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At least 235 records · Page 13
All sourcesNASA NTRSDOE OSTI
NASA NTRS2016

Optimum Strategies for Selecting Descent Flight-Path Angles

An information processing system and method for adaptively selecting an aircraft descent flight path for an aircraft, are provided. The system receives flight adaptation parameters, including aircraft flight descent time period, aircraft flight descent airspace region, and aircraft flight descent flyability constraints. The system queries a plurality of flight data sources and retrieves flight information including any of winds and temperatures aloft data, airspace/navigation constraints, airspace traffic demand, and airspace arrival delay model. The system calculates a set of candidate descent profiles, each defined by at least one of a flight path angle and a descent rate, and each including an aggregated total fuel consumption value for the aircraft following a calculated trajectory, and a flyability constraints metric for the calculated trajectory. The system selects a best candidate descent profile having the least fuel consumption value while the fly ability constraints metric remains within aircraft flight descent flyability constraints.

Wu, Minghong G.↗
NASA NTRS1970

Apollo 12

Apollo 12 Lunar Module high landing accuracy, discussing control actions, trajectory error sources and power descent

Conrad, C., Jr.↗
NASA NTRS1979

Evaluating and minimizing noise impact due to aircraft flyover

Existing techniques were used to assess the noise impact on a community due to aircraft operation and to optimize the flight paths of an approaching aircraft with respect to the annoyance produced. Major achievements are: (1) the development of a population model suitable for determining the noise impact, (2) generation of a numerical computer code which uses this population model along with the steepest descent algorithm to optimize approach/landing trajectories, (3) implementation of this optimization code in several fictitious cases as well as for the community surrounding Patrick Henry International Airport, Virginia.

Jacobson, I. D.↗
NASA NTRSDate not supplied

Overview of the Capture, Containment, and Return System (CCRS)

The Mars Sample Return (MSR) campaign is one of the most ambitious and complex planetary exploration missions currently underway. With the participation of NASA, ESA, and a large number of industry partners, MSR aims to bring Martian soil, rock, and atmospheric samples back to Earth, in order to answer key questions about Mars’ biological evolution. To accomplish this goal the campaign relies on four coordinated missions, each fulfilling a fundamental role to bring the samples to Earth. The Mars Perseverance rover, the first of the four missions, landed safely on Mars on February 18, 2021 and has already acquired candidate samples for Earth return. A selection of the samples of Martian soil and atmosphere that Perseverance has captured during its mission will be recovered, launched into Mars orbit, and transported back to Earth. The Sample Fetch Rover and Mars Ascent System, both parts of the Sample Return Lander project, perform the Mars surface missions to retrieve the collected samples and launch them into Mars orbit. NASA’s Capture, Containment, and Return System (CCRS), hosted on ESA’s Earth Return Orbiter (ERO), brings the samples back to Earth from Mars orbit. These retrieval and return missions are currently in the planning and design stages of development. The NASA-provided CCRS is the payload of the ESA ERO and is the focus of this presentation. ERO will enter Mars orbit and provide communication relay to Earth for the other MSR elements. The Sample Return Lander systems will fetch the sample tubes and integrate them into a protective vessel – the Orbiting Sample (OS) system – which is then launched into low Mars orbit. ERO will perform rendezvous maneuvers, allowing its CCRS payload to capture the OS, contain it, and perform the first automated in-space assembly of a spacecraft, the Earth Entry System (EES), while in Mars orbit. ERO will then begin its journey back to Earth, with CCRS and its assembled EES spacecraft. Three days prior to arrival, CCRS will release the EES on an Earth entry trajectory from a distance beyond the orbit of the Moon. The passive EES spacecraft will then enter Earth’s atmosphere, flying on a ballistic trajectory, followed by a terminal descent (without a parachute) and landing at the Utah Test and Training Range (UTTR). This presentation will show the current design of the CCRS system and its concept of operations. ERO and CCRS will perform several firsts in planetary exploration: (a) orbital rendezvous and capture in Mars orbit, (b) in-space sterilization and containment, (c) on-orbit spacecraft assembly at Mars, and (d) fully-passive entry, descent, and landing sequence for sample return.

