Accelerating the convergence of discretization algorithms
Accelerating convergence of discretization algorithms of approximate solution of nonlinear operator equations
ALGORITHM↗
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An Empirical Quantile Estimation Approach for Chance-Constrained Nonlinear Optimization Problems
We investigate an empirical quantile estimation approach to solve chance-constrained nonlinear optimization problems. Our approach is based on the reformulation of the chance constraint as an equivalent quantile constraint to provide stronger signals on the gradient. In this approach, the value of the quantile function is estimated empirically from samples drawn from the random parameters, and the gradient of the quantile function is estimated via a finite-difference approximation on top of the quantile-function-value estimation. We establish a convergence theory of this approach within the framework of an augmented Lagrangian method for solving general nonlinear constrained optimization problems. The foundation of the convergence analysis is a concentration property of the empirical quantile process, and the analysis is divided based on whether or not the quantile function is differentiable. In contrast to the sampling-and-smoothing approach used in the literature, the method developed in this paper does not involve any smoothing function and hence the quantile-function gradient approximation is easier to implement and there are less accuracy-control parameters to tune. Furthermore, we demonstrate the effectiveness of this approach and compare it with a smoothing method for the quantile-gradient estimation. Numerical investigation shows that the two approaches are competitive for certain problem instances.
Applied Probability↗
Strongly Correlated States of Transition Metal Spin Defects: The Case of an Iron Impurity in Aluminum Nitride
We investigate the electronic properties of an exemplar transition metal impurity in an insulator, with the goal of accurately describing strongly correlated defect states. Here, we consider iron in aluminum nitride, a material of interest for hybrid quantum technologies, and we carry out calculations with quantum embedding methods, density matrix embedding theory (DMET) and quantum defect embedding theory (QDET), and with spin-flip time-dependent density functional theory (TDDFT). We show that both DMET and QDET accurately describe the ground state and low-lying excited states of the defect and that TDDFT yields photoluminescence spectra in agreement with experiments. In addition, we provide a detailed discussion of the convergence of our results as a function of the active space used in the embedding methods, thus defining a protocol to obtain converged data directly comparable with experiments.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Formal convergence characteristics of elliptically constrained incremental Newton-Raphson algorithms
Various aspects of the convergence, uniqueness, and existence properties associated with solutions generated via the elliptically constrained incremental Newton-Raphson (ECINR) algorithm are analyzed. Several theorems are developed, and the formal behavior of the elliptically constrained scheme developed by Padovan (1981) is discussed in detail. Consideration is given to global and local rates of convergence, to the determination of the occurrence of safety zones wherein the algorithm yields inherently convergent results, to formal limitations on the class of functions which the scheme can be applied to solve, and to single and multidimensional formalisms on existence uniqueness and convergence. Special attention is given to functions whose Jacobian matrix exhibit positive, negative, semi and indefinite properties. Several significant advantages of ECINR over the classical INR are mentioned.
Padovan, J.↗
Efficient and accurate computation of the incomplete Airy functions
The incomplete Airy integrals serve as canonical functions for the uniform ray optical solutions to several high-frequency scattering and diffraction problems that involve a class of integrals characterized by two stationary points that are arbitrarily close to one another or to an integration endpoint. Integrals with such analytical properties describe transition region phenomena associated with composite shadow boundaries. An efficient and accurate method for computing the incomplete Airy functions would make the solutions to such problems useful for engineering purposes. In this paper a convergent series solution for the incomplete Airy functions is derived. Asymptotic expansions involving several terms are also developed and serve as large argument approximations. The combination of the series solution with the asymptotic formulae provides for an efficient and accurate computation of the incomplete Airy functions. Validation of accuracy is accomplished using direct numerical integration data.
Constantinides, E. D.↗
A Characteristics Approach to the Finite Element Method
Herein, we present a new method for solving the linear Boltzmann transport equation. Two commonly used and well-understood methods for solving partial differential equations are the method of characteristics (MOC) and the finite element method (FEM). We propose a new method that combines the fundamental concept of the FEM with the analytic solution from the MOC to obtain coefficients for the FEM basis function expansion. Traditionally, coefficients for the FEM basis function expansion are obtained via matrix inversion. Instead, we solve for the coefficients with the MOC and represent the underlying fields with the basis function expansion using these coefficients. We provide a convergence study for our method with results from two sets of FEM basis functions: Gauss-Legendre and Gauss-Lobatto sets. We also compare two different variations of our method categorized as short characteristics and intermediate characteristics.
