[American Institute of Aeronautics and Astronautics 53rd AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics and Materials Conference20th AIAA/ASME/AHS Adaptive Structures Conference14th

American Institute of Aeronautics and Astronautics

1

Analysis and Test Validation to Develop Mars Science

Laboratory EDL Loads – Mobility Deploy Event

Christopher V. White1, Chia-Yen Peng

2, Shyh-Shiuh Lih

3

California Institute of Technology, Jet Propulsion Laboratory, Pasadena, CA, 91109

George Antoun4 and Jeffery Tippmann

5

ATA Engineering, San Diego, CA 92130

The Mars Science Laboratory mission will use the Skycrane maneuver at the end of the

Entry Descent and Landing sequence to gently deliver a 900kg rover to the surface of Mars.

In the final few seconds of that maneuver, the spacecraft will undergo two simultaneous

deployments, that of the rover below the rocket controlled descent stage, and the deployment

of the rover’s mobility system. This coupled deployment phase is the source of driving loads

on both the rover deployment mechanism (the Bridle Umbilical Device) and on the mobility

system. This paper describes the deployment scenario in detail, describes the computational

models used to predict the loads, discusses key results and sensitivities in the predicted load,

and describes the experimental model validation program. This work presents a successful

attempt to employ both deterministic and statistical loads prediction approaches for this

complex process, and calls attention to the importance of accurately capturing load path

details in joints. Judged from an overall perspective, the loads model was most successful

for predicting loads and speeds in the Bridle Umbilical Device, and had the most difficulty

predicting loads throughout a redundant load path in the suspension system.

Nomenclature

MLE = Mars Lander Engines

GNC = Guidance, Navigation and Control

EDL = Entry, Descent & Landing

MSL = Mars Science Laboratory

RDP = Rocker Deploy Pivot

CDP = Center Differential Pivot

MDP = Main Differential Pivot

DTM = Developmental Test Model

V&V = Verification and Validation

I. Introduction

he Mars Science Laboratory Mission (MSL) was successfully launched on Nov 26, 2011 from Space Launch

Complex 41 on Cape Canaveral Air Force Station in Florida aboard an Atlas V. The mission will touchdown in

Gale Crater in the equatorial region of Mars on August 5, 2012. The scientific goal of the mission is to determine

whether Mars ever was, or is still today, an environment able to support microbial life. The mission features

“Curiosity”, a 900kg 6-wheeled rover that will traverse the Martian surface. Among the innovative technologies

employed on the mission will be the Skycrane landing maneuver1,3,7

, a rocket controlled soft-landing maneuver that

will land the rover using its own wheels as the landing gear. The EDL (Entry, Descent and Landing) timeline is

shown in Figure 1.

1 Senior Mechanical Systems Engineer, Entry, Descent & Landing. M/S 303-410, Senior Member AIAA

2 Principal Engineer, Spacecraft Structures and Dynamics

3 Senior Engineer, Instrument Systems, Advanced Technologies Group

4 Project Engineer, Aerospace Analysis Group

5 Engineer, Aerospace Analysis Group.

T

53rd AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics and Materials Conference<BR>20th AI23 - 26 April 2012, Honolulu, Hawaii

AIAA 2012-1392

Copyright © 2012 by the American Institute of Aeronautics and Astronautics, Inc. The U.S. Government has a royalty-free license to exercise all rights under the copyright claimed herein for Governmental purposes. All other rights are reserved by the copyright owner.

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Figure 1 MSL's Entry, Descent & Landing sequence, illustrating the mission’s Skycrane landing concept.

This paper will describe the program for computing and test-validating the mechanical loads occurring during

the two-body Rover Deploy phase of the EDL segment. The ideas described in this paper are significant in the way

they have allowed the project to meet the challenges of various mechanical system interactions occurring during the

Skycrane phase of EDL. The ideas involve application of system engineering methods, multi-body dynamics

models and simulations, and multiple tests on full-scale flight-like hardware.

The particular challenges dealt with in this paper result from the simultaneous, gravity-driven deployments of the

rover itself and the rover’s mobility system while tethered to the rocket-powered Descent Stage. The resulting

mechanical configurations occurring during the deployment event are dynamic, geometrically nonlinear, time-

variant, and highly coupled to one another. Despite the high level of coupling between the mechanical elements, the

Skycrane design architecture effectively renders these mechanical events only loosely coupled to the GNC

subsystem and to the Martian environment.

The work reported in this paper has three objectives: 1) to establish best methods for predicting the flight limit

loads, 2) to update and validate the loads models by leveraging the MSL structural verification test program and 3)

to the illustrate the accuracy levels of the models by comparison to test measurements.

