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In many regions of the world the urbanisation process is accelerating dramatically. This puts pressure on urban planners but also politics to develop strategies for sustainable city growth. With the rapidly increasing demand for living space in urban areas, cities typically grow vertically. This is largely driven by real estate markets and sometimes also by the desire for status symbols.
Certainly, vertical urban growth makes sense, when horizontal growth destroys important flora and Fauna (e.g. in rain forest regions), but in many cases vertical growth is result of real-estate business and Expansion limitation due to state or country borders. However, economics and borders are made by humans. They follow human-made rules. Gravity does not. Therefore, from a point of view of sustainable materials and resourceuse, the trending vertical growth of cities may come under scrutiny.
The following aspects should be considered, when a decision is taken between a new quarter with limited number of storeys or a new skyscraper.
Today, in scientific events often a certain separation between researchers from laboratories with highly sophisticated equipment and those from less privileged laboratories can be observed. It is not an uncommon situation that results presented at conferences are rubbished or ridiculed because the investigator only used low-end analytical methods.
The assessment of the study is then biased based on the equipment, regardless of the actual quality of the study.
Severe mechanical fatigue conditions for worldwide proliferating windfarms are a Major challenge for high-performance concrete in towers, connecting joints and foundations of wind turbines. High-performance concrete offers potential for the application in offshore windfarms, not only regarding its good mechanical, but also chemical resistivity due to low diffusivity in the highly densified microstructure. For a more reliable fatigue assessment, monitoring based on nondestructive testing can be a valuable complement to design rules. Both approaches demand reliable experimental data, information about scalability and the development of standardized testing methods. This article presents results of an ongoing research program of BAM (Bundesanstalt für Materialforschung und -prüfung), which is a part of a joint national project (WinConFat) funded by the German Federal Ministry for Economic Affairs and Energy. The subproject implemented by BAM examines the fatigue behavior in dependence of size and slenderness for varying concrete strength at different stress levels. Besides fatigue strength, nondestructive testing is carried out additionally.
Methods used are strain measurement and ultrasonic testing. The change of strain, stiffness and ultrasonic pulse velocity in the fatigue process is discussed. Results disclose a deeper insight into the damage process under cyclic loading of high-performance concrete and contribute to improve nondestructive monitoring.
Severe mechanical fatigue conditions for worldwide proliferating windfarms are a Major challenge for high-performance concrete in towers, connecting joints and foundations of wind turbines. High-performance concrete offers potential for the application in offshore windfarms, not only regarding its good mechanical, but also chemical resistivity due to low diffusivity in the highly densified microstructure. For a more reliable fatigue assessment, monitoring based on nondestructive testing can be a valuable complement to design rules. Both approaches demand reliable experimental data, information about scalability and the development of standardized testing methods. This article presents results of an ongoing research program of BAM (Bundesanstalt für Materialforschung und -prüfung), which is a part of a joint national project (WinConFat) funded by the German Federal Ministry for Economic Affairs and Energy. The subproject implemented by BAM examines the fatigue behavior in dependence of size and slenderness for varying concrete strength at different stress levels. Besides fatigue strength, nondestructive testing is carried out additionally.
Methods used are strain measurement and ultrasonic testing. The change of strain, stiffness and ultrasonic pulse velocity in the fatigue process is discussed. Results disclose a deeper insight into the damage process under cyclic loading of high-performance concrete and contribute to improve nondestructive monitoring.
Innovation, science and engineering are driving forces to mastering the global challenges of the next decades. The basis is education. ISEE stands for Innovation, Science, Engineering and education. This book summarises the presentations, discussions and Statements that were made during the ISEE-Africa conference held in Nairobi in 2019 from January 30 to February 1.
The ISEE conference is a gathering of international researchers, scholars, and students, who came together to discuss jointly relevant topics related to better education for the engineers and architects of the future.
Today, we know that the climate change is real. Many regions in the world are already suffering significantly, and the only way for humanity to overcome the challenges is to develop more sustainable technologies to the benefit of the entire global society. However, sustainable technologies require for deeper understanding, more conscious thinking, and smarter engineering. The only way how this can be achieved is to educate the developers, the decision makers, the engineers of tomorrow in a more knowledge driven way, and to equip them with the assertiveness required for the implementation.
In this book, topics of construction and sustainable materials are linked to educational challenges. It addresses teachers, academic and political decision makers, and change drivers. The specific objective is to be critical, thought-provoking and inspiring. This way, we do hope that the book can deliver credible solution strategies for enhanced education for a new generation of decision makers with higher awareness of global and environmental challenges as well as innovation potentials.
Sustainability means meeting the needs of today without compromising the needs of the next generations. How can we meet the needs of the next generations, if we do not even know what these needs are? If we do not listen to the next generation and learn from them? Do we even meet the needs of today for everyone on earth?
