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COMPUTER SCIENCE (1196 journals)                  1 2 3 4 5 6 | Last

Showing 1 - 200 of 872 Journals sorted alphabetically
3D Printing and Additive Manufacturing     Full-text available via subscription   (Followers: 20)
Abakós     Open Access   (Followers: 4)
ACM Computing Surveys     Hybrid Journal   (Followers: 27)
ACM Journal on Computing and Cultural Heritage     Hybrid Journal   (Followers: 8)
ACM Journal on Emerging Technologies in Computing Systems     Hybrid Journal   (Followers: 12)
ACM Transactions on Accessible Computing (TACCESS)     Hybrid Journal   (Followers: 3)
ACM Transactions on Algorithms (TALG)     Hybrid Journal   (Followers: 15)
ACM Transactions on Applied Perception (TAP)     Hybrid Journal   (Followers: 5)
ACM Transactions on Architecture and Code Optimization (TACO)     Hybrid Journal   (Followers: 9)
ACM Transactions on Autonomous and Adaptive Systems (TAAS)     Hybrid Journal   (Followers: 7)
ACM Transactions on Computation Theory (TOCT)     Hybrid Journal   (Followers: 12)
ACM Transactions on Computational Logic (TOCL)     Hybrid Journal   (Followers: 3)
ACM Transactions on Computer Systems (TOCS)     Hybrid Journal   (Followers: 18)
ACM Transactions on Computer-Human Interaction     Hybrid Journal   (Followers: 15)
ACM Transactions on Computing Education (TOCE)     Hybrid Journal   (Followers: 5)
ACM Transactions on Design Automation of Electronic Systems (TODAES)     Hybrid Journal   (Followers: 4)
ACM Transactions on Economics and Computation     Hybrid Journal  
ACM Transactions on Embedded Computing Systems (TECS)     Hybrid Journal   (Followers: 3)
ACM Transactions on Information Systems (TOIS)     Hybrid Journal   (Followers: 19)
ACM Transactions on Intelligent Systems and Technology (TIST)     Hybrid Journal   (Followers: 8)
ACM Transactions on Interactive Intelligent Systems (TiiS)     Hybrid Journal   (Followers: 3)
ACM Transactions on Multimedia Computing, Communications, and Applications (TOMCCAP)     Hybrid Journal   (Followers: 9)
ACM Transactions on Reconfigurable Technology and Systems (TRETS)     Hybrid Journal   (Followers: 6)
ACM Transactions on Sensor Networks (TOSN)     Hybrid Journal   (Followers: 8)
ACM Transactions on Speech and Language Processing (TSLP)     Hybrid Journal   (Followers: 9)
ACM Transactions on Storage     Hybrid Journal  
ACS Applied Materials & Interfaces     Full-text available via subscription   (Followers: 29)
Acta Automatica Sinica     Full-text available via subscription   (Followers: 2)
Acta Informatica Malaysia     Open Access  
Acta Universitatis Cibiniensis. Technical Series     Open Access  
Ad Hoc Networks     Hybrid Journal   (Followers: 11)
Adaptive Behavior     Hybrid Journal   (Followers: 11)
Advanced Engineering Materials     Hybrid Journal   (Followers: 28)
Advanced Science Letters     Full-text available via subscription   (Followers: 10)
Advances in Adaptive Data Analysis     Hybrid Journal   (Followers: 7)
Advances in Artificial Intelligence     Open Access   (Followers: 15)
Advances in Calculus of Variations     Hybrid Journal   (Followers: 2)
Advances in Catalysis     Full-text available via subscription   (Followers: 5)
Advances in Computational Mathematics     Hybrid Journal   (Followers: 19)
Advances in Computer Engineering     Open Access   (Followers: 4)
Advances in Computing     Open Access   (Followers: 2)
Advances in Data Analysis and Classification     Hybrid Journal   (Followers: 51)
Advances in Engineering Software     Hybrid Journal   (Followers: 27)
Advances in Geosciences (ADGEO)     Open Access   (Followers: 13)
Advances in Human Factors/Ergonomics     Full-text available via subscription   (Followers: 22)
Advances in Human-Computer Interaction     Open Access   (Followers: 20)
Advances in Materials Sciences     Open Access   (Followers: 14)
Advances in Operations Research     Open Access   (Followers: 12)
Advances in Parallel Computing     Full-text available via subscription   (Followers: 7)
Advances in Porous Media     Full-text available via subscription   (Followers: 5)
Advances in Remote Sensing     Open Access   (Followers: 44)
Advances in Science and Research (ASR)     Open Access   (Followers: 6)
Advances in Technology Innovation     Open Access   (Followers: 5)
AEU - International Journal of Electronics and Communications     Hybrid Journal   (Followers: 8)
African Journal of Information and Communication     Open Access   (Followers: 9)
African Journal of Mathematics and Computer Science Research     Open Access   (Followers: 4)
AI EDAM     Hybrid Journal  
Air, Soil & Water Research     Open Access   (Followers: 11)
AIS Transactions on Human-Computer Interaction     Open Access   (Followers: 6)
Algebras and Representation Theory     Hybrid Journal   (Followers: 1)
Algorithms     Open Access   (Followers: 11)
American Journal of Computational and Applied Mathematics     Open Access   (Followers: 5)
American Journal of Computational Mathematics     Open Access   (Followers: 4)
American Journal of Information Systems     Open Access   (Followers: 5)
American Journal of Sensor Technology     Open Access   (Followers: 4)
Anais da Academia Brasileira de Ciências     Open Access   (Followers: 2)
Analog Integrated Circuits and Signal Processing     Hybrid Journal   (Followers: 7)
Analysis in Theory and Applications     Hybrid Journal   (Followers: 1)
Animation Practice, Process & Production     Hybrid Journal   (Followers: 5)
Annals of Combinatorics     Hybrid Journal   (Followers: 4)
Annals of Data Science     Hybrid Journal   (Followers: 12)
Annals of Mathematics and Artificial Intelligence     Hybrid Journal   (Followers: 12)
Annals of Pure and Applied Logic     Open Access   (Followers: 2)
Annals of Software Engineering     Hybrid Journal   (Followers: 13)
Annual Reviews in Control     Hybrid Journal   (Followers: 6)
Anuario Americanista Europeo     Open Access  
Applicable Algebra in Engineering, Communication and Computing     Hybrid Journal   (Followers: 2)
Applied and Computational Harmonic Analysis     Full-text available via subscription   (Followers: 1)
