The incidence of building fires has increased significantly due to increase in high-rise structures, the extensive use of electrical equipment etc. Investigating the fire resistance of building materials is critical for mitigating such risks and ensuring safety. Innovative construction materials, including 3D-printed concrete (3DCP) and agro-industrial waste-enhanced 3DCP (3DCP-AIW), are gaining widespread acceptance in high-rise construction. Understanding their fire behavior is essential. This study focuses on thermal behavior at ambient and at different elevated temperatures (upto 550 degrees C) as well as fire behavior at elevated temperatures from 100 degrees C to 800 degrees C. Additionally, the research evaluates the mechanical properties and performance of non-destructive testing (NDT) of these fire-exposed specimens. Further, based on the residual compressive strength at elevated temperature, best-fit models for different grades of concrete were proposed. By analyzing the thermal, fire, mechanical and NDT behavior of these innovative concretes, the study provides critical insights into enhancing fire safety in buildings.
Transportation Mode Identification (TMI) based on GPS trajectory data is vital for data-driven urban mobility analysis and sustainable transportation planning. Despite recent advances in deep learning-based spatiotemporal modeling, effectively integrating heterogeneous contextual information into TMI remains a challenge. This paper proposes CALRCN, a Context-aware Attentive Long-term Recurrent Convolutional Network that jointly models spatial, temporal, and contextual characteristics of human mobility. The framework employs a structured input representation that separates GPS-based motion features from GIS-based contextual features. Spatial patterns are extracted using a convolutional module with channel-wise attention, while long-term temporal dependencies are captured through a Bidirectional Long Short-Term Memory (BiLSTM) with additive attention. Weather information is further incorporated to enhance contextual awareness. Experiments on the Geolife dataset demonstrate that CALRCN achieves an accuracy of 95.7%, outperforming existing deep learning baselines. Further evaluation supports the framework's generalizability, while ablation studies validate the effectiveness of context fusion and attention mechanisms.
Influenced by situational crime prevention (SCP) and zemiology, this research proposes situational harm reduction (SHR) as a new way of thinking about flood risk management (FRM). SCP adopts a problem-oriented approach to crime by implementing techniques and strategies that reduce opportunity structures. The SHR framework applies these principles towards flood adaptation, demonstrating how the development of bottom-up, complementary strategies of flood mitigation and resilience can help individual community members and businesses reduce the social and economic harms associated with flooding. Drawing on a qualitative research methodology that included semi-structured interviews and a focus group with a total of forty local residents and business owners in Matlock Town, Derbyshire, the findings show that members of the community used prior flooding experience, knowledge of flooding precipitators, and social networks to develop sustainable solutions in flood adaptation and resilience. The strategies adopted by individuals and business owners include property-level flood defenses, early-warning systems, individual drainage maintenance, recognition of the role of nature-based solutions in flood mitigation, and collective challenging of unsustainable urban developments. A SHR approach to FRM provides a holistic, multidisciplinary framework that may serve as a practical foundation for future collaboration between researchers, policymakers, and flood-affected communities alike.
Risk and resilience assessment of buried pipeline networks is essential to better understanding of how our communities will respond to natural hazards. This study presents an integrated multi-hazard risk and resilience framework for pipeline networks subjected to earthquakes and moisture-induced differential swelling in expansive soils. The framework introduces multi-hazard fragility models developed using three-dimensional finite element analyses of soil-pipe interaction and statistical methods to quantify the combined effects of both hazards. Component-level damage probabilities are integrated into a GIS-based model to evaluate system-level functionality and resilience. The framework enables identification of the most vulnerable pipeline segments, supporting resilience-informed decisions on pipe replacement and soil improvement measures. An illustrative case study of the water distribution network in Lawton, Oklahoma, demonstrates the framework's capability to quantify multi-hazard damage and assess system performance. Results show the effectiveness of the proposed approach for supporting risk-informed mitigation planning and enhancing infrastructure resilience.
Critical infrastructures are the spine of every functioning economy. These infrastructures are susceptible to disruptive events that interrupt their functional performance. Previous studies recommend public-private partnership (PPP) as an approach to building critical infrastructure resilience (CIR). In this study, a decision-making model is developed using system dynamics and partial least squares (PLS) for resilience strategies for building CIR using PPP. A questionnaire survey was conducted to collect data from 157 respondents, which were used for the data analysis. PLS and system dynamics were used to perform an empirical analysis in the study. This study identified five critical resilience strategies for PPP in CIR. The prominent strategies amongst them are collecting risk data, defining responsibilities, developing an inventory of critical infrastructure, developing a legal framework and financial reserves. The model provides a graphical view of the impact of the resilience strategies for PPP in CIR and how these strategies can positively impact CIR.
