TY - CONF A1 - Kullolli, Borana T1 - A generalized plasticity model adapted for shearing interface problems N2 - The response of many geotechnical systems, whose structural behavior depends on shearing effect, is closely related to soil structure interaction phenomenon. Experimentally it is found that the localisation of these effect happens at a narrow soil layer next to the structure. Numerically, this behavior can be modelled through interface elements and adequate constitutive models. In this work, a constitutive model in the framework of Generalized Plasticity for sandy soils has been chosen to be adapted for the interface zone. From the direct shear experiments a sandy soil at loose and dense states under different normal pressures is considered. The adapted constitutive model is able to reproduce contraction and dilatation of the soil according to its relative density and it shows a good agreement with the experimental data. T2 - Numerical Geotechnics CY - Porto, Portugal DA - 25/06/2018 KW - Interface model KW - Cyclic axial shearing KW - Numerical model PY - 2018 AN - OPUS4-47068 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Eichner, Lukas A1 - Gerards, Paul A1 - Schneider, Ronald A1 - Herrmann, Ralf A1 - Hille, Falk A1 - Baeßler, Matthias T1 - A framework for data and structural integrity management for support structures in offshore wind farms based on building information modelling N2 - Support structures of wind turbines in German offshore wind farms are regularly inspected. Currently, inspection outcomes are generally not systematically recorded. This prevents their consistent handling and processing, which is a key requirement to enable an efficient structural integrity management. As part of the DiMoWind-Inspect project, a data model and reference designation system for such inspection results is developed to facilitate their identification, localization, quantification, tracing and linking throughout the lifetime of a wind farm and beyond. The inspection results together with structural health monitoring results and information on repairs form the basis for assessing and predicting the structural condition, estimating the remaining lifetime, and planning of future inspections, structural health monitoring, and repairs. As a basis for developing a digital structural integrity management, a generic framework is proposed in this paper, which describes the stakeholders, data, models, processes and workflows of the integrity management of support structures in offshore wind farms and their interrelations. The framework adopts a building information modelling approach to describe the information relevant to the structural integrity management. The central digital space of the framework is a common data environment. An implementation of the framework will enable a digital structural integrity management in which inspection, structural health monitoring, repair, assessment and planning outcomes generated throughout the life cycle of a wind farm can be consistently collected, managed, shared and processed by the relevant shareholders. T2 - 8th International Symposium on Reliability Engineering and Risk Management CY - Hannover, Germany DA - 04.09.2022 KW - Offshore wind energy KW - Support structures KW - Building information modelling KW - Structural health monitoring KW - Structural integrity maintenance PY - 2022 AN - OPUS4-55651 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Eichner, Lukas A1 - Gerards, Paul A1 - Herrmann, Ralf A1 - Schneider, Ronald A1 - Hille, Falk A1 - Baeßler, Matthias T1 - A framework for data and structural integrity management for support structures in offshore wind farms based on building information modelling N2 - Support structures of wind turbines in German offshore wind farms are regularly inspected. Currently, inspection outcomes are generally not systematically recorded. This prevents their consistent handling and processing, which is a key requirement to enable an efficient structural integrity management. As part of the DiMoWind-Inspect project, a data model and reference designation system for such inspection results is developed to facilitate their identification, localization, quantification, tracing and linking throughout the lifetime of a wind farm and beyond. The inspection results together with structural health monitoring results and information on repairs form the basis for assessing and predicting the structural condition, estimating the remaining lifetime, and planning of future inspections, structural health monitoring, and repairs. As a basis for developing a digital structural integrity management, a generic framework is proposed in this paper, which describes the stakeholders, data, models, processes and workflows of the integrity management of support structures in offshore wind farms and their interrelations. The framework adopts a building information modelling approach to describe the information relevant to the structural integrity management. The central digital space of the framework is a common data environment. An implementation of the framework will enable a digital structural integrity management in which inspection, structural health monitoring, repair, assessment and planning outcomes generated throughout the life cycle of a wind farm can be consistently collected, managed, shared and processed by the relevant shareholders. T2 - 8th International Symposium on Reliability Engineering and Risk Management CY - Hannover, Germany DA - 04.09.2022 KW - Offshore wind energy KW - support structures KW - structural health monitoring KW - building information modelling KW - structural integrity management PY - 2022 DO - https://doi.org/10.3850/978-981-18-5184-1_MS-04-161-cd SP - 111 EP - 117 PB - Research Publishing