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At least 559 records · Page 31

Using pyrometry to identify porosity in additively manufactured structures

A method and apparatus for identifying porosity in a structure made by an additive manufacturing process in which a laser is scanned across layers of material to form the structure. Pyrometry data comprising images of the layers acquired during additive manufacturing of the structure is received. The pyrometry data is used to generate temperature data comprising estimated temperatures of points in the layers in the images of the layers. The temperature data is used to identify shapes fit to high temperature areas in the images of the layers. Conditions of the shapes fit to the high temperature areas in the images of the layers are identified. Outlier shapes are identified in the shapes fit to the high temperature areas in the images of the layers using the conditions of the shapes.

Mitchell, John A.↗

Application of the van der Pauw method for electrical conductivity measurements at high temperatures using an insulating compressing ring

High quality data on the high temperature electrical properties of ceramics, particularly oxides, is of great value for material selection, design, and modeling for a broad range of emerging applications. Utilizing the mismatch in the coefficient of thermal expansion between two materials, a purely mechanical method for establishing electrical contact in the van der Pauw geometry to measure the bulk resistivity of ceramic disks at high temperatures is presented. Measurements of a reference material, 20 mol. % Gd-doped cerium oxide, are presented up to 1000 °C. The viability of electrical measurements up to a maximum temperature of 1600 °C is also considered. Measurements are performed using multiple techniques and compared to literature values finding excellent agreement. Finally, the approach described in this work enables the van der Pauw method to be applied to many ceramic materials over a wide range of temperatures and environments.

47 OTHER INSTRUMENTATION↗

Diffusion Behavior of Oversized Fission Products in bcc Fe Cladding: A First-Principles Study

Fuel-Cladding Chemical Interaction (FCCI) poses significant challenges in nuclear reactors, where fission products from nuclear fuel interact with Fe-based cladding materials, potentially compromising their structural integrity. This study investigates the diffusion behavior of oversized fission products, Pr, Nd, Ce, and La, within bcc Fe cladding using density functional theory (DFT), nudged elastic band (NEB) method, and self-consistent mean field (SCMF) theory. Our results reveal significant long-range vacancy binding energies, particularly up to the 6th nearest neighbor, with La exhibiting the strongest binding affinity, followed by Nd, Ce, and Pr. The NEB calculations indicate significant high barriers for the dissociation of 1nn vacancy-solute pairs for all fission products. The tracer diffusion coefficients of these fission products was derived in Arrhenius form. The significant trapping effect of vacancies by a very dilute amount of fission products reduces vacancy mobility, leading to an oversaturation of point defects, void nucleation, and swelling. These are critical issues for irradiated cladding materials. The tracer diffusion coefficients indicate that Nd diffuses the fastest, followed by La, Ce, and Pr. This study provides essential insights for developing advanced cladding materials and design strategies to mitigate FCCI, ultimately enhancing nuclear reactor safety and performance.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Precision slew/settle technologies for flexible spacecraft

Many spacecraft missions in the next decade will require both a high degree of agility and precision pointing. Agility includes both rotational maneuvering for retargeting and translational motion for orbit adjustment and threat avoidance. The major challenge associated with such missions is the need for control over a wide range of amplitudes and frequencies, ranging from tens of degrees at less than 1 Hz to a few micron radians at hundreds of Hz. TRW's internally funded Precision Control of Agile Spacecraft (PCAS) project is concerned with developing and validating in hardware the tools necessary to successfully complete the combined agile maneuvering/precision pointing missions. Development has been undertaken on a number of fronts for quietly slewing flexible structures. Various methods for designing slew torque profiles have been investigated. Prime candidates for slew/settle scenarios include Inverse Dynamics and Parameterized Function Space. Joint work with Processor Bayo at the University of California, Santa Barbara and Professor Flashner at the University of Southern California has led to promising torque profile design methods. Active and passive vibration suppression techniques also play a key role for rapid slew/settle mission scenarios. Active members with local control loops and passive members with high loss factor viscoelastic material have been selected for hardware verification. Progress in each of these areas produces large gains in the quiet slewing of flexible spacecraft. The main thrust of the effort to date has been the development of a modular testbed for hardware validation of the precision control concepts. The testbed is a slewing eighteen foot long flexible truss. Active and passive members can be interchanged with the baseline aluminum members to augment the inherent damping in the system. For precision control the active members utilize control laws running on a high speed digital structural control processor. Tip and midspan motions of the truss are determined using optical sensors while accelerometers can be used to monitor the motions of other points of interest. Preliminary results indicate that a mix of technologies produces the greatest benefit. For example, shaping the torque profile produces large improvements in slew/settle performance, but without added damping settling times may still be excessive. With the introduction of moderate amounts of damping, slew/settle performance is vastly improved. On the other hand, introducing damping without shaping the torque profile may not yield the desired level of performance.

