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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 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
NASA NTRS2005

GPS Remote Sensing Measurements Using Aerosonde UAV

In February 2004, a NASA-Langley GPS Remote Sensor (GPSRS) unit was flown on an Aerosonde unmanned aerial vehicle (UAV) from the Wallops Flight Facility (WFF) in Virginia. Using direct and surface-reflected 1.575 GHz coarse acquisition (C/A) coded GPS signals, remote sensing measurements were obtained over land and portions of open water. The strength of the surface-reflected GPS signal is proportional to the amount of moisture in the surface, and is also influenced by surface roughness. Amplitude and other characteristics of the reflected signal allow an estimate of wind speed over open water. In this paper we provide a synopsis of the instrument accommodation requirements, installation procedures, and preliminary results from what is likely the first-ever flight of a GPS remote sensing instrument on a UAV. The correct operation of the GPSRS unit on this flight indicates that Aerosonde-like UAV's can serve as platforms for future GPS remote sensing science missions.

Grant, Michael S.↗
DOE OSTI2021

Identifying Light-Duty Vehicle Travel from Large-Scale Multimodal Wearable GPS Data with Novelty Detection Algorithms

Identifying travel mode within travel survey data sets, especially light-duty vehicle (LDV) travel, is foundational, though nontrivial, to travel behavior analysis and fuel consumption estimation. Current travel mode detection approaches require well-sampled and balanced data sets with ground truth travel mode labels. They are rarely applied and validated on large-scale, real-world data sets, which may not satisfy the data requirements. This paper proposes an LDV travel mode detection model as a supplement to current travel mode detection methods, for the case when the training set is highly (and/or completely) unbalanced, to the extent that classical machine-learning approaches become difficult or impossible to deploy. The proposed model uses a novelty detection technique-one-class support vector machines (OCSVMs)-and a novel exhaustive feature extraction (EFE) technique on continuous time series data (i.e., Global Positioning System [GPS] speed profiles) for single-mode trip trajectories. Training and validation of the model are conducted on a large-scale, real-world data set. The proposed method accurately identifies LDV trips from a broad set of multimodal trips by leveraging a wealth of preexisting in-vehicle GPS travel data. Additional sensitivity analysis sheds light on the optimal training size, which will benefit applications limited by highly imbalanced data. The paper also discusses performance comparison with regular machine-learning approaches, the model's robustness, and the potential to extend the proposed model to multimodal prediction.

47 OTHER INSTRUMENTATION↗
NASA NTRS2001

SHARP-B2: Flight Test Objectives, Project Implementation and Initial Results

On September 28, 2000 the SHARP-B2 flight experiment was launched from Vandenberg Air Force Base, California. SHARP-B2 is the 2nd Ballistic flight test in the SHARP (Slender Hypervelocity Aerothermodynamic Research Probes) program which develops and tests new thermal protection materials and sharp body concepts. The flight tested Ultra-High Temperature Ceramics (UHTCs), which may radically change the design and performance of future aerospace vehicles. The new designs may overturn an age-old tenet of aerodynamics: that blunt-body aerospace vehicles, but not those with sharp leading edges, can survive the searing temperatures created as the vehicles tear through the atmosphere. Sharp leading edges offer numerous advantages over the blunt-body design currently in use. They could allow a space shuttle or crew return vehicle to maneuver in space more like an airplane and potentially allow astronauts to return to Earth from anywhere on orbit. They may allow improved astronaut safety by decreasing the risk of aborting into the ocean. They may reduce the electromagnetic interference that causes the communications blackouts that plague reentering blunt-body space vehicles. Reducing the amount of drag could lead to a reduction in propulsion requirements. Planetary probes could make use of sharp-body technology for aerobraking and to maximize their maneuvering capability. SHARP-B2 was a joint effort among NASA Ames, Sandia National Laboratories, the U.S. Air Force and the U.S. Army. It was funded by the Pathfinder Program at NASA's Marshall Space Flight Center. The SHARP-B2 payload was carried aboard a U.S. Air Force Minuteman III missile carrying a modified Mk 12A reentry vehicle (RV), which blasted off from Vandenberg Air Force Base near Lompoc, CA, at 3:01 a.m. PDT on Sept. 28. The RV was equipped with four 5. 1 inch-long strakes, or sharp leading edges. Each strake contained three UHTCs: ZrB2/SiC/C; ZrB2/SiC; and HfB2/SiC. Once it reached an altitude of about 400 nautical miles, the RV was released, returning through Earth's atmosphere at speeds exceeding Mach 22. One pair of strakes was designed to retract just before reaching temperatures high enough to cause the material to begin ablating. The other pair was designed to retract shortly after ablation began, at an expected temperature of nearly 5,100 degrees Fahrenheit. Sensors in the strakes measured how closely performance matched pre-flight calculations, and data was successfully collected throughout the 23-minute flight. A parachute was deployed (but not fully inflated) and the RV splashed down in a lagoon at the Kwajalein missile range in the Pacific Ocean. Within 3 hours radar track analysis showed ocean entry to be precisely at the latitude/longitude coordinates estimated during pre-flight simulation. An hour later a ship was deployed by the Army to recover the reentry vehicle, which was recovered in 165 feet of water, just 500 feet from its planned splash-down point. This is the first RV recovery in over a decade.