42 ENGINEERING↗
Multi-strain analysis of Pseudomonas putida reveals the metabolic and genetic diversity of the species
Pseudomonas putida is a gram-negative bacterial species increasingly utilized in biotechnology due to its robust growth, ability to degrade aromatic compounds, solvent tolerance, and genetic tractability. In this study, we report a comprehensive multi-strain analysis of 164 P. putida strains based on the reconstruction of a pan-putida metabolic network and the formulation of strain-specific genome-scale metabolic models (GEMs). We performed whole-genome sequencing and hybrid assembly for 40 strains, contributing a ~8% increase to the available genomic data for P. putida . Furthermore, high-throughput phenotypic profiling using the Biolog phenotype microarray system for 24 strains on 190 unique carbon sources, along with 15 aromatic compounds not present on Biolog plates, yielded 4,920 unique strain-phenotype measurements. These data were leveraged to curate GEMs for 24 representative strains, including a refined model for strain KT2440, which comprised 1,480 genes and 2,191 metabolites, achieving a prediction accuracy of 91.2% in carbon utilization. Systematic comparison of genomes and GEMs revealed both conserved core pathways and significant allelic and functional divergence across strains, highlighting strain-specific variation in aromatic degradation. While pathways for protocatechuate and phenylacetate degradation were widely conserved, metabolic capabilities for compounds such as ferulate, phenol, and cresols varied markedly, suggesting adaptation to distinct ecological niches. Alleleome analysis of enzymes, such as PcaI and PcaJ, revealed distinct, functionally similar clades, indicating possible convergent evolution or horizontal gene transfer. These results provide computable resources and informative models for selecting P. putida strains with desired traits for biomanufacturing and bioremediation and offer insights into the evolution and phylogeny of the P. putida species.
aromatics utilization↗
Adaptive computing techniques
Adaptive local algorithm and convergence speed of multimodal multidimensional function
Schmitt, E.↗
Variational calculations of vibrational properties of ozone
A variational method is used to obtain vibrational-rotational properties for ozone from an experimental quartic force field. Band positions, average structures, matrix elements for calculating infrared intensities, and effective rotational constants are reported for (O-16)3 and its O-18 isotopic species. Also, the degree to which the vibrational energies and properties are converged is investigated as a function of the basis set parameters and basis set size, and of the method of obtaining the Hamiltonian matrix elements. A convenient procedure for assigning the vibrational states is developed for variational vibrational wavefunction expansions.
Carney, G. D.↗
Approximation of Optimal Infinite Dimensional Compensators for Flexible Structures
The infinite dimensional compensator for a large class of flexible structures, modeled as distributed systems are discussed, as well as an approximation scheme for designing finite dimensional compensators to approximate the infinite dimensional compensator. The approximation scheme is applied to develop a compensator for a space antenna model based on wrap-rib antennas being built currently. While the present model has been simplified, it retains the salient features of rigid body modes and several distributed components of different characteristics. The control and estimator gains are represented by functional gains, which provide graphical representations of the control and estimator laws. These functional gains also indicate the convergence of the finite dimensional compensators and show which modes the optimal compensator ignores.
Gibson, J. S.↗
Always-Convergent Iterative Noise Removal and Deconvolution for Image Data
Linear filtering techniques currently used for the restoration of noisy, blurred or otherwise degraded image data are discussed and new techniques related to the iterative techniques of Morrison and van Cittert are developed and implemented. Programs written for the implementation are discussed in the appendices. It is shown that the new techniques are convergent for any system response function, and they are applied to the task of restoring a severely blurred image.
Ioup, G. E.↗
An improved method of Nusselt number calculation
A novel method for calculating the Nusselt number, Nu, in a steady-state Rayleigh-Benard convection problem is presented, in which calculations are done for a square box with constant temperature, free-slip boundary conditions at the top and bottom, and a reflection symmetry along the side walls. The element heat flux is obtained by averaging over the entire element; element heat fluxes are then projected to the adjacent nodes. Compared with previous methods, the approach reduces the calculated depth variation in horizontally averaged flux by more than a factor of 10 and shows more rapid convergence of Nu as a function of grid size.
Ho-Liu, Phyllis↗
Conditioned taste aversion induced by motion is prevented by selective vagotomy in the rat
The role of the vagus nerve in motion-induced conditioned taste aversion (CTA) was studied in hooded rats. Animals with complete, selective gastric vagotomy failed to form conditioned taste aversion after multiple conditioning sessions in which the conditioned stimulus (a cider vinegar solution) was drunk immediately before a 30-min exposure to vertical axis rotation at 150 deg/s. Results are discussed with reference to the use of CTA as a measure of motion-induced 'sickness' or gastrointestinal disturbance, and because motion-induced CTA requires that both the vagus nerve and the vestibular apparatus be intact, in light of the possible convergence of vegal and vestibular functions.
