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At least 1,207 records · Page 67

Data-driven Minimum Entropy Control for Stochastic Nonlinear Systems using the Cumulant-Generating Function

Here, we present a novel minimum entropy control algorithm for a class of stochastic nonlinear systems subjected to non-Gaussian noises. The entropy control can be considered as an optimization problem for the system randomness attenuation, but the mean value has to be considered separately. To overcome this disadvantage, a new representation of the system stochastic properties was given using the cumulant-generating function based on the moment-generating function, in which the mean value and the entropy was reflected by the shape of the cumulant-generating function. Based on the samples of the system output and control input, a time-variant linear model was identified, and the minimum entropy optimization was transformed to system stabilization. Then, an optimal control strategy was developed to achieve the randomness attenuation, and the boundedness of the controlled system output was analyzed. The effectiveness of the presented control algorithm was demonstrated by a numerical example. In this paper, a data-driven minimum entropy design is presented without pre-knowledge of the system model; entropy optimization is achieved by the system stabilization approach in which the stochastic distribution control and minimum entropy are unified using the same identified structure; and a potential framework is obtained since all the existing system stabilization methods can be adopted to achieve the minimum entropy objective.

42 ENGINEERING↗

TICC Clustering Library v.1.0

SAND2024-01234O TICC is a clustering algorithm that labels a sequence of data points according to numerical properties. This library is a Python implementation of the algorithm described in "Toeplitz Inverse Covariance-Based Clustering of Multivariate Time Series Data" (Hallac et al. 2017). It includes documentation, performance improvements, examples, and test coverage. This library allows users to automatically segment a series of multivariate data points according to their covariance—that is, the way the values at each data point are changing in relation to one another. This is useful for identifying periods in which a system is behaving. For example, if a sensor is measuring a car's velocity, steering wheel angle, braking and acceleration, TICC can determine when the car was stopped, beginning/exiting a turn, slowing or accelerating at an intersection, or driving on straight or curved roads. TICC can be applied to measure multiple quantities at known times. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525

Dalbey, Keith↗

Error-correcting codes for fermionic quantum simulation

Utilizing the framework of \mathbb{Z}_2 ℤ 2 lattice gauge theories in the context of Pauli stabilizer codes, we present methodologies for simulating fermions via qubit systems on a two-dimensional square lattice. We investigate the symplectic automorphisms of the Pauli module over the Laurent polynomial ring. This enables us to systematically increase the code distances of stabilizer codes while fixing the rate between encoded logical fermions and physical qubits. We identify a family of stabilizer codes suitable for fermion simulation, achieving code distances of d=2,3,4,5,6,7, allowing correction of any \lfloor \frac{d-1}{2} \rfloor ⌊ d − 1 2 ⌋ -qubit error. In contrast to the traditional code concatenation approach, our method can increase the code distances without decreasing the (fermionic) code rate. In particular, we explicitly show all stabilizers and logical operators for codes with code distances of d=3,4,5. We provide syndromes for all Pauli errors and invent a syndrome-matching algorithm to compute code distances numerically.

Physics↗

Development of a Subchannel Capability for Liquid-Metal Fast Reactors in Pronghorn

This report details the development and demonstration of an entirely new capability in Pronghorn, namely the ability to model liquid-metal fast reactor (LMFR) flow conditions on the engineering scale. We developed two modeling approaches for LMFR that can be used separately or be combined into a hybrid simulation: (1) a modern subchannel capability called Pronghorn-Subchannel for square and hexagonal lattices, and (2) a porous flow capability for LMFR geometries. The report emphasizes the novel aspects of the developed subchannel capability and the interoperability of the subchannel capability, porous flow capability, and multiphysics tools within the multiphysics object oriented simulation environment (MOOSE). Here we demonstrate the ability to: (1) Accurately model subchannel flow in hexagonal lattices; (2) Couple the subchannel flow model to multidimensional finite-element method (FEM) or finite-volume method (FVM) heat conduction models; (3) Model LMFRs using Pronghorn’s porous media FVM approach; (4) Couple porous flow FVM and subchannel models in a single simulation; (5) Explicitly model inter-wrapper flows along with conjugate heat transfer from the intra-element flow; and (6) Demonstrate the numerical robustness of the subchannel algorithm by simulating intra-element flow recirculation in a high-buoyancy, low-flow fuel element.

