Results for “Puma” — Page 4

NASA NTRSDate not supplied

Updates on the Predictive Materials Modeling Software Tools

Updates on NASA‘s efforts to build a Predictive Material Modeling (PMM) framework from the micro-scale to the macro-scale are presented in this abstract. The PMM effort is part of the Entry Systems Modeling (ESM) project under NASA’s Game Changing Development (GCD) program. To reduce the need for extensive testing and accelerate the design cycle process, ESM is developing simulation and modeling tools that enable the characterization of the properties of thermal protection materials and their response to extremely hot plasma. The Porous Microstructure Analysis (PuMA) software has been developed to compute effective material properties and perform material response simulations on digitized microstructures of porous media. PuMA is able to import three-dimensional digital images obtained from X-ray microtomography or to generate artificial microstructures that mimic real materials. PuMA also provides a module for interactive 3D visualizations. Version 3, which was recently released as open-source, includes modules to compute simple morphological properties such as porosity, volume fractions, pore diameter, and specific surface area. Additional capabilities include the determination of effective thermal and electrical conductivity (both radiative and solid conduction - including the ability to simulate local anisotropy for the latter); effective diffusivity and tortuosity from the continuum to the rarefied regime; techniques to determine the local material orientation, as well as mechanical properties (elasticity coefficients), and permeability. Computed properties are then used to inform a macro-scale material response model, such as those implemented in the Porous material Analysis Toolbox based on OpenFOAM (PATO) software developed within ESM. The computational model in PATO is a generic heat and mass transfer model for porous reactive materials containing several solid phases and a single gas phase. The detailed chemical interactions occurring between the solid phases and the gas phase are modeled at the pore scale, assuming Local Thermal Equilibrium. Recent efforts include the development of a mechanical erosion model as well as a unified model allowing an intrinsic coupling between fluid and material. Comparison to flight data (Mars Science Laboratory [MSL] Entry Descent and Landing Instrument [MEDLI] and Mars 2020 MEDLI2) is critical in order to validate these computational tools. Examples of ablative material response using the code will be presented, including 3D simulations of the full-scale heatshield of the MSL capsule. The simulations demonstrated the ability of the modern material response code, PATO, to handle the material response of geometrically complex and large domains through the use of massively parallel computations.

material modeling↗

NASA NTRSDate not supplied

In-situ Imaging of Pyrolyzing Aerospace Materials

Tracking morphological changes of materials during heating is crucial to understand its response in fire protection, biofuel production, thermal protection systems (TPS) for hypersonic flight. As materials are heated, they undergo physical and chemical changes due to water loss, stretching or shrinking, pyrolysis and chemical reactions in the ambient environment. The effects of these changes can have a profound impact on the material’s performance, indicated by changes in on the porosity and volume. While materials such as wood shrink as they pyrolyze and lose mass, others swell due to their inherent characteristics when exposed to heat [1]. This study focuses on experiments conducted at the Advanced Light Source (ALS) beamline 8.3.2, where in situ micro-computed tomography (µ-CT) is performed on materials as they are being pyrolyzed. Through in situ µ-CT, the change in total volume and porosity can be obtained in real-time, allowing for better understanding of the underlying thermophysical and chemical processes as a function of temperature. This study also focuses on the implementation of the Porous Microstructure Analysis software (PuMA) [2] to obtain thermal conductivity, permeability, and other properties of the material from the 3D tomographies. The information gained from these tomographies will supplement microscale model development of material morphological change and will aid macroscale modeling for high-temperature applications. For this study, Room Temperature Vulcanizing silicone (RTV) [3-5] is heated from room temperature to 1000°C using an infrared lamp heating system, and tomographies are continuously collected as the sample is heated. The tomographies are then segmented to obtain solid and void phases, from which estimates of pore size, porosity and total volume are extracted as a function of temperature. PuMA is deployed on the segmented tomographies to obtain thermal conductivity, permeability, and other properties as a function of temperature. Preliminary results show that RTV first intumesces (swells) as pyrolysis begins, due to build-up of pyrolysis gases in closed pores, and then shrinks significantly as more open pores are formed and the pyrolysis gases outgas. Pore network visualization of the tomographies using OpenPNM [6] showed the increase in pore connectivity with increase in temperature. Future work will focus on using PuMA to obtain macroscopic properties of RTV as a function of temperature.

