Engineering topics

Kutty, Prasad

Publications and source records attributed to Kutty, Prasad.

10 records

NASA NTRS2016

Coupled Inertial Navigation and Flush Air Data Sensing Algorithm for Atmosphere Estimation

This paper describes an algorithm for atmospheric state estimation based on a coupling between inertial navigation and flush air data-sensing pressure measurements. The navigation state is used in the atmospheric estimation algorithm along with the pressure measurements and a model of the surface pressure distribution to estimate the atmosphere using a nonlinear weighted least-squares algorithm. The approach uses a high-fidelity model of atmosphere stored in table-lookup form, along with simplified models propagated along the trajectory within the algorithm to aid the solution. Thus, the method is a reduced-order Kalman filter in which the inertial states are taken from the navigation solution and atmospheric states are estimated in the filter. The algorithm is applied to data from the Mars Science Laboratory entry, descent, and landing from August 2012. Reasonable estimates of the atmosphere are produced by the algorithm. The observability of winds along the trajectory are examined using an index based on the observability Gramian and the pressure measurement sensitivity matrix. The results indicate that bank reversals are responsible for adding information content. The algorithm is applied to the design of the pressure measurement system for the Mars 2020 mission. A linear covariance analysis is performed to assess estimator performance. The results indicate that the new estimator produces more precise estimates of atmospheric states than existing algorithms.

Karlgaard, Christopher D.↗

NASA NTRS2015

Supersonic Flight Dynamics Test: Trajectory, Atmosphere, and Aerodynamics Reconstruction

The Supersonic Flight Dynamics Test is a full-scale flight test of a Supersonic Inflatable Aerodynamic Decelerator, which is part of the Low Density Supersonic Decelerator technology development project. The purpose of the project is to develop and mature aerodynamic decelerator technologies for landing large mass payloads on the surface of Mars. The technologies include a Supersonic Inflatable Aerodynamic Decelerator and Supersonic Parachutes. The first Supersonic Flight Dynamics Test occurred on June 28th, 2014 at the Pacific Missile Range Facility. This test was used to validate the test architecture for future missions. The flight was a success and, in addition, was able to acquire data on the aerodynamic performance of the supersonic inflatable decelerator. This paper describes the instrumentation, analysis techniques, and acquired flight test data utilized to reconstruct the vehicle trajectory, atmosphere, and aerodynamics. The results of the reconstruction show significantly higher lofting of the trajectory, which can partially be explained by off-nominal booster motor performance. The reconstructed vehicle force and moment coefficients fall well within pre-flight predictions. A parameter identification analysis indicates that the vehicle displayed greater aerodynamic static stability than seen in pre-flight computational predictions and ballistic range tests.

Kutty, Prasad↗

NASA NTRS2015

Coupled Inertial Navigation and Flush Air Data Sensing Algorithm for Atmosphere Estimation

This paper describes an algorithm for atmospheric state estimation that is based on a coupling between inertial navigation and flush air data sensing pressure measurements. In this approach, the full navigation state is used in the atmospheric estimation algorithm along with the pressure measurements and a model of the surface pressure distribution to directly estimate atmospheric winds and density using a nonlinear weighted least-squares algorithm. The approach uses a high fidelity model of atmosphere stored in table-look-up form, along with simplified models of that are propagated along the trajectory within the algorithm to provide prior estimates and covariances to aid the air data state solution. Thus, the method is essentially a reduced-order Kalman filter in which the inertial states are taken from the navigation solution and atmospheric states are estimated in the filter. The algorithm is applied to data from the Mars Science Laboratory entry, descent, and landing from August 2012. Reasonable estimates of the atmosphere and winds are produced by the algorithm. The observability of winds along the trajectory are examined using an index based on the discrete-time observability Gramian and the pressure measurement sensitivity matrix. The results indicate that bank reversals are responsible for adding information content to the system. The algorithm is then applied to the design of the pressure measurement system for the Mars 2020 mission. The pressure port layout is optimized to maximize the observability of atmospheric states along the trajectory. Linear covariance analysis is performed to assess estimator performance for a given pressure measurement uncertainty. The results indicate that the new tightly-coupled estimator can produce enhanced estimates of atmospheric states when compared with existing algorithms.

