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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 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Transient dynamics, damping, and mode coupling of nonlinear systems with internal resonances

The study of both linear and nonlinear structural vibrations routinely circles the concise yet complex problem of choosing a set of coordinates which yield simple equations of motion. In both experimental and mathematical methods, that choice is a difficult one because of measurement, computational, and interpretation difficulties. Often times, researchers choose to solve their problems in terms of linear, undamped mode shapes because they are easy to obtain; however, this is known to give rise to complicated phenomena such as mode coupling and internal resonance. This work considers the nature of mode coupling and internal resonance in systems containing non-proportional damping, linear detuning, and cubic nonlinearities through the method of multiple scales as well as instantaneous measures of effective damping. The energy decay observed in the structural modes is well approximated by the slow-flow equations in terms of the modal amplitudes, and it is shown how mode coupling enhances the damping observed in the system. Moreover, in the presence of a 3:1 internal resonance between two modes, the nonlinearities not only enhance the dissipation, but can allow for the exchange and transfer of energy between the resonant modes. However, this exchange depends on the resonant phase between the modes and is proportional to the energy in the lowest mode. The results of the analysis tie together interpretations used by both experimentalists and theoreticians to study such systems and provide a more concrete way to interpret these phenomena.

42 ENGINEERING↗
DOE OSTI2022

RFB Side Effects - Shunt Currents

The various models related to fluid flow, electrochemistry and shunt current, and their interactions are reviewed, and gaps identified in the development of flow battery holistic models. In a flow battery stack, the cells are electrically connected through the manifolds via the electrolyte. This results in shunt current through the electrolyte, which is a source of loss in the battery stack. This issue is examined in depth with a mathematical method of calculating shunt current distribution, the associated losses, and strategies to mitigate shunt current losses, along with the trade-offs.

Crawford, Aladsair J.↗
DOE OSTI2018

Design of machine learning models with domain experts for automated sensor selection for energy fault detection

Data-driven techniques that extract insights from sensor data reduce the cost of improving system energy performance through fault detection and system health monitoring. To lower cost barriers to widespread deployment, a methodology is proposed that takes advantage of existing sensor data, encodes expert knowledge about the application system to create ‘virtual sensors’ and applies statistical and mathematical methods to reduce the time required for manual configurations. The approach combines sensor data points with encoded expert knowledge that is generic to the application system but independent of a particular deployment, thereby reducing the need to tailor to individual deployments. Additionally, this paper not only presents a method that detects faults from measured energy data, but also (1) describes an engagement method with experts in the energy system domain to identify data, (2) integrates domain knowledge with the data, (3) automatically selects from among the large pool of potential input data, and (4) uses machine learning to automatically build a data-driven fault detection model. Demonstration on a commercial building chiller plant shows that only a small number of virtual sensors is necessary for fault detection with high accuracy rates. This corresponds to the use of only five out of 52 original sensor data points features. With as few as four features, classification F1 scores exceed 90% on the training set and 80% on the testing set. The results are implementable and realizable using off-the-shelf tools. The goal is to design with domain experts an energy monitoring system that can be configured once and then widely deployed with little additional cost or effort.

47 OTHER INSTRUMENTATION↗
DOE OSTI2022

Quadratic Unitary Coupled-Cluster Singles and Doubles Scheme: Efficient Implementation, Benchmark Study, and Formulation of an Extended Version

An efficient implementation of the quadratic unitary coupled-cluster singles and doubles (qUCCSD) scheme for calculations of electronic ground and excited states using an unrestricted molecular spin–orbital formulation and an efficient tensor contraction library is reported. The accuracy of the qUCCSD scheme and the efficiency of the present implementation are demonstrated using extensive benchmark calculations of excitation energies and an application to S o → S 1 vertical excitation energies for cis- and trans-4a,4b-dihydrotriphenylene. The qUCCSD scheme has been shown to provide improved excitation energies compared with the UCC3 scheme formulated based on perturbation theory. Here, a UCC truncation scheme that can provide excitation energies correct through the fourth order is also presented to further improve the accuracy of the qUCCSD scheme.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2016