II. The Mobility Deploy Scenario

Mobility Deploy is a mechanically complex configuration

change whose function is to un-stow the mobility system to

become the rover’s landing gear. The mobility deploy event is

initiated while the rover is separating from the descent stage,

and completes a fraction of a second before the touchdown

event takes place. The entire Skycrane process depicted in

Figure 1 is performed under closed-loop control by the GNC

subsystem. The goal of GNC in this phase of EDL is to

descend at a constant vertical rate of 0.75 m/s while

maintaining a stable platform for the rover to deploy and

ultimately touchdown. Figure 2 shows the rover and descent

stage coupled together in the Powered Descent Vehicle

configuration. Figure 3 shows the principal parts of Curiosity’s

mobility system.

Figure 2 The MSL Powered Descent

Vehicle.

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Figure 3 The MSL mobility system, a rocker-bogie

design with an external differential.

Figure 4 The Bridle Umbilical Device (BUD),

showing the conical spool, electromagnetic brake,

triple bridle, confluence pulley, and rover-

mounted bridle exit guides.

Note that in Figure 3 the mobility system is shown in the ‘deployed’ configuration, while in Figure 2 it is shown

in the ‘stowed’ configuration. With reference to Figure 3, the stowed configuration is achieved by a multi-step

process. In step one, the four corner wheels are steered to a preferred direction. In the second step, a pyro pin is

engaged on the rover top deck to restrain rotation of the central differential pivot. In step three, the forward bogies

are rotated up around the bogie pivot to connect a fitting near the mid-wheel to a fitting on the aft rocker. The

connection is made with a cup-cone feature and a 3/8” separation bolt. Step four rotates the four rockers about the

RDP (Rocker Deploy Pivots) so that the four corner wheels can be connected to the corners of the chassis, with 5/8”

separation bolts. A final step in achieving the PDV configuration is to connect the descent stage with the rover by

means of three 5/8” diameter separation bolts. Also in this final step, the three bridles, which are wound around the

Bridle-Umbilical Device (BUD) spool, are attached to the rover.

The BUD, shown in Figure 4, is a passive electromagnetic braking device whose function is to control the speed

of rover deployment under the descent stage. The spool and brake are attached to the Descent Stage, and the bridles

route over the confluence pulley and terminate on slack take-up devices mounted to the rover top deck. In the

Powered Descent Vehicle configuration, the bridles are wound tightly around the spool, but dressed with a small

amount of slack in each bridle. The bridle slack is purposely built into the system to help ensure a clean separation

from the descent stage. As the rover is pulled away under gravitational acceleration, the force in the bridles turns

the spool, thus engaging the electromagnetic brake. The end of the bridles are firmly anchored to a lug in the bridle

spool, so when the bridles have fully spooled off at the end of the deployment, there is a ‘snatch load’ as the load

path no longer goes through the braking device. The entire rover deployment under the BUD takes about 5 seconds.

The Mobility Deploy event is initiated during the rover deployment, and is essentially a reverse of the process

used to stow mobility: first, the aft rockers are released, followed by the forward rockers 125ms later. The bogies

are released at the mid-wheel restraint 6 seconds after rover separation. The final release is the central differential

pin and this takes place 0.25s prior to the earliest possible touchdown. The wheels are not re-steered for touchdown.

The driving force for mobility deploy is also acceleration, but the acceleration is dependent on the difference

between gravity and the acceleration of the rover as controlled by the BUD. The mobility deployment is not

actuated in any way and does not have a brake.

One very significant feature of the system architecture described above is that the two uncontrolled mechanical

deployment (BUD and mobility) occur in parallel. Simultaneous deployment events generally should be avoided,

and this architecture was not a first choice, but became a necessity during system design due to a tight timeline

throughout EDL. Alternative architectures that decoupled these deployments presented other difficulties and were

not acceptable. The next section of this paper describes several of the many challenges for loads prediction that are

imbedded in this mobility deployment scenario.

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III. Mobility Deploy Loads Environment

The discussion begins with a description of the mobility latch-up load path and the importance of event timing.

The discussion continues with a description of the redundant load path, and concludes with a discussion about the

importance of rover kinematics as part of the loads process.

As a rocker is released, it pivots about the RDP (Rocker Deploy Pivot) through an angular arc of approximately

50 degrees. The pivot axes are also canted with respect to the horizontal, so as the rocker pivots, it is sweeping

down and out. At the end of travel, a feature on the rocker fitting impinges on a hardstop, while a latch drops down

over a tooth to prevent backwards rotation due to rebound. This is illustrated in Figure 5. There is a built-in

rotational gap of several degrees between the hardstop and tooth-latch for each rocker. The hardstop which arrests

the motion is connected directly to the differential mechanism, so as the rocker hits the hardstop and latches, the

load travels through the RDP shaft and up through the differential system – the vertical swing arm, the adjustment

link, and the horizontal swing arm (Figure 3). The load is reacted out at the CDP in both a fore-aft shear component,

and due to the pyro pin that the restrains rotational motion at the central differential pivot, a moment is reacted out.

