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All sourcesNASA NTRSDOE OSTI
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 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

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 NTRS1982

Geology team

Evaluating of the combined utility of narrowband and multispectral imaging in both the infrared and visible for the lithologic identification of geologic materials, and of the combined utility of multispectral imaging in the visible and infrared for lithologic mapping on a global bases are near term recommendations for future imaging capabilities. Long term recommendations include laboratory research into methods of field sampling and theoretical models of microscale mixing. The utility of improved spatial and spectral resolutions and radiometric sensitivity is also suggested for the long term. Geobotanical remote sensing research should be conducted to (1) separate geological and botanical spectral signatures in individual picture elements; (2) study geobotanical correlations that more fully simulate natural conditions; and use test sites designed to test specific geobotanical hypotheses.

Source record↗
NASA NTRSDate not supplied

Recent Advancements in the PATO Material Response Code

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

Material Response↗
NASA NTRSDate not supplied

Recent Advancements in the PATO Material Response Code

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

Thermal Protection Systems↗
NASA NTRS1992

Lumley's energy cascade dissipation rate model for boundary-free turbulent shear flows

True dissipation occurs mainly at the highest wavenumbers where the eddy sizes are comparatively small. These high wavenumbers receive their energy through the spectral cascade of energy starting with the largest eddies spilling energy into the smaller eddies, passing through each wavenumber until it is dissipated at the microscopic scale. However, a small percentage of the energy does not spill continuously through the cascade but is instantly passed to the higher wavenumbers. Consequently, the smallest eddies receive a certain amount of energy almost immediately. As the spectral energy cascade continues, the highest wavenumber needs a certain time to receive all the energy which has been transferred from the largest eddies. As such, there is a time delay, of the order of tau, between the generation of energy by the largest eddies and the eventual dissipation of this energy. For equilibrium turbulence at high Reynolds numbers, there is a wide range where energy is neither produced by the large eddies nor dissipated by viscosity, but is conserved and passed from wavenumber to higher wavenumbers. The rate at which energy cascades from one wavenumber to another is proportional to the energy contained within that wavenumber. This rate is constant and has been used in the past as a dissipation rate of turbulent kinetic energy. However, this is true only in steady, equilibrium turbulence. Most dissipation models contend that the production of dissipation is proportional to the production of energy and that the destruction of dissipation is proportional to the destruction of energy. In essence, these models state that the change in the dissipation rate is proportional to the change in the kinetic energy. This assumption is obviously incorrect for the case where there is no production of turbulent energy, yet energy continues to cascade from large to small eddies. If the time lag between the onset on the energy cascade to the destruction of energy at the microscale can be modeled, then there will be a better representation of the dissipation process. Development of an energy cascade time scale equation is discussed.

Duncan, B. S.↗
NASA NTRSDate not supplied

TPSAS-NF1676L-31770-DND

HREBSD (high resolution electron backscatter diffraction) is a scanning electron microscope based diffraction technique that measures stress, elastic strain and dislocation density in crystalline materials with a spatial resolution on the order of tens of nanometers. This information represents a glut of quantitative data that may be directly incorporated in microscale crystal plasticity models. However, concerns over the accuracy of HREBSD make integration of microscopy data with material models problematic. This presentation addresses a number of issue concerning the accuracy of HREBSD, including pattern center error, cross-correlation error and random noise. Additionally, a computational framework is presented that allows for rapid, non-deterministic calibration of material models. Finally, several tests cases are presented where HREBSD is cross-validated with other diffraction techniques: X-ray diffraction, electron channeling contrast imaging and transmission electron microscopy. The accuracy of HREBSD, when incorporating these new techniques, is sufficient to measure local stress to below 10 MPa and to detect individual dislocations.

Timothy J Ruggles↗
NASA NTRS2013

Experimental and Analytical Characterization of the Macromechanical Response for Triaxial Braided Composite Materials

Increasingly, carbon composite structures are being used in aerospace applications. Their highstrength, high-stiffness, and low-weight properties make them good candidates for replacing many aerospace structures currently made of aluminum or steel. Recently, many of the aircraft engine manufacturers have developed new commercial jet engines that will use composite fan cases. Instead of using traditional composite layup techniques, these new fan cases will use a triaxially braided pattern, which improves case performance. The impact characteristics of composite materials for jet engine fan case applications have been an important research topic because Federal regulations require that an engine case be able to contain a blade and blade fragments during an engine blade-out event. Once the impact characteristics of these triaxial braided materials become known, computer models can be developed to simulate a jet engine blade-out event, thus reducing cost and time in the development of these composite jet engine cases. The two main problems that have arisen in this area of research are that the properties for these materials have not been fully determined and computationally efficient computer models, which incorporate much of the microscale deformation and failure mechanisms, are not available. The research reported herein addresses some of the deficiencies present in previous research regarding these triaxial braided composite materials. The current research develops new techniques to accurately quantify the material properties of the triaxial braided composite materials. New test methods are developed for the polymer resin composite constituent and representative composite coupons. These methods expand previous research by using novel specimen designs along with using a noncontact measuring system that is also capable of identifying and quantifying many of the microscale failure mechanisms present in the materials. Finally, using the data gathered, a new hybrid micromacromechanical computer model is created to simulate the behavior of these composite material systems under static and ballistic impact loading using the test data acquired. The model also quantifies the way in which the fiber/matrix interface affects material response under static and impact loading. The results show that the test methods are capable of accurately quantifying the polymer resin under a variety of strain rates and temperature for three loading conditions. The resin strength and stiffness data show a clear rate and temperature dependence. The data also show the hydrostatic stress effects and hysteresis, all of which can be used by researchers developing composite constitutive models for the resins. The results for the composite data reveal noticeable differences in strength, failure strain, and stiffness in the different material systems presented. The investigations into the microscale failure mechanisms provide information about the nature of the different material system behaviors. Finally, the developed computer model predicts composite static strength and stiffness to within 10 percent of the gathered test data and also agrees with composite impact data, where available.

