TY - JOUR A1 - Benseghier, Z. A1 - Luu, L.-H. A1 - Cuéllar, Pablo A1 - Bonelli, S. A1 - Philippe, P. T1 - On the erosion of cohesive granular soils by a submerged jet: a numerical approach JF - Granular Matter N2 - This paper presents an erosion interpretation of cohesive granular materials stressed by an impinging jet based on the results of a micromechanical simulation model. The numerical techniques are briefly described, relying on a two-dimensional Lattice Boltzmann Method coupled with a Discrete Element Methods including a simple model of solid intergranular cohesion. These are then used to perform a parametric study of a planar jet in the laminar regime impinging the surface of granular samples with different degrees of cohesive strength. The results show the pertinence of using a generalized form of the Shields criterion for the quantification of the erosion threshold, which is valid for cohesionless samples, through empirical calibration, and also for cohesive ones. Furthermore, the scouring kinetics are analysed here from the perspective of a selfsimilar expansion of the eroded crater leading to the identification of a characteristic erosion time and the quantification of the classical erosion coefficient. However, the presented results also challenge the postulate of a local erosion law including erodibility parameters as intrinsic material properties. The paper then reviews the main limitations of the simulation and current interpretation models, and discusses the potential causes for the observed discrepancies, questioning the pertinence of using time-averaged macroscopic relations to correctly describe soil erosion. The paper concludes addressing this question with a complementary study of the presented simulations re-assessed at the particle-scale. The resulting local critical shear stress of single grains reveals a very wide dispersion of the data but nevertheless appears to confirm the general macroscopic trend derived for the cohesionless samples, while the introduction of cohesion implies a significant but systematic quantitative deviation between the microscopic and macroscopic estimates. Nevertheless, the micro data still shows consistently that the critical shear stress does actually vary approximately in linear proportion of the adhesive force. KW - Soil erosion KW - Granular cohesion KW - Lattice Boltzmann Method KW - Discrete Element Method KW - Impinging jet PY - 2023 DO - https://doi.org/10.1007/s10035-022-01289-5 VL - 25 IS - 8 SP - 1 EP - 20 PB - Springer AN - OPUS4-56525 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Eichner, Lukas A1 - Schneider, Ronald A1 - Baeßler, Matthias T1 - Optimal vibration sensor placement for jacket support structures of offshore wind turbines based on value of information analysis JF - Ocean Engineering N2 - Information on the condition and reliability of an offshore jacket structure provided by a vibration-based structural health monitoring system can guide decisions on inspection and maintenance. When selecting the sensor setup, the designer of the monitoring system must assess its overall benefit compared to its costs before installation. The potential benefit of continuously monitoring the dynamic response of a jacket structure can be formally quantified through a value of information analysis from Bayesian decision theory. In this contribution, we present a framework for optimizing the placement of vibration sensors on offshore jacket structures by maximizing the value of information of the monitoring system. To solve the resulting discrete optimization problem, we adapt a genetic algorithm. The framework is demonstrated in a numerical example considering a redundant jacket-type steel frame. The numerical study shows that monitoring the vibration response of the frame is beneficial. Good sensor setups consist of relatively few sensors located towards the upper part of the frame. The adapted genetic algorithm performs similarly well as established sequential sensor placement algorithms and holds substantial promise for application to real jacket structures. KW - Optimal sensor placement KW - Value of information KW - Jacket support structure KW - Offshore wind turbine KW - Monitoring-informed inspection and maintenance planning PY - 2023 DO - https://doi.org/10.1016/j.oceaneng.2023.115407 SN - 0029-8018 VL - 288 IS - 2 PB - Elsevier Ltd. CY - Amsterdam AN - OPUS4-58725 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Titscher, Thomas A1 - van Dijk, T. A1 - Kadoke, Daniel A1 - Robens-Radermacher, Annika A1 - Herrmann, Ralf A1 - Unger, Jörg F. T1 - Bayesian model calibration and damage detection for a digital twin of a bridge demonstrator JF - Engineering reports N2 - Using digital twins for decision making is a very promising concept which combines simulation models with corresponding experimental sensor data in order to support maintenance decisions or to investigate the reliability. The quality of the prognosis strongly depends on both the data quality and the quality of the digital twin. The latter comprises both the modeling assumptions as well as the correct parameters of these models. This article discusses the challenges when applying this concept to realmeasurement data for a demonstrator bridge in the lab, including the data management, the iterative development of the simulation model as well as the identification/updating procedure using Bayesian inference with a potentially large number of parameters. The investigated scenarios include both the iterative identification of the structural model parameters as well as scenarios related to a damage identification. In addition, the article aims at providing all models and data in a reproducibleway such that other researcher can use this setup to validate their methodologies. KW - Damage detection KW - Finite element analysis KW - Load identification KW - Model updating KW - Estimation KW - System identification KW - Variational Bayesian statistics PY - 2023 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-574496 DO - https://doi.org/10.1002/eng2.12669 SN - 2577-8196 SP - 1 EP - 27 PB - Wiley CY - Hoboken, NJ AN - OPUS4-57449 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER -