Innovative Infrastructure Solutions

Mirzabozorg, Hassan; Ebadi, Shadi

2025 Innovative Infrastructure Solutions

doi: 10.1007/s41062-024-01809-7

Long-term creep in concrete induces significant stress release, which is a critical consideration for the maintenance strategies, safety, and risk assessment of concrete dams. This study examines the effects of creep on the structural behavior of high concrete arch dams, focusing on Karun I as a detailed case study. By applying Norton formulation parameters obtained from experimental creep data, we performed a comprehensive set of thermal and structural analyses calibrated with real data from instruments installed in the dam. Our findings reveal that neglecting the effects of creep can lead to substantial inaccuracies in structural modeling, particularly when contraction joints are included, which amplify the impact of creep. We conclude that existing international guidelines inadequately account for the creep phenomenon, emphasizing the need for updated models in evaluating the structural integrity of older concrete arch dams. This research has important implications for improving codes and maintenance practices, ultimately enhancing the safety and longevity of concrete infrastructure.

Nasir, Amna; Butt, Faheem; Ahmad, Farhan

2025 Innovative Infrastructure Solutions

doi: 10.1007/s41062-024-01803-z

The rapid increase in plastic waste due to urbanization and population growth is causing significant environmental and health concerns. Simultaneously, the high demand for concrete in infrastructure projects is depleting natural resources. To address both challenges, many studies have explored using recycled plastic waste in concrete, primarily for non-structural applications. Although plastic waste generally reduces concrete’s mechanical properties, various additives like fly ash and silica fume have been used to improve strength. However, limited research exists on the structural performance of concrete with recycled plastic coarse aggregate (PCA). This study examines the mechanical and axial behavior of recycled plastic aggregate concrete (RPAC) reinforced with silica fume, steel fiber (SF), and polypropylene fiber (PPF). Results reveal a significant increase in mechanical and axial properties for RPAC mixes modified with silica fume and fibers. The RPAC mix (M3) with 20% PCA, 20% silica fume, and 0.75% steel fiber (SF) achieved the highest compressive strength (CS) of 17.9 MPa, split tensile strength (ST) of 1.81 MPa, and flexural strength (FL) of 2.96 MPa. Similarly, an enhanced ultimate load capacity of approximately 927 kN was achieved, significantly reducing the load capacity loss from 18.2% (RPAC with only 20% PCA) to just 4.83%. Additionally, columns containing PCA exhibited an improved ductility index compared to the control column without PCA, with a maximum enhancement of approximately 59.1% observed in RPAC columns (M3) modified with silica fume and SF. Overall, M3 with 20% PCA, 20% silica fume, and 0.75% SF exhibited excellent performance with enhanced mechanical, axial, and ductility behavior.

Keshta, Mostafa M.; Eltawil, Khalid A.; Elshikh, Mohamed M. Yousry; Youssf, Osama

2025 Innovative Infrastructure Solutions

doi: 10.1007/s41062-024-01802-0

Sustainable materials and technologies used in engineered cementitious composites (ECC) and engineered geopolymer composites (EGC) have gained significant attention from concrete researchers in recent decades, owing to their superior performance compared to traditional concrete. In this study, the performance of sustainable ECC and EGC made of metakaolin (MK) and magnetized water (MW) is evaluated and compared. This was carried out using 14 mixes (7 for ECC and 7 for EGC). The control ECC mix contained cement and ground granulated blast furnace slag (GGBFS) and the control EGC mix contained fly ash (FA) and GGBFS. In ECC, the cement and GGBFS were partially replaced by MK; and in EGC, the FA and GGBFS were replaced by MK. The replacement ratios were 20%, 40%, 60%, and 80% by volume. The tap water (TW) was completely replaced by MW in ECC and EGC mixes containing 0% and 20% MK. Fresh, mechanical, and durability properties were measured for both ECC and EGC such as; slump, compressive and flexural strength, water absorption, and sorptivity. The effect of different curing environments (tap water and seawater) on ECC/EGC compressive strength was also studies. Furthermore, microstructural analyses were performed on specific ECC and EGC mixtures. The microstructure analyses included scanning electronic microscope (SEM), energy dispersive X-ray (EDX), and mapping of the morphology surface. The fresh and mechanical properties indicated that EGC exhibited higher slump values (by up to 7.3 times) and higher compressive strengths (by up to 90%) than those of ECC, especially in the presence of MW. Seawater curing enhanced the EGC compressive strength by up to 16%. The durability results showed that absorption rates and sorptivity of EGC were relatively higher than those of the corresponding ECC. The SEM analysis showed that the concentration of gelatinous materials as CSH and ASG in the mixes using MW was higher than the similar mixes with made with TW, especially in the presence of MK. The EDX analysis and mapping showed that the ratio of Ca/Si was low in EGC compared to that in ECC.

Hoang, Huong-Giang Thi; Nguyen, Thuy-Anh; Ly, Hai-Bang

2025 Innovative Infrastructure Solutions

doi: 10.1007/s41062-024-01808-8

Assessment of structural health in buildings and infrastructure is critical for ensuring safety and long-term durability. This paper presents a novel approach using supervised machine learning (ML) models for the prediction of concrete compressive strength (denoted as FCU), which is a key parameter in the evaluation of structural integrity. Ultrasonic pulse velocity (UPV) and concrete mix design parameters were employed as the basis for the predictive models. Four distinct ML models are proposed, each characterized by a unique set of hyperparameters that significantly impact performance. Hyperparameter tuning is conducted before model training to maximize predictive accuracy. This study investigates the impact of four essential hyperparameters: learning rate, number of iterations, maximum depth, and subsample. Parameter selection is maintained consistently across all models to ensure fair comparison. The sand cat swarm optimization (SCSO) is used for model optimization and refinement. Evaluation based on RMSE (Root Mean Square Error) values reveals that the LGB model with N_pop = 10 exhibits superior performance. Shapley Additive exPlanations analysis is employed to gain insights into the factors impacting FCU, offering understanding of strength development mechanisms. A user-friendly graphical user interface (GUI) was developed to streamline the practical application of this research. The GUI enables practitioners and researchers to easily estimate FCU on the basis of readily available input parameters.

Barma, Niladri S.; Dhandole, Satish D.; Saravanan, T. Jothi

2025 Innovative Infrastructure Solutions

doi: 10.1007/s41062-024-01796-9

Damage identification in engineering disciplines such as mechanical, civil, and aerospace engineering has become a critical area of research. This study introduces a methodology to address structural damage-induced loss of stiffness. The approach assumes that structures exhibit linear elastic behavior before and after the damage and considers them time-invariant. To demonstrate the applicability of the proposed method, a representative beam structure is selected to mimic various components found in buildings, bridges, and dams. The methodology involves developing a numerical model using the finite element (FE) method in ANSYS and a program developed in MATLAB. Additionally, experimental data is collected using vibrational transducers. The classical modal strain energy and mode shape curvature methods are compared to identify structural damage. The extent of this damage is determined by analyzing modal frequencies using a combined numerical and experimental approach. A modal assurance criterion is employed to gauge the similarity of mode shapes. The analytical FE model is refined through a direct model updating procedure using MATLAB scripts. In this iterative process, the numerical parameters of the FE model are fine-tuned to align more closely with the experimental data, ensuring the model accurately represents the real structure. This study combines experimental data with the improved numerical FE model to identify and quantify damage by measuring the loss of stiffness. Integrating expert knowledge and feedback into the model updating process, it can enhance the accuracy and interpretability of updated models.

Sravanthi, B.; Radhakrishnan, Vishnu; Andrews, Jithin Kurian; Saudagar, Asim Sarfaraj Rahimoddin

2025 Innovative Infrastructure Solutions

doi: 10.1007/s41062-024-01782-1

Fly ash based geopolymer stabilized base layers (FA-GB) are considered as stabilized pavement materials which have the potential to replace the conventional cement-treated base layers (CTB). The present study aims to carry out a comparative performance assessment of FA-GB and CTB under laboratory conditions. FA-GB considered in the present study were prepared at different molarities of alkali activator − 4 M, 6 M and 8 M, and was compared with CTB with 6% cement. Class C Fly Ash was used in the present investigation. Performance assessment of these mixes was carried out in terms of compaction characteristics, unconfined compressive strength (UCS), durability, indirect tensile strength (ITS), resilient modulus (Mr) and fatigue performance of the mixes. FA-GB with 6 M and 8 M exhibited nearly 50% higher UCS value than CTB, while the UCS of FA-GB with 4 M was marginally less than that of CTB. It was interesting to note that FA-GB required more time for strength gain when compared to CTB. However, the ITS and Mr of the FA-GB mixes were nearly twice that of CTB. Fatigue performance studies were carried out at stress ratios of 0.5, 0.65 & 0.8, and it was observed that CTB mixes exhibited comparatively lower fatigue life when compared with FA-GB. The observed fatigue performances were further used in this study for calculate the strain reduction below the stabilized base layers and also fatigue analysis provide the reliable estimates about the relative performance of the base layer mixes. It was found that the critical strain values decreased nearly 16-30% when CTB was replaced by the FA-GB prepared with 6 M.