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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 1,567 records · Page 87
All sourcesNASA NTRSDOE OSTI
NASA NTRS2000

Navigation Strategy for the Mars 2001 Lander Mission

The Mars Surveyor Program (MSP) is an ongoing series of missions designed to robotically study, map and search for signs of life on the planet Mars. The MSP 2001 project will advance the effort by sending an orbiter, a lander and a rover to the red planet in the 2001 opportunity. Each vehicle will carry a science payload that will Investigate the Martian environment on both a global and on a local scale. Although this mission will not directly search for signs of life, or cache samples to be returned to Earth, it will demonstrate certain enabling technologies that will be utilized by the future Mars Sample Return missions. One technology that is needed for the Sample Return mission is the capability to place a vehicle on the surface within several kilometers of the targeted landing site. The MSP'01 Lander will take the first major step towards this type of precision landing at Mars. Significant reduction of the landed footprint will be achieved through two technology advances. The first, and most dramatic, is hypersonic aeromaneuvering; the second is improved approach navigation. As a result, the guided entry will produce in a footprint that is only tens of kilometers, which is an order of magnitude improvement over the Pathfinder and Mars Polar Lander ballistic entries. This reduction will significantly enhance scientific return by enabling the potential selection of otherwise unreachable landing sites with unique geologic interest and public appeal. A landed footprint reduction from hundreds to tens of kilometers is also a milestone on the path towards human exploration of Mars, where the desire is to place multiple vehicles within several hundred meters of the planned landing site. Hypersonic aeromaneuvering is an extension of the atmospheric flight goals of the previous landed missions, Pathfinder and Mars Polar Lander (MPL), that utilizes aerodynamic lift and an autonomous guidance algorithm while in the upper atmosphere. The onboard guidance algorithm will control the direction of the lift vector, via bank angle modulation, to keep the vehicle on the desired trajectory. While numerous autonomous guidance algorithms have been developed for use during hypersonic flight at Earth, this will be the first flight of an autonomously directed lifting entry vehicle at Mars. However, without sufficient control and knowledge of the atmospheric entry conditions, the guidance algorithm will not perform effectively. The goal of the interplanetary navigation strategy is to deliver the spacecraft to the desired entry condition with sufficient accuracy and knowledge to enable satisfactory guidance algorithm performance. Specifically, the entry flight path angle must not exceed 0.27 deg. to a 3 sigma confidence level. Entry errors will contribute directly to the size of the landed footprint and the most significant component is entry flight path angle. The size of the entry corridor is limited on the shallow side by integrated heating constraints, and on the steep side by deceleration (g-load) and terminal descent propellant. In order to meet this tight constraint it is necessary to place a targeting maneuver seven hours prior to the time of entry. At this time the trajectory knowledge will be quite accurate, and the effects of maneuver execution errors will be small. The drawback is that entry accuracy is dependent on the success of this final late maneuver. Because propulsive maneuvers are critical events, it is desirable to minimize their occurrence and provide the flight team with as much response time as possible in the event of a spacecraft fault. A mission critical maneuver at Entry - 7 hours does not provide much fault tolerance, and it is desirable to provide a strategy that minimizes reliance on this maneuver. This paper will focus on the Improvements in interplanetary navigation that will decrease entry errors and will reduce the landed footprint, even in the absence of aeromaneuvering. The easiest to take advantage of are Improvements In the knowledge of the Mars ephemeris and gravity field due to the MGS and MSP'98 missions. Improvements In data collection and reduction techniques such as "precislon ranging' and near-simultaneous tracking will also be utilized. In addition to precise trajectory control, a robust strategy for communications and flight operations must also be demonstrated. The result Is a navigation and communications strategy on approach that utilizes optimal maneuver placement to take advantage of trajectory knowledge, minimizes risk for the flight operations team, is responsive to spacecraft hardware limitations, and achieves the entry corridor. The MSP2001 mission Is managed at JPL under the auspices of the Mars Exploration Directorate. The spacecraft flight elements are built and managed by Lockheed-Martin Astronautics in Denver, Colorado.

