November 2012

NASA/TM–2012-217785 

Development and Calibration of a 

System-Integrated Rotorcraft Finite Element 

Model for Impact Scenarios 

Martin S. Annett, Lucas G. Horta, and Karen E. Jackson 

Langley Research Center, Hampton, Virginia 

Michael A. Polanco and Justin D. Littell 

ATK Space Systems, Hampton, Virginia 
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November 2012

NASA/TM–2012-217785 

Development and Calibration of a 

System-Integrated Rotorcraft Finite Element 

Model for Impact Scenarios 

Martin S. Annett, Lucas G. Horta, and Karen E. Jackson 

Langley Research Center, Hampton, Virginia 

Michael A. Polanco and Justin D. Littell 

ATK Space Systems, Hampton, Virginia 
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Development and Calibration of a System-Integrated Rotorcraft Finite Element Model for Impact 

Scenarios

v

Abstract

Two full-scale crash tests of an MD-500 helicopter were conducted in 2009 and 2010 at NASA 

Langley's Landing and Impact Research Facility in support of NASA’s Subsonic Rotary Wing 

Crashworthiness Project. The first crash test was conducted to evaluate the performance of an

externally mounted composite deployable energy absorber (DEA) under combined impact 

conditions. In the second crash test, the energy absorber was removed to establish baseline loads

that are regarded as severe but survivable. The presence of this energy absorbing device reduced 

the peak impact acceleration levels by a factor of three.

Accelerations and kinematic data collected from the crash tests were compared to a systemintegrated finite element model of the test article developed in parallel with the test program. In 

preparation for the full-scale crash test, a series of sub-scale and MD-500 mass simulator tests 

were conducted to evaluate the impact performances of various components and subsystems, 

including new crush tubes and the DEA blocks. Parameters defined for the system-integrated 

finite element model were determined from these tests. Results from 19 accelerometers placed 

throughout the airframe were compared to finite element model responses. 

The model developed for the purposes of predicting acceleration responses from the first crash 

test was inadequate when evaluating more severe conditions seen in the second crash test. A 

newly developed model calibration approach that includes uncertainty estimation, parameter 

sensitivity, impact shape orthogonality, and numerical optimization was used to calibrate model 

results for the full-scale crash test without the DEA. This combination of heuristic and 

quantitative methods identified modeling deficiencies, evaluated parameter importance, and 

proposed required model changes.

The multidimensional calibration techniques presented here are particularly effective in 

identifying model adequacy. Acceleration results for the calibrated model were compared to test 

results and the original model results. There was a noticeable improvement in the pilot and 

copilot region, a slight improvement in the occupant model response, and an over-stiffening 

effect in the passenger region. One lesson learned was that this approach should be adopted early 

on, in combination with the building-block approaches that are customarily used, for model 

development and pretest predictions. Complete crash simulations with validated finite element 

models can be used to satisfy crash certification requirements, potentially reducing overall 

development costs.
Development and Calibration of a System-Integrated Rotorcraft Finite Element Model for Impact 

Scenarios

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Development and Calibration of a System-Integrated Rotorcraft Finite Element Model for Impact 

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vii

TABLE OF CONTENTS

Introduction.............................................................................................................................11

Full-scale Crash Test Description..........................................................................................15

Model Component Development............................................................................................21

DEA Model Development......................................................................................... 21

Skid Gear System Model Development ................................................................... 22

Fuselage Model Development ................................................................................. 26

Seat Model Development......................................................................................... 27

ATD Model Development......................................................................................... 29

Initial System-Integrated Model ............................................................................... 31

Test/Analysis Results: Crash Test with DEA .......................................................................32

Test/Analysis Results: Crash Test Without DEA .................................................................37

Airframe Model Calibration Based on Full-Scale Test without DEA....................................42

Background.............................................................................................................. 42

Calibration Results................................................................................................... 44

Updated Responses for Calibrated System-Integrated Model.............................................51

Crash Test without DEA........................................................................................... 51

Crash Test with DEA................................................................................................ 55

Concluding Remarks ..............................................................................................................58

References ..............................................................................................................................60
Development and Calibration of a System-Integrated Rotorcraft Finite Element Model for Impact 

Scenarios

viii

LIST OF TABLES

Table 1. Full-scale test impact conditions. ............................................................................18

Table 2. Calibrated parameters. ...........................................................................................52

LIST OF FIGURES

Figure 1. NASA Langley Landing and Impact Research Facility. ......................................15

Figure 2. MD-500 helicopter..............................................................................................16

Figure 3. DEA concept......................................................................................................17

Figure 4. Vertical struts. ....................................................................................................18

Figure 5. Test sequence from south camera, crash test with DEA. ...................................19

Figure 6. Test sequence from south camera, crash test without DEA. ..............................20

Figure 7. DEA FEM...........................................................................................................22

Figure 8. Crush tube dynamic testing................................................................................23

Figure 9. Skid gear FEM. ..................................................................................................23

Figure 10. MD-500 mass simulator with DEA......................................................................24

Figure 11. Mass simulator/DEA, test versus analysis comparison, acceleration..................25

Figure 12. Mass simulator/DEA, test versus analysis comparison, axial strain....................26

Figure 13. MD-500 fuselage FEM. ......................................................................................27

Figure 14. MD-500 seats and seat FEMs............................................................................28

Figure 15. Seat mesh dynamic testing. ...............................................................................29

Figure 16. ATD FEMs. ........................................................................................................30

Figure 17. MD-500 system-integrated FEM. .......................................................................31

Figure 18. MD-500 FEM deformation, crash test with DEA. ................................................32

Figure 19. Comparison of test and analysis, pilot seat box vertical acceleration; crash test 

with DEA............................................................................................................34

Figure 20. Comparison of test and analysis, pilot seat box vertical change in velocity; crash 

test with DEA. ....................................................................................................34

Figure 21. Comparison of test and analysis, passenger floor vertical acceleration; crash test 

with DEA............................................................................................................35

Figure 22. Comparison of test and analysis, passenger floor change in vertical velocity; 

crash test with DEA............................................................................................36

Figure 23. Comparison of test and analysis, pilot pelvis vertical acceleration; crash test with 

DEA. ..................................................................................................................36

Figure 24. MD-500 FEM deformation, crash test without DEA. ...........................................37

Figure 25. Comparison of test and analysis, pilot seat box and floor vertical acceleration; 

crash test without DEA.......................................................................................39

Figure 26. Comparison of test and analysis, pilot seat box and floor change in vertical 

velocity; crash test without DEA. .......................................................................39

Figure 27. Pilot subfloor: posttest photograph versus analysis...........................................40

Figure 28. Comparison of test and analysis, passenger floor, vertical acceleration; crash test 

without DEA.......................................................................................................41

Figure 29. Comparison of test and analysis, passenger floor, change in vertical velocity; 

crash test without DEA.......................................................................................41

Figure 30. Calibration FEM. ................................................................................................45

Figure 31. Uncertainty bounds for interim calibration cycle. ................................................47

Figure 32. Variance for interim calibration cycle..................................................................48

Figure 33. Uncertainty bounds for final calibration cycle. ....................................................49
Development and Calibration of a System-Integrated Rotorcraft Finite Element Model for Impact 

Scenarios

ix

Figure 34. Orthogonality for final calibration cycle...............................................................50

Figure 35. Final calibrated system-integrated FEM. ............................................................52

Figure 36. Pilot floor vertical acceleration; crash test without DEA......................................53

Figure 37. Passenger floor vertical acceleration; crash test without DEA............................54

Figure 38. Pilot pelvic vertical acceleration; crash test without DEA....................................55

Figure 39. Pilot floor vertical acceleration; crash test with DEA...........................................56

Figure 40. Passenger floor vertical acceleration; crash test with DEA.................................56

Figure 41. Pilot pelvic vertical acceleration; crash test with DEA.........................................57
Development and Calibration of a System-Integrated Rotorcraft Finite Element Model for Impact 

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x

Nomenclature

AATD Aviation Applied Technology Directorate

ACAP Advanced Composite Airframe Program

ANOVA analysis of variance

APL Applied Physics Laboratory

ATD Anthropomorphic Test Device

CAD computer aided design

CG center of gravity

DEA Deployable Energy Absorber

DOD Department of Defense

ERBF Extended Radial Basis Functions

FEM finite element model

HSTM Human Surrogate Torso Model

HTFEM Human Torso Finite Element Model

LandIR landing and impact research 

LSTC Livermore Software Technology Corporation

MELB Mission Enhanced Little Bird

NASA National Aeronautics and Space Administration

OML outer mold line

SRW Subsonic Rotary Wing Project
Development and Calibration of a System-Integrated Rotorcraft Finite Element Model for Impact 

Scenarios

11

INTRODUCTION

Crashworthiness is the study of a vehicle structure’s ability to withstand impact loads by 

sustaining occupied volume and limiting occupant loads and injury risk. The rotorcraft 

community is researching and incorporating novel crashworthy features that significantly absorb 

kinetic energy for impacts ranging from mild to severe-but-survivable. These crashworthy 

concepts require large inelastic deformations to be effective. For example, airbags and crushable 

composite cushions are two external energy absorbing systems that can be easily stowed and 

rapidly deployed without affecting the vehicle operability. Internal systems, including load 

limiting seats, crushable subfloors, and frangible interfaces, are currently in operation but are 

limited in effectiveness by available space. 

The National Aeronautics and Space Administration (NASA) Subsonic Rotary Wing Project 

(SRW) has sponsored research to evaluate new materials and structural concepts to improve 

rotorcraft crashworthiness and to increase occupant survivability. The tasks identified under the 

SRW project include evaluation of a composite honeycomb Deployable Energy Absorber (DEA) 

(ref. 1), material parameter uncertainty quantification, occupant modeling, and injury risk 

assessment. A task was also established to develop and validate a system-integrated rotorcraft 

finite element model (FEM), which incorporates aspects of the aforementioned tasks. As part of 

this effort, two full-scale helicopter tests were conducted to study structural concepts for 

crashworthiness, to develop and validate component models to predict energy absorption 

performance, and, lastly, to validate system-integrated finite element models. In the first fullscale test, the DEA performance was evaluated. To assess the nominal landing loads, a second 

full-scale test was conducted that did not include the DEA. 

For the Department of Defense (DOD), the standard document for light fixed wing and rotary 

wing crash resistance, MIL–STD–1290A, details seven crash impact design scenarios and 

specifies occupant seat acceleration limits and occupied volume reduction constraints (ref. 2). 

These design conditions are intended to encompass all weight classes and to account for two 

impact surfaces, rigid and plowed soil. Federal Aviation Regulations specify minimum velocity 

and velocity rise-time conditions that must be evaluated for occupant protection (ref. 3). The 

analytical capabilities available when these standards were established were limited; therefore, it 

was expected that crash testing would be primarily used to determine compliance. Ever since, 

more crashworthy features have been implemented into designs, more mishap data has been 

accumulated, and modeling and prediction tools for crashworthiness and injury biomechanics 

have improved.

