Results in Engineering最新文献_第8页

Enhanced CO2 adsorption using Cu-MOF/carbon composites from tea twigs via one-step plasma activation 通过一步等离子体活化，利用茶枝Cu-MOF/碳复合材料增强CO2吸附

IF 7.9 Q1 ENGINEERING, MULTIDISCIPLINARY

Results in Engineering

Pub Date : 2026-03-01 Epub Date: 2025-11-27 DOI: 10.1016/j.rineng.2025.108467

Ary Mauliva Hada Putri , Tanti Ardiyati , Dieni Mansur , Latifah Hauli , Benni F. Ramadhoni , Hafiizh Prasetia

The rising concentration of atmospheric CO₂ has intensified the need for high-performance and sustainable adsorbent materials. In this study, composite CO₂ adsorbents were synthesized from tea twig waste via a one-step physical activation method using Arc Plasma, followed by integration with copper- and nickel-based metal–organic framework (MOF). Arc Plasma activation rapidly produced mesoporous carbon with high structural integrity and accessible surface area, eliminating the need for corrosive chemical activating agents. The resulting activated carbon was subsequently composited with Cu-MOF and Ni-MOF through mild solvothermal treatment to form hybrid materials. Among them, the Cu-MOF/AC composite prepared at 700 °C exhibited the best performance, with a BET surface area of 926.79 m² g^-1, a pore volume of 0.725 cm³ g^-1, and a CO₂ adsorption capacity of 2.5767 mmol g^-1, significantly higher than pristine AC or MOF alone. The composite also retained over 87 % of its initial capacity after ten regeneration cycles, confirming good cyclic stability. These enhancements are attributed to the synergistic interaction between MOF crystallites and the mesoporous carbon framework, which together promote hierarchical porosity, enhanced gas diffusion, and increased active site availability. Despite the absence of full equilibrium isotherms, the observed uptake trends support a dual-mode adsorption mechanism, involving Langmuir-type binding on microporous MOF domains and multilayer physisorption within mesoporous carbon structures. Structural (XRD), morphological (SEM), and chemical (FTIR, XRF) analyses confirmed successful MOF integration without compromising crystallinity or functional group stability. This study demonstrates a clean, scalable, and environmentally benign route for fabricating MOF–carbon composites from underutilized biomass using plasma-based processing. The developed materials exhibit strong potential for post-combustion CO₂ capture, offering a green alternative to conventional adsorbents that rely on harsh chemical treatments.

大气中二氧化碳浓度的上升加剧了对高性能和可持续吸附剂材料的需求。本研究以茶枝废料为原料，采用电弧等离子体一步物理活化法合成复合CO2吸附剂，然后与铜基和镍基金属有机骨架（MOF）结合。电弧等离子体活化快速产生具有高结构完整性和可接近表面积的介孔碳，无需腐蚀性化学活化剂。随后，通过温和的溶剂热处理，将所得活性炭与Cu-MOF和Ni-MOF复合，形成杂化材料。其中，在700℃下制备的Cu-MOF/AC复合材料性能最佳，BET表面积为926.79 m2 g-1，孔体积为0.725 cm3 g-1， CO2吸附量为2.5767 mmol g-1，明显高于原始AC或MOF。经过10次再生循环后，复合材料仍保持了87%以上的初始容量，证实了良好的循环稳定性。这些增强是由于MOF晶体和介孔碳框架之间的协同作用，它们共同促进了分层孔隙度，增强了气体扩散，增加了活性位点的可用性。尽管没有完整的平衡等温线，但观察到的吸收趋势支持双模式吸附机制，包括微孔MOF结构域上的langmuir型结合和介孔碳结构内的多层物理吸附。结构（XRD）、形态（SEM）和化学（FTIR、XRF）分析证实了MOF的成功整合，同时没有影响结晶度和官能团的稳定性。这项研究展示了一种清洁、可扩展、环保的途径，可以利用等离子体加工技术从未充分利用的生物质中制造mof -碳复合材料。开发的材料在燃烧后二氧化碳捕获方面表现出强大的潜力，为依赖苛刻化学处理的传统吸附剂提供了一种绿色替代品。

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引用次数: 0

Integration of silt waste into cement mortar as sand replacement for sustainable infrastructure development 将淤泥废物整合到水泥砂浆中，作为可持续基础设施发展的沙子替代品

IF 7.9 Q1 ENGINEERING, MULTIDISCIPLINARY

Results in Engineering

Pub Date : 2026-03-01 Epub Date: 2025-12-02 DOI: 10.1016/j.rineng.2025.108552

Mubashera Ishaq , Hafiz Suleman Habib , Nida Kanwal , Abdul Ahad Hussain , Kashif Kamran , Abdul Ghuffar

The sustainable utilization of industrial silt waste in construction materials can provide a pathway for waste management while reducing dependence on natural resources. In this context, the present study focuses on the development and characterization of new waste materials derived from textile industry and on testing their mechanical and thermal performance when utilized in construction materials. For this purpose, small sized cement-sand blocks were prepared in which natural sand was partially replaced with textile industry silt at replacement ratios of 0 %, 10 %, 15 %, 20 %, and 30 % by weight. The samples were then analyzed for water absorption, porosity, bulk density, compressive strength, and microstructural characteristics. The findings indicate that silt can be effectively utilized in cementitious materials at an optimum proportion of 15–20 %. For numerical study of thermal/ heat transfer through these cement blocks, the COMSOL Multiphysics tool was used and the numerical model was successfully validated against experimental results. Thus these results eventually lead to development of building materials with excellent performance and realize the efficient transformation of resources.

工业淤泥废弃物在建筑材料中的可持续利用为废弃物管理提供了一条途径，同时减少了对自然资源的依赖。在这种情况下，本研究的重点是开发和鉴定来自纺织工业的新废料，并测试它们在建筑材料中使用时的机械和热性能。为此，制备了小型水泥砂块，其中天然砂部分由纺织工业粉砂代替，替代比例分别为重量的0%、10%、15%、20%和30%。然后分析样品的吸水率，孔隙率，体积密度，抗压强度和微观结构特征。研究结果表明，粉砂在胶凝材料中的最佳配比为15 ~ 20%时，可以得到有效利用。利用COMSOL Multiphysics工具对水泥砌块的热/热传递进行了数值研究，并将数值模型与实验结果进行了验证。从而最终开发出性能优良的建筑材料，实现资源的高效转化。

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引用次数: 0

Machine learning nested MCDM model to enhance decision reliability for transport safety engineering 机器学习嵌套MCDM模型提高交通安全工程决策可靠性

IF 7.9 Q1 ENGINEERING, MULTIDISCIPLINARY

Results in Engineering

Pub Date : 2026-03-01 Epub Date: 2025-12-01 DOI: 10.1016/j.rineng.2025.108543

Xingjian Zhang , Nanbo (Aaron) Zhang , Jialin Li , Qintao Li , Xingze Liu , Chuanpu (Lukas) Cao , Hao Mao , Ruikang Yan , Yunlong Qi , Xinyi (Chenny) Yang , Jialun Li , Aaron Kaiqiang Zhou , Xu Yan , Hanrui Feng , Faan Chen

Ensuring robust and defensible decision is a critical attribute of multi-criteria decision-making (MCDM) activities, particularly in public sector decision-making (e.g., transport safety engineering). To this end, this study introduces an advanced machine learning embedded MCDM model that integrates the preference selection index (PSI), an alternative ranking order method accounting for two-step normalization (AROMAN), and a Gaussian mixture model (GMM), i.e., PSI–AROMAN–GMM, aiming to provide a reliable decision support system in transport safety engineering. In particular, the proposed model incorporates a machine learning algorithm (i.e., t-distributed stochastic neighbor embedding (t-SNE)) to reduce the computational load and enable efficient handling of large datasets. Specifically, this approach addresses the challenge faced by conventional GMM in uncertain initialization and identification of distinct natural clusters, and it also resolves the issue of GMM in setting correct number of Gaussian components to avoid the model overfitting or underfitting. Through a case study on transport safety engineering for G20 countries, multilevel empirical comparisons validate the robustness of the proposed model, highlighting its practicality and efficiency in informing reliable decisions and policy insights. Overall, this study provides decision-makers, practitioners, and engineers with a comprehensive framework for handling real-world socio-economic activities, especially in transport safety engineering across varied national contexts, with substantial reliability and applicability.

