Results in Engineering最新文献

{"title":"Study on refined thermal boundary conditions for bridge temperature field analysis","authors":"Yin-Gang Wang ,&nbsp;Xiong-Jun He ,&nbsp;Kai Hu ,&nbsp;Fang Ouyang","doi":"10.1016/j.rineng.2025.107101","DOIUrl":"10.1016/j.rineng.2025.107101","url":null,"abstract":"<div><div>Accurate calculation of bridge temperature fields is of great significance for accurately assessing bridge thermal behavior. Currently, simplified thermal boundary condition models are widely used in bridge thermal analysis, but their deviations from exact solutions remain unquantified. This study systematically investigates the heat exchange mechanisms between bridges and their environment, develops rigorous expressions for bridge thermal boundary conditions, and evaluates the potential errors introduced by simplified models. Results indicate that accurate calculation of long-wave radiation is the primary challenge in bridge thermal analysis. Although some simplified models yield vertical thermal gradients within acceptable engineering accuracy, inappropriate models may overestimate the overall structural temperature by up to 5°C. These findings are validated through field temperature measurements from a concrete bridge. The potential errors arising from model selection should be given sufficient attention when evaluating bridge thermal effects.</div></div>","PeriodicalId":36919,"journal":{"name":"Results in Engineering","volume":"28 ","pages":"Article 107101"},"PeriodicalIF":7.9,"publicationDate":"2025-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145047543","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":"Global insights into biomass pyrolysis mechanisms: A scientometric and mechanistic approach","authors":"Kunmi Joshua Abioye ,&nbsp;Kehinde James Falua ,&nbsp;Mohammad Rezaee ,&nbsp;Mohammad Amin Zamiri ,&nbsp;Fenglou Zou ,&nbsp;Bishnu Acharya","doi":"10.1016/j.rineng.2025.107123","DOIUrl":"10.1016/j.rineng.2025.107123","url":null,"abstract":"<div><div>This review provides a comprehensive analysis of biomass pyrolysis by combining scientometric evaluation with mechanistic insight. The scientometric analysis, based on 174 articles retrieved from Scopus database, traced the evolution of biomass pyrolysis mechanism research from 1989, with significant growth observed from 2019 onwards. China, United States, and United Kingdom emerged as leading contributors in publication output, while China, United States, and Italy led in citation impact. Influential researchers such as Chen Hanping and Yang Haiping, along with key journals including <em>Journal of Analytical and Applied Pyrolysis, Fuel</em>, and <em>Energy &amp; Fuels</em>, have significantly shaped the field. Keyword co-occurrence analysis identified five major research themes: thermal decomposition and analytical techniques; co-pyrolysis and synergistic effects; catalytic pyrolysis and product analysis; component chemistry in biomass conversion; and reactor design and performance. The mechanistic analysis focused on the distinct thermal degradation behaviors of all the six biomass components, which underwent characteristic reactions such as dehydration, depolymerization, and decarboxylation, influencing the yield of pyrolysis products. By combining scientometric trends with mechanistic understanding, this study clarifies research evolution, key contributors, dominant themes, and reaction mechanisms in biomass pyrolysis. This review offers valuable guidance for researchers, industries, and policymakers working toward efficient biomass conversion, sustainable energy production, and environmental management.</div></div>","PeriodicalId":36919,"journal":{"name":"Results in Engineering","volume":"28 ","pages":"Article 107123"},"PeriodicalIF":7.9,"publicationDate":"2025-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145011225","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 circular economy in reconditioned spare parts through artificial intelligence and genetic algorithms","authors":"Abderrahman Mansouri ,&nbsp;Abdelouahad Bellat ,&nbsp;Idriss Bennis ,&nbsp;Ali Siadat ,&nbsp;Fatiha Akef","doi":"10.1016/j.rineng.2025.107122","DOIUrl":"10.1016/j.rineng.2025.107122","url":null,"abstract":"<div><div>The increasing global focus on sustainability and resource conservation has spurred industries to adopt circular economy (CE) principles, particularly in areas with significant environmental impact, such as spare parts management for industrial maintenance. This study explores a multi-objective optimization approach to maintenance scheduling, aiming to balance reliability, cost, environmental impact, and circular economy contributions when selecting between new and reconditioned spare parts. We propose a robust, AI-driven model based on genetic algorithms to optimize these criteria simultaneously, generating a set of Pareto-optimal solutions that highlight the trade-offs among cost, reliability, carbon footprint, and resource reuse. By integrating reconditioned components, the model enables notable reductions in environmental impact and cost, though with a slight compromise in reliability. This highlights the importance of well-defined thresholds and strategic decision-making. The approach empowers stakeholders to adopt tailored maintenance solutions that align with both economic objectives and sustainability goals. Empirical results reveal significant improvements in emissions reduction and waste minimization, validating the feasibility of incorporating CE principles into spare parts logistics without compromising operational performance. Overall, this work delivers a comprehensive, data-driven strategy that supports sustainable maintenance by aligning circularity goals with industrial constraints and decision-making priorities.