Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “DESCENT TRAJECTORY”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
NASA NTRS1986

Optimal landing of a helicopter in autorotation

The landing of a helicopter in autorotation is formulated as a nonlinear optimal control problem. A unique feature in the present formulation is the addition of path inequality constraints on both the control and the state vectors. The control variable inequality constraint is a reflection of the limitation on the rotor thrust coefficient. The state-variable inequality constraint is an upper bound on the vertical sink-rate of the helicopter during descent. Optimal trajectories are calculated for entry conditions well within the height-velocity (H-V) restriction curve, with the helicopter initially in hover or in forward flight. The optimal solutions exhibited control techniques similar to those used by helicopter pilots in actual autorotational landings. The study indicates that, subject to pilot acceptability, a substantial reduction could be made in the H-V restriction zone using optimal control techniques.

Lee, A. Y.↗
NASA NTRS2011

Adaptation of G-TAG Software for Validating Touch-and-Go Comet Surface Sampling Design Methodology

The G-TAG software tool was developed under the R&TD on Integrated Autonomous Guidance, Navigation, and Control for Comet Sample Return, and represents a novel, multi-body dynamics simulation software tool for studying TAG sampling. The G-TAG multi-body simulation tool provides a simulation environment in which a Touch-and-Go (TAG) sampling event can be extensively tested. TAG sampling requires the spacecraft to descend to the surface, contact the surface with a sampling collection device, and then to ascend to a safe altitude. The TAG event lasts only a few seconds but is mission-critical with potentially high risk. Consequently, there is a need for the TAG event to be well characterized and studied by simulation and analysis in order for the proposal teams to converge on a reliable spacecraft design. This adaptation of the G-TAG tool was developed to support the Comet Odyssey proposal effort, and is specifically focused to address comet sample return missions. In this application, the spacecraft descends to and samples from the surface of a comet. Performance of the spacecraft during TAG is assessed based on survivability and sample collection performance. For the adaptation of the G-TAG simulation tool to comet scenarios, models are developed that accurately describe the properties of the spacecraft, approach trajectories, and descent velocities, as well as the models of the external forces and torques acting on the spacecraft. The adapted models of the spacecraft, descent profiles, and external sampling forces/torques were more sophisticated and customized for comets than those available in the basic G-TAG simulation tool. Scenarios implemented include the study of variations in requirements, spacecraft design (size, locations, etc. of the spacecraft components), and the environment (surface properties, slope, disturbances, etc.). The simulations, along with their visual representations using G-View, contributed to the Comet Odyssey New Frontiers proposal effort by indicating problems and/or benefits of different approaches and designs.

Mandic, Milan↗
NASA NTRS2014

Trajectory Prediction Accuracy and Error Sources for Regional Jet Descents: Results of a 2010 Flight Trial at Denver International Airport using SkyWest Revenue Flights - Part II

The Efficient Descent Advisor (EDA) controller automation tool generates trajectory-based speed, path, and altitude-profile advisories to facilitate efficient, continuous descents into congested terminal airspace. While prior field trials have assessed the trajectory prediction accuracy for large jet (i.e., Boeing and Airbus) types, smaller (i.e., regional and business) jet types present unique challenges involving different descent procedures and Flight Management System (FMS) capabilities. This paper quantifies the trajectory prediction accuracy for small jet revenue flight descents based on SkyWest Canadair Regional Jet 200, 700, and 900 aircraft arrivals to Denver in the fall of 2010. Post flight test data analysis and SkyWest pilot interviews uncovered unexpected variation between flight crews due to different interpretations of (1) which fixed flight path angle (FPA) to fly based on the flight trial procedure and (2) how to fly the descent to achieve the target FPA. Pilot reports were used to select a subset of flights where pilots indicated an FPA according to the flight trial procedure to remove the unexpected variation due to (1) to focus on (2). Results for the subset for en-route descents, from prior to top of descent to the meter fix 30 to 130 nmi downstream, indicate that aircraft arrived to the meter fix six seconds early with about a twelve second standard deviation. Large FPA errors up to one degree relative to the EDA flight trial procedure were detected after the flight trial as a characteristic of the unexpected variation. It is recommended that quantitative validation be performed during future flight trials so that experimental procedures can be adjusted if unexpected results are detected.

Field Test Results↗
NASA NTRS2014

Trajectory Prediction Accuracy and Error Sources for Regional Jet Descents: Results of a 2010 Flight Trial at Denver International Airport using a Global 5000 Test Aircraft - Part I

