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Abstract This paper describes a novel partitioned algorithm for fluid–structure interaction (FSI) problems that couples the motion of rigid bodies and incompressible flow. This is the first partitioned algorithm that remains stable and second-order accurate, without sub-time-step iterations, for very light, and even zero-mass, bodies in three dimensions. This new added-mass partitioned (AMP) algorithm extends the previous developments in [1,2] by generalizing the added-damping tensors to account for arbitrary three-dimensional rotations, and by employing a general quadrature for the surface integral over a rigid body to derive the discrete AMP interface condition for the fluid pressure. Stability analyses for two three-dimensional model problems show that the algorithm remains stable for bodies of any mass when applied to the relevant model problems. The resulting AMP algorithm is implemented in parallel using a moving composite grid framework to treat one or more rigid bodies in complex three-dimensional configurations. The new three-dimensional algorithm is verified and validated though several benchmark problems, including the motion of a sphere in a viscous incompressible fluid and the interaction of a bi-leaflet mechanical heart valve and a pulsating fluid. Numerical simulations confirm the predictions of the stability analysis even for complex problems, and show that the AMP algorithm remains stable, without sub-iterations, for light and even zero-mass three-dimensional rigid bodies of general shape. These benchmark problems are further used to examine the parallel performance of the algorithm and to investigate the conditioning of the linear system for the pressure including the newly derived AMP interface conditions. Highlights • A partitioned FSI scheme for incompressible flow and rigid bodies is extended to 3D. • Stability for simple geometries is proved using 3D model problems. • Numerical results confirm stability and accuracy for light bodies of general shapes. • A benchmark for a bi-leaflet mechanical heart valve is designed and conducted. • Refinement studies for the heart valve are provided. [ABSTRACT FROM AUTHOR]

In this paper we introduce an efficient algorithm for identifying conductive objects using induction data derived from eddy currents. Our method consists of first extracting geometric features from the induction data and then matching them to precomputed data for known objects from a given dictionary. The matching step relies on fundamental properties of conductive polarization tensors and new invariance properties introduced in this paper. A new shape identification scheme is developed and tested in numerical simulations in the presence of measurement noise. Resolution and stability properties of the proposed identification algorithm are investigated. [ABSTRACT FROM AUTHOR]

In this paper, we develop a shape optimization-based algorithm for the electrical impedance tomography (EIT) problem of determining a piecewise constant conductivity on a polygonal partition from boundary measurements. The key tool is to use a distributed shape derivative of a suitable cost functional with respect to movements of the partition. Numerical simulations showing the robustness and accuracy of the method are presented for simulated test cases in two dimensions. [ABSTRACT FROM AUTHOR]

Hybrid polynomial correlated function expansion (H-PCFE) is a novel metamodel formulated by coupling polynomial correlated function expansion (PCFE) and Kriging. Unlike commonly available metamodels, H-PCFE performs a bi-level approximation and hence, yields more accurate results. However, till date, it is only applicable to medium scaled problems. In order to address this apparent void, this paper presents an improved H-PCFE, referred to as locally refined hp – adaptive H-PCFE. The proposed framework computes the optimal polynomial order and important component functions of PCFE, which is an integral part of H-PCFE, by using global variance based sensitivity analysis. Optimal number of training points are selected by using distribution adaptive sequential experimental design. Additionally, the formulated model is locally refined by utilizing the prediction error, which is inherently obtained in H-PCFE. Applicability of the proposed approach has been illustrated with two academic and two industrial problems. To illustrate the superior performance of the proposed approach, results obtained have been compared with those obtained using hp – adaptive PCFE. It is observed that the proposed approach yields highly accurate results. Furthermore, as compared to hp – adaptive PCFE, significantly less number of actual function evaluations are required for obtaining results of similar accuracy. [ABSTRACT FROM AUTHOR]

