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Energies, Volume 15, Issue 12 (June-2 2022) – 329 articles

Cover Story (view full-size image): In general, the finite element method (FEM) is used to accurately analyze the electromagnetic field characteristic of a permanent magnet generator. Various and complex models, such as overhang and bolting structures, require a characteristic analysis using 3D FEM. However, it is difficult to always reflect the 3D FEM in the initial design, where the analysis time is proportional to the complex design element. In this paper, in order to shorten the analysis time, a semi-3D characteristic analysis of the permanent magnet synchronous generator was performed by considering the overhang and bolting structures in the 2D FEM. The usability of the analysis method is evaluated in terms of the near agreement from results compared to performance. View this paper
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11 pages, 2984 KiB  
Article
Solar Energy Storage in an All-Vanadium Photoelectrochemical Cell: Structural Effect of Titania Nanocatalyst in Photoanode
by Hao Feng, Jian Liu, Ying Zhang and Dong Liu
Energies 2022, 15(12), 4508; https://doi.org/10.3390/en15124508 - 20 Jun 2022
Cited by 2 | Viewed by 1922
Abstract
Solar energy storage in the form of chemical energy is considered a promising alternative for solar energy utilization. High-performance solar energy conversion and storage significantly rely on the sufficient active surface area and the efficient transport of both reactants and charge carriers. Herein, [...] Read more.
Solar energy storage in the form of chemical energy is considered a promising alternative for solar energy utilization. High-performance solar energy conversion and storage significantly rely on the sufficient active surface area and the efficient transport of both reactants and charge carriers. Herein, the structure evolution of titania nanotube photocatalyst during the photoanode fabrication and its effect on photoelectrochemical activity in a microfluidic all-vanadium photoelectrochemical cell was investigated. Experimental results have shown that there exist opposite variation trends for the pore structure and crystallinity of the photocatalyst. With the increase in calcination temperature, the active surface area and pore volume were gradually declined while the crystallinity was significantly improved. The trade-off between the gradually deteriorated sintering and optimized crystallinity of the photocatalyst then determined the photoelectrochemical reaction efficiency. The optimal average photocurrent density and vanadium ions conversion rate emerged at an appropriate calcination temperature, where both the plentiful pores and large active surface area, as well as good crystallinity, could be ensured to promote the photoelectrochemical activity. This work reveals the structure evolution of the nanostructured photocatalyst in influencing the solar energy conversion and storage, which is useful for the structural design of the photoelectrodes in real applications. Full article
(This article belongs to the Special Issue Advances in Solar Energy and Materials)
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19 pages, 2335 KiB  
Article
Immobilization of Zn and Cu in Conditions of Reduced C/N Ratio during Sewage Sludge Composting Process
by Aleksandra Leśniańska, Beata Janowska and Robert Sidełko
Energies 2022, 15(12), 4507; https://doi.org/10.3390/en15124507 - 20 Jun 2022
Cited by 5 | Viewed by 1474
Abstract
In this paper we present results of research on the transformation of chemical forms of two elements (Cu, Zn) that occurred at the highest concentration in sewage sludge being processed in a composting process. The factor that had impact on the direction of [...] Read more.
In this paper we present results of research on the transformation of chemical forms of two elements (Cu, Zn) that occurred at the highest concentration in sewage sludge being processed in a composting process. The factor that had impact on the direction of the observed transformation was the amount of straw added to the mix with sewage sludge at the batch preparation stage including elimination of an additional source of organic carbon (straw). The analysis of contents of Cu and Zn chemical forms was performed applying Tessiere’s methodology. It was ascertained that reduction of supplementation has positive impact on the allocation of tested elements in organic (IV) and residual (V) fractions with a simultaneous decrease of heavy metals mobile forms share in bioavailable fractions, mostly ion exchangeable (I) and carbonate (II). Using an artificial neural network (ANN), a tool was developed to classify composts based on Austrian standards taking into account only I ÷ IV fractions treated as a labile, potentially bioavailable, part of heavy metals bound in various chemical forms in compost. The independent variables that were predictors in the ANN model were the composting time, C/N, and total content of the given element (total Cu, Zn). The sensitivity coefficients for three applied predictors varied around 1, which proves their significant impact on the final result. Correctness of the predictions of the generated network featuring an MLP 3-5-3 structure for the test set was 100%. Full article
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15 pages, 6088 KiB  
Article
Numerical Investigation of the Pre-Chamber and Nozzle Design in the Gasoline Engine of an Agricultural Tractor
by Bowen Zheng, Quan Zhou, Zhenghe Song, Enrong Mao, Zhenhao Luo, Xuedong Shao, Yuxi Liu and Wenjie Li
Energies 2022, 15(12), 4506; https://doi.org/10.3390/en15124506 - 20 Jun 2022
Viewed by 1444
Abstract
With the rapid development of agriculture in China today, the demand for agricultural machinery is rapidly increasing. A large amount of exhaust gas emissions poses a severe threat to the environment. To better promote engine fuel and air mixing, enhance engine performance, and [...] Read more.
With the rapid development of agriculture in China today, the demand for agricultural machinery is rapidly increasing. A large amount of exhaust gas emissions poses a severe threat to the environment. To better promote engine fuel and air mixing, enhance engine performance, and achieve low emissions, we conducted a numerical study of the pre-chamber and nozzle design in a gasoline engine for an agricultural tractor by using the G-equation method in Converge CFD software. The relevant optimization of the three model parameters in the G-equation was performed using the improved particle swarm algorithm (PSO). The model parameters after optimization by the PSO algorithm were: a1=0.77, b1=2.0, b3=1.0. It was confirmed that the predicted engine performance was enhanced greatly with the pre-chamber system. More importantly, the results reveal that the volume and area ratios of the pre-chamber played a crucial role in the performance of the pre-chamber. Through a series of parametric studies on the pre-chamber and main chamber characteristics, we can identify the best sets of volume and area ratios based on the combustion reaction progress, the turbulent mixing profiles, and the exhaust gas emission. The turbulent maximum strength and the exhaust gas concentration of nitrogen oxides can differ by 13 and 18 times, respectively. In practical design, we recommend the optimization of the concerned metrics with the findings in the paper. Full article
(This article belongs to the Special Issue Experiments and Simulations of Combustion Process)
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21 pages, 5562 KiB  
Article
Full-Scale Demonstration of Combined Ground Source Heating and Sustainable Urban Drainage in Roadbeds
by Søren Erbs Poulsen, Theis Raaschou Andersen and Karl Woldum Tordrup
Energies 2022, 15(12), 4505; https://doi.org/10.3390/en15124505 - 20 Jun 2022
Cited by 1 | Viewed by 1632
Abstract
This paper proposes and demonstrates, in full scale, a novel type of energy geostructure (“the Climate Road”) that combines a ground-source heat pump (GSHP) with a sustainable urban drainage system (SUDS) by utilizing the gravel roadbed simultaneously as an energy source and a [...] Read more.
