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Computation, Volume 9, Issue 6 (June 2021) – 13 articles

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Article
Density Functional Theory of Highly Excited States of Coulomb Systems
Computation 2021, 9(6), 73; https://0-doi-org.brum.beds.ac.uk/10.3390/computation9060073 - 21 Jun 2021
Cited by 1 | Viewed by 548
Abstract
The density functional theory proposed earlier for excited states of Coulomb systems is discussed. The localized Hartree–Fock (LHF) and the Krieger, Li, and Iafrate (KLI) methods combined with correlation are generalized for excited states. Illustrative examples include some highly excited states of Li [...] Read more.
The density functional theory proposed earlier for excited states of Coulomb systems is discussed. The localized Hartree–Fock (LHF) and the Krieger, Li, and Iafrate (KLI) methods combined with correlation are generalized for excited states. Illustrative examples include some highly excited states of Li and Na atoms. Full article
(This article belongs to the Special Issue Electronic Correlation)
Article
District-Heating-Grid Simulation in Python: DiGriPy
Computation 2021, 9(6), 72; https://0-doi-org.brum.beds.ac.uk/10.3390/computation9060072 - 16 Jun 2021
Viewed by 542
Abstract
DiGriPy is a newly developed Python tool for the simulation of district heating networks published as open-source software in GitHub and offered as a Python package on PyPI. It enables the user to easily build a network model, run large-scale demand time series, [...] Read more.
DiGriPy is a newly developed Python tool for the simulation of district heating networks published as open-source software in GitHub and offered as a Python package on PyPI. It enables the user to easily build a network model, run large-scale demand time series, and automatically compare different temperature-control conditions. In this paper, implementation details and usage instructions are given. Tests showing the results of different scenarios are presented and interpreted. Full article
(This article belongs to the Section Computational Engineering)
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Article
Analysing the Influential Parameters on the Monopile Foundation of an Offshore Wind Turbine
Computation 2021, 9(6), 71; https://0-doi-org.brum.beds.ac.uk/10.3390/computation9060071 - 12 Jun 2021
Viewed by 783
Abstract
Countries around the world generate electricity from renewable resources to decarbonise their societies and reduce global warming. Some countries have already outlined their wishes to produce a part of their total energy consumption from renewable sources in the coming years and gradually reduce [...] Read more.
Countries around the world generate electricity from renewable resources to decarbonise their societies and reduce global warming. Some countries have already outlined their wishes to produce a part of their total energy consumption from renewable sources in the coming years and gradually reduce the use of nuclear energy and fossil fuel in favour of cleaner fuels. While renewable energies are significant factors in tackling climate change, the parameters that can influence their performance should be analysed in detail during the design process. One of these parameters is the foundation of an offshore wind turbine. Offshore wind turbines allow more energy to be produced than an onshore installation, and do not have any harmful effects on human beings, while their geotechnical aspects need to be clearly determined in advance. In this study, the influential parameters such as soil type, the number of bolts in the design, and the size of the structure were analysed using the finite element method for three different designs. The simulations showed that some soil properties, such as cohesion, do not influence the results, while Young’s modulus has a large influence on the designs. Additionally, the results of this study showed that the maximum stress concentrations are at the bolts and connection joints where they are too close to the steel’s yield stress. It also proves that the non-elastic behaviour of the soil does not require to be assigned for such analyses and it can be simplified only with its elastic behaviour. The embedded length affects the lateral displacement, while the number of bolts influences the structure’s resistance to external loads. Full article
(This article belongs to the Section Computational Engineering)
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Article
LMI-Based Results on Robust Exponential Passivity of Uncertain Neutral-Type Neural Networks with Mixed Interval Time-Varying Delays via the Reciprocally Convex Combination Technique
Computation 2021, 9(6), 70; https://0-doi-org.brum.beds.ac.uk/10.3390/computation9060070 - 10 Jun 2021
Viewed by 654
Abstract
The issue of the robust exponential passivity analysis for uncertain neutral-type neural networks with mixed interval time-varying delays is discussed in this work. For our purpose, the lower bounds of the delays are allowed to be either positive or zero adopting the combination [...] Read more.
