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At least 163 records · Page 9

In-situ digital image correlation and thermal monitoring in directed energy deposition additive manufacturing

As in welding, directed energy deposition (DED) additive manufacturing (AM) generates complex residual stresses and distortions commensurate with the complexity of the scan pattern used for deposition. To date, measuring DED distortions on complex geometries has only been achieved post process, discarding the complex thermomechanical history that leads to that final material state. In this work, surround stereo digital image correlation (DIC) is used to 3D map surfaces and strain tensors in-situ in a powder-blown laser DED system. Infrared thermography is then projected onto these surfaces to record the full thermomechanical history of printed parts. DIC presents a unique challenge to DED AM, as no part exists at the beginning of deposition, which (a) prevents application of an appropriate speckle pattern and (b) denies the user a zero strain reference frame. Solutions to these problems are proposed and their limitations explored herein. In sum, this work presents a relatively low-cost solution to monitoring and optimizing the unique temporal artifacts induced by complex scan strategies that was previously unobtainable.

42 ENGINEERING↗

Fiber Optic Strain Sensor for Planetary Gear Diagnostics

This paper presents a new sensing approach for helicopter damage detection in the planetary stage of a helicopter transmission based on a fiber optic strain sensor array. Complete helicopter transmission damage detection has proven itself a difficult task due to the complex geometry of the planetary reduction stage. The crowded and complex nature of the gearbox interior does not allow for attachment of sensors within the rotating frame. Hence, traditional vibration-based diagnostics are instead based on measurements from externally mounted sensors, typically accelerometers, fixed to the gearbox exterior. However, this type of sensor is susceptible to a number of external disturbances that can corrupt the data, leading to false positives or missed detection of potentially catastrophic faults. Fiber optic strain sensors represent an appealing alternative to the accelerometer. Their small size and multiplexibility allows for potentially greater sensing resolution and accuracy, as well as redundancy, when employed as an array of sensors. The work presented in this paper is focused on the detection of gear damage in the planetary stage of a helicopter transmission using a fiber optic strain sensor band. The sensor band includes an array of 13 strain sensors, and is mounted on the ring gear of a Bell Helicopter OH-58C transmission. Data collected from the sensor array is compared to accelerometer data, and the damage detection results are presented

Kiddy, Jason S.↗

Scalable Simulation of Pressure Gradient-Driven Transport of Rarefied Gases in Complex Permeable Media Using Lattice Boltzmann Method

Accurate representations of slip and transitional flow regimes present a challenge in the simulation of rarefied gas flow in confined systems with complex geometries. In these regimes, continuum-based formulations may not capture the physics correctly. This work considers a regularized multi-relaxation time lattice Boltzmann (LB) method with mixed Maxwellian diffusive and halfway bounce-back wall boundary treatments to capture flow at high Kn. The simulation results are validated against atomistic simulation results from the literature. We examine the convergence behavior of LB for confined systems as a function of inlet and outlet treatments, complexity of the geometry, and magnitude of pressure gradient and show that convergence is sensitive to all three. The inlet and outlet boundary treatments considered in this work include periodic, pressure, and a generalized periodic boundary condition. Compared to periodic and pressure treatments, simulations of complex domains using a generalized boundary treatment conserve mass but require more iterations to converge. Convergence behavior in complex domains improves at higher magnitudes of pressure gradient across the computational domain, and lowering the porosity deteriorates the convergence behavior for complex domains.

