TY - CONF A1 - Hille, Falk A1 - Nerger, Deborah A1 - Moosavi, Robabeh A1 - Grunwald, Marcel T1 - Discussion on data evaluation of tomographic and numerical results N2 - The contribution discusses the processing and analysis of data generated on two different ways of investigations for impact damage in reinforced concrete structures. Damage investigations are essential to determine type and characteristics of damage and thus the residual capacity. Damage describing data is generated using two different types of investigation, a non-destructive tomographic as well as numerical examination. Subsequently, data of both sources was merged and analysed. Within the research project “Behaviour of structural components during impact load conditions caused by aircraft fuel tank collision” reinforces concrete plates were damaged by impact loading, see Hering (2020). Afterwards the damaged specimens were investigated tomographically as well as numerically using several methods and models. Aim of the presented research work was to specify an objective comparability of numerical data with experimentally determined damage patterns and based on this, to establish a quantitative damage evaluation. T2 - 26th International Conference on Structural Mechanics in Reactor Technology CY - Potsdam, Germany DA - 10.07.2022 KW - Impact damage of reinforced concrete KW - Tomographic damage evaluation KW - Numerical simulation of impact damage PY - 2022 AN - OPUS4-55476 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 - Simon, Patrick A1 - Herrmann, Ralf A1 - Schneider, Ronald A1 - Hille, Falk A1 - Baeßler, Matthias A1 - El-Athman, Rukeia T1 - Research Data Management of Structural Health Monitoring Projects and Subsequent Applications of Artificial Intelligence Methods N2 - Structural health monitoring (SHM) intends to improve the management of engineering structures. The number of successful SHM projects – especially SHM research projects – is ever growing, yielding added value and more scientific insight into the management of infrastructure asset. With the advent of the data age, the value of accessible data becomes increasingly evident. In SHM, many new data-centric methods are currently being developed at a high pace. A consequent application of research data management (RDM) concepts in SHM projects enables a systematic management of raw and processed data, and thus facilitates the development and application of artificial intelligence (AI) and machine learning (ML) methods to the SHM data. In this contribution, a case study based on an institutional RDM framework is presented. Data and metadata from monitoring the structural health of the Maintalbrücke Gemünden for a period of 16 months are managed with the RDM system BAM Data Store, which makes use of the openBIS data management software. An ML procedure is used to classify the data. Feature engineering, feature training and resulting data are performed and modelled in the RDM system. T2 - 11th International Conference on Bridge Maintenance, Safety and Management (IABMAS2022) CY - Barcelona, Spain DA - 11.07.2022 KW - Research data management KW - Structural health monitoring KW - Artificial intelligence PY - 2022 AN - OPUS4-55494 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Eichner, Lukas A1 - Schneider, Ronald A1 - Simon, Patrick A1 - Baeßler, Matthias T1 - Optimal sensor placement for vibration-based structural health monitoring obtained via value of information analysis as part of a digital structural integrity management of offshore structures N2 - A digital structural integrity management of offshore structures enables an optimized planning of inspections and repairs with risk-based methods. In a risk-based approach, the inspection and repair strategy that minimizes the expected lifetime costs consisting of the expected inspection, repair and failure costs is determined. In addition to inspections, information on the structural condition can be continuously obtained by monitoring the vibration response of the structural system. Changes in the vibration characteristics quantified in terms of modal properties can be an indication of structural damage. In risk-based inspection and repair planning, the effect of monitoring results is determined via Bayesian updating of the structural condition and reliability. This