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Calo, Victor M. (48)

Collier, Nathan (12)Ghommem, Mehdi (10)Efendiev, Yalchin R. (8)Hughes, Thomas Jr R (8)View MoreDepartmentEnvironmental Science and Engineering Program (48)Numerical Porous Media SRI Center (NumPor) (47)Physical Sciences and Engineering (PSE) Division (45)Applied Mathematics and Computational Science Program (34)Earth Science and Engineering Program (24)View MoreJournalComputer Methods in Applied Mechanics and Engineering (6)Journal of Computational Physics (6)Computers & Mathematics with Applications (4)International Journal for Numerical Methods in Engineering (2)Journal of Computational and Applied Mathematics (2)View MorePublisherElsevier BV (30)Society of Petroleum Engineers (SPE) (4)Wiley (3)Civil-Comp, Ltd. (2)Springer Nature (2)View MoreSubjectIsogeometric analysis (7)Finite element method (6)Discontinuous Petrov-Galerkin (3)Model reduction (3)NURBS (3)View MoreTypeArticle (35)Conference Paper (13)Year (Issue Date)2018 (1)2015 (4)2014 (13)2013 (14)2012 (4)View MoreItem AvailabilityMetadata Only (44)Open Access (3)Embargoed (1)

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Cell-element simulations to optimize the performance of osmotic processes in porous membranes

Calo, Victor M.; Iliev, Oleg; Nunes, Suzana Pereira; Printsypar, Galina; Shi, Meixia (Computers & Mathematics with Applications, Elsevier BV, 2018-05-11) [Article]

We present a new module of the software tool PoreChem for 3D simulations of osmotic processes at the cell-element scale. We consider the most general fully coupled model (see e.g., Sagiv and Semiat (2011)) in 3D to evaluate the impact on the membrane performance of both internal and external concentration polarization, which occurs in a cell-element for different operational conditions. The model consists of the Navier–Stokes–Brinkman system to describe the free fluid flow and the flow within the membrane with selective and support layers, a convection–diffusion equation to describe the solute transport, and nonlinear interface conditions to fully couple these equations. First, we briefly describe the mathematical model and discuss the discretization of the continuous model, the iterative solution, and the software implementation. Then, we present the analytical and numerical validation of the simulation tool. Next, we perform and discuss numerical simulations for a case study. The case study concerns the design of a cell element for the forward osmosis experiments. Using the developed software tool we qualitatively and quantitatively investigate the performance of a cell element that we designed for laboratory experiments of forward osmosis, and discuss the differences between the numerical solutions obtained with the full 3D and reduced 2D models. Finally, we demonstrate how the software enables investigating membrane heterogeneities.

Consistent model reduction of polymer chains in solution in dissipative particle dynamics: Model description

Moreno Chaparro, Nicolas; Nunes, Suzana Pereira; Calo, Victor M. (Computer Physics Communications, Elsevier BV, 2015-06-30) [Article]

We introduce a framework for model reduction of polymer chain models for dissipative particle dynamics (DPD) simulations, where the properties governing the phase equilibria such as the characteristic size of the chain, compressibility, density, and temperature are preserved. The proposed methodology reduces the number of degrees of freedom required in traditional DPD representations to model equilibrium properties of systems with complex molecules (e.g., linear polymers). Based on geometrical considerations we explicitly account for the correlation between beads in fine-grained DPD models and consistently represent the effect of these correlations in a reduced model, in a practical and simple fashion via power laws and the consistent scaling of the simulation parameters. In order to satisfy the geometrical constraints in the reduced model we introduce bond-angle potentials that account for the changes in the chain free energy after the model reduction. Following this coarse-graining process we represent high molecular weight DPD chains (i.e., ≥200≥200 beads per chain) with a significant reduction in the number of particles required (i.e., ≥20≥20 times the original system). We show that our methodology has potential applications modeling systems of high molecular weight molecules at large scales, such as diblock copolymer and DNA.

Stretch-minimising stream surfaces

Barton, Michael; Kosinka, Jin; Calo, Victor M. (Graphical Models, Elsevier BV, 2015-05) [Article]

We study the problem of finding stretch-minimising stream surfaces in a divergence-free vector field. These surfaces are generated by motions of seed curves that propagate through the field in a stretch minimising manner, i.e., they move without stretching or shrinking, preserving the length of their arbitrary arc. In general fields, such curves may not exist. How-ever, the divergence-free constraint gives rise to these 'stretch-free' curves that are locally arc-length preserving when infinitesimally propagated. Several families of stretch-free curves are identified and used as initial guesses for stream surface generation. These surfaces are subsequently globally optimised to obtain the best stretch-minimising stream surfaces in a given divergence-free vector field. Our algorithm was tested on benchmark datasets, proving its applicability to incompressible fluid flow simulations, where our stretch-minimising stream surfaces realistically reflect the flow of a flexible univariate object. © 2015 Elsevier Inc. All rights reserved.