42 ENGINEERING↗

Assessment of Sodium Thermal Stratification Models Utilizing the TSTF Benchmark

As a result of certain transient scenarios, a thermally stratified layer of liquid sodium can develop in the bulk coolant volumes of a sodium-cooled fast reactor (SFR). In addition to the effects a stratification layer has on the temperature of the heat transport system, a stratification layer can also influence the transition to and establishment of natural circulation flow, which plays an important role in passive cooling and the inherent safety of a pool-type SFR. Therefore, the ability to accurately capture thermal stratification phenomena is important when demonstrating the safety basis of a pool-type SFR during transient sequences. The present work assesses various computational models with different fidelities in their ability to predict thermal stratification in the upper plenum of an SFR. Each computational model will be assessed using the data generated at the Thermal Stratification Test Facility (TSTF) located at the University of Wisconsin-Madison. Using measured flow rate and inlet temperature data, the measured temperature distributions of the tests are compared to the predictions of the lumped volume-based models in SAS4A/SASSYS-1, a 1D-based model in SAM, and a 3-D computational fluid dynamics (CFD) model using STAR-CCM+. The relative performance of the various computational methods is assessed with respect to key metrics such as bulk coolant temperature distribution and plenum exit temperature. A total of eight tests are analyzed, covering different combinations of flow rates (3 and 10 GPM) and upper internal structure (UIS) configurations (none, solid, porous, and open) The perfect mixing model of SAS4A/SASSYS-1 provides the highest accuracy when the flow rate is high and there is no UIS in the test vessel, as high flow rate injection promotes thermal mixing of the sodium in the test vessel. For most of the analyzed tests, the stratified volume model of SAS4A/SASSYS-1 is able to predict the delay in the outlet temperature drop and temperature distribution in the test vessel by a small number of layers to represent thermal stratification. However, the stratified volume model can only simulate a maximum of three temperature layers within a volume and when a layer approaches the elevation of the outlet, the predicted outlet temperature can demonstrate rapid, non-physical changes. The 1-D axial mixing model of SAM provides results that agree reasonably well with the measured data in the prediction of the temporal evolution of the outlet temperature with the exception of the case with a high flow rate and no UIS. The SAM 1-D model has a similar level of accuracy to CFD results when it comes to predicting the outlet temperature. CFD shows overall good agreement in predicting the temperature distribution in the test vessel and outlet temperature. As CFD can model the test vessel geometry in detail, it performs well in the cases of complex geometries such as tests that included a UIS and internal flow through the UIS resulting in active mixing of the coolant in the test vessel. Each of the models discussed in the present work has the potential to be useful during the various stages of reactor design, analysis, and licensing. The lumped-volume approach can be applied for fast turnaround safety calculations to obtain overall reactor behavior during transients. The 1-D models provide improved accuracy when stratification is expected for a relatively low increase in the computational cost. The CFD model can be utilized for confirmatory analysis of the 1-D model, when experimental measurements are not available.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Quantitative Electron Probe Microanalysis: State of the Art

Quantitative electron-probe microanalysis (EPMA) has improved due to better instrument design and X-ray correction methods. Design improvement of the electron column and X-ray spectrometer has resulted in measurement precision that exceeds analytical accuracy. Wavelength-dispersive spectrometer (WDS) have layered-dispersive diffraction crystals with improved light-element sensitivity. Newer energy-dispersive spectrometers (EDS) have Si-drift detector elements, thin window designs, and digital processing electronics with X-ray throughput approaching that of WDS Systems. Using these systems, digital X-ray mapping coupled with spectrum imaging is a powerful compositional mapping tool. Improvements in analytical accuracy are due to better X-ray correction algorithms, mass absorption coefficient data sets,and analysis method for complex geometries. ZAF algorithms have ban superceded by Phi(pz) algorithms that better model the depth distribution of primary X-ray production. Complex thin film and particle geometries are treated using Phi(pz) algorithms, end results agree well with Monte Carlo simulations. For geological materials, X-ray absorption dominates the corretions end depends on the accuracy of mass absorption coefficient (MAC) data sets. However, few MACs have been experimentally measured, and the use of fitted coefficients continues due to general success of the analytical technique. A polynomial formulation of the Bence-Albec alpha-factor technique, calibrated using Phi(pz) algorithms, is used to critically evaluate accuracy issues and can be also be used for high 2% relative and is limited by measurement precision for ideal cases, but for many elements the analytical accuracy is unproven. The EPMA technique has improved to the point where it is frequently used instead of the petrogaphic microscope for reconnaissance work. Examples of stagnant research areas are: WDS detector design characterization of calibration standards, and the need for more complete treatment of the continuum X-ray fluorescence correction.

