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Acoustic-based monitoring and machine learning of component status for microreactor applications
This report provides a description and assessment of recent efforts to couple acoustic-based experimental measurements and characterization with machine learning models in order to enhance structural health monitoring capabilities for nuclear microreactors. With resilient embedded sensors in development by others supported by programs funded by the US Department of Energy’s Office of Nuclear Energy, the work described herein builds upon ongoing efforts to improve non-destructive testing technology that relates measured acoustic signatures to component stresses and/or structural defects, using a combination of new experimental measurements and machine learning architectures. The experimental procedure remained similar to that developed for the previous year’s demonstration of damage detection by the authors, with the same damaged sample tested under similar applied stress conditions. Notably, a new mounting fixture was designed and implemented to improve measurement consistency and a more sophisticated laser Doppler vibrometer was employed to make high-fidelity vibration measurements. Two nominally identical sets of training data were collected for each experimental setup to better understand the repeatability of the experiment and to better test the generality of trained neural network models. Additionally, we obtained new high-quality 3D mode shapes of the damaged test article at various stress and excitation levels, providing greater insights into the physical response of the sample during testing. Previously, we demonstrated that a machine learning model based on a convolutional neural network can predict structural details of an artificially introduced interface (intact, rough cut, smooth cut), and the applied torque level. In this study, we have transitioned to graph-based neural network architectures to better develop and test a flexible framework that is more suitable to being transferred away from controlled benchtop experiments and into more applied settings where less-structured data inputs may be expected. In general, performance testing of a graph neural network on frequency-domain representations of the data indicates strong and consistent identification of test conditions for datasets recorded on damaged components. With goals of predicting damage location and other changing experimental conditions using limited datasets, predictive models using a graph neural network architecture correctly predicted the applied torque level with an accuracy of 85% using only a single measurement point and predicted within one torque level in 95% of test windows. Predictions of damage location had limited success due to the symmetry and minimal number of the damage scenarios presented during model training. Results were ambiguous as to whether the model could detect the location of the artificial damage, or if it was instead learning the location of a given measurement point on the part and subsequently detecting which points were closest to the location of the damage. This finding will be factored into upcoming planned work on damaged graphite components, where new experimental tests with a larger number and variety of damage scenarios are expected to provide improved validation of recent developments in monitoring methodology.
Effects of Focused Ion Beam Lithography on La 2– x Sr x CuO 4 Single Crystals
Focused ion beam (FIB) milling is a mask-free lithography technique that allows the precise shaping of 3D materials on the micron and sub-micron scale. The recent discovery of electronic nematicity in La 2–x Sr x CuO 4 (LSCO) thin films triggered the search for the same phenomenon in bulk LSCO crystals. With this motivation, we have systematically explored FIB patterning of bulk LSCO crystals into micro-devices suitable for longitudinal and transverse resistivity measurements. We found that several detrimental factors can affect the result, ultimately compromising the possibility of effectively using FIB milling to fabricate sub-micrometer LSCO devices, especially in the underdoped regime.
Waverider design for generalized shock geometries
A new design method for waverider configurations with generalized shock geometries is presented. A cross-stream Euler marching procedure is used to define the post-shock flow field, and an arbitrary 3D shock shape is specified as an input. This approach makes it possible to use nonaxisymmetric shock topologies with nonconstant shock strengths. The problem is reformulated in the proper curvilinear coordinate system to suppress its fundamental ill-posedness.
An Overview of 2014 SBIR Phase 1 and Phase 2 Air-Breathing Propulsion
NASA's Small Business Innovation Research (SBIR) program focuses on technological innovation by investing in development of innovative concepts and technologies to help NASA mission directorates address critical research needs for Agency programs. This report highlights nine of the innovative SBIR 2014 Phase I and Phase II projects that emphasize one of NASA Glenn Research Center's six core competencies-Air-Breathing Propulsion. The technologies cover a wide spectrum of applications such as development of X-ray computed tomography (CT) imaging method for the measurement of complex 3D ice shapes, phased array techniques for low signal-to-noise ratio wind tunnels, compact kinetic mechanisms for petroleum-derived and alternative aviation fuels, and hybrid electric propulsion systems for a multirotor aircraft. Each featured technology describes an innovation, technical objective, and highlights NASA commercial and industrial applications. This report provides as an opportunity for NASA engineers, researchers, and program managers to learn how NASA SBIR technologies could help their programs and projects, and lead to collaborations and partnerships between the small SBIR companies and NASA that would benefit both.
