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DOE OSTI2022

Multiscale and multiphysics FEA simulation and materials optimization for laser ultrasound transducers

In this study, the relationship between the nanocomposite design and the laser ultrasound transducer (LUT) characteristics was investigated through simulations in multiple scale levels for material behavior, device response, and acoustic wave propagation in media. First, the effects of the nanoparticle size and concentration on the effective properties of composites were quantitatively investigated with the finite element analysis (FEA) method. Second, the effective properties of the nanocomposite were assigned to the layer, which is modeled as a homogeneous material, in the FEA for the LUT simulating the energy conversion from the incident laser to the acoustic wave. Finally, the ultrasound propagation in the water was calculated by a theoretical wave propagation model. The FEA-based prediction was compared with the experimental data in the literature and a theoretical analysis for LUT based on Thermal-Acoustic coupling. As a result, the ultrasound waves on the transducer surface and at a distance in the water could be predicted. Based on the hierarchically integrated prediction procedure, the optimal conditions of the photoacoustic nanocomposites were investigated through the parametric study with the particle size and concentration as variables. The results guide the material designs optimized for different device characteristics, such as high pressure and broad bandwidth.

36 MATERIALS SCIENCE↗

NASA NTRS1981

Instrumentation applications to Space Shuttle models and thermal protection system tiles tested in NASA-AMES wind tunnels

The highlights of the many wind-tunnel tests conducted in the course of the Space Shuttle development program are presented with emphasis on instrumentation applications. The examples of tests discussed include airframe aerodynamics, aerodynamic heating, aerodynamic noise, tile dynamic response, and tile loads. Many of the tests were conducted with standard wind-tunnel instrumentation. Most of the more unusual instrumentation requirements were related to the thermal protection system, where some pressure-sensor concepts were adapted to measure airloads on tiles. These measurements provided the only quantitative data that could be used to confirm the airload analysis procedure. Limited applications of computers to experimental control, in conjunction with data taken during Shuttle tests, have resulted in substantial benefits in overall test efficiency.

Coe, C. F.↗

NASA NTRS1991

Navier-Stokes calculation of transonic flow past the NTF 65 deg delta wing

Models of four delta wings were built and tested in the 8 x 8 ft Transonic Wind Tunnel at LaRC. The wings are identical in planform shape with a swept-back angle of 65 degrees, but bear different leading edge profiles. The models were tested under pressurized and cryogenic conditions to simulate true flight Reynolds numbers. Data on the aerodynamic forces and pressure distributions at various locations on the wings were taken at various flight Mach numbers and angles of attack. Effects of high Reynolds number and leading edge radius on the aerodynamic characteristics of the wings are being accessed. To thoroughly understand the turbulent, vortical flow around the wings, an effort to perform computational aerodynamic analysis is being made. The objective of the analysis is to supplement and validate the experimental data and explain the high Reynolds number and leading edge effects. GRIDGEN, a software developed by General Dynamics, is being used to generate the grid topology for the flow field around the wings. The flow solver to be used is CFL3D, a computation fluid dynamics code developed at LaRC. Based on the geometric description of the wings, a FORTRAN program called WINGSURF was written to generate the databases defining the surface geometry of the wings. To match the true geometry of the models in the wind tunnel for realistic comparison with experimental results, databases defining the sting support for the wing models were also created by two other FORTRAN programs, STINJOIN and STINREAR. Listing of the programs are attached and the geometry of a typical wing model with the sting support is shown. Other aspects of the investigation are discussed.

Wu, Chivey C.↗

DOE OSTI2023

Reactor Network Analysis with Various Reaction Mechanisms to Investigate Hydrogen vs. Methane Fuel at Varying Flame Temperatures with Experimental Data