information should be applied to inform decisions on inspections and may result in a reduced inspection effort. The benefit of continuously monitoring the structural health can be quantified in terms of the value of information, which corresponds to the difference between the expected lifetime costs with and without monitoring. In this work, we demonstrate in a numerical example how an optimized sensor placement for a vibration-based structural health monitoring system can be determined by maximizing the value of information. T2 - 3rd International Conference on Health Monitoring of Civil & Maritime Structures (HeaMES 2022) CY - Online meeting DA - 08.06.2022 KW - Bayesian System Identification KW - Offshore Wind Energy KW - Optimal Sensor Placement KW - Structural Health Monitoring KW - Value of Information PY - 2022 AN - OPUS4-55473 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Simon, Patrick A1 - Schneider, Ronald A1 - Herrmann, Ralf A1 - Hille, Falk A1 - Baeßler, Matthias T1 - Sensorbasierte Systemidentifikation N2 - Die aktuelle Instandhaltungsstrategien von Ingenieurbauwerken arbeiten zustandsbasiert und stützen sich auf visuelle Inspektionen in kurzen, starren Intervallen. Beim Übergang zu Predicitive-Maintenance-Strategien können Sensordaten eigesetzt werden um Prognosemodelle der Bauwerke zu aktualisieren. Ein erster Schritt hierzu ist die sensorbasierte Systemidentifikation. T2 - Abschlussveranstaltung AISTEC CY - Berlin, Germany DA - 02.05.2022 KW - Systemidentifikation KW - Strukturmonitoring PY - 2022 AN - OPUS4-55495 LA - deu AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Schneider, Ronald A1 - Simon, Patrick A1 - Herrmann, Ralf A1 - Hille, Falk A1 - Baeßler, Matthias T1 - Belastungsversuch und Methodenvalidierung an der Maintalbrücke Gemünden N2 - Im Projekt AISTEC wurden Methoden entwickelt, die der prädiktiven Instandhaltung von Ingenieurbauwerken dienen. Zur Validierung dieser Methoden wurden an einem Referenzbauwerk - der Maintalbrücke Gemünden - Belastungstests durchgeführt. T2 - Abschlussveranstaltung AISTEC CY - Berlin, Germany DA - 02.05.2022 KW - Belastungsfahrt KW - GNSS KW - Einflusslinien PY - 2022 AN - OPUS4-55496 LA - deu AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Schneider, Ronald T1 - Von der Datenerfassung bis zur Entscheidungsfindung: Jede Brücken-Überwachung bedarf einer Gesamtmethodik N2 - Brücken müssen laufend überwacht werden, damit die Unsicherheiten hinsichtlich ihres Zustands, ihrer Beanspruchung und ihrer Leistungsfähigkeit verringert werden können. Diese Aufgabe soll künftig mit digitalen Methoden erleichtert werden. Im folgenden Beitrag werden deshalb die digitale Bauwerksmodellierung und die Entscheidungsfindung beleuchtet. Dazu wird gezeigt, wie Zustandsdiagnosen und -prognosen digital ermöglicht werden und wie durch diagnostische und prognostische Modelle eine wissenschaftliche Basis für risikobasierte Entscheidungen über Erhaltungsmaßnahmen und für den Übergang vom reaktiven zum vorausschauenden Brückenmanagement gebildet werden kann. Dabei wird klar: Jede Brücken-Überwachung bedarf einer Gesamtmethodik, ihre wichtigsten Elemente sind: Datenerfassung, Datenmanagement, Datenanalyse, Bauwerksmodellierung, Bauwerksbewertung und die letztendlichen Entscheidungen über notwendige Erhaltungsmaßnahmen. KW - Prädiktive Instandhaltung KW - Brücken KW - Erhaltungsmanagement KW - Digitale Zwillinge PY - 2023 IS - 62 SP - 76 EP - 83 AN - OPUS4-57811 LA - deu AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Schneider, Ronald A1 - Simon, Patrick A1 - Hille, Falk A1 - Herrmann, Ralf A1 - Baeßler, Matthias T1 - Vibration-based system identification of a large steel box girder bridge N2 - The Bundesanstalt für Materialforschung und -prüfung (BAM) collaborates with TNO to develop a software framework for automated calibration of structural models based on monitoring data. The ultimate goal is to include such models in the asset management process of engineering structures. As a basis for developing the framework, a multi-span road bridge consisting of ten simply supported steel box girders was selected as a test case. Our group measured output-only vibration data from one box girder under ambient conditions. From the data, we determined eigenfrequencies and mode shapes. In parallel, we developed a preliminary