Diffusion processes in tumors: A nuclear medicine approach

The number of counts used in nuclear medicine imaging techniques, only provides physical information about the desintegration of the nucleus present in the the radiotracer molecules that were uptaken in a particular anatomical region, but that information is not a real metabolic information. For this reason a mathematical method was used to find a correlation between number of counts and {sup 18}F-FDG mass concentration. This correlation allows a better interpretation of the results obtained in the study of diffusive processes in an agar phantom, and based on it, an image from the PETCETIX DICOM sample image set from OsiriX-viewer software was processed. PET-CT gradient magnitude and Laplacian images could show direct information on diffusive processes for radiopharmaceuticals that enter into the cells by simple diffusion. In the case of the radiopharmaceutical {sup 18}F-FDG is necessary to include pharmacokinetic models, to make a correct interpretation of the gradient magnitude and Laplacian of counts images.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2022

An analytical approach to evaluating magnetic-field closure and topological changes in FRC devices

Here, we describe mathematical methods based on optimizing a modified non-linear flux function (MFF) to evaluate whether odd-parity perturbations affect the local closure of magnetic field lines in field-reversed configurations. Using the MFF methodology, quantitative formulas are derived that provide the shift of the field minimum and the threshold for field-line opening, a discontinuous change in field topology.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Physically interpretable approximations of many-body spectral functions

The rational function approximation provides a natural and interpretable representation of response functions such as the many-body spectral functions. We apply the vector fitting (VFIT) algorithm to fit a variety of spectral functions calculated from the Holstein model of electron-phonon interactions. We show that the resulting rational functions are highly efficient in their fitting of sharp features in the spectral functions, and could provide a means to infer physically relevant information from a spectral data set. The position of the peaks in the approximated spectral function are determined by the location of poles in the complex plane. Additionally, we developed a variant of VFIT that incorporates regularization to improve the quality of fits. With this procedure, we demonstrate it is possible to achieve accurate spectral function fits that vary smoothly as a function of physical conditions.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2016

MO-AB-BRA-02: Modeling Nanoparticle-Eluting Spacer Degradation During Brachytherapy Application with in Situ Dose-Painting

Purpose: Brachytherapy application with in situ dose-painting using gold nanoparticles (GNP) released from GNP-loaded brachytherapy spacers has been proposed as an innovative approach to increase therapeutic efficacy during brachytherapy. This work investigates the dosimetric impact of slow versus burst release of GNP from next generation biodegradable spacers. Methods: Mathematical models were developed based on experimental data to study the release of GNP from a spacer designed with FDA approved poly(lactic-co-glycolic acid) (PLGA) polymer. The diffusion controlled released process and PLGA polymer degradation kinetics was incorporated in the calculations for the first time. An in vivo determined diffusion coefficient was used for determining the concentration profiles and corresponding dose enhancement based on initial GNP-loading concentrations of 7 mg/g. Results: The results showed that there is significant delay before the concentration profile of GNP diffusion in the tumor is similar to that when burst release is assumed as in previous studies. For example, in the case of burst release after spacer administration, it took up to 25 days for all the GNP to be released from the spacer using diffusion controlled release process only. However, it took up to 45 days when a combined model for both diffusion and polymer degradation processes was used. Based on the tumor concentration profiles, a significant dose enhancement factor (DEF >20%), could be attained at a tumor distances of 5 mm from a spacer loaded with 10 nm GNP sizes. Conclusion: The results highlight the need to take the slow release of GNP from spacers and factors such as biodegradation of polymers into account in research development of GNP-eluting spacers for brachytherapy applications with in-situ dose-painting using gold nanoparticles. The findings suggest that I-125 may be the more appropriate for such applications given the relatively longer half-live compared to other radioisotopes like Pd-103 and Cs-131.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Balrog

