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Bridges are essential elements in the built environment since they underpin the functioning of transportation systems. Nevertheless, they are vulnerable due to aggressive environment, demand beyond the design level, and other contingencies such as extreme events. The management of bridges represents a significant challenge for improving transport performance and ensure the safety of users. In Italy, bridge management is addressed by the recent “Guidelines for risk classification and management, safety evaluation and monitoring of existing bridges” which were issued by the Italian Ministry for Public Work in 2020. The guidelines propose an operational approach with distinctive characteristics: (i) risk‐based, i.e., based on the typical parameters of hazard, vulnerability, and exposure; (ii) multi‐level, i.e., they include six assessment levels (0‐5) of increasing complexity; and (iii) multi‐risk, i.e., they assess structural/foundation, seismic, hydrological and landslide risk. This paper presents a general overview of the 2020 Italian Guidelines and their application to a selected case study. Lessons from the application to the case study are drafted and possible criticalities highlighted.
As part of a nuclear safety research project, large-scale impact tests were conducted on reinforced concrete slabs to investigate the structural integrity of containment structures under aircraft crash scenarios. The aim was to experimentally validate numerical models for both hard and soft impact conditions. Using a drop tower, concrete slabs were subjected to controlled impacts with a 404 kg impactor dropped from a height of 9.5 meters. The tests included force measurements, photogrammetric evaluations, and 3D scans to analyze deformations and damage. A total of six impact experiments were performed (2x hard impact, 2x combined hard/soft impact). The results provide a robust basis for advancing safety assessments of nuclear facilities.
This paper presents a comprehensive fire simulation study that models the pyrolysis process of beech wood using kinetic parameters with the Fire Dynamics Simulator (FDS). The kinetic methodology is based on the application of these kinetic parameters to govern the underlying pyrolysis reactions. The primary objective was to numerically model the pyrolysis process for beech wood using both single-component (single-step, single reaction scheme) and multi-component (single-step, multi-reaction scheme) kinetic reaction schemes. The accuracy of the numerical model was validated by comparing FDS simulation results with experimental data obtained from thermogravimetric analysis (TGA) and cone calorimeter tests. This approach aids in identifying reliable kinetic reaction input parameters for modelling wood fires. A case study was included to demonstrate the implementation of the kinetic reaction schemes. Numerical results from the TGA simulations for the small-scale pure cellulose test using the single-component approach exhibit consistency with the experimental data. Furthermore, the results demonstrated that the multi-component approach more accurately replicates the shape of the experimental curve for beech wood compared to the single-component approach. However, discrepancies in the tail regions of the curves obtained from the FDS simulations showed the need for further improvement in the modelling approach, particularly regarding the exclusion of char oxidation reactions, which needs to be investigated further.
Um den Folgen des Klimawandels für unsere Infrastrukturen zu begegnen, sind grundlegende Änderungen unserer bisherigen Praxis erforderlich. Dies umfasst sowohl den Umgang mit Unsicherheiten in der Prognose kommender Ereignisse als auch den Wechsel von Struktur- auf Systemebene zur Aufrechterhaltung grundlegender Funktionen.
Das jährlich im Herbst an wechselnden Forschungsstandorten stattfindende DAfStb-Forschungskolloquium wurde im Jahr 2024 von der BAM Bundesanstalt für Materialforschung und -prüfung in Berlin ausgerichtet. Unter der Überschrift „Green Intelligent Building“ referierten rd. 35 Vortragende in fünf Sitzungen unterschiedlicher Thematik über verschiedene betonbezogene Forschungsschwerpunkte in der BAM. Anhand der überwiegend von Doktoranden und Post-Docs dargebotenen Vorträge konnten sich die Teilnehmerinnen und Teilnehmer ein aktuelles Bild von der Qualität der wissenschaftlichen Arbeit und der hervorragenden Forschungsmöglichkeiten in der BAM machen. Durch die Vernetzung unterschiedlich ausgerichteter Fachbereiche innerhalb der BAM werden Synergie-Effekte genutzt. Analytische, baustoffliche, konstruktive, umweltorientierte und auf die Verfahrensentwicklung ausgerichtete Bereiche der BAM forschen gemeinsam zum Thema Stahlbetonbau. Es folgen ausführliche Zusammenfassungen der Tagungsinhalte.
Sensitivity Analyses of Probabilistic Thermo-Mechanical Fire Safety Assessment of Tunnel Linings
(2021)
Fire safety structural analyses contain uncertainties related to the mechanical aspects, such as compressive strength and tensile strength, and the thermal aspects, such as conductivity, specific heat and fire loads. The uncertainties related to the mechanical aspects are explicitly considered by the applicable standards. However, the uncertainties related to the conductivity and specific heat are implicitly considered by the standards, while the uncertainties related to the fire loads are only considered in the German National Annex of the Eurocode 1991-1-2. Nevertheless, considering the severe nature of tunnel fires, these uncertainties must be incorporated into the design. The complexity of the stresses in a tunnel lining in fire can be determined by a probabilistic thermo-mechanical analysis as proposed in the methodology presented in this work. The methodology presented here to investigate the influence of thermal parameters on the fire safety of concrete structures in tunnels is based on the thermo-mechanical finite element analysis. The methodology includes the design of experiments executed by a Correlation Latin Hypercube Sampling. This work includes three case studies to illustrate the use of the proposed methodology. The second and the third studies contain reliability analyses to evaluate the probabilities of failure. The first case study uses an analytical thermo-mechanical analysis based on the 500 °C isotherm method. It considers the uncertainties related to the thermal and mechanical properties of the concrete, the soil load, and the temperatures described by the standard temperature-time curve. The results demonstrate the importance of incorporating the characteristic values of conductivity and specific heat in the semi-probabilistic structural fire design. The probability of failure is Pf = 3.1 × 10−3.
