Mutlu Seçer^*, Ali Alper Saylan

CMES-Computer Modeling in Engineering & Sciences, Vol.148, No.1, 2026, DOI:10.32604/cmes.2026.084228 - 27 July 2026

Abstract Climate change modifies environmental exposure conditions and affects the corrosion-driven deterioration of steel bridges, thereby challenging conventional maintenance planning approaches. Thus, more advanced maintenance management strategies are required to address the challenges associated with varying corrosion rate projections. In this study, a novel adaptive maintenance management framework is proposed for steel truss bridges to address climate change-induced corrosion under evolving deterioration conditions. Adaptivity is achieved by updating corrosion rates to consider time-varying deterioration conditions associated with climate change. This enables time-dependent representation of corrosion progression under changing environmental conditions. The framework is demonstrated on a… More >

Nada Alzaben¹, Muhammad I. Khan², Hafeez Ur Rehman Siddiqui³, Abeer Rashad Mirdad⁴, Saeed Ali Bahaj^5,*

CMC-Computers, Materials & Continua, Vol.88, No.3, 2026, DOI:10.32604/cmc.2026.083649 - 23 July 2026

Abstract Industrial predictive maintenance is a critical challenge in modern manufacturing, where unexpected equipment failures cause significant economic losses through downtime, repair costs, and disrupted production. Conventional maintenance approaches, whether reactive or schedule-based, are becoming inadequate to manage the high-dimensional sensor information of the IoT-enabled machineries. The paper presents a novel hybrid neuro-symbolic digital twin that builds upon Remaining Useful Life (RUL) estimation by combining temporal transformers, physics-informed constraints, and counterfactual reasoning. The model integrates complementary approaches into a single and interpretable predictive system. A temporal transformer backbone is a model of long-range dependencies in multivariate… More >

Joonhyeok Moon¹, Siheon Jeong¹, Byeonghyun Lee¹, Jeik Choi¹, Ki-Yong Oh^1,2,*

CMES-Computer Modeling in Engineering & Sciences, Vol.147, No.3, 2026, DOI:10.32604/cmes.2026.081475 - 30 June 2026

Abstract Maintaining overhead distribution facilities inherently involves high risks for operators, where ensuring worker safety and operational efficiency remains a paramount challenge. In particular, automating the positioning of aerial work platforms is crucial to mitigate electrocution hazards during live-line maintenance tasks. This paper proposes a novel autonomous framework for detecting jumper lines that could be employed to estimate the optimal bucket position in live-line maintenance of overhead distribution systems. The proposed framework comprises three core modules to form a unified pipeline for autonomous field inspection: a 4D multi-modal map, Sparse-dense fusion network (SDFNet), and Rotational multi-pyramid… More >

Wei Chen, Zhi Wei^*, Tingting Pei, Jianghao Zhu, Yang Wu

Energy Engineering, Vol.123, No.6, 2026, DOI:10.32604/ee.2025.073843 - 27 May 2026

Abstract Wind turbine gearboxes are critical components in large-scale power generation systems, and their unexpected failures often result in significant economic losses, long downtime, and decreased energy efficiency. Accurate prediction of their Remaining Useful Life (RUL) is therefore vital for enhancing operational reliability, implementing condition-based maintenance, and optimizing lifecycle management. However, existing approaches often neglect the memory effect in degradation processes and fail to establish an effective interaction between stochastic degradation modeling and RUL prediction. To address these challenges, this study proposes a novel fusion method that integrates a stochastic degradation model with an intelligent prediction framework.… More >

Mustapha Hatoum¹, Alessandro P. Fantilli^1,*, Bernardino Chiaia¹, Georgios Kalamaras²

Structural Durability & Health Monitoring, Vol.20, No.3, 2026, DOI:10.32604/sdhm.2026.076141 - 18 May 2026

Abstract This study investigates the contribution of fibers to the durability of reinforced concrete tunnel linings. Two cast-in-situ tunnels are herein analyzed after twenty years of service. Tunnel #1, made with plain concrete and steel rebar, has shown significant spalling at joints between two consecutive tunnel panels, caused by poor workmanship and construction details. Conversely, in Tunnel #2, close to Tunnel #1 on the same motorway, fiber-reinforced concrete (FRC) was used in combination with steel rebar. During the service life, the amount of FRC spalled from the cold joints of this lining has been significantly lower than More >