The Efficient Descent Advisor (EDA) controller automation tool generates trajectory-based speed, path, and altitude-profile advisories to facilitate efficient, continuous descents into congested terminal airspace. While prior field trials have assessed the trajectory-prediction accuracy for large jet (i.e., Boeing and Airbus) types, smaller (i.e., regional and business) jet types present unique challenges involving different descent procedures and Flight Management System (FMS) capabilities. A small-jet field trial was conducted at Denver in the fall of 2010 with the objective of measuring trajectory prediction accuracy and quantifying the primary sources of error. This paper uses data collected onboard a Bombardier Global 5000 test aircraft to quantify the size and sources of trajectory prediction error. Error sources were quantified for the 44 runs by incrementally replacing predicted data with data collected onboard the aircraft and measuring the effect on time error. Results for en-route descents, from prior to top of descent to the meter fix 60-120 nmi downstream, indicate that the aircraft arrived an average 15 seconds earlier than predicted, with a standard deviation of 10 seconds. Target Mach and CAS deceleration were found to be the two largest error sources. If CAS deceleration error was reduced using a typical, more predictable level flight deceleration then the arrival time prediction error in 2010 would be on par with a 2009 flight trial of Airbus and Boeing revenue flights. Four of the error sources, tracker jumps, CAS deceleration, target Mach, and path distance, lend themselves to significant reductions with modest to no changes to ATC automation andor procedures. Wind error and its impact on arrival time error was significantly reduced in 2010 compared to a 1994 flight test using NASAs Boeing 737 test aircraft.

Trajectory Prediction Error↗
NASA NTRS2005

Entry Abort Determination Using Non-Adaptive Neural Networks for Mars Precision Landers

The 2009 Mars Science Laboratory (MSL) will attempt the first precision landing on Mars using a modified version of the Apollo Earth entry guidance program. The guidance routine, Entry Terminal Point Controller (ETPC), commands the deployment of a supersonic parachute after converging the range to the landing target. For very dispersed cases, ETPC may not converge the range to the target and safely command parachute deployment within Mach number and dynamic pressure constraints. A full-lift up abort can save 85% of these failed trajectories while abandoning the precision landing objective. Though current MSL requirements do not call for an abort capability, an autonomous abort capability may be desired, for this mission or future Mars precision landers, to make the vehicle more robust. The application of artificial neural networks (NNs) as an abort determination technique was evaluated by personnel at the National Aeronautics and Space Administration (NASA) Johnson Space Center (JSC). In order to implement an abort, a failed trajectory needs to be recognized in real time. Abort determination is dependent upon several trajectory parameters whose relationships to vehicle survival are not well understood, and yet the lander must be trained to recognize unsafe situations. Artificial neural networks (NNs) provide a way to model these parameters and can provide MSL with the artificial intelligence necessary to independently declare an abort. Using the 2009 Mars Science Laboratory (MSL) mission as a case study, a non-adaptive NN was designed, trained and tested using Monte Carlo simulations of MSL descent and incorporated into ETPC. Neural network theory, the development history of the MSL NN, and initial testing with severe dust storm entry trajectory cases are discussed in Reference 1 and will not be repeated here. That analysis demonstrated that NNs are capable of recognizing failed descent trajectories and can significantly increase the survivability of MSL for very dispersed cases. NN testing was then broadened to evaluate fully dispersed entry trajectories. The NN correctly classified 99.7% of descent trajectories as abort or nonabort and reduced the probability of an unsafe parachute deployment by 83%. This second, broader testing phase is discussed in this paper.

Graybeal, Sarah R.↗
NASA NTRS2016

An Inertial Dual-State State Estimator for Precision Planetary Landing with Hazard Detection and Avoidance

The navigation filter architecture successfully deployed on the Morpheus flight vehicle is presented. The filter was developed as a key element of the NASA Autonomous Landing and Hazard Avoidance Technology (ALHAT) project and over the course of 15 free fights was integrated into the Morpheus vehicle, operations, and flight control loop. Flight testing completed by demonstrating autonomous hazard detection and avoidance, integration of an altimeter, surface relative velocity (velocimeter) and hazard relative navigation (HRN) measurements into the onboard dual-state inertial estimator Kalman flter software, and landing within 2 meters of the vertical testbed GPS-based navigation solution at the safe landing site target. Morpheus followed a trajectory that included an ascent phase followed by a partial descent-to-landing, although the proposed filter architecture is applicable to more general planetary precision entry, descent, and landings. The main new contribution is the incorporation of a sophisticated hazard relative navigation sensor-originally intended to locate safe landing sites-into the navigation system and employed as a navigation sensor. The formulation of a dual-state inertial extended Kalman filter was designed to address the precision planetary landing problem when viewed as a rendezvous problem with an intended landing site. For the required precision navigation system that is capable of navigating along a descent-to-landing trajectory to a precise landing, the impact of attitude errors on the translational state estimation are included in a fully integrated navigation structure in which translation state estimation is combined with attitude state estimation. The map tie errors are estimated as part of the process, thereby creating a dual-state filter implementation. Also, the filter is implemented using inertial states rather than states relative to the target. External measurements include altimeter, velocimeter, star camera, terrain relative navigation sensor, and a hazard relative navigation sensor providing information regarding hazards on a map generated on-the-fly.

