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Item type:Publication, Access status: with files , Experimental investigation and probabilistic analysis of the buckling load of isotropic cylinders under multiaxial loading(Elsevier, 2024-08-30); ; ; ; This paper presents a multitude of experimental results for cylindrical shells under combined loading. The loading is a combination of axial compression and bending moment. These are accompanied with numerical simulations. The load ratio itself is subject to scatter, a direct comparison and application of results for the sizing of shells is not straight forward. Therefore, a new approach is presented, which transfers the results to normalized load factors.Publicationtype: Journal Article39 73 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: without files , Probabilistic analysis of composite stiffened panels including random AFP-produced defects towards enhanced design allowables(2023-06-01); ; ; ; Automated fiber placement introduces defects such as gaps and overlaps during production, which add uncertainty to the mechanical behavior of composite parts. This study describes a probabilistic methodology which allows the direct introduction of random defects to the composite part and the calculation of the allowable design values through probabilistic virtual testing. The method is applied on a stiffened panel and is based on measurements regarding the random defect magnitude. An offline database of knock-down factors for stiffness and strength properties is first generated via detailed defected FE models. The factors are then assigned to the panel FE model accordingly, and via a Monte Carlo procedure the statistical response sample of the part is calculated. The process is further accelerated by a machine learning technique able to emulate the relationship between the random input and the selected responses. Several parametric analyses reveal that the number of defects on the panel is often more sensitive than the defect size, while the intensity of the defect at the through-the-thickness direction and the affected plies have a rather strong effect. Moreover, the conservatism of the deterministic design approach based on safety factors is proven by a direct comparison to the described probabilistic approach.Publicationtype: Journal Article70 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: without files , Uncertainty quantification of composite structures with manufacturing defects within the SuCoHS project(2022-06); ; Due to their high weight specific mechanical properties, fibre reinforced composite materials are increasingly utilized for high performance primary structures within aircraft wing and fuselage components. Yet, further exploitation is often limited due to rather high material and manufacturing costs including post-processing, concessions and rework. Additionally, very conservative engineering allowables are currently applied in order to account for uncertainties arising from manufacturing as well as operation phase. Further significant weight savings are expected for new structural components that are currently made from metals e.g. by reason of combined high thermal, mechanical or fire loading that cannot be bared by state-of-the-art composites. In order to maintain the leadership of the European aeronautics, the European funded project SuCoHS investigated potential weight and cost savings in expanding the use of composite materials in areas of demanding thermal conditions (temperature and fire). In particular, SuCoHS envisages new structural concepts with novel multi-material composites to provide high robustness against thermal, mechanical and fire loading. These developments also cater for high production rates, providing a cost competitive manufacturing process at minimum material and energy consumption, while reducing the requirement for visual inspection or rework. New solutions for structural health monitoring are considered within the structures to enable condition-based maintenance considering actual loading and structural conditions. The presentation will give an overview of the project and provide some detailed insight into the developed probabilistic sizing approach. For the latter, randomly occurring manufacturing defects (fibre tow gaps) as well as uncertain temperature distributions are taken into account in a probabilistic multiscale approach. The effect of fibre tow gaps is homogenized using meso-scale models and embedded into Monte Carlo simulations of the macro models using surrogate models.Publicationtype: Conference Presentation146 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: without files , A variable-fidelity hybrid surrogate approach for quantifying uncertainties in the nonlinear response of braided compositesThe ultimate strength prediction of textile composite materials requires high-fidelity FE modeling with information-passing multiscale schemes and damage initiation and propagation algorithms. The numerical demand of this procedure together with the complexity of the observed response surface, hampers the quantification of uncertainties contributing to the scatter of strength values. This study proposes a surrogate methodology able to efficiently emulate the nonlinear multiscale procedure, based on a combination of artificial neural networks and Kriging modeling under a variable-fidelity framework. A triaxially braided textile under longitudinal tension is used as a use-case and the methodology is employed to identify the most critical parameters in terms of variance via a global sensitivity analysis technique. Results show strong interaction effects between the uncertain parameters. The approach is non-intrusive and can be easily extended to other types of textiles and load cases.Publicationtype: Journal Article99 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: without files , Data-driven inverse uncertainty quantification in the transverse tensile response of carbon fiber reinforced composites(2021-07-28); ; Uncertainty