Mase, Robert A.↗
NASA NTRS1988

Entry aeromaneuvering capabilities of transatmospheric vehicles

The landing footprint of a conceptual high-lift transatmospheric vehicle is defined for aeromaneuvering entry from a typical low-earth orbit. The flight strategy for trajectory construction to maximize the landing area by extending downrange and crossrange as far as possible is developed in four phases by optimal programming of the vehicle's roll angle. Trajectories that reach any given landing site were calculated with the corresponding heating rates at three critical vehicle locations (stagnation point, wing leading edge, and body centerline). An optimization methodology was developed that demonstrates the trades between crossrange, peak heating and total heat loads as a function of three key flight parameters (altitude, flight-path angle, and vehicle roll angle). The maximum extent of the landing footprint was found to be 29,690 km downrange and 6560 km crossrange. Large variations in the ballistic coefficient had negligible effect on the extent of the footprint but could significantly affect heating. However, the footprint's longitude was displaced downstream or upstream with increasing or decreasing ballistic coefficient, respectively.

Menees, Gene P.↗
NASA NTRS2015

An Analytical Solution for Yaw Maneuver Optimization on the International Space Station and Other Orbiting Space Vehicles

This paper presents a new method for optimizing yaw maneuvers, which are the most common large maneuvers on the International Space Station (ISS). The goal of the maneuver optimization is to find a maneuver trajectory with minimal torques acting on the vehicle during the maneuver. Therefore, the thruster firings necessary to perform the maneuver are minimized. Reduction of thruster firings saves propellant and decreases structural loads and contamination of the vehicle critical elements, thus saving the service life of the thrusters and the vehicle itself. Equations describing the pitch and roll motion needed to counteract the major torques during a yaw maneuver are obtained. Also, a yaw rate profile is suggested. In the obtained optimized case, the torques are significantly reduced. The proposed approximate analytical solution does not require extensive computer resources and, therefore, can be implemented using software onboard the ISS. As a result, the maneuver execution will be automatic. This is one of the major benefits of the simplified solution presented in this paper with respect to existing computational approaches. The suggested maneuver optimization method can be used not only for the ISS, but for other space vehicles as well.

Dobrinskaya, Tatiana↗
NASA NTRS1974

Vehicle control for fuel optimization

The problem of predicting the minimum fuel trajectory for a six degree of freedom vehicle which has a motion characterized by the first order differential equations of translational and rotational dynamics is considered. The thrust direction and center of gravity of the vehicle are assumed to be fixed with respect to the vehicle. Thrust magnitude and the control moment are used as control variables and appear linearly in the equation of motion. Pontryagin's Maximum Principle is used to solve the variational problem. With this formulation, the extremal controls are bang-bang with the exception of the singular case.

Dannenberg, K. D.↗
NASA NTRSDate not supplied

Robust Trajectory Design for Rendezvous in a Near Rectilinear Halo Orbit

Future NASA Artemis missions will require complex docking plans between the Orion capsule and Lunar Gateway that meet predetermined safety constraints while minimizing fuel usage and state uncertainty at rendezvous. In this paper, linear covariance analysis is applied to a first order relative form of Near-Rectilinear Halo Orbit dynamics to determine the nominal trajectories and state dispersions associated with various maneuver profiles in the Sun-referenced Local Vertical Local Horizontal reference frame of the lunar Gateway. These maneuver profiles are optimized using a particle swarm optimizer and direct search algorithm to find trajectories that satisfy approach corridor, free drift, velocity magnitude, under-burn, and maneuver transfer time safety constraints to 3-sigma certainty.

Linear Covariance Analysis↗
DOE OSTI2018

Fuel Efficient Speed Optimization for Real-World Highway Cruising

This paper introduces an eco-driving highway cruising algorithm based on optimal control theory that is applied to a conventionally-powered connected and automated vehicle. Thanks to connectivity to the cloud and/or to infrastructure, speed limit and slope along the future route can be known with accuracy. This can in turn be used to compute the control variable trajectory that will minimize energy consumption without significantly impacting travel time. Automated driving is necessary to the implementation of this concept, because the chosen control variables (e.g., torque and gear) impact vehicle speed. An optimal control problem is built up where quadratic models are used for the powertrain. The optimization is solved by applying Pontryagin’s minimum principle, which reduces the problem to the minimization of a cost function with parameters called co-states. The proposed algorithm assumes piecewise constant slopes and speed limits, and it solves the transition vehicle speeds for each junction of such segments. In addition, a method to extract route information from digital maps is presented, which complies with the proposed optimization algorithm. The algorithms are evaluated in simulation, using Autonomie, a simulation tool for vehicle energy consumption modeling. The optimal control trajectory (e.g., torque, gear) is first computed offline. It is then applied in an open-loop fashion in online simulation, using a forward-looking model of the vehicle in Autonomie. Simulation results show over 8% fuel saving for two selected real-world routes.

