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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 685 records · Page 38
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Structural features of sodium silicate glasses from reactive force field-based molecular dynamics simulations

Atomistic computer simulations can offer insights into silicate glass-environment interactions with the recent development of reactive potentials. Yet, the accuracy of generated glass structures with these potential was usually not fully examined. In this paper, the capability of the reactive force field (ReaxFF) to describe the short and medium range structure features of sodium silicate glasses in molecular dynamics simulations is investigated by comparing a widely used partial charge pairwise potential and available experimental data. Glass structure information such as pair distribution function (PDF), coordination number, Qn species, neutron broadened structure factor, and X-ray broadened structure factor of the glass structures from ReaxFF simulations were calculated and compared to evaluate the generated glass structure. Advantages and limitations of the potentials and glass forming procedures, as well as areas of further improvement, were discussed. The results show that the recently refined ReaxFF parameters through the proposed procedure enable the simulations of sodium silicate glass structures with minimal defects, which paves the way to investigate water-glass interaction mechanisms with the reactive enabled potentials.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Calibration of RAFM Micromechanical Model for Creep Using Bayesian Optimization for Functional Output

A Bayesian optimization procedure is presented for calibrating a multimechanism micromechanical model for creep to experimental data of F82H steel. Reduced activation ferritic martensitic (RAFM) steels based on Fe(8–9)%Cr are the most promising candidates for some fusion reactor structures. Although there are indications that RAFM steel could be viable for fusion applications at temperatures up to 600°C, the maximum operating temperature will be determined by the creep properties of the structural material and the breeder material compatibility with the structural material. Due to the relative paucity of available creep data on F82H steel compared to other alloys such as Grade 91 steel, micromechanical models are sought for simulating creep based on relevant deformation mechanisms. As a point of departure, this work recalibrates a model form that was previously proposed for Grade 91 steel to match creep curves for F82H steel. Due to the large number of parameters (9) and cost of the nonlinear simulations, an automated approach for tuning the parameters is pursued using a recently developed Bayesian optimization for functional output (BOFO) framework (Huang et al., 2021, “Bayesian optimization of functional output in inverse problems,” Optim. Eng., 22, pp. 2553–2574). Incorporating extensions such as batch sequencing and weighted experimental load cases into BOFO, a reasonably small error between experimental and simulated creep curves at two load levels is achieved in a reasonable number of iterations. In conclusion, validation with an additional creep curve provides confidence in the fitted parameters obtained from the automated calibration procedure to describe the creep behavior of F82H steel.

42 ENGINEERING↗
DOE OSTI2022

New Machine Learning Techniques for Simulation-Based Inference: InferoStatic Nets, Kernel Score Estimation, and Kernel Likelihood Ratio Estimation

We propose an intuitive, machine-learning approach to multiparameter inference, dubbed the InferoStatic Networks (ISN) method, to model the score and likelihood ratio estimators in cases when the probability density can be sampled but not computed directly. The ISN uses a backend neural network that models a scalar function called the inferostatic potential $\varphi$. In addition, we introduce new strategies, respectively called Kernel Score Estimation (KSE) and Kernel Likelihood Ratio Estimation (KLRE), to learn the score and the likelihood ratio functions from simulated data. We illustrate the new techniques with some toy examples and compare to existing approaches in the literature. We mention en passant some new loss functions that optimally incorporate latent information from simulations into the training procedure.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

R-matrix calculations for opacities: I. Methodology and computations

Abstract An extended version of the R -matrix methodology is presented for calculation of radiative parameters for improved plasma opacities. Contrast and comparisons with existing methods primarily relying on the distorted wave approximation are discussed to verify accuracy and resolve outstanding issues, particularly with reference to the opacity project (OP). Among the improvements incorporated are: (i) large-scale Breit–Pauli R -matrix calculations for complex atomic systems including fine structure, (ii) convergent close coupling wave function expansions for the ( e + ion) system to compute oscillator strengths and photoionization cross sections, (iii) open and closed shell iron ions of interest in astrophysics and experiments, (iv) a treatment for plasma broadening of autoionizing resonances as function of energy-temperature-density dependent cross sections, (v) a ‘top-up’ procedure to compare convergence with R -matrix calculations for highly excited levels, and (vi) spectroscopic identification of resonances and bound ( e + ion) levels. The present R -matrix monochromatic opacity spectra are fundamentally different from OP and lead to enhanced Rosseland and Planck mean opacities. An outline of the work reported in other papers in this series and those in progress is presented. Based on the present re-examination of the OP work, opacities of heavy elements might require revisions in high temperature-density plasma sources.

