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Results for “matrix power”

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 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Structure–property relations in graphitic pebbles for nuclear applications

This work presents an analytical approach for holistically characterizing graphitic matrix pebbles for nuclear applications whereby the macrostructure, microstructure, and thermophysical properties of pebbles are determined. A systematic sectioning method was applied to several pebbles to describe the regional properties of the samples. Intact matrix-only spheres and sections of spheres fabricated by Kairos Power were characterized via optical imaging, x-ray computed tomography, x-ray diffraction, and ellipsometry to determine 2D and 3D macrostructure and anisotropy. The thermophysical properties of these materials were determined via measurements of density, specific heat, thermal expansion, and thermal diffusivity. The results of this study indicate that the pebble fabrication methods and their resultant effect on microstructure have a nontrivial effect on thermophysical properties, confirming the importance of robust characterization of these components. A discussion of the characterization approach and its applicability to nuclear fuel development activities is also included.

42 ENGINEERING↗
DOE OSTI2023

Experimental Assessment of Mammalian Lipidome Complexity Using Multimodal 21 T FTICR Mass Spectrometry Imaging

Herein, we assess the complementarity and complexity of data that can be detected within mammalian lipidome mass spectrometry imaging (MSI) via matrix-assisted laser desorption ionization (MALDI) and nanospray desorption electrospray ionization (nano-DESI). We do so by employing 21 T Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS) with absorption mode FT processing in both cases, allowing unmatched mass resolving power per unit time (≥613k at m/z 760, 1.536 s transients). While our results demonstrated that molecular coverage and dynamic range capabilities were greater in MALDI analysis, nano-DESI provided superior mass error, and all annotations for both modes had sub-ppm error. Taken together, these experiments highlight the coverage of 1676 lipids and serve as a functional guide for expected lipidome complexity within nano-DESI-MSI and MALDI-MSI. To further assess the lipidome complexity, mass splits (i.e., the difference in mass between neighboring peaks) within single pixels were collated across all pixels from each respective MSI experiment. The spatial localization of these mass splits was powerful in informing whether the observed mass splits were biological or artificial (e.g., matrix related). Mass splits down to 2.4 mDa were observed (i.e., sodium adduct ambiguity) in each experiment, and both modalities highlighted comparable degrees of lipidome complexity. Further, we highlight the persistence of certain mass splits (e.g., 8.9 mDa; double bond ambiguity) independent of ionization biases. Here, we also evaluate the need for ultrahigh mass resolving power for mass splits ≤4.6 mDa (potassium adduct ambiguity) at m/z > 1000, which may only be resolved by advanced FTICR-MS instrumentation.

21T-FTICR-MS↗
DOE OSTI2026

Adaptive Stiffness Power Take-Off System for a Hydraulic Hose-Pump Point Absorber Wave Energy Converter

Two crucial challenges faced in the design of ocean wave energy converters (WECs) are maintaining high capacity factors and remaining robust in everchanging, harsh ocean environments. This study introduces a novel mechanism for achieving reactive WEC control with a soft hydraulic power take-off, thereby addressing both challenges. The device of interest involves a hydraulic pump, constructed from a fluidic flexible matrix composite (F2MC), which is cyclically stretched by driving waves and pressurizes working fluid through a turbine-generator. This class of fiber-reinforced stretch hoses is established for ocean use as robust moorings and shock absorbers. The dynamic properties of the F2MC pump depend on internal pressure, which can be controlled by a continuously variable transmission between the turbine and generator, allowing the system to be adapted for better performance over a wide range of wave conditions. This work presents a dynamic model for operation and adaptive behavior of this power take-off system, experimentally validates components of the model, and performs dynamic simulations of the system that show increases in power production and capacity factor compared to non-adaptive operation for a variety of driving wave conditions. This work develops the basis for future large-scale experimental testing and controller design of this system.

Wave energy conversion, fluidic flexible matrix co↗
DOE OSTI2021

Unraveling Cu Chemical Signature in CdTe by Spectral Fluorescence Mapping

X-ray absorption spectroscopy (XAS) has been shown to be a powerful tool to unravel the chemical environment of a given atom within a matrix. When used in correlative X-ray microscopy approaches, XAS allows one to probe with nanoscale precision regions of particular interest in an absorber. Herein, we use X-ray absorption near edge structure (XANES) to evaluate the chemical environment of Cu atoms within a CdTe solar cell. The reconstruction of XANES spectra from XRF maps have unfolded 2D maps of Cu chemical structures. In this work, we found that most Cu atoms exist in Cu 2 Te and Cu 1.4 Te phase. Moreover, we found traces of CuTe, Cu 2 O, CuO, Cu 2 S, CuS, and metallic Cu phase. Investigating Cu chemical structures at different performing areas, we found no observable correlation between Cu chemical structures and electrical performance. This approach allows tracking of Cu chemical structures along with electrical performance and elemental distribution simultaneously, with high spatial resolution in a statistically practical way.

CdTe↗
DOE OSTI2025

Window convolution of the galaxy clustering bispectrum

In galaxy survey analysis, the observed clustering statistics do not directly match theoretical predictions but rather have been processed by a window function that arises from the survey geometry including the sky footprint, redshift-dependent background number density and systematic weights. While window convolution of the power spectrum is well studied, for the bispectrum with a larger number of degrees of freedom, it poses a significant numerical and computational challenge. In this work, we consider the effect of the survey window in the tripolar spherical harmonic decomposition of the bispectrum and lay down a formal procedure for their convolution via a series expansion of configuration-space three-point correlation functions, which was first proposed by Sugiyama et al. (2019). We then provide a linear algebra formulation of the full window convolution, where an unwindowed bispectrum model vector can be directly premultiplied by a window matrix specific to each survey geometry. To validate the pipeline, we focus on the Dark Energy Spectroscopic Instrument (DESI) Data Release 1 (DR1) luminous red galaxy (LRG) sample in the South Galactic Cap (SGC) in the redshift bin 0.4 ≤ z ≤ 0.6. We first perform convergence checks on the measurement of the window function from discrete random catalogues, and then investigate the convergence of the window convolution series expansion truncated at a finite of number of terms as well as the performance of the window matrix. This work highlights the differences in window convolution between the power spectrum and bispectrum, and provides a streamlined pipeline for the latter for current surveys such as DESI and the Euclid mission.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

On the connection between perturbation theory and new semiclassical expansion in quantum mechanics

Here, it is shown that for the one-dimensional anharmonic oscillator with potential V(x) = ax 2 + bgx 3 + ... = $\frac{1}{g^2}$ $\hat{V}$ (gx), as well as for the radial oscillator V(r) = $\frac{1}{g^2}$ $\hat{V}$ (gr) and for the perturbed Coulomb problem V(r) = $\frac{a}{r}$ + βgr + ... = g $\tilde{V}$ (gr), the Perturbation Theory in powers of the coupling constant g (weak coupling regime) and the semiclassical expansion in powers of $\hbar$ 1/2 for the energies coincide. This is related to the fact that the dynamics developed in two spaces: x (r)-space and gx (gr)-space, lead to the same energy spectra. The equations which govern dynamics in these two spaces, the Riccati-Bloch equation and the Generalized Bloch equation, respectively, are presented. It is shown that the perturbation theory for the logarithmic derivative of the wavefunction in - space leads to (true) semiclassical expansion in powers of $\hbar$ 1/2 ; for the one-dimensional case this corresponds to the flucton calculus for the density matrix in the path integral formalism in Euclidean (imaginary) time proposed by one of the authors. Matching the perturbation theory in powers of g and the semiclassical expansion in powers of $\hbar$ 1/2 for the wavefunction leads to a highly accurate local approximation in the entire coordinate space, its expectation value for the Hamiltonian provides a prescription for the summation of the perturbative (trans)-series.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2020

