Interpretation of defects in field ion images - Fcc materials.
Computer shell model simulating dislocation configurations selection in field ion images of fcc structures
Hren, J. J.↗
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Using Digital Image Correlation for Material Testing at Cryogenic Temperatures
Recent efforts were made to parametrize an aluminum alloy at cryogenic temperatures to calibrate finite element models simulating material deformation. Digital image correlation (DIC) was used to measure material properties using front/back strains of specimens during tensile tests. Data acquired from DIC was compared to physical extensometer measurements. Two camera pairs (front and back) were mounted via aluminum extrusion to the exterior of an environmental chamber of a hydraulic test stand. Images were taken through single-pane optical glass windows of the environment chamber. Positive pressure bags encased the cameras, attaching to the perimeter of the glass to keep out moisture and prevent windows from frosting. Figure 1 shows the environmental setup and the camera setup during cryogenic testing. Some of the challenges during testing at cryogenic temperatures include the gaseous flow of liquid nitrogen in the optical path of the mounted cameras, frost buildup on the windows as seen in Figure 1b, and frost on the test coupon. The temperature gradient present during the introduction of liquid nitrogen into the chamber can increase the projection error of images captured of the specimen. Figure 2 shows the estimated projection error from DIC as a function of temperature during the cool down process. This presentation addresses some of the concerns and observations when using DIC for testing at cryogenic temperatures using methods of isolated camera system and techniques for maintaining the glass panel clear from frost.
Joseph Cochran↗
X-ray Micro-Tomography of Ablative Heat Shield Materials
X-ray micro-tomography is a non-destructive characterization technique that allows imaging of materials structures with voxel sizes in the micrometer range. This level of resolution makes the technique very attractive for imaging porous ablators used in hypersonic entry systems. Besides providing a high fidelity description of the material architecture, micro-tomography enables computations of bulk material properties and simulations of micro-scale phenomena. This presentation provides an overview of a collaborative effort between NASA Ames Research Center and Lawrence Berkeley National Laboratory, aimed at developing micro-tomography experiments and simulations for porous ablative materials. Measurements are carried using x-rays from the Advanced Light Source at Berkeley Lab on different classes of ablative materials used in NASA entry systems. Challenges, strengths and limitations of the technique for imaging materials such as lightweight carbon-phenolic systems and woven textiles are discussed. Computational tools developed to perform numerical simulations based on micro-tomography are described. These enable computations of material properties such as permeability, thermal and radiative conductivity, tortuosity and other parameters that are used in ablator response models. Finally, we present the design of environmental cells that enable imaging materials under simulated operational conditions, such as high temperature, mechanical loads and oxidizing atmospheres.Keywords: Micro-tomography, Porous media, Ablation
tomography↗
Fabrication and Characterization of A Lunar Simulant-Based Sintered Construction Material
In-situ resource utilization (ISRU) is critical to enable future efforts to have a long-term human presence on the Moon as well as Mars. ISRU technologies are being developed for radiation protection, dust mitigation, thermal insulation, and other applications. One such ISRU technology for creating construction materials out of lunar and Martian regolith is sintering, which is a thermal-based construction process that bonds finely grained material together at temperatures below the melting point. However, the conditions employed during the sintering, such as temperature, atmospheric composition, duration of the process, and pressure, can have a significant impact on the quality and strength of the resulting materials. In parallel, the development of methods for characterizing the quality, porosity, density, and other properties of these materials is critical. X-ray computed tomography (X-ray CT) can image large changes in density within a material, such as the presence of pores throughout an otherwise uniform medium, with relatively high spatial resolution. Similarly, Terahertz time-domain spectroscopic (THz-TDS) imaging is sensitive to density variations within samples, but is restricted to non-conducting materials. Specifically, previous work has shown that the refractive index (n eff ) values obtained through the analysis of THz-TDS images increases with increasing density within plastic samples. Even further, this work showed that it is possible to create a calibration curve for a given material from samples of different, but known density, which can enable one to directly convert n eff to density for samples having the same composition, but unknown density. Here, we report on the fabrication of a lunar simulant-based sintered construction material using vacuum hot pressed (VHP) sintering, then show X-ray CT and THz-TDS imaging results of the sample, which show spatial variations in the material. This has important implications for efforts to improve these types of lunar construction material processes and verify the quality of these materials in terms of consolidation. To the best of our knowledge, there is no previous work utilizing VHP sintering to make lunar simulant-based construction materials or exploring the feasibility of THz imaging to spatially map the density variation through a lunar simulant-based construction material.
