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Purpose: Hexahedral meshing is one of the most important steps in performing an accurate simulation using the finite element analysis (FEA). However, the current hexahedral meshing method in the industry is a nonautomatic and inefficient method, i.e. manually decomposing the model into suitable blocks and obtaining the hexahedral mesh from these blocks by mapping or sweeping algorithms. The purpose of this paper is to propose an almost automatic decomposition algorithm based on the 3D frame field and model features to replace the traditional time-consuming and laborious manual decomposition method. Design/methodology/approach: The proposed algorithm is based on the 3D frame field and features, where features are used to construct feature-cutting surfaces and the 3D frame field is used to construct singular-cutting surfaces. The feature-cutting surfaces constructed from concave features first reduce the complexity of the model and decompose it into some coarse blocks. Then, an improved 3D frame field algorithm is performed on these coarse blocks to extract the singular structure and construct singular-cutting surfaces to further decompose the coarse blocks. In most modeling examples, the proposed algorithm uses both types of cutting surfaces to decompose models fully automatically. In a few examples with special requirements for hexahedral meshes, the algorithm requires manual input of some user-defined cutting surfaces and constructs different singular-cutting surfaces to ensure the effectiveness of the decomposition. Findings: Benefiting from the feature decomposition and the 3D frame field algorithm, the output blocks of the proposed algorithm have no inner singular structure and are suitable for the mapping or sweeping algorithm. The introduction of internal constraints makes 3D frame field generation more robust in this paper, and it can automatically correct some invalid 3–5 singular structures. In a few examples with special requirements, the proposed algorithm successfully generates valid blocks even though the singular structure of the model is modified by user-defined cutting surfaces. Originality/value: The proposed algorithm takes the advantage of feature decomposition and the 3D frame field to generate suitable blocks for a mapping or sweeping algorithm, which saves a lot of simulation time and requires less experience. The user-defined cutting surfaces enable the creation of special hexahedral meshes, which was difficult with previous algorithms. An improved 3D frame field generation method is proposed to correct some invalid singular structures and improve the robustness of the previous methods. [ABSTRACT FROM AUTHOR]

Purpose: The present paper aims at the multi-objective optimization of a reentrant hexagonal cell auxetic structure. In addition, a parametric analysis will be carried out to verify how each of the design factors impact each of the responses. Design/methodology/approach: The multi-objective optimization of five different responses of an auxetic model was considered: mass, critical buckling load under compression effort, natural frequency, Poisson's ratio and failure load. The response surface methodology was applied, and a new meta-heuristic of optimization called the multi-objective Lichtenberg algorithm was applied to find the optimized configuration of the model. It was possible to increase the failure load by 26.75% in compression performance optimization. Furthermore, in the optimization of modal performance, it was possible to increase the natural frequency by 37.43%. Finally, all 5 responses analyzed simultaneously were optimized. In this case, it was possible to increase the critical buckling load by 42.55%, the failure load by 28.70% and reduce the mass and Poisson's ratio by 15.97 and 11%, respectively. This paper addresses something new in the scientific world to date when evaluating in a multi-objective optimization problem, the compression and modal performance of an auxetic reentrant model. Findings: It was possible to find multi-objective optimized structures. It was possible to increase the critical buckling load by 42.82%, and the failure load in compression performance by 26.75%. Furthermore, in the optimization of modal performance, it was possible to increase the natural frequency by 37.43%, and decrease the mass by 15.97%. Finally, all 5 responses analyzed simultaneously were optimized. In this case, it was possible to increase the critical buckling load by 42.55%, increase the failure load by 28.70% and reduce the mass and Poisson's ratio by 15.97 and 11%, respectively. Originality/value: There is no work in the literature to date that performed the optimization of 5 responses simultaneously of a reentrant hexagonal cell auxetic structure. This paper also presents an unprecedented statistical analysis in the literature that verifies how the design factors impact each of the responses. [ABSTRACT FROM AUTHOR]

Purpose: The Wiener-Hammerstein nonlinear system is made up of two dynamic linear subsystems in series with a static nonlinear subsystem, and it is widely used in electrical, mechanical, aerospace and other fields. This paper considers the parameter estimation of the Wiener-Hammerstein output error moving average (OEMA) system. Design/methodology/approach: The idea of multi-population and parameter self-adaptive identification is introduced, and a multi-population self-adaptive differential evolution (MPSADE) algorithm is proposed. In order to confirm the feasibility of the above method, the differential evolution (DE), the self-adaptive differential evolution (SADE), the MPSADE and the gradient iterative (GI) algorithms are derived to identify the Wiener-Hammerstein OEMA system, respectively. Findings: From the simulation results, the authors find that the estimation errors under the four algorithms stabilize after 120, 30, 20 and 300 iterations, respectively, and the estimation errors of the four algorithms converge to 5.0%, 3.6%, 2.7% and 7.3%, which show that all four algorithms can identify the Wiener-Hammerstein OEMA system. Originality/value: Compared with DE, SADE and GI algorithm, the MPSADE algorithm not only has higher parameter estimation accuracy but also has a faster convergence speed. Finally, the input–output relationship of laser welding system is described and identified by the MPSADE algorithm. The simulation results show that the MPSADE algorithm can effectively identify parameters of the laser welding system. [ABSTRACT FROM AUTHOR]

Purpose: Sizing functions are crucial inputs for unstructured mesh generation since they determine the element distributions of resulting meshes to a large extent. Meanwhile, automating the procedure of creating a sizing function is a prerequisite to set up a fully automatic mesh generation pipeline. In this paper, an automatic algorithm is proposed to create a high-quality sizing function for an unstructured surface and volume mesh generation by using a triangular mesh as the background mesh. Design/methodology/approach: A practically efficient and effective solution is developed by using local operators carefully to re-mesh the tessellation of the input Computer Aided Design (CAD) models. A nonlinear programming (NLP) problem has been formulated to limit the gradient of the sizing function, while in this study, the object function of this NLP is replaced by an analytical equation that predicts the number of elements. For the query of the sizing value, an improved algorithm is developed by using the axis-aligned bounding box (AABB) tree structure. Findings: The local operations of re-meshing could effectively and efficiently resolve the banding issue caused by using the default tessellation of the model to define a sizing function. Experiments show that the solution of the revised NLP, in most cases, could provide a better solution at the lower cost of computational time. With the help of the AABB tree, the sizing function defined at a surface background mesh can be also used as the input of volume mesh generation. Originality/value: Theoretical analysis reveals that the construction of the initial sizing function could be reduced to the solution of an optimization problem. The definitions of the banding elements and surface proximity are also given. Under the guidance of this theoretical analysis, re-meshing and ray-casting technologies are well-designed to initial the sizing function. Smoothing with the revised NLP and querying by the AABB tree, the paper provides an automatic method to get a high-quality sizing function for both surface and volume mesh generation. [ABSTRACT FROM AUTHOR]

Purpose: Workpiece sorting is a key link in industrial production lines. The vision-based workpiece sorting system is non-contact and widely applicable. The detection and recognition of workpieces are the key technologies of the workpiece sorting system. To introduce deep learning algorithms into workpiece detection and improve detection accuracy, this paper aims to propose a workpiece detection algorithm based on the single-shot multi-box detector (SSD). Design/methodology/approach: Propose a multi-feature fused SSD network for fast workpiece detection. First, the multi-view CAD rendering images of the workpiece are used as deep learning data sets. Second, the visual geometry group network was trained for workpiece recognition to identify the category of the workpiece. Third, this study designs a multi-level feature fusion method to improve the detection accuracy of SSD (especially for small objects); specifically, a feature fusion module is added, which uses "element-wise sum" and "concatenation operation" to combine the information of shallow features and deep features. Findings: Experimental results show that the actual workpiece detection accuracy of the method can reach 96% and the speed can reach 41 frames per second. Compared with the original SSD, the method improves the accuracy by 7% and improves the detection performance of small objects. Originality/value: This paper innovatively introduces the SSD detection algorithm into workpiece detection in industrial scenarios and improves it. A feature fusion module has been added to combine the information of shallow features and deep features. The multi-feature fused SSD network proves the feasibility and practicality of introducing deep learning algorithms into workpiece sorting. [ABSTRACT FROM AUTHOR]

