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Results for “atmospheric reconstruction”

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 19 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS1976

An investigation of the effects of mass loss, shape change and real gas aerodynamics on a Jovian atmospheric reconstruction experiment

A survey of the effects of mass loss, shape change and real-gas aerodynamics on a Jovian atmospheric reconstruction experiment is carried out. Techniques used to reconstruct atmospheric profiles from entry probe measurements are discussed and some of the parameters which affect their accuracy are identified. Trajectory analyses and real-gas, radiatively-coupled flow field analyses (which include the effects of mass loss and shape change) are carried out for several candidate probe configurations. From these analyses, uncertainties in the atmospheric reconstruction procedure are estimated. Finally, the prospects for reducing these uncertainties by optimizing probe configuration and by instrumentation of the probe heat shield to measure actual shape change are considered.

Walberg, G. D.↗
NASA NTRS2021

Mars Exploration Rovers EDL Trajectory and Atmosphere Reconstruction using NewSTEP

This document describes the trajectory and atmosphere reconstruction of the Mars Exploration Rovers (Spirit and Opportunity) Entry, Descent, and Landing using the New Statistical Trajectory Estimation Program. The approach utilizes a Kalman filter to blend inertial measurement unit data with initial conditions and radar altimetry to obtain the inertial trajectory of the entry vehicle. The nominal aerodynamic database is then used in combination with the sensed accelerations to obtain estimates of the atmosphere-relative state. The reconstructed atmosphere profile is then blended with pre-flight models to construct an estimate of the as-flown atmosphere.

EDL↗
NASA NTRS2019

Mars Phoenix EDL Trajectory and Atmosphere Reconstruction Using NewSTEP

This document describes the trajectory and atmosphere reconstruction of the Mars Phoenix Entry, Descent, and Landing using the New Statistical Trajectory Estimation Program. The approach utilizes a Kalman filter to blend inertial measurement unit data with initial conditions and radar altimetry to obtain the inertial trajectory of the entry vehicle. The nominal aerodynamic database is then used in combination with the sensed accelerations to obtain estimates of the atmosphere-relative state. The reconstructed atmosphere pro le is then blended with pre-flight models to construct an estimate of the as-flown atmosphere.

Karlgaard, Christopher D.↗
NASA NTRSDate not supplied

Mars InSight Entry, Descent, and Landing Trajectory and Atmosphere Reconstruction

The InSight mission landed on the surface of Mars on November 26th, 2018. The InSight system performance met all design requirements, although several performance metrics fell near the boundaries of the predictions. The peak deceleration was high, the overall timeline was short, and the landing site was uprange and crossrange from the target. This paper describes the reconstruction of the entry, descent, and landing trajectory and atmosphere. The approach utilizes a Kalman filter to blend sensor data to obtain the vehicle trajectory. The aerodynamic database is used in combination with the sensed accelerations to obtain estimates of the atmosphere-relative state, which in turn is used to derive the free-stream atmospheric conditions during entry, until the time of parachute deployment. The results indicate that the reconstructed atmosphere was approximately 1σbelow the preflight atmosphere. Analysis of the reconstructed vehicle attitude angles indicate that the aerodynamic lift was oriented downward at entry. The vehicle developed a roll rate during entry, which directed a component of the lift to the north. The low density and aerodynamic lift direction are determined to be the primary causes of the high deceleration, short timeline, and location of the landing site relative to the target.

