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Computation
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Applications of Computational Mathematics to Simulation and Data Analysis
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Applications of Computational Mathematics to Simulation and Data Analysis

A special issue of Computation (ISSN 2079-3197). This special issue belongs to the section "Computational Engineering".

Deadline for manuscript submissions: closed (31 December 2022) | Viewed by 11343

Special Issue Editors

Dr. Carlos Balsa

E-Mail Website
Guest Editor
Research Centre in Digitalization and Intelligent Robotics (CeDRI), Instituto Politécnico de Bragança, Bragança, Portugal
Interests: mathematical modeling and computational simulation; data analysis; fluid mechanics and heat transfer; weather forecasting; bioinformatics
Special Issues, Collections and Topics in MDPI journals
Dr. Teresa Guarda

E-Mail Website
Guest Editor
CIST Research and Innovation Center, Faculty of Systems and Telecommunications, Santa Elena Provincial State University, La Libertad, Ecuador; ALGORITMI Research Centre of Minho University, Guimarães, Portugal
Interests: pervasive systems; intelligent systems; information science; computer theory; knowledge management; cybersecurity
Special Issues, Collections and Topics in MDPI journals
Dr. Ronan Guivarch

E-Mail Website
Guest Editor
Institut de Recherche en Informatique de Toulouse (IRIT), Université de Toulouse, Toulouse, France
Interests: high performance computing; parallel programming; data analysis; clustering
Special Issues, Collections and Topics in MDPI journals
Dr. Sílvio Gama

E-Mail Website
Guest Editor
Centro de Matemática da Universidade do Porto, Rua do Campo Alegre 687, 4169-007 Porto, Portugal
Interests: turbulence, magnetohydrodynamics, computational fluid dynamics, econophysics, optimization
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

This Special Issue will publish a set of selected papers from ACMaSDA 2021—Applications of Computational Mathematics to Simulation and Data Analysis, integrated in ARTIIS 2021, to be held on 25–27 November, Salinas, Ecuador. This Special Issue focuses on the applications of computational mathematics to simulation and data analysis in various fields of science and engineering. It seeks to highlight the potential of interdisciplinary interactions as a source of new knowledge.

Contributions with new research results involving computational mathematics, numerical methods, high-performance computing, and their applications in different fields, such as fluid mechanics, mass and heat transfer, weather forecasts, and medical or biological processes are welcome.

The list of topics of interest includes but is not limited to the following:

  • Simulation and data analysis;
  • Computation in Earth sciences;
  • Computational mechanics;
  • Computing in healthcare and biosciences;
  • Digital image processing;
  • High-performance computing;
  • Numerical algorithms for computational science;
  • Weather and environment forecast.

Dr. Carlos Balsa
Dr. Teresa Guarda
Dr. Ronan Guivarch
Dr. Sílvio Gama
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Computation is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1800 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • computational mathematics
  • numerical methods
  • data analysis
  • computational simulation
  • high-performance computing
  • engineering and science applications

Published Papers (5 papers)

