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Frontier (2021): Process Engineering and Control Systems

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A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "K: State-of-the-Art Energy Related Technologies".

Deadline for manuscript submissions: closed (20 April 2022) | Viewed by 15764

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Special Issue Editor

Prof. Dr. Dagmar Janacova

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Guest Editor

Tomas Bata University in Zlin, Faculty of Applied Informatics, Nad Stranemi 4511, 76005 Zlin, Czech Republic
Interests: process engineering; process optimization; chemical engineering; control systems; modeling and simulation; mathematical modelling

Special Issue Information

Dear Colleagues,

This Special Issue will include contributions that highlight the important combination of process engineering and automatic control. The use of process engineering tools such as process optimization based on material, energy balances, mathematical modeling, and simulations, followed by the application of automatic control for streamlining and saving processes, which allow solving and implementing process engineering tasks to minimize process costs, minimize waste production, the design of new recycling technologies, and even new waste-free technologies, are of interest. Therefore, we invite contributions on innovative technical development, reviews, case studies, and analytical and evaluation contributions from various fields that are relevant in the field of process engineering and control systems.

Prof. Dr. Dagmar Janacova
Guest Editor

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. Energies 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

Process engineering
Automatic control
Control systems
Mathematic modelling
Optimization of process

Published Papers (6 papers)

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Research

12 pages, 3361 KiB

Open AccessArticle

Numerical Simulation of Gas Flow Passing through Slots of Various Shapes in Labyrinth Seals

by Vadym Baha, Natalia Lishchenko, Serhiy Vanyeyev, Jana Mižáková, Tetiana Rodymchenko and Ján Piteľ

Energies 2022, 15(9), 2971; https://doi.org/10.3390/en15092971 - 19 Apr 2022

Cited by 2 | Viewed by 1556

Abstract

Labyrinth seals are widely used in centrifugal compressors, turbines, and many other pneumatic systems due to their simplicity of design, reliability, and low cost. The calculation scheme for the movement of the working medium in a labyrinth seal is constructed by analogy with the movement of the working medium through holes with a sharp edge. Annular and flat slots, holes, and such a factor as the shaft rotation with a calculated sector of 3 degrees were studied. The purpose of the study is to determine the flow coefficient when the working medium flows through slots of various shapes. To achieve this purpose, modeling of the working medium flow in the FlowVision software was performed. The mass flow and flow coefficients are determined for the studied slot shapes. The convergence of the calculation results was determined by comparing the values of the mass flow rate at the inlet and outlet of the slot. Differences in visualizations of the flow for the studied variants of slots were established. The resulting difference should be taken into account in practical calculations of the working medium mass flow through the slot using a conditional flow rate factor which is determined by the slot design. Full article

(This article belongs to the Special Issue Frontier (2021): Process Engineering and Control Systems)

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22 pages, 9341 KiB

Open AccessFeature PaperArticle

Selected Mathematical Optimization Methods for Solving Problems of Engineering Practice

by Alena Vagaská, Miroslav Gombár and Ľuboslav Straka

Energies 2022, 15(6), 2205; https://doi.org/10.3390/en15062205 - 17 Mar 2022

Cited by 15 | Viewed by 2039

Abstract

Engineering optimization is the subject of interest for many scientific research teams on a global scale; it is a part of today’s mathematical modelling and control of processes and systems. The attention in this article is focused on optimization modelling of technological processes of surface treatment. To date, a multitude of articles are devoted to the applications of mathematical optimization methods to control technological processes, but the situation is different for surface treatment processes, especially for anodizing. We perceive their lack more, so this state has stimulated our interest, and the article contributes to filling the gap in scientific research in this area. The article deals with the application of non-linear programming (NLP) methods to optimise the process of anodic oxidation of aluminium using MATLAB toolboxes. The implementation of optimization methods is illustrated by solving a specific problem from engineering practice. The novelty of this article lies in the selection of effective approaches to the statement of optimal process conditions for anodizing. To solve this complex problem, a solving strategy based on the design of experiments approach (for five factors), exploratory data analysis, confirmatory analysis, and optimization modelling is proposed. The original results have been obtained through the experiment (performed by using the DOE approach), statistical analysis, and optimization procedure. The main contribution of this study is the developed mathematical-statistical computational (MSC) model predicting the thickness of the resulting aluminium anodic oxide layer (AOL). Based on the MSC model, the main goal has been achieved—the statement of optimal values of factors acting during the anodizing process to achieve the thickness of the protective layer required by clients, namely, for 5, 7, 10, and 15 [μm]. Full article

(This article belongs to the Special Issue Frontier (2021): Process Engineering and Control Systems)

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21 pages, 672 KiB

Open AccessArticle

A Data-Centric Machine Learning Methodology: Application on Predictive Maintenance of Wind Turbines

by Maryna Garan, Khaoula Tidriri and Iaroslav Kovalenko

Energies 2022, 15(3), 826; https://doi.org/10.3390/en15030826 - 24 Jan 2022

Cited by 15 | Viewed by 4290

Abstract

Nowadays, the energy sector is experiencing a profound transition. Among all renewable energy sources, wind energy is the most developed technology across the world. To ensure the profitability of wind turbines, it is essential to develop predictive maintenance strategies that will optimize energy production while preventing unexpected downtimes. With the huge amount of data collected every day, machine learning is seen as a key enabling approach for predictive maintenance of wind turbines. However, most of the effort is put into the optimization of the model architectures and its parameters, whereas data-related aspects are often neglected. The goal of this paper is to contribute to a better understanding of wind turbines through a data-centric machine learning methodology. In particular, we focus on the optimization of data preprocessing and feature selection steps of the machine learning pipeline. The proposed methodology is used to detect failures affecting five components on a wind farm composed of five turbines. Despite the simplicity of the used machine learning model (a decision tree), the methodology outperformed model-centric approach by improving the prediction of the remaining useful life of the wind farm, making it more reliable and contributing to the global efforts towards tackling climate change. Full article

