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Eng, Volume 5, Issue 3 (September 2024) – 18 articles

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14 pages, 990 KiB  
Article
Assessing Digestate at Different Stabilization Stages: Application of Thermal Analysis and FTIR Spectroscopy
by Silvia González-Rojo, Daniela Carrillo-Peña, Rubén González González and Xiomar Gómez
Eng 2024, 5(3), 1499-1512; https://doi.org/10.3390/eng5030080 - 19 Jul 2024
Viewed by 165
Abstract
Anaerobic digestion is a biological process that transforms high-strength organic effluents into biogas with multiple benefits. However, concurrent with organics’ biological transformation, a liquid phase with a high solid content is also derived from this process. Valorizing this fraction is not an easy [...] Read more.
Anaerobic digestion is a biological process that transforms high-strength organic effluents into biogas with multiple benefits. However, concurrent with organics’ biological transformation, a liquid phase with a high solid content is also derived from this process. Valorizing this fraction is not an easy task if an agronomic application cannot be considered as a suitable option. The thermal valorization of this fraction allows for energy extraction but also gives rise to additional capital investment and increases the energy demand of the global process. In addition, the thermal treatment of digestate has to deal with a mineralized material. The changes in organic matter due to anaerobic digestion were studied in the present manuscript, by evaluating the thermal behavior of samples, activation energy, and organic transformation using Fourier transform infrared (FTIR) spectroscopy. Digested samples of a mixture composed of manure and glycerin (5% v/v) were studied. The stabilization caused a dramatic decrease in aliphatic compounds, greatly increasing the mineral content of the sample. Results from differential scanning calorimetry (DSC) indicated an energy content of 11 kJ/g for the feed material and a reduction to 9.6 kJ/g for the long-term stabilized sample. The activation energy of the feed was 249.5 kJ/mol, whereas this value was reduced to 70–80 kJ/mol for digested samples. If the valorization route selected for digestates is thermal conversion, the lower energy content and more complex structure of these materials (higher content of lignin and protein-type compounds) must be carefully evaluated. Full article
(This article belongs to the Section Chemical, Civil and Environmental Engineering)
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14 pages, 3512 KiB  
Article
Development of a Methodology for Railway Bolster Beam Design Enhancement Using Topological Optimization and Manufacturing Constraints
by Alessio Cascino, Enrico Meli and Andrea Rindi
Eng 2024, 5(3), 1485-1498; https://doi.org/10.3390/eng5030079 - 19 Jul 2024
Viewed by 192
Abstract
Rolling stock manufacturers are finding innovative structural solutions to improve the quality and reliability of railway vehicle components. Structural optimization processes represent an effective strategy for reducing manufacturing costs, resulting in geometries that are easier to design and produce combined with innovative materials. [...] Read more.
Rolling stock manufacturers are finding innovative structural solutions to improve the quality and reliability of railway vehicle components. Structural optimization processes represent an effective strategy for reducing manufacturing costs, resulting in geometries that are easier to design and produce combined with innovative materials. In this framework, the present paper proposes the development of a design methodology to innovate a railway bolster beam using topological optimization techniques, assessing the effect of different manufacturing constraints oriented to the casting process. A comprehensive numerical testing campaign was conducted to establish an effective testing procedure. Two different designs were obtained and compared, statically and dynamically, evaluating the difference in terms of mass, mechanical performance and manufacturability. Reductions in stress values up to 70% were observed, along with an 8% increase in the first natural frequency of the component, leading to beneficial effects in terms of stiffness. The methodology shows encouraging results to streamline the design of complex casting components, moving to a new generation of structural railway components. Full article
(This article belongs to the Special Issue Feature Papers in Eng 2024)
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21 pages, 1443 KiB  
Review
Machine and Deep Learning Trends in EEG-Based Detection and Diagnosis of Alzheimer’s Disease: A Systematic Review
by Marcos Aviles, Luz María Sánchez-Reyes, José Manuel Álvarez-Alvarado and Juvenal Rodríguez-Reséndiz
Eng 2024, 5(3), 1464-1484; https://doi.org/10.3390/eng5030078 - 16 Jul 2024
Viewed by 404
Abstract
This article presents a systematic review using PRISMA methodology to explore trends in the use of machine and deep learning in diagnosing and detecting Alzheimer’s disease using electroencephalography. This review covers studies published between 2013 and 2023, drawing on three leading academic databases: [...] Read more.