CY - Singapore AN - OPUS4-55656 LA - deu AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Gerards-Wünsche, Paul A1 - Ratkovac, Mirjana A1 - Schneider, Ronald A1 - Hille, Falk A1 - Baeßler, Matthias T1 - A framework for assessing the reliability of crack luminescence – an automated fatigue crack detection system N2 - The new crack luminescence method offers the possibility of making fatigue surface cracks in metallic materials more visible during inspections through a special coating system. This coating system consists of two layers, whereby the first layer has fluorescent properties and emits visible light as soon as it is irradiated by UV light. The top layer is black and is designed to prevent the fluorescent layer from emitting if no crack develops in the underlying material. The technique proved particularly useful in a wide variety of fatigue tests of steel components under laboratory conditions. Moreover, it has the potential to be used in various industrial applications. To enable industrial deployment and integration into maintenance strategies, a concept study is developed in this contribution, resulting in a qualification framework that can serve as a foundation for determining the reliability of the crack luminescence system in terms of a probability of detection curve. Within this study, factors causing measurement variability and uncertainty are being determined and their influences assessed. Due to the extension of the system by a moving computer vision system for automated crack detection using artificial intelligence, additional long-term effects associated with structural health monitoring systems need to be incorporated into an extended probability of detection study as part of the technical justification. Finally, important aspects and findings related to design of experiments are discussed, and a framework for reliability assessment of a new optical crack monitoring method is presented, emphasizing the influence of various uncertainty parameters, including long-term effects such as system ageing. T2 - SPIE Conference Smart Structures + Nondestructive Evaluation 2023 CY - Long Beach, CA, USA DA - 24.03.2023 KW - Structural Health Monitoring KW - Non-Destructive Evaluation KW - Probability of Detection KW - Reliability KW - Artificial Intelligence KW - Computer Vision KW - Crack Luminescence PY - 2023 AN - OPUS4-57245 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Gerards-Wünsche, Paul A1 - Ratkovac, Mirjana A1 - Schneider, Ronald A1 - Hille, Falk A1 - Baeßler, Matthias T1 - A framework for assessing the reliability of crack luminescence – an automated fatigue crack detection system N2 - The new crack luminescence method offers the possibility of making fatigue surface cracks in metallic materials more visible during inspections through a special coating system. This coating system consists of two layers, whereby the first layer has fluorescent properties and emits visible light as soon as it is irradiated by UV light. The top layer is black and is designed to prevent the fluorescent layer from emitting if no crack develops in the underlying material. The technique proved particularly useful in a wide variety of fatigue tests of steel components under laboratory conditions. Moreover, it has the potential to be used in various industrial applications. To enable industrial deployment and integration into maintenance strategies, a concept study is developed in this contribution, resulting in a qualification framework that can serve as a foundation for determining the reliability of the crack luminescence system in terms of a probability of detection curve. Within this study, factors causing measurement variability and uncertainty are being determined and their influences assessed. Due to the extension of the system by a moving computer vision system for automated crack detection using artificial intelligence, additional long-term effects associated with structural health monitoring systems need to be incorporated into an extended probability of detection study as part of the technical justification. Finally, important aspects and findings related to design of experiments are discussed, and a framework for reliability assessment of a new optical crack monitoring method is presented, emphasizing the influence of various uncertainty parameters, including long-term effects such as system ageing. T2 - SPIE Conference Smart Structures + Nondestructive Evaluation 2023 CY - Long Beach, CA, USA DA - 24.03.2023 KW - Structural Health Monitoring KW - Non-Destructive Evaluation KW - Probability of Detection KW - Reliability KW - Artificial Intelligence KW - Computer Vision KW - Crack Luminescence KW - Wind PY - 2023 SN - 978-1-5106-6086-1 DO - https://doi.org/10.1117/12.2658390 SP - 1 EP - 15 AN - OPUS4-57244 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Kemmler, Samuel A1 - Cuéllar, Pablo A1 - Köstler, Harald T1 - A Fluid Solid Coupled Micromechanical Simulation of Piping Erosion During the Installation of a Suction Bucket for the Foundation of an Offshore Wind Turbine N2 - We present our approach and methodology for simulating piping erosion, which occurs during the installation process of suction bucket foundations for offshore wind turbines. We show several simulations and analyze the hydrodynamic and contact forces acting on the granular fabric and the differential pressure of the fluid phase. We demonstrate weak scaling performance on the LUMI supercomputer with a parallel efficiency of up to 90% for 4096 Graphics Compute Dies. T2 - 9th European Congress on Computational Methods in Applied Sciences and Engineering (ECCOMAS) CY - Lisbon, Potugal DA - 03.06.2024 KW - Offshore wind turbine KW - Suction bucket KW - Coupled fluid-particle simulation KW - High-performance