Electronic structure with direct diagonalization on a D-wave quantum annealer

Quantum chemistry is regarded to be one of the first disciplines that will be revolutionized by quantum computing. Although universal quantum computers of practical scale may be years away, various approaches are currently being pursued to solve quantum chemistry problems on near-term gate-based quantum computers and quantum annealers by developing the appropriate algorithm and software base. This work implements the general Quantum Annealer Eigensolver (QAE) algorithm to solve the molecular electronic Hamiltonian eigenvalue-eigenvector problem on a D-Wave 2000Q quantum annealer. The approach is based on the matrix formulation, efficiently uses qubit resources based on a power-of-two encoding scheme and is hardware-dominant relying on only one classically optimized parameter. We demonstrate the use of D-Wave hardware for obtaining ground and excited electronic states across a variety of small molecular systems. The approach can be adapted for use by a vast majority of electronic structure methods currently implemented in conventional quantum-chemical packages. The results of this work will encourage further development of software such as qbsolv which has promising applications in emerging quantum information processing hardware and has expectation to address large and complex optimization problems intractable for classical computers.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

ZMPY3D: accelerating protein structure volume analysis through vectorized 3D Zernike moments and Python-based GPU integration

Abstract Motivation Volumetric 3D object analyses are being applied in research fields such as structural bioinformatics, biophysics, and structural biology, with potential integration of artificial intelligence/machine learning (AI/ML) techniques. One such method, 3D Zernike moments, has proven valuable in analyzing protein structures (e.g., protein fold classification, protein–protein interaction analysis, and molecular dynamics simulations). Their compactness and efficiency make them amenable to large-scale analyses. Established methods for deriving 3D Zernike moments, however, can be inefficient, particularly when higher order terms are required, hindering broader applications. As the volume of experimental and computationally-predicted protein structure information continues to increase, structural biology has become a “big data” science requiring more efficient analysis tools. Results This application note presents a Python-based software package, ZMPY3D, to accelerate computation of 3D Zernike moments by vectorizing the mathematical formulae and using graphical processing units (GPUs). The package offers popular GPU-supported libraries such as CuPy and TensorFlow together with NumPy implementations, aiming to improve computational efficiency, adaptability, and flexibility in future algorithm development. The ZMPY3D package can be installed via PyPI, and the source code is available from GitHub. Volumetric-based protein 3D structural similarity scores and transform matrix of superposition functionalities have both been implemented, creating a powerful computational tool that will allow the research community to amalgamate 3D Zernike moments with existing AI/ML tools, to advance research and education in protein structure bioinformatics. Availability and implementation ZMPY3D, implemented in Python, is available on GitHub (https://github.com/tawssie/ZMPY3D) and PyPI, released under the GPL License.

Lai, Jhih-Siang (ORCID:0000000156775890)↗
DOE OSTI2021

Mitigating baryonic effects with a theoretical error covariance

ABSTRACT One of the primary sources of uncertainties in modelling the cosmic-shear power spectrum on small scales is the effect of baryonic physics. Accurate cosmology for stage-IV surveys requires knowledge of the matter power spectrum deep in the non-linear regime at the per cent level. Therefore, it is important to develop reliable mitigation techniques to take into account baryonic uncertainties if information from small scales is to be considered in the cosmological analysis. In this work, we develop a new mitigation method for dealing with baryonic physics for the case of the shear angular power spectrum. The method is based on an augmented covariance matrix that incorporates baryonic uncertainties informed by hydrodynamical simulations. We use the results from 13 hydrodynamical simulations and the residual errors arising from a fit to a ΛCDM model using the extended halo model code HMCode to account for baryonic physics. These residual errors are used to model a so-called theoretical error covariance matrix that is added to the original covariance matrix. In order to assess the performance of the method, we use the 2D tomographic shear from four hydrodynamical simulations that have different extremes of baryonic parameters as mock data and run a likelihood analysis comparing the residual bias on Ωm and σ8 of our method and the HMCode for an LSST-like survey. We use different modelling of the theoretical error covariance matrix to test the robustness of the method. We show that it is possible to reduce the bias in the determination of the tested cosmological parameters at the price of a modest decrease in the precision.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Design and Evaluation of Environmental Barrier Coatings for Protection of Ceramic Matrix Composites in Hydrogen-Based Turbines