structural model of the box girder for the purpose of predicting its modal properties. In this contribution, we provide an overview of the measurement campaign, the operational modal analysis, the structural modeling and qualitatively compare the identified with the predicted modes. As an outlook, we discuss the further steps in the calibration process and future applications of the calibrated model. T2 - XII International Conference on Structural Dynamics (EURODYN 2023) CY - Delft, Netherlands DA - 02.07.2023 KW - Bridge KW - Safety KW - Fatigue KW - Modal system identification KW - Model updating PY - 2023 AN - OPUS4-57863 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Niederleithinger, Ernst A1 - Hille, Falk A1 - Hofmann, Detlev A1 - Kind, Thomas ED - Isecke, B. ED - Krieger, J. T1 - Überwachung der Brücke Altstädter Bahnhof, Brandenburg./H. Begleituntersuchungen mit moderner Sensorik und zerstörungsfreier Prüfung N2 - Die B1 Brücke am Altstädter Bahnhof in Brandenburg an der Havel wurde im Dezember 2019 aufgrund von während einer turnusmäßigen Inspektion entdeckten Rissen und Hohlstellen entlang der vorgespannten Längsträger gesperrt und im Mai 2021 abgebrochen. In der Zwischenzeit wurde die Brücke detailliert überwacht. Vor dem Abriss wurden zudem umfangreiche Untersuchungen zur Bestandsaufnahme und Schadensanalyse sowie Tests moderner Sensorik vorgenommen. Dabei konnte sowohl die richtige, zuvor nicht sicher bekannte Anzahl von Spanngliedern in den Querträgern sicher ermittelt werden als auch durch moderne Varianten der Schwingungsmessungen und der faseroptischen Sensorik zusätzliche Kenntnisse püber das Bauwerksverhalten ermittelt werden . In dem Beitrag werden die Verfahren mit ihren Möglichkeiten und Grenzen vorgestellt, die Ergebnissee an der Brücke in Brandenburg erläutert und zukünftige Einsatzmöglichkeiten diskutiert. T2 - 5. Brückenkolloquium CY - Ostfildern, Germany DA - 06.09.2022 KW - Monitoring KW - Brücke KW - Radar KW - Vibration KW - Faseroptik PY - 2022 SN - 978-3-8169-3549-0 SP - 555 EP - 566 PB - Expert Verlag CY - Tübingen AN - OPUS4-55627 LA - deu 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 - Hille, Falk A1 - Herrmann, Ralf A1 - Ziegler, Fred A1 - Said, Samir A1 - Baeßler, Matthias A1 - Wille, Frank A1 - Quercetti, Thomas A1 - Minack, Mathias A1 - Sterthaus, Jens T1 - Structural Health Monitoring am Großen Fallturm der BAM N2 - Am Fallturm auf dem Testgelände Technische Sicherheit (TTS) der BAM wurden bei Inspektionen Vorspannungsverluste in den Bolzen der Stahlverbindungen festgestellt. Um ein Verständnis für die zugrundeliegenden Trag- und Schädigungsmechanismen zu erlangen und um den Zustand der vorgespannten Schraubverbindungen langzeitlich zu überwachen, wurde am Fallturm ein Structural Health Monitoring (SHM) System installiert. Für die Auslegung des Monitoringsystems sowie zur Unterstützung der Untersuchung des Schädigungsprozesses wurde ein numerisches Modell erstellt und in Bezug auf die gemessenen Antworten des Tragwerks kalibriert. Im Vortrag werden die experimentellen und numerischen Untersuchungen zur Systemidentifikation des Stahlrohrgitterturms als auch die Überwachungskampagne mit dem eingesetzten Monitoringsystem sowie die Messergebnisse und deren Bewertung vorgestellt. T2 - Seminar "Zerstörungsfreie Prüfung" am Lehrstuhl für Zerstörungsfreie Prüfung ,Technische Universität München CY - Online meeting DA - 13.01.2022 KW - Structural Health Monitoring KW - Schadensüberwachung KW - Schwingungsmonitoring PY - 2022 AN - OPUS4-56667 LA - deu AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Eichner, Lukas A1 - Schneider, Ronald A1 - Simon, Patrick A1 - Baeßler, Matthias T1 - Optimal sensor placement for vibration-based structural health monitoring obtained via value of information analysis as part of a digital structural integrity management of offshore structures N2 - A digital structural integrity management of offshore structures enables an optimized planning of inspections and repairs with risk-based methods. In a risk-based approach, the inspection and repair strategy that minimizes the expected lifetime costs consisting of the expected inspection, repair and failure costs is determined. In addition to inspections, information on the structural condition can be continuously obtained by monitoring the