Authors:Liang Xia; Piotr Breitkopf Pages: 227 - 249 Abstract: Abstract Research on topology optimization mainly deals with the design of monoscale structures, which are usually made of homogeneous materials. Recent advances of multiscale structural modeling enables the consideration of microscale material heterogeneities and constituent nonlinearities when assessing the macroscale structural performance. However, due to the modeling complexity and the expensive computing requirement of multiscale modeling, there has been very limited research on topology optimization of multiscale nonlinear structures. This paper reviews firstly recent advances made by the authors on topology optimization of multiscale nonlinear structures, in particular techniques regarding to nonlinear topology optimization and computational homogenization (also known as FE2) are summarized. Then the conventional concurrent material and structure topology optimization design approaches are reviewed and compared with a recently proposed FE2-based design approach, which treats the microscale topology optimization process integrally as a generalized nonlinear constitutive behavior. In addition, discussions on the use of model reduction techniques is provided in regard to the prohibitive computational cost. PubDate: 2017-04-01 DOI: 10.1007/s11831-016-9170-7 Issue No:Vol. 24, No. 2 (2017)

Authors:T. Karthikeya Sharma; G. Amba Prasad Rao; K. Madhu Murthy Pages: 251 - 280 Abstract: Abstract Ranque–Hilsch vortex tube is a simple devise with no moving parts which could generate cold and hot air/gas streams simultaneously with compressed air/gas as a working fluid. The energy and flow separation in a vortex tube is highly depends on factors like nozzle shape, nozzle number, diameter and length of the vortex tube, inlet pressure, control valve, diaphragm hole size and cold mass fraction. As the energy separation and flow patterns in a vortex tube are highly complex and were not explained successfully by any researcher, a computational study of vortex tube flow and energy separation will give a better understanding about the physics and mechanism involved. Many researchers conducted computational fluid dynamic analysis of the vortex to have a deep insight about the process of flow separation. In this paper computational analysis of vortex by many researchers were presented along with the results obtained and suggestions to improve the performance of the vortex tube. Researchers considered Turbulence models which predict the performance precisely were discussed in the present paper. Researchers considered turbulence models like LES, k–ε, k–ω and RMS to predict the energy separation in vortex tube. Some researchers considered artificial neural networks (ANN) and Taguchi methods for their analysis. Comparison of the predictions with simulation results were also presented to give a clear idea for the reader about the CFD models prediction capabilities. PubDate: 2017-04-01 DOI: 10.1007/s11831-016-9166-3 Issue No:Vol. 24, No. 2 (2017)

Authors:Gabriel Hattori; Jon Trevelyan; Charles E. Augarde; William M. Coombs; Andrew C. Aplin Pages: 281 - 317 Abstract: Abstract Extracting gas from shale rocks is one of the current engineering challenges but offers the prospect of cheap gas. Part of the development of an effective engineering solution for shale gas extraction in the future will be the availability of reliable and efficient methods of modelling the development of a fracture system, and the use of these models to guide operators in locating, drilling and pressurising wells. Numerous research papers have been dedicated to this problem, but the information is still incomplete, since a number of simplifications have been adopted such as the assumption of shale as an isotropic material. Recent works on shale characterisation have proved this assumption to be wrong. The anisotropy of shale depends significantly on the scale at which the problem is tackled (nano, micro or macroscale), suggesting that a multiscale model would be appropriate. Moreover, propagation of hydraulic fractures in such a complex medium can be difficult to model with current numerical discretisation methods. The crack propagation may not be unique, and crack branching can occur during the fracture extension. A number of natural fractures could exist in a shale deposit, so we are dealing with several cracks propagating at once over a considerable range of length scales. For all these reasons, the modelling of the fracking problem deserves considerable attention. The objective of this work is to present an overview of the hydraulic fracture of shale, introducing the most recent investigations concerning the anisotropy of shale rocks, then presenting some of the possible numerical methods that could be used to model the real fracking problem. PubDate: 2017-04-01 DOI: 10.1007/s11831-016-9169-0 Issue No:Vol. 24, No. 2 (2017)

