Convergence Acceleration Techniques Research Articles

Annular Newtonian Poiseuille flow with pressure-dependent wall slip

We investigate the effect of pressure-dependent wall slip on the steady Newtonian annular Poiseuille flow employing Navier’s slip law with a slip parameter that varies exponentially with pressure. The dimensionless governing equations and accompanying auxiliary conditions are solved analytically up to second order by implementing a regular perturbation scheme in terms of the small dimensionless pressure-dependence slip parameter. An explicit formula for the average pressure drop, required to maintain a constant volumetric flowrate, is also derived. This is suitably post-processed by applying a convergence acceleration technique to increase the accuracy of the original perturbation series. The effects of pressure-dependent wall slip are more pronounced when wall slip is weak. However, as the slip coefficient increases, these effects are moderated and eventually eliminated as the perfect slip case is approached. The results show that the average pressure drop remains practically constant until the Reynolds number becomes sufficiently large. It is worth noting that all phenomena associated with pressure-dependent wall slip are amplified as the annular gap is reduced.

Instantons in ϕ4 theories: Transseries, virial theorems, and numerical aspects

We discuss numerical aspects of instantons in two- and three-dimensional ϕ4 theories with an internal O(N) symmetry group, the so-called N-vector model. By combining asymptotic transseries expansions for large arguments with convergence acceleration techniques, we obtain high-precision values for certain integrals of the instanton that naturally occur in loop corrections around instanton configurations. Knowledge of these numerical properties is necessary in order to evaluate corrections to the large-order factorial growth of perturbation theory in ϕ4 theories. The results contribute to the understanding of the mathematical structures underlying the instanton configurations. Published by the American Physical Society 2024

On the implementation in Abaqus of the global–local iterative coupling and acceleration techniques

This paper presents results and convergence study of the Global–Local Iterative Coupling through the implementation in the commercial software Abaqus making use of the co-simulation engine. A hierarchical modeling and simulation approach is often required to alleviate modeling burdens. Particular focus has been devoted here on convergence acceleration and performance optimization. Two applications in statics with nonlinear material behavior and geometrically nonlinear formulation are considered here: first a holed curved plate under traction with elastic–plastic material, then a pre-stressed bolted joint connecting two plates between each other and subjected to traction load. Three different convergence acceleration techniques are compared in terms of convergence performance and accuracy. An inexact solver strategy is proposed to improve computing time performance. The results show promising results for the coupling technology and constitute a step forward in the availability of non-intrusive multi-scale modeling capabilities for complex structures and assemblies.

A computational model for generating multihyperuniform distributions for realistic antenna array and metasurface designs

This paper is aimed at studying the concept of multihyperuniformity and applying it to the design of shared-aperture antenna arrays and multi-bit coding metasurfaces. By formulating the theoretical foundation and essential geometric aspects related to this distribution, we create a computational model capable of generating both single hyperuniform and multihyperuniform distributions. Moreover, we put forward specific convergence acceleration techniques that effectively minimize computational time, particularly when dealing with a substantial number of elements. Considering the shape, size, and corresponding geometric constraints of the elements, we generate patterns suitable for practical designs of antenna arrays, as well as metasurfaces. We present an example of a multihyperuniform shared-aperture antenna array as illustration. Specifically, a penta-band circular patch antenna array operating in the C-band with low sidelobes and high realized gain over five different frequency bands is demonstrated. The computational model is also implemented for the design of a multi-bit coding metasurface with scattering reduction attributes.

Thermal conductivity of glasses: first-principles theory and applications

Predicting the thermal conductivity of glasses from first principles has hitherto been a very complex problem. The established Allen-Feldman and Green-Kubo approaches employ approximations with limited validity—the former neglects anharmonicity, the latter misses the quantum Bose-Einstein statistics of vibrations—and require atomistic models that are very challenging for first-principles methods. Here, we present a protocol to determine from first principles the thermal conductivity κ(T) of glasses above the plateau (i.e., above the temperature-independent region appearing almost without exceptions in the κ(T) of all glasses at cryogenic temperatures). The protocol combines the Wigner formulation of thermal transport with convergence-acceleration techniques, and accounts comprehensively for the effects of structural disorder, anharmonicity, and Bose-Einstein statistics. We validate this approach in vitreous silica, showing that models containing less than 200 atoms can already reproduce κ(T) in the macroscopic limit. We discuss the effects of anharmonicity and the mechanisms determining the trend of κ(T) at high temperature, reproducing experiments at temperatures where radiative effects remain negligible.