</div></div>","PeriodicalId":36919,"journal":{"name":"Results in Engineering","volume":"28 ","pages":"Article 107122"},"PeriodicalIF":7.9,"publicationDate":"2025-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145047512","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 solar drying systems through integrated thermal energy storage and solar-assisted heat pump technologies: A pathway to sustainable food processing","authors":"Dhass AD ,&nbsp;Beemkumar N ,&nbsp;Sunil Kumar M ,&nbsp;Ganesan Subbiah ,&nbsp;Ritesh Pratap Singh ,&nbsp;Kamakshi Priya K","doi":"10.1016/j.rineng.2025.107125","DOIUrl":"10.1016/j.rineng.2025.107125","url":null,"abstract":"<div><div>The growing global demand for sustainable and energy-efficient food preservation technologies has accelerated research into solar drying systems, particularly for remote and energy-constrained regions. While solar dryers offer significant environmental and economic benefits, their performance is often constrained by the intermittent nature of solar radiation, leading to reduced energy efficiency, inconsistent drying rates, and potential quality degradation of end products. This review synthesises recent advancements in integrating thermal energy storage (TES) and solar-assisted heat pump (SAHP) technologies into various solar dryer configurations—direct, indirect, mixed-mode, and hybrid systems. Special emphasis is placed on the selection and performance evaluation of sensible heat materials, phase change materials (PCMs), and thermochemical storage media, assessed based on thermal stability, storage capacity, cost-effectiveness, and adaptability to diverse climatic conditions. The role of SAHP integration is examined for its ability to maintain optimal drying temperatures and relative humidity, thereby extending drying periods and improving product quality retention. Comparative analyses from literature indicate that TES–SAHP hybrid systems can improve overall system efficiency by up to 35 % and reduce drying time by 20–40 %, depending on design and operating conditions. Furthermore, the review explores advancements in hybrid system optimisation, and techno-economic feasibility, highlighting applications for high-value agricultural and food products. Finally, the paper identifies key challenges—such as system complexity, initial investment costs, and material degradation—and outlines future research directions to enable the large-scale deployment of next-generation solar drying technologies in sustainable food processing.</div></div>","PeriodicalId":36919,"journal":{"name":"Results in Engineering","volume":"28 ","pages":"Article 107125"},"PeriodicalIF":7.9,"publicationDate":"2025-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145020859","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":"Slope deformation monitoring and prediction based on InSAR and deep learning model","authors":"Zhixing Deng ,&nbsp;Wubin Wang ,&nbsp;Yuan Luo ,&nbsp;Shun Zhang ,&nbsp;Linrong Xu ,&nbsp;Qian Su","doi":"10.1016/j.rineng.2025.107113","DOIUrl":"10.1016/j.rineng.2025.107113","url":null,"abstract":"<div><div>Slope instability hazards pose significant risks to transportation lines and infrastructure safety. Slope deformation monitoring results provide insights into hazard development. To retrospectively monitor slope deformation and predict its deformation trends, we propose a slope deformation monitoring and prediction method based on interferometric synthetic aperture radar (InSAR) and deep learning. First, InSAR is used to obtain the deformation characteristics of the target slope from January 2019 to February 2020. Next, the deformation rates in the study area and the characterization of spatio-temporal deformation on the target slope are analyzed. Then, the adaptive boosting support vector regression (AdaBoost-SVR) algorithm is used to continuously process the slope time-series deformation data and establish a data set. The whale optimization algorithm (WOA) is used to optimize the hyperparameters of four deep learning models. Subsequently, the prediction performance is assessed to determine the optimal model. Finally, the discussion verifies WOA's effectiveness and compares its performance to traditional prediction models. The results reveal an overall sliding trend in the target slope, with deformation rates predominantly between 0 and -20 mm/yr. Cumulative deformation varies spatially and temporally within the target area, exhibiting higher values at higher elevations compared to lower elevations. The fitness values of the four models rapidly decrease and then stabilize, indicating the WOA algorithm’s effectiveness in minimizing prediction errors. Based on training and test assessments, WOA-BiGRU is identified as the optimal model for slope deformation prediction, outperforming traditional models in both prediction accuracy and error. The findings could provide a reference for slope deformation prediction and hazard prevention.