Terahertz time-domain spectroscopic imaging↗
From Tomography to Material Properties of Thermal Protection Systems
The X-ray micro-tomography technique provides non-destructive characterizations of three-dimensional material micro-structures at spatial resolutions from the sub-micron to the centimeter scale. High quality micro-tomography images of NASA Thermal Protection System (TPS) materials are obtained using one of the brightest synchrotron X-ray sources available. Leveraging on NASA supercomputing capabilities, material properties and response are computed from tomography-data. This talk highlights the process and challenges of going from 3D images of actual material structures to simulations of properties and phenomena relevant to TPS material response, such as thermal conductivity, permeability, mass transport and high temperature reactions. The talk is addressed to a broad audience including scientists, engineers, researchers, educators, programmers, managers, and members of the media.
tomography↗
Recent Developments to the Porous Microstructure Analysis (PuMA) Software
Introduction The Porous Microstructure Analysis (PuMA) software is an open source framework for image-based simulation, primarily used to determine effective properties based on material microstructure. PuMA was originally developed for the study of NASA thermal protection materials; however, many of the solvers in PuMA have applicability to a broad range of materials science applications. PuMA version 3.2 computes material surface area, pore diameters, effective thermal conductivity, continuum and rarefied tortuosity, and permeability. For anisotropic materials, PuMA can estimate material orientation and compute anisotropic thermal conductivity and elasticity. In this talk, a brief overview of the PuMA software and underlying methods will be presented, as well as some recent and ongoing developments, including the use of immersed boundary methods for image-based simulation and the development of a new weave segmentation tool, called TomoSAM. Cut-Cell method for heat and mass transfer For simulations on complex microstructures, traditional unstructured meshing techniques often prove to be difficult and time-intensive. Voxel-based solvers, which represent the surface as a staircase structure, are relatively simple to implement but can lose accuracy when feature resolution is poor. In this work, we present a novel 3D cut-cell method for solving the variable coefficient Poisson equation on complex microstructures, suitable for the determination of effective thermal conductivity or tortuosity of a material. The method uses a Marching Cubes/Marching Squares surface reconstruction to create cut-cells and determine geometric quantities. A flux-correction method is extended to 3D, with least squares gradient reconstruction, to solve for the boundary fluxes in the cut-cells. Verification cases show the solver achieves globally 2nd order accuracy on complex microstructures. TomoSAM TomoSAM, a module of the PuMA software, has been developed as a plugin for 3D Slicer, a software platform used for 3D image processing and visualization. It utilizes the Segment Anything Model (SAM), a deep learning model capable of identifying objects and generating image masks based on minimal user input. This feature enables efficient segmentation of complex 3D datasets, particularly of woven materials, from tomography or similar imaging methods, reducing the need for manual segmentation.