Convergence Acceleration of the Harmonic Balance Method Using a Time-Level Preconditioner

The harmonic balance method is nowadays widely applied for numerically solving problems that are known to possess time-periodic solutions. Key reasons for its success are its wide range of applicability, relative ease of implementation, and computational efficiency compared to time-accurate approaches. The computational efficiency of the harmonic balance method is partly derived from the fact that it searches directly for a periodic solution instead of integrating the governing equations in time until a periodic solution is reached. Convergence acceleration techniques such as multigrid, implicit residual smoothing, and local time stepping may also be used to improve the efficiency of the harmonic balance method. This paper considers another option for accelerating convergence, namely, a novel time-level preconditioner that can be applied to the harmonic balance residual locally in each computational cell. The benefit of employing this preconditioner is analyzed both from a theoretical perspective, by performing a rigorous stability analysis based on the linearized Euler equations, and from a numerical perspective, by applying it to two test cases.

Mixed finite element approximations of a singular elliptic problem based on some anisotropic and hp-adaptive curved quarter-point elements

Mixed finite element methods are applied to a Poisson problem with a singularity at a boundary point. The approximation spaces are based on quarter-point elements, the shape functions inheriting the singular behavior of their quadratic geometric maps. Two mesh scenarios are considered, by fixing some macro quarter-point elements at the coarse level, and subdividing them by mapping uniformly refined square meshes on the master element by their corresponding geometric transforms. For eight-noded coarse quadrilateral quarter-point elements, placing two mid-side nodes near the singular vertex, the radial singularity is exactly captured along element edges, and their refinements reveal shape regular curved meshes. For an improved version, using collapsed quadrilateral quarter-point elements obtained by reducing one of the quadrilateral element edges to the singular point, the radial singularity is captured inside the coarse macro elements as well. Their uniform refinement generates anisotropic meshes, grading towards the singular point. The assembly of the required H(div)-conforming approximation spaces based on these kinds of meshes are described. Results for a typical test problem demonstrate superior effectiveness of the proposed techniques for convergence acceleration, when confronted with usual affine finite elements, for h, p and hp-adaptive refinements. Especially, collapsed quarter-point elements applied to the singular problem reveal accuracy rates equivalent to standard regular contexts, of smooth solutions discretized on uniform affine meshes.

Locally adaptive pseudo-time stepping for high-order Flux Reconstruction

This paper proposes a novel locally adaptive pseudo-time stepping convergence acceleration technique for dual time stepping which is a common integration method for solving unsteady low-Mach preconditioned/incompressible Navier-Stokes formulations. In contrast to standard local pseudo-time stepping techniques that are based on computing the local pseudo-time steps directly from estimates of the local Courant-Friedrichs-Lewy limit, the proposed technique controls the local pseudo-time steps using local truncation errors which are computed with embedded pair RK schemes. The approach has three advantages. First, it does not require an expression for the characteristic element size, which are difficult to obtain reliably for curved mixed-element meshes. Second, it allows a finer level of locality for high-order nodal discretisations, such as FR, since the local time-steps can vary between solution points and field variables. Third, it is well-suited to being combined with P-multigrid convergence acceleration. Results are presented for a laminar 2D cylinder test case at Re=100. A speed-up factor of 4.16 is achieved compared to global pseudo-time stepping with an RK4 scheme, while maintaining accuracy. When combined with P-multigrid convergence acceleration a speed-up factor of over 15 is achieved. Detailed analysis of the results reveals that pseudo-time steps adapt to element size/shape, solution state, and solution point location within each element. Finally, results are presented for a turbulent 3D SD7003 airfoil test case at Re=60,000. Speed-ups of similar magnitude are observed, and the flow physics is found to be in good agreement with previous studies.

