Journal Description
Computation
Computation
is a peer-reviewed journal of computational science and engineering published monthly online by MDPI.
- Open Access— free for readers, with article processing charges (APC) paid by authors or their institutions.
- High Visibility: indexed within Scopus, ESCI (Web of Science), CAPlus / SciFinder, Inspec, dblp, and other databases.
- Journal Rank: JCR - Q2 (Mathematics, Interdisciplinary Applications) / CiteScore - Q2 (Applied Mathematics)
- Rapid Publication: manuscripts are peer-reviewed and a first decision is provided to authors approximately 19.7 days after submission; acceptance to publication is undertaken in 4.6 days (median values for papers published in this journal in the first half of 2024).
- Recognition of Reviewers: reviewers who provide timely, thorough peer-review reports receive vouchers entitling them to a discount on the APC of their next publication in any MDPI journal, in appreciation of the work done.
Impact Factor:
1.9 (2023);
5-Year Impact Factor:
2.0 (2023)
Latest Articles
Networks Based on Graphs of Transient Intensities and Product Theorems in Their Modelling
Computation 2024, 12(10), 195; https://doi.org/10.3390/computation12100195 - 27 Sep 2024
Abstract
This paper considers two models of queuing with a varying structure based on the introduction of additional transient intensities into known models or their combinations, which create stationary distributions convenient for calculation. In the first model, it is a probabilistic mixture of known
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This paper considers two models of queuing with a varying structure based on the introduction of additional transient intensities into known models or their combinations, which create stationary distributions convenient for calculation. In the first model, it is a probabilistic mixture of known stationary distributions with given weights. In the second model, this uniform distribution is repeatedly used in physical statistics. Both models are based on the selection of states, between which additional transient intensities are introduced. The algorithms used in this paper for introducing new transient intensities are closely related to the concept of flow in a deterministic transport network. The introduced controls are selected so that the marginal distribution of the combined system is a mixture of the marginal distributions of the combined systems with different weights determined by the introduced transient intensities. As a result, the process of functioning of the combined system is obtained by switching processes corresponding to different combined systems at certain points in time.
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(This article belongs to the Section Computational Engineering)
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Dynamics of Blood Flows in the Cardiocirculatory System
by
Maria Pia D’Arienzo and Luigi Rarità
Computation 2024, 12(10), 194; https://doi.org/10.3390/computation12100194 - 25 Sep 2024
Abstract
Models and simulations of blood flow in vascular networks are useful to deepen knowledge of cardiovascular diseases. This paper considers a model based on partial differential equations that mimic the dynamics of vascular networks in terms of flow velocities and arterial pressures. Such
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Models and simulations of blood flow in vascular networks are useful to deepen knowledge of cardiovascular diseases. This paper considers a model based on partial differential equations that mimic the dynamics of vascular networks in terms of flow velocities and arterial pressures. Such quantities are found by using ad hoc numerical schemes to examine variations in the pressure and homeostatic conditions of a whole organism. Two different case studies are examined. The former uses 15 arteries—a network that shows the real oscillations in pressures and velocities due to variations in artery volume. The latter focuses on the 55 principal arteries, and blood flows are studied by using a model of a heart valve that opens and closes via the differences in the aortic and left ventricle pressures. This last case confirms the possibility of autonomously regulating blood pressure and velocity in arteries in general and when tilt tests are applied to patients.
