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At least 163 records · Page 9

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↗

Comparison of Micromechanics Theories for Modeling Discontinuous Long Fiber Reinforced Composites

Two micromechanics theories, the high fidelity generalized method of cells and Carrera Unified Formulation, are used to model a repeating unit cell of a discrete long fiber composite. The models are used to predict the effective properties of a single fiber with varying fiber-to-fiber end gap lengths, as well as the local stresses in the fiber and matrix. Both models produced similar results and demonstrated that they could capture the complex local load transfer due to the shear lag effect.

discrete long fiber composites↗

Determination of Significant Composite Processing Factors by Designed Experiment (MSFC Center Director's Discretionary Fund)

To determie composite material properties' effects from porcessing variables, a 3 factorial designed experiment with two replicates was conducted. The factors were cure method (oven versus autoclave), layup (hand versus tape-laying machine), and thickness (8 versus 52 ply). Four material systems were tested: AS4/3501-6, IM7/8551-7, IM7/F655 bismaleimide (BMI), and shear tests on IM7/F584. Material properties were G(sub 12), v(sub 12), E(sub 1c) and E(sub 2c). Since the samples were necessarily nonstandard, strengths, though recorded, cannot be considered valid. Void content was also compared. Autoclave curing helped material properties for the low modulus fiber material but showed little benefit for higher stiffness fibers. The number of plies was very important for epoxy composites but not for the BMI. E(sub 1) was generally unaffected by any factor. Particularly high void content did correlate to reduced properties. Autoclave curing reduced void content over oven curiing but a moderate amount of voids, less than 1 percent void content, didnot correlate with material properties. Oven cures and hand layups can produce high-quality parts. Part thickness of epoxy composites is important, though cure optimization may improve performance. Significant variations can be caused by processing and it is important that test coupons always reflect the layup and processes of the final part.

Finckenor, J. L.↗

Small particle transport across turbulent nonisothermal boundary layers

The interaction between turbulent diffusion, Brownian diffusion, and particle thermophoresis in the limit of vanishing particle inertial effects is quantitatively modeled for applications in gas turbines. The model is initiated with consideration of the particle phase mass conservation equation for a two-dimensional boundary layer, including the thermophoretic flux term directed toward the cold wall. A formalism of a turbulent flow near a flat plate in a heat transfer problem is adopted, and variable property effects are neglected. Attention is given to the limit of very large Schmidt numbers and the particle concentration depletion outside of the Brownian sublayer. It is concluded that, in the parameter range of interest, thermophoresis augments the high Schmidt number mass-transfer coefficient by a factor equal to the product of the outer sink and the thermophoretic suction.

Rosner, D. E.↗

Substituent Effects on Transient, Carbodiimide-Induced Geometry Changes in Diphenic Acids

Nucleotide-induced conformational changes in motor proteins are key to many important cell functions. Inspired by this biological behavior, we report a simple chemically fueled system that exhibits carbodiimide-induced geometry changes. Bridging via transient anhydride formation leads to a significant reduction of the twist about the biaryl bond of substituted diphenic acids, giving a simple molecular clamp. The kinetics are well-described by a simple mechanism, allowing structure–property effects to be determined. The kinetic parameters can be used to derive important characteristics of the system such as the efficiencies (anhydride yields), maximum anhydride concentrations, and overall lifetimes. Transient diphenic anhydrides tolerate steric hindrance ortho to the biaryl bond but are significantly affected by electronic effects, with electron-deficient substituents giving lower yields, peak conversions, and lifetimes. Furthermore, the results provide useful guidelines for the design of functional systems incorporating diphenic acid units.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

U-net architected deep material network training with microstructure local field information

The Deep Material Network (DMN) has recently emerged as a powerful reduced-order modeling framework for simulating the mechanical response of heterogeneous materials such as composites. Unlike most data-driven approaches that directly learn a material’s response under prescribed loading, the DMN acts as a homogenization operator, learning the kinematic constraints and mechanical interactions of the underlying microstructure. However, traditional DMN training relies exclusively on homogenized effective properties derived from Direct Numerical Simulations (DNS), discarding the rich local field data that govern microstructural interactions. In this work, we extend the DMN framework to incorporate such local field information into the offline training process. Utilizing a U-Net architecture, we augment the DMN training objective to include the first and second statistical moments of the local stress fields obtained from linear DNS. This ensures that the learned network topology not only fits the effective stiffness but also accurately reflects the internal local stress and strain partitioning of the microstructure. The results confirm that supervising the localization process during training yields a superior surrogate model, reducing local prediction errors by an order of magnitude and significantly improving generalization to unseen nonlinear constitutive behaviors compared to traditional DMNs.