Applied Artificial Intelligence: An International Journal     Hybrid Journal   (Followers: 12)
Applied Categorical Structures     Hybrid Journal   (Followers: 2)
Applied Computational Intelligence and Soft Computing     Open Access   (Followers: 11)
Applied Computer Systems     Open Access   (Followers: 2)
Applied Informatics     Open Access  
Applied Mathematics and Computation     Hybrid Journal   (Followers: 33)
Applied Medical Informatics     Open Access   (Followers: 10)
Applied Numerical Mathematics     Hybrid Journal   (Followers: 5)
Applied Soft Computing     Hybrid Journal   (Followers: 16)
Applied Spatial Analysis and Policy     Hybrid Journal   (Followers: 5)
Applied System Innovation     Open Access  
Architectural Theory Review     Hybrid Journal   (Followers: 3)
Archive of Applied Mechanics     Hybrid Journal   (Followers: 5)
Archive of Numerical Software     Open Access  
Archives and Museum Informatics     Hybrid Journal   (Followers: 142)
Archives of Computational Methods in Engineering     Hybrid Journal   (Followers: 5)
arq: Architectural Research Quarterly     Hybrid Journal   (Followers: 7)
Artifact     Hybrid Journal   (Followers: 2)
Artificial Life     Hybrid Journal   (Followers: 7)
Asia Pacific Journal on Computational Engineering     Open Access  
Asia-Pacific Journal of Information Technology and Multimedia     Open Access   (Followers: 1)
Asian Journal of Computer Science and Information Technology     Open Access  
Asian Journal of Control     Hybrid Journal  
Assembly Automation     Hybrid Journal   (Followers: 2)
at - Automatisierungstechnik     Hybrid Journal   (Followers: 1)
Australian Educational Computing     Open Access   (Followers: 1)
Automatic Control and Computer Sciences     Hybrid Journal   (Followers: 4)
Automatic Documentation and Mathematical Linguistics     Hybrid Journal   (Followers: 5)
Automatica     Hybrid Journal   (Followers: 11)
Automation in Construction     Hybrid Journal   (Followers: 6)
Autonomous Mental Development, IEEE Transactions on     Hybrid Journal   (Followers: 9)
Basin Research     Hybrid Journal   (Followers: 5)
Behaviour & Information Technology     Hybrid Journal   (Followers: 52)
Big Data and Cognitive Computing     Open Access   (Followers: 2)
Biodiversity Information Science and Standards     Open Access  
Bioinformatics     Hybrid Journal   (Followers: 295)
Biomedical Engineering     Hybrid Journal   (Followers: 15)
Biomedical Engineering and Computational Biology     Open Access   (Followers: 13)
Biomedical Engineering, IEEE Reviews in     Full-text available via subscription   (Followers: 21)
Biomedical Engineering, IEEE Transactions on     Hybrid Journal   (Followers: 37)
Briefings in Bioinformatics     Hybrid Journal   (Followers: 47)
British Journal of Educational Technology     Hybrid Journal   (Followers: 140)
Broadcasting, IEEE Transactions on     Hybrid Journal   (Followers: 12)
c't Magazin fuer Computertechnik     Full-text available via subscription   (Followers: 1)
CALCOLO     Hybrid Journal  
Calphad     Hybrid Journal   (Followers: 2)
Canadian Journal of Electrical and Computer Engineering     Full-text available via subscription   (Followers: 15)
Capturing Intelligence     Full-text available via subscription  
Catalysis in Industry     Hybrid Journal   (Followers: 1)
CEAS Space Journal     Hybrid Journal   (Followers: 2)
Cell Communication and Signaling     Open Access   (Followers: 2)
Central European Journal of Computer Science     Hybrid Journal   (Followers: 5)
CERN IdeaSquare Journal of Experimental Innovation     Open Access   (Followers: 3)
Chaos, Solitons & Fractals     Hybrid Journal   (Followers: 3)
Chemometrics and Intelligent Laboratory Systems     Hybrid Journal   (Followers: 14)
ChemSusChem     Hybrid Journal   (Followers: 7)
China Communications     Full-text available via subscription   (Followers: 7)
Chinese Journal of Catalysis     Full-text available via subscription   (Followers: 2)
CIN Computers Informatics Nursing     Full-text available via subscription   (Followers: 11)
Circuits and Systems     Open Access   (Followers: 15)
Clean Air Journal     Full-text available via subscription   (Followers: 1)
CLEI Electronic Journal     Open Access  
Clin-Alert     Hybrid Journal   (Followers: 1)
Cluster Computing     Hybrid Journal   (Followers: 1)
Cognitive Computation     Hybrid Journal   (Followers: 4)
COMBINATORICA     Hybrid Journal  
Combinatorics, Probability and Computing     Hybrid Journal   (Followers: 4)
Combustion Theory and Modelling     Hybrid Journal   (Followers: 14)
Communication Methods and Measures     Hybrid Journal   (Followers: 12)
Communication Theory     Hybrid Journal   (Followers: 21)
Communications Engineer     Hybrid Journal   (Followers: 1)
Communications in Algebra     Hybrid Journal   (Followers: 3)
Communications in Computational Physics     Full-text available via subscription   (Followers: 2)
Communications in Partial Differential Equations     Hybrid Journal   (Followers: 3)
Communications of the ACM     Full-text available via subscription   (Followers: 52)
Communications of the Association for Information Systems     Open Access   (Followers: 16)
COMPEL: The International Journal for Computation and Mathematics in Electrical and Electronic Engineering     Hybrid Journal   (Followers: 3)
Complex & Intelligent Systems     Open Access   (Followers: 1)
Complex Adaptive Systems Modeling     Open Access  
Complex Analysis and Operator Theory     Hybrid Journal   (Followers: 2)
Complexity     Hybrid Journal   (Followers: 6)
Complexus     Full-text available via subscription  
Composite Materials Series     Full-text available via subscription   (Followers: 8)
Computación y Sistemas     Open Access  
Computation     Open Access   (Followers: 1)
Computational and Applied Mathematics     Hybrid Journal   (Followers: 2)
Computational and Mathematical Methods in Medicine     Open Access   (Followers: 2)
Computational and Mathematical Organization Theory     Hybrid Journal   (Followers: 2)
Computational and Structural Biotechnology Journal     Open Access   (Followers: 2)
Computational and Theoretical Chemistry     Hybrid Journal   (Followers: 9)