Carlie H. Zumwalt↗
NASA NTRS1975

Fixed-range optimum trajectories for short-haul aircraft

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). This assumption allows energy to be used as the independent variable in the increasing and decreasing energy segments, thereby eliminating the integration of a separate adjoint differential equation and simplifying the calculus of variations problem to one requiring only pointwise extremization of algebraic functions. 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. For the CTOL aircraft and the minimum-fuel performance function, the optimum controls, consisting of air-speed and engine power setting, are continuous functions of the energy in both climb and descent as well as near the maximum or cruise energy. This is also true for the STOL aircraft except in the descent where at one energy level a nearly constant energy dive segment occurs, yielding a discontinuity in the airspeed at that energy. The reason for this segment appears to be the relatively high fuel flow at idle power of the engines used by this STOL aircraft. Use of a simplified trajectory which eliminates the dive 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 NTRS1972

Performance Analysis and Design Synthesis (PADS) computer program. Volume 3: User manual

The two-fold purpose of the Performance Analysis and Design Synthesis (PADS) computer program is discussed. The program can size launch vehicles in conjunction with calculus-of-variations optimal trajectories and can also be used as a general purpose branched trajectory optimization program. For trajectory optimization alone or with sizing, PADS has two trajectory modules. The first trajectory module uses the method of steepest descent. The second module uses the method of quasi-linearization, which requires a starting solution from the first trajectory module.

Source record↗
NASA NTRS1961

Guidance and Control During Direct-Descent Parabolic Reentry

The results of studies of four reentry guidance and control techniques for the energy management of vehicles returning to the earth at escape speeds are compared in this paper. The reentry trajectories are constrained to those of direct descent, that is, where the vehicle does not leave that portion of the atmosphere where useful aerodynamic forces are available after its initial entry. The guidance techniques compared are: (1) a piloted simulator study reference trajectory techniques; 2) An automatic controller using reference trajectory techniques; 3) A predictor system employing linear prediction (perturbation) techniques; and 4) A repetitive prediction system employing rapid-time computer techniques.

Foudriat, Edwin C.↗
NASA NTRS2024

Flight Mechanics Modeling and Simulation of the Earth Entry System

Introduction: The Mars Sample Return (MSR) Campaign being planned by NASA and ESA has the ambitious goal to return Mars samples back to Earth. This international collaboration had developed a concept of operations that included a ESA-designed Earth Return Orbiter (ERO) and NASA-designed Capture, Containment, and Return System (CCRS). The Earth Entry System (EES), consisting of a protective aeroshell that houses the samples as well as sample containment vessels, would conduct entry, descent, and landing (EDL) on a direct Earth trajectory. The EES would enter on a spin-stabilized ballistic trajectory with the goal to passively achieve aerodynamic stability throughout all regions of flight. The EDL sequence would end with the EES impacting the soft playa soil of the Utah Test and Training Range (UTTR). As of the submission of this abstract, the MSR campaign is undergoing a re-architecture leading to a pause in EES development. However, the novel approaches developed in flight mechanics modeling and simulation can significantly benefit the greater IPPW community in the development of Earth return vehicles. This paper will present the latest state of EES flight mechanics modeling and simulation. The paper will highlight the simulation architecture developed and key lessons learned from understanding of EDL trajectory sensitivities. Modeling and Simulation: Figure 1 provides a high-level concept of operations for the approach, entry, descent, and landing (AEDL) phase of the CCRS-portion of MSR. The objective of EES flight mechanics is to model and simulate the EES trajectory from ERO separation to ground impact at UTTR. A variety of flight mechanics simulation models were utilized to model both exo-atmopsheric and atmospheric portions of flight. 42, a 6-DOF simulation developed at Goddard Space Flight Center, is utilized for propagating the attitude of EES during exo-atmospheric flight. 42 allows for a variety of spin eject mechanism scenarios to be simulated for analysis. 10 minutes prior to entry, the 42 states are handed off to the EDL sims. The prime EDL sim utilized by EES is the Program to Optimize Simulated Trajectories II (POST2), a 6-DOF sim developed at Langley Research Center, and the independent verification and validation EDL sim utilized is DSENDS, a 6-DOF sim developed at Jet Propulsion Laboratory. Figure 2 provides a visualization of the flight mechanics simulation model flow through various points in the AEDL phase. Due to the existence of a variety of sim models, the EES flight mechanics team developed processes for data hand-off. These processes included the development of a centralized coordinate frame document, utilization of a single, centralized simulation input document for all sims to reference, and hand-off files containing both the technical data to be ingested by other flight mechanics sims as well as annotations of modeling assumptions utilized to generate the data. Figure~\ref{fig:post2simarchitecture} provides an overview of the POST2 sim architecture wherein POST2 ingests numerous subsystem models and input files. The dispersed state file generated by MONTE provides the position/velocity state of the trajectory while the 42 Handoff file provides the attitude. The aerodynamics database, delivered by the EES aeroscience team, is utilized to simulate the aerodynamic forces and moments experienced during EDL. A custom atmosphere model, developed by EES atmosphere team, is utilized to simulate the anticipated atmosphere environment around the region of Earth through which the EES trajectory flys. These inputs and subsystem models can be varied depending on the AEDL flight mechanics scenario being simulated. Monte Carlo simulations are utilized to generate statistical AEDL performance metrics in the form of scorecards and violin plots. Furthermore, outputs from the POST2 simulation are utilized for follow-on analyses including aerothermal and landing performance. \section{Flight Mechanics Lessons Learned} Though the EES flight mechanics team uncovered a variety of lessons learned through the analysis conducted to support CCRS through preliminary design review, this paper will highlight the most important lessons. A key AEDL performance goal is to ensure the landing footprint of EES remains on the UTTR south range. A common modeling strategy used in EDL analysis is One-Variable-At-a-Time (OVAT). OVAT analysis provides insight into the key drivers that affect AEDL performance metrics. Figure 3 shows the landing ellipses for single dispersion sources as compared to the baseline aggregate of all dispersions. The figure shows that atmosphere winds alone dominate the size of the footprint ellipse (note: EES does not use a parachute unlike previous Earth-return missions and is in wind-driven free fall for ~5min). The significance of the wind led the EES flight mechanics team to pursue the development of a Custom Atmosphere Model [4], in lieu of EarthGRAM [1], built on actual radiosonde wind measurements around the UTTR-region. This decision was driven by the realism in the generated footprint ellipses and lessons-learned from Stardust [5]. These findings will be invaluable for future Earth-return missions in providing an early understanding of the key drivers affecting footprint size and modeling considerations for which to account. Another lesson learned is tied to the AEDL performance goal of achieving passive stability throughout all regions of flight. It is well understood that blunt-body aeroshells are less stable as they transition from supersonic to subsonic. Eliminating a backshell does help improvestability; however, other phenomena such as roll-induced instability during terminal descent can still arise. The EES flight mechanics team developed stability metrics as tools to better understand the causes of and better predict the onset of dynamic instability. These tools were built upon analytical models developed by Jaffe [3] and Murphy [2]. The tools were shown to both be very accurate in correlation with actual unstable cases and useful in developing stability margin policies based on the vehicle design and simulation considerations (e.g. sphere-cone angle change, mass change, wind turbulence). These tools allowed for the current EES design to demonstrate the ability to achieve passive stability and can be an invaluable tool for consideration in the design of parachute-less Earth-return vehicles.

