Abstract: This paper deals with the application of genetic algorithm (GA) optimization technique to predict peak particle velocity (PPV). PPV is one of the important parameters to be determined to minimize the damage caused by ground vibration. A number of previous researchers have tried to use different empirical methods to predict PPV but these empirical methods have their limitations due to their less versatile application. In this paper, GA technique is used for the prediction of PPV by incorporating blast design and explosive parameters and the suitability of one technique over other has been analyzed based on the results. Datasets have been obtained from one of the Kurasia mines. 127 data sets were used to establish GA architecture and 10 data sets have been used for validation of GA model to observe its prediction capability. The results obtained have been compared with different traditional vibration predictors, multivariate regression analysis, artificial neural network and the superiority of application of GA over previous methodology have been discussed. The mean absolute percentage error in the proposed architect is very low (0.08) as compared to other predictors.

Abstract: Ground vibrations induced by blasting are one of the fundamental problems in the mining industry and may cause severe damage to structures and plants nearby. Therefore, a vibration control study plays an important role in the minimization of environmental effects of blasting in mines. In this paper, an attempt has been made to predict the peak particle velocity using support vector machine (SVM) by taking into consideration of maximum charge per delay and distance between blast face to monitoring point. To investigate the suitability of this approach, the predictions by SVM have been compared with conventional vibration predictor equations. Coefficient of determination (CoD) and mean absolute error were taken as a performance measure.

Abstract: In this study, two computational approaches, Genetic Algorithm and Simulated Annealing, are applied to search for a set of optimal process parameters value that leads to the minimum value of machining performance. The objectives of the applied techniques are: (1) to estimate the minimum value of the machining performance compared to the machining performance value of the experimental data and regression modeling, (2) to estimate the optimal process parameters values that has to be within the range of the minimum and maximum coded values for process parameters of experimental design that are used for experimental trial and (3) to evaluate the number of iteration generated by the computational approaches that lead to the minimum value of machining performance. Set of the machining process parameters and machining performance considered in this work deal with the real experimental data of the non-conventional machining operation, abrasive waterjet. The results of this study showed that both of the computational approaches managed to estimate the optimal process parameters, leading to the minimum value of machining performance when compared to the result of real experimental data.

Abstract: Metamodeling methods have been widely used in engineering applications to create surrogate models for complex systems. In the past, the input–output relationship of the complex system is usually approximated globally using only a single metamodel. In this research, a new metamodeling method, namely multi-surrogate approximation (MSA) metamodeling method, is developed using multiple metamodels when the sample data collected from different regions of the design space are of different characteristics. In this method, sample data are first classified into clusters based on their similarities in the design space, and a local metamodel is identified for each cluster of the sample data. A global metamodel is then built using these local metamodels considering the contributions of these local metamodels in different regions of the design space. Compared with the traditional approach of global metamodeling using only a single metamodel, this MSA metamodeling method can improve the modeling accuracy considerably. Applications of this metamodeling method have also been demonstrated in this research.

Abstract: This paper reports the simulation results for the unsteady cavitating turbulent flow in a Francis turbine using the mixture model for cavity–liquid two-phase flows. The RNG k–e turbulence model is employed in the Reynolds averaged Navier–Stokes equations in this study. In the mixture model, an improved expression for the mass transfer is employed which is based on evaporation and condensation mechanisms with considering the effects of the non-dissolved gas, the turbulence, the tension of interface at cavity and the effect of phase change rate and so on. The computing domain includes the guide vanes, the runner, and the draft tube, which is discretized with a full three-dimensional mesh system of unstructured tetrahedral shapes. The finite volume method is used to solve the governing equations of the mixture model and a full coupled method is combined into the algorithm to accelerate the solution. The computing results with the mixture model have been compared with those by the single-phase flow model as well as the experimental data. The simulation results show that the cavitating flow computation based on the improved mixture model agrees much better with experimental data than that by the single-phase flow calculation, in terms of the amplitude and dominated frequency of the pressure fluctuation. It is also observed from the present simulations that the amplitude of the pressure fluctuation at small flow rate is larger than that at large flow rate, which accords with the experimental data.

