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All sources NASA NTRS DOE OSTI

DOE OSTI2020

Efficient and Robust Dynamic Simulation of Power Systems With Holomorphic Embedding

Dynamic simulation is vitally important in power system analysis, but traditional approaches based on numerical integration over small time steps are time-consuming. Also, the Newton-Raphson method suffers from difficulty in convergence when solving nonlinear algebraic equations. In this paper, we propose a novel dynamic simulation approach based on holomorphic embedding. By obtaining a high-order approximation of system dynamics, it achieves a much larger time step and thus enhances the computational efficiency significantly. In addition, the new approach avoids non-convergence issues in solving algebraic equations, which improves robustness. The approach includes flexible modeling of synchronous generators and controllers, and we propose a method for modeling generator coordinate transformations. The approach is tested on the IEEE 39-bus, 10-generator system and a Polish 2383-bus, 327-generator system. The results demonstrate promising computational efficiency and satisfactory numerical robustness for the analysis of large-scale power systems.

42 ENGINEERING↗

NASA NTRSDate not supplied

Natural Fiber Simulations and Analysis for Composites

As the U.S. government and the aviation industry strive to achieve net-zero carbon emissions by 2050, the Sustainable Manufacturing of Aircraft (SUMAC) project, supported by the Convergent Aeronautics Solutions (CAS) program of the National Aeronautics and Space Administration (NASA), aims to develop sustainably derived thermoplastic composites and manufacturing technologies for future aviation. A multidisciplinary team of experts drives this initiative through a collective effort. The team’s key focus areas are sustainably derived thermoplastic resins, natural fiber reinforcement, composite manufacturing, structural health monitoring, computational materials modeling, and systems analysis. This presentation will give an overview of the SUMAC project. Fiber-scale microscopy analysis characterized fiber cross sections finding that hemp and flax fibers are very deformable and non-circular (circularities of 0.2 were observed), and diameters range from submicron to 20 μm. Fiber shapes range from flattened, with aspect ratios Rlong/Rshort up to 5, to round, Rlong/Rshort =1. And Fiber core perimeters, which likely drives deformability, were calculated Pcore=7 μm. Explicit-fiber yarn simulations, parameterized from single-fiber measurements, resolved and identified slack as a cause for yarn strain-hardening tensile behavior. The bonded network model of PLA, PHA and PA11 resins captures tensile behavior, and can model an infused weave. Computational models of the weave unit cells matched the pattern (including plain, twill and triaxial braid), yarn ply (1to 2), and yarn twist from optical microscopy.

thermoplastic↗

NASA NTRSDate not supplied

Natural Fiber Simulations and Analysis for Composites

thermoplastic↗

DOE OSTI2018

Grains and Strains from Cepstral Analysis of 4D-STEM Nano-Diffraction Datasets

We report the availability of fast, high dynamic range pixel array detectors makes scanning convergent beam electron diffraction (CBED) a powerful tool for rapid, spatially resolved characterization of lattice structure over a wide range of length scales. However, to extract useful structural information from the large 4-dimensional datasets, especially for complex, 3D specimens, we must confront challenges with CBED intensity variations due to crystal mistilts and multiple scattering as well as challenges with precisely localizing diffracted disk centers.

36 MATERIALS SCIENCE↗

NASA NTRS1989

Development of higher-order modal methods for transient thermal and structural analysis

A force-derivative method which produces higher-order modal solutions to transient problems is evaluated. These higher-order solutions converge to an accurate response using fewer degrees-of-freedom (eigenmodes) than lower-order methods such as the mode-displacement or mode-acceleration methods. Results are presented for non-proportionally damped structural problems as well as thermal problems modeled by finite elements.

Camarda, Charles J.↗

DOE OSTI2022

Error analysis of numerical methods for thick diffusive neutron transport problems on Shishkin mesh

A thin layer will develop at the boundary if the incoming angular flux is anisotropic in thick diffusive neutron transport problems. Solving such singularly perturbed problems, which have non-smooth solutions with singularity near the boundary, is computationally challenging. Standard finite difference schemes on a uniform mesh cannot yield ε-uniform convergence, where ε is a small parameter, while it can be achieved on a suitable piecewise-uniform Shishkin mesh. We present a formal error analysis of the diamond difference (DD) method and step difference (SD) method for solving the S{sub N} neutron transport equation. The analysis can be extended to other finite difference methods. Numerical results are presented to confirm the error estimates and the advantages of the Shishkin mesh. (author)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

NASA NTRS1997

Design of Neural Networks for Fast Convergence and Accuracy: Dynamics and Control

