37 research outputs found

    Decision making in structural engineering problems under polymorphic uncertainty : a benchmark proposal

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    The treatment of diverse uncertainties is an important challenge in structural engineering problems, especially from the viewpoint of realistic analysis. Inaccuracy and variability are always present and have to be quantified by either probabilistic, possibilistic, polymorphic or other uncertainty approaches. Regardless to the applied uncertainty quantification method, the numerical predictions have to be useful for structural assessment and decision making. The authors propose in this contribution a benchmark example of a portal frame structure including various uncertainties. The goal of this benchmark study is to compare justifications and decisions provided by probabilistic and non-probabilistic methods with respect to clear challenges of decision making with and without measurements and data assimilation. The engineering problem itself is simple enough to understand and complex enough not to be reduced to a simple formula with uncertain parameters.DFG, 273721697, SPP 1886: Polymorphe Unschärfemodellierungen für den numerischen Entwurf von Strukture

    Acquisition of polymorphic uncertain data based on computer tomographic scans and integration in numerical models of adhesive bonds

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    Since commercial wind turbines were introduced around 1980, the length of rotor blades has increased substantially up to 80m with consequently higher demands on availability and failure prevention. One of the typical failure mechanisms of rotor blades in operation are fatigue cracks in adhesive bonds often caused by air voids with a-priori unknown properties, which results from the manufacturing process. In this contribution, the usage of computer tomography as non-destructive testing (NDT) on a representative sub-component, called the Henkel beam, is proposed for air void detection and quantification. By using the NDT data, structural failure is simulated by means of a finite element approach under polymorphic uncertainties to consider diverse uncertainty sources in the data acquisition. On the one hand, aleatory irreducible uncertainties are described with stochastic variables and on the other hand, interval and fuzzy variables are used for epistemic reducible uncertainties. For solving the problem under polymorphic uncertainties, different computational methods within a MATLAB framework called PolyUQ are used and compared with regard to accuracy and efficiency.DFG, 273721697, SPP 1886: Polymorphe Unschärfemodellierungen für den numerischen Entwurf von Strukture

    Parameterization of arbitrary hole shapes using non-destructive testing and resulting stress concentration in a 2D plate with finite dimensions

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    Air void inclusions are mostly unavoidable in many different materials resulting from manufacturing processes or environmental conditions. In this contribution, non-destructive testing (NDT) like computer tomography (CT) is used for air void detection and quantification. The air voids lead to stress concentrations around them which influence significantly the structural integrity and at worst, lead to structural failure. By nature, air voids exhibit arbitrary shapes on which circular, elliptical, slotted and rounded rectangular holes are fitted by a least-square optimization algorithm to reduce the amount of necessary shape parameters. The mentioned shapes are compared in relation to the arbitrary one and with regard to the resulting stress concentration factor as well as the location of the maximum first principal stress in a 2D plate with finite dimensions under uniaxial tension. Finally, aleatory and epistemic uncertainties are derived from the conducted CT analysis which leads to a problem under polymorphic uncertainties. The problem is solved by a surrogate model based on cubic spline interpolation and points out the importance of the consideration of different hole shapes for analyzing the stress concentration.DFG, 273721697, SPP 1886: Polymorphe Unschärfemodellierungen für den numerischen Entwurf von Strukture

    Decision making in structural engineering problems under polymorphic uncertainty : a benchmark proposal

    Get PDF
    The treatment of diverse uncertainties is an important challenge in structural engineering problems, especially from the viewpoint of realistic analysis. Inaccuracy and variability are always present and have to be quantified by either probabilistic, possibilistic, polymorphic or other uncertainty approaches. Regardless to the applied uncertainty quantification method, the numerical predictions have to be useful for structural assessment and decision making. The authors propose in this contribution a benchmark example of a portal frame structure including various uncertainties. The goal of this benchmark study is to compare justifications and decisions provided by different uncertainty models with respect to clear challenges of decision making with and without measurements, data assimilation and design. The engineering problem itself is simple enough to understand and complex enough not to be reduced to a simple formula with uncertain parameters.DFG, 273721697, SPP 1886: Polymorphe Unschärfemodellierungen für den numerischen Entwurf von Strukture

    Comparison of monomorphic and polymorphic approaches for uncertainty quantification with experimental investigations