This article presents a systematic review using PRISMA methodology to explore trends in the use of machine and deep learning in diagnosing and detecting Alzheimer’s disease using electroencephalography. This review covers studies published between 2013 and 2023, drawing on three leading academic databases: Scopus, Web of Science, and PubMed. The validity of the databases is evaluated considering essential factors such as the arrangement of EEG electrodes, data acquisition methodologies, and the number of participants. Additionally, the specific properties of the databases used in the research are highlighted, including EEG signal classification, filtering, segmentation approaches, and selected features. Finally, the performance metrics of the classification algorithms are evaluated, especially the accuracy achieved, offering a comprehensive view of the current state and future trends in the use of these technologies for the diagnosis of Alzheimer’s disease. Full article
(This article belongs to the Special Issue Feature Papers in Eng 2024)
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13 pages, 8148 KiB  
Article
Influence of Processing Parameters on Laser-Assisted Reactive Sintering of a Mixture of Ni and Ti Powders
by Naiara Vieira Le Sénéchal, Pedro Henrique Poubel Mendonça da Silveira, Patrícia Freitas Rodrigues, Danilo Abílio Corrêa Gonçalves, Silvelene Alessandra Silva Dyer, Rodolfo da Silva Teixeira, Rafael Humberto Mota de Siqueira, Milton Sergio Fernandes de Lima, Daniel Leal Bayerlein and Andersan dos Santos Paula
Eng 2024, 5(3), 1451-1463; https://doi.org/10.3390/eng5030077 - 15 Jul 2024
Viewed by 267
Abstract
Additive manufacturing (AM) plays a crucial role in the development of NiTi alloys, enabling the creation of complex and customized structures while optimizing properties for various biomedical and industrial applications. The aim of this paper was to investigate the influence of laser scanning [...] Read more.
Additive manufacturing (AM) plays a crucial role in the development of NiTi alloys, enabling the creation of complex and customized structures while optimizing properties for various biomedical and industrial applications. The aim of this paper was to investigate the influence of laser scanning speed on laser-assisted reactive sintering of a mixture of No and Ti powders. The samples were sintered at two different beam speeds, 4 and 5 4 mm/s and their morphological and microstructural characteristics were investigated. Scanning electron microscopy with energy dispersive X-ray spectroscopy (SEM/EDX) and X-ray diffraction (XRD) analyses revealed the presence of intermetallic compounds rich in Ni and Ti for both scanning speeds; however, the scanning speed of 5 mm/s produced a microstructure with greater porosity, leading to a sintered body with poorer consolidation. Thus, employing a slower beam scanning of 4 mm/s seems to be a better alternative in the laser-assisted reactive sintering of NiTi alloys. Full article
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16 pages, 2584 KiB  
Article
Correlation Analysis between Young Driver Characteristics and Visual/Physiological Attributes at Expressway Exit Ramp
by Zeng’an Wang, Xinyue Qi, Chenzhu Wang, Said M. Easa, Fei Chen and Jianchuan Cheng
Eng 2024, 5(3), 1435-1450; https://doi.org/10.3390/eng5030076 - 12 Jul 2024
Viewed by 216
Abstract
More collisions occur at the exit ramps of expressways due to frequent lane-changing behavior and interweaving between vehicles. Young drivers with shorter driving mileage and driving experience, radical driving styles, and worse behavior prediction are likelier to be involved in collisions at the [...] Read more.
More collisions occur at the exit ramps of expressways due to frequent lane-changing behavior and interweaving between vehicles. Young drivers with shorter driving mileage and driving experience, radical driving styles, and worse behavior prediction are likelier to be involved in collisions at the exit ramps. This paper focuses on the correlation analysis between young drivers’ characteristics and their visual and physiological attributes at expressway exit ramps. First, the driver’s gender, driving experience, and mileage are classified. Then, seven expressway exit models are established using the UC/Win road modeling software. The driver’s driving plane vision is divided into four areas using the K-means clustering algorithm. In addition, the driver’s visual and heart rate attributes were analyzed at 500 m, 300 m, 200 m, and 100 m away from an expressway exit. The results show that the visual attributes, gender, and driving mileage of young drivers strongly correlate with the fixation times and average saccade amplitude. In contrast, the driving experience has almost no correlation with the fixation behavior of young drivers. Young drivers’ driving experience and mileage strongly correlate with cardiac physiological attributes, but there is virtually no correlation with gender. The practical implications of these results should be helpful to highway planners and designers. Full article
(This article belongs to the Special Issue Feature Papers in Eng 2024)
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13 pages, 2736 KiB  
Article
Enhancing Metabolic Syndrome Detection through Blood Tests Using Advanced Machine Learning
by Petros Paplomatas, Dimitris Rigas, Athanasia Sergounioti and Aristidis Vrahatis
Eng 2024, 5(3), 1422-1434; https://doi.org/10.3390/eng5030075 - 10 Jul 2024
Viewed by 426
Abstract
The increasing prevalence of metabolic syndrome (MetS), a serious condition associated with elevated risks of cardiovascular diseases, stroke, and type 2 diabetes, underscores the urgent need for effective diagnostic tools. This research carefully examines the effectiveness of 16 diverse machine learning (ML) models [...] Read more.
