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Identification of Optimal Topologies for Continuum Structures Using Metaheuristics: A Comparative Study Arch. Computat. Methods Eng. (IF 6.73) Pub Date : 2021-01-23 Pooya Rostami, Javad Marzbanrad
The development of low dimensional explicit based topology optimization approaches such as moving morphable components method increased the hopes to develop and expand evolutionary based solutions in the topology optimization of continuum structures. Despite the low dimensionality of the parametrization which helps to increase the efficiency, due to the multimodal behavior of the objective function
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Integration of BIM and GIS for Construction Automation, a Systematic Literature Review (SLR) Combining Bibliometric and Qualitative Analysis Arch. Computat. Methods Eng. (IF 6.73) Pub Date : 2021-01-22 Sina Karimi, Ivanka Iordanova
For several decades now, the construction industry is suffering from low productivity, especially in comparison to manufacturing industries which have succeeded to benefit from digitalization of their processes. Furthermore, scarceness of qualified workforce is expected in the near future. Construction automation is introduced as a solution to these challenges. The capabilities of construction robots
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A Comparison of Constraint Handling Techniques on NSGA-II Arch. Computat. Methods Eng. (IF 6.73) Pub Date : 2021-01-21 Jared G. Hobbie, Amir H. Gandomi, Iman Rahimi
Almost all real-world and engineering problems involve multi-objective optimization of some sort that is often constrained. To solve these constrained multi-objective optimization problems, constrained multi-objective optimization evolutionary algorithms (CMOEAs) are enlisted. These CMOEAs require specific constraint handling techniques. This study aims to address and test the most successful constraint
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A Comparative Study of Recent Multi-objective Metaheuristics for Solving Constrained Truss Optimisation Problems Arch. Computat. Methods Eng. (IF 6.73) Pub Date : 2021-01-16 Natee Panagant, Nantiwat Pholdee, Sujin Bureerat, Ali Riza Yildiz, Seyedali Mirjalili
Multi-objective truss optimisation is a research topic that has been less investigated in the literature compared to the single-objective cases. This paper investigates the comparative performance of fourteen new and established multi-objective metaheuristics when solving truss optimisation problems. The optimisers include multi-objective ant lion optimiser, multi-objective dragonfly algorithm, multi-objective
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Time Integration Algorithms for Elasto-Viscoplastic Models with Multiple Hardening Laws for Geomaterials: Enhancement and Comparative Study Arch. Computat. Methods Eng. (IF 6.73) Pub Date : 2021-01-15 Jian Li, Zhen-Yu Yin
To describe the behaviours of geomaterials such as time-dependency, anisotropy and destructuration, multiple hardening parameters and laws are generally needed for application in advanced elasto-viscoplastic models. Time integration with stress updating is a key step in the application of elasto-viscoplastic models to engineering practice. However, the robustness of time integration algorithms for
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An Abridged Review of Empirical Formulae for Computation of Penetration, Scabbing and Perforation Depth Under Projectile Impact Arch. Computat. Methods Eng. (IF 6.73) Pub Date : 2021-01-13 M. D. Goel, Krishna Prasad Kallada, I. L. Muthreja
Computation of penetration, scabbing and perforation depth under projectile impact is a highly non-linear and complex phenomenon. There exist various formulae, mainly empirical in nature, to estimate these depths under a given scenario. However, there exist a large difference between these depths computed using available empirical formulae and those observed during actual tests. In the present study
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Soft Computing Methods for Attaining the Protective Device Coordination Including Renewable Energies: Review and Prospective Arch. Computat. Methods Eng. (IF 6.73) Pub Date : 2021-01-12 Abdelmonem Draz, Mahmoud M. Elkholy, Attia A. El-Fergany
The optimized coordination of directional over current relays (DOCRs) in power systems is still a challenging task. This optimization problem has been augmented in the literature through coping with various methodologies and the progress is not over yet. Thanks to the advance in technology, this task is mitigated in terms of time consuming and computational errors via applying different metaheuristic
