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Computer programs for simulating mathematical models describing characteristics for economics, performance, reliability, launch vehicle, regression, and optimization systems
After listing the basic requirements such as operational demands and lunar environmental conditions, characteristic design data of the roving vehicle are given with special attention to the four wheel drive and its control system, the steering system, and the navigational instrumentation. The overall system is optimized in view of total mass, range, mobility, load carrying capability, safety, highest reliability through redundancy, and last but not least, cost and development time. Optimization of the drive and power system has first been evaluated by mathematical models and computational simulation of the vehicle hardware, the wheel/soil interaction, and the lunar terrain profile. The next step to refine optimization and evaluation of the drive, steering, and power system including man/machine interaction has been carried out by the use of a six-degree-of-freedom simulator subjecting the astronauts in their space suits to simulated vehicle motions while driving over a simulated terrain, observable on a cathode ray tube display.
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.
A Space Robot Simulator Vehicle (SRSV) was constructed to model a free-flying robot capable of doing construction, manipulation and repair work in space. The SRSV is intended as a test bed for development of dynamic and static control methods for space robots. The vehicle is built around a two-foot-diameter air-cushion vehicle that carries batteries, power supplies, gas tanks, computer, reaction jets and radio equipment. It is fitted with one or two two-link manipulators, which may be of many possible designs, including flexible-link versions. Both the vehicle body and its first arm are nearly complete. Inverse dynamic control of the robot's manipulator has been successfully simulated using equations generated by the dynamic simulation package SDEXACT. In this mode, the position of the manipulator tip is controlled not by fixing the vehicle base through thruster operation, but by controlling the manipulator joint torques to achieve the desired tip motion, while allowing for the free motion of the vehicle base. One of the primary goals is to minimize use of the thrusters in favor of intelligent control of the manipulator. Ways to reduce the computational burden of control are described.
The NASA Exploration program is investigating the merits of land landing concepts for the Crew Exploration Vehicle (CEV). Four options are under investigation: retro-rockets which fire and slow the vehicle before contact with the landing surface, deployable crushable material which deploys just before landing and crushes during land contact, airbags which deploy just before landing and deflate during land contact, and deployable legs which deploy before landing and contain material that absorbs energy during land contact. The purpose of the present work is to determine the effectiveness of the deployable leg concept. To accomplish this goal, structural models of the deployable leg concept are integrated with the Crew Model (CM) and computational simulations are performed to determine vehicle and component loadings and acceleration levels. Details of the modeling approach, deployable leg design, and resulting accelerations are provided.
Aerodynamic data books for Space Launch System vehicles require databases for the integrated forces and moments and section loads during liftoff and transition to the ascent phase of flight. While the force and moment database can be generated from wind tunnel results, computational analyses are necessary to provide the extensive surface information required to generate proper lineloads. Of the two flight regimes, the liftoff problem is the more costly and complex situation to simulate, as it requires modeling of the vehicle in proximity to the launch tower. The effects of massive separation on the leeward pressure fields of both the tower and vehicle are not well captured with RANS methods, necessitating the use of more advanced methods, such as Delayed Detached Eddy Simulation, in conjunction with computational grids sufficiently refined to resolve the wakes. Details on the computational setup for employing the Kestrel flow solver to address the liftoff problem are presented. The methodology involves the use of independent unstructured near-body grids for the vehicle and the tower, overset by a solution adaptive Cartesian off-body grid. Results from the simulations are compared to experimental results from a test in the NASA Langley Research Center 14- by 22-Foot Subsonic Tunnel.