Purpose: The cross-docking strategy has a significant influence on supply chain and logistics efficiency. This paper aims to investigate the most suitable and efficient way to schedule the transfer of logistics activities and present a meta-heuristic method of the truck scheduling problem in cross-docking logistics. A truck scheduling problem with products time window is investigated with objectives of minimizing the total product transshipment time and earliness and tardiness cost of outbound trucks. Design/methodology/approach: This research proposed a meta-heuristic method for the truck scheduling problem with products time window. To solve the problem, a lower bound of the problem is built through a novel two-stage Lagrangian relaxation problem and on account of the NP-hard nature of the truck scheduling problem, the novel red deer algorithm with the mechanism of the heuristic oscillating local search algorithm, as well as adaptive memory programming was proposed to overcome the inferior capability of the original red deer algorithm in the aspect of local search and run time. Findings: Theory analysis and simulation experiments on an industrial case of a cross-docking center with a product's time window are conducted in this paper. Satisfactory results show that the performance of the red deer algorithm is enhanced due to the mechanism of heuristic oscillating local search algorithm and adaptive memory programming and the proposed method efficiently solves the real-world size case of truck scheduling problems in cross-docking with product time window. Research limitations/implications: The consideration of products time window has very realistic significance in different logistics applications such as cold-chain logistics and pharmaceutical supply chain. Furthermore, the novel adaptive memory red deer algorithm could be modified and applied to other complex optimization scheduling problems such as scheduling problems considering energy-efficiency or other logistics strategies. Originality/value: For the first time in the truck scheduling problem with the cross-docking strategy, the product's time window is considered. Furthermore, a mathematical model with objectives of minimizing the total product transshipment time and earliness and tardiness cost of outbound trucks is developed. To solve the proposed problem, a novel adaptive memory red deer algorithm with the mechanism of heuristic oscillating local search algorithm was proposed to overcome the inferior capability of genetic algorithm in the aspect of local search and run time. [ABSTRACT FROM AUTHOR]

Purpose: This paper aims to introduce a novel algorithm to solve initial/boundary value problems of high-order ordinary differential equations (ODEs) and high-order system of ordinary differential equations (SODEs). Design/methodology/approach: The proposed method is based on Hermite polynomials and extreme learning machine (ELM) algorithm. The Hermite polynomials are chosen as basis function of hidden neurons. The approximate solution and its derivatives are expressed by utilizing Hermite network. The model function is designed to automatically meet the initial or boundary conditions. The network parameters are obtained by solving a system of linear equations using the ELM algorithm. Findings: To demonstrate the effectiveness of the proposed method, a variety of differential equations are selected and their numerical solutions are obtained by utilizing the Hermite extreme learning machine (H-ELM) algorithm. Experiments on the common and random data sets indicate that the H-ELM model achieves much higher accuracy, lower complexity but stronger generalization ability than existed methods. The proposed H-ELM algorithm could be a good tool to solve higher order linear ODEs and higher order linear SODEs. Originality/value: The H-ELM algorithm is developed for solving higher order linear ODEs and higher order linear SODEs; this method has higher numerical accuracy and stronger superiority compared with other existing methods. [ABSTRACT FROM AUTHOR]

Purpose: Integrality of surface mesh is requisite for computational engineering. Nonwatertight meshes with holes can bring inconvenience to applications. Unlike simple modeling or visualization, the downstream industrial application scenarios put forward higher requirements for hole-filling, although many related algorithms have been developed. This study aims at the hole-filling issue in industrial application scenarios. Design/methodology/approach: This algorithm overcomes some inherent weakness of general methods and generates a high-level resulting mesh. Initially, the primitive hole boundary is filled with a more appropriate triangulation which introduces fewer geometric errors. And in order for better performances on shape approximation of the background mesh, the algorithm also refines the initial triangulation with topology optimization. When obtaining the background mesh defining the geometry and size field, spheres on it are packed to determine the vertex configuration and then the resulting high-level mesh is generated. Findings: Through emphasizing geometry recovery and mesh quality, the proposed algorithm works well in hole-filling in industrial application scenarios. Many experimental results demonstrate the reliability and the performance of the algorithm. And the processed meshes are capable of being used for industrial simulation computations directly. Originality/value: This paper makes input meshes more adaptable for solving programs through local modifications on meshes and perfects the preprocessing technology of finite element analysis (FEA). [ABSTRACT FROM AUTHOR]

Purpose: The purpose of this paper is to modify the crow search algorithm (CSA) to enhance both exploration and exploitation capability by including two novel approaches. The positions of the crows are updated in two approaches based on awareness probability (AP). With AP, the position of a crow is updated by considering its velocity, calculated in a similar fashion to particle swarm optimization (PSO) to enhance the exploiting capability. Without AP, the crows are subdivided into groups by considering their weights, and the crows are updated by conceding leaders of the groups distributed over the search space to enhance the exploring capability. The performance of the proposed PSO-based group-oriented CSA (PGCSA) is realized by exploring the solution of benchmark equations. Further, the proposed PGCSA algorithm is validated over recently published algorithms by solving engineering problems. Design/methodology/approach: In this paper, two novel approaches are implemented in two phases of CSA (with and without AP), which have been entitled the PGCSA algorithm to solve engineering benchmark problems. Findings: The proposed algorithm is applied with two types of problems such as eight benchmark equations without constraint and six engineering problems. Originality/value: The PGCSA algorithm is proposed with superior competence to solve engineering problems. The proposed algorithm is substantiated hypothetically by using a paired t-test. [ABSTRACT FROM AUTHOR]

Purpose: During the industrial design process, a product is usually modified and analyzed repeatedly until reaching the final design. Modifying the model and regenerating a mesh for every update during this process is very time consuming. To improve efficiency, it is necessary to circumvent the computer-aided design modeling stage when possible and directly modify the meshes to save valuable time. The purpose of this paper is to develop a method for mesh modifications. Design/methodology/approach: In contrast to existing studies, which focus on one or a class of modifications, this paper comprehensively studies mesh union, mesh gluing, mesh cutting and mesh partitioning. To improve the efficiency of the method, the paper presents a fast and effective surface mesh remeshing algorithm based on a ball-packing method and controls the remeshing regions with a size field. Findings: Examples and results show that the proposed mesh modification method is efficient and effective. The proposed method can be also applied to meshes with different material properties, which is very different with previous work that is only suitable for the meshes with same material property. Originality/value: This paper proposes an efficient and comprehensive tetrahedral mesh modification method, through which engineers can directly modify meshes instead of models and save time. [ABSTRACT FROM AUTHOR]

Purpose: This paper aims to introduce a new target tracking method based on risk theory in a 2-D discrete environment. After that, the related sensor scheduling method is proposed. This can make up the blank of target tracking and sensor management in the 2-D discrete environment. Design/methodology/approach: The definition of risk is proposed based on risk decision theory firstly. Then the target tracking model in a two-dimensional discrete environment is built. The motion state updating and estimation method of target's motion state based on Bayes theory is given. Thirdly, the method of computing sensor emission interception risk is provided. Afterwards, the optimization rule of obtaining the minimum risk is followed to model the sensor scheduling objective function. The lion algorithm is adjusted and improved combined with Chaos theory to generate the optimal sensor management projects. Findings: The risk-based sensor target tracking method and sensor management method are both effective in a 2-D discrete environment. Originality/value: To the best of the authors' knowledge, this paper is the first to study the target tracking method and sensor scheduling method in a 2-D environment. Furthermore, the lion algorithm is improved combined with Chaos theory to show a better optimization performance. [ABSTRACT FROM AUTHOR]

Purpose: This paper aims to present a new multi-community meta-heuristic optimization algorithm, which is called shuffled shepherd optimization algorithm (SSOA). In this algorithm. Design/methodology/approach: The agents are first separated into multi-communities and the optimization process is then performed mimicking the behavior of a shepherd in nature operating on each community. Findings: A new multi-community meta-heuristic optimization algorithm called a shuffled shepherd optimization algorithm is developed in this paper and applied to some attractive examples. Originality/value: A new metaheuristic is presented and tested with some classic benchmark problems and some attractive structures are optimized. [ABSTRACT FROM AUTHOR]