Simulation and modeling, Optimization, Vehicle net↗
NASA NTRS2017

MColl: Monte Collocation Trajectory Design Tool

In this paper we describe a prototype low-thrust optimization software being developed at JPL. The software tool is based on a collocation algorithm where a trajectory discretization is fitted and adjusted until the underlying dynamics equations of motion are satisfied. The resulting large scale non-linear programming problem may either be optimized with IPOPT or KNITRO. The user specifies path constraints, boundary constraints, and objectives. We describe the collocation algorithm as well as various mesh refinement strategies, and apply the software tool to solve various example problems.

Grebow, Daniel J.↗
NASA NTRSDate not supplied

Reference Command Optimization for the Transition Flight Mode of a Lift plus Cruise Vehicle

Advanced air mobility mainly utilizes vehicles that are capable of vertical takeoff and landing (VTOL) for the simplicity of operation and large-scale deployment. However, VTOL vehicles need specialized trajectory and command design for the transition phase, where the vehicles transition between rotor-borne flight and wing-borne flight. Since VTOL vehicles are commonly designed as over-actuated systems for redundancy, one challenge that arises is actuator ambiguity, where it is unclear how to uniquely command actuators for the VTOL vehicle to track a given trajectory. We propose a method to design optimal reference commands for the transition mode. By formulating an 𝑙 1 -norm cost function on the rotor thrusts of the vehicle, we can achieve economical operation of the rotors such that they only operate when necessary and efficiently utilize the aerodynamics to save energy from reduced rotor actuation. We validate our approach in simulations and show its benefit compared to the commonly used differential flatness-based method.

John L Bullock↗
NASA NTRS2010

Particle Swarm Optimization Toolbox

The Particle Swarm Optimization Toolbox is a library of evolutionary optimization tools developed in the MATLAB environment. The algorithms contained in the library include a genetic algorithm (GA), a single-objective particle swarm optimizer (SOPSO), and a multi-objective particle swarm optimizer (MOPSO). Development focused on both the SOPSO and MOPSO. A GA was included mainly for comparison purposes, and the particle swarm optimizers appeared to perform better for a wide variety of optimization problems. All algorithms are capable of performing unconstrained and constrained optimization. The particle swarm optimizers are capable of performing single and multi-objective optimization. The SOPSO and MOPSO algorithms are based on swarming theory and bird-flocking patterns to search the trade space for the optimal solution or optimal trade in competing objectives. The MOPSO generates Pareto fronts for objectives that are in competition. A GA, based on Darwin evolutionary theory, is also included in the library. The GA consists of individuals that form a population in the design space. The population mates to form offspring at new locations in the design space. These offspring contain traits from both of the parents. The algorithm is based on this combination of traits from parents to hopefully provide an improved solution than either of the original parents. As the algorithm progresses, individuals that hold these optimal traits will emerge as the optimal solutions. Due to the generic design of all optimization algorithms, each algorithm interfaces with a user-supplied objective function. This function serves as a "black-box" to the optimizers in which the only purpose of this function is to evaluate solutions provided by the optimizers. Hence, the user-supplied function can be numerical simulations, analytical functions, etc., since the specific detail of this function is of no concern to the optimizer. These algorithms were originally developed to support entry trajectory and guidance design for the Mars Science Laboratory mission but may be applied to any optimization problem.

Grant, Michael J.↗
NASA NTRS2011

Fuel-Efficient Descent and Landing Guidance Logic for a Safe Lunar Touchdown

The landing of a crewed lunar lander on the surface of the Moon will be the climax of any Moon mission. At touchdown, the landing mechanism must absorb the load imparted on the lander due to the vertical component of the lander's touchdown velocity. Also, a large horizontal velocity must be avoided because it could cause the lander to tip over, risking the life of the crew. To be conservative, the worst-case lander's touchdown velocity is always assumed in designing the landing mechanism, making it very heavy. Fuel-optimal guidance algorithms for soft planetary landing have been studied extensively. In most of these studies, the lander is constrained to touchdown with zero velocity. With bounds imposed on the magnitude of the engine thrust, the optimal control solutions typically have a "bang-bang" thrust profile: the thrust magnitude "bangs" instantaneously between its maximum and minimum magnitudes. But the descent engine might not be able to throttle between its extremes instantaneously. There is also a concern about the acceptability of "bang-bang" control to the crew. In our study, the optimal control of a lander is formulated with a cost function that penalizes both the touchdown velocity and the fuel cost of the descent engine. In this formulation, there is not a requirement to achieve a zero touchdown velocity. Only a touchdown velocity that is consistent with the capability of the landing gear design is required. Also, since the nominal throttle level for the terminal descent sub-phase is well below the peak engine thrust, no bound on the engine thrust is used in our formulated problem. Instead of bangbang type solution, the optimal thrust generated is a continuous function of time. With this formulation, we can easily derive analytical expressions for the optimal thrust vector, touchdown velocity components, and other system variables. These expressions provide insights into the "physics" of the optimal landing and terminal descent maneuver. These insights could help engineers to achieve a better "balance" between the conflicting needs of achieving a safe touchdown velocity, a low-weight landing mechanism, low engine fuel cost, and other design goals. In comparing the computed optimal control results with the preflight landing trajectory design of the Apollo-11 mission, we noted interesting similarities between the two missions.

