TY - CONF A1 - Zinas, Orestis A1 - Wilhelm, Sigrid T1 - CPT-based probabilistic design of monopile foundations N2 - This work was presented in the two-day workshop ‘Reliability-based methods in geotechnics’ organized by BAM and DGGT AK 2.15 in cooperation with the DGGT Academy. The presentation provides an overview of the sources of uncertainty in geotechnical analyses. A probabilistic 3D ground model of the cone-tip resistance from CPTs is developed utilizing sparse CPT data from a real offshore wind farm site in the North Sea. The predictive cone tip resistance model is used to derive a design property, such as the friction angle, using geotechnical transformation models. The friction angle profiles are then used to show an example of monopile design under uncertainty. T2 - Workshop: Einführung in die zuverlässigkeitsbasierte Bemessung in der Geotechnik 2024 CY - Berlin, Germany DA - 19.11.2024 KW - Geotechnical site-characterization KW - CPT KW - Spatial variability KW - Gaussian process regression KW - Design of monopiles KW - Offshore wind farms PY - 2024 AN - OPUS4-61716 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Zinas, Orestis A1 - Papaioannou, Iason A1 - Schneider, Ronald A1 - Cuéllar, Pablo T1 - Spatial modeling of heterogeneous geotechnical site investigation data using multivariate Gaussian Process N2 - This presentation is part of the Engineering Risk Analysis group open seminars. It aims to showcase the results of an ongoing study centered on developing a novel probabilistic methodology for 3D geotechnical site characterization. This methodology integrates data from Cone Penetration Tests (CPTs) and categorical borehole data. The presentation covers the mathematical details of the proposed Multivariate Gaussian Process model and demonstrates its application to a real geotechnical site in New Zealand. T2 - ERA Seminars CY - Munich, Germany DA - 24.07.2024 KW - Geotechnical site-characterization KW - CPT KW - Boreholes KW - Gaussian Process PY - 2024 AN - OPUS4-60716 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 - TY - CONF A1 - Zinas, Orestis T1 - 3D spatial modelling of CPT data for probabilistic preliminary assessment of potential pile tip damage upon collision with boulders N2 - Tip damage of monopiles from boulder collisions during installation has emerged as a critical design issue, primarily due to the combination of the widespread use of large-diameter piles and the complexity of the ground conditions at the available sites. Recently, a framework relating potential pile tip damage to cone tip resistance from Cone Penetration Tests (CPTs) has been proposed in the literature. Gaussian processes are powerful stochastic models that enable probabilistic spatial interpolation of soil data at any location within a site. On this basis, this study utilizes sparse CPT data from a site in the North Sea, to first develop an efficient Gaussian process regression model, which is used to derive a three-dimensional (3D) probabilistic predictive map of the cone tip resistance. Assuming deterministic loading conditions and a factual collision with a boulder of pre-defined properties, the cone tip resistance predictive model is subsequently used for a probabilistic preliminary assessment of potential pile tip damage. Results of the analysis are realistic 3D probability maps of potential damage that aim to support engineering judgment and contribute towards cost-effective site investigation planning and offshore wind farm design. T2 - 5th International Symposium on Frontiers in Offshore Geotechnics (ISFOG) CY - Nantes, France DA - 09.06.2025 KW - CPT data KW - Gaussian process regression KW - Boulder impact KW - Preliminary pile tip damage assessment PY - 2025 AN - OPUS4-63444 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Zinas, Orestis T1 - Stochastic variational Gaussian process for 3D site characterization N2 - This work was presented at the the 2nd Workshop on Future of Machine Learning in Geotechnics (2FOMLIG) & the 5th Machine Learning in Geotechnics Dialogue (5MLIGD), in Chengdu, China. In this study, we propose an efficient multivariate Gaussian process regression model, utilizing the Linear Model of Coregionalization, stochastic variational inference and Dirichlet-based transformations, to jointly model continuous CPT and categorical (USCS) borehole variables. The predictive performance of the model is assessed using a real dataset from a site located in Christchurch, New Zealand. T2 - 2nd Workshop on Future of Machine Learning in Geotechnics (2FOMLIG) & the 5th Machine Learning in Geotechnics Dialogue (5MLIGD) CY - Chengdu, China DA - 11.10.2024 KW - Geotechnical site-characterization KW - Cone Penetration Tests KW - Multivariate