Results in Engineering最新文献

英文中文

Optimizing NZEB performance: A review of design strategies and case studies

IF 6 Q1 ENGINEERING, MULTIDISCIPLINARY

Results in Engineering

Pub Date : 2025-01-06 DOI: 10.1016/j.rineng.2025.103950

Mohanad M. Ibrahim , María Jose Suarez-Lopez , Ahmed A. Hanafy , Micheal A. William

The world confronts significant energy issues, propelled by increasing energy consumption in buildings and escalating apprehensions regarding carbon emissions from the industry. Inefficient building practices exacerbate energy instability, especially in areas experiencing increased urbanization. Nearly-zero Energy Buildings (NZEBs) present an effective remedy to these challenges, markedly decreasing energy usage and carbon emissions while fostering sustainability.

This research thoroughly assesses the development of NZEBs from 1995 to 2024, emphasizing design concepts, technological innovations, and their impact on energy efficiency. An analysis of key impediments to implementation reveals high prices, limited technological feasibility, regulatory limitations, and insufficient stakeholder participation. The paper examines the revolutionary impact of artificial intelligence (AI) on enhancing NZEB performance, highlighting applications such as predictive energy analytics, intelligent HVAC systems, and real-time energy management. Focusing on Egypt within the larger MENA region, this article emphasizes the unique difficulties faced by the country due to its varied climates and different stages of regulatory development. The research delineates region-specific ways to surmount challenges, including the integration of sophisticated renewable energy systems, the optimization of building envelopes, and the promotion of multi-stakeholder engagement.

The results highlight the necessity for customized solutions and improved regional and worldwide cooperation to expedite the implementation of NZEBs, fostering a sustainable and resilient built environment. This analysis offers practical insights for researchers, policymakers, and industry stakeholders aiming to promote NZEB adoption in the MENA area and beyond.

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引用次数: 0

The role of biodiesel in marine decarbonization: Technological innovations and ocean engineering challenges

IF 6 Q1 ENGINEERING, MULTIDISCIPLINARY

Results in Engineering

Pub Date : 2025-01-05 DOI: 10.1016/j.rineng.2025.103974

D. Christopher Selvam , T. Raja , Beemkumar Nagappan , Vijay J. Upadhye , J. Guntaj , Yuvarajan Devarajan , Ruby Mishra

The maritime sector, which contributes approximately 3 % to the total global greenhouse gas (GHG) emissions, is under increasing scrutiny to meet the decarbonization targets set forth by the International Maritime Organization (IMO) for the year 2050. Biodiesel, characterized by its renewable attributes and potential to diminish GHG emissions by as much as 80 %, emerges as a plausible alternative to traditional marine fuels. This research conducts a comprehensive analysis of the significance of biodiesel in the context of marine decarbonization, accentuating its benefits, which include reductions in Nitrogen oxide (Nox) emissions by up to 40 % and enhancements in fuel efficiency ranging from 3 % to 5 %, achieved through advancements such as nanoparticle additives and hybrid engine technologies. The study identifies challenges associated with biodiesel, including its 10 % to 12 % lower energy density and suboptimal cold flow characteristics, while proposing solutions that encompass innovative additives and thermal management strategies. The discourse further encompasses policy implications, logistical considerations of the supply chain, and the exploration of emerging feedstocks, notably algae-derived biodiesel. These insights establish biodiesel as a pragmatic, scalable, and ecologically sustainable fuel alternative for the maritime sector while delineating avenues to mitigate technological and operational challenges.