guidance logic↗
NASA NTRS1995

Comparison of Two Multidisciplinary Optimization Strategies for Launch-Vehicle Design

The investigation focuses on development of a rapid multidisciplinary analysis and optimization capability for launch-vehicle design. Two multidisciplinary optimization strategies in which the analyses are integrated in different manners are implemented and evaluated for solution of a single-stage-to-orbit launch-vehicle design problem. Weights and sizing, propulsion, and trajectory issues are directly addressed in each optimization process. Additionally, the need to maintain a consistent vehicle model across the disciplines is discussed. Both solution strategies were shown to obtain similar solutions from two different starting points. These solutions suggests that a dual-fuel, single-stage-to-orbit vehicle with a dry weight of approximately 1.927 x 10(exp 5)lb, gross liftoff weight of 2.165 x 10(exp 6)lb, and length of 181 ft is attainable. A comparison of the two approaches demonstrates that treatment or disciplinary coupling has a direct effect on optimization convergence and the required computational effort. In comparison with the first solution strategy, which is of the general form typically used within the launch vehicle design community at present, the second optimization approach is shown to he 3-4 times more computationally efficient.

Braun, R. D.↗
NASA NTRS2021

OSIRIS-REx Extended Mission Trajectory Design & Target Search

After jettisoning its Sample Return Capsule (SRC) containing regolith samples from the near-Earth asteroid (101955) Bennu to Earth in September 2023, the Origins, Spectral Interpretation, Resource Identification, and Security–Regolith Explorer (OSIRIS-REx) spacecraft will perform a divert maneuver and safely fly by Earth at an altitude of 250 km. SRC return and the divert maneuver officially mark the completion of the spacecraft’s primary mission; however, it will continue on in heliocentric orbit with a nearly fully-functional instrument suite and enough propellant for nearly 600 m/s Delta-V. The post-Earth flyby trajectory fortuitously enables an exciting extended mission opportunity: rendezvous with the near-Earth asteroid (99942)Apophis immediately following its historic Earth close approach in April 2029. In this paper, we detail the discovery, optimization, and analysis of the Apophis rendezvous trajectory for an extended OSIRIS-REx mission. We also present the technical approach for an alternate target search and corresponding results, assessing the alternate trajectories compared to the baseline Apophis rendezvous from a trajectory design standpoint.

Brian Sutter↗
DOE OSTI2023

Implementation of a feature selection algorithm in FARM to identify important state variables and time-invariant matrices

The FARM (Feasible Actuator Range Modifier) software module is a component of the RAVEN-based FORCE framework for analysis of Integrated Energy Systems (IES). FARM aids the HERON software module in the evaluation of the optimal dispatch for the different IES components. Set-point trajectories are required to meet limits on both production variables (i.e., the variables to be optimized such as the electrical power, the hydrogen production rate, etc.) and process variables tied to the service life of equipment (e.g., steam flowrate, vessel pressure, turbine firing temperature, etc.). To evaluate the feasibility of HERON generated set-points and to do so in an acceptable time, FARM employs reduced order models to represent the dynamic behavior of the systems to be dispatched. These surrogate models take the form of a linear dynamic system with sets of Linear Parameter Varying (LPV) matrices that are mapped to the system operating space. These matrices are derived from the trajectories of system state variables and system output variables during transients. The accuracy of LPV matrices depends on the selection of state variables. In previous reports, state variables were selected by adopting a complicated workflow requiring multiple software licenses and an advanced level of user expertise. In this report, a new workflow that automates the state variable selection process is presented. It significantly reduces the frequency of user interventions and does not require multiple software licenses. Each module in the new workflow is described in detail, and the input / output examples in each step of the workflow are provided. It was demonstrated that this workflow can greatly reduce the complexity of the state variable selection process, and that the updated FARM-Gamma and FARM-Delta validators can benefit from this workflow when solving the power dispatch problem of a representative IES test case. Finally, some code improvements that can further enhance the efficiency are suggested.