Gaussian process regression KW - Categorical borehole data KW - Stratigraphy prediction KW - Linear Model of Coregionalization PY - 2024 AN - OPUS4-61775 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Zinas, Orestis T1 - CPT-based probabilistic analysis of monopile foundations considering spatial and transformation uncertainties N2 - This study utilizes cone penetration testing data data from a real offshore windfarm project in the North Sea and presents a method for incorporating both, statistical and spatial uncertainties, in a reliability-based assessment of monopile foundations. Initially, a Gaussian Process regression model is constructed to predict a 3D map of the cone tip resistance and the associated uncertainties in the predictions and the hyperparameters, leveraging Markov Chain Monte Carlo methods. The CPT-based prediction is combined with a correlation derived from data collected at a nearby site to predict the probability distribution of the friction angle at a test location, which is subsequently used to evaluate the probability of failure for a monopile foundation with a finite element model. T2 - 9th International Symposiumon Geotechnical Safety and Risk (ISGSR) CY - Oslo, Norway DA - 25.08.2025 KW - Monopile design KW - Cone Penetration Test KW - Gaussian process regression KW - Bayesian Inference PY - 2025 AN - OPUS4-64001 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Zinas, Orestis T1 - Potentials of probabilistic approaches in offshore foundation installation N2 - 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. T2 - Colloquium Buckling of Offshore Wind Energy Structures CY - Berlin, Germany DA - 14.02.2024 KW - Wind KW - Offshore KW - Buckling KW - Probabilistic KW - Ground PY - 2024 AN - OPUS4-59538 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Zinas, Orestis T1 - A Modular Gaussian Process Regression Toolbox for Uncertainty Aware Geotechnical Site Characterization N2 - A modular Gaussian Process Regression toolbox for efficient large-scale geotechnical site characterization from sparse 1D data was presented at the Third Future of Machine Learning in Geotechnics (3FOMLIG), Florence, Italy, October 16, 2025. The PyTorch/GPyTorch-based framework enables multivariate modeling of correlated soil properties and joint regression-classification of continuous CPT parameters with categorical soil units through Dirichlet transformations. Stochastic Variational Inference reduces computational complexity from O(N³) to O(M³), enabling GPU-accelerated processing of 100,000+ measurements. Validated on a 33 km² North Sea offshore wind farm site with 100+ sparse investigation points, the toolbox generates uncertainty-aware 3D predictions, supporting univariate, multivariate (LMC), and sequential multi-group modeling strategies. T2 - Third Future of Machine Learning in Geotechnics (3FOMLIG) CY - Florence, Italy DA - 15.10.2025 KW - Probabilistic site-characterization KW - Gaussian process regression KW - Bayesian inference KW - Offshore Wind Farms PY - 2025 AN - OPUS4-64423 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Wiehle, Philipp T1 - Feuchteverhalten von Lehmsteinmauerwerk unter natürlichen Klimabedingungen N2 - Druckfestigkeit und Elastizitätsmodul von Lehmsteinmauerwerk nehmen mit steigendem Feuchtegehalt ab, weswegen die Mauerwerksdruckfestigkeit bei der Bemessung gemäß DIN 18940 in Abhängigkeit der maximal zu erwartenden Ausgleichsfeuchte abgemindert wird. Da bisher allerdings keine Messdaten zum Feuchtegehalt von Lehmsteinmauerwerk unter natürlichen Klimabedingungen vorliegen, stellen die normativen Grenzwerte lediglich eine konservative Abschätzung dar. Um die Feuchtegehalte von Lehmsteinmauerwerk und somit die Tragfähigkeit realitätsnah einschätzen zu können, wurden im Rahmen der vorliegenden Arbeit sowohl experimentelle als auch numerische Untersuchungen zum feuchtetechnischen Verhalten durchgeführt. Dabei wurden erstmalig magnetresonanzspektroskopische Untersuchungen an tragenden Lehmsteinen unterschiedlicher Herstellungsmethoden angewandt Weiterhin wurden Luftfeuchtesensoren in Lehmsteinmauerwerk eingebettet, um hygrische Langzeitfeuchtemessungen unter natürlichen Klimabedingungen durchzuführen. Auf Basis dieser Erkenntnisse wurde schließlich ein numerisches Modell kalibriert und Parameterstudien durchgeführt, um den unter realen Klimabedingungen tatsächlich auftretenden Feuchtegehalt im Lehmmauerwerk sowie dessen Verteilung über den Querschnitt einschätzen zu können und die normativen Grenzwerte zu überprüfen. Gezeigt wurde, dass die realitätsnahe instationäre Berechnung des Feuchtetransports mit üblichen hygrothermischen Simulationsprogrammen auf Basis einfacher feuchtetechnischer Kennwerte auch