February 2011 

NASA/TM-2011-217055

Entry, Descent and Landing Systems Analysis 

Study: Phase 2 Report on Exploration

)HHGForward Systems 

Alicia M. Dwyer Ciancolo, Jody L. Davis, Walter C. Engelund, D. R. Komar, Eric M. Queen, 

Jamshid A. Samareh, David W. Way, and Thomas A. Zang 

NASA Langley Research Center, Hampton, Virginia 

Jeff G. Murch, Shawn A. Krizan, Aaron D. Olds, Richard W. Powell, and Jeremy D. Shidner 

Analytical Mechanics Associates, Inc., Hampton, Virginia 

David J. Kinney and M. Kathleen McGuire 

NASA Ames Research Center, Moffett Field, California 

James O. Arnold 

University of California, Santa Cruz, California

M. Alan Covington 

ERC, Inc., Edwards AFB, California 

Ronald R. Sostaric and Carlie H. Zumwalt 

NASA Johnson Space Center, Houston, Texas 

Eduardo G. Llama 

GBTech, Inc., Houston, Texas
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February 2011 

NASA/TM-2011-217055

Entry, Descent and Landing Systems Analysis 

Study: Phase 2 Report on Exploration 

)HHGForward Systems 

Alicia M. Dwyer Ciancolo, Jody L. Davis, Walter C. Engelund, D. R. Komar, Eric M. Queen, 

Jamshid A. Samareh, David W. Way, and Thomas A. Zang 

NASA Langley Research Center, Hampton, Virginia 

Jeff G. Murch, Shawn A. Krizan, Aaron D. Olds, Richard W. Powell, and Jeremy D. Shidner 

Analytical Mechanics Associates, Inc., Hampton, Virginia 

David J. Kinney and M. Kathleen McGuire 

NASA Ames Research Center, Moffett Field, California

James O. Arnold 

University of California, Santa Cruz, California 

M. Alan Covington 

ERC, Inc., Edwards AFB, California 

Ronald R. Sostaric and Carlie H. Zumwalt 

NASA Johnson Space Center, Houston, Texas 

Eduardo G. Llama 

GBTech, Inc, Houston, Texas 
Available from: 

NASA Center for AeroSpace Information 

7115 Standard Drive 

Hanover, MD 21076-1320 

443-757-5802 
i

Table of Contents 

Table of Contents...........................................................................................................................................i

List of Figures ..............................................................................................................................................iii

List of Tables................................................................................................................................................ iv

Acronyms...................................................................................................................................................... v

Acknowledgements.....................................................................................................................................vii

Abstract ......................................................................................................................................................viii

1 Executive Summary ................................................................................................................................ 1

2 Exploration Feed Forward Methodology................................................................................................ 3

3 Landed Mass Assessment ....................................................................................................................... 5

3.1 Payload ............................................................................................................................................. 5

3.2 Hypersonic Inflatable Aerodynamic Decelerator (HIAD)............................................................... 6

3.3 Thermal Protection System Trade.................................................................................................... 6

3.4 Descent Stage ................................................................................................................................... 8

3.5 Recommendations for Future Enhancements................................................................................. 11

4 HIAD Controllability Assessment ........................................................................................................ 12

4.1 Overview ........................................................................................................................................ 12

4.2 Guidance Algorithms Considered .................................................................................................. 12

4.2.1 Hybrid Predictor-Corrector Aerocapture Scheme (HYPAS) .................................................. 12

4.2.2 Terminal Point Controller (TPC)............................................................................................. 12

4.2.3 Numerical Predictor-Corrector Guidance (NPC) .................................................................... 13

4.2.4 Shape Integral (SI)................................................................................................................... 13

4.3 Control Algorithms ........................................................................................................................ 13

4.3.1 6DOF Bank Angle Controller.................................................................................................. 13

4.3.2 6DOF Center of Gravity (CG) Controller ............................................................................... 13

4.4 Exploration Feed Forward Nominal Configuration ....................................................................... 14

4.4.1 Nominal Configuration Inputs................................................................................................. 14

4.4.2 Aerocapture Monte Carlo Results ........................................................................................... 14

4.4.3 Trade 1: L/D of 0.1 Versus L/D of 0.25 .................................................................................. 15

4.4.4 Trade 2: Jettison Versus No Jettison ....................................................................................... 16

4.4.5 Trade 3: L/D of 0.25 with 500 km Circular Target Orbit Versus 1 sol Target Orbit .............. 18

4.5 HIAD Controllability Conclusions................................................................................................. 18

5 ALHAT Sensor Assessment ................................................................................................................. 20

5.1 Entry Guidance Performance ......................................................................................................... 20

5.2 Powered Descent Performance....................................................................................................... 21

5.2.1 TRN and HAD Feasibility....................................................................................................... 22

5.3 Navigation Performance................................................................................................................. 23

5.4 Recommendations and Future Work.............................................................................................. 24

6 Conclusions........................................................................................................................................... 26

7 Bibliography ......................................................................................................................................... 26

8 Appendix A - Design Reference Mission, Ground Rules and Assumptions and Evaluation Criteria.. 27

8.1 Design Reference Mission ............................................................................................................. 27

8.2 EDL-SA Ground Rules and Assumptions...................................................................................... 28

8.2.1 General Ground Rules and Assumptions................................................................................. 28

8.2.2 Feed Forward Study Ground Rules & Assumptions ............................................................... 29

8.2.3 Mass Growth Allowance and System Margin Policy.............................................................. 29

8.2.4 Monte Carlo Parameters.......................................................................................................... 30

8.3 Evaluation Criteria ......................................................................................................................... 32
ii

8.4 Feed Forward Study Products........................................................................................................ 33

Appendix B - EDL Technology Needs....................................................................................................... 34

Appendix C - HIAD Diameter Trade Study Results................................................................................... 36

Appendix D - Simulation Monte Carlo Dispersions................................................................................... 39

Appendix E - Simulation Monte Carlo Navigation and Sensor Dispersions.............................................. 40
iii

List of Figures 

Figure 1. EFF Architectures......................................................................................................................... 4

Figure 2. Movable Fission Power System Concept [4]................................................................................ 4

Figure 3. Mass Model Process ...................................................................................................................... 5

Figure 4. Propulsion Trade Results............................................................................................................... 9

Figure 5. Parameteric Performance and Sizing Maps for a Pump-Fed NTO/MMH Rocket ...................... 10

Figure 6. Heat Rate and Total ΔV for EFF-1 Aerocapture ......................................................................... 15

Figure 7. Apoapsis Altitude vs Periapsis Altitude for L/D = 0.10 (left) and 0.25 (right)........................... 15

Figure 8. Plane Change Maneuver ΔV for L/D of 0.10 (left) and 0.25 (right) ........................................... 16

Figure 9. Vacuum Apoapsis and Periapsis Altitude vs. Time With and Without HIAD Jettison............... 16

Figure 10. L/D = 0.10: Apoapsis vs. Periapsis Altitude for Jettison (left) and No Jettion (right) .............. 17

Figure 11. L/D = 0.10: Periapsis Raise Maneuver DV for Jettison (a) and No Jettison (b) ....................... 17

Figure 12. L/D = 0.25: Apoapsis vs Periapsis Altitude for Jettison (a) and No Jettison (b)....................... 18

Figure 13. Apoapsis vs. Periapsis Altitude for the 1 sol (left) and 500 km circular (right) target orbits.... 18

Figure 14. Reference Bank Profile.............................................................................................................. 20

Figure 15. Entry Performance Summary..................................................................................................... 21

Figure 16. Pitch Profile During Powered Descent ...................................................................................... 22

Figure 17. Range Scatter Plot Comparison at Engine Ignition and Touchdown. ....................................... 24

Figure 18. Feed Forward DRM................................................................................................................... 28

Figure C-19. Mass Model Trade for Single HIAD Concept (EFF-2)......................................................... 36

Figure C-20. Mass Model Trade for Direct Entry Concept (EFF-3) .......................................................... 37

Figure C-21. Mass Model Trade for Direct Entry Concept (EFF-4) ......................................................... 38
iv

List of Tables 

Table 1. TDP EFF Recommenations............................................................................................................ 2

Table 2. Results of the HIAD Diameter Mass Trade ................................................................................... 7

Table 3. Sensitivity Analysis for TPS Areal Density.................................................................................... 7

Table 4. Mass Closure Results for each Architecture Concept................................................................... 10

Table 5. Nominal Aerocapture Parameters................................................................................................. 14

Table 6. Key Parameters for Feed Forward DRM ...................................................................................... 28

Table 7. MSL-I Robotic Study Monte Carlo Parameters............................................................................ 31

Table 8. Feed Forward Robotic Study Monte Carlo Parameters ............................................................... 32

Table 9. Feed Forward TPS and Control Method Options ......................................................................... 33

Table 10. High-level Products for FF Study ............................................................................................... 33
v

Acronyms 

ALHAT Autonomous Landing and Hazard Avoidance Technology 

Al-Li Aluminum Lithium 

APC Analytic Predictor-Correction

ARMD Aeronautics Research Mission Directorate

CCRB Customer Content Review Board 

CG Center of Gravity 

CH4 Methane 

deg degrees 

deg/sec2

 degrees per second squared 

DLV Descent Landing Vehicle 

DRA5 Design Reference Architecture 5.0 

DRM Design Reference Mission 

EDL Entry, Descent and Landing 

EDL-SA Entry, Descent and Landing Systems Analysis 

EFF Exploration Feed Forward 

EKF Extended Kalman Filter 

ESMD Exploration Systems Mission Directorate 

ETDP Exploration Technology Development Program 

ETDD Exploration Technology Development and Demonstration 

EXAMINE Exploration Architecture Model for IN-space and Earth-to-orbit 

GR&A Ground Rule and Assumption 

HDA Hazard Detection and Avoidance 

HIAD Hypersonic Inflatable Aerodynamic Decelerator 

HYPAS Hybrid Predictor-Corrector Aerocapture Scheme 

IAD Inflatable Aerodynamic Decelerator 

IMU Inertial Measurement Unit 

IRVE Inflatable Re-entry Vehicle 

Isp Specific Impulse 

ISRU In-situ Resource Utilization 

kg kilograms

kg/m2 kilograms per square meter 

km kilometers 
vi

kN kilo Newtons 

kW kilo Watt 

lbf pounds of force 

LCH4 Liquid Methane 

LOX Liquid Oxygen 

LQR Linear Quadratic Regulator 

L/D Lift-to-Drag Ratio 

m meters 

m/s meters/second 

MGA Mass Growth Allowance 

MLI Multilayer Insulation 

MMH monomethylhydrazine 

MOLA Mars Orbiter Laser Altimeter 

MPS Main Propulsion System 

MSL Mars Science Laboratory 

t metric ton

NPC Numerical Predictor-Corrector 

NTO nitrogen tetroxide 

OCE Office of the Chief Engineer 

PICA Phenolic Impregnated Carbon Ablator

PID Proportional Integral Derivative 

RCS Reaction Control System 

RSE Response Surface Equation 

s seconds 

SI Shape Integral 

SMD Science Mission Directorate 

SRP Supersonic Retro-propulsion 

TDP Technology Development Project 

TISC Technology Investment Steering Committee 

TPS Thermal Protection System 

TRL Technology Readiness Level 

TRN Terrain Relative Navigation 

T/W Thrust-to-Weight Ratio 

ΔV change in velocity 
vii

Acknowledgements 

In addition to the authors of this report, other individuals have contributed in some way to the 

Exploration Feed Forward Study. The HIAD insulative TPS mass model was provided by Joseph Del 

Corso, Stephen J. Hughes and F. McNeil Cheatwood. Useful comments on the HIAD TPS mass models 

were given by Kamran Daryabeigi. The details on the Movable Fission Power System payload were 

furnished by Lee E. Mason. The EDL-SA assessment of ALHAT technology at Mars benefited from the 

input of the ETDD ALHAT Team (Chirold D. Epp and Edward Robertson). Furthermore, the work 

reported in this paper benefited greatly from all those who contributed to the first year of the EDL-SA 

Study. 

Feedback on the draft Design Reference Missions, Ground Rules and Assumption, and the Evaluation 

Criteria was provided by Bret C. Drake, Dana C. Gould, and Charles M. Lundquist. The Internal Peer 

Review Panel (Anthony M. Calomino, Charles H. Campbell, Christopher J. Cerimele, Karl T. Edquist, 

Chirold D. Epp, Mark M Hammerschmidt, Stephen J. Hughes, Mark D. Rezin and Michael J. Wright) 

provided valuable comments. 

The team is appreciative of the efforts of Farhad Tahmasabi and Harold M. Bell of the Office of the 

Chief Engineer for their guidance and support, and especially for the efforts of our sponsor, Mike

Ryschkewitsch, the NASA Chief Engineer. Finally, the EDL Systems Analysis Study was only possible 

because of the persistent and effective advocacy of Walter C. Engelund and Stephen P. Sandford. 
viii

Abstract 

NASA senior management commissioned the Entry, Descent and Landing Systems Analysis (EDLSA) Study in 2008 to identify and roadmap the Entry, Descent and Landing (EDL) technology 

investments that the agency needed to successfully land large payloads at Mars for both robotic and 

human-scale missions. Year 1 of the study focused on technologies required for Exploration-class 

missions to land payloads of 10 to 50 t. Inflatable decelerators, rigid aeroshell and supersonic retropropulsion emerged as the top candidate technologies. In Year 2 of the study, low TRL technologies 

identified in Year 1, inflatables aeroshells and supersonic retropropulsion, were combined to create a 

demonstration precursor robotic mission. This part of the EDL-SA Year 2 effort, called Exploration Feed 

Forward (EFF), took much of the systems analysis simulation and component model development from 

Year 1 to the next level of detail. 

