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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 361 records · Page 20
All sourcesNASA NTRSDOE OSTI
NASA NTRS1971

Dynamic upper atmospheric force model on stabilized vehicles for a high-precision trajectory computer program

The upper atmosphere model draws heavily on the behavior of the earth's upper atmosphere which exhibits cyclic as well as irregular variations in density profile, temperature, pressure, and composition in unison with solar activities as deduced from the more recent land-based and satellite observations. The lift and drag model is designed specifically for inertially stabilized vehicles of the Mariner class, with possible extension to gravity gradient stabilized vehicles of the GEOS class. The model considers operation in the free molecular flow regimes with large Knudsen numbers. The vehicle is considered a composite structure with basic components having well-defined shapes, each with its own surface characteristics in terms of temperature, reflectivity, and accommodation of free stream molecules. The model takes into account both the calculation of precise aerodynamic force coefficients in terms of expansion of modified Bessel functions in speed ratios and angle of attack, and approximate force coefficients when the speed ratios approach infinity. Other considerations include specular and diffused reflectivity, shielding, and shadow effects.

Khatib, A. R.↗
DOE OSTI2020

Deep Learning-Based Queue-Aware Eco-Approach and Departure System for Plug-In Hybrid Electric Buses at Signalized Intersections: A Simulation Study

Eco-Approach and Departure (EAD) has been considered as a promising eco-driving strategy for vehicles traveling in an urban environment, where information such as signal phase and timing (SPaT) and geometric intersection description is well utilized to guide vehicles passing through intersections in the most energy-efficient manner. Previous studies formulated the optimal trajectory planning problem as finding the shortest path on a graphical model. While this method is effective in terms of energy saving, its computation efficiency can be further enhanced by adopting machine learning techniques. In this paper, we propose an innovative deep learning-based queue-aware eco-approach and departure (DLQ-EAD) system for a plug-in hybrid electric bus (PHEB), which is able to provide an online optimal trajectory for the vehicle considering both the downstream traffic condition (i.e. traffic lights, queues) and the vehicle powertrain efficiency. Based on optimal solutions obtained from the graph-based trajectory planning algorithm (GTPA), a deep neural network (DNN) is developed to learn the optimal vehicle speed for the next time step given its current state. It is demonstrated that the trained DNN can provide energy-efficient trajectories with high computational efficiency and high flexibility adopting to dynamic changes in the surrounding environment. To address the impact of downstream traffic, a queue prediction model is further developed using data from radars and connected vehicles (CVs), as well as signal timing data from SPaT messages. A comprehensive simulation study in the microscopic traffic modeling software PTV VISSIM shows that the proposed DLQ-EAD can achieve 18.7%-24.0% energy efficiency improvements for a single PHEB on various traffic congestion levels. The proposed queue prediction model can be of practical significance even at low penetration rates of CVs. Specifically, additional energy savings of 2.0%-8.2% can be further achieved with 20% vehicles in the network.

Ye, Fei↗
NASA NTRSDate not supplied

Path Planning: Differential Dynamic Programming and Model Predictive Path Integral Control on VTOL Aircraft

This paper explores two optimal control approaches, widely used in robotics, to establish their viability as real-time trajectory planners for vehicle configurations envisioned for the emerging aviation sector of Urban Air Mobility (UAM). Differential Dynamic Programming (DDP) enables planning over highly nonlinear dynamics using second-order approximations along a nominal trajectory, and displays quadratic convergence to a local solution. Model Predictive Path Integral (MPPI) is a stochastic sampling-based algorithm that can optimize for general cost criteria, including potentially highly nonlinear formulations, and supports parallel computation through the use of modern GPU hardware. In this work, DDP and MPPI were implemented using model predictive control (MPC), and the results indicate they are able to successfully transition the aircraft over different flight envelopes and generate trajectories unique to UAM vehicles.

Differential Dynamic Programming↗
NASA NTRS2007

Preliminary Performance Analyses of the Constellation Program ARES 1 Crew Launch Vehicle