Abstract: Optimizing surface and volume triangulations is critical for many advanced numerical simulation applications. We present a variational approach for smoothing triangulated surface and volume meshes to improve their overall mesh qualities. Our method seeks to reduce the discrepancies between the actual elements and ideal reference elements by minimizing two energy functions based on conformal and isometric mappings. We derive simple, closed-form formulas for the values, gradients, and Hessians of these energy functions, which reveal important connections of our method with some well-known concepts and methods in mesh generation and surface parameterization. We then introduce a simple and efficient iterative algorithm for minimizing the energy functions, including a novel asynchronous step-size control scheme. We demonstrate the effectiveness of our method experimentally and compare it against Laplacian smoothing and some other mesh smoothing techniques.

Abstract: We describe a two-level method for computing a function whose zero-level set is the surface reconstructed from given points scattered over the surface and associated with surface normal vectors. The function is defined as a linear combination of compactly supported radial basis functions (CSRBFs). The method preserves the simplicity and efficiency of implicit surface interpolation with CSRBFs and the reconstructed implicit surface owns the attributes, which are previously only associated with globally supported or globally regularized radial basis functions, such as exhibiting less extra zero-level sets, suitable for inside and outside tests. First, in the coarse scale approximation, we choose basis function centers on a grid that covers the enlarged bounding box of the given point set and compute their signed distances to the underlying surface using local quadratic approximations of the nearest surface points. Then a fitting to the residual errors on the surface points and additional off-surface points is performed with fine scale basis functions. The final function is the sum of the two intermediate functions and is a good approximation of the signed distance field to the surface in the bounding box. Examples of surface reconstruction and set operations between shapes are provided.

Abstract: Registration methods are used in the meshing field to “adapt” a given mesh to a target domain Finite element method (FEM) is applied to the resulting mesh to compute an approximate solution to the system of partial differential equations (PDE) representing the physical phenomena under study Prior to FE analysis the Jacobian matrix determinant must be checked for all mesh elements The value of this Jacobian depends on the configuration of the element nodes If it is negative for a given node, the element is invalid and therefore the FE analysis cannot be carried out Similarly, some elements, although valid, can present poor quality regarding Jacobian-based indicator values, such as the Jacobian ratio Mesh registration procedures are likely to produce invalid and/or poor quality elements if the Jacobian parameter is ignored To repair invalid and poor quality elements after mesh registration, we propose a relaxation procedure driven by specific validity and quality energy formulations derived from the Jacobian value The algorithm first recovers mesh validity and further improves elements quality, focusing primarily on nodes that make the elements invalid or of poor quality Our novel approach has been developed in the context of non-rigid mesh registration and validated on a data set of 60 clinical cases in the context of orthopaedic and orthognathic hard and soft tissues modelling studies The proposed repair method achieves a valid state of the mesh and also raises the quality of the elements to a level suitable for commercial FE solvers

Abstract: Genetic programming (GP) is an evolutionary algorithm-based methodology that employs a binary tree topology with optimized functional operators. This study introduced weight coefficients to each GP linkage in a tree in order to create a new weighted genetic programming (WGP) approach. Two distinct advantages of the proposed WGP include (1) balancing the influences of the two front input branches and (2) incorporating weights throughout generated formulas. Resulting formulas contain a certain quantity of optimized functions and weights. Genetic algorithms are employed to accomplish WGP optimization of function selection and proper weighting tasks. Case studies presented herein highlight a high-strength concrete reference study. Results showed that the proposed WGP not only improves GP in terms of introduced weight coefficients, but also provides both accurate results and formula outputs.

Abstract: Higher-order finite element method requires valid curved meshes in three-dimensional domains to achieve the solution accuracy. When applying adaptive higher-order finite elements in large-scale simulations, complexities that arise include moving the curved mesh adaptation along with the critical domains to achieve computational efficiency. This paper presents a procedure that combines Bezier mesh curving and size-driven mesh adaptation technologies to address those requirements. A moving mesh size field drives a curved mesh modification procedure to generate valid curved meshes that have been successfully analyzed by SLAC National Accelerator Laboratory researchers to simulate the short-range wakefields in particle accelerators. The analysis results for a 8-cavity cryomodule wakefield demonstrate that valid curvilinear meshes not only make the time-domain simulations more reliable, but also improve the computational efficiency up to 30%. The application of moving curved mesh adaptation to an accelerator cavity coupler shows a tenfold reduction in execution time and memory usage without loss in accuracy as compared to uniformly refined meshes.

