1,720,991 research outputs found
An Efficient Reliability-based Design Approach to Reduce Rockfall Risk Below a Target Threshold
Full text linkRockfalls are expected to increase due to global warming and extreme events induced by climate change. An accurate quantification of the risk is fundamental for Administrations to predispose effective risk mitigation plans. Risk value should account for all the possible events that can occur in a specific time, i.e. for a magnitude (block volume) frequency relationship. Among structural protective measures, rockfall barriers are widely selected. Despite their design method has been almost defined, even not standardized, the widely adopted safety factors approach with fixed factors does not allow obtaining a specific probability of failure. Moreover, the event magnitude-frequency relationship is not accounted. A novel time- independent reliability-based approach has been recently conceived by the Authors, allowing obtaining the design values for a specific failure probability. The method accounts for all the possible events, integrating them in time with their probability. In this way, an increase of rockfall events can been accurately considered. The obtained barrier failure probability can be used to compute the risk reduction in a given time or, conversely, to define the maximum failure probability of a barrier that could be accepted
Costruire in alta quota. Nuove sfide e opportunità
Full text linkL’alta quota è un territorio molto vulnerabile in cui sussiste un precario equilibrio tra uomo e natura. Come tutti gli ambienti estremi, essa è il termometro del pianeta quando si parla di cambiamenti climatici, ed è caratterizzata da fenomeni naturali molto significativi dal punto di vista geologico. Per queste ragioni, il tema del costruire diventa in questo ambito un campo di sperimentazione di grande interesse che solleva questioni centrali relativamente alla presenza antropica nei contesti sensibili quali la messa in sicurezza del territorio, il rapporto con il paesaggio, la sostenibilità e la compatibilità ambientale, l’efficienza energetica, la prefabbricazione, l’organizzazione e la gestione del cantiere. Proprio per via della natura complessa e polisemica dell’alta montagna, anche le costruzioni in questo contesto non possono che essere oggetto di confronto tra tutte le figure professionali coinvolte nell’articolato processo che è la progettazione, la realizzazione e la gestione delle strutture antropiche. Il saggio propone una lettura multidisciplinare volta mettere in luce le criticità e le potenzialità degli aspetti progettuali (relativi all’ingegneria e all’architettura) che caratterizzano questo particolare ambito di lavoro, nell’ottica di sviluppare riflessioni declinabili anche in altri contesti in cui si richiede capacità di adattamento, attenzione agli aspetti ambientali e climatici, necessità di un approccio essenziale ed efficiente dell’abitare
Optimization methods for the evaluation of the parameters of a rockfall fractal fragmentation model
No full textIn rockfall events, the falling blocks impacting the slope can experience fragmentation due to their kinetic energy. This process produces new blocks, smaller than the initial ones, moving along independent trajectories. As a result, the in situ block size distribution (related to the slope face of the source area) and the rockfall block size distribution (related to the deposit) differ. The present paper proposes and compares two optimization procedures for choosing the parameters of an iterative fractal fragmentation model based aimed at describing the rockfall fragmentation process on the base of source and deposit block distributions. To discuss the effectiveness of each approach, the two distributions are considered free of uncertainties. The influence of the number of iterations and optimization approach are discussed in terms of easiness of interpretation of the results
NaTech risk in production plants in regions subjected to high seismicity, tornado or flooding hazard
Full text linkReliability analysis and partial safety factors approach for rockfall protection structures
No full textThe design of rockfall protection structures must consider several variables, such as the energy and the height of the impacting block. Nevertheless, the statistical distributions of these variables do not follow a predefined law. Reliability analyses aim at finding how the random nature of the parameters describing a structure affects its performance and safety. In the geotechnical framework, generally, the limit states approach is adopted, accounting for the design values of both effects of actions and resistances. The present paper proposes a solution to a time-variant reliability problem to define the design values of the parameters for net fences design, i.e. velocity, mass and trajectory height of the impacting block, accounting for the spreading of their distributions and rockfall occurrence process. The proposed approach is incorporated into the semi-probabilistic design framework and the equivalent partial safety factors of the main variables and the corresponding characteristic values are discussed. The results highlights that the values of the partial safety factors are affected by the ratios between two relevant values of the right-tail of the distributions of height and velocity, i.e. the 99th and the 95th percentiles, and by the parameters of the statistical distribution of the blocks found at the foot of the cliff
Catenary mechanism in steel columns under extreme lateral loading: A basis for building progressive collapse analysis
Full text linkThe studies on progressive collapse have primarily focused on threat-independent methods, wherein a sudden column removal is suggested in codes. However, a real collapse scenario is necessarily threat-dependent. Focusing on blast- and impact-induced progressive collapses, the current study considers cases in which damage is concentrated in a single member, without resulting in complete column loss. It is demonstrated that the progressive collapse performance under specific threats can be better or worse compared to that of sudden column removal. Thus, dynamic column removal does not necessarily guarantee the most critical scenario, as the response in a damaged system can sometimes exceed expectations. A simple analytical model is proposed to describe in detail the observed phenomena and emphasizes the development of catenary forces in the columm under lateral extreme loading scenarios. The results provide a deeper insight into the progressive collapse performance of frame systems and the involved member-level resisting mechanisms