Emissions data were evaluated for a set of test hardware that adapts Collins Aerospace’s aeroengine liquid fueled injector technology to a ground-based turbine. The hardware was specifically developed to operate on 100% hydrogen; however it has the ability to operate on both pure methane and hydrogen and mixtures in between. 16 injector configurations and seven factors (air split, fuel and air swirl, pressure drop, preheat temperature, fuel composition, and flame temperature) were investigated based on a Box Behnken statistical model. Of the 16, configuration 3 was selected for further discussion being in the middle of the statistical design space. A chemical reactor network was developed based on the experimental data obtained and was assessed with three different mechanisms: GRI Mech 3.0, UCSD, and Galway. All factors were held constant except the fuel composition to directly compare chemical pathways for methane and hydrogen. This study was conducted across different flame temperatures of 1500K, 1675K, and 1850K for both hydrogen and methane. Additional lower flame temperatures of 1100K and 1300K were evaluated for hydrogen. Moreover, results for fully premixed and non-premixed results were compared to obtain information on the implications of mixedness on emissions. These results were compared with the Leonard and Stegmaier plot for methane and a similar plot was constructed for hydrogen.

08 HYDROGEN↗

DOE OSTI2023

A database of synthetic inelastic neutron scattering spectra from molecules and crystals

Abstract Inelastic neutron scattering (INS) is a powerful tool to study the vibrational dynamics in a material. The analysis and interpretation of the INS spectra, however, are often nontrivial. Unlike diffraction, for which one can quickly calculate the scattering pattern from the structure, the calculation of INS spectra from the structure involves multiple steps requiring significant experience and computational resources. To overcome this barrier, a database of INS spectra consisting of commonly seen materials will be a valuable reference, and it will also lay the foundation of advanced data-driven analysis and interpretation of INS spectra. Here we report such a database compiled for over 20,000 organic molecules and over 10,000 inorganic crystals. The INS spectra are obtained from a streamlined workflow, and the synthetic INS spectra are also verified by available experimental data. The database is expected to greatly facilitate INS data analysis, and it can also enable the utilization of advanced analytics such as data mining and machine learning. Notice: This manuscript has been authored by UT-Battelle, LLC under Contract No. DE-AC05-00OR22725 with the U.S. Department of Energy. The United States Government retains and the publisher, by accepting the article for publication, acknowledges that the United States Government retains a non-exclusive, paid-up, irrevocable, world-wide license to publish or reproduce the published form of this manuscript, or allow others to do so, for United States Government purposes. The Department of Energy will provide public access to these results of federally sponsored research in accordance with the DOE Public Access Plan ( http://energy.gov/downloads/doe-public-access-plan ).

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

NASA NTRS1980

Initial characterization of an Experimental Referee Broadened-Specification (ERBS) aviation turbine fuel

Characterization data and a hydrocarbon compositional analysis are presented for a research test fuel designated as an experimental referee broadened-specification aviation turbine fuel. This research fuel, which is a special blend of kerosene and hydrotreated catalytic gas oil, is a hypothetical representation of a future fuel should it become necessary to broaden current kerojet specifications. It is used as a reference fuel in research investigations into the effects of fuel property variations on the performance and durability of jet aircraft components, including combustors and fuel systems.

Prok, G. M.↗

DOE OSTI2021

Informing nuclear physics via machine learning methods with differential and integral experiments

Information from differential nuclear-physics experiments and theory is often too uncertain to accurately define nuclear-physics observables such as cross sections or energy spectra. Integral experimental data, representing the applications of these observables, are often more precise but depend simultaneously on too many of them to unambiguously identify issues in the observable with human expert analysis alone. Here, we explore how we can leverage physics knowledge gained from differential experimental data, nuclear theory, integral experiments, and neutron-transport calculations to better understand nuclear-physics observables in the context of the application area represented by integral experiments. We support this task with machine-learning methods to discern trends in a large amount of convoluted data. Differential and integral information was used in an analysis augmented by the random forest and the Shapley additive explanations metric. We chose as an application area one that is represented by criticality measurements and pulsed-sphere neutron-leakage spectra. We show one representative example ( 241 Pu fission observables) where the combination of differential and integral information allowed to resolve issues in data representing these observables. As a starting point, the machine learning (ML) algorithms highlighted several observables as leading potentially to bias in simulating integral experiments. Differential information, paired with sensitivity to integral quantities, allowed us then to pinpoint one specific observable ( 241 Pu fission cross section) as the main driver of bias. The comparison to integral experiments, on the other hand, allowed us to indicate a likely reliable experiment among several discrepant ones for this observables. In other cases (e.g., 239 Pu observables), we were not able to resolve the confounding introduced by integral experiments but instead highlighted the need for targeted new experiments and theory developments to better constrain the nuclear-physics space for the application area represented by integral experiments. We were able to combine information from differential experimental data, nuclear-physics theory, integral experiments, and neutron-transport simulations of the latter experiments with the help of the random forest algorithm and expert judgment. This combination of knowledge allows to improve our description of nuclear-physics observables as applied to a particular application area.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

