Publications

Li, W, Zhao, H & Wang, K 2025, Nanocharacterization of Cementitious Composites, Springer Nature Singapore.
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Alqaisi, R, Le, M-T, Khabbaz, H & Fatahi, B 2025, 'Eggshell Powder as an Ameliorating Agent for Cement-Stabilised Expansive Soil in Road Construction' in Lecture Notes in Civil Engineering, Springer Nature Singapore, pp. 55-68.
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Lim, JY, Kang, KW, Li, J & Wu, C 2025, 'Numerical Simulation for Combined Blast and Fragmentation Effects on Steel-Concrete Composite Panels' in Lecture Notes in Civil Engineering, Springer Nature Switzerland, pp. 813-822.
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Nimbalkar, S, Farooq, MA, Punetha, P & Meena, NK 2025, 'Computational Models and Applications in Railway Geotechnics' in Lecture Notes in Civil Engineering, Springer Nature Singapore, pp. 1-11.
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Nimbalkar, S, Punetha, P, Meena, NK & Farooq, MA 2025, 'Recent Advances in Computational Methods, Predictions, and Applications to Critical Zones in Railways' in Recent Advances and Innovative Developments in Transportation Geotechnics, Springer Nature Singapore, pp. 191-201.
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Punetha, P & Nimbalkar, S 2025, 'Three-Dimensional Finite Element Modelling of Sealed and Unsealed Roads Considering Effects of Moving Wheel Loads' in Lecture Notes in Civil Engineering, Springer Nature Singapore, pp. 113-120.
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Riyad, ASM, Qi, Y, Arachchige, CK, Indraratna, B & Khabbaz, H 2025, 'Predicting the Behavior of a Synthetic Energy Absorbing Layer for Subballast Using Nor-Sand Model' in Lecture Notes in Civil Engineering, Springer Nature Singapore, pp. 71-76.
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Soundararajan, S, Raychowdhury, P & Nimbalkar, S 2025, 'Performance Assessment of Existing Railway Track Subjected to Varying Train Speed' in Lecture Notes in Civil Engineering, Springer Nature Singapore, pp. 129-136.
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Toledo Filho, RD & Li, W 2025, 'Mix Proportion Design Method of RAC and Properties of Fresh RA' in RILEM State-of-the-Art Reports, Springer Nature Switzerland, pp. 109-159.
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Vaseghi, S, Sheng, D, Kodikara, J & Khabbaz, H 2025, 'Effect of Principal Stress Rotation on Plastic Strain Accumulation in Granular Materials' in Lecture Notes in Civil Engineering, Springer Nature Singapore, pp. 11-20.
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Basack, S & Khabbaz, H 2025, 'Analytical solution for single pile in two-layered soil subjected to torsion', Geomechanics and Geoengineering, vol. 20, no. 3, pp. 618-634.
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Bhandari, S, Fatahi, B, Nguyen, LD & Karimi, R 2025, 'Cyclic and post-cyclic responses of cement-treated landfill waste under triaxial testing', Soil Dynamics and Earthquake Engineering, vol. 197, pp. 109525-109525.
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Chen, D, Li, J, Liu, J & Wu, C 2025, 'Damage assessment of ultra-high-performance concrete protective wall against gaseous explosion', Engineering Structures, vol. 332, pp. 120071-120071.
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Chen, D, Wu, C & Li, J 2025, 'A fast and reliable model for predicting hydrogen-methane-air blast loading in unconfined spaces for blast-resistant design', International Journal of Hydrogen Energy, vol. 97, pp. 1316-1326.
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Chen, K, Dong, W, Huang, Y, Wang, F, Zhou, JL & Li, W 2025, 'Photocatalysis for sustainable energy and environmental protection in construction: A review on surface engineering and emerging synthesis', Journal of Environmental Chemical Engineering, vol. 13, no. 5, pp. 117529-117529.
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Chen, Q, Xiong, Z, Tao, G, Tian, Z & Nimbalkar, S 2025, 'Strength, Durability, Corrosion Resistance, and Microstructure of Cemented Soil Incorporating Nano-MgO under Static and Cyclic Loading: A Laboratory Study', Journal of Materials in Civil Engineering, vol. 37, no. 4.
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Chen, Z, Li, J, Zong, Z, Li, J, Li, M & Wu, C 2025, 'Damage analysis of RC panels subjected to shock wave and bubble pulse in underwater explosion', Engineering Structures, vol. 335, pp. 120331-120331.
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Chi, K, Li, J, Shao, R & Wu, C 2025, 'Experimental study on dynamic characterisation of ultra-high performance concrete (UHPC) after cryogenic freeze-thaw cycles', Cement and Concrete Composites, vol. 160, pp. 106011-106011.