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(This article belongs to the Section Computational Engineering)
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Computational Modeling of the Coffee Consumer Experience and Its Impact on the Sustainability of the Regional Industry in Peru
by
Emma Verónica Ramos Farroñán, Marco Agustín Arbulu-Ballesteros, Nancy Mercedes Soto Deza, Sandra Elizabeth Pagador Flores and Karla Paola Agurto Ruiz
Computation 2024, 12(10), 193; https://doi.org/10.3390/computation12100193 - 24 Sep 2024
Abstract
This study addresses the significant social value of understanding consumer experiences in the coffee market, which is crucial for enhancing local economic sustainability and consumer satisfaction in the cities of Piura, Trujillo, and Chiclayo in Peru. The objective of this research was to
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This study addresses the significant social value of understanding consumer experiences in the coffee market, which is crucial for enhancing local economic sustainability and consumer satisfaction in the cities of Piura, Trujillo, and Chiclayo in Peru. The objective of this research was to evaluate the coffee consumption experience of 1190 consumers using structural equation modeling. Methodologically, a detailed survey was employed to capture various dimensions of consumer experience. The results revealed a strong positive effect of perceived quality on hedonic value (β = 0.776; p < 0.001), underscoring the importance of high sensory standards. Brand experiences significantly influenced quality beliefs (β = 0.399; p < 0.001) and perceived utility (β = 0.733; p < 0.001), though there was no direct connection with hedonic valuation, indicating the need for further analysis. The findings highlighted that hedonic value, associated with emotional satisfaction, predominates over utilitarian value in driving brand loyalty (β = 0.908 vs. β = 0.076; p < 0.001). This provides strategic insights into incorporating symbolic and experiential benefits in marketing. In conclusion, the study offers quantitative evidence on shaping consumer experiences in the coffee market by focusing on sensory quality and affective brand identity.
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(This article belongs to the Section Computational Engineering)
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Computational Analysis of a Novel Iterative Scheme with an Application
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Fayyaz Ahmad, Kifayat Ullah, Junaid Ahmad, Ahmad Aloqaily and Nabil Mlaiki
Computation 2024, 12(9), 192; https://doi.org/10.3390/computation12090192 - 21 Sep 2024
Abstract
The computational study of fixed-point problems in distance spaces is an active and important research area. The purpose of this paper is to construct a new iterative scheme in the setting of Banach space for approximating solutions of fixed-point problems. We first prove
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The computational study of fixed-point problems in distance spaces is an active and important research area. The purpose of this paper is to construct a new iterative scheme in the setting of Banach space for approximating solutions of fixed-point problems. We first prove the strong convergence of the scheme for a general class of contractions under some appropriate assumptions on the domain and a parameter involved in our scheme. We then study the qualitative aspects of our scheme, such as the stability and order of convergence for the scheme. Some nonlinear problems are then considered and solved numerically by our new iterative scheme. The numerical simulations and graphical visualizations prove the high accuracy and stability of the new fixed-point scheme. Eventually, we solve a 2D nonlinear Volterra Integral Equation (VIE) via the application of our main outcome. Our results improve many related results in fixed-point iteration theory.
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(This article belongs to the Section Computational Engineering)
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Waiting Time Control Chart for M/G/1 Retrial Queue
by
Yih-Bey Lin, Tzu-Hsin Liu, Yu-Cheng Tsai and Fu-Min Chang
Computation 2024, 12(9), 191; https://doi.org/10.3390/computation12090191 - 19 Sep 2024
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Retrial queues are used extensively to model many practical problems in service systems, call centers, data centers, and computer network systems. The average waiting time is the main observable characteristic of the retrial queues. Long queues may cause negative impacts such as waste
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Retrial queues are used extensively to model many practical problems in service systems, call centers, data centers, and computer network systems. The average waiting time is the main observable characteristic of the retrial queues. Long queues may cause negative impacts such as waste of manpower and unnecessary crowding leading to suffocation, and can even cause trouble for customers and institutions. Applying control chart technology can help managers analyze customers’ waiting times to improve the effective performance of service and attention. This paper pioneers the developing and detailed study of a waiting time control chart for a retrial queue with general service times. Two waiting time control charts, the Shewhart control chart, and a control chart using the weighted variance method are constructed in this paper. We present three cases for the Shewhart control chart in which the service time obeys special distributions, such as exponential, Erlang, and hyper-exponential distributions. The case of an exponentially distributed service time is also presented for the control chart using the weighted variance method. Based on the numerical simulations conducted herein, managers can better monitor and analyze the customers’ waiting times for their service systems and take preventive measures.
