Beyond Repair: A Critical Review of Smart, Sustainable, and AI-Driven Strengthening Techniques for Aging Civil Infrastructure
COMPARISION OF HYPSOMETRIC PARAMETERS OF BANGLAORE URBAN WATERSHEDS USING REMOTE SENSING AND GIS TECHNIQUES
To Study The Mechanical Properties Of Concrete Containing Cement and Sand with Biomaterial and Glass Waste in Concrete
A Case Study On Design, Optimisation and Effects of Traffic Signals at Sarakki Junction
Assessment Of Soil Erosion In The Western Ghats Region Of Kannur Using The RUSLE Model And Remote Sensing Data
Estimating the Soil Moisture Index using Normalized Difference Vegetation Index (NDVI) And Land Surface Temperature (LST) for Bidar and Kalaburagi District, Karnataka
Roughness Evaluation of Flexible Pavements Using Merlin and Total Station Equipment
Site Suitability Analysis for Solid Waste Dumping in Ranchi City, Jharkhand Using Remote Sensing and GIS Techniques
Unsaturated Seepage Modeling of Lined Canal Using SEEP/W
Strengthening and Rehabilitation of RC Beams with Openings Using CFRP
A Seasonal Autoregressive Model Of Vancouver Bicycle Traffic Using Weather Variables
Prediction of Compressive Strength of Concrete by Data-Driven Models
Predicting the 28 Days Compressive Strength of Concrete Using Artificial Neural Network
Measuring Compressive Strength of Puzzolan Concrete by Ultrasonic Pulse Velocity Method
Design and Analysis of Roller Compacted Concrete Pavements for Low Volume Roads in India
The structural soundness of civil infrastructure is progressively undermined by factors such as deterioration due to age, excessive utilization, environmental pressures, and natural calamities. Strengthening interventions—once dominated by material-heavy, reactive strategies—are undergoing a transformative shift toward smarter, more sustainable, and digitally driven solutions. This analysis rigorously investigates the progression of reinforcement methodologies, transitioning from traditional approaches to intelligent and adaptive frameworks, with a specific focus on the assessment of structural performance, the incorporation of smart materials, and the integration of artificial intelligence (AI) alongside digitalization. The discussion expands into sustainable and circular approaches that align with global environmental goals, advocating for resource efficiency, component reuse, and lifecycle thinking. Finally, the paper explores forward-looking innovation directions, including AI co-design, 3D-printed retrofits, and bio-inspired adaptive systems. By synthesizing current research and future potentials, this review aims to guide the development of next-generation strengthening strategies that are resilient, adaptive, and environmentally responsible.
Hypsometric analysis is considered as an effective tool to understand the stages of geomorphic status and geological development of river basin and for delineation of erosion proneness of watershed. Bangalore urban has been subjected for rapid urbanisation due to which there is an increased water demand over a period of time. Hence, to tackle the growing water scarcity and reoccurrence of droughts and floods, an attempt has been made in the present study to investigate and understand the morphometry and derivation of hypsometric curves and hypsometric integrals of the watersheds of Bangalore urban area. Bengaluru Urban is a densely populated city which is geographically lies between 12o49’5” N to 13o8’32” N and 77o27’29” E to 77o47’2” E. In Bangalore urban area, KC valley and Hebbal flows towards south-east direction and Vrishabhavathi valley towards south-west direction and divide Bengaluru into three distinct and separate drainage zones. The SRTM-DEM data has been used for hypsometric analysis purposes. The downloaded DEM tiles are mosaiced in the Arc map version 10.4 environment. Using Arc Spatial analysis tool, hypsometric analysis has been carriedipout and generated the hypsometric curves and hypsometic integrals on watershed wise. The hypsometric curves which is concave upwards at higher elevations and convex downward at low elevation indicates that KC valley, Vrishabhavathi valley and Hebbal valley are approaching the mature stage will have less rate of erosion and characterised by concave upward at high elevation having HI values 0.45, 0.54 and 0.48 respectively. The findings will help in recommendation of appropriate mitigation measures.
This study looks into using local materials to Improve concrete by replacing some of its traditional Components. Specifically, it examines how Rice Husk Ash (RHA) can partially replace Pozzolanic Portland Cement (PPC) and how glass powder waste can substitute sand. The Goal is to find the best combination that strengthens RCC Beams for concrete grades M35 and M40. This research also Tackles the issue of managing agricultural waste, such as Rice husks, and addresses the growing concern over glass Waste, which is increasing due to high production rates and Slow decomposition. By reducing cement use, we aim to Minimize the environmental impact, as cement production Uses a lot of raw materials and releases harmful gases. The Primary focus is on determining the optimal amount of glass Powder waste that can replace sand in concrete, as it has Excellent pozzolanic properties. Additionally, the study Looks at how RHA, a local biodegradable material, can Replace part of the PPC. Ultimately, this project seeks to Find effective solutions for managing agricultural and glass Waste, while promoting more sustainable construction practices.
Urban intersections in growing cities like Bengaluru are increasingly strained by rising traffic volumes and inconsistent signal operations. Sarakki Junction, a key node in South Bengaluru’s Outer Ring Road corridor, reflects these urban mobility challenges, with recurring congestion, long delays, and poor pedestrian safety. This study investigates the existing conditions at Sarakki Junction and proposes improvements through data-driven signal optimization.A comprehensive field survey was undertaken, combining manual classified vehicle counts with feedback collected from road users through structured questionnaires. The aim was to understand both quantitative traffic flow patterns and qualitative perceptions of delay, safety, and infrastructure adequacy.Using this data, a detailed simulation model of the junction was developed in PTV VISSIM. The model incorporated actual geometric layouts, signal configurations, and observed vehicle behaviors. To improve reliability, local driving styles—marked by frequent lane changes and limited discipline—were calibrated into the model. Subsequently, signal timings were optimized using standard methodologies and tested under simulated conditions.The optimization led to a significant reduction in average delay times across all approaches. Results indicate that with improved signal phasing and vehicle movement logic, even complex intersections like Sarakki can experience measurable performance gains. Additionally, the study emphasizes the importance of integrating simulation tools with on-ground user feedback for urban traffic management.By showcasing the practical benefits of microsimulation-based optimization, this case study contributes to ongoing efforts in making Bengaluru's traffic infrastructure more responsive, efficient, and commuter-friendly.
Soil erosion is a critical factor undermining the ecological resilience and farm productivity of the Western Ghats, particularly in regions like Kannur, Kerala, where high rainfall intensity and steep terrain prevail. This research estimates future soil erosion for the years 2025 and 2026 using the Revised Universal Soil Loss Equation (RUSLE) model, integrated with GIS and remote sensing technologies. The analysis incorporates key RUSLE factors including rainfall erosivity (R), soil erodibility (K), slope length and steepness (LS), land cover (C), and conservation practices (P) to simulate spatial patterns of erosion across the landscape. The predicted annual soil loss for both years is estimated to average 16.92 t/ha/year, with spatial variation indicating erosion severity ranging from slight to highly severe. The LS and C factors were identified as the most influential contributors to soil erosion, especially in hilly regions with sparse vegetation. The resulting erosion risk maps classify the area from least to most severely erosive zones, aiding in the prioritization of areas that require urgent soil conservation interventions. The insights from this study provide valuable inputs for sustainable land management and targeted conservation planning in the ecologically sensitive Western Ghats.