This presentation at the 2024 FECM Spring Project Review Meeting summarizes ongoing work at NETL aimed at enabling the use of ceramic matrix composite (CMC) materials in next-generation high-efficiency power generation turbines fueled by hydrogen, natural gas, or other fuels. The work broadly involves three aspects (1) phase-field damage modeling of CMCs and the environmental barrier coatings (EBCs) used to protect them (2) computational design of new and improved EBCs and (3) performance testing of EBCs using a novel gas turbine combustion simulation rig developed at NETL. An overview on current status and next steps for each aspect of the project are presented.

ceramic matrix composite (CMC)↗
DOE OSTI2021

A Cyber Threat Mitigation Approach For Wide Area Control of SVCs using Stability Monitoring

We propose a stability monitoring approach for the mitigation of cyber threats directed at the wide area control (WAC) system used for coordinated control of Flexible AC Transmission Systems (FACTS) used for power oscillation damping (POD) of active power flow on inter-area tie lines. The approach involves monitoring the modes of the active power oscillation on an inter-area tie line using the Matrix Pencil (MP) method. We use the stability characteristics of the observed modes as a proxy for the presence of destabilizing cyber threats. We monitor the system modes to determine whether any destabilizing modes appear after the WAC system engages to control the POD. If the WAC signal exacerbates the POD performance, the FACTS falls back to POD using local measurements. The proposed approach does not require an expansive system-wide view of the network. We simulate replay, control integrity, and timing attacks for a test system and present results that demonstrate the performance of the SM approach for mitigation.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Voltage Stability Constrained Moving Target Defense Against Net Load Redistribution Attacks

Moving target defense (MTD) using distributed flexible AC transmission system (D-FACTS) devices is a promising defense strategy to detect stealthy false data injection (FDI) attacks against the power system state estimation. However, all existing studies myopically perturb the reactance of D-FACTS lines without considering the system voltage stability. In this paper, we first illustrate voltage instability induced by MTDs in a three-bus system. To address this issue, we further propose a novel MTD framework that explicitly considers system voltage stability by using continuation power flow and voltage stability indices. We mathematically derive the sensitivity matrix of voltage stability index to line impedance, on which an optimization problem for maximizing voltage stability index is formulated. This framework is tested on the IEEE 14-bus and the IEEE 118-bus transmission systems, in which net load redistribution attacks are launched by sophisticated attackers. Here, the simulation results show the effectiveness of the proposed framework in circumventing the voltage instability while maintaining the detection effectiveness of MTD. We conduct case studies with and without the proposed framework under different MTD planning and operational methods. The impacts of the proposed two methods on attack detection effectiveness and system economic metrics are also revealed.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

Copper–Carbon Nanotube Composites Enabled by Electrospinning for Advanced Conductors

The power losses associated with the electrical resistance of copper (Cu) have generated considerable interest in the development of advanced conductors that incorporate carbon nanotubes (CNTs) into the Cu matrix—ultraconductive Cu (UCC) composites—to increase energy efficiency in various industrial and residential applications, ranging from electric power transmission and rotating machinery to electronic devices. To meet this demand, we describe an electrospinning-based polymer nanofiber templating strategy for the fabrication of UCC composites with electrical and mechanical performance exceeding that of Cu. Our approach involves electrospinning of polyvinylpyrrolidone (PVP)-based solutions containing CNTs into aligned PVP/CNT nanofibers onto Cu foil substrates, followed by vacuum-assisted thermal removal of organic solvent/polymer from the CNT matrix to achieve a uniformly distributed CNT layer on the Cu surface. Following additional Cu deposition, the Cu–CNT–Cu composites demonstrated similar electrical conductivity, higher current carrying capacity, and improved mechanical properties compared with those obtained from reference Cu. Importantly, after the heat treatment, Raman analysis of the CNT network displayed an increased metallic character that supports the enhanced electrical properties of the UCC composites. Thus, we believe that these performance characteristics together with the commercial viability of the present approach could open new possibilities in designing advanced conductors for a broad range of electrical systems and industrial applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Generalized Analytical Estimation of Sensitivity Matrices in Unbalanced Distribution Networks