确保稳健和可防御的决策是多标准决策（MCDM）活动的关键属性，特别是在公共部门决策（例如，运输安全工程）中。为此，本研究引入了一种先进的机器学习嵌入式MCDM模型，该模型集成了偏好选择指数（PSI）、两步归一化替代排序法（AROMAN）和高斯混合模型（GMM），即PSI - AROMAN - GMM，旨在为运输安全工程提供可靠的决策支持系统。特别是，所提出的模型结合了机器学习算法（即t分布随机邻居嵌入（t-SNE）），以减少计算负荷并实现对大型数据集的有效处理。具体而言，该方法解决了传统GMM在不确定初始化和不同自然聚类识别方面面临的挑战，并解决了GMM在设置正确的高斯分量数以避免模型过拟合或欠拟合方面的问题。通过对G20国家运输安全工程的案例研究，多层次实证比较验证了所提出模型的稳健性，突出了其在提供可靠决策和政策见解方面的实用性和效率。总体而言，本研究为决策者、从业者和工程师提供了一个全面的框架，用于处理现实世界的社会经济活动，特别是在不同国家背景下的运输安全工程中，具有很高的可靠性和适用性。

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引用次数: 0

Design, modeling, and simulation of Archimedes Wave Swing technology for renewable powering of seawater desalination plants in Dakhla City, Moroccan Atlantic coast 摩洛哥大西洋沿岸达赫拉市海水淡化厂可再生能源阿基米德摆波技术的设计、建模和仿真

IF 7.9 Q1 ENGINEERING, MULTIDISCIPLINARY

Results in Engineering

Pub Date : 2026-03-01 Epub Date: 2025-11-29 DOI: 10.1016/j.rineng.2025.108490

Hicham Mastouri , Meryiem Derraz , Mohammed Remaidi , Amine Ennawaoui , Chouaib Sayaghi , Chouaib Ennawaoui

Morocco’s increasing dependence on seawater desalination to address chronic water scarcity demands sustainable energy solutions capable of operating in coastal environments. This study investigates the feasibility of using an Archimedes Wave Swing (AWS) device as a renewable power source for desalination stations, with a case study in the wave-rich region of Dakhla. An analytical model was developed to describe the hydrodynamic, hydraulic, and electromechanical behavior of the system, and was validated through simulations. The proposed configuration, based on a scaled prototype, achieved a stable electrical output of 520 mW for the modeled dimensions, corresponding to a power density of 0.660 mW/cm³ under representative wave conditions (H = 3 m, T = 8 s). Parametric analysis highlighted the influence of wave frequency, stiffness, and damping on float displacement and power conversion, revealing an optimal frequency range where energy capture is maximized. These results demonstrate the system’s adaptability to Moroccan wave climates and its potential to power modular desalination units, with future work focusing on scaling strategies to meet the demands of full-scale desalination plants.

摩洛哥越来越依赖海水淡化来解决长期缺水问题，因此需要能够在沿海环境中运行的可持续能源解决方案。本研究调查了使用阿基米德波浪摆动（AWS）设备作为海水淡化站可再生能源的可行性，并以Dakhla波浪丰富的地区为例进行了研究。建立了一个分析模型来描述系统的水动力、液压和机电行为，并通过仿真进行了验证。所提出的配置基于缩放原型，在模型尺寸下实现了520 mW的稳定电输出，对应于代表性波浪条件（H = 3 m, T = 8 s）下的功率密度为0.660 mW/cm³。参数分析强调了波浪频率、刚度和阻尼对浮子位移和功率转换的影响，揭示了能量捕获最大化的最佳频率范围。这些结果证明了该系统对摩洛哥波浪气候的适应性及其为模块化海水淡化装置提供动力的潜力，未来的工作重点是扩大战略，以满足全面海水淡化厂的需求。

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引用次数: 0

Exploring design configurations of micro heat sink for thermal performance management and heat transfer augmentation 探索微散热器的热性能管理和热传递增强的设计配置

IF 7.9 Q1 ENGINEERING, MULTIDISCIPLINARY

Results in Engineering

Pub Date : 2026-03-01 Epub Date: 2025-12-08 DOI: 10.1016/j.rineng.2025.108651

Mahmoud S. El-Sebaey , Pranav Mehta , Aissa Atia , Abdullah Alrashidi , Abdullah Alghafis , S. Shanmugan , Syed Noman , Athikesavan Muthu Manokar , A. Johnson Santhosh

