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Die Oberflächentexturierung der Betonfahrbahndecken mittels Grinding und Grooving steht seit einigen Jahren im Mittelpunkt der Forschung und Entwicklung des Betonstraßenbaus in Deutschland. In den vergangenen Jahren wurden die vorteilhaften Oberflächenperformances derartiger Texturen, wie z.B. Griffigkeit, Ebenheit, Lärmminderung, in zahlreichen Forschungsprojekten umfassend untersucht. Im Kontext des gegenwärtig verfolgten ganzheitlichen performanceorientierten Ansatzes liegt der Fokus nun verstärkt auf der Analyse und Charakterisierung der Oberflächentopografie von Grinding- bzw. Groovingtexturen. Insbesondere gilt ein Hauptaugenmerk hierbei der zeitlichen Entwicklung der Oberflächentexturen in Abhängigkeit von äußeren Einwirkungen durch Klima und Verkehr.
Im Rahmen eines von der Bundesanstalt für Straßenwesen (BASt) geförderten Forschungsvorhabens wurden zunächst die messtechnischen Voraussetzungen für eine hochaufgelöste dreidimensionale Erfassung der Oberflächentopografie von Grinding- und Groovingtexturen in situ geschaffen. Das schließt auch die Entwicklung einer Messanordnung, die eine Wiederholbarkeit der 3D-Messungen gewährleistet und somit die Erfassung der zeitlichen Texturveränderungen ermöglicht. Basierend darauf wurden Auswerteroutinen zur qualitativen und quantitativen Beschreibung der Oberflächentexturen und deren Veränderungen entwickelt und angewandt. Anschließend wurde der Zustand von Grinding- und Groovingtexturen an ausgewählten Praxisstrecken in definierten Zeitintervallen erfasst. Unter Verwendung der erarbeiteten Auswerteroutinen wurden die erfassten Oberflächen analysiert und repräsentative Texturkennwerte abgeleitet.
Simulation-based digital twins have emerged as a powerful tool for evaluating the mechanical response of bridges. As virtual representations of physical systems, digital twins can provide a wealth of information that complements traditional inspection and monitoring data. By incorporating virtual sensors and predictive maintenance strategies, they have the potential to improve our understanding of the behavior and performance of bridges over time. However, as bridges age and undergo regular loading and extreme events, their tructural characteristics change, often differing from the predictions of their initial design. Digital twins must be continuously adapted to reflect these changes. In this article, we present a Bayesian framework for updating simulation-based digital twins in the context of bridges. Our approach integrates information from measurements to account for inaccuracies in the simulation model and quantify uncertainties. Through its implementation and assessment, this work demonstrates the potential for digital twins to provide a reliable and up-to-date representation of bridge behavior, helping to inform decision-making for maintenance and management.
Simulation-based digital twins have emerged as a powerful tool for evaluating the mechanical response of bridges. As virtual representations of physical systems, digital twins can provide a wealth of information that complements traditional inspection and monitoring data. By incorporating virtual sensors and predictive maintenance strategies, they have the potential to improve our understanding of the behavior and performance of bridges over time. However, as bridges age and undergo regular loading and extreme events, their structural characteristics change, often differing from the predictions of their initial design. Digital twins must be continuously adapted to reflect these changes. In this article, we present a Bayesian framework for updating simulation-based digital twins in the context of bridges. Our approach integrates information from measurements to account for inaccuracies in the simulation model and quantify uncertainties. Through its implementation and assessment, this work demonstrates the potential for digital twins to provide a reliable and up-to-date representation of bridge behavior, helping to inform decision-making for maintenance and management.
There is no consensus on which hydration stoppage method is optimal to preserve the microstructure and mineral composition of samples, especially considering the specific aspects of different testing methods, such as TGA, MIP, or XRD. This paper presents a quantitative comparison between the most popular hydration stoppage strategies and parameters such as the sample piece size, the soaking time in a solvent, and the type, as examined on cement paste hydrated for 7 days. It was found that the carbonation appears either for samples smaller than 2.36 mm and bigger than 4.75 mm or samples soaked in a solvent for longer than 1 h. Fast solvent replacement leads to ettringite diminution and total pore volume increase. Among others, solvent replacement with subsequent gentle heating under a vacuum was found to be the most efficient, whereas it was experimentally demonstrated that isopropyl alcohol stops hydration faster than ethanol and acetone.