(This article belongs to the Special Issue Frontier (2021): Process Engineering and Control Systems)

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17 pages, 2500 KiB

Open AccessArticle

Mathematical Modeling of Urea Reaction with Sulfuric Acid and Phosphoric Acid to Produce Ammonium Sulfate and Ammonium Dihydrogen Phosphate Respectively

by Juan Carlos Beltrán-Prieto and Karel Kolomazník

Energies 2021, 14(23), 8004; https://doi.org/10.3390/en14238004 - 30 Nov 2021

Cited by 1 | Viewed by 3783

Abstract

Urea is the final product of protein metabolism in mammals and can be found in different biological fluids. Use of mammalian urine in agricultural production as organic fertilizer requires safe handling to avoid the formation of ammonia that will decrease the fertilizer value due to the loss of nitrogen. Safe handling is also required to minimize the decomposition of urea into condensed products such as biuret and cyanuric acid, which will also have a negative impact on the potential sustainable production of crops and sanitation technologies. The study of thermodynamics and reaction kinetics of urea stabilization plays a key role in understanding the conditions under which undesirable compounds and impurities in urea-based fertilizers and urea-based selective catalytic reduction systems are formed. For this reason, we studied the reaction of urea in acid media to achieve urea stabilization by modeling the reaction of urea with sulfuric acid and phosphoric acid, and estimating the reaction enthalpy and adiabatic heat difference for control of the heat released from the neutralization step using Ca(OH)₂ or MgO for the safety of the process. Numerical and simulation analyses were performed by studying the effect of the surrounding temperature, the ratio of acid reagent to urea concentration, the rate of addition, and the reaction rate to estimate the required time to achieve an optimum value of urea conversion into ammonium dihydrogen phosphate or ammonium sulfate as potential technological opportunities for by-product valorization. Full conversion of urea was achieved in about 10 h for reaction rates in the order of 1 × 10⁻⁵s⁻¹ when the ratio of H₂SO₄ to CH₄N₂O was 1.5. When increasing the ratio to 10, the time required for full conversion was considerably reduced to 3 h. Full article

(This article belongs to the Special Issue Frontier (2021): Process Engineering and Control Systems)

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21 pages, 23153 KiB

Open AccessArticle

Relay Identification Using Shifting Method for PID Controller Tuning

by Milan Hofreiter

Energies 2021, 14(18), 5945; https://doi.org/10.3390/en14185945 - 18 Sep 2021

Cited by 8 | Viewed by 1609

Abstract

The aim of this study was to present a relay shifting method for relay feedback identification of dynamical systems suitable for PID controller tuning. The proposed technique uses a biased relay to determine frequency response points from a single experiment without any assumptions about a model transfer function. The method is applicable for open-loop stable, unstable, and integration processes, even with a delay, and regardless of whether they are oscillating or non-oscillating. The core of this technique was formed by the so-called relay shifting filter. In this study, the method was applied to a parameter estimation of a second-order time-delayed (SOTD) model that can describe, with acceptable accuracy, the dynamics of most processes (even with a transport delay) near the operating point. Simultaneously, a parameter setting for the PID controller was derived based on the model parameters. The applicability of the proposed method was demonstrated on various simulated processes and tested on real laboratory apparatuses. Full article

(This article belongs to the Special Issue Frontier (2021): Process Engineering and Control Systems)

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20 pages, 6199 KiB

Open AccessArticle

Evaluating the Effect of Demand Response Programs (DRPs) on Robust Optimal Sizing of Islanded Microgrids

by Mahdi Karami Darabi, Hamed Ganjeh Ganjehlou, Amirreza Jafari, Morteza Nazari-Heris, Gevork B. Gharehpetian and Mehrdad Abedi

Energies 2021, 14(18), 5750; https://doi.org/10.3390/en14185750 - 13 Sep 2021

Cited by 7 | Viewed by 1570

Abstract

A microgrid is a small-scale energy system with its own generation and storage facilities and energy management system, which includes shiftable and traditional loads. The purpose of this research is to determine the size of the microgrid through (i) investigating the effect of a shiftable demand response program (DRP) on sizing of an islanded microgrid and (ii) studying the uncertainty of power output of renewable energy sources by applying the robust optimization (RO) method. Since the RO method solves the problem for lower power outputs of renewable energy sources (RES) than the predicted values, the results obtained are pessimistic and will increase the project cost. To deal with the increment of project cost, the application of a load shifting DRP is proposed to reduce the cost. In addition, DRPs are suitable means to reduce the effects of uncertain power sources. Therefore, it is shown that a shiftable DRP is effective in reducing the overall project cost and the dependency on energy storage systems by defining different scenarios and simulating them with General Algebraic Modeling System (GAMS) software. Moreover, it is indicated that the shiftable DRP and battery state of charge have correlations with solar irradiance and wind speed, respectively. Full article

(This article belongs to the Special Issue Frontier (2021): Process Engineering and Control Systems)

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