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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 361 records · Page 20

Application of periodic perturbations to a RELAP5 hydraulic simulation to determine frequency response

Time series analysis requires a collection of data taken sequentially in time to apply techniques for identification, modeling, prediction or control purposes. Some systems operating at steady state are perturbed with white noise to extract system information using autoregressive models or spectral analysis, and then the dynamic response is used to assess system properties. If it is not possible to perturb the physical system, a mathematical model can be used to work with and study the perturbation effect. In this work, the system object of perturbation study is a RELAP5 hydraulic model, and since the excitation with a white noise sequence is not readily implementable, an alternative is proposed to apply a series of periodic steps in a square wave pattern. With this periodic excitation, the output of a RELAP5 model for a hydraulic piping system can be analyzed with frequency domain tools. The piping systems can be found in the balance of plant of a steam power plant, and the aim of this work is to explore the capability of RELAP5 to determine system frequency characteristics linked to mechanical vibration in operating lines of a power plant. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

A Novel Approach for Real-Time Quality Monitoring in Machining of Aerospace Alloy through Acoustic Emission Signal Transformation for DNN

Gamma titanium aluminide (γ-TiAl) is considered a high-performance, low-density replacement for nickel-based superalloys in the aerospace industry due to its high specific strength, which is retained at temperatures above 800 °C. However, low damage tolerance, i.e., brittle material behavior with a propensity to rapid crack propagation, has limited the application of γ-TiAl. Any cracks introduced during manufacturing would dramatically lower the useful (fatigue) life of γ-TiAl components, making the workpiece surface’s quality from finish machining a critical component to product quality and performance. To address this issue and enable more widespread use of γ-TiAl, this research aims to develop a real-time non-destructive evaluation (NDE) quality monitoring technique based on acoustic emission (AE) signals, wavelet transform, and deep neural networks (DNN). Previous efforts have opted for traditional approaches to AE signal analysis, using statistical feature extraction and classification, which face challenges such as the extraction of good/relevant features and low classification accuracy. Hence, this work proposes a novel AI-enabled method that uses a convolutional neural network (CNN) to extract rich and relevant features from a two-dimensional image representation of 1D time-domain AE signals (known as scalograms), subsequently classifying the AE signature based on pedigreed experimental data and finally predicting the process-induced surface quality. The results of the present work show good classification accuracy of 80.83% using scalogram images, in-situ experimental data, and a VGG-19 pre-trained neural network, establishing the significant potential for real-time quality monitoring in manufacturing processes.

36 MATERIALS SCIENCE↗

Broken-Symmetry Density Functional Theory Analysis of the Ω Intermediate in Radical S -Adenosyl- l -methionine Enzymes: Evidence for a Near-Attack Conformer over an Organometallic Species

Radical S-adenosyl-L-methionine (SAM) enzymes are found in all domains of life and catalyze a wide range of biochemical reactions. Recently, an organometallic intermediate, Ω, has been experimentally implicated in the 5'-deoxyadenosyl radical generation mechanism of the radical SAM superfamily. In this work, we employ broken-symmetry density functional theory to evaluate several structural models of Ω. The results show that the calculated hyperfine coupling constants (HFCCs) for the proposed organometallic structure of Ω are inconsistent with the experiment. In contrast, a near-attack conformer of SAM bound to the catalytic [4Fe–4S] cluster, in which the distance between the unique iron and SAM sulfur is ~3 Å, yields HFCCs that are all within 1 MHz of the experimental values. Furthermore, these results clarify the structure of the ubiquitous Ω intermediate and suggest a paradigm shift reversal regarding the mechanism of SAM cleavage by members of the radical SAM superfamily.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

MORPHOLOGICAL AND RADIATION DAMAGE INFORMED THERMAL PROPERTY PREDICTION IN SCALED GEOMETRIC DOMAINS

This proposed work has the potential to rewrite the way the nuclear industry investigates new fuel and nuclear material designs. The current rubric of nuclear material design has myriad steps in the process, and while certain physics are modeled accurately, each step must be connected in order to obtain an entire description of the process. At present, neutronic, thermal, microstructural, fission product chemistry and migration, and radiation defect analysis (hereafter referred to together as “combined analysis”) are performed, albeit separately. There is no existing method which combines these physics in an attempt to understand the natural interactions between these phenomena. Consequently, the timeline for design, fabrication, experiment, validation, and licensing can take years. A disruptive approach is required to accelerate the development of new technology. This proposed undertaking creates a validated computational framework, generating a new microscopic-to-macroscopic methodology yielding thermal property predictions for nuclear fuels and materials at an engineering spatial scale.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Adaptive Learning for Reliability Analysis using Support Vector Machines