A procedure for the design and training of artificial neural networks, used for rapid and efficient controls and dynamics design and analysis for flexible space systems, has been developed. Artificial neural networks are employed, such that once properly trained, they provide a means of evaluating the impact of design changes rapidly. Specifically, two-layer feedforward neural networks are designed to approximate the functional relationship between the component/spacecraft design changes and measures of its performance or nonlinear dynamics of the system/components. A training algorithm, based on statistical sampling theory, is presented, which guarantees that the trained networks provide a designer-specified degree of accuracy in mapping the functional relationship. Within each iteration of this statistical-based algorithm, a sequential design algorithm is used for the design and training of the feedforward network to provide rapid convergence to the network goals. Here, at each sequence a new network is trained to minimize the error of previous network. The proposed method should work for applications wherein an arbitrary large source of training data can be generated. Two numerical examples are performed on a spacecraft application in order to demonstrate the feasibility of the proposed approach.

Maghami, Peiman G.↗

DOE OSTI2018

Solving linear equations with messenger-field and conjugate gradient techniques: An application to CMB data analysis

We discuss linear system solvers invoking a messenger-field and compare them with (preconditioned) conjugate gradient approaches. We show that the messenger-field techniques correspond to fixed point iterations of an appropriately preconditioned initial system of linear equations. We then argue that a conjugate gradient solver applied to the same preconditioned system, or equivalently a preconditioned conjugate gradient solver using the same preconditioner and applied to the original system, will in general ensure at least a comparable and typically better performance in terms of the number of iterations to convergence and time-to-solution. We illustrate our conclusions with two common examples drawn from the cosmic microwave background (CMB) data analysis: Wiener filtering and map-making. In addition, and contrary to the standard lore in the CMB field, we show that the performance of the preconditioned conjugate gradient solver can depend significantly on the starting vector. In conclusion, this observation seems of particular importance in the cases of map-making of high signal-to-noise ratio sky maps and therefore should be of relevance for the next generation of CMB experiments.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2023

Diel dynamics of multi-omics in elkhorn fern provide new insights into weak CAM photosynthesis

Crassulacean acid metabolism (CAM) has high water-use efficiency (WUE) and is widely recognized to have evolved from C 3 photosynthesis. Different plant lineages have convergently evolved CAM, but the molecular mechanism that underlies C 3 -to-CAM evolution remains to be clarified. Platycerium bifurcatum (elkhorn fern) provides an opportunity to study the molecular changes underlying the transition from C 3 to CAM photosynthesis because both modes of photosynthesis occur in this species, with sporotrophophyll leaves (SLs) and cover leaves (CLs) performing C 3 and weak CAM photosynthesis, respectively. Here, we report that the physiological and biochemical attributes of CAM in weak CAM-performing CLs differed from those in strong CAM species. We investigated the diel dynamics of the metabolome, proteome, and transcriptome in these dimorphic leaves within the same genetic background and under identical environmental conditions. We found that multi-omic diel dynamics in P. bifurcatum exhibit both tissue and diel effects. Our analysis revealed temporal rewiring of biochemistry relevant to the energy-producing pathway (TCA cycle), CAM pathway, and stomatal movement in CLs compared with SLs. We also confirmed that PHOSPHOENOLPYRUVATE CARBOXYLASE KINASE (PPCK) exhibits convergence in gene expression among highly divergent CAM lineages. Gene regulatory network analysis identified candidate transcription factors regulating the CAM pathway and stomatal movement. Taken together, our results provide new insights into weak CAM photosynthesis and new avenues for CAM bioengineering.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2017

Variance Estimation in Monte Carlo Eigenvalue Simulations Using Spectral Analysis Method

The Monte Carlo (MC) method is the 'gold standard' for performing nuclear reactor calculations and criticality safety analyses because of its ability to handle complex geometries and physics. Reactor and criticality safety analyses require solving eigenvalue problems in complex nuclear systems. Once a stationary fission source distribution is obtained in MC simulations, the sample mean of many stationary cycles is calculated. The MC simulation sample mean is typically referred to as a tally. Variance, or standard deviation, of the sample mean/tally is needed to indicate the level of statistical uncertainty in the simulation and to understand the convergence of the sample mean. Current MC codes typically use sample variance to estimate the statistical uncertainty of the simulation and assume that the MC stationary cycles are independent. However, it is known that cycles are correlated, and estimators of the variance that ignore these correlations systematically underestimate the variance. In this paper, we propose a novel method in the Fourier frequency domain to estimate the variance of the sample mean in MC eigenvalue calculations. Results indicate that the proposed estimator can be unbiased compared to the real variance. The proposed estimator requires minimal additional computing effort.