computing PY - 2024 AN - OPUS4-60207 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Simon, Patrick A1 - Schneider, Ronald A1 - Baeßler, Matthias A1 - Morgenthal, Guido ED - Cha, Young-Jin T1 - A Bayesian Probabilistic Framework for Building Models for Structural Health Monitoring of Structures Subject to Environmental Variability N2 - Managing aging engineering structures requires damage identification, capacity reassessment, and prediction of remaining service life. Data from structural health monitoring (SHM) systems can be utilized to detect and characterize potential damage. However, environmental and operational variations impair the identification of damages from SHM data. Motivated by this, we introduce a Bayesian probabilistic framework for building models and identifying damage in monitored structures subject to environmental variability. The novelty of our work lies (a) in explicitly considering the effect of environmental influences and potential structural damages in the modeling to enable more accurate damage identification and (b) in proposing a methodological workflow for model‐based structural health monitoring that leverages model class selection for model building and damage identification. The framework is applied to a progressively damaged reinforced concrete beam subject to temperature variations in a climate chamber. Based on deflections and inclinations measured during diagnostic load tests of the undamaged structure, the most appropriate modeling approach for describing the temperature‐dependent behavior of the undamaged beam is identified. In the damaged state, damage is characterized based on the identified model parameters. The location and extent of the identified damage are consistent with the cracks observed in the laboratory. A numerical study with synthetic data is used to validate the parameter identification. The known true parameters lie within the 90% highest density intervals of the posterior distributions of the model parameters, suggesting that this approach is reliable for parameter identification. Our results indicate that the proposed framework can answer the question of damage identification under environmental variations. These findings show a way forward in integrating SHM data into the management of infrastructures. KW - Verkehrsinfrastukturen KW - SHM KW - Model Updating KW - Environmental and Operational Variability KW - Damage Identification KW - Model Building PY - 2024 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-605027 DO - https://doi.org/10.1155/2024/4204316 VL - 2024 IS - 1 SP - 1 EP - 23 PB - Wiley AN - OPUS4-60502 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Sadowski, A. A1 - Seidel, M. A1 - Al-Lawati, H. A1 - Azizi, E. A1 - Balscheit, Hagen A1 - Böhm, M. A1 - Chen, Lei A1 - van Dijk, I. A1 - Doerich-Stavridis, C. A1 - Kunle Fajuyitan, O. A1 - Filippidis, A. A1 - Winther Fischer, A. A1 - Fischer, C. A1 - Gerasimidis, S. A1 - Karampour, H. A1 - Kathirkamanathan, L. A1 - Subramanian, S. A1 - Topkaya, Cem A1 - Wagner, H. N. R. A1 - Wang, J. A1 - Wang, J. A1 - Kumar Yadav, K. A1 - Yun, X. A1 - Zhang, P. T1 - 8-MW wind turbine tower computational shell buckling benchmark - Part 1: An international ‘round-robin’ exercise N2 - An assessment of the elastic-plastic buckling limit state for multi-strake wind turbine support towers poses a particular challenge for the modern finite element analyst, who must competently navigate numerous modelling choices related to the tug-of-war between meshing and computational cost, the use of solvers that are robust to highly nonlinear behaviour, the potential for multiple near-simultaneously critical failure locations, the complex issue of imperfection sensitivity and finally the interpretation of the data into a safe and economic design. This paper reports on an international ‘round-robin’ exercise conducted in 2022 aiming to take stock of the computational shell buckling expertise around the world which attracted 29 submissions. Participants were asked to perform analyses of increasing complexity on a standardised benchmark of an 8-MW multi-strake steel wind turbine support tower segment, from a linear elastic stress analysis to a linear bifurcation analysis to a geometrically and materially nonlinear buckling analysis with imperfections. The results are a showcase of the significant shell buckling expertise now available in both industry and academia. This paper is the first of a pair. The second paper presents a detailed reference solution to the benchmark, including an illustration of the Eurocode-compliant calibration of two important imperfection forms. KW - Wind turbine tower KW - Computational KW - Shell buckling KW - Benchmark PY - 2023 DO - https://doi.org/10.1016/j.engfailanal.2023.107124 SN - 1350-6307 VL - 148 SP - 1 EP - 23 PB - Elsevier Science CY - Oxford AN - OPUS4-57019 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Zinas, Orestis T1 - 3D Probabilistic Site Characterization N2 - The aim of the study is to infer the soil stratification from the provided CPT and borehole data. We infer the soil type at any location within the domain of interest from the SBT index Ic (Robertson, 2009). This index can be directly related to the CPT data through an empirical correlation model. In addition, the soil classes contained in the borehole logs can be expressed as bounds on Ic. A log-transformation was applied to Ic, Y = ln(Ic), and Y was modelled by a 3D Random Field, with a fully Bayesian hierarchical Gaussian Process model to explicitly capture uncertainties. T2 - 19th eawe PhD Seminar CY - Hannover, Germany DA - 06.09.2023 KW - Wind Energy KW - Site-characterization KW - Probabilistic PY - 2023 AN - OPUS4-58940 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER -