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Recent Developments to the Porous Microstructure Analysis (PuMA) Software

The Porous Microstructure Analysis (PuMA) software is a suite of tools for the analysis of porous materials and generation of material microstructures. From microstructural data, often obtained through X-ray microtomography, PuMA can determine a number of effective material properties and perform material response simulations. Version 2.2 includes capabilities for computing volume fractions, porosity, specific surface area, effective thermal and electrical conductivities, and continuum and rarefied diffusive tortuosity. PuMA can also simulate competitive diffusion/reaction processes at the micro-scale, such as surface oxidation. In this poster, recent advancements to the PuMA software are detailed, including the full refactoring of PuMA into v3.0, a new module to compute heat conduction in anisotropic materials, a particle method for simulating molecular beam experiments, a new finite-volume Laplace solver, complex fibrous material generation, woven material generation, and a coupling of PuMA with the DAKOTA software for advanced statistics.

PuMA

Porous Microstructure Analysis (PuMA) software

The Porous Microstructure Analysis (PuMA) software was developed to provide a robust and efficient framework for computing material properties based on their microstructures. The development was motivated by advancements in X-ray microtomography, an imaging technology that can resolve the structure of a material at a sub-micron scale, in 3D and even in 4D (over time). PuMA provides the capability of computing a comprehensive spectrum of properties, from the most fundamental geometric features of a microstructure, to advanced anisotropic thermo-elastic properties. In addition, the software can generate artificial microstructures, ranging from simple analytical shapes to complex fibrous woven and non- woven geometries, which can be used in performance optimization studies. This presentation will highlight many of the capabilities of the recent open-source release.

microtomography

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

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

The Porous Microstructure Analysis (PuMA) software

The open-source Porous Microstructure Analysis (PuMA) software was implemented to offer an efficient framework for determining material characteristics from 3D microstructures. Its development was inspired by progress in X-ray microtomography, an imaging technology that captures the internal structure of materials in 3D, and even in a 4D temporal context. Over recent years, this method has transformed the domain of materials science due to its capability to non-destructively examine material microstructures while presenting digital data about their geometrical details. It has provided insights into materials relevant to several NASA missions, including heatshields, parachute fabrics, meteorites, and other advanced composites. PuMA, in its current version 3, delivers an array of features, spanning from basic geometric insights of a microstructure to intricate anisotropic thermo-elastic and chemical behavior. Specifically, the software evaluates morphological attributes (specific surface area, volume fractions, mean intercept lengths, orientation) and physical characteristics (conductivity, elasticity, permeability, and tortuosity). Additionally, it can model material degradation processes, such as oxidation and surface chemistry interactions. The software can generate synthetic microstructures, from straightforward geometrical designs to intricate woven and non-woven geometries. Coupling material generation and characterization enable parametric studies and sensitivity analysis to optimize the microstructural performance and inform design decisions and reliability assessment based on uncertainty quantification. A recent addition to PuMA includes the TomoSAM plugin, devised to incorporate the cutting-edge Segment Anything Model (SAM). SAM is a promptable deep learning model that can identify objects and create image masks in a zero-shot manner, based only on a few user clicks. The synergy between these tools aids in the segmentation of complex 3D datasets from tomography or other imaging techniques, which would otherwise require a laborious manual segmentation process.