Efforts are underway to revisit the existing requirements and generate full spectrum 

crashworthiness criteria across all DOD services that account for weight class, operating 

conditions, and impact conditions (ref. 4). Essential in this effort is the development and 

assessment of modeling tools to relate impact velocities, attitudes, and terrains to seat interface 

and occupant acceleration loads, commonly known as G-loads. Ultimately, crash safety 

certification by analysis is sought to lessen the necessity for costly full-scale crash tests. As the 

technology evolves to efficiently incorporate more modeling and simulation into the design 

process, next generation rotorcraft will include more crashworthy features without sacrificing 

performance and minimizing weight increases. Survivability envelopes for a range of velocities, 
Development and Calibration of a System-Integrated Rotorcraft Finite Element Model for Impact 

Scenarios

12

attitudes, and terrains can be developed from both tests and system-integrated models with a high 

degree of confidence. 

The analytical techniques necessary to reliably assess impact loads are less mature compared 

with other dynamic analyses required to assess other phases of rotorcraft flight. Highly nonlinear 

deformation, contact loading, and material response characterize the energy absorption 

mechanisms of the airframe. The inclusion of all components in a single comprehensive 

computational model allows for interactions that one might neglect when analyzing systems 

using uncoupled models. Modeling detailed representations of the airframe, seats, restraints, and 

occupants into a single FEM is now a common practice within the automotive crashworthiness 

community (ref. 5 and 6). Prior to the mid 1990s, most impact analyses were sequentially 

coupled, with vehicle model responses defined as pulse inputs for occupant, seat, and restraint 

models. Interaction between the vehicle and occupant models required simplifying assumptions. 

Efforts to conduct integrated simulations have progressed along with advances in computing 

capability.

Attempts to compare aerospace vehicle-level simulations with full-scale testing originated in the 

late 1970s with the KRASH analysis program (ref. 7). The airframe structure was represented as 

a framework of concentrated mass and bar elements, which relied heavily on semi-empirical data 

to tailor the model response. Cronkhite and Mazza (ref. 8) initially compared a US Army 

Advanced Composite Airframe Program (ACAP) helicopter crash test to KRASH simulations. 

Throughout the 1980s, codes that apply explicit time integration techniques to solve transient 

dynamic problems and provide the capability to handle both material and geometric 

nonlinearities became commonplace. Jackson et al. (ref. 9) compared simulations with the 

explicit finite element analysis program MSC/DYTRAN to the ACAP test. KRASH was coupled 

with MSC/DYTRAN to provide a hybrid computational framework for correlation with UH-1 

helicopter water impact tests (ref. 10). Recently, LS-DYNA has become the predominant 

commercial code for conducting crashworthiness simulations because of its robust contact 

algorithms and extensive material library (ref. 11). Jackson and Fasanella compared results from 

a vertical drop test of an ATR42-300 fixed wing commuter aircraft with simulation using LS–

DYNA (ref. 12).

Recent advancements in computational techniques have allowed for streamlined and efficient 

evaluations of the crash performance of rotorcraft. Finite element models have been developed 

that contain sufficient fidelity to model plastic deformation within the airframe during impact 

and are yet computationally affordable. Detailed representations of seats, occupants, and 

restraints are included to account for the load transfer between the airframe and the occupant and 

to directly assess the likelihood of occupant injury. Allowing for increasingly complex models 

does not guarantee the accuracy of their predictions. Complementary to the development of any 

impact finite element model is the process of verification and validation (ref. 13). Verification of 

models involves determining if the mathematical realization of the equation of motion is 

accurately implemented. Impact dynamics analyses typically rely on commercial finite element 

codes. Therefore, it is assumed that verification of the code is accounted for by the code vendor. 

The validation phase involves establishing confidence that the model results accurately represent 

that the physics of the problem over an applicable domain. In addition, model uncertainty must 

be quantified against the experimental data and be consistent across the entire range of impact 
Development and Calibration of a System-Integrated Rotorcraft Finite Element Model for Impact 

Scenarios

13

conditions. Full-scale impact tests are costly and infrequently conducted; therefore, identification 

of valuable validation metrics is vital.

Typically, validation comparisons between test and analysis are both qualitative and quantitative. 

One qualitative approach, only possible by the use of high-fidelity finite element models, is to 

compare post-impact airframe deformations and regions of damage. Quantitatively, the assertion 

of a properly validated model can be first made by comparing error in kinematic responses such 

as position, velocity, or pitch angle. Any discernible differences that do exist between test and 

analysis require identifying and adjusting parameters within the model; however, kinematic 

responses alone may not provide enough insight to guide adjustment. Output time history 

responses such as acceleration, velocity, strain, and pressure are then compared between sensor 

locations and their respective model nodes or elements. Relative errors for magnitude, time of 

arrival, and pulse duration can be used to compute comparison metrics such as Sprague and 

Geers (ref. 14) and Russell (ref. 15). These metrics can reinforce model adequacy if acceptance 

criteria are satisfied, but they provide minimal guidance into required modifications to model 

parameters in the case of significant discrepancies.

Model calibration, or model updating, is undertaken throughout the verification and validation 

process to infer model parameters that would improve the agreement between the analysis and 

test results. Calibration based on a sparse set of test data does not imply validation over the entire 

applicable design space. With additional test results, it can be demonstrated that model 

calibration successfully validates the model. Test and analysis acceleration responses often 

contain high frequency oscillations, particularly for thin-walled airframe components under 

severe impact conditions. Correlating individual time-history magnitudes and durations becomes 

challenging and ambiguous. Low-pass filtering results may obscure deficiencies in the model 

that would need to be improved to reconcile test with analysis. An approach is desired that 

reveals both the temporal and spatial distribution of acceleration responses, taking advantage of 

the wealth of instrumentation available in full-scale tests. The approach initially discussed by 

Horta in (ref. 16) is used when calibrating specific airframe parameters to crash test results. 

Development of the system-integrated FEM was predicated on a series of tests, ranging from the 

component level to the culminating full-scale crash test. These component tests included 

quasi-static and dynamic loading of a crush tube shock strut, seat mesh impact testing, 

coefficient of friction testing, and MD-500 mass simulator swing tests. An independent 

calibration effort was performed for the model of a Hybrid III Anthropomorphic Test Device 

(ATD) (ref. 17). A series of rigid seat drop tests with Hybrid II and Hybrid III ATDs were used 

to improve model responses in the pelvic region of the Hybrid III FEM. The fully calibrated 

model is executed for both crash test conditions, encompassing a design space and loading that 

extends from benign to severe.

Finite element analyses of these ATD tests were also performed in parallel. This hierarchical 

approach expanded confidence and mitigated uncertainties in component representation within 

the FEM. Airframe calibration is conducted based on results from the second full-scale crash 

test. For calibration, both heuristic and quantitative methods are used to identify modeling 

deficiencies, evaluate parameter importance, and propose required model changes. Calibration 

requires multiple model simulations with a variety of parameter inputs. Therefore, calibration 
Development and Calibration of a System-Integrated Rotorcraft Finite Element Model for Impact 

Scenarios

14

approaches are adopted that are computationally affordable yet include sufficient modeling 

detail. 

The report organization is as follows. First, a detailed description of the full-scale crash test 

program is presented, which includes a description of the facility and a description of the various 

test configurations and test conditions. Second, a discussion of the pretest model component 

development is included. In this section components such as the DEA, crush tube analysis and 

testing, the MD-500 mass-simulator and skid gear analysis and testing, the seat FEM model 

development, and the Hybrid II and III Anthropomorphic Test Device FEM calibration efforts 

are presented. Third, a discussion of the MD-500 helicopter analysis and test results with the 

DEA is provided followed by results without the DEA. Fourth, the model calibration 

methodology using the test with the DEA is discussed. This discussion is followed by updated 

results using both test configurations (with and without DEA). Finally, the concluding remarks 

present a summary of findings and lessons learned. 
Development and Calibration of a System-Integrated Rotorcraft Finite Element Model for Impact 

Scenarios

15

FULL-SCALE CRASH TEST DESCRIPTION

Full-scale crash tests of the MD-500 helicopter were performed at NASA Langley’s Landing and 

Impact Research Facility (LandIR) in November 2009 and March 2010 (ref. 18). The LandIR 

facility is a 240 ft tall gantry structure with swing cables attached at one end and a movable 

pullback platform positioned on the opposite end. Two pullback cables raise the test article to a 

prescribed height. Upon pyrotechnic release of the pullback cable, the test article swings along 

two pairs of swing cables attached to the test article. The two pairs of swing cables are equally 

spaced to form a parallelogram. This configuration controls pitch, roll, and yaw rate during the 

swing. The swing cables are pyrotechnically severed just prior to impact. Figure 1 shows an 

aerial view of the facility and a notional schematic of a swing test. 

(a) Photograph of LandIR. (b) Schematic of LandIR.

Figure 1. NASA Langley Landing and Impact Research Facility.

Target impact conditions were 26 ft/sec vertical and 40 ft/sec horizontal while maintaining zero 

pitch, roll, and yaw attitude. Although this impact condition is severe, it is still considered 

survivable. The test was conducted by suspending the helicopter from the gantry structure using 

two sets of cables: pullback cables and swing cables. These cables were attached to the airframe 

at hard points that enabled the helicopter to be lifted through its center of gravity (CG). 

An MD-500 airframe was provided by the US Army's Mission Enhanced Little Bird (MELB) 

program. Variants of this helicopter, including the OH-6 and the MD-530, have been flown in 

civilian and military applications for more than 40 years. A photograph of the MD-500E 

helicopter, manufactured by MD Helicopters, Inc. of Mesa, Arizona, is shown in Figure 2a. 

Currently the MD-500 is used as a general purpose utility and executive transport helicopter for 

both military and civilian applications. The MD-500 helicopter is designed to seat four 

occupants, two crew and two passengers. The test article is shown in Figure 2b. Occupants were 

placed in standard civilian-issue seats and restrained using four point harnesses for the crew and 

three point harnesses for the passengers. Seats consisted of a framework of aluminum tubing and 

nylon mesh fabric stretched over the frames to form a seat pan and seat back.

andIR. (b) Photograph of LandIR.

R. (b) Photograph of LandIR.

 (a) Schematic of LandIR. (b

(a) Schematic of LandIR. (b) P

(a) Photograph of LandIR (b) Schematic of LandIR
Development and Calibration of a System-Integrated Rotorcraft Finite Element Model for Impact 

Scenarios

16

(a) MD-500E helicopter.

(b) MD-500 crash test article with two DEA blocks attached.