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引用次数: 0

Recent advancements in additively manufactured hip implant design using topology optimization technique

IF 6 Q1 ENGINEERING, MULTIDISCIPLINARY

Results in Engineering

Pub Date : 2025-01-02 DOI: 10.1016/j.rineng.2025.103932

Abdulla All Noman , Mohd Shamil Shaari , Hassan Mehboob , Abdul Hadi Azman

The recent advancement of additive manufacturing (AM) offers many benefits for the medical sector, which is revolutionizing modern bone repair surgery for patients, including those with damaged hip joints. Consequently, AM enables the fabrication of hip replacements made of alloys like titanium, cobalt-chromium, stainless steel, and their alloys. Porous additive-manufactured hip implants possess various advantages, including patient-specific implant design, reduced production cost, mass reduction, and a longer implant life by alleviating stress shielding. Mass and stress shielding reduction of the implants can be achieved through topology optimization techniques incorporating cellular structures. Therefore, porous implant design, topology optimization, and additive manufacturing can merge to improve patient health and medical advancement. Hence, by integrating these three elements, this review represents the recent advancements in the topology optimization of hip implants using the AM technique for designing and fabricating porous hip implants.

引用次数: 0

Artificial intelligence-enhanced solubility predictions of greenhouse gases in ionic liquids: A review

IF 6 Q1 ENGINEERING, MULTIDISCIPLINARY

Results in Engineering

Pub Date : 2025-01-02 DOI: 10.1016/j.rineng.2024.103851

Bilal Kazmi , Syed Ali Ammar Taqvi , Dagmar Juchelkov , Guoxuan Li , Salman Raza Naqvi

Greenhouse gas emissions from human activities pose a significant threat to the ecosystem, causing climate change and ecological disruptions. Ionic liquids (ILs) show promise for gas separation and carbon capture, but predicting gas solubility in ILs is challenging due to limited data and complex thermodynamics. Artificial intelligence (AI) offers an innovative approach to improve the efficiency and accuracy of solubility predictions. This review analyzes recent advancements in AI-enabled solubility predictions, focusing on methodologies, models, and applications in gas separation and carbon capture. It examines artificial neural networks, deep learning models, and support vector machines for predicting solubility in ILs, and presents valuable results demonstrating the potential of these techniques. The study highlights AI's transformative power in understanding gas-IL interactions and inspiring environmentally friendly separation processes. It also discusses integrating AI-driven predictions with process modeling tools like Aspen Hysys and Aspen Plus, aiming to stimulate further research in gas separation technologies and pave the way for practical implementation.

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引用次数: 0

Recent developments in stimuli-responsive polymer for emerging applications: A review

IF 6 Q1 ENGINEERING, MULTIDISCIPLINARY

Results in Engineering

Pub Date : 2025-01-01 DOI: 10.1016/j.rineng.2024.103900

Abdelrahman K.A. Khalil , Yeit Haan Teow , Mohd Sobri Takriff , Abdul Latif Ahmad , Muataz Ali Atieh

Stimuli-responsive polymers (SRPs) are among the most significant classes of smart materials (SM), undergoing dynamic changes in response to environmental stimuli such as temperature, pH, and electromagnetic fields. These versatile materials are increasingly critical in domains including drug delivery (DD), tissue engineering (TE), water treatment (WT), and environmental sensing (ES). Recent advancements in SRPs, as reported in the literature, are classified into thermo-, pH-, and multi-responsive categories. Both natural and synthetic varieties are examined, focusing on their properties, behaviors, and mechanisms that enable adaptive functionalities. Special emphasis is placed on their applications in developing more efficient DD systems, innovative solutions for TE, and highly sensitive environmental sensors. The synthesis, functionalities, and integration of SRPs with complex biomedical and technological systems are discussed, highlighting their potential to revolutionize these fields. This review offers comprehensive and critically valuable insights into the use of SRPs in SM applications, paving the way for developing more effective and sustainable responsive technologies.

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引用次数: 0

A review on bio-inspired corrosion resistant superhydrophobic coating on copper substrate: recent advances, mechanisms, constraints, and future prospects

IF 6 Q1 ENGINEERING, MULTIDISCIPLINARY

Results in Engineering

Pub Date : 2024-12-31 DOI: 10.1016/j.rineng.2024.103868

Himanshu Prasad Mamgain , Pravat Ranjan Pati , Krishna Kanta Samanta , Ranjeet Brajpuriya , Rajeev Gupta , Jitendra Kumar Pandey , Jayant Giri , T Sathish , Mohammad Kanan