36 MATERIALS SCIENCE↗

Arctic Stratus Cloud Properties and Their Effect on the Surface Radiation Budget: Selected Cases from FIRE ACE

To study Arctic stratus cloud properties and their effect on the surface radiation balance during the spring transition season, analyses are performed using data taken during three cloudy and two clear days in May 1998 as part of the First ISCCP Regional Experiment (FIRE) Arctic Cloud Experiment (ACE). Radiative transfer models are used in conjunction with surface- and satellite-based measurements to retrieve the layer-averaged microphysical and shortwave radiative properties. The surface-retrieved cloud properties in Cases 1 and 2 agree well with the in situ and satellite retrievals. Discrepancies in Case 3 are due to spatial mismatches between the aircraft and the surface measurements in a highly variable cloud field. Also, the vertical structure in the cloud layer is not fully characterized by the aircraft measurements. Satellite data are critical for understanding some of the observed discrepancies. The satellite-derived particle sizes agree well with the coincident surface retrievals and with the aircraft data when they were collocated. Optical depths derived from visible-channel data over snow backgrounds were overestimated in all three cases, suggesting that methods currently used in satellite cloud climatologies derive optical depths that are too large. Use of a near-infrared channel with a solar infrared channel to simultaneously derive optical depth and particle size appears to alleviate this overestimation problem. Further study of the optical depth retrieval is needed. The surface-based radiometer data reveal that the Arctic stratus clouds produce a net warming of 20 W m(exp -2) in the surface layer during the transition season suggesting that these clouds may accelerate the spring time melting of the ice pack. This surface warming contrasts with the net cooling at the top of the atmosphere (TOA) during the same period. All analysis of the complete FIRE ACE data sets will be valuable for understanding the role of clouds during the entire melting and refreezing process that occurs annually in the Arctic.

Doug, Xiquan↗

Investigation of Effects of Material Architecture on the Elastic Response of a Woven Ceramic Matrix Composite

To develop methods for quantifying the effects of the microstructural variations of woven ceramic matrix composites on the effective properties and response of the material, a research program has been undertaken which is described in this paper. In order to characterize and quantify the variations in the microstructure of a five harness satin weave, CVI SiC/SiC, composite material, specimens were serially sectioned and polished to capture images that detailed the fiber tows, matrix, and porosity. Open source quantitative image analysis tools were then used to isolate the constituents and collect relevant statistics such as within ply tow spacing. This information was then used to build two dimensional finite element models that approximated the observed section geometry. With the aid of geometrical models generated by the microstructural characterization process, finite element models were generated and analyses were performed to quantify the effects of the microstructure and its variation on the effective stiffness and areas of stress concentration of the material. The results indicated that the geometry and distribution of the porosity appear to have significant effects on the through-thickness modulus. Similarly, stress concentrations on the outer surface of the composite appear to correlate to regions where the transverse tows are separated by a critical amount.

Goldberg, Robert K.↗

Robust Thermal Control of Propulsion Lines for Space Missions

A document discusses an approach to insulating propulsion lines for spacecraft. In spacecraft that have propulsion lines that are located externally with open bus architecture, the lines are typically insulated by Multi Layer Insulation (MLI) blankets. MLI on propulsion lines tends to have large and somewhat random variances in its heat loss properties (effective emittance) from one location to the next, which makes it an un-robust approach to control propulsion line temperatures. The approach described here consists of a clamshell design in which the inner surface of the shell is coated with low-emissivity aluminized Kapton tape, and the outer surface is covered with black tape. This clamshell completely encloses the propulsion line. The line itself is covered with its heater, which in turn, is covered completely with black tape. This approach would be low in heater power needs because even though the outer surface of the prop line (and its heater) is covered with black tape as well as the outer surface of the clamshell, the inner surface of the clamshell is covered with low-emissivity aluminized Kapton tape. Hence, the heat loss from the line will be small and comparable to the MLI based one. In terms of contamination changing the radiative properties of surfaces, since the clamshell s inner surface is always protected during handling and is only installed after all the work on the prop line has been completed, the controlling surface, which is the clamshell s inner surface, is always in pristine condition. This proposed design allows for a much more deterministic and predictable design using a very simple and implementable approach for thermal control. It also uses low heater power and is robust to handling and contamination during and after implementation.

