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At least 1,009 records · Page 56

Numerical Analysis Of Interlaminar-Fracture Toughness

Finite-element analysis applied in conjunction with strain-energy and micromechanical concepts. Computational procedure involves local, local-crack-closure, and/or the "unique" local-crack-closure method developed at NASA Lewis Research Center, for mathematical modeling of ENF and MMF. Methods based on three-dimensional finite-element analysis in conjunction with concept of strain-energy-release rate and with micromechanics of composite materials. Assists in interpretation of ENF and MMF fracture tests performed to obtain fracture-toughness parameters, by enabling evaluation of states of stress likely to induce interlaminar fractures.

Chamis, C. C.↗

Sequential Linearization Method for Bound-Constrained Mathematical Programs with Complementarity Constraints

Here, we propose an algorithm for solving bound-constrained mathematical programs with complementarity constraints on the variables. Each iteration of the algorithm involves solving a linear program with complementarity constraints in order to obtain an estimate of the active set. The algorithm enforces descent on the objective function to promote global convergence to B-stationary points. We provide a convergence analysis and preliminary numerical results on a range of test problems. We also study the effect of fixing the active constraints in a bound-constrained quadratic program that can be solved on each iteration in order to obtain fast convergence.

97 MATHEMATICS AND COMPUTING↗

Equivalence of quantum barren plateaus to cost concentration and narrow gorges

Optimizing parameterized quantum circuits (PQCs) is the leading approach to make use of near-term quantum computers. However, very little is known about the cost function landscape for PQCs, which hinders progress towards quantum-aware optimizers. In this work, we investigate the connection between three different landscape features that have been observed for PQCs: (1) exponentially vanishing gradients (called barren plateaus (BPs)), (2) exponential cost concentration about the mean, and (3) the exponential narrowness of minima (called narrow gorges). Here we analytically prove that these three phenomena occur together, i.e., when one occurs then so do the other two. A key implication of this result is that one can numerically diagnose BPs via cost differences rather than via the computationally more expensive gradients. More broadly, our work shows that quantum mechanics rules out certain cost landscapes (which otherwise would be mathematically possible), and hence our results could be interesting from a quantum foundations perspective.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Pauli potential formalism at finite temperature

At zero temperature, the Pauli potential—the functional derivative of the Pauli kinetic energy density functional—is the key to the accuracy of the orbital-free density functional theory (OFDFT) as it is supposed to capture all the effects associated with the Pauli exclusion principle. Here, we extend this concept to finite temperature by defining Pauli free energy and the modified Pauli free energy, both representing the natural generalizations of the Pauli term from zero- T to finite- T . We discuss their physical interpretation, the mathematical nuances, and the applicability, arguing that the modified Pauli potential should be used as an extension of the zero- T counterpart within the OF-DFT framework. Through analytical and numerical methods, we then analyze some of the exact properties concerning the modified Pauli free- and kinetic-energy terms and examine the temperature dependence of the modified Pauli potential.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Deterministic Linear Time for Maximal Poisson‐Disk Sampling using Chocks without Rejection or Approximation

Abstract We show how to sample uniformly within the three‐sided region bounded by a circle, a radial ray, and a tangent, called a “chock.” By dividing a 2D planar rectangle into a background grid, and subtracting Poisson disks from grid squares, we are able to represent the available region for samples exactly using triangles and chocks. Uniform random samples are generated from chock areas precisely without rejection sampling. This provides the first implemented algorithm for precise maximal Poisson‐disk sampling in deterministic linear time. We prove O(n · M(b) log b), where n is the number of samples, b is the bits of numerical precision and M is the cost of multiplication. Prior methods have higher time complexity, take expected time, are non‐maximal, and/or are not Poisson‐disk distributions in the most precise mathematical sense. We fill this theoretical lacuna.