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Optimization of Load-Carrying Hierarchical Stiffened Shells: Comparative Survey and Applications of Six Hybrid Heuristic Models Arch. Computat. Methods Eng. (IF 6.73) Pub Date : 2021-01-11 Shun-Peng Zhu, Behrooz Keshtegar, Kuo Tian, Nguyen-Thoi Trung
The accurate result of heuristic models combined by social inspired optimization methods is interesting issue for optimizations of hierarchical stiffened shells (HSS). In this paper, six heuristic combined by social-inspired optimization is compared for both ability and accuracy in optimization of load-carrying capacities of HSS. A three level optimization method is employed as (1) explicit dynamic
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Optimizing Neural Networks for Efficient FPGA Implementation: A Survey Arch. Computat. Methods Eng. (IF 6.73) Pub Date : 2021-01-11 Riadh Ayachi, Yahia Said, Abdessalem Ben Abdelali
The deep learning has become the key for artificial intelligence applications development. It was successfully used to solve computer vision tasks. But the deep learning algorithms are based on Deep Neural Networks (DNN) with many hidden layers which need a huge computation effort and a big storage space. Thus, the general-purpose graphical processing units (GPGPU) are the best candidate for DNN development
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Mean-CVaR Portfolio Optimization Approaches with Variable Cardinality Constraint and Rebalancing Process Arch. Computat. Methods Eng. (IF 6.73) Pub Date : 2021-01-11 Fernando G. D. C. Ferreira, Rodrigo T. N. Cardoso
This work compares Mean-CVaR portfolio optimization models with variable cardinality constraint and rebalancing process. It considers integer and continuous decision variables, the number of asset lots and asset investment rate, respectively, and the linear and non-linear formulations of CVaR. Exact methods are used to solve the linear models and parallel evolutionary algorithms are used to solve the
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Using Machine Learning to Predict the Sentiment of Online Reviews: A New Framework for Comparative Analysis Arch. Computat. Methods Eng. (IF 6.73) Pub Date : 2021-01-08 Gregorius Satia Budhi, Raymond Chiong, Ilung Pranata, Zhongyi Hu
Online reviews are becoming increasingly important for decision-making. Consumers often refer to online reviews for opinions before making a purchase. Marketers also acknowledge the importance of online reviews and use them to improve product success. However, the massive amount of online review data, as well as its unstructured nature, is a challenge for anyone wanting to derive a conclusion quickly
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Selection of Renewable Energy Alternatives for Green Blockchain Investments: A Hybrid IT2-based Fuzzy Modelling Arch. Computat. Methods Eng. (IF 6.73) Pub Date : 2021-01-07 Juan Liu, Jun Lv, Hasan Dinçer, Serhat Yüksel, Hüsne Karakuş
In this study, it is aimed to determine the most suitable renewable energy alternatives that can be used in blockchain investments. In this context, firstly, a wide literature review is made and 6 different criteria that could have an impact on this decision are determined. The analysis process of the consists of two different stages. Firstly, the significance levels of these criteria are calculated
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State-of-the-Art Review of Machine Learning Applications in Constitutive Modeling of Soils Arch. Computat. Methods Eng. (IF 6.73) Pub Date : 2021-01-05 Pin Zhang, Zhen-Yu Yin, Yin-Fu Jin
Machine learning (ML) may provide a new methodology to directly learn from raw data to develop constitutive models for soils by using pure mathematic skills. It has presented success and versatility in cases of simple stress paths due to its strong non-linear mapping capacity without limitations of constitutive formulations. However, current studies on the ML-based constitutive modeling of soils is
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Particle Swarm Optimization Variants for Solving Geotechnical Problems: Review and Comparative Analysis Arch. Computat. Methods Eng. (IF 6.73) Pub Date : 2020-11-23 Ali R. Kashani, Raymond Chiong, Seyedali Mirjalili, Amir H. Gandomi
Optimization techniques have drawn much attention for solving geotechnical engineering problems in recent years. Particle swarm optimization (PSO) is one of the most widely used population-based optimizers with a wide range of applications. In this paper, we first provide a detailed review of applications of PSO on different geotechnical problems. Then, we present a comprehensive computational study