Karlgaard, Christopher D.↗

NASA NTRS2014

The Aerodynamics of Axisymmetric Blunt Bodies Flying at Angle of Attack

The Mars Science Laboratory entry capsule is used as an example to demonstrate how a blunt body of revolution must be treated as asymmetric in some respects when flying at a non-zero trim angle of attack. A brief description of the axisymmetric moment equations are provided before solving a system of equations describing the lateral-directional moment equations for a blunt body trimming at an angle of attack. Simplifying assumptions are made which allow the solution to the equations to be rearranged to relate the roll and yaw stability with sideslip angle to the frequency of oscillation of the vehicle body rates. The equations show that for a blunt body the roll and yaw rates are in phase and proportional to each other. The ratio of the rates is determined by the static stability coefficients and mass properties about those axes. A trajectory simulation is used to validate the static yaw stability parameter identification equation and a simple method of identifying the oscillation frequency from the body rates. The approach is shown to successfully extract the modeled yaw stability coefficient along a simulated Mars entry in agreement with data earlier analysis of MSL flight data.

Schoenenberger, Mark↗

NASA NTRS2013

Mars Science Laboratory Entry, Descent, and Landing Trajectory and Atmosphere Reconstruction

On August 5th 2012, The Mars Science Laboratory entry vehicle successfully entered Mars atmosphere and landed the Curiosity rover on its surface. A Kalman filter approach has been implemented to reconstruct the entry, descent, and landing trajectory based on all available data. The data sources considered in the Kalman filtering approach include the inertial measurement unit accelerations and angular rates, the terrain descent sensor, the measured landing site, orbit determination solutions for the initial conditions, and a new set of instrumentation for planetary entry reconstruction consisting of forebody pressure sensors, known as the Mars Entry Atmospheric Data System. These pressure measurements are unique for planetary entry, descent, and landing reconstruction as they enable a reconstruction of the freestream atmospheric conditions without any prior assumptions being made on the vehicle aerodynamics. Moreover, the processing of these pressure measurements in the Kalman filter approach enables the identification of atmospheric winds, which has not been accomplished in past planetary entry reconstructions. This separation of atmosphere and aerodynamics allows for aerodynamic model reconciliation and uncertainty quantification, which directly impacts future missions. This paper describes the mathematical formulation of the Kalman filtering approach, a summary of data sources and preprocessing activities, and results of the reconstruction.

Karlgaard, Christopher D.↗

NASA NTRS2013

Assessment of the Reconstructed Aerodynamics of the Mars Science Laboratory Entry Vehicle

On August 5, 2012, the Mars Science Laboratory entry vehicle successfully entered Mars atmosphere, flying a guided entry until parachute deploy. The Curiosity rover landed safely in Gale crater upon completion of the Entry Descent and Landing sequence. This paper compares the aerodynamics of the entry capsule extracted from onboard flight data, including Inertial Measurement Unit (IMU) accelerometer and rate gyro information, and heatshield surface pressure measurements. From the onboard data, static force and moment data has been extracted. This data is compared to preflight predictions. The information collected by MSL represents the most complete set of information collected during Mars entry to date. It allows the separation of aerodynamic performance from atmospheric conditions. The comparisons show the MSL aerodynamic characteristics have been identified and resolved to an accuracy better than the aerodynamic database uncertainties used in preflight simulations. A number of small anomalies have been identified and are discussed. This data will help revise aerodynamic databases for future missions and will guide computational fluid dynamics (CFD) development to improved prediction codes.

