Purpose - Nature-inspired algorithms are among the most powerful algorithms for optimization. The purpose of this paper is to introduce a new nature-inspired metaheuristic optimization algorithm, called bat algorithm (BA), for solving engineering optimization tasks.Design methodology approach - The proposed BA is based on the echolocation behavior of bats. After a detailed formulation and explanation of its implementation, BA is verified using eight nonlinear engineering optimization problems reported in the specialized literature.Findings - BA has been carefully implemented and carried out optimization for eight well-known optimization tasks; then a comparison has been made between the proposed algorithm and other existing algorithms.Originality value - The optimal solutions obtained by the proposed algorithm are better than the best solutions obtained by the existing methods. The unique search features used in BA are analyzed, and their implications for future research are also discussed in detail.
Purpose – The purpose of this paper is to elucidate the detailed flow field and cavitation effect in the centrifugal pump volute at partial load condition. Design/methodology/approach – Unsteady flows in a centrifugal pump volute at non-cavitation and cavitation conditions are investigated by using a computation fluid dynamics framework combining the re-normalization group k-e turbulence model and the mass transport cavitation model. Findings – The flow field in pump volute is very complicated at part load condition with large pressure gradient and intensive vortex movement. Under cavitation conditions, the dominant frequency for most of the monitoring points in volute transit from the blade passing frequency to a lower frequency. Generally, the maximum amplitudes of pressure fluctuations in volute at serious cavitation condition is twice than that at non-cavitation condition because of the violent disturbances caused by cavitation shedding and explosion. Originality/value – The detailed flow field and cavitation effect in the centrifugal pump volute at partial load condition are revealed and analysed.
Purpose - Meta-heuristic algorithms are efficient in achieving the optimal solution for engineering problems. Hybridization of different algorithms may enhance the quality of the solutions and improve the efficiency of the algorithms. The purpose of this paper is to propose a novel, robust hybrid meta-heuristic optimization approach by adding differential evolution (DE) mutation operator to the accelerated particle swarm optimization (APSO) algorithm to solve numerical optimization problems. Design/methodology/approach - The improvement includes the addition of DE mutation operator to the APSO updating equations so as to speed up convergence. Findings - A new optimization method is proposed by introducing DE-type mutation into APSO, and the hybrid algorithm is called differential evolution accelerated particle swarm optimization (DPSO). The difference between DPSO and APSO is that the mutation operator is employed to fine-tune the newly generated solution for each particle, rather than random walks used in APSO. Originality/value - A novel hybrid method is proposed and used to optimize 51 functions. It is compared with other methods to show its effectiveness. The effect of the DPSO parameters on convergence and performance is also studied and analyzed by detailed parameter sensitivity studies.
Purpose - The complexity of analysis of geotechnical behavior is due to multivariable dependencies of soil and rock responses. In order to cope with this complex behavior, traditional forms of engineering design solutions are reasonably simplified. Incorporating simplifying assumptions into the development of the traditional models may lead to very large errors. The purpose of this paper is to illustrate capabilities of promising variants of genetic programming (GP), namely linear genetic programming (LGP), gene expression programming (GEP), and multi-expression programming (MEP) by applying them to the formulation of several complex geotechnical engineering problems.Design methodology approach - LGP, GEP, and MEP are new variants of GP that make a clear distinction between the genotype and the phenotype of an individual. Compared with the traditional GP, the LGP, GEP, and MEP techniques are more compatible with computer architectures. This results in a significant speedup in their execution. These methods have a great ability to directly capture the knowledge contained in the experimental data without making assumptions about the underlying rules governing the system. This is one of their major advantages over most of the traditional constitutive modeling methods.Findings - In order to demonstrate the simulation capabilities of LGP, GEP, and MEP, they were applied to the prediction of: relative crest settlement of concrete-faced rockfill dams; slope stability; settlement around tunnels; and soil liquefaction. The results are compared with those obtained by other models presented in the literature and found to be more accurate. LGP has the best overall behavior for the analysis of the considered problems in comparison with GEP and MEP. The simple and straightforward constitutive models developed using LGP, GEP and MEP provide valuable analysis tools accessible to practicing engineers.Originality value - The LGP, GEP, and MEP approaches overcome the shortcomings of different methods previously presented in the literature for the analysis of geotechnical engineering systems. Contrary to artificial neural networks and many other soft computing tools, LGP, GEP, and MEP provide prediction equations that can readily be used for routine design practice. The constitutive models derived using these methods can efficiently be incorporated into the finite element or finite difference analyses as material models. They may also be used as a quick check on solutions developed by more time consuming and in-depth deterministic analyses.