The issue of the robust exponential passivity analysis for uncertain neutral-type neural networks with mixed interval time-varying delays is discussed in this work. For our purpose, the lower bounds of the delays are allowed to be either positive or zero adopting the combination of the model transformation, various inequalities, the reciprocally convex combination, and suitable Lyapunov–Krasovskii functional. A new robust exponential passivity criterion is received and formulated in the form of linear matrix inequalities (LMIs). Moreover, a new exponential passivity criterion is also examined for systems without uncertainty. Four numerical examples indicate our potential results exceed the previous results. Full article
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Review
RFID Applications and Security Review
Computation 2021, 9(6), 69; https://0-doi-org.brum.beds.ac.uk/10.3390/computation9060069 - 10 Jun 2021
Cited by 2 | Viewed by 903
Abstract
Radio frequency identification (RFID) is widely used in several contexts, such as logistics, supply chains, asset tracking, and health, among others, therefore drawing the attention of many researchers. This paper presents a review of the most cited topics regarding RFID focused on applications, [...] Read more.
Radio frequency identification (RFID) is widely used in several contexts, such as logistics, supply chains, asset tracking, and health, among others, therefore drawing the attention of many researchers. This paper presents a review of the most cited topics regarding RFID focused on applications, security, and privacy. A total of 62,685 records were downloaded from the Web of Science (WoS) and Scopus core databases and processed, reconciling the datasets to remove duplicates, resulting in 40,677 unique elements. Fundamental indicators were extracted and are presented, such as the citation number, average growth rate, and average number of documents per year. We extracted the top topics and reviewed the relevant indicators using a free Python tool, ScientoPy. The results are discussed in the following sections: the first is the Applications Section, whose subsections are the Internet of Things (IoT), Supply Chain Management, Localization, Traceability, Logistics, Ubiquitous Computing, Healthcare, and Access Control; the second is the Security and Privacy section, whose subsections are Authentication, Privacy, and Ownership Transfer; finally, we present the Discussion section. This paper intends to provide the reader with a global view of the current status of trending RFID topics and present different analyses from different perspectives depending on motivations or background. Full article
(This article belongs to the Special Issue Bibliometrics)
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Article
Improved Equilibrium Optimization Algorithm Using Elite Opposition-Based Learning and New Local Search Strategy for Feature Selection in Medical Datasets
Computation 2021, 9(6), 68; https://0-doi-org.brum.beds.ac.uk/10.3390/computation9060068 - 10 Jun 2021
Cited by 1 | Viewed by 839
Abstract
The rapid growth in biomedical datasets has generated high dimensionality features that negatively impact machine learning classifiers. In machine learning, feature selection (FS) is an essential process for selecting the most significant features and reducing redundant and irrelevant features. In this study, an [...] Read more.
The rapid growth in biomedical datasets has generated high dimensionality features that negatively impact machine learning classifiers. In machine learning, feature selection (FS) is an essential process for selecting the most significant features and reducing redundant and irrelevant features. In this study, an equilibrium optimization algorithm (EOA) is used to minimize the selected features from high-dimensional medical datasets. EOA is a novel metaheuristic physics-based algorithm and newly proposed to deal with unimodal, multi-modal, and engineering problems. EOA is considered as one of the most powerful, fast, and best performing population-based optimization algorithms. However, EOA suffers from local optima and population diversity when dealing with high dimensionality features, such as in biomedical datasets. In order to overcome these limitations and adapt EOA to solve feature selection problems, a novel metaheuristic optimizer, the so-called improved equilibrium optimization algorithm (IEOA), is proposed. Two main improvements are included in the IEOA: The first improvement is applying elite opposite-based learning (EOBL) to improve population diversity. The second improvement is integrating three novel local search strategies to prevent it from becoming stuck in local optima. The local search strategies applied to enhance local search capabilities depend on three approaches: mutation search, mutation–neighborhood search, and a backup strategy. The IEOA has enhanced the population diversity, classification accuracy, and selected features, and increased the convergence speed rate. To evaluate the performance of IEOA, we conducted experiments on 21 biomedical benchmark datasets gathered from the UCI repository. Four standard metrics were used to test and evaluate IEOA’s performance: the number of selected features, classification accuracy, fitness value, and p-value statistical test. Moreover, the proposed IEOA was compared with the original EOA and other well-known optimization algorithms. Based on the experimental results, IEOA confirmed its better performance in comparison to the original EOA and the other optimization algorithms, for the majority of the used datasets. Full article
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Article
Improved Genetic Algorithm for Phase-Balancing in Three-Phase Distribution Networks: A Master-Slave Optimization Approach
Computation 2021, 9(6), 67; https://0-doi-org.brum.beds.ac.uk/10.3390/computation9060067 - 09 Jun 2021
Cited by 4 | Viewed by 605
Abstract
This paper addresses the phase-balancing problem in three-phase power grids with the radial configuration from the perspective of master–slave optimization. The master stage corresponds to an improved version of the Chu and Beasley genetic algorithm, which is based on the multi-point mutation operator [...] Read more.