Computational cost of isogeometric multi-frontal solvers on parallel distributed memory machines

Woźniak, Maciej; Paszyński, Maciej R.; Pardo, D.; Dalcin, Lisandro; Calo, Victor M. (Computer Methods in Applied Mechanics and Engineering, Elsevier BV, 2015-02) [Article]

This paper derives theoretical estimates of the computational cost for isogeometric multi-frontal direct solver executed on parallel distributed memory machines. We show theoretically that for the Cp-1 global continuity of the isogeometric solution, both the computational cost and the communication cost of a direct solver are of order O(log(N)p2) for the one dimensional (1D) case, O(Np2) for the two dimensional (2D) case, and O(N4/3p2) for the three dimensional (3D) case, where N is the number of degrees of freedom and p is the polynomial order of the B-spline basis functions. The theoretical estimates are verified by numerical experiments performed with three parallel multi-frontal direct solvers: MUMPS, PaStiX and SuperLU, available through PETIGA toolkit built on top of PETSc. Numerical results confirm these theoretical estimates both in terms of p and N. For a given problem size, the strong efficiency rapidly decreases as the number of processors increases, becoming about 20% for 256 processors for a 3D example with 1283 unknowns and linear B-splines with C0 global continuity, and 15% for a 3D example with 643 unknowns and quartic B-splines with C3 global continuity. At the same time, one cannot arbitrarily increase the problem size, since the memory required by higher order continuity spaces is large, quickly consuming all the available memory resources even in the parallel distributed memory version. Numerical results also suggest that the use of distributed parallel machines is highly beneficial when solving higher order continuity spaces, although the number of processors that one can efficiently employ is somehow limited.

Preconditioners based on the Alternating-Direction-Implicit algorithm for the 2D steady-state diffusion equation with orthotropic heterogeneous coefficients

Gao, Longfei; Calo, Victor M. (Journal of Computational and Applied Mathematics, Elsevier BV, 2015-01) [Article]

In this paper, we combine the Alternating Direction Implicit (ADI) algorithm with the concept of preconditioning and apply it to linear systems discretized from the 2D steady-state diffusion equations with orthotropic heterogeneous coefficients by the finite element method assuming tensor product basis functions. Specifically, we adopt the compound iteration idea and use ADI iterations as the preconditioner for the outside Krylov subspace method that is used to solve the preconditioned linear system. An efficient algorithm to perform each ADI iteration is crucial to the efficiency of the overall iterative scheme. We exploit the Kronecker product structure in the matrices, inherited from the tensor product basis functions, to achieve high efficiency in each ADI iteration. Meanwhile, in order to reduce the number of Krylov subspace iterations, we incorporate partially the coefficient information into the preconditioner by exploiting the local support property of the finite element basis functions. Numerical results demonstrated the efficiency and quality of the proposed preconditioner. © 2014 Elsevier B.V. All rights reserved.

Multiscale empirical interpolation for solving nonlinear PDEs

Calo, Victor M.; Efendiev, Yalchin R.; Galvis, Juan; Ghommem, Mehdi (Journal of Computational Physics, Elsevier BV, 2014-12) [Article]

In this paper, we propose a multiscale empirical interpolation method for solving nonlinear multiscale partial differential equations. The proposed method combines empirical interpolation techniques and local multiscale methods, such as the Generalized Multiscale Finite Element Method (GMsFEM). To solve nonlinear equations, the GMsFEM is used to represent the solution on a coarse grid with multiscale basis functions computed offline. Computing the GMsFEM solution involves calculating the system residuals and Jacobians on the fine grid. We use empirical interpolation concepts to evaluate these residuals and Jacobians of the multiscale system with a computational cost which is proportional to the size of the coarse-scale problem rather than the fully-resolved fine scale one. The empirical interpolation method uses basis functions which are built by sampling the nonlinear function we want to approximate a limited number of times. The coefficients needed for this approximation are computed in the offline stage by inverting an inexpensive linear system. The proposed multiscale empirical interpolation techniques: (1) divide computing the nonlinear function into coarse regions; (2) evaluate contributions of nonlinear functions in each coarse region taking advantage of a reduced-order representation of the solution; and (3) introduce multiscale proper-orthogonal-decomposition techniques to find appropriate interpolation vectors. We demonstrate the effectiveness of the proposed methods on several nonlinear multiscale PDEs that are solved with Newton's methods and fully-implicit time marching schemes. Our numerical results show that the proposed methods provide a robust framework for solving nonlinear multiscale PDEs on a coarse grid with bounded error and significant computational cost reduction.