Authors:Pramod Kumar Parida; Tshilidzi Marwala; Snehashish Chakraverty Pages: 319 - 335 Abstract: Abstract In causal study we are interested in finding the graphical structure in the form of directed acyclic graphs (DAGs). These DAGs describe the directions and connection strength to connecting variables represented by nodes. In this regard, various methods have been developed to estimate the appropriate structure of the causal model and to explain a fair number of its features. Our review aims to provide a complete and systematic analysis of selected articles from past few decades, having powerful methods to infer the area of study. In this article, we categorized all selected articles in three groups, on the basis of techniques these used to construct the causal model. To provide a full comparative study under categories of probabilistic, statistical and algebraic approaches, we discussed underlying difficulties, limitations, merits and disadvantages in applying these techniques. The reader will find it helpful to choose and use the appropriate method for a better implication. PubDate: 2017-04-01 DOI: 10.1007/s11831-016-9168-1 Issue No:Vol. 24, No. 2 (2017)

Authors:Asif Afzal; Zahid Ansari; Ahmed Rimaz Faizabadi; M. K. Ramis Pages: 337 - 363 Abstract: Abstract Computational fluid dynamics (CFD) is one of the most emerging fields of fluid mechanics used to analyze fluid flow situation. This analysis is based on simulations carried out on computing machines. For complex configurations, the grid points are so large that the computational time required to obtain the results are very high. Parallel computing is adopted to reduce the computational time of CFD by utilizing the available resource of computing. Parallel computing tools like OpenMP, MPI, CUDA, combination of these and few others are used to achieve parallelization of CFD software. This article provides a comprehensive state of the art review of important CFD areas and parallelization strategies for the related software. Issues related to the computational time complexities and parallelization of CFD software are highlighted. Benefits and issues of using various parallel computing tools for parallelization of CFD software are briefed. Open areas of CFD where parallelization is not much attempted are identified and parallel computing tools which can be useful for parallelization of CFD software are spotlighted. Few suggestions for future work in parallel computing of CFD software are also provided. PubDate: 2017-04-01 DOI: 10.1007/s11831-016-9165-4 Issue No:Vol. 24, No. 2 (2017)

Authors:Ismet Baran; Kenan Cinar; Nuri Ersoy; Remko Akkerman; Jesper H. Hattel Pages: 365 - 395 Abstract: Abstract The increased usage of fiber reinforced polymer composites in load bearing applications requires a detailed understanding of the process induced residual stresses and their effect on the shape distortions. This is utmost necessary in order to have more reliable composite manufacturing since the residual stresses alter the internal stress level of the composite part during the service life and the residual shape distortions may lead to not meeting the desired geometrical tolerances. The occurrence of residual stresses during the manufacturing process inherently contains diverse interactions between the involved physical phenomena mainly related to material flow, heat transfer and polymerization or crystallization. Development of numerical process models is required for virtual design and optimization of the composite manufacturing process which avoids the expensive trial-and-error based approaches. The process models as well as applications focusing on the prediction of residual stresses and shape distortions taking place in composite manufacturing are discussed in this study. The applications on both thermoset and thermoplastic based composites are reviewed in detail. PubDate: 2017-04-01 DOI: 10.1007/s11831-016-9167-2 Issue No:Vol. 24, No. 2 (2017)

Authors:Arnab Banerjee; Avishek Chanda; Raj Das Pages: 397 - 422 Abstract: Abstract The impact is one of the most abundant phenomena in the field of multi-body dynamics when two or more bodies come in close vicinity and depending on the interaction properties and geometry, all the interacting bodies experience certain impulsive force for an infinitesimal duration. Nowadays, impact modelling becomes an intrinsic part in the modelling of structural pounding, granular materials, crash and machinery analysis, robotics and bio-mechatronics applications. Since the time of Newton, numerous literatures have been published on the modelling of both normal and oblique contact phenomena. The scope of this critical review is limited to consolidate the existing knowledge on the computational model of normal directional impact on rigid bodies. The literature related to modelling of oblique impact, soft body impact, impact damage in composites and associated stress wave propagation are excluded from the scope of this critical review. Smooth and non-smooth mechanics are two schools of thought in simulating the normal directional impact. In this review, the shortcomings of all the classes of compliance and non-smooth models are analysed in the unified dimensionless frame-work to compare their response output with the conventional stereo-mechanical model. This review opens a new avenue for future researchers in selecting a proper contact formulation for specific application. PubDate: 2017-04-01 DOI: 10.1007/s11831-016-9164-5 Issue No:Vol. 24, No. 2 (2017)

