Search Results (1,021)

Large-span bridges are critical components of transportation networks. Environmental variability, material degradation, and cumulative fatigue continuously affect their long-term performance. Digital Twin (DT) technology has emerged as a promising paradigm for integrating sensing, modeling, and data analytics. Most existing DT implementations in civil infrastructure rely on dense sensor networks, assume near-complete observability, and primarily serve as passive visualization or diagnostic tools, limiting their scalability and practical applicability. This paper proposes a DT framework specifically designed for the monitoring and management of existing large-span bridges under sparse sensing conditions. The framework adopts an information-centric perspective in which limited physical measurements are complemented by full-field state reconstruction through the integration of physics-based modeling, data-driven learning, and uncertainty-aware inference. A synchronized reference configuration, termed State 0, is introduced as the initial basis for tracking structural changes over time, while allowing conditional re-baselining through a Dynamic State 0 (DS0) when verified reassessment justifies it. On this basis, the proposed DT is formulated as an adaptive and decision-oriented cyber–physical system that supports optimization-based recommendations for sensing, inspection, and maintenance planning. Full article

The digital transformation of construction processes has highlighted the need for integrated and sustainable automation frameworks, particularly in public-sector infrastructure planning where cost estimation, documentation, and approval workflows remain fragmented. This study proposes OnlinePlan, a computational and system-level framework that operationalizes a regulation-compliant cost estimation process within an integrated digital platform. The framework integrates heterogeneous data sources, category-specific engineering models, and regulatory transformations into a structured workflow that combines the Standard Construction Cost Estimation System, the Construction Planning and Budget Documentation System, and the Highway Maintenance Budget Planning Information System, with interoperability to PlanNET. A real-world dataset of 74 projects is used to evaluate system performance against traditional workflows. The results demonstrate zero computational deviation (0.00%) and significant efficiency improvements, with total processing time reduced by approximately 75.7%. Statistical validation confirms strong significance (t = 35.09, p < 0.001) and an exceptionally large effect size (Cohen’s d = 7.85), indicating substantial practical impact. The findings reveal that the primary contribution of construction automation lies not only in computational acceleration but in the integration of estimation, documentation, and approval processes into a workflow-governed digital system. This study contributes a scalable and interpretable framework for sustainable construction automation, advancing ICT-enabled decision-making, resource efficiency, and institutional transparency in infrastructure management. These dimensions are explicitly interpreted as measurable indicators of sustainability in public-sector infrastructure management. The primary contribution lies in the integration of estimation, documentation, and approval workflows into a unified system, rather than in the formulation of new cost equations. Full article

Deformation monitoring of bridges is essential to ensure the structural integrity and serviceability of these critical civil infrastructures. In this context, geodetic measurements using total stations and 3D terrestrial laser scanning (TLS) surveys can provide accurate and reliable data. Multitemporal geodetic observations from total stations enable the tracking of displacements at discrete points, whereas TLS surveys allow for the extension of deformation analysis to entire surfaces. Both techniques can achieve comparable millimeter-level precision. These methods were applied to monitor the deformation of the Ponte della Costituzione (PdC), the most recent pedestrian arch bridge spanning the Grand Canal in Venice (Italy). A total station was used to measure the displacements of six control points installed on structurally significant locations of the bridge. Between 3 October 2023 and 2 February 2026, 28 multitemporal measurement campaigns were conducted. In addition, four TLS surveys, using two different laser scanners, were carried out on 1 August 2025 and 2 February 2026, in order to capture conditions corresponding to maximum annual thermal deformation. The results derived from geodetic measurements reveal a strong correlation among: (i) variations in the distance between the abutments (on the order of 6–7 mm); (ii) vertical displacements of the central upper points of the arch (ranging from 9 to 12 cm); and (iii) fluctuations in ambient temperature. TLS data highlighted a spatially homogeneous deformation pattern extending from the crown of the arch to the abutments, demonstrating that longitudinal displacements affect the entire lateral structure. Mid-term deformation analysis over the two-year period from 6 February 2024 to 2 February 2026 indicates displacement rates of approximately 1.4 mm/year for increasing separation between the abutments and 16.2 mm/year for the decrease in elevation of the central arch point. However, these trends are significantly influenced by environmental temperature variations, as evidenced by an estimated temperature change rate of −3.5 °C/year over the same period. Therefore, continued deformation monitoring of the PdC bridge is recommended in the coming years, particularly in light of ongoing climate change and the associated increase in temperature variability. Full article