Versatile stochastic model for predictive KMC simulation of fcc metal nanostructure evolution with realistic kinetics
Stochastic lattice-gas models provide the natural framework for analysis of the surface diffusion-mediated evolution of crystalline metal nanostructures on the appropriate time scale (often 10 1 –10 4 s) and length scale. Model behavior can be precisely assessed by kinetic Monte Carlo simulation, typically incorporating a rejection-free algorithm to efficiently handle the broad range of Arrhenius rates for hopping of surface atoms. The model should realistically prescribe these rates, or the associated barriers, for a diversity of local surface environments. However, commonly used generic choices for barriers fail, even qualitatively, to simultaneously describe diffusion for different low-index facets, for terrace vs step edge diffusion, etc. We introduce an alternative Unconventional Interaction–Conventional Interaction formalism to prescribe these barriers, which, even with few parameters, can realistically capture most aspects of behavior. Here, the model is illustrated for single-component fcc metal systems, mainly for the case of Ag. It is quite versatile and can be applied to describe both the post-deposition evolution of 2D nanostructures in homoepitaxial thin films (e.g., reshaping and coalescence of 2D islands) and the post-synthesis evolution of 3D nanocrystals (e.g., reshaping of nanocrystals synthesized with various faceted non-equilibrium shapes back to 3D equilibrium Wulff shapes).
Chemically controlled shape-morphing of elastic sheets
Two-dimensional responsive materials that change shape into complex three-dimensional structures are valuable for creating systems ranging from wearable electronics to soft robotics. Typically, the final 3D structure is unique and predetermined through the materials’ processing. Here, we use theory and simulation to devise a distinctive approach for driving shape changes of 2D elastic sheets in fluid-filled microchambers. The sheets are coated with catalyst to generate controllable fluid flows, which transform the sheets into complex 3D shapes. A given shape can be achieved by patterning the arrangement of the catalytic domains on the sheet and introducing the appropriate reactant to initiate a specific catalytic reaction. Moreover, a single sheet that encompasses multiple catalytic domains can be transformed into a variety of 3D shapes through the addition of one or more reactants. Materials systems that morph on-demand into a variety of distinct structures can simplify manufacturing processes and broaden the utility of soft materials.
Crystal structure and shape selection in the growth of 3D metallic crystallites on layered materials: Fe on MoS 2
Nucleation and growth of supported 3D metal clusters or crystallites during deposition on MoS 2 , or on other weakly-adhering layered materials, can potentially produce diverse growth shapes, and even crystal structures differing from the bulk metal. For Fe deposition on MoS 2 , SEM and AFM observations reveal three distinct crystallite shapes. By comparison with atomistic structure models incorporating realistic Fe-MoS 2 interface structures, here we conclude that these are: triangular fcc(111) pyramids with sloped {100} side facets; bcc(110) A-frame tents with sloped {100} side facets; and bcc(110) mesas with vertical {100} and {110} side facets. The following picture is proposed for the competitive formation of clusters and crystallites with different structures: (i) small nanoclusters formed at the onset of deposition exhibit facile fluxional dynamics allowing sampling of different crystal structures and shapes; (ii) sufficient fluxionality implies a Boltzmann distribution of sampled structures, and thus coexistence of different structures follows from the demonstrated similar energies for those structures; (iii) growing clusters reach a threshold size above which the characteristic time scale for restructuring exceeds that for cluster growth. Thereafter, clusters are locked-in to a specific crystal structure and shape as revealed by imaging of larger crystallites. Despite a penalty for fcc(111) over bcc(111) pyramids based on bulk energetics, favorable surface and interface energies makes them preferable for smaller sizes.
Bridging the Bondi and Event Horizon Scales: 3D GRMHD Simulations Reveal X-shaped Radio Galaxy Morphology
X-shaped radio galaxies (XRGs) produce misaligned X-shaped jet pairs and make up ≲10% of radio galaxies. XRGs are thought to emerge in galaxies featuring a binary supermassive black hole (SMBH), SMBH merger, or large-scale ambient medium asymmetry. We demonstrate that XRG morphology can naturally form without such special, preexisting conditions. Our 3D general-relativistic magnetohydrodynamic (GRMHD) simulation for the first time follows magnetized rotating gas from outside the SMBH sphere of influence of radius RB to the SMBH of gravitational radius Rg at the largest scale separation, RB/Rg = 103, to date. Initially, our axisymmetric system of constant-density hot gas contains a weak vertical magnetic field and rotates in the equatorial plane of a rapidly spinning SMBH. We seed the gas with small-scale 2% level pressure perturbations. Infalling gas forms an accretion disk, and the SMBH launches relativistically magnetized collimated jets reaching well outside RB. Under the pressure of the infalling gas, the jets intermittently turn on and off, erratically wobble, and inflate pairs of cavities in different directions, resembling an X-shaped jet morphology. Synthetic X-ray images reveal multiple pairs of jet-powered shocks and cavities. Large-scale magnetic flux accumulates on the SMBH, becomes dynamically important, and leads to a magnetically arrested disk state. The SMBH accretes at 2% of the Bondi rate ($\dot{M}\simeq 2.4\times {10}^{-3}{M}_{\odot }\,{\mathrm{yr}}^{-1}$ for M87*) and launches twin jets at η = 150% efficiency. These jets are powerful enough (P jets ≃ 2 × 10 44 erg s -1 ) to escape along the SMBH spin axis and end the short-lived intermittent jet state, whose transient nature can account for the rarity of XRGs.
