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Mathematics
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Advanced Analytical and Numerical Techniques for Technological Processes and Applications
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Advanced Analytical and Numerical Techniques for Technological Processes and Applications

A special issue of Mathematics (ISSN 2227-7390). This special issue belongs to the section "Computational and Applied Mathematics".

Deadline for manuscript submissions: closed (30 June 2022) | Viewed by 7361

Special Issue Editors

Dr. Mario Versaci

E-Mail Website
Guest Editor
Dipartimento di Ingegneria Civile Energia Ambiente e Materiali (DICEAM), “Mediterranea” University, 89122 Reggio Calabria, Italy
Interests: magnetorheological fluids; theoretical models for magnetorheological fluids; experimental models for magnetorheological fluids; magnetorheological fluids for industrial applications
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Maria Paola Speciale

E-Mail Website
Guest Editor
Department of Mathematics and Computer Science, Messina University, Messina, Italy
Interests: mathematical physics; applied mathematics
Prof. Dr. Alessandra Jannelli

E-Mail Website
Guest Editor
Department of Mathematics and Computer Science, Messina university, Messina, Italy
Interests: soft computing for electrical engineering; modeling MEMS; modeling magnetorheological fluids; numerical methods for fields and circuits

Special Issue Information

Dear Colleagues,

The proposed Special Issue is devoted to exploring up-to-date analytical and numerical techniques ranging from the Laplace–Fourier transform techniques to the Green function approach, the Adomian decomposition, the Lie symmetries theory, and the homotopy perturbation methods approach to finite difference, finite volume and finite element schemes, and spectral methods and their applications in various fields relevant to practical engineering cases. In particular, interdisciplinary approaches in civil, industrial, biomedical and ICT engineering or strong conceptual foundations in newly evolving topics are especially welcome. The primary goal of this Special Issue is to promote research that overlaps among different research fields, inviting the investigators to contribute with original research papers.

The papers could also concentrate on a comparison between novel techniques and state-of-the-art approaches by accentuating the benefits that can be obtained.

Prof. Dr. Mario Versaci
Prof. Dr. Maria Paola Speciale
Prof. Dr. Alessandra Jannelli
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. Mathematics is an international peer-reviewed open access semimonthly 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 2600 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

  • mathematical analysis and numerical techniques for technological processes
  • soft computing methodologies (fuzzy systems, neural networks, machine learning) for applications in industrial and technologies issues
  • probabilistic techniques for engineering applications

Published Papers (4 papers)