Carpernter, P. K.↗

Conservative zonal schemes for patched grids in 2 and 3 dimensions

The computation of flow over complex geometries, such as realistic aircraft configurations, poses difficult grid generation problems for computational aerodynamicists. The creation of a traditional, single-module grid of acceptable quality about an entire configuration may be impossible even with the most sophisticated of grid generation techniques. A zonal approach, wherein the flow field is partitioned into several regions within which grids are independently generated, is a practical alternative for treating complicated geometries. This technique not only alleviates the problems of discretizing a complex region, but also facilitates a block processing approach to computation thereby circumventing computer memory limitations. The use of such a zonal scheme, however, requires the development of an interfacing procedure that ensures a stable, accurate, and conservative calculation for the transfer of information across the zonal borders.

Hessenius, Kristin A.↗

Progress in Grid Generation: From Chimera to DRAGON Grids

Hybrid grids, composed of structured and unstructured grids, combines the best features of both. The chimera method is a major stepstone toward a hybrid grid from which the present approach is evolved. The chimera grid composes a set of overlapped structured grids which are independently generated and body-fitted, yielding a high quality grid readily accessible for efficient solution schemes. The chimera method has been shown to be efficient to generate a grid about complex geometries and has been demonstrated to deliver accurate aerodynamic prediction of complex flows. While its geometrical flexibility is attractive, interpolation of data in the overlapped regions - which in today's practice in 3D is done in a nonconservative fashion, is not. In the present paper we propose a hybrid grid scheme that maximizes the advantages of the chimera scheme and adapts the strengths of the unstructured grid while at the same time keeps its weaknesses minimal. Like the chimera method, we first divide up the physical domain by a set of structured body-fitted grids which are separately generated and overlaid throughout a complex configuration. To eliminate any pure data manipulation which does not necessarily follow governing equations, we use non-structured grids only to directly replace the region of the arbitrarily overlapped grids. This new adaptation to the chimera thinking is coined the DRAGON grid. The nonstructured grid region sandwiched between the structured grids is limited in size, resulting in only a small increase in memory and computational effort. The DRAGON method has three important advantages: (1) preserving strengths of the chimera grid; (2) eliminating difficulties sometimes encountered in the chimera scheme, such as the orphan points and bad quality of interpolation stencils; and (3) making grid communication in a fully conservative and consistent manner insofar as the governing equations are concerned. To demonstrate its use, the governing equations are discretized using the newly proposed flux scheme, AUSM+, which will be briefly described herein. Numerical tests on representative 2D inviscid flows are given for demonstration. Finally, extension to 3D is underway, only paced by the availability of the 3D unstructured grid generator.

Liou, Meng-Sing↗

Computational Analysis of Static and Dynamic Behaviour of Magnetic Suspensions and Magnetic Bearings

Static modelling of magnetic bearings is often carried out using magnetic circuit theory. This theory cannot easily include nonlinear effects such as magnetic saturation or the fringing of flux in air-gaps. Modern computational tools are able to accurately model complex magnetic bearing geometries, provided some care is exercised. In magnetic suspension applications, the magnetic fields are highly three-dimensional and require computational tools for the solution of most problems of interest. The dynamics of a magnetic bearing or magnetic suspension system can be strongly affected by eddy currents. Eddy currents are present whenever a time-varying magnetic flux penetrates a conducting medium. The direction of flow of the eddy current is such as to reduce the rate-of-change of flux. Analytic solutions for eddy currents are available for some simplified geometries, but complex geometries must be solved by computation. It is only in recent years that such computations have been considered truly practical. At NASA Langley Research Center, state-of-the-art finite-element computer codes, 'OPERA', 'TOSCA' and 'ELEKTRA' have recently been installed and applied to the magnetostatic and eddy current problems. This paper reviews results of theoretical analyses which suggest general forms of mathematical models for eddy currents, together with computational results. A simplified circuit-based eddy current model proposed appears to predict the observed trends in the case of large eddy current circuits in conducting non-magnetic material. A much more difficult case is seen to be that of eddy currents in magnetic material, or in non-magnetic material at higher frequencies, due to the lower skin depths. Even here, the dissipative behavior has been shown to yield at least somewhat to linear modelling. Magnetostatic and eddy current computations have been carried out relating to the Annular Suspension and Pointing System, a prototype for a space payload pointing and vibration isolation system, where the magnetic actuator geometry resembles a conventional magnetic bearing. Magnetostatic computations provide estimates of flux density within airgaps and the iron core material, fringing at the pole faces and the net force generated. Eddy current computations provide coil inductance, power dissipation and the phase lag in the magnetic field, all as functions of excitation frequency. Here, the dynamics of the magnetic bearings, notably the rise time of forces with changing currents, are found to be very strongly affected by eddy currents, even at quite low frequencies. Results are also compared to experimental measurements of the performance of a large-gap magnetic suspension system, the Large Angle Magnetic Suspension Test Fixture (LAMSTF). Eddy current effects are again shown to significantly affect the dynamics of the system. Some consideration is given to the ease and accuracy of computation, specifically relating to OPERA/TOSCA/ELEKTRA.