Abstract: In this paper, we consider the problem of generating independent samples from a conditional distribution when independent samples from the prior distribution are available. Although there are exact methods for sampling from the posterior (e.g. Markov chain Monte Carlo or acceptance/rejection), these methods tend to be computationally demanding when evaluation of the likelihood function is expensive, as it is for most geoscience applications. As an alternative, in this paper we discuss deterministic mappings of variables distributed according to the prior to variables distributed according to the posterior. Although any deterministic mappings might be equally useful, we will focus our discussion on a class of algorithms that obtain implicit mappings by minimization of a cost function that includes measures of data mismatch and model variable mismatch. Algorithms of this type include quasi-linear estimation, randomized maximum likelihood, perturbed observation ensemble Kalman filter, and ensemble of perturbed analyses (4D-Var). When the prior pdf is Gaussian and the observation operators are linear, we show that these minimization-based simulation methods solve an optimal transport problem with a nonstandard cost function. When the observation operators are nonlinear, however, the mapping of variables from the prior to the posterior obtained from those methods is only approximate. Errors arise from neglect of the Jacobian determinant of the transformation and from the possibility of discontinuous mappings. [Copyright &y& Elsevier]

Anisotropic metric-based mesh adaptation has proved its efficiency to reduce the CPU time of steady and unsteady simulations while improving their accuracy. However, its extension to time-dependent problems with body-fitted moving geometries is far from straightforward. This paper establishes a well-founded framework for multiscale mesh adaptation of unsteady problems with moving boundaries. This framework is based on a novel space–time analysis of the interpolation error, within the continuous mesh theory. An optimal metric field, called ALE metric field, is derived, which takes into account the movement of the mesh during the adaptation. Based on this analysis, the global fixed-point adaptation algorithm for time-dependent simulations is extended to moving boundary problems, within the range of body-fitted moving meshes and ALE simulations. Finally, three dimensional adaptive simulations with moving boundaries are presented to validate the proposed approach. [ABSTRACT FROM AUTHOR]

Abstract: High-order methods that can resolve interactions of flow-disturbances with shock waves are critical for reliable numerical simulation of shock wave and turbulence interaction. Such problems are not well understood due to the limitations of numerical methods. Most of the popular shock-capturing methods are only first-order accurate at the shock and may incur spurious numerical oscillations near the shock. Shock-fitting algorithms have been proposed as an alternative which can achieve uniform high-order accuracy and can avoid possible spurious oscillations incurred in shock-capturing methods by treating shocks as sharp interfaces. We explore two ways for shock-fitting: conventional moving grid set-up and a new fixed grid set-up with front tracking. In the conventional shock-fitting method, a moving grid is fitted to the shock whereas in the newly developed fixed grid set-up the shock front is tracked using Lagrangian points and is free to move across the underlying fixed grid. Different implementations of shock-fitting methods have been published in the literature. However, uniform high-order accuracy of various shock-fitting methods has not been systematically established. In this paper, we carry out a rigorous grid-convergence analysis on different variations of shock-fitting methods with both moving and fixed grids. These shock-fitting methods consist of different combinations of numerical methods for computing flow away from the shock and those for computing the shock movement. Specifically, we consider fifth-order upwind finite-difference scheme and shock-capturing WENO schemes with conventional shock-fitting and show that a fifth-order convergence is indeed achieved for a canonical one-dimensional shock-entropy wave interaction problem. We also show that the method of finding shock velocity from one characteristic relation and Rankine–Hugoniot jump condition performs better than the other methods of computing shock velocities. A high-order front-tracking implementation of shock-fitting is also presented in this paper and nominal rate of convergence is shown. The front-tracking results are validated by comparing to results from the conventional shock-fitting method and a linear-interaction analysis for a two-dimensional shock disturbance interaction problem. [Copyright &y& Elsevier]