Bhandari, Pradeep↗

Measured backscatter and attenuation properties, including polarization effects, of various dispersions at 0.9 micron

The optical properties of a wide variety of atmospheric dispersions were studied using a 0.9-micron lidar system which included a GaAs laser stack transmitter emitting a horizontally polarized beam of 4 milliradians vertical divergence and 1.5 milliradians horizontal divergence. A principal means for assessing optical properties was the polarization ratio, that is, the backscattered radiation power perpendicular to the transmitter beam divided by the backscattered radiation power parallel to the beam polarization. The ratio of the backscattered fraction to the attenuation coefficient was also determined. Data on the dispersion properties of black carbon smoke, road dust, fog, fair-weather cumulus clouds, snow and rain were obtained; the adverse effects of sunlight-induced background noise on the readings is also discussed.

Kohl, R. H.↗

A Green’s function fast multipole method for computation of micromechanical fields in heterogeneous materials

Computation of micromechanical fields in heterogeneous materials is usually performed using either the finite element method or the Green’s function method based on FFTs. The finite element method allows for accurate discretization and for non-periodic boundary conditions but is computationally expensive. On the other hand, the FFT-based method is computationally efficient but requires discretization on a regular grid of hexahedral voxels. In this paper, a Green’s function method allowing for accurate discretization using tetrahedral elements and for non-periodic boundary conditions is proposed. The convolution is computed using the fast multipole method, which provides good accuracy even for low-order expansion due to the fast decay of interactions between elements. The proposed Green’s function fast multipole method is verified by comparison with analytical and FFT-based solutions. Furthermore, the computational time is analyzed and compared to the FFT-based method for non-periodic convolution. Finally, effective properties of an elastic polycrystalline microstructure containing thin intergranular cracks are computed and analyzed.

36 MATERIALS SCIENCE↗

Computational design of microarchitected porous electrodes for redox flow batteries

Porous electrodes are used as the core reactive component across electrochemical technologies. In flowing systems, controlling the fluid distribution, species transport, and reactive environment is critical to attaining high performance. However, conventional electrode materials like felts and papers provide few opportunities for precise engineering of the electrode and its microstructure. To address these limitations, architected electrodes composed of unit cells with spatially varying geometry determined via computational optimization are proposed. Resolved simulation is employed to develop a homogenized description of the constituent unit cells. These effective properties serve as inputs to a continuum model for the electrode when used in the negative half-cell of a vanadium redox flow battery. Porosity distributions minimizing power loss are then determined via computational design optimization to generate architected porosity electrodes. The architected electrodes are compared to bulk, uniform porosity electrodes and found to lead to increased power efficiency across operating flow rates and currents. The design methodology is further used to generate a scaled-up electrode with comparable power efficiency to the bench-scale systems. Finally, the variable porosity architecture and computational design methodology presented here thus offers a novel pathway for automatically generating spatially engineered electrode structures with improved power performance.

25 ENERGY STORAGE↗

Mechanisms and models of the turbulent boundary layers at transcritical conditions

Computational models for high-pressure transcritical turbulence in wall-modeled large-eddy simulation typically rely on wall-function models to overcome the need for resolving the boundary layer structures. However, the mechanisms and models of turbulent boundary layer at transcritical conditions remain poorly understood since the near-wall flow and heat transfer are significantly affected by the enhanced fluctuations and steep gradients in thermodynamic properties. Here, to address this issue, we study the mechanisms of transcritical turbulent boundary layers and wall-attached models at transcritical conditions. It is shown that the real-fluid variable-property effects are associated with the coupling between the near-wall cycle and the wall-normal coherent motions in the outer layer, resulting in the amplification of turbulent energy in the outer layer and noticeable energy transfer between the log-layer and the outer layer; hence, turbulence in the log-layer is modulated by the outer layer. Based on this underlying physical principle, we propose the characteristic velocity and length scales for the attached eddy at transcritical conditions, and extend the attached eddy model to transcritical turbulent boundary layers by introducing a mixed scaling that incorporates both inner and outer scalings. We show that the new characteristic scales and extended attached-eddy model perform well in characterizing the structures in transcritical turbulent boundary layers.