Figure 2. MD-500 helicopter.

The target mass for the test article was set to 2,900 lb, which is roughly the maximum gross 

takeoff weight for the MD-500E. The empty weight was approximately 500 lb. Ballast mass was 

distributed onto the test article by adding steel tubing for swing cabling fixtures, steel plates and 

tubing to represent rotor and tail mass, and data acquisition support hardware to represent the 

transmission. Sand bags were placed in the subfloor region to account for fuel mass. The total 

weights of the test article with and without the DEA were 2,940 lb and 2,906 lb, respectively. 

The weight and balance information was determined prior to the tests. 

Four instrumented ATDs were used to represent two crew and two passengers. The pilot in the 

front left crew position was a 50th percentile Hybrid III male ATD with a straight lumbar spine 

similar to the Hybrid II. The copilot in the front right crew position was a 50th percentile Hybrid 

II male ATD, and the rear passenger on the left side was a 50th percentile Hybrid II male ATD. 

The Hybrid II and III ATDs weigh 180 lb. For the right rear passenger a specialized Human 

Surrogate Torso Model (HSTM) developed by The Johns Hopkins University Applied Physics 

Laboratory (APL) was used (ref. 19). This biofidelic HSTM contains detailed representations of 

thoracic organs, skeletal structure, and soft tissue and is mated to the pelvis and legs of a 50th 

percentile Hybrid III male ATD. The weight of the HSTM/Hybrid III ATD is 170 lb.

The critical component evaluated in the first impact test was the externally mounted DEA, which 

was conceived and patented by Dr. Sotiris Kellas of NASA LaRC (ref. 20). The DEA is a 

Kevlar-129 fabric/epoxy design that consists of multiple hexagonal cells. The cell wall flat facet 

(a) MD-500E helicopter

(b) MD-500 Crash Test Article with 2 

DEA Blocks Attached

Hybrid III HSTM

DEA

(a) MD-500E helicopter

(b) MD-500 Crash Test Article with 2 

DEA Blocks Attached

Hybrid III HSTM

DEA
Development and Calibration of a System-Integrated Rotorcraft Finite Element Model for Impact 

Scenarios

17

width is one inch and the heights vary from 16 to 20 inches. Two DEA's blocks, spanning the 

fuselage belly surface, were secured to the fuselage outer skin with parachute cord, which was 

restrained to the fuselage with two aluminum rails mounted below the door openings. The 

flexible honeycomb design allows for the DEA to be stowed nearly flat external to the fuselage 

belly and to be deployed into the hexagonal configuration as notionally shown in Figure 3a. In 

this configuration, the DEA is loaded along the cell normal axis causing the cell to permanently 

deform under load and thereby absorb energy. When loaded, the cell walls fold to form a 

controlled accordion-like pattern (see Figure 3b). Effectiveness of the DEA was evaluated using 

a building-block approach beginning with material coupon static tests, progressing to subcomponent static and dynamic tests, and culminating with the full-scale crash tests. 

(a) DEA in deployed configuration. (b) Post-impact DEA deformation.

Figure 3. DEA concept.

The MD-500 standard oleo-pneumatic struts, mounted between the skid gear and the airframe, 

are rated for 6 feet-per-second vertical impact conditions. With the high impact velocities 

expected in the full-scale crash, the airframe hard points were likely to be overloaded as the

struts bottom out and become rigid under the high impact velocities expected in the full-scale 

crash test. Consequently, the oleo-pneumatic struts were replaced with a set of crush tubes to

absorb energy through inversion drawing. The crush tubes allow the skid gear to properly swing 

out on impact without being overloaded. The tubes are overwrapped with graphite/epoxy, which 

strengthens the column buckling strength beyond the crush load. Rod ends are attached at either 

end of the tube to impose purely axial loads through the strut length. The crush tube design is 

shown in Figure 4.

(a) DEA in deployed configuration (b) Post-impact DEA deformation

1.0 in.
Development and Calibration of a System-Integrated Rotorcraft Finite Element Model for Impact 

Scenarios

18

Figure 4. Vertical struts.

For instrumentation the fuselage and skid gear used a combination of strain gages and 

accelerometers. ATD instrumentation includes head, chest, and pelvic accelerometers, lumbar 

load cells, restraint load cells, and pressure gages. Data, totaling 160 channels, were collected at 

a sample rate of 10,000 Hz. Measurements of vehicle kinematics were taken using two and three

dimensional large field photogrammetry (ref. 21).

A detailed description of the test results is provided in (ref. 18). The impact conditions for the 

two full-scale helicopter tests are summarized in Table 1. Note that the pitch, roll, and yaw 

attitudes for the test with DEA were off-nominal. It was determined that the variations in the 

distribution of swing cable tension loads prior to release introduced rotational motion upon 

release. Several prelift tests were conducted prior to the second full-scale crash test to determine

proper alignment procedures for cable loads that resulted in impact conditions closer to nominal

for roll and yaw.

Table 1. Full-scale test impact conditions.

Test Parameters Nominal 

Conditions

MD-500 

with DEA

MD-500 

Without DEA

Vehicle Weight (lb) 2,900 2,940 2,906

Linear 

Velocity 

(ft/sec)

Forward 40.0 38.8 39.1

Vertical 26.0 25.6 24.1

Lateral 0 0.5 0.6

Attitude 

(deg)

Pitch 0 –5.69 –6.2

Roll 0 7.04 1.9

Yaw 0 9.3 2.1

Angular 

Velocity 

(deg/sec)

Pitch Rate 0 0.44 0.54

Roll Rate 0 1.11 0.68

Yaw Rate 0 4.82 1.65
Development and Calibration of a System-Integrated Rotorcraft Finite Element Model for Impact 

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19

Figure 5 shows test sequence photos for the crash test with the DEA. Picture 5a shows the 

helicopter approximately 30 ms before impact, pitched down and with some slight yaw. Picture 

5b shows the helicopter at the point of first skid gear impact when the right gear touches the 

ground. Picture 5c shows the point of maximum DEA crushing, and picture 5d shows postimpact rebound. The front right side skid gear impacted the ground first, which was caused by 

the yaw and roll introduced during the swing. At the point of maximum crushing of the DEA 

(picture 5c), the helicopter leveled out to show almost no pitch. After the point of maximum 

crush, the nose pitched forward on rebound, and the Hybrid ATD heads and torsos flailed 

forward and to the left. 

(a) Helicopter approximately 30 ms before (b) Helicopter at the point of first skid gear 

impact. impact.

(c) Point of maximum DEA crushing. (d) Post-impact rebound.

Figure 5. Test sequence from south camera, crash test with DEA.

Overall, the damage to the test article was minor. Impact occurred initially on the front right skid 

gear. Slight tears in the skin above the fuselage opening were evident for both skid gears. The 

DEA restraint support rail impeded the gear from additional movement that caused the right gear 

to bend along the rail. Damage along the fuselage belly was limited to the right front section of 

the belly forward of the front bulkhead. On the other hand, the subfloor and airframe were 

considered intact, and minimal repair work was required on the forward keel beam and belly to 

prepare the test article for the crash test without DEA.

a b

c d

a b

c d
Development and Calibration of a System-Integrated Rotorcraft Finite Element Model for Impact 

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20

Figure 6 shows a sequence of photos for the test without the DEA. Picture 6a shows the 

helicopter approximately 20 ms before impact. Picture 6b shows the helicopter at the point of 

first skid gear impact. As with the MD-500 crash test without DEA, the right gear impacted the 

ground first, but the amount of yaw and roll was lower than the test with the DEA. The fuselage 

belly impacted the ground approximately 80 ms after gear impact, and the highest vertical 

deceleration loads were seen thereafter. Picture 6c shows the point of maximum vertical 

displacement, where the helicopter maintained a slight nose down pitch. Picture 6d shows minor 

post-impact rebound. After the point of maximum subfloor deformation, the nose pitched 

forward on rebound, and flailing of the ATD heads and torsos occurred.

(a) Helicopter approximately 20 ms before (b) Helicopter at the point of first skid gear 

impact. impact.

(c) Point of maximum vertical displacement. (d) Minor post-impact rebound.

Figure 6. Test sequence from south camera, crash test without DEA.

c d

a b

c d

a b
Development and Calibration of a System-Integrated Rotorcraft Finite Element Model for Impact 

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21

MODEL COMPONENT DEVELOPMENT

All impact analyses were performed using the explicit nonlinear transient dynamic code LS–

DYNA version 971 (ref. 11). LS–DYNA applies explicit time integration techniques to solve 

transient dynamic problems and provides the capability to handle both material and geometric 

nonlinearities. All analyses were conducted using shared memory processors (typically four 

CPUs per run) on a Windows platform.

DEA Model Development

Two fundamental approaches were used to model the DEA. In the first approach, the cell 

geometry is represented as a continuum with solid elements (ref. 1) and material properties 

assumed to be elastic-plastic and orthotropic. Material orientation is along the longitudinal axis 

of the cell wall. With this approach at high volumetric strains, compaction occurs and the slope 

of the yield stress versus volumetric strain curve in the cell longitudinal direction sharply 

increases. For the second approach, the cell walls are represented with shell elements that are 

assigned elastic-plastic and isotropic material properties. The compaction of the DEA is directly 

replicated as the cell walls plastically hinge and fold (ref. 22). The modeling approaches were 

evaluated against dynamic crush tests of DEA sections. 

The solid based DEA option is attractive since the nonlinearities and crushing response are 

captured inherently within the material model. Potential users should know that the shell based 

option requires a large number of elements, when compared to the solid based option, to 

replicate the folding patterns accurately. Note that nonlinearities in the shell based option are 

characterized by both geometric and constitutive modeling. The energy attenuation behavior of 

the solid and shell based DEA models were comparable for vertical only impact conditions. 

However, when horizontal velocity exists at impact, the solid based model deformation in the inplane shear direction is not consistent with the test deformations. Furthermore, the crush and 

deformation patterns differ between the shell and solid based models. In particular, the in-plane 

response of the shell based model is primarily governed by geometry. Therefore, the collapse of 

the cell structures and the weak in-plane shear response are intrinsic. 

For the shell based models, convergence studies revealed that the maximum acceptable nominal 

element edge length was approximately 0.3 inches. This dimension corresponds to hundreds of 

thousands of elements per DEA component. Because adequate computing capacity was available 

and the solution time was not prohibitive, the shell based model was selected for the 

system-integrated model. Figure 7a illustrates a typical mesh topology for the shell based DEA 

model. To model the elastic and piecewise linear plastic behavior of the material, Young's 

Modulus was set to 340 ksi and initial yield stress to 7,500 psi. Figure 7b shows the plot of the 

yield stress versus plastic strain curve.
Development and Calibration of a System-Integrated Rotorcraft Finite Element Model for Impact 

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22

(a) Shell bases DEA FEA.