Computational Astrophysics and Cosmology     Open Access   (Followers: 1)
Computational Biology and Chemistry     Hybrid Journal   (Followers: 12)
Computational Chemistry     Open Access   (Followers: 2)
Computational Cognitive Science     Open Access   (Followers: 2)
Computational Complexity     Hybrid Journal   (Followers: 4)
Computational Condensed Matter     Open Access  
Computational Ecology and Software     Open Access   (Followers: 9)
Computational Economics     Hybrid Journal   (Followers: 9)
Computational Geosciences     Hybrid Journal   (Followers: 16)
Computational Linguistics     Open Access   (Followers: 23)
Computational Management Science     Hybrid Journal  
Computational Mathematics and Modeling     Hybrid Journal   (Followers: 8)
Computational Mechanics     Hybrid Journal   (Followers: 5)
Computational Methods and Function Theory     Hybrid Journal  
Computational Molecular Bioscience     Open Access   (Followers: 2)
Computational Optimization and Applications     Hybrid Journal   (Followers: 7)
Computational Particle Mechanics     Hybrid Journal   (Followers: 1)
Computational Research     Open Access   (Followers: 1)
Computational Science and Discovery     Full-text available via subscription   (Followers: 2)
Computational Science and Techniques     Open Access  
Computational Statistics     Hybrid Journal   (Followers: 14)
Computational Statistics & Data Analysis     Hybrid Journal   (Followers: 30)
Computer     Full-text available via subscription   (Followers: 96)
Computer Aided Surgery     Open Access   (Followers: 6)
Computer Applications in Engineering Education     Hybrid Journal   (Followers: 8)
Computer Communications     Hybrid Journal   (Followers: 16)
Computer Journal     Hybrid Journal   (Followers: 9)
Computer Methods in Applied Mechanics and Engineering     Hybrid Journal   (Followers: 23)
Computer Methods in Biomechanics and Biomedical Engineering     Hybrid Journal   (Followers: 12)
Computer Methods in the Geosciences     Full-text available via subscription   (Followers: 2)
Computer Music Journal     Hybrid Journal   (Followers: 19)
Computer Physics Communications     Hybrid Journal   (Followers: 7)

        1 2 3 4 5 6 | Last

Journal Cover
Advances in Engineering Software
Journal Prestige (SJR): 1.159
Citation Impact (citeScore): 4
Number of Followers: 27  
  Hybrid Journal Hybrid journal (It can contain Open Access articles)
ISSN (Print) 0965-9978
Published by Elsevier Homepage  [3162 journals]
  • Ship inner shell optimization based on the improved particle swarm
           optimization algorithm
    • Abstract: Publication date: September 2018Source: Advances in Engineering Software, Volume 123Author(s): Guan Guan, Qu Yang, Wenwen Gu, Wenying Jiang, Yan Lin To improve the changeability of ship inner shell (SIS), so that both performance and design efficiency of transport ship can be improved, a new method for SIS optimization is proposed in this study. The method is based on the parametric expression model of SIS, which is a fully-associative model driven by dimensions. Based on the parameters of SIS, the computing system of hold capacity is developed to calculate the floating status and stability automatically. Furthermore, a parametric SIS optimization model is created, including optimization objective, constraints, optimization model solving etc., in which the maximized hold capacity and minimized ballast capacity are optimization objectives, the requirements and rules for SIS design are used as the constraints. The particle swarm optimization (PSO) algorithm is improved to solve this optimization model. The proposed method is applied to a 50,000 DWT product oil tanker, and it is proved to be feasible, highly efficient, and engineering practical.
  • Numerical simulation of missile warhead operation
    • Abstract: Publication date: September 2018Source: Advances in Engineering Software, Volume 123Author(s): G. Martynenko, M. Chernobryvko, K. Avramov, V. Martynenko, A. Tonkonozhenko, V. Kozharin, D. Klymenko Numerical simulation of a missile warhead dynamic fracture is considered. The design of the warhead basic units is treated. The approach for simulations of the warhead fracture in software ANSYS is proposed. This approach is split on three stages. (I). The analysis of the static stress-strain state of the warhead, which is arisen owing to its assembling. (II). Calculations of the dynamic stress state of the structure. (III). Analysis of dynamic fracture of the most loaded units. The parameters of the warhead are chosen in order to a fracture takes place in the structure specified area.
  • Performance based discrete topology optimization of steel braced frames by
           a new metaheuristic
    • Abstract: Publication date: September 2018Source: Advances in Engineering Software, Volume 123Author(s): Saeed Gholizadeh, Mehrdad Ebadijalal Seismic topology optimization of structures is a challenging field of structural engineering. So far, a little number of studies has been conducted on this regard and all of them have presented conceptual designs which are of limited practical applicability. The main aim of the present study is to find the practical optimal placement of X- and diagonal bracing systems in steel braced frames subject to seismic loading. To achieve this purpose, a discrete topology optimization formulation is proposed in the framework of seismic performance-based design. A new metaheuristic algorithm, center of mass optimization (CMO), is proposed to deal with the performance-based discrete topology optimization (PBDTO) problem based on the physical concept of center of mass for mass distribution in space. Two challenging benchmark structural optimization problems are presented in order to demonstrate the computational merit of the proposed CMO algorithm compared to a number of algorithms in literature. Furthermore, PBDTO process is implemented for four multi-story steel braced frames by CMO. Performance of the proposed CMO-based discrete topology optimization framework in finding practical topology of bracing members for SBFs is demonstrated on PBDTO examples.