42 ENGINEERING↗
NASA NTRS2015

Multi-Objective Hybrid Optimal Control for Interplanetary Mission Planning

Preliminary design of low-thrust interplanetary missions is a highly complex process. The mission designer must choose discrete parameters such as the number of flybys, the bodies at which those flybys are performed and in some cases the final destination. In addition, a time-history of control variables must be chosen which defines the trajectory. There are often many thousands, if not millions, of possible trajectories to be evaluated. The customer who commissions a trajectory design is not usually interested in a point solution, but rather the exploration of the trade space of trajectories between several different objective functions. This can be a very expensive process in terms of the number of human analyst hours required. An automated approach is therefore very diserable. This work presents such as an approach by posing the mission design problem as a multi-objective hybrid optimal control problem. The method is demonstrated on a hypothetical mission to the main asteroid belt.

Optimization↗
DOE OSTI2017

Optimisation of dynamic reactive power sources using mesh adaptive direct search

Dynamic reactive power sources can be used to effectively mitigate the fault-induced delayed voltage recovery and transient voltage instability issues. When many var sources need to be installed at planned locations, optimisation of their sizes is a complicated non-linear optimisation problem due to its non-convexity and the dependence of the constraint on time-series trajectories of post-fault voltages. Solving this optimal sizing problem needs to utilise both a non-linear optimisation solver and a power system differential-algebraic equation solver. This study proposes a new approach for solving this problem under both a single contingency and multiple contingencies by using the mesh adaptive direct search algorithm interfaced with a power system simulator. The proposed approach is validated by case studies on a North American Eastern Interconnection model to optimise the sizes of planned STATCOMs against critical contingencies.

Huang, Weihong↗
DOE OSTI2025

High order interpolation of magnetic fields with vector potential reconstruction for particle simulations

We propose a method for interpolating divergence-free continuous magnetic fields via vector potential reconstruction using Hermite interpolation, which ensures high-order continuity for applications requiring adaptive, high-order ordinary differential equation (ODE) integrators, such as the Dormand-Prince method. The method provides C(m) continuity and achieves high-order accuracy, making it particularly suited for particle trajectory integration and Poincaré section analysis under optimal integration order and timestep adjustments. Through numerical experiments, we demonstrate that the Hermite interpolation method preserves volume and continuity, which are critical for conserving toroidal canonical momentum and magnetic moment in guiding center simulations, especially over long-term trajectory integration. Furthermore, we analyze the impact of insufficient derivative continuity on Runge-Kutta schemes and show how it degrades accuracy at low error tolerances, introducing discontinuity-induced truncation errors. Lastly, we demonstrate performant Poincaré section analysis in two relevant settings of field data collocated from finite element meshes.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Continuous Emulation and Multiscale Visualization of Traffic Flow Using Stationary Roadside Sensor Data

With the advent of the next-generation traffic monitoring systems, there has been a significant increase in the spatial-temporal resolution of vehicle mobility data in many cities. Effective analysis and visualization of such data can provide transportation planners with data-driven insights, which can facilitate the understanding of multiscale traffic dynamics. In this paper, we present a web-based traffic emulator for emulating and visualizing near-real-time and historical traffic flows on highways using data from road-side sensors. To construct a continuous traffic flow, the emulator adopts an analytical pipeline that can (a) integrate traffic data collected from discrete road-side radar detection sensors, (b) interpolate traffic conditions (vehicle speed and volume) on unmeasured road segments based on traffic flow theory, and (c) generate lane-specific vehicle trajectories and movements using a mathematically optimized representation of the road network. Our app also provides an integrated visual workflow that allows users to explore the interconnected traffic dynamics using an appropriate traffic flow visualization selected based on the level of detail. We devise two innovative geo-visualization techniques that utilize an animated strips-network representation and a lane usage matrix to visualize lane performances. To ensure a smooth emulation of large-scale traffic flow in an easy-to-access web environment, we implement the emulator using client-side GPU-accelerated techniques. Lastly, we close with a case study that visualizes traffic dynamics of two scenarios - an afternoon peak hour and a traffic accident - in Chattanooga, Tennessee. Our app visualizes the responses of traffic dynamics during different traffic conditions, and to the presence of the traffic accident at different spatial scales.

42 ENGINEERING↗