Authors:Francesco Pesavento; Bernhard A. Schrefler; Giuseppe Sciumè Pages: 423 - 448 Abstract: Abstract In this work we present a general model for the analysis of multiphase flow in deforming porous media with particular regard to concrete and biological tissues. Such problems are typically multi-physics ones with overlapping domains where diffusion, advection, adsorption, phase change, deformation, chemical reactions and other phenomena take place in the porous medium. For the analysis of such a complex system, the model here proposed is obtained from microscopic scale by applying the thermodynamically constrained averaging theory which guarantees the satisfaction of the second law of thermodynamics for all constituents both at micro and macro-level. Furthermore, one can obtain some important thermodynamic restrictions for the evolution equations describing the material deterioration. Two specific forms of the general model adapted to the cases of cementitious and biological materials respectively are shown. Some numerical simulations aimed at proving the validity of the approach adopted, are also presented and discussed. PubDate: 2017-04-01 DOI: 10.1007/s11831-016-9171-6 Issue No:Vol. 24, No. 2 (2017)

Abstract: Abstract The first goal of this work is to present a literature review regarding the use of several sets of admissible functions in the Ritz method. The papers reviewed deal mainly with the analysis of buckling and free vibration of isotropic and anisotropic beams and plates. Theoretically, in order to obtain a correct solution, the set of admissible functions must not violate the essential or geometric boundary conditions and should also be linearly independent and complete. However, in practice, some of the sets of functions proposed in the literature present a bad numerical behavior, namely in terms of convergence, computational time and stability. Thus, a second goal of the present work is to compare the performance of several sets of functions in terms of these three features. To achieve this objective, the free vibration analysis of a fully clamped rectangular plate is carried out using six different sets of functions, along with the study of the convergence of natural frequencies and mode shapes, the computational time and the numerical stability. PubDate: 2017-03-24

Authors:Alejandro Moreno-Gomez; Carlos A. Perez-Ramirez; Aurelio Dominguez-Gonzalez; Martin Valtierra-Rodriguez; Omar Chavez-Alegria; Juan P. Amezquita-Sanchez Abstract: Abstract In the last years, the occurrence of natural hazards around the world has evinced the necessity of having structural health monitoring schemes that can allow the continuous assessment of the structural integrity of the civil structures or infrastructures, in order to avoid potential economic or human loses; further, it also allows the application of new sensing technologies and signal processing algorithms. An important step in a structural health monitoring strategy is the appropriate selection of the sensor used to measure the required physical variable. Although several reviews have been published, they focus on presenting and/or explaining the methodologies and signal processing techniques used in structural health monitoring. This article presents a state-of-the-art review of the sensing technologies used in structural health monitoring. Further, some candidate sensor technologies with potential of use in this area are also reviewed, where the main issues that affect their implementation in real-life schemes are also discussed. PubDate: 2017-03-17 DOI: 10.1007/s11831-017-9217-4

Authors:Emmanuel Tromme; Alexander Held; Pierre Duysinx; Olivier Brüls Abstract: Abstract This paper reviews the state-of-the-art methods to perform structural optimization of flexible mechanisms. These methods are based on a system-based approach, i.e. the formulation of the design problem incorporates the time response of the mechanism that is obtained from a dynamic simulation of the flexible multibody system. The system-based approach aims at considering as precisely as possible the effects of nonlinear dynamic loading under various operating conditions. Also, the optimization process enhances most existing studies which are limited to (quasi-) static or frequency domain loading conditions. This paper briefly introduces flexible multibody system dynamics and structural optimization techniques. Afterwards, the two main methods, named the weakly and the fully coupled methods, that couple both disciplines are presented in details and the influence of the multibody system formalism is analyzed. The advantages and drawbacks of both methods are discussed and future possible research areas are mentioned. PubDate: 2017-03-07 DOI: 10.1007/s11831-017-9215-6

Authors:Ursula Rasthofer; Volker Gravemeier Abstract: Abstract The variational multiscale method is reviewed as a framework for developing computational methods for large-eddy simulation of turbulent flow. In contrast to other articles reviewing this topic, which focused on large-eddy simulation of turbulent incompressible flow, this study covers further aspects of numerically simulating turbulent flow as well as applications beyond incompressible single-phase flow. The various concepts for subgrid-scale modeling within the variational multiscale method for large-eddy simulation proposed by researchers in this field to date are illustrated. These conceptions comprise (i) implicit large-eddy simulation, represented by residual-based and stabilized methods, (ii) functional subgrid-scale modeling via small-scale subgrid-viscosity models and (iii) structural subgrid-scale modeling via the introduction of multifractal subgrid scales. An overview on exemplary numerical test cases to which the reviewed methods have been applied in the past years is provided, including explicit computational results obtained from turbulent channel flow. Wall-layer modeling, passive and active scalar transport as well as developments for large-eddy simulation of turbulent two-phase flow and combustion are discussed to complete this exposition. PubDate: 2017-02-27 DOI: 10.1007/s11831-017-9209-4