This paper addresses the phase-balancing problem in three-phase power grids with the radial configuration from the perspective of master–slave optimization. The master stage corresponds to an improved version of the Chu and Beasley genetic algorithm, which is based on the multi-point mutation operator and the generation of solutions using a Gaussian normal distribution based on the exploration and exploitation schemes of the vortex search algorithm. The master stage is entrusted with determining the configuration of the phases by using an integer codification. In the slave stage, a power flow for imbalanced distribution grids based on the three-phase version of the successive approximation method was used to determine the costs of daily energy losses. The objective of the optimization model is to minimize the annual operative costs of the network by considering the daily active and reactive power curves. Numerical results from a modified version of the IEEE 37-node test feeder demonstrate that it is possible to reduce the annual operative costs of the network by approximately 20% by using optimal load balancing. In addition, numerical results demonstrated that the improved version of the CBGA is at least three times faster than the classical CBGA, this was obtained in the peak load case for a test feeder composed of 15 nodes; also, the improved version of the CBGA was nineteen times faster than the vortex search algorithm. Other comparisons with the sine–cosine algorithm and the black hole optimizer confirmed the efficiency of the proposed optimization method regarding running time and objective function values. Full article
(This article belongs to the Special Issue Recent Advances in Process Modeling and Optimisation)
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Article
1D–2D Numerical Model for Wave Attenuation by Mangroves as a Porous Structure
Computation 2021, 9(6), 66; https://0-doi-org.brum.beds.ac.uk/10.3390/computation9060066 - 07 Jun 2021
Viewed by 778
Abstract
In this paper, we investigate wave attenuation caused by mangroves as a porous media. A 1-D mathematical model is derived by modifying the shallow water equations (SWEs). Two approaches are used to involve the existing of mangrove: friction term and diffusion term. The [...] Read more.
In this paper, we investigate wave attenuation caused by mangroves as a porous media. A 1-D mathematical model is derived by modifying the shallow water equations (SWEs). Two approaches are used to involve the existing of mangrove: friction term and diffusion term. The model will be solved analytically using the separation of variables method and numerically using a staggered finite volume method. From both methods, wave transmission coefficient will be obtained and used to observe the damping effect induced by the porous media. Several comparisons are shown to examine the accuracy and robustness of the derived numerical scheme. The results show that the friction coefficient, diffusion coefficient and vegetation’s length have a significant effect on the transmission coefficient. Moreover, numerical observation is extended to a 2-D SWEs, where we conduct a numerical simulation over a real bathymetry profile. The results from the 2-D numerical scheme will be validated using the data obtained from the field measurement which took place in Demak, Central Java, Indonesia. The results from this research will be beneficial to determine the characteristics of porous structures used for coastal protection. Full article
(This article belongs to the Section Computational Engineering)
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Article
Computational Performance of Disparate Lattice Boltzmann Scenarios under Unsteady Thermal Convection Flow and Heat Transfer Simulation
Computation 2021, 9(6), 65; https://0-doi-org.brum.beds.ac.uk/10.3390/computation9060065 - 31 May 2021
Viewed by 738
Abstract
The present work highlights the capacity of disparate lattice Boltzmann strategies in simulating natural convection and heat transfer phenomena during the unsteady period of the flow. Within the framework of Bhatnagar-Gross-Krook collision operator, diverse lattice Boltzmann schemes emerged from two different embodiments of [...] Read more.