Corrosion poses significant challenges, leading to material deterioration and adverse effects on characteristics like conductivity and malleability, resulting in infrastructure failures and economic losses. Traditional corrosion prevention methods have limitations, such as high costs and limited effectiveness. Nanostructured superhydrophobic coatings (SH) have emerged as promising solutions due to their effectiveness in preventing corrosion and diverse industrial applications. These coatings leverage low surface energy and high surface roughness to create micro air pockets, reducing contact with corrosive media and water droplets, thus enhancing corrosion resistance. This review discusses recent advancements in physical and chemical techniques for producing corrosion-resistant SH coatings on copper substrates and their compatibility with other metals while maintaining stability. Researchers have explored various surface morphologies, textures, and energies to impede corrosion effectively. The paper emphasizes the novelty of these developments, highlighting both limitations and potential future directions for SH coatings.

{"title":"A review on bio-inspired corrosion resistant superhydrophobic coating on copper substrate: recent advances, mechanisms, constraints, and future prospects","authors":"Himanshu Prasad Mamgain , Pravat Ranjan Pati , Krishna Kanta Samanta , Ranjeet Brajpuriya , Rajeev Gupta , Jitendra Kumar Pandey , Jayant Giri , T Sathish , Mohammad Kanan","doi":"10.1016/j.rineng.2024.103868","DOIUrl":"10.1016/j.rineng.2024.103868","url":null,"abstract":"<div><div>Corrosion poses significant challenges, leading to material deterioration and adverse effects on characteristics like conductivity and malleability, resulting in infrastructure failures and economic losses. Traditional corrosion prevention methods have limitations, such as high costs and limited effectiveness. Nanostructured superhydrophobic coatings (SH) have emerged as promising solutions due to their effectiveness in preventing corrosion and diverse industrial applications. These coatings leverage low surface energy and high surface roughness to create micro air pockets, reducing contact with corrosive media and water droplets, thus enhancing corrosion resistance. This review discusses recent advancements in physical and chemical techniques for producing corrosion-resistant SH coatings on copper substrates and their compatibility with other metals while maintaining stability. Researchers have explored various surface morphologies, textures, and energies to impede corrosion effectively. The paper emphasizes the novelty of these developments, highlighting both limitations and potential future directions for SH coatings.</div></div>","PeriodicalId":36919,"journal":{"name":"Results in Engineering","volume":"25 ","pages":"Article 103868"},"PeriodicalIF":6.0,"publicationDate":"2024-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143166242","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Deployment of piezoelectric transducers for diverse technical applications: A comprehensive review

IF 6 Q1 ENGINEERING, MULTIDISCIPLINARY

Results in Engineering

Pub Date : 2024-12-31 DOI: 10.1016/j.rineng.2024.103881

Chirantan Shee, Swagata Banerjee, R. Alagirusamy, S. Wazed Ali

Piezoelectric materials are used in various applications due to its unique electro-mechanical coupling ability. To restrict the consumption of exhaustible energy sources, piezoelectric materials have been widely explored for converting mechanical energy into electrical energy. However, exploration of piezoelectric materials in other various advanced applications like sound absorption, water treatment, oil-water separation are not documented systematically to the best of our knowledge. It appears that piezoelectric materials are conventionally explored extensively for energy harvesting applications. But their other innovative technical applications are still in their infancy stage. There lies a huge scope in development and implementation of these materials for other new domains. Thus, the prime focus of the present article is to explore such unique materials in areas other than their conventional usages. The compilation would help the readers to expand their domain knowledge for utilization of piezoelectric materials in innovative applications and motivate the researchers to explore applications for future needs. In the onset of this review, the basic understanding of piezoelectricity is explained. Thereafter, different applications of piezoelectric materials like energy harvesting, sound absorption, water treatment, structural health monitoring and applications in biomedical segment are critically analyzed.