The increasing prevalence of metabolic syndrome (MetS), a serious condition associated with elevated risks of cardiovascular diseases, stroke, and type 2 diabetes, underscores the urgent need for effective diagnostic tools. This research carefully examines the effectiveness of 16 diverse machine learning (ML) models in predicting MetS, a multifaceted health condition linked to increased risks of heart disease and other serious health complications. Utilizing a comprehensive, unpublished dataset of imbalanced blood test results, spanning from 2017 to 2022, from the Laboratory Information System of the General Hospital of Amfissa, Greece, our study embarks on a novel approach to enhance MetS diagnosis. By harnessing the power of advanced ML techniques, we aim to predict MetS with greater accuracy using non-invasive blood test data, thereby reducing the reliance on more invasive diagnostic methods. Central to our methodology is the application of the Borda count method, an innovative technique employed to refine the dataset. This process prioritizes the most relevant variables, as determined by the performance of the leading ML models, ensuring a more focused and effective analysis. Our selection of models, encompassing a wide array of ML techniques, allows for a comprehensive comparison of their individual predictive capabilities in identifying MetS. This study not only illuminates the unique strengths of each ML model in predicting MetS but also reveals the expansive potential of these methods in the broader landscape of health diagnostics. The insights gleaned from our analysis are pivotal in shaping more efficient strategies for the management and prevention of metabolic syndrome, thereby addressing a significant concern in public health. Full article
(This article belongs to the Special Issue Feature Papers in Eng 2024)
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15 pages, 9411 KiB  
Article
A Probabilistic Study of CO2 Plume Geothermal and Hydrothermal Systems: A Sensitivity Study of Different Reservoir Conditions in Williston Basin, North Dakota
by Emmanuel Gyimah, Olusegun Tomomewo, Luc Yvan Nkok, Shree Om Bade, Ebenezer Asare Ofosu and Maxwell Collins Bawuah
Eng 2024, 5(3), 1407-1421; https://doi.org/10.3390/eng5030074 - 10 Jul 2024
Viewed by 323
Abstract
The exploration of alternative energy sources has gained significant traction in recent years, driven by the urgent need to mitigate greenhouse gas emissions and transition towards sustainable energy. Among these alternatives, CO2 plume geothermal and hydrothermal systems have emerged as promising [...] Read more.
The exploration of alternative energy sources has gained significant traction in recent years, driven by the urgent need to mitigate greenhouse gas emissions and transition towards sustainable energy. Among these alternatives, CO2 plume geothermal and hydrothermal systems have emerged as promising options due to their potential for providing clean, renewable energy. This study presents a probabilistic investigation into the sensitivity of CO2 plume geothermal and hydrothermal systems under various reservoir conditions in the Williston Basin, North Dakota. In addition to elucidating the impact of reservoir conditions on system performance, the study utilizes probabilistic methods to assess energy output of CO2 plume geothermal and hydrothermal systems. Insights derived from this probabilistic investigation offer valuable guidance for the working fluid selection, systems design and optimization in the Williston Basin and beyond. Results from the sensitivity analysis reveal the profound influence of reservoir conditions on the behavior and efficiency of CO2 plume geothermal and hydrothermal systems. Our case study on Red River Formation and Deadwood Formations shows a potential of 34% increase and 32% decrease in heat extraction based on varying reservoir conditions. Our investigations in the Beaver Lodge field within the Red River Formation yielded arithmetic mean values for CO2 best case resources, hydrothermal resources and the CO2 worst case as 6.36 × 1018 J, 4.75 × 1018 J and 3.24 × 1018 J, respectively. Overall, this research contributes to advancing the knowledge and understanding of CO2 plume geothermal and hydrothermal systems as viable pathways towards sustainable energy production and carbon sequestration. By highlighting the sensitivity of these systems to reservoir conditions, the study provides valuable insights that can inform decision-making processes and future research endeavours aimed at fostering the transition to a low-carbon energy landscape. Full article
(This article belongs to the Special Issue GeoEnergy Science and Engineering 2024)
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8 pages, 1239 KiB  
Article
Calotropis Gigantea Latex-Derived Zinc Oxide Nanoparticles: Biosynthesis, Characterization, and Biofunctional Applications
by Jayalekshmi C, Rajiv Periakaruppan, Valentin Romanovski, Karungan Selvaraj Vijai Selvaraj and Noura Al-Dayan
Eng 2024, 5(3), 1399-1406; https://doi.org/10.3390/eng5030073 - 9 Jul 2024
Viewed by 427
Abstract
Latex of C. gigantea was used to synthesize zinc oxide nanoparticles (ZnO NPs) by the green chemistry approach. The crystalline size, shape, and purity of as-synthesized ZnO NPs were characterized through scanning electron microscopy with energy-dispersive X-ray spectroscopy, transmission electron microscopy, X-ray diffraction [...] Read more.