A main objective of the study was to determine the maximum payload mass capability of a Delta IVH launch vehicle (launch mass of 7.2 t) for the 2024 Mars opportunity. The simulation results, using the 

latest component mass models, indicated that a direct entry system could deliver approximately 3.5 t to 0 

km above the Mars Orbiter Laser Altimeter (MOLA) areoid. A second objective was to characterize the 

performance required of the supersonic retro-propulsion system. The study, which assumed four engines 

with a specific impulse of 338s and a system thrust-to-weight of 3.7 Mars g’s, yielded descent engine 

initiation between Mach 1.4 and 1.8 at an altitude between 3 and 8 km. A third major objective was to use 

the high fidelity entry simulation to characterize an Autonomous Landing and Hazard Avoidance 

Technology (ALHAT) like sensor suite for Mars. Initial performance range results were obtained for 

terrain relative navigation, hazard detection and avoidance, velocimeter and altimeter sensor systems. 

This document provides a summary of the analysis performed to meet the EFF objectives and 

provides recommendations, based on the results, for future investment. 
1

1 Executive Summary 

The Exploration-class missions studied in the first year of the Entry, Descent and Landing Systems 

Analysis (EDL-SA) [1] effort identified technologies required to land cargo or crewed missions requiring 

payloads between 10 and 50 t on Mars. The technology areas included the rigid aeroshell from the Mars 

Design Reference Architecture 5.0 (DRA5) [2], inflatable aerodynamic decelerators and supersonic 

retropropulsion. Candidate technology areas were assessed against a set of eight “EDL Architectures”, 

i.e., representative architectures (high-level designs) against which the benefits of the technology areas 

were evaluated. As a result of the study, two technology areas that presented substantial potential for high 

mass to the surface—hypersonic inflatable aerodynamic accelerators (HIADs) and supersonic 

retropropulsion (SRP)—were combined to create a robotic precursor demonstration mission for detailed 

evaluation in the EDL-SA Year 2 effort. 

The precursor demonstration mission of Year 2 is referred to as Exploration Feed Forward (EFF). The 

Design Reference Mission (DRM), Ground Rules & Assumptions (GR&As) and Evaluation criteria (see 

Appendix A) for the study were approved by the managers of the ARMD, ESMD and SMD technology 

programs in June 2010, prior to the execution of the simulation and evaluation of results. 

The EFF baseline mission includes a conceptual 2 t nuclear power source payload that is aerocaptured 

into a 500 km circular orbit at Mars using a 14 m HIAD. Following aerocapture the 14 m HIAD is 

jettisoned and an 8 m entry HIAD is inflated. The vehicle has a nominal Lift-to-Drag (L/D) ratio equal to 

0.25 and is guided. At approximately Mach 2 the entry HIAD is jettisoned and supersonic retropropulsion 

is initiated. The mission terminates with a touchdown velocity of 1 m/s at 0 km above the MOLA areoid. 

The goals of EFF, evaluated using the single architecture described above, included the following. 

1. Determine the maximum payload delivery capability of a Delta IV-H 

2. Determine required performance of supersonic retropropulsion 

3. Increase the level of fidelity of all models 

4. Determine optimal materials, L/D and HIAD size for aerocapture and entry 

5. Determine if center of gravity control provides benefits over bank control for the HIAD 

6. Determine sensor performance for an ALHAT system at Mars. 

Under the assumptions made for EFF, the maximum deliverable payload of a Delta IV-H is 

approximately 3.5 t (Sect 3). Simulation results indicate that SRP performance for a mission of this class, 

assuming 4 engines with a specific impulse of 338 s and a thrust to weight of 3.7 Mars g’s, requires 

engine initiation between Mach 1.4 and 1.8 at altitudes between 3 and 8 km (Sect 5.1). Using models of 

TPS materials currently being developed by the Inflatable Re-entry Vehicle 3 (IRVE-3) and the Entry, 

Descent and Landing Technology Development Project (EDL TDP), analysis shows that TPS materials 

maturation is required, but that the materials appear feasible for the application considered (Sect. 4). 

Performance of ALHAT like sensors for Mars is assessed for a system that excluded terrain relative 

navigation. The initial sensor results were provided to the ALHAT project (Sect 5). Details of the EFF 

packaging (Sect. 3) indicate that the configuration may require a redesign to eliminate or account for the 

risk of heating due to flow recircularization behind the HIADs. Schedule and funding constraints limited 

the HIAD controllability assessment to a more detailed assessment of the bank controller used in the Year 

1 Exploration-class missions; however the analysis did evaluate the effects of additional guidance options 

(Sect. 4).

The primary technology recommendations that resulted from the EFF work are listed in Table 1 and 

are intended to complement the recommendations of EDL-SA Year 1 Exploration-class analysis. The 
2

combined technology recommendations from Years 1 and 2 are provided in Appendix B. Also an internal 

peer review was conducted Dec. 1-2, 2010. The feedback received was extremely beneficial and is 

documented [3] elsewhere. 

Table 1. TDP EFF Recommenations 

Technology Area TDP Content

Rigid Aeroshell

(1) Though not considered here, new knowledge of potential Mars 

payloads (being half the length considered for DRA5[2]) 

suggest that size shape and mass optimization is needed. 

(2) Transition maneuvers need to be fully examined

(3) Software configuration of system analysis studies is essential

Supersonic Retro-Propulsion Recommend to accelerate SRP development to a point that 

feasibility has been demonstrated ASAP

Deployable/Inflatable 

Decelerators

(1) Consider size, shape and mass optimization, effect of charring, 

and alternate modes of guidance and control and transitions. 

(2) Consider rigid deployables not considered above

(3) Utilize software configuration control mechanisms in systems 

analysis studies

GN&C Additional insight into performance requirements was gained, but no 

fundamentally new objectives were identified

Aerocapture Development

(1) Consider ability to jettison drag device after aerocapture pass 

but while in sensible atmosphere

(2) Investigate torques caused by aero/RCS interactions 

(3) Double aerodynamic uncertainties in systems analysis

Supersonic Retro-Propulsion 

& Deployable/Inflatable 

Decelerator Flight Test 

Program

Consider developing a dedicated reusable testbed to test critical EDL 

technologies and flight instrumentation

Aerocapture Flight Test Remains a high priority

Feed-Forward Technology 

Mars Flight Test

Flight demonstration (TRL=8) of EFF technologies at Mars with real 

payload; Use technologies from EDL-SA (or future studies) EFF robotic 

mission design as baseline
3

2 Exploration Feed Forward Methodology 

The design methodology used for the EFF study is based on lessons learned from both DRA5 [2] and 

the EDL-SA Year 1 Exploration-class study [1] and recent developments in several technology areas. 

Primary technology recommendations from the EDL-SA Exploration study included HIADs, rigid 

aeroshells and supersonic retropropulsion. Since the conclusion of the Year 1 study, development has 

continued in NASA technology programs on the IRVE inflatable concept (ARMD). In addition, testing of 

both ablator (ESMD) and insulator (ARMD) materials has demonstrated TPS feasibility. The continued 

development has led to an increase in maturity in inflatable aeroshell technology and suggests that 

inflatables should continue to be considered for exploration missions due to the potential for large arrival 

mass reductions or significant payload fraction increases. The development of ALHAT sensors for lunar 

missions has prompted the desire for detailed simulation analysis of a similar system for Mars missions. 

Also, recent packaging arrangements for the Exploration-class mission payloads indicate that the 10 x 30 

m aeroshell considered in DRA5 and EDL-SA Year 1 may be too long by a factor or two. Another 

concern recognized in the EDL-SA Exploration study was the lack in understanding the ability to control 

large HIADs during aerocapture and entry. These, coupled with the desire to ascertain details of the next 

level of exploration system design, encompass the motivation for the architecture considered for EFF. 

Resources available for the EDL-SA Year 2 EFF work necessitated the selection of a single 

architecture class that would enable analysis of the maximum number of feed forward technologies. The 

baseline architecture, EFF-1, shown in Figure 1, considers a Dual HIAD system, (14 m HIAD for 

aerocapture and 8 m HIAD for entry; sizes were optimized to maximize landed payload mass), supersonic 

retropropulsion, a Movable Fission Power System candidate payload [4] (see Figure 2) and an ALHAT 

sensor suite. EFF assumed a maximum launch mass capability of a Delta IV-H (7.2 t) and an arrival 

velocity at Mars of 7.3 km/s., consistent with the 2024 opportunity chosen for the DRM. Other mission 

assumptions can be found in Appendix A. Variations of this baseline were considered to examine the 

impact on landed payload. EFF-2 considers the use of a single HIAD sized for both aerocapture and entry, 

and EFF-3 and 4 consider HIADs sized for a direct entry of 7.3 (2024 “worse case” opportunity) and 5.8 

(MSL like) km/s respectively. All EFF configurations are shown in Figure 1. 

Fidelity of the POST2 simulation from Year 1, as well as many of the models (goal #3 in Sect 1) 

increased significantly over exploration work in EDL-SA Year 1. The model upgrades required the 

simulation to upgrade from 3 Degrees of Freedom (DOF) to 6DOF. Identifying a defined payload allowed 

for an estimation of vehicle mass properties including inertias. The 6DOF aerocapture simulation allowed 

for analysis of vehicle performance using several guidance and control algorithms. The 6DOF entry 

simulation allowed for sensor performance analysis of the ALHAT like sensor suite and provided 

environmental characteristics for a SRP system. 

The initial intent was to optimize the 6DOF aerocapture and 6DOF entry simulations using the 

lightest mass model derived from technology program input. Next, using the closed EFF-1 system, 

perform the HIAD controllability analysis using multiple controllers and guidance algorithms on the 

aerocapture configuration. Then, using the selected optimal guidance/controller combination, compare the 

landed mass capability by evaluating the mass savings of a single HIAD (EFF-2) and direct entry (EFF-3 

&4). Finally the ALHAT assessment would be performed on the configuration that landed the maximum 

payload. However, a major lesson learned in EFF, is that detailed model development takes time that the 

EFF project was not able to accommodate. Therefore, a slightly revised approach was taken that allowed 

the decoupling of the three major assessments -- optimum landed mass (Sect 3), the HIAD controllability 

(Sect 4) and the ALHAT sensor performance (Sect 5). The details of the approach and analysis performed 

for each assessment is described in the following sections. Each section also summarizes the technology 

recommendations, other lessons learned, and proposed work for future Exploration-class system analysis 

studies. 
4

Figure 1. EFF Architectures 

Figure 2. Movable Fission Power System Concept [4]
5

3 Landed Mass Assessment 

The landed mass assessment required an update to mass models used in the EDL-SA Explorationclass study, which assumed a 40 t payload. A lesson learned from Year 1 was that parametric models 

allow for much easier design optimization and trade studies. Therefore, EFF followed an approach to 

perform simultaneous vehicle sizing and mission design for all four architectures. The approach requires a 

parametric mass model that mathematically represents mass components as a function of vehicle 

dimensions and key mission environmental parameters such as maximum dynamic pressures and total 

heat load. 

The four architectures shown in Figure 1 share three major mass components: payload, Hypersonic 

Inflatable Aerodynamic Decelerator (HIAD), and descent landing vehicle (DLV). Figure 3 shows the 

overall process used to develop the required 

parametric mass models. A Java and Python 

based mass estimating tool was developed to 

approximate mass for inflatable elements of 

HIADs. This tool was used to generate masses 

for a large number of HIAD diameters, and 

these approximate masses were fitted with 

response surface equations (RSE). Technology 

programs provided two TPS mass models -- an 

ablator (from EDL TDP) and an insulator 

material (from IRVE). These were provided as a set of tables and simple analytical equations. An RSE 

was also used to model DLV mass. The RSEs, tables, and simple equations were combined into a set of C 

routines with additional equations for other mass components (e.g., rigid heatshield). The resulting C 

routines were integrated into POST2 for vehicle sizing and mission design. This process was similar to 

the approach used for Year 1 [1]. A margin of 49.5% was applied across all mass components including 

TPS. The next subsections include detailed discussion on the payload, HIAD, and TPS mass models. The 

last subsection concludes with a list of mass modeling specific recommendations for future 

enhancements. 

3.1 Payload 

The candidate payload for this study was a small Movable Fission Power System (MFPS) [4] shown 

in Figure 2. The power plant mass is 1615 kg, and the mass for power management and distribution 

system is 415 kg, yielding a target landed payload of approximately 2 t. There are two options for payload 

surface mobility: 1) attach the payload to a rover that will act as a mobile platform for the power plant, 

and 2) pre-deploy a rover and a crane that will move the power plant to the operating site. Neither of these 

two mobility options was included in the current study, although there appears to be sufficient landed 

payload capability to include them with the MFPS on a single lander. Analysis was done to determine the 

payload’s mass properties as defined in Ref [4]. The values were used in the HIAD controllability and 

ALHAT 6DOF analyses. However, mass modeling simulation considered only 3DOF trajectories to 

determine maximum landed mass and did not rescale the payload mass properties according to landed 

payload capability greater than 2 t. The impact of the change in the mass properties to accommodate 

larger vehicle was not evaluated. However, the controller was designed to generated pure accelerations 

and did not define thruster size, location or orientation. Therefore the 6DOF analysis could be performed 

independent of the payload mass properties. 