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Hybridisable Discontinuous Galerkin Formulation of Compressible Flows Arch. Computat. Methods Eng. (IF 6.73) Pub Date : 2020-11-21 Jordi Vila-Pérez, Matteo Giacomini, Ruben Sevilla, Antonio Huerta
This work presents a review of high-order hybridisable discontinuous Galerkin (HDG) methods in the context of compressible flows. Moreover, an original unified framework for the derivation of Riemann solvers in hybridised formulations is proposed. This framework includes, for the first time in an HDG context, the HLL and HLLEM Riemann solvers as well as the traditional Lax–Friedrichs and Roe solvers
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A Study on the LATIN-PGD Method: Analysis of Some Variants in the Light of the Latest Developments Arch. Computat. Methods Eng. (IF 6.73) Pub Date : 2020-11-16 R. Scanff, S. Nachar, P. -A. Boucard, D. Néron
The LATIN-PGD method is a powerful alternative to the Newton–Raphson scheme for solving non-linear time-dependent problems in combination with reduced-order modeling methods. Many developments have been carried out over the last few decades and have led to some variants of the LATIN-PGD method. However, only few comparisons have been made between these variants and none using the digital resources
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Application of Soft Computing Models for Simulating Nitrate Contamination in Groundwater: Comprehensive Review, Assessment and Future Opportunities Arch. Computat. Methods Eng. (IF 6.73) Pub Date : 2020-11-02 Masoud Haghbin, Ahmad Sharafati, Barnali Dixon, Vinod Kumar
Groundwater is one of the major resources to supply the agriculture and urban water demand. Vulnerability of groundwater resources due to chemical substances is a crucial concern for groundwater quality management. The different nitrogen compounds, especially nitrate, plays an important role in groundwater quality. In last two decades, the efficient approaches called soft computing (SC) models were
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Measurement and Mitigation of Residual Stress in Wire-Arc Additive Manufacturing: A Review of Macro-Scale Continuum Modelling Approach Arch. Computat. Methods Eng. (IF 6.73) Pub Date : 2020-10-30 Shekhar Srivastava, Rajiv Kumar Garg, Vishal S. Sharma, Anish Sachdeva
Wire-arc additive manufacturing (WAAM) has recently attracted researchers to produce metal components with a high-deposition rate. Many researchers are trying to establish the WAAM process as a high-deposition metal additive manufacturing (AM) process. A computationally efficient mathematical model used for the metal-AM process yields a framework for component qualification as per international standards
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Domain-Specific Language Techniques for Visual Computing: A Comprehensive Study Arch. Computat. Methods Eng. (IF 6.73) Pub Date : 2020-10-27 Liming Shen, Xueyi Chen, Richen Liu, Hailong Wang, Genlin Ji
As a part of domain-specific development, Domain-Specific Language (DSL) is widely used in both the academia and industry to solve different aspects of the problems in engineering. A DSL is a customized language whose expressiveness is tailored to a well-defined application domain, so as to offer an effective interface for the domain experts. To mitigate the programming complexity of the General-Purpose
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A Comprehensive Study of Reversible Data Hiding (RDH) Schemes Based on Pixel Value Ordering (PVO) Arch. Computat. Methods Eng. (IF 6.73) Pub Date : 2020-10-25 Gurjinder Kaur, Samayveer Singh, Rajneesh Rani, Rajeev Kumar
Reversible data hiding (RDH) plays a significant role in the field of information security which allows safe transmission of secret data inside a cover media. Additionally, RDH allows extraction of secret data and lossless recovery of the cover media at the decoding end which makes it applicable for the applications like medical imaging and military services. In recent years, variety of RDH techniques
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Correction to: Qualitative and Quantitative Performance Comparison of Recent Optimization Algorithms for Economic Optimization of the Heat Exchangers Arch. Computat. Methods Eng. (IF 6.73) Pub Date : 2020-10-23 Vivek K. Patel, Bansi D. Raja, Vimal J. Savsani, Ali Rıza Yıldız
The original online version of this article was revised to exclude the Ethics Disclosure. There is no conflict of interest in the sense referred to in academic publishing. The authors regret causing confusion and possible damage due to this unfortunate misunderstanding.
