Abstract: Publication date: August 2019Source: Advances in Engineering Software, Volume 134Author(s): Erfan Niazi, James G. McDonald, Marianne Fenech Over the past several decades, image processing and automated tracking of particles has emerged as a useful tool for the study of biological particles behaviour. This article describes an open-source computational implementation of a method for determining particle velocity and size distributions of large groups of particles by analyzing video sequences acquired using a video-microscopic systems. Although, in this study, red blood cells are used as a subject, this implementation can be used for any particle-laden flow where particles present a range of sizes and details of the velocity distribution of each size is of interest.From each single image, the current program detects particles and classifies them according to their size. It uses sequential images to track particles and compute the instantaneous velocity distribution of the particles. The tool can also assign an ellipse to each particle and report the major axis, the minor axis and the orientation of particles in each image. Use of the program improves repeatability of image processing and is suitable for studies related to particle dynamics, colloids, and microfluidic flow measurement. The size distribution and the velocity distribution of particles is often useful in the study of effect of parameters like shear stress on particle collision rate, agglomeration and breakage rate.

Abstract: Publication date: August 2019Source: Advances in Engineering Software, Volume 134Author(s): Chunming Fu, Lixiong Cao An interval differential evolution (IDE) with adaptive subinterval decomposition analysis is suggested to directly solve the nonlinear uncertain optimization problems with interval parameters. The adaptive subinterval decomposition analysis technique is proposed to calculate the upper and lower bounds of objective function and constraints caused by interval uncertainties. An adaptive convergence mechanism is utilized to ensure the accuracy of achieved bounds. Moreover, within the framework of IDE, the interval possibility model is employed to deal with the interval constraints of uncertain optimization problems and the interval preferential rule is used to select the promising solutions to retain into the next evolutionary population. Both numerical and engineering examples are eventually given to demonstrate the validity of the proposed method.

Abstract: Publication date: Available online 9 May 2019Source: Advances in Engineering SoftwareAuthor(s): V. Partimbene, T. Garcia, P. Spiteri, P. Marthon, L. Ratsifandrihana This paper deals with the solution of fluid-structure interaction problems using an algorithm consisting in the coupling between two solvers, each one related to the fluid and the structure respectively. Due to the difficult decomposition of the domain into sub-domains, we consider for each environment a parallel multi-splitting algorithm which corresponds to an unified presentation of sub-domain methods with or without overlapping. Such method combines several contractant fixed point mappings and, we show that, under appropriate assumptions, each fixed point mapping are contractive in finite dimensional spaces normed by Hilbertian and non-Hilbertian norms. Moreover, we show in a novel way that such study is valid for the parallel synchronous and more generally asynchronous large scale linear systems arising in the solution of fluid-structure interaction problems and can be extended to the case where the displacement of the structure is submitted to some constraints. We perform parallel simulations for a fluid-structure test case on different clusters, considering blocking and non-blocking communications. The performances of the parallel simulations are presented and analyzed.

Abstract: Publication date: July 2019Source: Advances in Engineering Software, Volume 133Author(s): Deborah Briccola, Matteo Bruggi A new numerical procedure is presented to perform the analysis of three-dimensional linear elastic no-tension structures exploiting the application programming interface of a general purpose finite element analysis software. Masonry is replaced by an equivalent orthotropic material with spatially varying elastic properties and negligible stiffness in the case of cracking strain. A non-incremental algorithm is implemented to define the distribution of the equivalent material, minimizing the strain energy so as to achieve a compression-only state of stress for any given compatible load. Applications are shown for masonry-like solids of general shape visualizing load paths in walls subject to dead loads and out-of-plane live loads, circular domes under self-weight and a groin vault acted upon by both vertical and horizontal seismic loading.

Abstract: Publication date: July 2019Source: Advances in Engineering Software, Volume 133Author(s): José A. López-Campos, Abraham Segade, Enrique Casarejos, José R. Fernández, Gustavo R. Días In this work we highlight the capabilities of genetic algorithms to characterize the behavior shown by hyperelastic materials. We use three fitting tools, two of them included in commercial Finite Element packages and one developed using genetic algorithm methods. Four classic hyperelastic models are employed to test the different tools and to characterize a rubbery material. We show that automatic tools provide accurate data in limited ranges depending in the models. Indeed, not always can fit large strain ranges for the models. However, the dedicated genetic algorithm method performed correctly with all models and wide strain ranges, providing a robust and efficient fitting method. The results are included in a finite element model to study the differences appearing for complex stress states produced only by the selection of the material model. Compressibility effects are also studied to show the large differences in the results if only uniaxial tensile test data is used to characterize compressible hyper-elastic materials, independently of the efficiency of the fitting tools and the selection of the material model.