The ongoing trend toward miniaturization and increasing power densities in electronic devices has created significant challenges in managing the resulting heat. Overheating in electronic components can lead to performance degradation, reduced efficiency, and even permanent failure. Heat sinks play a vital role in thermal management, ensuring that devices such as CPUs, GPUs, and LEDs operate within safe temperature limits. This review manuscript presents an overview of the latest advancements in heat-sink configurations, heat-transfer enhancement techniques, and advanced optimization strategies for electronic cooling. It highlights key innovations—including microchannels, porous structures, and vortex generators—that contribute to improved thermal performance and energy efficiency. Additionally, the review discusses enhanced geometrical designs and materials, such as pin fins, plate fins, and perforated structures, which help increase heat dissipation while minimizing pressure drop. The study emphasizes how optimized heat-sink designs address challenges related to compactness, reliability, and sustainability, supporting the growing needs of modern technologies. It also serves as a comprehensive reference for engineers and researchers seeking to improve thermal management solutions in electronic systems. Future research is recommended to explore novel configurations and integrate advanced materials for broader applications and enhanced thermal efficiency.

电子器件的小型化趋势和功率密度的不断增加，在管理由此产生的热量方面带来了重大挑战。电子元件过热会导致性能下降，效率降低，甚至永久失效。散热器在热管理中起着至关重要的作用，确保cpu， gpu和led等设备在安全温度范围内工作。这个审查手稿提出了在散热器配置，传热增强技术的最新进展的概述，并为电子冷却先进的优化策略。它强调了关键的创新，包括微通道、多孔结构和涡流发生器，这些都有助于提高热性能和能源效率。此外，该综述还讨论了增强的几何设计和材料，如钉鳍、板鳍和穿孔结构，有助于增加散热，同时最大限度地减少压降。该研究强调了优化的散热器设计如何解决与紧凑性、可靠性和可持续性相关的挑战，以支持日益增长的现代技术需求。它也为寻求改进电子系统热管理解决方案的工程师和研究人员提供了全面的参考。未来的研究建议探索新的结构和集成先进材料，以更广泛的应用和提高热效率。

{"title":"Exploring design configurations of micro heat sink for thermal performance management and heat transfer augmentation","authors":"Mahmoud S. El-Sebaey , Pranav Mehta , Aissa Atia , Abdullah Alrashidi , Abdullah Alghafis , S. Shanmugan , Syed Noman , Athikesavan Muthu Manokar , A. Johnson Santhosh","doi":"10.1016/j.rineng.2025.108651","DOIUrl":"10.1016/j.rineng.2025.108651","url":null,"abstract":"<div><div>The ongoing trend toward miniaturization and increasing power densities in electronic devices has created significant challenges in managing the resulting heat. Overheating in electronic components can lead to performance degradation, reduced efficiency, and even permanent failure. Heat sinks play a vital role in thermal management, ensuring that devices such as CPUs, GPUs, and LEDs operate within safe temperature limits. This review manuscript presents an overview of the latest advancements in heat-sink configurations, heat-transfer enhancement techniques, and advanced optimization strategies for electronic cooling. It highlights key innovations—including microchannels, porous structures, and vortex generators—that contribute to improved thermal performance and energy efficiency. Additionally, the review discusses enhanced geometrical designs and materials, such as pin fins, plate fins, and perforated structures, which help increase heat dissipation while minimizing pressure drop. The study emphasizes how optimized heat-sink designs address challenges related to compactness, reliability, and sustainability, supporting the growing needs of modern technologies. It also serves as a comprehensive reference for engineers and researchers seeking to improve thermal management solutions in electronic systems. Future research is recommended to explore novel configurations and integrate advanced materials for broader applications and enhanced thermal efficiency.</div></div>","PeriodicalId":36919,"journal":{"name":"Results in Engineering","volume":"29 ","pages":"Article 108651"},"PeriodicalIF":7.9,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145790541","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}

引用次数: 0

GIS based hybrid multi criteria decision making on the fuzzy environment to delineate flood susceptibility region in kr. keureuto catchment area, North Aceh 基于GIS的模糊环境混合多准则决策在亚齐北部kr. keureuto流域洪水易发区划分中的应用

