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At least 1,279 records · Page 71

Extended forward sensitivity analysis of one-dimensional isothermal flow

Sensitivity analysis and uncertainty quantification is an important part of nuclear safety analysis. In this work, forward sensitivity analysis is used to compute solution sensitivities on 1-D fluid flow equations typical of those found in system level codes. Time step sensitivity analysis is included as a method for determining the accumulated error from time discretization. The ability to quantify numerical error arising from the time discretization is a unique and important feature of this method. By knowing the relative sensitivity of time step with other physical parameters, the simulation is allowed to run at optimized time steps without affecting the confidence of the physical parameter sensitivity results. The time step forward sensitivity analysis method can also replace the traditional time step convergence studies that are a key part of code verification with much less computational cost. One well-defined benchmark problem with manufactured solutions is utilized to verify the method; another test isothermal flow problem is used to demonstrate the extended forward sensitivity analysis process. Through these sample problems, the paper shows the feasibility and potential of using the forward sensitivity analysis method to quantify uncertainty in input parameters and time step size for a 1-D system-level thermal-hydraulic safety code. (authors)

97 MATHEMATICS AND COMPUTING↗

Correspondence of NNGP Kernel and the Matérn Kernel

Kernels representing limiting cases of neural network architectures have recently gained popularity. However, the application and performance of these new kernels compared to existing options, such as the Matérn kernel, is not well studied. We take a practical approach to explore the neural network Gaussian process (NNGP) kernel and its application to data in Gaussian process regression. We first demonstrate the necessity of normalization to produce valid NNGP kernels and explore related numerical challenges. We further demonstrate that the predictions from this model are quite inflexible, and therefore do not vary much over the valid hyperparameter sets. We then demonstrate a surprising result that the predictions given from the NNGP kernel correspond closely to those given by the Matérn kernel under specific circumstances, which suggests a deep similarity between overparameterized deep neural networks and the Matérn kernel. Finally, we demonstrate the performance of the NNGP kernel as compared to the Matérn kernel on three benchmark data cases, and we conclude that for its flexibility and practical performance, the Matérn kernel is preferred to the novel NNGP in practical applications.

97 MATHEMATICS AND COMPUTING↗

Cross Entropy Benchmark for Measurement-Induced Phase Transitions

Here, we investigate prospects of employing the linear cross entropy to experimentally access measurement-induced phase transitions without requiring any postselection of quantum trajectories. For two random circuits that are identical in the bulk but with different initial states, the linear cross entropy χ between the bulk measurement outcome distributions in the two circuits acts as an order parameter, and can be used to distinguish the volume law from area law phases. In the volume law phase (and in the thermodynamic limit) the bulk measurements cannot distinguish between the two different initial states, and χ = 1. In the area law phase χ < 1. For circuits with Clifford gates, we provide numerical evidence that χ can be sampled to accuracy ϵ from O⁢(1/ϵ 2 ) trajectories, by running the first circuit on a quantum simulator without postselection, aided by a classical simulation of the second. We also find that for weak depolarizing noise the signature of the measurement-induced phase transitions is still present for intermediate system sizes. In our protocol we have the freedom of choosing initial states such that the “classical” side can be simulated efficiently, while simulating the “quantum” side is still classically hard.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

PyApprox: A software package for sensitivity analysis, Bayesian inference, optimal experimental design, and multi-fidelity uncertainty quantification and surrogate modeling

PyApprox is a Python-based one-stop-shop for probabilistic analysis of numerical models such as those used in the earth, environmental and engineering sciences. Easy to use and extendable tools are provided for constructing surrogates, sensitivity analysis, Bayesian inference, experimental design, and forward uncertainty quantification. The algorithms implemented represent a wide range of methods for model analysis developed over the past two decades, including recent advances in multi-fidelity approaches that use multiple model discretizations and/or simplified physics to significantly reduce the computational cost of various types of analyses. An extensive set of Benchmarks from the literature is also provided to facilitate the easy comparison of new or existing algorithms for a wide range of model analyses. Here, this paper introduces PyApprox and its various features, and presents results demonstrating the utility of PyApprox on a benchmark problem modeling the advection of a tracer in groundwater.

54 ENVIRONMENTAL SCIENCES↗

Unbiased particle conformation extraction from scattering spectra using orthonormal basis expansions

A strategy is outlined for quantitatively evaluating the particle density profiles from small-angle scattering spectra of dilute solutions. The approach employs an orthonormal basis function expansion method, enabling the determination of characteristic mass distributions in self-assembled structures without the need for a specific structural model. Through computational benchmarking, the efficacy of this approach is validated by effectively reconstructing the density profile of soft-ball systems with varying fuzziness from their scattering signatures. Further, the feasibility of the method is demonstrated by fitting small-angle neutron scattering data obtained from Pluronic L64 micelles at different temperatures. This proposed approach is both simple and analytical, eliminating the requirement for a presumptive structural model in scattering analysis. The new method could therefore facilitate quantitative descriptions of complex nanoscopic structures inherent to numerous soft-matter systems using small-angle scattering techniques.