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Research

26 pages, 679 KiB  
Article
A New Extension of the Kumaraswamy Generated Family of Distributions with Applications to Real Data
by Salma Abbas, Mustapha Muhammad, Farrukh Jamal, Christophe Chesneau, Isyaku Muhammad and Mouna Bouchane
Computation 2023, 11(2), 26; https://0-doi-org.brum.beds.ac.uk/10.3390/computation11020026 - 05 Feb 2023
Cited by 3 | Viewed by 1614
Abstract
In this paper, we develop the new extended Kumaraswamy generated (NEKwG) family of distributions. It aims to improve the modeling capability of the standard Kumaraswamy family by using a one-parameter exponential-logarithmic transformation. Mathematical developments of the NEKwG family are provided, such as the [...] Read more.
In this paper, we develop the new extended Kumaraswamy generated (NEKwG) family of distributions. It aims to improve the modeling capability of the standard Kumaraswamy family by using a one-parameter exponential-logarithmic transformation. Mathematical developments of the NEKwG family are provided, such as the probability density function series representation, moments, information measure, and order statistics, along with asymptotic distribution results. Two special distributions are highlighted and discussed, namely, the new extended Kumaraswamy uniform (NEKwU) and the new extended Kumaraswamy exponential (NEKwE) distributions. They differ in support, but both have the features to generate models that accommodate versatile skewed data and non-monotone failure rates. We employ maximum likelihood, least-squares estimation, and Bayes estimation methods for parameter estimation. The performance of these methods is discussed using simulation studies. Finally, two real data applications are used to show the flexibility and importance of the NEKwU and NEKwE models in practice. Full article
(This article belongs to the Special Issue Applications of Computational Mathematics to Simulation and Data Analysis)
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21 pages, 2877 KiB  
Article
Modelling the Thermal Effects on Structural Components of Composite Slabs under Fire Conditions
by Carlos Balsa, Matheus Silveira, Valerian Mange and Paulo A. G. Piloto
Computation 2022, 10(6), 94; https://0-doi-org.brum.beds.ac.uk/10.3390/computation10060094 - 08 Jun 2022
Cited by 2 | Viewed by 3660
Abstract
This paper presents a finite-element-based computational model to evaluate the thermal behaviour of composite slabs with a steel deck submitted to standard fire exposure. This computational model is used to estimate the temperatures in the slab components that contribute to the fire resistance [...] Read more.
This paper presents a finite-element-based computational model to evaluate the thermal behaviour of composite slabs with a steel deck submitted to standard fire exposure. This computational model is used to estimate the temperatures in the slab components that contribute to the fire resistance according to the load-bearing criterion defined in the standards. The numerical results are validated with experimental results, and a parametric study of the effect of the thickness of the concrete on the temperatures of the slab components is presented. Composite slabs with normal or lightweight concrete and different steel deck geometries (trapezoidal and re-entrant) were considered in the simulations. In addition, the numerical temperatures are compared with those obtained using the simplified method provided by the standards. The results of the simulations show that the temperatures predicted by the simplified method led, in most cases, to an unsafe design of the composite slab. Based on the numerical results, a new analytical method, alternative to the simplified method, is defined in order to accurately determine the temperatures at the slab components and, thus, the bending resistance of the composite slabs under fire conditions. Full article
(This article belongs to the Special Issue Applications of Computational Mathematics to Simulation and Data Analysis)
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21 pages, 872 KiB  
Article
Cluster-Based Analogue Ensembles for Hindcasting with Multistations
by Carlos Balsa, Carlos Veiga Rodrigues, Leonardo Araújo and José Rufino
Computation 2022, 10(6), 91; https://0-doi-org.brum.beds.ac.uk/10.3390/computation10060091 - 02 Jun 2022
Cited by 4 | Viewed by 1582
Abstract
The Analogue Ensemble (AnEn) method enables the reconstruction of meteorological observations or deterministic predictions for a certain variable and station by using data from the same station or from other nearby stations. However, depending on the dimension and granularity of the historical datasets [...] Read more.
The Analogue Ensemble (AnEn) method enables the reconstruction of meteorological observations or deterministic predictions for a certain variable and station by using data from the same station or from other nearby stations. However, depending on the dimension and granularity of the historical datasets used for the reconstruction, this method may be computationally very demanding even if parallelization is used. In this work, the classical AnEn method is modified so that analogues are determined using K-means clustering. The proposed combined approach allows the use of several predictors in a dependent or independent way. As a result of the flexibility and adaptability of this new approach, it is necessary to define several parameters and algorithmic options. The effects of the critical parameters and main options were tested on a large dataset from real-world meteorological stations. The results show that adequate monitoring and tuning of the new method allows for a considerable improvement of the computational performance of the reconstruction task while keeping the accuracy of the results. Compared to the classical AnEn method, the proposed variant is at least 15-times faster when processing is serial. Both approaches benefit from parallel processing, with the K-means variant also being always faster than the classic method under that execution regime (albeit its performance advantage diminishes as more CPU threads are used). Full article
