Cleaner Engineering and Technology最新文献

{"title":"Optimization of engine parameters and emission profiles through bio-additives: Insights from ANFIS Modeling of Diesel Combustion","authors":"Abbas Rohani ,&nbsp;Javad Zareei ,&nbsp;Kourosh Ghadamkheir ,&nbsp;Seyed Alireza Farkhondeh","doi":"10.1016/j.clet.2025.100994","DOIUrl":"10.1016/j.clet.2025.100994","url":null,"abstract":"<div><div>The effects of bio-additives on combustion characteristics and engine performance in an OM355 EU II diesel engine were investigated. Numerical simulations were conducted across a wide range of operating conditions, including engine speed, fuel blends, equivalence ratio, and exhaust gas recirculation (EGR) rates. Key performance metrics, such as torque, power, engine efficiency, indicated specific fuel consumption (ISFC), combustion noise, NOx emissions, and soot behavior, were evaluated. It was found that a reduction in bioethanol content, combined with an increase in the equivalence ratio to 1.2, resulted in a significant improvement in Brake Mean Effective Pressure (BMEP). Furthermore, an increase in soybean methyl ester (SME) content in the fuel blend was observed to reduce combustion noise by alleviating sharp pressure gradients. Higher bioethanol content and EGR rates were associated with lower soot production and NOx emissions, with a blend of 50 % bioethanol and 10 % EGR achieving a 16.7 % reduction in NOx emissions compared to diesel fuel with 0 % EGR. Additionally, an Adaptive Neuro-Fuzzy Inference System (ANFIS) model was developed to predict combustion characteristics, engine parameters, and exhaust gas emissions. Various machine learning configurations and training algorithms were employed to optimize the model's performance. The findings of this study provide valuable insights into the optimization of engine performance and the reduction of emissions through the use of bio-additives.</div></div>","PeriodicalId":34618,"journal":{"name":"Cleaner Engineering and Technology","volume":"27 ","pages":"Article 100994"},"PeriodicalIF":5.3,"publicationDate":"2025-05-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144107604","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":"Optimization of a resilient circular closed-loop supply chain network under uncertainty","authors":"Samira Mehrabi ,&nbsp;Hassan Mina ,&nbsp;Shahryar Sorooshian","doi":"10.1016/j.clet.2025.100995","DOIUrl":"10.1016/j.clet.2025.100995","url":null,"abstract":"<div><div>Lubricating oils are among the most widely used petroleum fractions since they are used by different machines and vehicles. In addition to cooling the engine and reducing the friction between moving mechanical parts, motor oil also absorbs pollutants such as sludge, peroxides, and debris that are accumulated in the engine. Therefore, used motor oils are the dangerous materials that can have adverse impacts on the environment and living organisms if not properly managed. Hence, for the first time, this article develops a new bi-objective mixed-integer linear programming (BOMILP) model to form a resilient circular closed-loop supply chain network for managing the used motor oils. Moreover, with the aim of achieving advanced sustainability and circularity goals, the proposed model manages collecting, recycling, producing, and purchasing gallons. Moreover, this study applies a scenario-based stochastic programming method to control the demand uncertainty, and provides a novel fuzzy goal programming method to solve the developed BOMILP model. Finally, the data of an Iranian motor oil production company is applied to validate the proposed optimization model and evaluate the performance of the presented multi-objective solution approach. The results derived from implementing the developed optimization model in the real world and conducting the sensitivity analysis process denote the effectiveness and accuracy of the developed optimization model and solution method.</div></div>","PeriodicalId":34618,"journal":{"name":"Cleaner Engineering and Technology","volume":"27 ","pages":"Article 100995"},"PeriodicalIF":5.3,"publicationDate":"2025-05-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144090239","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":"Enhancing carbon fiber composites with fish scale biochar for superior strength and environmental sustainability","authors":"Sundarakannan Rajendran ,&nbsp;Geetha Palani ,&nbsp;Arumugaprabu Veerasimman ,&nbsp;Vigneshwaran Shanmugam ,&nbsp;Uthayakumar Marimuthu ,&nbsp;Kinga Korniejenko ,&nbsp;Herri Trilaksana ,&nbsp;Arnas Majumder ,&nbsp;Flavio Stochino","doi":"10.1016/j.clet.2025.100996","DOIUrl":"10.1016/j.clet.2025.100996","url":null,"abstract":"<div><div>There is a pressing need to develop carbon fiber composites with sustainable fillers that enhance their strength without increasing costs or environmental impact. Such advancements would not only improve performance in high-stress applications but also align with global sustainability goals by utilizing eco-friendly materials and reducing waste. This study explores the use of biochar derived from fish scales as a sustainable filler material in carbon fiber epoxy composites. The biochar was produced through pyrolysis and incorporated into the composites at various weight percentages (0 %, 1 %, 3 %, 6 %, 9 %, 12 %, and 15 %). Mechanical properties, including tensile strength, flexural strength, impact strength, and interlaminar shear strength, were evaluated according to ASTM standards. The results demonstrated that the incorporation of biochar significantly improved the mechanical properties of the composites, with optimal performance observed at 9 % biochar content. At this concentration, the tensile strength increased by 60.02 %–674.21 MPa, the tensile modulus by 74.96 % to 46.05 GPa, the flexural modulus by 58.32 GPa, and the impact strength reached 102.32 kJ/m². It was found that achieving the optimal performance requires an optimal weight percentage of biochar. This study highlights the potential of fish scale-derived biochar as an effective and sustainable filler material for enhancing the performance of carbon fiber composites.</div></div>","PeriodicalId":34618,"journal":{"name":"Cleaner Engineering and Technology","volume":"27 ","pages":"Article 100996"},"PeriodicalIF":5.3,"publicationDate":"2025-05-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143937888","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":"Sustainability analysis and impact assessment of food waste reduction campaign in Chinese higher institution: Towards cleaner environment and energy efficiency","authors":"Bahareh Asefi ,&nbsp;François Nkinahamira ,&nbsp;Olusegun K. Abass ,&nbsp;Moughni Said Maenrouf ,&nbsp;Yunting Liang ,&nbsp;Yuan Meng ,&nbsp;Peizheng Wang","doi":"10.1016/j.clet.2025.100998","DOIUrl":"10.1016/j.clet.2025.100998","url":null,"abstract":"<div><div>Food waste (FW) in China has drawn increasing global attention due to its significant environmental, economic, and societal impacts, necessitating effective management strategies. This study evaluates the “Empty Plate, Full Pocket” initiative, an educational campaign at Hainan Tropical Ocean University (HNTOU), to reduce FW in university canteens and its implications for cleaner production. Using direct weight calculations and questionnaire surveys, FW patterns, environmental emissions, and economic costs were analyzed in two service styles: self-service (SS) and table-service (TS). The campaign achieved an 83 % reduction in per capita FW for SS and 68 % for TS, resulting in an overall 50 % decrease in total FW. Rice and vegetables were the primary contributors to waste, with dissatisfaction with taste accounting for 80 % of FW. In TS settings, larger portion sizes led to higher waste levels. Environmental benefits derived from the initiative resulted in CO₂ emissions reduction by 86 % for TS and 64 % for SS, while FW-associated economic costs fell by 82 % in TS and 99 % in SS. The study also identified caloric content as a factor influencing purchasing behavior and highlighted key drivers of FW generation. The findings demonstrate how behavioral interventions can complement engineering approaches to address FW challenges, reduce environmental emissions, and enhance resource efficiency in institutional settings. This initiative showcases the potential of targeted campaigns to integrate sustainability principles and cleaner production practices, providing valuable insights for scalable FW management strategies in educational institutions and beyond.