This paper proposes and demonstrates, in full scale, a novel type of energy geostructure (“the Climate Road”) that combines a ground-source heat pump (GSHP) with a sustainable urban drainage system (SUDS) by utilizing the gravel roadbed simultaneously as an energy source and a rainwater retarding basin. The Climate Road measures 50 m × 8 m × 1 m (length, width, depth, respectively) and has 800 m of geothermal piping embedded in the roadbed, serving as the heat collector for a GSHP that supplies a nearby kindergarten with domestic hot water and space heating. Model analysis of operational data from 2018–2021 indicates sustainable annual heat production levels of around 0.6 MWh per meter road, with a COP of 2.9–3.1. The continued infiltration of rainwater into the roadbed increases the amount of extractable heat by an estimated 17% compared to the case of zero infiltration. Using the developed model for scenario analysis, we find that draining rainwater from three single-family houses and storing 30% of the annual heating consumption in the roadbed increases the predicted extractable energy by 56% compared to zero infiltration with no seasonal energy storage. The Climate Road is capable of supplying three new single-family houses with heating, cooling, and rainwater management year-round. Full article
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13 pages, 3449 KiB  
Article
Carbon-Neutral Cellular Network Operation Based on Deep Reinforcement Learning
by Hojin Kim, Jaewoo So and Hongseok Kim
Energies 2022, 15(12), 4504; https://doi.org/10.3390/en15124504 - 20 Jun 2022
Viewed by 1416
Abstract
With the exponential growth of traffic demand, ultra-dense networks have been proposed to cope with such demand. However, the increase of the network density causes more power use, and carbon neutrality becomes an important concept to decrease the emission and production of carbon. [...] Read more.
With the exponential growth of traffic demand, ultra-dense networks have been proposed to cope with such demand. However, the increase of the network density causes more power use, and carbon neutrality becomes an important concept to decrease the emission and production of carbon. In cellular networks, emission and production can be directly related to power consumption. In this paper, we aim to achieve carbon neutrality, as well as maximize network capacity with given power constraints. We assume that base stations have their own renewable energy sources to generate power. For carbon neutrality, we control the power consumption for base stations by adjusting the transmission power and switching off base stations to balance the generated power. Given such power constraints, our goal is to maximize the network capacity or the rate achievable for the users. To this end, we carefully design the objective function and then propose an efficient Deep Deterministic Policy Gradient (DDPG) algorithm to maximize the objective. A simulation is conducted to validate the benefits of the proposed method. Extensive simulations show that the proposed method can achieve carbon neutrality and provide a better rate than other baseline schemes. Specifically, up to a 63% gain in the reward value was observed in the DDPG algorithm compared to other baseline schemes. Full article
(This article belongs to the Special Issue Green Economics and Sustainable Management of Energy Sources)
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18 pages, 3478 KiB  
Article
A Simplified Solution Method for End-of-Term Storage Energy Maximization Model of Cascaded Reservoirs
by Xinyu Wu, Ruixiang Cheng and Chuntian Cheng
Energies 2022, 15(12), 4503; https://doi.org/10.3390/en15124503 - 20 Jun 2022
Viewed by 1237
Abstract
In medium-term scheduling, the end-of-term storage energy maximization model is proposed to create conditions for the safety, stability and economic operation of the hydropower system after control term, which satisfies the system load demand undertaken by the cascaded system in a given scheduling [...] Read more.
In medium-term scheduling, the end-of-term storage energy maximization model is proposed to create conditions for the safety, stability and economic operation of the hydropower system after control term, which satisfies the system load demand undertaken by the cascaded system in a given scheduling period. This paper presents a simplified solution method based on the Lagrangian relaxation method (LR) to solve the end-of-term storage energy maximization model. The original Lagrange dual problem with multiple Lagrange multipliers is converted to that with only one Lagrange multiplier by an entropy-based aggregate function method, which relaxes the complex cascaded hydropower system load balance constraints. The subgradient method and successive approximation of dynamic programming (DPSA) are adopted to update the Lagrange multiplier iteratively and solve the subproblem of the Lagrange dual problem, respectively. The Wujiang cascaded hydropower system is studied, and the result shows that the simplified solution method for the end-of-term storage energy maximization model both improves solving efficiency and ensures solving accuracy to a great extent. Full article
(This article belongs to the Section L: Energy Sources)
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30 pages, 3790 KiB  
Article
Evaluation of Alternatives for Energy Supply from Fuel Cells in Compact Cities in the Mediterranean Climate; Case Study: City of Valencia
by Irene Martínez Reverte, Tomás Gómez-Navarro, Carlos Sánchez-Díaz and Carla Montagud Montalvá
Energies 2022, 15(12), 4502; https://doi.org/10.3390/en15124502 - 20 Jun 2022
Cited by 1 | Viewed by 1717
Abstract
A study of energy supply alternatives was carried out based on a cogeneration fuel cell system fed from the natural gas network of compact Mediterranean cities. As a case study it was applied to the residential energy demands of the L’Illa Perduda neighbourhood, [...] Read more.
A study of energy supply alternatives was carried out based on a cogeneration fuel cell system fed from the natural gas network of compact Mediterranean cities. As a case study it was applied to the residential energy demands of the L’Illa Perduda neighbourhood, located in the east of the city of Valencia and consisting of 4194 residential cells. In total, eight different alternatives were studied according to the load curve, the power of the system, the mode of operation and the distribution of the fuel cells. In this way, the advantages and disadvantages of each configuration were found. This information, together with the previous study of the energy characteristics of the neighbourhood, enabled selection of the most promising configuration and to decide whether or not to recommend investment. The chosen configuration was a centralised system of phosphoric acid fuel cells in cogeneration, with approximately 4 MW of thermal power and an operating mode that varied according to the outside temperature. In this way, when heating is required, the plant adjusts its production to the thermal demand, and when cooling is required, the plant follows the electrical demand. This configuration presented the best energy results, as it achieved good coverage of thermal (62.5%) and electrical (88.1%) demands with good primary energy savings (28.36 GWh/year). However, due to the high power of the system and low maturity (i.e., high costs) of this technology, would be necessary to make a large initial economic investment of 15.2 M€. Full article
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15 pages, 8734 KiB  
Article
Application of Machine Learning for Lithofacies Prediction and Cluster Analysis Approach to Identify Rock Type
by Mazahir Hussain, Shuang Liu, Umar Ashraf, Muhammad Ali, Wakeel Hussain, Nafees Ali and Aqsa Anees
Energies 2022, 15(12), 4501; https://doi.org/10.3390/en15124501 - 20 Jun 2022
Cited by 27 | Viewed by 3001
Abstract
Nowadays, there are significant issues in the classification of lithofacies and the identification of rock types in particular. Zamzama gas field demonstrates the complex nature of lithofacies due to the heterogeneous nature of the reservoir formation, while it is quite challenging to identify [...] Read more.
