7.7 Modellierung und Simulation
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- Structural build-up (2)
- 3D concrete printing (1)
- Bayesian Uncertainty Quantification (1)
- Beton (1)
- Brückenmonitoring (1)
- Concrete (1)
- Continnum damage model (1)
- Damage (1)
- Data provenance (1)
- Datenmanagement (1)
Organisationseinheit der BAM
Die sprunghaft zunehmende Wichtigkeit von FAIR- und Open-Data für die Qualitätssicherung, aber auch für die Nachnutzbarkeit von Daten und den Erkenntnisfortschritt führt zu enormem Flandlungsbedarf in Forschung und Entwicklung. Damit verbunden laufen derzeit vielfältige, ambitionierte Aktionen, z. B. bezüglich der Erstellung von Ontologien und Wissensgraphen. Das Knowhow entwickelt sich rasant, die Ansätze zur Implementation entstehen in verschiedenen Fachwelten bzw. mit
unterschiedlichen Zielsetzungen parallel, so dass recht heterogene Herangehensweisen resultieren.
Diese Veröffentlichung fokussiert auf Arbeiten, die derzeit als möglichst ganzheitlicher Ansatz für Materialdaten im Rahmen der Digitalisierungsinitiative „Plattform MaterialDigital" vorangetrieben werden. Die Autoren bearbeiten baustoffbezogene Aspekte im Verbundprojekt „LeBeDigital - Lebenszyklus von Beton". Zielsetzung ist die digitale Beschreibung des Materialverhaltens von Beton über den kompletten Herstellungsprozess eines Fertigteils mit einer Integration von Daten und Modellen innerhalb eines Workflows zur probabilistischen Material- und Prozessoptimierung.
Es wird über die Vorgehensweise und die dabei gewonnenen Erfahrungen berichtet, nicht ohne den Blick auf die oft unterschätzte Komplexität der Thematik zu lenken.
In recent years, the use of simulation-based digital twins for monitoring and assessment of complex mechanical systems has greatly expanded. Their potential to increase the information obtained from limited data makes them an invaluable tool for a broad range of real-world applications. Nonetheless, there usually exists a discrepancy between the predicted response and the measurements of the system once built. One of the main contributors to this difference in addition to miscalibrated model parameters is the model error. Quantifying this socalled model bias (as well as proper values for the model parameters) is critical for the reliable performance of digital twins. Model bias identification is ultimately an inverse problem where information from measurements is used to update the original model. Bayesian formulations can tackle this task. Including the model bias as a parameter to be inferred enables the use of a Bayesian framework to obtain a probability distribution that represents the uncertainty between the measurements and the model. Simultaneously, this procedure can be combined with a classic parameter updating scheme to account for the trainable parameters in the original model.
This study evaluates the effectiveness of different model bias identification approaches based on Bayesian inference methods. This includes more classical approaches such as direct parameter estimation using MCMC in a Bayesian setup, as well as more recent proposals such as stat-FEM or orthogonal Gaussian Processes. Their potential use in digital twins, generalization capabilities, and computational cost is extensively analyzed.
Structural build-up describes the stability and early-age strength development of fresh mortar used in 3D printing. lt is influenced by several factors, i.e. the composition of the print able material, the printing regime, and the ambient conditions. The existing modelling approaches for structural build-up usually define the model parameters for a specific material composition with out considering the influence of the ambient conditions. The goal of this contribution is to explicitly include the temperature dependency in the modelling approach. Temperature changes have signifi cant impact on the structural build-up process: an increase of the temperature leads to a faster dissol ution of cement phases and accelerates hydration. The proposed extended model includes temperature dependency using the Arrhenius theory. The new model parameters are successfully calibrated based on Viskomat measurement data using Bayesian inference. Furthermore, a higher impact of the temperature in the re-flocculation as in the structuration stage is observed.
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.
With increasing focus on industrialized processing, investigating, understanding, and modelling the structural build-up of cementitious materials becomes more important. The structural build-up governs the key property of fresh printable materials -- buildability -- and it influences the mechanical properties after the deposition. The structural build-up rate can be adjusted by optimization of the mixture composition and the use of concrete admixtures. Additionally, it is known, that the environmental conditions, i.e. humidity and temperature have a significant impact on the kinetic of cement hydration and the resulting hardened properties, such as shrinkage, cracking resistance etc. In this study, small amplitude oscillatory shear (SAOS) tests are applied to examine the structural build-up rate of cement paste subject to different temperatures under controlled humidity. The results indicate significant influences of the ambient temperature on the intensity of the re-flocculation (Rthix) rate, while the structuration rate (Athix) is almost not affected. A bi-linear thixotropy model extended by temperature dependent parameters coupled with a linear viscoelastic material model is proposed to simulate the mechanical behaviour considering the structural build-up during the SAOS test
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. The model is designed to represent failure under static loading as a particular case of fatigue failure after a single loading cycle. As a consequence, most of the material parameters can be deduced from statictests. Only a limit set of additional constitutive parameters is required to accurately describe the evolution under fatigue loading. Another advantage of the proposed model is the possibility to directly incorporate other multi-physics effects such as creep and shrinkage or thermal loading on the constitutive level. 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 implicit and explicit time integration schemes. Their performance and some limitations for specific loading regimes is discussed.
