7.2 Ingenieurbau
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- Zuggeschwindigkeit (2)
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- 3D imaging (1)
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- Asphalt (1)
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- Automated Modal Analysis for Tracking Structural Change during Construction and Operation Phases (1)
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- BAM Windenergie Fügetechnik (1)
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- DEM-LBM simulation (1)
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- DiMoWind RDS-PP Maintenance Digital Twin Offshore Wind Energy (1)
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Paper des Monats
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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.
Quantifying uncertainties in subsurface properties and stratigraphy can lead to better understanding of the ground conditions and enhance the design and assessment of geotechnical structures. Several studies have utilized Cone Penetration Test (CPT) data and employed Bayesian and Machine Learning methods to quantify the geological uncertainty, based on the Robertson’s soil classification charts and the Soil Behaviour Type Index (Ic). The incorporation of borehole data can reduce the stratigraphic uncertainty. Significant challenges can arise, however, mainly due to the intrinsic differences between field and laboratory-based soil classification systems, which can potentially lead to inconsistent soil classification. To this end, this study proposes a multivariate Gaussian Process model that utilizes site-specific data and: i) jointly models multiple categorical (USCS labels) and continuous (Ic) variables, ii) learns a (shared) spatial correlation structure and the betweenoutputs covariance, and iii) produces two types of dependent classification outputs. The results indicate that the integration of geotechnical and geological information into a unified model can provide more reliable predictions of the subsurface stratification, by allowing simultaneous interpretation of USCS and Ic profiles. Importantly, the model demonstrates the potential to integrate multiple variables of different types, aiming to contribute to the development of a methodology for joint modeling of geotechnical, geological and geophysical data.
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.
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.
Aim of this study is to provide information about moisture dependent material behaviour of unstabilised loadbearing earth blocks and mortars. Compressive strength and Young’s modulus were investigated after conditioning in varying relative humidity reaching from 40 % up to 95 %. The material composition and physical properties were investigated to understand the influence of relative humidity onto the mechanical properties. A normalisation of strength and stiffness by the values obtained at 23 ◦C and 50 % relative humidity reveals a linear dependence of compressive strength and Young’s modulus that is regardless of the material composition.
Thus, it is possible to describe the influence of relative humidity onto the load-bearing behaviour of unstabilised earth masonry materials in a generally valid formulation.
Die Bemessung von tragendem Lehmmauerwerk erfolgt in Deutschland auf Basis der Lehmbau Regeln. Das dort verankerte Nachweisverfahren beruht auf einem globalen Sicherheitskonzept, welches aus zuverlässigkeitstheoretischer Sicht nicht mehr dem Stand der Technik entspricht. Auf Grund dessen wird das Bemessungskonzept für Lehmmauerwerk vom Deutschen Institut für Bautechnik (DIBt) voraussichtlich 2023 außer Kraft gesetzt. Ein statischer Nachweis von tragenden Lehmbauten wäre in Deutschland dann ausschließlich mit einer Zustimmung im Einzelfall (ZiE) oder vorhabenbezogener Bauartgenehmigung (vBg) möglich. Beides ist mit erheblichem Mehraufwand und höheren Kosten verbunden, was für den Lehmmauerwerksbau einen entscheidenden Nachteil im Vergleich zum konventionellen Mauerwerksbau darstellt. Um eine unkomplizierte Praxisanwendung von Lehmmauerwerk zu ermöglichen, werden innerhalb eines Forschungsvorhabens, welches von der Bundesanstalt für Materialforschung und -prüfung (BAM), dem Institut für Massivbau der Technischen Universität Darmstadt sowie dem Ingenieurbüro ZRS durchgeführt wird, auf Basis der Produktnormen für Lehmsteine und Lehmmauermörtel Grundlagen für ein aktualisiertes Bemessungskonzept entwickelt. Im Rahmen des Projekts wird ebenfalls untersucht, inwiefern die Bemessungsregeln nach den vereinfachten Berechnungsmethoden für unbewehrtes Mauerwerk gemäß DIN EN 1996-3 / NA auf den Lehmmauerwerksbau übertragbar sind. Falls eine Anwendung des normativen Nachweisverfahrens bei Lehmmauerwerk möglich ist, wäre zukünftig eine Aufnahme von Lehmsteinen und Lehmmauermörtel in den nationalen Anhang des Eurocode 6 denkbar, was eine bedeutsame Erweiterung des Anwendungsbereichs von Lehmmauerwerk zur Folge hätte.