36 MATERIALS SCIENCE↗

Robust Recovery of Temporally Smooth Signals From Under-Determined Multiple Measurements

In this study, we consider the problem of recovering jointly sparse vectors from underdetermined measurements that are corrupted by both additive noise and outliers. This can be viewed as the robust extension of the Multiple Measurement Vector (MMV) problem. To solve this problem, we propose two general approaches. As a benchmark, the first approach preprocesses the input for outlier removal and then employs state-of-the-art technologies for signal recovery. The second approach, as the main contribution of this paper, is based on formulation of an innovative regularized fitting problem. By solving the regularized fitting problem, we jointly remove outliers and recover the sparse vectors. Furthermore, by exploiting temporal smoothness among the sparse vectors, we improve noise robustness of the proposed approach and avoid the problem of over-fitting. Extensive numerical results are provided to illustrate the excellent performance of the proposed approach.

47 OTHER INSTRUMENTATION↗

Prediction of Sound Waves Propagating Through a Nozzle Without/With a Shock Wave Using the Space-Time CE/SE Method

The benchmark problems in Category 1 (Internal Propagation) of the third Computational Aeroacoustics (CAA) Work-shop sponsored by NASA Glenn Research Center are solved using the space-time conservation element and solution element (CE/SE) method. The first problem addresses the propagation of sound waves through a nearly choked transonic nozzle. The second one concerns shock-sound interaction in a supersonic nozzle. A quasi one-dimension CE/SE Euler solver for a nonuniform mesh is developed and employed to solve both problems. Numerical solutions are compared with the analytical solution for both problems. It is demonstrated that the CE/SE method is capable of solving aeroacoustic problems with/without shock waves in a simple way. Furthermore, the simple nonreflecting boundary condition used in the CE/SE method which is not based on the characteristic theory works very well.

Wang, Xiao-Yen↗

Milestone Deliverable: FY18-Q1: Deploy production sliding mesh capability with linear solver benchmarking.

This milestone was focused on deploying and verifying a “sliding-mesh interface,” and establishing baseline timings for blade-resolved simulations of a sub-MW-scale turbine. In the ExaWind project, we are developing both sliding-mesh and overset-mesh approaches for handling the rotating blades in an operating wind turbine. In the sliding-mesh approach, the turbine rotor and its immediate surrounding fluid are captured in a “disk” that is embedded in the larger fluid domain. The embedded fluid is simulated in a coordinate system that rotates with the rotor. It is important that the coupling algorithm (and its implementation) between the rotating and inertial discrete models maintains the accuracy of the numerical methods on either side of the interface, i.e., the interface is “design order.”

17 WIND ENERGY↗

Numerical simulation of involute-plate research reactor flow behavior using RANS, LES and DNS

This paper investigates the flow behavior of involute-plate research reactors by performing Reynolds-Averaged Navier Stokes simulation (RANS), Large Eddy Simulation (LES) and Direct Numerical Simulation (DNS) of the channel flow between fuel plates. By modeling turbulence with different numerical approaches, this study provides data with three levels of fidelity. For the RANS simulation, three widely used turbulence models, i.e., k-ε, k-ω, Reynolds Stress Turbulence model (RST) are applied by using the commercial CFD code STAR-CCM +. For LES and DNS, the open-source CFD code, Nek5000, is used given its outstanding scalability on High Performance Computer (HPC) and high-order technique. The results from RANS simulations are compared with that from LES and DNS for benchmarking. Both macroscale parameters and turbulence statistics, such as velocity magnitude, lateral velocity and turbulence kinetic energy, are presented and analyzed. The results from RANS simulation achieve good agreement with LES and DNS on velocity and turbulence kinetic energy prediction. The RST turbulence model predicts the most similar flow pattern of lateral velocity as compared to LES and DNS. The Lambda-2 (λ2) criterion with a reasonable threshold is used to demonstrate the instantaneous vortices distribution in the involute channel from both LES and DNS calculation. The DNS simulation captures more detailed turbulence especially near the corner, which explains the discrepancy between LES and DNS results near the corner. The normalized RMS error are defined and calculated to assess the performance of those turbulence models. The RST model captures the anisotropic feature of turbulence, which enable it to outperform other turbulence models for predicting the flow behavior in an involute channel. Although some discrepancies are found between LES and DNS results in the corner, the overall deviations between LES and DNS are found to be small. In conclusion, given that the computational cost of DNS calculation is an order of magnitude higher, using LES data for benchmarking RANS model is a cost-effective approach.