Tomography↗

NASA NTRSDate not supplied

Investigation of the effect of etch pits on the material properties of carbon fiber structures

It is well known that etch pits are formed on carbon surfaces during their consumption in reactive gas environments such as during ablation of carbon-based thermal protection system (TPS) materials. These pits start out from atomic defects on the carbon surface, grow in size and then ultimately lead to the complete removal of the solid carbon material [1, 2]. However, the effect of such etch pits on the material properties of carbon ablators such as FiberForm are poorly understood, as the maximum size of pits are on the order of microns in size, which makes them hard to observe experimentally. Hence, we have developed a module within the Porous Microstructure Analysis code PuMA [3] that can generate etch pits on an arbitrary material surface, with a prescribed distribution of pit size and density. Figure 1 shows a FiberForm sample with artificially generated pits of varying radii and pit density. We use this newly developed module to calculate material properties of FiberForm, which is the base material for one of the most commonly used TPS materials - Phenolic Impregnated Carbon Ablator (PICA). The detailed microstructure of FiberForm in PuMA will either be generated synthetically or obtained from X-ray microtomography [4]. Our simulations show that material properties such as the thermal conductivity and tortuosity decrease with increasing degree of pitting. This will be helpful to more accurately predict the degradation of carbon-based TPS during ablation, and furthermore may allow us to identify previously unknown TPS failure modes due to pitting.

PuMA↗

NASA NTRSDate not supplied

Investigation of the Effect of Etch Pits on the Material Properties of Carbon Fiber Structures

It is well known that etch pits are formed on carbon surfaces during their consumption in reactive gas environments such as during ablation of carbon-based thermal protection system (TPS) materials. These pits start out from atomic defects on the carbon surface, grow in size and then ultimately lead to the complete removal of the solid carbon material. However, the effect of such etch pits on the material properties of carbon ablators such as FiberForm are poorly understood, as the maximum size of pits are on the order of microns in size, which makes them hard to observe experimentally. Hence, we have developed a module within the Porous Microstructure Analysis code PuMA that can generate etch pits on an arbitrary material surface, with a prescribed distribution of pit size and density. We use this newly developed module to calculate material properties of FiberForm, which is the base material for one of the most commonly used TPS materials - Phenolic Impregnated Carbon Ablator (PICA). The detailed microstructure of FiberForm in PuMA will either be generated synthetically or obtained from X-ray microtomography. Our simulations show that material properties such as the thermal conductivity and tortuosity decrease with increasing degree of pitting. This will be helpful to more accurately predict the degradation of carbon-based TPS during ablation, and furthermore may allow us to identify previously unknown TPS failure modes due to pitting.

PuMA↗

NASA NTRSDate not supplied

Boundary-Layer Flow Simulations Over Ablating Woven Thermal Protection System Material

