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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
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A method developed to compute two-body, optimal, N-impulse trajectories was presented. The necessary conditions established define the gradient structure of the primer vector and its derivative for any set of boundary conditions and any number of impulses. Inequality constraints, a conjugate gradient iterator technique, and the use of a penalty function were also discussed.
A nuclear electric propulsion (NEP) mission to Neptune is studied. Results of trajectory and propulsion parameter optimization are presented which lead to a selection of key electric propulsion system parameters. Spiral earth escape and spiral capture modes are assumed in the optimization studies. Flight time vs payload for Space Transportation System (STS)/Centaur injection and Triton-aided orbit capture at Neptune are also briefly investigated as methods of improving mission performance. Radiation effects of the earth spiral phase are discussed. The effects of NEP technology on science payloads and mission and system designs are evaluated. NEP is shown to be a very flexible and high performing propulsion technology.
Recent advances in control-system design and simulation are discussed in reviews and reports. Among the topics considered are fast algorithms for generating near-optimal binary decision programs, trajectory control of robot manipulators with compensation of load effects via a six-axis force sensor, matrix integrators for real-time simulation, a high-level control language for an autonomous land vehicle, and a practical engineering design method for stable model-reference adaptive systems. Also addressed are the identification and control of flexible-limb robots with unknown loads, adaptive control and robust adaptive control for manipulators with feedforward compensation, adaptive pole-placement controllers with predictive action, variable-structure strategies for motion control, and digital signal-processor-based variable-structure controls.
New capabilities have been added to a method that had been developed for determining optimal, i.e., minimum fuel, trajectories for the fixed-time cooperative rendezvous of two spacecraft. The method utilizes the primer vector theory. The new capabilities enable the method to accomodate cases in which there are fuel constraints on the spacecraft and/or enable the addition of a mid-course impulse to one of the vehicle's trajectories. Results are presented for a large number of cases, and the effect of varying parameters, such as vehicle fuel constraints, vehicle initial masses, and time allowed for the rendezvous, is demonstrated.
The NASA Autonomous Guidance, Navigation and Control (GN&C) Bridging program is reviewed to demonstrate the program plan and GN&C systems for the Space Shuttle. The ascent CN&C system is described in terms of elements such as the general-purpose digital computers, sensors for the navigation subsystem, the guidance-system software, and the flight-control subsystem. Balloon-based and lidar wind soundings are used for operations assessment on the day of launch, and the guidance software is based on dedicated units for atmospheric powered flight, vacuum powered flight, and abort-specific situations. Optimization of the flight trajectories is discussed, and flight-control responses are illustrated for wavelengths of 500-6000 m. Alternate sensors are used for load relief, and adaptive GN&C systems based on alternate gain synthesis are used for systems failures.
This paper documents the application of genetic algorithms (GAs) to the problem of robust flight path determination for Mars precision landing. The robust flight path problem is defined here as the determination of the flight path which delivers a low-lift open-loop controlled vehicle to its desired final landing location while minimizing the effect of perturbations due to uncertainty in the atmospheric model and entry conditions. The genetic algorithm was capable of finding solutions which reduced the landing error from 111 km RMS radial (open-loop optimal) to 43 km RMS radial (optimized with respect to perturbations) using 200 hours of computation on an Ultra-SPARC workstation. Further reduction in the landing error is possible by going to closed-loop control which can utilize the GA optimized paths as nominal trajectories for linearization.
Recently, strong evidence of liquid water under the surface of Mars and a meteorite that might contain ancient microbes have renewed interest in Mars exploration. With this renewed interest, NASA plans to send spacecraft to Mars approx. every 26 months. These future spacecraft will return higher-resolution images, make precision landings, engage in longer-ranging surface maneuvers, and even return Martian soil and rock samples to Earth. Future robotic missions and any human missions to Mars will require precise entries to ensure safe landings near science objective and pre-employed assets. Potential sources of water and other interesting geographic features are often located near hazards, such as within craters or along canyon walls. In order for more accurate landings to be made, spacecraft entering the Martian atmosphere need to use lift to actively control the entry. This active guidance results in much smaller landing footprints. Planning for these missions will depend heavily on Monte Carlo analysis. Monte Carlo trajectory simulations have been used with a high degree of success in recent planetary exploration missions. These analyses ascertain the impact of off-nominal conditions during a flight and account for uncertainty. Uncertainties generally stem from limitations in manufacturing tolerances, measurement capabilities, analysis accuracies, and environmental unknowns. Thousands of off-nominal trajectories are simulated by randomly dispersing uncertainty variables and collecting statistics on forecast variables. The dependability of Monte Carlo forecasts, however, is limited by the accuracy and completeness of the assumed uncertainties. This is because Monte Carlo analysis is a forward driven problem; beginning with the input uncertainties and proceeding to the forecasts outputs. It lacks a mechanism to affect or alter the uncertainties based on the forecast results. If the results are unacceptable, the current practice is to use an iterative, trial-and-error approach to reconcile discrepancies. Therefore, an improvement to the Monte Carlo analysis is needed that will allow the problem to be worked in reverse. In this way, the largest allowable dispersions that achieve the required mission objectives can be determined quantitatively.
