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The arbitrary Lagrangian—Eulerian (ALE) formulation, which is already well established in the hydrodynamics and fluid‐structure interaction fields, is extended to materials with memory, namely, non‐ linear path‐dependent materials. Previous attempts to treat non‐ linear solid mechanics with the ALE description have, in common, the implicit interpolation technique employed. Obviously, this implies a numerical burden which may be uneconomical and may induce to give up this formulation, particularly in fast‐transient dynamics where explicit algorithms are usually employed. Here, several applications are presented to show that if adequate stress updating techniques are implemented, the ALE formulation could be much more competitive than classical Lagrangian computations when large deformations are present. Moreover, if the ALE technique is interpreted as a simple interpolation enrichment, adequate—in opposition to distorted or locally coarse—meshes are employed. Notice also that impossible computations (or at least very involved numerically) with a Lagrangian code are easily implementable in an ALE analysis. Finally, it is important to observe that the numerical examples shown range from a purely academic test to real engineering simulations. They show the effective applicability of this formulation to non‐linear solid mechanics and, in particular, to impact, coining or forming analysis.

Compliant mechanism has been receiving a great interest in precision engineering. However, analytical methods involving their behavior analysis is still a challenge because there are unclear kinematic behaviors. Especially, design optimization for compliant mechanisms becomes an important task when the problem is more and more complex. Therefore, the purpose of this study is to design a new hybrid computational method. The hybridized method is an integration of statistics, numerical method, computational intelligence and optimization.

A tensural bistable compliant mechanism is used to clarify the efficiency of the developed method. A pseudo model of the mechanism is designed and simulations are planned to retrieve the data sets. Main contributions of design variables are analyzed by analysis of variance to initialize several new populations. Next, objective functions are transformed into the desirability, which are inputs of the fuzzy inference system (FIS). The FIS modeling is aimed to initialize a single-combined objective function (SCOF). Subsequently, adaptive neuro-fuzzy inference system is developed to modeling a relation of the main geometrical parameters and the SCOF. Finally, the SCOF is maximized by lightning attachment procedure optimization algorithm to yield a global optimality.

The results prove that the present method is better than a combination of fuzzy logic and Taguchi. The present method is also superior to other algorithms by conducting non-parameter tests. The proposed computational method is a usefully systematic method that can be applied to compliant mechanisms with complex structures and multiple-constrained optimization problems.

The novelty of this work is to make a new approach by combining statistical techniques, numerical method, computational intelligence and metaheuristic algorithm. The feasibility of the method is capable of solving a multi-objective optimization problem for compliant mechanisms with nonlinear complexity.

The purpose of this article is to analyze the state-of-the art in a systematic way, identifying the main research groups and their related topics. The types of studies found are fundamental for understanding the application of artificial neural networks (ANNs) in cemented soils and the potential for using the technique, as well as the feasibility of extrapolation to new geotechnical or civil and environmental engineering segments.

This work is characterized as being bibliometric and systematic research of an exploratory perspective of state-of-the-art. It also persuades the qualitative and quantitative data analysis of cemented soil improvement, biocemented or microbially induced calcite precipitation (MICP) soil improvement by prediction/modeling by ANN. This study sought to compile and study the state of the art of the topic which possibilities to have a critical view about the theme. To do so, two main databases were analyzed: Scopus and Web of Science. Systematic review techniques, as well as bibliometric indicators, were implemented.

This paper connected the network between the achievements of the researches and illustrated the main application of ANNs in soil improvement prediction, specifically on cemented-based soils and biocemented soils (e.g. MICP technique). Also, as a bibliometric and systematic review, this work could achieve the key points in the absence of researches involving soil-ANN, and it provided the understanding of the lack of exploratory studies to be approached in the near future.

Because of the research topic the article suggested other applications of ANNs in geotechnical engineering, such as other tests not related to geomechanical resistance such as unconfined compression test test and triaxial test.

This article systematically and critically presents some interesting points in the direction of future research, such as the non-approach to the use of ANNs in biocementation processes, such as MICP.

Regarding the social environment, the paper brings approaches on methods that somehow mitigate the computational use, or elements necessary for geotechnical improvement of the soil, thereby optimizing the same consequently.

Neural networks have been studied for a long time in engineering, but the current computational power has increased the implementation for several engineering applications. Besides that, soil cementation is a widespread technique and its prediction modes often require high computational strength, such parameters can be mitigated with the use of ANNs, because artificial intelligence seeks learning from the implementation of the data set, reducing computational cost and increasing accuracy.

To provide an improved version of SIMPLER algorithm which can enhance the convergence rate of the iterative solution procedure in the field of computational fluid dynamics analysis.

The improved version of SIMPLER algorithm is developed by modifying the coefficients of the velocity correction equation and implementing the correction of pressure within an iteration cycle.

The CSIMPLER algorithm (the improved version) can enhance the convergence rate for almost all cases tested, especially for the low under‐relaxation factor situations. The pressure correction term even can be overrelaxed to further enhance the convergence rate.

The CSIMPLER algorithm can enhance the rate of convergence to different degree for different problems. It can only be adopted to solve the incompressible fluid flow and heat transfer.

CSIMPLER is a simple and effectual method to enhance the convergence rate of the iterative process for the computational fluid dynamics analysis. The existing code of SIMPLER can be easily changed to CSIMPLER.

The paper developed an improved version of SIMPLER algorithm with some minor changes in the existing SIMPLER code.