Mitchell, Scott A.↗

Research on an augmented Lagrangian penalty function algorithm for nonlinear programming

The augmented Lagrangian (ALAG) Penalty Function Algorithm for optimizing nonlinear mathematical models is discussed. The mathematical models of interest are deterministic in nature and finite dimensional optimization is assumed. A detailed review of penalty function techniques in general and the ALAG technique in particular is presented. Numerical experiments are conducted utilizing a number of nonlinear optimization problems to identify an efficient ALAG Penalty Function Technique for computer implementation.

Frair, L.↗

Three-dimensional algebraic grid generation

One of the major approaches to numerical grid generation is the explicit algebraic expression of a physical grid as a function of a uniform grid in a rectangular computational coordinate system. The algebraic methods are based on mathematical interpolation, and the primary advantages are speed and directness. The relation between interpolation and grid generation is described. For three-dimensional grid generation, transfinite interpolation using the coordinate control processes developed in the multisurface method and two-boundary technique are advocated. Grid singularities encountered in three dimensions are discussed, and the exploration of multiple overlapping grids is proposed. Some aspects of interactive algebraic grid computation in three dimensions are discussed.

Smith, R. E.↗

Simulation of Airplane and Rocket Trajectories

Simulation and Optimization of Rocket Trajectories program (SORT) contains comprehensive mathematical models for simulating aircraft dynamics, freely falling objects, and many types of ballistic trajectories. Provides high-fidelity, three-degrees-of-freedom simulation for atmospheric and exoatmospheric flight. It numerically models vehicle subsystems and vehicle environment. Used for wide range of simulations. Written in machine-independent FORTRAN 77.

Wahbah, Magdy M.↗

Assigning Damping Parameters To Component Dynamical Modes

Damping parameters found by solving nonlinear optimization problem. Paper discusses assignment of matrices of damping parameters to mathematical models of vibrations and rotations of interconnected flexible components of large, flexible structure. Such models truncated at component level to reduce amount of computation necessary to simulate dynamics of structure numerically at both component and system levels.

Lee, Allan Y.↗

Peculiar Behavior of He II Disturbances due to Sloshing Dynamics Driven by Jitter Accelerations Associated with Slew Motion in Microgravity

The mathematical formulation of Dewar container sloshing dynamics when partially filled with superfluid liquid He 11 driven by the gravity jitter acceleration associated with slew motion in a microgravity environment is studied. Numerical computation of the sloshing dynamics is based on the non-inertia container bound co-ordinate, and solving time-dependent, three-dimensional formulations of partial differential equations subject to initial and boundary conditions. This study discloses the capillary effect of the sloshing dynamics governing the liquid-vapour interface fluctuations driven by the gravity jitter acceleration associated with slew motion, which affects the stability of the fluid system in a microgravity environment. The peculiar behaviour of superfluid helium when reacting to the sloshing dynamics driven by the gravity jitter acceleration associated with slew motion in a microgravity environment is also investigated.

Hung, R. J.↗

Molecular flow venting of a volume with an outgassing or desorbing source

A venting equation commonly used to describe the transient evolution of pressure within a volume containing an outgassing or offgassing source and a restrictive vent conductance under conditions of molecular flow has been solved analytically. Solutions are found for sources of finite thickness characterized by classical diffusion-limited behavior (proportional to inverse square root of time), as well as responses for thick material sources often observed in testing that are characterized by a more general form of power-law decay, up to inverse time behavior associated with surface desorption. Solutions involve evaluating integrals where both numerators and denominators of the integrands diverge with time, making wide-ranging transient solutions difficult to directly compute numerically. Usually, one can avoid evaluating these integrals by assuming quasistatic conditions at long time scales. A novel approach is used in this work to analytically produce solutions by generating bespoke mathematical functions, some of which solve integrals that have apparently had no previous analytical solution.