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引用次数: 0

Artificial intelligence and machine learning techniques for power quality event classification: a focused review and future insights

IF 6 Q1 ENGINEERING, MULTIDISCIPLINARY

Results in Engineering

Pub Date : 2024-12-31 DOI: 10.1016/j.rineng.2024.103873

Indu Sekhar Samanta , Sarthak Mohanty , Shubhranshu Mohan Parida , Pravat Kumar Rout , Subhasis Panda , Mohit Bajaj , Vojtech Blazek , Lukas Prokop , Stanislav Misak

Power Quality (PQ) disturbances are critical in modern power systems, significantly impacting electrical networks' stability, reliability, and efficiency. With the increasing penetration of renewable energy sources, non-linear loads, and power electronic devices, the detection, classification, and mitigation of PQ disturbances have become more complex. Traditional PQ analysis methods, which rely heavily on human expertise and rule-based systems, are often insufficient in handling the growing complexity and volume of data in real-time applications. This review comprehensively analyzes the latest advancements in Artificial Intelligence (AI) and Machine Learning (ML) techniques applied to PQ analysis, achieving classification accuracies as high as 99.94 % with hybrid approaches like dual-tree wavelet packet transforms combined with extreme learning machine (ELM). Integrating advanced signal processing techniques, such as wavelet transforms and empirical mode decomposition, has demonstrated accuracy improvements of up to 5 % in challenging scenarios. This paper explores the challenges associated with AI-based PQ analysis, including the need for large datasets, overfitting issues, and the lack of interpretability in complex models. Future research directions are outlined, emphasizing the development of hybrid models, explainable AI systems, and real-time adaptability to dynamic grid conditions. This review provides a holistic understanding of state-of-the-art AI/ML methods in PQ analysis. It highlights their potential to transform modern power systems by ensuring higher reliability, better fault detection, and more efficient power delivery.

{"title":"Artificial intelligence and machine learning techniques for power quality event classification: a focused review and future insights","authors":"Indu Sekhar Samanta , Sarthak Mohanty , Shubhranshu Mohan Parida , Pravat Kumar Rout , Subhasis Panda , Mohit Bajaj , Vojtech Blazek , Lukas Prokop , Stanislav Misak","doi":"10.1016/j.rineng.2024.103873","DOIUrl":"10.1016/j.rineng.2024.103873","url":null,"abstract":"<div><div>Power Quality (PQ) disturbances are critical in modern power systems, significantly impacting electrical networks' stability, reliability, and efficiency. With the increasing penetration of renewable energy sources, non-linear loads, and power electronic devices, the detection, classification, and mitigation of PQ disturbances have become more complex. Traditional PQ analysis methods, which rely heavily on human expertise and rule-based systems, are often insufficient in handling the growing complexity and volume of data in real-time applications. This review comprehensively analyzes the latest advancements in Artificial Intelligence (AI) and Machine Learning (ML) techniques applied to PQ analysis, achieving classification accuracies as high as 99.94 % with hybrid approaches like dual-tree wavelet packet transforms combined with extreme learning machine (ELM). Integrating advanced signal processing techniques, such as wavelet transforms and empirical mode decomposition, has demonstrated accuracy improvements of up to 5 % in challenging scenarios. This paper explores the challenges associated with AI-based PQ analysis, including the need for large datasets, overfitting issues, and the lack of interpretability in complex models. Future research directions are outlined, emphasizing the development of hybrid models, explainable AI systems, and real-time adaptability to dynamic grid conditions. This review provides a holistic understanding of state-of-the-art AI/ML methods in PQ analysis. It highlights their potential to transform modern power systems by ensuring higher reliability, better fault detection, and more efficient power delivery.</div></div>","PeriodicalId":36919,"journal":{"name":"Results in Engineering","volume":"25 ","pages":"Article 103873"},"PeriodicalIF":6.0,"publicationDate":"2024-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143166214","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Advanced control strategies for microgrids: A review of droop control and virtual impedance techniques