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Dong, Q, Wu, X, Song, Y, Du, Y, Qi, J, Huang, L, Li, W, Huang, Y & Shi, L 2025, 'Temperature behaviors of transparent solar PV panels under various operating modes: an experimental and numerical study', Renewable Energy, vol. 250, pp. 123279-123279.
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Dong, W, Ahmed, AH, Liebscher, M, Li, H, Guo, Y, Pang, B, Adresi, M, Li, W & Mechtcherine, V 2025, 'Electrical resistivity and self-sensing properties of low-cement limestone calcined clay cement (LC3) mortar', Materials & Design, vol. 252, pp. 113790-113790.
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Dong, W, Duan, Z, Peng, S, Chen, Y, Chu, D, Tai, H & Li, W 2025, 'Triboelectric nanogenerator-powering piezoresistive cement-based sensors for energy harvesting and structural health monitoring', Nano Energy, vol. 137, pp. 110823-110823.
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Dong, W, Gao, Z, Duan, Z, Zhang, Q, Xi, X, Peng, S, Tai, H, Wang, K, Chen, Y & Li, W 2025, 'Sliding-mode cement-based triboelectric nanogenerators in intelligent infrastructure for a new energy harvesting paradigm', Materials Today Energy, vol. 52, pp. 101943-101943.
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Dong, W, Peng, S, Wang, K, Huang, Y, Shi, L, Wu, F & Li, W 2025, 'Integrated triboelectric self-powering and piezoresistive self-sensing cementitious composites for intelligent civil infrastructure', Nano Energy, vol. 135, pp. 110656-110656.
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Dong, W, Tang, J, Wang, K, Huang, Y, Shah, SP & Li, W 2025, 'Cement-based batteries for renewable and sustainable energy storage toward an energy-efficient future', Energy, vol. 315, pp. 134382-134382.
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Dong, W, Zhao, C, Peng, S, Wu, C, Kim, T, Wang, K & Li, W 2025, 'Recycled carbon fibre/cement-based triboelectric nanogenerators toward energy-efficient and smart civil infrastructure', Composites Part B: Engineering, vol. 303, pp. 112603-112603.
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Faddoul, Y & Sirivivatnanon, V 2025, 'Sustainable concrete structures by optimising structural and concrete mix design', Australian Journal of Structural Engineering, vol. 26, no. 2, pp. 86-94.
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Fairley, N, Fatahi, B & Hokmabadi, AS 2025, 'Impacts of Transition Piece Designs on the Resilience of Large Offshore Wind Turbines Subject to Combined Earthquake, Wind and Wave Loads and Soil‐Structure Interaction', Earthquake Engineering & Structural Dynamics, vol. 54, no. 3, pp. 773-798.
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ABSTRACTThe urgent global drive to mitigate greenhouse gas emissions has significantly boosted renewable energy production, notably expanding offshore wind energy across the globe. With the technological evolution enabling higher‐capacity turbines on larger foundations, these installations are increasingly situated in earthquake‐prone areas, underscoring the critical need to ensure their seismic resilience as they become a pivotal component of the global energy infrastructure. This study scrutinises the dynamic behaviour of a 15 MW offshore wind turbine (OWT) under concurrent earthquake, wind and wave loads, focusing on the performance of the ultra‐high‐strength cementitious grout that bonds the monopile to the transition piece. Employing LS DYNA for numerical simulations, we explored the seismic responses of four OWT designs with diverse transition piece cone angles, incorporating nonlinear soil springs to model soil‐structure interactions (SSIs) and conducting a site response analysis (SRA) to account for local site effects on ground motion amplification. Our findings reveal that transition pieces with larger cone angles exhibit substantially enhanced stress distribution and resistance to grout damage, evidenced by decreased ovalisation in the coned sections of the transition piece and monopile, and improved bending flexibility. The observed disparities in damage across different cone angles highlight shortcomings in current design guidelines pertaining to the prediction of grout stresses in conical transition piece designs, with the current code‐specified calculations predicting higher stresses for transition piece designs with larger cone angles. This study also highlights the code's limitations when accounting for grout damage induced by stress concentrations in the grouted connections under seismic dynamic loading conditions. The results of the study demonstrate the need for refinement of these guidelines to improv...

Fan, Y, Feng, C, Hang, Z, Shen, L & Li, W 2025, 'Optimal design of electrical conductivity of hybrid multi-dimensional carbon fillers reinforced porous cement-based Composites: Experiment and modelling', Composite Structures, vol. 352, pp. 118714-118714.
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Gomes, SDC, Nguyen, QD, Li, W & Castel, A 2025, 'Shrinkage and carbonation of alkali-activated calcined clay-ground granulated blast furnace slag (GGBFS) concrete', Cement and Concrete Research, vol. 194, pp. 107899-107899.