Pradhan, A. K. (ORCID:0000000187753643)↗
DOE OSTI2017

Introducing Human Mandible Identification [(hu)MANid]: A Free, Web‐Based GUI to Classify Human Mandibles

Abstract Statistical programs have revolutionized the way in which forensic anthropologists conduct casework by allowing practitioners to use computationally complex analytics at the click of a button. Importantly, the products of these statistical programs are reproducible and contain measures of error or uncertainty, thereby strengthening conclusions. This paper is an introduction to (hu) MAN id, a free, web‐based application that uses linear and mixture discriminant function analyses to classify human mandibles into one of many worldwide and/or periodic reference groups. The mechanics, development, and use of the application will be discussed. Further, the program was tested against other software to compare model performances and classifications. Total correct classifications among the test cases and programs were identical. Ten mandibles were tested using both statistical procedures. Mixture discriminant analysis improved classification by an average of 9.3% and correctly identified three more mandibles than LDA . Therefore, we believe (hu) MAN id will be an asset to the anthropological community.

Berg, Gregory E.↗
DOE OSTI2023

Improved Water Sound Synthesis using Coupled Bubbles

We introduce a practical framework for synthesizing bubble-based water sounds that captures the rich inter-bubble coupling effects responsible for low-frequency acoustic emissions from bubble clouds. We propose coupled-bubble oscillator models with regularized singularities, and techniques to reduce the computational cost of time stepping with dense, time-varying mass matrices. Airborne acoustic emissions are estimated using finite-difference time-domain (FDTD) methods. We propose a simple, analytical surface-acceleration model, and a sample-and-hold GPU wavesolver that is simple and faster than prior CPU wavesolvers. Sound synthesis results are demonstrated using bubbly flows from incompressible, two-phase simulations, as well as procedurally generated examples using single-phase FLIP fluid animations. Our results demonstrate sound simulations with hundreds of thousands of bubbles, and perceptually significant frequency transformations with fuller low-frequency content.

Computer Science↗
DOE OSTI2013

ATRC Neutron Detector Testing Quick Look Report

As part of the Advanced Test Reactor (ATR) National Scientific User Facility (NSUF) program, a joint Idaho State University (ISU) / French Alternative Energies and Atomic Energy Commission (CEA) / Idaho National Laboratory (INL) project was initiated in FY-10 to investigate the feasibility of using neutron sensors to provide online measurements of the neutron flux and fission reaction rate in the ATR Critical Facility (ATRC). A second objective was to provide initial neutron spectrum and flux distribution information for physics modeling and code validation using neutron activation based techniques in ATRC as well as ATR during depressurized operations. Detailed activation spectrometry measurements were made in the flux traps and in selected fuel elements, along with standard fission rate distribution measurements at selected core locations. These measurements provide additional calibration data for the real-time sensors of interest as well as provide benchmark neutronics data that will be useful for the ATR Life Extension Program (LEP) Computational Methods and V&V Upgrade project. As part of this effort, techniques developed by Prof. George Imel will be applied by Idaho State University (ISU) for assessing the performance of various flux detectors to develop detailed procedures for initial and follow-on calibrations of these sensors. In addition to comparing data obtained from each type of detector, calculations will be performed to assess the performance of and reduce uncertainties in flux detection sensors and compare data obtained from these sensors with existing integral methods employed at the ATRC. The neutron detectors required for this project were provided to team participants at no cost. Activation detectors (foils and wires) from an existing, well-characterized INL inventory were employed. Furthermore, as part of an on-going ATR NSUF international cooperation, the CEA sent INL three miniature fission chambers (one for detecting fast flux and two for detecting thermal flux) with associated electronics for assessment. In addition, Prof. Imel, ISU, has access to an inventory of Self-Powered Neutron Detectors (SPNDs) with a range of response times as well as Back-to-Back (BTB) fission chambers from prior research he conducted at the Transient REActor Test Facility (TREAT) facility and Neutron RADiography (NRAD) reactors. Finally, SPNDs from the National Atomic Energy Commission of Argentina (CNEA) were provided in connection with the INL effort to upgrade ATR computational methods and V&V protocols that are underway as part of the ATR LEP. Work during fiscal year 2010 (FY10) focussed on design and construction of Experiment Guide Tubes (EGTs) for positioning the flux detectors in the ATRC N-16 locations as well as obtaining ATRC staff concurrence for the detector evaluations. Initial evaluations with CEA researchers were also started in FY10 but were cut short due to reactor reliability issues. Reactor availability issues caused experimental work to be delayed during FY11/12. In FY13, work resumed; and evaluations were completed. The objective of this "Quick Look" report is to summarize experimental activities performed from April 4, 2013 through May 16, 2013.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2017

