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27 pages, 9409 KiB

Open AccessArticle

Simulation Study of Hydrodynamic Conditions in Reaction Cell for Cement Biomineralization Using Factorial Design and Computational Fluid Dynamics: Prospects for Increased Useful Life of Concrete Structures and Energetic/Environmental Benefits

by Bruno Augusto Cabral Roque, Pedro Pinto Ferreira Brasileiro, Yana Batista Brandão, Hilario Jorge Bezerra de Lima Filho, Attilio Converti, Bahar Aliakbarian, Mohand Benachour and Leonie Asfora Sarubbo

Energies 2023, 16(8), 3597; https://doi.org/10.3390/en16083597 - 21 Apr 2023

Cited by 1 | Viewed by 1472

Abstract

Studies have reported the incorporation of microorganisms into cement to promote the formation of calcium carbonate in cracks of concrete, a process known as biomineralization. The paper aims to improve the process of the cascade system for biomineralization in cement by identifying the [...] Read more.

Studies have reported the incorporation of microorganisms into cement to promote the formation of calcium carbonate in cracks of concrete, a process known as biomineralization. The paper aims to improve the process of the cascade system for biomineralization in cement by identifying the best hydrodynamic conditions in a reaction cell in order to increase the useful life of concrete structures and, therefore, bring energy and environmental benefits. Two central composite rotatable designs were used to establish the positioning of the air inlet and outlet in the lateral or upper region of the geometry of the reaction cell. The geometries of the reaction cell were constructed in SOLIDWORKS^®, and computational fluid dynamics was performed using the Flow Simulation tool of the same software. The results were submitted to statistical analysis. The best combination of meshes for the simulation was global mesh 4 and local mesh 5. The statistical analysis applied to gas velocity and pressure revealed that air flow rate was the factor with the greatest sensitivity, with

R^{2}

values up to 99.9%. The geometry with the air outlet and inlet in the lateral region was considered to be the best option. Full article

(This article belongs to the Special Issue Valorisation of Wastes: Environmental Sustainability and Production of Biofuels by Advanced Technologies Ⅱ)

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27 pages, 7726 KiB

Open AccessArticle

Predicting Thermoelectric Power Plants Diesel/Heavy Fuel Oil Engine Fuel Consumption Using Univariate Forecasting and XGBoost Machine Learning Models

by Elias Amancio Siqueira-Filho, Maira Farias Andrade Lira, Attilio Converti, Hugo Valadares Siqueira and Carmelo J. A. Bastos-Filho

Energies 2023, 16(7), 2942; https://doi.org/10.3390/en16072942 - 23 Mar 2023

Cited by 2 | Viewed by 1774

Abstract

Monitoring and controlling thermoelectric power plants (TPPs) operational parameters have become essential to ensure system reliability, especially in emergencies. Due to system complexity, operating parameters control is often performed based on technical know-how and simplified analytical models that can result in limited observations. [...] Read more.

Monitoring and controlling thermoelectric power plants (TPPs) operational parameters have become essential to ensure system reliability, especially in emergencies. Due to system complexity, operating parameters control is often performed based on technical know-how and simplified analytical models that can result in limited observations. An alternative to this task is using time series forecasting methods that seek to generalize system characteristics based on past information. However, the analysis of these techniques on large diesel/HFO engines used in Brazilian power plants under the dispatch regime has not yet been well-explored. Therefore, given the complex characteristics of engine fuel consumption during power generation, this work aimed to investigate patterns generalization abilities when linear and nonlinear univariate forecasting models are used on a representative database related to an engine-driven generator used in a TPP located in Pernambuco, Brazil. Fuel consumption predictions based on artificial neural networks were directly compared to XGBoost regressor adaptation to perform this task as an alternative with lower computational cost. AR and ARIMA linear models were applied as a benchmark, and the PSO optimizer was used as an alternative during model adjustment. In summary, it was possible to observe that AR and ARIMA-PSO had similar performances in operations and lower error distributions during full-load power output with normal error frequency distribution of −0.03 ± 3.55 and 0.03 ± 3.78 kg/h, respectively. Despite their similarities, ARIMA-PSO achieved better adherence in capturing load adjustment periods. On the other hand, the nonlinear approaches NAR and XGBoost showed significantly better performance, achieving mean absolute error reductions of 42.37% and 30.30%, respectively, when compared with the best linear model. XGBoost modeling was 8.7 times computationally faster than NAR during training. The nonlinear models were better at capturing disturbances related to fuel consumption ramp, shut-down, and sudden fluctuations steps, despite being inferior in forecasting at full-load, especially XGBoost due to its high sensitivity with slight fuel consumption variations. Full article

