Search Results (2,814)

An investigation employing multiple diagnostic techniques was conducted to evaluate the post-fire condition and residual structural safety of a fire-damaged precast concrete industrial building. The evaluation included a detailed visual inspection, mechanical testing of extracted concrete cores, and mineralogical and microstructural analysis through thermo-chemical methods, namely X-ray Diffraction, Scanning Electron Microscopy, and Energy-Dispersive X-ray Spectroscopy, alongside tensile strength tests of reinforcement bars sampled from the affected structure. The building was divided into five sections according to the severity and extent of observed fire damage. Results indicated that the highest in situ temperatures were attained in the most heavily damaged section, whereas the remaining sections experienced progressively lower temperatures, remained below approximately 600 °C. Despite the severe fire exposure in localized areas, all assessed structural elements maintained adequate residual integrity. The reinforcing steel exhibited satisfactory residual mechanical properties, exhibiting yield strengths ranging from 550 to 600 MPa. The integration of visual, mechanical, and microstructural assessments provides a reliable framework for estimating fire temperatures and supporting structural rehabilitation decisions. Full article

Delayed switching faults in hydraulic directional control valves can significantly degrade system performance and reliability, yet their diagnosis remains challenging due to complex fault mechanisms and coupled sensor responses and limited fault samples in industrial applications. While data-driven approaches, including deep learning-based methods, have shown promising performance in fault diagnosis, their practical deployment in industrial quality inspection and condition monitoring is often constrained by limited fault data availability and insufficient physical interpretability of the diagnostic results. In this study, an interpretable fault diagnosis framework for delayed switching faults in hydraulic directional control valves is proposed based on a simulation-guided feature construction method and multi-pressure signal analysis. Instead of using simulation to generate synthetic training data, a physical simulation model is employed to analyze fault mechanisms and to guide the design of valve-level diagnostic features derived from inter-sensor pressure differences. These features are further evaluated using several classical machine learning classifiers, including RF, SVM, KNN, and LR under conditions of limited fault samples. Experimental results demonstrate that the proposed method effectively captures the structural imbalance caused by internal valve faults and achieves high diagnostic accuracy and robustness compared with conventional single-sensor approaches and purely data-driven black-box models. The proposed framework provides a practical and physically interpretable solution for hydraulic valve fault diagnosis under small-sample conditions and offers potential value for industrial quality inspection and maintenance applications. Full article

This paper presents the H-CoRE (Heterogeneous Cooperative Multi-Robot Execution) framework designed to enable autonomous multi-robot operations in GNSS-denied environments. Built on an ROS 2-based architecture, H-CoRE enables collaborative, structured task execution through standardized software stacks. Each robot’s stack combines a high-level executive system with an agent-specific motion layer and leverages multi-sensor fusion for localization and mapping. The framework is inherently reconfigurable, allowing individual agents to operate autonomously or as part of a multi-robot team for collaborative missions. In the considered scenario, the system integrates aerial and ground vehicles, a fixed pan–tilt–zoom camera, and a human supervisory interface within a unified, modular infrastructure. The proposed system has been deployed in indoor, GNSS-denied environments, demonstrating autonomous navigation, cooperative area coverage, and real-time information sharing across multiple agents. Experimental results confirm the effectiveness of H-CoRE in maintaining general awareness and mission continuity, paving the way for future applications in search-and-rescue, inspection, and exploration tasks. Full article