The risk analysis of road tunnels faces a growing complexity in fire scenarios, e.g. caused by new energy carriers. Essentially, such complex scenarios involve many interactions between the tunnel users, the fire source and the safety measures. One example is the alarm of tunnel users either initiated by the perception of smoke or by the fire alarm system. To consider these interactions for the quantification of consequences, e.g. fatalities, risk analysis requires a complex model. However, the complex model can compute in practice only few discrete scenarios due to its high computational cost, whereas risk analysis generally needs the consequences of a high number of random scenarios. Metamodels can solve this contradiction. They are able to approximate the consequences of many random scenarios with low computational cost based on the consequences of few discrete scenarios computed with the complex model. The efficiency of metamodels depends on the required number of these discrete scenarios. In this sense, this dissertation proposes an efficient metamodel within an innovative methodology for risk analysis of road tunnels to allow to consider an increased complexity of scenarios. This metamodel applies the following methods or models: the projection array-based design method specifies the experimental design for the discrete scenarios; the combination of the fire model FDS and the microscopic evacuation model FDS+Evac constitutes the complex model; and moving least squares produces the response surface model. The response surface model approximates the consequences of the random scenarios and therewith introduces an uncertainty, called metamodel uncertainty, which is quantified with the prediction interval method. Additionally, stochastic individual characteristics of tunnel users in discrete scenarios computed with FDS+Evac attribute evacuation uncertainties to the consequences. An original development in this dissertation, the ’direct approach’, directly transfers the evacuation uncertainties of the discrete scenarios to any random scenario. The evaluation of the metamodel in this dissertation shows following results. Firstly, the response surface model sufficiently represents the consequences of the complex model. Secondly, the metamodel uncertainty is also essential for this representation, but the prediction interval method reveals a drawback in the risk analysis. Potential approaches to deal with this drawback are discussed. Finally, the direct approach reproduces the evacuation uncertainty of the complex model which then clearly affects the consequences of random scenarios. Therefore, the consideration of the evacuation uncertainty plays an important role for the risk analysis. Furthermore, the projection array-based design method was adapted in this dissertation with two approaches, namely the combination of the experimental designs for FDS and FDS+Evac as well as their sequential refinement. Both approaches contribute to the efficiency of the metamodel. These results lead to following conclusions. Firstly, the metamodel efficiently integrates the consequences of discrete scenarios into risk analysis and thus allows to consider an increased complexity. Secondly, the metamodel is an advancement for risk analysis not only for road tunnelsbutalsomoregeneralinfiresafetyengineering. Forthesetworeasons,themetamodel might be interesting for other methodologies for risk analysis. In addition, the metamodel is generic and is therefore widely applicable on other issues beside from risk analysis, e.g. to assess the safety of structures related to time-consuming experiments depending on multiple variables.
Applications of Structural Health Monitoring (SHM) for the design and analysis of Offshore Wind Turbine (OWT) structures has gained much attention within the past few years. Being exposed to repeated cyclic wind and wave loads, OWTs are dynamically sensitive structures and can benefit from monitoring systems to predict time-dependent deterioration. This study focuses on the quantification of the value of SHM information on the maintenance of OWT structures, with emphasis on fatigue of welded joint. By utilizing the decision tree, structural reliability, SHM data, as well as the cost-benefit assessments, a value of information (VoI) analysis can be done to model the fundamental decision of whether the service life of an OWT foundation can be extended beyond the initial design life. The application is demonstrated on a butt weld of a monopile support structure of a 3 MW offshore wind turbine with a hub height of approximately 71m where the prior probability analysis is modelled as a probabilistic fatigue damage model based on S-N approach and designed wind data. The posterior probability of failure of welded joints is updated using the three-year measured oceanographic and one-year strain data. The expected value of SHM information can be found as the difference between the maximum utility obtained in posterior analysis with SHM information and the maximum utility obtained using only prior information. This work can provide insights on how much benefits can be achieved through SHM information, with practical relevance on reliability-based design optimization and fatigue life extension of OWT structures.
Fatigue safety verification of existing bridges that uses ‘‘re-calculation’’ based on codes, usually results in insufficient fatigue safety, triggering invasive interventions. Instead of “re-calculation”, Structural Health Monitoring (SHM) should be used for the assessment of the existing bridges. Monitoring systems provide data that can reduce uncertainties associated with the fatigue loading process and the structural resistance. The objective of this paper is to quantify the value of the SHM system implemented in a 60-years-old road viaduct to investigate its fatigue safety, through modeling of the fundamental decisions of performing monitoring in conjunction with its expected utility. The quantification of the conditional value of information is based on the decision tree analysis that considers the structural reliability, various decision scenarios as well as the cost-benefit assessments. This leads to a quantitative decision basis for the owner about how much time and money can be saved while the viaduct fulfills its function reliably and respects the safety requirements. The originality of this paper stands in the application of the value of information theory to an existing viaduct considering the fatigue failure of the system based on the monitoring data and the cost-benefit of monitoring method.
