Civil and Environmental Engineering - Journal articles
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Item End-of-life wind turbine blades and paths to a circular economy(Elsevier, 2025) Deeney, Peter; Leahy, Paul G.; Campbell, Kevin; Ducourtieux, Claire; Mullally, Gerard; Dunphy, Niall P.; Science Foundation Ireland; Irish Research Council; Sustainable Energy Authority of IrelandA structured literature review is used to identify barriers to the recommended methods of processing end-of-life wind turbine blades. The Waste Management Hierarchy recommends firstly avoidance, then repurposing, recycling, energy recovery and lastly, disposal. The review finds that most recent research articles are concerned with recycling, despite its position in third place in the Hierarchy. The review also identifies the following barriers to the first, second and third most recommended processes: misalignment of financial rewards for blade manufacturers making more durable blades; lack of information about blades which could help repurposing and recycling; and lack of financial incentives for any of the top three methods. Based on these findings the following solutions are proposed: alternative payment structures for blade ownership incentivising blade quality and longevity; an information exchange to facilitate the second hand market, repurposing and recycling; and the widespread use of compliance bonds to provide a financial incentive for repurposing and recycling.Item A low-carbon electricity transition for small island developing states: The case of Mauritius(Elsevier Ltd., 2024-12-20) Jaggeshar, Doorgeshwaree; Mao, Xianqiang; Guo, Zhi; Zusman, Eric; Tu, Kevin; Chen, Xing; Ma, Zhiyuan; Global Energy Interconnection GroupA clean energy transition can not only help rebuild the energy landscape of small island developing states (SIDS) but also boost their resilience and long-term development prospects. This study employs the Open-Source Energy Modeling System (OSeMOSYS) model to analyze low-carbon transition pathways for Mauritius, which are aligned with its nationally determined contribution (NDC) objectives to increase renewable energy to 60 % and phase out coal by 2030. The study applied key performance indicators to assess this pathway against energy self-sufficiency, economic, environmental and social criteria. The study showed that renewable energy sources, namely, solar, biomass, wind and waste-to-energy, can be game-changers for the island. The optimal transition pathway would achieve a renewable target of 76.8 % and reduce CO2 emissions by more than 67 % across the modeling period at an estimated cost of 1.94 billion USD by 2040. Finally, the study evaluated the implications of Mauritius' clean transition in terms of its effects on green jobs as well as whether there is sufficient infrastructure, administrative and financial capacity and energy pricing policies to support the optimal pathway. The study concludes that the experience modeling a low-carbon transition pathway for Mauritius could also offer useful lessons for other SIDS contemplating similar transitions.Item Prediction of load-bearing capacity of FRP-steel composite tubed concrete columns: Using explainable machine learning model with limited data(Elsevier Ltd., 2024-12-03) Liu, Xiaoyang; Sun, Guozheng; Ju, Ruiqing; Li, Jing; Li, Zili; Jiang, Yali; Zhao, Kai; Zhang, Ye; Jing, Yucai; Yang, Guotao; Natural Science Foundation of Shandong ProvinceThe complex interaction mechanism between the FRP jacket, steel tube, and confined concrete in the FRP-steel composite tubed concrete (F-STC) column makes the prediction of its mechanical behaviour a challenging task. This paper specifically investigates the application of machine learning models to predict the load-bearing capacity of F-STC columns. Since relatively few experimental works are performed on F-STC columns, the database established based on the test results from previous research contains only 69 data samples. In order to circumvent the training difficulties caused by the relatively small database, the application of the Gaussian process regression (GPR) model is trialled in this study. To make the predictions of the GPR model explainable, the Shapley additive explanations (SHAP) approach is incorporated with the GPR model in this study. Besides, four contrasting prediction models based on artificial neural network (ANN), support vector regression (SVR), decision tree (DT), and random forest (RF), are also proposed. The k-fold validation and test results indicate that the GPR model provides strong potential in predicting the load-bearing capacity of F-STC columns with high prediction accuracy and generalisation capability. Besides, 95 % and 99 % confidence intervals obtained by the GPR model are provided to show the uncertainty of the prediction results. Furthermore, the effect of the database size on the prediction performance of GPR, ANN, and SVR models is further examined by gradually reducing the number of data samples, and the comparisons illustrate the superiority of the GPR model.Item The impact of thermal–hydraulic variation on tunnel long-term performance: a tale of two tunnels(ICE Publishing; ICE Publishing collections are provided by Emerald Publishing, 2024-09-28) Wang, Chao ; Xiao, Zhipeng ; Di Murro, Vanessa ; Osborne, John; Friedman, Miles ; Li, Zili ; Irish Research Council; Horizon 2020; H2020 Marie Skłodowska-Curie Actions; Science Foundation Ireland; Transport Infrastructure IrelandLong-term structural performance of ageing tunnels is influenced by various natural and anthropogenic factors. This study examines the impacts of two rarely investigated climatic factors: rainfall and temperature. Two dedicated case studies were conducted on the European Organisation for Nuclear Research (CERN) TT10 tunnel and Dublin port tunnel (DPT) using distributed fibre optic strain sensing (DFOS) and wireless sensor network (WSN) monitoring, respectively. DFOS data showed an increasing deformation in TT10 tunnel, attributed to tunnel deteriorations and ground deformation, with seasonal variation of lining strains linked to rainfall-related seasonal change in pore water pressure. However, inconsistencies in the rainfall–strain correlation were also noted due to geological complexities and varying pore water pressure sources. In contrast, WSN measurements showed that DPT deformation correlated with temperature, instead of precipitation. DPT deformation increased in warmer seasons and decreased in colder ones, in the absence of external disturbances, comprising reversible thermal deformation and irreversible deterioration-induced deformation. Over time, cyclic and periodic temperature changes caused elastic deformation to reverse, while plastic deformation accumulated, leading to ongoing tunnel deformation. These findings bring more insights into the resilience of critical underground infrastructure vulnerable to climate change, groundwater variations and other environmental factors.Item Modelling the impact of deterioration on the long-term performance of Dublin Tunnel(Canadian Science Publishing, 2024-09-11) Wang, Chao; Xiao, Zhipeng; Friedman, Miles; Li, Zili; Science Foundation Ireland; Transport Infrastructure Ireland; National Natural Science Foundation of ChinaThe influence of tunnel deteriorations on its long-term performance has received extensive attention recently. Most studies considered deteriorations by manually varying the magnitude of parameters like permeability and stiffness, neglecting their time-dependent variation. This paper addresses this gap by investigating the impact of time-dependent deteriorations on the long-term behaviour of the aging Dublin Port Tunnel (DPT). A modified analytical relative ground-lining permeability model and calculated deteriorated permeability for DPT were presented, with steps and procedures generalised. The deteriorated permeability was incorporated into the hydraulic deterioration model, together with mechanical deterioration, offering a more holistic and realistic prediction of DPT’s long-term performance than previously available. Numerical results, compared against field measurements, showed (1) assuming constant permeability fails to accurately capture time-dependent liner deformation, and hydraulic deterioration is the dominant factor inducing an approaching squatting deformation mode; (2) continuous mechanical deterioration leads to a linear growth in vertical and horizontal convergence over time, with vertical convergence being more pronounced, indicating a squatting contraction deformation mode; (3) the comparison quantitatively evaluates the impact of individual and coupled hydro-mechanical deterioration on DPT’s long-term behaviour and the agreement between field data and numerical results confirms coupled lining deterioration is the root cause behind the observation.