Christopher D Karlgaard↗
NASA NTRS2020

Mars InSight Entry, Descent, and Landing Trajectory and Atmosphere Reconstruction

The InSight mission landed on the surface of Mars on November 26th, 2018. The InSight system performance met all design requirements, although several performance metrics fell near the boundaries of the predictions. The peak deceleration was high, the overall timeline was short, and the landing site was uprange and crossrange from the target. This paper describes the reconstruction of the entry, descent, and landing trajectory and atmosphere. The approach utilizes a Kalman filter to blend sensor data to obtain the vehicle trajectory. The aerodynamic database is used in combination with the sensed accelerations to obtain estimates of the atmosphere-relative state, which in turn is used to derive the free-stream atmospheric conditions during entry, until the time of parachute deployment. The results indicate that the reconstructed atmosphere was approximately 1σbelow the preflight atmosphere. Analysis of the reconstructed vehicle attitude angles indicate that the aerodynamic lift was oriented downward at entry. The vehicle developed a roll rate during entry, which directed a component of the lift to the north. The low density and aerodynamic lift direction are determined to be the primary causes of the high deceleration, short timeline, and location of the landing site relative to the target.

Christopher D Karlgaard↗
NASA NTRSDate not supplied

Mars Entry, Descent, and Landing Instrumentation 2 Trajectory, Aerodynamics, and Atmosphere Reconstruction

On February 18th, 2021, the Mars 2020 entry system successfully delivered the Perseverance rover to the surface of Mars at Jezero Crater. The entry capsule carried a set of instrumentation installed on the heat shield and backshell, named the Mars Entry, Descent, and Landing Instrumentation 2. The instruments include pressure transducers, thermocouples, heat flux gauges, and radiometers to measure the aerodynamic and aerothermodynamic performance of the entry vehicle. This paper describes the trajectory and atmosphere reconstruction results based on the pressure sensor measurements. The process uses a Kalman filter approach to estimate the freestream atmospheric properties from the pressure measurements combined with a model of the pressure distribution of the heatshield and other sensor inputs, including an inertial measurement unit and other on-board navigation sensors, and several external atmospheric observations. The results indicate upper altitude density was up to 150% higher than nominal, which is consistent with the observed early entry guidance start time. The density below 40 km was within 12% the pre-flight predictions. The reconstructed axial force coefficient was approximately 2% lower than the pre-flight prediction across the flight range.

Christopher D Karlgaard↗
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 NTRS1973

Linear filtering of ballistic-entry-probe data for atmospheric reconstruction.

A Kalman-Schmidt filter is used to estimate atmospheric and trajectory parameters for entry into the Venusian atmosphere. A significantly improved version of the Landing Trajectory Reconstruction (LTR) computer program, used to obtain the estimates is described. Major improvements involve precision and linearity control of numerical differencing, corrected perturbation modeling, and incorporation of a refractivity model. Important results show that gyroscopic data are not usable with LTR, that atmospheric properties are generally well estimated for altitudes less than 100 km, and that the two LTR modes of operation are complementary in performance.

Sabin, M. L.↗
NASA NTRS2003

Entry Trajectory and Atmosphere Reconstruction Methodologies for the Mars Exploration Rover Mission

The Mars Exploration Rover (MER) mission will land two landers on the surface of Mars, arriving in January 2004. Both landers will deliver the rovers to the surface by decelerating with the aid of an aeroshell, a supersonic parachute, retro-rockets, and air bags for safely landing on the surface. The reconstruction of the MER descent trajectory and atmosphere profile will be performed for all the phases from hypersonic flight through landing. A description of multiple methodologies for the flight reconstruction is presented from simple parameter identification methods through a statistical Kalman filter approach.

Desai, Prasun N.↗
NASA NTRS2012

Parametric 3D Atmospheric Reconstruction in Highly Variable Terrain with Recycled Monte Carlo Paths and an Adapted Bayesian Inference Engine

We describe a method for accelerating a 3D Monte Carlo forward radiative transfer model to the point where it can be used in a new kind of Bayesian retrieval framework. The remote sensing challenge is to detect and quantify a chemical effluent of a known absorbing gas produced by an industrial facility in a deep valley. The available data is a single low resolution noisy image of the scene in the near IR at an absorbing wavelength for the gas of interest. The detected sunlight has been multiply reflected by the variable terrain and/or scattered by an aerosol that is assumed partially known and partially unknown. We thus introduce a new class of remote sensing algorithms best described as "multi-pixel" techniques that call necessarily for a 3D radaitive transfer model (but demonstrated here in 2D); they can be added to conventional ones that exploit typically multi- or hyper-spectral data, sometimes with multi-angle capability, with or without information about polarization. The novel Bayesian inference methodology uses adaptively, with efficiency in mind, the fact that a Monte Carlo forward model has a known and controllable uncertainty depending on the number of sun-to-detector paths used.

