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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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At least 595 records · Page 33
All sourcesNASA NTRSDOE OSTI
NASA NTRS1997

Preliminary Design of Low-Thrust Interplanetary Missions

For interplanetary missions, highly efficient electric propulsion systems can be used to increase the mass delivered to the destination and/or reduce the trip time over typical chemical propulsion systems. This technology is being demonstrated on the Deep Space 1 mission - part of NASA's New Millennium Program validating technologies which can lower the cost and risk and enhance the performance of future missions. With the successful demonstration on Deep Space 1, future missions can consider electric propulsion as a viable propulsion option. Electric propulsion systems, while highly efficient, produce only a small amount of thrust. As a result, the engines operate during a significant fraction of the trajectory. This characteristic makes it much more difficult to find optimal trajectories. The methods for optimizing low-thrust trajectories are typically categorized as either indirect, or direct. Indirect methods are based on calculus of variations, resulting in a two-point boundary value problem that is solved by satisfying terminal constraints and targeting conditions. These methods are subject to extreme sensitivity to the initial guess of the variables - some of which are not physically intuitive. Adding a gravity assist to the trajectory compounds the sensitivity. Direct methods parameterize the problem and use nonlinear programming techniques to optimize an objective function by adjusting a set of variables. A variety of methods of this type have been examined with varying results. These methods are subject to the limitations of the nonlinear programming techniques. In this paper we present a direct method intended to be used primarily for preliminary design of low-thrust interplanetary trajectories, including those with multiple gravity assists. Preliminary design implies a willingness to accept limited accuracy to achieve an efficient algorithm that executes quickly.

Sims, Jon A.↗
NASA NTRS2017

Computationally Efficient Motion Planning Algorithms for Agile Autonomous Vehicles in Cluttered Environments

Fast, real-time motion planning of an agile, autonomous vehicle in a cluttered environment, with many geometrically-fixed obstacles, is a very complex problem, especially because of the vehicle dynamics constraints and resource constrained computational capabilities onboard the vehicle. In this paper, we present computationally-efficient versions of our novel motion planning algorithm called the Spherical Expansion and Sequential Convex Programming (SE–SCP) algorithm. The SE–SCP algorithm first uses a spherical-expansion-based randomized sampling algorithm to explore the workspace. Oncea path is found from the start position to the goal position, the algorithm computes a locally optimal trajectory, within its homotopy class for a desired cost function, by solving a sequence of convex optimization problems. Thus, the SE–SCP algorithm is anytime locally optimal and the trajectory is globally optimal if the number of samples tends to infinity. In this paper, we further enhance the computational efficiency of the SE–SCP algorithm using uni-directional and bi-directional rewiring techniques. We also present a detailed proof of the local optimality characteristics of the new SE–SCP algorithms for aspecial case of vehicle dynamics. Simulation examples involving quadrotor and spacecraft help demonstrate the effectiveness of our new algorithms.

Bandyopadhyay, Saptarshi↗
NASA NTRS2004

OTIS 3.2 Software Released

Trajectory, mission, and vehicle engineers concern themselves with finding the best way for an object to get from one place to another. These engineers rely upon special software to assist them in this. For a number of years, many engineers have used the OTIS program for this assistance. With OTIS, an engineer can fully optimize trajectories for airplanes, launch vehicles like the space shuttle, interplanetary spacecraft, and orbital transfer vehicles. OTIS provides four modes of operation, with each mode providing successively stronger optimization capability. The most powerful mode uses a mathematical method called implicit integration to solve what engineers and mathematicians call the optimal control problem. OTIS 3.2, which was developed at the NASA Glenn Research Center, is the latest release of this industry workhorse and features new capabilities for parameter optimization and mission design. OTIS stands for Optimal Control by Implicit Simulation, and it is implicit integration that makes OTIS so powerful at solving trajectory optimization problems. Why is this so important? The optimization process not only determines how to get from point A to point B, but it can also determine how to do this with the least amount of propellant, with the lightest starting weight, or in the fastest time possible while avoiding certain obstacles along the way. There are numerous conditions that engineers can use to define optimal, or best. OTIS provides a framework for defining the starting and ending points of the trajectory (point A and point B), the constraints on the trajectory (requirements like "avoid these regions where obstacles occur"), and what is being optimized (e.g., minimize propellant). The implicit integration method can find solutions to very complicated problems when there is not a lot of information available about what the optimal trajectory might be. The method was first developed for solving two-point boundary value problems and was adapted for use in OTIS. Implicit integration usually allows OTIS to find solutions to problems much faster than programs that use explicit integration and parametric methods. Consequently, OTIS is best suited to solving very complicated and highly constrained problems.

