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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 37 records · Page 2

Challenges in Postprocessing of Hybrid Manufacturing of Magnet Polymer Composites to Enhance the Energy Product of NdFeB Bonded Magnets

Bonded permanent magnets need to process magnetic filler particles and binder together which is a form of hybrid or composite manufacturing that needs to simultaneously process multimaterials. Polymer bonding of the permanent magnets decreases the energy product of the bonded magnets which varies with square of loading fraction of magnetic materials. However, due to high viscosity of bonding polymer prohibits loading higher than 80 volume % of magnetic materials in most efficient loading process such as compression molding. To further increase the loading of magnetic fraction in the bonded permanent magnets, it is expected to be beneficial to introduce a fraction of nonreacting thermally sacrificial polymer along with permanent bonding polymer in the least permissible of about 20 volume % of the polymer. This process of first adding the sacrificial polymer for higher processability for composites and later removing it via post processing such as heat treatment provides a simple example of inclusion of both the additive and the subtractive stages of hybrid manufacturing. These hybrid composite magnets can be heat treated to remove the sacrificial polymer to further increase the density and energy product which might require to implement hot isostatic pressing for compaction. Although the identification of such ideal polymer requires an extensive polymer chemistry research, we have compression molded several permanent bonding polymers such as nylon, polycarbonate (PC) and polyphenyl sulfide (PPS) and potential sacrificial polymer such as polyoxymethylene (POM), polystyrene (PS), and Acrylonitrile Butadiene Styrene (ABS) and heat treated to remove the sacrificial polymers. It is discovered that oxygen free low temperature pyrolizable polymers could be the potential candidates for increasing the magnet particles loading for achieving high energy products.

36 MATERIALS SCIENCE↗

A new computer approach to map mixed forest features and postprocess multispectral data

A computer technique for mapping mixed softwood and hardwood stands in multispectral satellite imagery of forest regions is described. The purpose of the technique is to obtain smoother resource maps useful in timber harvesting operations. The computer program relies on an algorithm which assesses the size and similarity of adjacent sections on satellite imagery (Landsat-1 data is used) and constructs, through an iteration of the basic algorithm, a more general map of timber mixtures, eliminating the mottled appearance of the raw imagery. Despite difficulties in the experimental analysis of a Texas forest, apparently due to relatively low resolution of the Landsat data, the computer classification approach outlined is suggested as a generally applicable method of creating serviceable maps from multispectral imagery.

Kan, E. P.↗

Interactive color graphical postprocessing as a unifying influence in numerical analysis research

The general capabilities and the hardware environment of an interactive color graphical postprocessor for three-dimensional numerical analysis are described as well as the synergistic influence of this aspect of interactive graphics on the research environment. Areas of practical concern include finite element analysis, fracture propagation, surface and framed structures. The interactive color graphical postprocessor, POSTPRO3D, is capable of displaying the scalar, vector, and tensor results of finite difference, finite element, and boundary element analysis. In the case of fatigue cracking in steel crane-rail girders, it was shown that POSTPRO3D offers a high level of flexibility, interactivity and features which minimize response time.

Abel, J. F.↗

Essentially nonoscillatory postprocessing filtering methods

High order accurate centered flux approximations used in the computation of numerical solutions to nonlinear partial differential equations produce large oscillations in regions of sharp transitions. Here, we present a new class of filtering methods denoted by Essentially Nonoscillatory Least Squares (ENOLS), which constructs an upgraded filtered solution that is close to the physically correct weak solution of the original evolution equation. Our method relies on the evaluation of a least squares polynomial approximation to oscillatory data using a set of points which is determined via the ENO network. Numerical results are given in one and two space dimensions for both scalar and systems of hyperbolic conservation laws. Computational running time, efficiency, and robustness of method are illustrated in various examples such as Riemann initial data for both Burgers' and Euler's equations of gas dynamics. In all standard cases, the filtered solution appears to converge numerically to the correct solution of the original problem. Some interesting results based on nonstandard central difference schemes, which exactly preserve entropy, and have been recently shown generally not to be weakly convergent to a solution of the conservation law, are also obtained using our filters.

Lafon, F.↗

Algorithms For Postprocessing Computed Flow Data

Paper discusses algorithms used to make visible displays from arrays of numerical data representing computed flow fields. Intended to help researchers discern flow structures. Displays include, principally, contours and particle traces on two-dimensional and three-dimensional grids.

Buning, Pieter↗

Pre- and postprocessing techniques for determining goodness of computational meshes

Research in error estimation, mesh conditioning, and solution enhancement for finite element, finite difference, and finite volume methods has been incorporated into AUDITOR, a modern, user-friendly code, which operates on 2D and 3D unstructured neutral files to improve the accuracy and reliability of computational results. Residual error estimation capabilities provide local and global estimates of solution error in the energy norm. Higher order results for derived quantities may be extracted from initial solutions. Within the X-MOTIF graphical user interface, extensive visualization capabilities support critical evaluation of results in linear elasticity, steady state heat transfer, and both compressible and incompressible fluid dynamics.