Extrudable magnetic ink and novel 3D printing method to fabricate bonded magnets of complex shape
A magnetic ink composition for three-dimensional (3D) printing a bonded magnet is provided. The magnetic ink composition includes magnetic particles, a polymer binder and a solvent. A 3D printing method for fabrication of a bonded magnet using the magnetic ink composition is also provided.
Near net shape bulk laminated silicon iron electric steel for improved electrical resistance and low high frequency loss
The invention involves producing discontinuous, flake-shaped particles of a soft magnetic material, coating the flake-shaped particles with an electrically insulating coating, and consolidating the coated flaked-shaped particles to form a soft magnetic bulk shape. The consolidated bulk shape can comprise a layer or a simple or complex 3D magnet part shape, which has a consolidated layered microstructure that includes laminated soft magnetic regions that are substantially encapsulated by an electrical insulating layer to increase the resistivity of soft magnetic material, especially when used in silicon iron magnet parts.
Shape evolution and growth mechanisms of 3D-printed nanowires
3D printing of nanowires using Focused Electron Beam Induced Deposition (FEBID) enables the direct-write fabrication of complex 3D objects on almost any substrate surface. The physical properties of such freestanding structures are determined by the dimensions of constituent nanowires. However, little knowledge is available about the exact shape of the nanowires, which is indispensable for calculations and simulations as well as for optimization in applications. In this study, we evaluate the thicknesses and widths of freestanding segments as a function of the inclination angles, primary electron energy, beam currents, and precursor flux. Furthermore, the cross-sectional shape, the cross-sectional area, and the evolution along the length of the wire are investigated. Basing on detailed scanning electron microscopy measurements and Monte Carlo/Finite Differences simulations, the effects that the growth parameters have on the segment growth are elucidated. Furthermore, the results shed light on the growth evolution of the structures and form the basis for future studies on the fabrication of high-precision, arbitrarily shaped nanowires.
The shape of convection in 2D and 3D global simulations of stellar interiors
Context. Theoretical descriptions of convective overshooting in stellar interiors often rely on a basic one-dimensional parameterization of the flow called the filling factor for convection. Several different definitions of the filling factor have been developed for this purpose, based on: (1) the percentage of the volume, (2) the mass flux, and (3) the convective flux that moves through the boundary. Aims. We examine these definitions of the filling factor with the goal of establishing their ability to explain differences between 2D and 3D global simulations of stellar interiors that include fully compressible hydrodynamics and realistic microphysics for stars. Methods. We study convection and overshooting in pairs of identical two-dimensional (2D) and three-dimensional (3D) global simulations of stars produced with MUSIC , a fully compressible, time-implicit hydrodynamics code. We examine pairs of simulations for (1) a 3 M ⊙ red giant star near the first dredge-up point, (2) a 1 M ⊙ pre-main-sequence star with a large convection zone, (3) the current sun, and (4) a 20 M ⊙ main-sequence star with a large convective core. Results. Our calculations of the filling factor based on the volume percentage and the mass flux indicate asymmetrical convection near the surface for each star with an outer convection zone. However, near the convective boundary, convective flows achieve inward-outward symmetry for each star that we study; for 2D and 3D simulations, these filling factors are indistinguishable. A filling factor based on the convective flux is contaminated by boundary-layer-like flows, making a theoretical interpretation difficult. We present two possible new alternatives to these frequently used definitions of a filling factor, which instead compare flows at two different radial points. The first alternative is the penetration parameter of Anders et al. (2022, ApJ, 926, 169). The second alternative is a new statistic that we call the plume interaction parameter. We demonstrate that both of these parameters captures systematic differences between 2D and 3D simulations around the convective boundary.