It was also recognized that the payload configuration presented in Ref [4] might not be optimal for the 

entry configuration (HIAD + SRP) selected for the study. Options to shorten the payload were considered 

but the team elected to use the payload as defined and impose constraints on the diameter of the HIAD 

Figure 3. Mass Model Process
6

and the angle of attack to mitigate flow impingement issues that may result from the long payload. 

3.2 Hypersonic Inflatable Aerodynamic Decelerator (HIAD) 

The HIAD model is a 65° sphere cone aeroshell that includes an inflatable decelerator, flexible TPS, 

separation mechanism, payload adapter, and a rigid spherical cap. The mass of the inflatable decelerator is 

based on the models developed by NASA in the 1960’s and 1970’s. The inflatable decelerator is identical 

to that used in the Year 1 study and is described in detail in the TM [1] and the AIAA paper on the mass 

model [5]. However, based on analysis and lessons learned in Year 1, the angle was changed from a 60°

to a 65° sphere cone to reduce heating while maintaining acceptable performance. 

3.3 Thermal Protection System Trade 

The aerothermal environments used in this study were developed using the same methodology and 

margins that were employed in the year 1 Exploration study [1]. Additional detail on the methodology is 

provided in [6]. 

The thermal protection system (TPS) is one of the key components of HIAD aeroshells; it protects the 

inflatable decelerator from the extreme thermal environment during the aerocapture and entry phases. The 

HIAD TPS must be lightweight, suitable for efficient packaging and be capable of performing its function 

upon deployment after being stowed for periods of up to 6 months. Ablator and insulator concepts are 

currently two primary candidates for the HIAD TPS. The ablator mass model used in this study was 

developed at NASA Ames Research Center, and it was based on SIRCA-flex (flexible Q-felt plus silicone 

matrix) and PICA-flex (flexible Q-felt plus phenolic matrix)) concepts [6,7]. The insulator mass model 

was developed at NASA Langley Research Center, and it was based on a multilayer concept with an outer 

fabric (Nextel 440), an insulator (Pyrogel 3350), and a laminated gas barrier (Kapton-Kevlar-Kapton 

layer). The model, based on the IRVE 3 and 4 concepts, does have manufacturability, packaging and 

development maturity. 

The ablator TPS concept has a higher areal density than that of the insulator, but can operate in 

environments with higher heat rates (up to 115 W/cm2

 for SIRCA-flex and up to 450 W/cm2 for PICAflex [7]). Insulators are currently limited to peak heat rates of ~60 W/cm2

. The optimal diameter for 

ablator and insulator HIADs are different: ablators tend to be more mass efficient for smaller diameter 

HIADs, while the insulators are more mass efficient for larger diameters HIADs. 

A diameter sweep trade study was performed to identify optimal diameters and resulting payloads for 

both ablator and insulator TPS concepts under the constraint that the HIAD diameter remain large enough 

to prevent shear layer impingement on the payload. Figure C-19 to C-21 in Appendix C show details of 

the trade study, and Table 2 shows the trade study summary. The maximum available payload varies 

between 2.6-3.6 t, depending on the architecture, the TPS concept, and the arrival velocity. Based on the 

EFF assumptions, the ablator concept can generally deliver larger payloads compared to the insulator 

model. While the delivered masses with the two TPS systems are comparable, the HIADs using ablator 

TPS have considerably smaller diameters, as expected. Specifically, this study suggests that a single, dual 

heat pulse, 8 meter HIAD with ablator TPS can deliver the largest payload for missions using aerocapture, 

while the largest mass delivered for a direct entry configuration (5.8 km/s) uses an 8 meter HIAD with 

insulator TPS. The mass penalty for aerocapture must be traded with the increased flexibility to mission 

and entry timeline. Using aerocapture, the vehicle can wait in the target orbit until all subsystems are 

checked out and environmental conditions are ideal for entry. 

As shown in Appendix C Figs. C-19-f, C-20-f, and C-21-f, the maximum available payload delivery 

is a strong function of TPS maximum operating heat rate; TPS concepts with higher maximum operating 

heat rate can deliver larger payloads. Since the current study considered HIADS of diameters that 
7

prevented flow impingement on the payload, SIRCA-flex was adequate for the ablative TPS. PICA-flex 

would be suitable for smaller diameter HIADs with the corresponding increased peak heating. 

Table 2. Results of the HIAD Diameter Mass Trade 

 A sensitivity analysis was performed for TPS areal density. The results are shown in Table 3. A 

25% increase in TPS areal density would result in 1.4 to 8.7% reduction in the maximum available 

payload. 

Table 3. Sensitivity Analysis for TPS Areal Density 
8

3.4 Descent Stage 

This section presents the approach used in EFF to establish an integrated mass model and to 

summarize the ground rules and assumptions used to size the SRP, herein referred to as the descent stage. 

The Exploration Architecture Model for IN-space and Earth-to-orbit (EXAMINE) [8] modeling 

framework, developed at NASA Langley Research Center, was used to model the mission events for each 

EFF configuration, develop the parametric mass estimates of the descent stage for all architectures, and to 

generate a mass model of the integrated system for use in the trajectory analysis. A methodology utilizing 

RSEs was employed for this effort to increase analytical efficiency and utility by enabling the following: 

• Eliminating manual trajectory-sizing iterations; 

• Enabling mass closure within the trajectory optimization framework; 

• Enabling optimization of system configuration and element sizing variables in conjunction with 

trajectory optimization. 

The primary descent stage structure is a 2.6 m diameter aluminum-lithium (Al-Li) cylinder that 

supports the tank system and payload. Thrust structure mass is based on a historical fit accounting for 

stage diameter, the number of engines and the thrust load. Secondary structure mass is 5% of the primary 

plus thrust structure masses. Landing gear mass is 2.5% of the landed mass on Mars. Multilayer insulation 

(MLI) is 5 cm thick (39.4 kg/m3) covering the exterior structure, providing thermal control of the 

spacecraft. During trans-Mars coast, a 3-junction gallium-arsenide photovoltaic array that provides 0.5 

kilowatts (kW) of power for the EFF spacecraft. During entry and landing, two lithium-ion batteries each 

provide 1 kW for 2 hours of operation with 100% depth of discharge. Power is managed and distributed 

with a 115 volt alternating current system sized to handle 1 kW peak power at 90% efficiency. Waste heat 

(up to 1 kW) is collected from coldplates using an ammonia fluid loop and rejected using a body-mounted 

radiator. Avionics, including command, control and data handling, communication, guidance, navigation 

and control (GN&C), and instrumentation, are derived from MSL. 

For the EFF study, the goal is to determine the maximum deliverable payload (~2-4 t) to the surface 

using a descent stage that provides retro-propulsion for supersonic, subsonic and terminal descent and 

landing. The model used for EDL-SA Year 1, which landed 40 t, was not well suited for this purpose. 

For a better comparison, EFF followed Mars Science Laboratory (MSL) in using a descent stage that 

employs a pressure-fed mono-propellant hydrazine propulsion system (with a specific impulse of less 

than 240 seconds [9]) to provide retro-propulsion for powered subsonic descent, sky crane, and flyaway 

maneuvers that deliver a payload to Mars’ surface that is less than one metric ton. Since the landed 

payload requirement and descent stage functionality (in terms of propulsive delta-V) required are greater 

for EFF relative to MSL, a higher performing propulsion system is needed given that the total mass 

delivered to trans-Mars insertion is limited to 7.2 metric tons by the Delta IV-H launch vehicle capability 

[10]. Thus, a pressure-fed engine burning nitrogen tetroxide (NTO) and monomethylhydrazine (MMH) 

propellants was initially selected for EFF due to its increased vacuum specific impulse (Isp) compared to 

the mono-propellant hydrazine. However, preliminary analysis using this pressure-fed engine indicated 

that the maximum payload delivery capability from the closure analysis would be less than desired. A 

trade study was then performed to evaluate the payload performance improvement of both a pump-fed 

NTO/MMH system and a pump-fed engine using liquid oxygen (LOX) and liquid methane (LCH4) 

propellants. This study assumed the same payload and delta-V for each option and total descent stage wet 

mass was used to evaluate performance relative to the pressure-fed NTO/MMH case. 

As shown in Figure 4, the pump-fed NTO/MMH stage mass decreased (relative to the pressure-fed 

NTO/MMH case) about 500 kg as both dry mass and propellant mass required decreased due to the 
9

increased Isp. The pump-fed LOX/CH4 stage mass also decreased relative to the pressure-fed NTO/MMH 

stage, but not as much as the pump-fed NTO/MMH case. This is because the low density of the cryogenic 

methane fuel requires more dry mass (larger tanks and more structure to support the tankage, increased 

tank thermal control) and the inert mass is increased relative to the storable options due to the boiloff of 

the cryogenic propellants during the 

interplanetary coast. 

Based on these results, a pump-fed

NTO/MMH engine system was selected for 

EFF. Note that selection of this system was 

based purely on performance potential. Two 

key issues related to risk need to be considered 

further: 

Mission risk associated with starting four 

pump-fed engines (utilizing a gas generator 

cycle) for the supersonic retro-propulsion 

maneuver following the 4-6 month 

interplanetary coast from Earth to Mars. 

Development risk to enable deep throttling 

of the pump-fed engine to support landing: four 

engines operating together require throttling to 

20% power level for landing while two engines operating together (with two shutdown) require throttling 

to 40% power level. 

This study, however, did not formally assess propulsion system risk. Future studies should carefully 

consider these issues. 

Four pump-fed NTO/MMH engines for the main propulsion system (MPS) operate at 856 psia 

chamber pressure and a mixture ratio of 2.05 and are assumed to be derived from the RS-72 engine in 

development at Rocketdyne that delivers 12,000 pounds of thrust per engine [11]. Since stage thrust-toweight (T/W) and engine area ratio were selected as independent variables, the required thrust varies from 

case to case and in the overall closure/optimization. Thus, a set of RSE’s for the MPS were developed to 

quickly predict the engine characteristics as a function of required thrust and area ratio. The open circle in 

Figure 5 shows the engine T/W, specific impulse, engine length and engine exit diameter data used in the 

performance and sizing. 

The MPS propellants are stored at 40 psia in two spherical graphite-wrapped aluminum tanks, one for 

NTO and one for MMH. Tank heaters and 10 layers of MLI provide thermal control for the tanks during 

the long interplanetary coast while a 6000 psia gaseous helium tank, constructed of graphite-wrapped 

aluminum, provides consumables for MPS tank pressurization. 

The reaction control system (RCS) has sixteen pressure-fed thrusters each producing a thrust of 100 

lbf. Each thruster operates at a chamber pressure of 125 psia, a mixture ratio of 1.65, and an area ratio of 

40 delivering an Isp of 301.3 sec. The RCS propellants are stored at 225 psia in two spherical graphitewrapped aluminum tanks, one for NTO and one for MMH. Tank heaters and 10 layers of MLI provide 

thermal control for the tanks during interplanetary coast while a 6000 psia gaseous helium tank, 

constructed of graphite-wrapped aluminum, provides consumables for RCS tank pressurization. 

Ground rules of the study (Appendix A) required the total mass margin be 49.5% of the basic dry 

mass, which includes allocations for both mass growth allowance (MGA) and project managers reserve. 

Figure 4. Propulsion Trade Results
10

Figure 5. Parameteric Performance and Sizing Maps for a Pump-Fed NTO/MMH Rocket 

 

A total of eight cases were evaluated: each of the four architecture concept cases was assessed using 

both an ablative and an insulating TPS. 

Results for the eight cases assessed, summarized in Table 4, are EXAMINE verification results based 

on the final optimized solution provided by the POST2 analysis. The maximum payload delivered from a 

Delta IV-H, using the assumptions presented herein, occurs using the EFF-4 configuration, a direct entry 

at 5.8 km/s, which can deliver a payload of approximately 3.5 t. 

Table 4. Mass Closure Results for each Architecture Concept 
11

3.5 Recommendations for Future Enhancements 

There are several areas that the EFF mass model can be improved in future studies: 

HIAD 

• Perform a trade study to better understand the relation between aeroshell stiffness and 

aerodynamic performance and its impact on aeroshell mass. 

• Investigate whether aeroelastic behavior creates local high curvatures on the aeroshell 

producing localized high heating regions. This could have a significant mass penalty. 

• Verify masses used for rigid load bearing components using a finite element analysis. 

• Investigate the impact of maximum allowable fabric seam loads on inflatable mass. 

• Design inflation system and determine the impact of leaks and ullage on mass. 

Payload 

• Determine the relation between minimum aeroshell diameter, angle attack, and payload 

height. The payload may be exposed to high thermal environment, and it may be required to 

be housed inside a shroud. The mass penalty for the shroud needs to be compared against 

flying at a lower angle of attack as well as smaller aeroshell diameter. 