Oden, J. Tinsley↗

Postprocessing of satellite altimetry return signals for improved sea surface topography accuracy

Retracked southern ocean data from the first 34 repeat cycles of the Geosat Exact Repeat Mission are analyzed. The difference between the surface heights calculated from the retracked data and the original on-board estimate is less than 10 cm for significant wave heights (SWH) lower than 10 m but increases to about 1.0 m at an SWH of 18 m. The electromagnetic (EM) bias coefficient calculated using the retracked data is generally slightly less than that using the unretracked data and does not decrease as much with SWH as to the EM bias coefficients calculated from the unretracked data. A map of the sea surface height variability of the southern ocean created using the retracked data shows differences from variability maps created using the unretracked data in regions of high wave heights. This study shows that retracking will improve altimeter precision.

Brenner, A. C.↗

Platform for Postprocessing Waveform-Based NDE

Taking advantage of the similarities that exist among all waveform-based non-destructive evaluation (NDE) methods, a common software platform has been developed containing multiple- signal and image-processing techniques for waveforms and images. The NASA NDE Signal and Image Processing software has been developed using the latest versions of LabVIEW, and its associated Advanced Signal Processing and Vision Toolkits. The software is useable on a PC with Windows XP and Windows Vista. The software has been designed with a commercial grade interface in which two main windows, Waveform Window and Image Window, are displayed if the user chooses a waveform file to display. Within these two main windows, most actions are chosen through logically conceived run-time menus. The Waveform Window has plots for both the raw time-domain waves and their frequency- domain transformations (fast Fourier transform and power spectral density). The Image Window shows the C-scan image formed from information of the time-domain waveform (such as peak amplitude) or its frequency-domain transformation at each scan location. The user also has the ability to open an image, or series of images, or a simple set of X-Y paired data set in text format. Each of the Waveform and Image Windows contains menus from which to perform many user actions. An option exists to use raw waves obtained directly from scan, or waves after deconvolution if system wave response is provided. Two types of deconvolution, time-based subtraction or inverse-filter, can be performed to arrive at a deconvolved wave set. Additionally, the menu on the Waveform Window allows preprocessing of waveforms prior to image formation, scaling and display of waveforms, formation of different types of images (including non-standard types such as velocity), gating of portions of waves prior to image formation, and several other miscellaneous and specialized operations. The menu available on the Image Window allows many further image processing and analysis operations, some of which are found in commercially-available image-processing software programs (such as Adobe Photoshop), and some that are not (removing outliers, Bscan information, region-of-interest analysis, line profiles, and precision feature measurements).

Roth, Don↗

Automatic Classification of Biological Targets in a Tidal Channel Using a Multibeam Sonar

Multibeam sonars are widely used for environmental monitoring of fauna at marine renewable energy sites. However, they can rapidly accrue vast volumes of data, which poses a challenge for data processing. Here, using data from a deployment in a tidal channel with peak currents of 1–2 m s –1 , we demonstrate the data-reduction benefits of real-time automatic classification of targets detected and tracked in multibeam sonar data. First, we evaluate classification capabilities for three machine learning algorithms: random forests, support vector machines, and k-nearest neighbors. For each algorithm, a hill-climbing search optimizes a set of hand-engineered attributes that describe tracked targets. Here, the random forest algorithm is found to be most effective—in postprocessing, discriminating between biological and nonbiological targets with a recall rate of 0.97 and a precision of 0.60. In addition, 89% of biological targets are correctly classified as either seals, diving birds, fish schools, or small targets. Model dependence on the volume of training data is evaluated. Second, a real-time implementation of the model is shown to distinguish between biological targets and nonbiological targets with nearly the same performance as in postprocessing. From this, we make general recommendations for implementing real-time classification of biological targets in multibeam sonar data and the transferability of trained models.

16 TIDAL AND WAVE POWER↗

Interactive color display of 3-D engineering analysis results

A general approach to three-dimensional postprocessing of engineering analyses is presented. The approach is versatile and may handle the results from a wide range of engineering analysis methods which involve the discretization of continua. To facilitate the understanding of complex three-dimensional numerical models, advanced interactive color postprocessing techniques are introduced. Finite element, finite difference, and boundary element models are evaluated with the prototype postprocessor. The existing color graphics program (POSTPRO3D) was ported to a high-resolution device. Interactive graphic tools were implemented to facilitate qualitative mesh evaluation from a single analysis. A postprocessing environment was design for workstation technology.