  • Parameter optimization design of vehicle E-HHPS system based on an
           improved MOPSO algorithm
    • Abstract: Publication date: September 2018Source: Advances in Engineering Software, Volume 123Author(s): Wanzhong Zhao, Zhongkai Luan, Chunyan Wang To improve the handling stability as well as reduce the steering energy consumption of heavy commercial vehicle, a novel electric-hydraulic hybrid power steering (E-HHPS) system with multiple steering modes is presented, which enables the vehicle to acquire the steering handiness at low speed and better steering road feeling at high speed by switching the actuator unit according to the current working condition. In this paper, to achieve the design goals of E-HHPS system, which are to reduce steering energy consumption and improve steering stability, three evaluation indexes of E-HHPS system are established, which convert the E-HHPS system parameter optimization problem into a multi-objective optimization model. Because it is difficult to approximate the Pareto front of the transformed optimization model by basic algorithms, a multi-objective particle swarm optimization algorithm based on adaptive decomposition (MOPSO/AD) is proposed. Test functions are used to verify the performance of the algorithm and test results show that the MOPSO/AD algorithm has better comprehensive performance and stability compared with the basic MOPSO algorithm and MOEA/D algorithm. The MOPSO/AD algorithm is applied to solve the E-HHPS system optimization model and simulation results show that the proposed MOPSO/AD algorithm has better convergence in solving the E-HHPS parameter optimization problem compared with MOPSO, which enables the optimized E-HHPS system has good handling stability and low steering energy consumption.
  • Hull form design optimization of twin-skeg fishing vessel for minimum
           resistance based on surrogate model
    • Abstract: Publication date: September 2018Source: Advances in Engineering Software, Volume 123Author(s): Yan Lin, Jingyi He, Kai Li Twin-skeg ship has better hydrodynamic performances than regular ship, however, it is still difficult to obtain an accurate relationship between skeg design and overall hydrodynamic performances. Resistance optimization is the major concern of developing twin-skeg ship. This paper proposes a combined approach for hull form design optimization of twin-skeg ship by using computational fluid dynamics (CFD) calculation and surrogate model. Main design parameters of skeg geometry and arrangement could be determined from the design domain by using the proposed method. Parametric modeling technology is adopted for performing design evaluations in an automatic manner with different design parameter combinations. A twin-skeg fishing vessel is selected as research object. In the proposed method, the sample set for constructing surrogate models is generated by using Optimal Latin Hypercube Sampling (OLHS) method, the corresponding responses are calculated through CFD simulations, and then the surrogate models are constructed by using Kriging modeling method, which represent the mathematical relationship between input design variables (skeg shape design variables) and output objective functions (resistance values under four different working conditions). The functional analysis of variance (ANOVA) is performed to investigate how much influence the design variables have on the objective functions. Finally, a multi-objective evolutionary algorithm (NSGA-II) is used to obtain the optimal solution, which shows 5.4% average decrease in the total resistance than the original design. The CFD calculation results of the optimal solution show that the proposed method can achieve minimum resistance design with high accuracy and low time cost.
  • Topology optimization of hyperelastic structure based on a directly
           coupled finite element and element-free Galerkin method
    • Abstract: Publication date: September 2018Source: Advances in Engineering Software, Volume 123Author(s): Yaqing Zhang, Wenjie Ge, Yonghong Zhang, Zhenfei Zhao, Jinwang Zhang Meshless methods can solve large classes of problems where grid-based methods are awkward to handle, such as the discretizing of complicated structures, the remeshing in large displacement problems and so on. In this study, a meshless-based topology optimization is proposed for large displacement problems of nonlinear hyperelastic structure. In order to circumvent nonlinear numerical instabilities, the linear and nonlinear analyses are set in the low- and high-stiffness region, respectively. Thus, an interpolation scheme is adopted for hybridizing the linearity and nonlinearity in the structure analysis. A directly coupled finite element and meshless method is introduced to reduce the computational cost of meshless methods and an auto-coupling strategy is proposed for the adaptive arrangement of finite element and meshless regions. Several numerical examples are given to demonstrate the effectiveness of the proposed method.
  • Optimizing presetting attributes by softcomputing techniques to improve
           tapered roller bearings working conditions
    • Abstract: Publication date: September 2018Source: Advances in Engineering Software, Volume 123Author(s): Roberto Fernandez Martinez, Ruben Lostado Lorza, Ana A. Santos Delgado, Nelson O. Piedra Pullaguari Double-row Tapered Roller Bearings are mechanical devices that have been designed to support a combination of loads that are fixed on an optimal presetting to ensure correct working conditions. The emergence of high contact stresses, fatigue spalling and pitting on the bearing railway makes it important to have a tool that enables knowing in advance whether certain presetting loads will lead to excellent working conditions or the opposite. This work proposes a methodology to classify the working condition on the basis of the values of presenting loads on four classes. To achieve this goal, a three-dimensional Finite Element (FE) model was generated. Later, a design of experiments was designed to provide the greatest amount of information by reducing the computational cost of the simulations based on FE models. Then, one of the four classes of working conditions was assigned to each of the experiments. Later, a statistical analysis and machine learning techniques were used to create classification models. Feature transformation and reduction, algorithm parameter tuning and validation methods were used to achieve robust classification models. The best results were obtained based on flexible discriminant analysis. As it provided acceptable accuracy, both the methodology and final model were validated.
  • A dynamic ductile failure analysis of shell structures using a nonlocal
           XFEM method with experimental validation
    • Abstract: Publication date: September 2018Source: Advances in Engineering Software, Volume 123Author(s): C.T. Wu, N. Ma, Y. Guo, W. Hu, K. Takada, H. Okada, K. Saito This paper presents a finite element continuous-discontinuous approach for the dynamic ductile failure analysis of shell structures. The continuum damage model based on continuous displacements is used in the continuous stage to describe the diffuse micro-cracking in ductile failure of high-strength steel before a macro-crack is formed. In the context of a fully integrated shear deformable shell formulation, a nonlocal modeling procedure based on a projection of mid-plane reference surface is introduced to regularize the element-wise strain fields induced by the continuum damage model. In the discontinuous stage, an incorporation of velocity discontinuities in shell finite elements is pursued by XFEM method when the damage variable exceeds a critical value and the transition from a continuous to a discontinuous model is permitted. A phantom-node approach is employed in the XFEM method to simplify the numerical treatment of velocity discontinuities in the shell finite element formulation. Several numerical benchmarks are examined using the explicit dynamics analysis and the results are compared with the experimental data to demonstrate the effectiveness and accuracy of the proposed method.