NASA NTRS1986

Experimental evaluation criteria for constitutive models of time dependent cyclic plasticity

Notched members were tested at temperatures far above those recorded till now. Simulation of the notch root stress response was accomplished to establish notch stress-strain behavior. Cyclic stress-strain profiles across the net-section were recorded and on-line direct notch strain control was accomplished. Data are compared to three analysis techniques with good results. The objective of the study is to generate experimental data that can be used to evaluate the accuracy of constitutive models of time dependent cyclic plasticity.

Martin, J. F.↗

NASA NTRS1992

Flow analysis and design optimization methods for nozzle-afterbody of a hypersonic vehicle

This report summarizes the methods developed for the aerodynamic analysis and the shape optimization of the nozzle-afterbody section of a hypersonic vehicle. Initially, exhaust gases were assumed to be air. Internal-external flows around a single scramjet module were analyzed by solving the 3D Navier-Stokes equations. Then, exhaust gases were simulated by a cold mixture of Freon and Ar. Two different models were used to compute these multispecies flows as they mixed with the hypersonic airflow. Surface and off-surface properties were successfully compared with the experimental data. The Aerodynamic Design Optimization with Sensitivity analysis was then developed. Pre- and postoptimization sensitivity coefficients were derived and used in this quasi-analytical method. These coefficients were also used to predict inexpensively the flow field around a changed shape when the flow field of an unchanged shape was given. Starting with totally arbitrary initial afterbody shapes, independent computations were converged to the same optimum shape, which rendered the maximum axial thrust.

Baysal, O.↗

NASA NTRS1999

Aero-Structural Interaction, Analysis, and Shape Sensitivity

A multidisciplinary sensitivity analysis technique that has been shown to be independent of step-size selection is examined further. The accuracy of this step-size independent technique, which uses complex variables for determining sensitivity derivatives, has been previously established. The primary focus of this work is to validate the aero-structural analysis procedure currently being used. This validation consists of comparing computed and experimental data obtained for an Aeroelastic Research Wing (ARW-2). Since the aero-structural analysis procedure has the complex variable modifications already included into the software, sensitivity derivatives can automatically be computed. Other than for design purposes, sensitivity derivatives can be used for predicting the solution at nearby conditions. The use of sensitivity derivatives for predicting the aero-structural characteristics of this configuration is demonstrated.

Newman, James C., III↗

DOE OSTI2021

SCALE 6.2.4 Validation for Light Water Reactor Decay Heat Analysis

Energy release from the decay of radionuclides in nuclear fuel after its discharge from reactor is a critical parameter for design, safety, and licensing analyses of used nuclear fuel storage, transportation, and repository systems. Well-validated computational tools and nuclear data are essential for decay heat prediction. This paper summarizes the validation of the SCALE nuclear analysis code system version 6.2.4, used with ENDF/B-VII.1 libraries, for decay heat analysis of light water reactor used fuel. The experimental data used for validation include full-assembly decay heat measurements that cover assembly burnups of 5 to 51 GWd/tonne U, cooling times after discharge in the 2- to 27-year range, and initial fuel enrichments up to 4 wt% 235U. The comparison between calculated (C) and experimental (E) decay heat showed very good agreement, with an average C/E over all considered measurements of 1.006 (σ = 0.016) for pressurized water reactor and 0.984 (σ = 0.077) for boiling water reactor assembly measurements. The effect of using assembly-average versus axially varying modeling data on the calculated decay heat, important to thermal analyses for used fuel transportation and storage systems, is discussed.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