Development of a new IEC Standard on cybersecurity controls for I and C in Nuclear Power Plants - IEC 63096 - 158

Standards are promoting the enhancement of cybersecurity in Nuclear Power Plants (NPP). Standardizing processes and procedures are also crucial to achieve successful international collaboration. Many information security standards were developed in recent years; however, not many of them could be directly applied to NPPs. This paper provides an overview of the development of a new cybersecurity standard dealing with cybersecurity controls for nuclear power plants around the world. For I and C systems in NPPs, the new IEC 63096 standard targeted for issue in 2019, focuses specifically on the selection and application of cybersecurity controls from the included security controls catalogue. The role of selected and applied cybersecurity controls is to prevent, detect and react to digital attacks against computer-based I and C systems. This standard applies to the I and C of new nuclear power plants and to the I and C modernization in existing plants. It is being prepared and based on IEC 62645 , ISO/IEC 27000 series , IAEA , and country specific guidance in this expanding the technical and the security focus area. The Standard is intended to be used by designers and operators of NPPs (utilities), systems evaluators, vendors and subcontractors, and by licensors. While the development of international standards is essential it is also a lengthy process, taking multiple years. Especially with regard to cybersecurity, all involved stakeholders have to collaborate. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2014

Configuration interaction wave functions: A seniority number approach

This work deals with the configuration interaction method when an N-electron Hamiltonian is projected on Slater determinants which are classified according to their seniority number values. We study the spin features of the wave functions and the size of the matrices required to formulate states of any spin symmetry within this treatment. Correlation energies associated with the wave functions arising from the seniority-based configuration interaction procedure are determined for three types of molecular orbital basis: canonical molecular orbitals, natural orbitals, and the orbitals resulting from minimizing the expectation value of the N-electron seniority number operator. The performance of these bases is analyzed by means of numerical results obtained from selected N-electron systems of several spin symmetries. The comparison of the results highlights the efficiency of the molecular orbital basis which minimizes the mean value of the seniority number for a state, yielding energy values closer to those provided by the full configuration interaction procedure.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

New machine learning techniques for simulation-based inference: InferoStatic nets, kernel score estimation, and kernel likelihood ratio estimation

We propose an intuitive, machine-learning approach to multiparameter inference, dubbed the InferoStatic Networks (ISN) method, to model the score and likelihood ratio estimators in cases when the probability density can be sampled but not computed directly. The ISN uses a backend neural network that models a scalar function called the inferostatic potential \varphi φ . In addition, we introduce new strategies, respectively called Kernel Score Estimation (KSE) and Kernel Likelihood Ratio Estimation (KLRE), to learn the score and the likelihood ratio functions from simulated data. We illustrate the new techniques with some toy examples and compare to existing approaches in the literature. We mention en passant some new loss functions that optimally incorporate latent information from simulations into the training procedure.

Kong, Kyoungchul↗
DOE OSTI2020

An Alternative Casting Technique to Improve the Creep Resistance of Cast INCONEL Alloy 740H

The increasing performance requirements of power plant designs, such as advanced-ultra supercritical (A-USC), require the use of Ni-based superalloys to replace high-strength, ferritic-martensitic steels for components subjected to temperatures above 898 K (625 °C) and for austenitic stainless steels components at temperatures above 973 K (700 °C). To date, commercial Ni-based superalloy INCONEL 740H has been shown to be appropriate for use in A-USC power plants as boiler components in a wrought product. However, large complex components in boilers as well as other casings in the turbine and valve chest require castings of a thick-wall nature. Using the alloy in its cast form would be significantly valuable in terms of range of component size, geometry and complexity. Previous investigations revealed short creep lives from cast INCONEL alloy 740H. Here in this investigation, an alternative casting route that utilized a melt procedure resulting in a fine-grain casting, and in conjunction with a computationally optimized homogenization heat treatment, not only controlled the grain size and grain boundary structure but minimized chemistry variability and segregation. A primarily equiaxed and homogenous grain size distribution was obtained from this approach with better repartition of M 23 C 6 carbides along the grain boundaries. Furthermore, better than 38 pct increase was obtained for this material in comparison to the creep life obtained from the best performing conventionally cast material. More importantly, the fine-grain homogenized (FGH) casting route resulted in the Larson–Miller plot for this material that coincided with that of wrought alloy 740. At low creep stresses (with a test still in progress), the FGH casting is resulting in higher values of the LMP than the wrought alloy.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Entity Resolution at Large Scale: Benchmarking and Algorithmics