IF 7.9 Q1 ENGINEERING, MULTIDISCIPLINARY

Results in Engineering

Pub Date : 2026-03-01 Epub Date: 2026-01-11 DOI: 10.1016/j.rineng.2026.109064

Maimun Rizalihadi , Alfiansyah Yulianur , Yuwaldi Away , Ella Meilianda

Flood susceptibility mapping is a vital tool for risk assessment and disaster mitigation. This study presents a Geographic Information System (GIS)–based approach that integrates two fuzzy Multi-Criteria Decision-Making (MCDM) methods, fuzzy Analytical Hierarchy Process (FAHP) and fuzzy Technique for Order of Preference by Similarity to Ideal Solution (FTOPSIS), to delineate flood-prone zones in the Kr. Keureuto catchment, north Aceh. The key innovation is applying a generalized-mean ranking method to define context-sensitive ideal and negative‐ideal solutions, replacing the usual fixed fuzzy positive and negative ideal solutions (FPIS/FNIS), to produce more robust weights and rankings under data uncertainty. Eleven hydrological, topographic, and land surface factors were analyzed, including rainfall, flow accumulation, elevation, slope, drainage density, proximity to rivers, topographic wetness index, land use/land cover, vegetation index, curvature, and soil type. Rainfall (weight: 0.223), flow accumulation (0.140), proximity to rivers (0.115), TWI (0.112), and drainage density (0.094) were the most influential factors. The resulting flood-susceptibility map shows that about 38 % of the basin, mainly downstream, is at high to very high risk, while the remaining 62 % is at moderate to low risk. Validation with observed flood records produced an area-under-the-curve- receiver operating characteristic (AUC-ROC) value of 0.921, demonstrating excellent predictive performance. By clearly linking spatial analysis with a more flexible decision framework, this research provides a practical decision-support tool for planners, disaster-management agencies, and local authorities to identify priority zones for structural and non-structural mitigation, guide land-use planning, and strengthen early-warning and evacuation strategies.

洪水易感性绘图是风险评估和减灾的重要工具。本研究提出了一种基于地理信息系统（GIS）的方法，该方法集成了两种模糊多标准决策（MCDM）方法，即模糊层次分析法（FAHP）和模糊理想解决方案相似偏好排序法（FTOPSIS），以划定亚齐北部Kr. Keureuto流域的洪水易发区。关键的创新是应用广义平均排序方法来定义上下文敏感的理想和负理想解，取代通常的固定模糊正理想解和负理想解（FPIS/FNIS），从而在数据不确定性下产生更稳健的权重和排名。分析了11个水文、地形和地表因子，包括降雨量、流量积累、高程、坡度、排水密度、靠近河流、地形湿度指数、土地利用/土地覆盖、植被指数、曲率和土壤类型。降雨量（权重：0.223）、流量累积（0.140）、靠近河流（0.115）、TWI（0.112）和排水密度（0.094）是最主要的影响因素。由此得出的洪水易感性图显示，约38%的流域（主要是下游）处于高至极高风险，而其余62%处于中至低风险。经实测洪水记录验证，曲线下面积接收者工作特征（AUC-ROC）值为0.921，具有较好的预测效果。通过将空间分析与更灵活的决策框架清晰地联系起来，本研究为规划者、灾害管理机构和地方当局提供了一个实用的决策支持工具，以确定结构性和非结构性减灾的优先区域，指导土地利用规划，并加强预警和疏散策略。

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引用次数: 0

Effect of thermal-hydro-mechanical (THM) on wood shape memory effect and its mechanism 热-水-机械对木材形状记忆效应的影响及其机理

IF 7.9 Q1 ENGINEERING, MULTIDISCIPLINARY

Results in Engineering

Pub Date : 2026-03-01 Epub Date: 2025-11-29 DOI: 10.1016/j.rineng.2025.108498

Yali Shao , Zhuopei Wang , Hui Liu , Lili Li , Wanxin Zhao , Kai Wang , Ximing Wang

This study investigates the three-dimensional (3D) crosslinked network of wood under thermohydromechanical (THM) treatment and elucidates the mechanisms by which THM disrupts this network, causing loss of the shape memory effect (SME). Above a critical threshold temperature of 200 °C, high-temperature THM treatment markedly weakens or eliminates the SME. Specifically, after treatment at 220 °C, dry and wet shape recoveries decreased by 93 % and 79 %, respectively, while shape springback stress dropped by 62.1 %, as confirmed by mechanical analysis. Microstructural and chemical analyses revealed that THM disrupts the 3D crosslinked network of the cell wall through hemicellulose pyrolysis and lignin crosslinking, accompanied by a 10.1 % decrease in crystallinity and a 35.6 % expansion of the cellulose unit cell size at 200 °C. These changes reduce the entropic elasticity and internal stress recovery capacity of the wood. The findings provide a scientific basis for achieving permanent shape fixation in compressed wood, with direct implications for industrial processing of wood-based products and the development of sustainable shape memory materials.