Abel, John F.↗

Scientific visualization in computational aerodynamics at NASA Ames Research Center

The visualization methods used in computational fluid dynamics research at the NASA-Ames Numerical Aerodynamic Simulation facility are examined, including postprocessing, tracking, and steering methods. The visualization requirements of the facility's three-dimensional graphical workstation are outlined and the types hardware and software used to meet these requirements are discussed. The main features of the facility's current and next-generation workstations are listed. Emphasis is given to postprocessing techniques, such as dynamic interactive viewing on the workstation and recording and playback on videodisk, tape, and 16-mm film. Postprocessing software packages are described, including a three-dimensional plotter, a surface modeler, a graphical animation system, a flow analysis software toolkit, and a real-time interactive particle-tracer.

Bancroft, Gordon V.↗

Integration of Dynamical System Scaling to RAVEN and Facility Application

As part of the design optimization and model validation effort within the hybrid energy systems program, the research to implement dynamical system scaling (DSS) code to RAVEN is funded under the Integrated Energy System program in collaboration with the Digital Reactor Technology & Development department. The DSS data processing algorithm has been coded within the RAVEN framework along with other metrics and postprocessing models. The implemented code was tested using a gravity-driven draining tank draining case modeled in RELAP5-3D and generated data was successfully postprocessed based on the scaling analyses defined by DSS. Postprocessed data concluded less agreement for the tank exit velocity and indicated that the modeled input deck for RELAP5-3D requires modification to enforce minimal pressure differential effects to the draining process.

97 MATHEMATICS AND COMPUTING↗

Fourier Neural Networks as Function Approximators and Differential Equation Solvers

We present a Fourier neural network (FNN) that can be mapped directly to the Fourier decomposition. The choice of activation and loss function yields results that replicate a Fourier series expansion closely while preserving a straightforward architecture with a single hidden layer. The simplicity of this network architecture facilitates the integration with any other higher-complexity networks, at a data pre- or postprocessing stage. We validate this FNN on naturally periodic smooth functions and on piecewise continuous periodic functions. We showcase the use of this FNN for modeling or solving partial differential equations with periodic boundary conditions. The main advantages of the current approach are the validity of the solution outside the training region, interpretability of the trained model, and simplicity of use.

Fourier decomposition↗

Conditioning the Surface and Bulk of High-Nickel Cathodes with a Nb Coating: An In Situ X-ray Study

Surface coating is commonly employed by industries to improve the cycling and thermal stability of high-nickel (Ni) transition metal (TM) layered cathodes for their practical use in lithium-ion batteries. Niobium (Nb) coating or substitution has been shown to be effective in stabilizing LiNi 0.8 Mn 0.1 Co 0.1 O 2 (NMC811) cathodes; in addition, the electrochemical performance of the final products varies depending on the postprocessing. In this follow-up study, we use in situ synchrotron X-ray diffraction to investigate the kinetic processes and the involved structural evolution in Nb-coated NMC811 upon heat treatment. Furthermore, quantitative structure analysis reveals thermally driven concurrent changes in the bulk and surface, in particular, the phase evolution of the coating layer and Nb/TM interdiffusion that facilitates penetration of Nb into the bulk and particle growth at the increased temperatures. Findings from this study highlight the new opportunities for the intended control of the structure and surface properties of high-Ni cathodes through surface coating in conjunction with postprocessing.

36 MATERIALS SCIENCE↗

Ultrathin VO 2 Films on Functional Substrates

The metal–insulator transition (MIT) in vanadium dioxide (VO 2 ) thin films is strongly affected by grain size, thickness, and interfacial properties. Typically, a minimum thickness around 50 nm is required for VO 2 to exhibit a significant MIT when functional substrates like sapphire and silicon are used. Several works have shown that thin films below 20 nm, with up to 2–3 decades of change in the resistance across the MIT, can be achieved but require complex pre- or postprocessing of the samples. We show that predeposition substrate condition control facilitates the direct growth of VO 2 ultrathin 15 nm films, exhibiting a resistance change between 3 and 4 decades across the MIT. Our findings indicate that the interface between the film and the substrate is crucial in determining the initial growth layers and the structural evolution. With appropriate substrate surface treatment, the desired VO 2 MIT can be enhanced regardless of the substrate crystallographic orientation. Moreover, we propose a novel approach to obtain large resistance changes across the MIT in ultrathin VO 2 films by incorporating a predeposited 1.5 nm vanadium oxide buffer layer, thereby eliminating the need to use different materials or complex pre- or postprocessing of the samples. Here we also demonstrate that this method improves the transition of 25–50 nm VO 2 thin films on silicon substrates. Our study reveals a simple approach for direct growth of ultrathin VO 2 films exhibiting a significant MIT, which is commonly accepted unattainable over substrates of technological importance, such as sapphire and silicon.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Laser-Assisted Synthesis of Monolayer 2D MoSe 2 Crystals with Tunable Vacancy Concentrations: Implications for Gas and Biosensing