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Gomes, SDC, Pang, Y, Nguyen, QD, Li, W, Vessalas, K & Castel, A 2025, 'The effect of calcined clay reactivity on the mechanical properties and chloride diffusion resistance of alkali-activated calcined clay-GGBFS concrete', Journal of Building Engineering, vol. 102, pp. 111996-111996.
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Guo, X-Y, Fang, S-E, Zhu, X & Li, J 2025, 'A semi-Markov process based digital twin for safety evaluation of cable-stayed bridges with cable corrosion', Advanced Engineering Informatics, vol. 65, pp. 103270-103270.
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The cables of a cable-stayed bridge are susceptible to structural degradation due to environmental corrosion and fatigue, which directly affects the safety and operational performance of the bridge. As the process of the degradation in practice is very slow, it is difficult to be monitored during the bridge service life. Hence, this study aims to develop a novel semi-Markov process based digital twin (DT) framework for safety evaluation of cable-stayed bridges considering cable corrosion. The framework encompasses a physical twin layer, a DT layer and the information interaction medium. The physical twin layer mainly comprises the bridge physical entity and its associated monitoring system that provides a variety of perceptual data for DT modeling. In the DT layer, the DT model acts as a virtual counterpart of the physical bridge for mirroring and forecasting the bridge's mechanical behaviors. The information interaction medium plays a crucial role in the bidirectional information communication between the physical and digital twin layers. Two types of information interaction media have been utilized including a cable force influence matrix and a semi-Markov process. The former enables updating the DT model to precisely match the data measured from the physical bridge. Meanwhile, the semi-Markov process depicts the probability of the bridge's condition considering the cable corrosion during the different service periods. The proposed procedure can predict the bridge state and evaluate the safety by comparing the predicted state with the monitored values. The proposed framework has been successfully validated on a real-world cable-stayed bridge. The results showed the proposed DT framework was reliable and effective for evaluating the bridge condition.

Guo, Y, Qu, F, Tiwari, R, Yoo, D-Y, Wang, K, Wang, Y & Li, W 2025, 'Development of self-sensing asphalt cementitious composites using conductive carbon fibre and recycled copper tailing', Construction and Building Materials, vol. 474, pp. 140965-140965.
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Hassani, S, Mustapha, S, Li, J, Mousavi, M & Dackermann, U 2025, 'Next-generation coupled structure-human sensing technology: Enhanced pedestrian-bridge interaction analysis using data fusion and machine learning', Information Fusion, vol. 118, pp. 102983-102983.
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Hayatdavoodi, A & Li, Y 2025, 'An analytical method to determine the ultimate shear strength of continuous steel plate girders', Asian Journal of Civil Engineering, vol. 26, no. 2, pp. 565-575.
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Hu, Z, Chen, Q, Xu, C, Nimbalkar, S & Huang, N 2025, 'Effectiveness and Optimization Analysis of Vibration Isolation Performance of Circular and Rectangular Hollow Pipes: Numerical Modeling', International Journal of Geomechanics, vol. 25, no. 4.
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Huang, J, Li, J, Shao, R & Wu, C 2025, 'Effect of high temperature and cooling method on compression and fracture properties of geopolymer-based ultra-high performance concrete', Journal of Building Engineering, vol. 105, pp. 112433-112433.
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Hussain, T, Li, Y, Ren, M & Li, J 2025, 'Pixel-level crack segmentation and quantification enabled by multi-modality cross-fusion of RGB and depth images', Construction and Building Materials, vol. 487, pp. 141961-141961.
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Jia, H, Wei, H, Li, J, Cui, S, Xu, L & Zheng, S 2025, 'Blast resistance of steel jacket reinforced double-column bridge pier', Engineering Structures, vol. 329, pp. 119882-119882.
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Jin, X, Rao, P, Feng, W, Cui, J, Nimbalkar, S & Chen, Q 2025, 'Coupled Electric‐Thermal Damage Model for Lightning Strikes on Buried Pipeline', Contributions to Plasma Physics, vol. 65, no. 4.
