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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
NASA NTRSDate not supplied

SLS Integrated Modal Test Uncertainty Quantification using the Hybrid Parametric Variation Method

Uncertainty in structural loading during launch is a significant concern in the development of spacecraft and launch vehicles. Small variations in launch vehicle and payload mode shapes and their interaction can result in significant variation in system loads. In many cases involving large aerospace systems it is difficult, not economical, or impossible to perform a system modal test. However, it is still vital to obtain test results that can be compared with analytical predictions to validate models. Instead, the “Building Block Approach” is used in which system components are tested individually. Component models are correlated and updated to agree as best they can with test results. The Space Launch System consists of a number of components that are assembled into a launch vehicle. Finite element models of the components are developed, reduced to Hurty/Craig-Bampton models and assembled to represent different phases of flight. The only opportunity to obtain modal test data from an assembled Space Launch System will be during the Integrated Modal Test. There is always uncertainty in every model, which flows into uncertainty in predicted system results. Uncertainty Quantification is used to determine statistical bounds on prediction accuracy based on model uncertainty. For the Space Launch System, model uncertainty is at the Hurty/Craig-Bampton component level. Uncertainty in the Hurty/Craig-Bampton components is quantified using the hybrid parametric variation approach that combines parametric and nonparametric uncertainty. Uncertainty in model form is one of the biggest contributors to uncertainty in complex built-up structures. This type of uncertainty cannot be represented by variations infinite element model input parameters and thus cannot be included in a parametric approach. However, model-form uncertainty can be modeled using a nonparametric approach based on random matrix theory. The hybrid parametric variation method requires the selection of dispersion values for the Hurty/Craig-Bampton fixed-interface eigenvalues, and the Hurty/Craig-Bampton stiffness matrices. Component test/analysis frequency error is used to identify the fixed-interface eigenvalue dispersions, while test/analysis cross-orthogonality is used to identify stiffness dispersion values. The hybrid parametric variation uncertainty quantification approach is applied to the Space Launch System Integrated Modal Test configuration. Monte Carlo analysis is performed, and statistics are determined for modal correlation metrics, frequency response from Integrated Modal Test shakers to selected accelerometers, as well as other metrics for determining how well target modes are excited and identified. If the predicted uncertainty envelopes future Integrated Modal Test results, then there will be increased confidence in the utility of the component-based hybrid parametric variation uncertainty quantification approach.

Uncertainty Quantification↗
NASA NTRSDate not supplied

Ground Tests on the BOLT Geometry at Mach 7: Cross-Facility Comparison and Stability Analysis

Transition measurements have been obtained through two experimental campaigns conducted independently by the German Aerospace Center and the French Aerospace Lab with the French Alternative Energies and Atomic Energy Commission on subscale models of the BOLT-1 flight experiment geometry. This paper details a cross-facility comparison of measurements obtained at Mach 7, as well as subsequent computational analysis. Infrared (IR) thermography measurements obtained by both campaigns have facilitated a global comparison of the transition front across facilities at analagous conditions, which are found to be in good agreement. High-frequency surface pressure fluctuation data demonstrate significant amplification of instabilities with Mack-mode characteristics in the outboard regions of the acreage. These measurements are compared to stability analyses of varying fidelity. The computational methods employed to characterize the boundary-layer transition phenomena include the traditional line-marching implementation of the Parabolized Stability Equations (PSE), 2D eigenvalue analysis coupled with PSE, and Adaptive Mesh Refinement Wavepacket Tracking. While the 2D eigenvalue analysis is found to predict instabilities, which correlate in terms of frequency and acreage location to the experimental measurements, the predicted amplification for these instabilities is lower than would typically be expected for transition. Line-marching results for traveling crossflow produce the best match to the experimental transition front, with a consistent transition N factor of approximately 3-3.5.