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    Unavoidable uncertainties due to natural variability, inaccuracies, imperfections or lack of knowledge are always present in real world problems. To take them into account within a numerical simulation, the probability, possibility or fuzzy set theory as well as a combination of these are potentially usable for the description and quantification of uncertainties. In this work, different monomorphic and polymorphic uncertainty models are applied on linear elastic structures with non-periodic perforations in order to analyze the individual usefulness and expressiveness. The first principal stress is used as an indicator for structural failure which is evaluated and classified. In addition to classical sampling methods, a surrogate model based on artificial neural networks is presented. With regard to accuracy, efficiency and resulting numerical predictions, all methods are compared and assessed with respect to the added value. Real experiments of perforated plates under uniaxial tension are validated with the help of the different uncertainty models

    Global stability failure of a 3D composite structure accompanied by unavoidable polymorphic uncertainties

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    In this study, a non-linear stability analysis of a carbon fiber reinforced plastic (CFRP) considering unavoidable polymorphic uncertainties is conducted. For the realistic incorporation of the uncertainties in the finite element model, thickness variations and geometrical inaccuracies have been detected in advance by non-destructive testing. For that, a structure made of CFRP has been designed. Additionally, the material parameters have been defined as dependent stochastic variables based on reference studies in the literature. The distinction in aleatory and epistemic uncertainties leads to different uncertainty models and to a computationally costly fuzzy-stochastic analysis. Strains and displacements have been measured in a symmetric three-point bending test and compared to the numerical predictions. In addition to the present uncertain parameters, a case study shows that the fiber volume content and a small pre-deformation should be taken into account to minimize the deviation from the experimental results

    Uniformly coated highly porous graphene/MnO2 foams for flexible asymmetric supercapacitors

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    Supercapacitors are called to play a prominent role in the newly emerging markets of electric vehicles, flexible displays and sensors, and wearable electronics. In order to compete with current battery technology, supercapacitors have to be designed with highly conductive current collectors exhibiting high surface area per unit volume and uniformly coated with pseudocapacitive materials, which is crucial to boost the energy density while maintaining a high power density. Here, we present a versatile technique to prepare thickness-controlled thin-film micro graphene foams (μGFs) with pores in the lower micrometer range grown by chemical vapor deposition which can be used as highly conductive current collectors in flexible supercapacitors. To fabricate the μGF, we use porous metallic catalytic substrates consisting of nickel/copper alloy synthesized on nickel foil by electrodeposition in an electrolytic solution. Changing the duration of the electrodeposition allows the control of the thickness of the metal foam, and thus of the μGF, ranging from a few micrometers to the millimeter scale. The resulting μGF with a thickness and pores in the micrometer regime exhibits high structural quality which leads to a very low intrinsic resistance of the devices. Transferred onto flexible substrates, we demonstrate a uniform coating of the μGFs with manganese oxide, a pseudocapacitively active material. Considering the porous structure and the thickness of the μGFs, square wave potential pulses are used to ensure uniform coverage by the oxide material boosting the volumetric and areal capacitance to 14 F cm and 0.16 F cm. The μGF with a thickness and pores in the micrometer regime in combination with a coating technique tuned to the porosity of the μGF is of great relevance for the development of supercapacitors based on state-of-the-art graphene foams

    Single-layer graphene modulates neuronal communication and augments membrane ion currents

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    The use of graphenebased materials to engineer sophisticated biosensing interfaces that can adapt to the central nervous system requires a detailed understanding of how such materials behave in a biological context. Graphene's peculiar properties can cause various cellular changes, but the underlying mechanisms remain unclear. Here, we show that singlelayer graphene increases neuronal firing by altering membraneassociated functions in cultured cells. Graphene tunes the distribution of extracellular ions at the interface with neurons, a key regulator of neuronal excitability. The resulting biophysical changes in the membrane include stronger potassium ion currents, with a shift in the fraction of neuronal firing phenotypes from adapting to tonically firing. By using experimental and theoretical approaches, we hypothesize that the graphene\u2013ion interactions that are maximized when singlelayer graphene is deposited on electrically insulating substrates are crucial to these effects