(b) DEA material properties.

Figure 7. DEA FEM.

Skid Gear System Model Development

A critical element of the skid gear is a set of crush tubes, which are modeled as one dimensional 

truss elements to transfer axial loads to the helicopter frame. Bending loads are introduced into 

the fuselage when the truss element nodes exceed a rotation angle, and the rod ends come in 

contact with the surrounding clevises. Data from dynamic impact tests were used to model the 

stress versus stroke behavior. Figure 8 shows a photograph of the dynamic test setup and a time 

history of the load. For modeling purposes, the yield stress was defined equivalent to the 

dynamic crush load of 2,300 lb. A nearly perfectly plastic behavior is assumed upon attaining the 

crush load. 

0

10000

20000

30000

40000

50000

0 0.1 0.2 0.3 0.4 0.5 Yield Stress

Plastic Strain

Young's Modulus = 340 ksi

Poisson's Ratio = 0.3

Yield Stress=7,500 psi

(a) Shell Based DEA FEA

(b) DEA Material Properties

(psi)

0

10000

20000

30000

40000

50000

0 0.1 0.2 0.3 0.4 0.5 Yield Stress

Plastic Strain

Young's Modulus = 340 ksi

Poisson's Ratio = 0.3

Yield Stress=7,500 psi

(a) Shell Based DEA FEA

(b) DEA Material Properties

(psi)

Young’s Modulus =340 ksi

Poisson’s Ratio = 0.3

Initial Yield Stress = 7,500 psi

Plastic Strain (%)
Development and Calibration of a System-Integrated Rotorcraft Finite Element Model for Impact 

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23

Figure 8. Crush tube dynamic testing.

The skid gear, acquired from an MD-500 parts manufacturer, is composed primarily of 

Aluminum 7075 T73 die forgings. Each skid gear is attached to a lateral support and hinged 

along the body centerline. An FEM was created using elastic-plastic shell elements and based on 

the overall dimensions and wall thickness of the skid gear. Figure 9 shows the skid gear and 

strut model with a total weight of 80 lbs.

Figure 9. Skid gear FEM.

Lateral Support

Crush Tube

(1D 

Element)
Development and Calibration of a System-Integrated Rotorcraft Finite Element Model for Impact 

Scenarios

24

The performance of the skid gear, crush tubes, and DEA was verified by conducting an impact

test of an MD-500 mass simulator. The simulator is a 2,500 lb, 4 in thick aluminum plate 

attached to the skid gear with stainless steel brackets and lateral supports. It was instrumented 

with a triaxial accelerometer at the center of gravity and uniaxial strain gages on the vertical 

tubes of the skid gear. The mass simulator swing test was conducted at the full-scale vertical and 

horizontal impact velocities of 26 ft/sec and 40 ft/sec, respectively. It included two DEAs 

approximately 14 inches in height, secured to the underside of the flat plate with parachute cord. 

Based on results from parametric studies of the DEA (ref. 22), the orientation of the DEA 

segments was optimized for the specific test impact conditions and set at 20 degrees from 

vertical. Figure 10 shows both the test article and corresponding FEM. 

(a) Test article.

(b) FEM.

Figure 10. MD-500 mass simulator with DEA.
Development and Calibration of a System-Integrated Rotorcraft Finite Element Model for Impact 

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25

The LS–DYNA model consisted mostly of solid elements for the aluminum plate and brackets.

The concrete surface was represented with a planar rigid wall. To model the kinematic interface, 

the aluminum plate is attached to the gear using brackets and lateral supports hinged and pinned 

with rigid revolute joints.

Figure 11 shows the vertical and horizontal acceleration responses for both test and analysis. To 

remove high frequency oscillations from the response, the acceleration data were filtered with a 

Butterworth 60 Hz low pass filter. Note that the pulse shapes and magnitudes for the vertical 

acceleration were comparable. However, impact surface friction plays a key role in the behavior 

of the system during slide out. Therefore, a separate effort was undertaken to conduct 

independent slow-rate friction drag tests using representative DEA sections. From this test a 

friction coefficient value 0.5 was computed. However, based on the measured horizontal 

accelerations, the friction coefficient of 0.5 was too high and had to be reduced to 0.3 for all 

subsequent simulations with the DEA to provide better correlation.

Figure 11. Mass simulator/DEA, test versus analysis comparison, acceleration.

Figure 12 shows test and analysis axial strains for the right forward vertical leg of the skid gear. 

From these results it is apparent that the vertical members are highly loaded upon impact and

exhibit a tension/compression bending response. In spite of this high load, the strains do not 

exceed the yield allowable for the aluminum, and no plastic deformation was observed from the 

posttest examination of the skid gear. Because acceleration and strain results compare well 

between test and analysis, the modeling approach for the skid gear with the crush tubes was 

deemed adequate.

Filter: 60 Hz 

Butterworth
Development and Calibration of a System-Integrated Rotorcraft Finite Element Model for Impact 

Scenarios

26

Figure 12. Mass simulator/DEA, test versus analysis comparison, axial strain.

Results from the mass simulator test validated the DEA, skid gear, and crush tube models. In 

preparation for the full-scale crash test, the remainder of the MD-500 test article was modeled. 

Attention was given to the components susceptible to damage during impact, namely the 

fuselage and seats.

Fuselage Model Development

A computer aided design (CAD) model of the MD-500 fuselage was provided by the Army 

Aviation Applied Technology Directorate (AATD). The geometry model consisted of surface 

representations of the fuselage outer mold line (OML), bulkheads, seat pan, and floor. A more 

comprehensive geometry was required that represented the internal primary and secondary 

structures and could be readily meshed into an FEM. Geometry that contains compatible surface 

edges eliminates the need to manually manipulate and merge nodes. The model must contain 

enough detail to represent the expected plastic deformation and accurately transmit loads into the 

seats and occupants. This underlying geometry provides the foundation for more refined meshing 

or parameter studies. 

Ribs and stiffeners not present in the baseline geometry model were measured and added to the 

existing geometry. Thickness measurements were taken using ultrasonic transducers and 

calipers. The skin thicknesses typically ranged from 0.02–0.04 in. The keel beam, a critical shear 

load path for the subfloor, was added. Material densities were scaled up by as much as 50 

percent to account for the mass of additional ribs and stiffeners not discretely modeled.

Filter: 60 Hz 

Butterworth
Development and Calibration of a System-Integrated Rotorcraft Finite Element Model for Impact 

Scenarios

27

Figure 13 shows the LS–DYNA FEM of the MD-500 fuselage. To keep the computational time 

low, the element count for the fuselage was targeted not exceed 500,000 elements, including 

seats and occupants. The original fuselage model was only 27,000 elements (not including skid 

gear) and composed of shell elements representing airframe skins, ribs and stiffeners. 

Refinement was concentrated around the subfloor. Ballast representing rotor mass, tail mass, and 

fuel was incorporated in the FEM as concentrated mass elements. Other components like the 

pullback and swing fixtures were added as rigid shells. The platform that supported the DAS was 

mounted in the tail and also modeled as a rigid shell. Although the original geometry had a blunt 

nose, the FEM was modified to a chine nose to represent the actual fuselage. Material properties 

for the fuselage were based on the MD-500 Structural Repair Manual (ref. 23) for Aluminum 

2024 and 7075 with elastic-plastic properties. The nose was made from fiberglass and the engine 

fairing was made from a Kevlar fabric. The fiberglass and Kevlar material properties were

estimated.

Figure 13. MD-500 fuselage FEM.

Seat Model Development

Two crew seats and a single passenger bench seat were obtained from an MD-500 parts supplier. 

The seats are standard military issue with aluminum frames and nylon mesh fabric stretched over 

the frames. Because no geometry was available, the seat geometry was reconstructed using target 

tracking 3-D photogrammetric techniques. Targets were attached to the seat, and point clouds 

were generated from images of the targets and converted to parametric solids, which were used 

to generate a finite element mesh. The as-received passenger bench seat was vulnerable to 

structural failure at the rear seat pan tubes during impact. Additional support braces, typical of 

military applications, were added from the front edge of the seat pan to the floor. Rigid links 

representing this attachment scheme were used in the FEM. The modeling process for the crew 

seat is illustrated in Figure 14, with both crew seat and passenger bench FEMs included.

Pullback and 

Rotor Ballast 

Fixture

DAS 

Platform

Swing 

Fixture

Engine 

Fairing

Nose
Development and Calibration of a System-Integrated Rotorcraft Finite Element Model for Impact 

Scenarios

28

Figure 14. MD-500 seats and seat FEMs.

The seat fabric material properties were determined by dynamic drop tests of a 20 lb 

hemispherical mass onto the fabric. An accelerometer mounted within the drop mass measured 

the vertical acceleration, which was compared to the FEM simulations. The modulus of the 

material was modified to match test and analysis accelerations. Figure 15 shows the drop test 

setup, FEM simulation, and acceleration data comparison. The calculated effective dynamic 

modulus is 4,000 psi, which exceeded the modulus determined from quasi-static load cell testing 

by a factor of three.

Targets Geometry

FEM
Development and Calibration of a System-Integrated Rotorcraft Finite Element Model for Impact 

Scenarios

29

(a) Drop test. (b) FEM.

(c) Drop mass acceleration.

Figure 15. Seat mesh dynamic testing.

ATD Model Development

A model of the 50th percentile HYBRID III male was used for the HYBRID II and III ATDs

(ref. 24). A third model, provided by the LS–DYNA vendor Livermore Software Technology 

Corporation (LSTC), is denoted as the LSTC FEM. THE LSTC FEM contains a combination of 

rigid and deformable discretizations for body parts. Springs and dampers are defined at joints 

between body parts. Using the LS–DYNA preprocessor, the ATD FEMs are easily imported and 

positioned within the helicopter model. Figure 16 shows the LSTC FEM containing 4,295 

elements with a wide range of element types and joint definitions.
Development and Calibration of a System-Integrated Rotorcraft Finite Element Model for Impact 

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30

(a) LSTC Hybrid III FEM. (b) Reduced HTFEM.

Figure 16. ATD FEMs.

Note that the Hybrid II and III ATDs used in the crash tests are notably different from the LSTC 

Hybrid III FEM. It is also important to note that the LSTC Hybrid III FEM has been calibrated 

for automotive frontal impact conditions, with emphasis on capturing head/neck and chest 

kinematics. For testing in aerospace applications, the Hybrid II and III ATDs contain straight 

lumbar spines, whereas the LSTC Hybrid III FEM includes the automotive curved spine. 