Boundary Layer Transition↗
NASA NTRSDate not supplied

Coherent Mode Decomposition for Kolmogorov Optical Turbulence in a Finite Aperture

An analysis of the coherent mode decomposition of an optical field after propagation through atmospheric turbulence is presented. The coherent modes represent an ideal basis by which to decompose the field for design of mode-limited optical systems. Using the rotational symmetry of the Fredholm integral operator for Kolmogorov optical turbulence, it is shown that the coherent modes exhibit separable solutions classified by radial and azimuthal quantum numbers. The study of the coherent modes is then reduced that of the radial functions determined by the aperture-coherence diameter ratio and obscuration ratio. Analysis of the spectrum of eigenvalues yields sharp bounds on the efficiency of receivers using incoherent or coherent combining with mode-limited photonic devices in the presence of Kolmogorov turbulence. The effective number of modes needed to represent Kolmogorov optical turbulence is studied via the von Neumann entropy, purity, and largest eigenvalue, and the differences in the different definitions is discussed. The similarity of the coherent modes to linearly polarized (LP) fiber modes is quantified yielding a precise characterization of the maximum gain that can be achieved in mode-limited systems via mode shaping techniques. As a final application, a mode sorting technique is presented for optimally splitting power from atmospherically degraded light into a finite number of modes simultaneously maximizing total coupling efficiency and minimizing the average and instantaneous power ratio between channels.

free-space optical communication↗
NASA NTRSDate not supplied

Coherent Mode Decomposition for Kolmogorov Optical Turbulence in a Finite Aperture

An analysis of the coherent mode decomposition of an optical field after propagation through atmospheric turbulence is presented. The coherent modes represent an ideal basis by which to decompose the field for design of mode-limited optical systems. Due to rotational symmetry of the Fredholm integral operator for Kolmogorov optical turbulence, the coherent modes exhibit separable solutions classified by a radial and azimuthal mode index. The study of the coherent modes is then reduced to that of the radial functions determined by the coherence ratio and obscuration ratio. Analysis of the spectrum of eigenvalues yields sharp bounds on the efficiency of receivers using incoherent or coherent combining with mode-limited photonic devices in the presence of Kolmogorov turbulence. The effective number of modes needed to represent Kolmogorov optical turbulence is studied via the von Neumann entropy, purity, and largest eigenvalue, and the differences in the different definitions is discussed. The similarity of the coherent modes to linearly polarized (LP) fiber modes is quantified yielding a precise characterization of the maximum gain that can be achieved in mode-limited systems via mode shaping techniques. As a final application, a mode sorting technique is presented for optimally splitting power from atmospherically degraded light into a finite number of modes simultaneously maximizing total coupling efficiency and minimizing the difference in average power between channels.

free-space optical communication↗
DOE OSTI2020

Physics-constrained Deep Recurrent Neural Models of Building Thermal Dynamics

We develop physics-constrained and control-oriented predictive deep learning models for the thermal dynamics of a real-world commercial office building. The proposed method is based on the systematic encoding of physics-based prior knowledge into a structured recurrent neural architecture. Specifically, our model mimics the structure of the building thermal dynamics model and leverages penalty methods to model inequality constraints. Additionally, we use constrained matrix parameterization based on the Perron-Frobenius theorem to bound the eigenvalues of the learned network weights. We interpret the stable eigenvalues as dissipativeness of the learned building thermal model. We demonstrate the effectiveness of the proposed approach on a dataset obtained from an office building with $20$ thermal zones.

Building Energy, structured neural networks↗
DOE OSTI2021

On the Stochastic Stability of Deep Markov Models

Deep Markov models (DMM) are generative models which are scalable and expressive generalization of Markov models for representation, learning, and inference problems. DMMs using deep neural networks to parametrize the transition of Markov probability distributions have recently been shown to provide more expressiveness in modeling sequential data and dynamical system responses. However, the fundamental stochastic stability guarantees of such models have not been thoroughly investigated. In this paper, we present a rigorous analytical method to prove the necessary and sufficient conditions of DMM's stochastic stability. This task is achieved by spectral analysis of the efficiently computed Jacobians of probabilistic maps modeled by deep neural networks. We make theoretical connections between the eigenvalues of neural network's weights and the different activation function types used on the stability and overall dynamic behavior of DMMs with Gaussian distributions. We empirically substantiate our theoretical results on stochastic stability and eigenvalue spectra via several numerical experiments. Formal stability guarantees of DMMs can substantially improve their robustness and trustworthiness, necessary for reliable use in safety-critical real-world applications.

