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At least 1,531 records · Page 85

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NASA NTRS1996

Design and Laboratory Validation of a Capacitive Sensor for Measuring the Recession of Thin-Layered Ablator

Flight vehicles are typically instrumented with subsurface thermocouples to estimate heat transfer at the surface using inverse analysis procedures. If the vehicle has an ablating heat shield, however, temperature time histories from subsurface thermocouples no longer provide enough information to estimate heat flux at the surface. In this situation, the geometry changes and thermal energy leaves the surface in the form of ablation products. The ablation rate is required to estimate heat transfer to the surface. A new concept for a capacitive sensor has been developed to measure ablator depth using the ablator's dielectric effect on a capacitor's fringe region. Relying on the capacitor's fringe region enables the gage to be flush mounted in the vehicle's permanent structure and not intrude into the ablative heat shield applied over the gage. This sensor's design allows nonintrusive measurement of the thickness of dielectric materials, in particular, the recession rates of low-temperature ablators applied in thin (0.020 to 0.060 in. (0.05 to 0.15 mm)) layers. Twenty capacitive gages with 13 different sensing element geometries were designed, fabricated, and tested. A two-dimensional finite-element analysis was performed on several candidate geometries. Calibration procedures using ablator-simulating shims are described. A one-to-one correspondence between system output and dielectric material thickness was observed out to a thickness of 0.055 in. (1.4 mm) for a material with a permittivity about three times that of air or vacuum. A novel method of monitoring the change in sensor capacitance was developed. This technical memorandum suggests further improvements in gage design and fabrication techniques.

Gregory K Noffz↗

DOE OSTI2020

Thermo-mechanical modeling and experimental validation for multilayered metallic microstructures

This paper presents thermo-mechanical modeling on multilayered metallic microstructures consisting of two bilayers that enable 3D deployment once being Joule heated. Additionally, a representative design of such microstructures, as well as their working principle is introduced. Furthermore, a mathematical model is derived using Euler–Bernoulli beam theory, and analytical solutions describing out-of-plane displacement of the multilayered microstructures when uniformly heated, which is validated by finite element analysis. Parametric analysis on thermal load and dimensional change of beam shows a good agreement between the analytical solutions and results given by finite element analysis. The phases of the near-equiatomic NiTi layer are analyzed by EDS and XRD, which prove to be austenite during the Joule heating process. The mechanical properties of austenite NiTi are incorporated into the analytical solutions that provides a good estimation of 3D deployment of microstructures made of NiTi and aluminum. The experimental results provide an approximately 7 µm out-of-plane deployment by applying a uniform temperature increase of 132 K, and parametric analysis on the dimension of top aluminum beam offers another promising approach to larger 3D deployment. The proposed mathematical model provides an efficient tool for predicting the out-of-plane deployment of such multilayered microstructures.

36 MATERIALS SCIENCE↗

NASA NTRS1990

Constraint treatment techniques and parallel algorithms for multibody dynamic analysis

Computational procedures for kinematic and dynamic analysis of three-dimensional multibody dynamic (MBD) systems are developed from the differential-algebraic equations (DAE's) viewpoint. Constraint violations during the time integration process are minimized and penalty constraint stabilization techniques and partitioning schemes are developed. The governing equations of motion, a two-stage staggered explicit-implicit numerical algorithm, are treated which takes advantage of a partitioned solution procedure. A robust and parallelizable integration algorithm is developed. This algorithm uses a two-stage staggered central difference algorithm to integrate the translational coordinates and the angular velocities. The angular orientations of bodies in MBD systems are then obtained by using an implicit algorithm via the kinematic relationship between Euler parameters and angular velocities. It is shown that the combination of the present solution procedures yields a computationally more accurate solution. To speed up the computational procedures, parallel implementation of the present constraint treatment techniques, the two-stage staggered explicit-implicit numerical algorithm was efficiently carried out. The DAE's and the constraint treatment techniques were transformed into arrowhead matrices to which Schur complement form was derived. By fully exploiting the sparse matrix structural analysis techniques, a parallel preconditioned conjugate gradient numerical algorithm is used to solve the systems equations written in Schur complement form. A software testbed was designed and implemented in both sequential and parallel computers. This testbed was used to demonstrate the robustness and efficiency of the constraint treatment techniques, the accuracy of the two-stage staggered explicit-implicit numerical algorithm, and the speed up of the Schur-complement-based parallel preconditioned conjugate gradient algorithm on a parallel computer.

