Urban growth in developing countries like India has led to increased traffic congestion, delays, and environmental pollution, highlighting the need for sustainable transportation alternatives. Inland Water Transport (IWT) emerges as an eco-friendly mode of transportation, but its development remains constrained. The study identifies 29 significant obstacles which are ranked based on expert opinions from 15 professionals in the field of IWT, collected through online surveys, face-to-face interviews, and phone calls, and analyzed using the Plithogenic Set based Neutrosophic Analytic Hierarchy Process method. The results show that infrastructural barriers, i.e., inadequate waterways and terminals (0.0476), and economic barriers, i.e., limited private party investment in infrastructure and buying vessels (0.0439), emerge as the primary barriers. The current research provides a structured Multi-Criteria Decision-Making (MCDM) framework for policymakers to eradicate key barriers by implementing various strategies. The study contributes to Sustainable Development Goals (SDGs), particularly SDG-9 (resilient infrastructure), SDG-11 (sustainable cities), and SDG-13 (climate action). The findings provide valuable insights for policymakers to prioritize actions and investments in IWT development. These recommendations can be applied not only to India but also to other regions facing similar challenges in developing sustainable inland waterway transport systems.
An efficient urban drainage solution, sustainable pervious concrete mitigates stormwater runoff but exhibits highly non-linear hydraulic behavior based on its constituents. This study presents an explainable data-driven framework to accurately predict pervious concrete permeability. A 70:30 holdout partitioning strategy was applied to a meta-dataset of 150 experimental records to train and validate four distinct machine learning algorithms: Artificial Neural Networks (ANN), K-Nearest Neighbors (KNN), Support Vector Regression (SVR), and Extreme Gradient Boosting (XGB). The input space comprised critical mix design parameters (aggregate-to-binder, fly ash-to-binder, and water-to-binder ratios, alongside mean aggregate size), while SHapley Additive exPlanations (SHAP) interpreted the optimal model. Among the evaluated machine learning algorithms, the XGB model demonstrated superior predictive capability for pervious concrete permeability compared to ANN, SVR, and KNN models. Post-hoc SHAP analysis successfully decoded the model’s “black box,” proving that the aggregate-to-binder ratio and aggregate size are primary drivers governing interconnected void space. In conclusion, the developed framework replaces tedious, trial-and-error laboratory iterations with highly accurate, physically consistent virtual simulations.
Abstract This research develops a sustainable and cost-effective composite cladding engineered from recycled polyethylene terephthalate (PET), reinforced with recycled tire steel fibers (RSFs), river sand, and rice husk ash (RHA). Highlighting the potential need for fire-resilient building materials, this study valorizes non-biodegradable waste to provide a high-performance alternative to traditional cladding. Specimens were produced via hot-mixing with a fixed concentration of 2.5% RSFs and 50% PET; RHA-replaced sand at fractions from 0% to 20% (maintaining a 1:1 PET-to-sand ratio in the control mix) to optimize performance. Physical and mechanical evaluations demonstrated an inverse relationship between density and RHA content, with density decreasing from 2.5 g/cm³ (0% RHA) to 1.5 g/cm³ (20% RHA). Water absorption increased proportionally from 1.8% to 3.4% with higher ash content, remaining within acceptable limits. Compressive strength peaked at 12.2% RHA, reaching 27.4 MPa, surpassing the 22.6 MPa control sample, thanks to the crack-arresting action of RSFs. Fire testing confirmed structural integrity up to 150 °C, with melting observed at 300 °C, confirming suitability for standard external environments. An economic analysis establishes that the optimal composite formulation-comprising 48.7% PET, 2.5% RSFs, 12.2% RHA, and 36.6% river sand, yields a standard panel (2.44 m x 1.22 m x 0.02 m, weighing 112.52 kg) with a raw material production cost of approximately USD 7.71 per m² (about USD 22.94 per panel, including a 10% contingency). This offers significant economic savings compared to traditional granite and ceramic cladding, presenting a durable, high-performance solution for sustainable construction.
Abstract A corpus of 54 full-text-appraised studies was synthesised to determine how bond transfer, anchorage and mixed-mode fracture govern basalt fibre-reinforced polymer (BFRP) strengthening of reinforced-concrete (RC) beams. The corrected PRISMA 2020 flow comprised 923 identified records, 284 records retained after database filtering, 214 unique records screened, 187 reports assessed for eligibility and 54 included studies. Externally bonded (EB) sheets and plates, near-surface-mounted (NSM) bars and ropes, and BFRP grids embedded in polymer cement mortar, engineered cementitious composite or engineered geopolymer composite were analysed as mechanically distinct systems. A structured quantitative narrative synthesis was adopted rather than a meta-analysis because the studies used non-equivalent beam geometries, strengthening ratios, control definitions, loading protocols, outcome metrics and failure classifications, while variance estimates required for statistical weighting were frequently unavailable. Across the included evidence, steel-plate anchorage increased ultimate load by 46.7% relative to its study control, epoxy anchors increased ultimate load by 13.1% and BFRP strain utilisation by 43.5%, anchored U-wraps increased ultimate capacity by approximately 56%, and BFRP-grid cementitious systems reported ultimate-load gains of up to 83.1%; these values are study-specific signals rather than pooled effect estimates. EB systems were primarily governed by intermediate-crack and plate-end debonding, whereas NSM systems were governed by groove-end splitting, pull-out and concrete-cover separation. The review further identifies the BFRP-specific cohesive parameters requiring calibration, including normal and shear stiffness, damage-initiation tractions, Mode I and Mode II fracture energies, mixed-mode interaction exponent, adhesive thickness, substrate fracture properties, width effects, anchorage stiffness and environmental degradation functions. Evidence was interpreted according to directness, with core BFRP beam and interface experiments separated from modelling studies, boundary BFRP evidence and non-BFRP comparator evidence. Existing ACI, fib, CSA and Eurocode-related guidance provides a transferable FRP design structure but does not remove the need for BFRP-specific interface qualification. The principal conclusion is that reliable BFRP strengthening should be designed as an integrated material-interface-anchorage system, with conclusions interpreted as directional because of substantial inter-study heterogeneity.
The construction industry is fast transforming to become more and more empowered by the next phase of the digital evolution, Construction 5.0, which is based on the use of new digital tools alongside human-centric, sustainable, and climate-resilient methods to address sustainability, labour shortage and climate resilience challenges. Organizational readiness for Construction 5.0 is still unclear as more technologies like AI, IoT, BIM and modular construction are being adopted, especially in developing countries such as India. Currently, this study proposes a fuzzy logic-based framework for evaluating the Construction 5.0 readiness in three major enablers, which are decomposed into seven criteria and twenty-six attributes: Resilience, Human Centricity and Environmental Sustainability. The framework is based on expert judgments from a medium-scale construction company in India, which quantifies the readiness of the enterprise using a Fuzzy Construction 5.0 Index and weak attributes by a Fuzzy Performance-Importance Index. In this single-case application, results indicate the case organisation is in the ‘Ready’ to ‘Very Ready’ range, with stronger resilience and basic human-centric practices and weaker advanced sustainability and assistive technologies. The fuzzy logic approach provides a structured, repeatable diagnostic and prioritisation roadmap to guide capability development toward Construction 5.0.