Drgona, Jan↗
DOE OSTI2022

Multigroup cross section generation capability in GRIFFIN

GRIFFIN is an advanced reactor multiphysics application built on the object-oriented simulation environment (MOOSE) and is jointly developed by Idaho National Laboratory and Argonne National Laboratory. The cross section application programming interface, originally developed for the PROTEUS code, has been integrated into GRIFFIN to prepare cross sections for thermal reactor applications with heterogeneous geometries. Additional improvements have been made by implementing an on-the-fly slowing down method, a double heterogeneity treatment capability, and updating the procedure to generate the fine multigroup library. The cross section preparation capability in GRIFFIN was verified for graphite-moderated TRISO fuel-based reactor benchmark problems: unit-cell problems of VHTR and EMPIRE micro reactor and HTTR assembly problems. Eigenvalues and multigroup cross sections of GRIFFIN agreed very well with those of the continuous-energy Monte Carlo code Serpent2 within 200 pcm in eigenvalue and 2% in cross sections. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2023

3D full core BEAVRS using OpenMOC with transport equivalence

Using an optimized implementation of the three-dimension method of characteristics for neutron transport, as well as a novel equivalence method for transport calculations de- signed to recover self-shielding errors from neglecting the angular dependence of reso- nant group absorption, a 3D full core light water reactor hybrid stochastic-deterministic eigenvalue calculation was achieved. This paper presents the optimizations developed and compares the transport solutions obtained. It realizes a runtime near 6,000 CPU hours for the statepoint, an improvement of an order of magnitude on previous works, with less than 1% error on pin fission/U-238 capture ratios and a few dozen pcms on the eigenvalue.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

Development of a Representative Molten Chloride Fast Reactor Model to Assess the Impact of Nuclear Data

The SCALE code system was employed to conduct a preliminary investigation of nuclear data impacts for a fast spectrum molten chloride salt reactor. A computationally effective depletion model that is representative of the reactor system was successfully developed and used to conduct fuel depletion simulations. Development of this model draws from the SLICE method that was developed at Oak Ridge National Laboratory to enable generation of fuel compositions for an advanced reactor core at equilibrium operation. Eigenvalue uncertainty calculations using the ENDF/B-VII.1 nuclear data library were performed for the reactor in the fresh fuel state and an irradiated fuel state. It was determined that the primary driver of eigenvalue uncertainty was the uncertainty in the 235U (n, 𝛾) cross section. Uncertainty calculation results from this study were compared to results available for a different fast system, a sodium-cooled fast reactor, to confirm similarities and identify differences with respect to nuclear data impacts between the two fast advanced reactor systems.

Hirji, Rakim [Georgia Institute of Technology]↗
DOE OSTI2021

Relativistic levels of mesic atoms

We revisit the derivation of the covariant two-body scalar-fermion equation with a Coulomb interaction, presented in a previous paper. We show that it can be given the formal aspect of a Dirac equation, but for the fact that the eigenvalue is also contained in one of the coefficients and thus it is not linearly included. The discussion of the boundary value problem is therefore different, although some properties of the Dirac equation can be recovered in an approximation bringing back to the concept of reduced mass. We discuss a mixed analytic-numerical method of solution which allows to obtain very accurate results and we calculate the lowest levels, states and QED corrections for pionic and kaonic atoms.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

On the missing magnetic flux and topological effects of a screw dislocation on a charged particle in an inhomogeneous magnetic field

Highlights: • Aharonov–Bohm-type effect associated with the missing magnetic flux. • Persistent currents associated with the missing magnetic flux. • Aharonov–Bohm-type effect associated with the screw dislocation topology. We study the interaction of an electron/hole with inhomogeneous magnetic field in the presence of a screw dislocation. We consider the internal structure of the defect, i.e., we consider the core that gives rise to a finite size to the defect. In addition, we assume that this core determines a forbidden region for the electron/hole. Then, we solve the Schrödinger equation and show that an Aharonov–Bohm-type effect arises from the influence of the topological defect and the missing magnetic flux on the eigenvalues of energy.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

