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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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DOE OSTI2016

Solving the Optimal Trading Trajectory Problem Using a Quantum Annealer

We solve a multi-period portfolio optimization problem using D-Wave Systems' quantum annealer. We derive a formulation of the problem, discuss several possible integer encoding schemes, and present numerical examples that show high success rates. The formulation incorporates transaction costs (including permanent and temporary market impact), and, significantly, the solution does not require the inversion of a covariance matrix. The discrete multi-period portfolio optimization problem we solve is significantly harder than the continuous variable problem. We present insight into how results may be improved using suitable software enhancements and why current quantum annealing technology limits the size of problem that can be successfully solved today. Here, the formulation presented is specifically designed to be scalable, with the expectation that as quantum annealing technology improves, larger problems will be solvable using the same techniques.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS2008

Chasing a Comet with a Solar Sail

Solar sail propulsion systems enable a wide range of missions that require constant thrust or high delta-V over long mission times. One particularly challenging mission type is a comet rendezvous mission. This paper presents optimal low-thrust trajectory designs for a range of sailcraft performance metrics and mission transit times that enables a comet rendezvous mission. These optimal trajectory results provide a trade space which can be parameterized in terms of mission duration and sailcraft performance parameters such that a design space for a small satellite comet chaser mission is identified. These results show that a feasible space exists for a small satellite to perform a comet chaser mission in a reasonable mission time.

Stough, Robert W.↗

NASA NTRS2012

Creation of an Upper Stage Trajectory Capability Boundary to Enable Booster System Trade Space Exploration

The problem of trajectory optimization is important in all space missions. The solution of this problem enables one to specify the optimum thrust steering program which should be followed to achieve a specified mission objective, simultaneously satisfying the constraints.1 It is well known that whether or not the ascent trajectory is optimal can have a significant impact on propellant usage for a given payload, or on payload weight for the same gross vehicle weight.2 Consequently, ascent guidance commands are usually optimized in some fashion. Multi-stage vehicles add complexity to this analysis process as changes in vehicle properties in one stage propagate to the other stages through gear ratios and changes in the optimal trajectory. These effects can cause an increase in analysis time as more variables are added and convergence of the optimizer to system closure requires more analysis iterations. In this paper, an approach to simplifying this multi-stage problem through the creation of an upper stage capability boundary is presented. This work was completed as part of a larger study focused on trade space exploration for the advanced booster system that will eventually form a part of NASA s new Space Launch System.3 The approach developed leverages Design of Experiments and Surrogate Modeling4 techniques to create a predictive model of the SLS upper stage performance. The design of the SLS core stages is considered fixed for the purposes of this study, which results in trajectory parameters such as staging conditions being the only variables relevant to the upper stage. Through the creation of a surrogate model, which takes staging conditions as inputs and predicts the payload mass delivered by the SLS upper stage to a reference orbit as the response, it is possible to identify a "surface" of staging conditions which all satisfy the SLS requirement of placing 130 metric tons into low-Earth orbit (LEO).3 This identified surface represents the 130 metric ton capability boundary for the upper stage, such that if the combined first stage and boosters can achieve any one staging point on that surface, then the design is identified as feasible. With the surrogate model created, design and analysis of advanced booster concepts is streamlined, as optimization of the upper stage trajectory is no longer required in every design loop.

Walsh, Ptrick↗

NASA NTRS2017

Automated Sensitivity Analysis of Interplanetary Trajectories for Optimal Mission Design

This work describes a suite of Python tools known as the Python EMTG Automated Trade Study Application (PEATSA). PEATSA was written to automate the operation of trajectory optimization software, simplify the process of performing sensitivity analysis, and was ultimately found to out-perform a human trajectory designer in unexpected ways. These benefits will be discussed and demonstrated on sample mission designs.

trajectory design↗

NASA NTRS2003

A Comparison of Electric Propulsion Systems for Mars Exploration

Earth-Mars trajectories for multiple solar-powered spacecraft configurations were generated using Hall and ion propulsion systems utilizing the Direct Trajectory Optimization Method. Payload and power trades versus trip time were examined. Performance was compared for purely interplanetary flight and interplanetary flight with estimated spiral in to Mars orbit. Evaluating current ion and Hall thruster technologies, similar payload masses were delivered by each at equivalent trip times, but with the Hall thruster operating at a power level 10 kilowatts, on average, less than the ion thruster. The power difference for equivalent payload delivered should result in a significant cost savings.

