7.0 Abteilungsleitung und andere
Filtern
Dokumenttyp
Schlagworte
- Value of information (11)
- Fatigue (7)
- CFD (5)
- LNG (5)
- Concrete (4)
- High-strength concrete (4)
- SHM (4)
- Sustainability (4)
- Ultrasonic testing (4)
- Africa (3)
Organisationseinheit der BAM
- 7 Bauwerkssicherheit (74)
- 7.0 Abteilungsleitung und andere (74)
- 7.1 Baustoffe (6)
- 7.2 Ingenieurbau (6)
- 5 Werkstofftechnik (3)
- 5.5 Materialmodellierung (3)
- S Qualitätsinfrastruktur (3)
- S.2 Digitalisierung der Qualitätsinfrastruktur (3)
- 5.2 Metallische Hochtemperaturwerkstoffe (2)
- 1 Analytische Chemie; Referenzmaterialien (1)
Paper des Monats
- ja (3)
Structural health monitoring systems have been widely implemented to provide real-time continuous data support and to ensure structural safety in the context of structural integrity management. However, the quantification of the potential benefits of structural health monitoring systems has not yet attracted widespread attention. At the same time, there is an urgent need to develop strategies, such as optimizing the monitoring period, monitoring variables, and other factors, to maximize the potential benefits of structural health monitoring systems. Considering the continuity of structural health monitoring information, a framework is developed in this article to support decision-making for structural Health monitoring systems arrangement in the context of structural integrity management, which integrates the concepts of value of information and risk-based inspection planning based on an approach which utilizes a conjugate prior probability distribution for updating of the probabilistic models of structural performances based on structural health Monitoring information. An example considering fatigue degradation of steel structures is investigated to illustrate the application of the proposed framework. The considered example shows that the choice of monitoring variables, the Monitoring period, and the monitoring quality may be consistently optimized by the application of the proposed framework and approach. Finally, discussions and conclusions are provided to clarify the potential benefits of the proposed Framework with a special view to practical applications of structural health monitoring systems.
Bewertung der Innenhydrophobierung als neuartige AKR-Vermeidungsstrategie bei Betonfahrbahndecken
(2023)
Zur Vermeidung von AKR-Schäden an Betonfahrbahndecken im deutschen Autobahnnetz wurden mit dem ARS 04/2013 verbindliche Eignungsprüfungen zum Ausschluss alkaliempfindlicher Gesteinskörnungen bei Neubau- und Erhaltungsmaßnahmen eingeführt. Das hatte eine signifikante Reduzierung geeigneter Gesteinskörnungen zur Folge. Deshalb wird geprüft, ob durch die Zugabe eines Hydrophobierungsmittels während der Betonherstellung grenzwertig alkaliempfindliche Gesteinskörnungen nutzbar gemacht werden können. In diesem Beitrag wird der Einfluss der Dosierung eines Compounds mit Hydrophobierungsmittel (HM) auf die Frisch- und Festbetoneigenschaften eines Waschbetons mit einer reaktiven Grauwacke dargestellt. Es zeigt sich, dass aufgrund des Antagonismus die zunehmende Dosierung des HM-Compounds eine signifikante Erhöhung der Zugabe des Luftporenbildners auf Wurzelharzbasis erfordert. Der AKR-Schädigungsprozess wird ab einer Dosierung des HM-Compounds von 0,75 M.-%, bezogen auf den Zementgehalt, hinreichend vermindert. Die mechanischen Eigenschaften des hydrophobierten Waschbetons verschlechtern sich im betrachteten Dosierungsbereich des HM-Compounds nur geringfügig. Auch der Frost-Tausalz-Widerstand vermindert sich, ohne den normativen Grenzwert für die Abwitterung zu überschreiten.
This paper analyses the suitability of the Sensible Enthalpy Rise Approach for measuring the heat release rate of electric-vehicle-scale lithium-ion batteries. An apparatus is designed that meets the conditions of an electric-vehicle-scale lithium-ion battery fire by using cement board as wall material. Modifications of the Sensible Enthalpy Rise Methodology are presented due to the high emissivity and inhomogeneous temperature distribution of the apparatus wall material: a power 4 approach for the heat flow from the walls to the ambient air and an alternative determination methodology for the wall temperature. A one factor at a time parameter study is performed with Computational Fluid Dynamics simulations, investigating a new calibration method based on a fit approach compared to common methods, the wall temperature determination, the approach for the ambient heat flow, the calibration power and the volume flow at the outlet. The simulations show, that suitable estimations of the heat release rate are obtained by using the modifications for wall temperature determination and the power 4 approach for the ambient heat flow. The three calibration methods provide suitable constants, if the calibration power in the same order of magnitude as the mean of the heat release rate profile of the test object.