Rohan Deshmukh↗
NASA NTRS1978

Characteristics of constrained optimum trajectories with specified range

Necessary conditions of optimality are derived for trajectories whose structure is limited to climb, steady cruise, and descent segments. The performance function consists of the sum of fuel and time costs, referred to as direct operating cost (DOC). The state variable is range to go and the independent variable is energy. In this formulation a cruise segment always occurs at the optimum cruise energy for sufficiently large range. At short ranges (500 n. mi. and less) a cruise segment may also occur below the optimum cruise energy. The existence of such a cruise segment depends primarily on the fuel flow vs thrust characteristics and on thrust constraints. If thrust is a free control variable along with airspeed, it is shown that such cruise segments will not generally occur. If thrust is constrained to some maximum value in climb and to some minimum in descent, such cruise segments generally will occur. Computer calculations of typical short-range trajectories obtained about a 1% cost penalty for constraining the thrust.

Erzberger, H.↗
NASA NTRS2018

Development of a Multi-Phase Mission Planning Tool for NASA X-57 Maxwell

The physical design and operation of electric aircraft like NASA Maxwell X-57 are significantly different than conventionally fueled aircraft. Operational optimization will require close coupling of aerodynamics, propulsion, and power. To address the uncertainty of electric aircraft operation, a system level Mission Planning Tool is developed to simulate all aircraft trajectory phases: taxi, motor run-up, takeoff, climb, cruise, and descent. The Mission Planning Tool captures performance parameters at each point of the trajectory including battery state of charge, the temperatures of components in the electrical system, and propulsion system thrust. This work describes the modeling of each mission phase, and compares the results of simulating a user-specified trajectory, and using a collocated optimal control approach to determine an optimal trajectory. The results show that optimization of the mission show a significant increase in the final battery state of charge over the user- specified simulation strategy. These results will inform the operation of the NASA Maxwell X-57 test flights that will take place this year.

Schnulo, Sydney L.↗
NASA NTRS1976

Flight with lift modulation inside a planetary atmosphere

A set of dimensionless variables (modified Chapman's variables) is introduced in a derivation of general equations for lifting flight and bank modulation within a planetary atmosphere. The atmosphere is assumed spherical and at rest, and a generalized lift-drag polar is also introduced. Corresponding equations for flight over a flat planet model are attained via a straightforward transformation. Two planar flight cases: flight at constant absolute speed over a spherical planet, and flight at constant descent rate over a flat planet, are analyzed, and the required lift control law (with negative or positive lift) is exhibited in each case. Glide at very high descent rate and plane flows of trajectories are analyzed.