NASA NTRSDate not supplied

Uncertainty Estimates for Sonic-Boom Pressure Signatures and Loudness Carpets

A non-intrusive uncertainty quantification method is applied to computational analysis of supersonic, low-boom aircraft. The mean and standard deviation statistics of the pressure waveforms and loudness metrics are evaluated through use of numerical quadrature. The probability density function (p.d.f.) of these outputs is evaluated via kernel density estimation. The simulations use an inviscid, embedded-boundary Cartesian-mesh flow solver in the nearfield combined with an augmented Burgers’ equation solver for propagation in the farfield. The results show that the p.d.f. of the waveform is bimodal at shocks, which makes the mean and standard deviation statistics inappropriate. Despite this limitation, we show that the moment statistics can provide effective assessment of discrepancies when comparing with experimental data. This is demonstrated by presenting uncertainty analysis of a wind-tunnel test and showing that we significantly improve the predictions when we include the test uncertainties in the simulation. Normal distributions are obtained for the ground signature and loudness metrics, which is primarily due to the careful shaping of the low-boom waveform. Separation of variables and error control are used to reduce computational cost. We demonstrate that this is an efficient approach in the sense of balancing numerical errors in the statistics quadrature with discretization errors in the solvers.

ARMD↗

NASA NTRS1997

Analysis of Emission Spectra from Arc-jet Shock Layer Flows

This paper reports computational comparisons with experimental studies of a nonequilibrium blunt body shock layer in a high enthalpy arc-jet wind tunnel at NASA Ames Research Center. The primary objective of this work is to investigate the existence of a thermochemical equilibrium region in the shock layer. The existence of such an equilibrium region is of interest for following reasons: (1) to understand the equilibration process behind the shock in an arc-jet flow environment; (2) to interpret measured surface heat transfer data for purpose of determining surface catalytic efficiency, and (3) to determine the total enthalpy from the spectroscopic measurements. The paper will present an analysis of the experimental data obtained in the arc-jet wind tunnel. Experimental data includes measurements of emission spectra of radiation emanating from a shock layer formed in front of a 6-inch flat-faced cylinder. The measurements, obtained using a two dimensional CCD camera mounted on a spectrograph, provide spatially resolved spectra along the stagnation streamline of the model. Computational analysis includes simulation of nonequilibrium flow in the arc-jet facility (flow in the conical nozzle and shock layer in front of a flat-faced cylinder) using 2-D/axisymmetric Navier-Stokes codes and prediction of the radiation spectra from the axisymmetric flowfield using NEQAIR radiation code. Various line-of-sight averaged flow properties such as vibrational and rotational temperatures, species number densities within the shock layer are deduced from the experimental spectra. Comparison of the computed and experimental line-of-sight averaged flow properties provides assessment of thermochemical equilibration processes in an arc-jet shock layer.

Gokcen, T.↗

DOE OSTI2023

Investigations of Baryon Spectroscopy via Electromagnetic and Hadronic Scattering (Final Report, May 1, 2019 to August 15, 2021)

The principal goal of this project is the experimental and phenomenological study of baryon spectroscopy. The P.I.’s group currently consists of himself and one student, Mr. Haoran Sun. Haoran’s project involves a new coupled-channel partial-wave analysis of all available world data for the reactions $K^0_Lp → K^0_Sp, K^+p → K^+p, K^+n → K^0p, K^0p → K^+n$, and $K^+n → K^+n$. The analysis of Mr. Sun is related to a conditionally approved proposal to develop a secondary $K^0_L$ beamline in Hall D at JLab, to be used with the GlueX setup. Mr. Sun’s analysis will establish some of the software codes necessary to analyze some of the data that could be measured at this facility. More importantly, the analysis will provide new experimental constraints on important background $\textit{KN}$ reactions, which are needed in order to help understand data that involve formation of Λ$^{\ast}$ and Σ$^{\ast}$ resonances.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2020

Rapid Identification of X-ray Diffraction Patterns Based on Very Limited Data by Interpretable Convolutional Neural Networks