IF 6 Q1 ENGINEERING, MULTIDISCIPLINARY

Results in Engineering

Pub Date : 2024-12-30 DOI: 10.1016/j.rineng.2024.103799

K.N. Yogithanjali Saimadhuri, M. Janaki

In microgrids, stability is ensured by maintaining a power ratio that balances total energy production and demand via coordinated management of various distributed generation (DG) units. In recent years, there has been intense research on incorporating advanced techniques into control methods for microgrids. However, a thorough examination of the hierarchical control methods for various microgrid topologies is rarely addressed. Specifically, the interplay between control methodologies namely centralized, decentralized, and distributed across AC, DC, and hybrid microgrids has not been thoroughly explored. This study fills that gap by offering a comprehensive overview of microgrid architectures and hierarchical control methods, with a special emphasis on their application to various topologies. In contrast to previous studies, this study critically investigates how two popular control strategies namely droop control and virtual impedance strategies are implemented in parallel-connected inverters for efficient power sharing. We also highlight various approaches, challenges, limitations, advancements and a comparative analysis to direct further study and real-world implementations. This review is a helpful resource for researchers and practitioners looking to improve the stability and efficiency of microgrid systems using novel control techniques.

{"title":"Advanced control strategies for microgrids: A review of droop control and virtual impedance techniques","authors":"K.N. Yogithanjali Saimadhuri, M. Janaki","doi":"10.1016/j.rineng.2024.103799","DOIUrl":"10.1016/j.rineng.2024.103799","url":null,"abstract":"<div><div>In microgrids, stability is ensured by maintaining a power ratio that balances total energy production and demand via coordinated management of various distributed generation (DG) units. In recent years, there has been intense research on incorporating advanced techniques into control methods for microgrids. However, a thorough examination of the hierarchical control methods for various microgrid topologies is rarely addressed. Specifically, the interplay between control methodologies namely centralized, decentralized, and distributed across AC, DC, and hybrid microgrids has not been thoroughly explored. This study fills that gap by offering a comprehensive overview of microgrid architectures and hierarchical control methods, with a special emphasis on their application to various topologies. In contrast to previous studies, this study critically investigates how two popular control strategies namely droop control and virtual impedance strategies are implemented in parallel-connected inverters for efficient power sharing. We also highlight various approaches, challenges, limitations, advancements and a comparative analysis to direct further study and real-world implementations. This review is a helpful resource for researchers and practitioners looking to improve the stability and efficiency of microgrid systems using novel control techniques.</div></div>","PeriodicalId":36919,"journal":{"name":"Results in Engineering","volume":"25 ","pages":"Article 103799"},"PeriodicalIF":6.0,"publicationDate":"2024-12-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143166247","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Transforming education with AI: A systematic review of ChatGPT's role in learning, academic practices, and institutional adoption

IF 6 Q1 ENGINEERING, MULTIDISCIPLINARY

Results in Engineering

Pub Date : 2024-12-30 DOI: 10.1016/j.rineng.2024.103837

Sayeed Salih , Omayma Husain , Mosab Hamdan , Samah Abdelsalam , Hashim Elshafie , Abdelwahed Motwakel

The integration of AI tools like ChatGPT into education has generated significant interest due to their potential to transform learning environments by providing personalized learning, automating tasks, and improving student engagement. However, gaps remain in the literature, particularly in comparing AI-supported education methods with traditional approaches and understanding ChatGPT's specific role in academic writing, literature reviews, and teacher development. This study addresses these gaps through a systematic literature review (SLR), evaluating the effectiveness of AI tools versus traditional teaching approaches. It focuses on ChatGPT's application in areas such as academic writing, lesson planning, student assessment, and the professional development of educators. Additionally, the study explores institutional strategies for balancing the benefits of AI with the need to maintain academic integrity and educational quality. The methodology involved a systematic search across academic databases with a structured analysis of key studies in AI-supported education. The main contributions include identifying the comparative advantages and limitations of AI in enhancing student learning, offering best practices for incorporating AI tools into teaching, and examining prompt engineering as a crucial factor in optimizing AI usage. The study reveals that ChatGPT and other AI tools significantly enhance educational efficiency and engagement, but they require careful management to prevent over-reliance. The study advocates for a balanced approach, integrating both AI and traditional methods to achieve optimal educational outcomes while maintaining academic integrity.

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