Littell, Justin D.↗
NASA NTRS2008

A Novel Multiscale Physics Based Progressive Failure Methodology for Laminated Composite Structures

A variable fidelity, multiscale, physics based finite element procedure for predicting progressive damage and failure of laminated continuous fiber reinforced composites is introduced. At every integration point in a finite element model, progressive damage is accounted for at the lamina-level using thermodynamically based Schapery Theory. Separate failure criteria are applied at either the global-scale or the microscale in two different FEM models. A micromechanics model, the Generalized Method of Cells, is used to evaluate failure criteria at the micro-level. The stress-strain behavior and observed failure mechanisms are compared with experimental results for both models.

Pineda, Evan J.↗
NASA NTRS2006

Ferroelectric Material Application: Modeling Ferroelectric Field Effect Transistor Characteristics from Micro to Nano

All present ferroelectric transistors have been made on the micrometer scale. Existing models of these devices do not take into account effects of nanoscale ferroelectric transistors. Understanding the characteristics of these nanoscale devices is important in developing a strategy for building and using future devices. This paper takes an existing microscale ferroelectric field effect transistor (FFET) model and adds effects that become important at a nanoscale level, including electron velocity saturation and direct tunneling. The new model analyzed FFETs ranging in length from 40,000 nanometers to 4 nanometers and ferroelectric thickness form 200 nanometers to 1 nanometer. The results show that FFETs can operate on the nanoscale but have some undesirable characteristics at very small dimensions.

MacLeod, Todd, C.↗
NASA NTRS2015

Microstructural Influence on Deformation and Fatigue Life of Composites Using the Generalized Method of Cells

A fully coupled deformation and damage approach to modeling the response of composite materials and composite laminates is presented. It is based on the semi-­‐analytical generalized method of cells (GMC) micromechanics model as well as its higher fidelity counterpart, HFGMC, both of which provide closed-form constitutive equations for composite materials as well as the micro scale stress and strain fields in the composite phases. The provided constitutive equations allow GMC and HFGMC to function within a higher scale structural analysis (e.g., finite element analysis or lamination theory) to represent a composite material point, while the availability of the micro fields allow the incorporation of lower scale sub­‐models to represent local phenomena in the fiber and matrix. Further, GMC's formulation performs averaging when applying certain governing equations such that some degree of microscale field accuracy is surrendered in favor of extreme computational efficiency, rendering the method quite attractive as the centerpiece in a integrated computational material engineering (ICME) structural analysis; whereas HFGMC retains this microscale field accuracy, but at the price of significantly slower computational speed. Herein, the sensitivity of deformation and the fatigue life of graphite/epoxy PMC composites, with both ordered and disordered microstructures, has been investigated using this coupled deformation and damage micromechanics based approach. The local effects of fiber breakage and fatigue damage are included as sub‐models that operate on the microscale for the individual composite phases. For analysis of laminates, classical lamination theory is employed as the global or structural scale model, while GMC/HFGMC is embedded to operate on the microscale to simulate the behavior of the composite material within each laminate layer. A key outcome of this study is the statistical influence of microstructure and micromechanics idealization (GMC or HFGMC) on the overall accuracy of unidirectional and laminated composite deformation and fatigue response.

Microscale Models↗
NASA NTRS1993

Scaling, soil moisture and evapotranspiration in runoff models

The effects of small-scale heterogeneity in land surface characteristics on the large-scale fluxes of water and energy in the land-atmosphere system has become a central focus of many of the climatology research experiments. The acquisition of high resolution land surface data through remote sensing and intensive land-climatology field experiments (like HAPEX and FIFE) has provided data to investigate the interactions between microscale land-atmosphere interactions and macroscale models. One essential research question is how to account for the small scale heterogeneities and whether 'effective' parameters can be used in the macroscale models. To address this question of scaling, the probability distribution for evaporation is derived which illustrates the conditions for which scaling should work. A correction algorithm that may appropriate for the land parameterization of a GCM is derived using a 2nd order linearization scheme. The performance of the algorithm is evaluated.