We seek scalable benchmarks for entity resolution problems. Solutions to these problems range from trivial approaches such as string sorting to sophisticated methods such as statistical relational learning. The theoretical and practical complexity of these approaches varies widely, so one of the primary purposes of a benchmark will be to quantify the trade-off between solution quality and runtime. We are motivated by the ubiquitous nature of entity resolution as a fundamental problem faced by any organization that ingests large amounts of noisy text data. A benchmark is typically a rigid specification that provides an objective measure usable for ranking implementations of an algorithm. For example the Top500 and HPCG500 bench- marks rank supercomputers based on their performance of dense and sparse linear algebra problems (respectively). These two benchmarks require participants to report FLOPS counts attainable on various machines. Our purpose is slightly different. Whereas the supercomputing benchmarks mentioned above hold algorithms constant and aim to rank machines, we are primarily interested in ranking algorithms. As mentioned above, entity resolution problems can be approached in completely different ways. We believe that users of our benchmarks must decide what sort of procedure to run before comparing implementations and architectures. Eventually, we also wish to provide a mechanism for ranking machines while holding algorithmic approach constant . Our primary contributions are parallel algorithms for computing solution quality mea- sures per entity. We find in some real datasets that many entities are quite easy to resolve while others are difficult, with a heavy skew toward the former case. Therefore, measures such as global confusion matrices, F measures, etc. do not meet our benchmarking needs. We design methods for computing solution quality at the granularity of a single entity in order to know when proposed solutions do well in difficult situations (perhaps justifying extra computational), or struggling in easy situations. We report on progress toward a viable benchmark for comparing entity resolution algo- rithms. Our work is incomplete, but we have designed and prototyped several algorithms to help evalute the solution quality of competing approaches to these problems. We envision a benchmark in which the objective measure is a ratio of solution quality to runtime.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

A Hybrid Gradient Method to Designing Bayesian Experiments for Implicit Models

Bayesian experimental design (BED) aims at designing an experiment to maximize the information gathering from the collected data. The optimal design is usually achieved by maximizing the mutual information (MI) between the data and the model parameters. When the analytical expression of the MI is unavailable, e.g.,having implicit models with intractable data distributions, a neural network-based lower bound of the MI was recently proposed and a gradient ascent method was used to maximize the lower bound [1]. However, the approach in [1] requires a pathwise sampling path to compute the gradient of the MI lower bound with respect to the design variables, and such a pathwise sampling path is usually inaccessible for implicit models. In this work, we propose a hybrid gradient approach that leverages recent advances in variational MI estimator and evolution strategies (ES)combined with black-box stochastic gradient ascent (SGA) to maximize the MI lower bound. This allows the design process to be achieved through a unified scalable procedure for implicit models without sampling path gradients. Several experiments demonstrate that our approach significantly improves the scalability of BED for implicit models in high-dimensional design space.

Zhang, Jiaxin↗
DOE OSTI2022

A correction procedure for self-induced velocity of a finite-sized particle in two-way coupled Euler–Lagrange simulations

The importance of incorporating a correction to undo the self-induced perturbation velocity of a particle, when its size becomes comparable to the Eulerian grid, in a two-way coupled Euler–Lagrange (EL) simulation is now well appreciated. The present work improves upon the prior correction procedures in a few important ways. First, the past correction procedures have been scalar-based with the assumption that the quasi-steady force is the source of self-induced velocity perturbation. Here we generalize to a vector correction procedure and thereby the directions of feedback force and relative velocity can be different. This allows the correction procedure to be used even in the presence of added-mass, history, and lift forces. Second, the effect of a nearby wall has been systematically included in the correction procedure. The correction procedure depends on fundamental Oseen solutions of streamwise and transverse regularized feedback forces. We present a Fourier transform-based analytical approach to obtaining these regularized Oseen solutions. We also present a step-by-step numerical procedure for obtaining the Oseen solutions in any EL code. With the analytical or numerical Oseen functions, the correction procedure can be easily implemented in any EL code. Iterations are required in solving the implicit correction equations and it is demonstrated that the correction procedure converges rapidly within three or four iterations. In conclusion, a simple empirical approach is also presented to account for unsteady effects in the correction procedure.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

A need to reduce premature CV mortality in the developing world: How could appropriate use of non-invasive imaging help?