A Nickel-Decorated Carbon Flower/Sulfur Cathode for Lean-Electrolyte Lithium–Sulfur Batteries
Lithium–sulfur (Li–S) batteries involve a reversible conversion reaction between sulfur and lithium sulfide (Li 2 S) via a series of soluble lithium polysulfide intermediates (LiPSs), enabling a high theoretical specific capacity of 1675 mAh g –1 . However, this process exhibits large polarization and low sulfur utilization and suffers critical capacity fade. The primary approach to tackle the problem has so far been to infiltrate sulfur into nanostructured carbon. Furthermore, most studies using porous carbon as host materials have tested with high electrolyte to sulfur ratios (E/S) (generally > 15 µL mg –1 ) that compromise the cell-level energy density. Here, a flower-shaped porous carbon structure with nickel nanoparticles that can address the problems discussed above is designed. First, the 3D flower-shaped carbon structure enables short ionic transport lengths. Second, the small pore diameters <10 nm and high specific surface areas > 3300 m 2 g –1 with sufficient pore volume are ideal for charging performance for low E/S ratios. Finally, Ni nanoparticles are employed onto the flower-shaped network to improve the reaction kinetics. Collectively, it is successfully demonstrated that the batteries with a high mass loading of 5 mg cm –2 and a 5 µL mg –1 E/S ratio can retain cycle retention of 70% after 150 cycles.
Ink Casting and 3D‐Extrusion Printing of Yb 14 MnSb 11 for High‐Temperature Thermoelectric Material
Abstract Complex shapes are created from Yb 14 MnSb 11 , a high‐temperature thermoelectric Zintl phase, via a two‐step process: i) layer‐by‐layer 3D‐extrusion of ink containing partially‐reacted powders which are ball‐milled from a blend of Yb, MnSb, and Sb powders; ii) heat treatment to synthesize the ternary compound Yb 14 MnSb 11 and densify the extruded powders. A high phase purity for Yb 14 MnSb 11 (83–94%) is achieved in both cast and 3D‐extruded ink specimens via a solid‐state reaction between Yb, MnSb, and Yb 4 Sb 3 during reactive sintering. Pressure‐free sintering at temperatures of 1200–1400 °C densifies the powders to 82% relative density but can also induce the decomposition of the Yb 14 MnSb 11 phase due to Yb sublimation. A process window with optimized sintering temperature and time is identified, achieving both low porosity and high phase purity and reaching a maximum zT = 0.61 at 1000 °C, about half of the maximum zT value for bulk Yb 14 MnSb 11 made via conventional processes (pressure sintering of precursor powders). The present approach – direct ink writing of ball‐milled powders, combined with reactive sintering – is a scalable and affordable method to fabricate thermoelectric legs with intricate 3D shapes, for enhanced performances in high‐temperature thermoelectric applications.
Macroscale Control of Reactivity using 3D Printed Materials with Intrinsic Catalytic Properties
The morphology of heterogeneous catalysts can impact their performance. However, standard manufacturing methods like extrusion or pelleting offer little options for tailoring catalyst shape. Herein, stereolithographic 3D printing is used to produce catalysts with controlled topologies to enhance their performance. A series of magnetic stir-bar compartments (SBC) were 3D printed and tested as catalysts for sucrose hydrolysis. The SBC were printed using acrylic acid (AA) and 1,6-hexanediol diacrylate (HDDA) as acid sites and hydrophobic crosslinking domains, respectively. Variations in the number and tilt direction of the SBC blades produced significant changes in their apparent catalytic activities. These changes resulted from differences in the fraction of active surface effectively interacting with the reactants in solution, as revealed by computational fluid dynamics simulations. Moreover, varying HDDA:AA ratios in SBC regulated reactant-surface interactions to control catalytic activity. Overall, 3D printing catalysts enables quick performance optimization by simultaneously controlling macroscopic structure and molecular composition.
High-Fidelity Roadway Modeling and Simulation
Roads are an essential feature in our daily lives. With the advances in computing technologies, 2D and 3D road models are employed in many applications, such as computer games and virtual environments. Traditional road models were generated by professional artists manually using modeling software tools such as Maya and 3ds Max. This approach requires both highly specialized and sophisticated skills and massive manual labor. Automatic road generation based on procedural modeling can create road models using specially designed computer algorithms or procedures, reducing the tedious manual editing needed for road modeling dramatically. But most existing procedural modeling methods for road generation put emphasis on the visual effects of the generated roads, not the geometrical and architectural fidelity. This limitation seriously restricts the applicability of the generated road models. To address this problem, this paper proposes a high-fidelity roadway generation method that takes into account road design principles practiced by civil engineering professionals, and as a result, the generated roads can support not only general applications such as games and simulations in which roads are used as 3D assets, but also demanding civil engineering applications, which requires accurate geometrical models of roads. The inputs to the proposed method include road specifications, civil engineering road design rules, terrain information, and surrounding environment. Then the proposed method generates in real time 3D roads that have both high visual and geometrical fidelities. This paper discusses in details the procedures that convert 2D roads specified in shape files into 3D roads and civil engineering road design principles. The proposed method can be used in many applications that have stringent requirements on high precision 3D models, such as driving simulations and road design prototyping. Preliminary results demonstrate the effectiveness of the proposed method.