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ABSTRACTA coupled electrothermal damage theory model for pipelines is proposed to assess the failure behavior of buried pipelines under lightning strikes. This article considers local thermal nonequilibrium (LTNE) conditions in the soil–water porous medium and the nonlinear characteristics of lightning functions. The calculation results show that the proposed theoretical model has better applicability and accuracy compared with previous models. Parametric analysis shows that under lightning conditions of Im = 20 kA and T1/T2 = 1.2/50 μs, the maximum local temperature of the soil around the pipeline can reach 2160 K, leading to pipeline breakdown. Metal pipelines are shown to be more effective in conducting charges, which alters the electric field distribution in the soil and impacts the formation of plasma channels. The half‐peak value of the lightning waveform has a significant impact on pipeline breakdown, and its increase will increase the risk of pipeline breakdown gradually. When considering LTNE conditions, the change in the pipeline surface temperature becomes more pronounced. Under 8/30 and 8/40 μs lightning waveforms, the pipeline surface temperature is approximately 150 and 550 K higher, respectively, compared with the thermal equilibrium conditions. The thermal conductivity and porosity of backfill soil can also affect the thermal damage of lightning‐struck pipelines. With clay filling, the highest pipeline surface temperature can reach 2590 K, while with fine sand and coarse sand, it is 1980 and 1510 K, respectively. The pipeline lightning disaster model proposed in this article has engineering significance for the investigation of pipeline lightning failure and disaster prevention mechanisms.

Le, NT, Keenan, M, Nguyen, A, Ghazvineh, S, Yu, Y, Li, J & Manalo, A 2025, 'A supervised machine learning approach for structural overload classification in railway bridges using weigh-in-motion data', Structures, vol. 71, pp. 108005-108005.
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Le, TH, Nguyen, HAD, Ha, QP, Ahmed, M, Barthelemy, X, Jiang, N, Duc, H, Azzi, M & Riley, M 2025, 'Dependable Dempster-Shafer Inference Framework for Urban Air Quality Monitoring', IEEE Sensors Journal, pp. 1-1.
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Li, C, Li, J & Zhu, X 2025, 'Flexural Behavior of Steel–Concrete Composite Beams Utilizing Innovative Long-Nut Shear Connectors: A Numerical and Experimental Study', Journal of Structural Engineering, vol. 151, no. 4.
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Li, Q, Li, H, Li, X, Li, J, Liu, K, Wei, X, Peng, K & Wu, C 2025, 'Radial Pressure Characteristics on Borehole Walls at Decoupled Charge Blasting', Rock Mechanics and Rock Engineering, vol. 58, no. 2, pp. 2403-2418.
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Lim, JY, Goh, CYM, Kang, KW, Li, J & Wu, C 2025, 'Structural response of steel-concrete composite panels to near field simultaneous blast and fragmentation loading', International Journal of Impact Engineering, vol. 195, pp. 105142-105142.
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Lin, X, Nguyen, QD, Castel, A, Deng, Z, Li, W & Tam, VWY 2025, 'Self-healing of biochar-cement composites with crystalline admixture exposed to sulphate solution and simulated seawater', Journal of Building Engineering, vol. 99, pp. 111564-111564.
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Lin, X, Nguyen, QD, Castel, A, Li, P, Tam, VWY & Li, W 2025, 'Self-healing efficiency of sustainable biochar-cement composites incorporating crystalline admixtures', Construction and Building Materials, vol. 458, pp. 139542-139542.
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Lin, X, Nguyen, QD, Castel, A, Pang, Y, Deng, Z, Shi, T, Li, W & Tam, VWY 2025, 'Durability of biochar-cementitious composites incorporating crystalline admixture in chloride and sulphate environments', Construction and Building Materials, vol. 458, pp. 139554-139554.
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Luo, H, Tao, M, Hong, Z, Xiang, G & Wu, C 2025, 'Analysis of the dynamic response and damage characteristic for the tunnel under near-field blasts and far-field earthquakes', Underground Space, vol. 21, pp. 331-351.
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Mehrabi, P, Mortazavi, M & Far, H 2025, 'Axisymmetric thermal post-buckling of the eccentric annular sector plate made of Gori-metamaterials: Introducing DNN-RF algorithm for solving the post-buckling problems', Thin-Walled Structures, vol. 208, pp. 112795-112795.
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Miao, L, Cheng, Z, Song, J, Zhang, Q, Cui, C & Li, J 2025, 'Numerical study on the effects of the mechanical degradation of UHPC layer and stud connectors on the fatigue performance of steel-UHPC composite bridge decks', Engineering Structures, vol. 332, pp. 120069-120069.
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Mostafaei, H, Kelishadi, M, Bahmani, H, Wu, C & Ghiassi, B 2025, 'Development of sustainable HPC using rubber powder and waste wire: carbon footprint analysis, mechanical and microstructural properties', European Journal of Environmental and Civil Engineering, vol. 29, no. 2, pp. 399-420.
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Nguyen, HAD, Le, HT, Barthelemy, X, Azzi, M, Duc, H, Jiang, N, Riley, M & Ha, QP 2025, 'A Deep-Learning-Based Visualization Tool for Air Pollution Forecasting', IEEE Software, vol. 42, no. 2, pp. 47-56.
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Qian, H, Li, J, Pan, Y, Zong, Z & Wu, C 2025, 'Blast performance of precast segmental utility tunnel against ground surface explosion. Part 1: Experimental analysis', Structures, vol. 71, pp. 108192-108192.