Simultaneous with the torque and fore-aft shear on the RDP shaft caused by the hardstop load, there is a substantial

vertical shear component, and a smaller but still significant lateral shear and moment about a vertical axis. In an

effort to minimize the RDP loads, the rockers are released in such a way that on each side of the vehicle, the fore

and aft rockers have the best chance to engage the hardstops at precisely the same instant. This way, minimum load

goes into the differential assembly. If deployments on both sides are likewise coordinated, then the small load from

each side that does go into the differential balances around the pivot and the moment at the central differential pivot

vanishes. This balancing strategy relies on having well-controlled latch-up times for the four latching rockers.

Tooth Latch

Hard

Stop

Figure 5 A cross section through the deployed and

latched Rocker Deploy Pivot. The red fitting

attaches the forward rocker; the green fitting the aft

rocker.

Figure 6 A view of the forward bogie in the stowed

configuration, highlighting the redundant load path

through the mid-wheel restraint. (Wheel removed for

clarity

When the latch-up loads are not balanced, the impulsive loads will cause the chassis to translate and rotate. The

chassis motion in turn influences the latch up times of the unlatched rockers. Generally speaking, any disturbance

which causes the chassis to pitch and roll during mobility deploy will influence the latch up timings. The initial

slack in the bridles is one example of such an influence. A different but related influence on latch-up timing is the

constraint placed on the rocker release times by the avionics system. The timing of successive mobility restraint

releases (pyro firings) must be no less than 125ms and must be commanded on 125ms spacings.

Another relevant feature of mobility deploy is the redundant load path that exists prior to deploying the bogie, as

shown in Figure 6. Load sharing between the rocker and bogie is determined by the degree of restraint provided by

bogie pivot at one end, and the cup-cone mid-wheel restraint on the other end. It is difficult to know how effective

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this load sharing is, due to tolerances in the pivot, to the compliance of associated brackets, and to the degree of

fixity provided by the cup-cone interface.

Rover kinematics and specifically, the pose of the mobility system is a significant concern for the mobility

deploy event. Because touchdown can occur anytime within a window of 9 to 17 seconds after rover separation, the

time allocated for completing the rover and mobility deploy events is 9 seconds. Upon completion of the

deployments, the rover must be ‘Ready For Touchdown,’ which requires that the rover kinematic states of pitch,

roll, pitch rate, roll rate, yaw rate and mobility system pose are within allowable limits. Limits on these states were

established to assure the rover would survive the loads and overturning moments generated by touchdown.

Explicitly stating limits on the Ready for Touchdown state vector formed a convenient interface between touchdown

and mobility deploy, decoupling the two events so they could be worked on in parallel or by different models. The

most challenging problem of meeting the Ready for Touchdown states was ensuring that the bogies were not

swinging with excessive amplitude at the opening of the touchdown window. The solution to this problem will be

discussed later in the paper.

IV. Loads Model Development

The commercial multi-body dynamics software ADAMS6 (Advanced Dynamic

Analysis of Mechanical Systems) was chosen as the loads prediction platform.

The mobility deploy ADAMS model consists of four major components: the GNC

subsystem, the descent stage, the BUD (bridle-umbilical device) and the rover.

Each of these elements is described below. Major sources of uncertainties in each

model are also identified throughout the discussion, and the model was constructed

so that uncertainty quantification could be performed by dispersing these

uncertainties.

The Descent Stage (DS) is a relatively stiff structure with vibration modes

safely above the bandwidth of the controller, and with relatively benign flight

loads during the skycrane maneuver. As such, the structure has been modeled as a

rigid body with mass properties prescribed and held fixed throughout the

simulation. The statistical uncertainties of the DS mass properties were accounted

for.

As described in Ref. 2, the GNC subsystem was approximated by simply

suspending the DS from a vertical spring and dashpot connected to ground. The

spring and dashpot parameters were tuned to achieve an optimal match to the

transfer function of the closed loop controller. The constant velocity of the vertical

descent was achieved by prescribing the ground as a moving boundary. An

identical treatment was used for lateral motions. Uncertainties on the horizontal

and vertical velocities were included, but the spring and dashpot values were not

considered random variables.

Bridle payout length, and therefore the BUD speed, is represented in ADAMS

by a series of 2nd-order differential equations that incorporate the time-dependent variations in spool radius and

bridle angle, using spool and brake angular displacements as the primary variables. These equations are explicitly

written into the ADAMS model using the command language syntax, and are internally and automatically appended

to the system equations of motion. Bridle stiffness is a variable quantity throughout the rover deploy event, and is

assigned a value at each integration time point from a lookup table based on the instantaneous bridle length.

Temperature effects on bridle stiffness are significant throughout the -135C to +50C temperature range, and was

accounted for in the simulation by applying a scale factor of between 0.45 and 1.92 to the nominal +23C stiffness

value. Nonlinear load-dependent stiffness was accounted for in a simplified way by using the tangent stiffness

corresponding to the load in the bridles due to rover self-weight. Load hysteresis effects in the bridles were not

modeled explicitly. Uncertainty was accounted for in the BUD model by creating random variables for bridle

stiffness temperature effects, brake drag coefficient, and initial uniform and differential bridle slack.

Figure 7 View of the

mobility deploy ADAMS

model.