Purpose: An identification scheme to identify interconnected discrete-time (DT) varying systems. Design/methodology/approach: The purpose of this paper is the identification of interconnected discrete time varying systems. The proposed technique permits the division of global system to many subsystems by building a vector observation of each subsystem and then using the gradient method to identify the time-varying parameters of each subsystem. The convergence of the presented algorithm is proven under a given condition. Findings: The effectiveness of the proposed technique is then shown with application to a simulation example. Originality/value: In the past decade, there has been a renewed interest in interconnected systems that are multidimensional and composed of similar subsystems, which interact with their closest neighbors. In this context, the concept of parametric identification of interconnected systems becomes relevant, as it considers the estimation problem of such systems. Therefore, the identification of interconnected systems is a challenging problem in which it is crucial to exploit the available knowledge about the interconnection structure. For time-varying systems, the identification problem is much more difficult. To cope with this issue, this paper addresses the identification of DT dynamical models, composed by the interconnection of time-varying systems. [ABSTRACT FROM AUTHOR]

Purpose: The purpose of this paper is to establish and implement a direct topological reanalysis algorithm for general successive structural modifications, based on the updating matrix triangular factorization (UMTF) method for non-topological modification proposed by Song et al. [Computers and Structures, 143(2014):60-72]. Design/methodology/approach: In this method, topological modifications are viewed as a union of symbolic and numerical change of structural matrices. The numerical part is dealt with UMTF by directly updating the matrix triangular factors. For symbolic change, an integral structure which consists of all potential nodes/elements is introduced to avoid side effects on the efficiency during successive modifications. Necessary pre- and post processing are also developed for memory-economic matrix manipulation. Findings: The new reanalysis algorithm is applicable to successive general structural modifications for arbitrary modification amplitudes and locations. It explicitly updates the factor matrices of the modified structure and thus guarantees the accuracy as full direct analysis while greatly enhancing the efficiency. Practical implications: Examples including evolutionary structural optimization and sequential construction analysis show the capability and efficiency of the algorithm. Originality/value: This innovative paper makes direct topological reanalysis be applicable for successive structural modifications in many different areas. [ABSTRACT FROM AUTHOR]

Purpose: This study/paper aims to present a separable identification algorithm for a multiple input single output (MISO) continuous time (CT) hybrid "Box–Jenkins". Design/methodology/approach: This paper proposes an optimal method for the identification of MISO CT hybrid "Box–Jenkins" systems with unknown time delays by using the two-stage recursive least-square (TS-RLS) identification algorithm. Findings: The effectiveness of the proposed scheme is shown with application to a simulation example. Originality/value: A two-stage recursive least-square identification method is developed for multiple input single output continuous time hybrid "Box–Jenkins" system with multiple unknown time delays from sampled data. The proposed technique allows the division of the global CT hybrid "Box–Jenkins" system into two fictitious subsystems: the first one contains the parameters of the system model, including the multiple unknown time delays, and the second contains the parameters of the noise model. Then the TS-RLS identification algorithm can be applied easily to estimate all the parameters of the studied system. [ABSTRACT FROM AUTHOR]

Purpose: This paper attempts to develop an efficient algorithm to solve the inverse problem of identifying constitutive parameters in VFG (viscoelastic functionally graded) materials/structures. Design/methodology/approach: An adaptive recursive algorithm with high fidelity is developed to acquire the derivatives of displacements with respect to constitutive parameters, which are required for the accurate and stable gradient based inverse analysis. A two-step strategy is presented in the process of identification, by which the unknown parameters can be separately identified and the scale and complexity of the inverse VFG problem are reduced. At each step, the process of identification is treated as an optimization problem that is solved by the Levenberg–Marquardt method. Findings: The solution accuracy of forward problems and derivatives of displacements can be stably achieved with different step sizes, and constitutive parameters of homogenous/regional-inhomogeneous VFG materials/structures can be effectively and accurately identified. By examining the reliability, resolution, impacts of reference information and noisy data, the effectiveness of the proposed approach is numerically verified via three numerical examples. Originality/value: An adaptive recursive algorithm is developed for derivatives computing with high fidelity, providing a solid platform for the sensitivity analysis and thereby a two-step strategy in conjunction with Levenberg–Marquardt method is presented in the process of identification. Consequently, an effective algorithm is developed to identify constitutive parameters of homogenous/regional-inhomogeneous VFG materials/structures. [ABSTRACT FROM AUTHOR]

Purpose: This paper aims to propose an efficient and convenient numerical algorithm for two-dimensional nonlinear Volterra-Fredholm integral equations and fractional integro-differential equations (of Hammerstein and mixed types). Design/methodology/approach: The main idea of the presented algorithm is to combine Bernoulli polynomials approximation with Caputo fractional derivative and numerical integral transformation to reduce the studied two-dimensional nonlinear Volterra-Fredholm integral equations and fractional integro-differential equations to easily solved algebraic equations. Findings: Without considering the integral operational matrix, this algorithm will adopt straightforward discrete data integral transformation, which can do good work to less computation and high precision. Besides, combining the convenient fractional differential operator of Bernoulli basis polynomials with the least-squares method, numerical solutions of the studied equations can be obtained quickly. Illustrative examples are given to show that the proposed technique has better precision than other numerical methods. Originality/value: The proposed algorithm is efficient for the considered two-dimensional nonlinear Volterra-Fredholm integral equations and fractional integro-differential equations. As its convenience, the computation of numerical solutions is time-saving and more accurate. [ABSTRACT FROM AUTHOR]

Purpose: This paper aims to develop a meshfree algorithm based on local radial basis functions (RBFs) combined with the differential quadrature (DQ) method to provide numerical approximations of the solutions of time-dependent, nonlinear and spatially one-dimensional reaction-diffusion systems and to capture their evolving patterns. The combination of local RBFs and the DQ method is applied to discretize the system in space; implicit multistep methods are subsequently used to discretize in time. Design/methodology/approach: In a method of lines setting, a meshless method for their discretization in space is proposed. This discretization is based on a DQ approach, and RBFs are used as test functions. A local approach is followed where only selected RBFs feature in the computation of a particular DQ weight. Findings: The proposed method is applied on four reaction-diffusion models: Huxley's equation, a linear reaction-diffusion system, the Gray–Scott model and the two-dimensional Brusselator model. The method captured the various patterns of the models similar to available in literature. The method shows second order of convergence in space variables and works reliably and efficiently for the problems. Originality/value: The originality lies in the following facts: A meshless method is proposed for reaction-diffusion models based on local RBFs; the proposed scheme is able to capture patterns of the models for big time T; the scheme has second order of convergence in both time and space variables and Nuemann boundary conditions are easy to implement in this scheme. [ABSTRACT FROM AUTHOR]

Purpose: This paper aims to propose a new neural-based enhanced extreme learning machine (EELM) algorithm, used as an online adaptive estimation model, regarding undetermined system dynamics and containing internal/external perturbations. Design/methodology/approach: The EELM structure bases on the single layer feed-forward neural (SLFN) model in which the hidden weighting coefficients are initiated in random and the weighting outputs of the SLFN are online modified using an online adaptive rule implemented from Lyapunov stability concept. Findings: Four different benchmark uncertain chaotic system tests have been satisfactorily investigated for demonstrating the superiority of proposed EELM technique. Originality/value: Authors confirm that this manuscript is original. [ABSTRACT FROM AUTHOR]