Accurate and consistent forensic bruise assessment is critical in ensuring positive clinical and legal outcomes for victims of violence. In this study, a framework for automated bruise detection is presented that, for the first time, integrates narrowband alternate-light-source (ALS) forensic imaging and ambient white light imaging. This evaluation framework is designed to address long-standing issues with respect to equitable performance across skin tones and lighting scenarios via a combination of novel model diagnostic strategies. In particular, skin-tone balancing during training and testing, threshold-sensitivity analysis, and embedding-similarity partitioning are employed to quantify the model robustness and deployment trade-offs that arise in forensic image analysis. Models were implemented with ImageNet-pretrained backbones and trained on a unique, multi-annotator full-consensus dataset comprising both white-light and ALS (415 nm and 450 nm) images. The protocol emphasizes three axes of operational relevance: (1) illumination composition in training (W/ALS ratio); (2) subgroup fairness via targeted balancing; and (3) model operating-point selection (confidence and IoU thresholds) informed by confidence-stability metrics and bootstrapped uncertainty estimates. Systematic W/ALS ratio sweeps indicate peak accuracy under ALS-dominant training and declining performance as the proportion of white-light images increases within the training set. Skin-tone balancing reduced failure rates for darker skin tones but increased overprediction in some demographic subgroups. Embedding-similarity and seen/unseen injury analyses demonstrate inflated generalization under image-level partitioning. Ultimately, the findings suggest that future researchers and developers should employ injury-level data partitioning and ensure a weighted balance of ALS images during training. Full article

Road-railway combined steel truss bridges are increasingly adopted in urban infrastructure due to their structural efficiency and versatility. This study proposes a three-level multi-scale finite element framework to investigate the safety reserve and progressive failure mechanism of a four-span (80 + 120 + 120 + 80 m) continuous steel truss bridge carrying both highway and railway traffic. At the macro level, a beam element model was established in Midas/Civil to determine the most unfavorable loading configurations, yielding a minimum buckling load factor of 31.0 under dead load and a maximum vertical displacement of 175 mm at mid-span under combined traffic loading. At the meso level, a mixed beam–shell element model incorporating geometric and material nonlinearities was developed in ABAQUS, revealing an ultimate load factor of 6.61 with distinct progressive failure characteristics: initial yielding occurs near the intermediate pier supports, where deformation is constrained, while final instability develops at Joint A17 due to its lower relative stiffness. At the micro level, a refined solid-shell submodel of the critical joint, driven by displacement boundary conditions extracted from the global model, was constructed to capture the local failure mechanism. The results demonstrate that the governing failure mode is shear buckling of the gusset plate, induced by a vertical displacement differential of approximately 30 mm between the web members on opposite sides of the joint arising from differential stiffness. The stress analysis further reveals pronounced stress concentrations in the splice plates adjacent to the more flexible web member, confirming the asymmetric load distribution mechanism. Based on these findings, strengthening measures including increased gusset plate thickness at pier-top joints, optimized chord sections, and the use of higher-strength steel in critical regions are recommended. Full article

National risks constitute an important but still underexplored dimension of sustainable development, particularly in countries exposed to institutional fragility, demographic decline, and geopolitical uncertainty. This study identifies and prioritizes the ten most significant risks facing Bulgaria’s development over the next decade, with particular attention to their fiscal and macro-financial transmission channels. The analysis is based on a structured expert survey conducted among 82 specialists from academia, business, research institutions, civil society, and public practice. Respondents assessed 32 potential risks according to likelihood and impact using a five-point scale. A combined priority index was constructed as the product of mean likelihood and mean impact scores. The results show that the most significant risks are concentrated around institutional and systemic vulnerabilities, especially distrust in the rule of law, ineffective healthcare, disinformation, corruption, crisis of statehood, demographic decline, and deterioration in education and infrastructure. The findings indicate that these risks affect Bulgaria’s long-term development through five main fiscal and macro-financial channels: higher sovereign risk premia, expenditure pressure, weaker revenue capacity and investment efficiency, labor market deterioration, and broader financial fragility. The study contributes to the literature on sustainability governance, sovereign resilience, and fiscal sustainability by showing that national resilience depends not only on the management of external shocks, but also on the institutional capacity of the state to absorb long-term structural pressures. The practical applicability of the study lies in the possibility and necessity of conducting a content analysis of the main strategic documents for the country’s development in order to establish the extent to which the identified main risks are reflected in them, as conclusions about the situation and as countermeasure policies. Full article