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The rover loads model consisted of a rigid chassis,

and a flexible and articulating mobility system (Figure

7). Chassis mass properties were explicitly assigned,

and uncertainties in all mass properties are accounted

for in the model.

The mobility system model is comprised of flexible

beam elements, lumped masses, and joint elements with

kinematic constraints. Flexible (BEAM) elements were

used both to capture compliance in the load path and

also as a means to introduce nodes (MARKERS) for

load recovery. The BEAM section properties were

computed from cross sectional areas of the members,

and in the case of the suspension tubes and the

horizontal and vertical swing arm, several elements

were used along the length. The articulating joint

elements were refined with normal-force friction

models, compliance, rotational dead zones, and

nonlinear hardstop springs with energy dissipation parameters.

Finite element analysis was used to estimate stiffnesses of some piece-parts or assemblies, in particular the latch,

tooth, and hardstop elements shown in Figure 5. A scalar stiffness value for these contacts was estimated using unit-

load analyses on the detailed stress FEM. The mid-wheel restraint fitting (Figure 8) is another example of where

finite element analysis was used. In this case, the compliance of the aft rocker RDP fitting was the dominant

compliant element, and its stiffness to unit loads imposed at the cup-cone interface was estimated using FEM. The

implementation in ADAMS was as a diagonal BUSHING element.

The dominant uncertainties in the mobility subsystem model were the friction coefficients in the rotational joints

and the restoring force levels provided by the constant force spring at the bogie pivot.

V. Flight Limit Load Generation

A. Monte Carlo Analysis

Statistical distributions were assigned for each of the uncertainties discussed above. Most variables were

assigned a uniform distribution within their ranges, but Gaussian distributions were used for the vertical and

horizontal skycrane velocities because the character of these errors could very reasonably be modeled as Gaussian.

Monte Carlo simulations were run by using a JPL in-house pre-processor to sample from the distributions and

generate the entire set of ADAMS input files. ADAMS was then run in batch mode on each of the input files. By

computing the statistical properties on the output quantities – peak bridle load for example- it could be determined

when a sufficient number of simulations had been run. The decision was based on the width of the 95% Confidence

Interval for the 99 percentile of load. When that interval width was small enough, typically about 1% to 2% of the

estimated 99%-ile value, the runs were stopped. The confidence interval was estimated using the non-parametric

Bootstrap method.

Output load time histories were saved to disk for each simulation. Upon completion of the runs, the time history

data files were read by a post-processor and sorted for each load component according to peak magnitude.

Typically, the simulation providing the closest value to the 99% load magnitude was selected for additional

processing and stress analysis. Rather than use time-consistent loading in the stress analysis, the other load

components at the same recovery point were reported with their max or min values within a 300ms window centered

on the time at which peak load occurred for the ‘main’ load component. The 300ms number is related to the period

of the dominant frequency in the deploy loads. Spreadsheets containing the design loads for each load component

were provided for piece-part stress analysis.

B. Selected Results

1. Bogie Settling Time

One of the first difficulties to be overcome for mobility deploy was that the rocker release and latch-up caused

the chassis to oscillate in pitch, which coupled to the swinging of the bogies after they were released. The bogie

swinging motions persisted in time such that when the touchdown window was entered 9 seconds after rover release,

the bogies had still not settled to within the required 5 degrees. In fact, preliminary simulation results show in Table

Collar

Catch Cup

RDP

Elbow

Cone Bracket

Catch Lid

Bogie Extension

Figure 8 Partial exploded view of the mid-wheel

restraint hardware.

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1 indicate that the 99%-ile bogie angle was 25.4 degrees at the opening of the touchdown window. Many solutions

to this problem were studied, including use of a bogie ‘deploy leash’, adding a damper to the bogie, small changes to

bogie release timeline, reliance on small inherent damping in bridles, and several others.

The solution to the bogie oscillation problem came from a statistical analysis which included the definition of the

touchdown window. First, the statistical distribution of the number of cases of ‘bogie not settled’ as a function of

time was created. Likewise, the touchdown window boundaries were actually the products of a statistical analysis of

errors related to landing radar performance, navigation error, and landing slope. In other words, the moment of

touchdown was a random variable with a 3-sigma low time value of 9 sec. The real likelihood of bogie not being

settled at touchdown was actually the convolution of the likelihood of touching down early and the likelihood of the

bogie not being settled at the opening of the window. The integral of the product of these two probabilities was

approximately 0.02% (Figure 9). As a result no corrective action was deemed necessary.

Table 1 Summary of preliminary 99%-ile responses

at the opening of the touchdown window 99th Percentile of Baseline Skycrane Monte Carlo Sim. Updated Skycrane Monte Carlo Sim. Current "Box" of

Ready-for-TD States 2000 Runs 2000 Runs Ready-for-TD States

Pitch Angle (deg) 5.7 5.8 6.0

Roll Angle (deg) 4.9 4.4 6.0

Pitch Rate (deg/sec) 15.4 14.8 25.0

Roll Rate (deg/sec) 14.8 13.5 25.0

Bogie Pose Angle (deg) 25.4 25.4 15.0

Rocker Angle (deg) 5.4 5.6 10.0

Probability that the

bogies are not settled

Probability of

Touchdown

Surface Slope

Figure 9 Probability estimates for bogie settling time

(blue) and moment of first contact (red) as a function

of time.