Britcher, Colin P.↗

Development of Additively Manufactured Complex Tools for Autoclave Cure Composites

IACMI Project 4.9, Tooling for Composites with Washout Features Produced by Additive Manufacturing, assembled a team including the industry lead, Ability Composites, NREL and Colorado State University (CSU). Ability Composites had originally expressed interest in alternate methods of producing tooling for composite parts. In follow-up discussions, it became clear that one of the bigger tooling challenges revolved around small production volume composite parts that were tooled on washout material due to the complex geometry. To build an understanding of the potential, both from a technology and a cost perspective, for replacing conventional washout tooling with 3D printed thermoplastic tooling, a number of commercially available dissolvable FDM printing materials were evaluated, leading to tooling representative of commercial articles of interest to Ability Composites. Ultimately, Ability Composites was able to directly compare autoclave processed prepreg composite parts produced on conventional washout tooling to composite parts molded on 3D printed dissolvable tooling produced at CSU. Small, laboratory test specimens were developed to investigate the structural performance of the candidate materials under autoclave processing conditions, which were nominally 121 °C (250 °F) and 345 kPa (50 psi). In addition, several internal structural configurations (infills) were evaluated under autoclave conditions using model materials. The results of these tests indicated that two materials, Stratasys ST 130 and Infinite Materials Solutions Aquasys 180 (AQ 180), were the best candidates, given the specified autoclave processing conditions. ST-130 was slightly more robust than AQ-180; however, the AQ-180 was carried forward as it was dissolvable in water, not requiring the basic solution needed to dissolve ST-130. Based on the preliminary material and 3D printed structures evaluations, larger tools with a truncated square pyramid geometry were created to produce prepreg composite test articles for 3D printed dissolvable tool evaluation under standard autoclave fabrication conditions. Two tools were manufactured using ST-130 and one tool using traditional ceramic washout tooling media. The tools were evaluated for geometric fidelity and surface roughness changes before and after carbon fiber/epoxy prepreg composites were manufactured on the tooling. The autoclave processing did not impact the geometry significantly and was completed at 121 °C and 345 kPa, indicating satisfactory tool performance. The results from surface roughness testing of both the resulting composite and the associated tooling indicated that an adequate surface resulted without the need for a surface sealing step, as was required for the conventional washout tooling. Based on results of the truncated pyramid tests as a basis, ST-130, AQ-120 and AQ-180 materials were carried forward to the tool geometry of interest to Ability Composites. These hollow rectangular bent ducts, which were complex in nature and not extractable after cure, were used to understand the impacts of tool material and thickness. One ST-130 tool was produced as a partially solid part, with an enclosed 40% dense infill region to reduce weight and material use. This was the same approach evaluated in the truncated pyramid portion of the study. This tool was to be envelope vacuum bagged and directly compared to a monolithic tool of conventional washout material. The traditional monolithic ceramic tool was manufactured by Ability composites using CNC-based subtractive methods. An additional five dissolvable polymer tools, manufactured from ST-130, AQ-120, and AQ-180, using a hollow design were 3D printed and used to produce carbon fiber/epoxy composite evaluation articles. These hollow dissolvable tools were expected to be less influenced by the autoclave conditions as the wall was solid and vacuum bagging was inside and outside the tool. This alternative geometry was also evaluated as an option in techno-economic modeling. Print times were reduced from in excess of 3 days to under 30 hours, while surface quality and and tool integrity were substantially improved in the transition from the partially solid tool to the hollow tooling concept. Ability Composites produced autoclave-cured prepreg ducts on each of these tools. The autoclave conditions utilized were more severe than those of the initial trials, reaching temperatures of 160 °C and a pressure of 414 kPa. Under these conditions, the partially solid 3D printed tool with skin and 40% dense