quantification is critical for the full exploitation of composite materials’ potential. Inverse methods offer the possibility of indirectly characterizing the uncertainty of microscopic parameters by employing data sets from standard structural tests in higher scales. Two crucial requirements though, are the efficient modeling especially for the nonlinear prediction, and the measurement error availability from the tests which affects the updated scatter. This study employs effective stiffness and strength experimental data in order to quantify uncertainties of a carbon fiber UD composite in the microscale. A polynomial chaos surrogate model is trained from finite element simulations, able to efficiently predict the homogenized stiffness and strength for the uncertainty quantification procedure. The random parameters which are influential enough to be updated, are identified via a variance-based global sensitivity analysis. The inverse problem is solved with the Bayesian inference method, which updates any prior estimation of the probability models of the input parameters, based on output observations from the tests. Results show significant uncertainty reduction in comparison with typically used variance values in the literature and can be used to enrich the composite material databases. The proposed methodology is applied for the transverse tensile load case, although its non-intrusive nature allows applications for more load cases and various setups.Publicationtype: Journal Article103 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: without files , Uncertainty identification of composite properties via inverse approaches: methods and virtual setupsPublicationtype: Conference Presentation71 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: without files , Inelastic static and dynamic seismic response assessment of frames with stochastic propertiesThe article studies the inelastic seismic response assessment of structures with spatially varying material properties via the stochastic finite element method. This is a problem with a complex response function due to stochastic variability and material nonlinearity. Existing formulations either assume linear-elastic behaviour, or use dense models in order to capture both stochasticity and inelasticity. This results to models that require excessive computational resources. The article shows that for material nonlinear problems, the stochastic variability can be taken into consideration using flexibility-based models which allow performing repeated time-history simulations within a reasonable computational time, without loss of accuracy. The interpolation can be adjusted through a user-defined parameter, thus avoiding the need for a dense FE mesh. Contrary to past research, the modelling proposed has many applications in structural engineering, since it allows nonlinear, static or dynamic, simulations of real-scale frame structures with stochastic properties. The proposed method is demonstrated in the framework of the spectral representation method combined with Monte Carlo simulations, but it can be combined with any other method for the description of the stochastic field. A generic single-storey steel frame and a six-storey reinforced concrete frame are considered in order to demonstrate the efficiency of the proposed modelling.Publicationtype: Journal Article124 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: without files , Manufacturing defect tolerance quantification for composite panels via inverse stochastic methodsPublicationtype: Conference Presentation52 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: without files , Stochastic modeling techniques for textile yarn distortion and waviness with 1D random fieldsWithin the concept of simulation approaches for manufacturing-induced imperfections of composite structures, this work proposes modeling frameworks for the consideration of stochastic deviations concerning the yarns of textile composite materials. The random distortion of a yarn's cross-section, is addressed by flexible 1D Fourier-based random fields, with the potential to be calibated from measurements of the deviations from the nominal yarn shape and their statistical characteristics. Furthermore, a Kriging-based modeling approach is presented, able to randomize any nominal yarn path in short or long range problems, considering data for the correlation and variance in a straightforward manner. The effects of defects due to stochastic yarn distortion and waviness, are investigated by simulating a forward uncertainty propagation problem of a triaxially braided composite material. The response variability concerning stiffness and strength for different uncertainty levels is highlighted, while several comments are offered regarding numerical issues and potential surrogate modeling techniques.Publicationtype: Journal Article151 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: without files , Linear and nonlinear buckling analysis for the material design optimization of wind turbine blades(2019-11-15); ; Purpose: The purpose of this paper is to investigate the buckling behavior of the load-carrying support structure of a wind turbine blade. Design/methodology/approach: Experimental experience has shown that local buckling is a major failure mode that dominantly influences the total collapse of the blade. Findings: The results from parametric analyses offer a clear perspective about the buckling capacity but also about the post-buckling behavior and strength of the models. Research limitations/implications: This makes possible to compare the response of the different fiber-reinforced polymers used in the computational model. Originality/value: Furthermore, this investigation leads to useful conclusions for the material design optimization of the load-carrying box girder, as significant advantages derive not only from the combination of different fiber-reinforced polymers in hybrid material structures, but also from Kevlar-fiber blades.Publicationtype: Journal Article60