</div></div>","PeriodicalId":34618,"journal":{"name":"Cleaner Engineering and Technology","volume":"27 ","pages":"Article 100998"},"PeriodicalIF":5.3,"publicationDate":"2025-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143937764","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":"Comparative analysis of machine learning and conventional methods for waste generation forecasting","authors":"Abdulrahman Abdeljaber ,&nbsp;Sara Al Smadi ,&nbsp;Manar Abu Talib ,&nbsp;Mohamed Abdallah","doi":"10.1016/j.clet.2025.100992","DOIUrl":"10.1016/j.clet.2025.100992","url":null,"abstract":"<div><div>The escalating complexity of waste management systems, driven by rapid environmental and socio-economic shifts, necessitates the development of robust multi-parameter waste generation prediction models. Conventional forecasting methods such as system dynamics, time series, and linear regression have been widely utilized; however, they often fail to fully capture the nuanced dynamics of waste generation, which is influenced by various seasonal and demographic factors. Artificial intelligence (AI) models have emerged as alternative predictors that perform advanced computational techniques to generate accurate forecasts. Despite the extensive research conducted, few review articles have assessed the feasibility of utilizing multiple prediction methods for different waste streams. None has comprehensively assessed and compared the various prediction methods for different waste streams. This review summarizes and analyzes the prediction methodologies implemented for different waste types. This systematic literature review compiles 119 articles from 2000 to 2024. A thorough analysis of AI-based models and a summary of the most influential explanatory variables were provided. The review indicates a predominant focus on municipal waste, with considerable gaps in the forecasting of construction and medical waste streams. System dynamics models were found to excel in strategic waste management planning but can be complex to calibrate and validate. Time series and regression analyses, while useful for identifying trends and relationships, often failed to adapt to rapid or unpredictable changes. Alternatively, machine learning algorithms offer robust capabilities for modeling complex and nonlinear data, although they require substantial data quality and are prone to overfitting. It is concluded that a combined hybrid approach is recommended, leveraging the strengths of different methods to provide more accurate waste generation forecasts. The critical analyses presented can offer insights to decision-makers in the waste management sector by providing key aspects concerning the efficiency and limitations of these predictors.</div></div>","PeriodicalId":34618,"journal":{"name":"Cleaner Engineering and Technology","volume":"27 ","pages":"Article 100992"},"PeriodicalIF":5.3,"publicationDate":"2025-05-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144069708","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":"Multi-criteria decision-making for wind power project feasibility: Trends, techniques, and future directions","authors":"Ade Gafar Abdullah ,&nbsp;Hasna Putri Utami ,&nbsp;Budi Gunawan ,&nbsp;Barito Mulyo Ratmono ,&nbsp;Naek Tua Pasaribu","doi":"10.1016/j.clet.2025.100987","DOIUrl":"10.1016/j.clet.2025.100987","url":null,"abstract":"<div><div>The selection of wind power plant (WPP) locations is critical for renewable energy development, directly impacting plant capacity and long-term socio-economic outcomes. This study analyzes scientific research on WPP location determination across countries, trends in multi-criteria decision-making (MCDM) methods over the past decade, MCDM's effectiveness in developing countries, and key criteria in site selection. A systematic review of 30 journal articles from 16 countries was conducted. Results show that China leads in scientific production, followed by Iran, with publication peaks in 2020, 2021, and 2024. The adoption of MCDM methods, such as AHP, PROMETHEE, and FAHP, has significantly increased, reflecting the need for more complex and accurate evaluations. MCDM enhances efficiency and effectiveness in WPP site selection in developing countries, including Turkey, Iran, Saudi Arabia, and Vietnam, by providing a systematic framework to evaluate criteria holistically. Four main categories of criteria were identified: technical (e.g., wind speed, proximity to grids), environmental (e.g., impacts on protected areas and birds), social (e.g., community acceptance), and economic (e.g., initial investment, maintenance costs). These approaches enable more efficient, sustainable, and context-specific decisions. Future research should integrate artificial intelligence to address dynamic criteria. These findings offer strategic guidance for policymakers and stakeholders to advance sustainable renewable energy development.