Li, Fangbo↗

Evaluation of Joint Cyber/Safety Risk in Nuclear Power Systems

This report presents an analysis of the Emergency Core Cooling System (ECCS) for a generic Boiling Water Reactor (BWR)-4 NPP. The Electric Power Research Institute (EPRI) developed Hazards and Consequences Analysis for Digital Systems (HAZCADS) process is applied to the ECCS and its subsystems to identify unsafe control actions (UCAs) which act as possible cyber events of concern. The analysis is performed for two design basis events: Small-break Loss of Coolant Accident (SLOCA) and general transients (TRANS), such as unintended reactor trip. In previous work, HAZCADS UCAs were combined with other cyber-attack analysis to develop a risk-informed approach; however, this was for a single system. This report explores advanced systems engineering modeling approaches to model the interactions between digital assets across multiple systems which may be targeted by cyber adversaries. The complex and interdependent design of digital systems has the potential to introduce emergent cyber properties that are generally not covered by hazard analyses nor formal nuclear Probabilistic Risk Assessment (PRA). The R&D and supporting analysis presented here explores approaches to predict and manage how interdependent system properties effect risk. To show the potential impact of a successful cyber-attack to formal PRA event tree probabilities, HAZCADS analysis was also used. HAZCADS was also used to model the automatic depressurization system (ADS) automatic actuation. This analysis extended to an integrated system analysis for common-cause failure (CCF). In this aspect, the HAZCADS analysis continued by analyzing plant design details for system connectivity in support of critical plant functions. A dependency matrix was developed to depict the integrated functionality of the interconnected systems. Areas of potential CCF are indicated. Future work could include adversary attack development to show how CCF could be caused, resulting in PRA events. Across the multiple systems that comprise the ECCS, the analysis shows that the change in such probabilities was very different between systems. This indicates that some systems have a larger potential risk impact from successful cyber-attack or digital failure, which indicates a need for these systems to have a higher priority for design and defensive measures. Furthermore, we were able to establish that a risk analysis using any arbitrary threat model establishes an ordering of components with regard to cyber-risk. This ordering can be used to influence the overall system design with an eye to lowering risk, or as a way to understand real-time risk to operational systems based on a current threat landscape. Expert knowledge of both the analysis process and the system being analyzed is required to perform a HAZCADS analysis. The need for a tiered risk analysis is demonstrated by the results of this report.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Compressive Response and Energy Absorption of Additively Manufactured Elastomers with Varied Simple Cubic Architectures

Additive manufacturing, and particularly the vat photopolymerization process, enables the fabrication of complex geometries at high resolution and small length scales, making it well-suited for fabricating cellular structures (e.g., foams and lattices). Among these, elastomeric cellular structures are of growing interest due to their tunable compliance and energy dissipation. However, comprehensive data on the compressive behavior of these structures remains limited, especially for investigating the structure-property effects from changing the density and distribution of material within the cellular structure. This study explores how the mechanical response of polyurethane-based simple cubic structures changes when varying volume fraction, unit cell length, and unit cell patterning, which have not been systematically investigated previously in additively manufactured elastomers. Increasing volume fraction from 10% to 50% yielded significant changes in compressive stress–strain performance (decreasing strain at 0.5 MPa by 41.6% and increasing energy absorption density by 3962.5%). Although changing the unit cell length between 2.5 and 7 mm in ~30 mm parts did not result in statistically different stress–strain responses, modifying the configuration of struts of different thicknesses across designs with 30% volume fraction altered the stress–strain behavior (differences of 12.5% in strain at 0.5 MPa and 109.4% for energy absorption density). Power law relationships were developed to understand the interactions between volume fraction, unit cell length, and elastic modulus, and experimental data showed strong fits (R 2 > 0.91). These findings enhance the understanding of how multiple structural design aspects influence the performance of elastomeric cellular materials, providing a foundation for informing strategic design of tailorable materials for diverse mechanical applications.

36 MATERIALS SCIENCE↗