On the computational efficiency of isogeometric methods for smooth elliptic problems using direct solvers

Collier, Nathan; Dalcin, Lisandro; Calo, Victor M. (International Journal for Numerical Methods in Engineering, Wiley, 2014-09-17) [Article]

SUMMARY: We compare the computational efficiency of isogeometric Galerkin and collocation methods for partial differential equations in the asymptotic regime. We define a metric to identify when numerical experiments have reached this regime. We then apply these ideas to analyze the performance of different isogeometric discretizations, which encompass C0 finite element spaces and higher-continuous spaces. We derive convergence and cost estimates in terms of the total number of degrees of freedom and then perform an asymptotic numerical comparison of the efficiency of these methods applied to an elliptic problem. These estimates are derived assuming that the underlying solution is smooth, the full Gauss quadrature is used in each non-zero knot span and the numerical solution of the discrete system is found using a direct multi-frontal solver. We conclude that under the assumptions detailed in this paper, higher-continuous basis functions provide marginal benefits.

Restrictions in Model Reduction for Polymer Chain Models in Dissipative Particle Dynamics

Moreno Chaparro, Nicolas; Nunes, Suzana Pereira; Calo, Victor M. (Procedia Computer Science, Elsevier BV, 2014-06-06) [Conference Paper]

We model high molecular weight homopolymers in semidilute concentration via Dissipative Particle Dynamics (DPD). We show that in model reduction methodologies for polymers it is not enough to preserve system properties (i.e., density ρ, pressure p, temperature T, radial distribution function g(r)) but preserving also the characteristic shape and length scale of the polymer chain model is necessary. In this work we apply a DPD-model-reduction methodology for linear polymers recently proposed; and demonstrate why the applicability of this methodology is limited upto certain maximum polymer length, and not suitable for solvent coarse graining.

Computational cost estimates for parallel shared memory isogeometric multi-frontal solvers

Woźniak, Maciej; Kuźnik, Krzysztof M.; Paszyński, Maciej R.; Calo, Victor M.; Pardo, D. (Computers & Mathematics with Applications, Elsevier BV, 2014-06) [Article]

In this paper we present computational cost estimates for parallel shared memory isogeometric multi-frontal solvers. The estimates show that the ideal isogeometric shared memory parallel direct solver scales as O( p2log(N/p)) for one dimensional problems, O(Np2) for two dimensional problems, and O(N4/3p2) for three dimensional problems, where N is the number of degrees of freedom, and p is the polynomial order of approximation. The computational costs of the shared memory parallel isogeometric direct solver are compared with those corresponding to the sequential isogeometric direct solver, being the latest equal to O(N p2) for the one dimensional case, O(N1.5p3) for the two dimensional case, and O(N2p3) for the three dimensional case. The shared memory version significantly reduces both the scalability in terms of N and p. Theoretical estimates are compared with numerical experiments performed with linear, quadratic, cubic, quartic, and quintic B-splines, in one and two spatial dimensions. © 2014 Elsevier Ltd. All rights reserved.

Fast isogeometric solvers for explicit dynamics

Gao, Longfei; Calo, Victor M. (Computer Methods in Applied Mechanics and Engineering, Elsevier BV, 2014-06) [Article]

In finite element analysis, solving time-dependent partial differential equations with explicit time marching schemes requires repeatedly applying the inverse of the mass matrix. For mass matrices that can be expressed as tensor products of lower dimensional matrices, we present a direct method that has linear computational complexity, i.e., O(N), where N is the total number of degrees of freedom in the system. We refer to these matrices as separable matrices. For non-separable mass matrices, we present a preconditioned conjugate gradient method with carefully designed preconditioners as an alternative. We demonstrate that these preconditioners, which are easy to construct and cheap to apply (O(N)), can deliver significant convergence acceleration. The performances of these preconditioners are independent of the polynomial order (p independence) and mesh resolution (h independence) for maximum continuity B-splines, as verified by various numerical tests. © 2014 Elsevier B.V.

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