SAND2022-12602 O Balrog uses mathematical methods to calculate spectral line shapes in high-energy-density plasmas. Line shapes are a result of atomic perturbations by their surrounding plasmas, and this model captures much of the physics and generates model spectrum that can be used in data analysis and as an input for other models. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Gomez, Thomas↗
DOE OSTI2023

Experimental Observations of the Topology of Convolutional Neural Network Activations

Topological data analysis (TDA) is a branch of computational mathematics, bridging algebraic topology and data science, that provides compact, noise-robust representations of complex structures. Deep neural networks (DNNs) learn millions of parameters associated with a series of transformations defined by the model architecture resulting in high-dimensional, difficult to interpret internal representations of input data. As DNNs become more ubiquitous across multiple sectors of our society, there is increasing recognition that mathematical methods are needed to aid analysts, researchers, and practitioners in understanding and interpreting how these models' internal representations relate to the final classification. In this paper we apply cutting edge techniques from TDA with the goal of gaining insight towards interpretability of convolutional neural networks used for image classification. We use two common TDA approaches to explore several methods for modeling hidden layer activations as high-dimensional point clouds, and provide experimental evidence that these point clouds capture valuable structural information about the model's process. First, we demonstrate that a distance metric based on persistent homology can be used to quantify meaningful differences between layers and discuss these distances in the broader context of existing representational similarity metrics for neural network interpretability. Second, we show that a mapper graph can provide semantic insight as to how these models organize hierarchical class knowledge at each layer. These observations demonstrate that TDA is a useful tool to help deep learning practitioners unlock the hidden structures of their models.

topological data analysis, deep learning↗
DOE OSTI2016

Lifetime Extension Report: Progress on the SAVY-4000 Lifetime Extension Program

The 3-year accelerated aging study of the SAVY-4000 O-ring shows very little evidence of significant degradation to samples subjected to aggressive elevated temperature and radiation conditions. Whole container thermal aging studies followed by helium leakage testing and compression set measurements were used to establish an estimate for a failure criterion for O-ring compression set of ≥65 %. The whole container aging studies further show that the air flow and efficiency functions of the filter do not degrade significantly after thermal aging. However, the degradation of the water-resistant function leads to water penetration failure after four months at 210°C, but does not cause failure after 10 months at 120°C (130°C is the maximum operating temperature for the PTFE membrane). The thermal aging data for O-ring compression set do not meet the assumptions of standard time-temperature superposition analysis for accelerated aging studies. Instead, the data suggest that multiple degradation mechanisms are operative, with a reversible mechanism operative at low aging temperatures and an irreversible mechanism dominating at high aging temperatures. To distinguish between these mechanisms, we have measured compression set after allowing the sample to physically relax, thereby minimizing the effect of the reversible mechanism. The resulting data were analyzed using two distinct mathematical methods to obtain a lifetime estimate based on chemical degradation alone. Both methods support a lifetime estimate of greater than 150 years at 80°C. Although the role of the reversible mechanism is not fully understood, it is clear that the contribution to the total compression set is small in comparison to that due to the chemical degradation mechanism. To better understand the chemical degradation mechanism, thermally aged O-ring samples have been characterized by Fourier Transform Infrared (FTIR), Electron Paramagnetic Resonance (EPR), Gel Permeation Chromatography (GPC), and Differential Scanning Calorimetry (DSC). These experiments detect no significant O-ring degradation below 80°C. Furthermore, durometer measurements indicate that there is no significant change in O-ring hardness at all aging conditions examined. Therefore, our current conservative lifetime estimate for the O-ring and the filter is 10 years at 80°C. In FY17, we will continue to probe the chemical degradation mechanism using oxygen consumption measurements under accelerated aging conditions to reveal temperatures at which oxidation occurs, along with any differences in oxidation rate at the low vs. high aging temperatures. We will also refine the failure criteria and finalize the radiation/thermal synergistic studies to determine a final design lifetime.