2. Rocker Deploy Timeline & Bridle-Umbilical Device Loads

A representative BUD torque curve is shown in Figure 10. The rising then falling nature of the torques is seen in

the figure. Startup transients are a result of sudden load application, and have greater amplitude with increased

bridle slack. Small black markers on the curve at the 3s time represent the release of the rockers, and the small blue

markers represent the 4 individual rocker latch-up times. It is clear from this curve that mobility deploy loads are a

significant load event for the BUD. In the example shown, the latch-up impulse is timed late enough so that the

additional mobility torque roughly equals but does not exceed that due to rover deploy alone.

The acceleration environment of the rover during BUD deploy is shown in Figure 11. As can be seen, a rocker

release timed 3s after rover separation occurs in a regime of maximum chassis braking. Ultimately, as a means to

mitigate mobility deploy loads, the rocker release was moved earlier in time to release 0.7s after rover separation.

Simulations show reduced loads throughout the mobility subsystem, and BUD torques and speeds within hardware

capabilities.

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0 0.5 1 1.5 2 2.5 3 3.5 4 4.5 5-50

0

50

100

150

200

250

300

350

Time (s)

BU

D T

orq

ue

(N

-m)

BUD Torque

Figure 10 Typical BUD torque curve showing torque

disturbances due to mobility deploy.

Figure 11 Envelope of rover accelerations (at center

of mass) while deploying under BUD.

3. Effects of latch-up timing on mobility deploy loads

Sensitivity studies were performed to determine the effect on loads of a timing delay between release of aft and

forward rockers, as shown in Figure 12. The baseline release time delay is 125 ms. Trends in this figure show that

delaying the forward rocker release would result in higher loads in the horizontal swing arm, vertical swing arm, and

the central differential pivot, but would actually decrease the loads in the rockers themselves.

Although the rocker release time is a design parameter (in 125 ms increments), it is the actual latch-up timing

difference which more directly influences the load. These two timings will be different due to chassis linear and

rotational accelerations in the time interval between release and latch up, as well as due to the differing rotational

inertias of the forward and aft rockers. Figure 13 illustrates results of one set of Monte Carlo simulations where the

actual time lag between latch-up for the forward and aft rockers has been plotted against structural margin for the

horizontal swing-arm. The Nominal data point represents having random variables take on their mean values. This

data illustrates that having a balanced latch-up would minimize loads in the differential, but perhaps more

importantly, highlights that the system is sensitive to latch-up delays on the order of only 10 ms.

Effect of Aft/Fwd Rocker Release Timing

-0.25

0.00

0.25

0.50

0.75

1.00

1.25

1.50

0.120 0.130 0.140 0.150 0.160 0.170 0.180

Lag btwn Aft/Fwd Rocker Release, sec

Min

Marg

in

CDP Shear Mrgn

CDP Moment Mrgn

Min VSA Mrgn

Min HSA Mrgn

Min Fwd Rckr Mrgn

Min Aft Rckr Mrgn

Min Fwd Rckr Riv Mrgn

Min Aft Rckr Riv Mrgn

Min Bogie Riv Mrgn

Figure 12 Effect on structural margins of a timing

delay between aft and forward rocker release time.

Figure 13 Effect of delay in rocker latch time on the

horizontal swing arm structural margin.

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VI. Test Validation of Models

A systematic Model Verification and Validation program provides increased confidence in the accuracy of

model predictions. The V&V program for the models described in this paper fits within the broader context of both

model V&V across the entire MSL mechanical system, and the hardware V&V program. Selected aspects of the

mechanical system V&V program - as it relates to mobility deploy - will be described in this section, and key

validation tests results will be presented to illustrate the predictive accuracies achieved.

As defined in Ref 4, model verification is the process of gathering evidence to establish that the computational

implementation of the mathematical model and its associated solution are correct, whereas model validation is the

process of determining the degree to which a model is an accurate representation of the real world from the

perspective of the intended uses of the model.

Verification activities which were carried out because of their high value for the ADAMS model include the

following: careful documentation and management of model and simulation parameters through a Configuration

Control Spreadsheet held by the mechanical system engineer; review and documentation of the location and

coordinate system orientations for all output requests in the model; checks of model solutions for unit loads, gravity,

and eigenvalues; solution convergence checks for time

histories of a number of response quantities; automated

searching of ADAMS solution message files to check for

run-time anomalies during batch solution; review of the

model by an MSC.ADAMS senior consultant and code

developer to check model implementation practices and

advise on techniques for solution robustness. An example

of a convergence check is shown in Figure 14.