Spallation is the mechanical removal of small chunks of material gets removed typically due to high shear conditions of the flow field. This reduces the ability of the thermal protection system (TPS) material to protect the spacecraft as well as cause turbulence in the flow causing higher heating rates. In this work, we focus on the material removal through ablation and high shear flow within the boundary layer region of woven TPS material. Woven TPS (WTPS) material is the latest class of material developed by NASA, to be used within the next generation of space flights. They are complex interlocked weaves designed to create a rigid structure that is highly resistant to heat and can be easily designed and tailored for a wide variety of entry environments. Due to material removal resulting from chemical degradation, the structural integrity of TPS material is affected. Spallation occurs when this structurally compromised material is exposed to the high shear flow conditions within the boundary layer. In order to understand the spallation mechanism within WTPS material, we first perform the material removal simulations which occur primarily through oxidation to obtain the microstructure at various stages of degradation. These simulations are performed using the Porous Microstructure Analysis (PuMA) software developed at NASA Ames. The micro-structure geometry used within these simulations were generated artificially to be similar to the 3D weave architecture of MSR-EEV (Mars Sample Return - Earth Entry Vehicle). The various eroded TPS micro-structures are then subjected to the boundary layer flow conditions to obtain critical surface quantities which contribute to the structural failure mechanism such as heat flux, pressure, and shear stress. The direct simulation Monte Carlo (DSMC) methodology is used to perform these simulations in order to accurately capture the strong gradients within the high-temperature boundary layer flow over the intricate geometry of WTPS material. The boundary layer profile is directly taken from the Computational Fluid Dynamics (CFD) simulation and provided as boundary conditions to the DSMC inlet and outlet. Further, the variation of these properties as the microstructure undergoes changes due to oxidation is also investigated. Finally, these quantities are used as input in PuMA to understand the material expansion/compression and strain within the woven TPS geometry and help in developing a comprehensive spallation and structure failure model.

microstructure↗

NASA NTRS2023

Importance of Ice Nucleation and Precipitation on Climate With the Parameterization of Unified Microphysics Across Scales Version 1 (PUMASv1)

Cloud microphysics is critical for weather and climate prediction. In this work, we document updates and corrections to the cloud microphysical scheme used in the Community Earth System Model (CESM) and other models. These updates include a new nomenclature for the scheme, now called Parameterization of Unified Microphysics Across Scales (PUMAS), and the ability to run the scheme on graphics processing units (GPUs). The main science changes include refactoring an ice number limiter and associated changes to ice nucleation, adding vapor deposition onto snow, and introducing an implicit numerical treatment for sedimentation. We also detail the improvements in computational performance that can be achieved with GPU acceleration. We then show the impact of these scheme changes on the (a) mean state climate, (b) cloud feedback response to warming, and (c) aerosol forcing. We find that corrections are needed to the immersion freezing parameterization and that ice nucleation has important impacts on climate. We also find that the revised scheme produces less cloud liquid and ice but that this can be adjusted by changing the loss process for cloud liquid (autoconversion). Furthermore, there are few discernible effects of the PUMAS changes on cloud feedbacks but some reductions in the magnitude of aerosol–cloud interactions (ACIs). Small cloud feedback changes appear to be related to the implicit sedimentation scheme, with a number of factors affecting ACIs.

Clouds↗

NASA NTRSDate not supplied

Boundary-Layer Flow Simulations Over Ablating Woven Thermal Protection System Material

Spallation is the mechanical removal of small chunks of material gets removed typically due to high shear conditions of the flow field. This reduces the ability of the thermal protection system (TPS) material to protect the spacecraft as well as cause turbulence in the flow causing higher heating rates. In this work, we focus on the material removal through ablation and high shear flow within the boundary layer region of woven TPS material. Woven TPS (WTPS) material is the latest class of material developed by NASA, to be used within the next generation of space flights. They are complex interlocked weaves designed to create a rigid structure that is highly resistant to heat and can be easily designed and tailored for a wide variety of entry environments. Due to material removal resulting from chemical degradation, the structural integrity of TPS material is affected. Spallation occurs when this structurally compromised material is exposed to the high shear flow conditions within the boundary layer. In order to understand the spallation mechanism within WTPS material, we first perform the material removal simulations which occur primarily through oxidation to obtain the microstructure at various stages of degradation. These simulations are performed using the Porous Microstructure Analysis (PuMA) software developed at NASA Ames. The micro-structure geometry used within these simulations were generated artificially to be similar to the 3D weave architecture of MSR-EEV (Mars Sample Return - Earth Entry Vehicle). The various eroded TPS micro-structures are then subjected to the boundary layer flow conditions to obtain critical surface quantities which contribute to the structural failure mechanism such as heat flux, pressure, and shear stress. The direct simulation Monte Carlo (DSMC) methodology is used to perform these simulations in order to accurately capture the strong gradients within the high-temperature boundary layer flow over the intricate geometry of WTPS material. The boundary layer profile is directly taken from the Computational Fluid Dynamics (CFD) simulation and provided as boundary conditions to the DSMC inlet and outlet. Further, the variation of these properties as the microstructure undergoes changes due to oxidation is also investigated. Finally, these quantities are used as input in PuMA to understand the material expansion/compression and strain within the woven TPS geometry and help in developing a comprehensive spallation and structure failure model.