Manning, R. A.↗

Mixed-Mode-Bending Delamination Apparatus

Mixed-mode-bending delamination apparatus generates two types of delamination stress simultaneously in specimen from single externally applied point load. In technique, indivial mode I and mode II contributions to delamination in specimen analyzed by use of simple beam-theory equations, eliminating need for time-consuming, difficult numerical analysis. Allows wider range of mode I/mode II ratios than possible with many other methods. Mixed-mode delamination testing of interest in all fields utilizing composite materials, used mostly in aerospace field, but also used in automobiles, lightweight armored military vehicles, boats, and sporting equipment. Useful in general lumber, plywood, and adhesive industries, as well.

Crews, John H., Jr.↗

Phased Array Beamforming and Imaging in Composite Laminates Using Guided Waves

This paper presents the phased array beamforming and imaging using guided waves in anisotropic composite laminates. A generic phased array beamforming formula is presented, based on the classic delay-and-sum principle. The generic formula considers direction-dependent guided wave properties induced by the anisotropic material properties of composites. Moreover, the array beamforming and imaging are performed in frequency domain where the guided wave dispersion effect has been considered. The presented phased array method is implemented with a non-contact scanning laser Doppler vibrometer (SLDV) to detect multiple defects at different locations in an anisotropic composite plate. The array is constructed of scan points in a small area rapidly scanned by the SLDV. Using the phased array method, multiple defects at different locations are successfully detected. Our study shows that the guided wave phased array method is a potential effective method for rapid inspection of large composite structures.

Tian, Zhenhua↗

Methods and systems for 3D printing with powders

A method of printing a three dimensional article (201) can include forming a bottom layer of the three dimensional article (201) by spraying a dry build material powder (210) onto a build platform (230) while heating the dry build material powder (210). The dry build material powder (210) can include metal or ceramic particles mixed with a polymeric binder having a softening point temperature. The dry build material powder (210) can be heated to a temperature above the softening point temperature such that the dry build material powder (210) adheres to the build platform (230). Subsequent layers can be formed by spraying dry build material powder (210) onto a lower layer while heating the dry build material powder (210) such that the dry build material powder (210) adheres to the lower layer.

Fang, Zhigang Zak↗

Fire safety experiments on MIR Orbital Station

The process of heterogeneous combustion of most materials under zero-g without forced motion of air is practically impossible. However, ventilation is required to support astronauts' life and cool equipment. The presence of ventilation flows in station compartments at accidental ignition can cause a fire. An additional, but exceedingly important parameter of the fire risk of solid materials under zero-g is the minimum air gas velocity at which the extinction of materials occurs. Therefore, the conception of fire safety can be based on temporarily lowering the intensity of ventilation and even turning it off. The information on the limiting conditions of combustion under natural conditions is needed from both scientific and practical points of view. It will enable us to judge the reliability of results of ground-based investigations and develop a conception of fire safety of inhabited sealed compartments of space stations to by provided be means of nontraditional and highly-effective methods without both employing large quantities of fire-extinguishing compounds and hard restrictions on use of polymers. In this connection, an experimental installation was created to study the process of heterogeneous combustion of solid non-metals and to determine the conditions of its extinction under microgravity. This installation was delivered to the orbital station 'Mir' and the cosmonauts Viktorenko and Kondakova performed initial experiments on it in late 1994. The experimental installation consists of a combustion chamber with an electrical systems for ignition of samples, a device for cleaning air from combustion products, an air suction unit, air pipes and a control panel. The whole experiment is controlled by telemetry and recorded with two video cameras located at two different places. Besides the picture, parameters are recorded to determine the velocity of the air flow incoming to the samples, the time points of switching on/off the devices, etc. The combustion chamber temperature is also controlled. The main objectives of experiments of this series were as follows: (1) verification of the reliability of the installation in orbital flight; (2) verification of the experimental procedure; and (3) investigation of combustion of two types of materials under microgravity at various velocities of the incoming air flow.