Latex of C. gigantea was used to synthesize zinc oxide nanoparticles (ZnO NPs) by the green chemistry approach. The crystalline size, shape, and purity of as-synthesized ZnO NPs were characterized through scanning electron microscopy with energy-dispersive X-ray spectroscopy, transmission electron microscopy, X-ray diffraction analysis, and Fourier-transform infrared spectroscopy techniques. Crystalline, spherical ZnO NPs with an average size of 21.8 nm were formed. In addition, the biological properties of the ZnO NPs, such as antioxidant and antibacterial activity, were evaluated by 2,2-diphenyl-1-picrylhydrazyl assay and the agar well-diffusion method. The highest free radical scavenging activities of 83.11 ± 1.89 % were observed at a concentration of 350 μg/mL of C. gigantea latex-mediated ZnO NPs. The latex in the C. gigantea latex-mediated ZnO NPs inhibited the growth of pathogenic bacteria. The maximum zone of inhibition was found in P. aeruginosa and S. aureus. C. gigantea latex-mediated ZnO NPs have significant biocompatibility and broad-spectrum antibacterial properties against wound-causing bacteria and, therefore, can be suggested for use in the formulation of novel creams or gels for healing applications. Full article
(This article belongs to the Special Issue REPER Recent Materials Engineering Performances)
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17 pages, 2164 KiB  
Article
Empowering Remote Living: Optimizing Hybrid Renewable Energy Systems in Mexico
by Juan Carlos León Gómez, Jesus Aguayo Alquicira, Susana Estefany De León Aldaco, Oscar Sánchez Vargas and Kenia Yadira Gómez Díaz
Eng 2024, 5(3), 1382-1398; https://doi.org/10.3390/eng5030072 - 8 Jul 2024
Viewed by 292
Abstract
The developing environmental consequences of excessive dependence on fossil fuels have pushed many countries to invest in clean and renewable energy sources. Mexico is a country that, due to its geographic and climatic diversity, can take advantage of this potential in renewable energy [...] Read more.
The developing environmental consequences of excessive dependence on fossil fuels have pushed many countries to invest in clean and renewable energy sources. Mexico is a country that, due to its geographic and climatic diversity, can take advantage of this potential in renewable energy generation and reduce its dependence on fossil fuels while developing strategies to improve its energy system. This study investigated the feasibility of the autonomous use of two hybrid renewable energy systems and a photovoltaic system to power homes in a remote location. With the help of HOMER Pro Version 3.14.5 software, a model was made to evaluate the operation of three systems for one year, and the demand was predicted according to a given scenario. In addition, the optimal configuration of the components of each system was determined. The results showed that the simultaneous use of solar systems with a converter and a backup system consisting of a diesel generator and batteries would be the most viable and reliable option for generating renewable energy at the selected location, offering electricity with a renewable fraction of more than 80%. Full article
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22 pages, 6572 KiB  
Article
Risk Management and Assessment Hybrid Framework for Business Process Reengineering Projects: Application in Automotive Sector
by Raffak Hicham, Lakhouili Abdallah and Mansouri Mohamed
Eng 2024, 5(3), 1360-1381; https://doi.org/10.3390/eng5030071 - 5 Jul 2024
Viewed by 242
Abstract
This study introduces an integrated method for managing process risks in a business process reengineering (BPR) project using robust data envelopment analysis (RDEA) and machine learning (ML). The goal is to prioritize risks based on three standard factors of PFMEA (severity, occurrence and [...] Read more.