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Qu, F, Zhang, Y, Li, M, Dong, W, Li, W & Tsang, DCW 2025, 'Resource recycling of industrial waste phosphogypsum in cementitious materials: Pretreatment, properties, and applications', Journal of Environmental Management, vol. 376, pp. 124291-124291.
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Riyad, ASM, Indraratna, B, Arachchige, CK, Qi, Y & Khabbaz, H 2025, 'An Extended Perspective on the Disturbed State Concept for Rubber–Mixed Waste Material Considering Modulus Degradation under Cyclic Loading', International Journal of Geomechanics, vol. 25, no. 5.
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Shao, R, Chengqing Wu & Li, J 2025, 'Enhanced in-situ utilization of lunar simulant for fibre-reinforced high-performance concrete: Mechanical properties and cost-effectiveness for lunar applications', Journal of Materials Research and Technology, vol. 35, pp. 6849-6863.
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Shao, R, Wu, C & Li, J 2025, 'Engineering cement-free high-performance Martian concrete with enhanced in-situ utilization of soil simulant: Curing across −20 °C–40 °C and CO2-rich environments', Journal of Environmental Management, vol. 375, pp. 124426-124426.
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Shi, Y, Han, L, Wu, P, Dai, K, Liu, Z & Wu, C 2025, 'Design of 3D printing green ultra-high performance concrete based on binder system optimization', Case Studies in Construction Materials, vol. 22, pp. e04625-e04625.
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Song, Y, Huang, L, Wang, Y, Du, Y, Song, Z, Dong, Q, Zhao, X, Qi, J, Zhang, G, Li, W & Shi, L 2025, 'Energy performance and fire risk of solar PV panels under partial shading: An experimental study', Renewable Energy, vol. 246, pp. 122910-122910.
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Talaei, S, Zhu, X, Li, J, Yu, Y & Chan, THT 2025, 'A hybrid domain adaptation approach for estimation of prestressed forces in prestressed concrete bridges under moving vehicles', Engineering Structures, vol. 330, pp. 119904-119904.
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Tao, G, Tang, W, Chen, Q, Zhou, H, Nimbalkar, S, Xiao, H & Huang, Z 2025, 'Fractal Shear Strength Model for Unsaturated Soils Considering the Combined Effects of Matric Suction and Surface Tension', International Journal of Geomechanics, vol. 25, no. 7.
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Tao, G, Yang, C, Chen, Q, Nimbalkar, S, Xiao, H & Wang, Q 2025, 'Laboratory assessment of tensile properties of root-soil composite of Amorpha fruticose', Journal of Mountain Science, vol. 22, no. 3, pp. 1062-1074.
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Thomas, PS, Mansell, B, Appadoo, D, Smallwood, AS, Aldridge, L & Stuart, BH 2025, 'Characterisation of the crystallisable water in precious opal using differential scanning calorimetry and synchrotron terahertz spectroscopy', Journal of Thermal Analysis and Calorimetry, vol. 150, no. 2, pp. 1093-1103.
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Torres, IJ, Aguilera, RP & Ha, QP 2025, 'Design and Performance Evaluation of Nonlinear Model-Predictive Control for 3-D Ground Target Tracking With Fixed-Wing UAVs', IEEE Open Journal of the Industrial Electronics Society, vol. 6, pp. 76-94.
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Vu, TH, Yang, Y, Dang, LC & Sirivivatnanon, V 2025, 'Comparative analysis of chloride and acid resistance in one-part geopolymer and low carbon concrete', Magazine of Concrete Research, vol. 77, no. 7-8, pp. 448-456.
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A comparative analysis of the chloride and acid resistance of one-part geopolymer and low carbon dioxide concretes is presented, with a focus on their potential to replace traditional systems based on ordinary Portland cement (OPC) in construction. The performance of geopolymer concretes (GPCs) was compared with concretes made with OPC and OPC blended with supplementary cementitious materials (fly ash and slag) under aggressive environmental conditions. The findings revealed that, while GPCs exhibit superior resistance to acid attack, their chloride resistance is highly dependent on the specific precursor materials used. The study also highlights the limitations of using rapid chloride permeability tests at standard voltages for GPCs, suggesting that lower voltage tests at 30 V may offer a more accurate assessment. Overall, the results underscore the need for optimised precursor selection in GPCs to enhance durability and advocate for further research into testing methodologies tailored to these innovative materials.

Wang, H, Li, D, Cai, F, Li, Y, Wang, J & Zheng, J 2025, 'Design and experiment study on a novel magnetorheological impact damper coupled with multiple parallel relief orifices for reducing higher impact peaks', Journal of Intelligent Material Systems and Structures, vol. 36, no. 4, pp. 242-258.