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Open AccessArticle
Bayesian Optimized Machine Learning Model for Automated Eye Disease Classification from Fundus Images
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Tasnim Bill Zannah, Md. Abdulla-Hil-Kafi, Md. Alif Sheakh, Md. Zahid Hasan, Taslima Ferdaus Shuva, Touhid Bhuiyan, Md. Tanvir Rahman, Risala Tasin Khan, M. Shamim Kaiser and Md Whaiduzzaman
Computation 2024, 12(9), 190; https://doi.org/10.3390/computation12090190 - 16 Sep 2024
Abstract
Eye diseases are defined as disorders or diseases that damage the tissue and related parts of the eyes. They appear in various types and can be either minor, meaning that they do not last long, or permanent blindness. Cataracts, glaucoma, and diabetic retinopathy
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Eye diseases are defined as disorders or diseases that damage the tissue and related parts of the eyes. They appear in various types and can be either minor, meaning that they do not last long, or permanent blindness. Cataracts, glaucoma, and diabetic retinopathy are all eye illnesses that can cause vision loss if not discovered and treated early on. Automated classification of these diseases from fundus images can empower quicker diagnoses and interventions. Our research aims to create a robust model, BayeSVM500, for eye disease classification to enhance medical technology and improve patient outcomes. In this study, we develop models to classify images accurately. We start by preprocessing fundus images using contrast enhancement, normalization, and resizing. We then leverage several state-of-the-art deep convolutional neural network pre-trained models, including VGG16, VGG19, ResNet50, EfficientNet, and DenseNet, to extract deep features. To reduce feature dimensionality, we employ techniques such as principal component analysis, feature agglomeration, correlation analysis, variance thresholding, and feature importance rankings. Using these refined features, we train various traditional machine learning models as well as ensemble methods. Our best model, named BayeSVM500, is a Support Vector Machine classifier trained on EfficientNet features reduced to 500 dimensions via PCA, achieving 93.65 ± 1.05% accuracy. Bayesian hyperparameter optimization further improved performance to 95.33 ± 0.60%. Through comprehensive feature engineering and model optimization, we demonstrate highly accurate eye disease classification from fundus images, comparable to or superior to previous benchmarks.
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(This article belongs to the Special Issue Deep Learning Applications in Medical Imaging)
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MATLAB Application for Determination of 12 Combustion Products, Adiabatic Temperature and Laminar Burning Velocity: Development, Coding and Explanation
by
Roberto Franco Cisneros and Freddy Jesus Rojas
Computation 2024, 12(9), 189; https://doi.org/10.3390/computation12090189 - 16 Sep 2024
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The determination of the characteristics and main combustion properties of fuels is necessary for post-implementation in different applications. Among the most important combustion properties of a fuel are the combustion products, flame temperature and laminar burning velocity. Therefore, this paper describes the step-by-step
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The determination of the characteristics and main combustion properties of fuels is necessary for post-implementation in different applications. Among the most important combustion properties of a fuel are the combustion products, flame temperature and laminar burning velocity. Therefore, this paper describes the step-by-step development and coding of a MATLAB application that can determine 12 combustion products, flame temperature and laminar burning velocity in order to understand the logic of calculus procedure, so any user would be able to make improvements of new functionalities (add more fuels, add more combustion products, etc.). The numerical procedure and methods (Gaussian elimination, Taylor Series and Newton–Raphson) parallel with their implementation as code lines for the development of the application are carried out using flow charts. In addition, simulations in Ansys Chemkin were performed and included in the application as part of the results comparison. It was found that: (1) The MATLAB Application codification and development were successfully explained in detail, (2) the functions and execution sequence are described by using flow charts and code extract, (3) the application is available to everyone for modifications, (4) the application can only be used for hydrocarbons fuels, (5) the application execution time registered was less than 8 s.