The management of large and heterogeneous building stocks requires decision-support tools capable of prioritising interventions under limited technical and financial resources. In this framework, the role of structural deterioration is rarely integrated within a unified prioritisation framework. This study proposes a rapid deterioration-based assessment for prioritising maintenance within heterogenous portfolios. The assessment is articulated into two levels. A Project Level (PL) is based on visual inspections and component-level condition ratings, while a Network Level (NL) introduces contextual and functional modifiers related to the relevance of each structural unit within the building stock. A seismic assessment procedure is integrated in proposed decision-making system for optimising intervention planning. The two assessments are integrated through a decision-tree logic providing an overall classification of buildings within portfolios. The proposed framework is applied to an industrial-oriented building stock located in Italy, comprising 79 structural units characterised by significant typological heterogeneity, including masonry, reinforced concrete, precast reinforced concrete, and steel buildings. The application illustrates the internal consistency of the proposed framework and its ability to support a transparent and articulated prioritisation process for maintenance and risk mitigation within heterogeneous building portfolios. Further applications to different building stocks are required to explore the general applicability of the methodology. Full article

This study investigates and compares Food Safety Management System (FSMS) compliance in retail shops across Mazovia (Poland) and Kerala (India). A structured visual inspection checklist with 51 indicators across seven FSMS sections was used in 500 shops per country: design and layout, general food safety, food handling and storing practices, display, personnel hygiene practices, sanitation and cleanliness, and pest control. Each section was scored using a four-point ordinal scale. Compliance scores were analyzed using the Mann-Whitney U test, Kruskal–Wallis test, Principal Component Analysis (PCA), and Cluster analysis to identify influencing factors and compliance patterns. The results demonstrate significant differences between the two countries, with Polish retail shops showing notably higher compliance (p < 0.001). No significant difference was observed in the design and layout section (p = 0.103). None of the assessed shop categories in either country achieved full compliance with all food safety requirements. Retail format, location, and number of employees were significantly associated with compliance levels. This is the first comparative study to examine FSMS compliance in retail shops in Mazovia, Poland, and Kerala, India, using a standardized visual inspection method. The findings contribute to a better understanding of FSMS performance in retail environments under different economic and regulatory conditions. Identifying how variations in retail format, staffing, and operational practices influence FSMS compliance can support the development of context-specific strategies to improve food safety performance. Full article

Personal protective equipment (PPE) is critical for defending against airborne biological hazards; however, current standard testing protocols often rely on “black-box” aggregate metrics or qualitative visual inspections that fail to pinpoint localized vulnerabilities. This study proposes a novel, spatially resolved quantitative methodology combining a whole-body fluorescent aerosol exposure chamber with an entropy-based image processing algorithm. By establishing a robust linear calibration mode, we accurately mapped and quantified localized aerosol ingress through protective clothing interfaces. Dynamic human-in-simulant tests were conducted using three suit models on two subjects with distinct body morphologies over 2- and 5-min exposure durations. Quantitative results revealed two distinct morphological failure mechanisms. A well-fitted suit resulted in steady “ Steady Accumulation,” where the total body leakage mass increased consistently (e.g., from 3.29 to 4.19 μg/cm²) while maintaining stable standard deviation, indicating preserved structural integrity. Conversely, an oversized fit induced “Structural Instability” and an erratic “Bellows Effect.” This mismatch was characterized by a dramatic inflation in aerosol leakage standard deviation during extended dynamic movements, rather than a simple increase in the mean leakage. Ultimately, this study empirically proves that protective clothing efficacy is highly morphology-dependent. The proposed quantitative methodology provides a rigorous scientific tool for diagnosing localized interface failures, thereby facilitating targeted improvements in PPE design and occupational safety. Full article

Pipe networks assure the transportation of primary commodities such as water, oil, and natural gas. Quantitative and early detection of defects avoids costly consequences. Due to low cost of water, high-profile accidents, and economic downturns, the research and development of nondestructive evaluation (NDE) and structural health monitoring (SHM) technologies for freshwater mains and urban water networks have received less attention with respect to the gas and oil industries. Moreover, the technical challenges associated with the practical deployment of monitoring systems and the fact that most water pipelines are buried underground demand synergistic interaction across several disciplines, which may limit the transition from laboratory to real structures. This paper reviews the most prominent NDE/SHM technologies for freshwater pipes. The challenges that said infrastructures pose, as well as the methodologies that can be translated into SHM approaches, are highlighted. The scope of this review is to provide a holistic view of the physical principles, the success, and the technological challenges associated with the inspection and monitoring of freshwater pipelines. Full article