bei Lehmbaustoffen möglich ist. Der Einfluss des Quellens und Schwindens der enthaltenen Tonminerale und organischen Bestandteile wurde durch eine Modifikation bei der Ermittlung des Wasseraufnahmekoeffizienten explizit berücksichtigt und ist somit auch in den daraus abgeleiteten Transportkoeffizienten enthalten. Darüber hinaus wurde die Feuchtespeicherfunktion im überhygroskopischen Bereich auf Grundlage der Porenvolumenverteilung abgeschätzt. Die Approximation der Transportkoeffizienten und der Feuchtespeicherfunktion stellt dabei eine wesentliche Vereinfachung für Lehmbaustoffe dar, da ihre experimentelle Bestimmung aufgrund des Kontaktes mit Flüssigwasser kaum möglich ist. In Bezug auf das Feuchteverhalten üblicher Außenwandaufbauten von Wohnräumen konnte festgestellt werden, dass die Ausgleichsfeuchte im Lehmsteinmauerwerk stets unterhalb des in Nutzungsklasse 1 gemäß DIN 18940 zulässigen Grenzwertes von 65 % liegt. Je nach Putzsystem und Dämmstoff reduziert sich die Ausgleichsfeuchte auf Werte unter 60 %, wobei sich eine annähernd gleichmäßige Verteilung der Feuchte über den Mauerwerksquerschnitt hinweg einstellt. Bei Außenwänden von unbeheizten Räumen ergab sich eine maximale Ausgleichsfeuchte, die über weite Teile des Querschnitts unterhalb von 80 % lag. Der Ansatz einer maximalen Ausgleichsfeuchte von 90 % in Nutzungsklasse 2 ist folglich zu hoch angesetzt. Die zulässige Ausgleichsfeuchte bzw. der Umgebungsfeuchtefaktor in Nutzungsklasse 2 sollte dementsprechend angepasst werden. T2 - LEHM 2024 - 9. Internationale Fachtagung für Lehmbau CY - Weimar, Germany DA - 27.09.2024 KW - Lehm KW - Mauerwerk KW - Feuchte KW - Tragverhalten KW - Bemessung PY - 2024 AN - OPUS4-61904 LA - deu AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Viefhues, Eva T1 - Fault detection for linear parameter varying systems under changes in the process noise covariance N2 - Detecting changes in the eigenstructure of linear systems is a comprehensively investigated subject. In particular, change detection methods based on hypothesis testing using Gaussian residuals have been developed previously. In such residuals, a reference model is confronted to data from the current system. In this paper, linear output-only Systems depending on a varying external physical parameter are considered. These systems are driven by process noise, whose covariance may also vary between measurements. To deal with the varying parameter, an interpolation approach is pursued, where a limited number of reference models { each estimated from data measured in a reference state { are interpolated to approximate an adequate reference model for the current parameter. The problem becomes more complex when the different points of interpolation correspond to different noise conditions. Then con icts May arise between the detection of changes in the eigenstructure due to a fault and the detection of changes due to different noise conditions. For this case, a new change detection approach is developed based on the interpolation of the eigenstructure at the reference points. The resulting approach is capable of change detection when both the external physical parameter and the process noise conditions are varying. This approach is validated on a numerical simulation of a mechanical system. T2 - 21st IFAC World Congress CY - Berlin, Germany DA - 13.07.2020 KW - Linear parameter varying systems KW - Fault detection KW - Changing process noise KW - Subspace-based residual KW - Model interpolation PY - 2020 AN - OPUS4-52366 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Viefhues, Eva T1 - Stochastic subspace-based damage detection of a temperature affected beam structure N2 - Structural health monitoring (SHM) of civil structures often is limited due to changing environmental conditions, as those changes affect the structural dynamical properties in a similar way like damages can do. In this article, an approach for damage detection under changing temperatures is presentedand applied to a beam structure. The used stochastic subspace-based algorithm relies on a reference null space estimate, which is confronted to data from the testing state in a residual function. For damage detection the residual is evaluated by means of statistical hypothesis tests. Changes of the system due to temperature effects are handled with a model interpolation approach from linear parameter varying system theory. From vibration data measured in the undamaged state at some few reference temperatures, a model of the dynamic system valid for the current testing temperature is interpolated. The reference null space and the covariance matrix for the hypothesis test is computed from this interpolated model. This approach has been