A mass-conserving lattice Boltzmann method (LBM) for multiphase flows is presented in this paper. The proposed LBM improves a previous model (Lee and Liu, 2010 [21] ) in terms of mass conservation, speed-up, and efficiency, and also extends its capabilities for implementation on non-uniform grids. The presented model consists of a phase-field lattice Boltzmann equation (LBE) for tracking the interface between different fluids and a pressure-evolution LBM for recovering the hydrodynamic properties. In addition to the mass conservation property and the simplicity of the algorithm, the advantages of the current phase-field LBE are that it is an order of magnitude faster than the previous interface tracking LBE proposed by Lee and Liu (2010) [21] and it requires less memory resources for data storage. Meanwhile, the pressure-evolution LBM is equipped with a multi-relaxation-time (MRT) collision operator to facilitate attainability of small relaxation rates thereby allowing simulation of multiphase flows at higher Reynolds numbers. Additionally, we reformulate the presented MRT-LBM on nonuniform grids within an adaptive mesh refinement (AMR) framework. Various benchmark studies such as a rising bubble and a falling drop under buoyancy, droplet splashing on a wet surface, and droplet coalescence onto a fluid interface are conducted to examine the accuracy and versatility of the proposed AMR-LBM. The proposed model is further validated by comparing the results with other LB models on uniform grids. A factor of about 20 in savings of computational resources is achieved by using the proposed AMR-LBM. As a more demanding application, the Kelvin–Helmholtz instability (KHI) of a shear-layer flow is investigated for both density-matched and density-stratified binary fluids. The KHI results of the density-matched fluids are shown to be in good agreement with the benchmark AMR results based on the sharp-interface approach. When a density contrast between the two fluids exists, a typical chaotic structure in the flow field is observed at a Reynolds number of 10000, which indicates that the proposed model is a promising tool for direct numerical simulation of two-phase flows. [ABSTRACT FROM AUTHOR]

In the paper, we develop the new conservative characteristic finite difference methods (C-CFD) for the atmospheric aerosol transport problems. We propose the time second-order and spatial high-order conservative characteristic finite difference methods for the aerosol vertical advection–diffusion process and the two-dimensional conservative characteristic finite difference methods for aerosol horizontal transport process in the second-order splitting algorithm. Based on the characteristic form of advection–diffusion equations tracking back along the characteristic curve, we treat the integrals over the tracking cells at the previous time level by the conservative interpolations and propose to treat the diffusion terms by the average along the characteristics, where the high-order discrete fluxes are obtained by approximating the cumulative mass function and are continuous at the tracking points. The important feature is that the proposed C-CFD schemes preserve mass and have second-order accuracy in time and high-order accuracy in space. Numerical tests are taken to show the accuracy in time and space and mass conservation of our C-CFD schemes, compared with the standard CFD method. A real case of air quality modelling during the 2008 Beijing Olympics and a severe haze in North China are further simulated and analyzed by using our C-CFD algorithm. Simulated results are in good agreement with observations. The developed C-CFD algorithm can be used for efficiently solving large scale atmospheric aerosol transport problems. [ABSTRACT FROM AUTHOR]

This paper is concerned with a comparison of two methods of treating solid wall boundaries in the weakly compressible (SPH) method. They have been chosen because of their wide use in simulations. These methods are the boundary force particles of Monaghan and Kajtar [24] and the use of layers of fixed boundary particles. The latter was first introduced by Morris et al. [26] but has since been improved by Adami et al. [1] whose algorithm involves interpolating the pressure and velocity from the actual fluid to the boundary particles. For each method, we study the effect of the density diffusive terms proposed by Molteni and Colagrossi [19] and modified by Antuono et al. [3] . We test the methods by a series of simulations commencing with the time-dependent spin-down of fluid within a cylinder and the behaviour of fluid in a box subjected to constant acceleration at an angle to the walls of the box, and concluding with a dam break over a triangular obstacle. In the first two cases the results from the two methods can be compared to analytical solutions while, in the latter case, they can be compared with experiments and other methods. These results show that the method of Adami et al. together with density diffusion is in very satisfactory agreement with the experimental results and is, overall, the best of the methods discussed here. [ABSTRACT FROM AUTHOR]