Bishop, Robert H.↗
NASA NTRS2024

End-to-End Mission Design & Trajectory Optimization

Need: A need exists for a generalized, robust, user-friendly and accessible end-to-end mission design optimization tool. Solution: Our solution to developing this capability was to interface two JSC tools—Copernicus and Genesis. Each of these tools has a specific area of the mission design process that it excels at. By utilizing them both, we can gain performance benefits not seen by either on their own. - Copernicus is a trajectory design and optimization software used for in-space trajectories around multiple bodies. - Genesis is a flight mechanics tool used to model ascent, entry, descent, and landing trajectories around a single planetary body. Year 1 was focused on combining these 2 software packages—allowing Copernicus to incorporate the ascent/descent capabilities of Genesis into the optimization problem—and developing this end-to-end mission design capability. Year 2 we focused on increasing the robustness of this capability by building the initial guess generator (IGG), which produces initial guesses based on simplifying assumptions and the physics of the problem. Year 3 of our project focused on utilizing the end-to-end mission design and optimization capabilities developed in the previous 2 years to analyze specific mission scenarios—scaling up from proof of concept to real analyses—capturing any resulting performance benefits, as well as addressing the Big Data challenges we’re faced with—namely, how we’re going to manage and interpret all the data that’s generated.

Kristin Nichols↗
NASA NTRS1975

Optimum flight profiles for short haul missions

An algorithm, based on the energy-state method, is derived for calculating optimum trajectories with a range constraint. The basis of the algorithm is the assumption that optimum trajectories consist of, at most, three segments: an increasing energy segment (climb); a constant energy segment (cruise); and a decreasing energy segment (descent). The algorithm is used to compute minimum fuel, minimum time, and minimum direct-operating-cost trajectories, with range as a parameter, for an in-service CTOL aircraft and for an advanced STOL aircraft. Use of a simplified trajectory increases the fuel consumption of the total descent trajectory by about 10 percent and the time to fly the descent by about 19 percent compared to the optimum.

Erzberger, H.↗
NASA NTRSDate not supplied

Propulsive Trajectory Optimization to Minimize Surface Contamination

Descent retroburns using hydrazine thrusters will generate contaminants in their exhaust that can alter underlying samples, such as water-rich surfaces coinciding with possible life signatures or other science measurements of interest. We present an optimization technique that aims to autonomously minimize contamination during surface approach and landing for propulsive vehicles. In addition to short-range hoppers, the optimization technique is also fully applicable to traditional orbit-to-surface landers. This study addresses scenarios where surface alterations from propulsion events are counterproductive or hazardous to the mission objectives. This is of interest for landers (whether human or robotic), that may rely on pristine soils collected in the immediate vicinity of landing sites to accomplish science investigations, mining, or In Situ Resource Utilization (ISRU) surface operations. Such missions are averse to various surface-plume interactions such as thermal scoring, physical agitation, and contamination. The capability can be applied with minimal impact to the baseline concept.

Plume↗
NASA NTRS2013

2011 Mars Science Laboratory Trajectory Reconstruction and Performance from Launch Through Landing

The Mars Science Laboratory (MSL) mission successfully launched on an Atlas V 541 Expendable Evolved Launch Vehicle (EELV) from the Eastern Test Range (ETR) at Cape Canaveral Air Force Station (CCAFS) in Florida at 15:02:00 UTC on November 26th, 2011. At 15:52:06 UTC, six minutes after the MSL spacecraft separated from the Centaur upper stage, the spacecraft transmitter was turned on and in less than 20 s spacecraft carrier lock was achieved at the Universal Space Network (USN) Dongara tracking station located in Western Australia. MSL, carrying the most sophisticated rover ever sent to Mars, entered the Martian atmosphere at 05:10:46 SpaceCraft Event Time (SCET) UTC, and landed inside Gale Crater at 05:17:57 SCET UTC on August 6th, 2012. Confirmation of nominal landing was received at the Deep Space Network (DSN) Canberra tracking station via the Mars Odyssey relay spacecraft at 05:31:45 Earth Received Time (ERT) UTC. This paper summarizes in detail the actual vs. predicted trajectory performance in terms of launch vehicle events, launch vehicle injection performance, actual DSN/USN spacecraft lockup, trajectory correction maneuver performance, Entry, Descent, and Landing events, and overall trajectory and geometry characteristics.

trajectory↗
NASA NTRS2021

Mars 2020 Perseverance trajectory reconstruction and performance from launch through landing

The Mars 2020 (M2020) Mission carrying Perseverance, the most advanced rover ever sent to Mars, successfully launched on an Atlas V 541 (AV-088) launch vehicle from the Eastern Test Range (ETR) at Cape Canaveral Air Force Station (CCAFS) in Florida at 11:50:00 UTC (T-Zero time) on July 30, 2020. After some station reconfiguration, carrier/telemetry were locked at both Deep Space Network (DSN) Canberra and Goldstone stations. Perseverance entered the Martian atmosphere at 20:36:50 Spacecraft Event Time (SCET) UTC, and landed inside Jezero Crater at 20:43:49 SCET UTC on February 18, 2021. Confirmation of nominal landing was received at the DSN Goldstone and Madrid tracking stations via the Mars Reconnaissance Orbiter at 20:55:11 Earth Received Time (ERT) UTC. This paper summarizes in detail the actual vs. predicted performance in terms of launch vehicle events, launch vehicle injection performance, actual DSN spacecraft lockup, trajectory correction maneuver performance, Entry, Descent, and Landing events, and overall trajectory and geometric characteristics.

Abilleira, Fernando↗