developed recently and was validated in an academic test case on simulations of a mass-spring-damper. In this paper, the approach is validated experimentally on a beam structure under varying temperature conditions in a climate chamber. Compared to other approaches, the interpolation approach leads to significantly less false positive alarms in the reference state when the structure is exposed to different temperatures, while faults can still be detected reliably T2 - 10th International Conference on Structural Health Monitoring of Intelligent Infrastructure, SHMII 10 CY - Online meeting DA - 30.06.2021 KW - Damage detection KW - Subspace methods KW - Temperature effects KW - Model interpolation KW - Climate chamber KW - Laboratory beam structure PY - 2021 AN - OPUS4-53000 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Thiele, Marc T1 - Detection and monitoring of the fatigue crack growth on welds – Application-oriented use of NDT methods N2 - Early detection of fatigue cracks and accurate measurements of the crack growth play an important role in the maintenance and repair strategies of steel structures exposed to cyclic loads during their service life. Observation of welded connections is especially of high relevance due to their higher susceptibility to fatigue damage. The aim of this contribution was to monitor fatigue crack growth in thick welded specimens during fatigue tests as holistically as possible, by implementing multiple NDT methods simultaneously in order to record the crack initiation and propagation until the final fracture. In addition to well-known methods such as strain gauges, thermography, and ultrasound, the crack luminescence method developed at the Bundesanstalt für Materialforschung und -prüfung (BAM), which makes cracks on the surface particularly visible, was also used. For data acquisition, a first data fusion concept was developed and applied in order to synchronize the data of the different methods and to evaluate them to a large extent automatically. The resulting database can ultimately also be used to access, view, and analyze the experimental data for various NDT methods. During the conducted fatigue tests, the simultaneous measurements of the same cracking process enabled a comprehensive comparison of the methods, highlighting their individual strengths and limitations. More importantly, they showed how a synergetic combination of different NDT methods can be beneficial for implementation in large-scale fatigue testing but also in monitoring and inspection programs of in-service structures - such as the support structures of offshore wind turbines. T2 - Fatigue Design 2023 CY - Senlis, France DA - 29.11.2023 KW - Crack growth KW - Fatigue KW - NDT KW - Welded PY - 2023 AN - OPUS4-62374 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Thiele, Marc T1 - Monitoring an Türmen von Onshore Windenergieanlagen in Betonbauweise im Hinblick auf Ermüdung N2 - Der Beitrag stellt das Messkonzept sowie dessen Umsetzung für ein umfassendes Monitoringsystem an einer onshore Windenergieanlage mit einem Hybridturm vor. Dieses ist Bestandteil des Forschungsvorhabens Win-ConFat–Structure, welches neben der Validierung geeigneter Sensorik auch die Bewertung des Zustands und der möglichen Restlebensdauer der ermüdungsbeanspruchten Betonstruktur zum Ziel hat. Neben dem Monitoringsystem werden erste Messergebnisse aus den Betriebsdaten sowie vom Verhalten der Turmstruktur vorgestellt. T2 - 11. Jahrestagung des DAfStb mit 63. Forschungskolloquium der BAM Green Intelligent Building CY - Berlin, Germany DA - 16.10.2024 KW - Onshore Windenergieanlagen KW - Ermüdung KW - Lebensdauerbewertung KW - Monitoring KW - WinConFat PY - 2024 AN - OPUS4-61773 LA - deu AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Thiele, Marc T1 - Fatigue crack detection methods for high-cyclic loaded steel structures and challenges in mechanical testing N2 - For the generation of renewable energy offshore wind farms play an important role. The majority of these wind generators are connected to steel foundation structures. Steady increasing power output of these wind turbines leads to new challenges as well for engineers of the related support structures. Caused by the high-cyclic loading of these structures by wind and waves fatigue plays a very important role. Besides the consideration of fatigue within the design process it is additionally an important topic and challenge to monitor the existing steel structures relating to potential fatigue cracks occurring during their lifetime. This plays a role for a fundamental understanding of mechanisms as investigated in testing but also for inspection in real structures. Since the structures of the offshore wind