By the time NASA's Exploration Systems Architecture Study (ESAS) report had been released to the public in December 2005, engineers at NASA's Marshall Space Flight Center had already initiated the first of a series of detailed design analysis cycles (DACs) for the Constellation Program Crew Launch Vehicle (CLV), which has been given the name Ares I. As a major component of the Constellation Architecture, the CLV's initial role will be to deliver crew and cargo aboard the newly conceived Crew Exploration Vehicle (CEV) to a staging orbit for eventual rendezvous with the International Space Station (ISS). However, the long-term goal and design focus of the CLV will be to provide launch services for a crewed CEV in support of lunar exploration missions. Key to the success of the CLV design effort and an integral part of each DAC is a detailed performance analysis tailored to assess nominal and dispersed performance of the vehicle, to determine performance sensitivities, and to generate design-driving dispersed trajectories. Results of these analyses provide valuable design information to the program for the current design as well as provide feedback to engineers on how to adjust the current design in order to maintain program goals. This paper presents a condensed subset of the CLV performance analyses performed during the CLV DAC-1 cycle. Deterministic studies include development of the CLV DAC-1 reference trajectories, identification of vehicle stage impact footprints, an assessment of launch window impacts to payload performance, and the computation of select CLV payload partials. Dispersion studies include definition of input uncertainties, Monte Carlo analysis of trajectory performance parameters based on input dispersions, assessment of CLV flight performance reserve (FPR), assessment of orbital insertion accuracy, and an assessment of bending load indicators due to dispersions in vehicle angle of attack and side slip angle. A short discussion of the various customers for the dispersion results, along with results and ramifications of each study, are also provided.

Phillips, Mark↗
NASA NTRS1993

Optimal RTLS abort trajectories for an HL-20 personnel launch vehicle

The primary objective of this study was to determine whether Return To Launch Site (RTLS) abort at T seconds along the launch trajectory of the Personnel Launch System (PLS) is possible using optimal control theory. The secondary objective is to assess effects of bank angle constraint, lift coefficient constraint, free and fixed final boundary conditions, etc. of the vehicle. The PLS is a complementary system to the Space Shuttle.

Dutton, Kevin↗
NASA NTRS1993

GRYPHON: Air launched space booster

The project chosen for the winter semester Aero 483 class was the design of a next generation Air Launched Space Booster. Based on Orbital Sciences Corporation's Pegasus concept, the goal of Aero 483 was to design a 500,000 pound air launched space booster capable of delivering 17,000 pounds of payload to Low Earth Orbit and 8,000 pounds of payload to Geosynchronous Earth Orbit. The resulting launch vehicle was named the Gryphon. The class of forty senior aerospace engineering students was broken down into eight interdependent groups. Each group was assigned a subsystem or responsibility which then became their field of specialization. Spacecraft Integration was responsible for ensuring compatibility between subsystems. This group kept up to date on subsystem redesigns and informed those parties affected by the changes, monitored the vehicle's overall weight and dimensions, and calculated the mass properties of the booster. This group also performed the cost/profitability analysis of the Gryphon and obtained cost data for competing launch systems. The Mission Analysis Group was assigned the task of determining proper orbits, calculating the vehicle's flight trajectory for those orbits, and determining the aerodynamic characteristics of the vehicle. The Propulsion Group chose the engines that were best suited to the mission. This group also set the staging configurations for those engines and designed the tanks and fuel feed system. The commercial satellite market, dimensions and weights of typical satellites, and method of deploying satellites was determined by the Payloads Group. In addition, Payloads identified possible resupply packages for Space Station Freedom and identified those packages that were compatible with the Gryphon. The guidance, navigation, and control subsystems were designed by the Mission Control Group. This group identified required tracking hardware, communications hardware telemetry systems, and ground sites for the location of the Gryphon's mission control center. The Structures group was responsible for ensuring the structural integrity of the vehicle. Their designs included the payload shroud, payload support structure, exterior hull and engine support struts. The Gryphon's power requirements were determined by the Power/Thermal/Attitude Control Group. This group then selected suitable batteries and other components to meet these requirements. The group also designed heat shielding and cooling systems to ensure subsystem performance. In addition to these responsibilities this group designed the attitude control methods and RCS components for the vehicle. The Aircraft Integration Group was responsible for all aspects of the booster aircraft connection. This included the design of the connection structure and the drop mechanism. This group also designed the vehicle assembly facility and identified possible ground bases for the plane.

Source record↗
NASA NTRS1991

Trajectory optimization and guidance for a hypersonic vehicle

The optimal ascent problem for a hypersonic vehicle is formulated as an inverse dynamic problem. This formulation is essential in solving the trajectory optimization problem via the nonlinear programming approach. Both minimum-fuel and minimax type of performance indices are considered. The results reveal important features of the optimal trajectory and controls, and they are subsequently used to construct a nonlinear feedback midcourse control law. This control law not only greatly simplifies the difficult constrained optimization problem and yields improved solutions, but is also suitable for onboard implementation. Finally, off-nominal trajectory guidance is addressed using combination of feedback compensation and onboard generation of control through the inverse dynamics approach.