Parametric uncertainties are encountered in the simulations of many physical systems, and may be reduced by an inverse modeling procedure that calibrates the simulation results to observations on the real system being simulated. Following Bayes' rule, a general approach for inverse modeling problems is to sample from the posterior distribution of the uncertain model parameters given the observations. However, the large number of repetitive forward simulations required in the sampling process could pose a prohibitive computational burden. This difficulty is particularly challenging when the posterior is multimodal. We present in this paper an adaptive importance sampling algorithm to tackle these challenges. Two essential ingredients of the algorithm are: 1) a Gaussian mixture (GM) model adaptively constructed as the proposal distribution to approximate the possibly multimodal target posterior, and 2) a mixture of polynomial chaos (PC) expansions, built according to the GM proposal, as a surrogate model to alleviate the computational burden caused by computational-demanding forward model evaluations. In three illustrative examples, the proposed adaptive importance sampling algorithm demonstrates its capabilities of automatically finding a GM proposal with an appropriate number of modes for the specific problem under study, and obtaining a sample accurately and efficiently representing the posterior with limited number of forward simulations. [ABSTRACT FROM AUTHOR]

In this paper, an improved SPH model for multiphase flows with complex interfaces and large density differences is developed. The multiphase SPH model is based on the assumption of pressure continuity over the interfaces and avoids directly using the information of neighboring particles' densities or masses in solving governing equations. In order to improve computational accuracy and to obtain smooth pressure fields, a corrected density re-initialization is applied. A coupled dynamic solid boundary treatment (SBT) is implemented both to reduce numerical oscillations and to prevent unphysical particle penetration in the boundary area. The density correction and coupled dynamics SBT algorithms are modified to adapt to the density discontinuity on fluid interfaces in multiphase simulation. A cut-off value of the particle density is set to avoid negative pressure, which can lead to severe numerical difficulties and may even terminate the simulations. Three representative numerical examples, including a Rayleigh–Taylor instability test, a non-Boussinesq problem and a dam breaking simulation, are presented and compared with analytical results or experimental data. It is demonstrated that the present SPH model is capable of modeling complex multiphase flows with large interfacial deformations and density ratios. [ABSTRACT FROM AUTHOR]

The paper presents a novel, efficient and accurate algorithm for laminar and turbulent flow simulations. The spatial discretisation is performed with help of the compact difference schemes (up to 10th order) for collocated and half-staggered grid arrangements. The time integration is performed by a predictor–corrector approach combined with the projection method for pressure–velocity coupling. At this stage a low order discretisation is introduced which considerably decreases the computational costs. It is demonstrated that such approach does not deteriorate the solution accuracy significantly. Following Boersma B.J. [13] the interpolation formulas developed for staggered uniform meshes are used also in the computations with a non-uniform strongly varying nodes distribution. In the proposed formulation of the projection method such interpolation is performed twice. It is shown that it acts implicitly as a high-order low pass filter and therefore the resulting algorithm is very robust. Its accuracy is first demonstrated based on simple 2D and 3D problems: an inviscid vortex advection, a decay of Taylor–Green vortices, a modified lid-driven cavity flow and a dipole–wall interaction. In periodic flow problems (the first two cases) the solution accuracy exhibits the 10th order behaviour, in the latter cases the 3rd and the 4th order is obtained. Robustness of the proposed method in the computations of turbulent flows is demonstrated for two classical cases: a periodic channel with Re τ = 395 and Re τ = 590 and a round jet with Re = 21 000 . The solutions are obtained without any turbulence model and also without any explicit techniques aiming to stabilise the solution. The results are in a very good agreement with literature DNS and LES data, both the mean and r.m.s. values are predicted correctly. [ABSTRACT FROM AUTHOR]

Abstract: In this paper, a novel algorithm for incompressible flows of two-phase granular mixtures is proposed. The algorithm constitutes a generalization of projection-type methods to multi-phase flows and employs a predictor–corrector time-marching scheme. For the computation of the phasial pressures, a Poisson equation and a second-order elliptic PDE with variable coefficients are solved at both the prediction and the correction stage. Further, the algorithm is combined with a regularization scheme for the numerical treatment of material interfaces which are a common characteristic of the flows of interest. The efficiency and robustness of the proposed algorithm are illustrated via numerical simulations of unsteady two-dimensional shear flows for a reference mixture of beach sand and water. [Copyright &y& Elsevier]

