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Organisationseinheit der BAM
- 7 Bauwerkssicherheit (713) (entfernen)
Paper des Monats
- ja (2)
The corrosion behavior of galvanized steels and zinc components under atmospheric exposure depends mostly on the corrosion product‐based cover layer formation under the prevailing conditions. The use of agar‐based gel electrolytes makes it possible to use electrochemical methods to obtain a characteristic value from these cover layers that describe their current and future protective capacity. It is shown here that different states of galvanized steel can be distinguished very well under laboratory conditions and that this method is also suitable for use under practical conditions. Based on the characteristic values and assuming future time of wetness, it is very easy to draw up a forecast for the future corrosion rate, which provides plausible values.
While alkali-activated binders offer certain advantages over traditional Portland cement binders, particu¬larly in terms of resistance against chemical attacks and potentially environmental footprint, their degra¬dation mechanisms remain incompletely understood at present, specifically carbonation. Thus, this study investigates the impact of natural and accelerated carbonation (1% and 4% CO2) on three different compositions of alkali-activated concretes: 100% calcined clay (C100) binder, 100% ground blast furnace slag (S100) binder, and a 40% calcined clay and 60% blast furnace slag blend (C40S60). C100 concretes exhibit faster carbonation kinetics, with five times greater natural carbonation depths than S100. This difference diminishes under accelerated carbonation, showing a 1.5 times difference for 1% CO2 and complete carbonation for 4% CO2 at 90 days. The results thus confirm that accelerated carbonation testing of low-Ca alkali-activated concretes yields results that are not representative of natural carbonation. The C40S60 sample demonstrates a carbonation profile similar to a CEM I concrete, i.e., a high carbonation resistance. Microstructure analysis indicates the formation of three polymorphs of calcium carbonate for S100 (calcite, vaterite, and aragonite), with a higher CO2 concentration favouring aragonite over vaterite. C100 exhibits no calcium carbonates; instead, sodium carbonates form, including trona for 4% CO2 and natrite for both accelerated tests. C40S60 shows calcium and sodium carbonates, although to a lesser extent, containing predominantly calcite and minor signals of natrite. Suitable compositions, like C40S60, prove as effective during natural or accelerated carbonation tests as conventional Portland cement concrete.
Esta pesquisa avaliou o fenômeno de autocicatrização nas propriedades mecânicas e absorção capilar de concretos estruturais. Foram avaliados dois aditivos cristalizantes em pó, dosados de acordo com o teor recomendado pelos fabricantes. Aditivos cristalizantes aumentam a densidade do gel C-S-H e formam cristais insolúveis, bloqueando fissuras. Três traços de concreto foram produzidos: referência, aditivo-X com 0,8% e aditivo-Y com 2,0% em relação a massa do cimento. Aplicou-se 75% da carga de ruptura aos 3- e 14-dias para gerar microfissuras e comparar com a referência. Posteriormente, a autocicatrização foi avaliada aos 28- e 76-dias. A propriedade de resistência à compressão axial foi determinada aos 28-dias, revelando que os aditivos cristalizantes contribuíram para um aumento médio de 12% desta propriedade. A idade do carregamento dos concretos não apresentou um impacto significativo na resistência à compressão axial, mas apontou resultados significativos entre os tipos de aditivos estudados, conforme ANOVA. As propriedades de absorção de água por capilaridade foram avaliadas aos 28- e 76-dias, indicando uma redução de absorção de água média de 42% devido ao uso dos aditivos cristalizantes. Em conclusão, a incorporação dos aditivos cristalizantes contribuiu de maneira positiva para a autocicatrização dos concretos estudados, indicando uma recuperação parcial das microfissuras.
Weltweit stellen Waldbrände eine große Bedrohung für Umwelt, Wirtschaft und menschliches Leben dar. Der fortschreitende Klimawandel verstärkt Trockenheit und Dürre, wodurch die Größe und Intensität von Waldbränden sowie das daraus resultierende Gefahrenpotential zusätzlich erhöht werden. Um im Risikofall eine schnelle und effektive Waldbrandbekämpfung zu gewährleisten, sollen Einsatzkräfte in Zukunft von KI-basierten Ausbreitungsmodellen unterstützt werden.
Der Einsatz von maschinellem Lernen ermöglicht dabei schnelle und zielgerichtete Ausbreitungsvorhersagen in Echtzeit, die in den Prozess der Brandbekämpfung als zusätzliche Information einfließen können. Im Rahmen des durch das EU-Förderprogram Horizon 2020 finanzierte Projekt TREEADS wird ein solches Modell für Europa entwickelt.