A launch vehicle ground-wind-loads program is underway at the NASA Langley Transonic Dynamics Tunnel. The objectives are to quantify key aerodynamic and structural characteristics that impact the occurrence of large wind-induced oscillations of a launch vehicle when exposed to ground winds prior to launch. Of particular interest is the dynamic response of a launch vehicle when a von Kármán vortex street forms in the wake of the vehicle resulting in quasiperiodic lift and drag forces. Vehicle response to these quasiperiodic forces can become quite large when the frequency of vortex shedding nears that of a lowly-damped structural mode thereby exciting a resonant response. Wind approaching the vehicle can be characterized by a varying speed with height and turbulence content. The combination of both the varying speed and turbulence content is referred to herein as the atmospheric boundary-layer. The importance of the atmospheric boundary-layer upon launch vehicle wind-induced oscillation response has long been questioned, and its effects are not well understood. Although there are several facilities around the world dedicated to replicating atmospheric boundary layers, the development of such a boundary layer in a wind tunnel capable of producing flight-representative Reynolds numbers for aeroelastically-scaled launch vehicle models has only recently been accomplished. The NASA Langley Transonic Dynamics Tunnel is capable of simulating flight-representative Reynolds numbers of launch vehicles on the pad and is uniquely capable of replicating many fluid-structure scaling parameters typical of aeroelastic tests. Recent test efforts successfully developed representative atmospheric boundary-layers for three launch sites in the Transonic Dynamics Tunnel, thereby allowing all known aerodynamic and fluid-structure coupling parameters to be simultaneously simulated for those sites. Dynamic aeroelastically-scaled models representative of typical large launch vehicles were constructed for testing. Aeroelastic scaling includes matching geometry, mode shapes, reduced frequencies, damping, running mass ratios, and running stiffness ratios. The models were tested in smooth uniform flow and then immersed in the atmospheric boundary-layer for comparison of these effects. Dynamic data were acquired measuring unsteady pressure, acceleration, and base bending moment. It was discovered that peak dynamic loads resulting from resonant wind-induced oscillation response are similar when acquired in either smooth uniform flow or an atmospheric boundary-layer. This indicates that resonant lock-in events are minimally impacted by representative turbulence and/or wind profile. Alternately, nonresonant wind-induced oscillation response events are stronger when acquired in an atmospheric boundary-layer. This indicates that a lowly-damped structural response will increase when exposed to an increased magnitude of random excitation, which is consistent with historical comparisons. Loads created by the resonant response events were substantially stronger than those from the nonresonant response events. Therefore, if testing is done to simply identify worst-case conditions and load magnitude, then smooth uniform flow is likely an adequate test technique. However, if nonresonant response loads are of primary interest, then atmospheric boundary-layer simulation is required.
This paper is concerned with the physics-based simulation of light tracked vehicles operating on rough deformable terrain. The focus is on small autonomous vehicles, which weigh less than 100 lb and move on deformable and rough terrain that is feature rich and no longer representable using a continuum approach. A scenario of interest is, for instance, the simulation of a reconnaissance mission for a high mobility lightweight robot where objects such as a boulder or a ditch that could otherwise be considered small for a truck or tank, become major obstacles that can impede the mobility of the light autonomous vehicle and negatively impact the success of its mission. Analyzing and gauging the mobility and performance of these light vehicles is accomplished through a modeling and simulation capability called Chrono::Engine. Chrono::Engine relies on parallel execution on Graphics Processing Unit (GPU) cards.
Apollo/Saturn V automatic checkout test verification and debug program using real time computer simulation with digital space vehicle system model
This paper considers the design of model-reference adaptive control systems using Liapunov functions. An adaption rule is developed analytically. This adaption rule results from the use of a Liapunov function which contains several positive semidefinite terms not included in previous references. The inclusion of these terms results in an adaption rule which is a function of the error, the plant states and the derivative and integral of these quantities. The adaption rule is applied to a simplified model of the Space Shuttle vehicle. Simulation results show that the maximum response error in the system is reduced by using this adaption rule.
The results are presented of analysis and simulation testing of both the Skylark 1 reaction control system digital autopilot (RCS DAP) and the thrust vector control (TVC) autopilot for use during the undocked portions of the Apollo/Soyuz Test Project Mission. The RCS DAP testing was performed using the Skylab Functional Simulator (SLFS), a digital computer program capable of simulating the Apollo and Skylab autopilots along with vehicle dynamics including bending and sloshing. The model is used to simulate three-axis automatic maneuvers along with pilot controlled manual maneuvers using the RCS DAP. The TVC autopilot was tested in two parts. A classical stability analysis was performed on the vehicle considering the effects of structural bending and sloshing when under control of the TVC autopilot. The time response of the TVC autopilot was tested using the SLFS. Results indicate that adequate performance stability margins can be expected for the CSM/DM configuration when under the control of the Apollo control systems tested.
Progress in the development of a performance optimized engine system design for an advanced LOX/hydrogen expander cycle engine is reported. Analysis of the components and engine and the resulting drawings is discussed. The status of the orbit transfer vehicle liquid engine transient simulation computer model is given.
Results of variable cycle engine (VCE) early acoustic engine and model scale tests are presented. A summary of an extensive series of far field acoustic, advanced acoustic, and exhaust plume velocity measurements with a laser velocimeter of inverted velocity and temperature profile, high radius ratio coannular plug nozzles on a YJ101 VCE static engine test vehicle are reviewed. Select model scale simulated flight acoustic measurements for an unsuppressed and a mechanical suppressed coannular plug nozzle are also discussed. The engine acoustic nozzle tests verify previous model scale noise reduction measurements. The engine measurements show 4 to 6 PNdB aft quadrant jet noise reduction and up to 7 PNdB forward quadrant shock noise reduction relative to a fully mixed conical nozzle at the same specific thrust and mixed pressure ratio. The influences of outer nozzle radius ratio, inner stream velocity ratio, and area ratio are discussed. Also, laser velocimeter measurements of mean velocity and turbulent velocity of the YJ101 engine are illustrated. Select model scale static and simulated flight acoustic measurements are shown which corroborate that coannular suppression is maintained in forward speed.