We report tuning the structural and electronic properties of atomically thin two-dimensional (2D) materials via defect and vacancy engineering is the key to enabling their potential use in various applications, including electronics, energy, and sensing devices. Vacancies are, for instance, becoming highly promising for the enhanced interaction of gases and biomolecules with 2D materials in energy and sensing applications. However, the deterministic generation of desirable vacancies with tunable concentrations remains a challenge in 2D materials due to the limitations in the current growth methods, such as the complex reaction chemistries and gas flow dynamics. Therefore, engineering defects and vacancies in 2D materials have been mainly limited to destructive top-down processes such as heating, ion bombardments, and laser postprocessing. Here, we introduce a single-step bottom-up synthesis approach for the growth of monolayer MoSe 2 crystals with tunable vacancy concentrations. This method utilizes the spatiotemporal properties and adjustable power densities of the lasers to control the vaporization dynamics of the stoichiometric MoSe 2 powders. Such a mechanism in the vaporization allows us to grow tunable stoichiometry monolayer MoSe 2–x crystals on the substrates. The localized and time-controlled (250 ms to 2 s) vaporization of the MoSe 2 powder by a CO 2 laser enables the formation of monolayer crystals with controlled vacancy concentrations ranging from ~1 to 20%. The effects of laser power, laser irradiation time, and background pressure on the tuning range and subsequent properties of the crystals are investigated and quantified using Raman and photoluminescence spectroscopy, scanning transmission electron microscopy (STEM), and time-correlated single-photon counting (TCSPC). This bottom-up synthesis is a promising approach that allows the deterministic vacancy tuning for future electronics and, in particular, gas and biosensing applications without the need for further postprocessing and potential structural disruption of the crystals.

2D materials↗

Current advances on Talbot–Lau x-ray imaging diagnostics for high energy density experiments (invited)

Talbot–Lau x-ray interferometry is a refraction-based diagnostic that can map electron density gradients through phase-contrast methods. The Talbot–Lau x-ray deflectometry (TXD) diagnostics have been deployed in several high energy density experiments. To improve diagnostic performance, a monochromatic TXD was implemented on the Multi-Tera Watt (MTW) laser using 8 keV multilayer mirrors (Δθ/θ = 4.5%-5.6%). Copper foil and wire targets were irradiated at 10 14 –10 15 W/cm 2 . Laser pulse length (~10 to 80 ps) and backlighter target configurations were explored in the context of Moiré fringe contrast and spatial resolution. Foil and wire targets delivered increased contrast <30%. The best spatial resolution (<6 μm) was measured for foils irradiated 80° from the surface. Further TXD diagnostic capability enhancement was achieved through the development of advanced data postprocessing tools. The Talbot Interferometry Analysis (TIA) code enabled x-ray refraction measurements from the MTW monochromatic TXD. Additionally, phase, attenuation, and dark-field maps of an ablating x-pinch load were retrieved through TXD. The images show a dense wire core of ~60 μm diameter surrounded by low-density material of ~40 μm thickness with an outer diameter ratio of ~2.3. Attenuation at 8 keV was measured at ~20% for the dense core and ~10% for the low-density material. Instrumental and experimental limitations for monochromatic TXD diagnostics are presented. Enhanced postprocessing capabilities enabled by TIA are demonstrated in the context of high-intensity laser and pulsed power experimental data analysis. Significant advances in TXD diagnostic capabilities are presented. Furthermore, these results inform future diagnostic technique upgrades that will improve the accuracy of plasma characterization through TXD.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Evaluating a quantum-classical quantum Monte Carlo algorithm with Matchgate shadows

Solving the electronic structure problem of molecules and solids to high accuracy is a major challenge in quantum chemistry and condensed matter physics. The rapid emergence and development of quantum computers offer a promising route to systematically tackle this problem. Recent work by [Huggins et al ., Nature (London) 603 , 416 (2022)] proposed a hybrid quantum-classical quantum Monte Carlo (QC-QMC) algorithm using Clifford shadows to determine the ground state of a Fermionic Hamiltonian. This approach displayed inherent noise resilience and the potential for improved accuracy compared to its purely classical counterpart. Nevertheless, the use of Clifford shadows introduces an exponentially scaling postprocessing cost. In this work, we investigate an improved QC-QMC scheme utilizing the recently developed Matchgate shadows technique [Commun. Math. Phys. 404 , 629 (2023)], which removes the aforementioned exponential bottleneck. We observe from experiments on quantum hardware that the use of Matchgate shadows in QC-QMC is inherently noise robust. We show that this noise resilience has a more subtle origin than in the case of Clifford shadows. Nevertheless, we find that classical postprocessing, while asymptotically efficient, requires hours of runtime on thousands of classical CPUs for even the smallest chemical systems, presenting a major challenge to the scalability of the algorithm.

Monte Carlo methods↗