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Conventional magnetorheological (MR) dampers exhibit the drawbacks of excessively large and non-adjustable peak force/acceleration during the initial impact in the context of high-impact loads, limiting their applicability in the field of impact resistance. This paper introduces an innovative MR damper (MRD), which, coupled with multiple parallel relief orifices, is capable of effectively mitigating the initial impact peak and enhancing the plateau effect during the mid and late stages of impact. Firstly, the configuration and principle of the novel MRD with multiple orifices (MRDWO) are illustrated and its nonlinear model, based on Bingham-Plastic model and accounting for minor loss, is established. Secondly, the structural design and fabrication of MRDWO were conducted. Simultaneously, for comparative purposes, a traditional MRD with an identical structure to MRDWO, except for the absence of relief orifices, was also fabricated. Then, experimental investigations were conducted separately on MRDWO and MRD without relief orifices (MRDWOO) under various impact velocities and control currents to study their damping forces, accelerations, and displacement responses. Finally, the experimental results of MRDWO were utilized to validate the reliability of the aforementioned nonlinear model. Additionally, a comparative analysis was conducted between MRDWO and MRDWOO under various operating conditions in terms of impact forces, accelerations, and displacements. The results indicate that the novel MRDWO significantly reduces the impact force/acceleration peak during the initial impact and enhances the plateau effect of force/acceleration in mid to later stages, thereby reducing the required displacement for absorbing. This is crucial for mitigating the initial impact damage and improving the damping efficiency of the MR damper.

Wang, JJ, Nie, XF, Yang, L, Li, WG & Zhang, SS 2025, 'Compressive behavior of FRP-UHPC-steel double-skin tubular columns', Engineering Structures, vol. 325, pp. 119451-119451.
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Wang, W, Wang, Z, Li, M, Xiong, Z, Chen, D & Wu, C 2025, 'Close-range blast behavior of hybrid FRP-concrete-steel double-skin tubular member', Thin-Walled Structures, vol. 211, pp. 113022-113022.
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Wang, X, Li, W, Guo, Y, Wang, K & Huang, Y 2025, 'Performance of Cement Mortar with Inorganic Na2SO4·10H2O-Na2HPO4·12H2O Shape-Stabilization Phase Change Materials', Journal of Materials in Civil Engineering, vol. 37, no. 4.
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Wu, L, Yang, J, Feng, S, Chen, H, Liu, H, Lin, Z & Nimbalkar, S 2025, 'Experimental assessment of freeze–thaw characteristics and microscopic mechanisms of coal-based solid waste improved loess filler', Transportation Geotechnics, vol. 54, pp. 101606-101606.
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Wu, P, Li, S, Li, Z, Xia, W & Li, Y 2025, 'Modular QZS metamaterials with enhanced load adaptability for low-frequency vibration isolation', Smart Materials and Structures, vol. 34, no. 5, pp. 055017-055017.
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Abstract This study introduces a modular quasi-zero-stiffness (QZS) metamaterial for low-frequency vibration isolation with adaptable load-carrying capacity. The proposed structure integrates a double-curved beam as a negative stiffness element and two pairs of V-shaped springs as positive stiffness elements, forming an extendable modular metamaterial. These metamaterials provide scalable and tunable load-adaptive performance through multiple modular configurations. Finite element analysis is utilized to optimize the design parameters, ensuring effective and consistent QZS behavior across the modules. A dynamic model, validated using harmonic balance methods, demonstrates the isolation effectiveness under varying loads and excitation amplitudes. By arranging multiple unit modules in series, parallel, or combined configurations, the QZS characteristics scale in a linear and predictable manner, enabling versatile load adaptability and tunability. Quasi-static tests confirm the predicted QZS behavior, while dynamic tests validate the vibration isolation performance. A single unit module attenuates vibrations at 8.6 Hz with a payload of 1420 g, while the modular configuration achieves vibration suppression above 3.6 Hz with a payload of 5680 g, without requiring alterations to the design parameters. These findings underscore the potential of the proposed modular QZS metamaterial for scalable, load-adaptive, and low-frequency vibration isolation in engineering applications.

Wu, Y, Dang, F, Nimbalkar, S, Chen, Y & Zhang, F 2025, 'Property Evolution Law and Damage Mechanism of Pervious Concrete under Different Cycle Modes', Jianzhu Cailiao Xuebao Journal of Building Materials, vol. 28, no. 1, pp. 9-18.