Monte Carlo↗
NASA NTRS1992

The Orbiter Experiments (OEX) Program

The objective of the Orbiter Experiments (OEX) program is to obtain research quality flight data for the augmentation and advancement of space transportation technologies. This includes the validation and advancement of analytical theories and of ground-test methods and techniques. The following topics are discussed: aerothermodynamic design tool development and validation; the freestream environment; trajectory reconstruction; atmospheric reconstruction; the Shuttle Entry Air Data System (SEADS); the Shuttle Upper Atmosphere Mass Spectrometer (SUMS); and aerodynamic forces and moments. The discussion is presented in vugraph form.

Throckmorton, David A.↗
NASA NTRS2015

Entry Descent and Landing Workshop Proceedings: Mars2020 Entry, Descent, and Landing Instrumentation (MEDLI2): Project Overview - Volume 1

Aerothermal & TPS: a) Determine Forebody Aerothermal Heating. b) Determine In-depth TPS Temperature. c) Determine Backshell Aerothermal Environment. Aerodynamics and Atmosphere: a) Reconstruct Atmospheric Density, Winds, and Wind-Relative Attitude. b) Determine Hypersonic & Supersonic Aerodynamics Forces. c) Base Pressure Contribution to Drag.

Bose, Deepak↗
DOE OSTI2026

Reconstruction of atmospheric neutrinos in DUNE’s horizontal-drift far-detector module

This paper reports on the capabilities in reconstructing and identifying atmospheric neutrino interactions in one of the Deep Underground Neutrino Experiment’s (DUNE) far detector modules, a liquid argon time projection chamber (LArTPC) with horizontal drift (FD-HD) of ionization electrons. The reconstruction is based upon the workflow developed for DUNE’s long-baseline oscillation analysis, with some necessary machine-learning models’ retraining and the addition of features relevant only to atmospheric neutrinos such as the neutrino direction reconstruction. Where relevant, the impact of the detection of the charged particles of the hadronic system is emphasized, and comparisons are carried out between the case when lepton-only information is considered in the reconstruction (as is the case for many neutrino oscillation experiments), versus when all particles identified in the LArTPC were included. Three neutrino direction reconstruction methods have been developed and studied for the atmospheric analyses: using lepton-only information, using all reconstructed particles, and using only correlations from reconstructed hits. The results indicate that incorporating more than just lepton information significantly improves the resolution of both neutrino direction and energy reconstruction. The angle reconstruction algorithms developed in this work result in no strong dependence on particle direction for reconstruction efficiencies or neutrino flavor identification. This comprehensive review of the reconstruction of atmospheric neutrinos in DUNE’s FD-HD LArTPC is the first step towards developing a first neutrino oscillation sensitivity analysis, which will ready DUNE for its first measurements.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
NASA NTRS1982

Reconstruction of atmospheric pollutant concentrations from remote sensing data - An application of distributed parameter observer theory

The reconstruction of a concentration distribution from spatially averaged and noise-corrupted data is a central problem in processing atmospheric remote sensing data. Distributed parameter observer theory is used to develop reconstructibility conditions for distributed parameter systems having measurements typical of those in remote sensing. The relation of the reconstructibility condition to the stability of the distributed parameter observer is demonstrated. The theory is applied to a variety of remote sensing situations, and it is found that those in which concentrations are measured as a function of altitude satisfy the conditions of distributed state reconstructibility.

Koda, M.↗