97 MATHEMATICS AND COMPUTING↗

Machine learning opportunities for nucleosynthesis studies

Nuclear astrophysics is an interdisciplinary field focused on exploring the impact of nuclear physics on the evolution and explosions of stars and the cosmic creation of the elements. While researchers in astrophysics and in nuclear physics are separately using machine learning approaches to advance studies in their fields, there is currently little use of machine learning in nuclear astrophysics. We briefly describe the most common types of machine learning algorithms, and then detail their numerous possible uses to advance nuclear astrophysics, with a focus on simulation-based nucleosynthesis studies. We show that machine learning offers novel, complementary, creative approaches to address many important nucleosynthesis puzzles, with the potential to initiate a new frontier in nuclear astrophysics research.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Geometric remapping of particle distributions in the Discrete Element Model for Sea Ice (DEMSI v0.0)

Abstract. A new sea ice dynamical core, the Discrete Element Model for Sea Ice (DEMSI), is under development for use in coupled Earth system models. DEMSI is based on the discrete element method, which models collections of ice floes as interacting Lagrangian particles. In basin-scale sea ice simulations the Lagrangian motion results in significant convergence and ridging, which requires periodic remapping of sea ice variables from a deformed particle configuration back to an undeformed initial distribution. At the resolution required for Earth system models we cannot resolve individual sea ice floes, so we adopt the sub-grid-scale thickness distribution used in continuum sea ice models. This choice leads to a series of hierarchical tracers depending on ice fractional area or concentration that must be remapped consistently. The circular discrete elements employed in DEMSI help improve the computational efficiency at the cost of increased complexity in the effective element area definitions for sea ice cover that are required for the accurate enforcement of conservation. An additional challenge is the accurate remapping of element values along the ice edge, the location of which varies due to the Lagrangian motion of the particles. In this paper we describe a particle-to-particle remapping approach based on well-established geometric remapping ideas that enforces conservation, bounds preservation, and compatibility between associated tracer quantities, while also robustly managing remapping at the ice edge. One element of the remapping algorithm is a novel optimization-based flux correction that enforces concentration bounds in the case of nonuniform motion. We demonstrate the accuracy and utility of the algorithm in a series of numerical test cases.

58 GEOSCIENCES↗

Studies in astronomical time series analysis: Modeling random processes in the time domain

Random process models phased in the time domain are used to analyze astrophysical time series data produced by random processes. A moving average (MA) model represents the data as a sequence of pulses occurring randomly in time, with random amplitudes. An autoregressive (AR) model represents the correlations in the process in terms of a linear function of past values. The best AR model is determined from sampled data and transformed to an MA for interpretation. The randomness of the pulse amplitudes is maximized by a FORTRAN algorithm which is relatively stable numerically. Results of test cases are given to study the effects of adding noise and of different distributions for the pulse amplitudes. A preliminary analysis of the optical light curve of the quasar 3C 273 is given.

Scargle, J. D.↗

Simulation of large motions of nonuniform beams in orbit. I - The cantilever beam

An algorithm is developed for producing numerical simulations of large motions of a nonuniform cantilever beam in orbit. Special emphasis is given to the effective formulation of equations of motion and to the use of the finite element method to construct modal functions. Finite element methods are used to generate modal functions in such a way as to permit a particularly harmonious relationship to be established between the disciplines of rigid body dynamics and structural analysis. Sufficient information is provided to enable a reader to create, with relatively little effort, his own simulation program; simulation results are reported, both to provide check cases for other investigators and to illustrate certain important facets of the behavior of flexible spacecraft.

Levinson, D. A.↗

Simulation of large motions of nonuniform beams in orbit. II - The unrestrained beam

An algorithm is developed for the numerical simulation of large motions of an unrestrained, nonuniform beam in orbit. Explicit provisions are made for the accommodation of general, physically significant initial conditions and for the specification of control forces in practical terms. The evaluation of certain constants that appear in the equations of motion is considered, the finite element method being used for this purpose. The importance of initial conditions in the study of spacecraft motions is stressed.

Kane, T. R.↗

Measurement accuracies in band-limited extrapolation

The problem of numerical instability associated with extrapolation algorithms is addressed. An attempt is made to estimate the bounds for the acceptable errors and to place a ceiling on the measurement accuracy and computational accuracy needed for the extrapolation. It is shown that in band limited (or visible angle limited) extrapolation the larger effective aperture L' that can be realized from a finite aperture L by over sampling is a function of the accuracy of measurements. It is shown that for sampling in the interval L/b absolute value of xL, b1 the signal must be known within an error e sub N given by e sub N squared approximately = 1/4(2kL') cubed (e/8b L/L')(2kL') where L is the physical aperture, L' is the extrapolated aperture, and k = 2pi lambda.

Kritikos, H. N.↗

An implicit solution of the three-dimensional Navier-Stokes equations for an airfoil spanning a wind tunnel

An implicit finite-difference algorithm is developed for the numerical solution of the incompressible three dimensional Navier-Stokes equations in the non-conservative primitive-variable formulation. The flow field about an airfoil spanning a wind-tunnel is computed. The coordinate system is generated by an extension of the two dimensional body-fitted coordinate generation techniques of Thompson, as well as that of Sorenson, into three dimensions. Two dimensional grids are stacked along a spanwise coordinate defined by a simple analytical function. A Poisson pressure equation for advancing the pressure in time is arrived at by performing a divergence operation on the momentum equations. The pressure at each time-step is calculated on the assumption that continuity be unconditionally satisfied. An eddy viscosity coefficient, computed according to the algebraic turbulence formulation of Baldwin and Lomax, simulates the effects of turbulence.

