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At least 1,207 records · Page 67

Physics-informed neural networks for identification of material properties using standing waves

A metallic structure in its initial stage of failure involves plastic deformation or environmental degradation that changes the elastic modulus and density. This work presents the detection of change in wave velocity (a function of elastic modulus and density) as a system identification problem. A physics-informed neural network (PINN) is proposed to solve the system identification problem. The PINN takes the spatial coordinates of scanning locations and time as inputs and provides the displacement and wave velocity as outputs. The governing partial differential equation of standing waves in a rod is incorporated into the neural network as physics in the form of a loss function. The wave velocity vector is randomly initiated. During the training of the network, physics is used to determine and update the wave velocity target vector from the network’s displacement predictions. The measured data, comprising sparse displacement response on the rod structure, are used to train the PINN. The wave velocity at the sparse locations on the rod is learned from the predicted displacements during the training. Using the predictions of the trained network, the response of free vibration or material property variation can be reconstructed at unscanned locations on the structure to obtain high-resolution maps for full-field imaging to detect and localize the changes caused by plastic deformation. The PINN’s sparse scanning and simultaneous prediction capability during training can lead to high scanning and data-processing speeds. This capability yields a nondestructive evaluation system that can predict the presence of degraded material locations as the structural vibrations are scanned and processed in real time.

Rathod, Vivek↗

Structural Benchmark Testing of Superalloy Lattice Block Subelements Completed

Superalloy lattice block panels, which are produced directly by investment casting, are composed of thin ligaments arranged in three-dimensional triangulated trusslike structures (see the preceding figure). Optionally, solid panel face sheets can be formed integrally during casting. In either form, lattice block panels can easily be produced with weights less than 25 percent of the mass of a solid panel. Inconel 718 (IN 718) and MarM-247 superalloy lattice block panels have been developed under NASA's Ultra-Efficient Engine Technology Project and Higher Operating Temperature Propulsion Components Project to take advantage of the superalloys' high strength and elevated temperature capability with the inherent light weight and high stiffness of the lattice architecture (ref. 1). These characteristics are important in the future development of turbine engine components. Casting quality and structural efficiency were evaluated experimentally using small beam specimens machined from the cast and heat treated 140- by 300- by 11-mm panels. The matrix of specimens included samples of each superalloy in both open-celled and single-face-sheet configurations, machined from longitudinal, transverse, and diagonal panel orientations. Thirty-five beam subelements were tested in Glenn's Life Prediction Branch's material test machine at room temperature and 650 C under both static (see the following photograph) and cyclic load conditions. Surprisingly, test results exceeded initial linear elastic analytical predictions. This was likely a result of the formation of plastic hinges and redundancies inherent in lattice block geometry, which was not considered in the finite element models. The value of a single face sheet was demonstrated by increased bending moment capacity, where the face sheet simultaneously increased the gross section modulus and braced the compression ligaments against early buckling as seen in open-cell specimens. Preexisting flaws in specimens were not a discriminator in flexural, shear, or stiffness measurements, again because of redundant load paths available in the lattice block structure. Early test results are available in references 2 and 3; more complete analyses are scheduled for publication in 2004.

Source record↗

Carbon Nanofiber-Based, High-Frequency, High-Q, Miniaturized Mechanical Resonators