本研究研究了热流体机械（THM）处理下木材的三维（3D）交联网络，并阐明了THM破坏该网络，导致形状记忆效应（SME）丧失的机制。在临界阈值温度200℃以上，高温THM处理显著削弱或消除了SME。具体来说，力学分析证实，在220°C处理后，干燥和湿形状恢复分别下降了93%和79%，而形状回弹应力下降了62.1%。微观结构和化学分析表明，THM通过半纤维素热解和木质素交联破坏了细胞壁的三维交联网络，在200°C时，纤维素的结晶度降低了10.1%，单位细胞尺寸扩大了35.6%。这些变化降低了木材的熵弹性和内应力恢复能力。研究结果为实现压缩木材的永久形状固定提供了科学依据，对木制品的工业加工和可持续形状记忆材料的开发具有直接意义。

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引用次数: 0

A review of the application of quarry dust in cement-based materials 采石场粉尘在水泥基材料中的应用综述

IF 7.9 Q1 ENGINEERING, MULTIDISCIPLINARY

Results in Engineering

Pub Date : 2026-03-01 Epub Date: 2026-02-11 DOI: 10.1016/j.rineng.2026.109562

Chee Ban Cheah, Yuan Xian Gong

Quarry dust, produced as a byproduct during rock processing in quarries, presents both environmental challenges and opportunities for sustainable construction. When strategically used in construction applications, this material offers a promising way to reduce environmental impacts while improving economic viability through lower material costs and reduced carbon footprints. This paper reviews recent research on the application of quarry dust in cement-based materials within the construction industry. It highlights and concludes the chemical composition of quarry dust and the outcomes of replacing aggregate and cement. It often reported optima in the 10–30% range for replacing cement, while replacing aggregates can achieve 100%.

采石场在岩石加工过程中产生的副产品采石场粉尘对可持续建筑既提出了环境挑战，也带来了机遇。当在建筑应用中战略性地使用时，这种材料提供了一种有希望的方法来减少对环境的影响，同时通过降低材料成本和减少碳足迹来提高经济可行性。本文综述了近年来采石场粉尘在水泥基材料中的应用研究。重点总结了采石场粉尘的化学成分及替代骨料和水泥的效果。通常报道替代水泥的最优率为10-30%，而替代骨料的最优率可达100%。

引用次数: 0

Advancing bridge management systems: Optimizing maintenance planning through deep learning, big data, and digital twins 推进桥梁管理系统：通过深度学习、大数据和数字孪生优化维护计划

IF 7.9 Q1 ENGINEERING, MULTIDISCIPLINARY

Results in Engineering

Pub Date : 2026-03-01 Epub Date: 2026-03-03 DOI: 10.1016/j.rineng.2026.109895

Vahid Mousavi , Maria Rashidi , Shayan Ghazimoghadam

Bridge infrastructure, as a critical capital asset and an integral component of transportation networks, is increasingly affected by aging, deterioration, and external damage, potentially compromising its safety, performance, and functionality. These challenges, compounded by the growing demand for infrastructure expansion and limited funding resources, underscore the necessity of adopting efficient bridge management systems to prioritize maintenance and remediation strategies. To address these demands, different Bridge Management Systems (BMSs) have been developed to support operators in maintaining safe operations while optimizing budget allocation and maintenance strategies. Despite advancements in this field, most state-of-the-art research lacks a comprehensive overview of the role of Digital Twins (DTs), Deep learning (DL) and Big Data (BD) integration in enhancing BMS, particularly in managing uncertainties across BMS modules. Therefore, this paper provides a dedicated review of recent research in BMSs, with particular emphasis on the integration of DT and DL-enabled frameworks into bridge management practices and organizes key sources of uncertainty and discusses how emerging technologies can address these aspects in BMSs, which has yet to be comprehensively addressed. The review critically explores current methodologies, highlights challenges and identifies opportunities for uncertainty management in BMSs through the integration of advanced technologies and future trends for more reliable bridge management.