Chiou, Jin-Chern↗

NASA NTRS1983

Aerodynamic optimization, comparison, and trim design of canard and conventional high performance general aviation configurations

A design study has been conducted to optimize trim cruise flight of high performance general aviation canard aircraft which achieve minimum drag. In order to investigate the advantages and disadvantages of canard configured aircraft, corresponding conventional tail-aft 'baseline' aircraft were designed and used for comparison. Two-dimensional predictions were obtained by coupling inviscid results from a vortex panel multi-element program to a momentum integral boundary layer analysis. Using the results of the two-dimensional vortex panel analysis, a vortex lattice method was employed to predict the finite wing results. The analysis utilized a turbulent airfoil and a natural laminar airfoil which are two NASA state-of-the-art airfoil sections. The canard aircraft designs give quantitative results of wing and canard loadings, wing-to-canard moment arm ratios, and aspect ratio effects for trim cruise flight for a wide range of wing-to-canard area ratios. Both canard and baseline aircraft achieved a 25 to 30 percent improvement in performance over typical current technology aircraft, but high canard loading necessary for trim resulted in slightly poorer performance of the canard aircraft as compared to the baseline designs.

Keith, M. W.↗

NASA NTRS1987

Space shuttle main engine high pressure fuel pump aft platform seal cavity flow analysis

A general purpose, three-dimensional computational fluid dynamics code named PHOENICS, developed by CHAM Inc., is used to model the flow in the aft-platform seal cavity in the high pressure fuel pump of the space shuttle main engine. The model is used to predict the temperatures, velocities, and pressures in the cavity for six different sets of boundary conditions. The results are presented as input for further analysis of two known problems in the region, specifically: erratic pressures and temperatures in the adjacent coolant liner cavity and cracks in the blade shanks near the outer diameter of the aft-platform seal.

Lowry, S. A.↗

NASA NTRS1983

Aeroelastic loads prediction for an arrow wing. Task 3: Evaluation of the Boeing three-dimensional leading-edge vortex code

Two separated flow computer programs and a semiempirical method for incorporating the experimentally measured separated flow effects into a linear aeroelastic analysis were evaluated. The three dimensional leading edge vortex (LEV) code is evaluated. This code is an improved panel method for three dimensional inviscid flow over a wing with leading edge vortex separation. The governing equations are the linear flow differential equation with nonlinear boundary conditions. The solution is iterative; the position as well as the strength of the vortex is determined. Cases for both full and partial span vortices were executed. The predicted pressures are good and adequately reflect changes in configuration.

Manro, M. E.↗

NASA NTRS1973

Separation of variables in the special diagonal Hamilton-Jacobi equation: Application to the dynamical problem of a particle constrained on a moving surface

For a time-dependent, n-dimensional, special diagonal Hamilton-Jacobi equation a necessary and sufficient condition for the separation of variables to yield a complete integral of the form was established by specifying the admissible forms in terms of arbitrary functions. A complete integral was then expressed in terms of these arbitrary functions and also the n irreducible constants. As an application of the results obtained for the two-dimensional Hamilton-Jacobi equation, analysis was made for a comparatively wide class of dynamical problems involving a particle moving in Euclidean three-dimensional space under the action of external forces but constrained on a moving surface. All the possible cases in which this equation had a complete integral of the form were obtained and these are tubulated for reference.