Moreover, the LSTC Hybrid III FEM does not contain an abdominal insert, which becomes an 

important load path from the pelvis to the ribcage under high vertical loading. Therefore, it is 

understood that the internal responses of the pelvic and lumbar region with the LSTC Hybrid III 

FEM are not accurate. Results reported in references 17 and 25 support this finding. In cases 

where shoulder restraints are used, the lack of fidelity in the mass distribution of the LSTC 

Hybrid III FEM is not as critical because of the limited torso flailing. Capturing the ATD/seat 

impact, subsequent rebound, and effective mass decoupling is critical for determining the loads 

in the airframe. The LSTC Hybrid III FEM captures this behavior and is therefore better than 

using lumped mass representations.

A reduced human torso FEM was constructed and adapted from APL's detailed Human Torso 

Finite Element Model (HTFEM) (ref. 19). This model includes organs and soft tissue 

components made from solid silicone elements; and the sternum, ribcage, vertebrae, and scapula 

are modeled with fiberglass bar and shell elements. The bar and shell elements are embedded 

within the solid elements and coupled with constraint algorithms. The reduced HTFEM, depicted 

in Figure 16b, was attached to the LSTC Hybrid III FEM pelvis and legs, and the total model 

size is 8,034 elements. The pilot and copilot FEMs are restrained with four point harnesses, and 
Development and Calibration of a System-Integrated Rotorcraft Finite Element Model for Impact 

Scenarios

31

the passenger FEM and reduced HTFEM are restrained with three point harnesses. Seatbelt shell 

elements were contoured to the torso and pelvis.

Initial System-Integrated Model

The system-integrated MD-500 FEM with the DEA is shown in Figure 17. This original model 

has approximately 400,000 elements in total, with 266,000 elements representing the DEA. This 

model size is commensurate with automotive crash model sizes. There are tradeoffs when 

refining models that use explicit finite element techniques where numerical stability is 

conditionally enforced if the time steps are sufficiently small. The time step is a function of the 

shortest element dimension; therefore, for more refined meshes, the time steps decrease and 

overall runtime increases. For simulation times of 0.2 seconds, the system-integrated MD-500 

model runtime is approximately 24 hours.

Figure 17. MD-500 system-integrated FEM.
Development and Calibration of a System-Integrated Rotorcraft Finite Element Model for Impact 

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32

TEST/ANALYSIS RESULTS: CRASH TEST WITH DEA

Figure 17 shows the impact orientation and deformation at peak load for test and analysis. 

Qualitatively, the global deformation pattern of the deployable energy absorber was similar to 

the deformation observed from the high speed video, primarily folding on the right side and 

crushing on the left side, relative to the passenger’s view. Consequently, higher impact loads 

were transferred at locations where the DEA cells simply buckled. However, because damage to 

the front right side was not evident in the analysis, these regions of folding and crushing do not 

correspond between test and analysis. Within the simulation, dimpling of the skin occurred in the 

region above the rear DEA, whereas the posttest inspection revealed no damage. The 

indiscriminate behavior of DEA folding, crushing, and sliding along the belly was due to the 

presence of roll attitude and combined lateral and longitudinal loading and was only partly 

captured with the shell-based DEA model. 

 

(a) Test article prior to impact. (b) Test article at peak acceleration.

Figure 18. MD-500 FEM deformation, crash test with DEA.
Development and Calibration of a System-Integrated Rotorcraft Finite Element Model for Impact 

Scenarios

33

(c) FEM prior to impact. (d) FEM at peak acceleration.

Figure 18. Concluded.

Despite the qualitative differences between local deformation patterns, the overall response of 

the airframe is in reasonable agreement. Nodal accelerations at two critical locations, the pilot 

seat box and the centerline of the floor beneath the passenger seats, are compared to 

accelerometer output. The reference coordinate system for the simulation and the test is fixed 

along the floor surface. The axis perpendicular to the floor represents the vertical direction. For 

purposes of evaluation of occupant injury criteria such as Eiband, Dynamic Response Index, and 

Brinkley (ref. 26–28), the responses for the pilot seat box and passenger floor are used as inputs. 

Comparisons for acceleration and velocity are plotted for 0.2 seconds, and acceleration signals 

are low-pass filtered with a second-order Butterworth 60 Hz filter. The pilot seat box vertical 

accelerations are plotted in Figure 19, and the changes in vertical velocity are plotted in Figure 

20. At t = 0, the skid gear initially impacts the surface. At t = 30 ms, the DEA begins to attenuate 

energy. As expected from previous testing of the DEA, the vertical acceleration waveforms of 

the airframe are effectively trapezoidal with durations of roughly 0.12 seconds from test and 0.10 

seconds from analysis. Note that the DEA performs as a load limiting shock absorber, regulating 

the loads between 10 and 15 g and expanding the deceleration pulse duration through crushing 

and folding. Two differences in the pilot seat box response are evident. The test change in 

velocity approximates the velocity at impact (~26 ft/sec); therefore, there was no rebound in the 

test article. In the analysis, the change in velocity is greater than the velocity at impact by more 

than 4 ft/sec, indicating that the simulation shows a rebound. Second the analysis does not show 

an abrupt increase in the acceleration attributed to compaction of the DEA. In the simulation, the 

airframe rebounded before considerable compaction of the DEA could occur. 
Development and Calibration of a System-Integrated Rotorcraft Finite Element Model for Impact 

Scenarios

34

Figure 19. Comparison of test and analysis, pilot seat box vertical acceleration; crash 

test with DEA.

Figure 20. Comparison of test and analysis, pilot seat box vertical change in velocity;

crash test with DEA.

-5

0

5

10

15

20

0 0.05 0.1 0.15 0.2 Acceleration (g)

Time (sec)

Test

Analysis

Filter: 60 Hz 

Butterworth

-5

0

5

10

15

20

25

30

35

0 0.05 0.1 0.15 0.2 Change in Velocity (ft/sec)

Time (sec)

Test

Analysis
Development and Calibration of a System-Integrated Rotorcraft Finite Element Model for Impact 

Scenarios

35

The passenger floor accelerations are plotted in Figure 21, and the changes in vertical velocity 

are plotted in Figure 22. The differences in acceleration pulse duration and velocity rebound are 

consistent with the pilot seat box responses. The rebounding behavior in the model could be 

attributed to whether all energy attenuating mechanisms are represented within the DEA shell 

elements, to contact with the DEA, or to overall interaction of the DEA interface with the belly. 

However, adjustments of the model to better correlate to the test data appear workable.

Figure 23 shows the predicted and experimental pilot pelvic vertical acceleration. The peak 

acceleration from the analysis is over twice that seen in the test and the pulse shape is also 

different. These results provided the first indication that the ATD models were not specifically 

calibrated for the dominant vertical loading environments experienced in a rotorcraft crash.

Figure 21. Comparison of test and analysis, passenger floor vertical acceleration; crash 

test with DEA.

-5

0

5

10

15

20

0 0.05 0.1 0.15 0.2 Acceleration (g)

Time (sec)

Test

Analysis

Filter: 60 Hz 

Butterworth
Development and Calibration of a System-Integrated Rotorcraft Finite Element Model for Impact 

Scenarios

36

Figure 22. Comparison of test and analysis, passenger floor change in vertical velocity;

crash test with DEA.

Figure 23. Comparison of test and analysis, pilot pelvis vertical acceleration; crash test 

with DEA.

-5

0

5

10

15

20

25

30

35

0 0.05 0.1 0.15 0.2 Change in Velocity (ft/sec)

Time (sec)

Test

Analysis

-10

-5

0

5

10

15

20

25

30

0 0.05 0.1 0.15 0.2 Acceleration (g)

Time (sec)

Test

Analysis

Filter: 60 Hz 

Butterworth
Development and Calibration of a System-Integrated Rotorcraft Finite Element Model for Impact 

Scenarios

37

TEST/ANALYSIS RESULTS: CRASH TEST WITHOUT DEA

The impact orientation and deformation at peak load is shown for test and analysis in Figure 24. 

Initial runs of the system-integrated FEM following the crash test without the DEA revealed key 

shortcomings in the FEM that were not evident when validating against the crash test with DEA. 

During the test, much of the subfloor secondary structure, including the keel beam and frames, 

exhibited structural failure. Pilot and copilot seat boxes were permanently deformed, and seat 

frames either buckled or failed in bending. Furthermore, the tail deformed significantly, and the 

forward swing cable fixture became dislodged at its interface to the bulkhead. Acceleration 

magnitudes increased by a factor of three, and pulse durations were reduced to around 0.040 

seconds. The pulses were triangular in shape but contained different peaks depending on 

airframe location. 

(a) Test article prior to impact. (b) Test article at peak acceleration.

Figure 24. MD-500 FEM deformation, crash test without DEA.
Development and Calibration of a System-Integrated Rotorcraft Finite Element Model for Impact 

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38

(c) FEM prior to impact. (d) FEM at peak acceleration.

Figure 24. Concluded.

Results from the airframe FEM showed that the subfloor mesh was too coarse to accurately 

capture the keel beam and subfloor frame deformation. The predicted tail deformation was 

overly compliant compared with the observed tail deformation. This behavior was attributed to a 

lack of detail, such as omitted frames and stiffeners. To correct for these modeling deficiencies, 

the subfloor and tail FEM were modified in terms of detail and mesh refinement that resulted in 

an increased number of airframe elements from 134,000 to 250,000. 

Despite some improvements in the FEM, there were inconsistencies in the accelerometer data. 

These inconsistencies are highlighted when examining measured and predicted pilot seat box and 

floor vertical accelerations in Figure 25 and change in velocities in Figure 26. The critical impact 

phase occurred between 0.07–0.13 seconds. The pilot seat box and floor acceleration pulse 

shapes and magnitudes differed between test and analysis. In addition, the test data show an 

abrupt spike of 60–70 g on the seat box and the floor, most likely from buckling and failure of 

the keel beam and shear panel under the seat box. This peak is not seen in the predicted seat box 

response that has a peak of approximately 30 g. Also, there is a spike of nearly 50 g in the 

predicted floor response, but the timing is not coincident. The analytical change in velocities for 

the floor is greater than 26 ft/sec, suggesting that there the floor heaved upwards in the model. 

The test velocities, integrated from accelerometer time histories, show that not all the vertical 

velocities were removed during the critical impact phase, which is inconsistent with the 

photogrammetry.
Development and Calibration of a System-Integrated Rotorcraft Finite Element Model for Impact 

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39

Figure 25. Comparison of test and analysis, pilot seat box and floor vertical acceleration; 

crash test without DEA.

Figure 26. Comparison of test and analysis, pilot seat box and floor change in vertical 

velocity; crash test without DEA.