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Performance Analysis and Optimization of a Channeled Photovoltaic Thermal System with Fin Absorbers and Combined Bi-Fluid Cooling
by
Hamza Nasri, Jamel Riahi, Hatem Oueslati, Hichem Taghouti and Silvano Vergura
Computation 2024, 12(9), 188; https://doi.org/10.3390/computation12090188 - 15 Sep 2024
Abstract
The conversion efficiency of photovoltaic (PV) cells can be increased by reducing high temperatures with appropriate cooling. Passive cooling systems using air, water, ethylene glycol, and air/water+TiO2 nano bi-fluid froth in the duct channel have been studied, but an overall assessment is
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The conversion efficiency of photovoltaic (PV) cells can be increased by reducing high temperatures with appropriate cooling. Passive cooling systems using air, water, ethylene glycol, and air/water+TiO2 nano bi-fluid froth in the duct channel have been studied, but an overall assessment is essential for its possible application. In the present work, a numerical study is adopted to investigate the impact of the fluid-duct channel type on the electrical and thermal efficiency of the photovoltaic thermal (PVT) collector. Such investigation is achieved by means of a MATLAB R2022b code based on the Runge–Kutta (RK4) method. Four kinds of fluid duct channels are used to optimize the best fluid for improving the overall efficiency of the investigated PVT system. The numerical validation of the proposed model has been made by comparing the numerical and experimental results reported in the literature. The outcomes indicate that varying the duct channel nature affects mainly the electrical and thermal efficiency of the PVT collector. Our results validate that the nature of the fluid affects weakly the electrical efficiency, whereas the thermal efficiency is strongly affected. Accordingly, it is observed that PVT collectors based on nano bi-fluid air/water+TiO2 give the best performance. In this context, an appreciable increase in the overall efficiency of 22% is observed when the water+TiO2 fluid is substituted by air/ water+TiO2 nano bi-fluid. Therefore, these motivating results make the PVT nano bi-fluid efficient and suitable for solar photovoltaic thermal applications since this system exhibits a daily overall efficiency of about 56.96%. The present work proves that controlling the design, cooling technique, and nature of the cooling fluid used is a crucial factor for improving the electrical, thermal, and overall efficiency of the PVT systems.
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(This article belongs to the Section Computational Engineering)
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Exploring Soliton Solutions for Fractional Nonlinear Evolution Equations: A Focus on Regularized Long Wave and Shallow Water Wave Models with Beta Derivative
by
Sujoy Devnath, Maha M. Helmi and M. Ali Akbar
Computation 2024, 12(9), 187; https://doi.org/10.3390/computation12090187 - 11 Sep 2024
Abstract
The fractional regularized long wave equation and the fractional nonlinear shallow-water wave equation are the noteworthy models in the domains of fluid dynamics, ocean engineering, plasma physics, and microtubules in living cells. In this study, a reliable and efficient improved F-expansion technique, along
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The fractional regularized long wave equation and the fractional nonlinear shallow-water wave equation are the noteworthy models in the domains of fluid dynamics, ocean engineering, plasma physics, and microtubules in living cells. In this study, a reliable and efficient improved F-expansion technique, along with the fractional beta derivative, has been utilized to explore novel soliton solutions to the stated wave equations. Consequently, the study establishes a variety of reliable and novel soliton solutions involving trigonometric, hyperbolic, rational, and algebraic functions. By setting appropriate values for the parameters, we obtained peakons, anti-peakon, kink, bell, anti-bell, singular periodic, and flat kink solitons. The physical behavior of these solitons is demonstrated in detail through three-dimensional, two-dimensional, and contour representations. The impact of the fractional-order derivative on the wave profile is notable and is illustrated through two-dimensional graphs. It can be stated that the newly established solutions might be further useful for the aforementioned domains.