Novel multilevel techniques for convergence acceleration in the solution of systems of equations arising from RBF-FD meshless discretizations

The present paper develops two new techniques, namely additive correction multicloud (ACMC) and smoothed restriction multicloud (SRMC), for the efficient solution of systems of equations arising from Radial Basis Function-generated Finite Difference (RBF-FD) meshless discretizations of partial differential equations (PDEs). RBF-FD meshless methods employ arbitrary distributed nodes, without the need to generate a mesh, for the numerical solution of PDEs. The proposed techniques are specifically designed for the RBF-FD data structure and employ simple restriction and interpolation strategies in order to obtain a hierarchy of coarse-level node distributions and the corresponding correction equations.Both techniques are kept as simple as possible in terms of code implementation, which is an important feature of meshless methods. The techniques are verified on 2D and 3D Poisson equations, defined on non-trivial domains , showing very high benefits in terms of both time consumption and work to convergence when comparing the present techniques to the most common solver approaches. These benefits make the RBF-FD approach competitive with standard grid-based approaches when the number of nodes is very high, allowing large size problems to be tackled by the RBF-FD method.

A multiscale method for semi-linear elliptic equations with localized uncertainties and non-linearities

A multiscale numerical method is proposed for the solution of semi-linear elliptic stochastic partial differential equations with localized uncertainties and non-linearities, the uncertainties being modeled by a set of random parameters. It relies on a domain decomposition method which introduces several subdomains of interest (called patches) containing the different sources of uncertainties and non-linearities. An iterative algorithm is then introduced, which requires the solution of a sequence of linear global problems (with deterministic operators and uncertain right-hand sides), and non-linear local problems (with uncertain operators and/or right-hand sides) over the patches. Non-linear local problems are solved using an adaptive sampling-based least-squares method for the construction of sparse polynomial approximations of local solutions as functions of the random parameters. Consistency, convergence and robustness of the algorithm are proved under general assumptions on the semi-linear elliptic operator. A convergence acceleration technique (Aitken’s dynamic relaxation) is also introduced to speed up the convergence of the algorithm. The performances of the proposed method are illustrated through numerical experiments carried out on a stationary non-linear diffusion-reaction problem.

Regularized nonlinear acceleration

We describe a convergence acceleration technique for unconstrained optimization problems. Our scheme computes estimates of the optimum from a nonlinear average of the iterates produced by any optimization method. The weights in this average are computed via a simple linear system, whose solution can be updated online. This acceleration scheme runs in parallel to the base algorithm, providing improved estimates of the solution on the fly, while the original optimization method is running. Numerical experiments are detailed on classical classification problems.

Three-Dimensional Elastic Analysis of a Structure with Holes Using Accelerated Coupling-Matrix-Free Iterative s-Version FEM

Some improvements of the coupling-matrix-free iterative s-version finite element method (FEM) to shorten its computational time are proposed. Then, the proposed method is applied to three-dimensional stress concentration problems. For sufficiently small computational time for practical use, two key techniques are introduced. First, the iteration is accelerated drastically by using the proposed convergence acceleration techniques. Secondly, stress transfers between global and local meshes are accelerated considerably by a bucket search algorithm. The proposed method was more than one hundred times faster than the straightforward algorithm of the coupling-matrix-free iterative s-version FEM.