From a fire safety point of view, the burning behavior of lithium-ion batteries is of high interest. The heat release rate (HRR) is the most important fire parameter to analyze the fire hazards of burning objects, so that an accurate determination of it is crucial. In this paper, two different measurement techniques, the Oxygen Consumption Calorimetry (OCC) and the Sensible Enthalpy Rise Approach (SERA) are simultaneously performed in the same calorimeter to measure the HRR of two different types of lithium-ion batteries. HRR values as well as total energies determined by SERA are higher than measured with OCC: The total energy released is about 10–12 times (SERA) and 6–9.5 times (OCC) the electrical stored energy for both battery types, whereas the timescales of the release differ strongly between the types, resulting in maximum HRRs of 3.4 MW (SERA) and 1.5 MW (OCC)
for one module of type A and 0.8 MW (SERA) and 0.6 (OCC) of type B respectively. Furthermore, a sensitive dependency of the HRR measurement with SERA on the position of the wall temperature measurement is observed.
Lithium-ion batteries are a key technology to achieve the goals of limiting climate change due to the important role as traction technology for Electric Vehicles and in stationary energy storage systems. Over(dis) charge, mechanical damage due to accidents or thermal abuse such as fires can initiate an accelerated self-heating process of the batteries, called thermal runaway. A thermal runaway can propagate from cell to cell within a larger assembly of cells such as modules or battery packs and can cause rapid heat and toxic gas emissions. The resulting battery fire can spread to adjacent facilities, e.g. other cars in underground car parks or to a whole building in case of a large stationary energy storage.
For proof of fire protection requirements or to design suitable fire protection systems, Computational Fluid Dynamic (CFD) simulations are getting more and more important. The aim of CFD fire simulations is to predict the global hazards of a fire to its surroundings, that is mainly characterized by the release of heat and smoke and its spread in the fire environment. There are many numerical investigations of lithium-ion batteries in the literature. One class of models is used to simulate the charge and discharge process of lithium-ion batteries and to predict the temperature or voltage evolution inside the battery. On the other hand, there are models describing batteries under abuse conditions to predict the consequences of a thermal runaway event to the local environment, like the temperatures inside a battery or at the battery surface. Henriksen et al. use a generic battery gas mixture to simulate an explosion of vented gases from a Lithium Iron Phosphate battery and compare experimental results for the explosion pressure and the position of the flame front to the outcomes of a simulation with Xifoam. Larsson et al. used a combination of CFD simulations with FDS and thermal model with COMSOL to predict the temperature development of neighboring cells in a thermal runaway propagation. Truchot et al. use a design Heat Release Rate (HRR) curve for a battery based on experimental measurements to build up an overall HRR curve for a truck loaded with 100 lithium-ion batteries. This summed up HRR and corresponding smoke production curve is then used as an input for a simulation of a truck fire in a tunnel with Fire Dynamics Simulator (FDS). The pre-definition of the HRR curve is a frequently used method in fire engineering. It has the disadvantage, that the heat release cannot be influenced by physical processes, such as changed ventilation conditions or extinguishing measures. In this paper, a model is presented that determines the release of heat and gases based on the thermal runaway mechanisms of the battery, which can be used in CFD fire simulations with focus on prediction of fire hazards to nearby environment.
The durability of concrete structures and its performance over the lifetime is strongly influenced by many interacting phenomena such as e.g. mechanical degradation due to fatigue loading, loss of prestress, degradation due to chemical reactions or creep and shrinkage. Failure due to cyclic loading is generally not instantaneous, but characterized by a steady damage accumulation.
Many constitutive models for concrete are currently available, which are applicable for specific loading regimes, different time scales and different resolution scales. A key limitation is that the models often do not address issues related to fatigue on a structural level. Very few models can be found in the literature that reproduce deterioration of concrete under repeated loading-unloading cycles.
The objective of this paper is the presentation of numerical methods for the simulation of concrete under fatigue loading using a temporal multiscale method.
First, a continuum damage model for concrete is developed with a focus on fatigue under compressive stresses. This includes the possibility to model stress redistributions and capture size effects. In contrast to cycle based approaches, where damage is accumulated based on the number of full stress cycles, a strain based approach is developed that can capture cyclic degradation under variable loading cycles including different amplitudes and loading frequencies. Second, a multiscale approach in time is presented to enable structural computations of fatigue failure with a reduced computational effort. The damage rate within the short time scale corresponding to a single cycle is computed based on a Fourier based approach. This evolution equation is then solved on the long time scale using different time integration schemes.
Accurate models for the long term behavior of concrete structures are important to ensure a durable and reliable design.