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(This article belongs to the Section Computational Engineering)
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Exploring Bifurcation in the Compartmental Mathematical Model of COVID-19 Transmission
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Olena Kiseleva, Sergiy Yakovlev, Dmytro Chumachenko and Oleksandr Kuzenkov
Computation 2024, 12(9), 186; https://doi.org/10.3390/computation12090186 - 11 Sep 2024
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This study proposes and theoretically substantiates a unique mathematical model for predicting the spread of infectious diseases using the example of COVID-19. The model is described by a special system of autonomous differential equations, which has scientific novelty for cases of complex dynamics
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This study proposes and theoretically substantiates a unique mathematical model for predicting the spread of infectious diseases using the example of COVID-19. The model is described by a special system of autonomous differential equations, which has scientific novelty for cases of complex dynamics of disease transmission. The adequacy of the model is confirmed by testing on the example of the spread of COVID-19 in one of the largest regions of Ukraine, both in terms of population and area. The practical novelty emerges through its versatile application in real-world contexts, guiding organizational decisions and public health responses. The model’s capacity to facilitate system functioning evaluation and identify significant parameters underlines its potential for proactive management and effective response in the evolving landscape of infectious diseases.
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Computationally Efficient Outlier Detection for High-Dimensional Data Using the MDP Algorithm
by
Michail Tsagris, Manos Papadakis, Abdulaziz Alenazi and Omar Alzeley
Computation 2024, 12(9), 185; https://doi.org/10.3390/computation12090185 - 11 Sep 2024
Abstract
Outlier detection, or anomaly detection as it is known in the machine learning community, has gained interest in recent years, and it is commonly used when the sample size is smaller than the number of variables. In 2015, an outlier detection procedure was
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Outlier detection, or anomaly detection as it is known in the machine learning community, has gained interest in recent years, and it is commonly used when the sample size is smaller than the number of variables. In 2015, an outlier detection procedure was proposed 7 for this high-dimensional setting, replacing the classic minimum covariance determinant estimator with the minimum diagonal product estimator. Computationally speaking, their method has two drawbacks: (a) it is not computationally efficient and does not scale up, and (b) it is not memory efficient and, in some cases, it is not possible to apply due to memory limits. We address the first issue via efficient code written in both R and C++, whereas for the second issue, we utilize the eigen decomposition and its properties. Experiments are conducted using simulated data to showcase the time improvement, while gene expression data are used to further examine some extra practicalities associated with the algorithm. The simulation studies yield a speed-up factor that ranges between 17 and 1800, implying a successful reduction in the estimator’s computational burden.
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(This article belongs to the Section Computational Biology)
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An Algorithm for Coding an Additive Manufacturing File from the Pressure Distribution of a Baropodometric Board for 3D Printing Customised Orthopaedic Insoles
by
Francesco Simi, Gabriele Maria Fortunato, Fabio Diana, Jacopo Gai and Carmelo De Maria
Computation 2024, 12(9), 184; https://doi.org/10.3390/computation12090184 - 10 Sep 2024
Abstract
Customised orthotic insoles play a critical role in addressing foot pathologies and improving comfort and biomechanical alignment for patients with specific needs. The use of 3D printing technology for the manufacturing of orthotic insoles has received considerable attention in recent years due to
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Customised orthotic insoles play a critical role in addressing foot pathologies and improving comfort and biomechanical alignment for patients with specific needs. The use of 3D printing technology for the manufacturing of orthotic insoles has received considerable attention in recent years due to its potential for customisation, rapid prototyping, and cost-effectiveness. This paper presents the implementation of an algorithm purposely developed to generate an Additive Manufacturing File (AMF) containing the geometry of a patient-specific insole and the stiffness distribution based on pressure analysis from a baropodometric board. The generated file is used to 3D print via Fused Deposition Modelling an insole with a variable infill percentage depending on the pressure distribution on the patient’s foot. Three inputs are used as source data for the AMF file coding: (i) the 3D model that defines the geometry of the insole designed by the orthopaedist; (ii) the pressure map of the patient’s feet obtained with a baropodometric board; and (iii) the stiffness of the material that will be used to fabricate the insole. The proposed approach allows the fabrication of a patient-specific insole, capable of restoring the correct pressure distribution on the foot by varying the infill percentage. Two types of insoles were successfully fabricated using the implemented algorithm: the first was 3D printed, adding a top layer to be ready-to-use; the second was 3D printed without a top surface to be further customised with different coatings. The method described in this paper is robust for the fabrication of customised insoles and aims at overcoming the limitations of the traditional approach based on milling machining (e.g., time, costs, and path planning) since it can be easily integrated into any orthopaedic workshop.
