Results in Engineering最新文献

{"title":"Indoor environmental quality and achieving performance goals for classroom enhancement: A systematic literature review and bibliometric analysis","authors":"Dedar Salam Khoshnaw ,&nbsp;Faris Ali Mustafa ,&nbsp;Tamás János Katona ,&nbsp;Bálint Baranyai","doi":"10.1016/j.rineng.2025.106082","DOIUrl":"10.1016/j.rineng.2025.106082","url":null,"abstract":"<div><div>School structures are crucial in shaping the upcoming generation's perspective on the future's sustainability. Therefore, to improve indoor environmental quality (IEQ) in school classrooms, four performance goals (PG) should be considered. These goals include reducing energy consumption, ensuring overall comfort, promoting occupant health, and enhancing student productivity. Ten holistic approach design methods (HAD) were identified to achieve these objectives. Despite the significant attention this field has garnered, there is uncertainty regarding the potential of different HAD types to influence the PG in various climate conditions. To address this uncertainty, 135 papers were reviewed across nine databases. This paper demonstrates the combined IEQ and key PG on enhancing classrooms through a systematic literature review and bibliometric analysis conducted to assess the development of this field. Then, the investigated HAD was introduced into PG in different climate zones. The review revealed that almost all HAD tested in the temperate zone (C) successfully achieved the goals. Conversely, tropical (A), dry (B), and cold (D) zones faced significant environmental challenges, complicating the implementation and effectiveness of these HAD. This review concluded that enhancing classrooms’ IEQ with HAD necessitates comprehensively considering multiple HADs rather than individual ones. Furthermore, most studies in climates A, B, and D have only focused on a few HAD aspects, resulting in substantial variations in the depth of research among different HAD categories and the applicability of PG in different climate zones. The result guides the selection of an appropriate HAD that is suitable for various climate zones to achieve PG and better IEQ in classrooms.</div></div>","PeriodicalId":36919,"journal":{"name":"Results in Engineering","volume":"27 ","pages":"Article 106082"},"PeriodicalIF":6.0,"publicationDate":"2025-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144604670","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Advancing metallic implant: A review of magnesium alloys as bio-absorbable alternatives to orthopedic devices","authors":"Biranu Kumsa Gonfa,&nbsp;Moera Gutu Jiru,&nbsp;Esmael Adem Esleman","doi":"10.1016/j.rineng.2025.106091","DOIUrl":"10.1016/j.rineng.2025.106091","url":null,"abstract":"<div><div>Permanent biomedical devices have been used as the backbone of orthopedic medical devices for decades due to their mechanical behavior, durability, and biocompatibility. However, these permanent devices showed limitations due to their stress-shielding effect, long-term inflammatory response, and require secondary surgery for removal of the implant after healing is completed. Consequently, the transformation is shifted from a permanent implant to a temporary implant, which is a bioabsorbable metallic implant used during bone tissue healing as a mechanical support for a temporary period and subsequently degrades and eliminates the need for secondary surgery. Magnesium alloy implants have shown as a promising bioabsorbable metallic implant due to their biodegradability, biocompatibility, and mechanical behavior related to bone. However, the abiding problem of Mg-based orthopedic implants is their fast degradation rate, release of Mg²⁺ and hydrogen (which causes bubbles and delayed healing) in the human body, and mechanical failure before completion of healing, thus hindering their clinical applicability. In order to improve the above problems, several researchers have explored and applied different techniques such as alloy composition, surface modification techniques as effective and efficient ways. Therefore, this review comprehensively examines the highlights of permanent and temporary implants, the degradation mechanism of magnesium in vivo, factors affecting the performance of magnesium alloys orthopedic implants, and performance optimization of magnesium-based orthopedic implants in orthopedic applications.</div></div>","PeriodicalId":36919,"journal":{"name":"Results in Engineering","volume":"27 ","pages":"Article 106091"},"PeriodicalIF":6.0,"publicationDate":"2025-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144604671","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Occupant-centric indoor assessments and control solutions in healthcare facilities: a critical review of restorative perception","authors":"Jiake Yang,&nbsp;Yidan Wu,&nbsp;S. Thomas Ng","doi":"10.1016/j.rineng.2025.106010","DOIUrl":"10.1016/j.rineng.2025.106010","url":null,"abstract":"<div><div>The primary function of healthcare facility environments is to support the recovery of its occupants. Numerous studies have examined how indoor environmental quality (IEQ) and physical design factors in healthcare facilities affect occupants and the effectiveness of control methods, respectively. However, results from independent studies on influential elements may conflict, lack transferability, and recoverability. Therefore, a holistic review on indoor environments and related control methods for healthcare facilities from the restorative perspective is needed. This study