Abstract: Mesh deformation is crucial to the accuracy and efficiency of the numerical simulations involving moving boundaries. In this paper, the disk relaxation algorithm and background mesh are applied to develop a new mesh deformation method. The disk relaxation algorithm rearranges the nodes in the mesh by repulsive and attractive interactions to preserve high mesh quality. With the help of background mesh, the computational region is divided into layers to transfer the boundary deformation uniformly and effectively in the pre-displacement procedure. We further introduce the post-smoothing procedure to avoid the negative volume of elements. Numerical applications including the rotation of airfoil, rotation and translation of rectangle, relative motion of multi-body, and complex boundary with irregular deformation are carried out. The results demonstrate that the new method generates the deformed mesh with high quality even in large deformations, especially concerning the boundary meshes. Comparisons with previous methods show that the deformation capability and efficiency of the new method are better than the widely used semi-torsional spring analogy, and the mesh quality of the deformed mesh obtained is superior to that of the spring method, as well as some new approaches presented recently when they undergo the same deformation in the cases. [Copyright &y& Elsevier]

Abstract: Unstructured meshes are in widespread use throughout computational physics, but calculating diagnostics of simulations on such meshes can be challenging. For example, in geophysical fluid dynamics, it is frequently desirable to compute directional integrals such as vertical integrals and zonal averages; however, it is difficult to compute these on meshes with no inherent spatial structure. This is widely regarded as an obstacle to the adoption of unstructured mesh numerical modelling in this field. In this paper, we describe an algorithm by which one can exactly compute such directional integrals on arbitrarily unstructured meshes. This is achieved via the solution of a problem of computational geometry, constructing the supermesh of two meshes. We demonstrate the utility of this approach by applying it to a classical geophysical fluid dynamics system: the thermally driven rotating annulus. This addresses an important objection to the more widespread use of unstructured mesh modelling. [Copyright &y& Elsevier]

Abstract: For numerical simulations of highly relativistic and transversely accelerated charged particles including radiation fast algorithms are needed. While the radiation in particle accelerators has wavelengths in the order of 100μm the computational domain has dimensions roughly five orders of magnitude larger resulting in very large mesh sizes. The particles are confined to a small area of this domain only. To resolve the smallest scales close to the particles subgrids are envisioned. For reasons of stability the alternating direction implicit (ADI) scheme by Smithe et al. [D.N. Smithe, J.R. Cary, J.A. Carlsson, Divergence preservation in the ADI algorithms for electromagnetics, J. Comput. Phys. 228 (2009) 7289–7299] for Maxwell equations has been adopted. At the boundary of the domain absorbing boundary conditions have to be employed to prevent reflection of the radiation. In this paper we show how the divergence preserving ADI scheme has to be formulated in perfectly matched layers (PML) and compare the performance in several scenarios. [Copyright &y& Elsevier]

Abstract: Laminar-turbulent transition of hypersonic boundary layers can be affected significantly by the existence of surface roughness. Currently many important mechanisms of roughness-induced transition are not well understood. In recent years, direct numerical simulation (DNS) has been extensively applied for investigating instability and transition mechanisms of hypersonic boundary layers. Most of the past DNS studies, however, have been based on body-fitted grids for smooth surfaces without roughness. Due to complex geometry of embedded roughness, the use of body-fitted grids can be very difficult for flow with arbitrary surface roughness. In this paper, we present a new high-order cut-cell method to overcome the natural complexities in grid generation around arbitrary surface of roughness. The new method combines a non-uniform-grid finite-difference method for discrete grid points near the solid boundary and a shock-fitting method for the treatment of the bow shock. The non-uniform-grid finite-difference formulas are expressed in a general explicit form so that they can be applied to different multi-dimensional problems without any modification. The computational accuracy of new algorithms of up to O(h 4) are tested on several one- and two-dimensional elliptic equations in irregular domains. In addition, the new method is applied to the simulation of the receptivity process of a Mach 5.92 flow over a flat plate under the combined effect of an isolated surface roughness element and surface blow and suction. A good agreement is found between the unsteady flow results and those obtained by a Linear Stability Theory (LST). [ABSTRACT FROM AUTHOR]