Authors:Georgios G. Vogiatzis; Doros N. Theodorou Abstract: Abstract Following the substantial progress in molecular simulations of polymer-matrix nanocomposites, now is the time to reconsider this topic from a critical point of view. A comprehensive survey is reported herein providing an overview of classical molecular simulations, reviewing their major achievements in modeling polymer matrix nanocomposites, and identifying several open challenges. Molecular simulations at multiple length and time scales, working hand-in-hand with sensitive experiments, have enhanced our understanding of how nanofillers alter the structure, dynamics, thermodynamics, rheology and mechanical properties of the surrounding polymer matrices. PubDate: 2017-02-22 DOI: 10.1007/s11831-016-9207-y

Authors:Giulia Scalet; Ferdinando Auricchio Abstract: Abstract The need of accurately reproducing the behaviour of elastoplastic materials in computational environments for the solution of engineering problems motivates the development of efficient and robust numerical schemes. These engineering problems often involve complex designs and/or conditions and are further complicated by the necessity of employing highly nonlinear and nonsmooth elastoplastic constitutive equations and constraints to describe material behaviour. Therefore, the numerical solution of such problems is not trivial and requires careful analyses to guarantee algorithm robustness, accuracy, and convergence in a reasonable amount of time. The aim of the present paper is to provide the reader with both an analysis and discussion, helpful in choosing the suitable numerical scheme when considering the implementation of a plasticity model. After a brief overview of the fundamental concepts for classical plasticity theory, we revise the state-of-the-art of computational methods by discussing conventional and less-conventional algorithms, formulated in a unified setting to allow for a comparison. Several approaches are implemented and discussed in representative numerical simulations. PubDate: 2017-02-21 DOI: 10.1007/s11831-016-9208-x

Authors:Luis Ramírez; Xesús Nogueira; Pablo Ouro; Fermín Navarrina; Sofiane Khelladi; Ignasi Colominas Abstract: Abstract In this work a higher-order accurate finite volume method for the resolution of the Euler/Navier–Stokes equations using Chimera grid techniques is presented. The formulation is based on the use of Moving Least Squares approximations in order to obtain higher-order accurate reconstruction and connectivity between the overlapped grids. The accuracy and performance of the proposed methodology is demonstrated by solving different benchmark problems. PubDate: 2017-02-14 DOI: 10.1007/s11831-017-9213-8

Authors:Biswarup Bhattacharyya Abstract: Abstract Surrogate models are widely used to predict response function of any system and in quantifying uncertainty associated with the response function. It is required to have response quantities at some preselected sample points to construct a surrogate model which can be processed in two way. Either the surrogate model is constructed using one shot experimental design techniques, or, the sample points can be generated in a sequential manner so that optimum sample points for a specific problem can be obtained. This paper addresses a comprehensive comparisons between these two types of sampling techniques for the construction of more accurate surrogate models. Two most popular one shot sampling strategies: Latin hypercube sampling and Sobol sequence, and four different type sequential experimental designs (SED) namely, Monte Carlo intersite projected (MCIP), Monte Carlo intersite projected threshold (MCIPT), optimizer projected (OP) and LOLA-Voronoi (LV) method are taken for the present study. Two most widely used surrogate models, namely polynomial chaos expansion and Kriging are used to check the applicability of the experimental design techniques. Three different types of numerical problems are solved using the two above-mentioned surrogate models considering all the experimental design techniques independently. Further, all the results are compared with the standard Monte Carlo simulation (MCS). Overall study depicts that SED performs well in predicting the response functions more accurately with an acceptable number of sample points even for high-dimensional problems which maintains the balance between accuracy and efficiency. More specifically, MCIPT and LV method based Kriging outperforms other combinations. PubDate: 2017-02-08 DOI: 10.1007/s11831-017-9211-x