This study introduces an integrated method for managing process risks in a business process reengineering (BPR) project using robust data envelopment analysis (RDEA) and machine learning (ML). The goal is to prioritize risks based on three standard factors of PFMEA (severity, occurrence and detection (S-O-D)) and incorporating two additional factors (breakdown cost and breakdown duration) seen as undesirable outputs. The model also accounts for the effect of uncertainty on expert-estimated values by applying disturbance percentages in the linear PFMEA-RDEA model. A machine-learning model is proposed to predict new values if partial or total modifications have been made to the processes. The approach was implemented in an automotive sector company, and the results showed the impact of uncertainty on values by comparing different approaches, such as RPN, PFMEA-DEA and PFMEA-RDEA. A new reduced risk categorization was achieved, which allowed for decision makers to focus on the necessary actions for reengineering. Full article
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23 pages, 6313 KiB  
Article
Transforming CO2 into Synthetic Fuels: Modeling, Simulation, and Optimization Analysis of Methanol Production from Industrial Wastes
by Vasiliki Kontou, Antonis Peppas, Sotiris Kottaridis, Chrysa Politi and Sotirios Karellas
Eng 2024, 5(3), 1337-1359; https://doi.org/10.3390/eng5030070 - 5 Jul 2024
Viewed by 427
Abstract
Carbon capture and utilization (CCU) has emerged in recent years as a promising decarbonization solution for hard-to-abate industries. Compared to carbon capture and storage (CCS), CCU aims not for the storage of carbon dioxide (CO2) but for its use in the [...] Read more.
Carbon capture and utilization (CCU) has emerged in recent years as a promising decarbonization solution for hard-to-abate industries. Compared to carbon capture and storage (CCS), CCU aims not for the storage of carbon dioxide (CO2) but for its use in the production of synthetic fuels, such as synthetic methanol (MeOH). Synthetic MeOH is produced through CO2 hydrogenation, utilizing green hydrogen (H2). Efficient use of CO2 and H2 feedstocks is essential to maximize the carbon reduction potential and energy efficiency of the process. This study performed an optimization analysis on a small-scale, containerized, and portable CO2 hydrogenation unit with a 5 kg MeOH/h production capacity goal, focusing on carbon conversion efficiency (CCE), MeOH yield, H2 consumption, and MeOH purity. The analysis was conducted using Aspen Plus V12. A single-pass model was used first to evaluate an initial reactor design. The reactor was then re-designed according to the results of the gas hourly space velocity (GHSV). The model was then expanded to include a recycling loop and the final reactor design was validated, aiming to maximize overall efficiency. The effects of the operational parameters including the reactor inlet temperature, reactor pressure, thermal fluid temperature, and condensation temperature were examined. The model was then further expanded to include the MeOH distillation process, and the effect of the distillation temperature was examined. The final product of the analysis was a fully-defined and optimized unit, achieving an 87.97% CCE and an 84.99% MeOH yield, consuming 1.11 kg H2/h for the production of 5.01 kg MeOH/h of 99.86 wt% purity. This study can provide valuable information and guidelines for designing small-scale, containerized, and portable CO2 hydrogenation units, which can serve as alternative solutions to address issues of H2 production and transportation related to large-scale installations. Full article
(This article belongs to the Section Chemical, Civil and Environmental Engineering)
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39 pages, 6346 KiB  
Review
Direct Air Capture (DAC) for Achieving Net-Zero CO2 Emissions: Advances, Applications, and Challenges
by Guihe Li and Jia Yao
Eng 2024, 5(3), 1298-1336; https://doi.org/10.3390/eng5030069 - 4 Jul 2024
Viewed by 553
Abstract
Carbon dioxide (CO2), as the primary greenhouse gas, has significant impacts on global climate change, leading to severe and irreversible adverse consequences for ecosystems and human environments. To address the issue of excessive CO2 emissions, efforts in recent years have [...] Read more.