High Q resonators are a critical component of stable, low-noise communication systems, radar, and precise timing applications such as atomic clocks. In electronic resonators based on Si integrated circuits, resistive losses increase as a result of the continued reduction in device dimensions, which decreases their Q values. On the other hand, due to the mechanical construct of bulk acoustic wave (BAW) and surface acoustic wave (SAW) resonators, such loss mechanisms are absent, enabling higher Q-values for both BAW and SAW resonators compared to their electronic counterparts. The other advantages of mechanical resonators are their inherently higher radiation tolerance, a factor that makes them attractive for NASA s extreme environment planetary missions, for example to the Jovian environments where the radiation doses are at hostile levels. Despite these advantages, both BAW and SAW resonators suffer from low resonant frequencies and they are also physically large, which precludes their integration into miniaturized electronic systems. Because there is a need to move the resonant frequency of oscillators to the order of gigahertz, new technologies and materials are being investigated that will make performance at those frequencies attainable. By moving to nanoscale structures, in this case vertically oriented, cantilevered carbon nanotubes (CNTs), that have larger aspect ratios (length/thickness) and extremely high elastic moduli, it is possible to overcome the two disadvantages of both bulk acoustic wave (BAW) and surface acoustic wave (SAW) resonators. Nano-electro-mechanical systems (NEMS) that utilize high aspect ratio nanomaterials exhibiting high elastic moduli (e.g., carbon-based nanomaterials) benefit from high Qs, operate at high frequency, and have small force constants that translate to high responsivity that results in improved sensitivity, lower power consumption, and im - proved tunablity. NEMS resonators have recently been demonstrated using topdown, lithographically fabricated ap - proaches to form cantilever or bridgetype structures. Top-down approaches, however, rely on complicated and expensive e-beam lithography, and often require a release mechanism. Reso - nance effects in structures synthesized using bottom-up approaches have also recently been reported based on carbon nanotubes, but such approaches have relied on a planar two-dimensional (2D) geometry. In this innovation, vertically aligned tubes synthesized using a bottom- up approach have been considered, where the vertical orientation of the tubes has the potential to increase integration density even further. The simulation of a vertically oriented, cantilevered carbon nanotube was performed using COMSOL Multi - physics, a finite element simulation package. All simulations were performed in a 2D geometry that provided consistent results and minimized computational complexity. The simulations assumed a vertically oriented, cantilevered nanotube of uniform density (1.5 g/cu cm). An elastic modulus was assumed to be 600 GPa, relative permittivity of the nanotube was assumed to be 5.0, and Poisson s ratio was assumed to be 0.2. It should be noted that the relative permittivity and Poisson s ratio for the nanotubes of interest are not known accurately. However, as in previous simulations, the relative permittivity and Poisson s ratios were treated as weak variables in the simulation, and no significant changes were recognized when these variables were varied.

Kaul, Anupama B.↗

Predicting the viscoplastic response of a crystallizing fluoropolymer using transient network theory

We employ a molecular theory of dynamic polymer networks to describe the viscoplastic response of rubbery FK-800, a thermoplastic copolymer of chlorotrifluoroethylene and vinylidene fluoride, over a broad range of thermal histories. The kinetics of crystallization at different annealing temperatures was modeled using a modified Avrami equation, whose parameters were found to evolve through simple relationships over the full temperature range of the rubbery state. By fitting experimental compression data, we discovered predictable trends for the physical parameters in our mechanical model over its full range of crystallinities (up to ≈20%) and provided insights based on molecular-level physics to justify them. Using this, an end-to-end model was developed to predict the yielding and post-yield behavior of rubbery FK-800 for arbitrary thermal histories. The model successfully predicted the highly nonlinear evolution of characteristic mechanical signatures (stiffness, yield point, post-yield drop) throughout the crystallization process. A statistical analysis of variance test was employed to determine that the measured variations in the mechanical behavior of rubbery FK-800 are primarily dictated by its fractional crystallinity, regardless of its exact thermal history.

36 MATERIALS SCIENCE↗

TRISO SiC Failure Probability for Reactivity Initiated Accidents in High-Temperature Gas-Cooled Reactors

This work analyzes the failure process of the silicon carbide (SiC) layer in tristructural isotropic (TRISO) during reactivity-initiated accident scenarios for a high-temperature gas-cooled reactor (HTGR) with BISON. Two cases are considered—a group control rod withdrawal (CRW) and a control rod ejection (CRE)—reproduced from a previous study. Failure probability is modeled using Weibull statistics, and worst-case scenario Weibull parameters are adopted to simulate the envelopes in BISON with a one-dimensional TRISO model. CRW scenario results are characterized by higher values of maximum energy deposition and final temperature and volumetric strain with respect to the CRE ones, but the latter have remarkably higher SiC failure probability, mainly due to the offset in strain rates between the two cases. This work also confirms the validity and conservatism of the performance envelopes produced in a previous work by replicating the envelope formulation using RELAP5-3D and RAVEN with a different sampling technique and obtaining consistent results. A sensitivity analysis using the Sobol variance decomposition method on SiC failure probability is then performed involving a set of inputs on both CRW and CRE. The two most important parameters are Weibull modulus and characteristic stress, and their relative importance depends on the specific case. The proposed interpretation of the results is that both energy deposition and strain rate influence the relative degree of importance of the failure parameters. Computation of 95% confidence intervals around worst-case scenario SiC failure probability values is also carried out for four different sets of Weibull parameters. Heren a new criterion for SiC TRISO quality classification built upon safety-based ranges of Weibull parameters is proposed to be integrated in future Fuel-Production Quality Assurance Plans.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Computational and Experimental Determination of the Properties, Structure, and Stability of Peptoid Nanosheets and Nanotubes