Authors:Mijo Nikolić; Emir Karavelić; Adnan Ibrahimbegovic; Predrag Miščević Abstract: Abstract This paper presents the lattice element models, as a class of discrete models, in which the structural solid is represented as an assembly of one-dimensional elements. This idea allows one to provide robust models for propagation of discontinuities, multiple cracks interaction or cracks coalescence. Many procedures for computation of lattice element parameters for representing linear elastic continuum have been developed, with the most often used ones discussed herein. Special attention is dedicated to presenting the ability of this kind of models to consider material disorder, heterogeneities and multi-phase materials, which makes lattice models attractive for meso- or micro-scale simulations of failure phenomena in quasi-brittle materials, such as concrete or rocks. Common difficulties encountered in material failure and a way of dealing with them in the lattice models framework are explained in detail. Namely, the size of the localized fracture process zone around the propagating crack plays a key role in failure mechanism, which is observed in various models of linear elastic fracture mechanics, multi-scale theories, homogenization techniques, finite element models, molecular dynamics. An efficient way of dealing with this kind of phenomena is by introducing the embedded strong discontinuity into lattice elements, resulting with mesh-independent computations of failure response. Moreover, mechanical lattice can be coupled with mass transfer problems, such as moisture, heat or chloride ions transfer which affect the material durability. Any close interaction with a fluid can lead to additional time dependent degradation. For illustration, the lattice approach to porous media coupling is given here as well. Thus, the lattice element models can serve for efficient simulations of material failure mechanisms, even when considering multi-physics coupling. The main peculiarities of such an approach have been presented and discussed in this work. PubDate: 2017-02-03 DOI: 10.1007/s11831-017-9210-y

Authors:Nitin Shrivastava; Zubair Mohd. Khan Abstract: Abstract It is well known that fossil fuels are depleting day by day, and with the increase in the number of vehicles the pollution has reached at an alarming stage. The need of the hour is to find an alternate fuel as well as to demote the exhaust emission and enhance the performance parameters of the internal combustion (I.C.) engine. Researches on I.C. engines are being conducted in order to come to a feasible solution. Since performing experiments on an I.C. engine is both time consuming and costly therefore many soft computing techniques are being adopted in this field. The term soft computing refers to find the solution of an inexact problem. Different soft computing techniques being used in this field are Artificial Neural Network, Fuzzy Based Approach, Adaptive Neuro Fuzzy Inference System, Gene Expression Programming, Genetic Algorithm and Particle Swarm Optimization. The motive of this work is to review the researches being carried out in the field of I.C. engine on different types of engines with various alternative fuels using these soft computing techniques. PubDate: 2017-02-01 DOI: 10.1007/s11831-017-9212-9

Authors:Guillermo Vilanova; Ignasi Colominas; Hector Gomez Abstract: Abstract Angiogenesis is the growth of new capillaries from preexisting ones. The ability to trigger angiogenesis is one of the hallmarks of cancer, and is a necessary step for a tumor to become malignant. This paper discusses computational modeling of tumor-induced angiogenesis with particular reference to mathematical modeling, numerical simulation, and comparison with experiments. We describe the basic biological phenomena associated with angiogenesis, and discuss how they can be incorporated into mathematical models. We emphasize the crucial role of numerical methods for model development. In particular, computational methods for tumor angiogenesis need to be geometrically flexible and capable of dealing with higher-order derivatives, which suggests isogeometric analysis as an ideal candidate. Finally, we propose an algorithm based on graph theory as a potential method for quantitative validation of tumor angiogenesis models. PubDate: 2017-01-16 DOI: 10.1007/s11831-016-9199-7

Authors:Jana Wäldchen; Patrick Mäder Abstract: Abstract Species knowledge is essential for protecting biodiversity. The identification of plants by conventional keys is complex, time consuming, and due to the use of specific botanical terms frustrating for non-experts. This creates a hard to overcome hurdle for novices interested in acquiring species knowledge. Today, there is an increasing interest in automating the process of species identification. The availability and ubiquity of relevant technologies, such as, digital cameras and mobile devices, the remote access to databases, new techniques in image processing and pattern recognition let the idea of automated species identification become reality. This paper is the first systematic literature review with the aim of a thorough analysis and comparison of primary studies on computer vision approaches for plant species identification. We identified 120 peer-reviewed studies, selected through a multi-stage process, published in the last 10 years (2005–2015). After a careful analysis of these studies, we describe the applied methods categorized according to the studied plant organ, and the studied features, i.e., shape, texture, color, margin, and vein structure. Furthermore, we compare methods based on classification accuracy achieved on publicly available datasets. Our results are relevant to researches in ecology as well as computer vision for their ongoing research. The systematic and concise overview will also be helpful for beginners in those research fields, as they can use the comparable analyses of applied methods as a guide in this complex activity. PubDate: 2017-01-07 DOI: 10.1007/s11831-016-9206-z