</div></div>","PeriodicalId":34618,"journal":{"name":"Cleaner Engineering and Technology","volume":"27 ","pages":"Article 100987"},"PeriodicalIF":5.3,"publicationDate":"2025-05-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143943192","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 DEA-based framework for evaluating sustainability and efficiency of vehicle types: Integrating undesirable inputs and social-environmental indicators","authors":"Sara Fanati Rashidi ,&nbsp;Maryam Olfati ,&nbsp;Seyedali Mirjalili ,&nbsp;Jan Platoš ,&nbsp;Vaclav Snášel","doi":"10.1016/j.clet.2025.100989","DOIUrl":"10.1016/j.clet.2025.100989","url":null,"abstract":"<div><div>The sustainability and efficiency of different vehicle types play a crucial role in reducing environmental impacts. As governments and industries move towards greener transportation, choosing an appropriate evaluation method remains a challenge. This study uses data envelopment analysis (DEA) to evaluate the efficiency of five major vehicle types – gasoline, diesel, hybrid, electric, and hydrogen – by considering key economic, environmental, and technical factors such as carbon emissions, fuel costs, and non-recyclable materials. The DEA results are then compared with a multiple regression model to analyze the impact of different independent variables on vehicle efficiency. The results of this study show that electric vehicles have the highest environmental and economic efficiency despite the challenges associated with battery recycling. In contrast, diesel vehicles have the lowest efficiency scores due to their high emissions and environmental costs. This study emphasizes the need for policy incentives to accelerate the adoption of sustainable vehicles, including infrastructure investments, financial incentives, and environmental considerations in efficiency assessments.</div></div>","PeriodicalId":34618,"journal":{"name":"Cleaner Engineering and Technology","volume":"27 ","pages":"Article 100989"},"PeriodicalIF":5.3,"publicationDate":"2025-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143937887","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 dual time-scale optimal dispatch algorithm for PV systems: Integrating centralized optimal power dispatch with distributed power deviation absorption in DC smart grids","authors":"Jiahua Ni ,&nbsp;Yuwei Chen ,&nbsp;Arman Goudarzi ,&nbsp;Tong Wang ,&nbsp;Lingang Yang ,&nbsp;Shengwei Mei","doi":"10.1016/j.clet.2025.100961","DOIUrl":"10.1016/j.clet.2025.100961","url":null,"abstract":"<div><div>The integration of Photovoltaic (PV) systems into DC smart grids faces challenges due to solar power’s inherent unpredictability. Traditional dispatch methods struggle to effectively manage PV power deviations in real-time. This paper proposes a dual time-scale strategy integrating centralized optimization with distributed consensus. On the long-term scale, a convex relaxation-based optimal power flow model minimizes line losses and stabilizes voltages. For short-term adjustments, a distributed consensus algorithm dynamically allocates power deviations among PV sources using reserve capacity, eliminating the need for probabilistic uncertainty modeling. The approach is validated through IEEE 14-node simulations and hardware-in-loop (HIL) tests, with comparisons against centralized methods considering forecast errors. The results demonstrate enhanced voltage stability, highlighting the framework’s practicality for real-time grid management.</div></div>","PeriodicalId":34618,"journal":{"name":"Cleaner Engineering and Technology","volume":"26 ","pages":"Article 100961"},"PeriodicalIF":5.3,"publicationDate":"2025-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143912177","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":"Modelling the effect of a carbon tax on the development of a cultivated protein industry: a Norwegian case study","authors":"Nicholas Roxburgh ,&nbsp;Rob J.F. Burton ,&nbsp;Klaus Mittenzwei ,&nbsp;J. Gareth Polhill","doi":"10.1016/j.clet.2025.100979","DOIUrl":"10.1016/j.clet.2025.100979","url":null,"abstract":"<div><div>Cultivated protein (also called <em>in vitro</em>, lab-based, cultured