(This article belongs to the Special Issue Applications of Computational Mathematics to Simulation and Data Analysis)
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13 pages, 1715 KiB  
Article
Optimal Control of a Passive Particle Advected by a Lamb–Oseen (Viscous) Vortex
by Gil Marques, Sílvio Gama and Fernando Lobo Pereira
Computation 2022, 10(6), 87; https://0-doi-org.brum.beds.ac.uk/10.3390/computation10060087 - 31 May 2022
Cited by 3 | Viewed by 1624
Abstract
This work concerns the optimal control of a passive particle in viscous flows. This is relevant since, while there are many studies on optimal control in inviscid flows, there is little to no work in this context for viscous flows, and viscosity cannot [...] Read more.
This work concerns the optimal control of a passive particle in viscous flows. This is relevant since, while there are many studies on optimal control in inviscid flows, there is little to no work in this context for viscous flows, and viscosity cannot always be neglected. Furthermore, in many tasks, there is a need to reduce the energy spent; thus, energy-optimal solutions to problems are important. The aim of this work is to investigate how to optimally move a passive particle advected by a Lamb–Oseen (viscous) vortex between two given points in space in a given time interval while minimising the energy spent on this process. We take a control acting only on the radial component of the motion, and, by using the Pontryagin’s Maximum Principle, we find an explicit time-dependent extremal. We also analyse how the energy cost changes with the viscosity of the flow.The problem is transformed into a parameter search problem with two parameters related to the radial and angular coordinates of the initial point. The energy cost of the process increases with viscosity as long as the passive particle maintains the number of full turns it makes around the vortex. However, the energy cost increases if the increase in viscosity forces the particle to make fewer full revolutions around the vortex. Full article
(This article belongs to the Special Issue Applications of Computational Mathematics to Simulation and Data Analysis)
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21 pages, 4806 KiB  
Article
Natural Convection Flow over a Vertical Permeable Circular Cone with Uniform Surface Heat Flux in Temperature-Dependent Viscosity with Three-Fold Solutions within the Boundary Layer
by Md Farhad Hasan, Md. Mamun Molla, Md. Kamrujjaman and Sadia Siddiqa
Computation 2022, 10(4), 60; https://0-doi-org.brum.beds.ac.uk/10.3390/computation10040060 - 09 Apr 2022
Cited by 9 | Viewed by 2087
Abstract
The aim of this study is to investigate the effects of temperature-dependent viscosity on the natural convection flow from a vertical permeable circular cone with uniform heat flux. As part of numerical computation, the governing boundary layer equations are transformed into a non-dimensional [...] Read more.
The aim of this study is to investigate the effects of temperature-dependent viscosity on the natural convection flow from a vertical permeable circular cone with uniform heat flux. As part of numerical computation, the governing boundary layer equations are transformed into a non-dimensional form. The resulting nonlinear system of partial differential equations is then reduced to local non-similarity equations which are solved computationally by three different solution methodologies, namely, (i) perturbation solution for small transpiration parameter (ξ), (ii) asymptotic solution for large ξ, and (iii) the implicit finite difference method together with a Keller box scheme for all ξ. The numerical results of the velocity and viscosity profiles of the fluid are displayed graphically with heat transfer characteristics. The shearing stress in terms of the local skin-friction coefficient and the rate of heat transfer in terms of the local Nusselt number (Nu) are given in tabular form for the viscosity parameter (ε) and the Prandtl number (Pr). The viscosity is a linear function of temperature which is valid for small Prandtl numbers (Pr). The three-fold solutions were compared as part of the validations with various ranges of Pr numbers. Overall, good agreements were established. The major finding of the research provides a better demonstration of how temperature-dependent viscosity affects the natural convective flow. It was found that increasing Pr, ξ, and ε decrease the local skin-friction coefficient, but ξ has more influence on increasing the rate of heat transfer, as the effect of ε was erratic at small and large ξ. Furthermore, at the variable Pr, a large ξ increased the local maxima of viscosity at large extents, particularly at low Pr, but the effect on temperature distribution was found to be less significant under the same condition. However, at variable ε and fixed Pr, the temperature distribution was observed to be more influenced by ε at small ξ, whereas large ξ dominated this scheme significantly regardless of the variation in ε. The validations through three-fold solutions act as evidence of the accuracy and versatility of the current approach. Full article
(This article belongs to the Special Issue Applications of Computational Mathematics to Simulation and Data Analysis)
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