Results for “Flight Trajectory” — Page 19

NASA NTRS2015

Fairing Separation Analysis Using SepTOOL

This document describes the relevant equations programmed in spreadsheet software, SepTOOL, developed by ZIN Technologies, Inc. (ZIN) to determine the separation clearance between a launch vehicle payload fairing and remaining stages. The software uses closed form rigid body dynamic solutions of the vehicle in combination with flexible body dynamics of the fairing, which is obtained from flexible body dynamic analysis or from test data, and superimposes the two results to obtain minimum separation clearance for any given set of flight trajectory conditions. Using closed form solutions allows SepTOOL to perform separation calculations several orders of magnitude faster compared to numerical methods which allows users to perform real time parameter studies. Moreover, SepTOOL can optimize vehicle performance to minimize separation clearance. This tool can evaluate various shapes and sizes of fairings along with different vehicle configurations and trajectories. These geometries and parameters are inputted in a user friendly interface. Although the software was specifically developed for evaluating the separation clearance of launch vehicle payload fairings, separation dynamics of other launch vehicle components can be evaluated provided that aerodynamic loads acting on the vehicle during the separation event are negligible. This document describes the development of SepTOOL providing analytical procedure and theoretical equations whose implementation of these equations is not disclosed. Realistic examples are presented, and the results are verified with ADAMS (MSC Software Corporation) simulations. It should be noted that SepTOOL is a preliminary separation clearance assessment software for payload fairings and should not be used for final clearance analysis.

fairings↗

NASA NTRS2015

A Maneuvering Flight Noise Model for Helicopter Mission Planning

A new model for estimating the noise radiation during maneuvering flight is developed in this paper. The model applies the Quasi-Static Acoustic Mapping (Q-SAM) method to a database of acoustic spheres generated using the Fundamental Rotorcraft Acoustics Modeling from Experiments (FRAME) technique. A method is developed to generate a realistic flight trajectory from a limited set of waypoints and is used to calculate the quasi-static operating condition and corresponding acoustic sphere for the vehicle throughout the maneuver. By using a previously computed database of acoustic spheres, the acoustic impact of proposed helicopter operations can be rapidly predicted for use in mission-planning. The resulting FRAME-QS model is applied to near-horizon noise measurements collected for the Bell 430 helicopter undergoing transient pitch up and roll maneuvers, with good agreement between the measured data and the FRAME-QS model.

Greenwood, Eric↗

NASA NTRS2016

Development of Constraint Force Equation Methodology for Application to Multi-Body Dynamics Including Launch Vehicle Stage Seperation

The objective of this report is to develop and implement a physics based method for analysis and simulation of multi-body dynamics including launch vehicle stage separation. The constraint force equation (CFE) methodology discussed in this report provides such a framework for modeling constraint forces and moments acting at joints when the vehicles are still connected. Several stand-alone test cases involving various types of joints were developed to validate the CFE methodology. The results were compared with ADAMS(Registered Trademark) and Autolev, two different industry standard benchmark codes for multi-body dynamic analysis and simulations. However, these two codes are not designed for aerospace flight trajectory simulations. After this validation exercise, the CFE algorithm was implemented in Program to Optimize Simulated Trajectories II (POST2) to provide a capability to simulate end-to-end trajectories of launch vehicles including stage separation. The POST2/CFE methodology was applied to the STS-1 Space Shuttle solid rocket booster (SRB) separation and Hyper-X Research Vehicle (HXRV) separation from the Pegasus booster as a further test and validation for its application to launch vehicle stage separation problems. Finally, to demonstrate end-to-end simulation capability, POST2/CFE was applied to the ascent, orbit insertion, and booster return of a reusable two-stage-to-orbit (TSTO) vehicle concept. With these validation exercises, POST2/CFE software can be used for performing conceptual level end-to-end simulations, including launch vehicle stage separation, for problems similar to those discussed in this report.