Wood, Eric F.↗
NASA NTRS2012

Effects of Subscale Size and Shape on Global Energy Dissipation in a Multiscale Model of a Fiber-Reinforced Composite Exhibiting Post-Peak Strain Softening Using Abaqus and FEAMAC

A mesh objective crack band model is implemented in the generalized method of cells (GMC) micromechanics model to predict failure of a composite repeating unit cell (RUC). The micromechanics calculations are achieved using the MAC/GMC core engine within the ImMAC suite of micromechanics codes, developed at the NASA Glenn Research Center. The microscale RUC is linked to a macroscale Abaqus/Standard finite element model using the FEAMAC multiscale framework (included in the ImMAC suite). The effects of the relationship between the characteristic length of the finite element and the size of the microscale RUC on the total energy dissipation of the multiscale model are investigated. A simple 2-D composite square subjected to uniaxial tension is used to demonstrate the effects of scaling the dimensions of the RUC such that the length of the sides of the RUC are equal to the characteristic length of the finite element. These results are compared to simulations where the size of the RUC is fixed, independent of the element size. Simulations are carried out for a variety of mesh densities and element shapes, including square and triangular. Results indicate that a consistent size and shape must be used to yield preserve energy dissipation across the scales.

Pineda, Evan, J.↗
NASA NTRS2024

Exploring the Role of Type-II Residual Stresses in A Laser Powder Bed Fusion Nickel-Based Superalloy Using Measurement and Modeling

Far-field high-energy X-ray diffraction microscopy (ff-HEDM) and the crystal plasticity finite element method (CPFEM) are used to investigate the role of grain-scale (Type-II) residual stresses on the fatigue life of additively manufactured (AM) Inconel alloy 625 (IN-625). Grain-averaged orientations, centroids, and residual elastic strain tensors from ff-HEDM data are used to instantiate a crystal plasticity model to simulate the effect of residual stresses at the grain scale. Simulation results indicate that the presence of tensile residual strains increase stress localization and heterogeneity within grains, triggering an earlier onset of plasticity. A microscale fatigue indicator parameter (FIP) is computed to model the impact of these residual strains on the cycles to fatigue crack nucleation. The crack nucleation model, based on the computed FIPs, predicts a significant reduction in the number of cycles for fatigue crack nucleation for mid- and high-cycle fatigue due to the residual strain induced localization, while the residual strains have minimal impact on low-cycle fatigue life.

Inconel↗
NASA NTRS1995

Microscale Effects from Global Hot Plasma Imagery

We have used a three-dimensional model of recovery phase storm hot plasmas to explore the signatures of pitch angle distributions (PADS) in global fast atom imagery of the magnetosphere. The model computes mass, energy, and position-dependent PADs based on drift effects, charge exchange losses, and Coulomb drag. The hot plasma PAD strongly influences both the storm current system carried by the hot plasma and its time evolution. In turn, the PAD is strongly influenced by plasma waves through pitch angle diffusion, a microscale effect. We report the first simulated neutral atom images that account for anisotropic PADs within the hot plasma. They exhibit spatial distribution features that correspond directly to the PADs along the lines of sight. We investigate the use of image brightness distributions along tangent-shell field lines to infer equatorial PADS. In tangent-shell regions with minimal spatial gradients, reasonably accurate PADs are inferred from simulated images. They demonstrate the importance of modeling PADs for image inversion and show that comparisons of models with real storm plasma images will reveal the global effects of these microscale processes.

Moore, T. E.↗
NASA NTRS1993

Heterogeneity and scaling land-atmospheric water and energy fluxes in climate systems

The effects of small-scale heterogeneity in land surface characteristics on the large-scale fluxes of water and energy in land-atmosphere system has become a central focus of many of the climatology research experiments. The acquisition of high resolution land surface data through remote sensing and intensive land-climatology field experiments (like HAPEX and FIFE) has provided data to investigate the interactions between microscale land-atmosphere interactions and macroscale models. One essential research question is how to account for the small scale heterogeneities and whether 'effective' parameters can be used in the macroscale models. To address this question of scaling, three modeling experiments were performed and are reviewed in the paper. The first is concerned with the aggregation of parameters and inputs for a terrestrial water and energy balance model. The second experiment analyzed the scaling behavior of hydrologic responses during rain events and between rain events. The third experiment compared the hydrologic responses from distributed models with a lumped model that uses spatially constant inputs and parameters. The results show that the patterns of small scale variations can be represented statistically if the scale is larger than a representative elementary area scale, which appears to be about 2 - 3 times the correlation length of the process. For natural catchments this appears to be about 1 - 2 sq km. The results concerning distributed versus lumped representations are more complicated. For conditions when the processes are nonlinear, then lumping results in biases; otherwise a one-dimensional model based on 'equivalent' parameters provides quite good results. Further research is needed to fully understand these conditions.

Wood, Eric F.↗