Egorov, S. D.↗

Enhancing Cluster Identification in Atom Probe Tomography Data Using Transfer Learning

Atom Probe Tomography (APT) is a powerful technique for visualizing the atomic-scale distribution of solutes in materials, but quantitative cluster analysis of APT datasets remains a challenge due to the need for subjective parameter selection in clustering algorithms. While distance-based and density-based methods such as HDBSCAN are widely used, their performance is highly sensitive to user-defined parameters, which undermines reproducibility and accuracy. This study proposes an image-based, deep learning-aided workflow for automating parameter selection and cluster detection in APT data analysis. By projecting 3D APT point clouds onto 2D planes, we leverage pretrained convolutional neural networks (ConvNeXt-Tiny and ResNet-50) through transfer learning to predict the number of clusters present in synthetic datasets. The output is used to guide K-means clustering and estimate HDBSCAN parameters, specifically minimum cluster size and minimum sample points. This approach reduces reliance on manual parameter tuning, improving consistency and scalability. The methodology demonstrates the feasibility of using image-based deep learning for interpreting complex spatial patterns in APT data, enabling faster and more objective analysis. The complete workflow and code are made publicly available to support reproducibility and future research.

Density-based clustering↗

Fabrication of High Surface Area Microporous ZnO from ZnO/Carbon Sacrificial Composite Monolith Template

Fabrication of porous materials from the standard sacrificial template method allows metal oxide nanostructures to be produced and have several applications in energy, filtration and constructing sensing devices. However, the low surface area of these nanostructures is a significant drawback for most applications. Here, we report the synthesis of ZnO/carbon composite monoliths in which carbon is used as a sacrificial template to produce zinc oxide (ZnO) porous nanostructures with a high specific surface area. The synthesized porous oxides of ZnO with a specific surface area of 78 m2/g are at least one order of magnitude higher than that of the ZnO nanotubes reported in the literature. The crucial point to achieving this remarkable result was the usage of a novel ZnO/carbon template where the carbon template was removed by simple heating in the air. As a high surface area porous nanostructured ZnO, these synthesized materials can be useful in various applications including catalysis, photocatalysis, separation, sensing, solar energy harvest and Zn-ion battery and as supercapacitors for energy storage.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

The influence of lattice defects, recombination, and clustering on thermal transport in single crystal thorium dioxide

Thermal transport is a key controlling property for thorium dioxide in many applications where defect-generating radiation fields are present. An understanding of the effect of nanoscale lattice defects on thermal transport in this material is currently unavailable due to a lack of high-quality, single crystal material from which unit processes may be investigated. In this work, a series of thorium dioxide single crystals are exposed to 2 MeV proton irradiation at room temperature and 600°C to create microscale regions with varying densities and types of point and extended defects. Defected regions are investigated using spatial domain thermoreflectance to quantify the change in thermal conductivity as a function of ion fluence as well as transmission electron microscopy and Raman spectroscopy to interrogate the structure of the generated defects. Together, this com- bination of methods provides important initial insight into defect formation, recombination, and clustering in thorium dioxide and the effect of those defects on thermal transport. These methods also provide a promising pathway for the quantification of the smallest-scale defects which cannot be captured using traditional microscopy techniques and play and outsized role in degrading thermal performance.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Atomistic Method Applied to Computational Modeling of Surface Alloys