Salute, Joan↗
DOE OSTI2022

Light-Duty Vehicle Trip Classification Using One-Class Novelty Detection and Exhaustive Feature Extraction

Travel mode classification within travel survey data sets, especially light-duty vehicle (LDV) trips, is foundational, though nontrivial, to emerging mobility systems, travel behavior analysis, and fuel consumption estimation. Current travel mode detection approaches require well-sampled and balanced data sets with ground truth travel mode labels. The detection approaches are rarely applied and validated on large-scale, real-world data sets, which may not satisfy the dataset requirements. This work proposes an LDV trip detection model as a supplement to current travel mode detection methods, for the case when the training set is highly (and/or completely) unbalanced, to the extent that classical machine-learning approaches become difficult or impossible to deploy. The proposed model uses a novelty detection technique - one-class support vector machines (OCSVMs) - and a novel exhaustive feature extraction (EFE) technique on continuous time series data (i.e., Global Positioning System [GPS] speed profiles) for single-mode trip trajectories. Training and validation of the model are conducted on a large-scale, real-world data set. The proposed method accurately identifies LDV trips from a broad set of multimodal trips by leveraging a wealth of preexisting in-vehicle GPS travel data. Additional sensitivity analysis sheds light on the optimal training size and feature selection, which will benefit applications limited by highly imbalanced data. The paper also discusses performance comparison with regular machine-learning approaches, the model's robustness, and the potential to extend the proposed model to multi-modal trip prediction.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2021

Dynamically Collected Local Density using Low-Cost Lidar and its Application to Traffic Models

This article demonstrates the use of traffic density observations collected dynamically in the vicinity of probe vehicles. Fixed position sensors cannot capture the longitudinal evolution of local traffic density in the corridor. In this research, dynamic traffic density observations were collected in a naturalistic driving setting that was free of any controlled experiment biases. Speed from global positioning system and space headway from a light detection and ranging module was collected on one arterial and one freeway segment, 2 and 4mi long, respectively. The combined data frequency was approximately 3Hz. Space headway was used to estimate the local density and consequently to identify the density of a specific location in a corridor. Besides, driver behavior was characterized using the relationship between instantaneous speed and local density under different regimes of the Wiedemann car-following model. Macroscopic traffic stream models were used to investigate the relationship between dynamically collected instantaneous speed and local density. Using the longitudinal evolution of density, precise local density across the corridor can be obtained along with the leader and follower trajectories. A method to identify driver behavior across density ranges was developed for different facility types using a microscopic relationship between instantaneous speed and local density. Overall driving behavior on the freeway segment can be represented by translating the instantaneous speed and local density relationship to macroscopic stream models.

Engineering↗
DOE OSTI2023

Comparing Regional Energy Consumption for Direct Drone and Truck Deliveries

Drone delivery, once thought of as fictitious, is becoming a reality with the efforts of both forward-looking enterprises and supportive government policies. This emerging mode of e-commerce delivery raises many concerns. One important concern is the energy efficiency of direct delivery drones compared with conventional delivery trucks at a regional systems level. Here, in this study, we develop and apply methods to quantify the regional energy impacts of drone delivery, then we assess these impacts and compare them with the impacts of truck delivery. To study this problem, we develop an optimization model that determines an optimal set of fulfillment centers (FCs) with variable service capacities that allow drones to make direct e-commerce deliveries. We adopt two drone delivery energy estimation models from the literature and use them as inputs to demonstrate the potential range of energy needs. We also develop another optimization model to account for the energy consumption of diesel trucks (DTs) and battery electric vehicles (BEVs). We test the models using validated simulation data for the Chicago metropolitan area in the U.S. to quantify the energy implications of these three delivery modes. For drone delivery, we further extend our analyses by considering the impact of wind speed and flight patterns. Our results show that direct delivery drones require 15.8% more energy than BEVs on an average windy day, and they need 15% more energy than DTs on a very windy day. We provide essential parameter values for reproducibility and list relevant open problems.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
NASA NTRSDate not supplied

