7 Bauwerkssicherheit
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- 2024 (53) (entfernen)
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- Flame retardancy (5)
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- 7 Bauwerkssicherheit (53)
- 7.4 Baustofftechnologie (13)
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- 7.7 Modellierung und Simulation (9)
- 7.6 Korrosion und Korrosionsschutz (6)
- 8 Zerstörungsfreie Prüfung (6)
- 7.1 Baustoffe (5)
- 2 Prozess- und Anlagensicherheit (2)
- 2.4 Prüfung und Bewertung von Explosivstoffen/Pyrotechnik (2)
Paper des Monats
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This presentation discusses the potentials of probabilistic methods in offshore foundation installation, from the perspective of probabilistic ground models and data-driven site characterization. We discuss about methodologies for utilizing site-specific geotechnical (CPT) and geological data, aiming to construct an integrated ground model that can predict stratigraphic profiles and useful for geotechnical design parameters at any location within a 3D domain. The predicted parameters and stratigraphy are then used to predict the probability of potential pile tip damage, upon collision with a boulder.
Maritime exposure poses particular challenges for corrosion
protection in plant construction. In addition to the right choice
of materials, special design features that can have an impact
on corrosion resistance must also be taken into account to
ensure long-lasting corrosion protection. In practice, structural
crevice arrangements are unavoidable, and therefore the
crevice corrosion resistances of stainless steels are of
particular importance. These and other influences are being
investigated in this joint project.
EPDM, HNBR and FKM materials were exposed at 150 ◦C to air under atmospheric pressure and to hydrogen at 50 bar for different ageing times. All measurements after hydrogen exposure were conducted on samples in degassed condition to assess irreversible effects resulting from that exposure and to compare them to those after ageing in air. Density, hardness, tensile properties, compression set, and hydrogen permeability of all samples were analysed. In both ageing environments, HNBR exhibited the most significant changes of material properties.
However, for both EPDM and HNBR, considerably less severe ageing effects were observed under hydrogen in comparison to ageing in air. On the other hand, FKM showed about the same low level of deterioration in both ageing environments but exhibited poor resistance against damage due to rapid gas decompression in hydrogen environment that can lead to seal failure. The obtained results may serve as a guidance toward a better understanding for design and utilisation of elastomeric materials in future hydrogen infrastructure components.
We introduce a novel adaptive Gaussian Process Regression (GPR) methodology for efficient construction of surrogate models for Bayesian inverse problems with expensive forward model evaluations. An adaptive design strategy focuses on optimizing both the positioning and simulation accuracy of training data in order to reduce the computational cost of simulating training data without compromising the fidelity of the posterior distributions of parameters. The method interleaves a goal-oriented active learning algorithm selecting evaluation points and tolerances based on the expected impact on the Kullback-Leibler divergence of surrogated and true posterior with a Markov Chain Monte Carlo sampling of the posterior. The performance benefit of the adaptive approach is demonstrated for two simple test problems.
The presentations discusses a use case for the optimization of concrete structures where structural and material design are integrated in a computational workflow. The workflow is based on both physics-based and data-based models and experimental data is used to calibrate/train these models with a specific focus on the integration of ucertainties.
The development of standards that include simulation models is often based on heuristics that include experimental data that is used to calibrate and validate the simulation models. However, these data and the corresponding calibration procedures are usually not part of the publicly accessible documentation making it very difficult to identify gaps in the current standard or extend it to new innovative solutions. The poster shows an adapted procedure that integrates the complete process into a database and a workflow to be published alongside the standard.
The dripping behaviour of polymers is often observed experimentally through the UL94 flammability standard test. In this work, polymeric dripping under fire is investigated numerically using particle finite element method. A parametric analysis was carried out to observe the influence of a single property on overall dripping behaviour via a UL94 vertical test model. Surrogates and property ranges were defined for variation of the following parameters: glass transition temperature (Tg), melting temperature (Tm), decomposition temperature (Td), density (ρ), specific heat capacity (Cp), apparent effective heat of combustion of the volatiles, char yield (μ), thermal conductivity (k), and viscosity (η). Polyamide, poly(ether ether ketone), poly(methyl methacrylate), and polysulfone were used as benchmarks. Simulated results showed that specific heat capacity, thermal conductivity, and char yield allied with viscosity were the properties that most influenced dripping behaviour (starting time and occurrence).
The output of C&D waste is increasing year by year, among which low-quality recycled brick aggregates (RBAs) have not been well utilized and brought environmental burden. The durability of steam-cured concrete (HCC) is often compromised due to the detrimental effects of this curing regime on the long-term performance and microstructure development of the concrete material. To address this issue, this study investigates the potential of incorporating RBAs to improve the long-term durability of HCC. The results demonstrate that the incorporation of a small amount of RBA (10–20%) not only enhances the 28-d strength of HCC by 2.5–11.3%, but also improves its impermeability by mitigating heat damage effects. The combined application of fine and coarse RBA was found to effectively balance the negative effects of coarse RBA on the performance of HCC. Furthermore, the utilization of RBA in HCC was shown to have economic and environmental benefits. The results of this study demonstrate a simple and effective approach to improve the long-term durability of HCC while promoting the high-value utilization of solid waste.
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.
Despite the advances in hardware and software techniques, standard numerical methods fail in providing real-time simulations, especially for complex processes such as additive manufacturing applications. A real-time simulation enables process control through the combination of process monitoring and automated feedback, which increases the flexibility and quality of a process. Typically, before producing a whole additive manufacturing structure, a simplified experiment in the form of a beadon-plate experiment is performed to get a first insight into the process and to set parameters suitably. In this work, a reduced order model for the transient thermal problem of the bead-on-plate weld simulation is developed, allowing an efficient model calibration and control of the process. The proposed approach applies the proper generalized decomposition (PGD) method, a popular model order reduction technique, to decrease the computational effort of each model evaluation required multiple times in parameter estimation, control, and optimization. The welding torch is modeled by a moving heat source, which leads to difficulties separating space and time, a key ingredient in PGD simulations. A novel approach for separating space and time is applied and extended to 3D problems allowing the derivation of an efficient separated representation of the temperature.
The results are verified against a standard finite element model showing excellent agreement. The reduced order model is also leveraged in a Bayesian model parameter estimation setup, speeding up calibrations and ultimately leading to an optimized real-time simulation approach for welding experiment using synthetic as well as real measurement data.