</div></div>","PeriodicalId":36919,"journal":{"name":"Results in Engineering","volume":"28 ","pages":"Article 107113"},"PeriodicalIF":7.9,"publicationDate":"2025-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145047282","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":"CFD-based evaluation of air induction nozzle performance: Integration with AI for predictive modeling","authors":"Jeekeun Lee ,&nbsp;Hamada Mohmed Abdelmotalib","doi":"10.1016/j.rineng.2025.107116","DOIUrl":"10.1016/j.rineng.2025.107116","url":null,"abstract":"<div><div>Air induction nozzles are commonly utilized in agricultural settings to reduce chemical drift, with internal fluid dynamics playing a critical role in their efficiency. However, experimental investigation of internal flows is often hindered by dimensional constraints. This study aims to identify optimal design parameters for air-induction nozzles to achieve a specified air-to-liquid ratio (ALR), employing a combined approach of computational fluid dynamics (CFD) and artificial intelligence methods. The impacts of several geometric factors, including the venturi air inlet diameter, length of air passage, mixing chamber length, V-cut angle, and nozzle inlet diameter, were assessed through computational fluid dynamics (CFD) analyses and AI modeling. The findings demonstrated that subtle variations in the design parameters distinctly influenced the internal two-phase flow and the resulting air-liquid ratio within the nozzle. An optimum venturi inlet diameter of 7 mm was found to produce the target air-liquid ratio of 0.00055 when combined with a throat diameter of 1.4 mm, a mixing chamber length of 7 mm, air passage length of 1.5 mm, an inlet nozzle diameter of 3 mm, and a V-cut angle of 32° The importance ranking highlighted that the venturi inlet air diameter was the most influential factor (35 %), with mixing chamber length and nozzle inlet diameter contributing equally (20 % each). These results offer practical design recommendations for refining air induction nozzle performance and demonstrate the value of integrating CFD with AI to enhance nozzle development and agricultural spraying methods.</div></div>","PeriodicalId":36919,"journal":{"name":"Results in Engineering","volume":"28 ","pages":"Article 107116"},"PeriodicalIF":7.9,"publicationDate":"2025-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145047239","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":"Adaptability analysis of distance protection in flexible low frequency ac outgoing transmission line of wind power system","authors":"Yue Dai ,&nbsp;Hongchun Shu ,&nbsp;Yutao Tang ,&nbsp;Haoming Liu","doi":"10.1016/j.rineng.2025.107118","DOIUrl":"10.1016/j.rineng.2025.107118","url":null,"abstract":"<div><div>The extension of offshore wind power to medium and far seas has promoted the development of flexible low-frequency AC transmission (FLFAC) technology. However, the fault responses of the power electronic interface-type power sources (wind turbines and modular multilevel matrix converters) connected at both ends of the low frequency (LF) line are actively regulated by control strategies, which are essentially different from traditional power frequency (PF) AC transmission systems, leading to the adaptability bottleneck of traditional relay protection. Existing studies have insufficient analysis on the adaptability of distance protection in FLFAC systems, especially lacking a systematic comparison of different types of distance protection. Therefore, this paper focuses on the adaptability issue of distance protection in FLFAC systems. It first elaborates on the basic principles of power frequency distance protection, power frequency fault component distance protection, phase comparison distance protection, and time-domain distance protection. Combined with the fault characteristics of low-frequency systems, it theoretically analyzes the influence mechanism of power electronic source fault responses on each protection. Then, it verifies the adaptability of protection on the wind farm side and the M3C low-frequency side through simulations. The research shows that time-domain distance protection has the optimal reliability under complex working conditions, which can provide a quantitative basis for the selection of FLFAC system protection schemes, has practical value for improving the reliability of system protection and engineering implementation, and also lays a theoretical foundation for subsequent protection improvement.</div></div>","PeriodicalId":36919,"journal":{"name":"Results in Engineering","volume":"28 ","pages":"Article 107118"},"PeriodicalIF":7.9,"publicationDate":"2025-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145011208","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":"Optimized multi-objective energy management strategy for solar-fuel cell hybrid electric vehicles using RSM and SFOA","authors":"Raghupathi M ,&nbsp;Susitra Dhanraj ,&nbsp;Poyyamozhi N ,&nbsp;Kamakshi Priya K","doi":"10.1016/j.rineng.2025.107106","DOIUrl":"10.1016/j.rineng.2025.107106","url":null,"abstract":"<div><div>This study presents an advanced energy management strategy for solar-assisted fuel cell hybrid electric vehicles (FC<img>HEVs), integrating lithium-ion battery storage, proton exchange membrane fuel cells (PEMFC), and photovoltaic (PV) panels. A comprehensive system model was developed, encompassing PV modules, FC stacks, power converters, and traction motors under both static and dynamic driving conditions. To optimize key operational parameters—namely, power split ratio, converter duty cycle, and load demand—Response Surface Methodology (RSM) was employed. This approach significantly enhanced system performance: energy efficiency improved to 88 %, surpassing the baseline range of 78–80 %, and battery state-of-charge (SoC) gain reached 2.4 %, compared to 1.1–1.8 % without optimization. Furthermore, fuel cell degradation was effectively minimized to 0.04, a substantial reduction from 0.1 observed in suboptimal conditions. These results highlight the potential of integrating statistical modeling with bio-inspired optimization techniques to achieve intelligent, real-time energy management in FC<img>HEVs, leading to greater energy utilization, extended driving range, and improved component longevity.