Tomography↗
Recent Developments to the Porous Microstructure Analysis (PuMA) Software
The Porous Microstructure Analysis (PuMA) software is an open source framework for image-based simulation, primarily used to determine effective properties based on material microstructure. PuMA was originally developed for the study of NASA thermal protection materials; however, many of the solvers in PuMA have applicability to a broad range of materials science applications. PuMA version 3.2 computes material surface area, pore diameters, effective thermal conductivity, continuum and rarefied tortuosity, and permeability. For anisotropic materials, PuMA can estimate material orientation and compute anisotropic thermal conductivity and elasticity. In this talk, a brief overview of the PuMA software and underlying methods will be presented, as well as some recent and ongoing developments, including the use of immersed boundary methods for image-based simulation and the development of a new weave segmentation tool, called TomoSAM. Cut-Cell method for heat and mass transfer For simulations on complex microstructures, traditional unstructured meshing techniques often prove to be difficult and time-intensive. Voxel-based solvers, which represent the surface as a staircase structure, are relatively simple to implement but can lose accuracy when feature resolution is poor. In this work, we present a novel 3D cut-cell method for solving the variable coefficient Poisson equation on complex microstructures, suitable for the determination of effective thermal conductivity or tortuosity of a material. The method uses a Marching Cubes/Marching Squares surface reconstruction to create cut-cells and determine geometric quantities. A flux-correction method is extended to 3D, with least squares gradient reconstruction, to solve for the boundary fluxes in the cut-cells. Verification cases show the solver achieves globally 2nd order accuracy on complex microstructures. TomoSAM TomoSAM, a module of the PuMA software, has been developed as a plugin for 3D Slicer, a software platform used for 3D image processing and visualization. It utilizes the Segment Anything Model (SAM), a deep learning model capable of identifying objects and generating image masks based on minimal user input. This feature enables efficient segmentation of complex 3D datasets, particularly of woven materials, from tomography or similar imaging methods, reducing the need for manual segmentation.
Tomography↗
Virtual image out-the-window display system study. Volume 2 - Appendix
Virtual image out-the-window display system imaging techniques and simulation devices - appendices containing background material
Baum, M.↗
Tortuosity Computations of Porous Materials using the Direct Simulation Monte Carlo
Low-density carbon fiber preforms, used as thermal protection systems (TPS) materials for planetary entry systems, have permeable, highly porous microstructures consisting of interlaced fibers. Internal gas transport in TPS is important in modeling the penetration of hot boundary-layer gases and the in-depth transport of pyrolysis and ablation products. The gas effective diffusion coefficient of a porous material must be known before the gas transport can be modeled in material response solvers; however, there are very little available data for rigid fibrous insulators used in heritage TPS.The tortuosity factor, which reflects the efficiency of the percolation paths, can be computed from the effective diffusion coefficient of a gas inside a porous material and is based on the micro-structure of the material. It is well known, that the tortuosity factor is a strong function of the Knudsen number. Due to the small characteristic scales of porous media used in TPS applications (typical pore size of the order of 50 micron), the transport of gases can occur in the rarefied and transitional regimes, at Knudsen numbers above 1. A proper way to model the gas dynamics at these conditions consists in solving the Boltzmann equation using particle-based methods that account for movement and collisions of atoms and molecules.In this work we adopt, for the first time, the Direct Simulation Monte Carlo (DSMC) method to compute the tortuosity factor of fibrous media in the rarefied regime. To enable realistic simulations of the actual transport of gases in the porous medium, digitized computational grids are obtained from X-ray micro-tomography imaging of real TPS materials. The SPARTA DSMC solver is used for simulations. Effective diffusion coefficients and tortuosity factors are obtained by computing the mean-square displacement of diffusing particles.We first apply the method to compute the tortuosity factors as a function of the Knudsen number for computationally designed materials such as random cylindrical fibers and packed bed of spheres with prescribed porosity. Results are compared to literature values obtained using random walk methods in the rarefied and transitional regime and a finite-volume method for the continuum regime. We then compute tortuosity factors for a real carbon fiber material with a transverse isotropic structure (FiberForm), quantifying differences between through-thickness and in-plain tortuosities at various Knudsen regimes.
