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Optimized space shuttle trajectory simulation

A computer program for simulating optimized space shuttle trajectories is presented. The program considers the ascent, return, and synergetic maneuvers of lifting boosters and spacecraft. Other constraints on optimum trajectory such as maximum heating, acceleration, angle of attack, and excluded or included overflight or impact regions are examined. Mathematical models are included to support the theoretical aspects of the discussion.

Tramonti, L.

Statistical Trajectory Estimation Program (STEP) implementation for BLDT post flight trajectory simulation

Tests were conducted to provide flight conditions for qualifying the Viking Decelerator System in a simulated Mars environment. A balloon launched decelerator test (BLDT) vehicle which has an external shape similar to the actual Mars Viking Lander Capsule was used so that the decelerator would be deployed in the wake of a blunt body. An effort was made to simulate the BLDT vehicle flights from the time they were dropped from the balloon, through decelerator deployment, until stable decelerator conditions were reached. The procedure used to simulate these flights using the Statistical Trajectory Estimation Program (STEP) is discussed. Using primarily ground-based position radar and vehicle onboard rate gyro and accelerometer data, the STEP produces a minimum variance solution of the vehicle trajectory and calculates vehicle attitude histories. Using film from cameras in the vehicle along with a computer program, attitude histories for portions of the flight before and after decelerator deployment were calculated independent of the STEP simulation. With the assumption that the vehicle motions derived from camera data are accurate, a comparison reveals that STEP was able to simulate vehicle motions for all flights both before and after decelerator deployment.

Shields, W. E.

Free-Flight Trajectory Simulation of the ADEPT Sounding Rocket Test Using CFD

A computational study of the Adaptive Deployable Entry and Placement Technology (ADEPT) Sounding Rocket (SR-1) Test is presented using the US3D flow solver. ADEPT SR-1 is intended, in part, to assess the dynamic stability of this entry vehicle architecture. Given that no dynamic stability data exists for the ADEPT geometry, a limited ballistic range campaign has been performed to characterize the vehicle's stability characteristics pre-flight for Mach numbers between 1.21 and 2.5. Here, this data is used to assess the accuracy of US3D's free-flight CFD capability. Computed trajectories from US3D and experimental data show that the flow solver compares well in vehicle oscillation frequency, downrange distance, and oscillatory amplitude during high Mach number flight (Mavg = 2.36). For Mach numbers below 1.5, the solver under predicts total angle-of-attack by an average of 16%, but compares well in oscillatory frequency and downrange distance. Additionally, a capability for simulating the trajectory of the flight article through the atmosphere using CFD is presented. This capability couples US3D's free-flight capability to an atmosphere model that accounts for changes in free-stream density and temperature as the vehicle descends. Two simulations for the purpose of demonstrating the capability and viability of this approach are applied to SR-1 flight article, and some unique challenges are discussed.

CFD

Trajectory Simulation for Air Traffic Management Employing a Multirotor Urban Air Mobility Aircraft Model

This paper describes a point-mass model of a multirotor electric vertical takeoff and landing aircraft designed to carry up to five passengers and a pilot. The model employs thrust, thrust vector angle and bank angle as controls, which are computed in part using the acceleration, heading-angle rate, and flight-path-angle rate generated by control systems in response to speed, heading angle, and flight-path angle commands. The equations of motion are integrated forward in time using the controls needed for following the desired vertical climb/descent and speed profiles, and horizontal path and cruise speed in the presence of wind to generate the flight trajectory.

trajectory simulation, urban air mobility aircraft

Trajectory Simulations of Upper Tropospheric Humidity

We present comparisons of simulations of upper tropospheric humidity at 215 and 146 hPa with satellite measurements. Our model uses diabatic trajectories to advect water vapor from an initial condition of 100% relative humidity to the final state. The model does not allow parcels' relative humidity to exceed 100%, and in this way crudely incorporates condensation. We find that this simple model does a good job of simulating the observations. Sensitivity studies suggest that one must have realistic wind velocities in order to accurately simulate the humidity distribution; microphysical parameterizations seem to be less important. Comparisions between simulations using UKMO and NCEP horizontal winds will be discussed.