Riverine bridges are critical infrastructure that are increasingly exposed to severe hydrological hazards. This study proposes and validates a synergistic methodology for the assessment of riverine bridge resilience, integrating the conceptual 4R framework (robustness, rapidity, resourcefulness, and redundancy) with field inspections, hydrological and hydraulic modeling, including scour evaluation, within a multicriteria analysis scheme. The methodology comprises: (i) a systematic review of literature and regulations to construct a 30-parameter matrix across five dimensions (technical, economic, social, organizational, and environmental); (ii) data acquisition through field inspections, detailed topography, and technical studies; and (iii) one-dimensional hydraulic modeling in HEC-RAS under extreme scenarios (return periods of 100 to 750 years and a critical 500 m³/s scenario representing a potential overflow of the Aguada Blanca reservoir). The Bridge Resilience Index (BRI) is computed through a weighted additive model and a sensitivity analysis. Application to the San Martín Bridge (Arequipa, Peru), a structure with more than 60 years of service and recurrent preventive closures during flood events, revealed critical conditions: minimum freeboard of 0.26 m, absence of hydraulic protections, and limited institutional capacity. The resulting BRI value (1.898) indicates a low resilience level. The proposed framework provides a useful tool for risk-informed decision-making, the prioritization of interventions, and the strengthening of resilience in critical infrastructure. Full article

Digital inspection technologies are increasingly being adopted in the construction industry to improve efficiency, decision quality, and sustainability performance. Mixed reality (MR) systems can reduce rework, minimise human error, and support resource-efficient inspection processes. However, empirical evidence on how perceptions of efficiency and safety influence professional acceptance of MR technologies remains limited. This study investigates the adoption of MR for construction inspection using an extended technology acceptance model (TAM) that incorporates task efficiency and safety perception as domain-specific human factors. A within-subjects scenario-based experimental design was applied, in which 103 construction professionals evaluated four inspection modalities: HoloLens MR, smart glasses, tablet-based systems, and traditional paper-based methods. Data was analysed using linear mixed-effects models, structural equation modelling, mediation analysis, and dominance analysis. The results show that HoloLens MR achieved the highest perceived efficiency and safety perception, while imposing the lowest cognitive demand. Perceived efficiency was a strong predictor of device preference and significantly predicted perceived usefulness (β = 0.322, p < 0.001), which fully mediated its effect on behavioural intention. Safety perception accounted for a substantial proportion of the variance in user evaluations (η² = 0.237). These findings indicate that sustainable adoption of MR in construction inspection depends on combined perceptions of efficiency gains, usability, and safety support. Full article

Sewerage systems are among the most fundamental and indispensable components of urban infrastructure. However, inadequate management can result in malfunctions and subsequent rehabilitation processes, leading to various negative consequences. Identifying areas at high risk of failure and conducting system-based inspections can significantly improve the performance of sewer networks. This study identified and categorized 33 criteria that could cause sewer system failures: structural, operational, hydraulic and environmental defects. A Bayesian network (BN) model was developed to determine dependencies between the criteria, quantify uncertainty, investigate new information about the structural condition of assets and calculate the effects and sensitivities of the criteria on the probability of failure. A probability-based risk assessment model was then created using a fuzzy inference system (FIS) to predict risk levels in sewerage systems under different combinations of physical and operational conditions and hydraulic and environmental effects. A case study was performed on a sewer network in Malatya, Turkey, determining its failure probability to be 76.6%, placing it in the high-risk category. When the probability of pipe failure was set to 100% in the Bayesian network model to evaluate the relative influence of different criteria, the most influential factors were identified as flow velocity (74.8%), clogging (71.4%), and failure rate (71.1%). Thanks to the flexible structure of BNs, the proposed model is expected to be useful for performing risk analyses in systems involving uncertainty or missing data. It can also be used to prioritize rehabilitation, inspection and maintenance programs, improve infrastructure service quality and ensure system reliability in urban sewerage systems. Full article