Tomography

The Porous Microstructure Analysis (PuMA) software

The open-source Porous Microstructure Analysis (PuMA) software was created to offer an efficient framework for determining material properties from 3D microstructures. Its development was inspired by progress in X-ray microtomography, an imaging technology that captures the internal structure of materials in 3D, and even in a 4D temporal context. Over recent years, this method has transformed the domain of materials science due to its capability to non-destructively examine material microstructures while presenting digital data about their geometrical details. It has provided insights into materials relevant to several NASA missions, including heatshields, parachute fabrics, meteorites, and other advanced composites. PuMA, in its current version 3, delivers an array of features, spanning from basic geometric insights of a microstructure to intricate anisotropic thermo-elastic and chemical behavior. Specifically, the software evaluates morphological attributes (specific surface area, volume fractions, mean intercept lengths, orientation) and physical characteristics (conductivity, elasticity, permeability, and tortuosity). Additionally, it can model material degradation processes, such as oxidation and surface chemistry interactions. The software can generate synthetic microstructures, from straightforward geometrical designs to intricate woven and non-woven geometries. Coupling material generation and characterization enables parametric studies and sensitivity analysis to optimize the microstructural performance and inform design decisions and reliability assessment based on uncertainty quantification. A recent addition to PuMA includes the TomoSAM plugin, devised to incorporate the cutting-edge Segment Anything Model (SAM) into our image segmentation workflow. SAM is a promptable deep learning model that can identify objects and create image masks in a zero-shot manner, based only on a few user clicks. The synergy between these tools aids in the segmentation of complex 3D datasets from tomography and other imaging techniques, which would otherwise require a laborious manual segmentation process.

Tomography

Computer vision in microstructural analysis

The following is a laboratory experiment designed to be performed by advanced-high school and beginning-college students. It is hoped that this experiment will create an interest in and further understanding of materials science. The objective of this experiment is to demonstrate that the microstructure of engineered materials is affected by the processing conditions in manufacture, and that it is possible to characterize the microstructure using image analysis with a computer. The principle of computer vision will first be introduced followed by the description of the system developed at Texas A&M University. This in turn will be followed by the description of the experiment to obtain differences in microstructure and the characterization of the microstructure using computer vision.

Srinivasan, Malur N.

Microstructural analysis of solar cell welds

Parallel-gap resistance welding of silicon solar cells with copper interconnects results in complex microstructural variations that depend on the welding variables. At relatively low heat input solid-state welds are produced. At medium heat the Ag-Cu eutectic forms resulting in a braze joint. High heat produces a fusion weld with complete melting of the silver layer on the silicon solar cell. If the silicon is also melted, cracking occurs in the silicon cell below the weld nugget. These determinations were made using light microscopy, microprobe, and scanning electron microscopy analyses.

Moore, T. J.

High-temperature deformation and microstructural analysis for Si3N4-Sc2O3

It was indicated that Si3N4 doped with Sc2O3 may exhibit high temperature mechanical properties superior to Si3N4 systems with various other oxide sintered additives. High temperature deformation of samples was studied by characterizing the microstructures before and after deformation. It was found that elements of the additive, such as Sc and O, exist in small amounts at very thin grain boundary layers and most of them stay in secondary phases at triple and multiple grain boundary junctions. These secondary phases are devitrified as crystalline Sc2Si2O7. Deformation of the samples was dominated by cavitational processes rather than movements of dislocations. Thus the excellent deformation resistance of the samples at high temperature can be attributed to the very small thickness of the grain boundary layers and the crystalline secondary phase.

Cheong, Deock-Soo

High-temperature deformation and microstructural analysis for silicon nitride-scandium(III) oxide

It was indicated that Si3N4 doped with Sc2O3 may exhibit high temperature mechanical properties superior to Si3N4 systems with various other oxide sintered additives. High temperature deformation of samples was studied by characterizing the microstructures before and after deformation. It was found that elements of the additive, such as Sc and O, exist in small amounts at very thin grain boundary layers and most of them stay in secondary phases at tripple and multiple grain boundary junctions. These secondary phases are devitrified as crystalline Sc2Si2O7. Deformation of the samples was dominated by cavitational processes rather than movements of dislocations. Thus the excellent deformation resistance of the samples at high temperature can be attributed to the very small thickness of the grain boundary layers and the crystalline secondary phase.