The formation of surface alloys is a growing research field that, in terms of the surface structure of multicomponent systems, defines the frontier both for experimental and theoretical techniques. Because of the impact that the formation of surface alloys has on surface properties, researchers need reliable methods to predict new surface alloys and to help interpret unknown structures. The structure of surface alloys and when, and even if, they form are largely unpredictable from the known properties of the participating elements. No unified theory or model to date can infer surface alloy structures from the constituents properties or their bulk alloy characteristics. In spite of these severe limitations, a growing catalogue of such systems has been developed during the last decade, and only recently are global theories being advanced to fully understand the phenomenon. None of the methods used in other areas of surface science can properly model even the already known cases. Aware of these limitations, the Computational Materials Group at the NASA Glenn Research Center at Lewis Field has developed a useful, computationally economical, and physically sound methodology to enable the systematic study of surface alloy formation in metals. This tool has been tested successfully on several known systems for which hard experimental evidence exists and has been used to predict ternary surface alloy formation (results to be published: Garces, J.E.; Bozzolo, G.; and Mosca, H.: Atomistic Modeling of Pd/Cu(100) Surface Alloy Formation. Surf. Sci., 2000 (in press); Mosca, H.; Garces J.E.; and Bozzolo, G.: Surface Ternary Alloys of (Cu,Au)/Ni(110). (Accepted for publication in Surf. Sci., 2000.); and Garces, J.E.; Bozzolo, G.; Mosca, H.; and Abel, P.: A New Approach for Atomistic Modeling of Pd/Cu(110) Surface Alloy Formation. (Submitted to Appl. Surf. Sci.)). Ternary alloy formation is a field yet to be fully explored experimentally. The computational tool, which is based on the BFS (Bozzolo, Ferrante, and Smith) method for the calculation of the energetics, consists of a small number of simple PCbased computer codes that deal with the different aspects of surface alloy formation. Two analysis modes are available within this package. The first mode provides an atom-by-atom description of real and virtual stages 1. during the process of surface alloying, based on the construction of catalogues of configurations where each configuration describes one possible atomic distribution. BFS analysis of this catalogue provides information on accessible states, possible ordering patterns, and details of island formation or film growth. More importantly, it provides insight into the evolution of the system. Software developed by the Computational Materials Group allows for the study of an arbitrary number of elements forming surface alloys, including an arbitrary number of surface atomic layers. The second mode involves large-scale temperature-dependent computer 2. simulations that use the BFS method for the energetics and provide information on the dynamic processes during surface alloying. These simulations require the implementation of Monte-Carlo-based codes with high efficiency within current workstation environments. This methodology capitalizes on the advantages of the BFS method: there are no restrictions on the number or type of elements or on the type of crystallographic structure considered. This removes any restrictions in the definition of the configuration catalogues used in the analytical calculations, thus allowing for the study of arbitrary ordering patterns, ultimately leading to the actual surface alloy structure. Moreover, the Monte Carlo numerical technique used for the large-scale simulations allows for a detailed visualization of the simulated process, the main advantage of this type of analysis being the ability to understand the underlying features that drive these processes. Because of the simplicity of the BFS method for e energetics used in these calculations, a detailed atom-by-atom analysis can be performed at any point in the simulation, providing necessary insight on the details of the process. The main objective of this research program is to develop a tool to guide experimenters in understanding and interpreting often unexpected results in alloy formation experiments. By reducing the computational effort without losing physical accuracy, we expect that powerful simulation tools will be developed in the immediate future, which will allow material scientists to easily visualize and analyze processes at a level not achievable experimentally.

Bozzolo, Guillermo H.↗

Synergetic Ferroelectricity and Superconductivity in Zero-Density Dirac Semimetals near Quantum Criticality

Here, we study superconductivity in a three-dimensional zero-density Dirac semimetal in proximity to a ferroelectric quantum critical point. We find that the interplay of criticality, inversion-symmetry breaking, and Dirac dispersion gives rise to a robust superconducting state at the charge-neutrality point, where no Fermi surface is present. Using Eliashberg theory, we show that the ferroelectric quantum critical point is unstable against the formation of a ferroelectric density wave (FDW), whose fluctuations, in turn, lead to a first-order superconducting transition. Surprisingly, long-range superconducting and FDW orders are found to cooperate with each other, in contrast to the more usual scenario of phase competition. Therefore, we suggest that driving charge neutral Dirac materials, e.g., Pb x Sn 1–x Te, through a ferroelectric quantum critical point may lead to superconductivity intertwined with FDW order.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Theory and Implementation of the Spectacular Nonlinear Viscoelastic Constitutive Model

This report is a comprehensive guide to the nonlinear viscoelastic Spectacular model, which is an isotropic, thermo-rheologically simple constitutive model for glass-forming materials, such as amorphous polymers. Spectacular is intermediate in complexity to the previous PEC and SPEC models (Potential Energy Clock and Simplified Potential Energy Clock models, respectively). The model form consists of two parts: a Helmholtz free energy functional and a nonlinear material clock that controls the rate of viscoelastic relaxation. The Helmholtz free energy is derived from a series expansion about a reference state. Expressions for the stress and entropy functionals are derived from the Helmholtz free energy following the Rational Mechanics approach. The material clock depends on a simplified expression for the potential energy, which itself is a functional of the temperature and strain histories. This report describes the thermo-mechanical theory of Spectacular, the numerical methods for time-integrating the model, model verification for its implementation in LAMÉ, a user guide for its implementation in LAMÉ, and ideas for future work. A number of appendices provide supplementary mathematical details and a description of the procedure used to derive the simplified potential energy from the full expression for the potential energy. The goal of this report is create a convenient point-of-entry for engineers who wish to learn more about Spectacular, but also to serve as a reference manual for advanced users of the model.