Water towers are historically significant hydraulic infrastructures that evolved from simple masonry structures to technologically advanced and architecturally expressive forms. This study presents a typological and material analysis of water towers, focusing on their construction techniques, durability, and potential for adaptive reuse. The research combines visual inspection, archival and bibliographic research, and photographic documentation, of selected European and Italian examples for comparative insights on design and materials choices. Data were collected and organized according to parameters such as construction materials, structural type, tank and roof form, access system, and current function. Assessments were conducted following the UNI EN 16096, providing a structured framework to evaluate heritage value, material conditions, and adaptive reuse potential. Main results demonstrate that water towers, beyond their original hydraulic function, retain significant technical, architectural, and cultural value, offering opportunities for adaptive reuse as cultural, educational, residential, or community spaces. Key findings identify material vulnerabilities, structural challenges (including wind, seismic, and thermo-hygrometric effects), and possibilities for sustainable interventions that respect historical authenticity. The study highlights how systematic typological assessment and documentation can guide evidence-based conservation and support innovative reuse strategies, integrating heritage preservation with urban regeneration and community engagement. Water towers exemplify the intersection of engineering, architecture, and cultural heritage, and their conservation requires a multidisciplinary approach between technical performance, material preservation, and socio-cultural significance. Finally, the implemented procedure is proposed as a methodological framework replicable and scalable for assessing similar infrastructures in other contexts. Full article

Background/Objectives: Impella support is increasingly utilized as a crucial bridge to durable left ventricular assist device (LVAD) in patients with refractory cardiogenic shock. However, the transvalvular path of the Impella catheter raises concerns regarding mechanical trauma, potentially precipitating or accelerating aortic regurgitation (AR). We aimed to characterize the complete longitudinal trajectory of AR following Impella bridge-to-LVAD and to determine its association with clinical and hemodynamic sequelae. Methods: We conducted a single-center retrospective cohort study including all patients bridged from Impella to durable LVAD between 2013 and 2024 (n = 19). At Impella initiation, all patients met the retrospective SCAI shock stage D or worse criteria. At LVAD implantation, all patients were classified as INTERMACS 1–2 (INTERMACS 2, n = 13). The Impella models were 5.0 in 11 (axillary access), 2.5 in 5 (femoral access), and CP in 3 (femoral access); no periprocedural Impella complications were recorded. The implanted LVAD systems were HeartMate II (n = 7), HVAD (n = 3), and HeartMate III (n = 9). Patients undergoing concomitant aortic valve intervention were excluded. Transthoracic/TEE echocardiography was performed at prespecified time points (pre-Impella, pre-LVAD, post-LVAD discharge, 12 months, and 24 months) with standardized aortic regurgitation (AR) grading. Right ventricular (RV) function was assessed qualitatively when quantitative indices (TAPSE) were unavailable. Primary endpoints were new or progressive AR and AR severity at LVAD implantation. Secondary endpoints included survival, renal dysfunction, biomarkers, and rehospitalization. Univariate analyses were used to compare outcomes according to AR severity. Results: Nineteen patients (68% male, median age 57 years, IQR 47–60) underwent Impella support for 13.3 ± 9.9 days before HeartMate 3 (84%) or HVAD (16%) implantation. All patients had competent aortic valves (grade 0 AR) at the time of LVAD implantation. AR ≥ mild developed in 9/18 (50%) at discharge, 12/15 (80%) at 12 months, and 13/15 (87%) at 24 months, and 8/15 (53%) progressed to ≥ moderate AR by 24 months. Patients with moderate-to-severe AR had higher NT-proBNP levels at 12 months (median 6318 vs. 2336 pg/mL, p = 0.137). Thirty-day and 24-month survival rates were 95% and 79%, respectively. Conclusions: Aortic regurgitation frequently develops or progresses from the pre-LVAD period to follow-up in patients bridged from Impella to durable LVAD. Although limited by a small sample size and incomplete quantitative RV metrics, these observations support structured echocardiographic surveillance after Impella use and management strategies—routine valve inspection at LVAD implantation and post-LVAD speed/blood pressure targets that encourage aortic valve opening—to mitigate the risk and clinical impact of aortic regurgitation. Full article