Robert A Fox↗
Preconditioning Operators on Unstructured Grids
We consider systems of mesh equations that approximate elliptic boundary value problems on arbitrary (unstructured) quasi-uniform triangulations and propose a method for constructing optimal preconditioning operators. The method is based upon two approaches: (1) the fictitious space method, i.e., the reduction of the original problem to a problem in an auxiliary (fictitious) space, and (2) the multilevel decomposition method, i.e., the construction of preconditioners by decomposing functions on hierarchical meshes. The convergence rate of the corresponding iterative process with the preconditioner obtained is independent of the mesh step. The preconditioner has an optimal computational cost: the number of arithmetic operations required for its implementation is proportional to the number of unknowns in the problem. The construction of the preconditioning operators for three dimensional problems can be done in the same way.
Nepomnyaschikh, S. V.↗
A Single-Lap Joint Adhesive Bonding Optimization Method Using Gradient and Genetic Algorithms
A natural process for any engineer, scientist, educator, etc. is to seek the most efficient method for accomplishing a given task. In the case of structural design, an area that has a significant impact on the structural efficiency is joint design. Unless the structure is machined from a solid block of material, the individual components which compose the overall structure must be joined together. The method for joining a structure varies depending on the applied loads, material, assembly and disassembly requirements, service life, environment, etc. Using both metallic and fiber reinforced plastic materials limits the user to two methods or a combination of these methods for joining the components into one structure. The first is mechanical fastening and the second is adhesive bonding. Mechanical fastening is by far the most popular joining technique; however, in terms of structural efficiency, adhesive bonding provides a superior joint since the load is distributed uniformly across the joint. The purpose of this paper is to develop a method for optimizing single-lap joint adhesive bonded structures using both gradient and genetic algorithms and comparing the solution process for each method. The goal of the single-lap joint optimization is to find the most efficient structure that meets the imposed requirements while still remaining as lightweight, economical, and reliable as possible. For the single-lap joint, an optimum joint is determined by minimizing the weight of the overall joint based on constraints from adhesive strengths as well as empirically derived rules. The analytical solution of the sin-le-lap joint is determined using the classical Goland-Reissner technique for case 2 type adhesive joints. Joint weight minimization is achieved using a commercially available routine, Design Optimization Tool (DOT), for the gradient solution while an author developed method is used for the genetic algorithm solution. Results illustrate the critical design variables as a function of adhesive properties and convergences of different joints based on the two optimization methods.
Smeltzer, Stanley S., III↗
Optimization Based Efficiencies in First Order Reliability Analysis
This paper develops a method for updating the gradient vector of the limit state function in reliability analysis using Broyden's rank one updating technique. In problems that use commercial code as a black box, the gradient calculations are usually done using a finite difference approach, which becomes very expensive for large system models. The proposed method replaces the finite difference gradient calculations in a standard first order reliability method (FORM) with Broyden's Quasi-Newton technique. The resulting algorithm of Broyden updates within a FORM framework (BFORM) is used to run several example problems, and the results compared to standard FORM results. It is found that BFORM typically requires fewer functional evaluations that FORM to converge to the same answer.
Peck, Jeffrey A.↗
Computations of internal turbulent flow with large separated flow regions
An implicit two-equation turbulence solver in generalized coordinates has been developed and is used in conjunction with the three-dimensional incompressible Navier-Stokes solver, INS3D, to calculate the internal flow in one channel and in an additional channel with a sudden 2:3 expansion. A new and consistent boundary procedure for a low Reynolds number form of the kappa-epsilon turbulence model is chosen to integrate the equations up to the wall. The high Reynolds number form of the equations are integrated using wall functions. The latter approach yields a faster convergence to the steady state solution than the former. For the case of channel flow, both the wall function and wall boundary condition approaches yield results in good agreement with the experimental data. the back-step (sudden expansion) flow is calculated using wall function approach. The predictions are in reasonable agreement with the experimental data.
Kaul, U. K.↗
Numerical evaluation of the incomplete airy functions and their application to high frequency scattering and diffraction
The incomplete Airy integrals serve as canonical functions for the uniform ray optical solutions to several high frequency scattering and diffraction problems that involve a class of integrals characterized by two stationary points that are arbitrarily close to one another or to an integration endpoint. Integrals of such analytical properties describe transition region phenomena associated with composite shadow boundaries. An efficient and accurate method for computing the incomplete Airy functions would make the solutions to such problems useful for engineering purposes. Here, a convergent series solution form for the incomplete Airy functions is derived. Asymptotic expansions involving several terms were also developed and serve as large argument approximations. The combination of the series solution form with the asymptotic formulae provides for an efficient and accurate computation of the incomplete Airy functions. Validation of accuracy is accomplished using direct numerical integration data.
Constantinides, E. D.↗