Article accepted for publication for upcomming Issues
Research article, Type: Subscription Accepted Date : 28.02.2026
Title: AI-Driven Seismic Resilience in High-Rise Structures
Author: Avinash Kumar et.al.
Abstract: AI-driven seismic resilience in high-rise structures leverages machine learning models like artificial neural networks (ANN) and support vector machines (SVM) to predict structural responses under dynamic earthquake loads. These models integrate real-time data from accelerometers, strain gauges, and fiber optic sensors to forecast inter-story drifts and lateral displacements with RMSE values as low as 0.089. Genetic algorithms (GA) optimize outrigger system configurations, including position, stiffness, and damping, achieving 46.67% reductions in lateral displacement and 55.56% in drifts compared to conventional designs. Pushover and time-history analyses validate these optimizations, enhancing energy dissipation by 33.33% in earthquake-prone regions like Bihar. Hybrid frameworks combine supervised learning with reinforcement refinement for adaptive retrofitting, outperforming empirical codes by enabling proactive damper adjustments.
Research article, Type: Subscription Accepted Date : 03.03.2026
Title: Examine the properties of self-Healing Concrete with IoT for Blast Resistance
Author: Adolf Kingal et.al.
Abstract: Self-healing concrete with IoT integration enhances blast resistance through autonomous crack repair mechanisms, primarily using bacteria-based (e.g., Bacillus species), microcapsule, or vascular systems that activate upon damage from shockwaves. Bacteria-induced healing relies on spores and nutrients like calcium lactate, which, triggered by water ingress post-blast, precipitate calcium carbonate to seal microcracks up to 200-300 µm within days to weeks, recovering 70-90% of mechanical strength. Microcapsule-based variants embed polymer shells (e.g., urea-formaldehyde with epoxy or polyurethane healing agents) that rupture under blast-induced strain, releasing agents for rapid closure (60-80% strength recovery in hours), with permeability reductions up to 99%. IoT sensors, such as embedded piezoelectric or fiber Bragg grating types, enable real-time monitoring of strain, pH, and crack propagation during and after blasts, transmitting data via wireless networks for predictive analytics. Blast resistance improves via reduced spalling and enhanced ductility; studies show self-healed samples exhibit 40-60% higher post-blast compressive strength retention compared to plain concrete under TNT equivalents.
Research article, Type: Subscription Accepted Date : 06.03.2026
Title: Digital twins integrated with generative AI for urban smart city infrastructure simulation
Author: Shravanee Budgude et.al.
Abstract: Digital twins integrated with generative AI revolutionize urban smart city infrastructure simulation by creating dynamic virtual replicas that fuse real-time IoT data from traffic, energy grids, and environmental sensors with AI-generated scenarios for predictive optimization. Generative models like GANs produce synthetic urban layouts and “what-if” tests for climate resilience, enabling rapid iteration of zoning, green corridors, and mobility networks to cut emissions by 20-30%. These systems support participatory planning through immersive VR visualizations, where AI automates 3D city modeling from GIS inputs, aligning with your digital twin research for smart infrastructure. In high-density areas like Delhi, they simulate flood risks and energy demands, optimizing microgrids and drainage via parametric designs tested against live data. This fusion accelerates sustainable development, bridging civil engineering with AI for carbon-neutral cities and disaster-ready frameworks.
Research article, Type: Subscription Accepted Date : 06.03.2026
Title: Using Finite Element Simulation to find out Soil-Structure Interaction in Tunnel Excavation
Author: Mahavir Prasad et.al.
Abstract: Finite element simulation of soil-structure interaction in tunnel excavation employs advanced 3D models to capture complex behaviors like ground deformation, lining stresses, and surface settlements during staged construction. Software such as Plaxis 3D or DeepEX discretizes the soil and tunnel lining into finite elements, incorporating nonlinear soil constitutive models like Mohr-Coulomb or Hardening Soil to simulate excavation unloading and lining activation sequences. Key outputs include convergence of tunnel displacements, bending moments in segmental linings, and plastic strain zones in surrounding soil, with results showing up to 60% variation based on intersection angles in twin tunnels. Compared to simplified soil-spring methods, full FEM provides superior accuracy for heterogeneous soils and multi-hazard scenarios, aiding optimized support design and risk assessment.