Positivity-preserving dual time stepping schemes for gas dynamics

A new approach at discretizing the temporal derivative of the Euler equations is here presented which can be used with dual time stepping. The temporal discretization stencil is derived along the lines of the Cauchy–Kowalevski procedure resulting in cross differences in spacetime but with some novel modifications which ensure the positivity of the discretization coefficients. It is then shown that the so-obtained spacetime cross differences result in changes to the wave speeds and can thus be incorporated within Roe or Steger–Warming schemes (with and without reconstruction–evolution) simply by altering the eigenvalues. The proposed approach is advantaged over alternatives in that it is positivity-preserving for the Euler equations. Further, it yields monotone solutions near discontinuities while exhibiting a truncation error in smooth regions less than the one of the second- or third-order accurate backward-difference-formula (BDF) for either small or large time steps. The high resolution and positivity preservation of the proposed discretization stencils are independent of the convergence acceleration technique which can be set to multigrid, preconditioning, Jacobian-free Newton–Krylov, block-implicit, etc. Thus, the current paper also offers the first implicit integration of the time-accurate Euler equations that is positivity-preserving in the strict sense (that is, the density and temperature are guaranteed to remain positive). This is in contrast to all previous positivity-preserving implicit methods which only guaranteed the positivity of the density, not of the temperature or pressure. Several stringent reacting and inert test cases confirm the positivity-preserving property of the proposed method as well as its higher resolution and higher computational efficiency over other second-order and third-order implicit temporal discretization strategies.

CERES: An ab initio code dedicated to the calculation of the electronic structure and magnetic properties of lanthanide complexes.

We have developed and implemented a new ab initio code, Ceres (Computational Emulator of Rare Earth Systems), completely written in C++11, which is dedicated to the efficient calculation of the electronic structure and magnetic properties of the crystal field states arising from the splitting of the ground state spin-orbit multiplet in lanthanide complexes. The new code gains efficiency via an optimized implementation of a direct configurational averaged Hartree-Fock (CAHF) algorithm for the determination of 4f quasi-atomic active orbitals common to all multi-electron spin manifolds contributing to the ground spin-orbit multiplet of the lanthanide ion. The new CAHF implementation is based on quasi-Newton convergence acceleration techniques coupled to an efficient library for the direct evaluation of molecular integrals, and problem-specific density matrix guess strategies. After describing the main features of the new code, we compare its efficiency with the current state-of-the-art ab initio strategy to determine crystal field levels and properties, and show that our methodology, as implemented in Ceres, represents a more time-efficient computational strategy for the evaluation of the magnetic properties of lanthanide complexes, also allowing a full representation of non-perturbative spin-orbit coupling effects. © 2017 Wiley Periodicals, Inc.

Convergence acceleration of continuous adjoint solvers using a reduced‐order model

SummaryA novel acceleration technique using a reduced‐order model is presented to speed up convergence of continuous adjoint solvers. The acceleration is achieved by projecting to an improved solution within an iterative process solely using early solution results. This is achieved by forming basis vectors from early iteration adjoint solutions to perform model order reduction of the adjoint equations. The reduced‐order model of the adjoint equations is then substituted into the full‐order discretized governing equations to determine weighting coefficients for each basis vector. With these coefficients, a linear combination of the basis vectors is used to project to an improved solution. The method is applied to 3 inviscid quasi‐1D nozzle flow cases including fully subsonic flow, subsonic inlet to supersonic outlet flow, and transonic flow with a shock. Significant cost reductions are achieved for a single application as well as repeated applications of the convergence acceleration technique.

Optimal Run Strategies in Monte Carlo Iterated Fission Source Simulations

The method of successive generations used in Monte Carlo simulations of nuclear reactor models is known to suffer from intergenerational correlation between the spatial locations of fission sites. One consequence of the spatial correlation is that the convergence rate of the variance of the mean for a tally becomes worse than O(N–1). In this work, we consider how the true variance can be minimized given a total amount of work available as a function of the number of source particles per generation, the number of active/discarded generations, and the number of independent simulations. We demonstrate through both analysis and simulation that under certain conditions the solution time for highly correlated reactor problems may be significantly reduced either by running an ensemble of multiple independent simulations or simply by increasing the generation size to the extent that it is practical. However, if too many simulations or too large a generation size is used, the large fraction of source particles discarded can result in an increase in variance. We also show that there is a strong incentive to reduce the number of generations discarded through some source convergence acceleration technique. Furthermore, we discuss the efficient execution of large simulations on a parallel computer; we argue that several practical considerations favor using an ensemble of independent simulations over a single simulation with very large generation size.