generators are very large and in addition partially under water effective and reliable methods for fatigue crack detection are required. This contribution will present results of recent investigations on different crack detection methods applied on high-cycle fatigue tests on small welded steel samples as well as on welded steel components. The comparison of these measurements will show what are the advantages and disadvantages of the different methods and which method is potentially more suitable for the application on real offshore wind structures. It is outlined where challenges for detection methods exist. Furthermore, in this context the resulting challenges for the execution of material testing especially caused by the increasing dimensions of wind energy converters will by exemplarily presented. T2 - EERA JP Wind & SETWind Online Annual Event 2020 CY - Online meeting DA - 14.09.2020 KW - Fatigue KW - Crack detection KW - Steel structures PY - 2020 AN - OPUS4-51356 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Strangfeld, Christoph T1 - Moisture diffusion affected by the Knudsen effect in temporal changing pore networks N2 - Almost all building materials in civil engineering have an open porosity and interact with or are affected by the environmental conditions. Structures might suffer from effects such as moisture adsorption, carbonation, corrosion, penetration of salt ions and chemical substances, etc. In the hygroscopic range, these processes are mostly driven by diffusion. Due to the confinement of small pores ( 1 m), the Knudsen effect reduces the molecular diffusion. This reduction can become more significant in case of temporal changing pore systems because of physisorption of water vapor, carbonation, or chemisorption. In this study, unstabilised earth blocks and earth masonry are investigated. In a first step, the pore size distribution of the blocks is measured and sorption isotherms are recorded in experiments. Besides the ordinary physisorption, the involved clay minerals undergo swelling or shrinking due to chemisorption. The following two effects must be considered: first, the reduction of the available pore space by the adsorbed water layer. For this, the Hillerborg sorption theory is used, which is a combination of the well-known Brunauer-Emmett-Teller sorption theory and the Kelvin equation. This allows the computation of adsorbed water layers even in curved pore geometries. Second, the variation of the initial pore size distribution due to chemisorption needs to be modelled. Based on these two models, the effective diffusion coefficient can be predicted. For validation, arrays of relative humidity sensors were embedded into a free-standing earth masonry wall. This monitoring was carried out over more than a year to have a broad variety of environmental conditions and was located in Berlin, Germany. The prediction of the effective diffusion coefficient can also be transferred to other processes and allows the investigation of materials having temporarily changing pore systems. Examples are the carbonation of cementitious materials, alkali silica reaction, calcium leaching of long-lasting structures, etc. This effect becomes most prominent in the meso-pore range and might alter the effective diffusion coefficient by more than 100 %. T2 - 4th International Congress on Materials & Structural Stability CY - Rabat, Morocco DA - 08.03.2023 KW - Earth masonry KW - Material moisture KW - Molecular diffusion KW - Chemisoprtion KW - Knudsen effect KW - Physisorption PY - 2023 AN - OPUS4-57140 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Simon, Patrick T1 - Experimente in der Klimakammer N2 - Im Rahmen des Verbundtreffens des Vorhabens AISTEC werden akutelle Versuche aus der Großklimakammer des FB 7.2 präsentiert. T2 - 5. Verbundtreffen AISTEC CY - Online meeting DA - 24.06.2021 KW - Klimakammer KW - Stochastic Subspace Damage Detection KW - Model Update KW - Asphalt PY - 2021 AN - OPUS4-52869 LA - deu AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Simon, Patrick T1 - Enhancing structural models with material tests and static response data - a case study considering a steel beam with asphalt layer subject to temperature variations N2 - Gradual or sudden changes in the state of structural systems caused, for example, by deterioration or accidental load events can influence their load-bearing capacity. Structural changes can be inferred from static and/or dynamic response data measured by structural health monitoring systems. However, they may be masked by variations in the structural response due to varying environmental conditions. Particularly, the interaction of nominally load-bearing components with nominally non-load bearing