Purpose – Mobile Service of Big Data can be supported by the fused technologies of computing, communication and digital multimedia. The purpose of this paper is to propose new agent-based proactive migration method and system for Big Data Environment (BDE). Design/methodology/approach – First, the authors have designed new relative fusion method for making decision based on fuzzy-neural network. The method can make the fusion belief degree to be improved. Then the authors have proposed agent-based proactive migrating method with service discovery and key frames selection strategy. Finally, the authors have designed the application system, which can support proactive seamless migration function for big data. The method has innovation in which mobile service task of big data can dynamically follow its mobile user from one device to another device. Findings – The authors have proposed agent-based proactive migrating method with service discovery and key frames selection strategy. The method has innovation in which mobile service task of big data can dynamically follow its mobile user from one device to another device. The designed system is convenient to work and use during mobility, and which is useful or helpful for mobile user in the BDE. Originality/value – The authors have clarified and realizes how to transfer service tasks among different distances in Big Data Environment (BDE). The authors have given a formal description and classification of the mobile service task, which is independent of the realization mechanism. In the designed and developed application system, the new idea adopts fuzzy-neural control theory to make decision for task-oriented proactive seamless migration application.
Purpose The effect of a magnetic field on nanofluid natural convection in a porous annulus is simulated. Control volume-based finite element method (CVFEM) is applied to find the influence of tilted angle and Darcy, Rayleigh and Hartmann numbers on nanofluid hydrothermal behavior. Vorticity stream function formulation is taken into account. Also, Brownian motion effect on nanofluid thermal conductivity is considered. Results reveal that Hartmann number and tilted angle make changes in nanofluid flow style. Nusselt number enhances with augment of Darcy number and buoyancy forces but reduces with rise of tilted angle and Hartmann number. Design/methodology/approach The influence of adding CuO nanoparticles in water on the velocity and temperature distribution in an inclined half-annulus was studied considering constant heat flux. CVFEM is applied to the simulation procedure. Findings Influences of CuO volume fraction, inclination angle and Rayleigh number on hydrothermal manners are presented. Originality/value Results indicate that inclination angle makes changes in flow style. The temperature gradient enhances with rise of buoyancy forces, whereas it reduces with augment of inclination angle.
Purpose The performance of the measurement matrix directly affects the quality of reconstruction of compressive sensing signal, and it is also the key to solve practical problems. In order to solve data collection problem of wireless sensor network (WSN), the authors design a kind of optimization of sparse matrix. The paper aims to discuss these issues. Design/methodology/approach Based on the sparse random matrix, it optimizes the seed vector, which regards elements in the diagonal matrix of Hadamard matrix after passing singular value decomposition (SVD). Compared with the Toeplitz matrix, it requires less number of independent random variables and the matrix information is more concentrated. Findings The performance of reconstruction is better than that of Gaussian random matrix. The authors also apply this matrix to the data collection scheme in WSN. The result shows that it costs less energy and reduces the collection frequency of nodes compared with general method. Originality/value The authors design a kind of optimization of sparse matrix. Based on the sparse random matrix, it optimizes the seed vector, which regards elements in the diagonal matrix of Hadamard matrix after passing SVD. Compared with the Toeplitz matrix, it requires less number of independent random variables and the matrix information is more concentrated.
Purpose The communication link in the engineering of Internet of Vehicle (IOV) is more frequent than the communication link in the Mobile ad hoc Network (MANET). Therefore, the highly dynamic network routing reliability problem is a research hotspot to be solved. Design/methodology/approach The graph theory is used to model the MANET communication diagram on the highway and propose a new reliable routing method for internet of vehicles based on graph theory. Findings The expanded graph theory can help capture the evolution characteristics of the network topology and predetermine the reliable route to promote quality of service (QoS) in the routing process. The program can find the most reliable route from source to the destination from the MANET graph theory. Originality/value The good performance of the proposed method is verified and compared with the related algorithms of the literature.