Fast and accurate estimation of sensitivity matrices is significant for the enhancement of distribution system modeling and automation. Analytical estimations have mainly focused on voltage magnitude sensitivity to active/reactive power injections for unbalanced networks with Wye-connected loads and neglecting DERs' smart inverter functionality. Hence, this paper enhances the scope of analytical estimation of sensitivity matrices for unbalanced networks with 1- Φ, 2- Φ, and 3- Φ Delta/Wye-connected loads, DERs with smart inverter functionality, and substation/line step-voltage regulators (SVR). A composite bus model comprising of DER, Delta- and Wye-connected load is proposed to represent a generic distribution bus, which can be simplified to load, PV, or voltage-controlled bus as required. Furthermore, the proposed matrix-based analytical method consolidates voltage magnitude and angle sensitivity to active/reactive power injection and tap-position of all SVRs into a single algorithm. Extensive case studies on IEEE and EPRI networks show the accuracy and wide scope of the proposed algorithm compared to the existing benchmark method.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Scalable, Infiltration-Free Ceramic Matrix Composite (SIF-CMC) manufacturing for Molten Salt Receiver: Investigation of particle-loaded preceramic resin

Due to their unique combination of high temperature, corrosion resistance, and toughness, Ceramic Matrix Composites (CMC) are the optimal materials to be used in the next generation of Concentrated Solar Power (CSP), which will operate at working temperatures up to 800 °C. However, today, CMC is too costly to be used in CSP applications due to its complex manufacturing process based on repeated infiltration-pyrolysis cycles. To solve this issue, PARC is developing a scalable, infiltration-free method (SIF) to manufacture CMC, which can reduce the production cost, increase batch consistency, and leverage all of the intrinsic advantages of current CMCs. The key to the SIF method is using a flowable preceramic resin with high loading of functional components. The formulation impregnates the fiber during curing and leads to high-density, low-shrinkage parts upon pyrolysis. In this paper, we demonstrate a proof-of-concept of the SIF process and report the relationships between key process parameters in the manufacturing process: functional material loading in the resin vs. resin’s flowability and morphology changes upon pyrolysis.

ceramic matrix composite, concentrated solar power↗
DOE OSTI2023

Bayesian High-Rank Hankel Matrix Completion for Nonlinear Synchrophasor Data Recovery

Phasor measurement units (PMUs) provide high temporal-resolution synchrophasor measurements for power system monitoring and control. The frequent data quality issues, such as missing and bad data, prevent the incorporation of synchrophasor data in real-time operations. Most existing data-driven data recovery methods assume the power system dynamics can be approximated by a linear dynamical system, and the recovery performance degrades significantly when the power system is experiencing nonlinear dynamics during significant events. Here, this paper proposes a data-driven Bayesian nonlinear synchrophasor data recovery method (Ba-NSDR) that can recover a consecutive time period of simultaneous data losses or errors across all channels, even when the underlying system is highly nonlinear. The idea is to lift the Hankel matrix of the spatial-temporal synchrophasor data to a higher dimension such that the lifted Hankel matrix is low-rank in that space and can be processed with the kernel trick. Our proposed Bayesian method then infers the probabilistic distributions of synchrophasor from the partial observations. Some distinctive features of Ba-NSDR include an uncertainty index to measure the accuracy of the recovery result and the robustness to parameter selections. Our method is verified on both synthetic and recorded event datasets.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

Scalable, Infiltration-Free Ceramic Matrix Composite Manufacturing for Molten Salt Receiver (SIF-CMC)

Ceramic Matrix Composite (CMC) with high thermomechanical properties is a promising material class for Concentrated Solar Power but current use is limited by a long and tedious manufacturing process with high costs and poor scalability. SIF-CMC provides a novel way to simplify the manufacturing process by dramatically increasing the char yield of the matrix from polymer to ceramic, which makes the CMC affordable and scalable.

Wei, Junhua↗