protein) startups emerged in the 2010s in response to technological advances in the medical/pharmaceutical sector alongside the global demand for more environmentally sustainable food systems. Offering greenhouse gas reductions of up to 97 %, these technologies could provide a means of rapidly reducing emissions from agriculture. However, heavy subsidisation of the livestock sector in many countries puts them at a considerable disadvantage. In this paper we explore what would happen if we rebalanced the equation through the introduction of a carbon tax on animal protein. Using an agent-based approach (ABM) we develop a detailed model of agricultural systems in Norway and explore a number of cost scenarios based around two main hypothetical events: the introduction of cultivated proteins without a carbon tax and the introduction of cultivated proteins alongside a carbon tax. Simulations reveal that conventional beef, lamb, milk, and egg production are more vulnerable to a steady loss of market share to cultivated protein than pork and chicken production – regardless of whether a carbon tax is in operation. However, the introduction of a carbon tax would result in a rapid and substantial decline in these sectors due to the dramatically increased costs imposed on conventional producers and the triggering of tipping points along value chains. Conventional pork and chicken sectors prove more robust due to their comparatively lower emissions. The overall conclusion is that the introduction of a carbon tax alongside the emergence of a cultivated protein industry could have severe impacts on the livestock sector that make the outcome politically unacceptable. Any global or Europe-wide carbon tax could thus, paradoxically, limit the introduction of revolutionary new low-carbon food technologies unless the introduction is carefully managed.</div></div>","PeriodicalId":34618,"journal":{"name":"Cleaner Engineering and Technology","volume":"26 ","pages":"Article 100979"},"PeriodicalIF":5.3,"publicationDate":"2025-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143904233","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":"Sustainable geopolymer footpath block using kaolin mining waste as fine aggregate with bagasse fly ash and coal fly ash as precursor","authors":"Kitisak Vongsook ,&nbsp;Aroondet Boonsung ,&nbsp;Itthikorn Phummiphan ,&nbsp;Suksun Horpibulsuk ,&nbsp;Veena Phunpeng ,&nbsp;Teerasak Yaowarat ,&nbsp;Kanchana Hiranwatthana ,&nbsp;Arul Arulrajah","doi":"10.1016/j.clet.2025.100975","DOIUrl":"10.1016/j.clet.2025.100975","url":null,"abstract":"<div><div>This study aims to develop environmentally friendly footpath blocks by utilizing Kaolin Mining Waste (KMW) as a fine aggregate and fly ash (FA)/bagasse fly ash (BFA) blends as a precursor in the geopolymerization process. These materials, considered industrial by-products, offer the potential for reuse, reducing the reliance on natural resources while promoting sustainability. The experimental works involved substituting FA with BFA at varying proportions by binder weight to identify the optimal ratio for producing footpath blocks that meet standard mechanical requirements. The mechanical characteristics of the footpath blocks were evaluated by testing compressive and flexural strengths, and water absorption. The results indicated that replacing 10 % of FA with BFA (FA90BFA10) accomplished the maximum 28-day compressive strength of 15.6 MPa. A KMW/P ratio of 1.0 proved most effective in increasing flexural strength and minimizing water absorption. Microstructural analysis revealed that combining BFA substitution and the optimal KMW/P ratio created a dense geopolymer matrix with low porosity, enhancing the material's strength and durability. This research demonstrates that integrating KMW, FA, and BFA effectively produces footpath blocks with mechanical properties that meet the local industry standard. Incorporating these agricultural and coal-combustion by-products reduces industrial waste while fostering the manufacture of sustainable footpath block which supports long-term resource conservation.</div></div>","PeriodicalId":34618,"journal":{"name":"Cleaner Engineering and Technology","volume":"26 ","pages":"Article 100975"},"PeriodicalIF":5.3,"publicationDate":"2025-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143886649","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}