Michael Woronowicz↗

Molecular flow venting of a volume with an outgassing or desorbing source

"A venting equation commonly used to describe the transient evolution of pressure within a volume containing an outgassing or offgassing source and a restrictive vent conductance under conditions of molecular flow has been solved analytically. Solutions are found for sources of finite thickness characterized by classical diffusion-limited behavior (proportional to inverse square root of time), as well as responses for thick material sources often observed in testing that are characterized by a more general form of power-law decay, up to inverse time behavior associated with surface desorption. Solutions involve evaluating integrals where both numerators and denominators of the integrands diverge with time, making wide-ranging transient solutions difficult to directly compute numerically. Usually, one can avoid evaluating these integrals by assuming quasistatic conditions at long time scales. A novel approach is used in this work to analytically produce solutions by generating bespoke mathematical functions, some of which solve integrals that have apparently had no previous analytical solution."

Michael Woronowicz↗

Towards scaling community detection on distributed-memory heterogeneous systems

Distributed multi-GPU systems pose significant challenges and opportunities for efficient execution of parallel applications. Graph algorithms are generally characterized by irregular memory accesses, low computation to communication ratios, and load balancing problems that are especially hard to address on multi-GPU systems. Graph community detection is an important problem in the emerging domain of graph analytics with numerous applications. In this paper, we present our ongoing work on distributed-memory multi-GPU implementation for graph community detection. Our work parallelizes the widely used (albeit serial) Louvain method on distributed multi-GPU platforms. Supported by an extensive set of experiments on a multi-GPU enabled supercomputer (OLCF Summit) and a single compute node (Nvidia DGX-2®), we demonstrate competitive performance to existing distributed-memory CPU-based implementation, and up to 6.5 better results than Nvidia RAPIDS® CUGRAPH. To the best of our knowledge, this work represents the first effort for community detection on distributed multi-GPU systems. Our approach and related findings can be extended to numerous other iterative graph algorithms on multi-GPU systems.

97 MATHEMATICS AND COMPUTING↗

A Bayesian Deep Learning Approach to Near-Term Climate Prediction

Since model bias and associated initialization shock are serious shortcomings that reduce prediction skills in state-of-the-art decadal climate prediction efforts, we pursue a complementary machine-learning-based approach to climate prediction. The example problem setting we consider consists of predicting natural variability of the North Atlantic sea surface temperature on the interannual timescale in the pre-industrial control simulation of the Community Earth System Model. While previous works have considered the use of recurrent networks such as convolutional LSTMs and reservoir computing networks in this and other similar problem settings, we currently focus on the use of feedforward convolutional networks. In particular, we find that a feedforward convolutional network with a Densenet architecture is able to outperform a convolutional LSTM in terms of predictive skill. Next, we go on to consider a probabilistic formulation of the same network based on Stein variational gradient descent and find that in addition to providing useful measures of predictive uncertainty, the probabilistic (Bayesian) version improves on its deterministic counterpart in terms of predictive skill. Finally, we characterize the reliability of the ensemble of machine learning models obtained in the probabilistic setting by using analysis tools developed in the context of ensemble numerical weather prediction.

54 ENVIRONMENTAL SCIENCES↗

An investigation of Newton-Sketch and subsampled Newton methods

Sketching, a dimensionality reduction technique, has received much attention in the statistics community. In this paper, we study sketching in the context of Newton's method for solving finite-sum optimization problems in which the number of variables and data points are both large. In this work, we study two forms of sketching that perform dimensionality reduction in data space: Hessian subsampling and randomized Hadamard transformations. Each has its own advantages, and their relative tradeoffs have not been investigated in the optimization literature. Additionally, our study focuses on practical versions of the two methods in which the resulting linear systems of equations are solved approximately, at every iteration, using an iterative solver. The advantages of using the conjugate gradient method vs. a stochastic gradient iteration are revealed through a set of numerical experiments, and a complexity analysis of the Hessian subsampling method is presented.

