Journal of Interior Designing and Regional Planning

Intelligent Urban Flood Modeling: Harnessing AI for Climate Resilience, Risk Assessment, and Insurance Innovation

Ramya B., Chetana M. S., Sindhushree — Wed, 19 Nov 2025 00:00:00 +0000

Urban flooding has become an increasingly serious issue for cities around the world, driven by rapid urban growth, changing weather patterns, and more frequent extreme rainfall events. Conventional flood prediction methods, such as hydrological and hydraulic models, often struggle to capture the complexity of urban environments and may not provide timely information for effective mitigation. Although artificial intelligence (AI) offers advanced capabilities for improving flood forecasting, current studies rarely integrate detailed urban infrastructure, climate projections, and socio-economic factors. Additionally, the practical applications of AI-based flood predictions, such as informing urban planning, guiding emergency response, and supporting insurance strategies, remain limited. This study presents a comprehensive AI-driven framework that addresses these gaps by delivering precise flood forecasts while assessing associated risks. By combining historical rainfall records, elevation data, land-use maps, and urban drainage system information, the framework can identify vulnerable areas, estimate potential impacts on communities and infrastructure, and assist decision-makers in allocating resources effectively. Furthermore, the framework provides practical insights for risk-based insurance, enabling more accurate premium setting, better claims management, and improved financial preparedness. The results demonstrate that integrating AI into urban flood management enhances predictive accuracy, strengthens city-wide resilience, and supports informed planning and policymaking. By linking advanced modeling with practical applications, this approach offers a holistic solution that helps cities mitigate flood risks, protect lives and property, and promote sustainable urban development.

Nonlinear Static and Dynamic Analysis of Retrofit of Four-story RC Structures with Concentric Steel Bracing

Birendra Kumar Bohara, Santosh Raj Bhatt — Thu, 06 Nov 2025 00:00:00 +0000

The study investigates the nonlinear seismic behaviors of 4-story retrofitted and non-retrofitted RC frames. The steel V-shaped bracings are used for retrofitting purposes. Nonlinear pushover and dynamic time history analyses were performed using seven earthquake records to assess the impact of retrofitting. The base shear, the fundamental time period (FTP) of the structure, capacity curves, failure patterns, maximum displacements, and maximum drifts are observed in both non-retrofitted RC frame and retrofitted RC frame structures. The steel V-shape bracings are designed to resist 50% of the total base shear of the structure. The steel bracings increase the base shear of the structures and decrease the fundamental time periods. Results show that the addition of steel V-bracing increased the base shear capacity from 1676kN to 2215kN and reduced the fundamental time period from 0.881s to 0.512s, indicating a significant improvement in lateral stiffness. Similarly, maximum displacements and inter-story drifts decreased by approximately 60%, demonstrating enhanced ductility and energy dissipation capacity. Adding the steel bracing in the existing structures improves the seismic base shear capacity and ductility of the structures. It also observed that to get the expected failure pattern, a minimum of 50% base shear is required to be resisted by the columns. The V bracings reduced the displacement and drift of the structures. The V-shaped steel bracings improve the seismic behaviors of the structures effectively.

Planning of Residential Building

Wed, 03 Dec 2025 00:00:00 +0000

Urban residential planning requires innovative approaches to utilize limited land effectively while meeting diverse user needs. This paper presents a dual-planning approach for a 1,250 sq ft residential plot by proposing two distinct building layouts: Option A, a residential standards building, and Option B, a normal residential building. Option A focuses on premium space standards, enhanced comfort, modern lifestyle features, and optimized ventilation, whereas Option B prioritizes affordability, functional compactness, and minimum essential requirements. A detailed comparative study is conducted covering room-wise area efficiency, built-up area, circulation, ventilation, cost, and functional performance. The results highlight significant variations in livability, design quality, and construction cost. The analysis emphasizes that both plans hold unique advantages and are suitable for different user needs and budget levels. The paper recommends adopting a dual-planning approach in urban housing to achieve flexible, user-oriented, and economically viable residential solutions.

The Implementation of Urban Nature-based Solutions to Reduce Environmental Pollution in Cities

Fatima Mohammed Hasan, Susan Abed Hassan — Fri, 17 Oct 2025 00:00:00 +0000

Cities around the world face mounting environmental challenges due to rapid and unregulated urbanization, most notably air pollution and the urban heat island (UHI) phenomenon, both of which have negative impacts on local climate, public health, and energy efficiency. These complex issues require integrated and sustainable solutions. A fundamental research challenge is the paucity of studies rigorously examining the effectiveness of nature-based solutions (NbS) in reducing urban air pollution, particularly those that mimic the biological behavior of organisms such as algae and plants. Despite the widespread use of green spaces, the lack of strategic integration of plant physiological or aerodynamic dynamics often underestimates the expected environmental impact, highlighting the need for smarter, nature-conscious urban interventions. This study aims to analyze the potential of NbS to mitigate urban air pollution and heat stress by presenting an applied framework for integrating these solutions into urban planning processes. This framework includes: (i) identifying priority areas characterized by simultaneous exposure to air pollution and heat stress, (ii) selecting plant species appropriate for the site’s specific environmental and spatial conditions, and (iii) integrating these solutions into the urban fabric in a flexible manner that takes into account spatial and formal constraints. This research seeks to bridge the existing knowledge gap and provide guidance to decision-makers through innovative environmental alternatives, presenting an analytical perspective and applied models that mimic the natural biological elements in the urban environment. The research presents an analytical study of global cities that applied NbS principles. The research identified the most prominent key indicators for nature-based solutions, including basic ecological function, main scale/impact, technology and mechanism, spatial efficiency/scale, co-benefits, basic implementation context, and development stage.

Enhancing Urban Intersection Efficiency through Signal Retiming: A SIDRA-based Case Study from Kathmandu

Tue, 09 Sep 2025 00:00:00 +0000

Enhancing intersection operations is crucial for reducing congestion and improving traffic safety, especially in rapidly urbanizing areas. This study analysed the congested Jorpati Intersection in Kathmandu, a key unsignalized junction handling 47,610 vehicles daily, with traffic increasing by 277% from 2012 to 2014, despite no major upgrades. Using detailed field surveys, video-based traffic data collection, and SIDRA Intersection software, the study assessed current conditions and evaluated four signal retiming scenarios during morning and evening peak hours under mixed-traffic conditions with vehicle-specific inputs. The SIDRA model was calibrated and validated using local conditions to replicate the real-world scenario by comparing queue lengths in each leg. The results revealed serious operational inefficiencies under current manual control systems, with vehicle delays of up to 97 seconds, queue lengths exceeding 280 metres (in the worst-performing lanes), and an average performance index (PI) of 1340 during peak hours. Among the simulated scenarios, the ‘left controlled phase’ with optimal cycle timing demonstrated the greatest improvements, reducing maximum queues by 63%, delays by 30%, and PI by 36%, while upgrading the level of service from C to B. These findings underscore the effectiveness of signal retiming in enhancing intersection performance in mixed-traffic environments. The study’s methodology provides a replicable framework for similar urban contexts and offers practical insights for managing traffic in rapidly urbanising areas where standard engineering solutions may need local adaptation.