A methodology for very fast design of 3DOF entry trajectories subject to all common inequality and equality constraints is developed. The approach make novel use of the well known quasi-equilibrium glide phenomenon in lifting entry as a center piece for conveniently enforcing the inequality constraints which are otherwise difficulty to handle. The algorithm is able to generate a complete feasible 3DOF entry trajectory, given the entry conditions, values of constraint parameters, and final conditions in about 2 seconds on a PC. Numerical simulations with the X-33 vehicle model for various entry missions to land at Kennedy Space Center will be presented.
A trade study reviewing the primary operational parameters concerning the deployment of imaging assets in support of the Hypersonic Thermodynamic Infrared Measurements (HYTHIRM) project was undertaken. The objective was to determine key variables and constraints for obtaining thermal images of the Space Shuttle orbiter during reentry. The trade study investigated the performance characteristics and operating environment of optical instrumentation that may be deployed during a HYTHIRM data collection mission, and specified contributions to the Point Spread Function. It also investigated the constraints that have to be considered in order to optimize deployment through the use of mission planning tools. These tools simulate the radiance modeling of the vehicle as well as the expected spatial resolution based on the Orbiter trajectory and placement of land based or airborne optical sensors for given Mach numbers. Lastly, this report focused on the tools and methodology that have to be in place for real-time mission planning in order to handle the myriad of variables such as trajectory ground track, weather, and instrumentation availability that may only be known in the hours prior to landing.
Adaptive flight control systems have the potential to be resilient to extreme changes in airplane behavior. Extreme changes could be a result of a system failure or of damage to the airplane. The goal for the adaptive system is to provide an increase in survivability in the event that these extreme changes occur. A direct adaptive neural-network-based flight control system was developed for the National Aeronautics and Space Administration NF-15B Intelligent Flight Control System airplane. The adaptive element was incorporated into a dynamic inversion controller with explicit reference model-following. As a test the system was subjected to an abrupt change in plant stability simulating a destabilizing failure. Flight evaluations were performed with and without neural network adaptation. The results of these flight tests are presented. Comparison with simulation predictions and analysis of the performance of the adaptation system are discussed. The performance of the adaptation system is assessed in terms of its ability to stabilize the vehicle and reestablish good onboard reference model-following. Flight evaluation with the simulated destabilizing failure and adaptation engaged showed improvement in the vehicle stability margins. The convergent properties of this initial system warrant additional improvement since continued maneuvering caused continued adaptation change. Compared to the non-adaptive system the adaptive system provided better closed-loop behavior with improved matching of the onboard reference model. A detailed discussion of the flight results is presented.
Since the atmospheric conditions and gravitational field are different for Mars and Earth, the operating flight environments are different, and necessitate Earth-based appropriate modeling, analysis, and simulation for Mars flight vehicles. This paper compares a hexacopter’s flight dynamics in the two environments. The analysis is necessary to determine if a dynamically matched surrogate hexacopter can be designed to conduct reliable testing on Earth, with the goal of successfully operation on Mars. To answer the question, the comprehensive tool FLIGHTLAB® is used to model the hexacopter flight dynamics. Frequency responses in heave, pitch, roll, and yaw rates of the hexacopter in hover are analyzed. The simulation result shows that each attitude response of the designed hexacopter responds very differently in the two environments. The closed-loop response of the hexacopter can be made stable on Earth but not on Mars. Therefore, the proportional feedback technique cannot be utilized to stabilize all four responses altogether. Due to the dynamics of the model being very different in each atmosphere, it is yet not feasible to create a dynamically matched surrogate helicopter that can operate in both environments.
The test results for a functional model ac motor controller for electric vehicles and a three-phase induction motor which were dynamically tested on the Lewis Research Center road load simulator are presented. Results show that the controller has the capability to meet the SAE-J227a D cycle test schedule and to accelerate a 1576-kg (3456-lb) simulated vehicle to a cruise speed of 88.5 km/hr (55 mph). Combined motor controller efficiency is 72 percent and the power inverter efficiency alone is 89 percent for the cruise region of the D cycle. Steady state test results for motoring, regeneration, and thermal data obtained by operating the simulator as a conventional dynamometer are in agreement with the contractor's previously reported data. The regeneration test results indicate that a reduction in energy requirements for urban driving cycles is attainable with regenerative braking. Test results and data in this report serve as a data base for further development of ac motor controllers and propulsion systems for electric vehicles. The controller uses state-of-the-art silicon controlled rectifier (SCR) power semiconductors and microprocessor-based logic and control circuitry. The controller was developed by Gould Laboratories under a Lewis contract for the Department of Energy's Electric and Hybrid Vehicle program.