microstructure↗

DOE OSTI2023

Importance of ice nucleation and precipitation on climate with the Parameterization of Unified Microphysics Across Scales version 1 (PUMASv1)

Cloud microphysics is critical for weather and climate prediction. In this work, we document updates and corrections to the cloud microphysical scheme used in the Community Earth System Model (CESM) and other models. These updates include a new nomenclature for the scheme, now called Parameterization of Unified Microphysics Across Scales (PUMAS), and the ability to run the scheme on graphics processing units (GPUs). The main science changes include refactoring an ice number limiter and associated changes to ice nucleation, adding vapor deposition onto snow, and introducing an implicit numerical treatment for sedimentation. We also detail the improvements in computational performance that can be achieved with GPU acceleration. We then show the impact of these scheme changes on the (a) mean state climate, (b) cloud feedback response to warming, and (c) aerosol forcing. We find that corrections are needed to the immersion freezing parameterization and that ice nucleation has important impacts on climate. We also find that the revised scheme produces less cloud liquid and ice but that this can be adjusted by changing the loss process for cloud liquid (autoconversion). Furthermore, there are few discernible effects of the PUMAS changes on cloud feedbacks but some reductions in the magnitude of aerosol–cloud interactions (ACIs). Small cloud feedback changes appear to be related to the implicit sedimentation scheme, with a number of factors affecting ACIs.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS1982

Applications of system identification methods to the prediction of helicopter stability, control and handling characteristics

A set of results on rotorcraft system identification is described. Flight measurements collected on an experimental Puma helicopter are reviewed and some notable characteristics highlighted. Following a brief review of previous work in rotorcraft system identification, the results of state estimation and model structure estimation processes applied to the Puma data are presented. The results, which were obtained using NASA developed software, are compared with theoretical predictions of roll, yaw and pitching moment derivatives for a 6 degree of freedom model structure. Anomalies are reported. The theoretical methods used are described. A framework for reduced order modelling is outlined.

Padfield, G. D.↗

NASA NTRS1992

Manipulator control for rover planetary exploration

An anticipated goal of Mars surface exploration missions will be to survey and sample surface rock formations which appear scientifically interesting. In such a mission, a planetary rover would navigate close to a selected sampling site and the remote operator would use a manipulator mounted on the rover to perform a sampling operation. Techniques for accomplishing the necessary manipulation for the sampling components of such a mission have been developed and are presented. We discuss the implementation of a system for controlling a seven (7) degree of freedom Puma manipulator, equipped with a special rock gripper mounted on a planetary rover prototype, intended for the purpose of performing the sampling operation. Control is achieved by remote teleoperation. This paper discusses the real-time force control and supervisory control aspects of the rover manipulation system. Integration of the Puma manipulator with the existing distributed computer architecture is also discussed. The work described is a contribution toward achieving the coordinated manipulation and mobility necessary for a Mars sample acquisition and return scenario.

Cameron, Jonathan M.↗

NASA NTRS1993

Direct model reference adaptive control of robotic arms

The results of controlling A PUMA 560 Robotic Manipulator and the NASA shuttle Remote Manipulator System (RMS) using a Command Generator Tracker (CGT) based Model Reference Adaptive Controller (DMRAC) are presented. Initially, the DMRAC algorithm was run in simulation using a detailed dynamic model of the PUMA 560. The algorithm was tuned on the simulation and then used to control the manipulator using minimum jerk trajectories as the desired reference inputs. The ability to track a trajectory in the presence of load changes was also investigated in the simulation. Satisfactory performance was achieved in both simulation and on the actual robot. The obtained responses showed that the algorithm was robust in the presence of sudden load changes. Because these results indicate that the DMRAC algorithm can indeed be successfully applied to the control of robotic manipulators, additional testing was performed to validate the applicability of DMRAC to simulated dynamics of the shuttle RMS.