Purpose: Highly non-linear optimization problems exist in many practical engineering applications. To deal with these problems, this study aims to propose an improved optimization algorithm, named, adaptive resistance and stamina strategy-based dragonfly algorithm (ARSSDA). Design/methodology/approach: To speed up the convergence, ARSSDA applies an adaptive resistance and stamina strategy (ARSS) to conventional dragonfly algorithm so that the search step can be adjusted appropriately in each iteration. In ARSS, it includes the air resistance and physical stamina of dragonfly during a flight. These parameters can be updated in real time as the flight status of the dragonflies. Findings: The performance of ARSSDA is verified by 30 benchmark functions of Congress on Evolutionary Computation 2014's special session and 3 well-known constrained engineering problems. Results reveal that ARSSDA is a competitive algorithm for solving the optimization problems. Further, ARSSDA is used to search the optimal parameters for a bucket wheel reclaimer (BWR). The aim of the numerical experiment is to achieve the global optimal structure of the BWR by minimizing the energy consumption. Results indicate that ARSSDA generates an optimal structure of BWR and decreases the energy consumption by 22.428% compared with the initial design. Originality/value: A novel search strategy is proposed to enhance the global exploratory capability and convergence speed. This paper provides an effective optimization algorithm for solving constrained optimization problems. [ABSTRACT FROM AUTHOR]

Purpose: Most of the existing ground filtering algorithms are based on the Cartesian coordinate system, which is not compatible with the working principle of mobile light detection and ranging and difficult to obtain good filtering accuracy. The purpose of this paper is to improve the accuracy of ground filtering by making full use of the order information between the point and the point in the spherical coordinate. Design/methodology/approach: First, the cloth simulation (CS) algorithm is modified into a sorting algorithm for scattered point clouds to obtain the adjacent relationship of the point clouds and to generate a matrix containing the adjacent information of the point cloud. Then, according to the adjacent information of the points, a projection distance comparison and local slope analysis are simultaneously performed. These results are integrated to process the point cloud details further and the algorithm is finally used to filter a point cloud in a scene from the KITTI data set. Findings: The results show that the accuracy of KITTI point cloud sorting is 96.3% and the kappa coefficient of the ground filtering result is 0.7978. Compared with other algorithms applied to the same scene, the proposed algorithm has higher processing accuracy. Research limitations/implications: Steps of the algorithm are parallel computing, which saves time owing to the small amount of computation. In addition, the generality of the algorithm is improved and it could be used for different data sets from urban streets. However, due to the lack of point clouds from the field environment with labeled ground points, the filtering result of this algorithm in the field environment needs further study. Originality/value: In this study, the point cloud neighboring information was obtained by a modified CS algorithm. The ground filtering algorithm distinguish ground points and off-ground points according to the flatness, continuity and minimality of ground points in point cloud data. In addition, it has little effect on the algorithm results if thresholds were changed. [ABSTRACT FROM AUTHOR]

Purpose This paper aims to represent an improved whale optimization algorithm (WOA) based on a Lévy flight trajectory and called the LWOA algorithm to solve engineering optimization problems. The LWOA makes the WOA faster, more robust and significantly enhances the WOA. In the LWOA, the Lévy flight trajectory enhances the capability of jumping out of the local optima and is helpful for smoothly balancing exploration and exploitation of the WOA. It has been successfully applied to five standard engineering optimization problems. The simulation results of the classical engineering design problems and real application exhibit the superiority of the LWOA algorithm in solving challenging problems with constrained and unknown search spaces when compared to the basic WOA algorithm or other available solutions.Design/methodology/approach In this paper, an improved WOA based on a Lévy flight trajectory and called the LWOA algorithm is represented to solve engineering optimization problems.Findings It has been successfully applied to five standard engineering optimization problems. The simulation results of the classical engineering design problems and real application exhibit the superiority of the LWOA algorithm in solving challenging problems with constrained and unknown search spaces when compared to the basic WOA algorithm or other available solutions.Originality value An improved WOA based on a Lévy flight trajectory and called the LWOA algorithm is first proposed. [ABSTRACT FROM AUTHOR]

Purpose: The purpose of this paper is to provide an automatic parallelization toolkit for unstructured mesh-based computation. Among all kinds of mesh types, unstructured meshes are dominant in engineering simulation scenarios and play an essential role in scientific computations for their geometrical flexibility. However, the high-fidelity applications based on unstructured grids are still time-consuming, no matter for programming or running. Design/methodology/approach: This study develops an efficient UNstructured Acceleration Toolkit (UNAT), which provides friendly high-level programming interfaces and elaborates lower level implementation on the target hardware to get nearly hand-optimized performance. At the present state, two efficient strategies, a multi-level blocks method and a row-subsections method, are designed and implemented on Sunway architecture. Random memory access and write–write conflict issues of unstructured meshes have been handled by partitioning, coloring and other hardware-specific techniques. Moreover, a data-reuse mechanism is developed to increase the computational intensity and alleviate the memory bandwidth bottleneck. Findings: The authors select sparse matrix-vector multiplication as a performance benchmark of UNAT across different data layouts and different matrix formats. Experimental results show that the speed-ups reach up to 26× compared to single management processing element, and the utilization ratio tests indicate the capability of achieving nearly hand-optimized performance. Finally, the authors adopt UNAT to accelerate a well-tuned unstructured solver and obtain speed-ups of 19× and 10× on average for main kernels and overall solver, respectively. Originality/value: The authors design an unstructured mesh toolkit, UNAT, to link the hardware and numerical algorithm, and then, engineers can focus on the algorithms and solvers rather than the parallel implementation. For the many-core processor SW26010 of the fastest supercomputer in China, UNAT yields up to 26× speed-ups and achieves nearly hand-optimized performance. [ABSTRACT FROM AUTHOR]

Purpose: The purpose of this paper is to propose an iterative Legendre technique to deal with a continuous optimal control problem (OCP). Design/methodology/approach: For the system in the considered problem, the control variable is a function of the state variables and their derivatives. State variables in the problem are approximated by Legendre expansions as functions of time t. A constant matrix is given to express the derivatives of state variables. Therefore, control variables can be described as functions of time t. After that, the OCP is converted to an unconstrained optimization problem whose decision variables are the unknown coefficients in the Legendre expansions. Findings: The convergence of the proposed algorithm is proved. Experimental results, which contain the controlled Duffing oscillator problem demonstrate that the proposed technique is faster than existing methods. Originality/value: Experimental results, which contained the controlled Duffing oscillator problem demonstrate that the proposed technique can be faster while securing exactness. [ABSTRACT FROM AUTHOR]

Purpose The time of tightly coupled transient calculation and the accuracy of conventional loosely coupled algorithm make it difficult to meet the engineering design requirements for long-term conjugate heat transfer (CHT) problems. The purpose of this paper is to propose a new loosely coupled algorithm with sufficient accuracy and less calculation time on the basis of the quasi-steady flow field. Through this algorithm, it will be possible to reduce the update frequency of the flow field and devise a strategy by which to reasonably determine the update steps.Design/methodology/approach In this paper, the new algorithm updates the flow field by solving the steady governing equations in the fluid region and by calculating the transient temperature distribution until the next update of the fluid flow, by means of solving the transient energy equations in the entire computational domain. The authors propose a strategy by which to determine the update step, by using the engineering empirical formula of the Nusselt number, on the basis of the changes of the inlet and outlet boundary conditions.Findings Taking a duct heated by an inner forced air flow heating process as an example, the comparison results for the tightly coupled transient calculation by Fluent software shows that the new algorithm is able to significantly reduce the calculation time of the transient temperature distribution with reasonable accuracy. For example, the respective computing times are reduced to 22.8 and 40 per cent, while the duct wall temperature deviations are 7 and 5 per cent, using the two flow update time steps of 100 and 50 s on the variable inlet-flow rate conditions.Originality/value The new algorithm outlined in this paper further improves the calculated performance and meets the engineering design requirements for long-term CHT problems. [ABSTRACT FROM AUTHOR]

Purpose: The purpose of this paper is to present a fast algorithm for the adaptive discretization of three-dimensional parametric curves. Design/methodology/approach: The proposed algorithm computes the parametric increments of all segments to obtain the parametric coordinates of all discrete nodes. This process is recursively applied until the optimal discretization of curves is obtained. The parametric increment of a segment is inversely proportional to the number of sub-segments, which can be subdivided, and the sum of parametric increments of all segments is constant. Thus, a new expression for parametric increment of a segment can be obtained. In addition, the number of sub-segments, which a segment can be subdivided is calculated approximately, thus avoiding Gaussian integration. Findings: The proposed method can use less CPU time to perform the optimal discretization of three-dimensional curves. The results of curves discretization can also meet requirements for mesh generation used in the preprocessing of numerical simulation. Originality/value: Several numerical examples presented have verified the robustness and efficiency of the proposed algorithm. Compared with the conventional algorithm, the more complex the model, the more time the algorithm saves in the process of curve discretization. [ABSTRACT FROM AUTHOR]