A novel algorithm is presented for adaptive learning of an unknown function that separates two regions of a domain.In the context of reliability analysis these two regions represent the failure domain, where a set of constraints or requirements are violated, and a safe domain where they are satisfied. The Limit State Function (LSF) separates these two regions. Evaluating the constraints for a given parameter point requires the evaluation of a computational model that may well be expensive. For this reason we wish to construct a meta-model that can estimate the LSFas accurately as possible, using only a limited amount of training data. This work presents an adaptive strategy employing a Support Vector Machine (SVM) as a meta-model to provide a semi-algebraic approximation of the LSF.We describe an optimization process that is used to select informative parameter points to add to training data at each iteration to improve the accuracy of this approximation. A formulation is introduced for bounding the predictions of the meta-model; in this way we seek to incorporate this aspect of Gaussian Process Models (GPMs) within anSVM meta-model. Finally, we apply our algorithm to two benchmark test cases, demonstrating performance that is comparable with, if not superior, to a standard technique for reliability analysis that employs GPMs

Adaptive learning↗

Domain wall and interphase boundary motion in (1−x)Bi(Mg{sub 0.5}Ti{sub 0.5})O{sub 3}–xPbTiO{sub 3} near the morphotropic phase boundary

Electric field-induced changes in the domain wall motion of (1−x)Bi(Mg{sub 0.5}Ti{sub 0.5})O{sub 3}–xPbTiO{sub 3} (BMT-xPT) near the morphotropic phase boundary (MPB) where x = 0.37 (BMT-37PT) and x = 0.38 (BMT-38PT), are studied by means of synchrotron x-ray diffraction. Through Rietveld analysis and profile fitting, a mixture of coexisting monoclinic (Cm) and tetragonal (P4mm) phases is identified at room temperature. Extrinsic contributions to the property coefficients are evident from electric-field-induced domain wall motion in both the tetragonal and monoclinic phases, as well as through the interphase boundary motion between the two phases. Domain wall motion in the tetragonal and monoclinic phases for BMT-37PT is larger than that of BMT-38PT, possibly due to this composition's closer proximity to the MPB. Increased interphase boundary motion was also observed in BMT-37PT. Lattice strain, which is a function of both intrinsic piezoelectric strain and elastic interactions of the grains (the latter originating from domain wall and interphase boundary motion), is similar for the respective tetragonal and monoclinic phases.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Superdiffusive heat conduction in semiconductor alloys. II. Truncated Lévy formalism for experimental analysis

Nearly all experimental observations of quasiballistic heat flow are interpreted using Fourier theory with modified thermal conductivity. Detailed Boltzmann transport equation (BTE) analysis, yet, reveals that the quasi-ballistic motion of thermal energy in semiconductor alloys is no longer Brownian but instead exhibits Lévy dynamics with fractal dimension α < 2 . In this work, we present a framework that enables full three-dimensional experimental analysis by retaining all essential physics of the quasiballistic BTE dynamics phenomenologically. A stochastic process with just two fitting parameters describes the transition from pure Lévy superdiffusion as short length and time scales to regular Fourier diffusion. The model provides accurate fits to time domain thermoreflectance raw experimental data over the full modulation frequency range without requiring any “effective” thermal parameters and without any a priori knowledge of microscopic phonon scattering mechanisms. Identified α values for InGaAs and SiGe match ab initio BTE predictions within a few percent. Our results provide experimental evidence of fractal Lévy heat conduction in semiconductor alloys. The formalism additionally indicates that the transient temperature inside the material differs significantly from Fourier theory and can lead to improved thermal characterization of nanoscale devices and material interfaces.

36 MATERIALS SCIENCE↗

Flutter-Constrained Optimization with the Linearized Frequency-Domain Approach

Due to the high computational cost associated with unsteady aeroelastic analysis, state-of-the-art aeroelastic optimizations based on computational fluid dynamics typically ignore critical constraints like flutter and aeroelastic gust response. The linearized frequency-domain method offers an approach for adding high-fidelity flutter constraints to multidisciplinary optimizations at relatively low cost compared to other unsteady computational fluid dynamics methods. In recent work, sensitivities have been implemented for the linearized frequency-domain method in FUN3D. In this work, the linearized frequency-domain method and associated sensitivities are applied to gradient-based aeroelastic optimization with flutter constraints based on computational fluid dynamics. An overview of the flutter constraint formulation and implementation is provided, and then two optimization problems are presented. The first optimization increases the flutter speed of a pitch and plunge airfoil at transonic conditions using the minimal amount of geometric changes. The second optimization minimizes the mass of the AGARD 445.6 wing subject to a flutter constraint.

Aeroelasticity↗

Flutter-Constrained Optimization with the Linearized Frequency-Domain Approach

Due to the high computational cost associated with unsteady aeroelastic analysis, state-of-the-art aeroelastic optimizations based on computational fluid dynamics typically ignore critical constraints like flutter and aeroelastic gust response. The linearized frequency-domain method offers an approach for adding high-fidelity flutter constraints to multidisciplinary optimizations at relatively low cost compared to other unsteady computational fluid dynamics methods. In recent work, sensitivities have been implemented for the linearized frequency-domain method in FUN3D. In this work, the linearized frequency-domain method and associated sensitivities are applied to gradient-based aeroelastic optimization with flutter constraints based on computational fluid dynamics. An overview of the flutter constraint formulation and implementation is provided, and then two optimization problems are presented. The first optimization increases the flutter speed of a pitch and plunge airfoil at transonic conditions using the minimal amount of geometric changes. The second optimization minimizes the mass of the AGARD 445.6 wing subject to a flutter constraint.

Aeroelasticity↗

Introducing NOODLES: Collaborative Visualization in a Flavorful Package

We introduce NOODLES, a lightweight collaborative visualization and analysis protocol. NOODLES was developed to enable new scientific workflows while enhancing existing pipelines. Using a technology-minimal approach to strengthen applicability, this protocol allows researchers to tie disparate software together as well as making domain specific visualizations accessible across various platforms and form factors. In this talk we discuss background, challenges, and gaps in the current tool landscape that lead to the development of the protocol. We then describe the design of the protocol and present several use cases to demonstrate the efficacy of NOODLES in addressing complex visualization challenges and how it co-exists with existing tools. We conclude by outlining in-progress work and potential avenues for future development within the NOODLES framework.

collaborative analysis↗

Growing antiphase-domain-free GaAs thin films out of highly ordered planar nanowire arrays on exact (001) silicon

We report the use of highly ordered, dense, and regular arrays of in-plane GaAs nanowires as building blocks to produce antiphase-domain-free GaAs thin films on exact (001) silicon. High quality GaAs nanowires were grown on V-grooved Si (001) substrates using the selective aspect ratio trapping concept. The 4.1% lattice mismatch has been accommodated by the initial GaAs, a few nanometer-thick with high density stacking faults. The bulk of the GaAs wires exhibited smooth facets and a low defect density. An unusual defect trapping mechanism by a “tiara”-like structure formed by Si undercuts was discovered. As a result, we were able to grow large-area antiphase-domain-free GaAs thin films out of the nanowires without using SiO{sub 2} sidewalls for defect termination. Analysis from XRD ω-rocking curves yielded full-width-at-half-maximum values of 238 and 154 arc sec from 900 to 2000 nm GaAs thin films, respectively, indicating high crystalline quality. The growth scheme in this work offers a promising path towards integrated III-V electronic, photonic, or photovoltaic devices on large scale silicon platform.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Long-range and local crystal structures of the S r 1 - x C a x Ru O 3 perovskites

Here, the crystal structures of the Sr 1–x Ca x RuO 3 (0 ≤ x ≤ 1) perovskites are investigated using both long-range and local structural probes. High-resolution synchrotron powder x-ray-diffraction characterization at ambient temperature shows that the materials have orthorhombic long-range crystal structures to high precision, and we support previous work showing that Ca 2+ substitution for Sr 2+ primarily changes the tilting of rigid corner-sharing RuO 6 octahedra at their shared oxygen vertices. X-ray pair-distribution function analysis for SrRuO 3 , CaRuO 3 , and one intermediate composition show them to display monoclinic symmetry at the local level; when averaged over different domain orientations this yields orthorhombic symmetry in the long range, and no long-range or local phase transitions are observed between 80 and 300 K for materials with intermediate compositions. High-resolution transmission electron microscopy shows that the Sr/Ca distribution is random at the nanoscale. Lastly, we plot magnetic characteristics such as the ferromagnetic T c , Curie-Weiss theta, effective moment, and ambient temperature susceptibility vs the octahedral tilt and unit-cell volume.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

SRBench++: Principled Benchmarking of Symbolic Regression With Domain-Expert Interpretation