Peptoids (N-substituted glycines) are a group of highly controllable peptidomimetic polymers. Amphiphilic diblock peptoids have been engineered to assemble crystalline nanospheres, nanofibrils, nanosheets, and nanotubes with biochemical, biomedical, and bioengineering applications. The mechanical properties of peptoid nanoaggregates and their relationship to the emergent self-assembled morphologies have been relatively unexplored and are critical for the rational design of peptoid nanomaterials. In this work, we consider a family of amphiphilic diblock peptoids consisting of a prototypical tube-former (Nbrpm6Nc6, a NH 2 -capped hydrophobic block of six N-((4-bromophenyl)methyl)glycine residues conjugated to a polar NH 3 (CH 2 ) 5 CO tail), a prototypical sheet-former (Nbrpe6Nc6, where the hydrophobic block comprises six N-((4-bromophenyl)ethyl)glycine residues), and an intermediate sequence that forms mixed structures ((NbrpeNbrpm)3Nc6). We combine all-atom molecular dynamics simulations and atomic force microscopy to determine the mechanical properties of the self-assembled 2D crystalline nanosheets and relate these properties to the observed self-assembled morphologies. We find good agreement between our computational predictions and experimental measurements of Young’s modulus of crystalline nanosheets. A computational analysis of the bending modulus along the two axes of the planar crystalline nanosheets reveals bending to be more favorable along the axis in which the peptoids stack by interdigitation of the side chains compared to that in which they form columnar crystals with π-stacked side chains. Here, we construct molecular models of nanotubes of the Nbrpm6Nc6 tube-forming peptoid and predict a stability optimum in good agreement with experimental measurements. A theoretical model of nanotube stability suggests that this optimum is a free energy minimum corresponding to a “Goldilocks” tube radius at which capillary wave fluctuations in the tube wall are minimized.

36 MATERIALS SCIENCE↗

Ceramics for the advanced automotive gas turbine engine: A look at a single shaft design

The results of a preliminary analysis of a single shaft regenerative design with a single stage radial turbine are presented to show the fuel economy that can be achieved at high turbine inlet temperatures, with this particular advanced design, if the turbine tip speed and regenerator inlet temperature are not limited. The engine size was 100 hp for application to a 3500 lb auto. The fuel economy was analyzed by coupling the engine to the auto through a continuously variable speed-ratio transmission and operating the system at constant turbine inlet temperature over the Composite Driving Cycle. The fuel was gasoline and the analysis was for a 85 F day. With a turbine inlet temperature of 2500 F the fuel economy was 26.2 mpg, an improvement of 18 percent over that of 22.3 mpg with a turbine inlet temperature of 1900 F. The turbine tip speed needed for best economy with the 2500 F engine was 2530 ft/sec. The regenerator temperature was approximately 2200 F at idle. Disk stresses were estimated for one single stage radial turbine and two two-stage radial-axial turbines and compared with maximum allowable stress curves estimated for a current ceramic material. Results show a need for higher Weibull Modulus, higher strength ceramics.