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The Role of Machine Learning Algorithms in Materials Science: A State of Art Review on Industry 4.0 Arch. Computat. Methods Eng. (IF 6.73) Pub Date : 2020-10-22 Amitava Choudhury
The 21st century has witnessed a rapid convergence of manufacturing technology, computer science and information technology. This has led to a paradigm of 4.0. The hitherto known developments in metallurgical and materials practices are largely driven by application of fundamental knowledge through experiments and experiences. However, the mounting demands of high performance products and environmental
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HDGlab : An Open-Source Implementation of the Hybridisable Discontinuous Galerkin Method in MATLAB Arch. Computat. Methods Eng. (IF 6.73) Pub Date : 2020-10-22 Matteo Giacomini, Ruben Sevilla, Antonio Huerta
This paper presents HDGlab, an open source MATLAB implementation of the hybridisable discontinuous Galerkin (HDG) method. The main goal is to provide a detailed description of both the HDG method for elliptic problems and its implementation available in HDGlab. Ultimately, this is expected to make this relatively new advanced discretisation method more accessible to the computational engineering community
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A Review on Machine Learning and Deep Learning Perspectives of IDS for IoT: Recent Updates, Security Issues, and Challenges Arch. Computat. Methods Eng. (IF 6.73) Pub Date : 2020-10-20 Ankit Thakkar, Ritika Lohiya
Internet of Things (IoT) is widely accepted technology in both industrial as well as academic field. The objective of IoT is to combine the physical environment with the cyber world and create one big intelligent network. This technology has been applied to various application domains such as developing smart home, smart cities, healthcare applications, wireless sensor networks, cloud environment,
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Computer Vision Techniques in Construction: A Critical Review Arch. Computat. Methods Eng. (IF 6.73) Pub Date : 2020-10-19 Shuyuan Xu, Jun Wang, Wenchi Shou, Tuan Ngo, Abdul-Manan Sadick, Xiangyu Wang
Computer vision has been gaining interest in a wide range of research areas in recent years, from medical to industrial robotics. The architecture, engineering and construction and facility management sector ranks as one of the most intensive fields where vision-based systems/methods are used to facilitate decision making processes during the construction phase. Construction sites make efficient monitoring
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Finite Element Modeling of Soil Structure Interaction System with Interface: A Review Arch. Computat. Methods Eng. (IF 6.73) Pub Date : 2020-10-15 Gaurav D. Dhadse, G. D. Ramtekkar, Govardhan Bhatt
Non-linear analysis of soil structure interaction problem is still an active field of research due to development of useful interface element between the soil–soil and soil–structure. In this paper a focused review on coupled finite element modeling of soil structure interaction (SSI) system with soil non-linearity and interface element modeling is discussed. The non-linearity in soil is reviewed with
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Finite Elements Using Neural Networks and a Posteriori Error Arch. Computat. Methods Eng. (IF 6.73) Pub Date : 2020-10-15 Atsuya Oishi, Genki Yagawa
As the finite element method requires many nodes or elements to obtain accurate results, the adaptive finite element method has been developed to obtain better results with fewer nodes, where error information is used to refine the initial mesh adaptively. In contrast to this, we propose in this paper two new methods to directly derive accurate results by artificial neural networks using information
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Artificial Intelligence in Materials Modeling and Design Arch. Computat. Methods Eng. (IF 6.73) Pub Date : 2020-10-11 J. S. Huang, J. X. Liew, A. S. Ademiloye, K. M. Liew
In recent decades, the use of artificial intelligence (AI) techniques in the field of materials modeling has received significant attention owing to their excellent ability to analyze a vast amount of data and reveal correlations between several complex interrelated phenomena. In this review paper, we summarize recent advances in the applications of AI techniques for numerical modeling of different
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Numerical Modeling and Lattice Method for Characterizing Hydraulic Fracture Propagation: A Review of the Numerical, Experimental, and Field Studies Arch. Computat. Methods Eng. (IF 6.73) Pub Date : 2020-10-08 Elham Bakhshi, Naser Golsanami, Lianjun Chen
In continuous formations, the rock properties and the state of in situ stresses control the propagation direction of an induced hydraulic fracture (HF) and its geometry. The present study succinctly reviews more than a hundred scientific papers that have deeply explored hydraulic fracture propagation from the rock mechanical perspective and summarizes the current state of knowledge on the propagation