Fiehler, Douglas↗

NASA NTRS1976

Nozzle selection for optimized single-stage shuttles

A computerized preliminary design procedure has been used to determine rocket-engine bell-nozzle configurations which achieve either minimum gross mass or minimum dry mass on an advanced technology winged single-stage-to-orbit launch vehicle. This procedure evaluates the trade offs between the optimized ascent flight trajectory performance and the flight vehicle sizing driven by the engine mass and propellant requirements. Numerous mission, flight, and vehicle related requirements and constraints are satisfied in this process. Propulsion system configurations which incorporate dual-position nozzles are evaluated and compared to configurations using all fixed nozzles.

Eldred, C. H.↗

NASA NTRS2017

Improvement of Automated POST Case Success Rate Using Support Vector Machines

Zwack, Mathew R.↗

NASA NTRS2017

Improvement of Automated POST Case Success Rate Using Support Vector Machines

During early conceptual design of complex systems, concept down selection can have a large impact upon program life-cycle cost. Therefore, any concepts selected during early design will inherently commit program costs and affect the overall probability of program success. For this reason it is important to consider as large a design space as possible in order to better inform the down selection process. For conceptual design of launch vehicles, trajectory analysis and optimization often presents the largest obstacle to evaluating large trade spaces. This is due to the sensitivity of the trajectory discipline to changes in all other aspects of the vehicle design. Small deltas in the performance of other subsystems can result in relatively large fluctuations in the ascent trajectory because the solution space is non-linear and multi-modal [1]. In order to help capture large design spaces for new launch vehicles, the authors have performed previous work seeking to automate the execution of the industry standard tool, Program to Optimize Simulated Trajectories (POST). This work initially focused on implementation of analyst heuristics to enable closure of cases in an automated fashion, with the goal of applying the concepts of design of experiments (DOE) and surrogate modeling to enable near instantaneous throughput of vehicle cases [2]. Additional work was then completed to improve the DOE process by utilizing a graph theory based approach to connect similar design points [3]. The conclusion of the previous work illustrated the utility of the graph theory approach for completing a DOE through POST. However, this approach was still dependent upon the use of random repetitions to generate seed points for the graph. As noted in [3], only 8% of these random repetitions resulted in converged trajectories. This ultimately affects the ability of the random reps method to confidently approach the global optima for a given vehicle case in a reasonable amount of time. With only an 8% pass rate, tens or hundreds of thousands of reps may be needed to be confident that the best repetition is at least close to the global optima. However, typical design study time constraints require that fewer repetitions be attempted, sometimes resulting in seed points that have only a handful of successful completions. If a small number of successful repetitions are used to generate a seed point, the graph method may inherit some inaccuracies as it chains DOE cases from the non-global-optimal seed points. This creates inherent noise in the graph data, which can limit the accuracy of the resulting surrogate models. For this reason, the goal of this work is to improve the seed point generation method and ultimately the accuracy of the resulting POST surrogate model. The work focuses on increasing the case pass rate for seed point generation.

Zwack, Matthew R.↗

NASA NTRS2023

Flight Mechanics Analysis Tools Interoperability and Component Sharing

As multiple flight mechanics (FM) analysis tools are developed to meet the unique scientific and operational requirements of NASA missions, sharing data, transferring models and trajectory information between tools can be complicated. The NESC recently explored ways that increase interoperability of three mission analysis tools: Copernicus, General Mission Analysis Tool (GMAT), and Mission-Analysis Operations Navigation Toolkit Environment (MONTE). These tools are used to generate a variety of products throughout all phases of a mission including: maneuver planning, trajectory optimization and design, orbit determination, performance and error analysis, trade studies and sizing. Establishing a framework to share models, component data and trajectory information is an efficient way to leverage the benefits of an analysis tool without expending development costs to duplicate functionality.

Flight Mechanics Simulation↗

NASA NTRS1982

Optimal short-range trajectories for helicopters

An optimal flight path algorithm using a simplified altitude state model and a priori climb cruise descent flight profile was developed and applied to determine minimum fuel and minimum cost trajectories for a helicopter flying a fixed range trajectory. In addition, a method was developed for obtaining a performance model in simplified form which is based on standard flight manual data and which is applicable to the computation of optimal trajectories. The entire performance optimization algorithm is simple enough that on line trajectory optimization is feasible with a relatively small computer. The helicopter model used is the Silorsky S-61N. The results show that for this vehicle the optimal flight path and optimal cruise altitude can represent a 10% fuel saving on a minimum fuel trajectory. The optimal trajectories show considerable variability because of helicopter weight, ambient winds, and the relative cost trade off between time and fuel. In general, reasonable variations from the optimal velocities and cruise altitudes do not significantly degrade the optimal cost. For fuel optimal trajectories, the optimum cruise altitude varies from the maximum (12,000 ft) to the minimum (0 ft) depending on helicopter weight.