vibration response of the structural system. Changes in the vibration characteristics quantified in terms of modal properties can be an indication of structural damage. In risk-based inspection and repair planning, the effect of monitoring results is determined via Bayesian updating of the structural condition and reliability. This information should be applied to inform decisions on inspections and may result in a reduced inspection effort. The benefit of continuously monitoring the structural health can be quantified in terms of the value of information, which corresponds to the difference between the expected lifetime costs with and without monitoring. In this work, we demonstrate in a numerical example how an optimized sensor placement for a vibration-based structural health monitoring system can be determined by maximizing the value of information. T2 - 3rd International Conference on Health Monitoring of Civil & Maritime Structures (HeaMES 2022) CY - Online meeting DA - 08.06.2022 KW - Structural Health Monitoring KW - Value of Information KW - Offshore Wind Energy KW - Optimal Sensor Placement KW - Bayesian System Identification PY - 2022 UR - https://www.researchgate.net/publication/362569906_Optimal_sensor_placement_for_vibration-based_structural_health_monitoring_obtained_via_value_of_information_analysis_as_part_of_a_digital_structural_integrity_management_of_offshore_structures SN - 978-1-8383226-7-0 SP - 23 EP - 32 AN - OPUS4-55465 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Straub, D. A1 - Schneider, Ronald A1 - Bismut, E. A1 - Kim, H.-J. T1 - Reliability analysis of deteriorating structural systems N2 - Reliability analysis of deteriorating structural systems requires the solution of time-variant reliability problems. In the general case, both the capacity of and the loads on the structure vary with time. This analysis can be approached by approximation through a series of time-invariant reliability problems, which is a potentially effective strategy for cases where direct solutions of the time-variant reliability problem are challenging, e.g. for structural systems with many elements or arbitrary load processes. In this contribution, we thoroughly Review the formulation of the equivalent time-invariant reliability problems and extend this approximation to structures for which inspection and monitoring data is available. Thereafter, we present methods for efficiently evaluating the reliability over time. In particular, we propose the combination of sampling-based methods with a FORM (first-order reliability method) approximation of the series system reliability problem that arises in the computation of the lifetime reliability. The framework and algorithms are demonstrated on a set of numerical examples, which include the computation of the reliability conditional on inspection data. KW - Monitoring KW - Reliability KW - Deterioration KW - Structural systems KW - Bayesian analysis KW - Inspection PY - 2020 DO - https://doi.org/10.1016/j.strusafe.2019.101877 VL - 82 SP - Paper 101877, 1 PB - Elsevier Ltd. AN - OPUS4-48952 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Viefhues, Eva A1 - Döhler, M. A1 - Hille, Falk A1 - Mevel, L. ED - Simani, S. ED - Patan, K. T1 - Asymptotic analysis of subspace-based data-driven residual for fault detection with uncertain reference N2 - The local asymptotic approach is promising for vibration-based fault diagnosis when associated to a subspace-based residual function and efficient hypothesis testing tools. It has the ability of detecting small changes in some chosen system parameters. In the residual function,the left null space of the observability matrix associated to a reference model is confronted to the Hankel matrix of output covariances estimated from test data. When this left null space is not perfectly known from a model, it should be replaced by an estimate from data to avoid model errors in the residual computation. In this paper, the asymptotic distribution of the resulting data-driven residual is analyzed and its covariance is estimated, which includes also the covariance related to the reference null space estimate. The advantages of the data-driven residual are demonstrated in a numerical study, and the importance of including the covariance of the reference null space estimate is shown, which