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Two programs, Hiltop I and Hiltop II, generate optimum trajectory data for electric propulsion missions of interest in exploration of solar system. Propulsion-system logic is activated by single program-input key; program modifications retain Hiltop I within framework of logic, so that Hiltop I input files, will run Hiltop II version and produce identical results as before.
The objective of this second phase research is to investigate the optimal ascent trajectory for the National Aerospace Plane (NASP) from runway take-off to orbital insertion and address the unique problems associated with the hypersonic flight trajectory optimization. The trajectory optimization problem for an aerospace plane is a highly challenging problem because of the complexity involved. Previous work has been successful in obtaining sub-optimal trajectories by using energy-state approximation and time-scale decomposition techniques. But it is known that the energy-state approximation is not valid in certain portions of the trajectory. This research aims at employing full dynamics of the aerospace plane and emphasizing direct trajectory optimization methods. The major accomplishments of this research include the first-time development of an inverse dynamics approach in trajectory optimization which enables us to generate optimal trajectories for the aerospace plane efficiently and reliably, and general analytical solutions to constrained hypersonic trajectories that has wide application in trajectory optimization as well as in guidance and flight dynamics. Optimal trajectories in abort landing and ascent augmented with rocket propulsion and thrust vectoring control were also investigated. Motivated by this study, a new global trajectory optimization tool using continuous simulated annealing and a nonlinear predictive feedback guidance law have been under investigation and some promising results have been obtained, which may well lead to more significant development and application in the near future.
The latest release of the Optimal Trajectories by Implicit Simulation (OTIS4) allows users to simulate and optimize aerospace vehicle trajectories. With OTIS4, one can seamlessly generate optimal trajectories and parametric vehicle designs simultaneously. New features also allow OTIS4 to solve non-aerospace continuous time optimal control problems. The inputs and outputs of OTIS4 have been updated extensively from previous versions. Inputs now make use of objectoriented constructs, including one called a metastring. Metastrings use a greatly improved calculator and common nomenclature to reduce the user s workload. They allow for more flexibility in specifying vehicle physical models, boundary conditions, and path constraints. The OTIS4 calculator supports common mathematical functions, Boolean operations, and conditional statements. This allows users to define their own variables for use as outputs, constraints, or objective functions. The user-defined outputs can directly interface with other programs, such as spreadsheets, plotting packages, and visualization programs. Internally, OTIS4 has more explicit and implicit integration procedures, including high-order collocation methods, the pseudo-spectral method, and several variations of multiple shooting. Users may switch easily between the various methods. Several unique numerical techniques such as automated variable scaling and implicit integration grid refinement, support the integration methods. OTIS4 is also significantly more user friendly than previous versions. The installation process is nearly identical on various platforms, including Microsoft Windows, Apple OS X, and Linux operating systems. Cross-platform scripts also help make the execution of OTIS and post-processing of data easier. OTIS4 is supplied free by NASA and is subject to ITAR (International Traffic in Arms Regulations) restrictions. Users must have a Fortran compiler, and a Python interpreter is highly recommended.
The ability to detect and resolve conflicts automatically is considered to be an essential requirement for the next generation air traffic control system. While systems for automated conflict detection have been used operationally by controllers for more than 20 years, automated resolution systems have so far not reached the level of maturity required for operational deployment. Analytical models and algorithms for automated resolution have been traffic conditions to demonstrate that they can handle the complete spectrum of conflict situations encountered in actual operations. The resolution algorithm described in this paper was formulated to meet the performance requirements of the Automated Airspace Concept (AAC). The AAC, which was described in a recent paper [1], is a candidate for the next generation air traffic control system. The AAC's performance objectives are to increase safety and airspace capacity and to accommodate user preferences in flight operations to the greatest extent possible. In the AAC, resolution trajectories are generated by an automation system on the ground and sent to the aircraft autonomously via data link .The algorithm generating the trajectories must take into account the performance characteristics of the aircraft, the route structure of the airway system, and be capable of resolving all types of conflicts for properly equipped aircraft without requiring supervision and approval by a controller. Furthermore, the resolution trajectories should be compatible with the clearances, vectors and flight plan amendments that controllers customarily issue to pilots in resolving conflicts. The algorithm described herein, although formulated specifically to meet the needs of the AAC, provides a generic engine for resolving conflicts. Thus, it can be incorporated into any operational concept that requires a method for automated resolution, including concepts for autonomous air to air resolution.