Symbolic regression searches for analytic expressions that accurately describe studied phenomena. The main promise of this approach is that it may return an interpretable model that can be insightful to users, while maintaining high accuracy. The current standard for benchmarking these algorithms is SRBench, which evaluates methods on hundreds of datasets that are a mix of real-world and simulated processes spanning multiple domains. At present, the ability of SRBench to evaluate interpretability is limited to measuring the size of expressions on real-world data, and the exactness of model forms on synthetic data. In practice, model size is only one of many factors used by subject experts to determine how interpretable a model truly is. Furthermore, SRBench does not characterize algorithm performance on specific, challenging sub-tasks of regression such as feature selection and evasion of local minima. In this work, we propose and evaluate an approach to benchmarking SR algorithms that addresses these limitations of SRBench by 1) incorporating expert evaluations of interpretability on a domain-specific task, and 2) evaluating algorithms over distinct properties of data science tasks. We evaluate 12 modern symbolic regression algorithms on these benchmarks and present an in-depth analysis of the results, discuss current challenges of symbolic regression algorithms and highlight possible improvements for the benchmark itself.

97 MATHEMATICS AND COMPUTING↗

Modeling of Macroscopic Dynamics in Three-Dimensional Plasma Configurations (Final Technical Report)

A numerical simulation-based study to investigate the stability properties of inherently three-dimensional plasma magnetic configurations is presented. These configurations, called stellarators and heliotrons, use external helical coils to provide the twisting magnetic field that is required to confine ionized plasma particles. In contrast to the tokamak configuration, which nominally has the property of axisymmetry, electrical current does not need to be induced in stellarator and heliotron plasma. Experiments have shown that these three-dimensional configurations are remarkably robust to macroscopic instability, even when driven to relatively high levels of plasma pressure. Our understanding of how the plasma is able to withstand macroscopic instability will be enhanced by the work proposed here. The effort will generalize existing numerical modeling capability, and it will apply the new capability to model macroscopic dynamics in these three-dimensional configurations. The development work has been applied to the NIMROD simulation code (https://nimrodteam.org) that was originally based on axisymmetric problem domains. It has been generalized to accommodate the three-dimensional shaping of the plasma volume in stellarators and heliotrons. Its use of equilibrium data has also been generalized, and the implementation allows different numerical representation of the magnetic field. Analysis has been performed to inform the selection of numerical methods, and a method to accelerate the iterative solution of the necessary algebraic systems has been developed and implemented. Verification of the new NIMSTELL code on benchmark problems has also been an important part of the effort.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

An evaluation of a computer code based on linear acoustic theory for predicting helicopter main rotor noise

Acoustic characteristics predicted using a recently developed computer code were correlated with measured acoustic data for two helicopter rotors. The analysis, is based on a solution of the Ffowcs-Williams-Hawkings (FW-H) equation and includes terms accounting for both the thickness and loading components of the rotational noise. Computations are carried out in the time domain and assume free field conditions. Results of the correlation show that the Farrassat/Nystrom analysis, when using predicted airload data as input, yields fair but encouraging correlation for the first 6 harmonics of blade passage. It also suggests that although the analysis represents a valuable first step towards developing a truly comprehensive helicopter rotor noise prediction capability, further work remains to be done identifying and incorporating additional noise mechanisms into the code.

Davis, S. J.↗

Enhancements to the SSME transfer function modeling code

This report details the results of a one year effort by Ohio University to apply the transfer function modeling and analysis tools developed under NASA Grant NAG8-167 (Irwin, 1992), (Bartholomew, 1992) to attempt the generation of Space Shuttle Main Engine High Pressure Turbopump transfer functions from time domain data. In addition, new enhancements to the transfer function modeling codes which enhance the code functionality are presented, along with some ideas for improved modeling methods and future work. Section 2 contains a review of the analytical background used to generate transfer functions with the SSME transfer function modeling software. Section 2.1 presents the 'ratio method' developed for obtaining models of systems that are subject to single unmeasured excitation sources and have two or more measured output signals. Since most of the models developed during the investigation use the Eigensystem Realization Algorithm (ERA) for model generation, Section 2.2 presents an introduction of ERA, and Section 2.3 describes how it can be used to model spectral quantities. Section 2.4 details the Residue Identification Algorithm (RID) including the use of Constrained Least Squares (CLS) and Total Least Squares (TLS). Most of this information can be found in the report (and is repeated for convenience). Section 3 chronicles the effort of applying the SSME transfer function modeling codes to the a51p394.dat and a51p1294.dat time data files to generate transfer functions from the unmeasured input to the 129.4 degree sensor output. Included are transfer function modeling attempts using five methods. The first method is a direct application of the SSME codes to the data files and the second method uses the underlying trends in the spectral density estimates to form transfer function models with less clustering of poles and zeros than the models obtained by the direct method. In the third approach, the time data is low pass filtered prior to the modeling process in an effort to filter out high frequency characteristics. The fourth method removes the presumed system excitation and its harmonics in order to investigate the effects of the excitation on the modeling process. The fifth method is an attempt to apply constrained RID to obtain better transfer functions through more accurate modeling over certain frequency ranges. Section 4 presents some new C main files which were created to round out the functionality of the existing SSME transfer function modeling code. It is now possible to go from time data to transfer function models using only the C codes; it is not necessary to rely on external software. The new C main files and instructions for their use are included. Section 5 presents current and future enhancements to the XPLOT graphics program which was delivered with the initial software. Several new features which have been added to the program are detailed in the first part of this section. The remainder of Section 5 then lists some possible features which may be added in the future. Section 6 contains the conclusion section of this report. Section 6.1 is an overview of the work including a summary and observations relating to finding transfer functions with the SSME code. Section 6.2 contains information relating to future work on the project.