Cover-collapse sinkholes are one of the most hazardous geohazards, causing severe damage to civil infrastructure, roadway networks, and substantial economic disruptions. In the United States alone, the economic loss caused by cover-collapse sinkholes exceed USD 300 million annually. Despite extensive research on the causes and formation mechanisms of cover-collapse sinkholes, reliable prediction of the collapse range remains a significant challenge because the development of cover-collapse sinkholes occurs underground and is generally undetectable at the ground surface until collapse occurs. This study presents a comprehensive review of 162 peer-reviewed journal articles, technical reports, and case studies to systematically identify the key factors governing the collapse range of cover-collapse sinkholes. This paper covers several influencing factors for collapse range of cover-collapse sinkholes, including soil properties, geometric characteristics of cavities and soil cover, hydraulic conditions, and the presence of buried structures. Among these factors, soil cohesion, friction angles, void ratio, soil cover thickness, and cavity geometry are identified as the key influencing factors for the collapse range of cover-collapse sinkholes. In addition, existing prediction methods were also summarized, which are predominantly empirical and have limited capability to capture the influence of multiple factors on the collapse range. Based on the literature review, this study finally identifies current research gaps and suggests future directions for developing more accurate and integrated models to predict collapse range of cover-collapse sinkholes. Full article

Textile-reinforced concrete (TRC) beams have attracted widespread interest in recent years as an alternative to fiber-reinforced polymer (FRP) techniques. However, despite their effectiveness, they are often associated with high material cost, sensitivity to elevated temperatures, and limitations in bonding performance under certain environmental and surface conditions. This research examines incorporating textile reinforcement internally (INT) by supplementing steel bars with glass fiber grids, as well as externally (EXT) by retrofitting existing members. The experimental work evaluates five RC beams: a control (CTR), two INT beams strengthened with alkali-resistant glass fabric textile (AR-GFT), one using one layer (INT1L) and the other three layers (INT3L), and two EXT beams where AR-GFT is bonded with mortar, again with one layer (EXT1L) and three layers (EXT3L). Altogether, 10 beams were tested, with duplicate specimens for every configuration. Observing load-deflection responses, cracking behavior, and the strengthening system’s performance revealed that AR-GFT contributes to enhanced load-bearing resistance in the RC beams. The INT1L beams exhibited negligible improvement compared with the CTR specimen, suggesting that internal strengthening alone does not meaningfully increase strength. Conversely, the INT3L beams demonstrated a 45% rise in strength for one sample, although the second performed similarly to the CTR specimen owing to slippage between the textile and adjacent matrix. EXT3L beams achieved up to a 90% increase in load-bearing capacity in one specimen. Nevertheless, the second specimen exhibited textile layer debonding and performed similarly to the CTR beam, underlining the necessity for correct textile positioning and sufficient mortar impregnation during application. Moreover, a three-dimensional (3D) nonlinear finite-element analysis (FEA) was performed to replicate beam responses, showing strong correlation with experimental observations. Overall, the results indicate that textile-based strengthening systems can successfully retrofit and upgrade RC structures, provided meticulous attention is paid to the quality and execution of the installation process. The study provides new insights into the flexural behavior of textile-strengthened RC beams, particularly in terms of the interaction between internal and external textile reinforcement with conventional steel. Full article