analyzes 249 articles to examine the indoor environment’s impact on residents’ restorative perceptions and related control behaviors. It also explores automation modeling methods across various healthcare settings. The results show that the setting of different environments and occupant roles in healthcare buildings can have an impact on the evaluation of the indoor environment. Indoor environmental factors are diverse but lack generalization, and existing standards and models fail to adequately address practical needs, highlighting the need for expanded cross-disciplinary research. Although qualitative evaluation and results on IEQ and physical design factors could be applied to satisfy some groups’ needs, there is a lack of quantitative, personalized and dynamic evaluation frameworks in current healthcare environments. Existing control methods are still predominantly manual, relying on personal literacy and perception, and lack integration and application with automated control technologies. To bridge this gap, this paper outlines future directions and designs a conceptual framework, offering insights for stakeholders on design standards and advanced technology applications to better align healthcare interiors with occupants' needs.</div></div>","PeriodicalId":36919,"journal":{"name":"Results in Engineering","volume":"27 ","pages":"Article 106010"},"PeriodicalIF":6.0,"publicationDate":"2025-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144580946","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The self-healing property of rock salt damage in underground gas storage: A review","authors":"Junsong Chang ,&nbsp;Yaodong Qi ,&nbsp;Ruixuan Yang ,&nbsp;Tian Hao","doi":"10.1016/j.rineng.2025.106098","DOIUrl":"10.1016/j.rineng.2025.106098","url":null,"abstract":"<div><div>Deep underground energy storage represents a crucial avenue for future energy reserve development. Rock salt is globally acknowledged as an optimal medium for energy storage due to its good creep, low permeability, and self-healing capabilities. However, underground compressed air salt caverns are susceptible to damage due to disturbances such as injection and production pressure, leading to increased permeability and compromising the sealing and stability of the reservoir. Rock salt exhibits strong self-healing capabilities and can recover under favorable conditions. This study examines the progress of research on the self-healing characteristics of rock salt damage and systematically reviews the mechanisms, influencing factors, and constitutive models of rock salt self-healing. The primary factors influencing rock salt self-healing include pressure, temperature, humidity, damage, and microstructure. Pressure and humidity facilitate rock salt self-healing, whereas temperature and damage exhibit threshold-dependent effects on the process. Crack tips, necking regions, and surface impurity zones of the crystal are particularly susceptible to healing. The self-healing constitutive models of rock salt were systematically reviewed, and key research challenges and future directions were discussed to provide critical references for ensuring the long-term stability and safe operation of underground rock salt gas storage.</div></div>","PeriodicalId":36919,"journal":{"name":"Results in Engineering","volume":"27 ","pages":"Article 106098"},"PeriodicalIF":6.0,"publicationDate":"2025-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144580945","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A comprehensive review of data analytics and storage methods in geothermal energy operations","authors":"Ali Basem ,&nbsp;Ahmed Kateb Jumaah Al-Nussairi ,&nbsp;Dana Mohammad Khidhir ,&nbsp;Narinderjit Singh Sawaran Singh ,&nbsp;Mohammadreza Baghoolizadeh ,&nbsp;Mohammad Ali Fazilati ,&nbsp;Soheil Salahshour ,&nbsp;S. Mohammad Sajadi ,&nbsp;Ali Mohammadi Hasanabad","doi":"10.1016/j.rineng.2025.106068","DOIUrl":"10.1016/j.rineng.2025.106068","url":null,"abstract":"<div><div>Geothermal energy storage (<em>GES</em>) systems are thoroughly examined in this research, with a focus on methods like borehole thermal energy storage (<em>BTES</em>), underground thermal energy storage (<em>UTES</em>), and aquifer thermal energy storage (<em>ATES</em>). It highlights the importance of thermal energy storage (<em>TES</em>) systems in addressing global energy challenges. The feasibility of <em>UTES</em> for large-scale energy storage and its integration with geothermal power plants is investigated. The <em>ATES,</em> with the advantage of large storage capacity and low operating costs has could be employed in regions with suitable aquifers. The adaptability of <em>BTES</em> to different ground conditions and its small land footprint made it a spotlight for the researchers. The study emphasizes the role of <em>TES</em> technologies in meeting the growing demand for renewable energy, reducing the impact of climate change, and providing efficient energy solutions for heating, ventilating, and air conditioning. <em>HVAC</em> systems. Also, the application of geothermal power plants and <em>TES</em> systems in decreasing the dependence on nonrenewable energy sources and increasing energy efficiency increase investigated. The development of reliable and affordable sensors, together with improvements in processing power, has made data-intensive algorithms and real-time operational decision-making applications in the field of geothermal energy. The study also delves into the potential of machine learning to optimize geothermal design, monitor performance, improve performance, find errors, and more. It was shown that artificial neural networks were the most common kind of trained model, while several other models were often used as benchmarks for performance. Picture selection, systematic time series feature engineering and model evaluation were all areas that showed a lot of promise in the systematic review for future research and practical applications.