increases the detection Performance. T2 - 10th IFAC Symposium on Fault Detection, Supervision and Safety for Technical Processes SAFEPROCESS 2018 CY - Warsaw, Poland DA - 29.08.2018 KW - Subspace-based method KW - Fault detection KW - Uncertainty in reference KW - Residual evaluation KW - Statistical tests KW - Vibration measurements PY - 2018 DO - https://doi.org/10.1016/j.ifacol.2018.09.610 SN - 2405-8963 VL - 51 IS - 24 SP - 414 EP - 419 PB - Elsevier AN - OPUS4-46303 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Schneider, Ronald T1 - Effect of repair models on risk based optimal inspection strategies for support structures of offshore wind turbines N2 - Owners or operators of offshore wind farms perform inspections to collect information on the condition of the wind turbine support structures and perform repairs if required. These activities are costly and should be optimized. Risk-based methods can be applied to identify inspection and repair strategies that ensure an optimal balance between the expected total service life cost of inspection and repair, and the achieved risk reduction. Such an optimization requires explicit modeling of repairs. In this paper, the impact of different repair models on the results of a risk-based optimization of inspection and repair strategies is quantified in a numerical example considering a jacket-type steel frame subject to high-cycle fatigue. The example showed that, in this specific application, there is no need for detailed modeling of the behavior of repaired welded connections. T2 - 5th International Conference on Smart Monitoring, Assessment and Rehabilitation of Civil Structures (SMAR 2019) CY - Potsdam, Germany DA - 27.08.2019 KW - risk, reliability, inspection planning, offshore wind turbines PY - 2019 AN - OPUS4-48830 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Herrmann, Ralf A1 - Rabe, J. A1 - Marx, S. ED - Baeßler, Matthias ED - Möller, G. ED - Rogge, Andreas ED - Schiefelbein, N. T1 - Datenmanagement und –analyse von kontinuierlichen Datenströmen bei Offshore Windparks N2 - Mit der Errichtung und der Inbetriebnahme des Windpark alpha ventus wurden umfangreiche Messungen an den Tragstrukturen und den Umgebungsparametern durchgeführt. Im Projekt Gigawind life wurde im TP1 ein Datenmanagementsystem zur kontinuierlichen und periodisch fortgeführten Datenauswertung für große Datenbestände (Big Data) entworfen und realisiert. Anhand von Performanceuntersuchungen konnte eine Verkürzung der Rechenzeit um den Faktor 10 in einem Rechencluster erreicht werden. Unter Anwendung einer Datenpipeline nach dem Publish/Subscribe Prinzip wird eine skalierbare Datenschnittstelle für Monitoringdaten vorgeschlagen. T2 - Messen im Bauwesen 2018 CY - Berlin, Germany DA - 13.11.2018 KW - Datenmanagement KW - Big Data KW - Windenergie PY - 2018 SN - 978-3-9818564-1-5 VL - 2018/1 SP - 89 EP - 98 PB - Bundesanstalt für Materialforschung und -prüfung (BAM) CY - Berlin AN - OPUS4-46918 LA - deu AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Kullolli, Borana A1 - Cuéllar, Pablo A1 - Baeßler, Matthias A1 - Stutz, Hans Henning T1 - Modelling and calibration for cyclic soil-structure interface behavior N2 - The structural performance of many geotechnical systems (e.g. axially-loaded pile foundations), depends on the shearing resistance at the soil interface, which may govern the load bearing capacity of the foundation. Experimental investigations have shown that this interaction is mainly localised within a narrow shear band next to the structure. Under cyclic loading, a contraction of the soil at the interface may arise (net volume loss), possibly leading to a stress relaxation and thus to a reduction of the load bearing capacity (the so-called friction fatigue). Based on the constitutive similarities between soil continua and interfaces, we propose here the adaption of a Generalized Plasticity model for sandy soils for the numerical analysis of interface problems. In this contribution, the results of an experimental campaign for the parameter calibration of the constitutive model are presented. The tests have been conducted with a ring shear device involving different normal stresses, roughness of the steel plates as well as cyclic loading. The new modelling approach shows promising results and has the additional practical advantage that the interface zone and the soil continuum can both be described with the same constitutive model in general boundary value problems. T2 - Konferenz :International Symposium of Geomaterials CY - Glasgow, Scotland, UK DA - 26.06.2019 KW - Offshore foundations KW - Soil-structure interaction PY - 2019 AN - OPUS4-48446 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Cuéllar, Pablo A1 - Benseghier, Z. A1 - Luu, L.