Dessler, A. E.

Simulated Trajectory Reconstruction of the Genesis Aeroballistic Testing for Dragonfly

Dragonfly is a NASA New Frontiers Program mission, led by Johns Hopkins Applied Physics Laboratory (APL), that will deliver a rotorcraft lander to Saturn’s moon, Titan, which uses a Genesis derived entry vehicle shape. During the Genesis mission, there were concerns with the dynamic stability of the configuration leading to testing at the Aeroballistic Research Facility at Eglin Air Force Base and Dragonfly shares these concerns given the similarity of the entry vehicle shapes. The focus of this paper is to compare the dynamics observed in the ballistic range shots from 1999 against the dynamics from simulation using the Program to Optimize Trajectories II (POST2). This analysis provides a confirmation that the aerodynamics developed during the Genesis mission, especially from ballistic range shots, is being used properly in the Dragonfly mission entry aerodynamics database.

Dragonfly

Simulation of Trajectories for High Specific Impulse Deep Space Exploration

Difficulties in approximating flight times and deliverable masses for continuous thrust propulsion systems have complicated comparison and evaluation of proposed propulsion concepts. These continuous thrust propulsion systems are of interest to many groups, not the least of which are the electric propulsion and fusion communities. Several charts plotting the results of well-known trajectory simulation codes were developed and are contained in this paper. These charts illustrate the dependence of time of flight and payload ratio on jet power, initial mass, specific impulse and specific power. These charts are intended to be a tool by which people in the propulsion community can explore the possibilities of their propulsion system concepts. Trajectories were simulated using the tools VARITOP and IPOST. VARITOP is a well known trajectory optimization code that involves numerical integration based on calculus of variations. IPOST has several methods of trajectory simulation; the one used in this paper is Cowell's method for full integration of the equations of motion. The analytical method derived in the companion paper was also used to simulate the trajectory. The accuracy of this method is discussed in the paper.

Polsgrove, Tara

Optimizing simulated trajectories

General-purpose rigid-body six-degrees-of-freedom program is used to solve wide variety of atmospheric flight mechanics and orbital transfer problems. Written for analysis of powered or unpowered vehicles operation near rotating oblate planet, typical applications include: guidance and flight-control system simulation and analysis, loads and dispersion-type analysis.

Brauer, G. L.

Implementation of a Landing Footprint Algorithm for the HTV-2 and Trajectory Simulations

This presentation details work performed during the Fall 2011 term in the Research Controls and Dynamics Branch at NASA Dryden Flight Research Center. Included is a study on a possible landing footprint algorithm, with direct application to the HTV-2. Also discussed is work in support of the MIPCC effort, which includes optimal trajectory solutions for the F-15A Streak Eagle aircraft and theoretical performance of an F-15A with a MIPCC propulsion system.

Clark, Casie M.

Interplanetary Program to Optimize Simulated Trajectories (IPOST). Volume 2: Analytic manual

The Interplanetary Program to Optimize Space Trajectories (IPOST) is intended to support many analysis phases, from early interplanetary feasibility studies through spacecraft development and operations. The IPOST output provides information for sizing and understanding mission impacts related to propulsion, guidance, communications, sensor/actuators, payload, and other dynamic and geometric environments. IPOST models three degree of freedom trajectory events, such as launch/ascent, orbital coast, propulsive maneuvering (impulsive and finite burn), gravity assist, and atmospheric entry. Trajectory propagation is performed using a choice of Cowell, Encke, Multiconic, Onestep, or Conic methods. The user identifies a desired sequence of trajectory events, and selects which parameters are independent (controls) and dependent (targets), as well as other constraints and the cost function. Targeting and optimization is performed using the Stanford NPSOL algorithm. IPOST structure allows subproblems within a master optimization problem to aid in the general constrained parameter optimization solution. An alternate optimization method uses implicit simulation and collocation techniques.