Carbon dioxide (CO2), as the primary greenhouse gas, has significant impacts on global climate change, leading to severe and irreversible adverse consequences for ecosystems and human environments. To address the issue of excessive CO2 emissions, efforts in recent years have yielded significant progress in the development of clean energy sources and the promotion of carbon capture, utilization, and storage (CCUS) technologies. Conventional CO2 capture techniques are limited in addressing global atmospheric CO2 excess effectively, as they target only high-concentration CO2 emissions and require implementation at specific emission points. Direct air capture (DAC) technology has emerged as a promising solution due to its flexibility in deployment, avoidance of land competition, and ability to capture legacy CO2 emissions. Additionally, DAC offers opportunities for producing synthetic clean fuels, thereby reducing reliance on traditional fossil fuels and aiding in reducing greenhouse gas emissions. This study provides a comprehensive review of DAC technology, encompassing its principles, technological advancements, real-world applications, challenges, and future research directions. By offering insights into the current state and potential of DAC technology, this study aims to guide global efforts in scaling up DAC deployment, ultimately contributing to achieving global carbon neutrality or even negative emissions. Full article
(This article belongs to the Special Issue Green Engineering for Sustainable Development 2024)
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32 pages, 4267 KiB  
Review
A State-of-the-Art Review in Big Data Management Engineering: Real-Life Case Studies, Challenges, and Future Research Directions
by Leonidas Theodorakopoulos, Alexandra Theodoropoulou and Yannis Stamatiou
Eng 2024, 5(3), 1266-1297; https://doi.org/10.3390/eng5030068 - 3 Jul 2024
Viewed by 698
Abstract
The explosion of data volume in the digital age has completely changed the corporate and industrial environments. In-depth analysis of large datasets to support strategic decision-making and innovation is the main focus of this paper’s exploration of big data management engineering. A thorough [...] Read more.
The explosion of data volume in the digital age has completely changed the corporate and industrial environments. In-depth analysis of large datasets to support strategic decision-making and innovation is the main focus of this paper’s exploration of big data management engineering. A thorough examination of the basic elements and approaches necessary for efficient big data use—data collecting, storage, processing, analysis, and visualization—is given in this paper. With real-life case studies from several sectors to complement our exploration of cutting-edge methods in big data management, we present useful applications and results. This document lists the difficulties in handling big data, such as guaranteeing scalability, governance, and data quality. It also describes possible future study paths to deal with these issues and promote ongoing creativity. The results stress the need to combine cutting-edge technology with industry standards to improve decision-making based on data. Through an analysis of approaches such as machine learning, real-time data processing, and predictive analytics, this paper offers insightful information to companies hoping to use big data as a strategic advantage. Lastly, this paper presents real-life use cases in different sectors and discusses future trends such as the utilization of big data by emerging technologies. Full article
(This article belongs to the Special Issue Feature Papers in Eng 2024)
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34 pages, 2458 KiB  
Review
Economic, Societal, and Environmental Impacts of Available Energy Sources: A Review
by Faisal Al Mubarak, Reza Rezaee and David A. Wood
Eng 2024, 5(3), 1232-1265; https://doi.org/10.3390/eng5030067 - 28 Jun 2024
Viewed by 482
Abstract
The impacts that the available energy sources have had on society, the environment, and the economy have become a focus of attention in recent years, generating polarization of opinions. Understanding these impacts is crucial for rational evaluation and the development of strategies for [...] Read more.