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(This article belongs to the Section Computational Engineering)
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Second-Order Modified Nonstandard Explicit Euler and Explicit Runge–Kutta Methods for n-Dimensional Autonomous Differential Equations
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Fawaz K. Alalhareth, Madhu Gupta, Hristo V. Kojouharov and Souvik Roy
Computation 2024, 12(9), 183; https://doi.org/10.3390/computation12090183 - 9 Sep 2024
Abstract
Nonstandard finite-difference (NSFD) methods, pioneered by R. E. Mickens, offer accurate and efficient solutions to various differential equation models in science and engineering. NSFD methods avoid numerical instabilities for large time steps, while numerically preserving important properties of exact solutions. However, most NSFD
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Nonstandard finite-difference (NSFD) methods, pioneered by R. E. Mickens, offer accurate and efficient solutions to various differential equation models in science and engineering. NSFD methods avoid numerical instabilities for large time steps, while numerically preserving important properties of exact solutions. However, most NSFD methods are only first-order accurate. This paper introduces two new classes of explicit second-order modified NSFD methods for solving n-dimensional autonomous dynamical systems. These explicit methods extend previous work by incorporating novel denominator functions to ensure both elementary stability and second-order accuracy. This paper also provides a detailed mathematical analysis and validates the methods through numerical simulations on various biological systems.
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(This article belongs to the Special Issue Advanced Numerical Methods for Solving Differential Equations with Applications in Science and Engineering)
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An Analysis of the Stress–Strain State of a Layer on Two Cylindrical Bearings
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Vitaly Miroshnikov, Oleksandr Denshchykov, Iaroslav Grebeniuk and Oleksandr Savin
Computation 2024, 12(9), 182; https://doi.org/10.3390/computation12090182 - 6 Sep 2024
Abstract
A spatial problem of elasticity theory is solved for a layer located on two bearings embedded in it. The bearings are represented as thick-walled pipes embedded in the layer parallel to its boundaries. The pipes are rigidly connected to the layer, and contact-type
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A spatial problem of elasticity theory is solved for a layer located on two bearings embedded in it. The bearings are represented as thick-walled pipes embedded in the layer parallel to its boundaries. The pipes are rigidly connected to the layer, and contact-type conditions (normal displacements and tangential stresses) are specified on the insides of the pipes. Stresses are set on the flat surfaces of the layer. The objective of this study is to obtain the stress–strain state of the body of the layer under different geometric characteristics of the model. The solution to the problem is presented in the form of the Lamé equation, whose terms are written in different coordinate systems. The generalized Fourier method is used to transfer the basic solutions between coordinate systems. By satisfying the boundary and conjugation conditions, the problem is reduced to a system of infinite linear algebraic equations of the second kind, to which the reduction method is applied. After finding the unknowns, using the generalized Fourier method, it is possible to find the stress–strain state at any point of the body. The numerical study of the stress state showed high convergence of the approximate solutions to the exact one. The stress–strain state of the composite body was analyzed for different geometric parameters and different pipe materials. The results obtained can be used for the preliminary determination of the geometric parameters of the model and the materials of the joints. The proposed solution method can be used not only to calculate the stress state of bearing joints, but also of bushings (under specified conditions of rigid contact without friction on the internal surfaces).