Purpose - The purpose of this paper is to consider the thermal-diffusion and diffusion-thermo effects on combined heat and mass transfer of a steady magnetohydrodynamic (MHD) convective and slip flow due to a rotating disk with viscous dissipation and Ohmic heating. The main goal of the present study is to find the approximate analytic solutions by the combination of the DTM and the Padé approximants for this problem.Design methodology approach - A new method, namely the DTM-Padé technique, which is a combination of the differential transform method and the Padé approximation, is employed.Findings - Graphical results for fluids of medium molecular weight (H2, air) are presented to investigate influence of the slip parameter, magnetic field parameter M, Eckert Ec, Schmidt Ec, Dufour Du and Soret Sr numbers on the profiles of the dimensionless velocity, temperature and concentration distributions. In order to show the effectiveness of the DTM-Padé, the results obtained from the DTM-Padé are compared with available solutions obtained using shooting method to generate the numerical solution.Originality value - This technique (DTM-Padé) is extended to give solutions for nonlinear differential equations with boundary conditions at the infinity.
Purpose – The purpose of this paper is to achieve numerical simulation of cohesive crack growth in concrete structures. Design/methodology/approach – The extended finite element method (XFEM) using four-node quadrilateral element associated with the fictitious cohesive crack model is used. A mixed-mode traction-separation law is assumed for the cohesive crack in the fracture process zone (FPZ). Enrichments are considered for both partly and fully cracked elements, and it thus makes the evolution of crack to any location inside the element possible. In all. two new solution procedures based on Newton-Raphson method, which differ from the approach suggested by Zi and Belytschko (2003), are presented to solve the nonlinear system of equations. The present formulation results in a symmetric tangent matrix, conveniently in finite element implementation and programming. Findings – The inconvenience in solving the inversion of an unsymmetrical Jacobian matrix encountered in the existing approach is avoided. Numerical results evidently confirm the accuracy of the proposed approach. It is concluded that the developed XFEM approach is especially suitable in simulating cohesive crack growth in concrete structures. Research limitations/implications – Multiple cracks and crack growth in reinforced concretes should be considered in further studies. Practical implications – The research paper presents a very useful and accurate numerical method for engineering application problems that has ability to numerically simulate the cohesive crack growth of concrete structures. Originality/value – The research paper provides a new numerical approach using two new solution procedures in solving nonlinear system of equations for cohesive crack growth in concrete structures that is very convenient in programming and implementation.
Purpose - The computational drawbacks of existing numerical methods have forced researchers to rely on heuristic algorithms. Heuristic methods are powerful in obtaining the solution of optimization problems. Although they are approximate methods (i.e. their solution are good, but not provably optimal), they do not require the derivatives of the objective function and constraints. Also, they use probabilistic transition rules instead of deterministic rules. The purpose of this paper is to present an improved ant colony optimization (IACO) for constrained engineering design problems.Design methodology approach - IACO has the capacity to handle continuous and discrete problems by using sub-optimization mechanism (SOM). SOM is based on the principles of finite element method working as a search-space updating technique. Also, SOM can reduce the size of pheromone matrices, decision vectors and the number of evaluations. Though IACO decreases pheromone updating operations as well as optimization time, the probability of finding an optimum solution is not reduced.Findings - Utilizing SOM in the ACO algorithm causes a decrease in the size of the pheromone vectors, size of the decision vector, size of the search space, the number of function evaluations, and finally the required optimization time. SOM performs as a search-space-updating rule, and it can exchange discrete-continuous search domain to each other.Originality value - The suitability of using ACO for constrained engineering design problems is presented, and applied to optimal design of different engineering problems.
Purpose - The purpose of this paper is to show how particle scale simulation of industrial particle flows using DEM (discrete element method) offers the opportunity for better understanding of the flow dynamics leading to improvements in equipment design and operation.Design methodology approach - The paper explores the breadth of industrial applications that are now possible with a series of case studies.Findings - The paper finds that the inclusion of cohesion, coupling to other physics such fluids, and its use in bubbly and reacting flows are becoming increasingly viable. Challenges remain in developing models that balance the depth of the physics with the computational expense that is affordable and in the development of measurement and characterization processes to provide this expanding array of input data required. Steadily increasing computer power has seen model sizes grow from thousands of particles to many millions over the last decade, which steadily increases the range of applications that can be modelled and the complexity of the physics that can be well represented.Originality value - The paper shows how better understanding of the flow dynamics leading to improvements in equipment design and operation can potentially lead to large increases in equipment and process efficiency, throughput and or product quality. Industrial applications can be characterised as large, involving complex particulate behaviour in typically complex geometries. The critical importance of particle shape on the behaviour of granular systems is demonstrated. Shape needs to be adequately represented in order to obtain quantitative predictive accuracy for these systems.