infill crushed significantly; however, the thicker ST-130 hollow tool showed good promise, deforming only slightly. The thinner hollow tool walls were unsuccessful as were the other materials. Overall, the hollow tool manufacturing process saved significant amounts of time and material in manufacturing as compared to the solid ducts and produced composite surface quality improvements compared to the traditional washout tooling. The TEM was developed to allow direct comparisons between conventional washout tool manufacturing processes and those developed at CSU. It also allowed for two separate 3D printed tool geometries to be analyzed and compared. In this case, the square bent duct tool geometry was determined to be representative of common washout tools. This geometry was compared with a scaled-up version of it to assess differences in the two manufacturing processes based on tool size. The model was developed to make use of user input in the form of geometry details, process steps, manufacturing parameters, bulk material costs, capital equipment costs, and general costs to calculate overall labor, material, capital equipment, and energy costs per manufactured tool for the conventional and additive manufacturing processes for the two representative geometries. It was also able to estimate step-by-step process times for the manufacturing process and geometries. Based on significant input from Ability Composites and CSU from their knowledge gained from hands-on manufacturing of the 3D printed bent duct tool geometry, costs and process times were calculated for the two manufacturing processes. Results showed that the additive manufacturing techniques developed at CSU can substantially reduce the costs of tool manufacturing by reducing labor times and material usage. This is because additive manufacturing is a relatively hands-off process and allows for the tool design to be optimized to reduce material usage. The disadvantage, however, is that process times for additive manufacturing are significantly longer. The three-dimensional (3D) printing process is slow if tight tolerances are required, but the analysis did show that print times could be reduced with the hollow tool geometry. Also, further advances in additive manufacturing could expedite the process. Costs and process times for the tool washout process were calculated separately. They showed that costs are relatively insignificant when compared to the overall tool manufacturing processes, but with increases in tool size, costs for the conventional manufacturing approach are larger than for additive manufacturing. Again, the washout process for conventional tools is very hands-on, whereas for additively manufactured tools the print medium is dissolved in an automated detergent bath at the sacrifice of process time. The analysis showed that optimizing the additively manufactured tools may also reduce washout times. Overall, Project 4.9 demonstrated that commercially available dissolvable 3D printing materials exist that can be used to produce dissolvable tooling capable of surviving prepreg composites fabrication under autoclave conditions of 121 °C (250 °F) and 345 kPa (50 psi). An alternative hollow dissolvable tool design was developed which was structurally superior to the initial concept and was cost and time effective versus conventional washout tooling. The 3D printed sacrificial tool required no added surface sealing steps prior to composite part layup and cure, offering a significant advantage over the porous conventional washout tooling.

36 MATERIALS SCIENCE↗

Experimental investigation of the crush performance of prepreg platelet molding compound tubes

This work presents an experimental study characterizing the crush performance of hollow cylindrical tubes made with prepreg platelet molding compound (PPMC). PPMC is a composite material system that uses platelets from chopped and slit unidirectional prepreg as the basis for a molding compound. This material system has a higher fiber volume fraction and better mechanical properties than traditional short fiber systems and can be molded into complex geometries unlike continuous fiber systems. As such, this material system shows promise for use with complex structural members in vehicles. The failure morphology and specific energy absorption of the material are evaluated with different thickness-to-diameter geometries and test speeds. In addition, this work investigates how PPMC components compare to traditional continuous fiber components and finds that PPMC performs as well as continuous fiber layups with similar effective laminate stiffnesses.

Materials Science↗

Factorization Machine‐Based Active Learning for Functional Materials Design with Optimal Initial Data

The optimization of functional materials is important to enhance their properties, but their complex geometries pose great challenges to optimization. Data-driven algorithms efficiently navigate such complex design spaces by learning relationships between material structures and performance metrics to discover high-performance functional materials. Surrogate-based active learning, continually improving its surrogate model by iteratively including high-quality data points, has emerged as a cost-effective data-driven approach. Furthermore, it can be coupled with quantum computing to enhance optimization processes, especially when paired with a special form of surrogate model (i.e., quadratic unconstrained binary optimization), formulated by factorization machine (FM). However, current practices often overlook the variability in design space sizes when determining the initial data size for optimization. In this work, we investigate the optimal initial data sizes required for efficient convergence across various design space sizes. By employing averaged piecewise linear regression, we identify initiation points where convergence begins, highlighting the crucial role of employing adequate initial data in achieving efficient optimization. These results contribute to the efficient optimization of functional materials by ensuring faster convergence and reducing computational costs in FM-based active learning.

active learning↗

Generating MCNP Input Files for Unstructured Mesh Geometries

Los Alamos National Laboratory's (LANL) Monte Carlo N-Particle (MCNP) transport code version 6 has the capability for tracking particles on unstructured mesh (UM) geometry models. The MCNP UM feature has been developed for performing calculations of complex geometry models. This capability tracks particles on hybrid geometries where finite element meshes are embedded into constructive solid geometry (CSG) cells. The MCNP UM feature was originally designed to read UM models created by Abaqus/CAE software suite. MCNP versions 6.2.0 and later can process UM models read from Abaqus input les or MCNPUM les converted from Abaqus input les. Sandia National Laboratory's Cubit Toolkit and other finite element analysis software packages may generate UM models and then convert these models into Abaqus input formats.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Transition Detection at Cryogenic Temperatures Using a Carbon-Based Resistive Heating Layer Coupled with Temperature Sensitive Paint

This paper will highlight the development and application of a carbon-based resistive heating layer for use in transition detection at cryogenic temperatures at the National Transonic Facility (NTF) for full-flight Reynolds number testing. This study builds upon previous work that was successfully demonstrated at the 0.3-m Transonic Cryogenic Tunnel on a smaller-scale airfoil shape of regular geometry. However, the test performed at the NTF involved a semispan wing with complex geometry and significantly larger than previous tests. This required the development of new coatings to provide suitable resistances to provide adequate heating rates for transition detection. Successful implementation of this technology has the ability to greatly enhance transition detection experiments at cryogenic temperatures as well as reducing perturbation in the tunnel caused by more traditional transition detection methods.

Watkins, A. Neal↗

Improved neutron activation prediction code system development

Two integrated neutron activation prediction code systems have been developed by modifying and integrating existing computer programs to perform the necessary computations to determine neutron induced activation gamma ray doses and dose rates in complex geometries. Each of the two systems is comprised of three computational modules. The first program module computes the spatial and energy distribution of the neutron flux from an input source and prepares input data for the second program which performs the reaction rate, decay chain and activation gamma source calculations. A third module then accepts input prepared by the second program to compute the cumulative gamma doses and/or dose rates at specified detector locations in complex, three-dimensional geometries.

Saqui, R. M.↗

Freeform Hybrid Manufacturing: Binderjet, Structured Light Scanning, Confocal Microscopy, and CNC Machining

This paper describes a hybrid manufacturing approach for silicon carbide (SiC) freeform surfaces using binder jet additive manufacturing (BJAM) to print the preform and machining to obtain the design geometry. Although additive manufacturing (AM) techniques such as BJAM allow for the fabrication of complex geometries, additional machining or grinding is often required to achieve the desired surface finish and shape. Hybrid manufacturing has been shown to provide an effective solution. However, hybrid manufacturing also has its own challenges, depending on the combination of processes. For example, when the subtractive and additive manufacturing steps are performed sequentially on separate systems, it is necessary to define a common coordinate system for part transfer. This can be difficult because AM preforms do not inherently contain features that can serve as datums. Additionally, it is important to confirm that the intended final geometry is contained within the AM preform. The approach described here addresses these challenges by using structured light scanning to create a stock model for machining. Results show that a freeform surface was machined with approximately 70 µm of maximum deviation from that which was planned.