Schoenenberger, Mark↗

NASA NTRS2013

The Mars Science Laboratory (MSL) Entry, Descent And Landing Instrumentation (MEDLI): Hardware Performance and Data Reconstruction

The Mars Science Laboratory (MSL) Entry, Descent and Landing Instrumentation (MEDLI) hardware was a first-of-its-kind sensor system that gathered temperature and pressure readings on the MSL heatshield during Mars entry on August 6, 2012. MEDLI began as challenging instrumentation problem, and has been a model of collaboration across multiple NASA organizations. After the culmination of almost 6 years of effort, the sensors performed extremely well, collecting data from before atmospheric interface through parachute deploy. This paper will summarize the history of the MEDLI project and hardware development, including key lessons learned that can apply to future instrumentation efforts. MEDLI returned an unprecedented amount of high-quality engineering data from a Mars entry vehicle. We will present the performance of the 3 sensor types: pressure, temperature, and isotherm tracking, as well as the performance of the custom-built sensor support electronics. A key component throughout the MEDLI project has been the ground testing and analysis effort required to understand the returned flight data. Although data analysis is ongoing through 2013, this paper will reveal some of the early findings on the aerothermodynamic environment that MSL encountered at Mars, the response of the heatshield material to that heating environment, and the aerodynamic performance of the entry vehicle. The MEDLI data results promise to challenge our engineering assumptions and revolutionize the way we account for margins in entry vehicle design.

Little, Alan↗

NASA NTRS2013

Mars Entry Atmospheric Data System Trajectory Reconstruction Algorithms and Flight Results

The Mars Entry Atmospheric Data System is a part of the Mars Science Laboratory, Entry, Descent, and Landing Instrumentation project. These sensors are a system of seven pressure transducers linked to ports on the entry vehicle forebody to record the pressure distribution during atmospheric entry. These measured surface pressures are used to generate estimates of atmospheric quantities based on modeled surface pressure distributions. Specifically, angle of attack, angle of sideslip, dynamic pressure, Mach number, and freestream atmospheric properties are reconstructed from the measured pressures. Such data allows for the aerodynamics to become decoupled from the assumed atmospheric properties, allowing for enhanced trajectory reconstruction and performance analysis as well as an aerodynamic reconstruction, which has not been possible in past Mars entry reconstructions. This paper provides details of the data processing algorithms that are utilized for this purpose. The data processing algorithms include two approaches that have commonly been utilized in past planetary entry trajectory reconstruction, and a new approach for this application that makes use of the pressure measurements. The paper describes assessments of data quality and preprocessing, and results of the flight data reduction from atmospheric entry, which occurred on August 5th, 2012.

Karlgaard, Christopher D.↗

NASA NTRS2011

The Best Estimated Trajectory Analysis for Pad Abort One

I. Best Estimated Trajectory (BET) objective: a) Produce reconstructed trajectory of the PA-1 flight to understand vehicle dynamics and aid other post flight analyses. b) Leverage all measurement sources taken of vehicle during flight to produce the most accurate estimate of vehicle trajectory. c) Generate trajectory reconstructions of the Crew Module (CM), Launch Abort System (LAS), and Forward Bay Cover (FBC). II. BET analysis was started immediately following the PA-1 mission and was completed in September, 2010 a) Quick look version of BET released 5/25/2010: initial repackaging of SIGI data. b) Preliminary version of BET released 7/6/2010: first blended solution using available sources of external measurements. c) Final version of BET released 9/1/2010: final blended solution using all available sources of data.

Kutty, Prasad↗

NASA NTRS2010

The Range Safety Debris Catalog Analysis in Preparation for the Pad Abort One Flight Test

With each flight test a Range Safety Data Package is assembled to understand the potential consequences of various failure scenarios. Debris catalog analysis considers an overpressure failure of the Abort Motor and the resulting debris field created 1. Characterize debris fragments generated by failure: weight, shape, and area 2. Compute fragment ballistic coefficients 3. Compute fragment ejection velocities.

Kutty, Prasad↗