Post-earthquake fires pose a significant risk to urban environments, often exacerbating the damage and disruption caused by seismic events. This study examines various aspects of post-earthquake fire, with an application to the municipality of Lisbon. Using ignition models and spatial analysis tools, high-risk zones for fire ignitions were identified, particularly in central and northeastern areas in the municipality of Lisbon where a combination of extensive building floor area and relatively high seismic hazard increases ignition likelihood. Results indicate that the typical delays in the firefighter response in post-earthquake scenarios can dramatically increase the collapse risk of non-seismically designed structures in high-risk zones. In extreme cases, most non-seismically design structures can collapse before firefighters can intervene. The results show a significant economic impact, which underscore the need for enhanced fire prevention, better emergency response planning, and improved urban resilience.
On 28 March 2025, a devastating Mw 7.7 supershear earthquake struck Myanmar along the Sagaing Fault, severely affecting Sagaing, Mandalay, and Naypyitaw. This study presents a Rapid Visual Assessment (RVA) of 1,556 residential buildings using UN-Habitat Level-1 and Level-2 evaluation forms. Results showed that 53.7% of buildings were classified as unsafe (Red), 21.2% required restricted use (Orange), and only 25.1% were safe (Blue). Structural vulnerability was strongly associated with building typology, particularly complex multi-story buildings with basements such as 6U-4L-2B and 4U-4L-3B, which recorded the highest Damage Severity Index (DSI) values. Common failure modes included soft-story collapse, foundation failures, column shear cracking, and frame joint damage. The study introduces a unified framework integrating DSI scoring with UN-Habitat placard outcomes, providing valuable insights for seismic risk mitigation, retrofitting strategies, emergency response, and urban resilience planning in Myanmar's high-risk seismic regions. The findings underscore the importance of seismic design and construction quality.
Modern society demands higher seismic resilience in structures. This study applies machine learning models to evaluate the Seismic Resilience Index (SRI) of a hospital building using nonlinear analysis-derived structural performance levels. Rather than proposing new algorithms, it integrates structural damage and recovery assumptions into a system-level resilience metric approximated via ensemble learning. Predictive models using Random Forest (RF) and Extreme Gradient Boosting (XGBoost) assess SRI for a seismic hazard level with a 2475-year return period. For this hazard level, RF predicted an SRI of 0.3015 (R & sup2; = 0.974), while XGBoost yielded 0.3658 (R & sup2; = 0.986). The near-perfect R & sup2; scores demonstrate exceptional variance explanation, with XGBoost performing marginally better. The approach effectively links structural performance parameters to resilience metrics, providing a powerful tool for seismic assessment of essential facilities.
This paper describes a new financial metric called the Renewal Capacity Ratio (RCR). It measures a municipality's independent financial capacity to manage capital renewal programs on municipal physical assets. It is important because municipalities cannot be expected to adopt best practices for infrastructure renewal and asset management if they do not have the control or capacity to do so. Awareness of the RCR and how it can be improved can empower municipalities to take steps towards financial independence and gain control of expenditures on capital. Conveniently, the RCR is derived from terms already reported by municipalities on the Municipal Budget Submission Form in the Canadian Province of Newfoundland and Labrador. The simplicity of computing the RCR and the recommendations that might come from analyzing it are illustrated by example.
This paper describes the application of wargaming-based approach (scenario-based planning via a tabletop training exercise) to address the complex issue of local climate impacts germane to Naval base operations within the context of its neighboring communities. Using a novel interdisciplinary approach, our team conducted a Military Installation Resilience Review to inform Naval Station Newport (Rhode Island, U.S.A.) and the three surrounding municipalities on fostering, protecting, and enhancing a resilient future against natural hazards. This approach - and its outcomes - provide a strong foundation for continued collaborative efforts of federal and local entities to build present-day resilience and response to natural hazards that may impact future operations and readiness. It addresses future environmental conditions, supporting long-term planning and mitigation for natural hazard risks. The project identifies numerous interdependencies between Naval Station Newport and the municipalities concerning critical infrastructure resilience. It sets the groundwork for a coastal hazard-resilient future that emphasizes collaboration and complements the socioeconomic and environmental components of its coastal community. Lastly, this pilot project serves as a model that may be applied to assessing infrastructure resilience at ports and other maritime bases.