Does civil society mobilization supplement or entirely supplant the state during crises? This distinction remains theoretically significant yet empirically underdeveloped. An empirical framework based on the State-in-Society theory is applied in this study to analyze state–civil society relations in Israel following the 7 October 2023 attacks. Using qualitative interviews with 19 civil society leaders from 12 organizations conducted in January 2024, we examine the comprehensive substitution of state functions by non-state actors across security, welfare, and logistics domains. Findings reveal that protest organizations rapidly transformed into primary service providers, creating hybrid governance structures that persisted for months. Unlike government failure (dysfunction within intact institutions) or chronic state failure (gradual erosion in fragile contexts), Israel experienced “localized state failure”—a rapid, geographically constrained yet comprehensive collapse of core state functions in a high-income democracy, with immediate substitution by organized domestic civil society rather than international actors. This mobilization, based on a preexisting protest movement, demonstrates how robust civic infrastructure, even when mobilized against the government, creates latent governance capacity that can be activated during crises. The study advances the state-in-society theory, hybrid governance, and institutional resilience, offering a new perspective for distinguishing temporary dysfunction from fundamental collapse in democratic contexts. Full article

Sustainable regional competitiveness and civil protection have traditionally been treated as distinct fields: the former rooted in regional economics and innovation studies, and the latter in disaster management, public safety, and risk governance. However, increasing climate-related hazards, technological disruptions, geopolitical instability, and the fragility of critical infrastructure demonstrate that competitiveness and resilience are deeply interconnected. This study presents a narrative literature review of publications from 2022 to 2025, integrating insights from evolutionary economic geography, institutional theory, sustainability studies, disaster risk reduction, spatial planning, and governance research. Building on this synthesis, we propose a novel conceptual framework that links civil protection capacity to long-term regional competitiveness. The framework introduces a multi-pillar model encompassing risk governance, institutional quality, critical infrastructure resilience, spatial planning systems, human capital dynamics and demographic stability, social trust and regional legitimacy, innovation driven by risk-management technologies, and multi-level governance coordination. Our analysis highlights how asymmetric threats are characterized by unpredictability, non-linearity, and uneven territorial impacts—interact with structural vulnerabilities, amplifying regional disparities and challenging conventional competitiveness strategies. Importantly, the framework demonstrates that robust institutions and integrated civil protection mechanisms can transform exposure to shocks into opportunities for adaptation, innovation, and structural upgrading. By conceptualizing competitiveness as a dynamic, emergent property shaped by economic, social, and risk-management capacities, this study positions civil protection as a strategic, measurable, and foundational component of sustainable regional development. The framework provides a theoretical foundation for future empirical research, policy design, and multi-criteria assessments aimed at fostering resilience-oriented competitiveness. Full article

The rapid proliferation of unmanned aerial vehicles (UAVs) in civilian sectors has generated diverse research spanning platform engineering, application deployment, and regulatory governance. This scoping review systematically maps the current knowledge landscape of civilian UAVs, their applications, and their regulatory frameworks, and aims to serve as initial practical guidance for researchers and practitioners initiating drone-based projects. Following PRISMA-ScR guidelines, a structured three-stream literature search was conducted using Google Scholar, yielding 109 sources published between 2015 and 2025. This review synthesises findings across three domains: (1) technical specifications, including UAV platform configurations, their common applications, their advantages and limitations, electromechanical systems, flight control architectures, and communication technologies, while also providing key guidance on how to choose the appropriate components for a given application; (2) civil applications across eight sectors—delivery logistics, infrastructure inspection, precision agriculture, environmental monitoring, emergency response, waste management, and commercial uses—to provide inspiration as well as to capture important details on drone projects; and (3) regulatory frameworks and ethical considerations governing UAV operations. Analysis reveals concentrated research attention on autonomy and AI-driven control systems and emerging focus on communication infrastructure. Geographic representation is dominated by US, European, and Chinese contexts, with limited coverage of developing regions. Key knowledge gaps include economic feasibility analyses, standardisation frameworks, developing-world deployment contexts, and environmental lifecycle assessments. Contradictions emerge between optimistic application scalability claims and fundamental constraints in energy storage, swarm communication reliability, and privacy–efficiency trade-offs. This review provides researchers and practitioners with a comprehensive map of current UAV knowledge, identifies critical research gaps, and establishes a foundation for future research in civilian drone technologies. This study aims to systematically consolidate and synthesise fragmented research on civilian UAV technologies, applications, and regulatory frameworks into a unified reference for research and practice. Full article