Blanchard, D. L.↗

NASA NTRS1983

A Computer Program for the Calculation of Three-Dimensional Transonic Nacelle/Inlet Flowfields

A highly efficient computer analysis was developed for predicting transonic nacelle/inlet flowfields. This algorithm can compute the three dimensional transonic flowfield about axisymmetric (or asymmetric) nacelle/inlet configurations at zero or nonzero incidence. The flowfield is determined by solving the full-potential equation in conservative form on a body-fitted curvilinear computational mesh. The difference equations are solved using the AF2 approximate factorization scheme. This report presents a discussion of the computational methods used to both generate the body-fitted curvilinear mesh and to obtain the inviscid flow solution. Computed results and correlations with existing methods and experiment are presented. Also presented are discussions on the organization of the grid generation (NGRIDA) computer program and the flow solution (NACELLE) computer program, descriptions of the respective subroutines, definitions of the required input parameters for both algorithms, a brief discussion on interpretation of the output, and sample cases to illustrate application of the analysis.

Vadyak, J.↗

DOE OSTI2025

Robust Spectral Anomaly Detection in EELS Spectral Images via 3D Convolutional Variational Autoencoders

Abstract A 3D Convolutional Variational Autoencoder (3D‐CVAE) is introduced for automated anomaly detection in electron energy‐loss spectroscopy spectrum imaging (EELS‐SI) data. This approach leverages the full 3D structure of EELS‐SI data to detect subtle spectral anomalies while preserving both spatial and spectral correlations across the datacube. By employing cross‐entropy loss and training on bulk spectra, the model learns to reconstruct bulk features characteristic of the defect‐free material. In exploring methods for anomaly detection, both the 3D‐CVAE approach and principal component analysis (PCA) are evaluated, testing their performance using FeL‐edge ΔEpeak shifts designed to simulate material defects. These results show that 3D‐CVAE achieves superior anomaly detection and maintains consistent performance across various shift magnitudes. The method demonstrates clear bimodal separation between bulk and anomalous spectra, enabling reliable classification. Further analysis verifies that lower‐dimensional representations are robust to anomalies in the data. While performance advantages over PCA diminish with decreasing anomaly concentration, our method maintains high reconstruction quality even in challenging, noise‐dominated spectral regions. This approach provides a robust framework for unsupervised automated detection of spectral anomalies in EELS‐SI data, particularly valuable for analyzing complex material systems.

Chemistry↗

DOE OSTI2020

Accelerated version of NUBEAM capabilities in DIII-D using neural networks

A neural network model of the effects of neutral beam injection on DIII-D has been developed. The training and testing data used by the model have been generated by the NUBEAM module of TRANSP for experimental discharges from the 2018 DIII-D campaign. Using a principle component analysis to reduce the dimensionality of profile data, the model has been shown to reproduce the results of the Monte Carlo code NUBEAM with a high level of accuracy and an execution time orders of magnitude faster than the execution time of NUBEAM. Furthermore, this makes the neural network model uniquely suited to applications in model-based scenario planning (off-line) and active control (on-line), where a large number of simulation runs are required by the associated optimization tasks that need to be performed before and during the discharge.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2021

Unsupervised learning for identifying events in active target experiments

This article presents novel applications of unsupervised machine learning methods to the problem of event separation in an active target detector, the Active-Target Time Projection Chamber (AT-TPC). The overarching goal is to group similar events in the early stages of the data analysis, thereby improving efficiency by limiting the computationally expensive processing of unnecessary events. The application of unsupervised clustering algorithms to the analysis of two-dimensional projections of particle tracks from a resonant proton scattering experiment on 46 Ar is introduced. We explore the performance of autoencoder neural networks and a pre-trained VGG16 Simonyan and Zisserman (2015) convolutional neural network. We study clustering performance on both data from a simulated 46 Ar experiment, and real events from the AT-TPC detector. We find that a -means algorithm applied to simulated data in the VGG16 latent space forms almost perfect clusters. Additionally, the VGG16+-means approach finds high purity clusters of proton events for real experimental data. Here, we also explore the application of clustering the latent space of autoencoder neural networks for event separation. While these networks show strong performance, they suffer from high variability in their results.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2020

Raman Spectroscopy Analysis of the Structure and Surface Chemistry of Ti3C2Tx MXene