Hui Zhang^1,*, Yingying Xie¹, Yu Zhang^2,*, Zhan Gao¹, Aijun Li¹, Sheng Shi¹, Xingyue Li¹, Zheming Zhou¹, Haotian Wang¹

Structural Durability & Health Monitoring, Vol.20, No.3, 2026, DOI:10.32604/sdhm.2026.075835 - 18 May 2026

Abstract A composite bridge deck system consisting of an orthotropic steel deck and a normal-temperature-cured reactive powder concrete (RPC) layer is proposed to address the problems of pavement damage and fatigue cracks in steel bridge decks. In this study, a local finite element model of a bridge segment was established using ANSYS to calculate and compare the stress states of four deck systems: normal-temperature-cured RPC composite box girders, high-temperature-cured RPC composite box girders, pure steel box girders, and ordinary concrete composite box girders. Additionally, static load tests were conducted on a scaled local model to validate… More > Graphic Abstract

Lyu Guanghua¹, Dingxiao Jiao², Abdulrahman AlKassem³, Dakan Ying¹, Rizwan Arshad¹, Jiahua Ni¹, Zhe Liu¹, Syed Hadi Hussain Shah^1,*

FDMP-Fluid Dynamics & Materials Processing, Vol.22, No.4, 2026, DOI:10.32604/fdmp.2026.077648 - 07 May 2026

Abstract Desert photovoltaic, PV, installations experience significant efficiency losses due to dust accumulation, which also promotes localized overheating, known as hotspots, caused by uneven solar irradiance and partial cell shading. These hotspots can accelerate material degradation and increase the risk of permanent panel damage. This study presents an autonomous maintenance strategy based on a cooperative swarm of unmanned aerial vehicles, UAVs, enabling contactless dust removal and active hotspot cooling. The approach combines high-fidelity computational fluid dynamics to characterize aerodynamic downwash for effective dust detachment with fluid–structure interaction analysis to verify the structural integrity of PV panels… More >

Chao Guo¹, Chao Deng², Xing Bai³, Ziyuan Fan⁴, Jintao Li², Yuan Ren^2,*

Structural Durability & Health Monitoring, Vol.20, No.2, 2026, DOI:10.32604/sdhm.2025.075363 - 31 March 2026

Abstract Hangers play a crucial role in transferring loads in suspension bridges, yet their condition often deteriorates faster than expected due to corrosion and fatigue effects. Premature hanger failure poses serious risks to bridge safety and results in significant economic loss due to frequent replacement and traffic interruption. To address these challenges, this study proposes an integrated framework to evaluate the life-cycle safety and operational cost of bridge hangers. Traffic data obtained from Weigh-in-Motion (WIM) systems are used to simulate dynamic hanger responses. A wire-to-hanger deterioration model is then employed to capture the time-dependent interaction between… More >

Abiodun Abiola^*, Francisca Segura, José Manuel Andújar, Antonio Javier Barragán

CMES-Computer Modeling in Engineering & Sciences, Vol.146, No.3, 2026, DOI:10.32604/cmes.2025.070788 - 30 March 2026

Abstract This paper presents an artificial intelligence (AI)-based observer that combines fuzzy logic and neural networks to detect abnormalities in sensors embedded in an electrolyser. Electrolysers are hydrogen production plants that require effective maintenance to guarantee suitable operation, prevent degradation, and avoid loss of efficiency. In this sense, predictive maintenance arises as one of the most advisable techniques for maintenance in electrolysers by using sensor data to predict potential abnormalities. However, if the sensor fails, there will be an incorrect forecasting of abnormalities. Among the different types of operational faults that sensors can present are drift-related… More >

Ahmad Junaid¹, Abid Iqbal^2,*, Abuzar Khan¹, Ghassan Husnain^1,*, Abdul-Rahim Ahmad³, Mohammed Al-Naeem⁴

CMC-Computers, Materials & Continua, Vol.87, No.1, 2026, DOI:10.32604/cmc.2025.073189 - 10 February 2026

Abstract Most predictive maintenance studies have emphasized accuracy but provide very little focus on Interpretability or deployment readiness. This study improves on prior methods by developing a small yet robust system that can predict when turbofan engines will fail. It uses the NASA CMAPSS dataset, which has over 200,000 engine cycles from 260 engines. The process begins with systematic preprocessing, which includes imputation, outlier removal, scaling, and labelling of the remaining useful life. Dimensionality is reduced using a hybrid selection method that combines variance filtering, recursive elimination, and gradient-boosted importance scores, yielding a stable set of… More >