The impacts that the available energy sources have had on society, the environment, and the economy have become a focus of attention in recent years, generating polarization of opinions. Understanding these impacts is crucial for rational evaluation and the development of strategies for economic growth and energy security. This review examines such impacts of the main energy resources currently exploited or in development, including fossil fuels, geothermal, biomass, solar, hydropower, hydrogen, nuclear, ocean, and wind energies on society through analysis and comparison. It is essential to consider how high energy demand influences energy prices, the workforce, and the environment and to assess the advantages and disadvantages of each energy source. One significant finding from this review is that the levelized cost of energy (LCOE) may vary substantially depending on the energy source used and show substantial ranges for different applications of the same energy source. Nuclear energy has the lowest LCOE range whereas ocean energy has the highest LCOE range among the nine energy sources considered. Fossil fuels were found to have the most substantial societal impacts, which involved on the positive side providing by far the largest number of jobs and highest tax revenues. However, on the negative side, fossil fuels, biomass, and nuclear energy sources pose the most significant health threats and social well-being impacts on communities and societies compared to other energy sources. On the other hand, solar, ocean and wind energy pose the lowest risk in terms of health and safety, with solar and wind also currently providing a substantial number of jobs worldwide. Regarding environmental consequences, fossil fuels generate the highest greenhouse gas (GHG) emissions and have the highest adverse impacts on ecosystems. In contrast, nuclear, ocean, solar and wind energies have the lowest GHG emissions and low to moderate impacts on ecosystems. Biomass, geothermal and hydropower energy sources have moderate to high ecosystem impacts compared to the other energy sources. Hydropower facilities require the most materials (mainly concrete) to build per unit of energy generated, followed by wind and solar energy, which require substantial steel and concrete per unit of energy generated. The lack of substantial materials recycling causes associated with solar and wind energy sources. All the energies that use thermal power generation process consume substantial quantities of water for cooling. The analysis and comparisons provided in this review identified that there is an urgent need to transition away from large-carbon-footprint processes, particularly fossil fuels without carbon capture, and to reduce the consumption of construction materials without recycling, as occurs in many of the existing solar and wind energy plants. This transition can be facilitated by seeking alternative and more widely accessible materials with lower carbon footprints during manufacturing and construction. Implementing such strategies can help mitigate climate change and have a positive impact on community well-being and economic growth. Full article
(This article belongs to the Special Issue GeoEnergy Science and Engineering 2024)
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23 pages, 4129 KiB  
Article
The Issue of Estimating the Maintenance and Operation Costs of Buildings: A Case Study of a School
by Dino Obradović, Martina Briš Alić and Ksenija Čulo
Eng 2024, 5(3), 1209-1231; https://doi.org/10.3390/eng5030066 - 27 Jun 2024
Viewed by 1008
Abstract
The operations and maintenance phase is typically the longest phase within the building life cycle. Proper and consistent building maintenance is imperative for several reasons, including extending the life of buildings, improving occupants’ comfort and safety, and ultimately saving on long-term costs. Budgets [...] Read more.
The operations and maintenance phase is typically the longest phase within the building life cycle. Proper and consistent building maintenance is imperative for several reasons, including extending the life of buildings, improving occupants’ comfort and safety, and ultimately saving on long-term costs. Budgets for maintenance should be foreseen. The costs of statutory periodic inspections, the costs of replacing worn materials and elements, the costs of periodic works and repairs, the costs of reactive maintenance and the costs of operation will be shown for the analyzed building—a school. This paper outlines the development of a 15-year maintenance plan and program for the building, covering the period from 2024 to 2038. The plan incorporates a discount rate of 3.64% and accounts for inflation when calculating costs. The present value of the costs of maintenance and operation of the building for 15 years is EUR 1,978,292.20 and the largest share of these costs is the operation cost of the building with EUR 1,599,002.18 (80.83%). A sensitivity analysis was conducted by varying the discount rate and analysis period, resulting in recalculated present values for maintenance costs. The analysis reveals a correlation of 26.73% between the present value of maintenance and operation costs over a 15-year period and the associated capital costs. Full article
(This article belongs to the Section Chemical, Civil and Environmental Engineering)
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26 pages, 8709 KiB  
Article
A New Algorithmic Method for Reverse Osmosis Desalination Analysis: Design Optimization and Parametric Study
by Rima Aridi, Mohamad Al Mawla, Elias Harika, Thierry Lemenand, Mahmoud Khaled and Mostafa Gad El-Rab
Eng 2024, 5(3), 1183-1208; https://doi.org/10.3390/eng5030065 - 26 Jun 2024
Viewed by 654
Abstract
Population growth, coupled with industrial and agricultural development, has resulted in increased demand for freshwater supply. For countries with scarce water resources, desalination constitutes the only viable solution to this problem. Reverse osmosis (RO) technology has become widely used as the membrane materials [...] Read more.