Dvorak, Jake (ORCID:0000000260989944)↗

National Combustion Code Validated Against Lean Direct Injection Flow Field Data

Most combustion processes have, in some way or another, a recirculating flow field. This recirculation stabilizes the reaction zone, or flame, but an unnecessarily large recirculation zone can result in high nitrogen oxide (NOx) values for combustion systems. The size of this recirculation zone is crucial to the performance of state-of-the-art, low-emissions hardware. If this is a large-scale combustion process, the flow field will probably be turbulent and, therefore, three-dimensional. This research dealt primarily with flow fields resulting from lean direct injection (LDI) concepts, as described in Research & Technology 2001. LDI is a concept that depends heavily on the design of the swirler. The LDI concept has the potential to reduce NOx values from 50 to 70 percent of current values, with good flame stability characteristics. It is cost effective and (hopefully) beneficial to do most of the design work for an LDI swirler using computer-aided design (CAD) and computer-aided engineering (CAE) tools. Computational fluid dynamics (CFD) codes are CAE tools that can calculate three-dimensional flows in complex geometries. However, CFD codes are only beginning to correctly calculate the flow fields for complex devices, and the related combustion models usually remove a large portion of the flow physics.

Iannetti, Anthony C.↗

Learning interpretable surface elasticity properties from bulk properties via neural network equation learners

Surface elasticity is central to understanding the mechanics and stability of surfaces and interfaces. It is characterized by quantities such as surface tension, residual surface stress, and surface stiffness. However their analytical expressions are typically difficult to derive from atomistic data, and depend strongly on modeling choices. This work presents a neural network-based equation learner which combines customized activation functions and connection-based pruning to discover parsimonious, closed-form equations for surface elasticity from atomistic simulations. Applying the method to seven face-centered cubic (FCC) metals, our equation learner uncovers interpretable equations that describe both low-Miller index and high-Miller index surface properties, capturing long-tail property distributions accurately. The discovered expressions are decoupled into two components: a universal, geometry-driven orientation function, and material-specific baseline coefficients. We find that lower-order properties such as surface tension are fundamentally geometry dependent, while higher-order properties such as surface stress and elasticity show more complex geometry and material dependence. We also relate material dependent coefficients to bulk properties, forming a clear map from bulk material properties to surface elasticity. Overall, this approach demonstrates that interpretable neurosymbolic machine learning can bridge the gap between atomistic simulations and physical laws, enabling the discovery of generalizable structure–property relationships for materials science phenomena such as surface elasticity.

Equation learning↗

Optimal design of acoustic metamaterial cloaks under uncertainty

In this work, we consider the problem of optimal design of an acoustic cloak under uncertainty and develop scalable approximation and optimization methods to solve this problem. The design variable is taken as an infinite-dimensional spatially-varying field that represents the material property, while an additive infinite-dimensional random field represents the variability of the material property or the manufacturing error. Discretization of this optimal design problem results in high-dimensional design variables and uncertain parameters. To solve this problem, we develop a computational approach based on a Taylor approximation and an approximate Newton method for optimization, which is based on a Hessian derived at the mean of the random field. We show our approach is scalable with respect to the dimension of both the design variables and uncertain parameters, in the sense that the necessary number of acoustic wave propagations is essentially independent of these dimensions, for numerical experiments with up to one million design variables and half a million uncertain parameters. Additionally, we demonstrate that, using our computational approach, an optimal design of the acoustic cloak that is robust to material uncertainty is achieved in a tractable manner. The optimal design under uncertainty problem is posed and solved for the classical circular obstacle surrounded by a ring-shaped cloaking region, subjected to both a single-direction single-frequency incident wave and multiple-direction multiple-frequency incident waves. Finally, we apply the method to a deterministic large-scale optimal cloaking problem with complex geometry, to demonstrate that the approximate Newton method’s Hessian computation is viable for large, complex problems.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