DOT HS 811 305 April 2010

Analysis of Helmet Impact 

Velocity Experimental Data and 

Statistical Tolerance Design
DISCLAIMER 

This publication is distributed by the U.S. Department of Transportation, National Highway 

Traffic Safety Administration, in the interest of information exchange. The opinions, findings, 

and conclusions expressed in this publication are those of the authors and not necessarily those 

of the Department of Transportation or the National Highway Traffic Safety Administration. 

The United States Government assumes no liability for its contents or use thereof. If trade names, 

manufacturers’names, or specific products are mentioned, it is because they are considered essential 

to the object of the publication and should not be construed as an endorsement. The United States 

Government does not endorse products or manufacturers. 
 

 

 

 

TECHNICAL REPORT DOCUMENTATION PAGE 

1. Report No. 

DOT HS 811 305 

2. Government Accession No. 3. Recipients Catalog No. 

4. Title and Subtitle 

Analysis of Helmet Impact Velocity Experimental Data and Statistical 

Tolerance Design 

5. Report Date 

April 2010 

6. Performing Organization Code 

NHTSA/NVS-421 

7. Authors 

Jingshu Wu,1

 Ph.D., P.E., Charles Fleming,1 Claudia Covell2 

1 – NCSA, 2- Enforcement of NHTSA 

8. Performing Organization Report No. 

9. Performing Organization Name and Address 

National Highway Traffic Safety Administration 

1200 New Jersey Avenue SE. 

Washington, DC 20590 

10. Work Unit No. 

11. Contract or Grant No. 

12. Sponsoring Agency Name and Address 

National Center for Statistics and Analysis 

National Highway Traffic Safety Administration 

1200 New Jersey Avenue SE., Washington, DC 20590 

13. Type of Report and Period Covered 

Technical Report 

14. Sponsoring Agency Code 

NHTSA 

15. Supplementary Notes 

Thanks for help and input from Shashi Kuppa, Rory Austin, Tom Kang, Alex Strashny, Chou-Lin Chen, and Mike Hernandez. Comments from engineers of NHTSA Rulemaking, Enforcement, and Research are appreciated. 

16. Abstract 

Helmet impact velocity experimental data is analyzed and various factors that influence the impact velocity are 

studied. One of the main goals of this report is to verify whether a tolerance of +/- 3 percent of mean velocity is 

feasible and will allow at least 95 percent of impacts to fall within the proposed impact velocity range. Statistical methods are applied to the design of impact velocity tolerances. Calibration procedures and data variances 

from several laboratories are also incorporated into this analysis. 

17. Key Words 

Helmet impact attenuation test, impact velocity, design of 

experiments, statistical tolerance analysis, General linear 

model, and calibration of test instruments. 

18. Distribution Statement: 

Document is available to the public from the National 

Technical Information Service www.ntis.gov 

19. Security Classification (of this report) 

UNCLASSIFIED 

20. Security Classification (of this 

page) 

UNCLASSIFIED 

21. No. of Pages 

19 

22. Price 

Form DOT F 1700.7 (8-72) Reproduction of completed page authorized 

i 
Table of Contents
 

1. INTRODUCTION .......................................................................................................... 1
 

2. IMPACT ATTENUATION TEST PROCEDURE......................................................... 1
 

3. METHODS ..................................................................................................................... 3
 

3.1 General Linear Model for Experimental Data .......................................................... 3
 

3.2 Statistical Consideration of Tolerance Design .......................................................... 4
 

4. RESULTS ....................................................................................................................... 6
 

4.1 Descriptive Tables of Helmet Impact Velocities ...................................................... 6
 

4.2 Impact Velocity Regression Results of General Linear Model ................................ 7
 

4.3 Deviations From Both Laboratory Instrument and Experimental Test Procedure ... 7
 

5. CONCLUSIONS............................................................................................................. 9
 

6. REFERENCES ............................................................................................................. 10
 