Convergence Acceleration of Fluid Dynamics Solvers Using a Reduced-Order Model

A new method based on reduced-order modeling is presented for the purpose of accelerating the convergence of an iterative solver via solution prediction in the framework of a computational fluid dynamics solver. Using a number of flow solutions as snapshots at preconvergent iterations of the explicit time-marching solver, the reduced-order-modeling-based acceleration technique is used to project to a more accurate solution. The method is first applied to accelerate the convergence of an incompressible Navier–Stokes solver, and the classical two-dimensional lid-driven cavity flow case is revisited for this purpose. Next, the proposed convergence acceleration technique is used in the framework of a density-based computational fluid dynamics solver, and subsonic as well as transonic (inviscid) flows over the NACA 0012 airfoil are studied. Additionally, the performance of the proposed convergence acceleration technique is investigated for turbulent transonic flow over the RAE 2822 airfoil.

로터 트랙 발란스(RTB) 파라미터 최적화를 위한 비선형 모델링 및 GA 기법 적용 연구

본 연구는 비선형 응답모델과 실수기반의 혼합형 유전자 알고리즘을 적용하여 로터의 트?-발란스(RTB) 기법을 개발하는 데 목적이 있다. 트?-발란스 조절 파라미터의 변화에 따른 트림해석 결과를 이용하여 2차의 근사함수를 이용하는 비선형 응답모델을 개발하였다. 트?편차와 기체의 진동응답을 최소화하기 위해 균형추 무게, 트림 탭(Trim Tab) 및 피치링크 길이를 최적화하기 위한 비선형계획 문제를 정식화하였다. 정식화 결과는 수렴성 향상을 위해 군집최적화 기법을 실변수기반의 유전자 알고리즘에 통합한 혼합형 유전자 기법을 사용함으로써 효율적인 해석이 가능하였다. 비선형 모델을 이용한 본 연구의 방법을 선형모델의 결과와 비교하여 본 연구의 방법을 검증하였으며 비선형모델을 사용하는 경우 선형모델의 결과보다 향상된 응답특성을 계산할 수 있음을 밝혔다. This paper intends to develop the rotor track and balance (RTB) algorithm using the nonlinear RTB models and a real-coded hybrid genetic algorithm. The RTB response data computed using the trim solutions with variation of the adjustment parameters have been used to build nonlinear RTB models based on the quadratic interpolation functions. Nonlinear programming problems to minimize the track deviations and the airframe vibration responses have been formulated to find optimum settings of balance weights, trim-tab deflections, and pitch-link lengths of each blade. The results are efficiently resolved using the real-coded genetic algorithm hybridized with the particle swarm optimization techniques for convergence acceleration. The nonlinear RTB models and the optimized RTB parameters have been compared with those computed using the linear models to validate the proposed techniques. The results showed that the nonlinear models lead to more accurate models and reduced RTB responses than the linear counterpart.

Accelerating the convergence of higher-order coupled cluster methods.

The problem of the generally inferior convergence behavior of higher-order coupled cluster methods, such as CCSDT and CCSDTQ, compared to CCSD is analyzed in terms of Møller-Plesset perturbation theory. A new structure for the CCSDT and CCSDTQ equations (and various approximations of these) is proposed which reorders contributions between the various cluster amplitudes and emphasizes lower-order corrections to the energy at each iteration. Numerical testing of the proposed method compared to the widely used direct inversion in the iterative subspace convergence acceleration technique shows significant improvement in the rate of convergence and total time-to-solution, especially for methods including quadruple excitations.

Fast arbitrary order moments and arbitrary precision solution of the general rate model of column liquid chromatography with linear isotherm

Algorithms and software are presented for efficiently computing reference solutions of the general rate model with proven error bounds. Moreover, algorithms and software are presented for efficiently computing moments of arbitrary order. The methods are based on numerical inverse Laplace transform, and support both quasi-stationary and dynamic linear binding models. The inlet concentration profiles are treated in a most general way using piecewise cubic polynomials. Algorithmic differentiation obviates manual derivation of the required derivatives. Arbitrary precision arithmetics are applied for minimizing numerical roundoff errors, and several convergence acceleration techniques are evaluated. The implemented software package is freely available as open source on GitHub.