Lu, Ping↗
NASA NTRS1974

Multivariant function model generation

The development of computer programs applicable to space vehicle guidance was conducted. The subjects discussed are as follows: (1) determination of optimum reentry trajectories, (2) development of equations for performance of trajectory computation, (3) vehicle control for fuel optimization, (4) development of equations for performance trajectory computations, (5) applications and solution of Hamilton-Jacobi equation, and (6) stresses in dome shaped shells with discontinuities at the apex.

Source record↗
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 NTRS1965

A maximum principle re-entry study

Mathematical model of maximum principle of Pontryagin used to find point-to-point reentry trajectory of space vehicle

REENTRY TRAJECTORY↗
NASA NTRS1981

Experiences in Delta mission planning

The Delta launch vehicle has experienced 153 successful launches since 1960 and 40 more are scheduled. Relying on up-to-date technology and proven flight hardware, the Delta vehicle has been used for low to high circular and geosynchronous transfer orbits, high elliptic probes, and lunar and planetary missions. A history of Delta launches and configuration modifications is presented, noting a 92-95% success rate and its cost effective role in reimbursable missions. Elements of mission planning such as feasibility studies (1-3 yrs), spacecraft restraints manuals, reference trajectories, preliminary mission analysis, detailed test objectives, range/safety studies, guided nominal trajectory, and mission specific studies are discussed. Trajectory shaping determines vehicle and spacecraft restraints, optimizes the trajectory, and maximizes the payload capabilities. Improvements in the Delta vehicle have boosted payloads from 100 to 2890 lbs., improving the price per pound ratio, as costs have risen, only by a factor of three. Current launch schedules extend well into 1985.

Kork, J.↗
NASA NTRS1986

Theory of idealized two-dimensional ballute in Newtonian hypersonic flow

A differential equation governing the geometry of a two-dimensional ballute in hypersonic flow and its constraining boundary conditions are derived under idealized assumptions. By solving these equations, the shape of the ballute is determined over a range of conditions. Lift, drag, pitching moment, and the allowed limit of center-of-gravity location for stability (meta-center) are then calculated using Newtonian hypersonic approximation. It is shown that the meta-center occurs near the forward end because of compliance of the ballute membrane to the shock layer pressures, especially at low free-stream densities. In order for the vehicle employing the ballute to be stable at all densities, the center of gravity must be within approximately the forward 20 percent of overall length of the vehicle. However, typical flight trajectories of an aeroassisted orbital transfer vehicle employing the ballute for aerobraking show that the vehicle may be able to complete its atmospheric flight without tumbling provided that the center of gravity is located within the forward 43 percent of the vehicle length because of the relatively short duration of flight through the destabilizing low-density regime.

Park, C.↗
NASA NTRS2011

Mesh-Based Entry Vehicle and Explosive Debris Re-Contact Probability Modeling

The risk to a crewed vehicle arising from potential re-contact with fragments from an explosive breakup of any jettisoned spacecraft segments during entry has long sought to be quantified. However, great difficulty lies in efficiently capturing the potential locations of each fragment and their collective threat to the vehicle. The method presented in this paper addresses this problem by using a stochastic approach that discretizes simulated debris pieces into volumetric cells, and then assesses strike probabilities accordingly. Combining spatial debris density and relative velocity between the debris and the entry vehicle, the strike probability can be calculated from the integral of the debris flux inside each cell over time. Using this technique it is possible to assess the risk to an entry vehicle along an entire trajectory as it separates from the jettisoned segment. By decoupling the fragment trajectories from that of the entry vehicle, multiple potential separation maneuvers can then be evaluated rapidly to provide an assessment of the best strategy to mitigate the re-contact risk.

McPherson, Mark A.↗
NASA NTRS1991

Spacecraft rendezvous operational considerations affecting vehicle systems design and configuration

One lesson learned from Orbiting Maneuvering Vehicle (OMV) program experience is that Design Reference Missions must include an appropriate balance of operations and performance inputs to effectively drive vehicle systems design and configuration. Rendezvous trajectory design is based on vehicle characteristics (e.g., mass, propellant tank size, and mission duration capability) and operational requirements, which have evolved through the Gemini, Apollo, and STS programs. Operational constraints affecting the rendezvous final approach are summarized. The two major objectives of operational rendezvous design are vehicle/crew safety and mission success. Operational requirements on the final approach which support these objectives include: tracking/targeting/communications; trajectory dispersion and navigation uncertainty handling; contingency protection; favorable sunlight conditions; acceptable relative state for proximity operations handover; and compliance with target vehicle constraints. A discussion of the ways each of these requirements may constrain the rendezvous trajectory follows. Although the constraints discussed apply to all rendezvous, the trajectory presented in 'Cargo Transfer Vehicle Preliminary Reference Definition' (MSFC, May 1991) was used as the basis for the comments below.

Prust, Ellen E.↗