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NASA NTRS2021

LiDAR-Based Map Relative Localization Performance Analysis for Landing on Europa

This paper presents preliminary simulations andanalyses done to assess the feasibility of performing Map RelativeLocalization (MRL) with the Europa Lander LiDAR beingdeveloped for the Europa Lander Pre-Phase A concept. MapRelative Localization is the process of determining the horizontalposition of a lander with respect to an onboard, a-priori map,by comparing the map to sensor observations of the terrain duringdeorbit, descent, and landing (DDL). Although kilometerscaleposition knowledge is commonly available during DDL,landing in hazard-rich environments requires position errors of100 m or less. Prior knowledge in the case of Europa Landerwill be visual and topographic maps collected by the upcomingEuropa Clipper mission. The Mars 2020 Lander Vision System(LVS) uses images from a camera to localize with respect tovisual maps. This technology, as well as a 3D imaging LiDAR indevelopment for hazard detection, is currently baselined for theEuropa Lander Pre-Phase A concept. This paper investigatesthe potential use of the hazard detection LiDAR to performMRL with respect to a 3D digital elevation model (DEM)provided by the Europa Clipper mission, as an alternative orbackup solution to passive optical MRL. Compared to passiveoptical MRL, one advantage of LiDAR-based localization isthat it is insensitive to lighting conditions, potentially relaxingrequirements on synchronizing map acquisition and landingtime of day. To analyze LiDAR based MRL performance,six representative terrains are synthetically up-sampled fromGalileo-derived maps of Europa to a resolution of 0.5 m/pxand covering an area of 4 km by 4 km. These maps are usedas ground-truth to generate simulated noisy a-priori onboardtopographic maps expected from Europa Clipper as well assimulated LiDAR DEMs generated at an altitude of 5 km duringEuropa Lander DDL. The simulated LiDAR DEM is matchedagainst the simulated map via 2D normalized cross-correlation,exploiting the accurately known spacecraft attitude to avoidthe need for more computationally intensive algorithms such asIterative Closest Point (ICP). Two sources of measurement errorare identified for analysis: 1) additive Gaussian noise in therange measurements from the Europa Lander LiDAR and theEuropa Clipper derived maps and 2) errors in the LiDAR DEMinduced by errors in the Europa Lander state estimate which isused to de-warp the LiDAR scan data into a DEM format. Weassess the effect of each of these types of errors independently onmatching performance as well as the overall performance whenall types of error are introduced. Additionally, we present theresult of a sensitivity study to terrain frequency content.