7. APPENDIX A: Instrumental Variability and Bias ....................................................... 11
 

8. APPENDIX B: Partial Drop Velocity Data.................................................................. 12
 

ii 
List of Figures
 

Figure 1: Helmet Drop Test Procedure ............................................................................... 3
 

Figure 2: Tolerance and Nominal ....................................................................................... 5

Figure 3: Gaussian Curve used for Statistical Tolerance Design ....................................... 5
 

Figure 4: Velocity Ranges During Impacts Onto the Hemispherical Anvil ....................... 8
 

Figure 5: Velocity Ranges During Impacts Onto the Flat Anvil ........................................ 9
 

iii 
List of Tables
 

Table 1: Velocity 95 percent CI and a Range of “Mean +/- 3 Percent Mean” ................... 6
 

Table 2: Impact Velocity Test Data by Laboratory ............................................................ 6
 

Table 3: GLM Regression Results of Impact Velocity Data .............................................. 7
 

Table 4: Velocity Tolerances Considering the Combined Data Deviations ....................... 8
 

Table 5: Partial Drop Velocity Data Onto Hemispherical Anvil ...................................... 12
 

Table 6: Partial Drop Velocity Data Onto Flat Anvil ....................................................... 12
 

iv 
1. INTRODUCTION 

The National Highway Traffic Safety Administration has the statutory authority to issue 

Federal Motor Vehicle Safety Standards (FMVSS) applicable to new motor vehicles and 

items of motor vehicle equipment, including motorcycle helmets. The law establishes a 

self-certification process in which the vehicle and equipment manufacturers themselves 

certify that their products are in compliance with all applicable FMVSS, which establish 

minimum criteria that the product must meet. NHTSA enforces the standards by randomly selecting and purchasing equipment from the marketplace and testing to the requirements of the standard at independent test laboratories. One such test is the motorcycle 

helmet impact attenuation test for the purpose of ensuring helmets to provide lower levels 

of energy attenuation during crashes. 

The objective of this analysis is to evaluate proposed drop velocity ranges for FMVSS 

No. 218 motorcycle helmet impacts onto the flat and hemispherical anvil in support of 

NHTSA’s response to comments received for the October 1, 2008, FMVSS No. 218 Notice of Proposed Rulemaking (NPRM). The impact attenuation test is specified in 

FMVSS No. 218 Sections S5.1 and S7.1. The nominal target velocity onto the hemispherical anvil is 5.2 meter/second and the nominal target velocity onto the flat anvil is 6.0 

meter/second. The NPRM proposed the impact velocity ranges of 4.8 to 5.6 meter/second, and 5.6 to 6.0 meter/second, respectively; however, many commenters proposed alternate tolerances. The most common suggestion was to limit the tolerance to +/- 

3 percent of nominal target velocity, which would suggest a velocity range of (97% nominal to 103% nominal), or 5.04 to 5.36 meter/second on the hemispherical anvil, and 

5.82 to 6.18 meter/second onto the flat anvil, respectively. 

One of the main interests of this analysis is to determine how many of the helmet impacts 

will fall within the proposed velocity range of +/- 3 percent of the nominal velocity, taking into account both uncertainty due to laboratory equipment variance (from calibration 

procedure and others) and all other variances (such as effects of testing different makes, 

helmet types, and styles of helmets at different locations that are potentially conditioned 

to different procedures by different technicians, etc.) as described in the NPRM. Conversely, if the alternative +/- 3 percent of nominal or mean velocity tolerance is determined not to be feasible, then the objective is to identify a tolerance range that would allow at least 95 percent of impacts to fall within the proposed velocity range. Statistical 

methods are applied to the design of drop velocity tolerances. 

The experimental data of helmet drop tests is analyzed, and various factors that influence 

the drop velocity are studied in detail using statistical regression methods. Instrumental 

calibration procedures and data variances from several laboratories are also compared 

with the National Institute of Standards and Technology (NIST) standard. 