  • Multi-surrogate-based Differential Evolution with multi-start exploration
           (MDEME) for computationally expensive optimization
    • Abstract: Publication date: September 2018Source: Advances in Engineering Software, Volume 123Author(s): Huachao Dong, Chengshan Li, Baowei Song, Peng Wang In this paper, we present a new global optimization algorithm MDEME for black-box problems with computationally expensive objectives. Considering that Differential Evolution (DE) is an efficient global optimization algorithm but has difficulty in expensive optimization problems, we combine DE with three surrogate models Kriging, Radial Basis Function (RBF), and Quadratic Polynomial Response (QRS) to realize surrogate-based optimization. Although the three surrogates have different approximate effects that may generate diverse updating points, the surrogate-based DE may still get stuck in local optimal regions. In order to enhance its exploration capability, a multi-start optimization algorithm with a new selecting strategy is proposed. The multi-start optimization algorithm can capture and select several promising points from Kriging and RBF that always generate multiple local optimal solutions per optimization cycle. In the whole optimization process, DE and the proposed multi-start optimization are alternately carried out on the three surrogate models that are dynamically updated. Once no more satisfactory points can be obtained from Kriging and RBF, the multi-start optimization will explore the sparsely sampled area using the estimated mean square error of Kriging. After the comparison with 5 global optimization algorithms on 17 representative cases, MDEME shows its high efficiency, strong stability and good parallelism capability in dealing with expensive optimization problems. Finally, MDEME is used for the shape optimization of a blended-wing-body underwater glider, and the design performance gets significantly improved.
  • In-plane torsional stiffness in a macro-panel element for practical finite
           element modelling
    • Abstract: Publication date: August 2018Source: Advances in Engineering Software, Volume 122Author(s): T.Q. Li, T. Ward, W.J. Lewis Finite element (FE) analysis produces results, which, in most cases, gain in accuracy, as the size of the FE mesh is reduced. However, this is not necessarily the case when beam and shell element connections induce in-plane torsional effects in the shell. In such situations, shell elements either do not allow for an in-plane torsional stiffness, or, when present, the in-plane torsional stiffness is incorrectly affected by the sizes of the elements. To overcome this problem, we propose a macro- panel element that has fewer degrees of freedom, includes a new model for in-plane torsional stiffness, and produces results with sufficient accuracy to meet engineering requirements. The panel element is based on the principle of sub-structuring, i.e., the panel is meshed internally by smaller shell elements. As shown in the paper, the proposed panel element can be quite large, yet, it can give accurate analysis results. This work helps to overcome a common dilemma in practical use of finite element analysis, where finite element theory requires element sizes to be sufficiently small, but practical considerations suggest the use of large-size elements that simplify the modelling process and reduce excesses in generated results. A model built using macro-panel elements is equivalent to the model built using smaller shell elements, with the normal and shear stresses in the former being the same as the stresses in the finely meshed shell element model, We identify a number of performance benefits that become available as a consequence of modelling the shell elements at a higher level of abstraction.
  • Optimal design of prestressed concrete hollow core slabs taking into
           account its fire resistance
    • Abstract: Publication date: August 2018Source: Advances in Engineering Software, Volume 122Author(s): V. Albero, H. Saura, A. Hospitaler, J.M. Montalvà, Manuel L. Romero Prestressed hollow core slabs are a concrete element widely used as construction floor product, which manufacturing process has greatly been improved in recent years. Several research studies focused on hollow core slab performance, mainly related to its fire behavior, have provided new limit states to be assessed throughout its life cycle. Therefore, the hollow core slab design needs to be reviewed to allow for these improvements, a process which may involve changes to its geometry. In order to deal with this review, modern computational optimization techniques offer an alternative approach to traditional structural product design procedure, mainly based on the engineer's prior experience.This paper proposes a hollow core slab model (including variables and constraints) to develop heuristic search algorithms, such as simulated annealing, in order to find the most economical slab design including the fire resistant constraint and taking into account all available manufacturing technologies. The optimal designs obtained by this process save up to 20% in cross-section area compared with common circular void designs from market, which is taken as a comparison pattern. The results show that traditional designs are deficient when the fire resistant constraint is considered, so that precast manufacturers and machinery designers should use optimization techniques to modify their hollow core slab geometry.
  • Discontinuous Galerkin method in numerical simulation of two-dimensional
           thermoelasticity problem with single stabilization parameter
    • Abstract: Publication date: August 2018Source: Advances in Engineering Software, Volume 122Author(s): Jan Jaśkowiec, Piotr Pluciński The aim of the paper is the development of discontinuous Galerkin with finite difference rules (DGFD) to a two-dimensional stationary and non-stationary thermoelasticity problem. Displacement and temperature fields are approximated on the same mesh frame but with various approximation orders, which are set independently for each of the fields. Because the DGFD method does not use nodes, special attention needs to be paid to applying boundary conditions. Various types of thermal and mechanical boundary conditions are considered. In the presented approach only one stabilization parameter for the coupled problem needs to be evaluated in the DGFD method. The same parameter used in thermal and in mechanical part. The considered domain is discretized by a polygonal mesh in which the polygonal elements may have arbitrary shapes, such as e.g. a fish shape, as well as typical rectangular shapes. The orthogonality of Chebyshev basis functions may be utilized for rectangular elements. Very high-order approximate solution can be obtained in such case. In the coupled problem, the same element may be high-order for displacement field while low-order to approximate temperature. The argument contained in the paper is illustrated with few examples.
  • Genetic programming for soil-fiber composite assessment
    • Abstract: Publication date: August 2018Source: Advances in Engineering Software, Volume 122Author(s): HV Kurugodu, S Bordoloi, Y Hong, Ankit Garg, Akhil Garg, S Sreedeep, AH Gandomi Unconfined compressive strength (UCS) of soil is one of the basic index parameters for representing the compressive bearing strength of soil. Fiber reinforced soil is one of the most popular and practical ground improvement approaches used in geotechnical infrastructures. Analytical models for estimating UCS of soil-fiber composites have been developed in the literature. However, these models rarely incorporate the combined effects of dynamic field parameters such as fiber content, soil moisture, and density. These effects can be studied by the development of a holistic model based on a dimensionless strength improvement factor (SIF), which is defined as the ratio of UCS of reinforced soil to the unreinforced UCS. The current model estimating SIF indicates the improvement expected in UCS of soil-PP fiber composite based on the three design conditions such as fiber content, soil density, and moisture content. For this purpose, a series of 108 laboratory tests were first conducted to measure UCS of both fiber-reinforced soil and unreinforced soil under different fiber contents, soil density, and soil moisture content. Clayey silt soil and commercially used polypropylene (PP) fibers were selected in this study as soil and fiber material respectively. Genetic programming (GP) approach was then used to formulate models based on the measured data. The hidden non-linear relationships between SIF and the three inputs were determined by sensitivity and parametric analysis of the GP model. It was found that the moisture content in the soil has the highest influence on the strength factor that accounts for the change in strength. Coupled effects of soil parameters (soil moisture, soil density) and fiber content have been studied using parametric analysis which includes different possible field conditions (parameters). The results have been discussed along with the reinforcement mechanism of PP fiber for different soil conditions. It is believed that the robust GP model developed will be useful to determine optimum input values for designing safe bearing foundation soils which are reinforced with PP fibers.