Hybrid eigensolvers for nuclear configuration interaction calculations

We examine and compare several iterative methods for solving large-scale eigenvalue problems arising from nuclear structure calculations. In particular, we discuss the possibility of using block Lanczos method, a Chebyshev filtering based subspace iterations and the residual minimization method accelerated by direct inversion of iterative subspace (RMM-DIIS) and describe how these algorithms compare with the standard Lanczos algorithm and the locally optimal block preconditioned conjugate gradient (LOBPCG) algorithm. Although the RMM-DIIS method does not exhibit rapid convergence when the initial approximations to the desired eigenvectors are not sufficiently accurate, it can be effectively combined with either the block Lanczos or the LOBPCG method to yield a hybrid eigensolver that has several desirable properties. We will describe a few practical issues that need to be addressed to make the hybrid solver efficient and robust.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Validation of Thermal Scattering Laws for Light Water at Elevated Temperatures with Diffusion Experiments

Light water is the most important neutron moderator in many reactor applications. Thermal neutron scattering kernels for H bound in H 2 O are represented by ENDF-format thermal scattering laws (TSLs) evaluated at discrete temperatures T . Nuclear data evaluations are conventionally validated utilizing a combination of critical benchmarks and experimental cross section data. Existing public critical benchmarks may be inadequate for testing water TSLs over the full range of T of interest in reactor applications, and experimental thermal scattering cross section data for water is sparse at elevated T . In this work, MC21 is used to simulate the decay of the equilibrium thermal neutron flux in light-water spheres of several radii. The fundamental-mode time eigenvalue $\mathcal{a}$ is calculated at 22 °C and 227 °C (at saturation pressure) for each sphere using three different H-H 2 O TSLs. Fitting $\mathcal{a}$ to a polynomial function of geometric buckling allows calculation of the thermal neutron diffusion length L . Extrapolation lengths are treated as a function of the transport mean free path and geometry. Experimental L data from 25 publications at 49 temperatures (from 10 °C to 295 °C), computed by several different time-dependent and space-dependent decay methods, is used to develop an empirical fit of L vs. T . The MC21-calculated L for the TSLs tested are within ±1% of the predicted values at 22 °C and 227 °C. This validation approach, which may be repeated at arbitrary T , constitutes an integral benchmark specific to and characterizing the detailed physics of the thermal scattering kernel applied.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

A Refinement-by-Superposition -Method for (curl)- and (div)-Conforming Discretizations

Here, we present refinement-by-superposition (RBS) hp-refinement infrastructure for computational electromagnetics (CEMs), which permits exponential rates of convergence. In contrast to dominant approaches to hp-refinement for continuous Galerkin methods, which rely on explicit constraint equations, the multilevel strategy presented drastically reduces the implementation complexity. Through the RBS methodology, enforcement of continuity occurs by construction, enabling arbitrary levels of refinement with ease, and without the practical (but not theoretical) limitations of constrained-node refinement. We outline the construction of the RBS hp-method for refinement with H (curl)- and H (div)-conforming finite cells. Numerical simulations for the 2-D finite element method (FEM) solution of the Maxwell eigenvalue problem demonstrate the effectiveness of RBS hp-refinement. As an additional goal of this work, we aim to promote the use of mixed-order (low- and high-order) elements in practical CEM applications.