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(This article belongs to the Special Issue Integrated Computer Technologies in Mechanical Engineering—Synergetic Engineering III)
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Some Aspects of the Effects of Dry Friction Discontinuities on the Behaviour of Dynamic Systems
by
Stelian Alaci, Costica Lupascu, Ionut-Cristian Romanu, Delia-Aurora Cerlinca and Florina-Carmen Ciornei
Computation 2024, 12(9), 181; https://doi.org/10.3390/computation12090181 - 5 Sep 2024
Abstract
Most studies in the literature consider the value of the coefficient of dynamic friction to be constant. We studied the evolution of a dynamic system when the coefficient of friction results in different values depending on the contact surfaces. A system with four
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Most studies in the literature consider the value of the coefficient of dynamic friction to be constant. We studied the evolution of a dynamic system when the coefficient of friction results in different values depending on the contact surfaces. A system with four balls fixed on an aluminium plate was driven with constant velocity into motion on the coaxial races of two identical outer bearing rings. The assembly presents a motion with periodic variable amplitude between two extremes, a fact that suggests the presence of a periodical excitation. The test was repeated, but this time, new bodies were used, which were two identical bodies made of two balls rigidised via a short cylindrical rod. When the rings were driven into rotational motion, the two bodies performed different motions; if the bodies were inter-changed, the differences between the motions remained. The rings were analysed, and a small region on the race of one ring was observed, where the roughness was considerably greater than the rest of the surface. Then, a mathematical model for the dynamic system with different friction coefficients was proposed and solved. This model is capable of simulating different situations, such as oscillatory motion and circular motion, with or without separation of the contacting bodies. Here, we present a dynamic model with Hertzian contact points in the presence of dry friction, with the coefficient of friction changing suddenly on the contacting surfaces.
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(This article belongs to the Section Computational Engineering)
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Optimized Calculation of Radial and Axial Magnetic Forces between Two Non-Coaxial Coils of Rectangular Cross-Section with Parallel Axes
by
Slobodan Babic, Eray Guven, Kai-Hong Song and Yao Luo
Computation 2024, 12(9), 180; https://doi.org/10.3390/computation12090180 - 4 Sep 2024
Abstract
In this paper, we introduce a new algorithm for calculating the radial and axial magnetic forces between two non-coaxial circular loops with parallel axes. These formulas are derived from a modified version of Grover’s formula for mutual inductance between the coils in question.
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In this paper, we introduce a new algorithm for calculating the radial and axial magnetic forces between two non-coaxial circular loops with parallel axes. These formulas are derived from a modified version of Grover’s formula for mutual inductance between the coils in question. Utilizing these formulas, we compute the radial and axial magnetic forces between two non-coaxial thick coils of rectangular cross-sections with parallel axes. In these calculations, we apply the filament method and conduct investigations to determine the optimal number of subdivisions for the coils in terms of computational time and accuracy. The method presented in this paper is also applicable to all conventional non-coaxial coils, such as disks, solenoids, and non-conventional coils like Bitter coils, all with parallel axes. This paper emphasizes the accuracy and computational efficiency of the calculations. Furthermore, the new method is validated according to several previously established methods.
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(This article belongs to the Section Computational Engineering)
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PyIncentiveBC: A Python Module for Simulation of Incentivization Mechanism Implemented in Blockchain-Based Systems
by
Abdellah Ouaguid, Mohamed Hanine, Zouhair Chiba, Noreddine Abghour and Mohammed Ouzzif
Computation 2024, 12(9), 179; https://doi.org/10.3390/computation12090179 - 3 Sep 2024
Abstract
The diversity of approaches for retaining participants in a Blockchain-based system complicates benchmarking. The majority of proposals for rewarding and penalizing participants in these systems are limited to their own set of data and scenarios, making it hard to compare their effectiveness. To
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The diversity of approaches for retaining participants in a Blockchain-based system complicates benchmarking. The majority of proposals for rewarding and penalizing participants in these systems are limited to their own set of data and scenarios, making it hard to compare their effectiveness. To overcome these challenges, we developed PyIncentiveBC, a free, open-source, and modular simulator designed to evaluate the reliability of any approach, incorporating a dynamic and proportionate incentivization mechanism proposed in our previous work. PyIncentiveBC aims to provide the scientific communities with an extensible software solution facilitating the benchmarking of existing approaches with new ones proposed by them.