Cheong, Deock-Soo

Microstructural analysis of the 2195 aluminum-lithium alloy welds

The principal objective of this research was to explain a tendency of 2195 Al-Li alloy to crack at elevated temperature during welding. Therefore, a study was made on the effect of welding and thermal treatment on the microstructure of Al-Li Alloy 2195. The critical roles of precipitates, boundaries, phases, and other features of the microstructure were inferred from the crack propagation paths and the morphology of fracture surface of the alloy with different microstructures. Particular emphasis was placed on the microstructures generated by the welding process and the mechanisms of crack propagation in such structures. Variation of the welding parameters and thermal treatments were used to alter the micro/macro structures, and they were characterized by optical and scanning electron microscopy. A theoretical model is proposed to explain changes in the microstructure of welded material. This model proposes a chemical reaction in which gases from the air (i.e., nitrogen) release hydrogen inside the alloy. Such a reaction could generate large internal stresses capable to induce porosity and crack-like delamination in the material.

Talia, George E.

Microstructural analysis of cracks generated during welding of 2195 aluminum-lithium alloy

This research summarizes a series of studies conducted at Marshall Space Flight Center to characterize the properties of 2195 Al-Li alloy. 2195 Al-Li alloy, developed by Martin Marietta laboratories, is designated as a replacement of 2219 Al-Cu alloy for the External Tank (E.T.) of the space shuttle. 2195 Al-Li alloy with its advantage of increased strength per weight over its predecessor, 2219 Al-Cu alloy, also challenges current technology. 2195 Al-Li has a greater tendency to crack than its predecessor. The present study began with the observation of pore formation in 2195 Al-Li alloy in a thermal aging process. In preliminary studies, Talia and Nunes found that most of the two pass welds studied exhibited round and crack-like porosity at the weld roots. Furthermore, the porosity observed was associated with the grain boundaries. The porosity level can be increased by thermal treatment in the air. A solid state reaction proceeding from dendritic boundaries in the weld fusion zone was observed to correlate with the generation of the porosity.

Talia, George E.

A Microstructural Analysis of Orientation Variation in Epitaxial AlN on Si, Its Probable Origin, and Effect on Subsequent GaN Growth

A structural examination of aluminum nitride growth on [111] silicon was carried out using transmission electron microscopy. Electron diffraction indicates that the basal planes of the wurtzitic overlayer mimic the orientation of the close-packed planes of the substrate. However, considerable, random rotation in the basal plane and random out-of-plane tilts were evident. This article examines these issues with a structural examination of AlN and GaN/AlN on silicon and compares the findings to those reported in the literature.

GaN AlN Si epitaxial aluminum gallium nitride

Post-Test Microstructural Analysis of Particle Impact-Tested Wrought Inconel, Additively Manufactured Inconel and Wrought Monel Targets

Particle impact testing in high pressure oxygen was performed to evaluate ignition susceptibility of Inconel 718 and Monel 400. Sapphire particles (1.5-mm diameter) under high pressure oxygen, travelling at hypersonic speeds, made impact with metal targets, resulting in surface indentations. This report details the post-test characterization of impact craters observed on three metallic target samples: wrought nickel-based superalloy Inconel 718 (IN718), additively manufactured Inconel 718 (AM-IN718) and nickel-copper alloy, Monel 400.

Ochoa, Ngozi C.

Microstructural Analysis Across a Hybrid Inconel 718 Turbopump Inducer Following a Scheduled Heat Treatment Process

Additive Manufacturing (AM) provides a low-cost method to fabricate near net shape complex parts. In this study, a turbopump inducer was fabricated using blown powder direct energy deposition (DED) of Inconel 718 to form the fins on a wrought hub. By utilizing this combination process, more cost-effective methods are possible for complex parts. A series of heat treatments were applied to the assembly per ASTM F330.

Inconel 718

Porous Microstructure Analysis (PuMA) software

- Motivation and objectives - Overview of PuMA - Open-source release - Material properties computation - Artificial geometry generation - Property homogenization for anisotropic media - Fiber orientation - Conductivity - Elasticity - Permeability

homogenization