Lifetime aspects including fatigue failure of concrete structures were traditionally only of minor importance. Because of the growing interest in maxing out the capacities of concrete, its fatigue failure under compression has become an issue. A variety of interacting phenomena such as e.g. loss of prestress, degradation due to chemical reactions or creep and shrinkage influence the fatigue resistance. Failure due to cyclic loads is generally not instantaneous, but characterized by a steady damage accumulation. Therefore, a reliable numerical model to predict the performance of concrete over its lifetime is required, which accurately captures order effects and full three-dimensional stress states.
Many constitutive models for concrete are currently available, which are applicable for specific loading regimes, different time scales and different resolution scales.
However, a key limitation of those models is that they generally 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. This is due to the computational effort necessary to explicitly resolve every cycle which exceeds the currently available computational resources. The limitation can only be overcome by the application of multiscale methods in time.
The objective of the paper is the development of numerical methods for the simulation of concrete under fatigue loading using temporal multiscale methods.
First, a continuum damage model for concrete is developed with a focus on fatigue under compressive stresses [1]. 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. The model is designed to represent failure under static loading as a particular case of fatigue failure after a single loading cycle. As a consequence, most of the material parameters can be deduced from static tests. Only a limit set of additional constitutive parameters is required to accurately describe the evolution under fatigue loading. Another advantage of the proposed model is the possibility to directly incorporate other multi-physics effects such as creep and shrinkage or thermal loading on the constitutive level.
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 [2]. This evolution equation is then solved on the long time scale using different implicit and explicit time integration schemes. Their performance and some limitations for specific loading regimes is discussed.
Finally, the developed methods will be validated and compared to experimental data.
[1] Vitaliy Kindrachuk, Marc Thiele, Jörg F. Unger. Constitutive modeling of creep-fatigue interaction for normal strength concrete under compression, International Journal of Fatigue, 78:81-94, 2015
[2] Vitaliy Kindrachuk, Jörg F. Unger. A Fourier transformation-based temporal integration scheme for viscoplastic solids subjected to fatigue deterioration, International Journal of Fatigue, 100:215-228, 2017
Die Brücken im Netz der Bundesverkehrswege sind überwiegend in einem ausreichenden bis guten Zustand. Allerdings steigt der Unterhalts- und Sanierungsaufwand aufgrund des inzwischen hohen Alters vieler Brücken sowie des ständig wachsenden Schwerlastverkehrs. Techniken zur Einschätzung der verbleibenden Lebensdauer von Brücken sowie zur dauerhaften Beobachtung des Tragverhaltens bzw. des Erfolges von Sanierungsmaßnahmen werden daher für den sicheren und wirtschaftlichen Betrieb dringend benötigt. Zur Evaluierung dafür geeigneter holistischer Ansätze wurde in der BAM das Projekt BLEIB - Bewertung, Lebensdauerprognose und Instandsetzung von Brückenbauwerken - ins Leben gerufen.
Ein zentrales Ergebnis des Projektes ist eine extern vorgespannte Stahlbetonbrücke als Zweifeldträger mit einer Gesamtlänge von 24 m, die für den Test verschiedenster Sensorsysteme, zur Validierung numerischer Modelle und zur Erprobung von Sanierungs- und Verstärkungsmaßnahmen entwickelt wurde. Für die Simulation unterschiedlicher Schädigungsgrade kann die Vorspannung der Brücke variiert werden. Die Brücke wird mit beweglichen Gewichten belastet und über einen Shaker zum Schwingen angeregt.
Das Brückenmodell wurde bewusst geschädigt, indem die Vorspannung der Struktur erstmalig schrittweise bis auf null reduziert wurde. Unter der Eigenlast verformte sich die Brücke, wodurch eine Rissbildung im Beton einsetzte. Die Zugspannung, die zuvor durch die Vorspannung aufgenommen wurde, übernahm Schritt für Schritt der Beton. Als die Zugspannungen die relativ geringe Zugfestigkeit des Betons überstiegen, begann dieser zu reißen und die schlaffe Bewehrung der Struktur nahm die Spannungen auf. Dieser Versuch wurde unter anderem von Schallemissionsmessungen begleitet. Der Rissbildungsprozess konnte damit, bei gleichzeitiger Aufzeichnung der Vorspannung, früh detektiert und die Risse geortet werden. Die Ergebnisse korrelieren gut mit den Ergebnissen der stereophotogrammetrischen Verformungsmessungen der Struktur.