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(This article belongs to the Section Computational Engineering)
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The Development of a Novel Transient Signal Analysis: A Wavelet Transform Approach
by
Eduardo Gómez-Luna, Dixon E. Cuadros-Orta, John E. Candelo-Becerra and Juan C. Vasquez
Computation 2024, 12(9), 178; https://doi.org/10.3390/computation12090178 - 3 Sep 2024
Abstract
This paper presents a new method for the analysis of transient signals in the frequency domain based on the Continuous Wavelet Transform (CWT). The proposed case study involves test signals measured from an electronic switch considering open and close operations. The source is
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This paper presents a new method for the analysis of transient signals in the frequency domain based on the Continuous Wavelet Transform (CWT). The proposed case study involves test signals measured from an electronic switch considering open and close operations. The source is connected to inductive, resistive, and capacitive loads. Resonance behaviors are introduced and compared with the Discrete Fourier Transform (DFT). Multiple factors, such as reliability, repeatability, high noise attenuation, and the smoothing of the analyzed spectrum, are considered in this study. This proposed study highlights the effectiveness of CWT in signal processing, especially in obtaining a detailed spectrum that reveals the behavior of electrical circuits. Resonance behaviors were analyzed, demonstrating that the signal processing performed by CWT is better for spectrum analysis than DFT. This study shows the potential of CWT to analyze transient electrical signals, specifically for identifying and characterizing the behavior of load connections and disconnections.
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(This article belongs to the Section Computational Engineering)
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Open AccessCorrection
Correction: Oldrieve, R.M. Teaching K–3 Multi-Digit Arithmetic Computation to Students with Slow Language Processing. Computation 2024, 12, 128
by
Richard M. Oldrieve
Computation 2024, 12(9), 177; https://doi.org/10.3390/computation12090177 - 3 Sep 2024
Abstract
Error in Figure/Table [...]
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(This article belongs to the Special Issue Computations in Mathematics, Mathematical Education, and Science)
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On the Impact of Discrete Atomic Compression on Image Classification by Convolutional Neural Networks
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Viktor Makarichev, Vladimir Lukin and Iryna Brysina
Computation 2024, 12(9), 176; https://doi.org/10.3390/computation12090176 - 1 Sep 2024
Abstract
Digital images play a particular role in a wide range of systems. Image processing, storing and transferring via networks require a lot of memory, time and traffic. Also, appropriate protection is required in the case of confidential data. Discrete atomic compression (DAC) is
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Digital images play a particular role in a wide range of systems. Image processing, storing and transferring via networks require a lot of memory, time and traffic. Also, appropriate protection is required in the case of confidential data. Discrete atomic compression (DAC) is an approach providing image compression and encryption simultaneously. It has two processing modes: lossless and lossy. The latter one ensures a higher compression ratio in combination with inevitable quality loss that may affect decompressed image analysis, in particular, classification. In this paper, we explore the impact of distortions produced by DAC on performance of several state-of-the-art classifiers based on convolutional neural networks (CNNs). The classic, block-splitting and chroma subsampling modes of DAC are considered. It is shown that each of them produces a quite small effect on MobileNetV2, VGG16, VGG19, ResNet50, NASNetMobile and NASNetLarge models. This research shows that, using the DAC approach, memory expenses can be reduced without significant degradation of performance of the aforementioned CNN-based classifiers.
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(This article belongs to the Special Issue Integrated Computer Technologies in Mechanical Engineering—Synergetic Engineering III)
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