</div></div>","PeriodicalId":36919,"journal":{"name":"Results in Engineering","volume":"28 ","pages":"Article 107106"},"PeriodicalIF":7.9,"publicationDate":"2025-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145047280","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":"Quantifying CO2 solubility and geochemistry reactions in multicomponent electrolyte solutions under CO2 geological sequestration conditions","authors":"Lei Ding ,&nbsp;Zuhair AlYousef ,&nbsp;Muhammad AlMajid ,&nbsp;Moataz Abu AlSaud","doi":"10.1016/j.rineng.2025.107119","DOIUrl":"10.1016/j.rineng.2025.107119","url":null,"abstract":"<div><div>CO₂ solubility trapping and CO₂-brine-mineral interactions are essential for understanding the fate and migration behavior of CO₂ during geological storage. An advanced instrument was developed to accurately quantify the CO₂ solubility in brine and CO₂-brine-mineral interactions. Nonetheless, the experimental measurements can be time-consuming and resource-intensive. CO₂SolTool, developed by integrating MATLAB with Phreeqc, provides a reliable approach for determining the quantity of dissolved CO₂ in brine, the properties (e.g., pH and density) of CO₂-saturated brine, and the interactions between mineral, brine, and CO₂. The calculated data are consistent with the experimental findings. CO₂SolTool can accurately simulate the quantity of dissolved CO₂ in brine in the presence of gas impurities throughout a wide range of temperature, pressure, and brine salinity and compositions. The Pitzer model is sufficiently accurate for thermodynamic and geochemical calculations at elevated brine salinity. The solubility of H₂S is higher than that of CO₂, while the solubility of N₂ and CH₄ is smaller than that of CO₂. The electrolytes, especially the HCO₃⁻, have a significant effect on the pH value of CO₂-saturated brine. The presence of impurities such as H₂S may moderately reduce the pH level of the CO₂-saturated brine, as it has higher solubility in brine than CO₂ under the same conditions. When minerals, e.g., dolomite or calcite, are present, the pH levels may rise after the CO₂-brine-mineral is equilibrated. Anhydrite and gypsum have limited impact on the pH value of CO₂-saturated brine. The potential determining ions, including HCO₃⁻, CO₃²⁻, Ca²⁺, can largely affect the electrical charge of the surface of calcite.</div></div>","PeriodicalId":36919,"journal":{"name":"Results in Engineering","volume":"28 ","pages":"Article 107119"},"PeriodicalIF":7.9,"publicationDate":"2025-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145047235","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 literature review-based evaluation framework for maintenance strategy selection in heavy vehicles","authors":"Malihe Goli ,&nbsp;Behzad Ghodrati ,&nbsp;Nick Eleftheroglou","doi":"10.1016/j.rineng.2025.107109","DOIUrl":"10.1016/j.rineng.2025.107109","url":null,"abstract":"<div><div>Effective maintenance strategies are critical for ensuring operational reliability, minimizing downtime, and optimizing resource utilization in fleet-based industrial operations. Among these, mining truck fleets represent a particularly high-risk, high-cost context where equipment failures can lead to substantial productivity losses and safety hazards. Despite the operational importance, existing literature lacks a structured framework to guide maintenance strategy selection that considers the practical constraints of data availability, diagnostic capability, and operational variability. To address this gap, this study proposes an evaluation framework that supports the selection and implementation of appropriate maintenance strategies. The framework is developed through a critical literature analysis, which is synthesized using a Frame of References approach. Unlike generic taxonomies, this model classifies maintenance strategies based on decision logic, response timing, data dependency, required infrastructure, and alignment with organizational capabilities. Building upon this structure, a two-level decision-support framework is introduced. The first decision tree assists practitioners in determining the appropriate class of maintenance strategy—corrective, planned, proactive, or predictive—based on operational constraints and system criticality. The second tree refines this selection by mapping available technological resources and data maturity to suitable analytical methods (e.g., rule-based, statistical, or AI-driven). While the framework is demonstrated in the context of mining truck operations, its modular design makes it applicable to other asset-intensive sectors, including logistics, construction, and heavy manufacturing. By bridging analytical insights with real-world constraints, this study offers a practical tool for organizations seeking to develop scalable, reliable, and context-sensitive maintenance strategies.</div></div>","PeriodicalId":36919,"journal":{"name":"Results in Engineering","volume":"28 ","pages":"Article 107109"},"PeriodicalIF":7.9,"publicationDate":"2025-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145047284","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}