桥梁基础设施作为重要的资本资产和交通网络的组成部分，日益受到老化、恶化和外部损坏的影响，潜在地危及其安全性、性能和功能。这些挑战，加上基础设施扩建需求的增长和有限的资金资源，强调了采用有效的桥梁管理系统来优先考虑维护和修复策略的必要性。为了满足这些需求，不同的桥梁管理系统（bms）已经开发出来，以支持运营商在优化预算分配和维护策略的同时保持安全运营。尽管这一领域取得了进展，但大多数最先进的研究缺乏对数字双胞胎（DTs）、深度学习（DL）和大数据（BD）集成在增强BMS中的作用的全面概述，特别是在管理BMS模块之间的不确定性方面。因此，本文对bms的最新研究进行了专门的回顾，特别强调了将DT和dl支持的框架集成到桥梁管理实践中，并组织了主要的不确定性来源，并讨论了新兴技术如何解决bms中的这些方面，这些方面尚未得到全面解决。该综述批判性地探讨了目前的方法，强调了挑战，并通过整合先进技术和未来趋势来确定bms不确定性管理的机会，以实现更可靠的桥梁管理。

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引用次数: 0

Fluorescence-based MOF biosensors toward simultaneous detection of COVID-19 and influenza: Design strategies and future prospects 基于荧光的MOF生物传感器用于同时检测COVID-19和流感：设计策略和未来展望

IF 7.9 Q1 ENGINEERING, MULTIDISCIPLINARY

Results in Engineering

Pub Date : 2026-03-01 Epub Date: 2026-02-19 DOI: 10.1016/j.rineng.2026.109657

Farida Korna , Rana Sabouni , Mehdi Ghommem , Amin F. Majdalawieh , Nouha Alcheikh

The concurrent threat of COVID-19 and influenza highlights the urgent need for rapid, accurate, and simultaneous diagnostic tools. Traditional techniques, such as PCR and ELISA, are limited by high costs, long turnaround times, and reliance on specialized laboratories. Metal-organic frameworks (MOFs) have demonstrated great potential as materials for viral biosensing due to their high porosity, tunability, and surface functionality, which enable multiple detection modalities, including fluorescence, electrochemical, and colorimetric sensing. This review explores the design strategies, detection mechanisms, and recent advances in MOF-based biosensors, with a focus on design strategies and sensing principles relevant to the simultaneous detection of COVID-19 and influenza. While true MOF-based fluorescence platforms enabling simultaneous differentiation of COVID-19 and influenza remain limited, this review consolidates transferable design principles from multi-virus systems to inform future diagnostics. It discusses the potential of functionalized MOFs for simultaneous virus recognition, highlights the integration of MOFs with microfluidic and wearable platforms, and emphasizes the role of artificial intelligence (AI), machine learning (ML), and smartphones in enhancing detection performance and scalability, as well as the ethical and legal considerations associated with the widespread use of biosensors. By consolidating recent findings, this review outlines key challenges, such as stability, reproducibility, and regulatory barriers, while proposing pathways for translating MOF-based simultaneous detection systems into clinically viable diagnostic tools.

COVID-19和流感的同时威胁凸显了对快速、准确和同步诊断工具的迫切需要。PCR和ELISA等传统技术受到成本高、周转时间长和依赖专门实验室的限制。金属有机框架（mof）由于其高孔隙率、可调性和表面功能性，能够实现多种检测方式，包括荧光、电化学和比色传感，已经证明了其作为病毒生物传感材料的巨大潜力。本文综述了基于mof的生物传感器的设计策略、检测机制和最新进展，重点介绍了与同时检测COVID-19和流感相关的设计策略和传感原理。虽然能够同时区分COVID-19和流感的真正基于mof的荧光平台仍然有限，但本综述整合了多病毒系统的可转移设计原则，为未来的诊断提供信息。它讨论了功能化MOFs同时识别病毒的潜力，强调了MOFs与微流体和可穿戴平台的集成，并强调了人工智能（AI），机器学习（ML）和智能手机在提高检测性能和可扩展性方面的作用，以及与广泛使用生物传感器相关的伦理和法律考虑。通过整合最近的发现，本综述概述了主要挑战，如稳定性、可重复性和监管障碍，同时提出了将基于mof的同时检测系统转化为临床可行诊断工具的途径。

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引用次数: 0