Diverse wissenschaftliche Untersuchungen konnten zeigen, dass bemessungsrelevante Festigkeits- und Verformungseigenschaften von Lehmmauerwerksbaustoffen stark von der vorherrschenden Materialfeuchte abhängen, welche im hygroskopischen Wassergehaltsbereich im Wesentlichen von der relativen Luftfeuchte (RLF) bestimmt wird. Auch die Zwischenergebnisse des laufenden Forschungsvorhabens zur Entwicklung eines Bemessungskonzepts für Lehmmauerwerk ergaben eine deutlich erkennbare Abhängigkeit zwischen der Materialfeuchte und den relevanten Festigkeits- und Verformungseigenschaften. Eine detaillierte Kenntnis des feuchteabhängigen Materialverhaltens von Lehmsteinen, -mörtel und -mauerwerk ist zwingend erforderlich, um ein konsistentes und zuverlässiges Bemessungskonzept für Lehmmauerwerk zu entwickeln. Im Rahmen des laufenden Forschungsprojektes werden deshalb umfangreiche Versuche zum Drucktragverhalten von Lehmsteinen und -mörtel sowie Lehmmauerwerk nach Konditionierung bei unterschiedlichen RLF durchgeführt und analysiert. Weiterhin werden auf Basis der experimentellen Ergebnisse numerische Modelle kalibriert, welche die detaillierte Analyse der Biegedrucktragfähigkeit von Lehmmauerwerk ermöglichen.
In diesem Beitrag werden zunächst die bisherigen Zwischenergebnisse bezüglich der experimentell ermittelten feuchteabhängigen Materialkennwerte von Lehmsteinen, -mörtel und -mauerwerk dargelegt. Darauf aufbauend werden numerische Untersuchungen zur Bestimmung der Systemtragfähigkeit von Lehmmauerwerk unter Feuchteeinflusses durchgeführt und erläutert.
block and mortar types is analysed with particular regard to the influence of varying relative humidity. The uniaxial compressive strength and deformation characteristics of unstabilised earth blocks and mortars as well as of unstabilised earth block masonry are studied in detail and compared to conventional masonry to evaluate whether the structural design can be made accordingly. An increase of 30 % points in relative humidity leads to a reduction of the masonry´s compressive strength between 33 % and 35 % whereas the Young´s modulus is reduced by 24–29 %. However, the ratio between the Young´s modulus and the characteristic compressive strength of earth block masonry ranges between E33/fk = 283–583 but is largely independent of the relative humidity. The results show that the mechanical properties of the investigated unstabilised earth block masonry are sufficient for load-bearing structures, yielding a masonry compressive strength between 2.3 MPa and 3.7 MPa throughout the range of moisture contents
investigated. In general, the design concept of conventional masonry can be adapted for unstabilised earth masonry provided that the rather low Young´s modulus as well as the moisture dependence of both, compressive strength and Young´s modulus, are sufficiently taken into
account.
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.
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.
The statistical subspace-based damage detection technique has shown promising theoretical and practical results for vibration-based structural health monitoring. It evaluates a subspacebased residual function with efficient hypothesis testing tools, and has the ability of detecting small changes in chosen system parameters. In the residual function, a Hankel matrix of Output covariances estimated from test data is confronted to its left null space associated to a reference model. The hypothesis test takes into account the covariance of the residual for decision making. Ideally, the reference model is assumed to be perfectly known without any uncertainty, which is not a realistic assumption. In practice, the left null space is usually estimated from a reference data set to avoid model errors in the residual computation. Then, the associated uncertainties may be non-negligible, in particular when the available reference data is of limited length. In this paper, it is investigated how the statistical distribution of the residual is affected when the reference null space is estimated. The asymptotic residual distribution is derived, where its refined covariance term considers also the uncertainty related to the reference null space estimate. The associated damage detection test closes a theoretical gap for real-world applications and leads to increased robustness of the method in practice. The importance of including the estimation uncertainty of the reference null space is shown in a numerical study
and on experimental data of a progressively damaged steel frame.