The purpose of this thesis is to design a machine learning algorithm platform that provides expanded knowledge of mission availability through a launch season by improving trajectory resolution and introducing launch mission forecasting. The specific scenario addressed in this paper is one in which data is provided for four deterministic translational maneuvers through a mission to a Near Rectilinear Halo Orbit (NRHO) with a 9:2 synodic frequency. Current launch availability knowledge under NASA's Orion Orbit Performance Team is established by altering optimization variables associated to given reference launch epochs. This current method can bean abstract task and relies on an orbit analyst to structure a mission based on an established mission design methodology associated to the performance of Orion and NASA's Space Launch System. Introducing a machine learning algorithm trained to construct mission scenarios within the feasible range of known trajectories reduces the required interaction of the orbit analyst by removing the needed step of optimizing the orbit to fit an expected translational response required of the spacecraft. In this study, k-Nearest Neighbor and Bayesian Linear Regression successfully predicted classical orbital elements for the launch windows observed. However both algorithms had limitations due to their approaches to model fitting. Training machine learning algorithms off of classical orbital elements introduced a repetitive approach to reconstructing mission segments for different arrival opportunities through the launch window and can prove to be a viable method of launch window scan generation for future missions.
An experimental investigation was conducted at the NASA Langley Research Center to measure the flow rate and trajectory of water spray generated by an aircraft tire operating on a flooded runway. Tests were conducted in the Hydrodynamics Research Facility and made use of a partial airframe and a nose tire from a general aviation aircraft. Nose tires from a commercial transport aircraft were also used. The effects of forward speed, tire load, and water depth on water spray patterns were evaluated by measuring the amount and location of water captured by an array of tubes mounted behind the test tire. Water ejected from the side of the tire footprint had the most significant potential for ingestion into engine inlets. A lateral wake created on the water surface by the rolling tire can dominate the shape of the spray pattern as the distance aft of the tire is increased. Forward speed increased flow rates and moved the spray pattern inboard. Increased tire load caused the spray to become less dense. Near the tire, increased water depths caused flow rates to increase. Tests using a fuselage and partial wing along with the nose gear showed that for certain configurations, wing aerodynamics can cause a concentration of spray above the wing.
A flexible method to describe and generate aircraft trajectories called GenProf was developed for the Center TRACON Automation System (CTAS) software research platform. Generally CTAS is used to prototype new air traffic management decision support tools and concepts. Beyond this purpose, the GenProf methodology has enabled a variety of research and validation tasks to be performed. This paper briefly describes the methodology and details these applications.
This paper presents research on the interoperability of trajectory-based automation concepts and technologies with modern Flight Management Systems and datalink communication available on many of today s commercial aircraft. A tight integration of trajectory-based ground automation systems with the aircraft Flight Management System through datalink will enable mid-term and far-term benefits from trajectory-based automation methods. A two-way datalink connection between the trajectory-based automation resident in the Center/TRACON Automation System and the Future Air Navigation System-1 integrated FMS/datalink in NASA Ames B747-400 Level D simulator has been established and extensive simulation of the use of datalink messages to generate strategic trajectories completed. A strategic trajectory is defined as an aircraft deviation needed to solve a conflict or honor a route request and then merge the aircraft back to its nominal preferred trajectory using a single continuous trajectory clearance. Engineers on the ground side of the datalink generated lateral and vertical trajectory clearances and transmitted them to the Flight Management System of the 747; the airborne automation then flew the new trajectory without human intervention, requiring the flight crew only to review and to accept the trajectory. This simulation established the protocols needed for a significant majority of the trajectory change types required to solve a traffic conflict or deviate around weather. This demonstration provides a basis for understanding the requirements for integration of trajectory-based automation with current Flight Management Systems and datalink to support future National Airspace System operations.
