Modeling accidental-type fluid–structure interaction problems with the SPH method

This paper presents the validation aspects of a unified numerical framework based on SPH formulation and devoted to the modeling of fluid–structure interaction problems involving large motion of the fluid and large deformation with a possible failure of the structure. The fluid domain is modeled according to an updated Lagrangian formulation. The solid domain (3D and shell models) uses the total Lagrangian formulation. The fluid–structure interaction is treated via a unilateral contact algorithm adapted to SPH context. The SPH framework is verified on academic test cases and validated by simulating an experiment involving the reservoir leakage.     

Parallel predator–prey interaction for evolutionary multi-objective optimization

Over the last decade, the predator?Cprey model (PPM) has emerged as an alternative algorithmic approach to multi-objective evolutionary optimization, featuring a very simple abstraction from natural species interplay and extensive parallelization potential. While substantial research has been done on the former, we for the first time review the PPM in the light of parallelization: We analyze the architecture and classify its components with respect to a recent taxonomy for parallel multi-objective evolutionary algorithms. Further, we theoretically examine benefits of simultaneous predator collaboration on a spatial population structure and give insights into solution emergence. On the prey level, we integrate a gradient-based local search mechanism to exploit problem independent parallelization and hybridize the model in order to achieve faster convergence and solution stability. This way, we achieve a good approximation and unfold further parallelization potential for the model.     

Partitioned strong coupling algorithms for fluid–structure interaction

Numerical simulation of fluid–structure interaction is often attempted in the context of partitioned methods, where already existing solvers for fluid or structure alone are used jointly. Mostly this is done by exchanging information from time step to time step in an alternating fashion. These weak coupling methods are explicit and hence suffer from possible instabilities. Therefore often strong coupling––where equilibrium is satisfied jointly between fluid and structure in each time step––is desired; the simplest computational procedure is similar to the time stepping an alternating iteration. We show why also this approach may experience difficulties, and how they may be circumvented with block-Newton methods, still in the partitioned framework, by only using the solvers of the subproblems fluid and structure.     

A novel hybrid PSO–GWO algorithm for optimization problems

Engineering with Computers - In this study, we propose a new hybrid algorithm fusing the exploitation ability of the particle swarm optimization (PSO) with the exploration ability of the grey wolf...     

Solution of non-linear optimization problems in power systems†

The application of differential dynamic programming or hybrid quasilinearization technique to the solution of non-linear optimization problems in power systems has encountered the problem of computational instability, particularly in higher order systems. This paper describes the application of a continuation procedure to alleviate this difficulty. Sixth order non-linear systems have been optimized with and without constraints on control variables. Both open-loop and, for the first time, closed-loop systems including both exciter and governor dynamics, are analysed. The studies presented show that this technique is quite effective in obtaining accurate solutions for non-linear boundary-value-problems in power systems.     

Topology optimization using a reaction–diffusion equation

This paper presents a structural topology optimization method based on a reaction–diffusion equation. In our approach, the design sensitivity for the topology optimization is directly employed as the reaction term of the reaction–diffusion equation. The distribution of material properties in the design domain is interpolated as the density field which is the solution of the reaction–diffusion equation, so free generation of new holes is allowed without the use of the topological gradient method. Our proposed method is intuitive and its implementation is simple compared with optimization methods using the level set method or phase field model. The evolution of the density field is based on the implicit finite element method. As numerical examples, compliance minimization problems of cantilever beams and force maximization problems of magnetic actuators are presented to demonstrate the method’s effectiveness and utility.     