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In order to investigate the effect of water on pervious concrete（PC）pavement，the performance evolution equations of PC under three cycle modes of dry-wet，freeze-thaw，dry-wet and freeze-thaw were studied，and the damage mechanism under single and double factors were revealed. The results show that the basalt fiber（BF）changes the pore structure and initial property of PC，but does not affect the freeze-thaw damage mechanism. The secondary cracks of PC pavement caused by freeze-thaw cycle increase exponentially，which is different from the performance evolution law under dry-wet cycle. Dry-wet cycle in the early stage of damage causes the dissolution，loss of pore wall surface material and edge curl and peel，while freeze-thaw in the late stage of damage causes the formation and expansion of cracks，resulting in intergranular fracture. Under the coupling effect of wet-dry cycle and freeze-thaw cycle，the PC performance index decreases more than the single factor superposition of wet-dry cycle and freeze-thaw cycle.

Wu, Y, Li, S, Li, J, Yu, Y, Li, J & Li, Y 2025, 'Deep learning in crack detection: A comprehensive scientometric review', Journal of Infrastructure Intelligence and Resilience, vol. 4, no. 3, pp. 100144-100144.
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Yang, T, Yang, YK, Liu, ZX, Xu, SC & Wu, CQ 2025, 'INVESTIGATION ON MECHANICAL PROPERTIES OF ULTRA-HIGH PERFORMANCE CONCRETE AFTER HIGH TEMPERATURE', Gongcheng Lixue Engineering Mechanics, vol. 42, no. 4, pp. 97-109.
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The mechanical properties of ultra-high-performance concrete (UHPC) after high temperature were studied by static and dynamic compression and splitting tests. Moreover, the microstructure of UHPC after different temperatures was observed by scanning electron microscope (SEM), which further revealed the reasons why the changes take place in mechanical properties of UHPC after different high temperatures. Five target temperatures were set, i.e., 25 ℃ (room temperature), 200 ℃, 400 ℃, 600 ℃, and 800 ℃, and a total of 120 specimens were tested. The results show that both the static and dynamic strength of UHPC increase first and then decrease with the temperature. At the same impact velocity, the compression and splitting impact toughness of UHPC also increases first and then decreases with the temperature. However, when the impact velocity is weak, the effect of temperature on the impact toughness is not significant. The formula for the variation range between strain rate and dynamic increase factor (DIF) was fitted in this study. The tensile dynamic increase factor (TDIF) of UHPC decreases first and then increases with the temperature (except 800 ℃). However, TDIF under different target temperatures (except 800 ℃) decreases with the increase of splitting strength, which shows that the strain rate enhancement effect of UHPC decreases with the splitting strength of UHPC.

Zhan, P, Wang, J, Yu, W, Deng, Z, She, A, Zuo, J, Li, W & Xu, J 2025, 'Insights into the hydration kinetics, microstructure and early strength of Portland cement containing synthetic C-S-H/PCE nanocomposites', Cement and Concrete Composites, vol. 157, pp. 105886-105886.
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Zhang, X, Zhao, H, Tao, Z & Li, W 2025, 'Performance of sustainable cementitious mortar incorporating hybrid waste glass powder and steel slag', Construction and Building Materials, vol. 472, pp. 140928-140928.
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Zhang, X, Zhu, X, Wang, Y & Li, J 2025, 'Structural damage detection based on transmissibility functions with unsupervised domain adaptation', Engineering Structures, vol. 322, pp. 119142-119142.
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Zhang, X, Zhu, X, Yu, Y & Li, J 2025, 'Transfer Learning-Based Structural Damage Identification for Building Structures with Limited Measurement Data', International Journal of Structural Stability and Dynamics, vol. 25, no. 09.
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Structural damage detection is crucial for ensuring the safety of civil building structures in operational environments. Recently, deep learning-based methods have gained increasing attention from engineers and researchers. The performance of conventional deep learning methods for structural damage detection relies on a large number of labeled training datasets. However, it is difficult or/and impossible to obtain sufficient datasets to cover various damage scenarios for in-service structures. A little research has been conducted to identify both the damage severity and location with limited labeled measurement data. A novel transfer learning-based method for structural damage identification with limited measurements has been proposed utilizing frequency response functions (FRFs) as the input. The real structure is regarded as the target domain and its numerical model is as the source domain. The samples for various damage scenarios are generated using the numerical model, and a designed deep convolutional neural network (CNN) is pre-trained. The knowledge of the pre-trained network is transferred to identify the damage location and severity of the real structure using limited measurement data. Numerical and experimental studies have been conducted on a three-story building structure to verify the performance of the proposed method. To understand transfer learning and model interpretability, the t-SNE feature visualization is adopted to show the feature distribution changes during transfer learning. Numerical and experimental results show that the proposed approach outperforms conventional CNN models, and it is effective and accurate in identifying structural damage location and severity in real structures with limited measurement data.