(This article belongs to the Special Issue Valorisation of Wastes: Environmental Sustainability and Production of Biofuels by Advanced Technologies Ⅱ)

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24 pages, 7153 KiB

Open AccessArticle

A Novel Remaining Useful Estimation Model to Assist Asset Renewal Decisions Applied to the Brazilian Electric Sector

by Hemir da Cunha Santiago, José Carlos da Silva Cavalcanti, Ricardo Bastos Cavalcante Prudêncio, Mohamed A. Mohamed, Leonie Asfora Sarubbo, Attilio Converti and Manoel Henrique da Nóbrega Marinho

Energies 2023, 16(6), 2513; https://doi.org/10.3390/en16062513 - 7 Mar 2023

Viewed by 1075

Abstract

Assets deteriorate over time, as well as being covered, corroded, or becoming old in less obvious ways. Maintenance can extend the remaining useful life (RUL) of an asset system, but sooner or later it must surely be replaced. In this study, we propose [...] Read more.

Assets deteriorate over time, as well as being covered, corroded, or becoming old in less obvious ways. Maintenance can extend the remaining useful life (RUL) of an asset system, but sooner or later it must surely be replaced. In this study, we propose a new RUL estimation methodology to assist in decision making for the maintenance and replacement of assets from prioritizing equipment in a renovation plan. Our methodology uses advanced data analysis techniques that consider multiple competing criteria with the goal of maximizing values of the asset throughout its life cycle, while considering the rules of remuneration and service quality of the current regulation, as well as the values at risk according to the decisions and actions taken. Experimental results with real datasets show the efficiency of the proposed approach. Finally, this work also presents the development of an analytical tool to optimize asset renewal decisions applying the RUL estimation methodology proposed and its application to the Brazilian electric sector. Full article

(This article belongs to the Special Issue Valorisation of Wastes: Environmental Sustainability and Production of Biofuels by Advanced Technologies Ⅱ)

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8 pages, 748 KiB

Open AccessArticle

Producing Refuse Derived Fuel with Refining Industry Oily Sludge and Mushroom Substrates

by Chien Li Lee and Chih-Ju G. Jou

Energies 2022, 15(24), 9451; https://doi.org/10.3390/en15249451 - 13 Dec 2022

Viewed by 959

Abstract

The sludge in this study was obtained from refinery crude oil storage tanks. It contained a high proportion of hydrocarbon composition and harmful substances (such as polycyclic aromatic hydrocarbons and benzene). Through the microwave irradiation treatment process, the harmful substances were removed from [...] Read more.

The sludge in this study was obtained from refinery crude oil storage tanks. It contained a high proportion of hydrocarbon composition and harmful substances (such as polycyclic aromatic hydrocarbons and benzene). Through the microwave irradiation treatment process, the harmful substances were removed from the sludge which was then recycled and combined with agricultural waste mushroom substrates to produce refuse derived fuel (RDF). The results showed that the calorific value of RDF was 7279 cal/g when the blending ratio (wt/wt) of oil sludge and mushroom substrates was 5:5. On the other hand, when the portion of the mushroom substrates was increased, the sludge became easier to ignite with better combustion reaction. When the blending ratio (wt/wt) was changed from 8:2 to 5:5, the ignition index and comprehensive performance index were increased by 51.9 and 50.2%. Therefore, mixing the sludge with agricultural waste mushroom substrates is in line with the concept of waste recycling and circular economy. Full article

(This article belongs to the Special Issue Valorisation of Wastes: Environmental Sustainability and Production of Biofuels by Advanced Technologies Ⅱ)