Magnetic Suspension Wind Tunnel Reconstruction Using an Extended Kalman Filter Framework

- Problem Statement: - Magnetic Suspension Balance System (MSBS) allows operation of wind tunnels without sting effect - Small-scale MSBS system has been demonstrated; NASA is building a full-scale MSBS wind tunnel for supersonic speeds - MSBS testing can provide data that addresses mission needs; current data reconstruction methods do not combine all measurement data - Reconstruction methods for aerodynamic coefficients and their uncertainties are piecemeal, and in their infancy - Mission Need: - Enhancement of Entry, Descent, and Landing (EDL) technology during atmospheric flight is a top priority - Accurate dynamic aerodynamic coefficients are necessary for stability and control of entry vehicles - Goal: - Develop an Extended Kalman Filter (EKF) based framework to do reduction of MSBS data that will estimate aerodynamics, trajectory, and uncertainty information, combining data sources from the tunnel

Christopher D. Karlgaard↗
NASA NTRS2017

Conceptual Feasibility Study of the Hyperloop Vehicle for Next-Generation Transport

The Hyperloop concept is proposed as a faster, cheaper alternative to high-speed rail and traditional short-haul aircraft. It consists of a passenger pod traveling through a tube under light vacuum while being propelled and levitated by a combination of permanent and electro-magnets. The concept addresses NASA's research thrusts for growth in demand, sustainability, and technology convergence for high-speed transport. Hyperloop is a radical departure from other advanced aviation concepts, however it remains an aeronautics concept that tackles the same strategic goals of low-carbon propulsion and ultra-effcient vehicles. System feasibility was investigated by building a multidisciplinary vehicle sizing model that takes into account aerodynamic, thermodynamic, structures, electromagnetic, weight, and mission analyses. The sizing process emphasized the strong coupling between the two largest systems: the tube and the passenger pod. The model was then exercised to examine Hyperloop from a technical and cost perspective. The structural sizing analysis of the travel tube demonstrates potential for signi cant capital cost reductions by considering an underwater route. Examination of varying passenger capacity indicates that the system can be operated with a wide range of passenger loads without significant change in operating expenses. Lastly, a high-level sizing study simulated variations in tube area, pressure, pod speed, and passenger capacity showing that there is a tube pressure that minimizes operating energy usage. The value of this optimal tube pressure is highly sensitive to numerous design details. These combined estimates of energy consumption, passenger throughput, and mission analyses all support Hyperloop as a faster and cheaper alternative to short-haul flights. The tools and expertise used to quantify these results also demonstrate how traditional aerospace design methods can be leveraged to handle the complex and coupled design process. Much of the technology development required for the Hyperloop is shared with next-generation aircraft. Furthermore, the substantial public interest and active commercial development make it an ideal candidate as an aircraft technology driver and test bed.

Hyperloop Vehicle↗
NASA NTRS1984

A comparison of aerobraking and aerocapture vehicles for interplanetary missions

Several design features for employing aerobraking and aerocapture techniques on interplanetary spacecraft are described. Recent studies have identified silica fabrics mounted on carbon composite ribs as suitable aerobraking spacecraft shield materials. Aerocapture is best achieved with a biconic aeroshell design, with the aeroshell supported by Al honeycomb panels and allowing primitive aerodynamic maneuverability. The aeroshell would be covered with thermal protection materials capable of elevated temperatures of magnitudes that are a function of the expected atmospheric density, the surface area, the entry speed, spacecraft mass and maneuverability. Both technologies are concluded ready for implementation and development costs are estimated for various missions, showing that aerocapture will provide for greater payload masses, except for a Jupiter mission.

Hoffman, S.↗
NASA NTRSDate not supplied

Machine Learning Methods for Estimating Propeller Source Noise Spheres

In this work, several neural network function approximations are compared for inter- polating, storing, and sampling acoustic source spheres with applications to propeller noise estimation. These methods are compared using an acoustic model of the three bladed GL-10 propeller at different flight conditions, with training data generated using NASA’s ANOPP-PAS module. The source spheres used to train the networks capture the tonal propeller noise due to both the blade thickness and loading. This tonal noise prediction method allows the vehicle noise to be estimated for auralization and acoustic control. Three radial basis function neural network architectures are compared in this work. The first two networks directly estimate the parameters of the source sphere at different flight conditions but differ in the number of layers used. The third network estimates the parameters of the source sphere using a weighted combination of spherical basis functions. These networks are trained on numerically generated source spheres, with operating points given in terms of the propeller rotation rate, freestream speed, and propeller angle of attack. The performance of the neural network is determined using a validation dataset of withheld data points. This performance is quantified in terms of the approximation error, training time, and sample time. The third network, which estimates the weights of the spherical basis functions, performs the best in both average and maximum approximation errors in all cases. This network’s worst case performance is 5.6 % relative dif- ference of a model parameter associated with acoustic pressure. The direct estimation network with a single layer has the worst approximation error in all cases. Additionally, the spherically defined network has the slowest sample time at 0.05 seconds per thousand points. Both direct estimation methods produce a thousand sample points in approximately 0.001 seconds.

Acoustics↗
DOE OSTI2024

Autonomous Emergency Landing for Fixed-Wing Aircraft with Energy-Constrained Closed-Loop Prediction

Here this paper presents a new approach for autonomous motion planning for aircraft suffering from a loss-of-thrust emergency. Specifically, we show how modifications to the Closed-Loop Rapidly exploring Random Trees (CL-RRT) framework combined with controlled energy dissipation can enable rapid and effective kinodynamic motion planning. This CL-RRT Glide algorithm uses closed-loop prediction not only for node connections but also to estimate the remaining energy and prune infeasible paths. This greatly speeds up the search process, which is essential for emergency situations. In addition, we improve the ability of the gliding aircraft to reach a goal position and energy state. We do so by creating a Dissipative Total Energy Control Scheme (TECS). Dissipative TECS enables the glider to lose excess altitude in order to reach a desired energy level. Simulation results illustrate how the proposed methods enable faster motion planning. We also integrate the system into a small unmanned aerial vehicle system and experimentally demonstrate autonomous glide planning and execution during a motor-failure event. This type of algorithm can primarily benefit unmanned aircraft but can also serve to assist pilots in stressful emergency situations.

42 ENGINEERING↗
NASA NTRS2007

Guidance and Control of an Autonomous Soaring UAV

Thermals caused by convection in the lower atmosphere are commonly used by birds and glider pilots to extend flight duration, increase cross-country speed, improve range, or simply to conserve energy. Uninhabited Aerial Vehicles (UAVs) can also increase performance and reduce energy consumption by exploiting atmospheric convection. An autonomous soaring research project was conducted at the NASA Dryden Flight Research Center to evaluate the concept through flight test of an electric-powered motorglider with a wingspan of 4.27 m (14 ft). The UAV's commercial autopilot software was modified to include outer-loop soaring guidance and control. The aircraft total energy state was used to detect and soar within thermals. Estimated thermal size and position were used to calculate guidance commands for soaring flight. Results from a total of 23 thermal encounters show good performance of the guidance and control algorithms to autonomously detect and exploit thermals. The UAV had an average climb of 172 m (567 ft) during these encounters.