Slater, G. L.↗

NASA NTRS2015

Coupled Low-thrust Trajectory and System Optimization via Multi-Objective Hybrid Optimal Control

The optimization of low-thrust trajectories is tightly coupled with the spacecraft hardware. Trading trajectory characteristics with system parameters ton identify viable solutions and determine mission sensitivities across discrete hardware configurations is labor intensive. Local independent optimization runs can sample the design space, but a global exploration that resolves the relationships between the system variables across multiple objectives enables a full mapping of the optimal solution space. A multi-objective, hybrid optimal control algorithm is formulated using a multi-objective genetic algorithm as an outer loop systems optimizer around a global trajectory optimizer. The coupled problem is solved simultaneously to generate Pareto-optimal solutions in a single execution. The automated approach is demonstrated on two boulder return missions.

Spacecraft Systems↗

NASA NTRS2011

Hayabusa Re-Entry: Trajectory Analysis and Observation Mission Design

On June 13th, 2010, the Hayabusa sample return capsule successfully re-entered Earth s atmosphere over the Woomera Prohibited Area in southern Australia in its quest to return fragments from the asteroid 1998 SF36 Itokawa . The sample return capsule entered at a super-orbital velocity of 12.04 km/sec (inertial), making it the second fastest human-made object to traverse the atmosphere. The NASA DC-8 airborne observatory was utilized as an instrument platform to record the luminous portion of the sample return capsule re-entry (~60 sec) with a variety of on-board spectroscopic imaging instruments. The predicted sample return capsule s entry state information at ~200 km altitude was propagated through the atmosphere to generate aerothermodynamic and trajectory data used for initial observation flight path design and planning. The DC- 8 flight path was designed by considering safety, optimal sample return capsule viewing geometry and aircraft capabilities in concert with key aerothermodynamic events along the predicted trajectory. Subsequent entry state vector updates provided by the Deep Space Network team at NASA s Jet Propulsion Laboratory were analyzed after the planned trajectory correction maneuvers to further refine the DC-8 observation flight path. Primary and alternate observation flight paths were generated during the mission planning phase which required coordination with Australian authorities for pre-mission approval. The final observation flight path was chosen based upon trade-offs between optimal viewing requirements, ground based observer locations (to facilitate post-flight trajectory reconstruction), predicted weather in the Woomera Prohibited Area and constraints imposed by flight path filing deadlines. To facilitate sample return capsule tracking by the instrument operators, a series of two racetrack flight path patterns were performed prior to the observation leg so the instruments could be pointed towards the region in the star background where the sample return capsule was expected to become visible. An overview of the design methodologies and trade-offs used in the Hayabusa re-entry observation campaign are presented.

Cassell, Alan M.↗

NASA NTRS1991

Mars entry-to-landing trajectory optimization and closed loop guidance

The guidance strategy of the Mars Rover Sample Return mission is presented in detail. Aeromaneuver versus aerobrake trades are examined, and an aerobrake analysis is presented which takes into account targeting, guidance, flight control, trajectory profile, delivery accuracy. An aeromaneuver analysis is given which includes the entry corridor, maneuver footprint, guidance, preentry phase, constant drag phase, equilibrium guide phase, variable drag phase, influence of trajectory profile on the entry flight loads, parachute deployment conditions and strategies, and landing accuracy. The Mars terminal descent phase is analyzed.

Ilgen, Marc R.↗

NASA NTRS1983

Optimal short range trajectories for helicopters

An optimal flight path algorithm using a simplified altitude state model and an apriori climb-cruise-descent flight profile has been developed and applied to determine minimum fuel and minimum cost trajectories for a helicopter flying a fixed range trajectory. The performance model is based on standard flight manual data and is such that on-line trajectory optimization is feasible with a relatively small computer. The results show that the optimal flight path and optimal cruise altitude can represent a 10 percent fuel saving on a minimum fuel trajectory. The optimal trajectories show considerable variability due to helicopter weight, ambient winds and the relative cost trade-off between time and fuel. In general, 'reasonable' variations from the optimal velocities and cruise altitudes do not significantly degrade the optimal cost.