Vinh, N. X.↗
NASA NTRS2004

Marbles for the Imagination

The end-to-end test would verify the complex sequence of events from lander separation to landing. Due to the large distances involved and the significant delay time in sending a command and receiving verification, the lander needed to operate autonomously after it separated from the orbiter. It had to sense conditions, make decisions, and act accordingly. We were flying into a relatively unknown set of conditions-a Martian atmosphere of unknown pressure, density, and consistency to land on a surface of unknown altitude, and one which had an unknown bearing strength. In order to touch down safely on Mars the lander had to orient itself for descent and entry, modulate itself to maintain proper lift, pop a parachute, jettison its aeroshell, deploy landing legs and radar, ignite a terminal descent engine, and fly a given trajectory to the surface. Once on the surface, it would determine its orientation, raise the high-gain antenna, perform a sweep to locate Earth, and begin transmitting information. It was this complicated, autonomous sequence that the end-to-end test was to simulate.

Shue, Jack↗
NASA NTRS2006

Landing and Population Hazard Analysis for Stardust Entry in Operations and Entry Planning

Stardust is a comet sample return mission that successfully returned to Earth on January 15, 2006. Stardust's targeted landing area was the Utah Test and Training Range in the Northwest corner of Utah. Requirements for the risks associated with landing were levied on Stardust by the Utah Test and Training Range and NASA. This paper describes the analysis to verify that these requirements were met and and includes calculation of debris survivability, generation of landing site selection plots, and identification of keep-out zones, as well as appropriate selection of the landing site. Operationally the risk requirements were all met for both of the GOMO-GO polls, so entry was authorized.

simulation↗
NASA NTRS2010

Analysis of Air Traffic Track Data with the AutoBayes Synthesis System

The Next Generation Air Traffic System (NGATS) is aiming to provide substantial computer support for the air traffic controllers. Algorithms for the accurate prediction of aircraft movements are of central importance for such software systems but trajectory prediction has to work reliably in the presence of unknown parameters and uncertainties. We are using the AutoBayes program synthesis system to generate customized data analysis algorithms that process large sets of aircraft radar track data in order to estimate parameters and uncertainties. In this paper, we present, how the tasks of finding structure in track data, estimation of important parameters in climb trajectories, and the detection of continuous descent approaches can be accomplished with compact task-specific AutoBayes specifications. We present an overview of the AutoBayes architecture and describe, how its schema-based approach generates customized analysis algorithms, documented C/C++ code, and detailed mathematical derivations. Results of experiments with actual air traffic control data are discussed.

Schumann, Johann Martin Philip↗
NASA NTRS2017

Future ATM Concepts Evaluation Tool (FACET) Interface Control Document

This Interface Control Document (ICD) documents the airspace adaptation and air traffic inputs of NASA's Future ATM Concepts and Evaluation Tool (FACET). Its intended audience is the project manager, project team, development team, and stakeholders interested in interfacing with the system. FACET equips Air Traffic Management (ATM) researchers and service providers with a way to explore, develop and evaluate advanced air transportation concepts before they are field-tested and eventually deployed. FACET is a flexible software tool that is capable of quickly generating and analyzing thousands of aircraft trajectories. It provides researchers with a simulation environment for preliminary testing of advanced ATM concepts. Using aircraft performance profiles, airspace models, weather data, and flight schedules, the tool models trajectories for the climb, cruise, and descent phases of flight for each type of aircraft. An advanced graphical interface displays traffic patterns in two and three dimensions, under various current and projected conditions for specific airspace regions or over the entire continental United States. The system is able to simulate a full day's dynamic national airspace system (NAS) operations, model system uncertainty, measure the impact of different decision-makers in the NAS, and provide analysis of the results in graphical form, including sector, airport, fix, and airway usage statistics. NASA researchers test and analyze the system-wide impact of new traffic flow management algorithms under anticipated air traffic growth projections on the nation's air traffic system. In addition to modeling the airspace system for NASA research, FACET has also successfully transitioned into a valuable tool for operational use. Federal Aviation Administration (FAA) traffic flow managers and commercial airline dispatchers have used FACET technology for real-time operations planning. FACET integrates live air traffic data from FAA radar systems and weather data from the National Weather Service to summarize NAS performance. This information allows system operators to reroute flights around congested airspace and severe weather to maintain safety and minimize delay. FACET also supports the planning and post-operational evaluation of reroute strategies at the national level to maximize system efficiency. For the commercial airline passenger, strategic planning with FACET can result in fewer flight delays and cancellations. The performance capabilities of FACET are largely due to its architecture, which strikes a balance between flexibility and fidelity. FACET is capable of modeling the airspace operations for the continental United States, processing thousands of aircraft on a single computer. FACET was written in Java and C, enabling the portability of its software to a variety of operating systems. In addition, FACET was designed with a modular software architecture to facilitate rapid prototyping of diverse ATM concepts. Several advanced ATM concepts have already been implemented in FACET, including aircraft self-separation, prediction of aircraft demand and sector congestion, system-wide impact assessment of traffic flow management constraints, and wind-optimal routing.

FACET↗