For simplicity, the shell thicknesses are considered constant over the whole region, which 

represents a smeared effective stiffness, whereas the actual hardware has edge doublers and 

rivets and small cutouts. These simplifying assumptions in the FEM may not account for 

multiple thin shell buckling and failure modes. This lack of model fidelity is further illustrated 

-5

0

5

10

15

20

25

30

35

40

45

50

0.07 0.09 0.11 0.13 0.15 Change in Vertical Velocity (ft/sec)

Time (sec)

Seat Box (Test)

Floor (Test)

Seat Box (Analysis)

Floor (Analysis)
Development and Calibration of a System-Integrated Rotorcraft Finite Element Model for Impact 

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40

when comparing the posttest pilot subfloor photographs to the analysis deformations in Figure 

27. From the analysis, plastic deformation occurred along the shear panel, and no failure was 

seen of the keel beam. In contrast, posttest photographs indicate a substantial rippled region of 

the keel beam forward of the shear panel. 

(a) Test. (b) Analysis.

Figure 27. Pilot subfloor: posttest photograph versus analysis.

The passenger floor accelerometer is mounted on a relatively stiff interface; thus, thin-walled 

effects are not introduced, and the filtered test data tracks better than the pilot response as shown 

with acceleration in Figure 28 and change in velocity in Figure 29. In this case, the passenger 

floor acceleration compares well in pulse shape and arrival time, but not in magnitude. 

Furthermore, the predicted pulse shape for the passenger floor is similar to the predicted pilot 

seat box and pilot floor pulse shapes.

Because the DEA significantly attenuated the impact response during the first crash test, one 

should not consider the model to be validated for more severe impact tests. The DEA acted as an 

isolator, imparting loads into the airframe while obscuring deficiencies in the airframe model. 

These deficiencies became apparent when severe loads produced highly nonlinear responses in 

the second full-scale test. There are multiple modes of failure in the test without the DEA, which 

may or may not need to be represented by the FEM. From the standpoint of matching 

acceleration pulse shapes, the FEM detail is adequate in the passenger region, but questionable 

for the pilot region. The previous assertion of an adequate FEM based on the crash test with the 

DEA was questioned. To determine if more physical detail is required in the model or if 

modifications to existing parameters is sufficient, a comprehensive model calibration was 

performed.

Test Analysis

Failure

Shear 

Panel

Keel Beam
Development and Calibration of a System-Integrated Rotorcraft Finite Element Model for Impact 

Scenarios

41

Figure 28. Comparison of test and analysis, passenger floor, vertical acceleration; crash 

test without DEA.

Figure 29. Comparison of test and analysis, passenger floor, change in vertical velocity;

crash test without DEA.

-20

-10

0

10

20

30

40

50

0 0.05 0.1 0.15 Acceleration (g)

Time (sec)

Test

Analysis

Filter: 60 Hz 

Butterworth

-5

0

5

10

15

20

25

30

0.07 0.09 0.11 0.13 0.15 Change in Vertical Velocity (ft/sec)

Time (sec)

Test

Analysis
Development and Calibration of a System-Integrated Rotorcraft Finite Element Model for Impact 

Scenarios

42

AIRFRAME MODEL CALIBRATION BASED ON FULL-SCALE TEST 

WITHOUT DEA

Background

A more computationally rigorous formulation initially discussed in (ref. 16) is applied to results 

from the second test without the DEA to calibrate the FEM. Fundamental to the success of the 

model calibration effort is to establish if the model can predict the observed behavior in the 

presence of modeling uncertainty. Although there is no universally accepted metric to judge 

model adequacy, the approach used following the second test incorporates uncertainty 

propagation and quantification to assess model adequacy. From a baseline FEM, the first step in 

this approach is parameter selection (parameters being in this case material properties, structural 

dimensions, and initial conditions), which relies heavily on the analyst’s knowledge and 

familiarity with the model and assumptions. After an initial parameter set is selected, uncertainty 

models to prescribe parameter variations are defined with the aid of empirical data, or,

oftentimes, one must resort to engineering judgment. With an initial parameter set and an 

uncertainty model at hand, parameter importance is assessed using uncertainty propagation. 

Parameter values in this paper are created using the Halton (ref. 29) deterministic sampling 

technique. Time history results are processed to compute the metrics and to assess variability. A 

by-product of this step produces variance-based sensitivity results that are used to rank the 

parameters. In the end, adequacy of the parameter set is judged based on the probability of one 

being able to reconcile the test with the analysis. 

Analysis of variance (ANOVA) is used for parameter sensitivity. In classical ANOVA studies, 

data are collected from multiple experiments while varying all parameters (factors) and also 

while varying one parameter at a time. These results are then used to quantify the output 

response variance due to variations of a particular parameter, as compared to the total output 

variance when varying all the parameters simultaneously. The ratio of these two variance 

contributions is a direct measure of the parameter importance. Sobol et al. (ref. 30) and others 

(ref. 31–33) have studied the problem as a means to obtain global sensitivity estimates using 

variance-based methods. To compute sensitivity using these variance based methods, one must 

be able to compute many response predictions as parameters are varied. For this report, after a 

suitable set of LS–DYNA solutions were obtained, response surface surrogates were used to 

estimate additional solutions. 

The Extended Radial Basis Functions (ERBF) response surface method, as described by Mullur 

(ref. 34, 35), is used to estimate time histories and interpolate among LS–DYNA responses. In 

this adaptive response surface approach, the total number of response surface parameters 

computed equals N(3np + 1), where np is the number of parameters and N is the number of LS–

DYNA solutions. The user must also prescribe two additional parameters: 1) the order of a local 

polynomial (set to 2 in the present case), and 2) a smoothness parameter (set to 0.15 here). 

Finally, the radial basis function is chosen to be an exponentially decaying function 

2 2 ( ) /2 i c p p r

e

 

with characteristic radius rc set to 0.15. A distinction with this response surface implementation 

is that ERBF is used to predict full time histories, as opposed to just extreme values. In addition, 

ERBF is able to match the responses with prediction errors of order 10–10 at the points used to 

create the surrogate. 
Development and Calibration of a System-Integrated Rotorcraft Finite Element Model for Impact 

Scenarios

43

Uncertainty propagation is conducted to evaluate uncertainty bounds and to gage the ability of 

the model to explain the observed behavior. The statistics of the 2-norm of a response vector 

between test and analysis are compared. An important benefit of using this metric is that it 

provides for a direct measure of multidimensional closeness of two models. In addition, when 

tracked as a function of time, closeness is quantified at each time step. Because parameters are 

uncertain, statistical measures of the metric need to be used to conduct assessments. With limited 

information about parameter uncertainty, a uniform distribution function is the most appropriate 

representation to model parameter uncertainty. This uncertainty model is used to create a family 

of N equally probable parameter vectors, where N is a scalar arbitrarily selected. From the 

perspective of a user, it is important to know the probability of being able to reconcile measured 

data with predictions, given a particular model for the structure and parameter uncertainty. To 

this end, let be a scalar time varying function of the 2-norm of the system 

response vector v, using parameter vector p at time t. Furthermore, let be the 

minimum value over all parameter variations, and let be the maximum 

value. With these definitions and N LS–DYNA solutions, a calibration metric used to bound the 

probability of test values falling inside the analysis bounds is

 

 

 

 

(1)

where Qe(t) is the 2-norm of responses from the experiment. Note that N controls tightness of the 

bounds and also the number of LS–DYNA solutions required. 

The use of norms, although convenient, tends to hide the spatial relationships that exist between 

responses at different locations in the model. In order to study this spatial multidimensional 

dependency explicitly, a different metric must be established. Work by Anderson et al. (ref. 36) 

and Horta et al. (ref. 37) proposed the application of singular value decomposition derived basis 

vectors or impact shapes. In this approach, time histories from analysis or experiments are 

decomposed as:

 

 

 

 

(2)

In this form, the impact shape vector 

i 

sized m x 1 contains the spatial distribution information 

for m sensors, g(t) contains the time modulation information,  contains scalar values with shape 

participation factors, and n is the number of impact shapes to be included in the decomposition, 

often truncated based on allowable reconstruction error. Although eq. 2 is written in continuous 

time form, for most applications, time is sampled at fixed intervals such that t = kΔT where the 

integer k = 0,..., L and ΔT is the sample time. In the discrete form of eq. 2, singular value 

decomposition is used to recover the basis functions (, σ, and g). The fractional contribution of 

the i

th impact shape to the total response is proportional to δi

, defined as: 

 

 

 

 

 

(3)
Development and Calibration of a System-Integrated Rotorcraft Finite Element Model for Impact 

Scenarios

44

Impact shapes can now be used to compare models using orthogonality. Orthogonality, 

computed as the dot product operation of vectors (or matrices), quantifies the projection of one 

vector onto another. If the projection is zero, vectors are orthogonal, i.e., distinct. This same idea 

applies when comparing test and analysis impact shapes. Numerically, the orthogonality metric 

is computed as:

 (4)

where 



is sized m x l with l measured impact shapes at m locations and 



sized m x l are 

shapes computed using simulation data. Note that both 



and 



are normalized matrices such 

that 

T    I

and 

T    I

. Because individual impact shape vectors are stacked column-wise, 

metric M2 is a matrix sized l x l with diagonal values corresponding to the vector projection 

numerical value. If vectors are identical then their projection equals 1. Consequently, when 

evaluating models, multidimensional closeness with the experiment is judged based on similarity 

of impact shapes and shape contributions. 

If the model can be reconciled based on both time and spatial calibration metrics, a parameter set 

is computed that minimizes the squared sum of the prediction error, as defined in eq. 5. The 

matrix W is used to scale or remove data points from the time history. 

1

1

( ( ) ( )) ( ( ) ( ))

L

T

e e

k

J y k T y k T W y k T y k T





       

(5)

Optimization is based on the constrained optimization using response surface (CORS) scheme 

developed by Regis and Shoemaker (ref. 38). Specifically, the algorithm starts by looking for 

parameter values away from the N initial set of LS–DYNA solutions, then slowly steps closer to 

known solutions by solving a series of local constrained optimization problems. This 

optimization process will produce a global optimum if enough steps are taken. Of course, the 

user controls the number of steps and therefore the accuracy and computational expense in 

conducting the optimization. In cases where the predictive capability of the surrogate model is 

poor, CORS adds solutions in needed areas. Because parameter uncertainty is not used explicitly 

in the optimization, this approach is deterministic. If a probabilistic approach was used instead, 

in addition to a reconciling set, the user should also be able to determine the probability that the 

parameter set found is correct. These metrics will now be used to analyze the data from the 

second test without the DEA.

Calibration Results

For the purposes of this calibration effort, 19 sensor locations, containing either triaxial or 

uniaxial accelerometers and totaling 23 channels, were used. At the outset of performing 

calibration runs, the velocity 2-norm of the sensor set was used as a comparison metric. Velocity 

metrics were used because high frequency responses of structures evident in acceleration time 

histories become naturally filtered once integrated to velocity. Direct comparison between test 

and analysis velocities is only achievable by integrating the test accelerometer time histories. The 

integrated test curves are shifted to match to the local initial velocities that are directly output in 

the respective local coordinate systems from the analysis. For many of the accelerometers, 

integration of the signal revealed drifting and inconsistent changes in velocity. The contribution 
Development and Calibration of a System-Integrated Rotorcraft Finite Element Model for Impact 

Scenarios

45

of drift was unique from sensor to sensor and was difficult to detrend. The accelerometers in the 

calibration sensor set could be successfully integrated and, therefore, retained. 