Trawny, Nikolas↗
NASA NTRSDate not supplied

Recent Advancements in the PATO Material Response Code

Introduction: Predicting the complicated multiphysics phenomena during atmospheric entry requires high-fidelity modeling tools to refine estimates of mission risks during entry. To this end, new capabilities are being added to the Porous-material Analysis Toolbox based on OpenFOAM (PATO). PATO is an open-source software for Computational Material Response (CMR) of reactive porous materials submitted to high-temperature environments. The objective of this work is to highlight current efforts to add to and improve upon the modeling capabilities of PATO. These include efforts to loosely couple PATO with other discipline specialized codes including hypersonic Computational Fluid Dynamics (CFD), to assess the interaction effects between pyrolysis gas blowing and the boundary layer, and Computational Solid Mechanics (CSM), to address modeling of mechanical erosion. Other refinements include surface phenomena modeling capabilities to address the effects of silicone-based coatings applied to the TPS during flight preparation, and a unified multiphase solver for a mixed porous-material and plain-fluid domain. Coupling CMR with CFD (CMR/CFD): A loose coupling between PATO and the Data Parallel Line Relaxation (DPLR) CFD code has been achieved by making use of a blowing boundary condition at the heatshield surface available in DPLR. Starting with heat flux estimates with no pyrolysis gas blowing at the surface, blowing gases are computed by the CMR and passed to the CFD such that aerothermal properties of the environment can be recomputed for a new CMR computation. This leads to an iterative process which is supplemented with an estimate of the radiative heat flux using the Nonequilibrium air radiation (NEQAIR) program. The entire iterative process is illustrated in Figure 1. This coupling strategy has been utilized in computing the MSL material response. The goal is to compare the coupled CMR/CFD results with material response results obtained using traditional blowing corrections. Coupling CMS with CMR: A mechanical erosion model is currently being implemented in PATO to account for the additional mass removal induced by high shear conditions. The modeling process at each timestep consists of updating the mechanical properties as a function of temperature and computing the stress tensor and displacement fields of the material. Then, a failure criteria model determines the regions in which the stress exceeds the ultimate strength values resulting in mesh movement to account for mass removal. This model allows the material response simulation to compute the recession due to both oxidation and shear-induced erosion. The model is demonstrated by computing material response of sphere-cone arc jet samples. Surface Modeling Capabilities: NuSil, a silicone-based coating, was sprayed onto the MSL and Mars 2020 heatshields to mitigate shedding of phenolic dust. To better understand the effects of the NuSil coating on the material response, a novel model has been implemented in PATO. In this model, the equilibrium of the charred NuSil surface is modeled as pure silica, and a constant offset, inspired by the classical spallation model, is added to the the char blowing rate and wall enthalpy to reproduce HyMETS experimental results. The model has also been used to estimate the 3D material response of the MSL heatshield. Unified Solver: In addition to the iterative loose coupling approach mentioned above, a multiphase unified solver is being developed to couple the environment (plain-fluid phase) and the porous-material phase. The solver is based on the volume averaged conservation of mass, momentum, and energy for the macroscale with closure models which include microscale effects through effective physicochemical properties. The unified solver has been used to compute flow through a porous plug and solve the Beavers and Joseph problem. Since the strong coupling between phases is inherent to this solver, modeling assumptions present in other coupling methods of material response are mitigated. This strategy also makes it feasible to capture the competition between surface and volume ablation in the same computational domain, which is usually not possible with other coupling approaches.

Material Response↗
NASA NTRSDate not supplied

Thermal Protection Materials and Systems at NASA Ames Research Center

Thermal Protection Systems (TPS) are critical for enabling NASA missions involving high-speed atmospheric flight where the entries usually include descending into the atmosphere followed by a trajectory that aims to burn off energy and result in a controlled landing. NASA Ames focuses on qualifying and certifying TPS for current missions, sustaining TPS for future missions, and developing new TPS for upcoming missions where a heritage solution is not viable. More recently there is also a focus on advancing and transferring technologies that can benefit both commercial and government space needs.Developing mature thermal protection systems is a lengthy process involving advanced tools, extensive research, and testing. Design and analysis tools are used to predict aerothermal environments, aid the design of test and flight hardware, and support the testing for the thermal/mechanical response of thermal protection systems. More recently, advances in computational methods help reduce the time and cost of technological advances, aid in optimized material architecture design, and improve material properties and performance. While high-enthalpy testing that simulates the conditions of space flight remains essential for the evaluation and development of TPS materials, computational tools are already showing promise in reducing the need for widespread testing and can help fast-trackthe design cycle.With the exploration of new destinations EDL instrumentation remains an important element of the heatshield and NASA Ames and partners have developed and delivered instrumentation flight hardware in support of recent Mars missions,including Mars Science Lab (MSL) and Mars 2020 (M2020),as well as Artemis Orion. Sensors installed on the heatshield and backshell of spacecraft provide coveted information about the aerodynamic and aerothermal environment during entry.Overthe years NASA Ames has brought several reusable and ablative TPS materials to a level of readiness to hand off to missions and the Thermal Protection Materials branch continues to serve as a TPS steward for the agency.