Dazu wird mit verschiedenen Satellitendaten des Copernicus-Programms und der NASA ein auf räumlicher und zeitlicher Ebene aufgelöster Datensatz zu europäischen Waldbränden aufgebaut. Zu den erfassten Waldbränden werden wichtigen Faktoren, die Einfluss auf die Brandausbreitung haben, ergänzt. Dazu gehören das von Copernicus bereitgestellte, digitale Geländemodell Europas und verschiedene, von Sentinel-2 Messungen abgeleitete Informationen zu Vegetation und Landnutzung. Dieser 2D-Trainingsdatensatz zu realen Waldbränden wird durch die zeitlich hochaufgelösten, meteorologischen Reanalyse-Produkte – Copernicus European Regional ReAnalysis (CERRA) und ERA5-Land – vervollständigt und ist die Grundlage für ein Modell zur Ausbreitungsvorhersage von Waldbränden.
Methoden des Maschinellen Lernens können komplexe Muster in den gesammelten Daten erkennen und so zu einer verbesserten Vorhersage der Brandausbreitung beitragen. Die vielfältigen, von Copernicus bereitgestellten Daten sind dabei ein unabdingbarer Bestandteil des Modells, mit dem den Einsatzkräften ein zusätzliches Tool für den effizienten Einsatz ihrer limitierten Ressourcen zur Verfügung steht.
Die Umweltwirkungen auf ein Material werden als Überlapp der Funktionskurven von Materialempfindlichkeit und einwirkenden Umweltparametern betrachtet. Wenn entweder die Empfindlichkeit oder die Beanspruchungen Null sind, ergibt sich auch keine Umweltwirkung und bei beidseitig Werten größer Null das jeweilige Produkt der beiden. Die Akkumulation der nicht-reversiblen Effekte über die Zeit und allen Eigenschaftsänderungen entspricht der Alterung des Materials für den jeweiligen Expositionszeitraum.
Die digitale Umweltsimulation gliedert sich hier in drei Teilaspekte. Ein erster, rein materialwissenschaftlicher Teil hat die Aufgabe, alle relevanten Materialempfindlichkeiten experimentell zu quantifizieren. Ein zweiter – unter Umständen numerischer Teil – hat die Aufgabe, das Bauteil und seine Einbaulage zu digitalisieren und aus den makroskopischen Umgebungsbedingungen die relevanten mikroklimatischen Umweltparameter für alle Oberflächen- oder Volumenelemente zu bestimmen. In einem dritten Teil werden die Einwirkungen über den betrachteten Zeitraum berechnet und kumuliert. Dieses Konzept, das auf den so genannten Expositions-Reaktions-Funktionen (ERF) basiert, wird an Beispielen der Photoxidation erläutert. Dieses Vorgehen wurde schon beim ViPQuali-Projekt als Numerische Umweltsimulation umgesetzt.
Überprüft werden muss das Modell unbedingt an einer realitätsnahen Validierungsbeanspruchung. Hier werden die ermittelten ERFs mit über den kompletten Beanspruchungszeitraum geloggten Umweltparametern gekoppelt, um die berechnete mit der experimentell erfahrenen Alterungswirkung zu vergleichen. Nur so kann sichergestellt sein, dass alle für die Anwendungsumgebung relevanten Materialempfindlichkeiten einbezogen wurden.
In the field of computational science and engineering, workflows often entail the application of various software, for instance, for simulation or pre- and postprocessing. Typically, these components have to be combined in arbitrarily complex workflows to address a specific research question. In order for peer researchers to understand, reproduce and (re)use the findings of a scientific publication, several challenges have to be addressed. For instance, the employed workflow has to be automated and information on all used software must be available for a reproduction of the results. Moreover, the results must be traceable and the workflow documented and readable to allow for external verification and greater trust. In this paper, existing workflow management systems (WfMSs) are discussed regarding their suitability for describing, reproducing and reusing scientific workflows. To this end, a set of general requirements for WfMSswere deduced from user stories that we deem relevant in the domain of computational science and engineering. On the basis of an exemplary workflow implementation, publicly hosted at GitHub (https:// this http URL), a selection of different WfMSs is compared with respect to these requirements, to support fellow scientists in identifying the WfMSs that best suit their requirements.
Multiscale modeling of linear elastic heterogeneous structures via localized model order reduction
(2024)
In this paper, a methodology for fine scale modeling of large scale linear elastic structures is proposed, which combines the variational multiscale method, domain decomposition and model order reduction. The influence of the fine scale on the coarse scale is modelled by the use of an additive split of the displacement field, addressing applications without a clear scale separation. Local reduced spaces are constructed bysolving an oversampling problem with random boundary conditions. Herein, we inform the boundary conditions by a global reduced problem and compare our approach using physically meaningful correlated samples with existing approaches using uncorrelated samples. The local spaces are designed such that the local contribution of each subdomain can be coupled in a conforming way, which also preserves the sparsity pattern of standard finite element assembly procedures. Several numerical experiments show the accuracy and efficiency of the method, as well as its potential to reduce the size of the local spaces and the number of training samples compared to the uncorrelated sampling
Die Umweltwirkungen auf ein Material werden als Überlapp der Funktionskurven von Materialempfindlichkeit und einwirkenden Umweltparametern betrachtet. Wenn entweder die Empfindlichkeit oder die Beanspruchungen Null sind, ergibt sich auch keine Umweltwirkung und bei beidseitig Werten größer Null das jeweilige Produkt der beiden. Die Akkumulation der nicht-reversiblen Effekte über die Zeit und allen Eigenschaftsänderungen entspricht der Alterung des Materials für den jeweiligen Expositionszeitraum.