Purpose Development of techniques for expedited design optimization of complex and numerically expensive electromagnetic (EM) simulation models of antenna structures validated both numerically and experimentally. The paper aims to discuss these issues. Design/methodology/approach The optimization task is performed using a technique that combines gradient search with adjoint sensitivities, trust region framework, as well as EM simulation models with various levels of fidelity (coarse, medium and fine). Adaptive procedure for switching between the models of increasing accuracy in the course of the optimization process is implemented. Numerical and experimental case studies are provided to validate correctness of the design approach. Findings Appropriate combination of suitable design optimization algorithm embedded in a trust region framework, as well as model selection techniques, allows for considerable reduction of the antenna optimization cost compared to conventional methods. Research limitations/implications The study demonstrates feasibility of EM-simulation-driven design optimization of antennas at low computational cost. The presented techniques reach beyond the common design approaches based on direct optimization of EM models using conventional gradient-based or derivative-free methods, particularly in terms of reliability and reduction of the computational costs of the design processes. Originality/value Simulation-driven design optimization of contemporary antenna structures is very challenging when high-fidelity EM simulations are utilized for performance utilization of structure at hand. The proposed variable-fidelity optimization technique with adjoint sensitivity and trust regions permits rapid optimization of numerically demanding antenna designs (here, dielectric resonator antenna and compact monopole), which cannot be achieved when conventional methods are of use. The design cost of proposed strategy is up to 60 percent lower than direct optimization exploiting adjoint sensitivities. Experimental validation of the results is also provided.
Purpose The purpose of this paper is to assess steady, two-dimensional natural convection flow of a viscoelastic, incompressible, electrically conducting and optically thick heat-radiating nanofluid over a linearly stretching sheet in the presence of uniform transverse magnetic field taking Dufour and Soret effects into account. Design/methodology/approach The governing boundary layer equations are transformed into a set of highly non-linear ordinary differential equations using suitable similarity transforms. Finite element method is used to solve this boundary value problem. Effects of pertinent flow parameters on the velocity, temperature, solutal concentration and nanoparticle concentration are described graphically. Also, effects of pertinent flow parameters on the shear stress, rate of heat transfer, rate of solutal concentration and rate of nanoparticle concentration at the sheet are discussed with the help of numerical values presented in graphical form. All numerical results for mono-diffusive nanofluid are compared with those of double-diffusive nanofluid. Findings Numerical results obtained in this paper are compared with earlier published results and are found to be in excellent agreement. Viscoelasticity, magnetic field and nanoparticle buoyancy parameter tend to enhance the wall velocity gradient, whereas thermal buoyancy force has a reverse effect on it. Radiation, Brownian and thermophoretic diffusions tend to reduce wall temperature gradient, whereas viscoelasticity has a reverse effect on it. Nanofluid Lewis number tends to enhance wall nanoparticle concentration gradient. Originality/value Study of this problem may find applications in engineering and biomedical sciences,e.g. in cooling and process industries and in cancer therapy.
Purpose This main purpose of this paper is to investigate the influence of Lorentz forces on magnetic nanofluid free convection in a porous media. Control volume based finite element method (CVFEM) is chosen to simulate the purpose of this paper. Influences of Darcy number, Fe3O4–water volume fraction, Hartmann and Rayleigh numbers on hydrothermal behavior are presented. Design/methodology/approach Magnetic nanofluid flow in a permeable medium is studied numerically using the non-Darcy model. Outputs are obtained by means of CVFEM. Findings Results indicated that isotherms become denser near the inner cylinder with augmentation of the permeability of the porous media. The Nusselt number enhances with an increase in buoyancy forces, Darcy number but it detracts with augment of Lorentz forces. Originality/value Results depict that the effect of the Hartmann number on rate of heat transfer is more observable in a medium with higher permeability.
Purpose This paper aims to review the existing bond-based peridynamic (PD) and state-based PD heat conduction models, and further propose a refined bond-based PD thermal conduction model by using the PD differential operator. Design/methodology/approach The general refined bond-based PD is established by replacing the local spatial derivatives in the classical heat conduction equations with their corresponding nonlocal integral forms obtained by the PD differential operator. This modeling approach is representative of the state-based PD models, whereas the resulting governing equations appear as the bond-based PD models. Findings The refined model can be reduced to the existing bond-based PD heat conduction models by specifying particular influence functions. Also, the refined model does not require any calibration procedure unlike the bond-based PD. A systematic explicit dynamic solver is introduced to validate 1 D, 2 D and 3 D heat conduction in domains with and without a crack subjected to a combination of Dirichlet, Neumann and convection boundary conditions. All of the PD predictions are in excellent agreement with the classical solutions and demonstrate the nonlocal feature and advantage of PD in dealing with heat conduction in discontinuous domains. Originality/value The existing PD heat conduction models are reviewed. A refined bond-based PD thermal conduction model by using PD differential operator is proposed and 3 D thermal conduction in intact or cracked structures is simulated.