The Global Infrastructure Resilience Survey (GIRS) provides one of the first datasets to examine how governance relates to infrastructure resilience. The survey gathered 378 observations in the water, wastewater, energy, and road sectors. Data was collected on the following governance dimensions: Resilience Policy, Maintenance and Standards, Accountability and Enforcement, Disaster Preparedness and Response, Financial Capacity, and Institutional Autonomy and Capacity. Hazard impact and recovery times were also collected as resilience measures. Statistical analyses indicate a weak relationship between governance and resilience, challenging the assumption that stronger governance translates into better resilience. Moderate correlations among governance metrics across sectors suggests inter-sectoral effects. Weak correlation between the GIRS data and international metrics implying that existing datasets do not capture the perception and experience of infrastructure experts. This work offers an initial empirical basis for understanding the relationship between governance and resilience and calls for future data collection to inform research and policy.
It is demonstrated that the increase in atmospheric CO2, due to climate change and urbanization, threatens the sustainability of RC structures by accelerating carbonation and corrosion of reinforcement, which reduces structural strength. This study proposes an analysis of the durability of an underground RC water tank, whose space above the dome has been converted into a parking area. A deterministic approach, based on the loss of reinforcement section, is used to quantify uniform corrosion of top ring beam steels. Three carbonation models are compared to evaluate the carbonation progression, and two corrosion current models are applied to analyze the residual area of steel cross-section. A uniform corrosion model is developed to determine the evolution in time of the reinforcements section in different environments. Several parameters influencing corrosion are taken into account. The study concludes that an increase of 10 mm of coating extends the service life by about 20 years, while a higher CO2 concentration accelerates corrosion.
This paper aims to explore how Indigenous/ traditional/ native knowledge of building design and construction techniques, processes and materials used in the construction of houses, the adoption of modern design and newly imported construction materials and how their knowledge system; design, use of material, construction process and techniques etc are marginalized in the name of earthquake resistance and facilities additions and their social hierarchy and prestige maintenance (status quo). Methodologically, the research combines qualitative ethnographic research (fieldwork, observation, interviews, participant observation and case studies) in the engineering of construction sectors. The findings of this research included the ongoing importance of TMBC in the contemporary cultural and technical system of building construction system and their norms and values. This study was an anthroengeneering perspective where the concepts of anthropology on engineering designs, planning, construction, and use of tools and techniques including materials were studied and found compatible, feasible, cost-effective and culturally appropriate.
Adopting eco-mobility in developing countries remains underexplored, as most existing studies focus on developed regions. This paper examines the barriers and enablers influencing eco-mobility adoption in the Global South, with a focus on Kumasi, Ghana. Using a quantitative cross-sectional survey, data were collected from 117 respondents and analysed using descriptive statistics, t-tests and the relative importance index. The findings indicate that while poor infrastructure, funding constraints, safety concerns, cultural perceptions, and institutional fragmentation continue to be major barriers, educational campaigns, community engagement, affordability, accessibility to destinations, and growing environmental awareness act as key enablers for the adoption of eco-mobility. By providing context-specific and exploratory insights from Kumasi, the study contributes to the ongoing discussion on sustainable urban transportation in the Global South. The paper recommends integrating eco-mobility into planning frameworks that promote social equity and inclusive urban growth to guide policymakers, urban planners, and stakeholders in supporting sustainable mobility transitions in the Global South.
The study analysed methods for reducing anthropogenic pressure on the environment through modular construction technology. It used data analysis, environmental performance assessment, and examination of practical applications. The findings showed that modular construction reduces construction waste, energy consumption, carbon emissions, and project duration compared with traditional methods. Shorter construction periods also lower noise, dust, traffic, and disruption to local communities and ecosystems. Factory-based module production improves labour conditions by reducing physical strain and occupational risks, while increasing demand for skilled and technologically competent workers. It also decreases emissions from construction equipment and transport and supports more efficient logistics. The use of energy-efficient and environmentally friendly materials helps reduce building heat loss, while automated production improves compliance with design standards and limits rework. Overall, modular construction demonstrates environmental and economic advantages, confirming its potential to reduce anthropogenic load, improve resource efficiency, and support sustainable development without compromising construction quality.