Riehl, John P.↗
NASA NTRS1972

Rocket ascent G-limited moment-balanced optimization program (RAGMOP)

This document describes the RAGMOP (Rocket Ascent G-limited Momentbalanced Optimization Program) computer program for parametric ascent trajectory optimization. RAGMOP computes optimum polynomial-form attitude control histories, launch azimuth, engine burn-time, and gross liftoff weight for space shuttle type vehicles using a search-accelerated, gradient projection parameter optimization technique. The trajectory model available in RAGMOP includes a rotating oblate earth model, the option of input wind tables, discrete and/or continuous throttling for the purposes of limiting the thrust acceleration and/or the maximum dynamic pressure, limitation of the structural load indicators (the product of dynamic pressure with angle-of-attack and sideslip angle), and a wide selection of intermediate and terminal equality constraints.

Lyons, J. T.↗
NASA NTRS1995

A open loop guidance architecture for navigationally robust on-orbit docking

The development of an open-hop guidance architecture is outlined for autonomous rendezvous and docking (AR&D) missions to determine whether the Global Positioning System (GPS) can be used in place of optical sensors for relative initial position determination of the chase vehicle. Feasible command trajectories for one, two, and three impulse AR&D maneuvers are determined using constrained trajectory optimization. Early AR&D command trajectory results suggest that docking accuracies are most sensitive to vertical position errors at the initial conduction of the chase vehicle. Thus, a feasible command trajectory is based on maximizing the size of the locus of initial vertical positions for which a fixed sequence of impulses will translate the chase vehicle into the target while satisfying docking accuracy requirements. Documented accuracies are used to determine whether relative GPS can achieve the vertical position error requirements of the impulsive command trajectories. Preliminary development of a thruster management system for the Cargo Transfer Vehicle (CTV) based on optimal throttle settings is presented to complete the guidance architecture. Results show that a guidance architecture based on a two impulse maneuvers generated the best performance in terms of initial position error and total velocity change for the chase vehicle.

Chern, Hung-Sheng↗
NASA NTRS1967

Computer program for mass optional solutions of some endpoint trajectory problems

Optimization of trajectories for propellant comsumption is achieved by incorporating a coast arc device into a three-dimensional fixed end-point steepest ascent computer program. It calculates a trajectory between any two points in space defined by initial and final position vectors, without restrictions on thrust or orbit characteristics.

Bennett, A. G.↗
NASA NTRS2020

Copernicus Spacecraft Trajectory Design and Optimization Program

Copernicus is a spacecraft trajectory design and optimization application developed at the NASA Johnson Space Center. Copernicus is written in Fortran and uses many features of the latest language standards. The tool is used for a wide range of projects at NASA, including the upcoming Artemis missions to flight test the Orion spacecraft and then return humans to the Moon. This presentation gives a brief overview of the software, its history, how it was designed, and how it is used.

Copernicus↗
DOE OSTI2016

TH-EF-BRB-04: 4π Dynamic Conformal Arc Therapy Dynamic Conformal Arc Therapy (DCAT) for SBRT

Purpose: To develop an efficient and effective trajectory optimization methodology for 4π dynamic conformal arc treatment (4π DCAT) with synchronized gantry and couch motion; and to investigate potential clinical benefits for stereotactic body radiation therapy (SBRT) to breast, lung, liver and spine tumors. Methods: The entire optimization framework for 4π DCAT inverse planning consists of two parts: 1) integer programming algorithm and 2) particle swarm optimization (PSO) algorithm. The integer programming is designed to find an optimal solution for arc delivery trajectory with both couch and gantry rotation, while PSO minimize a non-convex objective function based on the selected trajectory and dose-volume constraints. In this study, control point interaction is explicitly taken into account. Beam trajectory was modeled as a series of control points connected together to form a deliverable path. With linear treatment planning objectives, a mixed-integer program (MIP) was formulated. Under mild assumptions, the MIP is tractable. Assigning monitor units to control points along the path can be integrated into the model and done by PSO. The developed 4π DCAT inverse planning strategy is evaluated on SBRT cases and compared to clinically treated plans. Results: The resultant dose distribution of this technique was evaluated between 3D conformal treatment plan generated by Pinnacle treatment planning system and 4π DCAT on a lung SBRT patient case. Both plans share the same scale of MU, 3038 and 2822 correspondingly to 3D conformal plan and 4π DCAT. The mean doses for most of OARs were greatly reduced at 32% (cord), 70% (esophagus), 2.8% (lung) and 42.4% (stomach). Conclusion: Initial results in this study show the proposed 4π DCAT treatment technique can achieve better OAR sparing and lower MUs, which indicates that the developed technique is promising for high dose SBRT to reduce the risk of secondary cancer.