Abstract: Finite element mesh adaptation methods can be used to improve the efficiency and accuracy of solutions to computational modeling problems. In many applications involving hexahedral meshes, localized modifications which preserve a conforming all-hexahedral mesh are desired. Effective hexahedral refinement methods that satisfy these criteria have recently become available; however, due to hexahedral mesh topology constraints, little progress has been made in the area of hexahedral coarsening. This paper presents a new method to locally coarsen conforming all-hexahedral meshes. The method works on both structured and unstructured meshes and is not based on undoing previous refinement. Building upon recent developments in quadrilateral coarsening, the method utilizes hexahedral sheet and column operations, including pillowing, column collapsing, and sheet extraction. A general algorithm for automated coarsening is presented and examples of models that have been coarsened with this new algorithm are shown. While results are promising, further work is needed to improve the automated process.

Abstract: Tensegrity systems are lightweight structures composed of cables and struts. The nonlinear behavior of tensegrity systems is critical; therefore, the design of these types of structures is relatively complex. In the present study, a practical and efficient approach for geometrical nonlinear analysis of tensegrity systems is proposed. The approach is based on the point iterative method. Static equilibrium equations are given in nodes for subsystems, thus the maximum unknown displacement number in each step is three. Pre-stress forces in the system are taken into account in a tangent stiffness matrix, while similar calculations are carried out for each node in the system which has a minimum of one degree of freedom. In each iteration step, the values found in previous steps are used. When it reaches permissible tolerance of calculation, final displacements and internal forces are obtained. The structural behavior of the tensegrity systems were evaluated by the proposed method. The results show that the method can be used effectively for tensegrity systems.

Abstract: Agitation in a mixer-settler is one of the most common operations, yet presents one of the greatest challenges in the area of computer simulation. Mixer-settlers typically contain an impeller mounted on a shaft, and optionally can contain baffles. The hydrodynamic characteristics of mixer-settlers have been studied in the present study. The effect of different geometrical parameters on the efficiency characteristics of the system has been investigated. The effects of different width of impellers, impeller speed, inlet velocity, impeller diameter, etc. have been studied. Computational fluid dynamics (CFD) model has been developed to predict the efficiency characteristics. The model has been validated with the help of experimental data for different velocity outlets used in the work. This work has enabled developing efficiency that can produce higher condition than those reported in previous literature. From the CFD simulations results, optimum mixer-settler geometry has been proposed.

Abstract: Thin hard coatings deposited with physical vapor deposition (PVD) can enhance both the fatigue and the rolling contact fatigue resistance of mechanical components In this work a cheap and fast way to evaluate the best parameter levels of coating and bulk material is proposed Design of Experiments (DoE) was applied to the numerical results obtained from the simulation of meshing PVD-coated spur gears Preliminary analyses were performed to assess the fatigue behaviour of PVD-coated standard specimens for rotating bending tests The coating elastic modulus and thickness, and the trend of the residual stresses induced by the deposition process were considered among the variables affecting the fatigue and the rolling contact fatigue behaviour Different bulk materials, including steel and titanium alloys, were analyzed The proposed method may help to define the optimal coating design, especially when the replacement of traditional steels with light alloys constitutes a goal that is strongly recommended

Abstract: Practical aspects of implementing surfactant mass balance computation in finite elements models, where the model geometry shape change is captured by utilizing the arbitrary Lagrange–Eulerian method are discussed briefly. The discussion and the reported simulations are carried out in two-dimensional Cartesian coordinates. Two alternative approaches to formulating the governing equation of surfactant mass balance for solving it computationally are presented and discussed. One of the approaches is based on computing the boundary curvature and boundary tangential velocity, as well as their differentials on the boundary, directly. The other approach is based on reformulating the governing equation in order to track the proportional rate of change of local surface area. As a conclusion, it is found that though both of the presented approaches can be configured to perform adequately in terms of surfactant mass conservation, surface differentials that are necessary to compute the surface curvature and surface tangential velocity in the first one of the methods evoke numerical oscillations near those points of the boundary where it is not smooth. The text is accompanied by example simulations and figures.

