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MCA
Special Issues
Numerical and Symbolic Computation: Developments and Applications 2023
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Numerical and Symbolic Computation: Developments and Applications 2023

A special issue of Mathematical and Computational Applications (ISSN 2297-8747).

Deadline for manuscript submissions: closed (31 October 2023) | Viewed by 6033

Special Issue Editors

Dr. Maria Amélia Ramos Loja

E-Mail Website
Guest Editor
1. CIMOSM—Centro de Investigação em Modelação e Otimização de Sistemas Multifuncionais, ISEL, IPL—Instituto Politécnico de Lisboa, Av. Conselheiro Emídio Navarro 1, 1959-007 Lisboa, Portugal
2. IDMEC, Instituto Superior Técnico, Universidade de Lisboa, Avenue Rovisco Pais, 1, 1049-001 Lisboa, Portugal
Interests: computational mechanics of solids; composite materials; adaptive structures; optimization; reverse engineering
Special Issues, Collections and Topics in MDPI journals
Dr. Isabel Malico

E-Mail Website
Co-Guest Editor
Department of Physics, University of Évora, Colégio Luís António Verney, Rua Romão Ramalho, 59, 7002-554 Évora, Portugal
Interests: bioenergy; energy policy; energy conversion technologies; computational fluid dynamics
Special Issues, Collections and Topics in MDPI journals
Dr. Eugénio Garção

E-Mail Website
Co-Guest Editor
Department of Physics, University of Évora, Colégio Luís António Verney, Rua Romão Ramalho, 59, 7002-554 Évora, Portugal
Interests: electromechanics of continuous media; digital image correlation; material properties estimation; material behavior; vibration analysis

Special Issue Information

Dear Colleagues,

This Special Issue will mainly consist of selected papers presented at the 6th International Conference on Numerical and Symbolic Computation: Developments and Applications (www.symcomp2023.uevora.pt). Papers considered to fit the scope of the journal and to be of sufficient quality after evaluation by the reviewers will be published free of charge.

Dr. Maria Amélia Ramos Loja
Guest Editor

Dr. Isabel Malico
Dr. Eugénio Garção
Co-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. Mathematical and Computational Applications 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 1400 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.

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Published Papers (3 papers)

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Research

16 pages, 3437 KiB  
Article
Clustering of Wind Speed Time Series as a Tool for Wind Farm Diagnosis
by Ana Alexandra Martins, Daniel C. Vaz, Tiago A. N. Silva, Margarida Cardoso and Alda Carvalho
Math. Comput. Appl. 2024, 29(3), 35; https://doi.org/10.3390/mca29030035 - 9 May 2024
Cited by 1 | Viewed by 1305
Abstract
In several industrial fields, environmental and operational data are acquired with numerous purposes, potentially generating a huge quantity of data containing valuable information for management actions. This work proposes a methodology for clustering time series based on the K-medoids algorithm using a convex [...] Read more.
In several industrial fields, environmental and operational data are acquired with numerous purposes, potentially generating a huge quantity of data containing valuable information for management actions. This work proposes a methodology for clustering time series based on the K-medoids algorithm using a convex combination of different time series correlation metrics, the COMB distance. The multidimensional scaling procedure is used to enhance the visualization of the clustering results, and a matrix plot display is proposed as an efficient visualization tool to interpret the COMB distance components. This is a general-purpose methodology that is intended to ease time series interpretation; however, due to the relevance of the field, this study explores the clustering of time series judiciously collected from data of a wind farm located on a complex terrain. Using the COMB distance for wind speed time bands, clustering exposes operational similarities and dissimilarities among neighboring turbines which are influenced by the turbines’ relative positions and terrain features and regarding the direction of oncoming wind. In a significant number of cases, clustering does not coincide with the natural geographic grouping of the turbines. A novel representation of the contributing distances—the COMB distance matrix plot—provides a quick way to compare pairs of time bands (turbines) regarding various features. Full article
(This article belongs to the Special Issue Numerical and Symbolic Computation: Developments and Applications 2023)
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22 pages, 3253 KiB  
Article
Simulation of a Thermal Recuperative Incinerator of VOCs with a Special Focus on the Heat Exchanger
by Francisco Zdanowski, Isabel Malico, Paulo Canhoto and Rui Pedro Lima
Math. Comput. Appl. 2024, 29(1), 1; https://doi.org/10.3390/mca29010001 - 23 Dec 2023
Viewed by 1732
Abstract
Simulation and modeling of thermal recuperative incinerators may play an important role in enhancing efficiency and ensuring compliance with environmental regulations. In this context, the primary objective of this study is to simulate and comprehensively understand the operation of a geometrically complex thermal [...] Read more.
Simulation and modeling of thermal recuperative incinerators may play an important role in enhancing efficiency and ensuring compliance with environmental regulations. In this context, the primary objective of this study is to simulate and comprehensively understand the operation of a geometrically complex thermal recuperative incinerator with an integrated preheater featuring varying levels of heat recovery. To achieve this objective, a simple yet effective 0D model was developed. This modeling approach allows for a holistic evaluation of the performance of the incinerator, enabling the assessment of key parameters, such as temperatures and heat transfer rates, under varying operating conditions. Successful validation of the model is established by comparing its results with measurements from an industrial thermal recuperative incinerator in operation at a vehicle assembly plant, with maximum relative differences of around 9%. Simulations for different percentages of flue gases bypassing the preheater were conducted, indicating a good compromise between heat transfer and pressure drop and a 22% heat recovery at around 50%. The model presented in this paper provides a robust foundation for comprehensively assessing and optimizing the performance of thermal recuperative incinerators and systems that comprise thermal recuperative incinerators, with implications for waste management and sustainable energy recovery systems. Full article
(This article belongs to the Special Issue Numerical and Symbolic Computation: Developments and Applications 2023)
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13 pages, 1031 KiB  
Article
A Computational Method with Maple for Finding the Maximum Curvature of a Bézier-Spline Curve
by Henk Pijls and Le Phuong Quan
Math. Comput. Appl. 2023, 28(2), 56; https://doi.org/10.3390/mca28020056 - 8 Apr 2023
Cited by 2 | Viewed by 2019
Abstract
In this paper, we propose two Maple procedures and some related utilities to determine the maximum curvature of a cubic Bézier-spline curve that interpolates an ordered set of points in R2 or R3. The procedures are designed from closed-form formulas [...] Read more.
In this paper, we propose two Maple procedures and some related utilities to determine the maximum curvature of a cubic Bézier-spline curve that interpolates an ordered set of points in R2 or R3. The procedures are designed from closed-form formulas for such open and closed curves. Full article
(This article belongs to the Special Issue Numerical and Symbolic Computation: Developments and Applications 2023)
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