Liquefied Hydrogen (LH2) or Liquefied Natural Gas (LNG) establish themselves as important energy carriers in the transport sector. Its storage requires tanks with Thermal Super Insulations (TSI) to keep the transported fluid cold. TSI has proven itself in various applications over a long time, but not in the land transport sector, where accidents involving collisions, fires, and their combination are to be expected. The focus of this study is to investigate the behavior of different types of TSI when exposed to a heat source that represents a fire. Therefore, a High-Temperature Thermal Vacuum Chamber (HTTVC) was used that allows the thermal loading of thermal insulation material in a vacuum and measuring the heat flow through the TSI in parallel. Within this study, 5 samples were tested regarding 3 different types of MLI, rock wool, and perlites. The thermal exposure caused different effects on the samples. In practice, this can be connected to the rapid release of flammable gases as well as a Boiling Liquid Expanding Vapour Explosion (BLEVE). These results are relevant for the evaluation of accident scenarios, the improvement of TSI, and the development of emergency measures.
FAIR (findable, accessible, interoperable and reusable) data usage is one of the main principals that many of the research and funding organizations include in their strategic plans, which means that following the main principals of FAIR data is required in many research projects. The definition of data being FAIR is very general, and when implementing that for a specific application or project or even setting a standardized procedure within a working group, a company or a research community, many challenges arise. In this contribution, an overview about our experience with different methods, tools and procedures is outlined.
We begin with a motivation on potential use cases for the applications of FAIR data with increasing complexity starting from a reproducible research paper over collaborative projects with multiple participants such as Round-Robin tests up to data-based models within standardization codes, applications in machine learning or parameter estimation of physics-based simulation models.
In a second part, different options for structuring the data are discussed. On the one hand, this includes a discussion on how to define actual data structures and in particular metadata schema, and on the other hand, two different systems for storing the data are discussed. The first one is the openBIS system, which is an open-source Lab notebook and PostgreSQL based data management system. A second option are a semantic representations using RDF based ontologies for the domain of interest.
In a third section, requirements for workflow tools to automate data processing are discussed and their integration into reproducible data analysis is presented with an outlook on required information to be stored as metadata in the database.
Finally, the presented procedures are exemplarily demonstrated for the calibration of a temperature dependent constitutive model for additively manufactured mortar. Metadata schemata for a rheological measurement setup are derived and implemented in an openBIS database. After a short review of a potential numerical model predicting the structural build-up behaviour, the automatic workflow to use the stored data for model parameter estimation is demonstrated.
Safety characteristics are used to keep processes, including flammable gases, vapors, and combustible dusts, safe. In the standards for the determination of safety characteristics of gases and vapors, the induction spark is commonly used. However, classic transformers are hard to obtain, and replacement with new electronic transformers is not explicitly allowed in the standards. This article presents the investigation of five gases that are normally used to calibrate devices for the determination of safety characteristics, the maximum experimental safe gap (MESG), with an electronic transformer, and the values are compared to the ones that are obtained with the standard transformer. Additionally, calorimetric measurements on the net energy of both ignition sources were performed as well as open-circuit voltage measurements. It is concluded that the classic type of transformer can be replaced by the new type obtaining the same results for the MESG and introducing the same amount of energy into the system.
The hybrid mixture of combustible dusts and flammable gases/vapours widely exist in various industries, including mining, petrochemical, metallurgical, textile and pharmaceutical. It may pose a higher explosion risk than gas/vapor or dust/mist explosions since the hybrid explosions can still be initiated even though both the gas and the dust concentration are lower than their lower explosion limit (LEL) values. Understanding the explosion threat of hybrid mixtures not only contributes to the inherent safety and sustainability of industrial process design, but promotes the efficiency of loss prevention and mitigation. To date, however, there is no test standard with reliable explosion criteria available to determine the safety parameters of all types of hybrid mixture explosions, nor the flame propagation and quenching mechanism or theoretical explanation behind these parameters. This review presents a state-of-the-art overview of the comprehensive understanding of hybrid mixture explosions mainly in an experimental study level; thereby, the main limitations and challenges to be faced are explored. The discussed main contents include the experimental measurement for the safety parameters of hybrid mixtures (i.e., explosion sensitivity and severity parameters) via typical test apparatuses, explosion regime and criterion of hybrid mixtures, the detailed flame propagation/quenching characteristics behind the explosion severities/sensitivities of hybrid mixtures. This work aims to summarize the essential basics of experimental studies, and to provide the perspectives based on the current research gaps to understand the explosion hazards of hybrid mixtures in-depth.