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Recent Trends in Prediction of Concrete Elements Behavior Using Soft Computing (2010–2020) Arch. Computat. Methods Eng. (IF 6.73) Pub Date : 2020-10-07 Masoomeh Mirrashid, Hosein Naderpour
Soft computing (SC), due to its high abilities to solve the complex problems with uncertainty and multiple parameters, has been widely investigated and used, especially in structural engineering. They have successfully estimated the capacity of structural reinforced concrete (RC) members and determined the properties of concrete. There are so many articles in literature that applied SC methods for
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A Systematic Review on Firefly Algorithm: Past, Present, and Future Arch. Computat. Methods Eng. (IF 6.73) Pub Date : 2020-09-29 Vijay Kumar, Dinesh Kumar
Firefly Algorithm (FA) is one of the popular algorithm of Swarm Intelligence domain that can be used in most of the areas of optimization. FA and its variants are simple to implement and easily understood. These can be used to successfully solve the problems of different areas. Modification in original FA or hybrid FA algorithms are required to solve diverse range of engineering problems. In this paper
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Specific Soft Computing Strategies for Evaluating the Performance and Emissions of an SI Engine Using Alcohol-Gasoline Blended Fuels—A Comprehensive Analysis Arch. Computat. Methods Eng. (IF 6.73) Pub Date : 2020-09-28 Amit Kumar Thakur, Ajay Kumar Kaviti, Rajesh Singh, Anita Gehlot
The huge fossil fuel consumption has created an unprecedented situation and, with the accompanying rise in car numbers, pollution levels have been well beyond human control. This is alarming enough to note that the level of pollution has surpassed all levels and the need for the hour is to find an alternative fuel that can really be of great help in reducing exhaust emissions and that efficiency. Experiments
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A Systematic Review of the Techniques for the Automatic Segmentation of Organs-at-Risk in Thoracic Computed Tomography Images Arch. Computat. Methods Eng. (IF 6.73) Pub Date : 2020-09-23 Malvika Ashok, Abhishek Gupta
The standard treatment for the cancer is the radiotherapy where the organs nearby the target volumes get affected during treatment called the Organs-at-risk. Segmentation of Organs-at-risk is crucial but important for the proper planning of radiotherapy treatment. Manual segmentation is time consuming and tedious in regular practices and results may vary from experts to experts. The automatic segmentation
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A Selection of Benchmark Problems in Solid Mechanics and Applied Mathematics Arch. Computat. Methods Eng. (IF 6.73) Pub Date : 2020-09-18 Jörg Schröder, Thomas Wick, Stefanie Reese, Peter Wriggers, Ralf Müller, Stefan Kollmannsberger, Markus Kästner, Alexander Schwarz, Maximilian Igelbüscher, Nils Viebahn, Hamid Reza Bayat, Stephan Wulfinghoff, Katrin Mang, Ernst Rank, Tino Bog, Davide D’Angella, Mohamed Elhaddad, Paul Hennig, Alexander Düster, Wadhah Garhuom, Simeon Hubrich, Mirjam Walloth, Winnifried Wollner, Charlotte Kuhn, Timo Heister
In this contribution we provide benchmark problems in the field of computational solid mechanics. In detail, we address classical fields as elasticity, incompressibility, material interfaces, thin structures and plasticity at finite deformations. For this we describe explicit setups of the benchmarks and introduce the numerical schemes. For the computations the various participating groups use different
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Toward Smart Logistics: Engineering Insights and Emerging Trends Arch. Computat. Methods Eng. (IF 6.73) Pub Date : 2020-09-18 Yassine Issaoui, Azeddine Khiat, Ayoub Bahnasse, Hassan Ouajji
Each day, companies and organizations are facing new challenges. The customer requirements are increasing and global competition is leading to important changes in the industrial world. Against this background, the fourth industrial revolution aims to deal with these challenges. Besides the lack of comparable studies covering the new concepts in logistics, this study intends to study, and clarify diverse
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A Brief Review on Multi-objective Software Refactoring and a New Method for Its Recommendation Arch. Computat. Methods Eng. (IF 6.73) Pub Date : 2020-09-17 Satnam Kaur, Lalit K. Awasthi, A. L. Sangal
Software refactoring is a commonly accepted means of improving the software quality without affecting its observable behaviour. It has gained significant attention from both academia and software industry. Therefore, numerous approaches have been proposed to automate refactoring that consider software quality maximization as their prime objective. However, this objective is not enough to generate good
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Nighttime Image-Dehazing: A Review and Quantitative Benchmarking Arch. Computat. Methods Eng. (IF 6.73) Pub Date : 2020-09-16 Sriparna Banerjee, Sheli Sinha Chaudhuri
Visibility enhancement of images captured during hazy weather conditions is highly essential for various important applications like intelligent vehicles, surveillance, remote sensing, etc. In recent years, researchers proposed numerous image-dehazing methods mostly focusing on daytime images’ characteristics. In this work, we have highlighted the dissimilarities among the characteristics of daytime
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Latest Advancements in Heat Transfer Enhancement in the Micro-channel Heat Sinks: A Review Arch. Computat. Methods Eng. (IF 6.73) Pub Date : 2020-09-16 K. Naga Ramesh, T. Karthikeya Sharma, G. Amba Prasad Rao
Miniaturization of the energy systems and high powered electronic devices necessitates the high capacity compact heat exchangers to dissipate the heat generated. Microchannel heatsinks (MCHS) are modern heat exchangers with the fluid flowing channels of size in microscale. These are very compact heat exchangers with higher ratios of heat transfer area to the volume. Huge research work has been going
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Data Digitalisation in the Open-Pit Mining Industry: A Scoping Review Arch. Computat. Methods Eng. (IF 6.73) Pub Date : 2020-09-15 J. Duarte, M. Fernanda Rodrigues, J. Santos Baptista
Mining 4.0 has risen from the need of the extractive industry to answer the technical challenges that rapidly shift at the mining sites. Currently, many models can be developed to address this issue however, the way in which the digitalisation of information occurs is not entirely clear. Therefore, this scoping review aims to address the main digitalisation tools and processes used in the open-pit
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Performance Assessment of Concrete and Steel Material Models in LS-DYNA for Enhanced Numerical Simulation, A State of the Art Review Arch. Computat. Methods Eng. (IF 6.73) Pub Date : 2020-09-15 Masoud Abedini, Chunwei Zhang
One of the biggest challenges associated with modelling the behaviour of reinforced concrete is the difficulty of incorporating realistic material models that can represent the observable behaviour of the physical system. Experiments for relevant loading rates and pressures reveal that steel and concrete exhibits a complicated nonlinear behavior that is difficult to capture in a single constitutive
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Prediction of the Thermo-Mechanical Properties of the SiC f /SiC RVE Model via FEM and Asymptotic Homogenization Method: Process and Implementation Details Arch. Computat. Methods Eng. (IF 6.73) Pub Date : 2020-09-11 Xiuli Shen, Shuo Zhang, Xin Liu, Longdong Gong, Shaojing Dong
The study focuses on characterizing the thermo-mechanical properties of SiCf/SiC using micromechanics finite element method (FEM) and multi-scale thermal–mechanical coupling asymptotic homogenization methods. A multi-scale model of fiber, fiber bundle and 2D woven SiCf/SiC has been established, while the predicted properties of the model are verified with the relevant experiments. The detailed steps
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Derivation of General Acceleration and Hessian Matrix of Kinematic Limbs in Parallel Manipulator by Extended Skew-Symmetric Matrixes Arch. Computat. Methods Eng. (IF 6.73) Pub Date : 2020-09-09 Yi Lu, Nijia Ye, Zefeng Chang
A general acceleration model and a Hessian matrix of the kinematic limbs in the parallel manipulators are established using new skew-symmetric matrixes. First, several extended formulas of the skew-symmetric matrixes are derived and proved. Second, the differentiations of the sub-Jacobian matrixes of the general kinematic limbs are transformed into the multiplication of the general velocity transposition
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A New Lighting on Analytical Discrete Sensitivities in the Context of IsoGeometric Shape Optimization Arch. Computat. Methods Eng. (IF 6.73) Pub Date : 2020-09-07 T. Hirschler, R. Bouclier, A. Duval, T. Elguedj, J. Morlier
Isogeometric shape optimization has been now studied for over a decade. This contribution aims at compiling the key ingredients within this promising framework, with a particular attention to sensitivity analysis. Based on all the researches related to isogeometric shape optimization, we present a global overview of the process which has emerged. The principal feature is the use of two refinement levels
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Vehicular Ad Hoc Network (VANET) Localization Techniques: A Survey Arch. Computat. Methods Eng. (IF 6.73) Pub Date : 2020-09-07 Faruk Baturalp Günay, Ercüment Öztürk, Tuğrul Çavdar, Y. Sinan Hanay, Atta ur Rehman Khan
Localization has become an important area of research with the development of wireless communication technologies. Of particular prominence within this area is Vehicular Ad Hoc Networks (VANET), which plays an important role in many applications such as vehicle tracking, accident prevention, and efficient transportation. GPS technology, which can easily be integrated into vehicles has been instrumental