Quantification of the posterior utilities of SHM campaigns on an orthotropic steel bridge deck
(2019)
This paper contains a quantification and decision theoretical optimization of the posterior utilities for several options for monitoring campaigns on the particular case of fatigue life predictions of an orthotropic steel deck. The monitoring campaigns are defined by varying monitoring durations and phases. The decision analysis is performed with real data from the Structural Health Monitoring (SHM) of the Great Belt Bridge (Denmark) which, among others, consist of measured strains, pavement temperatures and traffic intensities. The fatigue loading prediction model is based on regression models linking daily averaged pavement temperatures, daily aggregated heavy-traffic Counts and derived S-N fatigue damages, all of them derived from the outcomes of different monitoring campaigns. A probabilistic methodology is utilized to calculate the fatigue reliability profiles of selected instrumented welded joints. The posterior utilities of SHM campaigns are then quantified by considering the structural fatigue reliability, various monitoring campaigns and the corresponding cost-benefit models. The decisions of identifying the optimal monitoring campaign and of extending the service life or not in conjunction with monitoring results are modelled. The optimal monitoring campaign is identified - retrospectively - by maximizing the expected benefits and minimize risks in dependency of the monitoring duration and the monitoring associated costs. The results, despite relying on a number of simplistic assumptions, pave the way towards the use of pre-posterior decision support to optimise the design of monitoring campaigns for similar bridges, with an overall goal to proof the cost efficiency of SHM approaches to civil infrastructure management.
Quantification of the posterior utilities of SHM campaigns on an orthotropic steel bridge deck
(2019)
This paper contains a quantification and decision theoretical optimization of the posterior utilities for several options for monitoring campaigns on the particular case of fatigue life predictions of an orthotropic steel deck. The monitoring campaigns are defined by varying monitoring durations and phases. The decision analysis is performed with real data from the Structural Health Monitoring (SHM) of the Great Belt Bridge (Denmark) which, among others, consist of measured strains, pavement temperatures and traffic intensities. The fatigue loading prediction model is based on regression models linking daily averaged pavement temperatures, daily aggregated heavy-traffic Counts and derived S-N fatigue damages, all of them derived from the outcomes of different monitoring campaigns. A probabilistic methodology is utilized to calculate the fatigue reliability profiles of selected instrumented welded joints. The posterior utilities of SHM campaigns are then quantified by considering the structural fatigue reliability, various monitoring campaigns and the corresponding cost-benefit models. The decisions of identifying the optimal monitoring campaign and of extending the service life or not in conjunction with monitoring results are modelled. The optimal monitoring campaign is identified - retrospectively - by maximizing the expected benefits and minimize risks in dependency of the monitoring duration and the monitoring associated costs. The results, despite relying on a number of simplistic assumptions, pave the way towards the use of pre-posterior decision support to optimise the design of monitoring campaigns for similar bridges, with an overall goal to proof the cost efficiency of SHM approaches to civil infrastructure management.
A method to determine the structural and damage detection system influencing parameters is proposed based on the value of information analysis. The value of information analysis utilizes the Bayesian pre-posterior decision theory to quantify the value of SHM for the structural integrity management during service life. First the influencing parameters of the structural system such as deterioration type and rate are introduced for the performance of the prior probabilistic system model. Then the damage detection system performance influencing parameters including number of sensors, sensor locations, measurement noise and the Type I error are investigated. The pre-posterior probabilistic model is computed utilizing the Bayes’ theorem to update the prior system model with the damage indication information. Finally, the value of information is quantified as the difference between the maximum utility obtained in pre-posterior and prior analysis based on the decision tree analysis, comprising structural probabilistic models, consequences as well as benefit and costs analysis associated with and without monitoring. With the developed approach, a case study on a statically determinate Pratt truss bridge girder is carried out to validate the method. The analysis shows that the higher the deterioration rate is, the more it is beneficial to do SHM. Furthermore, it shows that more sensors do not necessarily lead to a higher value of information; only specific sensor locations near the highest utilized components lead to a high value of information; measurement noise and the Type I error should be controlled and as small as possible. An optimal sensor employment with highest value of information is found. Moreover, it is found that the proposed method can be a powerful tool to develop optimal service life maintenance strategies - before implementation - for similar bridges and to optimize the damage detection system settings and sensor configuration for minimum expected costs and risks.
Basierend auf Methan aus regenerativen Quellen, stellt LNG einen alternativen Kraftstoff für den schweren Fernverkehr da. Gegenüber seinen positiven Eigenschaften birgt der Kraftstoff aber auch Risiken, durch seine sehr niedrige Temperatur und seine Brennbarkeit, für die Personen- und Bauwerkssicherheit. Für die Erforschung der Risiken eignen sich CFD-Modelle, deren Erforschung unter anderem Ziel des TF-SiVi Projekts der BAM war.
Einen Einblick in die angewendete Methodik zur Erforschung von Unfallszenarien mit LNG gibt der Vortrag.