Tortuosity↗
The Analysis of the Patterns of Radiation-Induced DNA Damage Foci by a Stochastic Monte Carlo Model of DNA Double Strand Breaks Induction by Heavy Ions and Image Segmentation Software
To create a generalized mechanistic model of DNA damage in human cells that will generate analytical and image data corresponding to experimentally observed DNA damage foci and will help to improve the experimental foci yields by simulating spatial foci patterns and resolving problems with quantitative image analysis. Material and Methods: The analysis of patterns of RIFs (radiation-induced foci) produced by low- and high-LET (linear energy transfer) radiation was conducted by using a Monte Carlo model that combines the heavy ion track structure with characteristics of the human genome on the level of chromosomes. The foci patterns were also simulated in the maximum projection plane for flat nuclei. Some data analysis was done with the help of image segmentation software that identifies individual classes of RIFs and colocolized RIFs, which is of importance to some experimental assays that assign DNA damage a dual phosphorescent signal. Results: The model predicts the spatial and genomic distributions of DNA DSBs (double strand breaks) and associated RIFs in a human cell nucleus for a particular dose of either low- or high-LET radiation. We used the model to do analyses for different irradiation scenarios. In the beam-parallel-to-the-disk-of-a-flattened-nucleus scenario we found that the foci appeared to be merged due to their high density, while, in the perpendicular-beam scenario, the foci appeared as one bright spot per hit. The statistics and spatial distribution of regions of densely arranged foci, termed DNA foci chains, were predicted numerically using this model. Another analysis was done to evaluate the number of ion hits per nucleus, which were visible from streaks of closely located foci. In another analysis, our image segmentaiton software determined foci yields directly from images with single-class or colocolized foci. Conclusions: We showed that DSB clustering needs to be taken into account to determine the true DNA damage foci yield, which helps to determine the DSB yield. Using the model analysis, a researcher can refine the DSB yield per nucleus per particle. We showed that purely geometric artifacts, present in the experimental images, can be analytically resolved with the model, and that the quantization of track hits and DSB yields can be provided to the experimentalists who use enumeration of radiation-induced foci in immunofluorescence experiments using proteins that detect DNA damage. An automated image segmentaiton software can prove useful in a faster and more precise object counting for colocolized foci images.
Ponomarev, Artem↗
Satellite Hyperspectral Imaging Simulation
Simulation of generic pushbroom satellite hyperspectral sensors have been performed to evaluate the potential performance and validation techniques for satellite systems such as COIS(NEMO), Warfighter-1(OrbView-4) and Hyperion(EO-1). The simulations start with a generation of synthetic scenes from material maps of studied terrain. Scene-reflected radiance is corrected for atmospheric effects and convolved with sensor spectral response using MODTRAN 4 radiance and transmissions calculations. Scene images are further convolved with point spread functions derived from Optical Transfer Functions (OTF's) of the sensor system. Photon noise and etectorr/electronics noise are added to the simulated images, which are also finally quantized to the sensor bit resolution. Studied scenes include bridges and straight roads used for evaluation of sensor spatial resolution, as well as fields of minerals, vegetation and manmade materials used for evaluation of sensor radiometric response and sensitivity. The scenes are simulated with various seasons and weather conditions. Signal-to-noise ratios and expected performance are estimated for typical satellite system specifications and are discussed for all the scenes.
Zanoni, Vicki↗
Satellite Hyperspectral Imaging Simulation
Simulations of generic pushbroom satellite hyperspetral sensors have been performed to evaluate the potential performance and validation techniques for satellite systems such as COIS (NEMO), Warfighter-1 (OrbView-4), and Hyperion (EO-1). The simulaitons start with a generation of synthetic scenes form material maps of studied terrain. Scene-reflected radiance is corrected for atmospheric effects and convolved with sensor spectral response uwing MODTRAN 4 radiance and transmission calculations. Scene images are further convolved with point spread functions derived from Optical Transfer Functions (OTF's) of the sensor system. Photon noise and detector/electronics noise are added to the simulated images, which are also finally quantized to the sensor bit resolution. Studied scenes include bridges and straight roads used for evaluation of sensor spatial resolution, as well as fields of minerals, vegetation, and manmade materials used for evaluation of sensor radiometric response and sensitivity. The scenes are simulated with various seasons and weather conditions. Signal-to-noise ratos and expected performance are estimated for typica satellite system specifications and are discussed for all the scenes.