The present work highlights the capacity of disparate lattice Boltzmann strategies in simulating natural convection and heat transfer phenomena during the unsteady period of the flow. Within the framework of Bhatnagar-Gross-Krook collision operator, diverse lattice Boltzmann schemes emerged from two different embodiments of discrete Boltzmann expression and three distinct forcing models. Subsequently, computational performance of disparate lattice Boltzmann strategies was tested upon two different thermo-hydrodynamics configurations, namely the natural convection in a differentially-heated cavity and the Rayleigh-Bènard convection. For the purposes of exhibition and validation, the steady-state conditions of both physical systems were compared with the established numerical results from the classical computational techniques. Excellent agreements were observed for both thermo-hydrodynamics cases. Numerical results of both physical systems demonstrate the existence of considerable discrepancy in the computational characteristics of different lattice Boltzmann strategies during the unsteady period of the simulation. The corresponding disparity diminished gradually as the simulation proceeded towards a steady-state condition, where the computational profiles became almost equivalent. Variation in the discrete lattice Boltzmann expressions was identified as the primary factor that engenders the prevailed heterogeneity in the computational behaviour. Meanwhile, the contribution of distinct forcing models to the emergence of such diversity was found to be inconsequential. The findings of the present study contribute to the ventures to alleviate contemporary issues regarding proper selection of lattice Boltzmann schemes in modelling fluid flow and heat transfer phenomena. Full article
(This article belongs to the Section Computational Engineering)
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Article
Exploring the Influence of Social Media Usage for Academic Purposes Using a Partial Least Squares Approach
Computation 2021, 9(6), 64; https://0-doi-org.brum.beds.ac.uk/10.3390/computation9060064 - 29 May 2021
Viewed by 935
Abstract
Social media applications have been increasingly gaining significant attention from online education and training platforms. Social networking tools provide multiple advantages for communicating, exchanging opinions, and discussing specific issues. Social media also helps to improve the processes of teaching and learning through sharing [...] Read more.
Social media applications have been increasingly gaining significant attention from online education and training platforms. Social networking tools provide multiple advantages for communicating, exchanging opinions, and discussing specific issues. Social media also helps to improve the processes of teaching and learning through sharing educational programs. In this study, we used a quantitative research technique based on the partial least-squares (PLS) linear regression method to determine the influence of using social media as an online discussion and communication platform for academic purposes by assessing the relationships among the skills obtained through social media, the usage of social media, and the purpose of social media. A total of 200 students participated in this study (88% female and 12% males), and a purposive sampling technique was used to select a suitable population for the study. The results show that 61.5% of the participants use the web daily for more than five hours, mainly for social communication (meaningful dialog and discussion skills) and entertainment. The students agreed that social media develops their creative thinking, but it has no positive impact on their academic performance. Full article
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Article
Numerical Investigation of a Radially Cooled Turbine Guide Vane Using Air and Steam as a Cooling Medium
Computation 2021, 9(6), 63; https://0-doi-org.brum.beds.ac.uk/10.3390/computation9060063 - 28 May 2021
Cited by 1 | Viewed by 779
Abstract
Gas turbine performance is closely linked to the turbine inlet temperature, which is limited by the turbine guide vanes ability to withstand the massive thermal loads. Thus, steam cooling has been introduced as an advanced cooling technology to improve the efficiency of modern [...] Read more.
