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Flight Mechanics Modeling and Simulation of the Earth Entry System

Introduction: The Mars Sample Return (MSR) Campaign being planned by NASA and ESA has the ambitious goal to return Mars samples back to Earth. This international collaboration had developed a concept of operations that included a ESA-designed Earth Return Orbiter (ERO) and NASA-designed Capture, Containment, and Return System (CCRS). The Earth Entry System (EES), consisting of a protective aeroshell that houses the samples as well as sample containment vessels, would conduct entry, descent, and landing (EDL) on a direct Earth trajectory. The EES would enter on a spin-stabilized ballistic trajectory with the goal to passively achieve aerodynamic stability throughout all regions of flight. The EDL sequence would end with the EES impacting the soft playa soil of the Utah Test and Training Range (UTTR). As of the submission of this abstract, the MSR campaign is undergoing a re-architecture leading to a pause in EES development. However, the novel approaches developed in flight mechanics modeling and simulation can significantly benefit the greater IPPW community in the development of Earth return vehicles. This paper will present the latest state of EES flight mechanics modeling and simulation. The paper will highlight the simulation architecture developed and key lessons learned from understanding of EDL trajectory sensitivities. Modeling and Simulation: Figure 1 provides a high-level concept of operations for the approach, entry, descent, and landing (AEDL) phase of the CCRS-portion of MSR. The objective of EES flight mechanics is to model and simulate the EES trajectory from ERO separation to ground impact at UTTR. A variety of flight mechanics simulation models were utilized to model both exo-atmopsheric and atmospheric portions of flight. 42, a 6-DOF simulation developed at Goddard Space Flight Center, is utilized for propagating the attitude of EES during exo-atmospheric flight. 42 allows for a variety of spin eject mechanism scenarios to be simulated for analysis. 10 minutes prior to entry, the 42 states are handed off to the EDL sims. The prime EDL sim utilized by EES is the Program to Optimize Simulated Trajectories II (POST2), a 6-DOF sim developed at Langley Research Center, and the independent verification and validation EDL sim utilized is DSENDS, a 6-DOF sim developed at Jet Propulsion Laboratory. Figure 2 provides a visualization of the flight mechanics simulation model flow through various points in the AEDL phase. Due to the existence of a variety of sim models, the EES flight mechanics team developed processes for data hand-off. These processes included the development of a centralized coordinate frame document, utilization of a single, centralized simulation input document for all sims to reference, and hand-off files containing both the technical data to be ingested by other flight mechanics sims as well as annotations of modeling assumptions utilized to generate the data. Figure~\ref{fig:post2simarchitecture} provides an overview of the POST2 sim architecture wherein POST2 ingests numerous subsystem models and input files. The dispersed state file generated by MONTE provides the position/velocity state of the trajectory while the 42 Handoff file provides the attitude. The aerodynamics database, delivered by the EES aeroscience team, is utilized to simulate the aerodynamic forces and moments experienced during EDL. A custom atmosphere model, developed by EES atmosphere team, is utilized to simulate the anticipated atmosphere environment around the region of Earth through which the EES trajectory flys. These inputs and subsystem models can be varied depending on the AEDL flight mechanics scenario being simulated. Monte Carlo simulations are utilized to generate statistical AEDL performance metrics in the form of scorecards and violin plots. Furthermore, outputs from the POST2 simulation are utilized for follow-on analyses including aerothermal and landing performance. \section{Flight Mechanics Lessons Learned} Though the EES flight mechanics team uncovered a variety of lessons learned through the analysis conducted to support CCRS through preliminary design review, this paper will highlight the most important lessons. A key AEDL performance goal is to ensure the landing footprint of EES remains on the UTTR south range. A common modeling strategy used in EDL analysis is One-Variable-At-a-Time (OVAT). OVAT analysis provides insight into the key drivers that affect AEDL performance metrics. Figure 3 shows the landing ellipses for single dispersion sources as compared to the baseline aggregate of all dispersions. The figure shows that atmosphere winds alone dominate the size of the footprint ellipse (note: EES does not use a parachute unlike previous Earth-return missions and is in wind-driven free fall for ~5min). The significance of the wind led the EES flight mechanics team to pursue the development of a Custom Atmosphere Model [4], in lieu of EarthGRAM [1], built on actual radiosonde wind measurements around the UTTR-region. This decision was driven by the realism in the generated footprint ellipses and lessons-learned from Stardust [5]. These findings will be invaluable for future Earth-return missions in providing an early understanding of the key drivers affecting footprint size and modeling considerations for which to account. Another lesson learned is tied to the AEDL performance goal of achieving passive stability throughout all regions of flight. It is well understood that blunt-body aeroshells are less stable as they transition from supersonic to subsonic. Eliminating a backshell does help improvestability; however, other phenomena such as roll-induced instability during terminal descent can still arise. The EES flight mechanics team developed stability metrics as tools to better understand the causes of and better predict the onset of dynamic instability. These tools were built upon analytical models developed by Jaffe [3] and Murphy [2]. The tools were shown to both be very accurate in correlation with actual unstable cases and useful in developing stability margin policies based on the vehicle design and simulation considerations (e.g. sphere-cone angle change, mass change, wind turbulence). These tools allowed for the current EES design to demonstrate the ability to achieve passive stability and can be an invaluable tool for consideration in the design of parachute-less Earth-return vehicles.

Rohan Deshmukh↗

Forward Skirt Structural Testing on the Space Launch System (SLS) Program

Structural testing was performed to evaluate heritage forward skirts from the Space Shuttle program for use on the Space Launch System (SLS) program. One forward skirt is located in each solid rocket booster. Heritage forward skirts are aluminum 2219 welded structures. Loads are applied at the forward skirt thrust post and ball assembly. Testing was needed because SLS ascent loads are roughly 40% higher than Space Shuttle loads. Testing objectives were to determine margins of safety, demonstrate reliability, and validate analytical models. Two forward skirts were structurally tested using the test configuration. The test stand applied loads to the thrust post. Four hydraulic actuators were used to apply axial load and two hydraulic actuators were used to apply radial and tangential loads. The first test was referred to as FSTA-1 (Forward Skirt Structural Test Article) and was performed in April/May 2014. The purpose of FSTA-1 was to verify the ultimate capability of the forward skirt subjected to ascent ultimate loads. Testing consisted of two liftoff load cases taken to 100% limit load followed by an ascent load case taken to 110% limit load. The forward skirt was unloaded to no load after each test case. Lastly, the forward skirt was tested to 140% limit and then to failure using the ascent loads. The second test was referred to as FSTA-2 and performed in July/August of 2014. The purpose of FSTA-2 was to verify the ultimate capability of the forward skirt subjected to liftoff ultimate loads. Testing consisted of six liftoff load cases taken to 100% limit load followed by the six liftoff cases taken to 140% limit load. Two ascent load cases were then tested to 100% limit load. The forward skirt was unloaded to no load after each test case. Lastly, the forward skirt was tested to 140% limit and then to failure using the ascent loads. The forward skirts on FSTA-1 and FSTA-2 successfully carried all applied liftoff and ascent load cases. Both FSTA-1 and FSTA-2 were tested to failure by increasing the ascent loads. Failure occurred in the forward skirt thrust post radius. The forward skirts on FSTA-1 and FSTA-2 had nearly identical failure modes. FSTA-1 failed at 1.72 times limit load and FSTA-2 failed at 1.62 times limit load. This difference is primarily attributed to variation in material properties in the thrust post region. Test data were obtained from strain gages, deflection gages, ARAMIS digital strain measurement, acoustic emissions, and high-speed video. Strain gage data and ARAMIS strain were compared to finite element (FE) analysis predictions. Both the forward skirt and tooling were modeled. This allows the analysis to simulate the loading as close as possible to actual test configuration. FSTA-1 and FSTA-2 were instrumented with over 200 strain gages to ensure all possible failure modes could be captured. However, it turned out that three gages provided critical strain data. One was located in the post bore and two on the post radius. More gages were not specified due to space limitations and the desire to not interfere with the use of the ARAMIS system on the post radius. Measured strains were compared to analysis results for the load cycle to failure. Note that FSTA-1 gages were lost before failure was reached. FSTA-2 gages made it to the failure load but one of the radius gages was lost before testing began. This gage was not replaced because of the time and cost associated with disassembly of the test structure. Correlation to analysis was excellent for FSTA-1. FSTA-2 was not quite as good because there was more residual strain from previous load cycles. FSTA-2 was loaded and unloaded with 12 liftoff cases and two ascent cases before taking the skirt to failure. FSTA-1 only had two liftoff cases and one ascent case before taking the skirt to failure. The ARAMIS system was used to determine strain at the post radius by processing digital images of a speckled paint pattern. Digital cameras recorded images of the speckled paint pattern. ARAMIS strain results for FSTA-2 just prior to failure. Note a high strain location develops near the left side. This high strain compares well to analysis prediction for both FSTA-1 and FSTA-2. The strain at this location was also plotted versus limit load. Both FSTA-1 and FSTA-2 had excellent correlation between ARAMIS and analysis strains. Acoustic emission (AE) sensors were used to monitor for damage formation that may occur during testing (e.g., crack formation and growth or propagation). AE was very important because after disassembly of FSTA-1, a crack was observed in the ball fitting radius. The ball fitting did not crack on FSTA-2. AE data was used to reconstruct when the crack occurred. The AE energy versus time plot for FSTA. The energy increased considerably at 850 seconds (152% limit load), indicating a crack could have formed at this point. The only visual evidence found that could have corresponded to this was the crack that initiated in the ball fitting. The cracks in the forward skirt aluminum structures would likely have been lower energy due to a lower modulus and all that were found after failure correlated to occurring after the initial crack in the post radius. This was verified by high-speed cameras used to record the failure.

Lohrer, J. D.↗