Model validation for mobility deploy followed a

hierarchical structure. Component and assembly tests

provided ranges of values for parameters such as drag

coefficients and stiffnesses. Subsystem tests on BUD and

mobility provided additional parameter values, and

provided a chance to tune models under optimized

boundary conditions and environmental factors. The final

validation opportunity for the model predictions was

provided by a single deployment test at the Mechanical

System level.

The mechanical tests were based on dedicated test

models (DTM) of Descent Stage, BUD, and Rover, built to

the same mechanical specifications as the flight hardware.

The need to minimize mass on the flight unit resulted in

waiving the standard Earth testability requirement. As a

result of the waiver, all mobility deployments had to be

carried out in a light-weighted configuration with the

wheels and actuators removed. Torque balances about the

bogie pivot require a mass at the mid-wheel to deploy the

bogie. Figure 15 shows the DTM rover moments before a

mobility deploy test.

Four tests of most relevance are described next: a) the Bogie Release Test, b) the Suspension Static Load Test, c)

the Mobility Deploy Tests, and d) the Skycrane Full Motion Drop Test (SFMDT). Model validation for the BUD as

a subsystem is not covered here. A thorough treatment of the BUD V&V program can be found in Ref 5.

A. Bogie Release Tests

The Bogie Release Tests allowed the correlation of the bogie joint constant-torque spring forces and bogie center

of mass. Fixed boundary conditions were imposed by mounting the DTM rover on the assembly cart, as shown in

Figure 16. Using masses of various sizes attached to the mid-wheel hub, the bogie was released and deployed while

a resolver recorded the bogie angle. Initially poor agreement of the model lead to scrutiny of the input mass

properties for the bogie assembly. Indeed, it was determined that the bogie assembly center of mass was incorrect

by 32mm. Once the mass values were corrected, slight changes to the modeled constant torque force value resulted

in excellent agreement with test data, Figure 17.

Figure 15 The MSL DTM rover (with wheels

and actuators removed) about to undergo

mobility deploy testing.

Figure 14 Showing convergence of CDP Shear

Force as a function of ADAMS integrator

settings.

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Figure 16 DTM rover mounted on assembly cart and

undergoing Bogie Release testing.

Figure 17 Bogie deploy time history from the test

setup of Figure 16, showing test/analysis agreement.

B. Suspension System Static Test

The structural capability of the suspension assembly was test-verified in a static load test program. The RDP

latch and tooth elements were in the primary load path in one of the load cases tested, as shown in Figure 18. Test

measurements were made of the applied load and the displacement of the load application point. Initial estimates of

the stiffness in the model were too low, and significantly over predicted the test measured deflection. The model

latch-tooth stiffness was increased by several orders of magnitude, resulting in the test/ADAMS agreement shown in

Figure 19. Further fine tuning of the latch-tooth stiffness was left for the correlation to the dynamic mobility

deployment test data. In this case, the static test measurements and model update were performed prior to

estimating the stiffness by FEM, so the FEM stiffness estimates were used for comparison to the already tuned

values.

C. Mobility Deployment Tests

Three verification and validation tests were carried out on the DTM rover to demonstrate the mobility deploy

functionality. Test 1 was a functional proof-of-concept test where the rockers and bogies were deployed but due to

an instrumentation error, no data was collected. Test 2 and test 3 were mostly identical with the exception of rocker

release timing: Test 2 fired the rocker separation bolts at symmetric port-starboard timings, while Test 3 had a 30ms

port-starboard timing delay to purposely increase the moment at the central differential pivot. In the context of

model validation, Test 2 was used to perform final correlations on the model, and Test 3 served as a validation

opportunity.

Boundary conditions consisted of statically suspending the rover from three long and soft nylon bridles. These

bridles were softer than the flight bridles to avoid a possible slack condition. With reference to Figure 20, the rover

was instrumented with bridle load cells, resolvers at mobility pivots, an inertial-measurement unit (IMU) to capture

chassis dynamics, a collection of over 50 strain gages, and a pair of pyroshock accelerometers mounted on the

hardstop of the RDPs to capture to latch-up events with high resolution. Strain gage, resolver, and load cell data was

collected at 1 kHz, IMU data at 400 Hz, and pyroshock data at 100 kHz.

Figure 18 Overhead illustration of Load Case 1 of the

Suspension Static Test.

Applied Force vs Disp

0

200

400

600

800

1000

1200

0 1 2 3 4 5 6 7Disp, in

Ap

plie

d F

orc

e, lb Test

Adams

Figure 19 Test/analysis agreement of Force-

displacement from Suspension Static Test data.

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Time-history waveforms of predicted

force/moment responses were compared to the test-

measured quantities. The model predictions were

based on best-estimates of parameter values, i.e.,

uncertainties were not accounted for in the model

predictions. After studying the ADAMS/test

comparison, various model parameter updates or

topological changes were implemented and the

test/analysis comparison was iterated.

