Search NASA⌕ Search

SEARCH · Search NASA

Results for “Porous”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,027 records · Page 57
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

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↗
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

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↗
NASA NTRSDate not supplied

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↗
NASA NTRSDate not supplied

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↗
NASA NTRS2026

Highly Porous Polyimide Gel for Use as Battery Separator with Room Temperature Ionic Liquid Electrolytes

Advanced aerospace vehicular concepts require advances in many existing technologies, including space power and energy storage systems. Batteries represent one of the major areas in need of improvement, both in terms of energy density and safety, with growing concerns over the fire safety of commercial lithium-ion batteries. This has prompted efforts to develop nonflammable battery components, namely the electrolyte and separator. Existing commercial lithium-ion batteries utilize polyolefin microporous membranes as separators with an electrolyte consisting of a lithium salt dissolved in a mixture of cyclic carbonate solvents. This separator/electrolyte combination has ionic conductivities in the range of 10 −2 to 10 −3 S/cm. However, the cyclic carbonate solvents are inherently flammable. Room-temperature ionic liquids (RTILs) appear to be a safer alternative. They offer good ionic conductivities and are inherently nonvolatile and nonflammable, giving them a safety advantage. However, many promising RTILs for battery electrolytes are not compatible with commercial polyolefin separator materials. Alternative separator materials, such as polyimides, are non-flammable and are capable of accepting RTILs into their structure. Polyimide gels, with a composition of 4,4′-oxydianiline, 3,3′,4,4′-tetracarboxylic dianhydride and cross-linked with Desmodur N3300A, possess an open-porous, fibrillar network architecture which offers a high degree of porosity (typically greater than 85% porosity) for lithium-ion transport and conduction, as well as good mechanical properties. Furthermore, these polyimide gels are compatible with selected imidazolium-based RTILs. Nonflammable separator/electrolyte systems with room-temperature conductivities in the range of 10 −3 S/cm have been evaluated. It has been demonstrated that 1-ethyl-3-methylimidazolium bis(trifluoromethylsulfonyl)imide was the most promising among six RTILs screened, in terms of both ionic conductivity and constant current cycling.

Polyimide↗
NASA NTRSDate not supplied

Mitigating Grazing Flow Impedance Eduction Errors in Additively Manufactured Porous Liners

Additively manufactured porous metamaterials, including triply periodic minimal surface (TPMS) cores, are promising candidates for aeroengine liners but often behave as extended-reacting treatments under grazing flow. Standard impedance eduction procedures assume locally-reacting behavior and can yield physically inconsistent results for such materials. This study evaluates internal partitions (thin solid walls inserted at regular intervals along the liner’s streamwise extent) as a means of suppressing internal streamwise propagation to improve eduction consistency. Six TPMS configurations were tested in the NASA Langley Grazing Flow Impedance Tube (GFIT) at partition spacings of 4′′, 2′′, and 1′′, as well as unpartitioned, and at Mach numbers up to 0.3. For most geometries, 2′′ partition spacing eliminated impedance discontinuities and substantially improved Prony correlation, though effectiveness varied with core topology. Partitions also altered the acoustic response of the liners: resistance increased, resonance frequencies shifted downward, and peak attenuation decreased while bandwidth broadened in some cases. Because partitions modify the liner itself, the educed impedance characterizes the partitioned system rather than the original unpartitioned core. These results establish partitioning as a practical pathway toward liners that are more compatible with standard eduction methods, while demonstrating that the intervention is itself an acoustic design change.

liners↗
DOE OSTI2020

Detection of analytes using porous mass spectrometry surface

The disclosure herein includes compositions and methods for ionizing targets and methods for making the compositions. In some embodiments, the compositions can include a porous substrate that has been etched for a desired average pore size, a desired porosity, or both for detection of one or more targets of interest. Also disclosed herein are methods for using the composition to ionize targets.