Nosek, S. M.↗

Elastic Properties in Tension and Shear of High Strength Nonferrous Metals and Stainless Steel - Effect of Previous Deformation and Heat Treatment

A resume is given of an investigation of the influence of plastic deformation and of annealing temperature on the tensile and shear elastic properties of high strength nonferrous metals and stainless steels in the form of rods and tubes. The data were obtained from earlier technical reports and notes, and from unpublished work in this investigation. There are also included data obtained from published and unpublished work performed on an independent investigation. The rod materials, namely, nickel, monel, inconel, copper, 13:2 Cr-Ni steel, and 18:8 Cr-Ni steel, were tested in tension; 18:8 Cr-Ni steel tubes were tested in shear, and nickel, monel, aluminum-monel, and Inconel tubes were tested in both tension and shear. There are first described experiments on the relationship between hysteresis and creep, as obtained with repeated cyclic stressing of annealed stainless steel specimens over a constant load range. These tests, which preceded the measurements of elastic properties, assisted in devising the loading time schedule used in such measurements. From corrected stress-set curves are derived the five proof stresses used as indices of elastic or yield strength. From corrected stress-strain curves are derived the secant modulus and its variation with stress. The relationship between the forms of the stress-set and stress-strain curves and the values of the properties derived is discussed. Curves of variation of proof stress and modulus with prior extension, as obtained with single rod specimens, consist in wavelike basic curves with superposed oscillations due to differences of rest interval and extension spacing; the effects of these differences are studied. Oscillations of proof stress and modulus are generally opposite in manner. The use of a series of tubular specimens corresponding to different amounts of prior extension of cold reduction gave curves almost devoid of oscillation since the effects of variation of rest interval and extension spacing were removed. Comparison is also obtained between the variation of the several properties, as measured in tension and in shear. The rise of proof stress with extension is studied, and the work-hardening rates of the various metals evaluated. The ratio between the tensile and shear proof stresses for the various annealed and cold-worked tubular metals is likewise calculated. The influence of annealing or tempering temperature on the proof stresses and moduli for the cold-worked metals and for air-hardened 13:2 Cr-Ni steel is investigated. An improvement of elastic strength generally is obtained, without important loss of yield strength, by annealing at suitable temperature. The variation of the proof stress and modulus of elasticity with plastic deformation or annealing temperature is explained in terms of the relative dominance of three important factors: namely, (a) internal stress, (b) lattice-expansion or work-hardening, and (c) crystal reorientation. Effective values of Poisson's ratio were computed from tensile and shear moduli obtained on tubular specimens. The variation of Poisson's ratio with plastic deformation and annealing temperature is explained in terms of the degree of anisotropy produced by changes of (a) internal stress and (b) crystal orientation.

METALS - ELASTICITY↗

Mesoporous silica-encapsulated gold core–shell nanoparticles for active solvent-free benzyl alcohol oxidation

Silica-encapsulated gold core@shell nanoparticles (Au@SiO2 CSNPs) were synthesized via a bottom-up procedure and used to catalyze the selective oxidation of benzyl alcohol. The pore size, morphology, crystallinity and composition of Au@SiO2 was evaluated using non-local density functional theory, transmission electron microscopy, high-energy x-ray diffraction and inductively coupled plasma-mass spectroscopy, respectively. The nanoparticles exhibit a mesoporous shell with an average thickness of 25.5 Å which can enhance selectivity via preferential transport of the desired product (i.e., benzaldehyde) relative to larger, undesired products (i.e, benzoic acid/benzyl benzoate). GC-FID analysis revealed the addition of potassium carbonate to the solvent-free oxidation of benzyl alcohol increased conversion from 17.3 to 60.4% while decreasing selectivity from 98.7 to 75.0%. Under equivalent conditions, a bare gold nanoparticle control catalyst deposited on a silica support with a similar gold surface area took 6 times as long to reach the same conversion, achieving only 49.4% selectivity. These results suggest that the pore size distribution within the inert silica shell of Au@SiO2 CSNPs inhibits the formation of undesired products to facilitate the selective oxidation of benzaldehyde despite a basic environment, which reduces selectivity under typical conditions. The CSNPs demonstrated a much lower activation energy than the Au-SiO2 control catalyst, 37 ± 1.9 kJ/mol and 72 ± 7.1 kJ/mol, respectively. Thiele modulus analysis indicates the CSNP pore structure does not create a mass transport limitation due to the nano-scale path of diffusion through the pore structure to the active surface. The lower activation energy and mesopore distribution together suggest the Au@SiO2 catalyst demonstrates higher activity through beneficial in-pore orientation, both reducing competitive adsorption and promoting a single, lower activation energy mechanistic pathway.