Slater, G. L.↗

NASA NTRS2020

Path-Adaptive Guidance Algorithm Trades for a Two-Stage Lunar Descent Vehicle

For the next generation of NASA’s missions, the necessity for path-adaptive guidance algorithms has become clear in order to provide the stability and customizability required for a safe and efficient descent to the lunar surface, while meeting specified program and vehicle constraints. Several descent algorithms have been tested and flown for single-stage landers through the Apollo and Altair programs, but thus far little analysis has been conducted involving the application of these algorithms for a two-stage descent vehicle. Due to the limited payload mass constraints of the existing fleet of launch vehicles, multi-stage descent architectures have become a viable course of action. This paper seeks to compare the performance of guidance configurations for a lunar lander system consisting of two stages, one of which separates partway through descent. Through development of this paper, an optimization suite has been written that is specifically designed for optimizing planetary non-atmospheric two-stage descent trajectories, and is used as a comparison baseline for the guidance algorithms tested. Time-to -go computational methods and ignition logic routines that may be employed in a lunar environment are also discussed. Further work is to be completed on trajectory design trades as well as the effects of modifying guidance targets in simulation based on trajectories that are optimized for different performance indices.

Jason M Everett↗

DOE OSTI2015

Noncoplanar VMAT for nasopharyngeal tumors: Plan quality versus treatment time

Purpose: The authors investigated the potential of optimized noncoplanar irradiation trajectories for volumetric modulated arc therapy (VMAT) treatments of nasopharyngeal patients and studied the trade-off between treatment plan quality and delivery time in radiation therapy. Methods: For three nasopharyngeal patients, the authors generated treatment plans for nine different delivery scenarios using dedicated optimization methods. They compared these scenarios according to dose characteristics, number of beam directions, and estimated delivery times. In particular, the authors generated the following treatment plans: (1) a 4π plan, which is a not sequenced, fluence optimized plan that uses beam directions from approximately 1400 noncoplanar directions and marks a theoretical upper limit of the treatment plan quality, (2) a coplanar 2π plan with 72 coplanar beam directions as pendant to the noncoplanar 4π plan, (3) a coplanar VMAT plan, (4) a coplanar step and shoot (SnS) plan, (5) a beam angle optimized (BAO) coplanar SnS IMRT plan, (6) a noncoplanar BAO SnS plan, (7) a VMAT plan with rotated treatment couch, (8) a noncoplanar VMAT plan with an optimized great circle around the patient, and (9) a noncoplanar BAO VMAT plan with an arbitrary trajectory around the patient. Results: VMAT using optimized noncoplanar irradiation trajectories reduced the mean and maximum doses in organs at risk compared to coplanar VMAT plans by 19% on average while the target coverage remains constant. A coplanar BAO SnS plan was superior to coplanar SnS or VMAT; however, noncoplanar plans like a noncoplanar BAO SnS plan or noncoplanar VMAT yielded a better plan quality than the best coplanar 2π plan. The treatment plan quality of VMAT plans depended on the length of the trajectory. The delivery times of noncoplanar VMAT plans were estimated to be 6.5 min in average; 1.6 min longer than a coplanar plan but on average 2.8 min faster than a noncoplanar SnS plan with comparable treatment plan quality. Conclusions: The authors’ study reconfirms the dosimetric benefits of noncoplanar irradiation of nasopharyngeal tumors. Both SnS using optimized noncoplanar beam ensembles and VMAT using an optimized, arbitrary, noncoplanar trajectory enabled dose reductions in organs at risk compared to coplanar SnS and VMAT. Using great circles or simple couch rotations to implement noncoplanar VMAT, however, was not sufficient to yield meaningful improvements in treatment plan quality. The authors estimate that noncoplanar VMAT using arbitrary optimized irradiation trajectories comes at an increased delivery time compared to coplanar VMAT yet at a decreased delivery time compared to noncoplanar SnS IMRT.

60 APPLIED LIFE SCIENCES↗

NASA NTRS2008

NASA's Planned Return to the Moon: Global Access and Anytime Return Requirement Implications on the Lunar Orbit Insertion Burns

Lunar orbit insertion LOI is a critical maneuver for any mission going to the Moon. Optimizing the geometry of this maneuver is crucial to the success of the architecture designed to return humans to the Moon. LOI burns necessary to meet current NASA Exploration Constellation architecture requirements for the lunar sortie missions are driven mainly by the requirement for global access and "anytime" return from the lunar surface. This paper begins by describing the Earth-Moon geometry which creates the worst case (delta)V for both the LOI and the translunar injection (TLI) maneuvers over the full metonic cycle. The trajectory which optimizes the overall (delta)V performance of the mission is identified, trade studies results covering the entire lunar globe are mapped onto the contour plots, and the effects of loitering in low lunar orbit as a means of reducing the insertion (delta)V are described. Finally, the lighting conditions on the lunar surface are combined with the LOI and TLI analyses to identify geometries with ideal lighting conditions at sites of interest which minimize the mission (delta)V.

Garn, Michelle↗

NASA NTRS2017

Automated Sensitivity Analysis of Interplanetary Trajectories

trajectory design↗