  • Phase field modeling of quasi-static and dynamic crack propagation: COMSOL
           implementation and case studies
    • Abstract: Publication date: August 2018Source: Advances in Engineering Software, Volume 122Author(s): Shuwei Zhou, Timon Rabczuk, Xiaoying Zhuang The phase-field model (PFM) represents the crack geometry in a diffusive way without introducing sharp discontinuities. This feature enables PFM to effectively model crack propagation compared with numerical methods based on discrete crack model, especially for complex crack patterns. Due to the involvement of “phased field”, phase-field method can be essentially treated a multifield problem even for pure mechanical problem. Therefore, it is supposed that the implementation of PFM based on a software developer that especially supports the solution of multifield problems should be more effective, simpler and more efficient than PFM implemented on a general finite element software. In this work, the authors aim to devise a simple and efficient implementation of phase-field model for the modelling of quasi-static and dynamic fracture in the general purpose commercial software developer, COMSOL Multiphysics. Notably only the tensile stress induced crack is accounted for crack evolution by using the decomposition of elastic strain energy. The width of the diffusive crack is controlled by a length-scale parameter. Equations that govern body motion and phase-field evolution are written into different modules in COMSOL, which are then coupled to a whole system to be solved. A staggered scheme is adopted to solve the coupled system and each module is solved sequentially during one time step. A number of 2D and 3D examples are tested to investigate the performance of the present implementation. Our simulations show good agreement with previous works, indicating the feasibility and validity of the COMSOL implementation of PFM.
  • Uncertainty analysis of an actuator for a shape memory alloy micro-pump
           with uncertain parameters
    • Abstract: Publication date: August 2018Source: Advances in Engineering Software, Volume 122Author(s): Ahmed Guerine, Tarek Merzouki, Abdelkhalak El Hami, Tarak Ben Zineb In this paper, we propose a method for taking into account uncertainties of a micro-pump system using Shape Memory Alloy (SMA), based on the perturbation method. The proposed method is used to determine the thermo-mechanical response of a system. Comparisons with the mean value reference solution, illustrate the efficiency of the proposed method. The results are discussed in order to investigate the influence of the most influential parameters of the thermomechanical SMA model. The simulation results are obtained by the proposed method for static analysis with uncertainties.The perturbation method results are compared with the mean value reference solution. The results are discussed in order to investigate the influence of the Young's modulus E, the two transformations strain magnitude ɛtracT and ɛtracTFA, the martensite start Ms and austenite finish Af temperatures and the stress reorientation Fε on the static response of a micro-pump system.
  • An enhanced explicit technique for the solution of non-Fourier heat
           transfer problems
    • Abstract: Publication date: August 2018Source: Advances in Engineering Software, Volume 122Author(s): Delfim Soares In this work, an enhanced explicit technique is proposed to analyze hyperbolic heat conduction models. As usual, the explicit approach allows the solution of the problem to be carried out without dealing with any system of equations, featuring a very efficient methodology. In addition, the proposed technique enables algorithmic dissipation, allowing the influence of spurious high modes to be properly eliminated, without introducing significant period elongation and amplitude decay errors into the analysis. As an explicit approach, the technique is conditionally stable; however, it exhibits high stability limits (its critical time-step is around 1.8 times that of the Central Difference Method), emphasizing its effectiveness. The technique is very accurate, truly self-starting and extremely direct to implement. At the end of the manuscript, numerical results are presented, illustrating the good performance of the discussed technique.
  • Suspension mechanical performance and vehicle ride comfort applying a
           novel jounce bumper based on negative Poisson's ratio structure
    • Abstract: Publication date: August 2018Source: Advances in Engineering Software, Volume 122Author(s): Yuanlong Wang, Wanzhong Zhao, Guan Zhou, Qiang Gao, Chunyan Wang Comparing with traditional honeycomb structures, Negative Poisson's Ratio (NPR) structures had better mechanical performances in some certain respects, especially the shear modulus and fracture toughness. However, few publications focused on the cylinder-shape NPR structure, which influence the diversity and possibility of NPR structure applications. In this paper, a cylindrical NPR structure was introduced and applied as a suspension jounce bumper in order to solve the issue that the ideal uniaxial compression load-displacement curve sometimes cannot be realized by traditional Polyurethane (PU) jounce bumper. The load-displacement curve of NPR jounce bumper was proved to be smoother and more ideal than that of traditional jounce bumper. Nevertheless, the influences of NPR jounce bumper on the suspension mechanical performance and vehicle ride comfort were not comprehended yet. In this study, the traditional and NPR jounce bumpers were both assembled into virtual prototypes of Macpherson, double wishbone and multi-link suspensions to conduct single wheel travel virtual tests. The results indicated that NPR jounce bumper can achieve more ideal wheel force vs. jounce height curve without adjusting free travel, which is beneficial to spare precise suspension space. Furthermore, a jounce bumper evaluation method using pulse ride comfort was proposed in this paper. The virtual ride comfort tests of travelling through bump and pothole were conducted using established vehicle virtual prototype. The maximum vertical accelerations and weighted root mean square (RMS) of acceleration of vehicle centroid at most speeds were reduced applying NPR jounce bumper. Thus, the NPR jounce bumper can apparently improve vehicle ride comfort.