Hong, P. E.

Interplanetary Program to Optimize Simulated Trajectories (IPOST). Volume 1: User's guide

IPOST is intended to support many analysis phases, from early interplanetary feasibility studies through spacecraft development and operations. The IPOST output provides information for sizing and understanding mission impacts related to propulsion, guidance, communications, sensor/actuators, payload, and other dynamic and geometric environments. IPOST models three degree of freedom trajectory events, such as launch/ascent, orbital coast, propulsive maneuvering (impulsive and finite burn), gravity assist, and atmospheric entry. Trajectory propagation is performed using a choice of Cowell, Encke, Multiconic, Onestep, or Conic methods. The user identifies a desired sequence fo trajectory events, and selects which parameters are independent (controls) and dependent (targets), as well as other constraints and the coat function. Targeting and optimization is performed using the Stanford NPSOL algorithm. IPOST structure allows sub-problems within a master optimization problem to aid in the general constrained parameter optimization solution. An alternate optimization method uses implicit simulation and collocation techniques.

Hong, P. E.

Simulated trajectories error analysis program, version 2. Volume 2: Programmer's manual

A series of three computer programs for the mathematical analysis of navigation and guidance of lunar and interplanetary trajectories was developed. All three programs require the integration of n-body trajectories for both interplanetary and lunar missions. The virutal mass technique is used in all three programs. The user's manual contains the information necessary to operate the programs. The input and output quantities of the programs are described. Sample cases are given and discussed.

Vogt, E. D.

Comparison of effects of copropagated and precomputed atmosphere profiles on Monte Carlo trajectory simulation

A realization of a stochastic atmosphere model for use in simulations is presented. The model provides pressure, density, temperature, and wind velocity as a function of latitude, longitude, and altitude, and is implemented in a three degree of freedom simulation package. This implementation is used in the Monte Carlo simulation of an aeroassisted orbital transfer maneuver and results are compared to those of a more traditional approach.

Queen, Eric M.

Program to Optimize Simulated Trajectories II (POST2) Surrogate Models for Mars Ascent Vehicle (MAV) Performance Assessment

The primary purpose of the multiPOST tool is to enable the execution of much larger sets of vehicle cases to allow for broader trade space exploration. However, this exploration is not achieved solely with the increased case throughput. The multiPOST tool is applied to carry out a Design of Experiments (DOE), which is a set of cases that have been structured to capture a maximum amount of information about the design space with minimal computational effort. The results of the DOE are then used to fit a surrogate model, ultimately enabling parametric design space exploration. The approach used for the MAV study includes both DOE and surrogate modeling. First, the primary design considerations for the vehicle were used to develop the variables and ranges for the multiPOST DOE. The final set of DOE variables were carefully selected in order to capture the desired vehicle trades and take into account any special considerations for surrogate modeling. Next, the DOE sets were executed through multiPOST. Following successful completion of the DOE cases, a manual verification trial was performed. The trial involved randomly selecting cases from the DOE set and running them by hand. The results from the human analyst's run and multiPOST were then compared to ensure that the automated runs were being executed properly. Completion of the verification trials was then followed by surrogate model fitting. After fits to the multiPOST data were successfully created, the surrogate models were used as a stand-in for POST2 to carry out the desired MAV trades. Using the surrogate models in lieu of POST2 allowed for visualization of vehicle sensitivities to the input variables as well as rapid evaluation of vehicle performance. Although the models introduce some error into the output of the trade study, they were very effective at identifying areas of interest within the trade space for further refinement by human analysts. The next section will cover all of the ground rules and assumptions associated with DOE setup and multiPOST execution. Section 3.1 gives the final DOE variables and ranges, while section 3.2 addresses the POST2 specific assumptions. The results of the verification trials are given in section 4. Section 5 gives the surrogate model fitting results, including the goodness-of-fit metrics for each fit. Finally, the MAV specific results are discussed in section 6.

Zwack, M. R.