Nowadays, there are significant issues in the classification of lithofacies and the identification of rock types in particular. Zamzama gas field demonstrates the complex nature of lithofacies due to the heterogeneous nature of the reservoir formation, while it is quite challenging to identify the lithofacies. Using our machine learning approach and cluster analysis, we can not only resolve these difficulties, but also minimize their time-consuming aspects and provide an accurate result even when the user is inexperienced. To constrain accurate reservoir models, rock type identification is a critical step in reservoir characterization. Many empirical and statistical methodologies have been established based on the effect of rock type on reservoir performance. Only well-logged data are provided, and no cores are sampled. Given these circumstances, and the fact that traditional methods such as regression are intractable, we have chosen to apply three strategies: (1) using a self-organizing map (SOM) to arrange depth intervals with similar facies into clusters; (2) clustering to split various facies into specific zones; and (3) the cluster analysis technique is used to identify rock type. In the Zamzama gas field, SOM and cluster analysis techniques discovered four group of facies, each of which was internally comparable in petrophysical properties but distinct from the others. Gamma Ray (GR), Effective Porosity(eff), Permeability (Perm) and Water Saturation (Sw) are used to generate these results. The findings and behavior of four facies shows that facies-01 and facies-02 have good characteristics for acting as gas-bearing sediments, whereas facies-03 and facies-04 are non-reservoir sediments. The outcomes of this study stated that facies-01 is an excellent rock-type zone in the reservoir of the Zamzama gas field. Full article
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12 pages, 2578 KiB  
Article
Employing GMDH-Type Neural Network and Signal Frequency Feature Extraction Approaches for Detection of Scale Thickness inside Oil Pipelines
by Abdullah M. Iliyasu, Abdulilah Mohammad Mayet, Robert Hanus, Ahmed A. Abd El-Latif and Ahmed S. Salama
Energies 2022, 15(12), 4500; https://doi.org/10.3390/en15124500 - 20 Jun 2022
Cited by 11 | Viewed by 1690
Abstract
In this paper, gamma attenuation has been utilised as a veritable tool for non-invasive estimation of the thickness of scale deposits. By simulating flow regimes at six volume percentages and seven scale thicknesses of a two phase-flow in a pipe, our study utilised [...] Read more.
In this paper, gamma attenuation has been utilised as a veritable tool for non-invasive estimation of the thickness of scale deposits. By simulating flow regimes at six volume percentages and seven scale thicknesses of a two phase-flow in a pipe, our study utilised a dual-energy gamma source with Ba-133 and Cs-137 radioisotopes, a steel pipe, and a 2.54 cm × 2.54 cm sodium iodide (NaI) photon detector to analyse three different flow regimes. We employed Fourier transform and frequency characteristics (specifically, the amplitudes of the first to fourth dominant frequencies) to transform the received signals to the frequency domain, and subsequently to extract the various features of the signal. These features were then used as inputs for the group method for data Hiding (GMDH) neural network framework used to predict the scale thickness inside the pipe. Due to the use of appropriate features, our proposed technique recorded an average root mean square error (RMSE) of 0.22, which is a very good error compared to the detection systems presented in previous studies. Moreover, this performance is indicative of the utility of our GMDH neural network extraction process and its potential applications in determining parameters such as type of flow regime, volume percentage, etc. in multiphase flows and across other areas of the oil and gas industry. Full article
(This article belongs to the Special Issue The Optimization of Well Testing Operations for Oil and Gas Field)
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31 pages, 16470 KiB  
Article
Simulative Study to Reduce DC-Link Capacitor of Drive Train for Electric Vehicles
by Osama Majeed Butt, Tallal Majeed Butt, Muhammad Husnain Ashfaq, Muhammad Talha, Siti Rohani Sheikh Raihan and Muhammad Majid Hussain
Energies 2022, 15(12), 4499; https://doi.org/10.3390/en15124499 - 20 Jun 2022
Cited by 3 | Viewed by 2213
Abstract
E-mobility is an emerging means of transportation, mainly due to the environmental impact of petroleum-based fuel vehicles and oil prices’ peak. However, electric vehicles face several challenges by the nature of technology. Consequently, electric vehicles have a limited travel range and are extremely [...] Read more.
E-mobility is an emerging means of transportation, mainly due to the environmental impact of petroleum-based fuel vehicles and oil prices’ peak. However, electric vehicles face several challenges by the nature of technology. Consequently, electric vehicles have a limited travel range and are extremely heavy. In this research, an investigation is carried out on different measures to reduce the DC-link capacitor size in the drive train of an electric vehicle. The investigation is based on software simulations. The DC-link capacitor must be dimensioned with regards to relevant points of operation, which are defined by the rotation speed and torque of the motor as well as the available DC-link voltage. This also includes the field-oriented control (FOC). In order to optimally operate a three-phase inverter in the electric drive train, a suitable type and sizing of the capacitor was studied based on mathematical equations and simulations. Two measures were examined in this study: firstly, an auxiliary passive notch filter introduced in the electric drive train circuit is explored. Based on this measure, an advanced modulation scheme exploiting the control of individual currents within segmented windings of the PMSM is investigated in detail. It was seen that saw-tooth carrier modulation used in the parallel three-phase inverter is found to reduce DC-link capacitor size in the electric drive train circuit by 70%. Full article
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18 pages, 11709 KiB  
Article
Sedimentary Basin Water and Energy Storage: A Low Environmental Impact Option for the Bananal Basin
by Julian David Hunt, Andreas Nascimento, Oldrich Joel Romero Guzman, Gilton Carlos de Andrade Furtado, Carla Schwengber ten Caten, Fernanda Munari Caputo Tomé, Walter Leal Filho, Bojan Đurin, Maurício Lopes and Yoshihide Wada
Energies 2022, 15(12), 4498; https://doi.org/10.3390/en15124498 - 20 Jun 2022
Cited by 2 | Viewed by 1625
Abstract
Groundwater storage is an important water management solution that is overlooked by several countries worldwide. This paper evaluates the potential for storing water in the Bananal sedimentary basin and proposes the construction of canals to reduce sediment obstructions in the river flow and [...] Read more.
Groundwater storage is an important water management solution that is overlooked by several countries worldwide. This paper evaluates the potential for storing water in the Bananal sedimentary basin and proposes the construction of canals to reduce sediment obstructions in the river flow and harmful flood events. This would allow for better control of the water level. The water stored in the sedimentary basin can be used as a climate change adaptation measure to ensure that the level of the flood plain is maintained high during a drought or low during an intense flood event. Additionally, the flood plain will function as a water reservoir, regulate the river flow downstream from the flood plain, and enhance hydropower generation. A significantly smaller reservoir area is expected to store water, as the water will be stored as groundwater in the sedimentary basin. Results show that the Bananal basin has the potential to store up to 49 km3 of water, which can add up to 11.7 TWh of energy storage to the Brazilian energy matrix for a CAPEX energy storage cost of 0.095 USD/kWh. This is an interesting solution for the Araguaia basin and several other basins worldwide. Full article
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26 pages, 11208 KiB  
Article
Digital Twin and Cloud BIM-XR Platform Development: From Scan-to-BIM-to-DT Process to a 4D Multi-User Live App to Improve Building Comfort, Efficiency and Costs
by Fabrizio Banfi, Raffaella Brumana, Graziano Salvalai and Mattia Previtali
Energies 2022, 15(12), 4497; https://doi.org/10.3390/en15124497 - 20 Jun 2022
Cited by 14 | Viewed by 3650
Abstract
Digital twins (DTs) and building information modelling (BIM) are proving to be valuable tools for managing the entire life cycle of a building (LCB), from the early design stages to management and maintenance over time. On the other hand, BIM platforms cannot manage [...] Read more.