Die digitale Umweltsimulation gliedert sich hier in drei Teilaspekte. Ein erster, rein materialwissenschaftlicher Teil hat die Aufgabe, alle relevanten Materialempfindlichkeiten experimentell zu quantifizieren. Ein zweiter – unter Umständen numerischer Teil – hat die Aufgabe, das Bauteil und seine Einbaulage zu digitalisieren und aus den makroskopischen Umgebungsbedingungen die relevanten mikroklimatischen Umweltparameter für alle Oberflächen- oder Volumenelemente zu bestimmen. In einem dritten Teil werden die Einwirkungen über den betrachteten Zeitraum berechnet und kumuliert. Dieses Konzept, das auf den so genannten Expositions-Reaktions-Funktionen (ERF) basiert, wird an Beispielen der Photoxidation erläutert. Dieses Vorgehen wurde schon beim ViPQuali-Projekt als Numerische Umweltsimulation umgesetzt.
Überprüft werden muss das Modell unbedingt an einer realitätsnahen Validierungsbeanspruchung. Hier werden die ermittelten ERFs mit über den kompletten Beanspruchungszeitraum geloggten Umweltparametern gekoppelt, um die berechnete mit der experimentell erfahrenen Alterungswirkung zu vergleichen. Nur so kann sichergestellt sein, dass alle für die Anwendungsumgebung relevanten Materialempfindlichkeiten einbezogen wurden.
Derzeit ist die Instandhaltung von großen Betontragwerken wie Brücken oder Windenergieanlagen problemorientiert und von einem reaktiven Vorgehen geprägt. Das bedeutet, erst wenn sichtbare Schäden vorliegen, werden diese meist unter Beeinträchtigung des Betriebs instand gesetzt. Im Hinblick auf die Entwicklung von prädiktiven Instandhaltungsstrategien, deren Fokus in der langfristigen Bauwerksüberwachung und der Vorhersage von Schädigungsentwicklungen liegt, wurde die Anwendung von Ultraschallverfahren für die Identifizierung der Degradationsprozesse von Betontragwerken unter Ermüdungsbeanspruchung untersucht. Hierzu fanden Arbeiten im vom Bundesministerium für Wirtschaft und Klimaschutz (BMWK) geförderten Verbundprojekt WinConFat zum "Einfluss der Probengeometrie und -größe auf die Ermüdung von Beton" an der Bundesanstalt für Materialforschung und -prüfung (BAM) und zu den "Methoden zur Zustandsanalyse von Windenergieanlagen" am Institut für Massivbau (IfMa) der Leibniz Universität Hannover (LUH) statt, welches zudem vom Deutschen Beton- und Bautechnik Verein e.V. (Forschungsvorhaben DBV-311) gefördert wurde. Dabei wurden verschiedene Einflussfaktoren auf die Schädigungsentwicklung unter Ermüdungsbeanspruchung wie die Probekörpergröße, das Belastungsniveau und die Betonfestigkeit untersucht. Als Schädigungsindikator und Vergleichsparameter wurden die Ultraschallgeschwindigkeit und der dynamische E-Modul des Betons verwendet. Um das Potential der Schädigungserfassung im Beton mittels Ultraschallprüfung umfassender zu bewerten, wurden zusätzlich Versuche an Betonproben unter monoton steigender Belastung, Kriechversuche, Temperaturversuche und Untersuchungen an großformatigen Balken durchgeführt.
Thermal transient problems, essential for modeling applications like welding and additive metal manufacturing, are characterized by a dynamic evolution of temperature. Accurately simulating these phenomena is often computationally expensive, thus limiting their applications, for example for model parameter estimation or online process control. Model order reduction, a solution to preserve the accuracy while reducing the computation time, is explored. This article addresses challenges in developing reduced order models using the proper generalized decomposition (PGD) for transient thermal problems with a specific treatment of the moving heat source within the reduced model. Factors affecting accuracy, convergence, and computational cost, such as discretization methods (finite element and finite difference), a dimensionless formulation, the size of the heat source, and the inclusion of material parameters as additional PGD variables are examined across progressively complex examples. The results demonstrate the influence of these factors on the PGD model’s performance and emphasize the importance of their consideration when implementing such models. For thermal example, it is demonstrated that a PGD model with a finite difference discretization in time, a dimensionless representation, a mapping for a moving heat source, and a spatial domain non-separation yields the best approximation to the full order model.