• Investigate whether a rover can be included with the payload. 

• Investigate telescoping approach to shorten the payload height during EDL phase. 

Overall 

• Develop a higher fidelity model for packaging and assess associated mass penalties. 

• Perform mass trade study for CG and bank maneuver mechanisms 

• Develop viable separation concepts and determine the required mass penalty for each 

concept. 

• Develop a better mass model for different guidance approaches. 

• Investigate feasibility and risk of using pump-fed engines for exploration precursor missions. 

• Perform a packaging effort to determine accurate inertias for 6DOF analysis. 
12

4 HIAD Controllability Assessment 

4.1 Overview 

Five of the eight Year 1 Exploration-class architectures included large HIADs as the light-weight 

alternative to land large payloads. Controllability of HIADs is a major question regarding their feasibility, 

and thus a 6DOF simulation was developed in Year 2 with the intent of characterizing HIAD 

controllability. The Year 1 Exploration-class analysis assumed bank angle control similar to Apollo and 

MSL, which uses a bank acceleration of 5 deg/s2

 and a maximum rate of 20 deg/s. One objective of the 

EFF study (#5 in Sect 1) was to analyze alternative control strategies. Direct center of gravity (CG) 

control, which uses a mechanism to independently move the payload both vertically and laterally to 

generate lift and side forces, was selected for consideration. Additionally, the Year 1 study assumed a L/D 

of 0.25. Based on recommendations at the end of Year 1 to finding the lower L/D limit capability of 

HIADs, EFF considered vehicle L/D’s down to 0.1. Because aerocapture is less complex than EDL, it was 

decided to use a 6DOF aerocapture mission for the controllability analysis. The trade study plan for 

assessing controllability included a L/D range of 0.1 to 0.25, atmospheric HIAD jettison and no jettison, 

and post-aerocapture target orbits of 500 km circular and 1 sol elliptical. In the absence of one guidance 

algorithm designed specifically for CG control, three available guidance algorithms and one new 

algorithm, developed and tested for bank control, were modified to accommodate CG control. What 

follows is a brief discussion of each guidance and control algorithm considered, as well as the description 

of the nominal aerocapture configuration and the results of the various trades performed to evaluate 

HIAD controllability. 

Initial evaluation of the CG controller in the 3 DOF simulation looked promising. However, as the 

modeling fidelity was increased in the 6 DOF simulation, it became apparent that the CG controller, as 

assumed for EFF, did not have the control authority required to successfully fly the EFF architectures. 

Also initial analysis of actuator torques indicated that the power required to move the 2 to 4 t payload 

might be prohibitively high. The CG controller was replaced with the bank controller for all trade studies 

presented in this section. Acknowledging the incomplete CG controller assessment, EFF strongly 

recommends considering alternative CG controllers for HIADs in future system analysis studies. 

4.2 Guidance Algorithms Considered 

4.2.1 Hybrid Predictor-Corrector Aerocapture Scheme (HYPAS) 

HYPAS is an analytical predictor-corrector algorithm that was developed and selected for the 

Aeroassist Fight Experiment, an aerocapture demonstrator mission that was canceled before launch. It has 

been used in numerous human and robotic exploration mission studies over the last 10 years for Earth and 

Mars, and has been proven to be robust to a wide variety of L/D, ballistic coefficients, atmospheres, entry 

conditions, and target orbits. It was considered for both the Mars Surveyor Program 2001 mission, and the 

CNES Mars 2005 Sample Return Orbiter, and later, the CNES Mars 2007 Premier Mission. Unfortunately 

all these missions were canceled before launch. HYPAS targets a lifting vehicle through the atmosphere 

to a desired exit orbit apoapsis and inclination by using an analytically-derived guidance algorithm based 

on deceleration due to drag and altitude rate error feedback to determine the bank angle magnitude, and 

the inclination error to determine bank direction. 

4.2.2 Terminal Point Controller (TPC) 

The TPC is an aerocapture guidance algorithm, closely related to the Apollo Earth Return entry 

guidance. TPC is based on the Calculus of Variations, with boundary conditions derived for the 
13

aerocapture mission. Originally developed for the Mars Surveyor Program 2001 mission, it was later 

adopted by the French space agency (CNES) for the NASA-CNES Mars 2005 Sample Return orbiter. 

TPC is extremely robust and consists of a very little on-board code. A reference trajectory is defined for 

the aerocapture mission and that trajectory is used to develop sensitivities of the terminal point to changes 

in the lift vector at any point along the trajectory. These sensitivities are used to adjust the bank angle 

during flight to achieve the desired apoapsis at atmospheric exit. Lateral control is achieved by reversing 

the sign of the bank angle whenever the lateral error exceeds a variable-width deadband. 

4.2.3 Numerical Predictor-Corrector Guidance (NPC) 

The Numerical Predictor-Corrector algorithm was originally developed as candidate guidance for 

both the aerocapture and entry of the Mars Surveyor Program 2001 mission, and the aerocapture of CNES 

Mars 2005 Sample Return Orbiter. Orion developed NPC guidance for its lunar return. The NPC 

guidance integrates a simplified set of the equations of motion and iterates the appropriate control 

parameter to meet the specified constraints. For the EDL-SA architectures, the NPC guidance determines 

the bank angle profiles and the required propulsion orientation during terminal descent to provide the 

proper landing conditions. Because of the necessity to integrate the equations of motion, the NPC 

algorithm is only called every 10 sec as a worse case approximation. In reality the calculations take a 

fraction of that time. 

4.2.4 Shape Integral (SI) 

The Shape Integral aerocapture guidance is a new guidance algorithm developed at the Langley 

Research Center. This algorithm is based on an algebraic solution to the equations of motion in a plane. 

Normalized integral quantities, termed shape integrals, are calculated from a reference trajectory, 

providing the guidance gains. The velocity equation is first solved to determine the time-to-go. Then the 

altitude rate equation is solved for the appropriate scaling of a reference lift profile that is required to meet 

the targeted terminal conditions at atmospheric exit. Bank reversals are commanded to maintain a wedge 

angle, with respect to the target orbital plane, within set deadbands. 

4.3 Control Algorithms 

Two control actuation schemes were considered for the EFF vehicle. The first was bank angle control 

achieved by applying torques to the vehicle via an assumed RCS system. The second was vertical and 

horizontal lift control achieved by moving massive components, which shifted the center of gravity CG of 

the vehicle. 

4.3.1 6DOF Bank Angle Controller 

Bank angle control was performed using a Linear Quadratic Regulator (LQR) formulation. LQR 

provides a systematic approach to multi-input, multi-output control systems. The EFF controller is based 

on aircraft equations of motion that have been decoupled into longitudinal and lateral/directional subsets 

and linearized. Currently, it is assumed that pure torques about each vehicle axis are available at any level 

desired. The same controller structure is used for both the aerocapture and entry missions with different 

sets of gains. 

4.3.2 6DOF Center of Gravity (CG) Controller 

The CG controller is actually a combination of CG control and a small RCS system to provide roll 

control. A single PID controller commanding a pure roll torque to drive the roll angle to zero provides roll 

control. In the vertical and horizontal channels, the guidance provides a commanded lift. Each of those 

commands is passed to a PID controller, which commands a payload position. The payload position 
14

command is passed to a second order actuator model, which moves the payload and the resultant CG is 

computed by the POST2 trajectory simulation. Forces to move the payload are assumed to be as large as 

necessary, but the actuator limits payload rates and accelerations. 

4.4 Exploration Feed Forward Nominal Configuration 

4.4.1 Nominal Configuration Inputs 

The primary nominal aerocapture parameters used in the controllability analysis are given in Table 5. 

Additional parameters are provided in Appendix D. 

Table 5. Nominal Aerocapture Parameters 

Parameter Value

Aeroshell Diameter 14 m

Vehicle Diameter 4 m

Ballistic Coefficient 33 kg/m2

Lift-to-Drag Ratio 0.25

Target Orbit 500 km circular

Entry Flight Path Angle Guidance 

dependent

These inputs are used to create the baseline EFF aerocapture configuration. The HIAD diameter was 

sized to satisfy a 3-sigma peak heat rate constraint of 50 W/cm2

 keeping in mind the minimum diameter 

constraint to prevent flow impingement. Also the budgeted delta-V required to clean up the postaerocapture orbit to match target orbit was constrained to 250 m/s. The clean up burn was modeled as a 3-

burn maneuver that included (1) an apoapsis raise/lower maneuver, (2) a plane change maneuver and (3) a 

periapsis raise maneuver. 

The Monte Carlo dispersions used in this analysis are given in full detail in slides 5 through 7 of 

Section 7.2 of the slide package presented at the IPR [12]. These dispersions were chosen to be 

intentionally overly conservative in order to stress the guidance. 8000 cases were run for each set of 

Monte Carlo results. 

4.4.2 Aerocapture Monte Carlo Results 

Figure 6 shows aerocapture heat rate and ΔV results for an L/D of 0.25 into a 500 km circular orbit. 

The histogram of heat rate shows these cases essentially met the 3-sigma peak heat rate requirement by 

not significantly exceeding 50 W/cm2, and the maximum delta-V required to cleanup the post-aerocapure 

orbit never approaches the 250 m/s budget. Additionally, the apoapsis values in this configuration form a 

very tight group around 500km, which demonstrates that an L/D of 0.25 is sufficient to hit the target 

apoapsis for this entry speed and target orbit.
15

Figure 6. Heat Rate and Total ΔV for EFF-1 Aerocapture 

4.4.3 Trade 1: L/D of 0.1 Versus L/D of 0.25 

Figure 6 shows that an L/D of 0.25 is sufficient to hit the target orbit apoapsis with the inputs and 

Monte Carlo dispersions listed in Table 5 and the references. Based on inquiries from both Year 1 and 

other technology programs (i.e. IRVE), a trade was performed to determine if the vehicle would still meet 

the target apoapsis, given less commandable lift. Therefore, this study considers differences in 

performance associated with flying at an L/D of 0.25 and an L/D of 0.10. 

Figure 7 shows the Monte Carlo results of the apoapsis and periapsis altitudes for a L/D of 0.10 and 

0.25. The vehicle with the L/D of 0.10 is still able to reach the target apoapsis, but inspection of the 

performance associated with individual lower L/D cases shows instances where the guidance is fully 

saturated. Guidance saturation occurs when the guidance must command maximum lift for the entire 

trajectory, leaving it no authority to fly out additional dispersions. To remedy this, the lateral corridor 

width is expanded for the lower L/D cases resulting in larger plane change maneuver delta-V, as shown in 

Figure 8. 

Figure 7. Apoapsis Altitude vs Periapsis Altitude for L/D = 0.10 (left) and 0.25 (right) 

This study shows that aerocapture using a low L/D vehicle is feasible but will likely result in larger 

propellant use. Additionally, these results are specific to the EFF configuration described. Changes to 

target orbit or entry speed may result in cases that are unable to reach the target apoapsis for a lower L/D 

vehicle. 

!100 !80 !60 !40 !20 0 350

400

450

500

550

600

650

Periapsis Altitude (km)

Apoapsis Altitude (km)

Mean: 509.1

1!Sig:17.9097

3!Sig:53.7292

Min: 359.3

00.13 %!tile: 432.1438

50.00 %!tile: 510.7622

99.87 %!tile: 584.2185

Max: 637.7117

!12.085

!12.016

!11.948

!11.879

!11.810

!11.742

!11.673

!11.604

!11.536

!11.467

!60 !40 !20 0 20 40 450

500

550

600

650

Periapsis Altitude (km)

Apoapsis Altitude (km)

Mean: 514.3

1!Sig:11.6117

3!Sig:34.8352

Min: 473.2

00.13 %!tile: 482.6005

50.00 %!tile: 513.0676

99.87 %!tile: 580.1916

Max: 615.8411

!12.307

!12.240

!12.174

!12.108

!12.042

!11.975

!11.909

!11.843

!11.776

!11.710

130 140 150 160 170 180 0

200

400

600

800

1000

1200

Total Post Aerocapture !V 

Total Post Aerocapture !V (m/s)

Occurences

Mean: 150.5 m/s

Std. Dev: 5.52 m/s

Max: 183.8 m/s

Min: 125.2 m/s

35 40 45 50

0

100

200

300

400

500

600

700

800

Heat Rate

Heat Rate (W/cm2)

Occurences

Mean: 42.68 m/s

Std. Dev: 2.62 m/s

3!Sigma: 50.5 W/cm2

Min: 32.99 m/s
16

Figure 8. Plane Change Maneuver ΔV for L/D of 0.10 (left) and 0.25 (right) 

 

4.4.4 Trade 2: Jettison Versus No Jettison 

Analyzing the results from the L/D trade study, specifically those from guidances that were unable to 

reach the target apoapsis for the lower L/D vehicle, led the team to consider alternatives that might 

improve low L/D performance. Realizing that better performance might be achieved by adding an 

additional control parameter, consideration was given to analyzing the effect of jettisoning the HIAD 

atmospherically. This prompted the following trade study. 

In an attempt to increase the ability of a specific guidance to hit the target orbit apoapsis, a subroutine 

was placed in the guidance, which used the current navigation states to calculated apoapsis at each time 

step. Once that calculated apoapsis reached a 

specified value, the HIAD would be released 

and the vehicle would go from a lifting body 

to drag only. The jettison was modeled as a 

step function in the simulation, where at one 

time step the HIAD is attached and the next 

it is released. Jettisoning the HIAD in the 

atmosphere also allows aerodynamic forces 

to aid in separation. However, details of 

HIAD separation were not considered in this 

study. 