2. IMPACT ATTENUATION TEST PROCEDURE 

This analysis requires understanding the test procedure for the impact attenuation test 

specified in Section S7.1 of FMVSS No. 218. This description of the test procedure consists of only those parts relevant to this analysis. 

1 
 

 

Impact attenuation is measured by determining acceleration imparted to an instrumented 

test headform on which test helmets are mounted. One test series typically consists of 

four helmets of the same size. Each one of the four helmets is conditioned to one of four 

conditioning procedures: ambient, low temperature, high temperature, and water immersion. Each of the four helmets is struck a total of eight times using a monorail drop assembly test device; therefore, each test series consists of 32 total drop tests. 

To accomplish the eight drop tests per helmet, the person conducting the test (hereafter 

called the technician) selects four locations on the shell of the helmet and places the ambient conditioned helmet onto the instrumented test headform, which is mounted to the 

monorail drop assembly. The helmeted headform is aligned so that the first impact location will fall onto the hemispherical anvil. 

The helmet impact velocity is determined by the drop height by the following Eq. (1): 

Impact Velocity (meter/second) = 2gh Eq. (1) 

Where “g” is gravity acceleration constant (9.81 meter/second2), and “h” is the drop 

height (meter). 

The helmet is raised to a height approximately 54.5 inches (1.38 meter) from the anvil 

and allowed to freely drop. The drop height of 54.5 inches (1.38 meter) allows a theoretical impact velocity of 5.2 meter/second from Eq. (1). The velocity is measured at the 

point when the helmet hits the anvil, and the test data is recorded. The technician raises 

the helmet and drops it for a second time onto the same location. The helmets conditioned to the low temperature, high temperature, and water-immersed procedures are 

tested at the same location. The ambient helmet is again placed onto the headform and 

the headform is realigned to allow impacts at the second location. Again, the helmet is 

tested with two successive drops at this location and then the other three helmets are 

tested. The third location is tested similarly. However, the hemispherical anvil is 

changed to a flat anvil and the drop height is increased to 72 inches (1.83 meter), which 

results in a theoretical impact velocity of 6.0 meter/second. Testing continues in this order until 32 total drop tests using all four helmets have been completed. 

The above test procedure, at each of two test laboratories, can be illustrated by the following flow chart (Figure 1). The two laboratories are kept anonymous, simply designated as “Lab A” and “Lab B.” 

The results, from an in depth statistical analysis, are presented below as Figure 1. 

2 
 

 

 

 

 Each Test Lab 

(A or B) 

2 Drop Anvils

 (2 Drop Heights) 

4 Helmet Conditions 2 Helmet Locations Drop Experience 

(1st /2nd drop) 

Figure 1: Helmet Drop Test Procedure 

Understanding this test procedure allowed the following factors to be considered (see 

Figure 1): 

•	 Does one laboratory more closely achieve the target velocity than another laboratory? 

•	 Is the target velocity for either anvil (hemispherical or flat, that is determined by 

drop height) easier to achieve than the other anvil? 

•	 Is the helmet conditioning procedure a factor in achieving target velocity? 

•	 Does the location of the impact influence the ability of the technician to achieve 

the target velocity? 

•	 Is drop experience (first and second drop) a factor in achieving a target velocity? 

These factors are considered as well as the feasibility of achieving the alternative proposed impact velocity ranges for each of the test anvils as described below using statistical tools. 

3. METHODS 

3.1 General Linear Model for Experimental Data 

Design of experiments (DOE) is a process of determining the variations of the interest 

variables (such as helmet impact velocity of this project), and reasoning about these 

variables based on the randomization, comparison, replication, blocking, orthogonality, 

3 
 

 

and factorial effects.2

 The analysis of DOE is built on the foundation of the analysis of 

variance (ANOVA). ANOVA is a collection of models in which the observed variance is 

partitioned into components due to different factors, and those factors are then estimated 

and tested against certain hypothesis. Helped by the ideas of advanced algebra and 

ordinary least squares (OLS), the general linear model (GLM), that including ANOVA, is 

a comprehensive method to analyze the experimental data. 