Purpose The paper aims to use a switching technique which allows to couple a nonlocal bond-based Peridynamic approach to the Meshless Local Exponential Basis Functions (MLEBF) method, based on classical continuum mechanics, to solve planar problems. Design/methodology/approach The coupling has been achieved in a completely meshless scheme. The domain is divided in three zones: one in which only Peridynamics is applied, one in which only the meshless method is applied and a transition zone where a gradual transition between the two approaches takes place. Findings The new coupling technique generates overall grids that are not affected by ghost forces. Moreover, the use of the meshless approach can be limited to a narrow boundary region of the domain, and in this way, it can be used to remove the “surface effect” from the Peridynamic solution applied to all internal points. Originality/value The current study paves the road for future studies on dynamic and static crack propagation problems.
Purpose The purpose of this paper is to apply the Peridynamic differential operator (PDDO) to incompressible inviscid fluid flow with moving boundaries. Based on the potential flow theory, a Lagrangian formulation is used to cope with non-linear free-surface waves of sloshing water in 2D and 3D rectangular and square tanks. Design/methodology/approach In fact, PDDO recasts the local differentiation operator through a nonlocal integration scheme. This makes the method capable of determining the derivatives of a field variable, more precisely than direct differentiation, when jump discontinuities or gradient singularities come into the picture. The issue of gradient singularity can be found in tanks containing vertical/horizontal baffles. Findings The application of PDDO helps to obtain the velocity field with a high accuracy at each time step that leads to a suitable geometry updating for the procedure. Domain/boundary nodes are updated by using a second-order finite difference time algorithm. The method is applied to the solution of different examples including tanks with baffles. The accuracy of the method is scrutinized by comparing the numerical results with analytical, numerical and experimental results available in the literature. Originality/value Based on the investigations, PDDO can be considered a reliable and suitable approach to cope with sloshing problems in tanks. The paper paves the way to apply the method for a wider range of problems such as compressible fluid flow.
Purpose This paper aims to construct smooth poly-ellipsoid shapes from synchrotron microcomputed tomography (SMT) images on sand and to develop a new discrete element method (DEM) contact detection algorithm. Design/methodology/approach Voxelated images generated by SMT on Colorado Mason sand are processed to construct smooth poly-ellipsoidal particle approximations. For DEM contact detection, cuboidal shape approximations to the poly-ellipsoids are used to speed up contact detection. Findings The poly-ellipsoid particle shape approximation to Colorado Mason sand grains is better than a simpler ellipsoidal approximation. The new DEM contact algorithm leads to significant speedup and accuracy is maintained. Research limitations/implications The paper limits particle shape approximation to smooth poly-ellipsoids. Practical implications Poly-ellipsoids provide asymmetry of particle shapes as compared to ellipsoids, thus allowing closer representation of real sand grain shapes that may be angular and unsymmetric. When incorporated in a DEM for computation, the poly-ellipsoids allow better representation of particle rolling, sliding and interlocking phenomena. Originality/value Method to construct poly-ellipsoid particle shapes from SMT data on real sands and computationally efficient DEM contact detection algorithm for poly-ellipsoids.
Purpose Currently, there are some finite element head models developed by research groups all around the world. Nevertheless, the majority are not geometrically accurate. One of the problems is the brain geometry, which usually resembles a sphere. This may raise problems when reconstructing any event that involves brain kinematics, such as accidents, affecting the correct evaluation of resulting injuries. Thus, the purpose of this study is to develop a new finite element head model more accurate than the existing ones. Design/methodology/approach In this work, a new and geometrically detailed finite element brain model is proposed. Special attention was given to sulci and gyri modelling, making this model more geometrically accurate than currently available ones. In addition, these brain features are important to predict specific injuries such as brain contusions, which usually involve the crowns of gyri. Findings The model was validated against experimental data from impact tests on cadavers, comparing the intracranial pressure at frontal, parietal, occipital and posterior fossa regions. Originality/value As this model is validated, it can be now used in accident reconstruction and injury evaluation and even as a design tool for protective head gear.