A variety of interacting phenomena, such as the loss of prestress, the degradation due to chemical reactions or creep and shrinkage, influence the fatigue resistance. Therefore, a reliable numerical model to predict the performance of concrete over its lifetime is required.
The presented fatigue model is an extension of a static damage model to allow easy coupling in a multiphysics context. The evolution equation of the damage driving variable is enhanced to allow damage growth below the static limit. The model is defined in the time domain and does not include the number of cycles as a parameter.
Thus, it can capture both static and cyclic failure.
Additionally, this allows calibrating the majority of the model parameters static experiments. The model is integrated by resolving each loading cycle, requiring about ten time steps per cycle. The high computational costs are handled via a time scale separation.
The short time scale describes one cycle with marginal changes in the internal variables. These changes are integrated along the large time scale of material deterioration. Various high-order time integration schemes are compared.
Wöhler curves relate loading amplitudes to the number of cycles that the material endures. They are used to validate the model against experimental data.
We analyse the performance of risk reduction strategies for Terrorist attacks with Improvised Explosive Devices (IEDs) for large governmental building structures in terms of cost-efficiency, significance and effectiveness Accounting for life safety in conjunction with societal preferences and capabilities. The approach builds upon an extended Bayesian pre-posterior decision analysis and the principles of the marginal lifesaving costs based on the Life Quality Index (LQI). The decision scenario is formulated for a decision maker responsible for the safety of governmental or large commercial buildings and consequently the direct risks, the indirect risks due to fatalities and economical importance of the building beside the expected cost for the individual risk reduction strategies are modelled, aggregated and optimised. The considered risk reduction strategies encompass an explicit consideration and distinction of information and actions such as (i) threat surveillance may trigger the temporary evacuation of the building, (ii) the implementation of protection provisions provided by codes and guidelines, (iii) a detailed progressive collapse assessment and specific protection measures and (iv) the combination of protection and surveillance. All considered strategies are found to contribute to risk reduction and can be costefficient, especially for higher threat probabilities. The risk reduction strategies comply with societal macroeconomic and demographical characteristics and societal preferences according to the LQI. The progressive collapse assessment with targeted protection measures is found to be the most cost-efficient, significant and effective counter-terrorism strategy. This finding points to the necessity for a comprehensive utilisation of scientific methods and sophisticated engineering for progressive collapse assessment to determine targeted protection measures.
Damage detection systems (DDS) provide information of the structural system integrity in contrast to e.g. local information by inspections or non-destructive testing techniques. In this paper, an approach is developed and demonstrated to utilize DDS information to update the structural system reliability and to integrate this information in structural system risk and utility analyses. For this aim, a novel performance modelling of DDS building upon their system characteristics and non-destructive testing reliability is introduced. The DDS performance modelling accounts for a measurement system in combination with a damage detection algorithm attached to a structural system in the reference and damage states and is modelled with the probability of indication accounting for type I and II errors. In this way, the basis for DDS performance comparison and assessment is provided accounting for the dependencies between the damage states in a structure. For updating of the structural system reliability, an approach is developed based on Bayesian updating facilitating the use of DDS information on structural system level and thus for a structural system risk analysis. The structural system risk analysis encompasses the static, dynamic, deterioration, reliability and consequence models, which provide the basis for the system model for calculating the direct risks due to component failure and the indirect risks due to system failure. Two case studies with the developed approach demonstrate a high Value of DDS Information due to risk and expected cost reduction.
This article introduces an approach and framework for the quantification of the value of structural health monitoring (SHM) in the context of the structural risk and integrity management for systems. The quantification of the value of SHM builds upon the Bayesian decision and utility theory, which facilitates the assessment of the value of information associated with SHM. The principal approach for the quantification of the value of SHM is formulated by modeling the fundamental decision of performing SHM or not in conjunction with their expected utilities. The expected utilities are calculated accounting for the probabilistic performance of a system in conjunction with the associated structural integrity and risk management actions throughout the life cycle, the associated benefits, structural risks, and costs and when performing SHM, the SHM information, their probabilistic outcomes, and costs. The calculation of the expected utilities necessitates a comprehensive and rigorous modeling, which is introduced close to the original formulations and for which analysis characteristics and simplifications are described and derived. The framework provides the basis for the optimization of the structural risk and integrity management based on utility gains including or excluding SHM and inspection information. Studies of fatigue deteriorating structural Systems and their characteristics (1) provide decision Support for the performance of SHM, (2) explicate the influence of the structural component and system characteristics on the value of SHM, and (3) demonstrate how an integral optimization of SHM and inspection strategies for an efficient structural risk and integrity management can be performed.