Digital twins (DTs) and building information modelling (BIM) are proving to be valuable tools for managing the entire life cycle of a building (LCB), from the early design stages to management and maintenance over time. On the other hand, BIM platforms cannot manage the geometric complexities of existing buildings and the large amount of information that sensors can collect. For this reason, this research proposes a scan-to-BIM process capable of managing high levels of detail (LODs) and information (LOIs) during the design, construction site management, and construction phases. Specific grades of generation (GOGs) were applied to create as-found, as-designed, and as-built models that interact with and support the rehabilitation project of a multi-level residential building. Furthermore, thanks to the sharing of specific APIs (Revit and Autodesk Forge APIs), it was possible to switch from static representations to novel levels of interoperability and interactivity for the user and more advanced forms of building management such as a DT, a BIM cloud, and an extended reality (XR) web platform. Finally, the development of a live app shows how different types of users (professionals and non-expert) can interact with the DT, in order to know the characteristics with which the environments have been designed, as well as the environmental parameters, increasing their degree of control, from the point of view of improving comfort, use, costs, behaviour, and good practices. Finally, the overall approach was verified through a real case study where the BIM-XR platform was built for energy improvements to existing buildings and façade renovations. Full article
(This article belongs to the Special Issue Algorithm and Intelligence for Optimizing Urban/Building Morphology)
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16 pages, 4789 KiB  
Article
A Novel Prediction Model of the Drag Coefficient of Shale Cuttings in Herschel–Bulkley Fluid
by Xiaofeng Sun, Minghao Sun and Zijian Li
Energies 2022, 15(12), 4496; https://doi.org/10.3390/en15124496 - 20 Jun 2022
Cited by 5 | Viewed by 1818
Abstract
In the drilling industry, it is of great significance to accurately predict the drag coefficient and settling velocity of drill cuttings falling in the non-Newtonian drilling fluid. However, the irregular shape of drill cuttings and the non-Newtonian rheological properties of drilling fluid (e.g., [...] Read more.
In the drilling industry, it is of great significance to accurately predict the drag coefficient and settling velocity of drill cuttings falling in the non-Newtonian drilling fluid. However, the irregular shape of drill cuttings and the non-Newtonian rheological properties of drilling fluid (e.g., shear-thinning and yield stress behavior) make it challenging to predict the settling velocity. In this study, the velocity of particle settlement was studied by a visual device and high-speed camera system. Experimental data of the free settlement of 224 irregular drilling cuttings and 105 spherical particles in the Herschel–Bulkley fluid were obtained. A mechanical model dependent on the force balance of settlement particles was adopted to conduct a detailed statistical analysis of the experimental results, and a prediction model of the drag coefficient of spherical particles in the Herschel–Bulkley fluid was established. A two-dimensional shape description parameter is introduced to establish a model for predicting the drag coefficient of irregular-shaped cuttings in a Herschel–Bulkley fluid. The model has high prediction accuracy for the settling velocity of irregular shale cuttings in Herschel–Bulkley fluid. The average relative error is 7.14%, verifying the model’s accuracy. Full article
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20 pages, 2924 KiB  
Article
Carbon Capture Utilisation and Storage Technology Development in a Region with High CO2 Emissions and Low Storage Potential—A Case Study of Upper Silesia in Poland
by Anna Śliwińska, Aleksandra Strugała-Wilczek, Piotr Krawczyk, Agnieszka Leśniak, Tomasz Urych, Jarosław Chećko and Krzysztof Stańczyk
Energies 2022, 15(12), 4495; https://doi.org/10.3390/en15124495 - 20 Jun 2022
Cited by 2 | Viewed by 2442
Abstract
The region of Upper Silesia, located in southern Poland, is characterised by very high emissions of carbon dioxide into the air—the annual emission exceeds 33 Mt CO2 and the emission ‘per capita’ is 7.2 t/y in comparison to the EU average emission [...] Read more.
The region of Upper Silesia, located in southern Poland, is characterised by very high emissions of carbon dioxide into the air—the annual emission exceeds 33 Mt CO2 and the emission ‘per capita’ is 7.2 t/y in comparison to the EU average emission per capita 6.4 t/y and 8.4 t/y for Poland in 2019. Although in the region there are over 100 carbon dioxide emitters covered by the EU ETS, over 90% of emissions come from approximately 15 large hard coal power plants and from the coke and metallurgical complex. The CCUS scenario for Upper Silesia, which encompasses emitters, capture plants, transport routes, as well as utilisation and storage sites until 2050, was developed. The baseline scenario assumes capture of carbon dioxide in seven installations, use in two methanol plants and transport and injection into two deep saline aquifers (DSA). The share of captured CO2 from flue gas was assumed at the level of 0.25–0.9, depending mainly on the limited capacity of storage. To recognise the views of society on development of the CCUS technologies in Upper Silesia, thirteen interviews with different types of stakeholders (industry, research and education, policy makers) were conducted. The respondents evaluated CCU much better than CCS. The techno-economic assessment of CCUS carried out on a scenario basis showed that the economic outcome of the scenario with CCUS is EUR 3807.19 million more favourable compared to the scenario without CO2 capture and storage. Full article
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26 pages, 6543 KiB  
Review
Global Research Trends on Building Indoor Environmental Quality Modelling and Indexing Systems—A Scientometric Review
by Soheil Roumi, Fan Zhang and Rodney A. Stewart
Energies 2022, 15(12), 4494; https://doi.org/10.3390/en15124494 - 20 Jun 2022
Cited by 5 | Viewed by 2175
Abstract
The purpose of this study is to provide a holistic review of two decades of research advancement in the indoor environmental quality modelling and indexing field (IEQMI) using bibliometric analysis methods. The explicit objectives of the present study are: (1) identifying researchers, institutions, [...] Read more.