Altogether, seven different calibration cycles were performed with different parameter sets and 

varying ranges for each parameter. For the first several calibration cycles, initial conditions were 

chosen as parameters to vary based on the supposition that there was variability in the initial 

velocities and attitudes from photogrammetry. However, impact conditions such as vertical and 

horizontal velocities and pitch angle had the highest contribution to the total response variance, 

which tended to overshadow the importance of structural parameter values. The photogrammetry 

results were reexamined, and initial conditions permanently fixed.

As calibration cycles were performed, it was also evident that solely using velocity as the 

comparison metric had a disadvantage. Integration removes critical low- to mid-frequency modes 

and responses that could be important in identifying shifting load paths as the airframe plastically 

deforms. Both acceleration and velocity 2-norms were used to determine whether the parameter 

sets and their range of values were appropriately chosen. 

Because of runtime stability issues, the ATD FEMs were removed from the model and their 

masses evenly distributed onto the seat frames and floor. In the meantime, the ATD FEM model 

was calibrated independent of the airframe calibration based on results from drop tests of the 

ATD onto a rigid seat platform (ref. 17). Figure 30a shows the FEM representation used for 

calibration, and Figure 30b shows the calibration sensor locations.

(a) Calibration model.

Figure 30. Calibration FEM.
Development and Calibration of a System-Integrated Rotorcraft Finite Element Model for Impact 

Scenarios

46

(c) Calibration sensor locations.

Figure 30. Concluded.

Parameter selection for the calibration study addresses two essential aspects of the model, 

stiffness and plasticity. Most of the critical airframe components in the load path are modeled 

with shell elements with effective stiffness properties. Seemingly, the thickness of components 

could be directly measured from the test article. However, the presence of rivets, doublers, and 

small stiffeners that could not be included in the model without sacrificing computational 

efficiency would stiffen the test article. Conversely, cutouts and holes would reduce the stiffness. 

The term “effective” accounts for the omission of these features. To change the effective 

in-plane and bending stiffness, either the modulus of elasticity or the thickness defined in the 

shell property can be modified. For this study, the thickness was modified for four structural 

components: belly thickness, keel beam thickness, seat box thickness, and seat box bulkhead 

thickness. These parameters were identified to significantly influence the load path and impact 

response. Additionally, because the airframe is a combination of different alloys of thin sheet or 

cast aluminum, the fifth parameter selected was the initial yield stress. Yield stress was chosen 

specifically for parts in the floor and subfloor region where extensive damage occurs and 

addresses the plasticity of the aluminum components.

To illustrate the value of computing the calibration metric M1, the acceleration and velocity 2-

norms are plotted in Figure 31 for a set of 60 LS–DYNA runs while varying the five parameters 

shown in the table in Figure 31. All acceleration data is low-pass filtered to SAE CFC 60. At this 

point the user must determine if the analysis 2-norm bounds, created with 60 LS–DYNA runs, 

envelop the test bounds. Based on the number of runs, the probability of being able to reconcile 

the model with the test if the experiment is outside the bounds is much less than 1/60. From 

Figure 31 it is apparent that both acceleration and velocity 2-norm bounds have regions of the 
Development and Calibration of a System-Integrated Rotorcraft Finite Element Model for Impact 

Scenarios

47

response that fall outside the analytical bounds. Hence, the LS–DYNA model is not likely to 

reconcile with the test in its present form. 

Additional acceleration results revealed that the time and spatial variation of load transfer are not 

matched. At the point of belly impact, there are large accelerations in the pilot and copilot region 

that contribute highly to the 2-norm. Qualitatively, the amount of deformation witnessed from 

posttest inspection of the subfloor is lower than the analytical predictions. To prevent early 

yielding and redistribution of loads, the range of probable keel beam thicknesses needed to be 

increased. This finding was also confirmed from the variance analysis shown in Figure 32. In 

here, the contribution of a single parameter variance to the total variance was computed to 

determine if parameters affected the response or not. In Figure 32, the sum total for the variance 

contribution of each parameter approaches one. From Figure 32, the parameter with the highest 

variance contribution immediately following belly impact (in red) is the keel beam thickness.

Figure 31. Uncertainty bounds for interim calibration cycle.

0 0.02 0.04 0.06 0.08 0.1 0.12 0.14 0.16

1000

1100

1200

1300

1400

1500

1600

1700

1800

Time (sec)

PV Bounds

Test

Upper Bound

Lower Bound

0 0.02 0.04 0.06 0.08 0.1 0.12 0.14 0.16

0

50

100

150

200

250

300

Time (sec)

PV Bounds

Test

Upper Bound

Lower Bound

No. Parameter Description Nominal

Upper 

Bound

Lower 

Bound

1 belly thickness (in) 0.09 0.12 0.08

2 keel beam thickness (in) 0.04 0.07 0.03

3 seat box thickness (in) 0.1 0.12 0.08

4 seat box bulkhead thickness (in) 0.05 0.07 0.03

5 Yield Stress (psi) 40,000 45,000 35,000 Acceleration 2-Norm Velocity 2-Norm
Development and Calibration of a System-Integrated Rotorcraft Finite Element Model for Impact 

Scenarios

48

Figure 32. Variance for interim calibration cycle.

Calibration runs were conducted with the keel beam thickness increased to a range of 0.10 to 

0.15 inches. A total of 60 LS–DYNA runs were performed using the newly defined keel beam 

parameter range, combined with four other parameters previously defined. Uncertainty bound 

results for acceleration indicate that the increase in keel beam thickness has shifted the peak 

acceleration response to align better with the test results. Results in Figure 33 indicate that, based 

on acceleration and velocity 2-norm, it is more likely that a set of parameters within the range 

established could reconcile the model with the test. 

Velocity

Time (sec)

Variance Contribution

Yield Stress

Seat Box Bulkhead Thickness

Seat Box Thickness

Keel Beam Thickness

Belly Thickness

Belly 

Impact
Development and Calibration of a System-Integrated Rotorcraft Finite Element Model for Impact 

Scenarios

49

Figure 33. Uncertainty bounds for final calibration cycle.

The spatially based metric M2 was used to perform orthogonality checks between the test and 

analysis basis vectors. Orthogonality results for the baseline set of parameters and parameters for 

Run #44 (of 60 runs), which is similar to the baseline but has a yield stress nearing the lower 

bound and a seat box thickness nearing the upper bound, are shown in Figure 34. The size of the 

orthogonality table is equal to the number of impact shapes chosen for both test and analysis, in 

this case n = 10. Basis vectors generated from acceleration time histories are compared for test 

and analysis; good agreement is indicated by the black and dark blue colors. The parameter set of 

Run #44 shows improved orthogonality for impact shapes 5 and 6. This does not imply that the 

selected case is optimal, but it does indicate that a slight change in these parameters can 

significantly alter the impact shapes. Because of time constraints and the fact that, with a model 

this complex, more component data was required, no additional calibration cycles were 

attempted. During this calibration phase, many problem areas of the model surfaced, but without 

additional data, they are difficult to correct. 

0 0.02 0.04 0.06 0.08 0.1 0.12 0.14 0.16

0

50

100

150

200

250

300

350

Time (sec)

PV Bounds

Test

Upper Bound

Lower Bound

0 0.02 0.04 0.06 0.08 0.1 0.12 0.14 0.16

1000

1100

1200

1300

1400

1500

1600

1700

1800

Time (sec)

PV Bounds

Test

Upper Bound

Lower Bound

No. Parameter Description Nominal

Upper 

Bound

Lower 

Bound

1 belly thickness (in) 0.09 0.12 0.08

2 keel beam thickness (in) 0.12 0.15 0.10

3 seat box thickness (in) 0.1 0.12 0.08

4 seat box bulkhead thickness (in) 0.05 0.07 0.03

5 Yield Stress (psi) 40000 45000 35000 Acceleration 2-Norm Velocity 2-Norm
Development and Calibration of a System-Integrated Rotorcraft Finite Element Model for Impact 

Scenarios

50

(a) Baseline.

(b) Run #44.

Figure 34. Orthogonality for final calibration cycle.

1 2 3 4 5 6 7 8 9 10

35.57

12.90

10.32

 6.98

 5.00

 4.05

 3.50

 3.31

 2.57

 2.25

Test LS-DYNA

MAC 

 

Frequency (Hz) 16.77 14.75 9.46 6.78 5.64 5.39 4.93 4.23 3.51 3.31

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

1 2 3 4 5 6 7 8 9 10

36.60

13.82

 8.92

 6.18

 4.74

 3.92

 3.49

 3.05

 2.84

 2.37

Test LS-DYNA

MAC 

 

Frequency (Hz) 16.77 14.75 9.46 6.78 5.64 5.39 4.93 4.23 3.51 3.31

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

Test

LS-DYNA

Test

LS-DYNA

Baseline

Run # 44

1 2 3 4 5 6 7 8 9 10

35.57

12.90

10.32

 6.98

 5.00

 4.05

 3.50

 3.31

 2.57

 2.25

Test LS-DYNA

MAC 

 

Frequency (Hz) 16.77 14.75 9.46 6.78 5.64 5.39 4.93 4.23 3.51 3.31

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

1 2 3 4 5 6 7 8 9 10

36.60

13.82

 8.92

 6.18

 4.74

 3.92

 3.49

 3.05

 2.84

 2.37

Test LS-DYNA

MAC 

 

Frequency (Hz) 16.77 14.75 9.46 6.78 5.64 5.39 4.93 4.23 3.51 3.31

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

Test

LS-DYNA

Test

LS-DYNA

Baseline

Run # 44
Development and Calibration of a System-Integrated Rotorcraft Finite Element Model for Impact 

Scenarios

51

UPDATED RESPONSES FOR CALIBRATED SYSTEM-INTEGRATED 

MODEL

Crash Test without DEA

The updated LSTC Hybrid III ATD FEM was calibrated using data from vertical drop tests (ref. 

17). The first modification performed was mesh refinement. With mesh refinement, the overall 

contact stiffness on the ATD was improved, and the noise present in the original vertical 

acceleration time histories was eliminated. In the original ATD model, several rigid parts in 

contact with the seat platform caused peak acceleration readings to rise above reasonable values. 