Pamadi, Bandu N.↗

NASA NTRS2017

Validation of a Low-Thrust Mission Design Tool Using Operational Navigation Software

Design of flight trajectories for missions employing solar electric propulsion requires a suitably high-fidelity design tool. In this work, the Evolutionary Mission Trajectory Generator (EMTG) is presented as a medium-high fidelity design tool that is suitable for mission proposals. EMTG is validated against the high-heritage deep-space navigation tool MIRAGE, demonstrating both the accuracy of EMTG's model and an operational mission design and navigation procedure using both tools. The validation is performed using a benchmark mission to the Jupiter Trojans.

Englander, Jacob A.↗

NASA NTRS2017

Validation of a Low-Thrust Mission Design Tool Using Operational Navigation Software

Design of flight trajectories for missions employing solar electric propulsion requires a suitably high-fidelity design tool. In this work, the Evolutionary Mission Trajectory Generator (EMTG) is presented as a medium-high fidelity design tool that is suitable for mission proposals. EMTG is validated against the high-heritage deep-space navigation tool MIRAGE, demonstrating both the accuracy of EMTG's model and an operational mission design and navigation procedure using both tools. The validation is performed using a benchmark mission to the Jupiter Trojans.

Englander, Jacob A.↗

NASA NTRS2017

Design Guide for Aerodynamics Testing of Earth and Planetary Entry Vehicles in a Ballistic Range

The purpose of this manual is to aid in the design of an aerodynamics test of an earth or planetary entry capsule in a ballistic range. In this manual, much use is made of the results and experience gained in 50 years of ballistic range aerodynamics testing at the NASA Ames Research Center, and in particular, that gained in the last 27 years, while the author was working at NASA Ames. The topics treated herein include: Data to be obtained; flight data needed to design test; Reynolds number and dynamic similarity of flight trajectory and ballistic range test; capabilities of various ballistic ranges; Calculations of swerves due to average and oscillating lift and of drag-induced velocity decreases; Model and sabot design; materials, weights and stresses; Sabot separation; Launches at angle of attack and slapping with paper to produce pitch/yaw oscillations.

Test Design↗

NASA NTRS2017

Flow-Tube Reactor Experiments on the High Temperature Oxidation of Carbon Weaves

Under entry conditions carbon weaves used in thermal protection systems (TPS) decompose via oxidation. Modeling this phenomenon is challenging due to the different regimes encountered along a flight trajectory. Approaches using equilibrium chemistry may lead to over-estimated mass loss and recession at certain conditions. Concurrently, there is a shortcoming of experimental data on carbon weaves to enable development of improved models. In this work, a flow-tube test facility was used to measure the oxidation of carbon weaves at temperatures up to 1500 K. The material tested was the 3D carbon weave used for the heat shield of the NASA Adaptive Deployable Entry and Placement Technology, ADEPT. Oxidation was characterized by quantifying decomposition gases (CO and CO2), by mass measurements, and by microscale surface analysis. The current set of measurements contributes to the development of finite rate chemistry models for carbon fabrics used in woven TPS materials.

Woven TPS↗

NASA NTRS2017

Estimation, Navigation and Control of Multi-Rotor Drones in an Urban Wind Field

The paper presents an on-board estimation, navigation and control architecture for multi-rotor drones flying in urban environment. It consists of adaptive algorithms to estimate vehicle's aerodynamic drag coefficients with respect to still air and the urban wind components along the flight trajectory, with guaranteed fast and reliable convergence to the true values; navigation algorithms to generate feasible trajectories between given way-points that take into account the estimated wind; and of control algorithms to track the generated trajectories as long as the vehicle retains sufficient number of functioning rotors capable of compensating for the estimated wind. All components of this on-board system are computationally effective and are intended for a real time implementation. The algorithms were tested in simulations.