Abstract: In this paper, the solution of the Riemann Problem for the one-dimensional, free-surface Shallow Water Equations over a bed step is analyzed both from a theoretical and a numerical point of view. Particular attention has been paid to the wave that is generated at the location of the bed discontinuity. Starting from the classical Shallow Water Equations, considering the bed level as an additional variable, and adding to the system an equation imposing its time invariance, we show that this wave is a contact wave, across which one of the Riemann invariants, namely the energy, is not constant. This is due to the fact that the relevant problem is nonconservative. We demonstrate that, in this type of system, Riemann Invariants do not generally hold in contact waves. Furthermore, we show that in this case the equations that link the flow variables across the contact wave are the Generalized Rankine–Hugoniot relations and we obtain these for the specific problem. From the numerical point of view, we present an accurate and efficient solver for the step Riemann Problem to be used in a finite-volume Godunov-type framework. Through a two-step predictor–corrector procedure, the solver is able to provide solutions with any desired accuracy. The predictor step uses a well-balanced Generalized Roe solver while the corrector step solves the exact nonlinear system of equations that consitutes the problem by means of an iterative procedure that starts from the predictor solution. In order to show the effectiveness and the accuracy of the proposed approach, we consider several step Riemann Problems and compare the exact solutions with the numerical results obtained by using a standard Roe approach far from the step and the novel two-step algorithm for the fluxes over the step, achieving good results. [Copyright &y& Elsevier]

Abstract: In this paper, a new method for calculating effective atomic radii within the generalized Born (GB) model of implicit solvation is proposed, for use in computer simulations of biomolecules. First, a new formulation for the GB radii is developed, in which smooth kernels are used to eliminate the divergence in volume integrals intrinsic in the model. Next, the fast Fourier transform (FFT) algorithm is applied to integrate smoothed functions, taking advantage of the rapid spectral decay provided by the smoothing. The total cost of the proposed algorithm scales as where M is the number of atoms comprised in a molecule and N is the number of FFT grid points in one dimension, which depends only on the geometry of the molecule and the spectral decay of the smooth kernel but not on M. To validate our algorithm, numerical tests are performed for three solute models: one spherical object for which exact solutions exist and two protein molecules of differing size. The tests show that our algorithm is able to reach the accuracy of other existing GB implementations, while offering much lower computational cost. [Copyright &y& Elsevier]

• A new, more efficient numerical algorithm for spatio-temporal chaos. • Gain reliable/convergent simulations of spatio-temporal chaos in a long duration. • Reliable simulation is used as benchmark to study influence of numerical noises. • Use of the double precision might lead to huge deviations even in statistics. Due to the butterfly-effect, computer-generated chaotic simulations often deviate exponentially from the true solution, so that it is very hard to obtain a reliable simulation of chaos in a long-duration time. In this paper, a new strategy of the so-called Clean Numerical Simulation (CNS) in physical space is proposed for spatio-temporal chaos, which is computationally much more efficient than its predecessor (in spectral space). The strategy of the CNS is to reduce both of the truncation and round-off errors to a specified level by implementing high-order algorithms in multiple-precision arithmetic (with sufficient significant digits for all variables and parameters) so as to guarantee that numerical noise is below such a critical level in a temporal interval t ∈ [ 0 , T c ] that corresponding numerical simulation remains reliable over the whole interval. Without loss of generality, the complex Ginzburg-Landau equation (CGLE) is used to illustrate its validity. As a result, a reliable long-duration numerical simulation of the CGLE is achieved in the whole spatial domain over a long interval of time t ∈ [ 0 , 3000 ] , which is used as a reliable benchmark solution to investigate the influence of numerical noise by comparing it with the corresponding ones given by the 4th-order Runge-Kutta method in double precision (RKwD). Our results demonstrate that the use of double precision in simulations of chaos might lead to huge errors in the prediction of spatio-temporal trajectories and in statistics, not only quantitatively but also qualitatively, particularly in a long interval of time. [ABSTRACT FROM AUTHOR]