Thermal protection materials↗
NASA NTRSDate not supplied

Recent Advancements in the PATO Material Response Code

Introduction: Predicting the complicated multiphysics phenomena during atmospheric entry requires high-fidelity modeling tools to refine estimates of mission risks during entry. To this end, new capabilities are being added to the Porous-material Analysis Toolbox based on OpenFOAM (PATO) [1,2,3]. PATO is an open-source software for Computational Material Response (CMR) of reactive porous materials submitted to high-temperature environments. The objective of this work is to highlight current efforts to add to and improve upon the modeling capabilities of PATO. These include efforts to loosely couple PATO with other discipline specialized codes including hypersonic Computational Fluid Dynamics (CFD), to assess the interaction effects between pyrolysis gas blowing and the boundary layer, and Computational Solid Mechanics (CSM), to address modeling of mechanical erosion. Other refinements include surface phenomena modeling capabilities to address the effects of silicone-based coatings applied to the TPS during flight preparation, and a unified multiphase solver for a mixed porous-material and plain-fluid domain. Coupling CMR with CFD (CMR/CFD): A loose coupling between PATO and the Data Parallel Line Relaxation (DPLR) [4] CFD code has been achieved by making use of a blowing boundary condition at the heatshield surface available in DPLR. Starting with heat flux estimates with no pyrolysis gas blowing at the surface, blowing gases are computed by the CMR and passed to the CFD such that aerothermal properties of the environment can be recomputed for a new CMR computation. This leads to an iterative process which is supplemented with an estimate of the radiative heat flux using the Nonequilibrium air radiation (NEQAIR) [5] program. The entire iterative process is illustrated in Figure 1. This coupling strategy has been utilized in computing the MSL material response. The goal is to compare the coupled CMR/CFD results with material response results obtained using traditional blowing corrections. Coupling CMS with CMR: A mechanical erosion model is currently being implemented in PATO to account for the additional mass removal induced by high shear conditions. The modeling process at each timestep consists of updating the mechanical properties as a function of temperature and computing the stress tensor and displacement fields of the material. Then, a failure criteria model determines the regions in which the stress exceeds the ultimate strength values resulting in mesh movement to account for mass removal. This model allows the material response simulation to compute the recession due to both oxidation and shear-induced erosion. The model is demonstrated by computing material response of sphere-cone arc jet samples. Surface Modeling Capabilities: NuSil, a silicone-based coating, was sprayed onto the MSL and Mars 2020 heatshields to mitigate shedding of phenolic dust. To better understand the effects of the NuSil coating on the material response, a novel model has been implemented in PATO. In this model, the equilibrium of the charred NuSil surface is modeled as pure silica, and a constant offset, inspired by the classical spallation model, is added to the the char blowing rate and wall enthalpy to reproduce HyMETS experimental results. The model has also been used to estimate the 3D material response of the MSL heatshield [6]. Unified Solver: In addition to the iterative loose coupling approach mentioned above, a multiphase unified solver is being developed to couple the environment (plain-fluid phase) and the porous-material phase. The solver is based on the volume averaged conservation of mass, momentum, and energy for the macroscale with closure models which include microscale effects through effective physicochemical properties. The unified solver has been used to compute flow through a porous plug and solve the Beavers and Joseph problem [7]. Since the strong coupling between phases is inherent to this solver, modeling assumptions present in other coupling methods of material response are mitigated. This strategy also makes it feasible to capture the competition between surface and volume ablation in the same computational domain, which is usually not possible with other coupling approaches.

Thermal Protection Systems↗
NASA NTRSDate not supplied

Characterizing Porous and Nonporous Phenolic Resins from Molecular Dynamics Simulations

Phenolic resins are an important component of many ablative heat shield materials, which protect spacecrafts from the extreme temperatures reached during atmospheric entry. Examples include the high-density Heritage Carbon Phenolic (HCP) used in the Pioneer-Venus and Galileo missions, as well as the low-density Phenolic Impregnated Carbon Ablator (PICA) used in the Mars Science Laboratory and Mars 2020 missions. Additionally, recent developments within NASA have produced the mid-density Heatshield for Extreme Entry Environment Technology (HEEET) and its derivative 3D Woven Mid-Density Carbon Phenolic (3MDCP). Unlike the nonporous phenolic in HCP, PICA and HEEET/3MDCP are fabricated by infusing preforms with diluted phenolic formulations to obtain a lower density porous matrix. Despite the importance of the phenolic phase to the material response during entry, the variation in properties of porous and nonporous phenolic is not well understood. Here, we present an investigation of porous and nonporous phenolic resins using molecular dynamics (MD) simulations. Resin cure is mimicked in the simulations through the inclusion of representative reaction templates to generate accurate models of the complex crosslinked structures. To create porous models, explicit solvent molecules are included during the cure simulations. We observe nanoscale separation of the phenolic and solvent phases, which results in significant differences in the final structures of porous and nonporous models. In addition to a quantitative assessment of the network structure and porosity, we elucidate the effects of the phenolic formulation on the final material properties. These results are compared with experimental data as appropriate.