Kaufman, Howard↗

NASA NTRS1993

An examination of the aerodynamic moment on rotor blade tips using flight test data and analysis

The analysis CAMRAD/JA is used to model two aircraft, a Puma with a swept-tip blade and a UH-60A Black Hawk. The accuracy of the analysis in predicting the torsion loads is assessed by comparing the predicted loads with measurements from flight tests. The influence of assumptions in the analytical model is examined by varying model parameters and comparing the predicted results to baseline values for the torsion loads. Flight test data from a research Puma are used to identify the source of torsion loads. These data indicate that the aerodynamic section moment in the region of the blade tip dominates torsion loading in high-speed flight. Both the aerodynamic section moment at the blade tip and the pitch-link loads are characterized by large positive (nose-up) moments in the first quadrant with rapid reversal of load so that the moment is negative in the second quadrant. Both the character and magnitude of this loading are missed by the CAMRAD/JA analysis.

Maier, Thomas H.↗

NASA NTRS2014

Miniaturized, Portable Sensors Monitor Metabolic Health

In order to measure astronauts' metabolic rates in space, Glenn Research Center partnered with Case Western University and the Cleveland Clinic to develop the Portable Unit for Metabolic Analysis (PUMA). Cleveland-based Orbital Research licensed and then modified PUMA to help the US Navy assess pilot oxygen problems and is now designing a device that can be used in hospitals.

Source record↗

NASA NTRSDate not supplied

Multi-Scale Analysis of Effective Mechanical Properties of 3D Woven Composite Materials

This work aims to compute and analyze the mechanical properties of 3D woven composite materials that share the same yarn structure but differ in their matrix porosity and fiber volume fraction. Assuming linear elastic behavior, the software PuMA, developed at NASA, was used to characterize the different composites from their constituents' data averaging their elastic properties in three main directions to obtain their effective orthotropic mechanical properties. This was performed in three steps: firstly, the different phases (yarns/matrix) were analyzed as anisotropic materials separately at the micro-scale; then, the results from these analyses were homogenized and used to obtain the anisotropic elasticity tensor at the meso-scale for the different woven materials; and finally, assuming orthotropic mechanical behavior for the unit cell the mechanical properties were obtained at the macro-scale. The 3D woven composite materials selected for this study are made of phenolic resin with porosity values between 0 and 0.6, and resin infiltrated carbon fiber with volume fractions between 0.5 and 0.9 for the yarns. Results from PuMA were validated with external FEA simulations for the non-porous 3D woven material with a fiber volume fraction of 0.9 in the yarns. Results will be included in the final paper after completing the study detailed in Section II.

Sergio Fraile Izquierdo↗

NASA NTRSDate not supplied

Bridging the Gap Between Microscale Modeling and Additive Manufacturing for TPS

An overview of the now open-source NASA ARC software PuMA will be provided. On top of the well-documented ability to import and compute material properties from micro-CT images, PuMA has the ability to design microstructures and compute/predict material properties such as: porosity, permeability, tortuosity, thermal and electrical conductivity, tensile strength, etc. Therefore, a whole new range of capabilities is available, and provides users with the ability to build TPS materials (both fibrous and woven types) and optimize their properties based on missions and requirements. This talk will aim to provide a seed to start bridging the gap between microscale modeling of TPS materials and additive manufacturing.