Irwin, R. Dennis↗

FX2 advanced fogging technology - 15711

Problem statement: The need for an advanced technology that can better address potential airborne contaminants at DOE Savannah River Site 235-F. Current methods of knocking down or fixing this contamination are labor intensive, costly, and sometimes ineffective. Thus, to make exposure ALARA, the advanced fogging effort is being tested using Idaho National Laboratory's FX2 fixative agent. The FX2 fogging agent is a proprietary mixture of water, latex paint (LTX), glycerin (GLY) and sodium lauryl sulfate (SLS). Initial development began in 2006 when a DOE Small Business Innovative Research (SBIR) grant resulted in the development of a conceptual advanced capture coating fog system. This coating is shown to be excellent at reducing airborne contamination and 'fixing' particulates in place as demonstrated by Idaho National Lab. Controlling Potential Airborne Particulates: Testing capacity to knockdown airborne particulates. Evaluating ability to fix to different surfaces (e.g., glass, wood, steel, concrete, brick). Line of sight as well as non-line of sight (shadowed) locations will be tested for coverage. Adhesiveness and Coverage of Surface Area: Contact area will be placed under air pressure to attempt dislodging of dried mixture. Particle analysis utilizing ImageJ will be conducted to determine quantifiable coverage. Ignitability: Observation of the FX2's reactivity to flame and heat sources as it is being applied. Results will provide useful information for the prevention of potential hazards. Determine Shielding Properties Against Alpha Sources: Determine the shielding abilities of the FX2. Fogging agent against an alpha particle emitting point source. Evaluating Critical Properties: These properties will be evaluated to better characterize the FX2 and allow for optimal understanding of results: ASTM E1354 - Burn Rate; NFPA 296-Flashover; ASTM D2196 - Viscosity; ASTM D1331 - Surface Tension; ASTM D792 - Density. Testing Innovations: Developed by the National Institutes of Health, ImageJ is a public domain image processing program that allows for the analysis that this effort requires. Coverage: Through contrast analysis, ImageJ can be used to determine the coverage of the agent upon any of the testing surfaces. Correlations: With the feature of coverage evaluation, a relationship, and thus a graphical representation, can be made between surface coverage and radiation shielding. Future work: Engineering and manufacturing of mobile robotic fogging device. ASTM WK5394: establishing performance specifications for stabilizers to minimize migration of dispersible radioactive contamination.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

An Overview of Atmospheric Features Over the Western North Atlantic Ocean and North American East Coast – Part 1: Analysis of Aerosols, Gases, and Wet Deposition Chemistry

The Western North Atlantic Ocean (WNAO) and adjoining East Coast of North America are of great importance for atmospheric research and have been extensively studied for several decades. This broad region exhibits complex meteorological features and a wide range of conditions associated with gas and particulate species from many sources regionally and other continents. As Part 1 of a 2‐part paper series, this work characterizes quantities associated with atmospheric chemistry, including gases, aerosols, and wet deposition, by analyzing available satellite observations, ground‐based data, model simulations, and reanalysis products. Part 2 provides insight into the atmospheric circulation, boundary layer variability, three‐dimensional cloud structure, properties, and precipitation over the WNAO domain. Key results include spatial and seasonal differences in composition along the North American East Coast and over the WNAO associated with varying sources of smoke and dust and meteorological drivers such as temperature, moisture, and precipitation. Spatial and seasonal variations of tropospheric carbon monoxide and ozone highlight different pathways towards the accumulation of these species in the troposphere. Spatial distributions of speciated aerosol optical depth and vertical profiles of aerosol mass mixing ratios show a clear seasonal cycle highlighting the influence of different sources in addition to the impact of intercontinental transport. Analysis of long‐term climate model simulations of aerosol species and satellite observations of carbon monoxide confirm that there has been a significant decline in recent decades among anthropogenic constituents owing to regulatory activities.

ACTIVATE↗