In this paper, we extend primer vector analysis to formation flying. Optimization of the classical rendezvous or free-time transfer problem between two orbits using primer vector theory has been extensively studied for one spacecraft. However, an increasing number of missions are now considering flying a set of spacecraft in close formation. Missions such as the Magnetospheric MultiScale (MMS) and Leonardo-BRDF (Bidirectional Reflectance Distribution Function) need to determine strategies to transfer each spacecraft from the common launch orbit to their respective operational orbit. In addition, all the spacecraft must synchronize their states so that they achieve the same desired formation geometry over each orbit. This periodicity requirement imposes constraints on the boundary conditions that can be used for the primer vector algorithm. In this work we explore the impact of the periodicity requirement in optimizing each spacecraft transfer trajectory using primer vector theory. We first present our adaptation of primer vector theory to formation flying. Using this method, we then compute the AV budget for each spacecraft subject to different formation endpoint constraints.
Presently, flight systems designed to perform payload-centric maneuvers require preconstructed procedures and special hand-tuned guidance modes. To enable intelligent maneuvering via strong coupling between the goals of payload-directed flight and the autopilot functions, there exists a need to rethink traditional autopilot design and function. Research into payload directed flight examines sensor and payload-centric autopilot modes, architectures, and algorithms that provide layers of intelligent guidance, navigation and control for flight vehicles to achieve mission goals related to the payload sensors, taking into account various constraints such as the performance limitations of the aircraft, target tracking and estimation, obstacle avoidance, and constraint satisfaction. Payload directed flight requires a methodology for accurate trajectory planning that lets the system anticipate expected return from a suite of onboard sensors. This paper presents an extension to the existing techniques used in the literature to quickly and accurately plan flight trajectories that predict and optimize the expected return of onboard payload sensors.
The concept of Traffic Aware Strategic Aircrew Requests (TASAR) combines Automatic Dependent Surveillance Broadcast (ADS-B) IN and airborne automation to enable user-optimal in-flight trajectory replanning and to increase the likelihood of Air Traffic Control (ATC) approval for the resulting trajectory change request. TASAR is designed as a near-term application to improve flight efficiency or other user-desired attributes of the flight while not impacting and potentially benefiting ATC. Previous work has indicated the potential for significant benefits for each TASAR-equipped aircraft. This paper will discuss the approach to minimizing TASAR's cost for implementation and accelerating readiness for near-term implementation.
The Asteroid Robotic Redirect Mission (ARRM) has been the topic of many mission design studies since 2011. The reference ARRM spacecraft uses a powerful solar electric propulsion (SEP) system and a bag device to capture a small asteroid from an Earth-like orbit and redirect it to a distant retrograde orbit (DRO) around the moon. The ARRM Option B spacecraft uses the same propulsion system and multi-Degree of Freedom (DoF) manipulators device to retrieve a very large sample (thousands of kilograms) from a 100+ meter diameter farther-away Near Earth Asteroid (NEA). This study will demonstrate that the ARRM Option B spacecraft design can also be used to return samples from Mars and its moons - either by acquiring a large rock from the surface of Phobos or Deimos, and or by rendezvousing with a sample-return spacecraft launched from the surface of Mars.
The ultimate goal of the Evolvable Mars Campaign is to build up a sustainable outpost at Mars that would be continually staffed with rotating crews. During this stage of human Mars exploration, it would be necessary to provision the crews with equipment and supplies both before and during their missions. In this paper, we study the use of 150 kW reusable SEP tugs as a means to deliver elements both to orbit and to the surface. The SEP tugs would make use of technology currently being developed for the proposed Asteroid Robotic Redirect Mission (ARRM). They would also be used to deliver food and supplies to sustain the crews similar to resupply missions for the International Space Station. The SEP tugs envisioned would be staged at a quasi-stable Lunar Near Rectilinear Orbit (NRO). The tugs would then mate with cargo vessels and xenon propellant being delivered by an SLS launch vehicle and continue on to Mars orbit where the cargo is delivered and the SEP tug returns to NRO to repeat the process. It was found that it is more efficient to deliver surface cargo via direct launch and entry versus using the tug cycler. Thousands of optimized low-thrust trajectories were simulated in order to create “Bacon plots” (like porkchop plots, but for low thrust transfers) in order to map out potential trajectories for dates from 2039 to 2052. This study maps out the buildup of a surface outpost as well as the necessary orbital and surface resupply launches in order to maintain it. In the steady state, a cadence of 9 cargo launches is required every 4 years to sustain the human outpost.