Although several major model updates were

implemented as a result of the correlation process with

Test 2 data; the most significant modeling updates

were made to the RDP. It was evident that the

modeling shortcut of using a single BISTOP element

to model both the latch-tooth stiffness and the lower

hardstop stiffness was not acceptable, so the single

BISTOP was split into two elements to allow

independent tuning of their properties. Rotational

compliance in the RDP, about an axis perpendicular to

the main axis of rotation, also had to be added to the

model. An analogous rotational compliance was also added to the bogie pivot. The previous model of coulomb and

viscous friction at the pivots was replaced by a normal force kinetic friction model. The coefficients of friction for

the forward and aft rocker arms on the RDP joint were independently tuned to achieve the correct rocker arm latch-

up times. An example of the quality of the tuned model predictions is provided in Figure 21.

Figure 21 Comparison of test/analysis data from mobility deploy test 2.

Test 3 featured a 30 ms port-starboard staggered rocker release time. Without further tuning of the model, the

peak loads were compared test to analysis, and summarized in Table 2, and shown in Figure 22. The peak rocker

moments and bogie moments in the dominant directions agreed to within 16% (with one exception); the adjustment

link loads and CDP moment agreed within 6%, again with one outlier. When looking at peak loads in the secondary

load directions, errors up to about 50% of the load were noted. The area of the model with the greatest uncertainty

was the dual load-path region highlighted in Figure 6. The stiffness of the mid-wheel restraint computed by FEA in

the axial direction of the tubes is low enough to effectively decouple the two components of the dual load-path;

however, the test data suggested a much higher degree of axial load-sharing between the aft rocker and the forward

bogie. Additionally, the symmetric mobility deployment test data showed significant asymmetry in the two forward

bogie axial responses that could not be replicated with the model.

a)

b)

Mobility Strain Gages (port/stbd mirror)

Resolvers

Bridle Load Cells

IMU

Figure 20 Partial map of sensor locations used in the

mobility deploy tests.

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Table 2 Summary of test/analysis comparisons of peak loads

for mobility deploy Test 2 and Test 3

Figure 22 A sample of test/analysis time history comparisons for mobility deploy Test 3

a)

b)

c)

d)

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D. Skycrane Full Motion Drop Test (SFMDT)

The mechanical system test known as SFMDT integrated the

DTM rover, descent stage, and BUD into a single ‘drop’ test to

demonstrate and verify the skycrane mechanical separations and

deployments. As required to manage peak loads, the entire DTM

rover was configured to the lowest possible mass (400 kg, nearly 3/8

mass of flight vehicle), the mobility wheels and drive and steer

actuators were removed, and the rocker release times were adjusted

to reduce deployment loads. Because of the decreased BUD deploy

times caused by Earth gravity, the bogie release timings had to be

adjusted to preserve the relative timing to the BUD snatch event as

used in flight. See Figure 23 and Figure 24 for images of the test

execution.

Data acquisition for model validation was a primary objective of

this test. In addition to the rover instrumentation suite used in the

mobility deploy tests, the SFMDT was instrumented with string

potentiometers, multiple high-speed and high definition video

cameras, descent stage accelerometers, and a rotational encoder on

the BUD brake drum. To the extent possible, sources of uncertainty

in the test setup were identified and ranges were assigned to them. A

test-specific configuration control spreadsheet was used to track

parameter values and ranges.

Test/analysis validation was performed in a statistical framework

because of uncertainties in the test setup and the test article, and

because the intended purpose of the loads model was to derive

statistical loads4. Test-measured time histories were inspected for data quality and to verify that intended event

timings were met. High speed videos were studied and heavily scrutinized. Test-measured peak loads were

compared to histograms of analytical peak load predictions. Analysis of test/analysis data sets led to questions and

issues that were tracked in a list. Over a period of several months each of the 16 open items on the list was closed.

Samples of test/analysis comparisons are shown in Figure 25.

Figure 24 A sequence of video frames capturing the Skycrane deployments. Note the relatively late mobility

deploy time made necessary by Earth gravity.

Figure 23 FMDT test article in the

Powered Descent configuration being

lifted into position for the drop test.

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a)

3 3.5 4 4.50

5

10

15

20

Snatch time, sec

Occu

rre

nce

s

MC L: Snatch Time

b)

0 1000 2000 3000 40000

5

10

15

20

25

30

Moment, N-m

Occu

rre

nce

s

MC L: Peak CDP Moment (LUF=1.0)

c)

0 0.05 0.1 0.150

10

20

30

40

50

60

70

Delay, sec

Occu

rre

nce

s

MC L: Port Fwd Latch-up Delay

d)

0 1000 2000 3000 40000

5

10

15

20

25

30

35

40

Moment, N-m

Occu

rre

nce

s

MC L: Peak Port Fwd Rocker Mres, Zeroed (LUF=1.0)

e)

f)

Figure 25 Test/analysis comparisons of Skycrane Full Motion Drop Test measurements. Red dashed lines

denote test measured values.