The purpose of this study is to provide a holistic review of two decades of research advancement in the indoor environmental quality modelling and indexing field (IEQMI) using bibliometric analysis methods. The explicit objectives of the present study are: (1) identifying researchers, institutions, countries (territories), and journals with the most influence in the IEQMI topic; (2) investigating the hot topics in the IEQMI field; and (3) thematically analysing the keyword evolution in the IEQMI field. A scientometric review was conducted using the bibliometric data of 456 IEQMI research articles published in the past two decades. VOSviewer software was employed for bibliometric analysis, and the SciMAT tool was used to investigate the keywords’ thematic evolution in three sub-periods (2004–2009; 2010–2015; 2016–2021). Results show that there is a continuous increment in the number of published papers in the field of IEQMI, and 60 out of 193 countries in the world have been involved in IEQMI studies. The IEQMI research mainly focuses on: (a) thermal comfort and energy efficiency; (b) occupant satisfaction and comfort; (c) IAQ and health issues; (d) methods and procedures. This field has undergone significant evolution. While ‘indoor environmental quality was initially the only theme in the first period’, ‘occupant satisfaction’, ‘buildings’, ‘impact’, ‘building information modelling’, and ‘health’ were added as the main thematic areas in the second period; ‘occupant behaviour’ and ‘energy’ were novel themes in IEQMI studies receiving much attention in the third period. Full article
(This article belongs to the Special Issue Energy Performance, Management and Recovery in Buildings)
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24 pages, 4142 KiB  
Article
Energy Assessment of the Thermal Bridging Effects on Different Structural Envelope Types Using Mixed-Equivalent-Wall Method
by Hameed Al-Awadi, Ali Alajmi and Hosny Abou-Ziyan
Energies 2022, 15(12), 4493; https://doi.org/10.3390/en15124493 - 20 Jun 2022
Cited by 2 | Viewed by 1445
Abstract
In this paper, the effect of house envelopes including thermal bridges on the daily, monthly, and annual consumption of the air conditioning system of a detached house and an attached house, with a façade in the east, west, north, or south direction, is [...] Read more.
In this paper, the effect of house envelopes including thermal bridges on the daily, monthly, and annual consumption of the air conditioning system of a detached house and an attached house, with a façade in the east, west, north, or south direction, is investigated; moreover, the capacity of the air conditioning system is calculated for detached and attached houses based on the maximum hourly peak load during severe weather conditions. The four tested house envelopes are exterior insulation and finish system (EIFS), autoclaved aerated concrete block (AAC-B), classical (cement blocks with insulation in between), and AAC column and beam (AAC-CB). The work is conducted using a method that combines the finite element method (COMSOL Multiphysics), building simulation (EnergyPlus), and the Engineering Equation Solver (EES) programs. The results indicated that the annual consumption of the air conditioning system using AAC-B, classical, and AAC-CB envelopes is larger than that of EIFS by about 3.74, 11.53, and 20.70% for the detached house, and 1.8, 2.9%, and 6.7% for the attached house, respectively. The annual consumption of the air conditioner of the detached house is larger than the average consumption of the attached house by about 25.3, 27.7, 35.8, and 41.7% for EIFS, AAC-B, classical, and AAC-CB house envelopes, respectively. Using the different façade directions of the attached house, the average effect of the house envelope type on the air conditioning system capacity is about 8.84%, with a standard deviation of 0.466%. Full article
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21 pages, 6102 KiB  
Article
Ultra-Short-Term Wind Speed Forecasting Using the Hybrid Model of Subseries Reconstruction and Broad Learning System
by Ming Pang, Lei Zhang, Yajun Zhang, Ao Zhou, Jianming Dou and Zhepeng Deng
Energies 2022, 15(12), 4492; https://doi.org/10.3390/en15124492 - 20 Jun 2022
Cited by 1 | Viewed by 1332
Abstract
The traditional decomposition–combination wind speed forecasting model has high complexity and a long calculation time. As a result, an ultra-short-term wind speed hybrid forecasting model based on a broad learning system (BLS) that combines improved variational mode decomposition (EPSO-VMD, EVMD) and subseries reconstruction [...] Read more.
The traditional decomposition–combination wind speed forecasting model has high complexity and a long calculation time. As a result, an ultra-short-term wind speed hybrid forecasting model based on a broad learning system (BLS) that combines improved variational mode decomposition (EPSO-VMD, EVMD) and subseries reconstruction (SR) is proposed in this work. The values of K and α in the EVMD are determined by minimum mean envelope entropy (MMEE) and enhanced particle swarm optimization (EPSO), and EVMD is used to decompose the original wind speed data. SR is applied to recombine the subseries obtained by EVMD to improve the forecasting efficiency. The sample entropy (SE) is used to quantify the subseries’ complexity, and they are then adaptively divided into high-entropy and low-entropy subseries. Adjacent high-entropy subseries of approximate entropy values are merged to obtain a new group of reconstructed high-entropy subseries, while the low-entropy subseries merge into a new subseries as well. Then, the forecasting results of the reconstructed high- and low-entropy subseries are calculated via the BLS and ARIMA models. Numerical simulation results show that the proposed method is more effective than traditional methods. Full article
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16 pages, 1126 KiB  
Article
The Sense and Non-Sense of PEDs—Feeding Back Practical Experiences of Positive Energy District Demonstrators into the European PED Framework Definition Development Process
by Han Vandevyvere, Dirk Ahlers and Annemie Wyckmans
Energies 2022, 15(12), 4491; https://doi.org/10.3390/en15124491 - 20 Jun 2022
Cited by 9 | Viewed by 3148
Abstract
This article discusses early developments of the Positive Energy District (PED) concept, both in terms of its definition and of its implementation in real world demonstrators. Based on the specific challenges for creating an operational definition for the European +CityxChange project, the feasibility [...] Read more.
This article discusses early developments of the Positive Energy District (PED) concept, both in terms of its definition and of its implementation in real world demonstrators. Based on the specific challenges for creating an operational definition for the European +CityxChange project, the feasibility of creating a PED was practically explored by identifying 4 possible subtypes that respond to varying constraints regarding the energy balance of the PED. This article provides the context and describes these 4 ambitions levels: PEDautonomous, PEDdynamic, PEDvirtual, and PrePED; and the 3 boundary modes: geographical, functional, and virtual. The work thus expands on the first general PED definitions as they were put forward in the SET-plan and by the European Commission, while allowing a better response to the specific boundary conditions of PEDs’ physical context. As such, it provides an operational, city-focused, bottom-up PED definition. The present study analyses how these efforts connect to current work being performed on the development of a European PED Framework Definition. In the latter, new elements such as context factors are introduced in order to account for the varying boundary conditions that PEDs must address, and in particular the difficulties of realising PEDs in existing and densely built-up urban areas. Hereby it can be argued that the approach with 4 subtypes is a bottom-up method of addressing the same challenges as a context factor based approach operating in a top-down manner, this time starting from the regional or national renewable energy potentials. Both approaches indeed strive towards an optimum setup of PEDs both within their geographical boundaries and in their interactions with the surrounding energy infrastructures and cities. These efforts are instrumental in helping to prevent that a PED is being regarded as a goal in se, functionally disconnected from its surroundings. There are strong arguments in favour of handling PEDs as building blocks for the broader realisation of carbon neutral cities and regions, thus contributing to the systemic change that is needed to futureproof the built environment as a whole. Without applying this integrating perspective, PEDs risk creating a sub-optimal lock-in within their sites and thus remain one-off experiments, lacking connection to the wider urban sustainability strategies that are needed to properly address today’s energy and climate emergencies. This holds even more when considering the quality-related requirements that come with sustainable urban design and governance. Therefore, this study further explores how PEDs can fully support such a deep urban sustainability transition, and what could consequently be the next steps towards successful and upscaled PED deployment. Full article
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24 pages, 1738 KiB  
Review
Opportunities for Using Analytical Hierarchy Process in Green Building Optimization
by Ghada Elshafei, Dušan Katunský, Martina Zeleňáková and Abdelazim Negm
Energies 2022, 15(12), 4490; https://doi.org/10.3390/en15124490 - 20 Jun 2022
Cited by 11 | Viewed by 3148
Abstract
The adoption of green building technology has become significant for ensuring sustainable development; it has become the main step to a sustainable future. The designs for green buildings include finding a balance between comfortable home construction and a sustainable environment. Moreover, the application [...] Read more.