We discuss premature deaths due to coronary heart disease (CHD) in developing countries and the importance of a comprehensive approach, involving clinical judgement, prevention, appropriate use of technology to diagnose and guide CHD treatment. Healthcare policies and levels of knowledge vary tremendously resulting heterogeneous utilization of diagnostic strategies and treatments worldwide. Many countries with high mortality have low utilization of non-invasive cardiac imaging. Appropriate use coupled with guideline-based management could help to improve care in the developing world and potentially result in better life expectancy already experienced by most high-income countries. In a scenario of increasing costs, a rational utilization of resources is imperative for all nations. A stepwise approach to suspected CHD is necessary, starting from good judgement, adding tests only as needed, preferably filtering patients who might benefit from advanced imaging. In stable patients, non-invasive tests should be used as filters to invasive procedure, preventing stable patients from undergoing revascularizations of questionable benefit. In this article, we review the relative role of exercise testing, myocardial perfusion imaging, and coronary computed tomography angiography to evaluate CHD and how these can be utilized as ways to help guide management that could impact premature mortality in developing nations.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2023

A Formulation of the Many-Body Expansion (MBE) for Periodic Systems: Application to Several Ice Phases

A new formulation of the many-body expansion (MBE) for periodic systems, based on their inherent translational symmetry, is introduced and applied to 7 ice polymorphs. This new formulation is built via a hierarchical procedure connecting gas phase unit cells over finite supercells to infinite solids. For finite supercells, it is demonstrated that this method successfully recovers the energetics while reducing the scaling of the calculation of the many-body terms by a factor of ~N, where N is the system size. Furthermore, the proposed framework delineates a straightforward way to obtain properties of macroscopic systems in the limit of an infinite cell. For periodic systems, the success of this approach is demonstrated by showing that the lattice energies computed (up to the 4-th order in the MBE) reproduce the lattice energies obtained using periodic boundary conditions with an Ewald summation for 7 polymorphs of ice (Ih, II, VIII, IX, XIII, XIV, XV). This development makes it possible to quantify, for the first time, the many-body contributions to the lattice energy of various ice polymorphs. The many-body (three-body and higher) interactions were found to vary significantly among the 7 ice phases, amounting between 7-24% of the total lattice energies. So, this development opens the door for obtaining insights into solid-state properties, while leveraging the computational benefits of the MBE.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Multi-fidelity machine-learning with uncertainty quantification and Bayesian optimization for materials design: Application to ternary random alloys

We present a scale-bridging approach based on a multi-fidelity (MF) machine-learning (ML) framework leveraging Gaussian processes (GP) to fuse atomistic computational model predictions across multiple levels of fidelity. Through the posterior variance of the MFGP, our framework naturally enables uncertainty quantification, providing estimates of confidence in the predictions. We used density functional theory as high-fidelity prediction, while a ML interatomic potential is used as low-fidelity prediction. Practical materials’ design efficiency is demonstrated by reproducing the ternary composition dependence of a quantity of interest (bulk modulus) across the full aluminum–niobium–titanium ternary random alloy composition space. The MFGP is then coupled to a Bayesian optimization procedure, and the computational efficiency of this approach is demonstrated by performing an on-the-fly search for the global optimum of bulk modulus in the ternary composition space. The framework presented in this manuscript is the first application of MFGP to atomistic materials simulations fusing predictions between density functional theory and classical interatomic potential calculations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Solving 3d gravity with Virasoro TQFT

We propose a precise reformulation of 3d quantum gravity with negative cosmological constant in terms of a topological quantum field theory based on the quantization of the Teichmüller space of Riemann surfaces that we refer to as “Virasoro TQFT”. This TQFT is similar, but importantly not equivalent, to SL(2, \mathbb{R} ℝ ) Chern-Simons theory. This sharpens the folklore that 3d gravity is related to SL(2, \mathbb{R} ℝ ) Chern-Simons theory into a precise correspondence, and resolves some well-known issues with this lore at the quantum level. Our proposal is computationally very useful and provides a powerful tool for the further study of 3d gravity. In particular, we explain how together with standard TQFT surgery techniques this leads to a fully algorithmic procedure for the computation of the gravity partition function on a fixed topology exactly in the central charge. Mathematically, the relation leads to many nontrivial conjectures for hyperbolic 3-manifolds, Virasoro conformal blocks and crossing kernels.

Collier, Scott↗