Under the GLM, the measured helmet drop velocity can be expressed by the following 

equation: 

Impact Velocity = μ +α + β + λ +δ +η +ε	 Eq. (2) 

Where μ is the overall velocity mean, α is the effect from drop contact “anvil” type (flat 

or hemispherical surfaces that are determined by drop heights), ß is the “lab” effect on 

velocity (Lab A or Lab B), λ is a “condition” effect on impact velocity (four helmet conditions), δ refers to the helmet location (two locations per anvil). Furthermore, we also 

consider the difference of first drop and second drop of the same location, using “drop 

experience,” or, η, as one extra variable, and ε is random error with an assumed zero 

mean and variance.3 

This statistical method will explore the following: 

1)	 Find out the effects on impact velocity from various helmet test conditions, laboratories, contact anvils (drop heights), impact locations and effect of “drop experience,” 

2)	 Compare the velocity mean differences and verify if these comparisons are significant, and 

3) Explore the velocity ranges and various confidence intervals (CI), such as common 95 percent CI and 99 percent CI. 

3.2 Statistical Consideration of Tolerance Design 

In engineering and manufacturing, it is not realistic to manufacture a part with a perfect 

dimension size, but it is common that a part dimension size has a mean value with a small 

tolerance. As one analogy and simplest example of tolerance here, a steel shaft diameter 

has a mean (or nominal) of μ =12 mm, with a tolerance of (+/- 0.015 mm), and this implies that the shaft diameter range of (11.985 to 12.015 mm) is acceptable4 5 (see Figure 

2). This same idea also applies to impact velocity that may have a small variation around 

its mean value. 

4 
 

 

 

 

 

Figure 2: Tolerance and Nominal 

Figure 3 further explains the statistical consideration of tolerance design – if the set of 

experimental data is large enough, and if it follows the Gaussian distribution curve 

around the mean value of μ with a standard deviation value ofσ , then the interval [ μ ­

3σ , μ +3σ ] will cover approximately 99.7 percent of the test data.2 4 Here, 3σ can be 

regarded as the absolute value of a statistical tolerance, which is a common engineering 

practice and is shown as Figure 3 (the percentage numbers of Figure 3 are approximate). 

μ

Figure 3: Gaussian Curve used for Statistical Tolerance Design 

Or, equivalently, standard deviation, σ = 1/3*(Tolerance), and hence, 

Tolerance Interval = [ μ -3σ , μ +3σ ] Eq. (3) 

The standard deviation in Eq. (3),σ , is the “pooled standard deviation” or “total standard 

deviation,”σ total , of considering human test errors while performing the experiments, 

σtest, and instrumental errors from different labs, σlab, which is described by Eq. (4) as following root sum square (RSS) method, if human test errors and instrumental errors are 

assumed to be reasonably independent to each other; 2 4 

2 2 σ = (σ +σ ) Eq. (4) total test lab 

5 
 

4. RESULTS 

4.1 Descriptive Tables of Helmet Impact Velocities 

Two test laboratories under contract to NHTSA during fiscal years 2007 and 2008, Lab A 

and Lab B, performed the helmet drop tests. Lab A performed 1,280 drops using 38 helmets, and Lab B performed 1,216 drops using 39 helmets. Figure 1 illustrates test procedure at either Lab A or Lab B; the helmets are dropped onto two different anvils (or drop 

surfaces /drop heights), struck at two helmet locations for each anvil, and two drops at 

each location (assume first drop as “not-experienced” and second drop as “experienced”). 

Furthermore, the helmets are with four different test conditions (low temperature, high 

temperature, and water-immersed). The appendix in Section 8 provides partial drop data 

samples onto two anvils. 