  • Evaluation of the Intel Xeon Phi offload runtimes for domain decomposition
    • Abstract: Publication date: Available online 8 July 2018Source: Advances in Engineering SoftwareAuthor(s): Lukas Maly, Jan Zapletal, Michal Merta, Lubomir Riha, Vit Vondrak In the paper we provide a comparison of several runtimes which can be used for offloading computationally intensive kernels to the Intel Xeon Phi coprocessors. The presented benchmark application is a stripped-down version of an iterative solver used within the Schur complement finite or boundary element tearing and interconnecting (FETI, BETI) domain decomposition methods where the sparse solve with local stiffness matrices is replaced by the multiplication with dense matrices in order to exploit coalesced memory access patterns. We present offload approaches based on the Intel Language Extension for Offload (LEO), Hetero Streams Library (hStreams), and Heterogeneous Active Messages (HAM), and compare their performance and ease of use.
  • Path-following interior point method: Theory and applications for the
           Stokes flow with a stick-slip boundary condition
    • Abstract: Publication date: Available online 8 July 2018Source: Advances in Engineering SoftwareAuthor(s): Tomáš Brzobohatý, Marta Jarošová, Radek Kučera, Václav Šátek A path-following interior point method is proposed for minimization of quadratic functions subject to box and equality constraints. The problems with the singular Hessian that is symmetric, positive definite on the null space of the equality constraint matrix are considered. The inner linear systems are solved by the projected conjugate gradient method preconditioned by oblique projectors. Numerical experiments include large-scale problems arising from the TFETI domain decomposition method applied for solving the Stokes flow with the stick-slip boundary condition.
  • Modelling fracture in heterogeneous materials on HPC systems using a
           hybrid MPI/Fortran coarray multi-scale CAFE framework
    • Abstract: Publication date: Available online 27 June 2018Source: Advances in Engineering SoftwareAuthor(s): A. Shterenlikht, L. Margetts, L. Cebamanos A 3D multi-scale cellular automata finite element (CAFE) framework for modelling fracture in heterogeneous materials is described. The framework is implemented in a hybrid MPI/Fortran coarray code for efficient parallel execution on HPC platforms. Two open source BSD licensed libraries developed by the authors in modern Fortran were used: CGPACK, implementing cellular automata (CA) using Fortran coarrays, and ParaFEM, implementing finite elements (FE) using MPI. The framework implements a two-way concurrent hierarchical information exchange between the structural level (FE) and the microstructure (CA). MPI to coarrays interface and data structures are described. The CAFE framework is used to predict transgranular cleavage propagation in a polycrystalline iron round bar under tension. Novel results enabled by this CAFE framework include simulation of progressive cleavage propagation through individual grains and across grain boundaries, and emergence of a macro-crack from merging of cracks on preferentially oriented cleavage planes in individual crystals. Nearly ideal strong scaling up to at least tens of thousands of cores was demonstrated by CGPACK and by ParaFEM in isolation in prior work on Cray XE6. Cray XC30 and XC40 platforms and CrayPAT profiling were used in this work. Initially the strong scaling limit of hybrid CGPACK/ParaFEM CAFE model was 2000 cores. After replacing all-to-all communication patterns with the nearest neighbour algorithms the strong scaling limit on Cray XC30 was increased to 7000 cores. TAU profiling on non-Cray systems identified deficiencies in Intel Fortran 16 optimisation of remote coarray operations. Finally, coarray synchronisation challenges and opportunities for thread parallelisation in CA are discussed.
  • Cloud agnostic Big Data platform focusing on scalability and
    • Abstract: Publication date: Available online 27 June 2018Source: Advances in Engineering SoftwareAuthor(s): Róbert Lovas, Enikő Nagy, József Kovács Nowadays a significant part of the cloud applications processes a large amount of data to provide the desired analytics, simulation and other results. Cloud computing is becoming a widely used IT model to address the needs of many scientific and commercial Big Data applications. In this paper, we present a Hadoop platform deployment method for various cloud infrastructures with the Occopus cloud orchestrator tool. Our automated solution provides an easy-to-use, portable and scalable way to deploy the popular Hadoop platform with the main goal to avoid vendor locking issues, i.e. there is no dependency on any cloud provider prepared and offered virtual machine image or “black-box” Platform-as-a-Service mechanism. The paper presents promising performance measurements results and cost analysis.
  • Transformations of Arm-Z modular manipulator with Particle Swarm
    • Abstract: Publication date: Available online 27 June 2018Source: Advances in Engineering SoftwareAuthor(s): Machi Zawidzki, Jacek Szklarski A novel concept of hyper-redundant, snake-like manipulator is presented. It is based on the reconfigurable modular construction system–Arm-Z (AZ). AZ is comprised of linearly joined congruent modules with possibility of relative twist. AZ is an Extremely Modular System, i.e. it is composed of a single basic unit and allows for creating free-form shapes. Required level of usefulness and efficiency are among the most challenging design aspects of such reconfigurable systems. Here AZ is considered in the context of kinematics of robotic arms. In general, due to its highly non-linear nature, it is very difficult to find transitions between given states (configurations), especially under realistic environmental and structural constraints. As a way to control the manipulator, an implementation of Particle Swarm Optimization (PSO) for finding transitions between AZ states in realistic scenarios is proposed. Four practical examples are presented which are variations of two distinct problems: bending of a hexagonal AZ in a narrow slot (strong environmental constraints), and reaching a given point in 3D space by the tip of dodecagonal AZ (acting as a robotic arm). The problem of AZ transformation has been defined as a multi-objective optimization. The methodology is general with no restrictions to the objective function. Since the problem is strongly non-linear, in order to cover large space of potential solutions, the algorithm runs for a relatively large number of random initial swarms. This task was distributed on a computer cluster. Although the nature of AZ reconfiguration is discrete, the optimization algorithm is continuous.
  • Parallel implementation of hyper-dimensional dynamical particle system on
    • Abstract: Publication date: Available online 7 April 2018Source: Advances in Engineering SoftwareAuthor(s): Jan Mašek, Miroslav Vořechovský The presented paper deals with possible approaches to parallel implementation of solution of a hyper-dimensional dynamical particle system. The proposed implementation approaches are generally applicable for similar particle systems of interest in various research and engineering fields. The original motivation for the present work was a simulation of particles that represent a space-filling design to be optimized for further use in design of experiments. Due to the underlying purpose of this particle system, the dimension of the particle system of interest is considered to be entirely arbitrary. Such a hyper-dimensional space is further folded into a periodically repeated domain.The theoretical background of the proposed particle system is provided along with the derivation of equations of motion of the dynamical system. As the complexity of the system is not limited by the number of particles nor the number of dimensions, the possibilities of utilizing the GPGPU platform are more restricted in comparison with today’s fast parallel implementations of common particle systems.Two distinct approaches to parallel implementation are presented, one aiming at a generalized usage of the fast on-chip resources, the other entirely relying on the GPU’s on-board global memory. Despite unambiguous mutual differences in their performance, both parallel implementations deliver major speedup compared to the single-thread CPU solution as well as a better scaling of execution time when increasing both the number of particles and dimensions.