Stepanyan, Vahram↗

NASA NTRS2019

Radiation Modeling for the Reentry of the Hayabusa Sample Return Capsule

Predicted shock-layer emission signatures during the reentry of the Japanese Hayabusa capsule are presented and compared with flight measurements conducted during an airborne observation mission in NASA's DC-8 Airborne Laboratory. For selected altitudes at 11 points along the flight trajectory of the capsule, lines of sight were extracted from flow field solutions computed using the in-house high-fidelity CFD code, DPLR. These lines of sight were used as inputs for the line-by-line radiation code NEQAIR, and emission spectra of the air plasma were computed in the wavelength range from 300 nm to 1600 nm, a range which covers all of the different experiments onboard the DC-8. In addition, the computed flow field solutions were post-processed with the material thermal response code FIAT, and the resulting surface temperatures of the heat shield were used to generate thermal emission spectra based on Planck radiation. Both spectra were summed and integrated over the flow field. The resulting emission at each trajectory point was propagated to the DC-8 position and transformed into incident irradiance to be finally compared with experimental data.

shock-layer radiation↗

NASA NTRS2020

COMDES-MELT: A Turbofan Engine Icing Risk Analysis Tool, User’s Manual

The computational tool COMDES-MELT was developed to predict the susceptibility of turbofan engines to ice accretion when flying in an ice crystal environment. COMDES-MELT is a first-generation computational tool that can estimate the conditions at which the accretion of ice can occur, location within the turbofan engine compression system, and at which engine operating points within the flight trajectory. This is accomplished by tracking the parameters of static wet bulb temperature, ice particle melt ratio, and the ice-water to airflow rates ratio as ice crystals are ingested into the engine compression system. It has been used successfully to predict engine operating points for simulation in an altitude wind tunnel with ice crystal ingestion. These engine tests occur in a simulated ice crystal cloud environment. This predictive analysis has been used to generate the test matrix in preparation for tests in the Propulsion Systems Laboratory, an altitude test facility at the NASA Glenn Research Center. Furthermore, due to the speed of the code during an engine icing test, adjustments to the test matrix can be provided to the test engineer in real time to focus on a particular area of ice accretion susceptibility. The use of the COMDES-MELT code will be examined in this manual.

Turbofan engine↗

NASA NTRSDate not supplied

Adaptive Pressure Profile Method to Locate the Isolator Shock Train Leading Edge Given Limited Pressure Information

To maximize the performance of high-speed air-breathing engines, such as dual-mode scramjets, the streamwise location of the shock train leading edge (STLE) is ideally placed as far upstream in the isolator as possible while avoiding engine unstart. Thus, it is of interest to quantify and control the STLE location as the vehicle travels along its flight trajectory. The STLE location is typically quantified using wall static pressure measurements but there are often restrictions on the number and placement of transducers, thus reducing the accuracy and overall capability of STLE detection methods. In this work, the Adaptive Pressure Profile (APP) method is introduced to address such sparsity concerns. This method is data driven and does not heavily rely on prior information about the flow regime or engine model. Instead, the \mname method uses real-time pressure measurements from a small number of transducers to adaptively learn the isolator pressure profile. This adaptively-learned profile is fit to the pressure data at each time instance to estimate STLE location. The \mname method produces accurate estimates even when (1) the STLE location is not bounded by two or more transducers or (2) when the STLE location is between two transducers that are situated several duct heights apart. Data from two direct-connect isolator models are used to evaluate the accuracy of the \mname method and demonstrate its robustness for different back-pressure scenarios and transducer configurations.