Large volumes of data from material characterizations call for rapid and automatic data analysis to accelerate materials discovery. Herein, we report a convolutional neural network (CNN) that was trained based on theoretical data and very limited experimental data for fast identification of experimental X-ray diffraction (XRD) patterns of metal–organic frameworks (MOFs). To augment the data for training the model, noise was extracted from experimental data and shuffled; then it was merged with the main peaks that were extracted from theoretical spectra to synthesize new spectra. For the first time, one-to-one material identification was achieved. Theoretical MOFs patterns (1012) were augmented to a whole data set of 72 864 samples. It was then randomly shuffled and split into training (58 292 samples) and validation (14 572 samples) data sets at a ratio of 4:1. For the task of discriminating, the optimized model showed the highest identification accuracy of 96.7% for the top 5 ranking on a test data set of 30 hold-out samples. Neighborhood component analysis (NCA) on the experimental XRD samples shows that the samples from the same material are clustered in groups in the NCA map. Analysis on the class activation maps of the last CNN layer further discloses the mechanism by which the CNN model successfully identifies individual MOFs from the XRD patterns. Furthermore, this CNN model trained by the data augmentation technique would not only open numerous potential applications for identifying XRD patterns for different materials, but also pave avenues to autonomously analyze data by other characterization tools such as FTIR, Raman, and NMR spectroscopies.

36 MATERIALS SCIENCE↗

NASA NTRS2003

Application of Probability Methods to Assess Crash Modeling Uncertainty

Full-scale aircraft crash simulations performed with nonlinear, transient dynamic, finite element codes can incorporate structural complexities such as: geometrically accurate models; human occupant models; and advanced material models to include nonlinear stress-strain behaviors, and material failure. Validation of these crash simulations is difficult due to a lack of sufficient information to adequately determine the uncertainty in the experimental data and the appropriateness of modeling assumptions. This paper evaluates probabilistic approaches to quantify the effects of finite element modeling assumptions on the predicted responses. The vertical drop test of a Fokker F28 fuselage section will be the focus of this paper. The results of a probabilistic analysis using finite element simulations will be compared with experimental data.

Lyle, Karen H.↗

NASA NTRS2007

Application of Probability Methods to Assess Crash Modeling Uncertainty

Lyle, Karen H.↗

NASA NTRSDate not supplied

Interlaminar R-Curve Effects in Thermoplastic Composites: Experiments and Model Correlations

The interlaminar fracture behavior of thermoplastic composites under Mode-I and Mode-II static loading is investigated in this research. The material system under consideration is a carbon fiber reinforced low melt semi-crystalline resin TC1225 LMPAEK T700G (T700/LMPAEK)†. Characterization experiments were conducted to measure the load-displacement response, peak load, and propagation of delamination from a pre-implanted Kapton® insert. The Mode-I response was characterized using a double cantilever beam (DCB) test according to the ASTM D5528-22 standard. It was observed that the propagation exhibited significant resistance to delamination growth, i.e., an R-Curve effect. The test data indicated that the steady-state fracture toughness, G SS I , was approximately twice the mean initiation fracture toughness, G Ic . The Mode-II response of an end notch flexure (ENF) specimen tested according to the ASTM D7905-19 standard exhibited an unexpected stable behavior upon attaining peak load. Prior to attaining peak load, the Mode-II response exhibited some non-linearity, which may be attributed to nonlinear bulk material response, e.g., hyper-elasticity, viscoelasticity, plasticity, etc., and potentially friction at the load/support rollers and R-Curve effects. Finite element models based on the Cohesive Zone Method (CZM) and the Virtual Crack Closure Technique (VCCT) were used to predict the DCB and ENF specimen responses. DCB analysis results obtained using G SS I predicted propagation consistent with experimental data. However, results obtained with the as characterized G Ic were inaccurate in predicting delamination growth onset and peak load. ENF analysis results obtained with the as-characterized Mode-II fracture toughness, G IIc , were inaccurate in predicting the peak load and propagation. Hence, R-Curve effects were included in both DCB and ENF simulations, which enabled improved predictions. The experimentally determined Mode-I R-Curve was used for the DCB simulations, whereas an R-Curve was derived for Mode-II assuming that the change in compliance of the specimen was associated with crack growth only.

Prabhakar M Rao↗