Allen, Michael J.↗
NASA NTRS2004

NASA Tech Briefs, August 2004

Topics covered include: Data Relay Board with Protocol for High-Speed, Free-Space Optical Communications; Software and Algorithms for Biomedical Image Data Processing and Visualization; Rapid Chemometric Filtering of Spectral Data; Prioritizing Scientific Data for Transmission; Determining Sizes of Particles in a Flow from DPIV Data; Faster Processing for Inverting GPS Occultation Data; FPGA-Based, Self-Checking, Fault-Tolerant Computers; Ultralow-Power Digital Correlator for Microwave Polarimetry; Grounding Headphones for Protection Against ESD; Lightweight Stacks of Direct Methanol Fuel Cells; Highly Efficient Vector-Inversion Pulse Generators; Estimating Basic Preliminary Design Performances of Aerospace Vehicles; Framework for Development of Object-Oriented Software; Analyzing Spacecraft Telecommunication Systems; Collaborative Planning of Robotic Exploration; Tools for Administration of a UNIX-Based Network; Preparing and Analyzing Iced Airfoils; Evaluating Performance of Components; Fuels Containing Methane of Natural Gas in Solution; Direct Electrolytic Deposition of Mats of MnxOy Nanowires; Bubble Eliminator Based on Centrifugal Flow; Inflatable Emergency Atmospheric-Entry Vehicles; Lightweight Deployable Mirrors with Tensegrity Supports; Centrifugal Adsorption Cartridge System; Ultrasonic Apparatus for Pulverizing Brittle Material; Transplanting Retinal Cells using Bucky Paper for Support; Using an Ultrasonic Instrument to Size Extravascular Bubbles; Coronagraphic Notch Filter for Raman Spectroscopy; On-the-Fly Mapping for Calibrating Directional Antennas; Working Fluids for Increasing Capacities of Heat Pipes; Computationally-Efficient Minimum-Time Aircraft Routes in the Presence of Winds; Liquid-Metal-Fed Pulsed Plasma Thrusters; Personal Radiation Protection System; and Attitude Control for a Solar-Sail Spacecraft.

Source record↗
NASA NTRS1994

Contributions of a Tunable Diode Laser Instrument (ATLAS) to the Stratospheric Ozone Depletion Question

The Airborne Tunable Laser Absorption Spectrometer - ATLAS - was designed and built at the NASA Ames Research Center and operates on the NASA ER-2 high altitude research aircraft. ATLAS has taken part in a number of important polar and mid-latitude research campaigns, since 1987, focused on various aspects of stratospheric ozone chemistry and dynamics. The chief measurement carried out by the ATLAS second harmonic diode laser spectrometer is of the important atmospheric tracer N2O. Using N2O as an inert tracer we have been able to gain significant new information on polar vortex dynamics and on the correlations of several important long-lived tracers in the stratosphere. The correlation of N2O with NOy (total reactive nitrogen) has been shown to be linear for a great variety of unperturbed stratospheric conditions, and the breakdown of this correlation has been used to detect denitrification by PSCs in the polar vortex, especially in the Antarctic spring. Denitrification is an important step in the process of ozone hole formation in the austral spring. Correlations of N2O with CFCs and CH4 have led to improved estimates of atmospheric lifetimes of these important molecules. Finally the correlation of N2O with CO2, the latter now being measured with great precision by a new instrument on the ER-2, has led to a significant new tool for studying horizontal and vertical mixing in the lower stratosphere, a tool which is very useful in assessing the potential effects of high speed civil transport aircraft in the lower stratosphere. A new, light-weight version of ATLAS is currently being built for unmanned high altitude aircraft, specifically the new Perseus vehicle. We will give a brief description of this effort.

Loewenstein, Max↗
NASA NTRS2007

Guidance and Control of an Autonomous Soaring UAV

Thermals caused by convection in the lower atmosphere are commonly used by birds and glider pilots to extend flight duration, increase cross-country speed, improve range, or simply to conserve energy. Uninhabited Aerial Vehicles (UAVs) can also increase performance and reduce energy consumption by exploiting atmospheric convection. An autonomous soaring research project was conducted at the NASA Dryden Flight Research Center to evaluate the concept through flight test of an electric-powered motor-glider with a wingspan of 4.27 m (14 ft). The UAV's commercial autopilot software was modified to include outer-loop soaring guidance and control. The aircraft total energy state was used to detect and soar within thermals. Estimated thermal size and position were used to calculate guidance commands for soaring flight. Results from a total of 23 thermal encounters show good performance of the guidance and control algorithms to autonomously detect and exploit thermals. The UAV had an average climb of 172 m (567 ft) during these encounters.

Allen, Michael J.↗
NASA NTRS1990

Integrated Inertial/gps

The presence of failures in navigation sensors can cause the determination of an erroneous aircraft state estimate, which includes position, attitude, and their derivatives. Aircraft flight control systems rely on sensor inputs to determine the aircraft state. In the case of integrated Inertial/NAVSTAR Global Positioning System (GPS), sensor failures could occur in the on-board inertial sensors or in the GPS measurements. The synergistic use of both GPS and the Inertial Navigation System (INS) allows for highly reliable fault detection and isolation of sensor failures. Integrated Inertial/GPS is a promising technology for the High Speed Civil Transport (HSCT) and the return and landing of a manned space vehicle.