36 MATERIALS SCIENCE↗

Investigating Core Gaps and the Development of Subcomponent Validation Methods for Wind Turbine Blades: Preprint

Core gaps are a common manufacturing defect observed in wind blade composite sandwich constructions, which occur when sheets of core material are not properly butted up against each other in the mold. The aim of this study was to characterize core gaps in composite sandwich constructions at the coupon scale. This was to gain an initial understanding of the defect before developing appropriate methodologies for more complex subcomponents as part of a much broader wind blade structural validation and damage tolerance program. Long beam flexure in 4-point-bending was chosen as the most appropriate loading scenario. Beam specimens were characterized with and without 10 mm core gaps in fiberglass/balsa sandwich beams. The core gaps were characterized with two separate resin systems; a Hexion epoxy and Arkema's Elium resins system (a novel, infusible thermoplastic). Results showed that the Elium beams without the core gaps were had a 15% lower static strength than their epoxy counterparts. The introduction of the core gap to the epoxy beams reduced their static strength by 35%. The Elium beams, however, exhibited negligible strength reductions with the inclusion of the core gap. Overall, this characterization study provided pertinent information with regards to core gaps as a manufacturing defect to allow for continued development of damage tolerance and subcomponent validation methodologies with the inclusion of manufacturing defects.

17 WIND ENERGY↗

Uncovering multiscale structure-property correlations via active learning in scanning tunneling microscopy

Atomic arrangements and local sub-structures fundamentally influence emergent material functionalities. These structures are conventionally probed using spatially resolved studies and the property correlations are deciphered by a researcher based on sequential explorations, thereby limiting the efficiency and scope. Here we demonstrate a multi-scale Bayesian deep-learning based framework that automatically correlates material structure with its electronic properties using scanning tunneling microscopy (STM) measurements in real-time. Its predictions are used to autonomously direct exploration toward regions of the sample that optimize a given material property. This method is deployed on a low-temperature ultra-high vacuum STM to understand the structure-property relationship in a europium-based semimetal, EuZn 2 As 2 , a promising candidate relevant to magnetism-driven topological phenomena. The framework employs a sparse-sampling approach to efficiently construct the scalar-property space using minimal measurements, about 1–10% of the data required in standard hyperspectral methods. Moreover, we formulate the problem hierarchically across length scales, implementing autonomous workflow to locate mesoscopic and atomic structures that correspond to a target material property. This framework offers the choice to design scalar-property from the spectroscopic data to steer sample exploration. Our findings reveal correlations of the electronic properties unique to surface terminations, local defect density, and point defects.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Automated optimization techniques for aircraft synthesis

Application of numerical optimization techniques to automated conceptual aircraft design is examined. These methods are shown to be a general and efficient way to obtain quantitative information for evaluating alternative new vehicle projects. Fully automated design is compared with traditional point design methods and time and resource requirements for automated design are given. The NASA Ames Research Center aircraft synthesis program (ACSYNT) is described with special attention to calculation of the weight of a vehicle to fly a specified mission. The ACSYNT procedures for automatically obtaining sensitivity of the design (aircraft weight, performance and cost) to various vehicle, mission, and material technology parameters are presented. Examples are used to demonstrate the efficient application of these techniques.

Vanderplaats, G. N.↗

Radial basis function network learns ceramic processing and predicts related strength and density

Radial basis function (RBF) neural networks were trained using the data from 273 Si3N4 modulus of rupture (MOR) bars which were tested at room temperature and 135 MOR bars which were tested at 1370 C. Milling time, sintering time, and sintering gas pressure were the processing parameters used as the input features. Flexural strength and density were the outputs by which the RBF networks were assessed. The 'nodes-at-data-points' method was used to set the hidden layer centers and output layer training used the gradient descent method. The RBF network predicted strength with an average error of less than 12 percent and density with an average error of less than 2 percent. Further, the RBF network demonstrated a potential for optimizing and accelerating the development and processing of ceramic materials.

Cios, Krzysztof J.↗