Moitra, A.↗

Finite element analysis of steadily moving contact fields

By introducing a moving updated Lagrangian observer, this paper develops traveling finite elements with the capacity to handle the global response resulting from steadily moving contact fields. The generality of the results is such that large deformation kinematics and kinetics as well as the full compliment of inertial fields can be handled. To streamline the handling of nonlinear behavior, an elliptically constrained solution algorithm is also developed. Employing this algorithm, the results of several numerical benchmarking studies are presented which illustrate the capacity of the moving updated Lagrangian formulation as well as the potential effects of nonlinearity.

Padovan, J.↗

Estimation of discontinuous coefficients in parabolic systems: Applications to reservoir simulation

Spline based techniques for estimating spatially varying parameters that appear in parabolic distributed systems (typical of those found in reservoir simulation problems) are presented. The problem of determining discontinuous coefficients, estimating both the functional shape and points of discontinuity for such parameters is discussed. Convergence results and a summary of numerical performance of the resulting algorithms are given.

Lamm, P. D.↗

Intersection of parametric surfaces using lookup tables

When primitive structures in the form of parametric surfaces are combined and modified interactively to form complex intersecting surfaces, it becomes important to find the curves of intersection. One must distinguish between finding the shape of the intersection curve, which may only be useful for display purposes, and finding an accurate mathematical representation of the curve, which is important for any meaningful geometric modeling, analysis, design, or manufacturing involving the intersection. The intersection curve between two or more parametric surfaces is important in a variety of computer-aided design and manufacture areas. A few examples are shape design, analysis of groins, design of fillets, and computation of numerically controlled tooling paths. The algorithm presented here provides a mathematical representation of the intersection curve to a specified accuracy. It also provides the database that can simplify operations such as hidden-surface removal, surface rendering, profile identification, and interference or clearance computations.

Hanna, S. L.↗

Retrieval of vertical moisture profiles with microwave radiometry

A statistical correlation technique is applied to the retrieval of vertical moisture profiles from downlooking radiometric measurements of atmospheric radiation at microwave wavelengths. Only an optimum subset of available radiometer channels is selected for estimating water vapor at specific pressure levels. To test its validity the algorithm was applied, in a numerical experiment, to 50 independent tropical radiosondes over a sea surface. It was also used to retrieve continuous sequences of atmospheric moisture profiles from a set of data obtained with a 4-channel microwave radiometer carried aboard an aircraft over a land surface.

Kakar, R. K.↗

High temperature thermomechanical analysis of ceramic coatings

This paper investigates the thermomechanical response of ceramically coated metal parts in elevated thermal environments. This is made possible through the development of an improved finite element algorithm that enables the efficient and stable solution of the inherently nonlinear elastic-creep (inelastic) type thermomechanical field equations associated with high temperature. Based on the improved algorithm, the results of several numerical experiments are presented. These illustrate the significant influence of inelastic behavior in generating residual stress fields.

Padovan, J.↗

A statistical correlation method for the retrieval of atmospheric moisture profiles by microwave radiometry

A statistical correlation technique is applied to the retrieval of vertical moisture profiles under clear-sky conditions from down-looking radiometric measurements of atmospheric radiation at microwave wavelengths. For a given set of channels, the method selects the optimum radiometric channels for estimating water vapor at specific pressure levels between the surface and 300 mb. The water vapor mixing ratio at these pressure levels is then calculated from a linear combination of the selected channel brightness temperatures. To test its validity the algorithm was applied, in a numerical experiment, to fifty independent tropical radiosondes. The rms absolute deviation of the estimated moisture profiles from the actual profiles was comparable to that obtained using an iterative retrieval method reported earlier. The statistical method, however, requires several orders of magnitude less computer time than the iterative method; it is suitable for high speed processing of large amounts of data.

Kakar, R. K.↗

Generalized formulation of a class of explicit and implicit TVD schemes

A one parameter family of second order explicit and implicit total variation diminishing (TVD) schemes is reformulated so that a simpler and wider group of limiters is included. The resulting scheme can be viewed as a symmetrical algorithm with a variety of numerical dissipation terms that are designed for weak solutions of hyperbolic problems. This is a generalization of Roe and Davis's recent works to a wider class of symmetric schemes other than Lax-Wendroff. The main properties of the present class of schemes are that they can be implicit, and when steady state calculations are sought, the numerical solution is independent of the time step.

Yee, H. C.↗