Purpose: Contact detection for convex polygons/polyhedra has been a critical issue in discrete/discontinuous modelling, such as the discrete element method (DEM) and the discontinuous deformation analysis (DDA). The recently developed 3D contact theory for polyhedra in DDA depends on the so-called entrance block of two polyhedra and reduces the contact to evaluate the distance between the reference point to the corresponding entrance block, but effective implementation is still lacking. Design/methodology/approach: In this paper, the equivalence of the entrance block and the Minkowski difference of two polyhedra is emphasised and two well-known Minkowski difference-based contact detection and overlap computation algorithms, GJK and expanding polytope algorithm (EPA), are chosen as the possible numerical approaches to the 3D contact theory for DDA, and also as alternatives for computing polyhedral contact features in DEM. The key algorithmic issues are outlined and their important features are highlighted. Findings: Numerical examples indicate that the average number of updates required in GJK for polyhedral contact is around 6, and only 1 or 2 iterations are needed in EPA to find the overlap and all the relevant contact features when the overlap between polyhedra is small. Originality/value: The equivalence of the entrance block in DDA and the Minkowski difference of two polyhedra is emphasised; GJK- and EPA-based contact algorithms are applied to convex polyhedra in DEM; energy conservation is guaranteed for the contact theory used; and numerical results demonstrate the effectiveness of the proposed methodologies. [ABSTRACT FROM AUTHOR]

Purpose: The purpose of this paper is to solve the problem that the analytic solution model of spatial three-dimensional coordinate measuring system based on dual-position sensitive detector (PSD) is complex and its precision is not high. Design/methodology/approach: A new three-dimensional coordinate measurement algorithm by optimizing back propagation (BP) neural network based on genetic algorithm (GA) is proposed. The mapping relation between three-dimensional coordinates of space points in the world coordinate system and light spot coordinates formed on dual-PSD has been built and applied to the prediction of three-dimensional coordinates of space points. Findings: The average measurement error of three-dimensional coordinates of space points at three-dimensional coordinate measuring system based on dual-PSD based on GA-BP neural network is relatively small. This method does not require considering the lens distortion and the non-linearity of PSD. It has simple structure and high precision and is suitable for three-dimensional coordinate measurement of space points. Originality/value: A new three-dimensional coordinate measurement algorithm by optimizing BP neural network based on GA is proposed to predict three-dimensional coordinates of space points formed on three-dimensional coordinate measuring system based on dual-PSD. [ABSTRACT FROM AUTHOR]

Purpose FastSLAM is a popular method to solve the problem of simultaneous localization and mapping (SLAM). However, when the number of landmarks present in real environments increases, there are excessive comparisons of the measurement with all the existing landmarks in each particle. As a result, the execution speed will be too slow to achieve the objective of real-time navigation. Thus, this paper aims to improve the computational efficiency and estimation accuracy of conventional SLAM algorithms.Design/methodology/approach As an attempt to solve this problem, this paper presents a computationally efficient SLAM (CESLAM) algorithm, where odometer information is considered for updating the robot’s pose in particles. When a measurement has a maximum likelihood with the known landmark in the particle, the particle state is updated before updating the landmark estimates.Findings Simulation results show that the proposed CESLAM can overcome the problem of heavy computational burden while improving the accuracy of localization and mapping building. To practically evaluate the performance of the proposed method, a Pioneer 3-DX robot with a Kinect sensor is used to develop an RGB-D-based computationally efficient visual SLAM (CEVSLAM) based on Speeded-Up Robust Features (SURF). Experimental results confirm that the proposed CEVSLAM system is capable of successfully estimating the robot pose and building the map with satisfactory accuracy.Originality/value The proposed CESLAM algorithm overcomes the problem of the time-consuming process because of unnecessary comparisons in existing FastSLAM algorithms. Simulations show that accuracy of robot pose and landmark estimation is greatly improved by the CESLAM. Combining CESLAM and SURF, the authors establish a CEVSLAM to significantly improve the estimation accuracy and computational efficiency. Practical experiments by using a Kinect visual sensor show that the variance and average error by using the proposed CEVSLAM are smaller than those by using the other visual SLAM algorithms. [ABSTRACT FROM AUTHOR]

Purpose: Bat algorithm (BA) is a global optimization method, but has a worse performance on engineering optimization problems. The purpose of this study is to propose a novel chaotic bat algorithm based on catfish effect (CE-CBA), which can effectively deal with optimization problems in real-world applications. Design/methodology/approach: Incorporating chaos strategy and catfish effect, the proposed algorithm can not only enhance the ability for local search but also improve the ability to escape from local optima traps. On the one hand, the performance of CE-CBA has been evaluated by a set of numerical experiment based on classical benchmark functions. On the other hand, five benchmark engineering design problems have been also used to test CE-CBA. Findings: The statistical results of the numerical experiment show the significant improvement of CE-CBA compared with the standard algorithms and improved bat algorithms. Moreover, the feasibility and effectiveness of CE-CBA in solving engineering optimization problems are demonstrated. Originality/value: This paper proposed a novel BA with two improvement strategies including chaos strategy and catfish effect for the first time. Meanwhile, the proposed algorithm can be used to solve many real-world engineering optimization problems with several decision variables and constraints. [ABSTRACT FROM AUTHOR]

Purpose This paper aims to demonstrate a cloud-based version of the improved Monte Carlo localization algorithm with robust orientation estimation (IMCLROE). The purpose of this system is to increase the accuracy and efficiency of indoor robot localization.Design/methodology/approach The cloud-based IMCLROE is constructed with a cloud–client architecture that distributes computation between servers and a client robot. The system operates in two phases: in the offline phase, two maps are built under the MapReduce framework. This framework allows parallel and even distribution of map information to a cloud database in pre-described formats. In the online phase, an Apache HBase is adopted to calculate a pose in-memory and promptly send the result to the client robot. To demonstrate the efficiency of the cloud-based IMCLROE, a two-step experiment is conducted: first, a mobile robot implemented with a non-cloud IMCLROE and a UDOO single-board computer is tested for its efficiency on pose-estimation accuracy. Then, a cloud-based IMCLROE is implemented on a cloud–client architecture to demonstrate its efficiency on both pose-estimation accuracy and computation ability.Findings For indoor localization, the cloud-based IMCLROE is much more effective in acquiring pose-estimation accuracy and relieving computation burden than the non-cloud system.Originality/value The cloud-based IMCLROE achieves efficiency of indoor localization by using three innovative strategies: firstly, with the help of orientation estimation and weight calculation (OEWC), the system can sort out the best orientation. Secondly, the system reduces computation burden with map pre-caching. Thirdly, the cloud–client architecture distributes computation between the servers and client robot. Finally, the similar energy region (SER) technique provides a high-possibility region to the system, allowing the client robot to locate itself in a short time. [ABSTRACT FROM AUTHOR]

Purpose The purpose of this paper is to propose a new explicit time integration algorithm for solution to the linear and non-linear finite element equations of structural dynamic and wave propagation problems.Design/methodology/approach The algorithm is completely explicit so that no linear equation system requires solving, if the mass matrix of the finite element equation is diagonal and whether the damping matrix does or not. The algorithm is a single-step method that has the simple starting and is applicable to the analysis with the variable time step size. The algorithm is second-order accurate and conditionally stable. Its numerical stability, dissipation and dispersion are analyzed for the dynamic single-degree-of-freedom equation. The stability of the multi-degrees-of-freedom non-proportional damping system can be evaluated directly by the stability theory on ordinary differential equation.Findings The performance of the proposed algorithm is demonstrated by several numerical examples including the linear single-degree-of-freedom problem, non-linear two-degree-of-freedom problem, wave propagation problem in two-dimensional layer and seismic elastoplastic analysis of high-rise structure.Originality/value A new single-step second-order accurate explicit time integration algorithm is proposed to solve the linear and non-linear dynamic finite element equations. The algorithm has advantages on the numerical stability and accuracy over the existing modified central difference method and Chung-Lee method though the theory and numerical analyses. [ABSTRACT FROM AUTHOR]