A numerical study on the fluid compressibility effects in strongly coupled fluid–solid interaction problems

Interactions between an incompressible fluid passing through a flexible tube and the elastic wall is one of the strongly coupled fluid–solid interaction (FSI) problems frequently studied in the literature due to its research importance and wide range of applications. Although incompressible fluid is a prevalent model in many simulation studies, the assumption of incompressibility may not be appropriate in strongly coupled FSI problems. This paper narrowly aims to study the effect of the fluid compressibility on the wave propagation and fluid–solid interactions in a flexible tube. A partitioned FSI solver is used which employs a finite volume-based fluid solver. For the sake of comparison, both traditional incompressible (ico) and weakly compressible (wco) fluid models are used in an Arbitrary Lagrangian–Eulerian (ALE) formulation and a PISO-like algorithm is used to solve the unsteady flow equations on a collocated mesh. The solid part is modeled as a simple hyperelastic material obeying the St-Venant constitutive relation. Computational results show that not only use of the weakly compressible fluid model makes the FSI solver in this case more efficient, but also the incompressible fluid model may produce largely unrealistic computational results. Therefore, the use of the weakly compressible fluid model is suggested for strongly coupled FSI problems involving seemingly incompressible fluids such as water especially in cases where wave propagation in the solid plays an important role.

     

A Lagrangian meshless finite element method applied to fluid–structure interaction problems

A method is presented for the solution of the incompressible fluid flow equations using a Lagrangian formulation. The interpolation functions are those used in the meshless finite element method and the time integration is introduced in a semi-implicit way by a fractional step method. Classical stabilization terms used in the momentum equations are unnecessary due to the lack of convective terms in the Lagrangian formulation. Furthermore, the Lagrangian formulation simplifies the connections with fixed or moving solid structures, thus providing a very easy way to solve fluid–structure interaction problems.     

On the use of multibody dynamics techniques to simulate fluid dynamics and fluid–solid interaction problems

Multibody System Dynamics - A multibody dynamics-based solution to the fluid dynamics problem is compared herein to two established Lagrangian-based techniques used by the computational fluid...     

A web-based platform for the simulation–optimization of industrial problems

This study presents a platform for industrial, real-world simulation–optimization based on web techniques. The design of the platform is intended to be generic and thereby make it possible to apply the platform in various problem domains. In the implementation of the platform, modern web techniques, such as Ajax, JavaScript, GWT, and ProtoBuf, are used. The platform is tested and evaluated on a real industrial problem of production optimization at Volvo Aero Corporation, a company that develops and manufactures high-technology components for aircraft and gas turbine engines. The results of the evaluation show that while the platform has several benefits, implementing a web-based system is not completely straightforward. At the end of the paper, possible pitfalls are discussed and some recommendations for future implementations are outlined.     

Multi-solver algorithms for the partitioned simulation of fluid–structure interaction

In partitioned fluid–structure interaction simulations, the flow equations and the structural equations are solved separately. As a result, a coupling algorithm is needed to enforce the equilibrium on the fluid–structure interface in cases with strong interaction. This coupling algorithm performs coupling iterations between the solver of the flow equations and the solver of the structural equations. Current coupling algorithms couple one flow solver with one structural solver. Here, a new class of multi-solver quasi-Newton coupling algorithms for unsteady fluid–structure interaction simulations is presented. More than one flow solver and more than one structural solver are used for a single simulation. The numerical experiments demonstrate that the duration of a simulation decreases as the number of solvers is increased.     

Combined interface boundary condition method for unsteady fluid–structure interaction

Traditionally, continuity of velocity and traction along interfaces are satisfied through algebraic interface conditions applied in a sequential or staggered fashion. In existing staggered procedures, the numerical treatment of the interface conditions can undermine the stability and accuracy of coupled fluid–structure simulations. This paper presents a new loosely-coupled partitioned procedure for modeling fluid–structure interaction called combined interface boundary condition (CIBC). The procedure relies on a higher-order treatment for improved accuracy and stability of fluid–structure coupling. By utilizing the CIBC technique on the velocity and momentum flux boundary conditions, a staggered coupling procedure can be constructed with similar order of accuracy and stability of standalone computations for either the fluids or structures. The new formulation involves a coupling parameter that adjusts the amount of interfacial traction in the form of acceleration correction, which plays a key role in the stability and accuracy of the coupled simulations. Introduced correction terms for velocity and traction transfer are explicitly added to the standard staggered time-stepping stencils based on the discretized coupling effects. The coupling scheme is demonstrated in the classical 1D closed- and open-domain elastic piston problems, but further work is needed to consider the analytical stability of these schemes, 3D problems and comparison to monolithic integration.     