The disadvantage of jettisoning the 

HIAD in the atmosphere is that it only aids 

in hitting the apoapsis target when the 

guidance targets an apoapsis value below the 

desired target. This requires a much steeper 

flight path angle and can result in guidance saturation as well as higher heat rates. The advantage of 

jettisoning the HIAD is that it allows the vehicle to hit very close to the target apoapsis every time by 

essentially fixing the apoapsis value at the jettison point and allowing the vehicle to coast to a lower 

value, as illustrated in Figure 9. 

This trade study considers the effect of the jettison vs. no jettison for vehicles with an L/D of both 

0.10 and 0.25. The first part of this study was performed for an L/D of 0.10, to determine what benefit the 

jettison maneuver might provide. Figure 10 shows the difference in apoapsis and periapsis values between 

the jettison and no jettison cases. By essentially fixing the apoapsis and periapsis values at the jettison 

point, the jettison maneuver allows the vehicle to hit the target with much better accuracy than the no 

200 250 300 350 400 450 500 550

0

250

500

750

1000

1250

1500

1750

2000

Apoapse (km)

Time (s)

Vacuum Apoapse and Periapse versus Time

200 250 300 350 400 450 500 550!300

!260

!220

!180

!140

!100

!60

!20

20

Periapse (km)

200 250 300 350 400 450 500 550!300

!260

!220

!180

!140

!100

!60

!20

20

Jettison

No Jettison

Point of Jettison

0 20 40 60 80 100 0

200

400

600

800

1000

1200

Post Aerocapture !V for PCM (m/s)

Occurences

Mean: 27.93

1!Sig:14.5811

3!Sig:43.7433

Min: 1.237

00.13 %!tile: 3.2099

50.00 %!tile: 20.3661

99.87 %!tile: 74.6979

Max: 95.582

0 20 40 60 80 100

500

1000

1500

Post Aerocapture !V for PCM (m/s)

Occurences

Mean: 12.07

1!Sig:3.2002

3!Sig:9.6007

Min: 0.9878

00.13 %!tile: 2.2651

50.00 %!tile: 12.2412

99.87 %!tile: 22.0967

Max: 28.4746

Figure 9. Vacuum Apoapsis and Periapsis Altitude vs. 

Time With and Without HIAD Jettison
17

jettison case. The smaller distribution in apoapsis and periapsis altitude values is reflected in Figure 10. 

The reduction can also be seen in distribution of periapsis raise maneuver ΔV shown in Figure 11. The 

four points in left of Figure 10 that are above 550 km are the cases where the calculated apoapsis value 

never reached the HIAD jettison condition, thus the HIAD remains attached for the duration of the flight. 

The second part of the study was performed for an L/D of 0.25 to determine if the benefits of the 

jettison maneuver persist at higher values of L/D. The observed effect of the jettison maneuver was a 

tightening of both the apoapsis and periapsis performance. This is evident in Figure 12. However, the 

performance associated with the higher L/D no jettison cases suggest that no additional control parameter 

is necessary to help these cases reach their target orbit apoapsis. 

Figure 10. L/D = 0.10: Apoapsis vs. Periapsis Altitude for Jettison (left) and No Jettion (right) 

Figure 11. L/D = 0.10: Periapsis Raise Maneuver DV for Jettison (a) and No Jettison (b) 

Figure 12. L/D = 0.25: Apoapsis vs Periapsis Altitude for Jettison (a) and No Jettison (b) 

!80 !60 !40 !20 0 20

400

450

500

550

600

650

700

Periapsis Altitude (km)

Apoapsis Altitude (km)

Mean: 502.4

1!Sig:8.1579

3!Sig:24.4738

Min: 457.6

00.13 %!tile: 466.5032

50.00 %!tile: 502.5975

99.87 %!tile: 526.4933

Max: 662.8558

!12.318

!12.249

!12.180

!12.110

!12.041

!11.972

!11.902

!11.833

!11.764

!11.694

!80 !60 !40 !20 0 20

400

450

500

550

600

650

700

Periapsis Altitude (km)

Apoapsis Altitude (km)

Mean: 502.3

1!Sig:27.6292

3!Sig:82.8875

Min: 387.1

00.13 %!tile: 415.1221

50.00 %!tile: 500.0332

99.87 %!tile: 644.5686

Max: 747.5561

!12.086

!12.016

!11.947

!11.878

!11.808

!11.739

!11.670

!11.601

!11.531

!11.462

110 115 120 125 130 135 140

500

1000

1500

2000

Post Aerocapture !V for PRM (m/s)

Occurences

Mean: 114.8

1!Sig:1.8495

3!Sig:5.5484

Min: 111.7

00.13 %!tile: 112.0485

50.00 %!tile: 114.3469

99.87 %!tile: 124.1589

Max: 124.7562

110 115 120 125 130 135 140

100

200

300

400

500

Post Aerocapture !V for PRM (m/s)

Occurences

Mean: 123.4

1!Sig:4.6659

3!Sig:13.9976

Min: 110.5

00.13 %!tile: 112.8625

50.00 %!tile: 123.2653

99.87 %!tile: 136.7037

Max: 139.0492

!80 !60 !40 !20 0 20

450

500

550

600

650

Periapsis Altitude (km)

Apoapsis Altitude (km)

Mean: 496.1

1!Sig:5.4281

3!Sig:16.2842

Min: 476.2

00.13 %!tile: 477.9914

50.00 %!tile: 496.3565

99.87 %!tile: 511.9307

Max: 515.7603

!12.157

!12.081

!12.005

!11.928

!11.852

!11.776

!11.700

!11.624

!11.548

!11.471

!80 !60 !40 !20 0 20

450

500

550

600

650

Periapsis Altitude (km)

Apoapsis Altitude (km)

Mean: 507.7

1!Sig:14.7607

3!Sig:44.282

Min: 448.2

00.13 %!tile: 473.5671

50.00 %!tile: 505.9716

99.87 %!tile: 597.28

Max: 642.2311

!12.317

!12.240

!12.164

!12.087

!12.010

!11.934

!11.857

!11.780

!11.704

!11.627
18

In summary the jettison maneuver does improve the vehicle’s ability to achieve a target orbit for any 

L/D. The necessity for the jettison maneuver becomes less critical at higher values of L/D and the 

decision to employ jettison for higher L/D vehicles will depend on mission specific requirements. 

Additionally, the modeling of the jettison maneuver is crude and factors such as HIAD separation and 

transitions would need to be considered if this concept were to be studied further. 

4.4.5 Trade 3: L/D of 0.25 with 500 km Circular Target Orbit Versus 1 sol Target Orbit 

One final trade study was performed to determine the effect of changing the post-aerocapture target 

orbit for a vehicle with an L/D of 0.25. The apoapsis altitude associated with a 1 sol target orbit is 33,793 

km, making it a much higher target apoapsis, requiring less energy (or ΔV) change compared to the 500 

km circular orbit. The aerocapture maneuver performance is improved when more energy can be removed 

from the aeropass, therefore targeting a much higher apoapsis makes executing the aerocapture maneuver 

more difficult. For the higher apoapsis orbits, velocity error is associated with a large error in target 

apoapsis altitude, which will require a larger ΔV to correct. Additionally, the lack of available corridor 

coupled with velocities that approach exit speeds creates the possibility of some single pass cases that do 

not capture into orbit. 

Figure 13 shows a comparison of apoapsis and periapsis altitudes for the two target orbit cases. 

Noting the difference in plotted scales, the 500 km circular orbit has a much smaller distribution. 

However, the 1 sol cases spend less time in the atmosphere and are able to maintain much higher 

periapsis values. The benefit is evident in the ΔV required to clean up the periapsis altitude error. The 

500 km circular orbit requires almost ten times as much ΔV (average 125 m/s) than the 1 sol orbit 

(average 13 m/s). When the apoapsis clean up burn is included, the total (periapsis + apoapsis + wedge 

angle burns) ΔV required for the different orbits is, on average 150 m/s for the 500 km circular orbit and 

40 m/s for the 1 sol orbit. 

In comparing the two target orbits, it is evident a large ΔV savings is achieved by changing to a target 

orbit with a higher apoapsis altitude but the propellant savings is at the cost of increased risk of skip-out. 

The results of this trade study are specific to the mission assumptions outlined here. Further work is 

needed to completely characterize the risk of skipping out of high-energy orbit as the L/D or approach 

velocity decreases. 

Figure 13. Apoapsis vs. Periapsis Altitude for the 1 sol (left) and 500 km circular (right) target orbits 

4.5 HIAD Controllability Conclusions 

Despite the results shown in the previous section, the HIAD controllability study is incomplete due to 

the lack of a full assessment of the CG controller. However, the information learned by evaluating 

guidances using the bank angle controller did reveal useful information for current and future studies. 

20 25 30 35

2

3

4

5

6

x 104

Periapsis Altitude (km)

Apoapsis Altitude (km)

Mean: 3.126e+04

1!Sig:2671.0098

3!Sig:8013.0294

Min: 1.976e+04

00.13 %!tile: 25501.9739

50.00 %!tile: 30954.5759

99.87 %!tile: 54774.8887

Max: 69704.9488

!12.105

!12.036

!11.966

!11.897

!11.828

!11.758

!11.689

!11.620

!11.550

!11.481

!80 !60 !40 !20 0

420

440

460

480

500

520

540

Periapsis Altitude (km)

Apoapsis Altitude (km)

Mean: 506.6

1!Sig:19.453

3!Sig:58.3589

Min: 409.9

00.13 %!tile: 429.5245

50.00 %!tile: 508.5451

99.87 %!tile: 550.9882

Max: 552.8221

!11.825

!11.761

!11.697

!11.633

!11.569

!11.505

!11.441

!11.377

!11.313

!11.249
19

First, the nominal EFF aerocapture mission using a L/D of 0.25 provides sufficient targeting capability 

while satisfying the constraints. Second, during the EFF study, the IRVE 4 team has uncovered potential 

dynamics due to flexure at the joint between the rigid heat shield and the HIAD that need to be included 

in future systems analysis studies. Third, the bank angle control was marginal (large number of 

trajectories saturated) for an L/D = 0.10 with no HIAD jettison. Forth, jettisoning the HIAD while in the 

sensible atmosphere indicates a capability to improve targeting, but more analysis is required to determine 

if it is a viable option. Finally, CG control was demonstrated in 3DOF trajectories to be a viable option, 

however, the 6DOF analysis uncovered issues that require further examination. The primary issue 

concerns how using CG control to both control and trim the vehicle induces dynamics that may require 

large actuator accelerations. One recommendation is to add other CG control options to the design space, 

which, for example, uses the CG control for trim and an RCS system to control the induced dynamics. 
20

5 ALHAT Sensor Assessment 

The objective of the ALHAT sensor assessment for EFF was to develop a 6DOF entry simulation to 

determine the sensor performance ranges for an ALHAT-like navigation and sensor system at Mars. The 

EFF simulation was developed and used to run initial integrated GNC and sensor performance and 

evaluate of SRP for Hazard Detection and Avoidance (HDA) and Terrain Relative Navigation (TRN). 

The EFF simulation included 6DOF entry with Apollo entry guidance and an LQR bank angle controller 

and 3DOF powered descent with Apollo powered descent guidance and a pseudo controller. The ALHAT 

Extended Kalman filter (EKF) is also included in the simulation, but it did not include TRN update 

capability. However, statistically-based IMU, startracker, altimeter and velocimeter models were 

integrated in the simulation and utilized in the analysis. 

The Apollo entry guidance, showing integrated guidance and controller performance with 6DOF 

entry Monte Carlo results are shown in Section 6.1. The SRP powered descent study and trajectory design 

and sensor feasibility is presented in Section 6.2 with 3DOF descent Monte Carlo results and flight 

condition assessments for HDA and TRN at Mars. Section 6.3 discusses initial results of the fully 

integrated GNC system & sensor performance, focusing on the ALHAT navigation filter, with 6DOF 

entry and 3DOF descent Monte Carlo results, without TRN versus an ideal TRN case for comparison. 

5.1 Entry Guidance Performance 

The entry guidance used in the Study is an Apollo-derived entry guidance. The Apollo-derived entry 

guidance algorithm is a terminal point controller that steers the vehicle to a HIAD separation point though 

bank commands that are based on deviations in range, drag acceleration and altitude rate from a stored 

reference trajectory (Figure 14). In the reference trajectory, the bank value of 45° for the constant bank 

phase is based on the expression 

Bankmin = acos(100%-ρ%-Cd%), 

where ρ% and Cd% are the dispersions in atmospheric density and on the drag coefficient, respectively. 

The lateral corridor is determined such that the number of reversals is 3 (the bank reversal deadband 

quadratic coefficients are 0.025 [first reversal] and 0.064, with the deadband constant coefficient being 

0.5). The nominal final altitude of the reference trajectory is determined such that all the powered descent 

dispersed cases are successful. 