The second case study is a probabilistic thermo-mechanical analysis of tunnels using the standard temperature-time curve. It considers the uncertainties related to the thermal and mechanical properties of the concrete, the soil load, and temperature. The probability of failure is Pf = 0.06. The third case study is a probabilistic thermo-mechanical analysis of the tunnel using natural fire calculated with CFast. It considers the uncertainties related to the thermal and mechanical properties of the concrete, the soil load, and the fire load. The probability of failure is Pf = 0.08. Although the natural fire in the third study results in higher temperatures than the standard fire in the second study, the difference between the failure probabilities of both case studies is smaller than expected. The reason for the small difference is probably that the effects due to the higher temperatures are compensated by the decay phase of the natural fire. The reliability assessments of both the second and the third case study show that the investigated structures do not meet the reliability requirements derived from the EN 1990 standard. Therefore, the structures would either need to be redesigned or more protective methods would need to be provided, such as the thermal boards or sprinklers.
The conductivity, specific heat, and fire load are the parameters that correlate to the results the most. For the tunnel structural fire design, the following safety factors are recommended based on this work: γfi = 1.76 for the conductivity, γfi = 0.31 for the specific heat, and γfi = 1.8 for the fire load. Given the range of results of the fire safety analyses, the inclusion of the uncertainties is demonstrated to be necessary. The choice of failure criterion has a significant influence on the probability of failure and is, therefore, a critical step in the safety analysis. For the tunnel fire, the model must be improved to accurately account for the fast heating rate and the cooling phase of tunnel fires.
Bridges are subject to a plethora of deterioration phenomena, such as corrosion, fatigue, and damaging events (e. g., truck impacts and earthquakes) that can affect their performance and compromise functionality and safety. These challenges, along with the expansion of physical infrastructures and limited economic resources, underscore the need for effective management systems to enhance the efficiency of maintenance activities. To address this need, bridge operators have developed Bridge Management Systems (BMSs), which assist in ensuring safe operations while optimizing budget allocation and intervention strategies. Existing state-of-the-art studies on BMSs, dating back several years, primarily focus on specific aspects of BMSs and do not provide exhaustive insight into the implemented processes. Consequently, a comprehensive analysis of the entire process is currently lacking. This review organizes and discusses the key features of existing BMSs and introduces a novel definition of BMS modules — data management, diagnosis, prognosis, and decision-making — where consensus is currently lacking. The paper covers the historical and current practices of the most common BMSs, outlining the main principles of each phase along with their critical aspects and future trends.
AbstractInnovation plays a crucial role in shaping technological, economic, and social progress in modern societies. In the realm of bridge integrity management, the development and diffusion of technologies to acquire information can significantly enhance industries' safety and functionality capabilities. Among the most widely diffused bridge types in Europe and North America, Gerber bridges are particularly susceptible to deterioration over time. Gerber saddles are typically not instrumented and are checked only through visual inspections. This paper introduces the metric of the Value of Information for Innovation to estimate the benefit associated with introducing an established technology in a new market of application. Herein, the operational value of implementing microelectromechanical inclinometers in the integrity management of Gerber saddles is quantified for the specific case of a bridge in northern Italy. Microelectromechanical systems companies may use these results to optimally select the technology price, investigate diverse market strategies, and optimize sensor arrangement.
ABSTRACTThe need for numerical‐based approaches to investigate the fire behaviour in buildings with combustible components is growing due to the increasing use of timber by the construction industry to meet the ‘Climate Action Plan 2050’. This requires consideration of the complex kinetic processes that take place during the burning of the wood in the numerical models. This is accomplished by using computational fluid dynamics (CFD) to numerically model the material pyrolysis and combustion processes. This article presents three different approaches for simulating the behaviour of a wood crib fire using the fire dynamics simulator (FDS). These approaches are based on either prescribing the burning rate of the wood directly from the physical experiments or using the kinetic parameters to govern the underlying processes, such as pyrolysis. Wooden crib fire experiments carried out by the RISE Research Institute in Sweden inside the combustion chamber that were used to validate all the methods. The numerical results from the method, that utilised the experimentally determined burning rate, were in good agreement with the experimental results, with a maximum deviation of 6% in the case of HRR. On the other hand, the model that needs kinetic parameters as its input has shown maximum discrepancies of 12% and 33% compared to experimental results. These methods are sensitive to the input parameters and the extent of dependency needs further investigation.