Archetypal Use of Artificial Intelligence for Bridge Structural Monitoring
Full text linkStructural monitoring is a research topic that is receiving more and more attention, especially in light of the fact that a large part our infrastructural heritage was built in the Sixties and is aging and approaching the end of its design working life. The detection of damage is usually performed through artificial intelligence techniques. In contrast, tools for the localization and the estimation of the extent of the damage are limited, mainly due to the complete datasets of damages needed for training the system. The proposed approach consists in numerically generating datasets of damaged structures on the basis of random variables representing the actions and the possible damages. Neural networks were trained to perform the main structural monitoring tasks: damage detection, localization, and estimation. The artificial intelligence tool interpreted the measurements on a real structure. To simulate real measurements more accurately, noise was added to the synthetic dataset. The results indicate that the accuracy of the measurement devices plays a relevant role in the quality of the monitoring
Progressive Collapse Assessment of Steel Moment-Resisting Frames Using Static- And Dynamic-Incremental Analyses
No full textA finite-element modeling study on the progressive collapse of steel moment-resisting frames under column removal scenarios is presented. Different parameters, such as location of initial local failure, number of story, material strain-rate effects, and column removal time (CRT), are considered. The model structures are analyzed using static- and dynamic-incremental analyses. The former being the well-known pushdown simulations, and the latter performed through dynamic column removal at various gravitational load levels. The progressive collapse potential is mainly related to location of initial failure and size (height) of the models, which determine the affected area after initial local failure. To compare the results, the displacement-based dynamic amplification factor (DAF) is also adopted. It is observed that above a certain gravitational load, the dynamic simulations accounting for material strain rate show displacements smaller than the ones predicted by the static analysis. With the decrease of CRT, the progressive collapse capacity decreases, but DAF tends to be independent from CRT when the systems experience large plastic displacements
A simplified method for assessing the response of RC frame structures to sudden column removal
Full text linkColumn loss is a type of damage that can occur in frame structures subjected to explosions or impacts. The response of such structures largely depends on the capacity of the assembly of elements and on the inertia effects due to the sudden nature of the phenomenon. Frame structures are able to develop various resisting mechanisms that prevent the collapse to progress. The assessment of the robustness often requires complex and detailed numerical modelling. For the preliminary design of a robust frame, simplified methods to assess the effectiveness of the redistribution of the loads after the removal of a member are welcome. In the present paper, an approach based on the idealisation of the damaged structure into a single degree-of-freedom system with an elastic-plastic compliance law is proposed. The output of the method is the dynamic response of a target point, which can serve for assessing the residual safety of the structure. Comparing the obtained results with the outputs of a more sophisticated FE (Finite Elements) analysis, a satisfying accuracy is found
Physics-informed machine learning for the structural health monitoring and early warning of a long highway viaduct with displacement transducers
Full text linkIn Bridge Structural Health Monitoring (SHM), damage detection is often hindered by environmental and operational variability. Confounding influences such as traffic, wind, and especially temperature can significantly affect measurements, making it difficult to distinguish true damage-related anomalies. This challenge is critical in static monitoring of long steel viaducts, where thermal effects dominate displacements, making small damage-induced perturbations difficult to detect. To address this, the study introduces a Physics-Informed Machine Learning (PIML) model that establishes a reliable baseline for the ‘normal conditions’ of the infrastructure. This baseline isolates anomalies attributable to structural damage while accounting for temperature effects. The proposed grey-box approach combines data-driven modelling with physical knowledge of thermal behaviour, enhancing both accuracy and interpretability. A real-world application is presented on a long-span highway viaduct, where longitudinal displacements are monitored using temperature and displacement sensors. By using only temperature and time as inputs, the model captures nonlinear daily and seasonal thermal cycles without additional instrumentation. To assess reliability, an Early Warning System (EWS) is developed based on displacement anomaly thresholds and Kernel Density Estimation (KDE). The PIML model is evaluated against black-box (purely data-driven) and white-box (purely physics-based) alternatives. Damage scenarios are simulated by introducing anomalies into experimental data to test each model’s capability to detect abnormal behaviour while filtering out environmental effects. Results show that the grey-box PIML consistently outperforms black- and white-box models in accuracy, robustness, and anomaly discrimination. These findings demonstrate the potential of PIML to advance SHM practices and enable reliable automated EWSs for bridge monitoring
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