Figure 14. Reference Bank Profile 

The performance was assessed using 6DOF Monte Carlo analysis comprised of 8000 runs with 

simple propagator navigation (Figure 15). The L/D overcontrol gain used is 2 and the overcontrol gain of 
21

the heading alignment phase is 60. Downrange error is not shown because the simulation end condition is 

based on range, thus, the downrange error is very small at separation. Downrange error at engine 

initiation is within ±200 m. The dispersions used in this phase are found on Appendix C. 

Figure 15. Entry Performance Summary 

Using the defined dispersions, the design of the entry guidance is capable of achieving the engine 

initiation conditions such that all the powered descent dispersed cases can be landed successfully. 

However, this design of the entry guidance should not be considered as a final design. There is room for 

improvement by fine tuning and improving the guidance parameters that affect the performance 

(reference profile, over-control settings, initial flight path angle, drag acceleration and L/D filter time 

constants and the drag and altitude controller gain scale factors).

5.2 Powered Descent Performance 

The objective of the powered descent is to steer the vehicle to a controlled touchdown using the main 

propulsion engines. The following assumptions were made for the powered descent analysis: 

• Apollo LM-derived guidance (2nd order polynomial in acceleration) 

• Initial states for powered descent from entry Monte Carlo results 

• 3-DOF pseudo control with 20 deg/sec and 5 deg/sec2

 attitude limits 

• Perfect navigation 

• Target touchdown velocity is 1 m/s vertical, 0 m/s horizontal 

• Fly out all position error prior to touchdown 

• 8000 case Monte Carlo 

• Dispersions as shown in Appendix D 

The termination conditions for entry were chosen such that all dispersions could be removed with the 

minimum amount of fuel. If the termination altitude for entry were lower, some cases would not be able 

to successfully achieve the target touchdown conditions. If entry were to end at higher altitude, additional 

fuel would be needed for powered descent. The 99.87%-tile value for propellant consumed was 870.5 kg. 
22

The 0.13%-tile value for propellant remaining at touchdown was 249.5 kg. Given the current dispersions 

and entry performance, the powered descent has sufficient propellant margin. Further study showing the 

effect of navigation on powered descent was completed and is discussed in Section 5.3. 

5.2.1 TRN and HAD Feasibility 

A brief investigation of feasibility of both TRN and HDA was undertaken. TRN works over a wide 

range of altitude and velocity and is possible anytime sensor measurements can be taken and a highquality map of the terrain is available. There are two basic forms of TRN; optical TRN, which uses 

optical cameras in the visible spectrum, and active TRN, which uses an altimeter, flash lidar, or other 

active sensor. Fundamentally, all that is needed is to ensure that this sensor has a view of the surface and 

that the navigation has a reasonable estimate of the vehicle’s inertial position. Since the attitude profile 

during the first 60 sec is well off of the vertical (see Figure 16), it can reasonably be assumed that TRN 

measurements can be taken and that TRN is feasible. 

Figure 16. Pitch Profile During Powered Descent 

Feasibility for HDA is more complex to demonstrate than for TRN. The flash lidar must scan the 

landing area, so it requires a line of sight to the landing area at the correct time during the descent. The 

lidar will be designed for optimum performance at a particular slant range from the landing site. The scan 

must occur at this distance to ensure that sufficient resolution is achieved and the full landing area can be 

scanned. 

An initial analysis of the nominal trajectory shows that HDA is feasible for the nominal by looking 

out the back side of the vehicle (in the same direction in which TRN would occur) at an altitude of 1 km. 

However, in dispersed cases the look angle may be close to zero and the distribution may be both positive 

and negative at the time of the scan. This would require two sensors, one on each side of the vehicle. The 

trajectory can likely be redesigned such that all look angles are positive, for a minimal cost in additional 

propellant usage – and only would require one HDA sensor. Further investigation is needed before a 

conclusive determination can be made regarding HDA feasibility. 
23

5.3 Navigation Performance 

The ALHAT navigation filter used in the study is an EKF that provides estimates of the vehicle state 

(inertial position, inertial velocity and attitude quaternion). The EKF uses the IMU for propagation while 

it receives updates (in the form of altimeter, startracker, velocimeter and TRN measurements) to improve 

state estimation. The ALHAT EKF initial performance and functionality was analyzed by running two 

Monte Carlo simulations, one with and one without TRN measurements. Since the delivery of the filter 

did not contain a TRN update capability, TRN measurements were mimicked using the simple propagator 

navigation filter for a comparison case. The following assumptions were used in the ALHAT EKF Monte 

Carlo: 

• 2000-dispersed cases 

• Same aerodynamic, atmosphere and initial state dispersed inputs as aerocapture Monte Carlos 

(Appendix D) 

• Dispersed sensor inputs (Appendix E) 

• 6DOF entry with Apollo entry guidance and LQR controller 

• 3DOF powered descent guidance and pseudo controller 

• Startracker measurements off at entry interface 

• Altimeter measurements start at engine ignition 

• Velocimeter measurements start at 2 km altitude 

• No TRN 

The comparison Monte Carlo has the same assumptions as the ALHAT EKF Monte Carlo, but was 

run with simple propagator navigation filter reducing navigation error manually during SRP to mimic 

TRN updates of an ideal ALHAT system. Three ‘mock’ TRN measurements were taken at 5 km, 2 km 

and 1 km altitudes. 

Inertial navigation position and velocity error throughout the trajectory, as well as range-to-target at 

touchdown, were parameters used to initially evaluate the ALHAT EKF performance. At deorbit, or 

simulation initialization, initial inertial position navigation error was 3.5 km (99.87%-tile) and inertial 

velocity navigation error was 3.5 m/s (99.87%-tile). These errors are very conservative and may be 

adjusted with sensor measurement updates prior to deorbit. The resulting inertial navigation position 

error at entry was improved through propagation of the IMU updates to 3 km (99.87%-tile) and inertial 

velocity error was 3 m/s (99.87%-tile). The altimeter updates in the ALHAT EKF Monte Carlo began at 

engine ignition (nominally, 6 km altitude) and improve the altitude navigation error from 3.4 km (44% 

error) down to 11 m (1% error) (99.87%-tile), also improving inertial navigation position error from 4 km 

down to 2.8 km (99.87%-tile) at touchdown. The velocimeter updates in the ALHAT EKF Monte Carlo 

began at a 2 km altitude and improve relative velocity error from 3 m/s (1% error) down to 2 cm/s (0.01% 

error) (99.87%-tile), also improving inertial navigation velocity error from 5 m/s down to 17 cm/s (3-

sigma). Fuel remaining at touchdown was similar to powered descent study results with perfect 

navigation discussed in Section 6.3. The results showed good initial ALHAT EKF performance. The 

range-to-target at touchdown, using the navigation updates and SRP, can get within 2.4 km (99.87%-tile) 

of the landing target. However, more improvement in navigation position error is needed to reduce the 

touchdown footprint. 

The ALHAT EKF Monte Carlo (no TRN) was compared to an ideal TRN Monte Carlo where three 

TRN updates were mimicked as position navigation error reductions down to 85 m (conservative, based 

on ALHAT project analysis) during SRP. Results showed that inertial navigation position error was 
24

reduced from 4 km at engine ignition down to 125 m (99.87%-tile) at touchdown, compared to a 

reduction down to only 2.8 km (99.87%-tile) from the ALHAT Monte Carlo results. Improvement in 

navigation position error in form of TRN updates is needed to reduce the touchdown footprint. 

Figure 17 shows scatter plots of downrange and crossrange for both Monte Carlos at engine ignition 

and touchdown. TRN updates are needed to get within 100 m (99.87%-tile) of the landing target. 

Figure 17. Range Scatter Plot Comparison at Engine Ignition and Touchdown. 

The initial results of the ALHAT EKF performance analysis show good navigation performance using 

SRP (with altimetry and velocimetry updates) and initial TRN comparison during descent to reduce 

navigation position error for precision landing. SRP during descent and altimetry and velocimetry 

navigation updates can get within 2.4 km of the landing target (99.87%-tile). However, TRN (or similar 

sensor) is needed to get landing accuracy down to 100 m (99.87%-tile) or less. For future work, TRN 

update capability in ALHAT EKF is needed to fully assess ALHAT navigation performance and to study 

TRN operating ranges and timing trades.

5.4 Recommendations and Future Work 

As a result of the study, the following investments are recommended: 

• Examine ALHAT-developed sensors for use in Mars EDL (to include laser altimeter, Doppler 

lidar velocimeter, and flash lidar) 

• Perform additional performance and feasibility studies concerning the use of TRN for Mars 

EDL 

• Investigate adapting HDA for Mars EDL and the effect on vehicle design 

Future Mars EDL studies should consider performing the following work: 

• Update current baseline navigation and integrated GNC performance with latest filter and 

sensor models 

• Update ALHAT sensor models and operating ranges for Mars 

• Update Star tracker operating range and conditions 

• Perform GNC performance sensitivity to measurement quality and availability 

• Perform early TRN Study 
25

• Trade timing, number of TRN measurements. Consider feasibility of performing TRN prior 

to Powered Descent. 

• Perform divert sensitivity study 

• Perform detailed HDA analysis for Mars landing 

• Consider terrain, landing footprint size including GNC errors, lidar performance, etc. 
26 

6 Conclusions 

This document attempts to summarize the analysis performed to evaluate feed forward technologies 

in a realistic but hypothetical mission to land a 2 to 4 t power plant on Mars. Table 1 in Section 1 

presents the major technology recommendations that resulted from the analysis presented in Sect 4, 5 and 

6. Much of the EFF effort focused on detailed subsystem model development, which uncovered many 

unanticipated issues. The remaining time was spent upgrading the POST2 simulation to incorporate and 

check the detailed models. Consequently, the analysis results were incomplete in some aspects as the 

team prepared of the final EDL-SA technical meeting, the EFF IPR. Software configuration management 

proved to be instrumental in allowing for rapid analysis of all aspects of the design late in the project 

schedule. The major recommendation from EDL-SA is that high fidelity systems analysis can leverage 

work being done at many NASA centers to identify advantages and disadvantages of specific 

technologies considered for investment. 

7 Bibliography 

1. Dwyer Cianciolo, A. M., et al. “ Entry, Descent and Landing Systems Analysis Study: Phase 1 

Report.” NASA/TM-2010-216720

2. Drake, B. G., editor., “Human Exploration of Mars Design Reference Architecture 5.0,” s.l. : NASASP-2009-566, July 2009 

3. Entry, Descent and Landing Systems Analysis (EDL-SA) for High Mass Exploration and Science 

Mars Mission Systems: Final Report, EDLSA-005, January 2011 (unpublished)

4. Mason, L. S., “A Summary of NASA Architecture Studies Utilizing Fission Surface Power 

Technology,” AIAA-2010-6599. 

5. Samareh, J. A., and Komar, D. R., “Parametric Mass Modeling for Mars Entry, Descent and Landing 

System Analysis Study,” AIAA-2011-1038, presented at the 49th AIAA Aerospace Sciences Meeting 

including the New Horizons Forum and Aerospace Exposition, Orlando, Florida, Jan. 4-7, 2011 

6. McGuire, M.K., Arnold, J. O., Covington, M.A. and Dupzyk, I. C. “Flexible Ablative Thermal 

Protection Sizing on Inflatable Decelerator Systems Technology for Human Mars Entry, Descent and 

Landing, AIAA Conference, Orlando FL, January 2011 AIAA-2011-344 

7. Beck, R. A. et al. “Overview of Initial Development of Flexible Ablators for Hypersonic Inflatable 

Aerodynamic Decelerators”, 21st AIAA Decelerator Conference and Seminar, 23-26 

May2011,Trinity College, Dublin, Ireland

8. Komar, D.R., Hoffman, J., and Olds, A., “Framework for the Parametric System Modeling of Space 

Exploration Architectures,” AIAA-2008-7845, 2008 

9. http://www.astronautix.com/props/hydazine.htm

10. http://en.wikipedia.org/wiki/Atlas_V

11. http://www.spaceandtech.com/spacedata/engines/rs72_specs.shtml

12. Dwyer Cianciolo, A. M., et al. “Entry, Descent and Landing Systems Analysis Exploration Feed 

Forward Internal Peer Review Slide Package”. NASA/TM-2011-217050
27

8 Appendix A - Design Reference Mission, Ground Rules and Assumptions 

and Evaluation Criteria 

This material is taken directly from Entry Descent Landing Systems Analysis for Large Robotic and 

Human Precursor Class Missions. Report of the Design Reference Missions, Ground Rules and 

Assumptions and Evaluation Criteria, EDLSA-004, June 28, 2010, and is included here for convenience. 

8.1 Design Reference Mission 

A Design Reference Mission (DRM) describes the objectives and top-level requirements for a 

representative future mission for the purposes of facilitating choices of architectures and technologies for 

a class of missions. The EDL-SA Year 2 Study encompasses two such classes—MSL-Improvement and 

Feed Forward. This section provides a summary of the respective DRMs for these two mission classes 

that will be used in the EDL-SA Study. 

This section provides a summary of the respective DRM that will be used in the EDL-SA Feed 

Forward Study. 

The DRM for the Feed Forward Study mission is designed to address technical issues identified in 

EDL-SA Year 1 that affect development planning. The configuration is based on results from Year 1 

work, which indicated that the masses of a single use HIAD for aerocapture and a single use HIAD for 

entry might offer a lighter arrival mass option compared to a single dual use ablator TPS HIAD (Year 1 

Architecture 2 and 6) provided heat rates could be kept below 50 W/cm2. Since the Feed Forward study 

considers the precursor mission class, the payload mass is much smaller (~2 t) compared to the Year 1 

study (40 t payload). 