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Computer Vision Models in Intelligent Aquaculture with Emphasis on Fish Detection and Behavior Analysis: A Review Arch. Computat. Methods Eng. (IF 6.73) Pub Date : 2020-09-05 Ling Yang, Yeqi Liu, Huihui Yu, Xiaomin Fang, Lihua Song, Daoliang Li, Yingyi Chen
Intelligence technologies play an important role in increasing product quality and production efficiency in digital aquaculture. Automatic fish detection will contribute to achieving intelligent production and scientific management in precision farming. Due to the availability and ubiquity of modern information technology, such as the internet of things, big data, and camera devices, computer vision
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A Review on Membrane Finite Elements with Drilling Degree of Freedom Arch. Computat. Methods Eng. (IF 6.73) Pub Date : 2020-09-04 Djamel Boutagouga
Membrane finite elements have gained increasing importance since the early years of the finite elements method due to their convenience to a wide range of plane and 3D shell problems. Many research works have been focussing on membrane elements with drilling rotation. These elements are plane stress finite elements with a rotational in-plane degree of freedom. The main motivation for introducing the
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A Review on the Effectiveness of Machine Learning and Deep Learning Algorithms for Cyber Security Arch. Computat. Methods Eng. (IF 6.73) Pub Date : 2020-09-02 R. Geetha, T. Thilagam
In recent years there exists a wide variety of cyber attacks with the drastic development of the internet technology. Detection of these attacks is of more significant in today’s cyber world scenario. Machine learning (ML) and deep learning (DL) methods have been preferred by researchers across different disciplines for providing solutions to their problems. In this paper we have presented a detailed
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Nature Inspired Techniques and Applications in Intrusion Detection Systems: Recent Progress and Updated Perspective Arch. Computat. Methods Eng. (IF 6.73) Pub Date : 2020-08-31 Kutub Thakur, Gulshan Kumar
Nowadays, it has become a necessity for operational and reliable operation of networks due to our increased dependency over the network services. However, intruders are continuously attempting to break into the networks and disturbing the network services using a variety of attack vectors and technologies. This motivates us to develop the techniques that ensure operational and reliable network, even
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A Review Approach for Sound Propagation Prediction of Plate Constructions Arch. Computat. Methods Eng. (IF 6.73) Pub Date : 2020-08-30 M. R. Zarastvand, M. Ghassabi, R. Talebitooti
In this contribution, a review study is established in order to gather, classify and organize all of the previous researches on the sound insulation characteristics of plate structures with span a period from 1967 to nowadays. Accordingly, more than 200 articles in the area of acoustic performance of these structures are rolled up and reviewed. To achieve this end, in the first step, all of the existence
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A Brief Review on the Application of Sound in Pavement Monitoring and Comparison of Tire/Road Noise Processing Methods for Pavement Macrotexture Assessment Arch. Computat. Methods Eng. (IF 6.73) Pub Date : 2020-08-29 Mohammad Reza Ganji, Ali Ghelmani, Amir Golroo, Hamid Sheikhzadeh
Data acquisition and data processing are at the core of pavement management systems. Nowadays, traditional methods of data collection are rarely used in developed countries due to the considerable disadvantages of the traditional methods compared to the automated ones, such as the slow pace of data collection, endangering the safety of the human operators collecting the data, considerable cost, collecting
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Stochastic Oblique Impact on Composite Laminates: A Concise Review and Characterization of the Essence of Hybrid Machine Learning Algorithms Arch. Computat. Methods Eng. (IF 6.73) Pub Date : 2020-08-27 T. Mukhopadhyay, S. Naskar, S. Chakraborty, P. K. Karsh, R. Choudhury, S. Dey
Due to the absence of adequate control at different stages of complex manufacturing process, material and geometric properties of composite structures are often uncertain. For a secure and safe design, tracking the impact of these uncertainties on the structural responses is of utmost significance. Composite materials, commonly adopted in various modern aerospace, marine, automobile and civil structures
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Qualitative and Quantitative Performance Comparison of Recent Optimization Algorithms for Economic Optimization of the Heat Exchangers Arch. Computat. Methods Eng. (IF 6.73) Pub Date : 2020-08-26 Vivek Patel, Bansi Raja, Vimal Savsani, Ali Rıza Yildiz
Solving applied problem of economic optimization is considered as a real test for the optimization algorithms. The present work explores the qualitative and quantitative comparative analysis of nine recently developed optimization algorithms for the economic optimization of the heat exchangers. Passing vehicle search, Salp swarm algorithm, Artificial flora optimization, Grey wolf optimizer, Electro-search