Zanoni, Vicki↗
Abundance recovery error analysis using simulated AVIRIS data
Measurement noise and imperfect atmospheric correction translate directly into errors in the determination of the surficial abundance of materials from imaging spectrometer data. The effects of errors on abundance recovery were investigated previously using Monte Carlo simulation methods by Sabol et. al. The drawback of the Monte Carlo approach is that thousands of trials are needed to develop good statistics on the probable error in abundance recovery. This computational burden invariably limits the number of scenarios of interest that can practically be investigated. A more efficient approach is based on covariance analysis. The covariance analysis approach expresses errors in abundance as a function of noise in the spectral measurements and provides a closed form result eliminating the need for multiple trials. Monte Carlo simulation and covariance analysis are used to predict confidence limits for abundance recovery for a scenario which is modeled as being derived from Airborne Visible/Infrared Imaging Spectrometer (AVIRIS).
Stoner, William W.↗
Evaluation of the Anisotropic Radiative Conductivity of a Low-Density Carbon Fiber Material from Realistic Microscale Imaging
The radiative heat transfer inside a low-density carbon fiber insulator is analyzed using a three-dimensional direct simulation model. A robust procedure is presented for the numerical calculation of the geometric configuration factor to compute the radiative energy exchange processes among the small discretized surface areas of the fibrous material. The methodology is applied to a polygonal mesh of a fibrous insulator obtained from three-dimensional microscale imaging of the real material. The anisotropic values of the radiative conductivity are calculated for that geometry. The results yield both directional and thermal dependence of the radiative conductivity.
Evaluation↗
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↗
Design and Development of Modules to Support Live Microscopic Imaging on Ground-Based Microgravity Simulators
In space, astronauts are exposed to environmental stressors that often result in physiological changes. One prominent stressor in spaceflight is microgravity, and research has shown that long term microgravity exposure causes muscle atrophy, bone loss, cardiovascular concerns, and vision impairment. It is critical to understand how altered gravity affects physiology on the cellular, molecular, and gene level in order to accurately assess health risks and to develop effective countermeasures. Ground-based microgravity simulators such as random positioning machines (RPMs) are used to produce some of the biological effects of altered gravity on different cell types and organisms. Real-time imaging during simulations are of particular interest as we can study how basic cell functions such as cell division, cell migration, and proliferation progress under microgravity conditions. However, design limitations of present microgravity simulators such as susceptibility to parasitic vibration and displacement of the sample from the center of rotation challenge the accuracy of experiment results and live images. We have developed a cell culture sample holder module suitable for live microscopic imaging on an RPM. CAD modeling and 3D printing technology were used to implement modifications to the sample holder and to install a digital microscope to perform live bright-field and fluorescent imaging. Vibration damping materials were also investigated to allow for stable imaging while the microgravity simulator was within a cell culture incubator. Novel methods and hardware modifications for improving live cell imaging on ground-based microgravity simulators were proposed and discussed.
3D printing↗
Nondestructive Evaluation (NDE) of structural ceramics by photoacoustic microscopy
Photoacoustic microscopy (PAM) was utilized to detect surface and subsurface defects in structural ceramic materials. A computerized PAM data acquisition, color imaging and analysis system was developed and used. Subsurface simulated cylindrical holes can be detected to about 1 mm below the interrograting surface. Simulated tight surface cracks of 96 microns length and 48 microns depth can be detected in these materials under optimum conditions.
Khandelwal, P. K.↗
Alteration of Optical Properties in Polymer Materials under Low Earth Orbit (LEO) Space and Simulated Exposure
This paper provides an overview of the 16th Materials International Space Station Experiment (MISSE) project, conducted by a multiorganizational team of researchers. The orbital environment during the mission, including environmental sensors data and unexpected occurrences, are discussed. The research further examines the spectral changes in selected material, Kapton TF, exposed to low Earth orbit conditions during the mission. Optical images of the material taken during the mission were analyzed using a machine learning approach. This process involved the use of a Radial Basis Function network to extract reflectance spectra from RGB/IR images. The findings were then compared with lab-based experiments of identical materials subjected to simulated space weather conditions. This comprehensive study aids in making accurate predictions about the performance of materials in space, thereby improving the reliability and safety of future space missions.
Insulators↗