    Production and processing of graphene and related materials

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    We present an overview of the main techniques for production and processing of graphene and related materials (GRMs), as well as the key characterization procedures. We adopt a 'hands-on' approach, providing practical details and procedures as derived from literature as well as from the authors' experience, in order to enable the reader to reproduce the results. Section I is devoted to 'bottom up' approaches, whereby individual constituents are pieced together into more complex structures. We consider graphene nanoribbons (GNRs) produced either by solution processing or by on-surface synthesis in ultra high vacuum (UHV), as well carbon nanomembranes (CNM). Production of a variety of GNRs with tailored band gaps and edge shapes is now possible. CNMs can be tuned in terms of porosity, crystallinity and electronic behaviour. Section II covers 'top down' techniques. These rely on breaking down of a layered precursor, in the graphene case usually natural crystals like graphite or artificially synthesized materials, such as highly oriented pyrolythic graphite, monolayers or few layers (FL) flakes. The main focus of this section is on various exfoliation techniques in a liquid media, either intercalation or liquid phase exfoliation (LPE). The choice of precursor, exfoliation method, medium as well as the control of parameters such as time or temperature are crucial. A definite choice of parameters and conditions yields a particular material with specific properties that makes it more suitable for a targeted application. We cover protocols for the graphitic precursors to graphene oxide (GO). This is an important material for a range of applications in biomedicine, energy storage, nanocomposites, etc. Hummers' and modified Hummers' methods are used to make GO that subsequently can be reduced to obtain reduced graphene oxide (RGO) with a variety of strategies. GO flakes are also employed to prepare three-dimensional (3d) low density structures, such as sponges, foams, hydro- or aerogels. The assembly of flakes into 3d structures can provide improved mechanical properties. Aerogels with a highly open structure, with interconnected hierarchical pores, can enhance the accessibility to the whole surface area, as relevant for a number of applications, such as energy storage. The main recipes to yield graphite intercalation compounds (GICs) are also discussed. GICs are suitable precursors for covalent functionalization of graphene, but can also be used for the synthesis of uncharged graphene in solution. Degradation of the molecules intercalated in GICs can be triggered by high temperature treatment or microwave irradiation, creating a gas pressure surge in graphite and exfoliation. Electrochemical exfoliation by applying a voltage in an electrolyte to a graphite electrode can be tuned by varying precursors, electrolytes and potential. Graphite electrodes can be either negatively or positively intercalated to obtain GICs that are subsequently exfoliated. We also discuss the materials that can be amenable to exfoliation, by employing a theoretical data-mining approach. The exfoliation of LMs usually results in a heterogeneous dispersion of flakes with different lateral size and thickness. This is a critical bottleneck for applications, and hinders the full exploitation of GRMs produced by solution processing. The establishment of procedures to control the morphological properties of exfoliated GRMs, which also need to be industrially scalable, is one of the key needs. Section III deals with the processing of flakes. (Ultra)centrifugation techniques have thus far been the most investigated to sort GRMs following ultrasonication, shear mixing, ball milling, microfluidization, and wet-jet milling. It allows sorting by size and thickness. Inks formulated from GRM dispersions can be printed using a number of processes, from inkjet to screen printing. Each technique has specific rheological requirements, as well as geometrical constraints. The solvent choice is critical, not only for the GRM stability, but also in terms of optimizing printing on different substrates, such as glass, Si, plastic, paper, etc, all with different surface energies. Chemical modifications of such substrates is also a key step. Sections IV–VII are devoted to the growth of GRMs on various substrates and their processing after growth to place them on the surface of choice for specific applications. The substrate for graphene growth is a key determinant of the nature and quality of the resultant film. The lattice mismatch between graphene and substrate influences the resulting crystallinity. Growth on insulators, such as SiO2, typically results in films with small crystallites, whereas growth on the close-packed surfaces of metals yields highly crystalline films. Section IV outlines the growth of graphene on SiC substrates. This satisfies the requirements for electronic applications, with well-defined graphene-substrate interface, low trapped impurities and no need for transfer. It also allows graphene structures and devices to be measured directly on the growth substrate. The flatness of the substrate results in graphene with minimal strain and ripples on large areas, allowing spectroscopies and surface science to be performed. We also discuss the surface engineering by intercalation of the resulting graphene, its integration with Si-wafers and the production of nanostructures with the desired shape, with no need for patterning. Section V deals with chemical vapour deposition (CVD) onto various transition metals and on insulators. Growth on Ni results in graphitized polycrystalline films. While the thickness of these films can be optimized by controlling the deposition parameters, such as the type of hydrocarbon precursor and temperature, it is difficult to attain single layer graphene (SLG) across large areas, owing to the simultaneous nucleation/growth and solution/precipitation mechanisms. The differing characteristics of polycrystalline Ni films facilitate the growth of graphitic layers at different rates, resulting in regions with differing numbers of graphitic layers. High-quality films can be grown on Cu. Cu is available in a variety of shapes and forms, such as foils, bulks, foams, thin films on other materials and powders, making it attractive for industrial production of large area graphene films. The push to use CVD graphene in applications has also triggered a research line for the direct growth on insulators. The quality of the resulting films is lower than possible to date on metals, but enough, in terms of transmittance and resistivity, for many applications as described in section V. Transfer technologies are the focus of section VI. CVD synthesis of graphene on metals and bottom up molecular approaches require SLG to be transferred to the final target substrates. To have technological impact, the advances in production of high-quality large-area CVD graphene must be commensurate with those on transfer and placement on the final substrates. This is a prerequisite for most applications, such as touch panels, anticorrosion coatings, transparent electrodes and gas sensors etc. New strategies have improved the transferred graphene quality, making CVD graphene a feasible option for CMOS foundries. Methods based on complete etching of the metal substrate in suitable etchants, typically iron chloride, ammonium persulfate, or hydrogen chloride although reliable, are time- and resource-consuming, with damage to graphene and production of metal and etchant residues. Electrochemical delamination in a low-concentration aqueous solution is an alternative. In this case metallic substrates can be reused. Dry transfer is less detrimental for the SLG quality, enabling a deterministic transfer. There is a large range of layered materials (LMs) beyond graphite. Only few of them have been already exfoliated and fully characterized. Section VII deals with the growth of some of these materials. Amongst them, h-BN, transition metal tri- and di-chalcogenides are of paramount importance. The growth of h-BN is at present considered essential for the development of graphene in (opto) electronic applications, as h-BN is ideal as capping layer or substrate. The interesting optical and electronic properties of TMDs also require the development of scalable methods for their production. Large scale growth using chemical/physical vapour deposition or thermal assisted conversion has been thus far limited to a small set, such as h-BN or some TMDs. Heterostructures could also be directly grown. Section VIII discusses advances in GRM functionalization. A broad range of organic molecules can be anchored to the sp2 basal plane by reductive functionalization. Negatively charged graphene can be prepared in liquid phase (e.g. via intercalation chemistry or electrochemically) and can react with electrophiles. This can be achieved both in dispersion or on substrate. The functional groups of GO can be further derivatized. Graphene can also be noncovalently functionalized, in particular with polycyclic aromatic hydrocarbons that assemble on the sp2 carbon network by π–π stacking. In the liquid phase, this can enhance the colloidal stability of SLG/FLG. Approaches to achieve noncovalent on-substrate functionalization are also discussed, which can chemically dope graphene. Research efforts to derivatize CNMs are also summarized, as well as novel routes to selectively address defect sites. In dispersion, edges are the most dominant defects and can be covalently modified. This enhances colloidal stability without modifying the graphene basal plane. Basal plane point defects can also be modified, passivated and healed in ultra-high vacuum. The decoration of graphene with metal nanoparticles (NPs) has also received considerable attention, as it allows to exploit synergistic effects between NPs and graphene. Decoration can be either achieved chemically or in the gas phase. All LMs, can be functionalized and we summarize emerging approaches to covalently and noncovalently functionalize MoS2 both in the liquid and on substrate. Section IX describes some of the most popular characterization techniques, ranging from optical detection to the measurement of the electronic structure. Microscopies play an important role, although macroscopic techniques are also used for the measurement of the properties of these materials and their devices. Raman spectroscopy is paramount for GRMs, while PL is more adequate for non-graphene LMs (see section IX.2). Liquid based methods result in flakes with different thicknesses and dimensions. The qualification of size and thickness can be achieved using imaging techniques, like scanning probe microscopy (SPM) or transmission electron microscopy (TEM) or spectroscopic techniques. Optical microscopy enables the detection of flakes on suitable surfaces as well as the measurement of optical properties. Characterization of exfoliated materials is essential to improve the GRM metrology for applications and quality control. For grown GRMs, SPM can be used to probe morphological properties, as well as to study growth mechanisms and quality of transfer. More generally, SPM combined with smart measurement protocols in various modes allows one to get obtain information on mechanical properties, surface potential, work functions, electrical properties, or effectiveness of functionalization. Some of the techniques described are suitable for 'in situ' characterization, and can be hosted within the growth chambers. If the diagnosis is made 'ex situ', consideration should be given to the preparation of the samples to avoid contamination. Occasionally cleaning methods have to be used prior to measurement
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