Therefore, the DRM for the Feed Forward effort includes an insulator TPS HIAD for aerocapture into 

a 500 km circular orbit. After some TBD time the HIAD is jettison prior to entry. Also in orbit prior to 

entry, the second HIAD is inflated. A deorbit burn is initiated and the vehicle enters the atmosphere of 

Mars at ~3.35 km/s. From the results of the Year 1 study, it was not clear whether bank angle control is 

feasible especially for HIADs with very large diameters. The decision was made to consider alternative 

modes of HIAD control. For this reason, center of gravity control has been considered for the nominal 

control method for the Feed Forward architecture. A full evaluation will be made regarding the control 

authority required and by the vehicle compared to the control authority physically available within the 

packaged vehicle. The vehicle will use a theoretical guidance to fly to a specified target. At Mach = ~2, 

the supersonic retro-propulsion will be activated and used to complete the terminal descent. Finally, the 

vehicle will slow to 1 m/s and maintain that velocity for five seconds prior to touch down at 0 km above 

the MOLA areoid. An illustration of the nominal DRM is provided in Figure 18. Table 6 provides a list 

of key parameters for the Feed Forward DRM. The notional payload for this DRM is a Movable Nuclear 

Power System (MNPS) [4], described in “A Summary of NASA Architecture Studies Utilizing Fission 

Surface Power Technology” and illustrated in Figure 2. For this uncrewed DRM, the H2O Shield is 

unnecessary. The CBE mass of the remaining components of the MNPS is approximately 2 t for the 10 

kWe system. To this payload must be added the mechanisms necessary to deploy the payload on the 

surface and the margins. This DRM is in conjunction with an additional lander with the demo system to 

be powered by the MNPS, e.g., an ISRU demo. The Feed Forward Study only considers the single 

mission for deploying the MNPS, using this payload (for which a detailed MEL and a CAD model exist) 

for representative volume, mass and inertias of a Feed Forward mission payload. 
28

Table 6. Key Parameters for Feed Forward DRM 

 Figure 18. Feed Forward DRM 

8.2 EDL-SA Ground Rules and Assumptions 

This section lists the Ground Rules and Assumptions (GR&A) as employed in the EDL-SA Study. 

8.2.1 General Ground Rules and Assumptions 

The ground rules and assumptions applicable to both robotic studies are 

• Mass growth allowances and margins will be applied to all technologies and systems as described 

in Sect. 8.2.3. 

• Subsystem performance parameters (e.g., engine Isp, engine T/W, vehicle inert mass fraction) are 

to be based upon historical data and trends. 

• The atmosphere model used for this study will be MarsGRAM 2005. 

• Turbulent flow onset will be estimated using the Reθ = 200 criterion. For Reθ >200, the entire 

forebody will be considered to be turbulent. 

• POST2 will be used for simulations. 

• Representative guidance algorithms will be developed. Theoretical guidance algorithms will also 

be used. 

Parameter Value

Launch

 Vehicle Delta IV-H

 Shroud Diameter 5 m

 Launch C3 15 km2/s2

Arrival

 Velocity 7.3 km/s

 Mass 7.2 t

 Orbit Aerocapture into a 500 

km circular orbit

 HIAD Shape 65 deg sphere cone

Entry

 Velocity 3.35 km/s

 HIAD Diameter TBD

 Nominal Control Method Center of Gravity

 SRP Mach range Mach >2

 Payload >=2 t

 Mass Properties TBD

 Loads paths and Attach points TBD

 Date

 Landing Altitude 0 km MOLA

 Landing Precision <50 m

 Keep Out Zone 1 km
29

• Vertical velocity at touchdown will be <= 1 m/s. 

• On-orbit assembly will not be considered. 

• Landed altitude capability will be a minimum of 0 km above MOLA. 

• Landing site altitude sensitivities will be evaluated for -1 km MOLA to 2.5 km MOLA. 

• Entry date: October 15, 2025. 

8.2.2 Feed Forward Study Ground Rules & Assumptions 

The following ground rules and assumptions are applicable to the Feed Forward Study. As the Feed 

Forward Mission DRM is intended to be a flight test of Exploration-class technologies, many of the 

ground rules and assumptions of the Exploration-class Study are included. 

• Launch vehicle will be the Delta IV-H.

• Emphasis is given to those technologies that emerged from the Exploration-class Study as 

promising new technologies for landing 40 t of payload. 

• Landed payload will be at least 2.0 t, constrained only by the capability of the Delta IV-H for the 

worst (highest arrival velocity) opportunity (2024) in the 2018–2028 time frame. [Note this 

assumption is changed from the original approved GR&A document] 

• Separation events will be modeled on the basis of conceptual mechanical designs. 

• Any shed drag device must never pass any closer than 1 km. to the target at any point in its 

trajectory (“keep-out zone” criterion). 

• Simulations will include a method (e.g., divert maneuver, fly away) to ensure the “keep out zone” 

criterion is met. 

• Aerocapture will be used to insert the vehicle into a 500 km apoapse orbit that will be circularized 

propulsively. 

• Vehicle will be 3 axis stabilized 

• Telecom is assumed to have body fixed antennas 

• Back of lander has solar arrays 

• HIADs are assumed to be rigid bodies 

• Structure will be sized based on loads and will include plumbing, legs, guide rails, actuators, 

thruster placement 

• System will assume sensor integration package (like MEDLI) 

• Only the final configuration selected for packing analysis will receive ALHAT 6DOF 

characterization 

• Subsystem performance parameters, e.g., engine Isp, engine T/W, inert mass fraction, will be 

based on historical data and trends. 

8.2.3 Mass Growth Allowance and System Margin Policy 

The design margins utilized in most previous Mars architecture/EDL studies have been quite 

optimistic. Indeed, some studies have carried no margin at all, and others have applied margins only to 

mass. The EDL-SA Study will use an integrated margin approach that is derived from current practice in 

the early phases of flight projects, e.g., development projects in the robotic missions in the Mars Program. 

This margin approach will provide an appropriate level of realism to the study results. 
30

General Margin Policy 

In developing mass estimates, three separate estimates should be provided. These are: 

Current Best Estimate (CBE) Mass: This mass constitutes an assessment of the most recent baseline 

design including factors of safety or various knockdown factors. The estimate does not include any mass 

growth allowance. 

Maximum Expected Value (MEV) Mass: This constitutes the CBE mass with the addition of mass 

growth allowance (MGA), where mass growth allowance consists of the predicted changes to the CBE 

based on an assessment of the design maturity. 

MEV Mass = Current Best Estimate + Mass Growth Allowance 

Allocated Mass: The allocated mass is the MEV mass with the addition of system margin. 

Allocated Mass = MEV Mass + System Margin 

The total mass growth allowance does not include any TRL-based augmentation. 

Feed Forward Unique Margin Policy 

The Feed Forward Study uses a baseline Mass Growth Allowance of 15%, based on the typical 

recommended range of 10–20% for designs at the layout stage given in AIAA S-120-2006. 

The system dry mass margin is taken to be 30%, based upon the recommended value in GSFC-STD1000E for a Pre-Phase A design. 

8.2.4 Monte Carlo Parameters 

The simulations used to perform system analyses in this study utilize Monte Carlo procedures to 

account for various uncertainties in the system and its environment. The uncertainties include both 

aleatory (variability) and epistemic (lack of knowledge) ones. We adopt the customary approach of 

describing the uncertainties by using probability density functions (PDFs). The PDFs represent the degree 

of belief about the distribution of the uncertain quantities—not only the nominal (most likely) values, but 

also their distribution between their plausible upper and lower limits. Of course, these subjective choices 

are informed by the statistical data that does exist and the team’s experience with Monte Carlo 

simulations of previous Mars missions (Mars Exploration Rovers, Phoenix, MSL). Conservative 

adjustments were made because of lack of detailed information (experimental data, high-fidelity analyses) 

on current concepts. Table 7 and 8 list the parameters that are treated probabilistically in the MSL-I and 

the Feed Forward Studies, respectively. For each uncertain parameter, the rationale for the choice of 

distribution is included. The aerodynamic databases used in the simulations are based upon engineeringlevel tools. Multipliers on the aerodynamic coefficients model the uncertainties in these data. The model 

for the uncertainty in the Mars atmosphere is the model contained in MarsGRAM; the range for the 

random number seed is provided in the tables. Atmospheric density and wind perturbations are applied to 

all cases except the nominal.
31

Table 7. MSL-I Robotic Study Monte Carlo Parameters 

Parameter Nominal Perturbation Distribution Rationale

Entry State 

Delivery and 

Knowledge 

Error

Position, 

Velocity as 

necessary to 

impact 

desired 

landing site.

Per Entry States 

File

Normal Entry states file generated assuming a 

MSL DSN only attitude control system. 

Nominal entry state determined to be 

consistent with the Earth/Mars transfer 

trajectory and desired landing location for 

the date and time assumed.

Attitude 

Knowledge 

Error

Angle of 

Attack = 

30deg.

Bank = 70 

deg.

0.25 deg about a 

varying rotation 

axis.

Direction of 

rotation axis 

computed 

uniformly in all 

directions (i.e. 

spherical 

distribution).

Again, a dsn only attitude control system 

is assumed. 

Mass Normal

Angle of 

Attack (deg)

Case 

dependent 

+/- 2 Normal The nominal angle of attack will vary to 

achieve the desired nominal L/D. 

Perturbation value is typical variation 

from the ideal due to stability oscillations 

about the nominal trim angle.

Axial Force

Coefficient 

Multiplier 

-1 +/- 10 % Normal Larger than would be expected to provide 

sensitivity analysis. The sensitivity 

characteristics of the technology are 

important considerations. Also the 

aerodynamics are uncorrelated, to further 

magnify the sensitivities. Many 

technologies will look good at their 

design point – one major discriminator 

will be sensitivity.

Normal Force

Coefficient 

multiplier

1 +/- 10 % Normal See Axial Force Coefficient Multiplier 

discussion.

Atm Random # 1 1-29999 Integer Uniform This is used by the atmosphere program 

to determine the variability in the density 

and wind profiles. The range is that 

allowed by the Mars atmosphere program 

used in the simulation. Also, other 

atmospheric parameters have been set, 

based on MSL experience, that would 

further stress the system.

Dusttau 0.7 0.1:0.9 Uniform This determines the dust loading and thus 

the density and wind profiles that the 

vehicle will experience. This range 

provides large variability, but would not 

include dust storms.
32

Table 8. Feed Forward Robotic Study Monte Carlo Parameters 

Parameter Nominal Perturbation Distribution Rationale

Mass Variation (kg) 0 +/- 100 Normal Not currently used – Sensitivity to 

ballistic coefficient needs to be 

quantified as the study matures – i.e. 

those technologies with less 

sensitivity would be favored over 

those with a high sensitivity. (also 

this sensitivity will be nonlinear in 

many instances). To minimize the 

number of Monte Carlo scripts that 

must be certified, this capability has 

already been added – but will not be 

exercised until later in the study.

Axial Force

Coefficient 

Multiplier 

-1 +/- 10 % Normal Larger than would be expected to 

provide sensitivity analysis. The

sensitivity characteristics of the 

technology are important 

considerations. Also the 

aerodynamics are uncorrelated, to 

further magnify the sensitivities. 

Many technologies will look good 

at their design point – one major 

discriminator will be sensitivity.

Normal Force

Coefficient 

multiplier

1 +/- 10 % Normal See Axial Force Coefficient 

Multiplier discussion.

Atm Random # 1 1-29999 Integer Uniform This is used by the atmosphere 

program to determine the variability 

in the density and wind profiles. 

The range is that allowed by the 

Mars atmosphere program used in 

the simulation. Also, other 

atmospheric parameters have been 

set, based on MSL experience, that 

would further stress the system.

Dusttau 0.1:0.9 Uniform This determines the dust loading 

and thus the density and wind 

profiles that the vehicle will 

experience. This range provides 

large variability, but would not 

include dust storms.

8.3 Evaluation Criteria 

The Feed Forward Robotic Study will use the following strategy for selecting an optimal Feed Forward 

system design. 

The nominal DRM for the FF study is described in section 8.1. The strategy for selecting an optimal 

design will include a three-step process. Step 1 will be to select the controller based on 6 DOF 

aerocapture simulations. Three controllers will be considered: y and z center of gravity (cg) control, bank 

angle control and a cg and bank combination controller, henceforth known simply as the combo 

controller. The controller will be selected based on the minimum number of failed (outlying) aerocapture 

trajectories, the maximum corridor width and ease of physical implementation. None of the control 
33

methods have been employed on vehicles of this size. Several detailed configurations will be generated 

to ensure that the vehicle does allow for the control authority required to adequately land the vehicle at 

the specified location. 

The second step will use the control method selected from Step 1. Step 2 will use the 6DOF 

aerocapture simulation and a 3 DOF entry simulation to determine which type of TPS material to be used 

on the aerocapture HIAD by considering HIAD size, controllability and packaging. The options include 

the insulator (case already set up from step 1) and the ablator. The trade will compare the potential 

reduction in development cost using the insulator because the same design potentially can be used for the 

entry HIAD compared to the advantage of packaging and controlling a smaller ablative TPS HIAD for 

aerocapture. 