Population growth, coupled with industrial and agricultural development, has resulted in increased demand for freshwater supply. For countries with scarce water resources, desalination constitutes the only viable solution to this problem. Reverse osmosis (RO) technology has become widely used as the membrane materials have been upgraded and the costs have been reduced. Nowadays, RO is the foremost technology for desalting different types of water such as seawater, brackish, and tap water. However, its design is critical since many parameters are involved in obtaining a good design. The high use of RO encourages the establishment of a procedure that facilitates the design process and helps in obtaining an optimum-performance RO desalination system. This paper presents a procedure divided into three parts: (1) classifying RO parameters; (2) choosing the parameters in a certain order and doing the calculation process through 12 steps; and (3) then inserting the selected parameters and the obtained values on RO System Analysis (ROSA) software. These points are then summarized by creating an algorithmic chart to follow during the design phase of the RO system using ROSA. An example on the proposed list is then taken to validate the procedure, and a comparison is conducted on choosing different values for the parameters. The results of this comparative study show that choosing different parameters affects the RO system productivity. Additionally, every design has a specific optimum set of parameters, which depends upon the design constraints set by the user. Full article
(This article belongs to the Section Chemical, Civil and Environmental Engineering)
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10 pages, 1863 KiB  
Article
Recalibrated Correlations between Dynamic Cone Penetrometer (DCP) Data and California Bearing Ratio (CBR) in Subgrade Soil
by Jirawat Chokkerd, Artit Udomchai, Sivarit Sultornsanee, Niwat Angkawisittpan, Piyanat Jantosut, Noppadol Sangiamsak and Nopanom Kaewhanam
Eng 2024, 5(3), 1173-1182; https://doi.org/10.3390/eng5030064 - 26 Jun 2024
Viewed by 878
Abstract
This study investigates the correlation between the California Bearing Ratio (CBR) and the Dynamic Cone Penetrometer (DCP) for subgrade soil analysis. The paper aims to provide practical equations for predicting CBR values from DCP test results, therefore enhancing the efficiency of soil assessments [...] Read more.
This study investigates the correlation between the California Bearing Ratio (CBR) and the Dynamic Cone Penetrometer (DCP) for subgrade soil analysis. The paper aims to provide practical equations for predicting CBR values from DCP test results, therefore enhancing the efficiency of soil assessments in engineering practice. By analyzing test data and proposing correlations for different soil groups, the study introduces recalibrated correlations that demonstrate high accuracy in predicting CBR values. The newly proposed equations offer reliable predictions with R2 values of 0.89, 0.92, and 0.94 for clean sand, silty sand or sandy silt, and cohesive soil, respectively. These correlations serve as valuable tools for engineers, enabling rapid and accurate CBR estimations for improved decision-making in various engineering projects. Full article
(This article belongs to the Section Chemical, Civil and Environmental Engineering)
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Article
An Investigation of Increased Power Transmission Capabilities of Elastic–Plastic-Designed Press–Fit Connections Using a Detachable Joining Device
by Jan Falter, Daniel Herburger, Hansgeorg Binz and Matthias Kreimeyer
Eng 2024, 5(3), 1155-1172; https://doi.org/10.3390/eng5030063 - 21 Jun 2024
Viewed by 614
Abstract
Drive systems are an important part of general mechanical engineering, automotive engineering, and various other fields, with shaft–hub connections being an important part of such systems. Decisive aspects in the development of such systems today are, for example, high transmittable forces and torques, [...] Read more.
Drive systems are an important part of general mechanical engineering, automotive engineering, and various other fields, with shaft–hub connections being an important part of such systems. Decisive aspects in the development of such systems today are, for example, high transmittable forces and torques, low masses, and the cheapest possible production of components. A possibly threefold increase in the force and torque transmission capacity can be achieved by using press–fit connections with an elastic–plastic design as opposed to regular elastically designed alternatives. An elastic–plastic design of the press–fit connection is achieved by using a large interference. A large transition geometry on the shaft (which replaces the conventional chamfer) is required to join such an interference. The material and space requirements have a negative impact on lightweight applications and limited building spaces. Therefore, the objective of the research presented in this paper is to design and analyze a detachable joining device that substitutes this geometry. A simulation study was conducted to determine the geometry of the joining device that improves the stress state and consequently the force and torque transmission capacity of the connection. Moreover, the influence of manufacturing tolerances of the joining device and the shaft, corresponding risks, and measures to mitigate them are analyzed using finite element analysis. The results show that large transition radii, enabled by using a joining device, lead to a homogenous distribution of plastic strain and pressure in the press–fit connection, even for large interferences ξ and soft hub materials like wrought aluminum alloys. The influence of manufacturing tolerances on the stress state was quantified, leading to design guidelines that minimize the risk of, e.g., the front face collision of a shaft and hub, while maximizing the power transmission of the connection. The results show the capability of a detachable joining device to enable elastic–plastic press–fit connections and the corresponding threefold increase in the force and torque transmission capacity in lightweight applications, resulting from the substitution of the installation space consuming and mass increasing the transition geometry of the shaft. Full article
(This article belongs to the Special Issue Feature Papers in Eng 2024)
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