DNS↗

A mathematical and numerical framework for the analysis of compressible thermal convection in gases at very high temperatures

The relevance of non-equilibrium phenomena, nonlinear behavior, gravitational effects and fluid compressibility in a wide range of problems related to high-temperature gas-dynamics, especially in thermal, mechanical and nuclear engineering, calls for a concerted approach using the tools of the kinetic theory of gases, statistical physics, quantum mechanics, thermodynamics and mathematical modeling in synergy with advanced numerical strategies for the solution of the Navier–Stokes equations. The reason behind such a need is that in many instances of relevance in this field one witnesses a departure from canonical models and the resulting inadequacy of standard CFD approaches, especially those traditionally used to deal with thermal (buoyancy) convection problems. Starting from microscopic considerations and typical concepts of molecular dynamics, passing through the Boltzmann equation and its known solutions, we show how it is possible to remove past assumptions and elaborate an algorithm capable of targeting the broadest range of applications. Moving beyond the Boussinesq approximation, the Sutherland law and the principle of energy equipartition, the resulting method allows most of the fluid properties (density, viscosity, thermal conductivity, heat capacity and diffusivity, etc.) to be derived in a rational and natural way while keeping empirical contamination to the minimum. Special attention is deserved as well to the well-known pressure issue. With the application of the socalled multiple pressure variables concept and a projection-like numerical approach, difficulties with such a term in the momentum equation are circumvented by allowing the hydrodynamic pressure to decouple from its thermodynamic counterpart. The final result is a flexible and modular framework that on the one hand is able to account for all the molecule (translational, rotational and vibrational) degrees of freedom and their effective excitation, and on the other hand can guarantee adequate interplay between molecular and macroscopic-level entities and processes. Performances are demonstrated by computing some incompressible and compressible benchmark test cases for thermal (gravitational) convection, which are then extended to the high-temperature regime taking advantage of the newly developed features.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Two-particle correlation functions in cluster perturbation theory: Hubbard spin susceptibilities

Cluster perturbation theory (CPT) is a computationally economic method commonly used to estimate the momentum- and energy-resolved single-particle Green's function. It has been used extensively in direct comparisons with experiments that effectively measure the single-particle Green's function, e.g., angle-resolved photoemission spectroscopy. However, many experimental observables are given by two-particle correlation functions. CPT can be extended to compute two-particle correlation functions by approximately solving the Bethe-Salpeter equation. We implement this method and focus on the transverse spin susceptibility, measurable via inelastic neutron scattering or with optical probes of atomic gases in optical lattices. Finally, we benchmark the method with the one-dimensional Fermi-Hubbard model by comparing with known results.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

HARD X-RAY ASYMMETRY LIMITS IN SOLAR FLARE CONJUGATE FOOTPOINTS

The transport of energetic electrons in a solar flare is modeled using a time-dependent one-dimensional Fokker–Planck code that incorporates asymmetric magnetic convergence. We derive the temporal and spectral evolution of the resulting hard X-ray (HXR) emission in the conjugate chromospheric footpoints, assuming thick target photon production, and characterize the time evolution of the numerically simulated footpoint asymmetry and its relationship to the photospheric magnetic configuration. The thick target HXR asymmetry in the conjugate footpoints is found to increase with magnetic field ratio as expected. However, we find that the footpoint HXR asymmetry saturates for conjugate footpoint magnetic field ratios ≥4. This result is borne out in a direct comparison with observations of 44 double-footpoint flares. The presence of such a limit has not been reported before, and may serve as both a theoretical and observational benchmark for testing a range of particle transport and flare morphology constraints, particularly as a means to differentiate between isotropic and anisotropic particle injection.

79 ASTRONOMY AND ASTROPHYSICS↗

Theoretical and computational studies on the scattering of radio frequency waves by fluctuations