Thorough evaluation of the complete data set and considerable effort examining model input parameters led to

the conclusion that the model was suited to the purpose of providing design loads for the mission. Accurate

prediction of BUD torques and speeds was seen to be a strength of the model. In several load locations, the test

measurements did not fall within the predicted histograms. The most significant deviations occurred in the rocker

torques. Rocker torque responses were highly asymmetric (by a factor of two) with the port side responses

matching the model well and the starboard side measurements higher than predicted; no definitive cause of the

asymmetry could be identified. Loads through the redundant load path area were also a mixed story but with a less

marked difference. The axial component of the load in the forward bogie correlated well to test data (Figure 25 -f) –

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and was symmetric, yet the forward bogie moments were asymmetric by a factor of 30% and were under-predicted

by the model on the starboard side. It is hypothesized that the asymmetry is caused by (unknown) differences in

hardware, since at this point in the V&V cycle the DTM rover had been in-service as a loads verification structure

for two years and the mobility had been deployed and restowed a number of times. Some difficulty stowing one

side of mobility had been noted.

In judging the suitability of the model, it is important to note that the flight limit loads predictions have a Model

Uncertainty Factor applied to them, yet the comparisons in Figure 25 are shown for factor of 1.0. Also important to

note is that not all load predictions are of equal importance. For example, the contribution of the rocker torque

component to suspension tube margin is on the order of a few percent, so if the Model Uncertainty Factor for the

torque load were to increase to a value of 2, it would not have any significant effect on the hardware stress margins.

One instance of unmodeled physics was uncovered in the validation process. Review of the high-speed video of

the BUD device during deployment revealed that a small and sudden bridle ‘jerk’ occurred during rover deployment.

This was associated with how the bridles installed onto the BUD spool. This slip was eventually modeled and the

effect on BUD and mobility loads was found to be insignificant.

VII. Conclusion

The mobility deploy event during the MSL Skycrane has presented numerous challenges for loads predictions

due to the simultaneous rover deploy and mobility deploy, due to the sensitivities to the precise timing of the rocker

latch-ups, and due to the need for the rover to be kinematically stable for the touchdown event. Model validation

has followed a hierarchical approach where component and assembly tests provided parameter values at the lowest

levels, and subsystem tests provided additional parameter values. Under controlled boundary conditions, the

subsystem tests also provided opportunities to both tune the models and validate the model’s predictive ability. The

final model validation took place in the context of the fully integrated Skycrane Full Motion Drop Test by

comparing test measurements with statistical predictions from the model.

The test validation of the models has been thorough and has demonstrated the range of errors that can be

expected from the models. These results have provided confidence that the model is suited for its intended purpose

of providing flight limit loads.

Results from these validation activities have shown that the loads models provide the most accuracy for the BUD

torques and speeds, but that the redundant load path through the mobility system is the most difficult to predict. The

importance of having a refined model for capturing small tolerances in the articulating joints has also been

demonstrated.

Acknowledgments

The authors would like to thank their colleagues John Bignell, Charlie Englehardt, John Gallon, Mike Gradziel,

Darlene Lee, Gary Ortiz, Tomasso Rivellini, Steve Sell, Adam Steltzner, Walter Tsuha, Jeff Umland, and Chris

Voorhees for their invaluable assistance in various aspects of this work. The research described in this paper was

carried out at the Jet Propulsion Laboratory, California Institute of Technology, under a contract with the National

Aeronautics and Space Administration.

References 1Steltzner, A., D. Kipp, A. Chen, D. Burkhart, C. Guernsey, G. Mendeck, R. Mitcheltree, R. Powell, T. Rivellini, M. San

Martin, D. Way “Mars Science Laboratory entry, descent, and landing system,” IEEE Aerospace Conference, 2006, Big Sky,

MT. 2Peng, C-Y., G. Ortiz, T. Rivellini, D. Lee, S-S. Lih, J. Waydo, C. White, S. Haggart, C. Voorhees, R. Rainen, “Dynamic

Simulations of Mars Science Laboratory EDL Landing Loads and Stability,” IEEE Aerospace Conference, 2007, Big Sky, MT. 3White, C.V., Antoun, G., Peng, C.-Y., Lih, S-S., Sell, S., Singh, G., Brugarolas, P., “System Verification of MSL Skycrane

Using an Integrated ADAMS Simulation,” IEEE Aerospace Conference, 2012, Big Sky, MT. 4ASME, Guide for Verification and Validation in Computational Solid Mechanics, American Society of Mechanical

Engineers, ASME V&V 10-2006, 2006, New York, NY. 5Gallon, J., “Verification and Validation Testing of the Bridle and Umbilical Device for Mars Science Laboratory,” IEEE

Aerospace Conference, 2012, Big Sky, MT. 6ADAMS, Software Package, Ver. 2007, R1, MSC Software, Santa Ana, CA, 2007. 7White, C.V., van der Walde, K. and Tippmann, J. “An Experimental Investigation of the Dynamics of the MSL Rover

Landing Event”, 49th AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics, and Materials Conference, Schaumburg,

IL, 2008

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Documents

[American Institute of Aeronautics and Astronautics 53rd AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics and Materials Conference20th AIAA/ASME/AHS Adaptive Structures Conference14th