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10 pages, 4003 KiB

Open AccessArticle

Hierarchical Porous Activated Carbon-Supported Ruthenium Catalysts for Catalytic Cleavage of Lignin Model Compounds

by Xuan-Tien Pham, Vy Anh Tran, Lan-Trinh Thi Tran, Tram Ngoc P. Nguyen, Thong Hoang Le, Huy Hoang, Thi-Hiep Nguyen, Khanh B. Vu and Thanh Khoa Phung

Energies 2022, 15(22), 8611; https://doi.org/10.3390/en15228611 - 17 Nov 2022

Cited by 2 | Viewed by 1658

Abstract

The catalytic conversion of lignin model compounds was performed using Ru/C catalysts and an autoclave reactor. The Ru/C catalysts were prepared by the impregnation method using highly porous homemade activated carbon and characterized by XRD, SEM, and specific surface area. The catalytic reactions [...] Read more.

The catalytic conversion of lignin model compounds was performed using Ru/C catalysts and an autoclave reactor. The Ru/C catalysts were prepared by the impregnation method using highly porous homemade activated carbon and characterized by XRD, SEM, and specific surface area. The catalytic reactions were performed in a high pressure/temperature reactor at different temperatures and with different solvents. The results showed that the novel Ru/C catalysts prepared from carbon supports activated by the KOH agent showed higher catalytic activity than the commercial catalyst. Ethanol and 2-propanol were suitable solvents for the cleavage of the β–O–4 ether bond of 2-phenoxy-1-phenyl ethanol (~65–70% conversion) over a Ru/C-KOH-2 catalyst at 220 °C in comparison to tert-butanol and 1-propanol solvents (~43–47% conversion of 2-phenoxy-1-phenyl ethanol). Also, the increase in reaction temperature from 200 °C to 240 °C enhanced the cleavage of the ether bond with an increase in phenol selectivity from 9.4% to 19.5% and improved the catalytic conversion of 2-phenoxy-1-phenyl ethanol from 46.6% to 98.5% over the Ru/C-KOH-2 catalyst and ethanol solvent. The Ru/C-KOH-2 catalyst showed outstanding conversion (98.5%) of 2-phenoxy-1-phenylethanol at 240 °C, 1 h, ethanol solvent. This novel hierarchical porous activated carbon-supported ruthenium catalyst (Ru/C-KOH-2) can be applied for the further conversion of the lignin compound. Full article

(This article belongs to the Special Issue Valorisation of Wastes: Environmental Sustainability and Production of Biofuels by Advanced Technologies Ⅱ)

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15 pages, 1484 KiB

Open AccessArticle

Framework for Optimized Analysis of Waste Bioenergy Projects

by Eliana M. A. Guerreiro, Maicon Silva, Marcio Guerreiro, Taís Carvalho, Attilio Converti, Hugo Valadares Siqueira and Cassiano Moro Piekarski

Energies 2022, 15(17), 6136; https://doi.org/10.3390/en15176136 - 24 Aug 2022

Viewed by 1226

Abstract

Over the years, cities have undergone transformations that, invariably, overload and even compromise the functioning of an energy matrix dependent on increasingly scarce resources. The high demand for energy has challenged stakeholders to invest in more sustainable alternatives, such as bioenergy, which, in [...] Read more.

Over the years, cities have undergone transformations that, invariably, overload and even compromise the functioning of an energy matrix dependent on increasingly scarce resources. The high demand for energy has challenged stakeholders to invest in more sustainable alternatives, such as bioenergy, which, in addition, helps to reduce the pressure for finite resources, enable the energy recovery of waste and contribute to the mitigation of carbon emissions. For these improvements to be successful, stakeholders need specific technological strategies, requiring tools, methods and solutions that support the decision-making process. In this perspective, the current work aimed to develop a framework optimizing the evaluation of waste bioenergy projects through the application of algorithms. Therefore, a literature review was carried out to select the algorithms and identify the sectors/areas and stages in which they are applied. These algorithms were then grouped into two sequential phases. The first targeted the evaluation of region, based on the type and supply of biomass, while the second sought to optimize aspects related to infrastructure and logistics. Both phases were concluded with the application of multi-criteria methods, thus, identifying the areas/regions with the greatest potential for implementing bioenergy projects. In general, it was observed that there are different algorithms and multi-criteria analysis methods that can be suitable in bioenergy projects. They were used to identify and select the regions with the greatest potential for bioenergy plant implementation, focusing on the type, quantity and perpetuity of biomass supply, to assess the operational efficiency of machines, equipment, processes and to optimize the logistics chain, especially the collection and transport of biomass. Thus, the joint work between the use of algorithms and multi-criteria decision methods provides greater assertiveness in choices, helping to identify the most viable projects and mitigating risks and uncertainties for decision-makers. Full article