36 MATERIALS SCIENCE↗
DOE OSTI2020

MESOSCALE THERMAL TRANSPORT MEASUREMENTS OF MULTI-PHASE AND POROUS NUCLEAR FUELS USING A SQUARE-WAVE PULSE THERMOREFLECTANCE TECHNIQUE

The safe and efficient operation of nuclear reactors require accurate knowledge of peak temperatures in the fuel assemblies. The temperature profiles are governed by the thermal transport properties of the fuel, namely the thermal conductivities (k) and thermal diffusivities (D). These values can be very difficult to measure as they are known to vary considerably from the measured bulk values of the fresh fuel, and quickly degrade with increasing burnup [1 -3] . Laser-based techniques have been effectively used for non-destructive and non-contact thermal transport measurements of a wide variety of materials, including nuclear materials [4-6] that would otherwise prove too hazardous or difficult to measure otherwise. In this study, a new thermoreflectance technique known as square-pulse transient thermoreflectance (SPTR) is described and used to determine the mesoscale thermal diffusivity of both uranium sesquisilicide (U3Si2) and uranium nitride (UN) phases in a composite fuel with micron level spatial resolution [7]. This technique employs a rapid train of square-wave pulses from an excitation laser to create a periodic heat flux on a gold coated sample surface. Surface adsorption results in transient film temperatures and hence rapid fluctuations in thermoreflectance that can be measured via a detection laser coupled with a digital oscilloscope. The lasers are coaxially focused on the sample surface, allowing for a sample measurement area of a single convolved laser spot size (~2 µm). A sensitivity analysis was conducted to identify key measurement parameters of this technique using reference materials with a range of thermal conductivities comparable to those of both ceramic, composite, and metal nuclear fuel types (1.4 – 27.2 W/m-K). The reference materials were measured using the new technique as well as a spatial-domain thermoreflectance technique (SDTR) previously reported for a comparison [8]. Additionally, measurements of several U3Si2 and UN phase regions of a polished UN/U3Si2 (70/30 vol.%) sample were taken, and the resulting calculated D values are reported, with both techniques showing excellent agreement between samples. This technique was used to scan a multiphase region at 5 micron increments to generate a local diffusivity map, demonstrating the utility of the techniques for measuring thermal transport properties in specimens with precipitates and secondary phases. Furthermore, the technique is currently being applied to measure thermal properties of Fast Flux Test Reactor (FFTR) irradiated metal fuel specimens whose porous microstructure make it very difficult to measure using other techniques. Comparison of the local scale measurements are compared with the pre-irradiated fuel samples to show the degradation of thermal transport in fuels due to pores from fission gas bubbles and other irradiation induced defects.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2021

Experimental Fabrication of Porous Additive Manufactured Material

Nuclear industries can benefit from materials that can perform well mechanically and thermally in high temperature and corrosion environments. Functionally graded materials (FGM) are materials manufactured with complex spatial, structural, and chemical compositions, creating components predesigned with tailored microstructural and mechanical properties. Porosity-graded FGMs are designed to introduce pores into a component’s structure as a mechanism to increase bulk or surface material performance, such as stress accommodation and negative thermal conductivity. Additive manufacturing (AM) techniques such as laser energy net shape (LENS) and wire arc additive manufacturing (WAAM), excel in high energy density, point-to-point metal deposition, and present in combination with other combinatorial approaches, exciting methods to manufacture porous FGM components. This project is also examining plasma jet printing as another means for method evaluations for smaller scale graded components. This study explores AM FGM process parameters and combinatorial fabrication methodologies for stainless steel components functionally graded in porosity levels. Preliminary characterization results are provided to attest the feasibility of the combinational fabrication techniques.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Calcium-silicate-based porous particles, composition, method of making and use thereof

A method for synthesizing calcium-silicate-based porous particles (CSPPs) is described. Control over CSPP morphology and pore size is achieved through a refined solution-based synthesis, allowing loading of a variety of sealants. These particles, upon external stimuli, release the loaded sealant into the surrounding material. Methods of loading the CSPPs with loading sealant are described. The CSPPs may be used in pure form or mixed with another material to deliver self-healing, sealing and multi-functional properties to a physical structure. The composition of the CSPPs is described, along with methods of use of the CSPPs.