42 ENGINEERING↗
DOE OSTI2021

Planetary normal mode computation: Parallel algorithms, performance and reproducibility

This report is an extension of work entitled “Computing planetary interior normal modes with a highly parallel polynomial filtering eigensolver.” by Shi et al., [1] originally presented at the SC18 conference. A highly parallel polynomial filtered eigensolver was developed and exploited to calculate the planetary normal modes. The proposed method is ideally suited for computing interior eigenpairs for large-scale eigenvalue problems as it greatly enhances memory and computational efficiency. In this article, the second-order finite element method is used to further improve the accuracy as only the first-order finite element method was deployed in the previous work. The parallel algorithm, its parallel performance up to 20k processors, and the great computational accuracy are illustrated. The reproducibility of the previous work was successfully performed on the Student Cluster Competition at the SC19 conference by several participant teams using a completely different Mars-model dataset on different clusters. Both weak and strong scaling performances of the reproducibility by the participant teams were impressive and encouraging. The analysis and reflection of their results are demonstrated and future direction is discussed.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Polynomial Preconditioned Arnoldi with Stability Control

Polynomial preconditioning can improve the convergence of the Arnoldi method for computing eigenvalues. Such preconditioning significantly reduces the cost of orthogonalization; for difficult problems, it can also reduce the number of matrix-vector products. Parallel computations can particularly benefit from the reduction of communication-intensive operations. Additoinally, the GMRES algorithm provides a simple and effective way of generating the preconditioning polynomial. For some problems high degree polynomials are especially effective, but they can lead to stability problems that must be mitigated. A two-level “double polynomial preconditioning” strategy provides an effective way to generate high-degree preconditioners.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Performing k eff Validation of As-Loaded Criticality Safety Calculations Using UNF-ST&DARDS: Sensitivity Calculations

The general method for performing validation of as loaded criticality safety calculations using UNF ST&DARDS is presented in a paper by Clarity, which includes a description of the UNF-ST&DARDS system. Proof-of-principle analyses were performed in the summer of 2019 for MPC-32 dual purpose canisters (DPCs) containing pressurized water reactor (PWR) fuel assemblies. Summaries of these results are presented in this and a companion paper for this conference. The current paper describes the TSUNAMI-3D calculations performed to generate sensitivity data, and the companion paper discusses the selection of critical experiments applicable for validation of the 11 MPC-32 DPCs considered. The generation of sensitivity data for as-loaded spent nuclear fuel (SNF) DPCs is a challenge given the detailed model of the fuel compositions generated by UNF ST&DARDS. Each fuel assembly is modeled with its own irradiation history in 18 axial nodes, unless the fuel assembly is damaged and thus considered as fresh by design basis. This results in a set of 576 fuel compositions, each of which must be processed separately in a multigroup (MG) calculation. Therefore, a continuous-energy (CE) TSUNAMI-3D method was chosen to alleviate this challenge. Two CE TSUNAMI-3D methods are available in SCALE 6.2.3: the iterated fission probability (IFP) and contribution-linked eigenvalue sensitivity/uncertainty estimation via track-length importance characterization (CLUTCH). Since the IFP method is not feasible because of memory requirements associated with its implementation in SCALE, the CLUTCH method was selected for these calculations. CLUTCH has been implemented in SCALE in parallel, allowing long calculations to be performed in reasonable timeframes. The two primary user inputs necessary for CLUTCH calculations are the F*(r) mesh and the number of latent generations used in determining the F*(r) function. This F*(r) function is used as the importance function for fission chains originating in a given volume element (voxel), and it is calculated using the IFP method in the skipped generations. A large number of skipped generations is thus required to ensure accurate calculation of this importance function. In these calculations, 500 generations were used to calculate the F*(r) function. For more information regarding the calculation of F*(r), see Jones [4]. The remainder of this paper is focused on the selection of the F*(r) mesh and the number of latent generations.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2020

Experiments at Sandia to Measure the Effect of Temperature on Critical Systems

Estimation of the uncertainty in a critical experiment attributable to uncertainties in the measured experiment temperature is done by calculating the variation of the eigenvalue of a benchmark configuration as a function of temperature. In the low-enriched water-moderated critical experiments performed at Sandia, this is done by 1) estimating the effects of changing the water temperature while holding the UO 2 fuel temperature constant, 2) estimating the effects of changing the UO 2 temperature while holding the water temperature constant, and 3) combining the two results. This assumes that the two effects are separable. The results of such an analysis are nonintuitive and need experimental verification. Critical experiments are being planned at Sandia National Laboratories (Sandia) to measure the effect of temperature on critical systems and will serve to test the methods used in estimating the temperature effects in critical experiments.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