-H. A1 - Bonelli, S. A1 - Philippe, P. A1 - Baeßler, Matthias T1 - A GPU-based micromechanical simulation model for submerged geotechnical problems N2 - Driven steel piles are commonly used as deep foundations for a wide range of engineering structures, particularly in the offshore branch. They are also an interesting example among the broad spectrum of geotechnical applications where the fluid-solid interaction at the pore-scale can play a major role for the macromechanical behaviour of the whole system. In the context of the geotechnical practice for offshore wind-farm structures, both the industrial design and the actual dimensions of the large piles used as foundations in the seabed are often driven by factors such as the soil resistance to driving (SRD), which are still not well understood and often estimated based on mere empirical correlations or overly simplified one-dimensional models. In particular, the role of the micromechanical effects during the installation process (e.g. local dilatancy or contractancy) and their consequences on the pore pressure levels at the pile-tip and on the effective resistance to driving, are generally either disregarded or at most assumed to be covered by the simplified engineering “black-box” solutions. Here, we propose a general framework to address such local aspects of a geotechnical application involving fluid-saturated soils while retaining the focus on the micro-scale phenomena. We advocate for an approach that combines the relative simplicity of the Discrete Element Method (DEM) for the solid mechanics with the capabilities of the Lattice Boltzmann Method (LBM) for the fluid dynamics. In this sense, we aim to compile some useful techniques and practical recommendations for an efficient GPU-based implementation of a micromechanical LBM-DEM simulation tool. T2 - DEM8, the 8th International Conference on Discrete Element Methods CY - University Twente, Enschede, The Netherlands DA - 20.07.2019 KW - Offshore geotechnics KW - Micromechanical modelling KW - GPU parallel computation PY - 2019 AN - OPUS4-48588 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Viefhues, Eva A1 - Döhler, M. A1 - Zhang, Q. A1 - Hille, Falk A1 - Mevel, L. T1 - Subspace-based Damage Detection with Rejection of the Temperature Effect and Uncertainty in the Reference N2 - Temperature variation can be a nuisance that perturbs vibration based structural health monitoring (SHM) approaches for civil engineering structures. In this paper, temperature affected vibration data is evaluated within a stochastic damage detection framework, which relies on a null space based residual. Besides two existing temperature rejection approaches – building a reference state from an averaging method or a piecewise method – a new approach is proposed, using model interpolation. In this approach, a General reference model is obtained from data in the reference state at several known reference temperatures. Then, for a particular tested temperature, a local reference model is derived from the general reference model. Thus, a well fitting reference null space for the formulation of a residual is available when new data is tested for damage detection at an arbitrary temperature. Particular attention is paid to the computation of the residual covariance, taking into account the uncertainty related to the null space Matrix estimate. This improves the test performance, contrary to prior methods, for local and global damages, resulting in a higher probability of detection (PoD) for the new interpolation approach compared to previous approaches. T2 - International Operational Modal Analysis Conference CY - Copenhagen, Danmark DA - 13.05.2019 KW - Un- certainty KW - Statistical method KW - Subspace-based method KW - Temperature rejection KW - Model interpolation PY - 2019 AN - OPUS4-48244 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER -