Automated Model Tuning for Multifidelity Trajectory Simulation Estimators
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James Warner↗
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Flight Mechanics Simulations: Trajectory and Testing Guidance, Navigation, and Control Algorithms in-the-loop
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Soumyo Dutta↗
Design of an Application Programming Interface for the Program to Optimize Simulated Trajectories II
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Anthony Williams↗
Deep learning enabled Lagrangian particle trajectory simulation
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Jingwei Gan↗
Titan Explorer Entry, Descent and Landing Trajectory Design
The Titan Explorer mission concept includes an orbiter, entry probe and inflatable airship designed to take remote and in-situ measurements of Titan's atmosphere. A modified entry, descent and landing trajectory at Titan that incorporates mid-air airship inflation (under a parachute) and separation is developed and examined for Titan Explorer. The feasibility of mid-air inflation and deployment of an airship under a parachute is determined by implementing and validating an airship buoyancy and inflation model in the trajectory simulation program, Program to Optimize Simulated Trajectories II (POST2). A nominal POST2 trajectory simulation case study is generated which examines different descent scenarios by varying airship inflation duration, orientation, and separation. The buoyancy model incorporation into POST2 is new to the software and may be used in future trajectory simulations. Each case from the nominal POST2 trajectory case study simulates a successful separation between the parachute and airship systems with sufficient velocity change as to alter their paths to avoid collision throughout their descent. The airship and heatshield also separate acceptably with a minimum distance of separation from the parachute system of 1.5 km. This analysis shows the feasibility of airship inflation on a parachute for different orientations, airship separation at various inflation times, and preparation for level-flight at Titan.
Fisher, Jody L.↗
POST2 End-To-End Descent and Landing Simulation for the Autonomous Landing and Hazard Avoidance Technology Project
The Program to Optimize Simulated Trajectories II (POST2) is used as a basis for an end-to-end descent and landing trajectory simulation that is essential in determining the design and performance capability of lunar descent and landing system models and lunar environment models for the Autonomous Landing and Hazard Avoidance Technology (ALHAT) project. This POST2-based ALHAT simulation provides descent and landing simulation capability by integrating lunar environment and lander system models (including terrain, sensor, guidance, navigation, and control models), along with the data necessary to design and operate a landing system for robotic, human, and cargo lunar-landing success. This paper presents the current and planned development and model validation of the POST2-based end-to-end trajectory simulation used for the testing, performance and evaluation of ALHAT project system and models.
Fisher, Jody l.↗
Simulation of Airplane and Rocket Trajectories
Simulation and Optimization of Rocket Trajectories program (SORT) contains comprehensive mathematical models for simulating aircraft dynamics, freely falling objects, and many types of ballistic trajectories. Provides high-fidelity, three-degrees-of-freedom simulation for atmospheric and exoatmospheric flight. It numerically models vehicle subsystems and vehicle environment. Used for wide range of simulations. Written in machine-independent FORTRAN 77.
Wahbah, Magdy M.↗
LDSD POST2 Simulation and SFDT-1 Pre-Flight Launch Operations Analyses
The Low-Density Supersonic Decelerator (LDSD) Project's first Supersonic Flight Dynamics Test (SFDT-1) occurred June 28, 2014. Program to Optimize Simulated Trajectories II (POST2) was utilized to develop trajectory simulations characterizing all SFDT-1 flight phases from drop to splashdown. These POST2 simulations were used to validate the targeting parameters developed for SFDT- 1, predict performance and understand the sensitivity of the vehicle and nominal mission designs, and to support flight test operations with trajectory performance and splashdown location predictions for vehicle recovery. This paper provides an overview of the POST2 simulations developed for LDSD and presents the POST2 simulation flight dynamics support during the SFDT-1 launch, operations, and recovery.
Bowes, Angela L.↗
Advances in POST2 End-to-End Descent and Landing Simulation for the ALHAT Project
Program to Optimize Simulated Trajectories II (POST2) is used as a basis for an end-to-end descent and landing trajectory simulation that is essential in determining design and integration capability and system performance of the lunar descent and landing system and environment models for the Autonomous Landing and Hazard Avoidance Technology (ALHAT) project. The POST2 simulation provides a six degree-of-freedom capability necessary to test, design and operate a descent and landing system for successful lunar landing. This paper presents advances in the development and model-implementation of the POST2 simulation, as well as preliminary system performance analysis, used for the testing and evaluation of ALHAT project system models.
Davis, Jody L.↗
LDSD POST2 Modeling Enhancements in Support of SFDT-2 Flight Operations
Program to Optimize Simulated Trajectories II (POST2) was utilized to develop trajectory simulations characterizing all flight phases from drop to splashdown for the Low-Density Supersonic Decelerator (LDSD) project's first and second Supersonic Flight Dynamics Tests (SFDT-1 and SFDT-2) which took place June 28, 2014 and June 8, 2015, respectively. This paper describes the modeling improvements incorporated into the LDSD POST2 simulations since SFDT-1 and presents how these modeling updates affected the predicted SFDT-2 performance and sensitivity to the mission design. The POST2 simulation flight dynamics support during the SFDT-2 launch, operations, and recovery is also provided.
White, Joseph↗
Assessment of the Mars 2020 Entry, Descent, and Landing Simulation
On February 18, 2021, the Mars 2020 Perseverance rover successfully landed inside Jezero Crater at 18.44463 deg North latitude and 77.45088 deg East longitude. At 1026 kg, Perseverance is the largest, most sophisticated rover ever delivered to another planet. This event marked the ninth successful landing and fifth rover to be delivered at Mars. The Program to Optimize Simulated Trajectories II (POST2) is a trajectory simulation tool maintained by the NASA Langley Research Center. POST2 was the prime EDL performance simulation for Mars 2020. This tool has significant heritage on the previous Pathfinder, MER, Phoenix, InSight, and MSL landings. This paper presents a few initial comparisons between EDL flight telemetry and POST2 simulation predictions. These comparisons are important in order to understand how each of the individual models performed, as well as the integrated simulation as a whole. This information is fed forward to future missions, which benefit from the knowing where additional resources or study are needed and where uncertainties may be reduced to enable improved performance.
David W Way↗
Assessment of the Mars 2020 Entry, Descent, and Landing Simulation
On February 18, 2021, the Mars 2020 Perseverance rover successfully landed inside Jezero Crater at 18.44463 deg North latitude and 77.45088 deg East longitude. At 1026 kg, Perseverance is the largest, most sophisticated rover ever delivered to another planet. This event marked the ninth successful landing and fifth rover to be delivered at Mars. The Program to Optimize Simulated Trajectories II (POST2) is a trajectory simulation tool maintained by the NASA Langley Research Center. POST2 was the prime EDL performance simulation for Mars 2020. This tool has significant heritage on the previous Pathfinder, MER, Phoenix, InSight, and MSL landings. This paper presents a few initial comparisons between EDL flight telemetry and POST2 simulation predictions. These comparisons are important in order to understand how each of the individual models performed, as well as the integrated simulation as a whole. This information is fed forward to future missions, which benefit from the knowing where additional resources or study are needed and where uncertainties may be reduced to enable improved performance.
David Way↗
ASTP (SA-210) Launch vehicle operational flight trajectory. Part 3: Final documentation
Trajectory data are presented for a nominal and two launch window trajectory simulations. These trajectories are designed to insert a manned Apollo spacecraft into a 150/167 km. (81/90 n. mi.) earth orbit inclined at 51.78 degrees for rendezvous with a Soyuz spacecraft, which will be orbiting at approximately 225 km. (121.5 n. mi.). The launch window allocation defined for this launch is 500 pounds of S-IVB stage propellant. The launch window opening trajectory simulation depicts the earliest launch time deviation from a planar flight launch which conforms to this constraint. The launch window closing trajectory simulation was developed for the more stringent Air Force Eastern Test Range (AFETR) flight azimuth restriction of 37.4 degrees east-of-north. These trajectories enclose a 12.09 minute launch window, pertinent features of which are provided in a tabulation. Planar flight data are included for mid-window reference.
Carter, A. B.↗
Handling Qualities and Trajectory Requirements for Terminal Lunar Landing, as Determined from Analog Simulation
Trajectory requirements for terminal lunar landing from analog simulation of spacecraft
LUNAR LANDING↗
Program For Simulation Of Trajectories And Events
Universal Simulation Executive (USE) program accelerates and eases generation of application programs for numerical simulation of continuous trajectories interrupted by or containing discrete events. Developed for simulation of multiple spacecraft trajectories with events as one spacecraft crossing the equator, two spacecraft meeting or parting, or firing rocket engine. USE also simulates operation of chemical batch processing factory. Written in Ada.
Gottlieb, Robert G.↗
CFD 2030 Grand Challenge: CFD-in-the-Loop Monte Carlo Flight Simulation for Space Vehicle Design
Flight qualification of space vehicles is markedly different from those typically employed for aircraft. The concept of an extensive flight test campaign for a space vehicle does not exist, and vehicle designers must look to alternative techniques for demonstrating robust and reliable performance of their vehicles prior to operational flight. A space vehicle may undergo only a handful of flight tests in its development cycle, with each flight representing a drastically different flight phase or flight configuration. For instance, NASA’s Space Launch System (SLS) launch vehicle and Orion spacecraft will only see a total of four flight demonstrations before flying a crew on its first operational mission, and each flight demonstrates a unique vehicle configuration and/or set of flight conditions. The SLS will be flown only one time before it becomes operational (Artemis 1). The Orion spacecraft Crew Module (CM) will have been tested twice, once on a Delta IV launch vehicle (Exploration Flight Test 1) and once as a fully integrated system with the SLS launch vehicle (Artemis 1). The Orion Launch abort system will have been tested twice, once in a pad abort scenario (Pad Abort 1) and once in an inflight abort scenario (Ascent Abort 2) on a modified Peacekeeper booster. Both of these latter tests involve only a boiler plate CM, not a functional Orion spacecraft. Thus, unlike aircraft, there is very little opportunity for engineers to assess and evaluate their preflight predictions. Instead, space vehicle designers rely on Monte Carlo flight simulations with detailed dispersions of predicted nominal flight behavior to determine how robust their design is to errors and uncertainties in the flight conditions their vehicle may encounter. These Monte Carlo analyses entail thousands of trajectory simulations to demonstrate that the vehicle can meet design requirements at a specified level of reliability. From an aerodynamics and aerothermodynamics perspective, these trajectory simulations are fueled by an extensive aerodynamic database that covers the complete range of expected flight conditions, vehicle configurations, and flight attitudes expected in a given mission. Today, these databases amount to a table of engineering parameters that can be quickly interrogated by the trajectory simulator. The aerodynamic and aerothermodynamic databases are assembled via a series of ground tests, empirical and analytical analysis, physics-based computational analysis, applicable past flight performance data, and in some cases, engineering judgment. These databases generally take years to assemble for a new space vehicle system and in the case of SLS/Orion, over a decade of test and analysis have been expended to develop the extensive databases required to cover the myriad of configurations and potential flight conditions required for the system. Recently, it has been proposed that Computational Fluid Dynamic (CFD) and computing capability may be reaching a point where it is foreseeable that CFD could be integrated directly into the production trajectory simulation tools used to design NASA’s space vehicles. To demonstrate this, NASA has embarked on two demonstrations of this type of capability, one where six degree of freedom flight trajectory simulation equations are embedded in an existing CFD solver and another where a production CFD solver is loosely coupled with a production trajectory simulation tool. These efforts represent an initial demonstration of a future approach to flight trajectory simulation, but they are a far cry from the capability required to perform a full-up CFD-in-the-loop Monte Carlo trajectory simulation. Therefore, this represents a viable grand challenge for computational methods addressing space vehicle design and development. The final paper/presentation will discuss the many hurdles, beyond simply raw computational power, to realizing this grand challenge and how they map directly to the CFD Vision 2030 ojectives. Among these are the wide range of flight conditions, including accelerating/decelerating flight, encountered by a space vehicle during launch and/or entry. The vehicle can also encounter numerous configuration changes, some of which can be quite drastic, during the course of its flight, so robust, automated geometry modeling, grid generation, and adaptation will play a huge role in reaching this goal. Multiply this by 1000’s of trajectory simulations occurring simultaneously in a given Monte Carlo analysis, and the problem readily scales to absorb virtually any size of supercomputer envisioned today. The concept of CFD-in-the-loop Monte Carlo trajectory simulation poses a formidable challenge for emerging and future computing systems, and it has the potential to shave years off the development cycle for aerodynamic and aerothermodynamic performance predictions as compared to today’s space vehicle design approach.
CFD 2030↗
Flight Deck Surface Trajectory-Based Operations (STBO): A Four-Dimensional Trajectory (4DT) Simulation
In four-dimensional trajectory (4DT) Surface Trajectory-Based Operations (STBO), aircraft are assigned a conflict-free 4DT which defines an expected location (x,y coordinates) at all times, t, along the taxi route (with altitude, being fixed). These 4DTs afford the highest temporal certainty at all points along the taxi route, and at the departure runway. In the present study, a 4DT flight deck display was presented on the Airport Moving Map (AMM) to support pilot conformance to a 4DT clearance while taxiing under manual control. This pilot-in-the-loop simulation compared the effect of 4DT flight deck display formats on distance from the expected 4DT location, conformance to the displayed tolerance band, eyes-out time, and pilot ratings of safety and workload. In the defined-tolerance display format, a graphical representation of the expected 4DT location, with a distance-based allowable-tolerance band, was depicted on the AMM. Two defined-tolerance band sizes were tested: plus or minus 164 feet and plus or minus 405 feet. In the undefined-tolerance display format, the expected 4DT location was displayed graphically on the AMM, with no indicated allowable-tolerance bounds. Each taxi trial included 4DT speed changes (two or five, per trial) and a range of 4DT taxi speeds. Results showed that the larger (plus or minus 405 feet) defined-tolerance band yielded higher conformance levels than the smaller (plus or minus 164 feet) band, with pilots staying within the specified and displayed conformance bounds more in the larger (99.71%) than the smaller defined-tolerance band (93.37 percent). However, in terms of being able to predict the location of the aircraft compared to the expected 4DT location, the smaller defined-tolerance band resulted in pilots keeping their aircraft closer to the 4DT location, for both average distance and for a given confidence interval (e.g., 95 percent), than either the larger defined-tolerance band or the undefined-tolerance display format. The larger tolerance band yielded more “eyes-out-the-window” time than the smaller tolerance band. Pilots also rated taxing with the larger tolerance band as safer than the smaller tolerance band.
STBO↗
Simulation Framework for Rapid Entry, Descent, and Landing (EDL) Analysis, Phase 2 Results
The NASA Engineering and Safety Center (NESC) was requested to establish the Simulation Framework for Rapid Entry, Descent, and Landing (EDL) Analysis assessment, which involved development of an enhanced simulation architecture using the Program to Optimize Simulated Trajectories II simulation tool. The assessment was requested to enhance the capability of the Agency to provide rapid evaluation of EDL characteristics in systems analysis studies, preliminary design, mission development and execution, and time-critical assessments. Many of the new simulation framework capabilities were developed to support the Agency EDL-Systems Analysis (SA) team that is conducting studies of the technologies and architectures that are required to enable human and higher mass robotic missions to Mars. The findings, observations, and recommendations from the NESC are provided in this report.
Murri, Daniel G.↗