60 APPLIED LIFE SCIENCES↗
NASA NTRS1981

Cost-minimized aircraft trajectories

For aircraft operating over fixed range, operating costs are basically sum of fuel cost and time cost; but determining minimum cost trajectory can be complex. Program optimizes trajectories with respect to cost function that is based on weighed sum of fuel cost and time cost. Minimum fuel, minimum time, and various delay trajectories are obtained by specifying particular values for fuel and time cost factors.

Lee, H.↗
NASA NTRS2005

Analysis of Chemical, REP, and SEP missions to the Trojan asteroids

Recent studies suggest significant benefits from using 1st and 2nd generation Radioisotope Power Systems (RPS) as a power source for electric propulsion (EP) missions to the outer planets. This study focuses on trajectories to the Trojan asteroids. A high level analysis is performed with chemical trajectories to determine potential canidates for REP trajectory optimization. Extensive analysis of direct trajectories using REP is performed on these candidates. Solar Electric Propulsion (SEP) trajectories are also considered for comparison against REP trajectories.

Trojan asteroids↗
NASA NTRS1976

Use of steepest descent and various approximations for efficient computation of minimum noise aircraft landing trajectories

The following areas related to landing trajectory optimization research were discussed: (1) programming and modifying the steepest descent optimization procedure, (2) successfully iterating toward the optimum for a four-mile trajectory, (3) beginning optimization runs for a twenty-mile trajectory, and (4) adapt wind tunnel data for computer usage. Other related areas were discussed in detail in the two previous annual reports.

Cook, G.↗
NASA NTRS2004

Optimizing Mars Airplane Trajectory with the Application Navigation System

Planning complex missions requires a number of programs to be executed in concert. The Application Navigation System (ANS), developed in the NAS Division, can execute many interdependent programs in a distributed environment. We show that the ANS simplifies user effort and reduces time in optimization of the trajectory of a martian airplane. We use a software package, Cart3D, to evaluate trajectories and a shortest path algorithm to determine the optimal trajectory. ANS employs the GridScape to represent the dynamic state of the available computer resources. Then, ANS uses a scheduler to dynamically assign ready task to machine resources and the GridScape for tracking available resources and forecasting completion time of running tasks. We demonstrate system capability to schedule and run the trajectory optimization application with efficiency exceeding 60% on 64 processors.

Frumkin, Michael↗
NASA NTRS1989

A real-time guidance algorithm for aerospace plane optimal ascent to low earth orbit

Problems of onboard trajectory optimization and synthesis of suitable guidance laws for ascent to low Earth orbit of an air-breathing, single-stage-to-orbit vehicle are addressed. A multimode propulsion system is assumed which incorporates turbojet, ramjet, Scramjet, and rocket engines. An algorithm for generating fuel-optimal climb profiles is presented. This algorithm results from the application of the minimum principle to a low-order dynamic model that includes angle-of-attack effects and the normal component of thrust. Maximum dynamic pressure and maximum aerodynamic heating rate constraints are considered. Switching conditions are derived which, under appropriate assumptions, govern optimal transition from one propulsion mode to another. A nonlinear transformation technique is employed to derived a feedback controller for tracking the computed trajectory. Numerical results illustrate the nature of the resulting fuel-optimal climb paths.

Calise, A. J.↗
NASA NTRS2004

A practical six-degree of freedom solar sail dynamics model for optimizing solar sail trajectories with torque constraints

Controlled flight of a solar sail-propelled spacecraft ('sailcraft') is a six-degree-of-freedom dynamics problem. Current state-of-the-art tools that simulate and optimize the trajectories flown by sailcraft do not treat the full kinetic (i.e. force and torque-constrained) motion, instead treating a discrete history of commanded sail attitudes, and either neglecting the sail attitude motion over an integration timestep, or treating the attitude evolution kinematically with a spline or similar treatment. The present paper discusses an aspect of developing a next generation sailcraf trajectory designing optimization tool JPL, for NASA's Solar Sail Spaceflight Simulation Software (SS). The aspect discussed in an experimental approach to modeling full six-degree-of-freedom kinetic motion of a solar sail in a trajectory propagator. Early results from implementing this approach in a new trajectory propagation tool are given.

six-degree-of-freedom↗