Abstract: In this work we develop a procedure to deform a given surface triangulation to obtain its alignment with interior curves. These curves are defined by splines in a parametric space and, subsequently, mapped to the surface triangulation. We have restricted our study to orthogonal mapping, so we require the curves to be included in a patch of the surface that can be orthogonally projected onto a plane (our parametric space). For example, the curves can represent interfaces between different materials or boundary conditions, internal boundaries or feature lines. Another setting in which this procedure can be used is the adaption of a reference mesh to changing curves in the course of an evolutionary process. Specifically, we propose a new method that moves the nodes of the mesh, maintaining its topology, in order to achieve two objectives simultaneously: the piecewise approximation of the curves by edges of the surface triangulation and the optimization of the resulting mesh. We will designate this procedure as projecting/smoothing method and it is based on the smoothing technique that we have introduced for surface triangulations in previous works. The mesh quality improvement is obtained by an iterative process where each free node is moved to a new position that minimizes a certain objective function. The minimization process is done on the parametric plane attending to the surface piece-wise approximation and to an algebraic quality measure (mean ratio) of the set of triangles that are connected to the free node. So, the 3-D local projecting/smoothing problem is reduced to a 2-D optimization problem. Several applications of this method are presented.

Abstract: Engineering design of thermal quality clothing is a promising solution by applying multi-disciplinary knowledge to achieve the design and production of clothing with desirable thermal functions. In this paper, a special simulation-based and lifestyle-oriented CAD system is introduced to help the user in engineering design of thermal quality clothing. The engineering-oriented simulation models endowed with explicit data availability arose from the material parameters that are the key issue for engineering application. To offer an easy-to-use tool, this system is implemented with a lifestyle-oriented design procedure. It can facilitate the designers to quickly implement design and simulate on the wearing scenario, and evaluate and optimize their design. Due to the design of thermal quality clothing can be achieved without making physical prototypes, it is able to speed up the design cycle and reduce the design and development cost.

Abstract: This paper presents a computational method for converting a non-conformal hex-dominant mesh to a conformal hex-dominant mesh without help of pyramid elements. During the conversion, the proposed method subdivides a non-conformal element by applying a subdivision template and conformal elements by a conventional subdivision scheme. Although many finite element solvers accept mixed elements, some of them require a mesh to be conformal without a pyramid element. None of the published automated methods could create a conformal hex-dominant mesh without help of pyramid elements, and therefore the applicability of the hex-dominant mesh has been significantly limited. The proposed method takes a non-conformal hex-dominant mesh as an input and converts it to a conformal hex-dominant mesh that consists only of hex, tet, and prism elements. No pyramid element will be introduced. The conversion thus considerably increases the applicability of the hex-dominant mesh in many finite element solvers.

Abstract: Streamflow forecasting is significantly important for planning and operating water resource systems. However, streamflow formation is a highly nonlinear, time varying, spatially distributed process and difficult to forecast. This paper proposes a nonlinear model which incorporates improved real-coded grammatical evolution (GE) with a genetic algorithm (GA) to predict the ten-day inflow of the De-Chi Reservoir in central Taiwan. The GE is a recently developed evolutionary-programming algorithm used to express complex relationships among long-term nonlinear time series. The algorithm discovers significant input variables and combines them to form mathematical equations automatically. Utilizing GA with GE optimizes an appropriate type of function and its associated coefficients. To enhance searching efficiency and genetic diversity during GA optimization, the macro-evolutionary algorithm (MA) is processed as a selection operator. The results using an example of theoretical nonlinear time series problems indicate that the proposed GEMA yields an efficient optimal solution. GEMA has the advantages of its ability to learn relationships hidden in data and express them automatically in a mathematical manner. When applied to a real world case study, the fittest equation generated through GEMA used only a single input variable in a reasonable nonlinear form. The predicting accuracies of GEMA were better than those of the traditional linear regression (LR) model and as good as those of the back-propagation neural network (BPNN). In addition, the predicting of ten-day reservoir inflows reveals the effectives of GEMA, and standardization is beneficial to model for seasonal time series.