The descriptive statistical results of impact velocities of combined two laboratories are 

listed as Table 1. The helmets are dropped onto two different surfaces, and the test results indicate that they have relatively small standard deviations due to test protocol and 

procedure by test technicians, σtest, and the ratio of standard deviation over the mean 

(coefficient of variation, or CV) is also small. The range of “mean +/- 3 percent mean” is 

wider than the range of 95 percent confidence interval. 

Table 1: Velocity 95 percent CI and a Range of “Mean +/- 3 Percent Mean” 

Drop 

Anvil 

Mean 

μ

Standard 

Deviation 

σtest 

CV= 

(σtest/ μ )100% 

95%CI, 

μ +/-(2 σtest) μ +/- (3% μ ) 

Hemispherical 5.23 0.045 0.86% [5.14 – 5.32] [5.07 – 5.39] 

Flat 6.00 0.048 0.80% [5.90 – 6.10] [5.82 – 6.18] 

Table 2 provides the velocity results of experimental data, per drop anvil, from two different labs, and it indicates that the result from Lab A has a smaller deviation for both 

anvils. 

Table 2: Impact Velocity Test Data by Laboratory 

Drop Anvil Lab Mean μ

Standard 

dev. σtest 

Minimum Maximum 

Hemispherical 

A 5.21 0.036 5.06 5.29 

B 5.25 0.046 5.11 5.37 

Flat 

A 5.99 0.036 5.87 6.08 

B 6.00 0.057 5.82 6.16 

6 
 

4.2 Impact Velocity Regression Results of General Linear Model 

The results from the GLM, as Eq. (2), indicate either a statistically significant or nonsignificant contribution to the variance in the dependent variable, impact velocity, from 

each independent variable, such as helmet location or test condition. The traditional pvalue of 0.05 is used as the threshold of statistical significance. For example, if a p-value 

of 0.20 is obtained for the variable “condition,” this implies that changes in condition do 

not result in statistically significant changes in drop velocity. 

Table 3: GLM Regression Results of Impact Velocity Data 

Source p-value Comments 

Anvil (height) <0.0001 Statistically significantly different 

Lab <0.0001 Statistically significantly different 

Experience 0.2123 Not statistically significantly different 

Location 0.7412 Not statistically significantly different 

Condition 0.3757 Not statistically significantly different 

Table 3 indicates that “anvil (drop height)” and “lab” are two statistically significant factors (with p-values far under 0.05) that influence the impact velocity, while “condition’, 

“location,” and “drop experience” (or first and second drop ) are not significant factors 

with p-values much larger than 5 percent. 

4.3 Deviations From Both Laboratory Instrument and Experimental Test 

Procedure 

This analysis has taken into account the deviations from laboratory instrument calibration, σlab, as well as experimental test protocol and procedures performed by technicians 

as shown in Tables 1, σtest. Every year the test equipment at each lab is calibrated to the 

NIST standards. Records from test labs showing the calibration traceability to the NIST 

are maintained for all measuring and test equipment. Higher order standards are produced 

by institutes or international organizations with responsibility for metrological traceability. 

Based on the RSS method as Eq. (4), the total standard deviations of the velocities when 

taking into account of labs (see Appendix of Section 7 for the calculation details of lab 

deviation,σ lab ) and experimental test procedure in Table 1, σtest, are estimated as follows:4 6 

7 
 

 

2 2 2 2 Hemispherical Anvil: σ = (σ +σ ) = (0.045 + 0.017 ) = 0.048 total test lab 

2 2 2 2 Flat Anvil: σ total test lab = (σ +σ ) = (0.048 + 0.020 ) = 0.052

Where σ lab is the result of focusing only on the instrumental errors and calibrations 

against NIST standard, and is independent from the test procedure error, σtest, and Section 

7 provides more details. 

The following Table 4 provides the drop velocity ranges with 95 percent CI, 99% CI, and 

the range of “velocity mean +/- 3% velocity mean.” It can be seen that both 95 percent CI 

and 99 percent CI are within the range of “velocity mean +/- 3 percent velocity mean.” 