A method is proposed for developing the necessary guidance logic to steer single-stage vehicles into orbit. The minimum-fuel ascent problem is first considered to analyze the effects of dynamic pressure, acceleration, and heating constraints on guidance systems to thereby develop the guidance logic. The optimal solution consists of behavior with two time scales, and the control law is used to develop near-optimal guidance. The solution uses the slow manifold to delineate the control for minimum-fuel reduced-order trajectory and a separate control for tracking the optimal reduced-order trajectory. A family of fast manifolds is then employed to resolve the tracking problem via the feedback linearization methodology from nonlinear geometric control theory. The two-time-scale decomposition is found to produce a near-optimal ascent by tracking the applicable state-constraint boundary, as well as to simplify the control-design task.
Minimum energy-loss guidance for the aero-assisted plane change of an orbiting vehicle is developed and applied to the plane change of a circular orbit. First, trajectories which minimize the fuel required to change the orbital plane are computed for a realistic vehicle. From these trajectories, it is observed that the fuel weight is minimized if the velocity at exit from the atmosphere is maximized. Next, for the atmospheric turn, approximate optimal controls (angle of attack and bank angle) which maximize the exit velocity are derived. Finally, the minimum-fuel problem is resolved using optimal guidance for the atmospheric part of the trajectory, and the optimization problem reduces to a one-dimensional parameter minimization. Successful plane changes up to 40 deg are demonstrated. Optimal guidance requires up to 14 percent more fuel than the 'true' optimum but only 50 percent of the fuel required by the single-impulse maneuver. Finally, the guidance law developed here is implementable because only algebraic manipulations are required.
Variable-speed pursuit-evasion and interception for two aircraft moving in a horizontal plane are analyzed in terms of a coordinate frame fixed in the plane at termination. Each participant's optimal motion can be represented by extremal trajectory maps. These maps are used to discuss sub-optimal approximations that are independent of the other participant. A method of constructing sections of the barrier, dispersal, and control-level surfaces and thus determining feedback strategies is described. Some examples are shown for pursuit-evasion and the minimum-time interception of a straight-flying target.
This work reports on incorporating complex terrain into wind farm simulations for the purpose of layout optimization. Adding complex terrain boundary conditions to NREL's medium fidelity computational fluid dynamics model, WindSE, produces significant separation, flow curvature, and speedup effects that would otherwise be difficult to capture with lower-fidelity models or a flat-terrain assumption. These flow features, in turn, can significantly impact the optimal turbine array layout. We demonstrate the impact of complex terrain on flow in both an idealized and real-world setting, and discuss modifications to the code that enable gradient-based optimization using terrain-aware adjoint gradients. Through several optimization case studies, we show that the layout optimization process takes advantage of speedup effects on terrain high points, and leverages flow curvature effects that modify wake trajectories. This yields substantial power improvements over gridded layouts, and hints at future research directions in simulation and optimization for wake trajectories in complex terrain.
This report describes the approach and results of an end-to-end simulation to deflect a long-period comet (LPC) by using a rapid rendezvous spacecraft and laser ablation system. The laser energy required for providing sufficient deflection DELTA V and an analysis of possible intercept/rendezvous spacecraft trajectories are studied in this analysis. These problems minimize a weighted sum of the flight time and required propellant by using an advanced propulsion system. The optimal thrust-vector history and propellant mass to use are found in order to transfer a spacecraft from the Earth to a targeted celestial object. One goal of this analysis is to formulate an optimization problem for intercept/rendezvous spacecraft trajectories. One approach to alter the trajectory of the object in a highly controlled manner is to use pulsed laser ablative propulsion. A sufficiently intense laser pulse ablates the surface of a near-Earth object (NEO) by causing plasma blowoff. The momentum change from a single laser pulse is very small. However, the cumulative effect is very effective because the laser can interact with the object over long periods of time. The laser ablation technique can overcome the mass penalties associated with other nondisruptive approaches because no propellant is required to generate the DELTA V (the material of the celestial object is the propellant source). Additionally, laser ablation is effective against a wide range of surface materials and does not require any landing or physical attachment to the object. For diverting distant asteroids and comets, the power and optical requirements of a laser ablation system on or near the Earth may be too extreme to contemplate in the next few decades. A hybrid solution would be for a spacecraft to carry a laser as a payload to a particular celestial body. The spacecraft would require an advanced propulsion system capable of rapid rendezvous with the object and an extremely powerful electrical generator, which is likely needed for the propulsion system as well. The spacecraft would station-keep with the object at a small standoff distance while the laser ablation is performed.
Abstract This work considers the topology optimization of hyperelastic structures for maximum stiffness (minimum compliance) subject to constraints on their volume and maximum stress. In contrast to almost all previous works, we subject the structures to nonproportional loading, wherein the maximum stress does not necessarily occur at the final load step. As such, the stress is constrained at each load step. The augmented Lagrangian method is used to formulate the optimization problem with its many constraints. In numerical examples, we investigate different load trajectories for the same terminal load and compare the optimized designs and their performances. The results show the importance of considering the entire load trajectory as the load history significantly influences the optimized designs.