  • Modelling of nitrogen leaching from watersheds with large drained peat
    • Abstract: Publication date: Available online 23 March 2018Source: Advances in Engineering SoftwareAuthor(s): Anatoli Vassiljev, Katrin Kaur, Ivar Annus The SOIL and MACRO models with different versions of SOILN initially developed for small field-scales were used to simulate the water flow and nitrate N concentrations in two watersheds in Estonia that contain large areas of peat soils. Monitoring data show that nitrogen concentrations tend to increase in some rivers even where the human activity is very low. This may be connected to soil self-degradation processes taking place in drained peat soils where it is difficult to use most of the hydrological models. Results show that SOIL, MACRO and SOILN may be successfully applied at the watershed scale to model the water quantity and quality on watersheds with high content of peat soils. The analysis revealed that the nitrate nitrogen level trends depend considerably on the meteorological conditions.
  • Parallel two-stage algorithms for solving the PageRank problem
    • Abstract: Publication date: Available online 13 March 2018Source: Advances in Engineering SoftwareAuthor(s): Héctor Migallón, Violeta Migallón, José Penadés In this work we present parallel algorithms based on the use of two-stage methods for solving the PageRank problem as a linear system. Different parallel versions of these methods are explored and their convergence properties are analyzed. The parallel implementation has been developed using a mixed MPI/OpenMP model to exploit parallelism beyond a single level. In order to investigate and analyze the proposed parallel algorithms, we have used several realistic large datasets. The numerical results show that the proposed algorithms can speed up the time to converge with respect to the parallel Power algorithm and behave better than other well-known techniques.
  • CUDA accelerated implementation of parallel dynamic relaxation
    • Abstract: Publication date: Available online 8 March 2018Source: Advances in Engineering SoftwareAuthor(s): P. Iványi The dynamic relaxation method has been widely used for the design and analysis of cable-membrane structures. The method iteratively determines a static solution and it has already been parallelized with the MPI environment to speed up the analysis process. This paper discusses a new parallelization approach, which is programmed with the NVIDIA CUDA API and executed on GPU systems. Since a GPU system has a large number of cores and a separate memory from the computer therefore the original dynamic relaxation method has to be reorganized. The paper also discusses the performance measurements of the dynamic relaxation method on GPU systems.
  • Comparative studies of metamodeling and AI-Based techniques in damage
           detection of structures
    • Abstract: Publication date: Available online 6 March 2018Source: Advances in Engineering SoftwareAuthor(s): Ramin Ghiasi, Mohammad Reza Ghasemi, Mohammad Noori Despite advances in computer capacity, the enormous computational cost of running complex engineering simulations makes it impractical to rely exclusively on simulation for the purpose of structural health monitoring. To cut down the cost, surrogate models, also known as metamodels, are constructed and then used in place of the actual simulation models. In this study, structural damage detection is performed using two approaches. In both cases ten popular metamodeling techniques including Back-Propagation Neural Networks (BPNN), Least Square Support Vector Machines (LS-SVMs), Adaptive Neural-Fuzzy Inference System (ANFIS), Radial Basis Function Neural network (RBFN), Large Margin Nearest Neighbors (LMNN), Extreme Learning Machine (ELM), Gaussian Process (GP), Multivariate Adaptive Regression Spline (MARS), Random Forests and Kriging are used and the comparative results are presented. In the first approach, by considering dynamic behavior of a structure as input variables, ten metamodels are constructed, trained and tested to detect the location and severity of damage in civil structures. The variation of running time, mean square error (MSE), number of training and testing data, and other indices for measuring the accuracy in the prediction are defined and calculated in order to inspect advantages as well as the shortcomings of each algorithm. The results indicate that Kriging and LS-SVM models have better performance in predicting the location/severity of damage compared with other methods. In the second approach, after locating precisely the eventual damage of a structure using modal strain energy based index (MSEBI), to efficiently reduce the computational cost of model updating during the optimization process of damage severity detection, the MSEBI of structural elements is evaluated using a properly trained surrogate model. The results indicate that after determining the damage location, the proposed solution method for damage severity detection leads to significant reduction of computational time compared to finite element method. Furthermore, engaging colliding bodies optimization algorithm (CBO) by efficient surrogate model of finite element (FE) model, maintains the acceptable accuracy of damage severity detection.
  • Static load estimation using artificial neural network: Application on a
           wing rib
    • Abstract: Publication date: Available online 7 February 2018Source: Advances in Engineering SoftwareAuthor(s): Samson B. Cooper, Dario DiMaio This paper presents a novel approach to predicting the static load on a large wing rib in the absence of load cells. A Finite Element model of the wing rib was designed and calibrated using measured data obtained from static experimental test. An Artificial Neural Network (ANN) model was developed to predict the static load applied on the wing rib, this was achieved by using random data and strain values obtained from the static test as input parameters. A number of two layer feed-forward networks were designed and trained in MATLAB using the back-propagation algorithm. The first set of Neural Networks (NN) were trained using random data as inputs, measured strain values were introduced as input into the already trained neural network to access the training algorithm and quantify the accuracy of the static load prediction produced by the trained NN. In addition, a procedure that combines ANN and FE modelling to create a hybrid inverse problem analysis and load monitoring tool is presented. The hybrid approach is based on using trained NN to estimate the applied load from a known FE structural response. Results obtained from this research proves that using an ANN to identify loads is feasible and a well-trained NN shows fast convergence and high degree of accuracy of 92% in the load identification process. Finally, additional trained network results showed that ANN as an inverse problem solver can be used to estimate the load applied on a structure once the load-response relationship has been identified.
  • A new nodal outflow function for head-dependent modelling of water
           distribution networks
    • Abstract: Publication date: Available online 19 January 2007Source: Advances in Engineering SoftwareAuthor(s): T.T. Tanyimboh, A.B. TemplemanThis article has been removed consistent with Elsevier Policy on Article Withdrawal. The Publisher apologises for any inconvenience this may cause.
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