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Research

18 pages, 10647 KiB  
Article
A Dynamic Analysis for Probabilistic/Possibilistic Problems Model Reduction Analysis Using Special Functions
by Hedi Hassis, Abir Jendoubi, Lioua Kolsi and Mohamed Omri
Mathematics 2022, 10(9), 1554; https://doi.org/10.3390/math10091554 - 5 May 2022
Viewed by 1145
Abstract
Information and data in mechanics, as in many other scientific disciplines, can be certainly known with an error-safety coefficient (deterministic), random with a known probability distribution (probabilistic), or random known with an uncertainty factor in the information (possibilistic). When the information on the [...] Read more.
Information and data in mechanics, as in many other scientific disciplines, can be certainly known with an error-safety coefficient (deterministic), random with a known probability distribution (probabilistic), or random known with an uncertainty factor in the information (possibilistic). When the information on the parameters is undermined, probabilistic/possibilistic mechanical techniques attempt to provide an estimate of the solution. For various mechanical problems involving probabilistic/possibility parameters, a constraint that must be met is sometimes added, as in the case of reliability analysis. In this paper, an approach for probabilistic/possibilistic dynamic analysis is introduced and validated. In addition, its extension for finite element structural analysis is presented. Full article
(This article belongs to the Special Issue Advanced Analytical and Numerical Techniques for Technological Processes and Applications)
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26 pages, 4689 KiB  
Article
Three-Dimensional Synthesis of Manufacturing Tolerances Based on Analysis Using the Ascending Approach
by Badreddine Ayadi, Lotfi Ben Said, Mohamed Boujelbene and Sid Ali Betrouni
Mathematics 2022, 10(2), 203; https://doi.org/10.3390/math10020203 - 10 Jan 2022
Cited by 1 | Viewed by 1542
Abstract
The present paper develops a new approach for manufacturing tolerances synthesis to allow the distribution of these tolerances over the different phases concerned in machining processes using relationships written in the tolerance analysis phase that have been well developed in our previous works. [...] Read more.
The present paper develops a new approach for manufacturing tolerances synthesis to allow the distribution of these tolerances over the different phases concerned in machining processes using relationships written in the tolerance analysis phase that have been well developed in our previous works. The novelty of the proposed approach is that the treatment of non-conventional surfaces does not pose a particular problem, since the toleranced surface is discretized. Thus, it is possible to study the feasibility of a single critical requirement as an example. During the present approach, we only look for variables that influence the requirements and the others are noted F (Free). These variables can be perfectly identified on the machine, which can be applied for known and unknown machining fixtures; this can be the base for proposing a normalized ISO specification used in the different machining phases of a mechanical part. The synthesis of machining tolerances takes place in three steps: (1) Analysis of the relationship’s terms, which include the influence of three main defects; the deviation on the machined surface, defects in the machining set-up, and the influence of positioning dispersions; then (2) optimization of machining tolerance through a precise evaluation of these effects; and finally (3) the optimization of the precision of the workpiece fixture, which will give the dimensioning of the machining assembly for the tooling and will allow the machining assembly to be qualified. The approach used proved its efficiency in the end by presenting the optimal machining process drawing that explains the ordered phases needed to process the workpiece object of the case study. Full article
(This article belongs to the Special Issue Advanced Analytical and Numerical Techniques for Technological Processes and Applications)
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23 pages, 13298 KiB  
Article
Application of a Fuzzy Inference System for Optimization of an Amplifier Design
by M. Isabel Dieste-Velasco
Mathematics 2021, 9(17), 2168; https://doi.org/10.3390/math9172168 - 5 Sep 2021
Cited by 4 | Viewed by 1910
Abstract
Simulation programs are widely used in the design of analog electronic circuits to analyze their behavior and to predict the response of a circuit to variations in the circuit components. A fuzzy inference system (FIS) in combination with these simulation tools can be [...] Read more.
Simulation programs are widely used in the design of analog electronic circuits to analyze their behavior and to predict the response of a circuit to variations in the circuit components. A fuzzy inference system (FIS) in combination with these simulation tools can be applied to identify both the main and interaction effects of circuit parameters on the response variables, which can help to optimize them. This paper describes an application of fuzzy inference systems to modeling the behavior of analog electronic circuits for further optimization. First, a Monte Carlo analysis, generated from the tolerances of the circuit components, is performed. Once the Monte Carlo results are obtained for each of the response variables, the fuzzy inference systems are generated and then optimized using a particle swarm optimization (PSO) algorithm. These fuzzy inference systems are used to determine the influence of the circuit components on the response variables and to select them to optimize the amplifier design. The methodology proposed in this study can be used as the basis for optimizing the design of similar analog electronic circuits. Full article
(This article belongs to the Special Issue Advanced Analytical and Numerical Techniques for Technological Processes and Applications)
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20 pages, 1302 KiB  
Article
Trust-Region Based Penalty Barrier Algorithm for Constrained Nonlinear Programming Problems: An Application of Design of Minimum Cost Canal Sections
by Bothina El-Sobky, Yousria Abo-Elnaga, Abd Allah A. Mousa and Mohamed A. El-Shorbagy
Mathematics 2021, 9(13), 1551; https://doi.org/10.3390/math9131551 - 1 Jul 2021
Cited by 7 | Viewed by 1761
Abstract
In this paper, a penalty method is used together with a barrier method to transform a constrained nonlinear programming problem into an unconstrained nonlinear programming problem. In the proposed approach, Newton’s method is applied to the barrier Karush–Kuhn–Tucker conditions. To ensure global convergence [...] Read more.
In this paper, a penalty method is used together with a barrier method to transform a constrained nonlinear programming problem into an unconstrained nonlinear programming problem. In the proposed approach, Newton’s method is applied to the barrier Karush–Kuhn–Tucker conditions. To ensure global convergence from any starting point, a trust-region globalization strategy is used. A global convergence theory of the penalty–barrier trust-region (PBTR) algorithm is studied under four standard assumptions. The PBTR has new features; it is simpler, has rapid convergerce, and is easy to implement. Numerical simulation was performed on some benchmark problems. The proposed algorithm was implemented to find the optimal design of a canal section for minimum water loss for a triangle cross-section application. The results are promising when compared with well-known algorithms. Full article
(This article belongs to the Special Issue Advanced Analytical and Numerical Techniques for Technological Processes and Applications)
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