The third and final step in the Feed Forward selection process will be to trade the configuration 

determined in Step 2 using the control method selected in Step 1 and trade the use of one dual use HIAD 

for aerocapture and entry versus using a two HIAD system (one larger HIAD for aerocapture and a 

smaller one for entry). In conjunction with Step 3 of the design selection process, detailed packaging 

analysis will be performed so that approximations of the inertias can be incorporated into both a 6DOF 

aerocapture and entry simulation. The goal of the design is to illustrate detailed packaging arrangements, 

ensure that the inertias are stable and that 6DOF system closes while providing maximum landed payload 

to the surface of Mars. 

The ALHAT sensor suite will be included only in the final Feed Forward design configuration. 

Sensor operation ranges will be determined using the 6DOF entry simulation. The results will be 

provided to the ALHAT team. 

In summary, the down select process for the Feed Forward effort involves five simulations, which are 

shown in Table 9. 

Table 9. Feed Forward TPS and Control Method Options 

Design NOM A B C D

AC TPS Insulator Insulator Insulator Ablator

Entry TPS Insulator Insulator Insulator Insulator Nom, A, B or C

Ctrl Method CG Bank Combo Nom or A or B Nom or A or B

8.4 Feed Forward Study Products 

The high-level products expected by the EDL-SA funders, as approved by CCRB and TISC decisions, are 

listed in Table 10. 

Table 10. High-level Products for FF Study 

Maximum payload the Delta IV-H can deliver

Required performance of supersonic retro-propulsion system

Next level of detail on packaging, mass properties, transitions, structures, propulsion, etc

Optimum material/TPS, L/D, and size of the HIAD for aerocapture and entry

Determine if active cg control provides benefits over the use of bank only

Determine the sensor performance ranges for an ALHAT like navigation & sensor system at Mars

It is expected that a final Technical Memorandum (TM), or similar, will be generated that will 

document a summary of all the products discussed above. 
34

Appendix B - EDL Technology Needs 

Category Technology TDP Objective-EDLSA Exploration Class Missions 

(Year 1) Mars EDL Rationale Refinements from EDLSA Exploration Feed Forward Study (Year 2)

Sub-Scale Component Analysis, Testing & Evaluation

Aeroshell/TPS 

Design and Dev

Rigid Aeroshell 

Tools

Develop, calibrate and validate tools & processes for 

generating aero/aerothermal databases with credible 

uncertainty estimates for slender rigid 

entry/aerocapture vehicles. Builds on existing low 

TRL (1-3) R&D program in ARMD.

Lower uncertainty aero/aerothermal database 

tools enable margin reduction for rigid aeroshells

Use software configuration control mechanisms 

for better productivity and verifiability

Aeroshell/TPS 

Design and Dev

Dual Heat-Pulse 

TPS

Maturation of rigid, dual heat-pulse TPS capable of 

Mars aerocapture, cool down in orbit, and subsequent 

entry with a single aeroshell 

Enables single heat shield (and structure) for 

aerocapture & entry, resulting in lower mass and 

cost

No refinements identified

Aeroshell/TPS 

Design and Dev

Rigid Aeroshell 

Vehicle Design 

Studies

Design and test rigid aeroshell shapes for 

aerodynamic performance and controllability for Mars 

aerocapture and entry. Perform pre-Phase A design 

for packaging, structures, and mechanisms in order to 

assemble Manufacturing Development Units. 

Trade studies and pre-Phase A design activities 

are necessary to ensure technology viability and 

to assess mass, volume and design maturation

Consider size, shape and mass optimization 

based on new knowledge that potential Mars 

Payloads will be significantly shorter than 

assumed for DRA5 (i.e. 10x13 m rather than 

10x30 m). Also need to fully examine all 

transition maneuvers.

SS Retro-Prop 

Dev

Supersonic 

Retro-Propulsion

Assess range of feasibility of using propulsion for 

supersonic deceleration for Exploration scale 

missions, considering multiple nozzle configurations 

and locations along with representative vehicle 

configurations 

Supersonic deceleration is a key technology 

gap, that appears to have a single-point 

technology solution—Supersonic 

Retropulsion—for landing large payloads on 

Mars. Aerodynamic decelerators do not meet 

the supersonic deceleration requirements of 

Exploration-class missions.

Recommend to accelerate SRP development 

to a point that feasibility has been 

demonstrated ASAP

Deployable/Inflt 

Decel Dev

Flexible 

Aeroshell Tools

Develop, calibrate and validate tools & processes for 

generating aero/aerothermal databases with credible 

uncertainty estimates for flexible entry/aerocapture 

vehicles, including aeroelastic effects. Builds on 

existing low TRL (1-3) R&D program in ARMD. 

Lower uncertainty aero/aerothermal database 

tools enable margin reduction for flexible 

aeroshells; existing methods are immature 

compared to the rigid case. Flight dynamics 

knowledge required to determine controllability 

issues & evaluate solutions. 

Include tools for rigid deployables not covered 

in Rigid Aeroshell Tools. Consider alternate 

modes (e.g. cg/RCS control, shape control) of 

guidance and control. Utilize software 

configuration control mechanisms for better 

productivity and verifiability

Deployable/Inflt 

Decel Dev

Deployable, 

Flexible 

Materials

Maturation of deployable (rigid and flexible) materials 

(high-temperature heatshield, insulation, and 

structures; flexible ablators; dual use systems) 

capable of Mars aerocapture and entry

Required for Deployable (Rigid and Flexible) 

Aerodynamic Decelerators

Consider size, shape and mass optimization 

and effect of charring

Deployable/Inflt 

Decel Dev

Flexible 

Aeroshell 

Vehicle Design 

Studies

Design and test deployable/inflatable (rigid and 

flexible) aeroshell shapes for aerodynamic 

performance, structural strength and controllability for 

Mars aerocapture and entry. Perform pre-Phase A 

design for packaging, structures, and mechanisms in 

order to assemble Manufacturing Development Units. 

Trade studies to select optimum deployable 

(rigid and inflatable) aeroshell shapes, materials 

and control surface/RCS systems are necessary

Investigate the ability to perform and model 

HIAD separation from the payload. Include all 

known dynamical effects including flexible joint 

interaction
35

GN&C

Autonomous 

Precision 

Navigation with 

Hazard 

Avoidance

Develop sensors, navigation and controls systems for 

precision landings with hazard avoidance on Mars.

This is in the current ETDD Program but is 

focused on lunar landings. The same technology 

will be needed at Mars, albeit with somewhat 

different requirements.

Additional insight into performance 

requirements was gained, but no fundamentally 

new objectives were identified

Aerocapture Dev Aerocapture 

Development

Establish requirements for an Aerocapture 

Technology Validation Flight Test, to provide systemlevel validation of blunt-body aerocapture applicable 

to Mars, Earth, Titan, and Venus 

Aerocapture reduces number of Ares V launches 

for Exploration-class missions from 11 to 7

Consider ability to jettison drag device after 

aerocapture pass but while in sensible 

atmosphere. Investigate torques caused by 

aero/RCS interactions. Double the usual 

aerodynamic uncertainties in systems analyses 

to account for flexibility effects.

Sub-Scale System Testing

Supersonic 

Retro-Propulsion 

Flight Test 

Program

Flight demonstration (TRL=6) of controllability of 

supersonic retro-propulsion descent system. A 

sounding rocket or a balloon will suffice. Includes 

funds for a second flight unit.

Supersonic deceleration is a key technology 

gap, that appears to be a single-point technology 

need for landing large payload on Mars. 

Aerodynamic decelerators do not meet the 

supersonic deceleration requirements of 

Exploration-class missions.

Consider developing a dedicated reusable 

testbed to test critical EDL technologies and 

flight instrumentation 

Deployable/Inflat

able Decelerator 

Flight Test 

Program

Flight demonstration (TRL=6) of Deployable, 

Inflatable Aerodynamic Decelerator. Includes funds 

for a second flight unit.

Enables lower ballistic entries for Explorationclass missions, increasing timeline margin, and 

permits decoupled tailoring of decelerator and 

payload. Simulation results indicate a savings of 

40 mT in Mars arrival Mars compared with a rigid 

aeroshell.

Consider developing a dedicated reusable 

testbed to test critical EDL technologies and 

flight instrumentation 

Aerocapture 

Flight Test

Flight demonstration (TRL=6–7) of Aerocapture in 

upper Earth's atmosphere

Aerocapture reduces number of Ares V launches 

for Exploration-class missions from 11 to 7 No refinements identified

Full-Scale System Testing

Feed-Forward 

Technology Mars 

Flight Test

Not addressed in Year 1

Flight demonstration (TRL=8) of EFF 

technologies at Mars with useful Exploration 

payload in the 2.5–3 t range. 

Use technologies from EDL-SA (or future 

studies) EFF robotic mission design—currently, 

aerocapture and entry with HIADs (single or 

dual), descent and landing with propulsion (cost 

does not include payload)
36

Appendix C - HIAD Diameter Trade Study Results 

Figure C-19. Mass Model Trade for Single HIAD Concept (EFF-2)
37

Figure C-20. Mass Model Trade for Direct Entry Concept (EFF-3)
38

Figure C-21. Mass Model Trade for Direct Entry Concept (EFF-4)
39

Appendix D - Simulation Monte Carlo Dispersions 

 Parameter Nominal Value Dispersion Units Distribution

Initial State

Entry Flight Path Angle Guidance 

Dependent +/- 0.25 deg Normal

Hyperbolic Velocity 5463.59 +/- 20 m/s Normal

B-plane Angle 270.0 +/- 0.1 deg Normal

Time of Flight -30.0 +/- 2.0 sec Normal

Atmospheric Uncertainties

Dust Tau 0.45 0.1 to 0.9 [nd] Uniform

Perturbation Seed Number 1 1 to 29999 [nd] Integer

Density Multiplier 1.0 +/- 15% [nd] Uniform

Initial Attitude and Rate 

Uncertainties

Alpha

-7 for L/D 0.10

-18.0 for L/D 

0.25

+/- 0.25 deg Normal

Beta 0.0 +/- 0.25 deg Normal

Bank Angle 0.0 +/- 0.25 deg Normal

Roll Rate BODY 0.0 +/- 0.10 deg/s Normal

Pitch Rate BODY 0.0 +/- 0.10 deg/s Normal

Yaw Rate BODY 0.0 +/- 0.10 deg/s Normal

Aerodynamic Uncertainties

CA Multiplier 1.0 0.9:1.1 [nd] Normal

CN Multiplier 1.0 0.9:1.1 [nd] Normal

CY Multiplier 1.0 0.9:1.1 [nd] Normal

Mass Property Uncertainties
40

Appendix E - Simulation Monte Carlo Navigation and Sensor Dispersions 

Parameter Dispersion

Mean Units 3-sigma Units Type

Sensors

Accelerometer* bias 0 m/s2 +/- 8.250E-04 m/s2 Gaussian

 (same error for 

each direction)

scale 

factor 0 % +/- 4.500E-04 % Gaussian

random 

noise m/s2 +/- 9.000E-05 m/s2 Gaussian

Gyro* bias 0 rad/s +/- 1.745E-07 rad/s Gaussian

 (same error for 

each direction)

scale 

factor 0 % +/- 2.700E-05 % Gaussian

random 

noise rad/s +/- 1.309E-07 rad/s Gaussian

Startracker* bias 0 deg +/- 0.01667 deg Gaussian

(same error for 

each direction)

random 

noise 0 deg +/- 0.04167 deg Gaussian

Altimeter bias 0 m +/- 0.0 m Gaussian

scale 

factor 0 % +/- 0.0 % Gaussian

random +/-

noise m +/- 15.000 m Gaussian

Velocimeter (lo-fi) bias 0 m/s +/- 0.003 m/s Gaussian

scale 

factor 0 % +/- 0.000 % Gaussian

random 

noise m/s +/- 0.018 m/s Gaussian

TRN bias 0 m/s +/- 15.000 m Gaussian

+/- 24.7 (12–15km)

+/-

 0.3225% alt – 14.025 

(7–12 km) 

TRN

random 

noise m +/- 8.55 (5–7 km) m Gaussian

Initial States

inertial 

position +/- 2.0 (xi) 

error +/- 2.0 (yi)

+/-

NAV States km +/-

 2.0 (zi)

km Gaussian

inertial 

velocity +/- 2.0 (vxi) 

+/- 2.0 (vyi)

error m/s +/- 2.0 (vzi) m/s Gaussian

attitude 

error deg +/- 0.04 deg Gaussian

*Monte Carlo run with IMU/startracker error only since ALHAT navigation filter 
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Entry, Descent and Landing Systems Analysis Study: Phase 2 Report on 

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identify and roadmap the Entry, Descent and Landing (EDL) technology investments that the agency needed to successfully 

land large payloads at Mars for both robotic and human-scale missions. Year 1 of the study focused on technologies required 

for Exploration-class missions to land payloads of 10 to 50 t. Inflatable decelerators, rigid aeroshell and supersonic 

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inflatables aeroshells and supersonic retropropulsion, were combined to create a demonstration precursor robotic mission. This 

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