A hybrid teaching–learning slime mould algorithm for global optimization and reliability-based design optimization problems

Neural Computing and Applications - Slime mould algorithm (SMA) is a novel metaheuristic algorithm with good performance for optimization problems, but it may encounter premature or low accuracy in...     

A differential evolution approach for solving constrained min–max optimization problems

Many problems occurring in engineering can be formulated as min–max optimization problems, for instance, in game theory, robust optimal control and many others. Min–max problems are considered difficult to solve, specially constrained min–max optimization problems. Approaches using co-evolutionary algorithms have successfully been used to solve min–max optimization problems without constraints. We propose a novel differential evolution approach consisting of three populations with a scheme of copying individuals for solving constrained min–max problems. Promising results have been obtained showing the suitability of the approach.     

Partitioned but strongly coupled iteration schemes for nonlinear fluid–structure interaction

We look at the computational procedure of computing the response of a coupled fluid–structure interaction problem. We use the so-called strong fluid–structure coupling––a totally implicit formulation. At each time step in an implicit formulation, new values for the solution variables have to be computed by solving a nonlinear system of equations, where we assume that we have solvers for the subproblems. This is often the case, when we have existing software to solve each subproblem separately, and want to couple both. We show how to solve the overall nonlinear system by using only the solvers for the subproblems. This is achieved not by considering the equilibrium equations, but the fixed-point problem resulting from the solution iteration for each of the subproblems.     

Min–Median–Max metamodel-based unconstrained nonlinear optimization problems

An important direction of metamodeling research focuses on developing methods which can iteratively improve the accuracy of the metamodel. The intention of these kinds of strategies is to use a space reduction strategy to lead response surface refinement to a smaller design space; and new sample points are commonly generated near the optimum. The potential risk is that some characteristics of given problems might be lost, especially for nonlinear problems. Therefore, a novel metamodel-assisted optimization called “Min–Median–Max” (M3) is proposed. This algorithm classifies sample points into three categories (maximum, median and minimum) based on corresponding objective function values, new sample points should be generated by considering combination of three kinds of samples. In order to avoid local convergence and control size of sample points, particle swarm optimization (PSO) algorithm and radial basis function (RBF) metamodeling technique are integrated to implement the suggested M3 strategy. To validate the performance of the M3 strategy, multiple mathematical test functions are used for evaluating the accuracy and efficiency. As a practical engineering application, drawbead design of a stamping system is optimized. The results demonstrate applicability and effectiveness of the M3 algorithm.     

A new nonmonotone filter Barzilai–Borwein method for solving unconstrained optimization problems

In this paper, a finite filter is used in the structure of the Barzilai–Browein (BB) gradient method in order to propose a new modified BB algorithm for solving large-scale unconstrained optimization problems. Our algorithm is equipped with a relaxed nonmonotone line search technique which allows the algorithm to enjoy the nonmonotonicity properties from scratch. Under some suitable conditions, the global convergence property of the new proposed algorithm is established. Numerical results on some test problems in CUTEr library show the efficiency and effectiveness of the new algorithm in practice too.     

Subgradient-based feedback neural networks for non-differentiable convex optimization problems

1 Introduction Optimization problems arise in a broad variety of scientific and engineering applica- tions. For many practice engineering applications problems, the real-time solutions of optimization problems are mostly required. One possible and very pr…     

A lattice Boltzmann based implicit immersed boundary method for fluid–structure interaction

The immersed boundary method is a practical and effective method for fluid–structure interaction problems. It has been applied to a variety of problems. Most of the time-stepping schemes used in the method are explicit, which suffer a drawback in terms of stability and restriction on the time step. We propose a lattice Boltzmann based implicit immersed boundary method where the immersed boundary force is computed at the unknown configuration of the structure at each time step. The fully nonlinear algebraic system resulting from discretizations is solved by an Inexact Newton–Krylov method in a Jacobian-free manner. The test problem of a flexible filament in a flowing viscous fluid is considered. Numerical results show that the proposed implicit immersed boundary method is much more stable with larger time steps and significantly outperforms the explicit version in terms of computational cost.