</div></div>","PeriodicalId":36919,"journal":{"name":"Results in Engineering","volume":"27 ","pages":"Article 106068"},"PeriodicalIF":6.0,"publicationDate":"2025-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144587496","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Predicting adverse drug reactions in oncology: A critical review of machine learning approaches and future directions","authors":"Abid Yahya ,&nbsp;Phatsimo Lobelo ,&nbsp;Afiya Eram ,&nbsp;Sana Althaf Hussain ,&nbsp;Irfan Anjum Badruddin ,&nbsp;Lory Liza D. Bulay-og ,&nbsp;Dionel O. Albina","doi":"10.1016/j.rineng.2025.106002","DOIUrl":"10.1016/j.rineng.2025.106002","url":null,"abstract":"<div><div>Because of polypharmacy and complicated treatment protocols, adverse drug reactions (ADRs) continue to be a major problem in oncology and frequently lead to serious clinical complications. Recent developments in the use of artificial intelligence (AI) and machine learning (ML) for ADR prediction in anticancer therapy are critically assessed in this review. We go over a variety of methods for utilizing both structured and unstructured clinical data, such as supervised, unsupervised, and deep learning models in addition to natural language processing (NLP) strategies. Strong performance has been demonstrated by ensemble techniques like Random Forest and Gradient Boosting, while deep neural networks allow for sophisticated feature extraction, albeit with interpretability issues. We highlight new integrative techniques based on current literature trends, such as integrating demographic information, treatment history, and physiological signals with CNN-based models and SHAP-based.</div></div>","PeriodicalId":36919,"journal":{"name":"Results in Engineering","volume":"27 ","pages":"Article 106002"},"PeriodicalIF":6.0,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144536021","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Predicting plant uptake of potential contaminants of emerging concerns using machine learning models (2018–2025): A global review","authors":"Alexis Munyengabe,&nbsp;Maria Fezile Banda,&nbsp;Wilma Augustyn","doi":"10.1016/j.rineng.2025.106050","DOIUrl":"10.1016/j.rineng.2025.106050","url":null,"abstract":"<div><div>This comprehensive review (2018–2025) synthesizes studies conducted on machine learning (ML) models to predict plant uptake of contaminants of emerging concerns (CECs). CECs are a global concern driven by anthropogenic activities, and their plant uptake is critical for environmental remediation and food safety. ML offers powerful predictive opportunities, fostering ecosystem preservation, human health and sustainable development. The review analyzes diverse ML algorithms, including ensemble models (random forest, gradient boosted regression trees, eXtreme gradient boosting) and deep learning (deep neural networks, recurrent neural networks, long short-term memory) alongside key predictors like soil pH, organic matter, and plant traits. It identifies dominant predictors and modelling approaches while highlighting significant research gaps: limited data, inconsistent feature reporting, and underexplored uncertainty-sensitivity coupling. A notable geographic imbalance exists, with China dominating research (82.1 % of 28 studies), followed by the USA (14.3 %) and Italy (3.6 %). Africa, particularly South Africa, is significantly underrepresented despite prevalent CEC pollution in African water bodies, including those used for irrigation, and agricultural vulnerabilities. This reveals a critical gap in global efforts to address crop contaminant risk, necessitating model retraining or transfer learning for African contexts given existing models' China-centric training. The findings underscore the urgent need for standardized databases, global sensitivity and uncertainty analysis and expanded geographic representation to enhance model generalizability and interpretability. This synthesis bridges environmental chemistry, plant physiology and artificial intelligence in predictive contaminant modelling, providing a foundation for future, globally relevant research.</div></div>","PeriodicalId":36919,"journal":{"name":"Results in Engineering","volume":"27 ","pages":"Article 106050"},"PeriodicalIF":6.0,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144571853","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Green Hydrogen: Unleashing the Potential for Sustainable Energy Generation","authors":"M.A. Elazab ,&nbsp;Abdelrahman T. Elgohr ,&nbsp;Mohamed Bassyouni ,&nbsp;Abd Elnaby Kabeel ,&nbsp;Mohammed El Hadi Attia ,&nbsp;Mohamed Kamel Elshaarawy ,&nbsp;Abdelrahman Kamal Hamed ,&nbsp;Hassan A.H. Alzahrani","doi":"10.1016/j.rineng.2025.106031","DOIUrl":"10.1016/j.rineng.2025.106031","url":null,"abstract":"<div><div>Green hydrogen is poised to play a pivotal role in the transition to a sustainable, carbon-neutral future. This study provides a comprehensive review of the production, storage, transportation, and applications of green hydrogen. Generated through electrolysis using renewable energy sources, green hydrogen is a