Kline, Paul↗
NASA NTRS2010

Stereoscopic Machine-Vision System Using Projected Circles

A machine-vision system capable of detecting obstacles large enough to damage or trap a robotic vehicle is undergoing development. The system includes (1) a pattern generator that projects concentric circles of laser light forward onto the terrain, (2) a stereoscopic pair of cameras that are aimed forward to acquire images of the circles, (3) a frame grabber and digitizer for acquiring image data from the cameras, and (4) a single-board computer that processes the data. The system is being developed as a prototype of machine- vision systems to enable robotic vehicles ( rovers ) on remote planets to avoid craters, large rocks, and other terrain features that could capture or damage the vehicles. Potential terrestrial applications of systems like this one could include terrain mapping, collision avoidance, navigation of robotic vehicles, mining, and robotic rescue. This system is based partly on the same principles as those of a prior stereoscopic machine-vision system in which the cameras acquire images of a single stripe of laser light that is swept forward across the terrain. However, this system is designed to afford improvements over some of the undesirable features of the prior system, including the need for a pan-and-tilt mechanism to aim the laser to generate the swept stripe, ambiguities in interpretation of the single-stripe image, the time needed to sweep the stripe across the terrain and process the data from many images acquired during that time, and difficulty of calibration because of the narrowness of the stripe. In this system, the pattern generator does not contain any moving parts and need not be mounted on a pan-and-tilt mechanism: the pattern of concentric circles is projected steadily in the forward direction. The system calibrates itself by use of data acquired during projection of the concentric-circle pattern onto a known target representing flat ground. The calibration- target image data are stored in the computer memory for use as a template in processing terrain images. During operation on terrain, the images acquired by the left and right cameras are analyzed. The analysis includes (1) computation of the horizontal and vertical dimensions and the aspect ratios of rectangles that bound the circle images and (2) comparison of these aspect ratios with those of the template. Coordinates of distortions of the circles are used to identify and locate objects. If the analysis leads to identification of an object of significant size, then stereoscopicvision algorithms are used to estimate the distance to the object. The time taken in performing this analysis on a single pair of images acquired by the left and right cameras in this system is a fraction of the time taken in processing the many pairs of images acquired in a sweep of the laser stripe across the field of view in the prior system. The results of the analysis include data on sizes and shapes of, and distances and directions to, objects. Coordinates of objects are updated as the vehicle moves so that intelligent decisions regarding speed and direction can be made. The results of the analysis are utilized in a computational decision-making process that generates obstacle-avoidance data and feeds those data to the control system of the robotic vehicle.

Mackey, Jeffrey R.↗
NASA NTRSDate not supplied

Trajectory Reconstruction of the Low-Earth Orbit Flight Test of an Inflatable Decelerator

The Low-Earth Orbit Flight Test of an Inflatable Decelerator (LOFTID) project conducted a flight test of a 6m inflatable aeroshell. The LOFTID test article was a secondary payload on an Atlas V launcher that carried the Joint Polar Satellite System-2 (JPSS-2) as its primary payload. The vehicle launched on November 10th, 2022. After reaching orbit, the LOFTID test article inflated the aeroshell, separated from the upper stage on an entry trajectory, and entered the atmosphere to splash down in the Pacific Ocean under parachutes. The test concept of operations is shown in Figure 1. The test article was instrumented with a variety of sensors to be used for post-flight evaluation of vehicle performance. Data from one of the key sensors for trajectory reconstruction, the Inertial Measurement Unit (IMU), was not captured in the data recorder due to a malfunction. Data from the nose cone mounted Flush Air Data Sensing (FADS) system were successfully acquired. The layout of the FADS sensors and the measured pressures during atmospheric entry are shown in Figure 2. The FADS data were combined with a Newtonian flow pressure model [1, 2] to produce estimates of the atmospheric relative trajectory. A Mach number anchoring technique given in [2] was used to stabilize estimates in high speed flight conditions. Since no IMU data were available, a trajectory simulation was used to provide the Mach number time history. The resulting estimates of the atmospheric-relative trajectory are shown in Figures 3. Given the loss of the IMU data, alternate methods for trajectory reconstruction are being explored. One approach under investigation is the use of the on-board video recorder data to be analyzed to reconstruct attitude motion. This approach is currently under investigation and will be reported on in the final paper. The Newtonian flow pressure model for the FADS analysis will also be updated with a CFD-based pressure model.

Christopher D Karlgaard↗