phenolic↗
NASA NTRSDate not supplied

Coupling CFD and Material Response for Analysis of Mars Entry

In computing the response of an ablating thermal protection system during atmospheric entry, the aerothermal environment and material response are generally computed separately with a blowing correction term in the material response model to account for the blowing of char and pyrolysis gases [1]. In this work, we apply a coupled approach in which pyrolysis blowing gases, computed in the PATO material response code [2], are used with a blowing boundary condition in the DPLR hypersonic CFD code [3]. This leads to an iterative method in which blowing products from PATO are input into DPLR to update surface heating estimates. The full iterative method, with the addition of radiative heating estimates using the NEQAIR radiation solver [4], is shown in Fig. 1. The method is demonstrated on a sphere case with the environment and material properties based on the Mars Science Laboratory entry. Future work includes utilizing this method in computing full 3D material response during the Mars 2020 entry.

Heat Transfer↗
NASA NTRSDate not supplied

Coupling CFD and Material Response for Analysis of Mars Entry

In computing the response of an ablating thermal protection system during atmospheric entry, the aerothermal environment and material response are generally computed separately with a blowing correction term in the material response model to account for the blowing of char and pyrolysis gases. In this work, we apply a coupled approach in which pyrolysis blowing gases, computed in the PATO material response code, are used with a blowing boundary condition in the DPLR hypersonic CFD code. This leads to an iterative method in which blowing products from PATO are input into DPLR to update surface heating estimates. The full iterative method, with the addition of radiative heating estimates using the NEQAIR radiation solver, is shown in Fig. 1. The method is demonstrated on a sphere case with the environment and material properties based on the Mars Science Laboratory entry. Future work includes utilizing this method in computing full 3D material response during the Mars 2020 entry.

Ablation↗
NASA NTRSDate not supplied

Development of Advanced Conformal and Soft Pica for Future Nasa Missions and Commercial Space

Phenolic Impregnated Carbon Ablator (PICA) is a low-density ablator that has been used as the planetary entry heatshield for several NASA missions since the late 90’s. Its low density and efficient performance characteristics have proven effective for use from Discovery to Flag-ship class missions, from Sample Return missions such as Stardust, OSIRIS-REx to large Mars Lander missions such as MSL and Mars 2020. Continued development of a more mass efficient and compliant versions of PICA that use a carbon felt as the substrate will be presented. The felt based versions of PICA known as Conformal PICA (C-PICA) and Soft PICA (S-PICA), are very comparable in terms of peak heat-flux capabilities compared to standard PICA. The lower density and of C-PICA and S-PICA further show a much higher thermal protection efficiency and hence more mass savings. The compliant nature of these materials allows for use on a wide variety of substrates and therefore makes it very attractive for commercial low earth orbit missions as well as NASA’s aerocapture missions to Ice Giants. NASA is currently working with several commercial partners (Varda and Inversion Space) to Technology Transfer C/S-PICA variants for commercial LEO missions. Thermal, mechanical, and representative environment arc-jet tests have been conducted comparing the performance of Conformal and Soft-PICA materials.

Matthew J Gasch↗
NASA NTRSDate not supplied

Stratigraphic Relationships of the Western Delta and Crater Floor in Jezero Crater From Rimfax Gpr Observations.

One of the most fundamental questions about the geology of Jezero prior to the arrival of Mars 2020 Perseverance rover was the relative sequence of emplacement of the western delta and the adjacent crater floor terrain. Based on orbital evidence, some authors favored delta formation to post-date crater floor emplacement, though crater floor material appears to exhibit embaying relationships in other areas. An older crater floor would also be inconsistent with the crater floor material consisting of lake or eroded delta sediments, which would be syn- or post-depositional with the delta.