The practical and economic viability of tokamak fusion reactors depends, in a significant way, on the efficiency of radio frequency (RF) waves to deliver energy and momentum to the plasma in the core of the reactor. Among the various attributes of RF waves is their ability to heat magnetically confined plasmas, induce plasma currents in an effort to achieve steady state, and modify the current profile so as to control plasma instabilities like the neoclassical tearing modes. The RF electromagnetic waves, excited by antenna structures placed near the wall of a tokamak, have to propagate through the turbulent plasma in the scrape-off layer (SOL) along their path to the core plasma. While the propagation and damping of RF waves in the core is reasonably well understood, the same is not true for RF propagation through the SOL. In present day fusion devices, the radial width of the SOL is of the order of a few centimeters. In ITER and in future fusion reactors this width will be of the order of tens of centimeters. Any deleterious effects on RF waves due to plasma turbulence in the SOL has to be properly understood in order to optimize the delivery of RF energy and momentum into the core. This paper is on a multi-pronged approach that is being pursued to quantify the effect of SOL plasma on RF waves. The SOL is composed of coherent filamentary, or blob like, structures and incoherent fluctuations. For coherent structures a full-wave theoretical model has been developed. This model is used to benchmark computational codes that are subsequently used to study general distribution of filaments, thereby extending the range of the theoretical formulation. For incoherent fluctuations, a common approach towards quantifying the effects of turbulence is the Kirchhoff technique. This technique is based on physical optics and the wave fields at any point on a spatially varying surface are approximated to be the same as the fields on a tangent plane at that point. The results from the theoretical analysis are compared with full-wave numerical simulations for incoherent fluctuations. The final part of these studies is to construct the effective permittivity of a turbulent plasma that is a mix of coherent and incoherent fluctuations. Towards this end, the ``effective medium approximation'' is being used to construct the permittivity of the turbulent plasma that will be used in full-wave and physical optics studies of scattering. All these approaches are distinctly different from previous studies on the RF wave propagation through turbulent plasmas. The theory and computations discussed in this paper apply to RF waves in any frequency range and for arbitrary variations in density, and reveal new and important physical insights into the scattering of RF waves.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

HOST combustion R and T overview

The overall objective of the Turbine Engine Hot Section Technology Combustion Project was to develop and verify improved and more accurate numerical analysis methods for increasing the ability to design with confidence combustion systems for advanced aircraft gas turbine engines. The objective was approached from two directions: computational and experimental. On the computational side, the approach was to first assess and evaluate existing combustor aerothermal analysis models. On the experimental side, three types of experiments are identified; first, fundamental experiments directed toward improved understanding of the flow physics and chemistry; second, experiments run to provide data for the empirical modeling of complex phenomena; and third, benchmark experiments for computer code validation.

Gaugler, Raymond E.↗

New Particle-in-Cell Code for Numerical Simulation of Coherent Synchrotron Radiation

We present a first look at the new code for self-consistent, 2D simulations of beam dynamics affected by the coherent synchrotron radiation. The code is of the particle-in-cell variety: the beam bunch is sampled by point-charge particles, which are deposited on the grid; the corresponding forces on the grid are then computed using retarded potentials according to causality, and interpolated so as to advance the particles in time. The retarded potentials are evaluated by integrating over the 2D path history of the bunch, with the charge and current density at the retarded time obtained from interpolation of the particle distributions recorded at discrete timesteps. The code is benchmarked against analytical results obtained for a rigid-line bunch. We also outline the features and applications which are currently being developed.

43 PARTICLE ACCELERATORS↗

Numerical study of the chemo-mechanical behavior of FEBEX bentonite in nuclear waste disposal based on the Barcelona expansive model

Experimental studies show that compacted bentonite used as a backfill material for nuclear waste repository experiences strong coupling between chemical and mechanical processes. Here, we use a dual-structure expansive soil model, referred to as the Barcelona Expansive Model (BExM), to predict the behavior of bentonite buffer in subsurface emplacement tunnels for high-level radioactive waste. After emplacement, the bentonite is subjected to complex and coupled Thermal-Hydraulic-Mechanical-Chemical (THMC) processes. The BExM constitutive model is implemented in a multi-phase reactive transport and geomechanics simulator, TOUGHREACT-FLAC3D, and the model is verified with one benchmark test on FEBEX bentonite. We utilize a one-way Chemo-Mechanical (C-M) coupling approach, in which chemical changes affect the mechanical behavior of bentonite through the BExM linked with the evolution of mass fraction of smectite, exchangeable cation concentration, and ionic strength via osmotic suction. The parameters of the new coupled model for FEBEX bentonite are calibrated against a series of laboratory experiments with various salinity solutions. Finally, coupled THMC modeling is conducted for a generic argillite repository with bentonite buffer under high temperature, focusing on the long-term chemical change and its effect on the mechanical process.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

An Expanded Role for Python in Expediting System Simulation Development

The Python programming language has traditionally been used as a “scripting” language and is not generally recognized as a language for building system simulations, where C++, Java, and other compiled languages are typically used. While very powerful and gaining favor for a large set of programming tasks, Python is generally regarded as not having the speed to directly do the extensive numeric computations required in large-scale simulation. This paper aims to present an approach, supported by case studies, to re-think this assertion. Directly using Python in this new role has the potential to expedite an agile, spiral cycle of development of design-test-modify for systems simulation.

programming language↗