The adoption of green building technology has become significant for ensuring sustainable development; it has become the main step to a sustainable future. The designs for green buildings include finding a balance between comfortable home construction and a sustainable environment. Moreover, the application of emerging technology is also used to supplement existing methods in the development of greener buildings to preserve a sustainable built environment. The main problem of this research is how to tackle the environmental parameters balance based on new techniques that are being used for green building optimization. To mitigate the cumulative effect of the constructed climate on human wellbeing and the regular ecosystem, the most popular goals for green buildings should be planned. This can be achieved by efficient use of natural resources such as energy, water, and other resources and minimizing waste. This will contribute to the security of occupant health, enhancement of work performance, emissions control, and improvement of the environment. In the construction of green buildings, several criteria that may contradict, interrelated indistinct and of qualitative and/or quantitative environment are broadened to utilize. This paper provides a detailed state of the art analysis on improving existing practices in green architecture/building using analytical hierarchy process (AHP) techniques to tackle the environmental balancing values based on optimal strategies and designs by green solutions to help make the best possible option from numerous options. Full article
(This article belongs to the Special Issue Green Buildings for Carbon Neutral)
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20 pages, 7859 KiB  
Article
Performance Evaluation of Convolutional Auto Encoders for the Reconstruction of Li-Ion Battery Electrode Microstructure
by Mona Faraji Niri, Jimiama Mafeni Mase and James Marco
Energies 2022, 15(12), 4489; https://doi.org/10.3390/en15124489 - 20 Jun 2022
Cited by 8 | Viewed by 1702
Abstract
Li-ion batteries play a critical role in the transition to a net-zero future. The discovery of new materials and the design of novel microstructures for battery electrodes is necessary for the acceleration of this transition. The battery electrode microstructure can potentially reveal the [...] Read more.
Li-ion batteries play a critical role in the transition to a net-zero future. The discovery of new materials and the design of novel microstructures for battery electrodes is necessary for the acceleration of this transition. The battery electrode microstructure can potentially reveal the cells’ electrochemical characteristics in great detail. However, revealing this relation is very challenging due to the high dimensionality of the problem and the large number of microstructure features. In fact, it cannot be achieved via the traditional trial-and-error approaches, which are associated with significant cost, time, and resource waste. In search for a systematic microstructure analysis and design method, this paper aims at quantifying the Li-ion battery electrode structural characteristics via deep learning models. Deliberately, here, a methodology and framework are developed to reveal the hidden microstructure characteristics via 2D and 3D images through dimensionality reduction. The framework is based on an auto-encoder decoder for microstructure reconstruction and feature extraction. Unlike most of the existing studies that focus on a limited number of features extracted from images, this study concentrates directly on the images and has the potential to define the number of features to be extracted. The proposed methodology and model are computationally effective and have been tested on a real open-source dataset where the results show the efficiency of reconstruction and feature extraction based on the training and validation mean squared errors between 0.068 and 0.111 and from 0.071 to 0.110, respectively. This study is believed to guide Li-ion battery scientists and manufacturers in the design and production of next generation Li-ion cells in a systematic way by correlating the extracted features at the microstructure level and the cell’s electrochemical characteristics. Full article
(This article belongs to the Section D: Energy Storage and Application)
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7 pages, 256 KiB  
Editorial
Improving the Efficiency of Oil Recovery in Research and Development
by Marcin Kremieniewski
Energies 2022, 15(12), 4488; https://doi.org/10.3390/en15124488 - 20 Jun 2022
Cited by 2 | Viewed by 1169
Abstract
By creating a special edition entitled Fundamentals of Enhanced Oil Recovery, the editors focus on the problem of the global increase in energy demand [...] Full article
(This article belongs to the Special Issue Fundamentals of Enhanced Oil Recovery)
15 pages, 2374 KiB  
Article
A Finite-Time Differentiator with Application to Nuclear Reactor Inverse Period Measurement
by Yunlong Zhu, Zhe Dong, Duo Li, Xiaojin Huang, Yujie Dong, Yajun Zhang and Zuoyi Zhang
Energies 2022, 15(12), 4487; https://doi.org/10.3390/en15124487 - 20 Jun 2022
Cited by 1 | Viewed by 1217
Abstract
The measurement of the growth rate, or the so-called inverse period, of a nuclear reactor is crucial for safety monitoring and control purposes. Due to the inevitable statistical fluctuation of neutron flux at low power-levels, it is difficult to precisely estimate the inverse [...] Read more.
The measurement of the growth rate, or the so-called inverse period, of a nuclear reactor is crucial for safety monitoring and control purposes. Due to the inevitable statistical fluctuation of neutron flux at low power-levels, it is difficult to precisely estimate the inverse period from the pulse counting data in the source range. Motivated by the equivalence of the measurement of inverse period and the differentiation of the logarithm of pulse count, a new differentiator is proposed, which is finite-time convergent with a bounded steady estimation error. The feasibility of this newly-built finite-time differentiator is verified by numerical simulation. Then, based on the pulse count data recorded during the startup of a test reactor, the differentiator is used to estimate the inverse period and its derivative, as well as the period and the reactivity of the reactor. The results show that the differentiator is capable of providing a satisfactory estimation of signal derivatives under strong noise. Full article
(This article belongs to the Special Issue Nuclear Power Instrumentation and Control)
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24 pages, 4797 KiB  
Article
Thermoeconomic Optimization Design of the ORC System Installed on a Light-Duty Vehicle for Waste Heat Recovery from Exhaust Heat
by Xialai Wu, Ning Zhang, Lei Xie, Wenyan Ci, Junghui Chen and Shan Lu
Energies 2022, 15(12), 4486; https://doi.org/10.3390/en15124486 - 20 Jun 2022
Cited by 3 | Viewed by 1346
Abstract
The organic Rankine cycle (ORC) has been widely studied to recover waste heat from internal combustion engines in commercial on-road vehicles. To achieve a cost-effective ORC, a trade-off between factors such as costs, power outputs, back pressure, and weight needs to be carefully [...] Read more.