Graphical displays of the same results are shown by Figures 4 and 5. 

Table 4: Velocity Tolerances Considering the Combined Data Deviations 

Drop 

anvil 

mean, 

μ σ test σ lab σ total 

95% CI: 

μ +/2σ total 

99% CI: 

μ +/-3σ total 

μ +/­

3% μ

Hemispherical 5.20 0.045 0.017 0.048 5.10 – 5.30 5.06 - 5.34 5.04 - 5.36 

Flat 6.00 0.048 0.020 0.052 5.90 – 6.10 5.84 - 6.16 5.82 - 6.18 

99% CI velocity 

range, (5.06-5.34) 

Velocity range: 

μ +/-(3%μ), (5.04-5.36) 

Mean of velocity μ=5.20 

95% CI velocity 

range (5.10-5.30) 

Velocity 

Figure 4: Velocity Ranges During Impacts Onto the Hemispherical Anvil 

8 
 

Mean of velocity μ=6.00 

99% CI velocity 

range, (5.84-6.16) 

Velocity range: 

μ +/-(3%μ), (5.82-6.18) 

95% CI velocity 

range (5.90-6.10) 

Velocity 

Figure 5: Velocity Ranges During Impacts Onto the Flat Anvil 

5. CONCLUSIONS 

•	 Experimental data of drop tests indicate that two factors are statistically significant in influencing impact velocities, the laboratory at which the test was conducted, and the drop height for each anvil. Conversely, test conditions, helmet locations, and drop experience are not statistically significant factors in influencing 

impact velocities. 

•	 The experimental design data variances are from both test procedures used by test 

technicians and laboratory instruments, and the combined variances are used to 

design the velocity tolerance ranges. 

•	 All test laboratories have satisfactory calibration standards comparable with the 

NIST standard. Lab A has a slightly smaller impact velocity deviation compared 

with Lab B, and both are satisfactory. 

•	 It is determined that on average more than 99 percent of impacts will fall within 

the impact velocity range, if the +/-3 percent nominal tolerance range is adopted, 

and the velocity interval of 97 percent nominal to 103 percent nominal is acceptable. 

9 
6. REFERENCES 

1.	 NHTSA. (2008). “Federal Motor Vehicle Safety Standards; Motorcycle Helmets.” 

Docket No. NHTSA–2008–0157. Washington, DC: National Highway Traffic 

Safety Administration. 

2.	 Box, G., W. Hunter, W., & Hunter, M. (1978). Statistics for Experimenters. New 

York: John Wiley & Sons, Inc. 

3.	 SAS Institute. (2005). Statistics II: ANOVA and Regression. Cary, NC: SAS Publishing. 

4.	 Scholz, F. (2007). “Statistical Tolerancing.” Unpublished Notes. Seattle, WA: 

Department of Statistics, University of Washington. 

5.	 Shigley, J. (1993). Mechanical Engineering Design. Columbus, OH: McGrawHill. 

6.	 McCarty, T., Daniels, L., Bremen, M., & Gupta, P. (2004). The Six Sigma Black 

Belt Handbook. Columbus, OH: McGraw-Hill Professional. 

10 
 

 

7. APPENDIX A: INSTRUMENTAL VARIABILITY AND BIAS 

According to the certificates of calibration, each instrument not only produces variable 

measurements of the velocities, but the measurements which it produces might be biased 

with respect to the NIST standards. The average relative bias of drop velocity based on 

five calibration certificates is as follows: 

(V −V ) lab NIST bias = ∑i=1toN V Eq.(5) 

NIST 

With a sample bias standard deviation of 

σ bias= 

1 

{ }2 

−

− − ∑

obs 

mean 

NIST 

lab NIST

n 

bias 

V 

VV

 Eq. (6) 

Where “nobs” is the number of comparisons observed between laboratory test data and 

NIST standard data for each lab, and “Vlab” stands for drop velocity measured by labs and 

“VNIST” Velocity measured by NIST. 