There is a widely available object oriented (OO) programming language that is usually overlooked in the OO analysis, OO design, OO programming literature. It was designed with most of the features of languages like C++, Eiffel, and Smalltalk. It has extensive and efficient numerical abilities including concise array and matrix handling, like Matlab®. In addition, it is readily extended to massively parallel machines and is backed by an international ISO and ANSI standard. The language is Fortran 90 (and Fortran 95). When the explosion of books and articles on OOP began appearing in the early 1990s many of them correctly disparaged Fortran 77 (F77) for its lack of object oriented abilities and data structures. However, then and now many authors fail to realize that the then new Fortran 90 (F90) standard established a well‐planned object oriented programming language while maintaining a full backward compatibility with the old F77 standard. F90 offers strong typing, encapsulation, inheritance, multiple inheritance, polymorphism, and other features important to object oriented programming. This paper will illustrate several of these features that are important to engineering computation using OOP.

Gives a bibliographical review of the error estimates and adaptive finite element methods from the theoretical as well as the application point of view. The bibliography at the end contains 2,177 references to papers, conference proceedings and theses/dissertations dealing with the subjects that were published in 1990‐2000.

Presents four examples which were researched in a large eddy simulation (LES) of turbulence for engineering applications. Explains that, in the former two cases, developments of the advanced LES are indicated in a Smagorinsky model and in the treatments of the wall and the external boundary, and, in the later cases, the LES on the boundary fitted grids are applied using the finite different method (FDM) and the finite element method (FEM), where new numerical treatments, a composite grid technique and a modified scheme, are adopted for efficient calculations. Evaluates the results, and discusses the possible application of the LES for engineering problems.

Purpose — The purpose of this paper is to seek improved solution techniques for combined boundary‐initial value problems (IVPs) associated with the time‐dependent creep deformation and rupture of engineering structures at high temperatures and hence to reconfigure a parallel iterative preconditioned conjugate gradient (PCG) solver and the DAMAGE XXX software, for 3‐D finite element creep continuum damage mechanics (CDM) analysis.Design/methodology/approach — The potential to speed up the computer numerical solution of the combined BV‐IVPs is addressed using parallel computers. Since the computational bottleneck is associated with the matrix solver, the parallelisation of a direct and an iterative solver has been studied. The creep deformation and rupture of a tension bar has been computed for a range of the number of degrees of freedom (ndf), and the performance of the two solvers is compared and assessed.Findings — The results show the superior scalability of the iterative solver compared to the direct solver, with larger speed‐ups gained by the PCG solver for higher degrees of freedom. Also, a new algorithm for the first trial solution of the PCG solver provides additional speed‐ups.Research limitations/implications — The results show that the ideal parallel speed‐up of the iterative solver of 16, relative to two processors, is achieved when using 32 processors for a mesh of ndf = 153,238. Originality/value — Techniques have been established in this paper for the parallelisation of CDM creep analysis software using an iterative equation solver. The significant computational speed‐ups achieved will enable the analysis of failures in weldments of industrial significance.

Traditional parallel methods for structural design, as well as modern preconditioned iterative linear solvers, do not scale well. This paper discusses the application of massively scalable cellular automata (CA) techniques to structural design, specifically trusses. There are two sets of CA rules, one used to propagate stresses and strains, and one to perform design updates. These rules can be applied serially, periodically, or concurrently, and Jacobi or Gauss‐Seidel style updating can be done. These options are compared with respect to convergence, speed, and stability for an example, problem of combined sizing and topology design of truss domain structures. The central theme of the paper is that the cellular automaton paradigm is tantamount to classical block Jacobi or block Gauss‐Seidel iteration, and consequently the performance of a cellular automaton can be rigorously analyzed and predicted.

This research study aims to develop regular cylindrical pore network models (RCPNMs) to calculate topology and geometry properties of explosively created fractures along with their resulting hydraulic permeability. The focus of the investigation is to define a method that generates a valid geometric and topologic representation from a computational modelling point of view for explosion-generated fractures in rocks. In particular, extraction of geometries from experimentally validated Eulerian smoothed particle hydrodynamics (ESPH) approach, to avoid restrictions for image-based computational methods.

Three-dimensional stabilized ESPH solution is required to model explosively created fracture networks, and the accuracy of developed ESPH is qualitatively and quantitatively examined against experimental observations for both peak detonation pressures and crack density estimations. SPH simulation domain is segmented to void and solid spaces using a graphical user interface, and the void space of blasted rocks is represented by a regular lattice of spherical pores connected by cylindrical throats. Results produced by the RCPNMs are compared to three pore network extraction algorithms. Thereby, once the accuracy of RCPNMs is confirmed, the absolute permeability of fracture networks is calculated.

The results obtained with RCPNMs method were compared with three pore network extraction algorithms and computational fluid dynamics method, achieving a more computational efficiency regarding to CPU cost and a better geometry and topology relationship identification, in all the cases studied. Furthermore, a reliable topology data that does not have image-based pore network limitations, and the effect of topological disorder on the computed absolute permeability is minor. However, further research is necessary to improve the interpretation of real pore systems for explosively created fracture networks.

Although only laboratory cylindrical rock specimens were tested in the computational examples, the developed approaches are applicable for field scale and complex pore network grids with arbitrary shapes.

It is often desirable to develop an integrated computational method for hydraulic conductivity of explosively created fracture networks which segmentation of fracture networks is not restricted to X-ray images, particularly when topologic and geometric modellings are the crucial parts. This research study provides insight to the reliable computational methods and pore network extraction algorithm selection processes, as well as defining a practical framework for generating reliable topological and geometrical data in a Eulerian SPH setting.