clean, versatile energy carrier with significant potential to decarbonize key sectors such as transportation, industry, and power generation. The decreasing costs of renewable energy, particularly solar and wind, coupled with advancements in electrolysis technologies, have enhanced the economic viability of green hydrogen production. However, challenges persist, including improving efficiency, reducing costs, scaling infrastructure, and ensuring safety. The study emphasizes the necessity of addressing these barriers to enable widespread adoption. Green hydrogen offers numerous environmental benefits, such as storing surplus renewable energy, acting as a zero-emission fuel, and significantly mitigating greenhouse gas emissions. Its application in hard-to-abate industries, like steel and cement manufacturing, further highlights its role in supporting global sustainability goals. This review also underscores the importance of collaborative efforts among governments, industries, and researchers to advance green hydrogen technologies. By fostering innovation and public acceptance, green hydrogen can accelerate the energy transition and contribute to long-term climate resilience. This work provides actionable insights to promote the adoption of green hydrogen, showcasing its potential to reshape energy systems and support a low-carbon economy.</div></div>","PeriodicalId":36919,"journal":{"name":"Results in Engineering","volume":"27 ","pages":"Article 106031"},"PeriodicalIF":6.0,"publicationDate":"2025-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144549734","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A review on the effectiveness of FRP and hybrid wrappings for strengthening concrete columns","authors":"Azzam Ahmed","doi":"10.1016/j.rineng.2025.106023","DOIUrl":"10.1016/j.rineng.2025.106023","url":null,"abstract":"<div><div>This review investigates the effectiveness of fibre-reinforced polymer (FRP) and hybrid wrappings in enhancing the axial compressive performance of concrete columns. It focuses on various FRP types, such as CFRP, GFRP, BFRP, and AFRP, as well as their configurations (full, partial, and hybrid). A systematic analysis covers mechanical performance, confinement efficiency, and recent advancements in analytical and finite element models. The review critically compares some selected design-oriented and analysis-oriented stress–strain models, categorizing them based on their applicability to fully and partially confined concrete. Emphasis is placed on low-strength concrete applications and novel hybrid systems. Unlike previous reviews, this study integrates recent experimental data, advanced modelling developments, and hybrid confinement systems into a unified framework, offering a comprehensive and practical resource for selecting and optimizing FRP confinement strategies, particularly for low-strength and partially confined concrete, thus addressing critical gaps in both research and design applications.</div></div>","PeriodicalId":36919,"journal":{"name":"Results in Engineering","volume":"27 ","pages":"Article 106023"},"PeriodicalIF":6.0,"publicationDate":"2025-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144518197","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Navigating the spectrum of battery health management in electric vehicles: A comprehensive review","authors":"Saranathan L ,&nbsp;Indragandhi Vairavasundaram ,&nbsp;Bragadeshwaran Ashok","doi":"10.1016/j.rineng.2025.106038","DOIUrl":"10.1016/j.rineng.2025.106038","url":null,"abstract":"<div><div>Lithium-ion batteries (LIBs) are a cornerstone of modern electric vehicles (EVs) due to their high energy density, long lifespan, and excellent performance. However, ensuring their reliability and longevity presents substantial challenges due to degradation caused by various internal and external factors. This review paper addresses the critical problem of accurately estimating the state of health (SoH), remaining useful life (RUL), and battery ageing in dynamic operating environments. The existing literature lacks a consolidated comparative analysis of traditional, adaptive, and emerging data-driven approaches to battery health management, particularly in the context of real-world applications. This review presents an in-depth synthesis of conventional methods, model-based techniques, adaptive filtering, and artificial intelligence (AI)-driven strategies including machine learning (ML), fuzzy logic, and cloud-integrated frameworks for SoH, RUL, and ageing prediction. Furthermore, the paper discusses the implications of battery cycling databases and highlights how open-source data and modern computational advancements support scalable predictive analytics. A comparative critique of various methodologies is provided to evaluate performance, adaptability, and real-world feasibility. The review identifies key challenges and research gaps, emphasizing the need for model interpretability, real-time validation, and long-term performance assessment. Overall, this paper contributes to the academic and industrial understanding of predictive battery management, guiding future research toward the development of accurate, interpretable, and scalable models that ensure sustainable EV battery operation.</div></div>","PeriodicalId":36919,"journal":{"name":"Results in Engineering","volume":"27 ","pages":"Article 106038"},"PeriodicalIF":6.0,"publicationDate":"2025-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144536020","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}