(This article belongs to the Special Issue Valorisation of Wastes: Environmental Sustainability and Production of Biofuels by Advanced Technologies Ⅱ)

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13 pages, 3925 KiB

Open AccessArticle

Cascade System for Biomineralization in Cement: Project, Construction and Operationalization to Enhance Building Energy Efficiency

by Pedro Pinto Ferreira Brasileiro, Bruno Augusto Cabral Roque, Yana Batista Brandão, Alessandro Alberto Casazza, Attilio Converti, Mohand Benachour and Leonie Asfora Sarubbo

Energies 2022, 15(14), 5262; https://doi.org/10.3390/en15145262 - 20 Jul 2022

Cited by 3 | Viewed by 1578

Abstract

Anthropogenic and natural actions cause internal and external fractures in concrete. To recover these structures, bio-concretes have been developed with bacteria of the genus Bacillus. These microorganisms consume calcium lactate, synthesize calcium carbonate and biomineralize CaCO₃ crystals within the structures of [...] Read more.

Anthropogenic and natural actions cause internal and external fractures in concrete. To recover these structures, bio-concretes have been developed with bacteria of the genus Bacillus. These microorganisms consume calcium lactate, synthesize calcium carbonate and biomineralize CaCO₃ crystals within the structures of concrete. The aim of the present study was to construct equipment, denominated “Cascade System for Biomineralization in Cement” (CSBC), to determine the limiting velocity of the biomineralization of CaCO₃. The construction of the equipment took into consideration chemical and biochemical phenomena responsible for biomineralization. Parts made with 3D printing and a circuit with Arduino UNO R3 board were used in the assembly of the system. The prototype proved to be stable and can be considered a promising tool for future application in research of the regeneration of reinforced concreted in a practical, fast and economical way, especially to the energy sector. Full article

(This article belongs to the Special Issue Valorisation of Wastes: Environmental Sustainability and Production of Biofuels by Advanced Technologies Ⅱ)

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Review

Jump to: Research

19 pages, 2396 KiB

Open AccessReview

Self-Healing Concrete: Concepts, Energy Saving and Sustainability

by Bruno Augusto Cabral Roque, Pedro Pinto Ferreira Brasileiro, Yana Batista Brandão, Alessandro Alberto Casazza, Attilio Converti, Mohand Benachour and Leonie Asfora Sarubbo

Energies 2023, 16(4), 1650; https://doi.org/10.3390/en16041650 - 7 Feb 2023

Cited by 2 | Viewed by 4878

Abstract

The production of cement accounts for 5 to 7% of carbon dioxide emissions in the world, and its broad-scale use contributes to climate imbalance. As a solution, biotechnology enables the cultivation of bacteria and fungi for the synthesis of calcium carbonate as one [...] Read more.

The production of cement accounts for 5 to 7% of carbon dioxide emissions in the world, and its broad-scale use contributes to climate imbalance. As a solution, biotechnology enables the cultivation of bacteria and fungi for the synthesis of calcium carbonate as one of the main constituents of cement. Through biomineralization, which is the initial driving force for the synthesis of compounds compatible with concrete, and crystallization, these compounds can be delivered to cracks in concrete. Microencapsulation is a method that serves as a clock to determine when crystallization is needed, which is assisted by control factors such as pH and aeration. The present review addresses possibilities of working with bioconcrete, describing the composition of Portland cement, analysis methods, deterioration, as well as environmental and energetic benefits of using such an alternative material. A discussion on carbon credits is also offered. The contents of this paper could strengthen the prospects for the use of self-healing concrete as a way to meet the high demand for concrete, contributing to the building of a sustainable society. Full article

(This article belongs to the Special Issue Valorisation of Wastes: Environmental Sustainability and Production of Biofuels by Advanced Technologies Ⅱ)

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