Raman spectroscopy is one of the most useful tools for the analysis of two-dimensional (2D) materials. While MXenes are a very large family of 2D transition metal carbides and nitrides, there have been just a few Raman studies of materials from this family. Here, we report on a systematic study of the most widely used and most important MXene to date: Ti 3 C 2 T x . By synthesizing material using different methods, we show that Raman spectra of Ti 3 C 2 T x are affected not only by the composition and surface groups but also by intercalated species and stacking. Due to a plasmonic peak of Ti 3 C 2 T x around 785 nm, resonant conditions are achieved, enabling us to observe an extra peak at ~120 cm –1 , when excited with a red diode laser. We report differences in Raman spectra collected from single flakes of Ti 3 C 2 T x , colloidal solutions, and multilayer films. Lastly, we show how an undesirable photoluminescent background could serve as evidence of material degradation, which leads to the formation of defective titania and amorphous carbon. Overall, this study shows how Raman spectroscopy can be used for the characterization of important emerging 2D materials: MXenes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2021

Distribution of Bound and Free Water in Anatomical Fractions of Pine Residues and Corn Stover as a Function of Biological Degradation

Biomass quality is influenced by water’s abundance, distribution, and status in relation to other chemical species within the polymer matrix. Water interacts with polymers that make up the cell walls, and these interactions govern the physical and chemical changes that occur during the storage and preprocessing of biomass feedstocks. Time-domain nuclear magnetic resonance (TD-NMR) was employed to explore variations in the physical constraints of water within the lignocellulosic microstructure in distinct anatomical fractions of biomass and as a function of biological degradation. The Carr–Purcell–Meiboom–Gill sequence, when combined with knowledge of the chemical composition and physical structure of pine residues and corn stover anatomical fractions, gives an accurate measurement of the bound and free water. In this work, the impacts of storage and biological degradation were investigated to elucidate changes in the status and distribution of water within distinct plant tissues. We also investigate how degradation during storage affects water interactions in different pine residues (e.g., bark, branch, and needle) and corn stover (e.g., cob, leaf, and stalk) anatomical fractions using transverse relaxation times (T2). As demonstrated herein, TD-NMR provides quantitative data on lignocellulosic biomass–water interactions within anatomical fractions, which can further aid in the investigation of preprocessing effects on feedstock quality. Our findings suggest that biological heating enhances biomass–water interactions at the cellular and macromolecular scale. In addition, analysis of three-dimensional scanning electron microscopy reconstructions indicates that surface roughness wavelengths align with microscale roughness, suggesting that pine forestry residue and corn stover particles have primarily hydrophobic exterior surfaces. Furthermore, this study offers multiscale insights into understanding the microstructure, wettability, and chemical environment that dictate diffusion, enzyme access, and recalcitrance of lignocellulosic biomass.

09 BIOMASS FUELS↗

DOE OSTI2024

3D multi-system Bayesian calibration with energy conservation to study rapidity-dependent dynamics of nuclear collisions

Considerable information about the early-stage dynamics of heavy ion collisions is encoded in the rapidity dependence of measurements. To leverage the large amount of experimental data, we perform a systematic analysis using three-dimensional hydrodynamic simulations of multiple collision systems — large and small, symmetric and asymmetric. Specifically, we perform fully 3D multi-stage hydrodynamic simulations initialized by a parameterized model for rapidity-dependent energy deposition, which we calibrate on the hadron multiplicity and anisotropic flow coefficients. We utilize Bayesian inference to constrain properties of the early- and late-time dynamics of the system, and highlight the impact of enforcing global energy conservation in our 3D model.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2021

The scaling of kinetic and transport behaviors in the solution-phase chemistry of a plasma–liquid interface

The reactions at a plasma–liquid interface often involve species such as the solvated electron or the hydroxyl radical, which initiate the reduction or oxidation of solution-phase reactants (so-called scavengers) or are consumed by their own second-order recombination. Here, the mathematical scaling of the reaction–diffusion equations at the interface is used to obtain a characteristic time that can be used to determine the transition from highly efficient scavenger reduction or oxidation to lower efficiencies due to transport limitations. The characteristic time (tc) is validated using numerical solutions of the reaction–diffusion equations. When the scavenger kinetics are faster than second-order recombination, this characteristic transition time scales proportionally with the scavenger diffusivity (Ds) and the square of the scavenger bulk concentration (SB) and inversely proportional to the electron flux (J) squared; that is, t c = D s S B 2 F 2 /J 2 , where F is Faraday’s constant. However, when the scavenger kinetics are comparable or slower than second-order recombination, this scaling does not hold. Extending this analysis to three-dimensional systems shows that the profile of the electron flux on the surface affects the spatial location where reactions are most effective. Finally, the assessment of the implications of these behaviors for the reactor design highlights how effectively controlling the electron flux and solution transport may be necessary to improve the efficiency of scavenger reactions.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2024