components exhibiting characteristics that vary as a function of the environmental conditions can significantly affect the monitored structural response. Ignoring these effects may hamper an inference of structural changes from the monitoring data. To address this issue, we adopt a probabilistic model-based framework as a basis for developing digital twins of structural systems that enable a prediction of the structural behavior under varying ambient condition. Within this framework, different types of data obtained from real the structural system can be applied to update the digital twin of the structural system using Bayesian methods and thus enhance predictions of the structural behavior. In this contribution, we implement the framework to develop a digital twin of a simply supported steel beam with an asphalt layer. It is formulated such that it can predict the static response of the beam in function of its temperature. In a climate chamber, the beam was subject to varying temperatures and its static response wass monitored. In addition, tests are performed to determine the temperature-dependent properties of the asphalt material. Bayesian system identification is applied to enhance the predictive capabilities of the digital twin based on the observed data. T2 - International Conference on Structural Health Monitoring of Intelligent Infrastructure (SHMII-10) CY - Online meeting DA - 30.06.2021 KW - Digital twin KW - Structural health monitoring KW - Material tests KW - Bayesian updating PY - 2021 AN - OPUS4-54130 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Simon, Patrick T1 - Zustandsbewertung von Bauwerken unter veränderlichen Umgebungsbedingungen mittels Structural Health Monitoring N2 - Brücken sind Teil der alternden Verkehrsinfrastruktur. Um die Nutzungsdauer zu verlängern und plötzliche Schäden zu detektieren kann Bauwerksmonitoring ("Structural Health Monitoring") eingesetzt werden. Der Einfluss von Umgebungsbedingungen, beispielsweise der Temperatur, auf das Bauwerksverhalten ist meist größer als der Einfluss von Schäden. Diese Einflüsse bestmöglich voneinander zu trennen und Veränderungen im Tragverhalten korrekt Schäden oder Umgebungsbedingungen zuzuordnen ist eine offene Forschungsfrage. Diese Arbeit zeigt eine mögliche Lösung, bei der gekoppelte Modelle von Umwelteinflüssen, Schäden und Tragverhalten des Bauwerks auf Grundlage von Monitoringdaten aktualisiert werden. Das Framework dazu wird vorgestellt und an einem Laborexperiment eines Stahlbetonbalkens in der Klimakammer angewandt. Die Ergebnisse bestätigen die Vorgehensweise. In nächsten Schritten müssen komplexere Tragwerke und die Sensitivität des Ansatzes untersucht werden. T2 - Forschungskolloquium, Institut für Konstruktiven Ingenieurbau, Bauhaus-Universität Weimar CY - Weimar, Germany DA - 28.06.2023 KW - Structural health monitoring KW - Bauwerksmonitoring KW - Umwelteinflüsse KW - Brücken PY - 2023 AN - OPUS4-58005 LA - deu AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Simon, Patrick T1 - Bayesian system identification of a reinforced concrete beam subject to temperature variations based on static response data N2 - Changes in the measured response of structural systems can be an indication of structural damages. However, such changes can also be caused by the effect of varying environmental conditions. To detect, localize and quantify changes or damages in structural systems subject to varying environmental conditions, physics-based models of the structural systems have to be applied which explicitly account for the influence of ambient conditions on the structural behavior. Data obtained from the structural systems should be used to calibrate the models and update predictions. Bayesian system identification is an effective framework for this task. In this paper, we apply this framework to learn the parameters of two competing structural models of a reinforced concrete beam subject to varying temperatures based on static response data. The models describe the behavior of the beam in the uncracked and cracked condition. The data is collected in a series of load tests in a climate chamber. Bayesian model class selection is then applied to infer the most plausible condition of the beam conditional on the available data. T2 - Tenth International Conference on Bridge Maintenance, Safety and Management (IABMAS 2020) CY - Online meeting DA - 11.04.2021 KW - Bayesian system identification KW - Reinforced concrete KW - Damage identification KW - Environmental effects KW - Structural health monitoring KW - Structural systems PY - 2021 AN - OPUS4-52812 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Simon, Patrick 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 -