Abstract: Hand-held laser scanners are commonly used in industry for reverse engineering and quality measurements. In this process, it is difficult for the human operator to scan the target object completely and uniformly. Therefore, an interactive triangulation of the scanned points can assist the operator in this task. In this paper, we describe the technical and implementational details of our real-time triangulation approach for point streams, presented at the 17th International Meshing Roundtable. Our method computes a triangulation of the point stream generated by the laser scanner online, i.e., the data points are added to the triangulation as they are received from the scanner. Multiple scanned areas and areas with a higher point density result in a finer mesh and a higher accuracy. On the other hand, the vertex density adapts to the estimated surface curvature. To guide the operator, the resulting triangulation is rendered with a visualization of its uncertainty and the display of an optimal scanning direction.

Abstract: Solid-shell elements can be seen as a class of typical double-surfaced shell elements with no rational degrees of freedom, which are more suitable for analyzing double-sided contact problems than conventional shell elements. In this study, a solid-shell finite element model is implemented into the explicit finite element software ABAQUS/Explicit as a user-defined element, through which the sheet metal forming processes are simulated. The main feature of this finite element model is that the solid-shell element formulation is embedded into an explicit finite element procedure, compared to the previous studies on the solid-shell elements under the implicit finite element framework. To obtain a straightforward element, a complete integration scheme is adopted. No loss of generality, a twelve-parameter enhance assumed strain method is employed to improve the element’s behavior. Two benchmarks from the NUMISHEET conference and a U-channel roll-forming process are simulated with this explicit solid-shell finite element model. The calculated results are comparable with experimental and numerical results presented in the literatures.

Abstract: Most engineering artifacts are designed and analyzed today within a 3-D computer aided design (CAD) environment. However, slender objects such as beams are designed in a 3-D environment, but analyzed using a 1-D beam-element, since their 3-D analysis exhibits locking and/or is computationally inefficient. This process is tedious and error-prone. Here, we propose a dual-representation strategy for designing and analyzing 3-D beams, directly within a 3-D CAD environment. The proposed method exploits classic 1-D beam physics, but is implemented within a 3-D CAD environment by appealing to the divergence theorem. Consequently, the proposed method is numerically and computationally equivalent to classic 1-D beam analysis for uniform cross-section beams. But, more importantly, it closely matches the accuracy of a full-blown 3-D finite element analysis for non-uniform beams.

Abstract: We present a constraint-based methodology which is successfully applied to a variety of engineering problems from a wide range of disciplines. Initially conceived from investigations of the engineering design process, the methodology has helped design engineers to identify and understand the initial limitations placed upon a system. Written as a set of algebraic expressions, the design objectives and design constraints can be formulated and minima found using numerical optimization techniques. These solutions provide initial configurations for the system, corresponding to how “true” all of the constraints are. A bespoke constraint-based modelling environment has been created which embodies the methodology. This is able to resolve large systems, comprising over 100 degrees-of-freedom, using an assortment of optimization routines—direct, gradient and evolutionary algorithms. These algorithms are appropriate for a number of problem types and their inclusion increase the scope of applicability of the methodology which is demonstrated using case studies from a number of engineering domains. Machines and mechanisms; human modelling; force and flow; structural geology and discrete disassembly processes are all studied using constraint-based formulations. The contribution of the paper lies in thus proving that complex (heterogeneous) systems-of-systems can be solved if the connectivity between the systems is expressed using constraint-rules.

Abstract: During the evolution of constraint modeling approaches, they have increased in their ability to resolve more and more complex problems. They all rely upon their ability to define the design problem by a set of constraint rules, which are true when the problem is solved, by the manipulation of selected free variables. However, as they have advanced differing techniques, they have been applied to address problems of increasing complexity. This study has been directed toward addressing those that are not only complex but also ill structured and evolving. In order to address such problems, an approach has been developed that employs sensitivity analysis and problem strategies to form an evolving direct search technique. While this is generic approach, which has been applied to a range of engineering problems, it is illustrated here through its use in a study into the posture modeling of humans. In this, it was recognized that such a new approach was required due to the complex description, limits, and postures possible in the human body.