97 MATHEMATICS AND COMPUTING↗

Trainability of ReLU networks and Data-dependent Initialization

Here, in this paper, we study the trainability of rectified linear unit (ReLU) networks at initialization. A ReLU neuron is said to be dead if it only outputs a constant for any input. Two death states of neurons are introduced–tentative and permanent death. A network is then said to be trainable if the number of permanently dead neurons is sufficiently small for a learning task. We refer to the probability of a randomly initialized network being trainable as trainability. We show that a network being trainable is a necessary condition for successful training, and the trainability serves as an upper bound of training success rates. In order to quantify the trainability, we study the probability distribution of the number of active neurons at initialization. In many applications, overspecified or overparameterized neural networks are successfully employed and shown to be trained effectively. With the notion of trainability, we show that overparameterization is both a necessary and a sufficient condition for achieving a zero training loss. Furthermore, we propose a data-dependent initialization method in an overparameterized setting. Numerical examples are provided to demonstrate the effectiveness of the method and our theoretical findings.

97 MATHEMATICS AND COMPUTING↗

Development of local hybrid density functionals to treat self-interaction error and many-electron effects

The goal of this project was to improve density functional theory (DFT) for systems where conventional semilocal approximations are limited by self-interaction error (SIE) and by near-degeneracy or strong many-electron effects. While DFT remains the only broadly practical first-principles framework for large-scale materials simulations, its predictive accuracy is often challenged in situations involving stretched bonds, charge transfer, transition-metal chemistry, magnetic couplings, band gaps, and correlated electronic states. This project addressed these limitations by developing physically grounded and numerically robust exchange–correlation functionals that retain the efficiency of modern DFT while extending its predictive scope.

36 MATERIALS SCIENCE↗

Polar Plate Theory for Orthogonal Anisotropy

Laminated fiber-reinforced (or filamentary) composites are used today for their high strength-to-weight and stiffness-to-weight ratios. However, because of the anisotropic behavior of composites, determining the response on a macroscopic scale is challenging. This is particularly evident in the evaluation of the governing differential equations of a circular disk with the fibers of the lamina oriented with rectilinear orthogonality. This includes any situation involving a composite plate of circular geometry in which out-of-plane displacements due to load are desired, such as fastener pull through loading of a composite plate. Current analysis techniques use numerical methods with rectilinear coordinate systems to solve problems with circular geometry. These analyses over predict plate stiffness by 20% and underpredict failure by 70%. Consequently, there is a need to transform classical composite plate theory to a polar coordinate system. In order to better analyze structures with circular geometries the classical composite plate equations are transformed into the plate equations for a rectilinearly anisotropic composite in polar coordinates. A composite plate is typically a laminate of fibers in rectilinear directions. Subsequent to the lay-tip the necessary geometry is cut out of a rectangular plate. In a similar manner, the derivation of the plate equation starts with the fundamental definitions of strain, displacement and curvature and incorporates the material property angular dependence into the equilibrium equations for a differential polar element. In the transformed state, the stiffness coefficients are no longer constant, adding to the complexity of the governing differential equations. This paper discusses the new derivation and evaluation of the plate equations for a circular composite disk with orthogonal rectilinear anisotropy. The resultant new three partial differential equations, which describe the circular anisotropic plate, can be used to evaluate out-of-plane displacements for given load conditions in design of composite Structures. Without the formation of these unique plate equations, design of such structures is not a precise engineering accomplishment due to the lack of precise design tools. Such structures are over designed to compensate and costly tests need to be performed after production to validate safety. Though impossible to present the mathematical solution within the limits of this paper, the application of the newly derived plate equation in its orthotropic form for a balanced symmetric laminate compared favorably with test results and surpassed the results of standard numerical methods. Within the limitations of the problem foundation the predictive model provides a mechanism for establishing out-of-plane deflection levels for a circular composite plate. Future work in this area should include incorporating the circular composite plate equations in Finite Element Models. The new anisotropic polar plate equations call be utilized as a design tool so that the design more accurately meets the requirements, thus taking full advantage of the weight savings of composites. These accomplishments have not previously been presented to the engineering community nor ever proposed to the IAF. Should the proposed paper be accepted for presentation, attendance is assured.

Bailey, Michelle D.↗