For this reason, the thighs, kneecaps, and feet in the ATD model were recharacterized using 

deformable material models. A layer of rubber shell elements was overwrapped onto the pelvis 

and upper thigh parts to represent the skin of the ATD. To represent the abdominal insert and to

restrict flailing of the ATD upon impact, linear springs were inserted between the ribcage and the 

pelvic insert. The spring stiffness was based on the effective material properties of the abdominal 

insert. Restraints were not incorporated back into the fully calibrated FEM because it was 

evident from test results that restraints were not significantly loaded during the initial impact and 

rebound. Restraints only became loaded during torso flail, which occurred well beyond the time 

duration considered here.

The fully calibrated MD-500 FEM with the updated ATD FEMs is shown in Figure 35 and 

consisted of approximately 590,000 elements in total. The calibrated set of values for the 

airframe FEM without the DEA is shown in Table 2. Of the five parameters, three remained 

close to the nominal value (belly thickness, keel beam thickness, and seat box thickness), while 

the seat box bulkhead thickness approached the upper bound, and the yield stress approached the 

lower bound. These changes are similar to the parameter change in Run #44.
Development and Calibration of a System-Integrated Rotorcraft Finite Element Model for Impact 

Scenarios

52

Figure 35. Final calibrated system-integrated FEM.

Table 2. Calibrated parameters.

No. Parameter Description Nominal Upper Bound Lower Bound Calibrated

1 belly thickness (in) 0.09 0.12 0.08 0.089

2 keel beam thickness (in) 0.12 0.15 0.10 0.12

3 seat box thickness (in) 0.10 0.12 0.08 0.11

4 seat box bulkhead thickness (in) 0.05 0.07 0.03 0.065

5 Yield Stress (psi) 40,000 45,000 35,000 35,210

The original approach of investigating individual acceleration time histories for calibration and 

validation had been set aside in favor of the uncertainty estimation, parameter sensitivity, and 

impact shape orthogonality approach. Nonetheless, it is worthwhile to revisit the time histories 

after modifying the model. The shape, duration, and magnitude of acceleration time histories 

remain important indicators when determining input pulses for seat certification or when 

evaluating occupant injury criteria such as Eiband, Dynamic Response Index, and Brinkley 

Index.

The vertical acceleration at the pilot floor is plotted in Figure 36. The overall pulse duration 

remains about 0.050 seconds. Note that the calibrated model shows a higher acceleration peak 

magnitude (60 g) than the original model (47 g) and better matches the test peak magnitude 

better (63 g). 
Development and Calibration of a System-Integrated Rotorcraft Finite Element Model for Impact 

Scenarios

53

Figure 36. Pilot floor vertical acceleration; crash test without DEA.

On the other hand, the passenger floor vertical accelerations are plotted in Figure 37. Although 

the analytical waveform shapes and duration agree well with the test, the peak magnitude of the 

original model was less than the test acceleration by 15 g. Thus, the increase in keel beam 

stiffness has caused an overcorrection in peak magnitude, from 30 g to 70 g. By treating the keel 

beam as one continuous property, the pilot–copilot region was calibrated properly, but the model 

behaves too conservatively when examining the passenger region. Hence, during calibration, the 

keel beam area should have been split into separate segments to adjust the areas independently.

-60

-40

-20

0

20

40

60

80

0 0.05 0.1 0.15 Acceleration (g)

Time (sec)

Test

Analysis-Original Model

Analysis-Calibrated Model

Filter: 60 Hz 

Butterworth
Development and Calibration of a System-Integrated Rotorcraft Finite Element Model for Impact 

Scenarios

54

Figure 37. Passenger floor vertical acceleration; crash test without DEA.

Figure 38 shows results for the vertical acceleration of the pilot pelvic area. To contrast, the 

original model shows a very high pelvic acceleration (140 g), while the calibrated model 

acceleration was reduced to 100 g. Despite all of the improvements within the ATD FEM, the 

analysis magnitude exceeds the test magnitude (42 g) by over a factor of two. For both the 

original and calibrated model, the acceleration spikes could be attributed to the pelvis and seat 

mesh contacting the seat pan. During posttest inspection, damage was plainly visible on the seat 

pan, suggesting that contact occurred. However, the spike in load is only evident in the analysis. 

More modifications are required in the LSTC ATD FEM, including further conversion of rigid 

components to deformable for instance, if results are to be reliably used to evaluate occupant 

injury.

-30

-20

-10

0

10

20

30

40

50

60

70

80

0 0.05 0.1 0.15 Acceleration (g)

Time (sec)

Test

Analysis- Original Model

Analysis- Calibrated Model

Filter: 60 Hz 

Butterworth
Development and Calibration of a System-Integrated Rotorcraft Finite Element Model for Impact 

Scenarios

55

Figure 38. Pilot pelvic vertical acceleration; crash test without DEA.

Crash Test with DEA

The pilot seat vertical accelerations are plotted in Figure 39. The responses for the original and 

calibrated model are similar in shape and magnitude, with load limiting crush performance of the 

DEA near 10 g. However, the calibrated model does capture the abrupt rise in acceleration at the 

end of the pulse. This behavior was not seen with the original model. The stiffening of the 

subfloor, specifically the keel beam, allowed the compaction phase of the DEA crushing to be 

transmitted into the cockpit. Similarly, the passenger floor vertical accelerations in Figure 40

also reveal a rise in loads near the end of the pulse. 

As shown in Figure 41, the calibrated ATD shows improvements in pelvic vertical acceleration 

predictions, not unlike the ATD results for the crash test without DEA. The pulse shape is more 

flattened and loads are reduced from 25 g to 18 g. Nevertheless, the differences are still 

significant, and the accuracy of the ATD model is still questionable.

-40

-20

0

20

40

60

80

100

120

140

160

0 0.05 0.1 0.15 Acceleration (g)

Time (sec)

Test

Analysis- Original Model

Analysis- Calibrated Model
Development and Calibration of a System-Integrated Rotorcraft Finite Element Model for Impact 

Scenarios

56

Figure 39. Pilot floor vertical acceleration; crash test with DEA.

Figure 40. Passenger floor vertical acceleration; crash test with DEA.

-5

0

5

10

15

20

0 0.05 0.1 0.15 0.2 Acceleration (g)

Time (sec)

Test

Analysis-Original Model

Analysis-Calibrated Model

Filter: 60 Hz 

Butterworth

-5

0

5

10

15

20

0 0.05 0.1 0.15 0.2 Acceleration (g)

Time (sec)

Test

Analysis-Original Model

Analysis-Calibrated Model

Filter: 60 Hz 

Butterworth
Development and Calibration of a System-Integrated Rotorcraft Finite Element Model for Impact 

Scenarios

57

Figure 41. Pilot pelvic vertical acceleration; crash test with DEA.

-10

-5

0

5

10

15

20

25

30

0 0.05 0.1 0.15 0.2 Acceleration (g)

Time (sec)

Test

Analysis

Analysis- Calibrated Model

Filter: 60 Hz 

Butterworth
Development and Calibration of a System-Integrated Rotorcraft Finite Element Model for Impact 

Scenarios

58

CONCLUDING REMARKS

Two full-scale helicopter crash tests, sponsored by the NASA Subsonic Rotary Wing Program, 

were conducted in an effort to evaluate new structural concepts to improve rotorcraft 

crashworthiness and to increase occupant survivability. In the first test a helicopter was fitted 

with a Deployable Energy Absorber (DEA) system, and the second test was conducted without 

the DEA. The tests demonstrated a peak acceleration reduction upon impact by a factor of three 

when using the DEA. 

A system-integrated finite element model for simulating rotorcraft crashworthiness was

developed and correlated to the tests. Component level analyses and tests were conducted to 

establish the material properties of the DEA, the crush tube shock struts, and the seat mesh. 

Full-scale mass simulator tests were conducted to develop confidence in both analysis and test 

methodologies and to reduce risk. Good agreement for skid gear strains and center of gravity 

accelerations was seen between the test and the analysis. 

Acceleration time histories at the pilot and passenger floor were compared to analysis for both 

crash tests. Agreement in acceleration magnitudes and pulse duration was seen between the test 

and the analysis for the crash test performed with the DEA. The acceleration waveforms and 

peak values were significantly different between the test and the analysis for the crash test 

performed without the DEA. One reason for this discrepancy is the fact that acceleration levels 

for the test with the DEA were significantly lower and, therefore, less energy went into 

deforming the fuselage. Consequently, model fidelity played less of a factor for the test with the 

DEA.

LS–DYNA model calibration was performed based on two new calibration metrics: (1) a 2-norm 

velocity bound metric, and (2) orthogonality of test and analysis impact shapes. Results with 

metric 1 were used to assess the probability of reconciling the test with the analysis after 

uncertainty propagation studies. Calibration parameters were selected or removed based on the 

results of metric 1. Orthogonality plots were used to determine if certain parameter sets produced 

better spatial agreement and clarified stiffness disparities for critical components. Results from 

this effort highlighted model deficiencies that were unexplainable without additional component 

data. 

The FEM of the airframe was validated by comparing acceleration time histories for the pilot and 

passenger regions following calibration. One key outcome of the calibration was the stiffening of 

the subfloor, particularly along the keel beam. Waveforms magnitudes and shapes were 

improved from the baseline models and relative error was reduced for both crash tests. The FEM 

of the ATD used in this study is not valid when computing internal forces such as pelvic 

acceleration and lumbar load, and improvements in the LSTC FEM detail are necessary. 

Several lessons learned from this effort should be considered in the future when conducting tests 

for the purpose of calibrating analytical models. First, the sensor suite must cover all critical 

components and should be mounted on relatively stiff components to avoid high frequency 

saturation of the acceleration output. Second, the accelerometers should be calibrated to ensure 

their velocity integration is accurate. Third, multiple validation metrics should be applied 

between the test and the analysis, which comprehensively identify modeling deficiencies, 
Development and Calibration of a System-Integrated Rotorcraft Finite Element Model for Impact 

Scenarios

59

evaluate parameter importance, and propose required model changes. Finally, when dealing with 

very complex structures, a building block approach to model calibration will help break up the 

problem into more manageable subsystems. The objective of certification by analysis cannot be 

achieved practically without methodologies established similar to those discussed here. 
Development and Calibration of a System-Integrated Rotorcraft Finite Element Model for Impact 

Scenarios

60

REFERENCES

1. Jackson, K., Kellas, S, Horta, L. G., Annett, M. S., Polanco, M. A., Littell, J. D., and 

Fasanella, E. L., "Experimental and Analytical Evaluation of a Composite Honeycomb 

Deployable Energy Absorber," NASA/TM–2011–217301, November 2011.

2. Anonymous, Military Standard, MIL–STD–1290A (AV), Light Fixed- and Rotary-Wing 

Aircraft Crash Resistance, Department of Defense, Washington DC, 20301, 26 September 

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Development and Calibration of a System-Integrated Rotorcraft Finite 

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