42 ENGINEERING↗

NASA NTRS2005

Controlling Reflections from Mesh Refinement Interfaces in Numerical Relativity

A leading approach to improving the accuracy on numerical relativity simulations of black hole systems is through fixed or adaptive mesh refinement techniques. We describe a generic numerical error which manifests as slowly converging, artificial reflections from refinement boundaries in a broad class of mesh-refinement implementations, potentially limiting the effectiveness of mesh- refinement techniques for some numerical relativity applications. We elucidate this numerical effect by presenting a model problem which exhibits the phenomenon, but which is simple enough that its numerical error can be understood analytically. Our analysis shows that the effect is caused by variations in finite differencing error generated across low and high resolution regions, and that its slow convergence is caused by the presence of dramatic speed differences among propagation modes typical of 3+1 relativity. Lastly, we resolve the problem, presenting a class of finite-differencing stencil modifications which eliminate this pathology in both our model problem and in numerical relativity examples.

Baker, John G.↗

DOE OSTI2016

Cosmological measurements with general relativistic galaxy correlations

We investigate the cosmological dependence and the constraining power of large-scale galaxy correlations, including all redshift-distortions, wide-angle, lensing and gravitational potential effects on linear scales. We analyze the cosmological information present in the lensing convergence and in the gravitational potential terms describing the so-called ''relativistic effects'', and we find that, while smaller than the information contained in intrinsic galaxy clustering, it is not negligible. We investigate how neglecting them does bias cosmological measurements performed by future spectroscopic and photometric large-scale surveys such as SKA and Euclid. We perform a Fisher analysis using the CLASS code, modified to include scale-dependent galaxy bias and redshift-dependent magnification and evolution bias. Our results show that neglecting relativistic terms, especially lensing convergence, introduces an error in the forecasted precision in measuring cosmological parameters of the order of a few tens of percent, in particular when measuring the matter content of the Universe and primordial non-Gaussianity parameters. The analysis suggests a possible substantial systematic error in cosmological parameter constraints. Therefore, we argue that radial correlations and integrated relativistic terms need to be taken into account when forecasting the constraining power of future large-scale number counts of galaxy surveys.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2019

Relating Convection to GCM Grid-Scale Fields Using Cloud-Resolving Model Simulation of a Squall Line Observed during MC3E Field Experiment

In this study, a WRF (Weather Research and Forecasting) model is used as a cloud-resolving model to simulate a squall line observed on 20 May 2011 in the Southern Great Plains (SGP) of the United States. The model output is then used to examine the relationships between convective precipitation and coarse-grained variables averaged over a range of subdomain sizes equivalent to various global climate model horizontal resolutions. The objective is to determine to what extent convection within the subdomains can be related to these “large-scale” variables, thus that they can potentially serve as closure in convective parameterization. Results show that convective precipitation is well correlated with the vertical velocity at 500 hPa, column integrated moisture convergence and CAPE change due to large-scale advective forcing (dCAPE) for various subdomain sizes, but the correlation decreases with decreasing subdomain size. dCAPE leads convective precipitation for all subdomain sizes examined; however, the lead time decreases with decreasing subdomain size. Moisture convergence leads convective precipitation for subdomain sizes greater than 32 km but has no lead time for smaller subdomain sizes. Mid-tropospheric vertical velocity has no lead time or slightly lags convective precipitation. The lead/lag composite analysis with respect to maximum precipitation time indicates that peaks of large-scale variables increase with decreasing subdomain size. The peaks of 500 hPa vertical velocity and column integrated moisture convergence occur at the same time as maximum precipitation, but maximum dCAPE leads maximum precipitation by twelve minutes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2022

A reliable workflow for improving nanoscale X-ray fluorescence tomographic analysis on nanoparticle-treated HeLa cells