Since there are six sets of calibration certificates from three different laboratories, six different bias deviations, σ1, σ2, ..., σ6, (i.e., 0.56%, 0.39%, 0.09%, 0.08%, 0.25%, and 

0.35%) from six lab tests, respectively, can be obtained using same equations as Eq. (5) 

and Eq.(6), and the following σ lab is the average of pooled , or total laboratory bias standard deviations by considering all six certificates, and this average deviation is used in 

Eq. (4) calculation of Section 4.3: 

σ = σ2 +σ2 + .... +σ2) / 6 =0.334% μ lab ( 1 2 6 

Where μ is the velocity mean, thus, the average standard deviations of the velocity for 

each of the two anvils are the following: 

Hemispherical Anvil: σ lab =0.00334(5.2 meter/second) =0.017meter/second 

Flat Anvil: σ lab = 0.00334(6.00 meter/second) =0.020 meter/second 

Furthermore, it is important to find out whether any significant difference between the 

laboratory results with NIST result occurs. The null hypothesis of no significant difference is tested against the alternative, based on five lab calibration certificates: 

H 0: relative bias =0 vs. H 1: relative bias not = 0 

The statistical significance level is 5 percent, and the t-test statistic of 0.409 is associated 

with a p-value of 0.703, or 70 percent (much larger than marginal value of 0.05 or 5%). 

Hence, there is no significant difference between lab results and the NIST standard. 

11 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

8. APPENDIX B: PARTIAL DROP VELOCITY DATA 

Table 5: Partial Drop Velocity Data Onto Hemispherical Anvil 

Helmet 

Condition 

Location1 

Drop1 

Location1 

Drop2 

Location2 

Drop1 

Location2 

Drop2 

Water Immersed 5.17 5.17 5.2 5.19 

High Temp 5.17 5.15 5.2 5.22 

Ambient 5.23 5.16 5.2 5.2 

Low Temp 5.17 5.17 5.22 5.19 

Low Temp 5.16 5.17 5.18 5.2 

Water Immersed 5.15 5.15 5.18 5.19 

Ambient 5.1 5.16 5.19 5.18 

High Temp 5.15 5.16 5.18 5.19 

Ambient 5.1 5.15 5.18 5.19 

Low Temp 5.16 5.17 5.2 5.18 

High Temp 5.17 5.17 5.19 5.19 

Water Immersed 5.16 5.16 5.19 5.2 

Low Temp 5.17 5.15 5.18 5.16 

Ambient 5.16 5.15 5.17 5.18 

Water Immersed 5.16 5.16 5.17 5.16 

High Temp 5.16 5.16 5.19 5.18 

Table 6: Partial Drop Velocity Data Onto Flat Anvil 

Helmet 

Condition 

Location1 

Drop1 

Location1 

Drop2 

Location2 

Drop1 

Location2 

Drop2 

Water Immersed 5.98 5.99 5.98 5.92 

High Temp 5.98 5.99 5.96 5.98 

Ambient 6.02 5.99 5.98 5.98 

Low Temp 5.99 6 5.98 5.98 

Low Temp 5.96 5.96 5.93 5.91 

Water Immersed 5.98 5.95 5.93 5.93 

Ambient 5.96 5.96 5.93 5.93 

High Temp 5.96 5.96 5.93 5.93 

Ambient 6 6 5.98 5.98 

Low Temp 6 6.02 5.98 5.98 

High Temp 6 6.02 5.98 5.98 

Water Immersed 6 6 5.98 5.99 

Low Temp 5.92 5.91 5.87 5.92 

Ambient 5.93 5.92 5.93 5.92 

Water Immersed 5.91 5.91 5.91 5.93 

High Temp 5.92 5.91 5.93 5.93 

12 
DOT HS 811 305

April 2010