A variational method for the sheath potential of hypersonic leading edges with space-charge limitations

Electron transpiration cooling for the leading edges (LE) of hypersonic aircraft utilizes thermionic emission; however, space-charge effects limit the electron emission rate, potentially diminishing the efficiency of this cooling mechanism. We develop a variational weak form of the Poisson equation that describes the sheath potential and then numerically solve it using the finite element method. This formulation has two main benefits: (1) the space-charge limit condition can be incorporated as a constraint and (2) it allows for the analysis of three-dimensional geometries with complex boundary conditions. We demonstrate that the current emitted from the surface of an LE is generally a small fraction of the Child–Langmuir limit due to space charge. We then propose several methods to enhance the emitted current from the surface and to boost the cooling effect of thermionic emission. These include increasing the plasma density, applying a negative surface potential, and using fringe fields under suitable geometric conditions. For a LaB6 emitting LE, the total emitted current is shown to be minimal and independent of the temperature of a surface with floating potential. However, when a negative potential is applied and the surface is heated, the emitted current follows the Richardson–Dushman relationship up to a critical temperature, beyond which it remains constant. At an applied surface potential of −5 V, the critical temperature is around 1700 K.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2025

Properties of different LLM-105 preparations

LLM-105 (2,6-diamino-3,5-dinitropyrazine-1-oxide) has been prepared at several different size quantities (~10–70 Kg) and not subjected to further purification, such as recrystallization. Chemical and physical properties were compared—small-scale safety testing (impact, friction, ESD), thermal (chemical reactivity, differential scanning calorimetry (DSC), thermogravimetric analysis (TGA), one-dimensional time-to-explosion (ODTX)), morphological (particle-size distribution (PSD), scanning electron microscopy (SEM), powder x-ray diffraction (PXRD), skeletal density). Each preparation had similar properties to the other preparations except for PSD and PXRD. For PSD, all preparations exhibited a mono-modal distribution with a variation in median values from ~ 40 μm to over 80 μm. All PXRD values indicated the same morphology with minor variations in crystal orientations. Possible polymorphism was also observed in a few cases. SEM images and PXRD indicate all preparations to be diamond-type and X-type crystals with some twinning. Impact, friction, and ESD and thermal sensitivities values are consistent with these type of crystal habits as seen in vast literature studies.

Explosive characterization↗

DOE OSTI2021

Plasma-assisted catalysis for ammonia synthesis in a dielectric barrier discharge reactor: key surface reaction steps and potential causes of low energy yield

Ammonia synthesis experiments were carried out in a coaxial dielectric barrier discharge (DBD) reactor packed with several different supports and metal catalysts. There was a marked increase in the reaction rate, over that obtained in an empty DBD plasma reactor, upon introduction of a packed bed of γ-Al 2 O 3 , Ru/γ-Al 2 O 3 , or SiO 2 particles. The difference in the reaction rates over γ-Al 2 O 3 and Ru/γ-Al 2 O 3 was minimal. Complementary zero-dimensional plasma kinetic model analysis was also performed using inputs from experimental data. This kinetic analysis allowed for gas phase reactions, Eley–Rideal (E–R) reactions, and direct adsorption of radical species on the γ-Al 2 O 3 surface. On the metal surface, dissociative adsorption of N 2 and H 2 , and Langmuir–Hinshelwood reactions were also included. This analysis revealed that, under the conditions of our experiments, ammonia synthesis proceeds principally by the formation of reactive radicals in the gas phase, which then adsorb and participate in E–R reactions on both the metal and support material surfaces. Furthermore, this finding illustrates a challenge for substantially increasing the energy yield for plasma-assisted ammonia synthesis in typical DBD reactors containing packed catalyst beads.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