Gas turbine performance is closely linked to the turbine inlet temperature, which is limited by the turbine guide vanes ability to withstand the massive thermal loads. Thus, steam cooling has been introduced as an advanced cooling technology to improve the efficiency of modern high-temperature gas turbines. This study compares the cooling performance of compressed air and steam in the renowned radially cooled NASA C3X turbine guide vane, using a numerical model. The conjugate heat transfer (CHT) model is based on the RANS-method, where the shear stress transport (SST) kω model is selected to predict the effects of turbulence. The numerical model is validated against experimental pressure and temperature distributions at the external surface of the vane. The results are in good agreement with the experimental data, with an average error of 1.39% and 3.78%, respectively. By comparing the two coolants, steam is confirmed as the superior cooling medium. The disparity between the coolants increases along the axial direction of the vane, and the total volume average temperature difference is 30 K. Further investigations are recommended to deal with the local hot-spots located near the leading- and trailing edge of the vane. Full article
(This article belongs to the Section Computational Engineering)
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Article
Hybrid Feedback Control for Exponential Stability and Robust H Control of a Class of Uncertain Neural Network with Mixed Interval and Distributed Time-Varying Delays
Computation 2021, 9(6), 62; https://0-doi-org.brum.beds.ac.uk/10.3390/computation9060062 - 28 May 2021
Viewed by 738
Abstract
This paper is concerned the problem of robust H control for uncertain neural networks with mixed time-varying delays comprising different interval and distributed time-varying delays via hybrid feedback control. The interval and distributed time-varying delays are not necessary to be differentiable. The [...] Read more.
This paper is concerned the problem of robust H control for uncertain neural networks with mixed time-varying delays comprising different interval and distributed time-varying delays via hybrid feedback control. The interval and distributed time-varying delays are not necessary to be differentiable. The main purpose of this research is to estimate robust exponential stability of uncertain neural network with H performance attenuation level γ. The key features of the approach include the introduction of a new Lyapunov–Krasovskii functional (LKF) with triple integral terms, the employment of a tighter bounding technique, some slack matrices and newly introduced convex combination condition in the calculation, improved delay-dependent sufficient conditions for the robust H control with exponential stability of the system are obtained in terms of linear matrix inequalities (LMIs). The results of this paper complement the previously known ones. Finally, a numerical example is presented to show the effectiveness of the proposed methods. Full article
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Article
Accurate and Efficient Derivative-Free Three-Phase Power Flow Method for Unbalanced Distribution Networks
Computation 2021, 9(6), 61; https://0-doi-org.brum.beds.ac.uk/10.3390/computation9060061 - 27 May 2021
Cited by 5 | Viewed by 978
Abstract
The power flow problem in three-phase unbalanced distribution networks is addressed in this research using a derivative-free numerical method based on the upper-triangular matrix. The upper-triangular matrix is obtained from the topological connection among nodes of the network (i.e., through a graph-based method). [...] Read more.
The power flow problem in three-phase unbalanced distribution networks is addressed in this research using a derivative-free numerical method based on the upper-triangular matrix. The upper-triangular matrix is obtained from the topological connection among nodes of the network (i.e., through a graph-based method). The main advantage of the proposed three-phase power flow method is the possibility of working with single-, two-, and three-phase loads, including Δ- and Y-connections. The Banach fixed-point theorem for loads with Y-connection helps ensure the convergence of the upper-triangular power flow method based an impedance-like equivalent matrix. Numerical results in three-phase systems with 8, 25, and 37 nodes demonstrate the effectiveness and computational efficiency of the proposed three-phase power flow formulation compared to the classical three-phase backward/forward method and the implementation of the power flow problem in the DigSILENT software. Comparisons with the backward/forward method demonstrate that the proposed approach is 47.01%, 47.98%, and 36.96% faster in terms of processing times by employing the same number of iterations as when evaluated in the 8-, 25-, and 37-bus systems, respectively. An application of the Chu-Beasley genetic algorithm using a leader–follower optimization approach is applied to the phase-balancing problem utilizing the proposed power flow in the follower stage. Numerical results present optimal solutions with processing times lower than 5 s, which confirms its applicability in large-scale optimization problems employing embedding master–slave optimization structures. Full article
(This article belongs to the Special Issue Recent Advances in Process Modeling and Optimisation)
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