benzyl alcohol oxidation, catalysis, confinement↗

A Validated Finite Element Modeling Tool for Hydrodynamic Loading and Structural Analysis of Ocean Deployed Macroalgae Farms

The objective of this project was to develop and validate a fine-tuned, 3D computational modeling tool for high-fidelity simulations of macroalgae cultivation and harvest systems. To develop this tool, a full understanding of the geometric, material and hydrodynamic properties associated with farming kelp in exposed environments was necessary. Experiments and numerical modeling were done at increasing scales from 1) tank tests with a 1 m model, 2) to field tests with a 61 m culture line at a sheltered site, 3) to field tests with a 122 m culture line at an exposed site and to 4) a 5- line array at the exposed site with 186 m of culture length. The results of the experimental tank tests yielded a set of hydrodynamic drag-area coefficients for a 1 m aggregate based on densely grown kelp at 16 kg/m with a length up to 3 m as described in Fredriksson et al. This work provided the basis to model kelp as a 1 m aggregate based on in-situ geometric and material properties to include measurements of kelp blade length and width, number of blades, yield per m, material mass density and cantilever tests to obtain modulus of elasticity.

54 ENVIRONMENTAL SCIENCES↗

Automated Tow Placed LaRC(TM)-PETI-5 Composites

LaRC(TM)-PETI-5 is a PhenylEthynyl-Terminated Imide resin developed at NASA Langley Research Center (LaRC) during the 1990s. It offers a combination of attractive composite and adhesive properties. IM7/LaRC(TM)-PETI-5 composites exhibit thermal and thermo-oxidative stability typical of polyimides, superior chemical resistance and processability, excellent mechanical properties, toughness and damage tolerance. It was selected for study in the High Speed Research program aimed at developing technologies for a future supersonic aircraft, the High Speed Civil Transport, with a projected life span of 60 000 h at a cruise speed up to Mach 2.4. Robust autoclave processing cycles for LaRC(TM)-PETI-5 composites have been thoroughly designed and demonstrated, which involved hand lay-up of solvent-ladened 'wet' prepregs. However, this type of processing is not only costly but also environmentally unfriendly. Volatile management and shrinkage could become serious problems in the fabrication of large complex airframe structural subcomponents. Robotic tow placement technology utilizing 'dry' material forms represents a new fabrication process which overcomes these deficiencies. This work evaluates and compares mechanical properties of composites fabricated by heated head automated tow placement (dry process) with those obtained by hand lay-up/autoclave fabrication (wet process). Thermal and rheological properties of the robotically as-placed uncured composites were measured. A post-cure cycle was designed due to the requirement of the PETI-5 resin for a 370 C/1 h hold to reach full cure, conditions which cannot be duplicated during heated head robotic placement. Mechanical properties such as 0 degree flexural strength and modulus, open hole tensile and compressive strength and moduli, reduced section compression dogbone compressive strength, and modified zippora-medium small (MZ-MS) tensile and compressive properties were obtained on the post-cured panels. These properties compared favourably with those obtained from the wet process.

Hou, T. H.↗

Multiscale Modeling of Reconstructed Tricalcium Silicate using NASA Multiscale Analysis Tool