Conventional borescopes are limited by inadequate mechanical flexibility, poor environmental adaptability and reachability, and heavy reliance on operator expertise during aero-engine inspections, making it difficult to meet the demands for efficient and dependable in situ nondestructive evaluation (NDE). This paper presents a novel telescopic continuum robot mechanism with an ultra-high aspect ratio (63.75:1) and three constant-curvature segments, achieving a synergistic design between the robot’s body structure and the long-stroke linear actuator of its central backbone to realize ultra-high-aspect-ratio configurations. This design improves the robot’s ability to access complex and confined internal spaces within aero-engines, thereby reducing inspection blind spots. Furthermore, a configuration-space control strategy integrating kinematic decoupling and driving tendon tension compensation is proposed. This strategy addresses the issues of multi-segment actuation coupling and tendon slack, ensuring the motion control performance for in situ aero-engine blade inspection. The feasibility of the mechanism design was validated through an experimental simulation platform incorporating both turbine blade and compressor blade scenarios. This work offers a new solution for in situ NDE in aero-engines by synergistically integrating an innovative ultra-high-aspect-ratio telescopic mechanism with a dedicated configuration-space controller that addresses multi-segment coupling and tendon slack. Full article

Industrial metaverse systems enable shared, immersive environments for coordinating complex, data-intensive industrial workflows; however, ensuring effective and usable interaction remains a key barrier to professional adoption. This study examines immersive point cloud- and CAD-based inspection tasks in an industrial metaverse context using a mixed-methods evaluation that combines perceived usability ratings, cognitive workload assessment (NASA-TLX), validated presence and flow instruments, qualitative interviews, and structured observation. The results indicate that users generally experienced smooth navigation, manageable cognitive workload, and a meaningful sense of spatial presence, supporting focused and task-oriented engagement. At the same time, execution-level challenges—particularly related to tool discoverability, annotation flexibility, system feedback clarity, and interaction ergonomics—introduced workflow friction for some users. By triangulating quantitative, qualitative, and observational evidence, the study derives actionable design recommendations, including adaptive onboarding, improved feedback mechanisms, and refinements to interaction design. Overall, the findings provide empirical insight into how usability, cognitive workload, presence, and flow jointly shape user experience in industrial metaverse inspection environments and inform the development of more robust, user-centered industrial systems. Full article

Smart energy networks, including electricity distribution and district heating, are increasingly operated as sensor-enabled infrastructures where maintenance decisions must be made under heterogeneous and time-varying operating conditions. In these settings, time-to-event data are rarely complete; preventive actions and limited observation horizons routinely introduce censoring and truncation, so models and validation procedures must account for partially observed lifetimes to avoid biased inference and misleading performance estimates. This review surveys survival models for predictive maintenance (PdM) and remaining useful life (RUL) estimation, spanning non-parametric, semi-parametric, parametric, and learning-based approaches, with emphasis on censoring-aware formulations and the use of static and time-varying covariates derived from sensor, inspection, and contextual information. A structured taxonomy and a systematic mapping of model families to data types, core assumptions (proportional hazards versus parametric distributional structure), and decision-oriented outputs such as risk ranking, horizon failure probabilities, and RUL distributions are presented. Evaluation practice is also synthesized by covering discrimination metrics, censoring-aware RUL accuracy measures, and probabilistic assessment via proper scoring rules, including the time-dependent Brier score and Integrated Brier Score (IBS). The review provides researchers and practitioners with a practical guide to selecting, fitting, and evaluating survival models for risk-informed maintenance planning in smart energy networks. Full article