P. S. Russell↗
NASA NTRSDate not supplied

Sedimentology and Stratigraphy of the Lower Delta Sequence, Jezero Crater, Mars.

In April 2022, the Mars 2020 Perseverance rover arrived at the base of the ancient delta in Jezero crater after completing the first year of its mission exploring and sampling aqueously altered igneous rocks of the present-day crater floor. Perseverance then spent ~200 sols exploring the lower ~25 m of rock exposed within the eastern scarp of the Jezero delta, a sedimentary sequence informally named the ‘Shenandoah’ formation. This study describes the sedimentology and stratigraphy of the Shenandoah formation explored by Perseverance at two sections—'Cape Nukshak’ and ‘Hawksbill Gap’—including a description, interpretation, and depositional framework for the facies that comprise it.

K. M. Stack↗
NASA NTRS2022

Visualizing Multi-process CPU Utilization using CUSP

The CPU Utilization Statistics Plotter (CUSP) tool automates the interpretation of detailed CPU Utilization trace data and statistics. It puts you on the cusp of understanding how CPU resources are split among the many parallel components of a software system.CUSP combines time-sampled CPU utilization numbers and Event Log annotations to generate human-readable plots and tables. It automatically splits up large CPU usage log files around interesting events, determines and highlights just the tasks of primary relevance by evaluating their changing contribution to each plot's total CPU usage, automatically eliminates irrelevant tasks, provides context by labeling plots with names and durations of all active commands, and uses consistent color-coding to enable quick visual comparison across multiple plots.CUSP has been used to process CPU Utilization trace logs on the Mars Science Laboratory and the Mars 2020 Rover missions during flight software development and Flight Operations on the Martian surface since December 2013.

Maimone, Mark W↗
NASA NTRSDate not supplied

Development of an Optical Model for the MEDLI2 Radiometer

We present an optical model of the MEDLI2 radiometer, which was flown onboard the Mars 2020 vehicle during atmospheric entry on February 18, 2021. The proposed model takes into account the radiometer geometry and optical phenomena such as reflection, refraction, and absorption to estimate the signal loss inherent in the design of the radiometer. The model serves as a filter, which can be used to convert predicted total radiative heat fluxes on the radiometer window into predicted measured heat fluxes, enabling more accurate comparisons of the radiometer flight data with predicted radiometer measurements. Optical properties of the radiometer’s sapphire window are inferred from spectral transmissivity measurements. A modified Lorentz Oscillator Model is used to represent the dielectric function of the window and is fit to the transmission data. The resulting optical model of the radiometer is validated against experimental data used to measure the dependence of the radiometer output voltage on the incident angle of the light impinging on it. Comparison of predicted radiometer measurements with the MEDLI2 flight data show good agreement between the predicted and measured peak heat fluxes, though offset at different times. A linear increase in the signal loss due to radiometer optics alone is also demonstrated, suggesting that the changing shock angle over the course of the trajectory impacts the signal loss.

MEDLI2↗
NASA NTRS2022

Multi-Mission Terrain Classifier for Safe Rover Navigation and Automated Science

We previously presented Soil Property and Object Classification (SPOC), a machine learning-based terrain classifier for Mars rovers, for automatically segmenting rover images by its surface type such as sand and bedrock. This paper presents a number of practical improvements to pave the way for potential future onboard deployment. First, we achieved 97.0% overall pixel accuracy, evaluated against the classification generated by human experts on images from Mars Science Laboratory (MSL) missions. The substantial increase in accuracy was primarily enabled by the sheer volume of data used for training; we created a new large-scale dataset of Martian terrain labels, namely AI4Mars, which contains more than 400k labels contributed by citizen scientists for 50k images taken by the Mars Exploration Rovers (MER) and Mars Science Laboratory (MSL) rover. Second, we demonstrated that SPOC can quickly adapt to a new mission landed on a previously unseen site. Specifically, we pretrained a model with MER and MSL data from the AI4Mars dataset and then adapted to the Mars 2020 Rover (M2020) by feeding a small volume of data between Sol 0 and 157; the adapted model was tested on Sol 200-203 and resulted in 84.2% overall pixel accuracy and 93.4% reliability (recall) for detecting sand, the most concerning class for rover’s traversability. Third, we found that pretraining can substantially mitigate the decline of accuracy over time. We showed that the performance of a SPOC model pretrained with the ImageNet dataset and then trained by MSL images only up to Sol 390 remains comparable to a model trained by images up to Sol 1689 on the test data after Sol 1689. Fourth, we reimplemented SPOC with a light-weight convolutional neural network (CNN), MobileNetV2, which typically runs within tens of milliseconds (ms) on mobile processors such as Qualcomm’s Snapdragon. Finally, we released the AI4Mars dataset to the public to encourage open innovation.