42 ENGINEERING↗
DOE OSTI2019

DiaMonD: An Integrated Multifaceted Approach to Mathematics at the Interfaces of Data, Models, and Decisions

DiaMonD is a multi-institutional DOE MMICC effort that aims to address the challenges of end-to-end, data-to-decisions modeling and simulation for complex computational science and engineering problems in a unified, systematic, and integrated fashion. Institutions involved are Colorado State, Florida State, Los Alamos, MIT, Oak Ridge, Stanford, and UT-Austin. The goals of DiaMonD are (1) to develop advanced mathematical methods and analysis for multimodel, multiphysics, multiscale model problems driven by frontier DOE applications, including those in subsurface energy and environmental flows, materials for energy storage and conversion, and ice sheet dynamics; (2) to create theory and algorithms for integrated inversion, optimization, and uncertainty quantification for these complex problems; and (3) to disseminate the philosophy of an integrated end-to-end, data-to-decisions approach to modeling and simulation of complex problems to the broader applied math and computational science communities through workshops and other outreach.

42 ENGINEERING↗
DOE OSTI2016

Comparative Architecture Analysis: Using Laminar Structure to Unify Multiple Grid Architectures

A great many architectures for various aspects of electric grids have been proposed over recent years and new ones continue to be suggested. Generally speaking, there is no means except ad hoc analysis by which one can reduce these architectures to some common basis, or extract common elements. This leads to confusion in choosing an architecture for implementation, as well as making it difficult to identify core product or platform opportunities with sufficient potential markets to encourage vendors to provide or develop them. The discipline of Grid Architecture as defined for the US Department of Energy (DOE) in 2014 has multiple purposes. Among them are two that are relevant here: Providing rigorous bases for architectural structures and Identifying common aspects of apparently divergent architectural structures. For the first of these, mathematical methods are applied where possible to provide the rigorous basis for structure. For the second, mapping of architectural structures to a canonical structure puts apparently disparate architectures onto a common basis. In the best case, these two methods coincide. In this paper, Laminar Coordination structure serves as the rigorously defined common basis for analysis of several real and proposed grid architectures.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

Advanced Fuel Cycle Cost Basis Report: Supporting Documents 3 Cost Correlations

This chapter provides an overview of the drivers for developing correlation coefficients, status on efforts to develop partial correlation coefficients, and recommended next steps. Mathematical methods for developing and using correlation coefficients were previously documented by the FCO EWG in Chapters 6 and 7 of [Ganda 2014].

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

Applications of Fuzzy Logic for Tritium Sensing Technology

Fuzzy Logic is a mathematical method that can represent human-like decisions by analyzing vagueness. The project is a practical approach for evaluating sensors using a fuzzy group best-worst method. Results What is the best sensor? The fuzzy logic methods give an answer to that through a selection system. The relationship between the inputs and the outputs gives consumers an understanding of how the best sensor was found through a scoring of each quality/criteria and their corresponding sub-criteria through expert opinion.

Holman, Allyson↗
DOE OSTI2022

The Local Topological Free Energy of the SARS-CoV-2 Spike Protein

The novel coronavirus SARS-CoV-2 infects human cells using a mechanism that involves binding and structural rearrangement of its Spike protein. Understanding protein rearrangement and identifying specific amino acids where mutations affect protein rearrangement has attracted much attention for drug development. In this manuscript, we use a mathematical method to characterize the local topology/geometry of the SARS-CoV-2 Spike protein backbone. Our results show that local conformational changes in the FP, HR1, and CH domains are associated with global conformational changes in the RBD domain. The SARS-CoV-2 variants analyzed in this manuscript (alpha, beta, gamma, delta Mink, G614, N501) show differences in the local conformations of the FP, HR1, and CH domains as well. Finally, most mutations of concern are either in or in the vicinity of high local topological free energy conformations, suggesting that high local topological free energy conformations could be targets for mutations with significant impact of protein function. Namely, the residues 484, 570, 614, 796, and 969, which are present in variants of concern and are targeted as important in protein function, are predicted as such from our model.

60 APPLIED LIFE SCIENCES↗