Robin L Hunt↗

NASA NTRSDate not supplied

Adaptive Pressure Profile Method to Locate the Isolator Shock Train Leading Edge Given Limited Pressure Information

To maximize the performance of high-speed air-breathing engines, such as dual-mode scramjets, the streamwise location of the shock train leading edge (STLE) is ideally placed as far upstream in the isolator as possible while avoiding engine unstart. Thus, it is of interest to quantify and control the STLE location as the vehicle travels along its flight trajectory. The STLE location is typically quantified using wall static pressure measurements but there are often restrictions on the number and placement of transducers, thus reducing the accuracy and overall capability of STLE detection methods. In this work, the Adaptive Pressure Profile (APP) method is introduced to address such sparsity concerns. This method is data driven and does not heavily rely on prior information about the flow regime or engine model. Instead, the \mname method uses real-time pressure measurements from a small number of transducers to adaptively learn the isolator pressure profile. This adaptively-learned profile is fit to the pressure data at each time instance to estimate STLE location. The \mname method produces accurate estimates even when (1) the STLE location is not bounded by two or more transducers or (2) when the STLE location is between two transducers that are situated several duct heights apart. Data from two direct-connect isolator models are used to evaluate the accuracy of the \mname method and demonstrate its robustness for different back-pressure scenarios and transducer configurations.

Robin Hunt↗

NASA NTRSDate not supplied

Cybersecurity - Host-based Intrusion Detection Systems (HIDS)

Given a set of flight trajectories, can we classify the trajectories that do not follow a normal path? By identifying abnormal trajectories, further analysis can be done to determine the reasoning for these actions. Addressing these scenarios can bring possible solutions for holding and rerouting problems when its time to incorporate UAM in the airspace.

DFR↗

NASA NTRSDate not supplied

Noise Impact Analysis for Urban Air Mobility in Dallas-Fort Worth Metroplex

This study supports re-design of airspace and procedures for management of Urban Air Mobility (UAM) fleet operations in a given metropolitan area. A goal of UAM is to maintain geographic separation of UAM flight tracks from densely populated areas in order to reduce the potential negative community impact of UAM and manage flight trajectory in anticipation of allowable noise levels and current land use. A UAM route inventory and a demographic-data-optimized topographic map are developed for the Dallas-Fort Worth metroplex to identify routes or baseline route segments for reduction of noise impact. Noise contours are computed for baseline route and alternative route design given the desired UAM demand level. The impact of UAM fleet noise is predicted based on predicted number of people and noise-sensitive facilities located inside the noise contours.

Urban Air Mobility↗

NASA NTRSDate not supplied

Noise Impact Analysis for Urban Air Mobility in Dallas-Fort Worth Metroplex

This study supports re-design of airspace and procedures for management of Urban Air Mobility (UAM) fleet operations in a given metropolitan area. A goal of UAM is to maintain geographic separation of UAM flight tracks from densely populated areas in order to reduce the potential negative community impact of UAM and manage flight trajectory in anticipation of allowable noise levels and current land use. A UAM route inventory and a demographic-data-optimized topographic map are developed for the Dallas-Fort Worth metroplex to identify routes or baseline route segments for reduction of noise impact. Noise contours are computed for baseline route and alternative route design given the desired UAM demand level. The impact of UAM fleet noise is predicted based on predicted number of people and noise-sensitive facilities located inside the noise contours.

Urban Air Mobility↗

NASA NTRSDate not supplied

NAIRAS Model transition to the CCMC: real-time dosimetric output and low-Earth orbit applications

NASA’s Nowcast of Atmospheric Ionizing Radiation for Aviation Safety (NAIRAS) model is areal-time, global, physics-based model originally developed to predict exposure to cosmic radiation to air travelers from both galactic and solar sources. A prototype operational NAIRAS model has provided tabular and graphical data products via its public web site for a number of years. We present the advances in the transition of NAIRAS to operations at the Community Coordinated Modeling Center (CCMC), located at NASA Goddard Space Flight Center, where global NAIRAS products are available for a real-time space weather version of the model. In addition, a runs-on-request version provides model output along user selected flight trajectories. We show the global dosimetric output from the model that are available in real-time as well as the new products developed to support commercial spaceflight missions to low-Earth orbit(LEO) and the International Space Station (ISS).