The organic Rankine cycle (ORC) has been widely studied to recover waste heat from internal combustion engines in commercial on-road vehicles. To achieve a cost-effective ORC, a trade-off between factors such as costs, power outputs, back pressure, and weight needs to be carefully worked out. However, the trade-off is still a huge challenge in engine waste heat recovery. In this study, a thermoeconomic optimization study of a vehicle-mounted ORC unit is proposed to recover waste heat from various exhaust gas conditions of a light-duty vehicle. The optimization is carried out for four organic working fluids with different critical temperatures, respectively. Under the investigated working fluids, the lower specific investment cost (SIC) and higher mean net output power (MEOP) of ORC can be achieved using the organic working fluid with higher critical temperature. The maximum mean net output power is obtained by taking RC490 as working fluid and the payback period (PB) is 3.01 years when the petrol is EUR 1.5 per liter. The proposed strategy is compared with a thermodynamic optimization method with MEOP as an optimized objective. It shows that the proposed strategy reached SIC results more economically. The importance of taking the ORC weight and the back pressure caused by ORC installation into consideration during the preliminary design phase is highlighted. Full article
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27 pages, 5352 KiB  
Article
Integration of Hydrogen and Synthetic Natural Gas within Legacy Power Generation Facilities
by German Dominguez-Gonzalez, Jose Ignacio Muñoz-Hernandez, Derek Bunn and Carlos Jesus Garcia-Checa
Energies 2022, 15(12), 4485; https://doi.org/10.3390/en15124485 - 20 Jun 2022
Cited by 3 | Viewed by 2097
Abstract
Whilst various new technologies for power generation are continuously being evaluated, the owners of almost-new facilities, such as combined-cycle gas turbine (CCGT) plants, remain motivated to adapt these to new circumstances and avoid the balance-sheet financial impairments of underutilization. Not only are the [...] Read more.
Whilst various new technologies for power generation are continuously being evaluated, the owners of almost-new facilities, such as combined-cycle gas turbine (CCGT) plants, remain motivated to adapt these to new circumstances and avoid the balance-sheet financial impairments of underutilization. Not only are the owners reluctant to decommission the legacy CCGT assets, but system operators value the inertia and flexibilities they contribute to a system becoming predominated with renewable generation. This analysis therefore focuses on the reinvestment cases for adapting CCGT to hydrogen (H2), synthetic natural gas (SNG) and/or retrofitted carbon capture and utilization systems (CCUS). Although H2, either by itself or as part of SNG, has been evaluated attractively for longer-term electricity storage, the business case for how it can be part of a hybrid legacy CCGT system has not been analyzed in a market context. This work compares the power to synthetic natural gas to power (PSNGP) adaptation with the simpler and less expensive power to hydrogen to power (P2HP) adaptation. Both the P2HP and PSNGP configurations are effective in terms of decarbonizations. The best results of the feasibility analysis for a UK application with low CCGT load factors (around 31%) were obtained for 100% H2 (P2HP) in the lower range of wholesale electricity prices (less than 178 GBP/MWh), but in the higher range of prices, it would be preferable to use the PSNGP configuration with a low proportion of SNG (25%). If the CCGT load factor increased to 55% (the medium scenario), the breakeven profitability point between P2HP and PSNGP decreased to a market price of 145 GBP/MWh. Alternatively, with the higher load factors (above 77%), satisfactory results were obtained for PSNGP using 50% SNG if with market prices above 185 GBP/MWh. Full article
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15 pages, 5379 KiB  
Article
Comparative Thermal and Demagnetization Analysis of the PM Machines with Neodymium and Ferrite Magnets
by Oleksandr Dobzhanskyi, Viktor Grebenikov, Rupert Gouws, Rostyslav Gamaliia and Eklas Hossain
Energies 2022, 15(12), 4484; https://doi.org/10.3390/en15124484 - 20 Jun 2022
Cited by 6 | Viewed by 1678
Abstract
This paper provides computer analysis and experiential investigation of the permanent magnet machines with neodymium and ferrite permanent magnets to discuss the feasibility of utilizing induction machines-oriented equipment for PM machine production. For this purpose, the machines are obtained by replacing the squirrel-cage [...] Read more.
This paper provides computer analysis and experiential investigation of the permanent magnet machines with neodymium and ferrite permanent magnets to discuss the feasibility of utilizing induction machines-oriented equipment for PM machine production. For this purpose, the machines are obtained by replacing the squirrel-cage rotor of the induction motor with the flux-focusing (tangential) and surface-mounted (radial) permanent magnet rotors. Electromechanical parameters of the machines as electromagnetic torque and output power are discussed and compared. The temperatures of the neodymium and ferrite magnets are also calculated at rated current, and short circuit scenarios and the performance of two different cooling systems in minimizing the temperature effect on the machines are investigated. Furthermore, the demagnetization of permanent magnets at various load conditions is also studied. Finally, the results of the computer modeling are validated by the physical prototypes of the machines. The characteristics of the electrical machines under study were calculated using the Simcenter MagNet and Simcenter MotorSolve software packages. Full article
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16 pages, 4191 KiB  
Article
Investigation of Rotating Detonation Fueled by Liquid Kerosene
by Jianping Zhou, Feilong Song, Shida Xu, Xingkui Yang and Yongjun Zheng
Energies 2022, 15(12), 4483; https://doi.org/10.3390/en15124483 - 20 Jun 2022
Cited by 8 | Viewed by 1737
Abstract
The performance of rotating detonation engines (RDEs) is theoretically better than that of traditional aero engines because of self-pressurization. A type of swirl injection scheme is introduced in this paper for two-phase detonation. On the one hand, experiments are performed on continuous rotating [...] Read more.
The performance of rotating detonation engines (RDEs) is theoretically better than that of traditional aero engines because of self-pressurization. A type of swirl injection scheme is introduced in this paper for two-phase detonation. On the one hand, experiments are performed on continuous rotating detonation of ternary “kerosene, hydrogen and oxygen-enriched air” mixture in an annular combustor. It is found that increasing the mass fraction of hydrogen can boost the wave speed and the stability of detonation waves’ propagation. One the other hand, characteristics of kerosene–hot air RDE is investigated for engineering application. Some unstable phenomena are recorded, such as changes of the number of detonation waves, low-frequency oscillations, and sporadic detonation. Full article
(This article belongs to the Topic Fuel Combustion Chemistry)
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20 pages, 3428 KiB  
Article
Biodiesel Production through Acid Catalyst In Situ Reactive Extraction of Chlorella vulgaris Foamate
by Shurooq T. Al-Humairi, Jonathan G. M. Lee, Musa Salihu and Adam P. Harvey
Energies 2022, 15(12), 4482; https://doi.org/10.3390/en15124482 - 20 Jun 2022
Cited by 12 | Viewed by 1941
Abstract
A method of biodiesel production from the freshwater microalgae Chlorella vulgaris based on the conversion of the dewatered algal biomass from a foam column (“foamate”) was investigated. The foam column collected and concentrated the microalgae. The foam was generated by passing air through [...] Read more.