Abstract: Publication date: July 2019Source: Advances in Engineering Software, Volume 133Author(s): Adrian R. G. Harwood This article develops novel application software which implements interactive, GPU-powered flow simulation on a group of wirelessly-connected mobile devices. Interactive simulation is an emerging field in engineering with use cases appearing in design, analysis and communication. Herein, we present a new Android-based, interactive flow solver capable of running on a wider range of multiple, wirelessly-connected mobile GPUs. The software consists of a 2D Lattice-Boltzmann Method flow physics solver, implemented using OpenGL ES 3.2, as well as a communication library which uses Wi-Fi Direct to communicate between connected devices. We compare the performance of the OpenGL-based solver against existing implementations in CUDA and demonstrate similar computational throughput. We also test a variety of communication strategies based on configurations of GPU memory mapping and communication frequency. Results confirm that passing large amounts of data infrequently offers the best overall efficiency. However, due to the extended time required to pass larger amounts of data to adjacent devices, this configuration can introduce an undesirable stuttering in an interactive application. Finally, comparisons between two and three device networks to the serial case show that, despite the inevitable cost of communication, it is possible to maintain an interactive frame rate across multiple devices; the extension of calculations across multiple devices in this way, allows the tackling of problems which are larger and of higher-resolution that previous.

Abstract: Publication date: July 2019Source: Advances in Engineering Software, Volume 133Author(s): Giuliano Vernengo, Luca Bonfiglio The engineering design of a three dimensional submerged hydrofoil operating at very high speeds is obtained leveraging a Differential Evolution (DE) approach. The final goal is to identify the optimal load distribution over the span of a super-cavitating hydrofoil by using a design by optimization approach driven by hydrodynamic analysis of complex, turbulent, multi-phase flows. We achieve this goal by modeling the load distribution over the hydrofoil by means of a B-spline curve, which provides a rigorous parametric description of the hydrofoil operating conditions through the points of the load distribution control polygon. The parametric model includes design variables representing the most relevant hydrofoil shape parameters. We predict hydrodynamic performance by means of a Viscous Lifting Line method specifically conceived for the application targeted in the present study. This computational model accounts for the strong non-linear hydrodynamic characteristics of super-cavitating hydrofoils. We demonstrate the validity of the proposed design by optimization framework for high speed super-cavitating hydrofoils showcasing two design applications, namely a fully submerged hydrofoil operating close to a rigid boundary and a surface-piercing hydrofoil with variable dihedral angle. A statistical analysis of DE algorithm is performed to assess its performance on such an engineering design problem.

Abstract: Publication date: July 2019Source: Advances in Engineering Software, Volume 133Author(s): Kazuki Hayashi, Makoto Ohsaki This paper presents a new efficient tool for simultaneous optimization of topology and geometry of truss structures. Force density method is applied to formulate optimization problem to minimize compliance under constraint on total structural volume, and objective and constraint functions are expressed as explicit functions of force density only. This method does not need constraints on nodal locations to avoid coalescent nodes, and enables to generate optimal solutions with a variety in topology and geometry. Furthermore, for the purpose of controlling optimal shapes, tensor product Bézier surface is introduced as a design surface. The optimization problem is solved using sensitivity coefficients and the optimizer is compiled as a component compatible with Grasshopper, an algorithmic modeling plug-in for Rhinoceros, which is a popular 3D modeling software. Efficiency and accuracy of the proposed method are demonstrated through two numerical examples of semi-cylindrical and semi-spherical models.

Abstract: Publication date: July 2019Source: Advances in Engineering Software, Volume 133Author(s): Guanghui Zhou, Xiongjun Yang, Chao Zhang, Zhi Li, Zhongdong Xiao Each complex product contains many special-shaped machining features required to be machined by the specific customized cutting tools. In this context, we propose a deep learning based cutting tool selection approach, which contributes to make it effective and efficiency for and also improves the intelligence of the process of cutting tool selection for special-shaped machining features of complex products. In this approach, one-to-one correspondence between each special-shaped machining feature and each cutting tool is first analyzed and established. Then, the problem of cutting tool selection could be transformed into a feature recognition problem. To this end, each special-shaped machining feature is represented by its multiple drawing views that contain rich information for differentiating each of these features. With numbers of these views as training set, a deep residual network (ResNet) is trained successfully for feature recognition, where the recognized feature's cutting tool could also be automatically selected based on the one-to-one correspondence. With the learned ResNet, engineers could use an engineering drawing to select cutting tools intelligently. Finally, the proposed approach is applied to the special-shaped machining features of a vortex shell workpiece to demonstrate its feasibility. The presented approach provides a valuable insight into the intelligent cutting tool selection for special-shaped machining features of complex products.

Abstract: Publication date: July 2019Source: Advances in Engineering Software, Volume 133Author(s): Xiaofei Wan, Xiandong Liu, Yingchun Shan, Er Jiang, Haiwen Yuan The effect of tire on the wheel should be considered in detail in the process of simulating 13° impact test of the automotive wheel. However, due to the complexity and nonlinearity of the tire, the tire is usually simplified or neglected in the current simulation of wheel impact test, and these often lead to insufficient simulation accuracy. In this paper, a numerical simulation approach is proposed to evaluate the impact performance of wheel, in which the finite element model of tire is established in terms of the real tire. The physical wheel 13° impact tests are also performed, and the comparison between the simulation and experiment indicate that the proposed simulation method provides an efficient tool for predicting the impact performance of the wheel in wheel 13° impact test. Furthermore, the effects of tire on wheel are discussed by comparing the simulation and experiment results, and the results show the tire has a dual effect on wheel performance during the wheel 13° impact test.

Abstract: Publication date: Available online 19 January 2007Source: Advances in Engineering SoftwareAuthor(s): T.T. Tanyimboh, A.B. TemplemanThis article has been removed consistent with Elsevier Policy on Article Withdrawal. The Publisher apologises for any inconvenience this may cause.