Conductivity↗

NASA NTRSDate not supplied

Multi-Scale Thermo-Mechanical Modeling of Porous 3D Woven TPS Materials

This work summarizes the process to compute and analyze the thermal conductivity and mechanical properties of 3D woven TPS materials such as 3MDCP (3D Mid-Density Carbon-Phenolic). The PuMA [1,2] software, developed at NASA Ames, was used to characterize different 3MDCP samples from their constituents' data, averaging their thermal conductivity and elastic properties in the three main directions to obtain their effective orthotropic thermo-mechanical properties. This was performed in multiple steps: firstly, TPS samples were digitally reconstructed using micro computed tomography (µCT) and their constituents were segmented; then, the porous matrix phase was analyzed at the micro-scale and these results were used, along with the fibers’ constituents information, to model the tows at the meso-scale; finally, results from the constituents were homogenized and used to model the thermo-mechanical behavior of the unit cell at the macro-scale. Additionally, to gain a better understanding of the tows’ morphology and distribution of the carbon-phenolic blended fibers, microscopy images of the tows’ cross-section were segmented using deep learning techniques and analyzed with PuMA. This workflow can be applied to any TPS material to computationally obtain its thermo-mechanical properties, enabling more informed TPS design and manufacturing choices.

Multi-Scale↗

NASA NTRSDate not supplied

Multi-Scale Thermo-Mechanical Modeling of Porous 3D Woven TPS Materials

This work summarizes the process to compute and analyze the thermal conductivity and mechanical properties of 3D woven TPS materials such as 3MDCP (3D Mid-Density Carbon-Phenolic). The PuMA software, developed at NASA Ames, was used to characterize different 3MDCP samples from their constituents' data, averaging their thermal conductivity and elastic properties in the three main directions to obtain their effective orthotropic thermo-mechanical properties. This was performed in multiple steps: firstly, TPS samples were digitally reconstructed using micro computed tomography (µCT) and their constituents were segmented; then, the porous matrix phase was analyzed at the micro-scale and these results were used, along with the fibers’ constituents information, to model the tows at the meso-scale; finally, results from the constituents were homogenized and used to model the thermo-mechanical behavior of the unit cell at the macro-scale. Additionally, to gain a better understanding of the tows’ morphology and distribution of the carbon-phenolic blended fibers, microscopy images of the tows’ cross-section were segmented using deep learning techniques and analyzed with PuMA. This workflow can be applied to any TPS material to computationally obtain its thermo-mechanical properties, enabling more informed TPS design and manufacturing choices.

Multi-Scale↗

NASA NTRSDate not supplied

AI-Enhanced Computational Tools for Entry Systems Modeling

To advance the understanding of complex atmospheric entry phenomena, NASA’s Entry Systems Modeling (ESM) team [1] has developed high-fidelity computational tools addressing multiscale challenges, from material microstructures to full-scale heatshield response. This abstract highlights a subset of ESM tools, focusing on AI integration to enhance workflows and predictive modeling. - PuMA [2] computes effective material properties from high-resolution micro-CT scans, supporting TPS analysis for NASA missions. - TomoSAM [3] automates 3D tomography dataset segmentation for PuMA using the Segment Anything Model, reducing manual effort and improving accuracy. - PATO [4] models porous reactive materials under extreme conditions, with advancements such as unified solvers, mechanical erosion, and TPS coatings for NASA missions. - arcjetCV [5] employs deep learning to analyze arc jet test footage, measuring recession rates, shape changes, and shock standoff distances, bridging simulations, and experiments to reveal TPS ablation behavior. - ARCHeS [6] simulates arc heater plasma flows, modeling turbulence, radiation, and electromagnetic interactions to optimize arc heater performance, validate TPS under extreme conditions, and serve as a foundation for developing digital twins of arc heater facilities. - SPARTA [7] simulates rarefied hypersonic flows and gas-surface interactions for planetary entry missions, leveraging GPU architectures for scalable and efficient aerothermal and ablation analyses. AI-driven solutions, such as deep learning segmentation, have streamlined workflows in ESM tools and still hold significant potential to further accelerate processes and enhance automation in entry systems modeling. [1] Haskins, J.B. (2023), [2] Ferguson, J.C. (2018), [3] Meurisse, J.B.E. (2018), [4] Semeraro, F. (2023), [5] Quintart, A. (2024) [6] Meurisse, J.B.E. (2022), [7] Plimpton, S.J. (2019)

Predictive Modeling↗