The development of a 3D digital cadastre is a key objective of Australia’s Cadastre 2034 strategy for modernising land information infrastructure. Jurisdictions across Australia are progressively transitioning from conventional 2D cadastral systems towards 3D cadastral models to better represent complex land and property rights, particularly in dense urban environments. In New South Wales (NSW), LandXML is currently the standard for digital cadastral lodgement. However, its limitations in supporting 3D spatial data representation have prompted investigation of alternative standards such as LandInfra and its InfraGML encoding. The aim of this study is to investigate how LandInfra handles existing cadastral information in New South Wales, Australia. In particular, this study is a technical and structural comparison of LandXML and InfraGML, examining data modelling workflows and geometric encoding. A hybrid research methodology integrating Design Science Research (DSR) and Case Study Research (CSR) was applied. Two representative cadastral plans—a standard deposited plan and a strata plan—were digitised using LISCAD 2025 v25.9.23.1 and AutoCAD Civil 3D 2026 V1 and subsequently modelled in both LandXML and InfraGML formats. Validation was conducted using KITModelViewer and schema validators, with comparative analysis of development cycle, modelling structure, usability, and workflow. This study demonstrates that InfraGML offers semantic richness and structural flexibility compared to LandXML within the scope of the examined case studies, although its practical adoption is constrained by limited commercial software support and may present adoption challenges for practitioners. The findings of this research suggest that LandInfra offers considerable potential for advancing the future development of 3D cadastre in Australia. In this context, InfraGML is positioned as a promising data standard for ongoing investigation and future research, rather than an immediate substitute for LandXML. Within the scope of this study, a fully operational 3D cadastral implementation is neither developed nor validated within existing legal or institutional frameworks, and complex 3D scenarios are not addressed. Future research should explore integration with CAD platforms, legislative implications of 3D survey features, complex volumetric cases, and formal 3D topological validation, and alternative modelling approaches, such as using Nested Parcels method and InfraJSON encoding. Full article

The escalating financial burden of deteriorating civil infrastructure worldwide necessitates a shift from conventional repair methods towards more durable and economically efficient long-term solutions. This paper presents a comprehensive techno-economic review of using carbon fibre-reinforced polymer (CFRP) fabrics for structural strengthening. Moving beyond a simple first-cost comparison, this review utilizes a life-cycle cost analysis (LCCA) framework to evaluate the total cost of ownership. The analysis deconstructs the complete cost profile, demonstrating that while CFRP systems have a high initial material cost, this is frequently offset by substantial savings in labour, equipment, and, critically, the indirect costs associated with reduced construction time and operational disruption. Furthermore, the inherent corrosion immunity of CFRP virtually eliminates future maintenance and repair expenditures, leading to a lower total life-cycle cost compared to traditional steel or concrete-based methods in a wide range of applications. Specifically, the conducted LCCA case study demonstrates that the CFRP alternative can reduce total life-cycle costs by nearly 25% relative to conventional steel sheet bonding, overwhelmingly driven by minimized operational downtime and related indirect costs. The value proposition is shown to be context-dependent, driven by minimizing user delay costs in bridges, mitigating catastrophic risk in seismic retrofitting, preserving cultural value in heritage structures, and maximizing revenue uptime in industrial facilities. The review also examines market dynamics, including the roles of standardization and government policy in driving adoption, and explores future trends such as inorganic matrix composites (TRM/FRCM), integrated structural health monitoring (SHM), and the push towards a circular economy. The findings conclude that a holistic, life-cycle-based economic assessment establishes CFRP strengthening as a cornerstone technology for the sustainable and resilient management of modern civil infrastructure. Full article

Reliable crack detection is essential for ensuring the safety, serviceability, and long-term performance of civil structures. Conventional manual inspections are labor-intensive and subjective, while existing computer vision models often exhibit reduced accuracy under variable field conditions. This study develops a computer vision-based automated crack detection framework utilizing a hybrid Transformer–CNN architecture to support infrastructure inspection and condition assessment. The proposed model leverages the global context modeling capability of Transformers and the local feature sensitivity of convolutional neural networks (CNNs) to enhance detection robustness. The optimized hybrid model achieved an Intersection over Union (IoU) of 91.8% and an accuracy of 98.7%, outperforming baseline CNN, Transformer-only, and LSTM architectures. Field validation on bridge inspection imagery demonstrated strong resilience to variations in illumination and texture. The developed approach contributes to digital inspection and intelligent lifecycle management of infrastructure assets by enabling reliable, automated, and non-intrusive structural condition evaluation under realistic field conditions. Full article