Purpose Dual-rotor wind turbines (DRWTs) are a novel type of wind turbines that can capture more power than their single-rotor counterparts. Because their surrounding flow fields are complex, evaluating a DRWT design requires accurate predictive simulations, which incur high computational costs. Currently, there does not exist a design optimization framework for DRWTs. Since the design optimization of DRWTs requires numerous model evaluations, the purpose of this paper is to identify computationally efficient design approaches.Design/methodology/approach Several algorithms are compared for the design optimization of DRWTs. The algorithms vary widely in approaches and include a direct derivative-free method, as well as three surrogate-based optimization methods, two approximation-based approaches and one variable-fidelity approach with coarse discretization low-fidelity models.Findings The proposed variable-fidelity method required significantly lower computational cost than the derivative-free and approximation-based methods. Large computational savings come from using the time-consuming high-fidelity simulations sparingly and performing the majority of the design space search using the fast variable-fidelity models.Originality/value Due the complex simulations and the large number of designable parameters, the design of DRWTs require the use of numerical optimization algorithms. This work presents a novel and efficient design optimization framework for DRWTs using computationally intensive simulations and variable-fidelity optimization techniques. [ABSTRACT FROM AUTHOR]

Purpose – A variety of meshless methods have been developed in the last 20 years with an intention to solve practical engineering problems, but are limited to small academic problems due to associated high computational cost as compared to the standard finite element methods (FEM). The purpose of this paper is to develop an efficient and accurate algorithms based on meshless methods for the solution of problems involving both material and geometrical nonlinearities. Design/methodology/approach – A parallel two-dimensional linear elastic computer code is presented for a maximum entropy basis functions based meshless method. The two-dimensional algorithm is subsequently extended to three-dimensional adaptive nonlinear and three-dimensional parallel nonlinear adaptively coupled finite element, meshless method cases. The Prandtl-Reuss constitutive model is used to model elasto-plasticity and total Lagrangian formulations are used to model finite deformation. Furthermore, Zienkiewicz and Zhu and Chung and Belytschko error estimation procedure are used in the FE and meshless regions of the problem domain, respectively. The message passing interface library and open-source software packages, METIS and MUltifrontal Massively Parallel Solver are used for the high performance computation. Findings – Numerical examples are given to demonstrate the correct implementation and performance of the parallel algorithms. The agreement between the numerical and analytical results in the case of linear elastic example is excellent. For the nonlinear problems load-displacement curve are compared with the reference FEM and found in a very good agreement. As compared to the FEM, no volumetric locking was observed in the case of meshless method. Furthermore, it is shown that increasing the number of processors up to a given number improve the performance of parallel algorithms in term of simulation time, speedup and efficiency. Originality/value – Problems involving both material and geometrical nonlinearities are of practical importance in many engineering applications, e.g. geomechanics, metal forming and biomechanics. A family of parallel algorithms has been developed in this paper for these problems using adaptively coupled finite element, meshless method (based on maximum entropy basis functions) for distributed memory computer architectures. [ABSTRACT FROM AUTHOR]

Purpose – The purpose of this paper is to present a method for simultaneous motion and vibration control of light-weight slender robotic arms, known as flexible manipulators. In this paper, a new control algorithm is proposed for a two-link manipulator with elastic links. Design/methodology/approach – The controller includes a MIMO H∞ Loop-Shaping Design (H∞LSD) as the feedback controller, and a command pre-shaping filter as the feed-forward controller. The conventional inputs and outputs of a typical two-link manipulator, that consists of the torques applied by the actuators at the joints, and the joint angles are chosen for the feedback control. Findings – It is shown that by selecting a proper desired loop shape, the H∞LSD is able to control the joint angles of the manipulator, and simultaneously, suppress vibrations of the system so that the high-frequency chatter due to the structural vibration modes does not appear at the outputs. Then it is shown that when the H∞LSD is equipped with a command pre-shaping filter, more efficient suppression of the chatter at the tip of the manipulator is achieved. The capability and effectiveness of the proposed control strategy in driving and stabilizing the manipulator to desired positions and simultaneously suppressing structural vibrations is shown by the simulation of the flexible manipulator in rest-to-rest maneuvers. Practical implications – The paper presents a flexible manipulator and looks at space manipulators. Originality/value – A robust MIMO controller is proposed for simultaneous motion and vibration control of flexible manipulator. [ABSTRACT FROM AUTHOR]

Purpose – The purpose of this paper is to present an efficient return mapping algorithm for elastoplastic constitutive problems of ductile metals with an exact closed form solution of the local constitutive problem in the small strain regime. A Newton Raphson iterative method is adopted for the solution of the boundary value problem. Design/methodology/approach – An efficient return mapping algorithm is illustrated which is based on an elastic predictor and a plastic corrector scheme resulting in an implicit and accurate numerical integration method. Nonlinear kinematic hardening rules and linear isotropic hardening rules are used to describe the components of the hardening variables. In the adopted algorithmic approach the solution of the local constitutive equations reduces to only one straightforward nonlinear scalar equation. Findings – The presented algorithmic scheme naturally leads to a particularly simple form of the nonlinear scalar equation which ultimately scales down to an algebraic (polynomial) equation with a single variable. The straightforwardness of the present approach allows to find the analytical solution of the algebraic equation in a closed form. Further, the consistent tangent operator is derived as associated with the proposed algorithmic scheme and it is shown that the proposed computational procedure ensures a quadratic rate of asymptotic convergence when used with a Newton Raphson iterative method for the global solution procedure. Originality/value – In the present approach the solution of the algebraic nonlinear equation is found in a closed form and accordingly no iterative method is required to solve the problem of the local constitutive equations. The computational procedure ensures a quadratic rate of asymptotic convergence for the global solution procedure typical of computationally efficient solution schemes. In the paper it is shown that the proposed algorithmic scheme provides an efficient and robust computational solution procedure for elastoplasticity boundary value problems. Numerical examples and computational results are reported which illustrate the effectiveness and robustness of the adopted integration algorithm for the finite element analysis of elastoplastic structures also under elaborate loading conditions. [ABSTRACT FROM AUTHOR]

Purpose – The purpose of this paper is to describe several novel techniques for implementing a crystal plasticity (CP) material model in a large deformation, implicit finite element framework. Design/methodology/approach – Starting from the key kinematic assumptions of CP, the presentation develops the necessary CP correction terms to several common objective stress rates and the consistent linearization of the stress update algorithm. Connections to models for slip system hardening are isolated from these processes. Findings – A kinematically consistent implementation is found to require a correction to the stress update to include plastic vorticity developed by slip deformation in polycrystals. A simpler, more direct form for the algorithmic tangent is described. Several numerical examples demonstrate the capabilities and computational efficiency of the formulation. Research limitations/implications – The implementation assumes isotropic slip system hardening. With simple modifications, the described approach extends readily to anisotropic coupled or uncoupled hardening functions. Practical implications – The modular formulation and implementation support streamlined development of new models for slip system hardening without modifications of the stress update and algorithmic tangent computations. This implementation is available in the open-source code WARP3D. Originality/value – In the process of developing the CP formulation, this work realized the need for corrections to the Green-Naghdi and Jaumann objective stress rates to account properly for non-zero plastic vorticity. The paper describes fully the consistent linearization of the stress update algorithm and details a new scheme to implement the model with improved efficiency. [ABSTRACT FROM AUTHOR]

