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)

Authors:Raquel García-Blanco; Pedro Díez; Domenico Borzacchiello; Francisco Chinesta Abstract: Abstract The power flow model performs the analysis of electric distribution and transmission systems. With this statement at hand, in this work we present a summary of those solvers for the power flow equations, in both algebraic and parametric version. The application of the Alternating Search Direction method to the power flow problem is also detailed. This results in a family of iterative solvers that combined with Proper Generalized Decomposition technique allows to solve the parametric version of the equations. Once the solution is computed using this strategy, analyzing the network state or solving optimization problems, with inclusion of generation in real-time, becomes a straightforward procedure since the parametric solution is available. Complementing this approach, an error strategy is implemented at each step of the iterative solver. Thus, error indicators are used as an stopping criteria controlling the accuracy of the approximation during the construction process. The application of these methods to the model IEEE 57-bus network is taken as a numerical illustration. PubDate: 2017-04-25 DOI: 10.1007/s11831-017-9223-6

Authors:Guangyuan Kan; Xiaoyan He; Jiren Li; Liuqian Ding; Yang Hong; Hongbin Zhang; Ke Liang; Mengjie Zhang Abstract: Abstract In this paper, the computer aided numerical method for hydrological model calibration is reviewed. The content includes review of the watershed hydrological models (data-driven model, conceptual model, and distributed model), review of the model calibration methods (manual calibration, single-objective automatic calibration, multi-objective automatic calibration, objective function, termination criterion, and data utilized for calibration), and review of the parallel computing accelerated model calibration (multi-node computer cluster, multi-core CPU, many-core GPU, and heterogeneous parallel computing). Recent development and the state-of-the-art are also analyzed. Three conclusions can be drawn: (1) Nowadays, different types of hydrological models have their own application fields and perform very well. Distributed hydrological model becomes the development direction and has a good future. (2) Computer aided automatic hydrological model calibration method has become the mainstream. Single-objective optimization method such as SCE-UA and multi-objective optimization method such as NSGA-II are very suitable to the model parameter calibration. (3) Heterogeneous parallel computing technology is the most powerful acceleration method for the hydrological model parameter calibration. However, researches about the acceleration of SCE-UA and NSGA-II based on heterogeneous parallel computing technique is rare and should be focused in the future. PubDate: 2017-04-25 DOI: 10.1007/s11831-017-9224-5

Authors:Sam Hewitt; Lee Margetts; Alistair Revell Abstract: Abstract The purpose of this paper is to provide a high level, holistic overview of the work being undertaken in the wind energy industry. It summarises the main techniques used to simulate both aerodynamic and structural issues associated with wind turbines and farms. The motivation behind this paper is to provide new researchers with an outlook of the modelling and simulation landscape, whilst highlighting the trends and direction research is taking. Each section summarises an individual area of simulation and modelling, covering the important historical research findings and a comprehensive analysis of recent work. This segregated approach emphasises the key components of wind energy. Topics range in geometric scales and detail, ranging from atmospheric boundary layer modelling, to fatigue and fracture in the turbine blades. More recent studies have begun to combine a range of scales and physics to better approximate real systems and provide higher fidelity and accurate analyses to manufacturers and companies. This paper shows a clear trend towards coupling both scales and physics into singular models utilising high performance computing system. PubDate: 2017-04-18 DOI: 10.1007/s11831-017-9222-7

Authors:Lionel Mathelin; Kévin Kasper; Hisham Abou-Kandil Abstract: Abstract This paper introduces a method for efficiently inferring a high-dimensional distributed quantity from a few observations. The quantity of interest (QoI) is approximated in a basis (dictionary) learned from a training set. The coefficients associated with the approximation of the QoI in the basis are determined by minimizing the misfit with the observations. To obtain a probabilistic estimate of the quantity of interest, a Bayesian approach is employed. The QoI is treated as a random field endowed with a hierarchical prior distribution so that closed-form expressions can be obtained for the posterior distribution. The main contribution of the present work lies in the derivation of a representation basis consistent with the observation chain used to infer the associated coefficients. The resulting dictionary is then tailored to be both observable by the sensors and accurate in approximating the posterior mean. An algorithm for deriving such an observable dictionary is presented. The method is illustrated with the estimation of the velocity field of an open cavity flow from a handful of wall-mounted point sensors. Comparison with standard estimation approaches relying on Principal Component Analysis and K-SVD dictionaries is provided and illustrates the superior performance of the present approach. PubDate: 2017-04-11 DOI: 10.1007/s11831-017-9219-2

Authors:Kailash Lachhwani; Abhishek Dwivedi Abstract: Abstract This paper presents taxonomy of detailed literature reviews on bi-level programming problems (BLPPs), multi-level programming problems (MLPPs) and associated research problems, while providing detail of solution techniques at the same time. In this taxonomy of review, we classified the multi-level programming problems into two types: (i) General multi-level programming problems (MLPPs) (ii) multi-level multi-objective programming problems (ML-MOPPs) which are further sub classified based on the algorithmic and optimality studies. Bi-level programming problems (BLPPs) are considered as special cases of multi-level programming problems with two level structures. The present literature review includes approximately all prior and latest references on BLPPs, and MLPPs, related solution methodologies. The general related concepts are briefly described while associated references are included for further investigations. The aim of this paper is to provide an easy and systematic road map of currently available literature studies on BLPPs and MLPPs for future researchers. PubDate: 2017-04-09 DOI: 10.1007/s11831-017-9216-5

Authors:Fayçal Ikhouane Abstract: Abstract The Duhem model is a simulacrum of a complex and hazy reality: hysteresis. Introduced by Pierre Duhem to provide a mathematical representation of thermodynamical irreversibility, it is used to describe hysteresis in other areas of science and engineering. Our aim is to survey the relationship between the Duhem model as a mathematical representation, and hysteresis as the object of that representation. PubDate: 2017-03-29 DOI: 10.1007/s11831-017-9218-3

Authors:Pablo Moreno-García; José V. Araújo dos Santos; Hernani Lopes 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 DOI: 10.1007/s11831-017-9214-7

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