A method of biodiesel production from the freshwater microalgae Chlorella vulgaris based on the conversion of the dewatered algal biomass from a foam column (“foamate”) was investigated. The foam column collected and concentrated the microalgae. The foam was generated by passing air through a pool of algae, to which a collector/surfactant cetyltrimethylammonium bromide (CTAB) had been added. To produce biodiesel, the resultant “foamate” was esterified in situ using sulfuric acid and methanol. The effect of reaction temperature (30–70 °C), reaction time (30–120 min) and methanol/oil molar ratio (100–1000), were examined in a single-stage extraction–transesterification experiment on biodiesel yield at concentration of the catalyst H2SO4/oil molar ratio of (8.5/1). The thermodynamics and kinetics of transesterification of the microalgae oil were also investigated. The maximum biodiesel yield (96 ± 0.2%) was obtained at a reaction temperature of 70 °C, a reaction time of 90 min and methanol/oil molar ratio of 1000/1. Reaction kinetic parameters were determined that fitted the experimental data at all temperatures. A reversible reaction with first order forward and second order backward kinetics were found to be a good match for the experimental results. The kinetic model fitted experiments well under various temperatures and methanol/oil mole ratios. Under the most suitable conditions of reaction temperature, reaction time and methanol/oil molar ratio, the apparent activation energy was found to be 18.7 kJ/mol and pre-exponential factor 51.4 min−1. The activation entropy (ΔS), change in Gibbs free energy (ΔG) and variation in activation enthalpy (ΔH) revealed that the transesterification reaction is endergonic and unspontaneous, while the endothermic nature of the reaction was confirmed by the positive value (16.6 kJ/mol) of the ΔH. The thermodynamic information and kinetic model reported here will provide valuable insight into the understanding of the in situ transesterification process from algae foamate to biodiesel. Full article
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13 pages, 2173 KiB  
Article
Theory of the Vom Berg Rheological Model and Its Use in Cloud-Native Application
by Rafał Wiśniowski and Grzegorz Orłowicz
Energies 2022, 15(12), 4481; https://doi.org/10.3390/en15124481 - 20 Jun 2022
Cited by 1 | Viewed by 1501
Abstract
Various technological fluids, such as drilling muds, drill-in fluids, fracturing fluids, spacers, washes and cement slurries are used in the wellbore drilling process. The fundamental issue, which needs to be addressed in order to become acquainted with the phenomena occurring during fluids flow [...] Read more.
Various technological fluids, such as drilling muds, drill-in fluids, fracturing fluids, spacers, washes and cement slurries are used in the wellbore drilling process. The fundamental issue, which needs to be addressed in order to become acquainted with the phenomena occurring during fluids flow through a circulatory system, is to establish mutual dependencies between a stream of fluid being pumped and flow resistances. The awareness of these dependencies enables the optimisation of hydraulic parameters in order to minimise costs and maximise drilling works safety. This article presents rheological models of drilling fluids and proposes the application of a new rheological model, not used in the drilling industry so far, namely the Vom Berg model. The model has been presented in other publications; however, there is an unsolved and unpublished problem of determining the effect of rheological parameters of the model on the value of resistance to laminar and turbulent flow. In this article, algorithms and Cloud-Native application enabling numerical determination of rheological properties of the Vom Berg fluid are presented. What is more, an algorithm for calculating pressure losses during the laminar flow of fluid in a pipe is provided. Taking an example from the industry, a practical application of the proposed calculation methodology is presented. Full article
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18 pages, 1500 KiB  
Article
Logistics and Costs of Agricultural Residues for Cellulosic Ethanol Production
by Luis Armando Becerra-Pérez, Luis Rincón and John A. Posada-Duque
Energies 2022, 15(12), 4480; https://doi.org/10.3390/en15124480 - 20 Jun 2022
Cited by 3 | Viewed by 2635
Abstract
There is global pressure to make advanced biofuels profitable. For cellulosic ethanol, three aspects remain as bottlenecks: collection of feedstocks, pretreatment methods, and enzyme production. In this paper, the first aspect is investigated, by addressing the main challenges for the logistics of agricultural [...] Read more.
There is global pressure to make advanced biofuels profitable. For cellulosic ethanol, three aspects remain as bottlenecks: collection of feedstocks, pretreatment methods, and enzyme production. In this paper, the first aspect is investigated, by addressing the main challenges for the logistics of agricultural residues. A logistic supply chain of corn stover collection and utilization for cellulosic ethanol production in Mexico is proposed, and a cost structure is designed for its estimation. By applying a value chain methodology, seven links and a set of three minimum selling prices (MSPs) of agricultural residues were determined. Furthermore, the harvest index (HI), crop residue index (CRI), nutrient substitution by extraction of agricultural residues, and harvest costs of corn stover were also calculated for a case study. The main results were a HI of 0.45, a CRI of 1.21, and nutrient substitution potential of 7 kg N, 2.2 kg P2O5, and 12.2 kg K2O per ton of corn stover. The set of the three estimated MSPs for corn stover was: $28.49 USD/ton (for delivery to the biorefinery’s gate), $31.15 USD/ton (for delivery and storage), and $48.14 USD/ton (for delivery, storage, and nutrient replenishment). Given the impact of the feedstock cost on the profitability of cellulosic ethanol, knowing details of the logistical information and its costs is critical to advancing the field of biofuels in Mexico. We also found that only 20% of farmers currently sell their residues; however, 65% of farmers would be willing to do so, a significant percentage for cellulosic ethanol production. Full article
(This article belongs to the Special Issue Biomass Energy for Environmental Sustainability)
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14 pages, 6816 KiB  
Article
Sustainable Oil Palm Resource Assessment Based on an Enhanced Deep Learning Method
by Xinni Liu, Kamarul H. Ghazali and Akeel A. Shah
Energies 2022, 15(12), 4479; https://doi.org/10.3390/en15124479 - 20 Jun 2022
Cited by 2 | Viewed by 1403
Abstract
Knowledge of the number and distribution of oil palm trees during the crop cycle is vital for sustainable management and predicting yields. The accuracy of the conventional image processing method is limited for the hand-crafted feature extraction method and the overfitting problem occurs [...] Read more.
Knowledge of the number and distribution of oil palm trees during the crop cycle is vital for sustainable management and predicting yields. The accuracy of the conventional image processing method is limited for the hand-crafted feature extraction method and the overfitting problem occurs due to the insufficient dataset. We propose a modification of the Faster Region-based Convolutional Neural Network (FRCNN) for palm tree detection to reduce the overfitting problem and improve the detection accuracy. The enhanced FRCNN (EFRCNN) leads to improved performance for detecting objects (in the same image) when they are of multiple sizes by using a feature concatenation method. Transfer learning based on a ResNet50 model is used to extract the features of the input image. High-resolution images of oil palm trees from a drone are used to form the data set, containing mature, young, and mixed oil palm tree regions. We train and test the EFRCNN, the FRCNN, a CNN used recently for oil palm image detection, and two standard methods, namely, the support vector machine (SVM) and template matching (TM). The results reveal an overall accuracy of ≥96.8% for the EFRCNN on the three test sets. The accuracy is higher than the CNN and FRCNN and substantially higher than SVM and TM. For large-scale plantations, the accuracy improvement is significant. This research provides a method for automatically counting the oil palm trees in large-scale plantations. Full article
(This article belongs to the Special Issue Sustainability Assessment of Renewable Energy Systems)
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