A trajectory design process is presented for a proposed National Launch System (NLS) vehicle configuration. A software trajectory planner was developed to generate near optimal pitch plane trajectories for variable mission plans, variable launch site selections, and last minute wind conditions at the time of launch. In addition, the trajectory planner performs in-flight near optimal trajectory redesign in the event of an engine-out or unexpected wind dispersions. The trajectory planner iteratively simulates trial trajectories defined by variables corresponding to a parameterized trajectory shape. The trajectory planner optimizes these trajectory parameters according to the fuel used to realize the trajectories. For prelaunch scenarios, the trajectory planner generated near optimal trajectories of consistent fuel performance irrespective of the winds encountered at the launch site. In-flight trajectory redesigns were also shown to be effective in fulfilling the mission plan and preserving the structural integrity of the vehicle. The in-flight redesign results indicate that closed-loop guidance in the early stages of ascent is highly effective in accommodating engine failures or wind dispersions. All trajectory designs were verified using a 6DOF simulation with flight controllers.
Lissajous orbits and approximation of their invariant manifolds are used to generate landing trajectories to the surface of Europa. Each lissajous is discretized into individual revolutions that each resemble a periodic orbit. The unstable manifolds of each individual revolution propagated forward in time generate more surface coverage than manifolds of simple libration point orbits such as halo or Lyapunov orbits. The stable manifolds propagated backwards in time from the individual lissajous revolutions provide direct connections to the last phase of a moon tour. The strategy developed produces ballistic landing trajectories with a wide surface coverage, and allows for the decoupling of the landing and moon tour phase by using the lissajous as an intermediate staging orbit. The multiple revolutions of the lissajous, multiple departure times along each revolution, multiple quasi periodic options at each energy, and multiple energies of the lissajous family provide many degrees of freedom in the design process.
The reuseable exterior insulation system (REI) is studied to determine the optimal reentry trajectory for a space shuttle, which minimizes the heat input to the fuselage. The REI is composed of titanium, covered by a surface insulation material. The method of perturbation functions was used to generate the trajectories, and proved to be an effective technique for generating families of solutions, once an initial trajectory has been obtained.
The impact of aircraft emissions and contrails on the environment adds an additional aspect to aircraft trajectory optimization. This study developed a three-dimensional trajectory optimization algorithm for trans-Atlantic flights in cruise to generate aircraft trajectories that minimize environmental impacts due to CO2 emissions and contrails in the presence of winds. The climate-optimal trajectory is developed using dynamic programming that adjusts a wind-optimal aircraft heading while determining the optimal locations, altitudes and times for en-route step climbs. Flying wind-optimal routes minimize aircraft travel time, fuel burn and associated emissions during cruise while adjusting aircraft heading and en-route step climbs at the optimal locations and times minimize climate impact of contrails. This capability integrates an air traffic management simulation with aircraft fuel burn and emissions models, contrail formation and dispersion models, simplified climate response models, and a common climate metric. A study was conducted to evaluate the potential cost and benefits of flying climate-optimal routes in North Atlantic Airspace and their impacts to the Organized Track System design based on the trans-Atlantic air traffic during a day, July 12, 2012. Results show eastbound flights achieved a larger environmental benefit with less additional fuel burn than westbound flights that operated in strong headwinds that caused more additional fuel burn and aircraft emissions to avoid traversing contrails favorable regions.
The Low-Earth Orbit Flight Test of an Inflatable Decelerator (LOFTID) successfully demonstrated the capability of an inflatable aeroshell. Prior to launch, flight mechanics analysis was conducted to better understand the predicted splashdown point of the re-entry vehicle and ejectable data recorder. Best estimated trajectory separation states were utilized to understand the LOFTID trajectory over the entire 36 minute launch window. Weather forecasting model were integrated into the simulation to improve trajectory prediction accuracy. Automation tools were developed to facilitate the rapid generation of trajectory predictions during operations. The resulting improvements to the flight mechanics modeling and simulation allowed for pre-launch splashdown point to be within 3 nautical miles of the actual splashdown point.
The Low-Earth Orbit Flight Test of an Inflatable Decelerator (LOFTID) successfully demonstrated the capability of an inflatable aeroshell. Prior to launch, flight mechanics analysis was conducted to better understand the predicted splashdown point of the re-entry vehicle and ejectable data recorder. Best estimated trajectory separation states were utilized to understand the LOFTID trajectory over the entire 36 minute launch window. Weather forecasting model were integrated into the simulation to improve trajectory prediction accuracy. Automation tools were developed to facilitate the rapid generation of trajectory predictions during operations. The resulting improvements to the flight mechanics modeling and simulation allowed for pre-launch splashdown point to be within 3 nautical miles of the actual splashdown point.