Abstract Scanning X-ray fluorescence (XRF) tomography provides powerful characterization capabilities in evaluating elemental distribution and differentiating their inter- and intra-cellular interactions in a three-dimensional (3D) space. Scanning XRF tomography encounters practical challenges from the sample itself, where the range of rotation angles is limited by geometric constraints, involving sample substrates or nearby features either blocking or converging into the field of view. This study aims to develop a reliable and efficient workflow that can (1) expand the experimental window for nanoscale tomographic analysis of local areas of interest within a laterally extended specimen, and (2) bridge 3D analysis at micrometer and nanoscales on the same specimen. We demonstrate the workflow using a specimen of HeLa cells exposed to iron oxide core and titanium dioxide shell (Fe3O4/TiO2) nanocomposites. The workflow utilizes iterative and multiscale XRF data collection with intermediate sample processing by focused ion beam (FIB) sample preparation between measurements at different length scales. Initial assessment combined with precise sample manipulation via FIB allows direct removal of sample regions that are obstacles to both incident X-ray beam and outgoing XRF signals, which considerably improves the subsequent nanoscale tomography analysis. This multiscale analysis workflow has advanced bio-nanotechnology studies by providing deep insights into the interaction between nanocomposites and single cells at a subcellular level as well as statistical assessments from measuring a population of cells.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

DOE OSTI2013

Design and Quasi-Equilibrium Analysis of a Distributed Frequency-Restoration Controller for Inverter-Based Microgrids

This paper discusses a proposed frequency restoration controller which operates as an outer loop to frequency droop for voltage-source inverters. By quasi-equilibrium analysis, we show that the proposed controller is able to provide arbitrarily small steady-state frequency error while maintaing power sharing between inverters without need for communication or centralized control. We derive rate of convergence, discuss design considerations (including a fundamental trade-off that must be made in design), present a design procedure to meet a maximum frequency error requirement, and show simulation results verifying our analysis and design method. The proposed controller will allow flexible plug-and-play inverter-based networks to meet a specified maximum frequency error requirement.

Distributed control↗

DOE OSTI2011

Functional renormalization group for quantized anharmonic oscillator

Highlights: > RG analysis with field dependent wavefunction renormalization. > The Taylor expansion does not work for the wavefunction renormalization. > The gap energy is RG scheme-dependent. > The O (N) symmetric anharmonic oscillator exhibits only a single phase. > The evolution equation for the 2PI effective action for the oscillator is solved. - Abstract: Functional renormalization group methods formulated in the real-time formalism are applied to the O(N) symmetric quantum anharmonic oscillator, considered as a 0 + 1 dimensional quantum field-theoric model, in the next-to-leading order of the gradient expansion of the one- and two-particle irreducible effective action. The infrared scaling laws and the sensitivity-matrix analysis show the existence of only a single, symmetric phase. The Taylor expansion for the local potential converges fast while it is found not to work for the field-dependent wavefunction renormalization, in particular for the double-well bare potential. Results for the gap energy for the bare anharmonic oscillator potential hint on improving scheme-independence in the next-to-leading order of the gradient expansion, although the truncated perturbation expansion in the bare quartic coupling provides strongly scheme-dependent results for the infrared limits of the running couplings.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2018

Modeling genome-wide enzyme evolution predicts strong epistasis underlying catalytic turnover rates

Systems biology describes cellular phenotypes as properties that emerge from the complex interactions of individual system components. Little is known about how these interactions have affected the evolution of metabolic enzymes. Here, we combine genome-scale metabolic modeling with population genetics models to simulate the evolution of enzyme turnover numbers (k cat s) from a theoretical ancestor with inefficient enzymes. This systems view of biochemical evolution reveals strong epistatic interactions between metabolic genes that shape evolutionary trajectories and influence the magnitude of evolved k cat s. Diminishing returns epistasis prevents enzymes from developing higher k cat s in all reactions and keeps the organism far from the potential fitness optimum. Multifunctional enzymes cause synergistic epistasis that slows down adaptation. The resulting fitness landscape allows k cat evolution to be convergent. Predicted k cat parameters show a significant correlation with experimental data, validating our modeling approach. Our analysis reveals how evolutionary forces shape modern k cat s and the whole of metabolism.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2024

The physics of gain relevant to inertial fusion energy target designs

In inertial confinement fusion, pellets of deuterium tritium fuel are compressed and heated to the conditions where they undergo fusion and release energy. The target gain (ratio of energy released from the fusion reactions to the energy in the drive source) is a key parameter in determining the power flow and economics of an inertial fusion energy (IFE) power plant. In this study, the physics of gain is explored for laser-direct-drive targets with driver energy at the megajoule scale. This analysis is performed with the assumption of next-generation laser technologies that are expected to increase convergent drive pressures to over 200 Mbar. This is possible with the addition of bandwidth to the laser spectrum and by employing focal-spot zooming. Simple physics arguments are used to derive scaling laws that describe target gain as a function of laser energy, adiabat, ablation pressure, and implosion velocity. Scaling laws are found for the unablated mass, ablation pressure, areal density, implosion velocity, and in-flight aspect ratio. Furthermore, those scaling laws are then used to explore the design space for IFE targets.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