Ono, Masahiro↗
NASA NTRS2021

Assessing Ceres’ Past and Current Habitability

Dwarf planet Ceres is a compelling target as an evolved ocean world with, at least, regional brine reservoirs and potentially ongoing geological activity. Situated in the Main Belt of asteroids, Ceres is the most water-rich body in the inner solar system (in relative abundance) and is accessible enough for a sample return with the resources of a typical medium-class (New Frontiers) NASA mission. NASA’s Dawn mission at Ceres revealed the presence of liquid, brine-driven activity, organic matter, and a rich salt chemistry. With this evidence, the overarching goals of the mission concept presented herein are to quantify Ceres’ current habitability potential and origin. A sample return from young evaporite deposits in Occator crater offers greater science return than an in situ exploration mission by enabling high-resolution analysis of (1) organic matter expected from terrestrial and chondritic analogs that are trapped in salt minerals and (2) isotopes of refractory elements for a similar cost and less science risk. The sample return concept would be executed with a single flight system due to Ceres’ relative proximity to Earth and low gravity. Solar electric propulsion was identified as the most cost-effective approach for getting to Ceres and back. De-orbiting, landing, and takeoff are performed with a throttleable monopropellant hydrazine system. The solar arrays are stowed prior to landing and takeoff. Sample acquisition builds on the pneumatic system designed by Honeybee Robotics. The sample return mission concept relies on the availability of key technologies: an enhanced landing vision system leveraging investments from Mars 2020; retractable/redeployable solar arrays, which have been demonstrated on the International Space Station but not at Ceres’ gravity; and an emerging design from upcoming missions for sample transfer from the pneumatic sampling system to the sample return capsule. Return of a sample of mass ~100 g from Ceres, maintained at ≤ -20°C, is without precedent for any currently advocated Ocean World mission, enabling a vast range of experimental techniques back on Earth with sensitivities and accuracies far beyond those feasible with in situ instruments. A sample of this size also enables analyses to benefit from techniques that will become available in the future.

Casillas, Raul Polit↗
NASA NTRS2021

Assessment of M2020 Terrain Relative Landing Accuracy: Flight Performance vs Predicts

Terrain Relative Navigation (TRN) was a critical enabling Entry, Descent, and Landing (EDL) technology that enabled Mars 2020 mission Perseverance rover to land at Jezero crater. TRN pro-vides real-time, autonomous, map-relative position determination and generates a landing target based on a priori knowledge of hazards. The required performance for TRN was to land within 60m of the selected target. The required 60m was sub-allocated to various error sources in three major categories: targeting error, knowledge error, and control error. The targeting error is the error in selecting an appropriate landing target and the knowledge of the target on the surface. It includes the Lander Vision System (LVS) position localization with respect the ground, the synchronization between the Lander Vision System measurement and the main Navigation filter, and errors associated with the LVS Reference Map and Safe Target Selec-tion (STS). The knowledge error is the contribution of knowledge growth from the synchronization with LVS to touchdown. The control error encompasses how accurately the system could stay on the desired reference trajectory. The TRN error budget uses a combination of analysis, simulation, and hardware test-ing results to bound the various error contributions obtained during the verification and validation process. This paper first presents a description the TRN system, focusing on the architecture of LVS and STS. The paper then gives detailed overview of the TRN error budget, with a description of the major error contribu-tions in each of the three categories. Next, the paper gives the results for three versions of the error budget, pre-launch, in-flight pre-landing, and post-landing. The paper compares the pre-flight analysis, the pre-landing analysis using in-flight data during cruise, to the post-landing analysis of the TRN performance. Pre-landing analysis best estimate of the landing performance was 33m, compared to the 60m require-ment. Post-landing analysis estimated a landing accuracy of 8.53m or better, much better than the 33m pre-landing estimate. The actual post-landing imagery calculated the distance of the rover to the targeted location to be 5m. The post-landing analysis closely bounds the image-based assessment of landing accu-racy, indicating the success of the error budget architecture in bounding the landing accuracy, as well as the fidelity of the simulations used to model and predict performance.