Zhao, C, Dong, W, Indra Mahlia, TM, Shi, L, Wang, K, Shah, SP & Li, W 2025, 'Enhancing energy storage capability for renewable energy systems through advanced cement-based supercapacitors', Energy and Buildings, vol. 338, pp. 115732-115732.
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Zhao, C, Dong, W, Liu, J, Peng, S & Li, W 2025, 'Toward intelligent buildings and civil infrastructure: A review on multifunctional concrete through nanotechnology', Cement and Concrete Composites, vol. 163, pp. 106165-106165.
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Zhao, C, Dong, W, Wang, K, Tao, Z & Li, W 2025, 'Investigation on effects of LiCl, KCl and polyethylene oxide on electrochemical properties of cement-based capacitors', Construction and Building Materials, vol. 481, pp. 141612-141612.
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Zhao, H, Gan, Y, Qu, F, Tang, Z, Peng, S, Chen, Y & Li, W 2025, 'Nano- and micro-characterisation on the heterogeneity of ITZs in recycled lump concrete', Cement and Concrete Composites, vol. 161, pp. 106078-106078.
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Zhou, S, Yang, D, Zhang, Z, Zhang, J, Qu, F, Punetha, P, Li, W & Li, N 2025, 'Enhancing autonomous pavement crack detection: Optimizing YOLOv5s algorithm with advanced deep learning techniques', Measurement, vol. 240, pp. 115603-115603.
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Haider, W, Batool, S, Milazzo, F & Ha, QP 1970, 'Machine Learning-Based Forecasting Active Power Loss in Distribution Systems', E3S Web of Conferences, EDP Sciences, pp. 04003-04003.
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This paper presents an ensemble learning approach to predict the active power losses during the allocation and sizing of distributed generation (DG) units in power distribution networks. The forecast model incorporates the Gradient Boosting Machine Regression (GBMR) to estimate DG location, bus voltages, DG size, and active losses without conventional power flow calculations. The results demonstrate that the suggested estimations of power losses and DG sizing are effective, practical, and adaptable for power system management. The accuracy of the proposed model has been validated using key performance metrics and tested on the standard IEEE 33 bus system. In the case of fixed load, the GBMR outperforms other machine learning techniques with the R-squared 0.9997, with a very low mean absolute percentage error (MAPE) (0.2216%) and a root mean square error (RMSE) of 1.0673 in predicting active power losses. This approach is promising in enabling grid operators to effectively manage DG unit integration of distributed energy resources from precise and reliable estimates of the power loss.

Le, TH, Nguyen, HAD, Ha, QP, Tran, MQ, Ahmed, M, Kong, J, Barthelemy, X, Duc, H, Jiang, N, Azzi, M & Riley, M 1970, 'Dempster-Shafer ensemble learning framework for air pollution nowcasting', E3S Web of Conferences, EDP Sciences, pp. 01003-01003.
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Deep-learning has emerged as a powerful approach to significantly improve forecast accuracy for air quality estimation. Several models have been developed, demonstrating their own merits in some scenarios and for certain pollutants. In nowcasting, the prediction of air pollution over a small time period essentially demands accurate and reliable estimates, especially in the event cases. From these, selecting the most suitable model to achieve the required forecast performance remains challenging. This paper presents an ensemble framework based on the Dempster-Shafer theory for data fusion to identify the most accurate and reliable forecasts of air pollution obtained from multiple deep neural network models. Our framework is evaluated against three popular machine learning methods, namely, LightGBM, Random Forest, and XGBoost. Experiments are conducted on two horizons: 6-hour and 12-hour predictions using real-world air quality data collected from state-run monitoring stations and low-cost wireless sensor networks.

Ren, Q, Wang, Y & Ha, QP 1970, 'Automatic Recognition and Segmentation of Overlapped GPR Target Signatures', E3S Web of Conferences, EDP Sciences, pp. 03003-03003.
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Ground penetrating radar (GPR) has been widely utilized for non-destructive inspection of civil infrastructure systems such as bridges and tunnels. However, the identification of GPR signatures poses significant challenges due to the overlapped multiple objects. To overcome the obstacle, we proposed an innovative Mask R-CNN based network considering spatial relationship between GPR signatures. Firstly, to capture the spatial relationship of overlapping signatures, we introduced an improved intersection over union considering central distance and aspect ratio between GPR signatures. Secondly, we further modified the Non-Maximum Suppression and enhanced the corresponding anchor generative mechanism. To validate the proposed method, we conducted testing on GPR scans obtained from real data from a bridge. The results demonstrate that the proposed method not only accurately detects GPR signatures, but also significantly outperforms existing Mask R-CNN in terms of segmenting overlapped GPR signature. Specially, the proposed method achieved an average accuracy of 46.8% in the segmentation task, marking a substantial advancement in the field.