Loading Configuration

See Figs. E1, E2, E3, E4, E5, E6, E7, E8, E9, E10, E11, E12, and E13.

Figure E1

− G_X, 10 G, 55 ms Rise Time (MB-6 Belt): comprehensive rating = 0.706.

Figure E2

− G_X, 10 G, 75 ms rise time (PCU-16/P Belt): comprehensive rating = 0.671.

Figure E3

+ G_X, 10 G, 30 ms rise time (CS Belt): comprehensive rating = 0.731.

Figure E4

+ G_X, 15-G, 16 ms rise time (CS Belt): comprehensive rating = 0.582.

Figure E5

+ G_X, 15 G, 25 ms rise time (CS Belt): comprehensive rating = 0.728.

Figure E6

+ G_X, 20 G, 20 ms rise time (CS Belt): comprehensive rating = 0.689

Figure E7

G_Y, 3 G, 35 ms rise time (CS belt): comprehensive rating = 0.667.

Figure E8

G_Y, 4.5 G, 35 ms rise time (CS belt): comprehensive rating = 0.713.

Figure E9

G_Y, 6 G, 35 ms rise time (CS belt): comprehensive rating = 0.667.

Figure E10

G_Y, 5 G, 75 ms rise time, contoured headrest (PCU-15/P Belt): comprehensive rating = 0.729.

Figure E11

G_Y, 5 G, 75 ms rise time, flat headrest (PCU-15/P Belt): comprehensive rating = 0.603.

Figure E12

+ G_Z, 8 G, 80 ms rise time (MB-6 Belt): comprehensive rating = 0.786.

Figure E13

+ G_Z, 10 G, 70 ms rise time (MB-6 Belt): comprehensive rating = 0.761.

Appendix F: Corridor Difficulty Scores (CDS)

See Fig. F1.

Figure F1

Head acceleration and chest acceleration data displayed contradicting trends when comparing the calculated CORA scores to the corridor difficulty score (CDS), which is a novel measure for the relative width of the generated corridors compared to signal magnitude.