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Review of Level Set in Image Segmentation Arch. Computat. Methods Eng. (IF 6.73) Pub Date : 2020-08-25 Zhaobin Wang, Baozhen Ma, Ying Zhu
Level set is one of active contour models, which is good at handling complex topologies and capturing boundary. The level set methods are specially used in image with intensity inhomogeneity, such as medical image, SAR image, etc. There are many methods based on level set, which are classified into region-based and edge-based. This article firstly derives the function of curve evolution and original
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A Review on Fault Diagnosis and Condition Monitoring of Gearboxes by Using AE Technique Arch. Computat. Methods Eng. (IF 6.73) Pub Date : 2020-08-24 Mahendra Singh Raghav, Ram Bihari Sharma
Gearboxes have a significant role in the operation of rotating machinery. Several techniques exist for the diagnosis of fault in gearboxes. This work presents the techniques for the condition monitoring and fault diagnosis of the gearboxes based on Acoustic Emission (AE). The review describes the application of AE to detect the various types of fault in the gearboxes for different types of gear, the
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State-of-the-Art and Comparative Review of Adaptive Sampling Methods for Kriging Arch. Computat. Methods Eng. (IF 6.73) Pub Date : 2020-08-18 Jan N. Fuhg, Amélie Fau, Udo Nackenhorst
Metamodels aim to approximate characteristics of functions or systems from the knowledge extracted on only a finite number of samples. In recent years kriging has emerged as a widely applied metamodeling technique for resource-intensive computational experiments. However its prediction quality is highly dependent on the size and distribution of the given training points. Hence, in order to build proficient
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On the Numerical Modelization of Moving Load Beam Problems by a Dedicated Parallel Computing FEM Implementation Arch. Computat. Methods Eng. (IF 6.73) Pub Date : 2020-08-18 Diego Froio, Luca Verzeroli, Rosalba Ferrari, Egidio Rizzi
The present work outlines an original numerical modelization approach for Moving Load (ML) beam problems, by a dedicated object-oriented C++ parallel computing FEM implementation, with the purposes of performing efficient numerical analyses resolving the complete dynamic response of beams under the effect of a high-velocity ML. Alongside, main framing state-of-the-art reviews are attempted, on the
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A Survey of Nash Equilibrium Strategy Solving Based on CFR Arch. Computat. Methods Eng. (IF 6.73) Pub Date : 2020-08-17 Huale Li, Xuan Wang, Fengwei Jia, Yifan Li, Qian Chen
Recently, with the rapid development of artificial intelligence technology, there are growing researchers drawing their attention on the field of computer game. In two-player zero-sum extensive games with imperfect information, counterfactual regret (CFR) method is one of the most popular method to solve Nash equilibrium strategy. Therefore, we have carried on a wide range of research and analysis
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State-of-the-Art of Research on Optimization of Shell and Tube Heat Exchangers by Methods of Evolutionary Computation Arch. Computat. Methods Eng. (IF 6.73) Pub Date : 2020-08-17 Wagner Henrique Saldanha, Felipe Raul Ponce Arrieta, Gustavo Luís Soares
This paper presents a comprehensive state-of-the-art review of optimization by evolutionary computation methods of shell and tubes heat exchangers (STHE) of single segmental baffles. It is seen that the heat transfer coefficient to the shell side is calculated by the Kern method or by the Bell Delaware method, and that the pressure drop to the shell side is calculated by the Kern method or by the Bell
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Tackling Flow Stress of Zirconium Alloys Arch. Computat. Methods Eng. (IF 6.73) Pub Date : 2020-08-13 Arpan Das
Flow stress during hot deformation is essentially controlled by the chemistry of material, initial microstructure/texture, strain, strain rate, strain path, stress triaxility and the temperature of deformation. A comprehensive literature survey has been performed to realize this fact completely. In the present research, a neural network model under Bayesian framework has been created to correlate the
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Breast Cancer Detection, Segmentation and Classification on Histopathology Images Analysis: A Systematic Review Arch. Computat. Methods Eng. (IF 6.73) Pub Date : 2020-08-10 R. Krithiga, P. Geetha
Digital pathology represents a major evolution in modern medicine. Pathological examinations constitute the standard in medical protocols and the law, and call for specific action in the diagnostic process. Advances in digital pathology have made it possible for image analysis to take advantage of the information analysis from hematoxylin and eosin stained images. In spite of concern, it is recorded