Performance Metrics

1
MULTI-MISSION EARTH ENTRY VEHICLE IMPACT
ANALYSIS
Nicole C. Bauer / Brandon P. Smith / Christopher
L. Tanner / David A. Spencer Georgia Institute of
Technology / Space Systems Design Lab / NASA
Langley Research Center
Overview
Performance Metrics This investigation focuses on
the energy absorbing system of the MMEEV and its
performance relative to two critical metrics the
payloads peak acceleration and the absorbers
stroke length.
Background The Earth Entry Vehicle (EEV) was
proposed as part of the Mars Sample Return (MSR)
mission as a simple, reliable capsule that used a
passive energy absorber instead of a more complex
parachute system to safely return a payload to
the Earths surface. The Multi-Mission Earth
Entry Vehicle (MMEEV) uses a similar passive
energy absorbing system meant to be robust and
responsive to various sample return missions.
MMEEV Components
Finite Element Model
Model Description To investigate the absorbers
performance, a finite element model of the MMEEV
was created and analyzed using the commercial
solver LS-DYNA. To reduce finite element
construction and analysis time, only those
components related to the impact absorbing system
of the MMEEV were modeled (payload, primary
structure, foam, forebody, and the impact
surface). All components were modeled after the
baseline case an impact into UTTR soil at 40.4
m/s with an aluminum forebody and Rohacell 
110WF foam.
MMEEV Computational Grid Used for Structural
Analysis
Analysis
Sensitivity Analysis By comparing the performance
metrics from a baseline case to those obtained
from independent variations of the design
variables, the model was found to be sensitive to
impact velocity, forebody density, soil density,
and the foams stress-strain curve
parameterizations (compressive strength, Youngs
modulus, and strain corresponding the compressive
strength). Regression Analysis Through an
automated process, a regression analysis on a
full-factorial run matrix created from values
in the adjacent table yields response surface
equations (RSEs) that approximate the system
response. The RSEs balance a maximum range of
validity with minimal error. The polynomial R2
terms are 0.98 and 0.93 for stroke and
acceleration respectively. Two types of model
error are investigated model fit error (MFE)
and model representation error (MRE).
Design Variable Levels Levels Levels Levels
rforebody  (kg/m3) 1.94E04 1.74E03 1.06E04 -- 
rground (kg/m3) 2.09E03 8.81E02 1.49E03 --
smax,foam (kPa) 4.40E02 3.45E03 7.97E03 --
Efoam (kPa) 6.23E04 1.67E05 3.32E05 --
e2, foam 0.3 0.5 0.7 --
Impact Velocity (m/s) 40.4 30.3 32.8 35.5
Model Fit Error of the RSE
Strain (e)
Stress (s)
Foam Constitutive Model Parameterization
Simulation Diagram
Performance Metrics Sensitivities
Conclusions
Design Limitations Of the total 972 runs, 15
returned a non-physical solution where the
impacting layer of foam collapsed on itself
rather than compressing the surrounding foam
elements. To reduce failures, smax should be
restricted to a lower bound of 2,000 kPa. This
boundary corresponds to Rohacell  foams 110WF,
200WF, and 300WF as well as many other high
density foams.
Practical Use For a vehicle of similar size,
geometry and material properties within limits of
the adjacent table, the RSEs provide an
approximation of the stroke with 15 error and
maximum acceleration with 30 error. These
approximations can be used in the preliminary
design process for rapid performance analysis.
Design Variable Unit Min Max
Forebody density kg/m3 1744 19380
Foam max stress kPa 2000 7970
Foam Young's modulus kPa 62280 332700
Foam strain at max stress -- 0.3 0.7
Ground density kg/m3 880.6 2092
Impact velocity m/s -40.4 -30.3
Design Variable Limits
Time Progression of a Nominal and a Non-Physical
Case