An important element of the Space Shuttle Orbiter safety improvement plan is the improved understanding of its aerodynamic performance so as to minimize the "black zones" in the contingency abort trajectories [1]. These zones are regions in the launch trajectory where it is predicted that, due to vehicle limitations, the Orbiter will be unable to return to the launch site in a two or three engine-out scenario. Reduction of these zones requires accurate knowledge of the aerodynamic forces and moments to better assess the structural capability of the vehicle. An interesting aspect of the contingency abort trajectories is that the Orbiter would need to achieve angles of attack as high as 60deg. Such steep attitudes are much higher than those for a nominal flight trajectory. The Orbiter is currently flight certified only up to an angle of attack of 44deg at high Mach numbers and has never flown at angles of attack larger than this limit. Contingency abort trajectories are generated using the data in the Space Shuttle Operational Aerodynamic Data Book (OADB) [2]. The OADB, a detailed document of the aerodynamic environment of the current Orbiter, is primarily based on wind-tunnel measurements (over a wide Mach number and angle-of-attack range) extrapolated to flight conditions using available theories and correlations, and updated with flight data where available. For nominal flight conditions, i.e., angles of attack of less than 45deg, the fidelity of the OADB is excellent due to the availability of flight data. However, at the off-nominal conditions, such as would be encountered on contingency abort trajectories, the fidelity of the OADB is less certain. The primary aims of a recent collaborative effort (completed in the year 2001) between NASA and Boeing were to determine: 1) accurate distributions of pressure and shear loads on the Orbiter at select points in the contingency abort trajectory space; and 2) integrated aerodynamic forces and moments for the entire vehicle and the control surfaces (body flap, speed brake, and elevons). The latter served the useful purpose of verification of the aerodynamic characteristics that went into the generation of the abort trajectories.
When performing Inertial Navigation System (INS) testing at the Marshall Space Flight Center's (MSFC) Contact Dynamics Simulation Laboratory (CDSL) early in 2017, a Leica Geosystems AT901 Laser Tracker system (LLT) measured the twist & sway trajectories as generated by the 6 Degree Of Freedom (6DOF) Table in the CDSL. These LLT measured trajectories were used in the INS software model validation effort. Several challenges were identified and overcome during the preparation for the INS testing, as well as numerous lessons learned. These challenges included determining the position and attitude of the LLT with respect to an INS-shared coordinate frame using surveyed monument locations in the CDSL and the accompanying mathematical transformation, accurately measuring the spatial relationship between the INS and a 6DOF tracking probe due to lack of INS visibility from the LLT location, obtaining the data from the LLT during a test, determining how to process the results for comparison with INS data in time and frequency domains, and using a sensitivity analysis of the results to verify the quality of the results. While many of these challenges were identified and overcome before or during testing, a significant lesson on test set-up was not learned until later in the data analysis process. It was found that a combination of trajectory-dependent gimbal locking and environmental noise introduced non-negligible noise in the angular measurements of the LLT that spanned the evaluated frequency spectrum. The lessons learned in this experiment may be useful for others performing INS testing in similar testing facilities.
Simulations are conducted to investigate a proposed NASA launch vehicle that is fully reusable, takes off horizontally, and uses airbreathing propulsion in a single stage. The propulsion model is based on a cycle analysis method, and the vehicle is assumed to be a rigid structure with distributed fuel, operating under a range of atmospheric conditions. The program to optimize simulated trajectories (POST) is modified to include a predictor-corrector guidance capability and then used to generate the trajectories. Significant errors are encountered during the unpowered coast phase due to uncertainty in the atmospheric density profile. The amount of ascent propellant needed is shown to be directly related to the thrust-vector angle and the location of the center of gravity of the vehicle because of the importance of aim-drag losses to total ideal velocity.
The optimum-thrust equations for both variable and constant thrust are presented. These thrust programs are used to generate rendezvous trajectories from the Earth to Mars for various flight times and launch dates during the years 1968-71. The manner in which the propulsion requirements vary with flight time and launch date are considered, and a comparison of vehicle performance using the variable- and constant-thrust programs is presented. The optimization of the pro- pulsion system parameters is discussed, and the existence of optimum launch dates is interpreted in terms of certain transversality conditions derivable from the calculus of variations. A brief comparison of the advanced propulsion vehicle and the ballistic vehicle propulsion requirements is made for Earth-Mars rendezvous trajectories. An appendix considering the analytical basis for this work is included.