To study microstructure characteristics of cementitious materials hydrated in space; previously, cement binder formations were processed under microgravity conditions and was further compared against ground-based experiments. For accurate estimation of process-structure-property linkage, particularly on samples hydrated in the microgravity environment, it is desired to have a high-fidelity volumetric representation of the microstructure. However, owing to small sample size and high porosity of the space-returned samples, conventional experimental characterization techniques are not viable. Hence, a deep learning-based reconstruction algorithm was employed to obtain high fidelity 3D volumes from sparse high resolution 2D Scanning Electron Microscopy (SEM) images, as inputs to micromechanics-based modeling. This machine learning-based reconstruction methodology validated against low-order statistical descriptors, captured the microstructural topology of both sample types (ground, 1g and microgravity, μg). Due to the lack of gravity, hydration products of the samples processed in space differed from those processed-on ground. Such AI-generated virtual samples were analyzed in a multiscale recursive micromechanics approach using the NASA Multiscale Analysis Tool (NASMAT). Here, we present a methodology to rapidly integrate and evaluate these AI-generated volumes in NASMAT. The synthesized microstructural volumes are directly employed as Representative Volume Elements (RVEs) to preserve the fidelity (1 pixel = 0.54 m). Invariably, analysis of such largescale problems (5123 voxels) requires huge amount of computational resources. By taking advantage of the NASMAT architecture, we also focused on systematic multiscale integration of these AI-reconstructed virtual volumes to reduce the computational demands. In this work, this methodology is demonstrated on the ground-based, 1g samples. The estimated stiffness value of 15.90 GPa is comparable to experimentally obtained modulus of hydrated tricalcium silicate sample. The workflow presented here paves the way for utilizing the NASMAT tool to perform multiscale analyses of other multi-phase material systems using either 3D virtual datasets synthesized using AI or obtained via micro-CT.

Machine Learning↗

AGC-2 Specimen Post Irradiation Data Package Report

This report documents results of the post-irradiation examination material property testing of the creep, control, and piggyback specimens from the irradiation creep capsule Advanced Graphite Creep (AGC)-2 are reported. This is the second of a series of six irradiation test trains planned as part of the AGC experiment to fully characterize the neutron irradiation effects and radiation creep behavior of current nuclear graphite grades. The AGC-2 capsule was irradiated in the Idaho National Laboratory Advanced Test Reactor at a nominal temperature of 600°C and to a peak dose of 5 dpa (displacements per atom). One half of the creep specimens were subjected to mechanical stresses (an applied stress of either 13.8, 17.2, or 20.7 MPa) to induce irradiation creep. All post-irradiation testing and measurement results are reported with the exception of the irradiation mechanical strength testing, which is the last destructive testing stage of the irradiation testing program. Material property tests were conducted on specimens from 15 nuclear graphite grades using a similar loading configuration as the first AGC capsule (AGC-1) to provide easy comparison between the two capsules. However, AGC-2 contained an increased number of specimens (i.e., 487 total specimens irradiated) and replaced specimens of the minor grade 2020 with the newer grade 2114. The data reported include specimen dimensions for both stressed and unstressed specimens to establish the irradiation creep rates, mass and volume data necessary to derive density, elastic constants (Young’s modulus, shear modulus, and Poisson’s ratio) from ultrasonic time of flight velocity measurements, Young’s modulus from the fundamental frequency of vibration, electrical resistivity, and thermal diffusivity and thermal expansion data from 100–500°C. No data outliers were determined after all measurements were completed. A brief statistical analysis was performed on the irradiated data and a limited comparison between pre- and post-irradiation properties is presented. A more complete evaluation of trends in the material property changes, as well as irradiation-induced creep due to irradiation, temperature, and applied load on specimens will be discussed in later AGC-2 post-irradiation examination analysis reports.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Finite Element Thermal Model for Ultrasonic Welding of Thermoplastic Composites

Ultrasonic welding, UW, is a fast and energy-efficient technique for joining thermoplastic composites. It involves the use of high-frequency mechanical vibrations and a static welding force to melt and join adherends. Ultrasonic welding is an enabling technology to reduce the cost and complexity of in-space construction because lightweight thermoplastic composite components can be packaged compactly for launch and then efficiently assembled using supervised autonomous robotic technologies on site. However, the temperatures in space present challenges to UW, and it is critical that the efficacy of process parameters selected for manufacturing in space is understood prior to launch. To this end, a three-dimensional finite element model is presented in this technical presentation. The model incorporates equations for effects of viscoelastic heating and heat transfer on the welding process. The proposed model is applied to predict the temperature distribution in single lap shear, SLS, samples composed of AS4/PEEK (TC1200) composite that were welded using a terrestrial machine as part of a comprehensive weldability study. Thermocouple and infrared spot sensor data from the SLS samples provide empirical temperature measurements for calibration and validation of the UW thermal model. Calibration and validation of the model is an important step given the significant uncertainties in material properties such as the loss modulus and necessary assumptions in the physics implementations which allow the model to converge in an acceptable amount of time. The validated thermal model can be used to simulate the process for the space environment. Future validation sample testing is planned in a vacuum chamber. The result will be a model capable of guiding process parameter selection to ensure acceptable weld bonds when manufacturing in space.