Abstract: We present a mesh optimization algorithm for adaptively improving the finite element interpolation of a function of interest. The algorithm minimizes an objective function by swapping edges and moving nodes. Numerical experiments are performed on model problems. The results illustrate that the mesh optimization algorithm can reduce the W 1,∞ semi-norm of the interpolation error. For these examples, the L 2, L ∞, and H 1 norms decreased also.

Abstract: Product catalogues constitute a valuable source of information for engineers engaged in design activities. Unfortunately, these catalogues provide only limited support to engineers in the earlier, conceptual stages of design. This research proposes the intelligent design catalogue consisting of a virtual design environment linked to catalogues of standard components. Engineers develop their design concepts within the virtual environment and refer to the catalogues as these concepts are refined. The selected components are assembled within the design environment. The intelligent design catalogue provides search aids as well as assessment tools. The theoretical framework draws on several engineering areas. Manufacturing demonstrates how process plans can be developed in a virtual environment independently of the machines on the shop floor just as products can be conceptually designed independently of the standard components available. The standard components themselves can be grouped borrowing from classification schemes of group technology. Object-oriented programming (OOP) provides an environment for the development of the software that runs the intelligent design catalogue. As the objects of OOP parallel standard components, OOP also serves as a design paradigm after which the catalogue can be modelled. Design theory suggests frameworks for developing a (semi-) hierarchical structure for cataloguing parts.

Abstract: From an engineering point of view, church bells are structures that, during ringing, are exposed to severe loading conditions. They are damaged due to material wear, fatigue loading, material deficiencies, different clapper-to-bell layouts, ringing conditions, etc. To get an insight into the wear-related damage of bells, experimental investigations and numerical simulations of the local contact between the clapper and the bell were carried out as part of the activities of an EU-funded project called Maintenance and Protection of Bells. In order to make a full-scale comparison between the measured and simulated results a simplified model was set up. In this model the clapper was replaced by a cylinder with a rounded tip that was dropped against a block representing the bell wall. The aim of the simplified model was to study the impact phenomenon in a controlled way and to adapt the numerical model for simulating the local contact. In the article the synthesis of a finite-element model for simulating the cylinder-drop test is presented. The results of the finite-element simulations of repetitive cylinder drops are compared to the data that were measured in the laboratory. The effects of the cylinder material, the cylinder radius and the drop height of the cylinder on the local elastic–plastic behaviour of the cylinder and the block are also presented and discussed.

Abstract: Metamodels are used to provide more efficient predictions than the underlying simulation models do, but at the price of reduced prediction accuracy. Statistics used to quantify this prediction accuracy include the root-mean square error (RMSE), the coefficient of determination R-square, and the average absolute error (AAE). Such statistics depend on the average prediction accuracy over the validation sample; i.e., these metrics are sensitive to the size of the validation sample. This article, therefore, introduces a new metric, called the Model acceptability score (MAS). Preliminary results indicate that MAS is less sensitive to the validation sample size. The article focuses on deterministic simulation, which is used in various engineering disciplines, e.g., electronic engineering.

Abstract: Large scale, multidisciplinary, engineering designs are always difficult due to the complexity and dimensionality of these problems. Direct coupling between the analysis codes and the optimization routines can be prohibitively time consuming due to the complexity of the underlying simulation codes. One way of tackling this problem is by constructing computationally cheap(er) approximations of the expensive simulations that mimic the behavior of the simulation model as closely as possible. This paper presents a data driven, surrogate-based optimization algorithm that uses a trust region-based sequential approximate optimization (SAO) framework and a statistical sampling approach based on design of experiment (DOE) arrays. The algorithm is implemented using techniques from two packages—SURFPACK and SHEPPACK that provide a collection of approximation algorithms to build the surrogates and three different DOE techniques—full factorial (FF), Latin hypercube sampling, and central composite design—are used to train the surrogates. The results are compared with the optimization results obtained by directly coupling an optimizer with the simulation code. The biggest concern in using the SAO framework based on statistical sampling is the generation of the required database. As the number of design variables grows, the computational cost of generating the required database grows rapidly. A data driven approach is proposed to tackle this situation, where the trick is to run the expensive simulation if and only if a nearby data point does not exist in the cumulatively growing database. Over time the database matures and is enriched as more and more optimizations are performed. Results show that the proposed methodology dramatically reduces the total number of calls to the expensive simulation runs during the optimization process.