Chen, Allen↗
NASA NTRSDate not supplied

Atmospheric Entry Heat Flux Sensor Calibration and Flight Data Analysis

- Recent NASA missions have included total heat flux sensors (THFS) embedded in the thermal protection system (TPS) to measure the combined convective and radiative heating during atmospheric entry. These measurements are key to fundamental entry science and mission design. - The THFSs for the Mars Entry, Descent, and Landing Instrumentation 2 (MEDLI2) sensor suite on the Mars 2020 entry vehicle and the Low-Earth Orbit Flight Test of an Inflatable Decelerator (LOFTID) technology demonstration mission were passively cooled Schmidt–Boelter gauges. - As presented at IPPW 2021, THFS calibration is notoriously difficult and includes several sources of measurement uncertainty [1]. - Recent work has been conducted to understand and quantify the measurement uncertainty in the MEDLI2 and LOFTID Schmidt-Boelter THFSs.

R. A. Miller↗
NASA NTRSDate not supplied

Coupled Material Response Simulations of Dragonfly Capsule and DrEAM Reconstruction

Icarus is a three-dimensional, unstructured, finite-volume material response solver developed at NASA Ames Research Center and has been recently used to analyze the material response of the Dragonfly capsule for a variety of problems. Since the Dragonfly capsule will be instrumented in a similar manner to the Mars 2020 and MSL capsules, it is important to assess how our current simulation tools can aid in understanding Dragonfly Entry Aerosciences Measurements (DrEAM). In this presentation, the Ares multi-physics tool that couples Icarus to the flow and radiation physics of the aerothermal environment will be used to better understand how modeling sensitivities might affect environment reconstructions and our understanding of measured data. Ares couples Icarus to the US3D flow solver and NERO, a reduced-order, finite-volume radiation transport solver and uses a customized time-scale management to enable coupled simulations for a large portion of the Dragonfly trajectory. As a result of the coupling, a more accurate and consistent assessment of modelling sensitivities to aerothermal reconstruction can be assessed. For example, the radiometer is sensitive to the quantity of CN in the flow, which is a byproduct of the free-stream methane but also the pyrolysis gas products injected into the boundary layer due to ablation of the heatshield. Ares will be used to conduct a simulation of the full Dragonfly capsule for 50 seconds of the trajectory. The different aerothermal and material response models will be discussed and the key results will be presented in terms of the simulated thermocouple and radiometer measurements on the backshell.

Ablation↗
NASA NTRSDate not supplied

Hybrid Flush and Synthetic Air Data Filter for Entry Vehicle Atmospheric State Estimation

A hybrid flush/synthetic air data sensing filter utilizing Kalman-Schmidt and Rach-Tung-Striebel smoothers is developed to obtain entry vehicle atmosphere estimates. The filter/smoother blends information from pressure sensors distributed on the heatshield with measurements of the vehicle aerodynamic forces and moments computed from mass properties and inertial measurement unit data, and prior estimates of the atmosphere. The filter produces estimates of the atmospheric conditions along the entry trajectory, and systematic error estimates to reconcile differences between the pressure and aerodynamic data sources. The filter is applied to data acquired during the Mars Science Laboratory and Mars 2020 entry, descent, and landing at Gale crater and at Jezero crater, respectively. The results show that the hybrid filter produces estimates of the freestream flight condition with lower uncertainty than either the flush or synthetic air data algorithms. The filter accomplishes this result by incorporating additional data and computing estimates of systematic error parameters in the pressure data and the aerodynamic model to further reduce the uncertainties.

Christopher D. Karlgaard↗