Shahsavari, Rouzbeh↗
DOE OSTI2021

Superhydrophobic coated micro-porous carbon foam membrane and method for solar-thermal driven desalination

A solar membrane distillation apparatus includes a housing comprising a light transmitting wall. A solar distillation membrane is positioned in the housing to receive solar radiation transmitted through the light transmitting wall. The solar distillation membrane includes a porous graphitic foam and a coating of a hydrophobic composition on the surface and pores of the graphitic foam. A water chamber within the housing is provided for retaining water adjacent to the solar distillation membrane. A vapor chamber is provided for collecting water vapor distilling through the solar distillation membrane. A condenser is provided for condensing distilled water vapor from the vapor chamber into liquid water. A separation membrane and a method of solar distillation are also disclosed.

Jang, Gyoung Gug↗
DOE OSTI2021

Brazing methods using porous interlayers and related articles

The disclosure relates to a brazing method for joining substrates, in particular where one of the substrates is difficult to wet with molten braze material. The method includes formation of a porous metal layer on a first substrate to assist wetting of the first substrate with a molten braze metal, which in turn permits joining of the first substrate with a second substrate via a braze metal later in an assembled brazed joint. Ceramic substrates can be particularly difficult to wet with molten braze metals, and the disclosed method can be used to join a ceramic substrate to another substrate. The brazed joint can be incorporated into a solid-oxide fuel cell, for example as a stack component thereof, in particular when the first substrate is a ceramic substrate and the joined substrate is a metallic substrate.

Nicholas, Jason Dale↗
DOE OSTI2021

Hierarchical porous metals with deterministic 3D morphology and shape via de-alloying of 3D printed alloys

The present disclosure relates to a method for forming a three dimensional, hierarchical, porous metal structure with deterministically controlled 3D multiscale pore architectures. The method may involve providing a feedstock able to be applied in an additive manufacturing process, and using an additive manufacturing process to produce a three dimensional (3D) structure using the feedstock. The method may involve further processing the 3D structure through at least a de-alloying operation to form a metallic 3D structure having an engineered, digitally controlled macropore morphology with integrated nanoporosity.

Qi, Zhen↗
DOE OSTI2021

Methods of forming fuel rods comprising porous fuel materials

A method of forming a fuel rod for a nuclear reactor comprises disposing a powder comprising particles of a fuel material on a substrate, exposing the powder to energy from an energy source to form a first layer of a nuclear fuel, the first layer comprising inter-granular bonds between the particles of the fuel material, disposing additional powder comprising particles of the fuel material over the first layer of the nuclear fuel, and exposing the additional powder to energy from the energy source to form a second layer of the nuclear fuel and to form the nuclear fuel to have a void fraction greater than about 0.20, the second layer comprising inter-granular bonds between the additional powder and the first layer of the nuclear fuel. Related nuclear fuels comprising a porous structure, fuel rods, nuclear reactors, and methods are disclosed.

O'Brien, Robert C.↗
DOE OSTI2022

Methods, systems, and apparatuses for in-line variably porous surfaces

Variably porous panels and panel assemblies incorporating shape memory alloy components along with methods for actuating the shape memory alloys are disclosed to predictably alter the porosity of a substrate surface, with the shape memory alloy maintained in an orientation relative to the panel that is in-plane with a mold-line of the panel outer surface.

36 MATERIALS SCIENCE↗
DOE OSTI2022

System with buffer for lateral flow on a porous membrane

Systems are described, based on a primary binding compound and a secondary binding compound used in combination with a support to detect a target in a sample. The systems includes at least one support structure, at least one small primary support portion containing at least one molecule covalently bound to a visual colloidal marker, a plurality of secondary support portions comprising secondary binding compounds that are covalently bound to the support portions and chemically active, at least one pH litmus indicator, at least one pH strip, a buffer for lateral flow on the porous membrane support that allows preservation and activity of binding compounds.

Bearinger, Jane P.↗