Guillaume Gronof↗

NASA NTRSDate not supplied

Aerial Vehicle Routing and Scheduling for UAS Traffic Management: A Monte Carlo Tree Search Approach

Numerous unmanned aircraft systems operating at low altitudes to deliver goods and services may one day become ubiquitous in our cities. In the Unmanned Aircraft Systems (UAS) Traffic Management (UTM) framework, such a concept is envisioned, where aerial vehicles operate beyond visual line of sight (BVLOS) within specifically reserved and time stamped “corridors” in the airspace. For example, these corridors or operational intent volumes can connect an aerial vehicle’s origin site to its destination site for package delivery operations. There may also be more than one corridor available for an aerial vehicle to choose from and often different corridors may intersect with one another. Thus, it is imperative to ensure flight trajectories belonging to different aerial vehicles are not in conflict. Per the UTM CONOPs, we assume that a vehicle almost always stays inside its corridor or operational volume. This work provides a framework for strategic deconfliction of UTM or package delivery drones, where we schedule the departure time of all vehicles subject to various temporal constraints (including the corridor deconfliction at the intersections). We present the “multi-route weighted package delivery problem” which serves as an exemplifying model for strategic deconfliction in UTM. In the multi-route weighted package delivery problem, a graph network is given which consists of a set of depots (source) and drop-off (destination) nodes, with multiple routes (defined as a sequence of waypoints) connecting the depots to drop-off nodes. In addition, routes are weighted by the associated ground risk and total travel distance for package delivery. The goal is for a known set of aerial vehicles to depart from the depots, choose a route and take off time, while avoiding conflicts with other aerial vehicles, and minimizing both risk and distance traveled. We provide a mixed integer linear programming (MILP) formulation of the problem, as well as a heuristic solution based on Monte Carlo Tree Search (MCTS) – a method used in game theory and artificial intelligence – to overcome limitations inherent to optimal solvers. Computational results show the advantages of using MCTS over the MILP formulation; the former can provide a sub-optimal solution quickly, and may sometimes even reach an optimal solution, whereas the latter may not even produce a solution in reasonable time. Furthermore, results from both the MILP formulation and MCTS methods were validated using a preliminary agent-based simulator implementing the UTM concept of operations. Thus, the MCTS method can be seen as a scalable solution to the complex multi-route weighted package delivery problem and may possibly be extended to similar complex optimization problems.

Kenny Chour↗

NASA NTRSDate not supplied

L2-Charged Particle Environment (L2-CPE)Low Energy Radiation Fluence Model

The L2 Charged Particle Environment (L2-CPE) model provides estimates of number flux and fluence for the low energy electron, proton, and alpha particle populations in the near Earth solar wind and the Earth’s distant magnetosheath and magnetotail. The model is an engineering tool for specifying radiation environments over an energy range from a few eV to a few MeV of importance to surface dose and radiation damage to thin space exposed materials and is intended for use in space system design applications. Mission fluences are obtained by simulating a spacecraft flight trajectory through time-dependent bow shock and magnetopause boundaries with dimensions and orientations driven by solar wind parameters. Monte Carlo sampling of flux environments within individual plasma regimes and/or fluence accumulated along a fight trajectory through multiple regimes is used to determine statistical variations (means and extremes) of the differential number flux and fluence environments for each of the three charged particle species. Model output is differential (in energy) number fluence and flux for the three particle species in units of particles/cm2-keV and particles/cm2-sec-keV, respectively. Users can select the energy range of interest but the current version of the code (L2-CPE Version 1.4.2d) is limited to an energy range of 1 eV to 10 MeV. Flux is integrated over angle to give flux and fluence to surfaces in the ±XGSE, ±YGSE, and/or ±ZGSE directions. Figure 1 shows the opening screen from the L2-CPE graphical user interface (GUI) with options for flux, fluence, plotting model output. The flux scene generate is not currently implemented in the GUI.

Joseph I Minow↗