Purpose – The purpose of this paper is to propose a new four-node membrane element model with bending modification based on the equilibrium principle of element nodal internal forces and bending moments for the application of the one-step algorithm for bus rollover collision. And it can be concluded whether the proposed four-node membrane element model has practical value in engineering application or not. Design/methodology/approach – Based on the equilibrium principle of element nodal internal forces and bending moments, the paper puts forward a four-node membrane element model with bending modification. A case study on the rollover of a typical bus body section is carried out by using the one-step algorithm for bus rollover collision to verify the effectiveness of the proposed element model. Findings – For the simulation of bus rollover collision, the computational accuracy can be guaranteed, meanwhile, the calculated amount is much smaller than the shell element, and computational efficiency is improved significantly. Originality/value – The proposed four-node membrane element model is used for the simulation of bus rollover collision for the first time. It holds the advantage of high computational efficiency of membrane element, and the computational accuracy is improved as well. In conclusion, it has some practical value in engineering application. [ABSTRACT FROM AUTHOR]

Purpose – It is well known that the selection of initial cluster centers can significantly affect K-means clustering results. The purpose of this paper is to propose an improved, efficient methodology to handle such a challenge. Design/methodology/approach – According to the fact that the inner-class distance among samples within the same cluster is supposed to be smaller than the inter-class distance among clusters, the algorithm will dynamically adjust initial cluster centers that are randomly selected. Consequently, such adjusted initial cluster centers will be highly representative in the sense that they are distributed among as many samples as possible. As a result, local optima that are common in K-means clustering can then be effectively reduced. In addition, the algorithm is able to obtain all initial cluster centers simultaneously (instead of one center at a time) during the dynamic adjustment. Findings – Experimental results demonstrate that the proposed algorithm greatly improves the accuracy of traditional K-means clustering results and, in a more efficient manner. Originality/value – The authors presented in this paper an efficient algorithm, which is able to dynamically adjust initial cluster centers that are randomly selected. The adjusted centers are highly representative, i.e. they are distributed among as many samples as possible. As a result, local optima that are common in K-means clustering can be effectively reduced so that the authors can achieve an improved clustering accuracy. In addition, the algorithm is a cost-efficient one and the enhanced clustering accuracy can be obtained in a more efficient manner compared with traditional K-means algorithm. [ABSTRACT FROM AUTHOR]

Purpose The purpose of this paper is to provide an effective solution method for the truck and trailer routing problem (TTRP) which is one of the important NP-hard combinatorial optimization problems owing to its multiple real-world applications. It is a generalization of the famous vehicle routing problem (VRP), involving a group of geographically scattered customers served by the vehicle fleet including trucks and trailers.Design/methodology/approach The meta-heuristic solution approach based on bat algorithm (BA) in which a local search procedure performed by five different neighborhood structures is developed. Moreover, a self-adaptive (SA) tuning strategy to preserve the swarm diversity is implemented. The effectiveness of the proposed SA-BA is investigated by an experiment conducted on 21 benchmark problems that are well known in the literature.Findings Computational results indicate that the proposed SA-BA algorithm is computationally efficient through comparison with other existing algorithms found from the literature according to solution quality. As for the actual computational time, the SA-BA algorithm outperforms others. However, the scaled computational time of the SA-BA algorithm underperforms the other algorithms.Originality/value In this work the authors show that the proposed SA-BA is effective as a method for the TTRP problem. To the authors’ knowledge, the BA has not been applied previously, as in this work, to solve the TTRP problem. [ABSTRACT FROM AUTHOR]

Purpose The paper aims to apply a modified version of the MPS method to a double-dam-breaking test in which high dispersion zones and high natural clusterization zones are present, such as when the water column collapses into two sides and the two solitary waves collide, respectively.Design/methodology/approach The work takes advantage of the mixed source term from the cheaper computational version of the moving particle semi-implicit (MPS) method to reduce one step from the MPS classical algorithm. The proposed test can be successfully simulated by applying modifications to the variance parameter in the Laplacian operator and gradient model.Findings The results show stable behavior in dispersion and clusterization zones. Also, the collision and merging produced by solitary waves was successfully simulated.Research limitations/implications The main limitation in this work was the development of a comparison between the obtained results and the simulations with the original cheaper computational version of the MPS, this limitation is due to the overestimation of inter particle repulsive forces from its gradient model.Practical implications The application of solitary waves is of paramount importance in a number of applications, and this stems from the fact that the interaction of solitary waves with ships and other floating structures could generate highly deformed and complex free surface flows.Social implications For future work, the modified version of the MPS method can be applied in flow over sill base simulations, in close and open channels, and in simulating breaking waves to determine impact pressures by using solitary wave propagation.Originality/value The simulation of interaction of large groups of particles as in the case when two solitary waves collide could cause severe instability problems in pressure, causing the computer analysis to stop. MPS classical algorithm takes into account an explicit step that, in this case, may provoke the problem. For this reason, the cheaper version of MPS method is used to correctly simulate solitary wave interactions. [ABSTRACT FROM AUTHOR]

Purpose – Generally, iterative methods which have some instability solutions in complex structural and non-linear mechanical problems are used to compute reliability index. The purpose of this paper is to establish a non-linear conjugate gradient (NCG) optimization algorithm to overcome instability solution of the Hasofer-Lind and Rackwitz-Fiessler (HL-RF) method in first-order reliability analysis. The NCG algorithms such as the Conjugate-Descent (CD) and the Liu-Storey (LS) are used for determining the safety index. An algorithm is found based on the new line search in the reliability analysis. Design/methodology/approach – In the proposed line search for calculating the safety index, search direction is computed by using the conjugate gradient approach and the HL-RF method based on the new and pervious gradient vector of the reliability function. A simple step size is presented for the line search in the proposed algorithm, which is formulated by the Wolfe conditions based on the new and previous safety index results in the reliability analysis. Findings – From the current work, it is concluded that the proposed NCG algorithm has more efficient, robust and appropriate convergence in comparison with the HL-RF method. The proposed methods can eliminate numerical instabilities of the HL-RF iterative algorithm in highly non-linear performance function and complicated structural limit state function. The NGC optimization is applicable to reliability analysis and it is correctly converged on the reliability index. In the NCG method, the CD algorithm is slightly more efficient than the LS algorithm. Originality/value – This paper usefully shows how the HL-RF algorithm and the NCG scheme are formulated in first-order reliability analysis. The proposed algorithm is validated from six numerical and structural examples taken from the literature. The HL-RF method is not converged on several non-linear mathematic and complex structural examples, while the two proposed conjugate gradient methods are appropriately converged for all examples. The CD algorithm is converged about twice faster than the LS algorithm in most of the problems. Therefore, application of the NCG method is possible in reliability analysis. [ABSTRACT FROM AUTHOR]

Purpose – The particle damper is an efficient vibration control device and is widely used in engineering projects; however, the performance of such a system is very complicated and highly nonlinear. The purpose of this paper is to accurately simulate the particle damper system properly, and help to understand the underlying physical mechanics. Design/methodology/approach – A high-fidelity simulation process is well established to account for all significant interactions among the particles and with the host structure system, including sliding friction, gravitational forces, and oblique impacts, based on the modified discrete element method. In this process, a suitable particle damper system is modeled, reaction forces between particle aggregates and the primary structure are incorporated, a reasonable contact force model and time step are determined, and an efficient contact detection algorithm is adopted. Findings – The numerical results are further validated by both special computational tests and shaking table tests, with good agreements to the experimental results. The method is shown to be effective and accurate to simulate the particle damper system. Originality/value – The approaches described in this paper provide an efficient numerical way to investigate complex particle damper systems. [ABSTRACT FROM AUTHOR]

Purpose – The linear matrix equations have wide applications in engineering, physics, economics and statistics. The purpose of this paper is to introduce iterative methods for solving the systems of linear matrix equations. Design/methodology/approach – According to the hierarchical identification principle, the authors construct alternating direction gradient-based iterative (ADGI) methods to solve systems of linear matrix equations. Findings – The authors propose efficient ADGI methods to solve the systems of linear matrix equations. It is proven that the ADGI methods consistently converge to the solution for any initial matrix. Moreover, the constructed methods are extended for finding the reflexive solution to the systems of linear matrix equations. Originality/value – This paper proposes efficient iterative methods without computing any matrix inverses, vec operator and Kronecker product for finding the solution of the systems of linear matrix equations. [ABSTRACT FROM AUTHOR]