Josh Fody↗

Enhancing high-fidelity neural network potentials through low-fidelity sampling

The efficacy of neural network potentials (NNPs) critically depends on the quality of the configurational datasets used for training. Prior research using empirical potentials has shown that well-selected liquid–solid transitional configurations of a metallic system can be translated to other metallic systems. This study demonstrates that such validated configurations can be relabeled using density functional theory (DFT) calculations, thereby enhancing the development of high-fidelity NNPs. Training strategies and sampling approaches are efficiently assessed using empirical potentials and subsequently relabeled via DFT in a highly parallelized fashion for high-fidelity NNP training. Our results reveal that relying solely on energy and force for NNP training is inadequate to prevent overfitting, highlighting the necessity of incorporating stress terms into the loss functions. To optimize training involving force and stress terms, we propose employing transfer learning to fine-tune the weights, ensuring that the potential surface is smooth for these quantities composed of energy derivatives. This approach markedly improves the accuracy of elastic constants derived from simulations in both empirical potential-based NNPs and relabeled DFT-based NNPs. Overall, this study offers significant insights into leveraging empirical potentials to expedite the development of reliable and robust NNPs at the DFT level.

97 MATHEMATICS AND COMPUTING↗

Enabling resonant ultrasound spectroscopy in high magnetic fields

Resonant ultrasound spectroscopy (RUS) is a powerful method to determine elastic constants with high accuracy and precision from a single measurement of the mechanical resonances of a sample. Conventionally, the quantitative extraction of elastic moduli with RUS assumes free boundary conditions which can often lead to the adoption of unstable sample positioning between ultrasonic transducers that is incompatible with extreme environments like high magnetic fields. We show that, under specific conditions, introducing a small amount of adhesive between a RUS sample and ultrasonic transducers introduces a perturbation to the free resonance condition which can be accounted for by a simple model. This means elastic constants can be determined to within the uncertainty of conventional RUS, but with significant improvements including sample stability and control of sample orientation. We demonstrate the efficacy of this approach with measurements on a range of materials including room temperature measurements on polycrystalline metals, temperature-dependent measurements of the structural phase transition in strontium titanate single crystals, and magnetic field-dependent measurements of magnetic phase transitions in gadolinium polycrystals up to 14 T.

47 OTHER INSTRUMENTATION↗

Design and scale-up of 3D printed bat houses with biomass-derived polymer composites

Biomass (e.g., pine sawdust, especially high–ash content pine sawdust) is commonly disposed of as waste. Combining biomass with polymers to make composite feedstocks for 3D printing has been explored as a method to reduce or repurpose the biomass waste. Although not all biocomposite properties are known, the wood-based polylactic acid (PLA) composite has promising qualities for applications in ecological settings. In this work, pine wood–PLA composite feedstock was used to 3D print supplemental roost structures for endangered tree-roosting bats, which often face a paucity of suitable naturally occurring roosts. This material combination was selected because it is estimated to degrade faster than the synthetic material systems that are used widely in supplemental bat roosting structures to aid in the conservation of tree roosting bats. The layered, rough surface created by the 3D printing process serves as a surface that bats can grip while roosting. Computer-aided design (CAD) models were generated based on natural roost structures, and a full-size bat house was successfully additively manufactured using a pellet-fed large-scale 3D printing system. The 3D printed hexagon exhibited a tensile strength of 22–23 MPa and a Young’s modulus of 3202–3218 MPa in the x-direction. It has been demonstrated that the 3D printed bat house can be installed on a tree in a stable fashion. This successful demonstration of a bat roost manufactured using a bioderived composite should promote its use in other fish and wildlife structures and broader industrial applications such as construction and automobiles.

3D printing↗