Purpose – This paper aims to show an evolutionary topology optimization procedure for the design of compliant electro-thermal mechanisms. Design/methodology/approach – The adopted methodology is based in the evolutionary structural optimization (ESO) method. This approach has been successfully applied by this group for compliant mechanisms optimization under directly applied input loads and simple thermal loads. This work proposes an extension of this procedure, based on an additive version of the method, to solve the more complicated case of electro-thermal actuators optimum design, based on Joule's resistive heating. Findings – Examples solved for the design of plane compliant mechanisms are presented to check the validity of this technique. The designs obtained are compared favorably with results obtained by other authors to illustrate and validate the method, showing the viability of this technique for the optimization of compliant mechanisms under electro-thermal actuation. Research limitations/implications – This investigation is based on and additive version of the evolutionary method. Since this approach does not have the capability to remove material it could be combined with the classic element rejection evolutionary method to overcome these deficiencies, developing an improved bi-directional algorithm, which should be analyzed and applied for these types of designs in future works. Practical implications – Electro-thermal actuators have widespread use in MicroElectroMechanical Systems applications. Since these elements cannot be manufactured using typical assembly processes compliant mechanisms optimization play a crucial role for their successful design. The proposed methodology could help engineers to rapidly conceive complex and efficient actuators. Social implications – The topology optimization procedure developed in this paper enables systematic design of these devices, which can result in a save of manufacturing time and cost. Originality/value – Most applications of the ESO method have considered maximum stiffness structure design, and even if it has been successfully applied to some other optimum material distribution problems, electro-thermal actuators design has not been considered yet. This paper shows that this methodology could be useful also in the design of electro-thermal compliant mechanisms, and provides engineers with a very simple and practical alternative design tool. [ABSTRACT FROM AUTHOR]

Purpose – The purpose of this paper is to study the identification methods for multivariable nonlinear Box-Jenkins systems with autoregressive moving average (ARMA) noises, based on the auxiliary model and the multi-innovation identification theory. Design/methodology/approach – A multi-innovation generalized extended least squares (MI-GELS) and a multi-innovation generalized ex-tended stochastic gradient (MI-GESG) algorithms are developed for multivariable nonlinear Box-Jenkins systems based on the auxiliary model. The basic idea is to construct an auxiliary model from the measured data and to replace the unknown terms in the information vector with their estimates (i.e. the outputs of the auxiliary model). Findings – It is found that the proposed algorithms can give high accurate parameter estimation compared with existing stochastic gradient algorithm and recursive extended least squares algorithm. Originality/value – In this paper, the AM-MI-GESG and AM-MI-GELS algorithms for MIMO Box-Jenkins systems with nonlinear input are presented using the multi-innovation identification theory and the proposed algorithms can improve the parameter estimation accuracy. The paper provides a simulation example. [ABSTRACT FROM AUTHOR]

Purpose |!|#8211; The purpose of this paper is to find two iterative methods to solve the general coupled matrix equations over the generalized centro-symmetric and central antisymmetric matrices. Design/methodology/approach |!|#8211; By extending the idea of conjugate gradient (CG) method, the authors present two iterative methods to solve the general coupled matrix equations over the generalized centro-symmetric and central antisymmetric matrices. Findings |!|#8211; When the general coupled matrix equations are consistent over the generalized centro-symmetric and central anti-symmetric matrices, the generalized centro-symmetric and central anti-symmetric solutions can be obtained within nite iterative steps. Also the least Frobenius norm generalized centrosymmetric and central anti-symmetric solutions can be derived by choosing a special kind of initial matrices. Furthermore, the optimal approximation generalized centrosymmetric and central anti-symmetric solutions to given generalized centro-symmetric and central anti-symmetric matrices can be obtained by finding the least Frobenius norm generalized centro-symmetric and central anti-symmetric solutions of new matrix equations. The authors employ some numerical examples to support the theoretical results of this paper. Finally, the application of the presented methods is highlighted for solving the projected generalized continuous-time algebraic Lyapunov equations (GCALE). Originality/value |!|#8211; By the algorithms, the solvability of the general coupled matrix equations over generalized centro-symmetric and central anti-symmetric matrices can be determined automatically. The convergence results of the iterative algorithms are also proposed. Several examples and an application are given to show the efficiency of the presented methods. [ABSTRACT FROM AUTHOR]

Purpose – The purpose of this paper is to present a novel gradient-based iterative algorithm for the joint diagonalization of a set of real symmetric matrices. The approximate joint diagonalization of a set of matrices is an important tool for solving stochastic linear equations. As an application, reliability analysis of structures by using the stochastic finite element analysis based on the joint diagonalization approach is also introduced in this paper, and it provides useful references to practical engineers. Design/methodology/approach – By starting with a least squares (LS) criterion, the authors obtain a classical nonlinear cost-function and transfer the joint diagonalization problem into a least squares like minimization problem. A gradient method for minimizing such a cost function is derived and tested against other techniques in engineering applications. Findings – A novel approach is presented for joint diagonalization for a set of real symmetric matrices. The new algorithm works on the numerical gradient base, and solves the problem with iterations. Demonstrated by examples, the new algorithm shows the merits of simplicity, effectiveness, and computational efficiency. Originality/value – A novel algorithm for joint diagonalization of real symmetric matrices is presented in this paper. The new algorithm is based on the least squares criterion, and it iteratively searches for the optimal transformation matrix based on the gradient of the cost function, which can be computed in a closed form. Numerical examples show that the new algorithm is efficient and robust. The new algorithm is applied in conjunction with stochastic finite element methods, and very promising results are observed which match very well with the Monte Carlo method, but with higher computational efficiency. The new method is also tested in the context of structural reliability analysis. The reliability index obtained with the joint diagonalization approach is compared with the conventional Hasofer Lind algorithm, and again good agreement is achieved. [ABSTRACT FROM AUTHOR]

Purpose - This paper seeks to describe a design approach which can be used to manufacture better-performing reciprocating compressors. This design approach relates the drive kinematic characteristics to the thermodynamic performance of the compressor. Design/methodology/approach - The presented approach is based on employing a stochastic optimisation algorithm to find the best piston trajectory within one cycle of operation and couple that with a gradient-based technique to find the best dimensions of the mechanism which can realise this trajectory. Findings - The mathematical models presented to implement the proposed design approach have been coded in a computer program which has been employed for simulation purposes. A case study given at the end of the paper asserts the usefulness of the proposed method and proves that a few percentage points increase in a defined set of performance indices has been gained from the optimisation exercise. Research limitations/implications - The presented models are only relevant to reciprocating compressors. Practical implications - The promising results obtained in this paper will lead to the creation of better performing and more reliable compressor drives, designed to fulfil a set of desired performance criteria. Originality/value - The paper offers originality in two different aspects. The mechanism design process has been undertaken in full consideration to the thermodynamic performance of the compressor; and the coupling of the stochastic and the gradient-based optimisation methods to produce the desired outcome. [ABSTRACT FROM AUTHOR]

Purpose - The purpose of this paper is to develop a hybrid-Trefftz (HT) finite element model (FEM) for simulating heat conduction in nonlinear functionally graded materials (FGMs) which can effectively handle continuously varying properties within an element. Design/methodology/approach - In the proposed model, a T-complete set of homogeneous solutions is first derived and used to represent the intra-element temperature fields. As a result, the graded properties of the FGMs are naturally reflected by using the newly developed Trefftz functions (T-complete functions in some literature) to model the intra-element fields. The derivation of the Trefftz functions is carried out by means of the well-known Kirchhoff transformation in conjunction with various variable transformations. Findings - The study shows that, in contrast to the conventional FEM, the HT-FEM is an accurate numerical scheme for FGMs in terms of the number of unknowns and is insensitive to mesh distortion. The method also performs very well in terms of numerical accuracy and can converge to the analytical solution when the number of elements is increased. Originality/value - The value of this paper is twofold: a T-complete set of homogeneous solutions for nonlinear FMGs has been derived and used to represent the intra-element temperature; and the corresponding variational functional and the associated algorithm has been constructed. [ABSTRACT FROM AUTHOR]