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An assessment of the elastic-plastic buckling limit state for multi-strake wind turbine support towers poses a particular challenge for the modern finite element analyst, who must competently navigate numerous modelling choices related to the tug-of-war between meshing and computational cost, the use of solvers that are robust to highly nonlinear behaviour, the potential for multiple near-simultaneously critical failure locations, the complex issue of imperfection sensitivity and finally the interpretation of the data into a safe and economic design.
This paper reports on an international ‘round-robin’ exercise conducted in 2022 aiming to take stock of the computational shell buckling expertise around the world which attracted 29 submissions. Participants were asked to perform analyses of increasing complexity on a standardised benchmark of an 8-MW multi-strake steel wind turbine support tower segment, from a linear elastic stress analysis to a linear bifurcation analysis to a geometrically and materially nonlinear buckling analysis with imperfections. The results are a showcase of the significant shell buckling expertise now available in both industry and academia.
This paper is the first of a pair. The second paper presents a detailed reference solution to the benchmark, including an illustration of the Eurocode-compliant calibration of two important imperfection forms.
We report on the use of a sprayable and thermogelating biomaterial (Poloxamer; a.k.a. Pluronic) in optical imaging of pH values, local oxygen and temperature. The material is highly biocompatible and easy to handle. We also show that the material is well permeable to oxygen (thus making it a good choice for use in oxygen sensors), and is stable in liquid solution and at elevated temperature. We demonstrate its applicability in optical sensors for oxygen, pH and temperature. This was accomplished by incorporating appropriate luminescent probes in various kinds of microparticles (which act as hosts for the probes and prevent dye leaching and aggregation), and then dispersing the microparticles in the thermogelating polymer. The resulting sensor gels were deposited on the surface of interest via spraying at temperatures of <20 °C. At these temperatures, the gels adhere well to the target, even on uneven surfaces such as skin, wounds, and bacterial cultures. If temperature is risen to above 25 °C, the gels form a thin and soft but solid sensing layer which, however, can be simply removed from surface of interest by cooling and wiping it off, or by washing with water. Sprayable thermogelating sensors present obvious advantages over other sensors by not causing damage to the surface of interest. In our perception, the sensing materials also have wide further applicability in sensors for other species including clinically relevant gases, enzyme substrates (such as glucose or lactate) and ions.
Structural modularity of polymer frameworks is a key advantage of covalent organic polymers, however, only C, N, O, Si and S have found their way into their building blocks so far. Here, we expand the toolbox available to polymer and materials chemists by one additional nonmetal, phosphorus. Starting with a building block that contains a λ⁵‐phosphinine (C₅P) moiety, we evaluate a number of polymerisation protocols, finally obtaining a π‐conjugated, covalent phosphinine‐based framework (CPF‐1) via Suzuki‐Miyaura coupling. CPF‐1 is a weakly porous polymer glass (72.4 m2 g‐1 N2 BET at 77 K) with green fluorescence (λmax 546 nm) and extremely high thermal stability. The polymer catalyzes hydrogen evolution from water under UV and visible light irradiation without the need for additional co‐catalyst at a rate of 33.3 μmol h‐¹ g‐¹. Our results demonstrate for the first time the incorporation of the phosphinine motif into a complex polymer framework. Phosphinine‐based frameworks show promising electronic and optical properties that might spark future interest in their applications in light‐emitting devices and heterogeneous catalysis.
Fatigue is one of the most prevalent issues, which directly influences the service life expectancy of concrete structures. Fatigue has been investigated for years for steel structures. However, recent findings suggest that concrete structures may also be significantly subjected to fatigue phenomena that could lead to premature failure of certain structural elements. To date, fatigue of reinforced concrete has been given little focus. Knowledge on the influence factors and durability/capacity effects on this material should be improved. Current technological means to measure fatigue in civil structures like bridges and wind turbines (both onshore and offshore) are outdated, imprecise and inappropriate.
Meanwhile, this topic has got much more attention as time-variant loading on concrete structures plays an increasing role, e.g. in bridges with increasing traffic and heavier trucks, and for wind turbines for renewable energy production, e.g. for offshore wind turbine support structures affected by wind and waves.
The European Innovative Training Networks (ITN) Marie Skłodowska-Curie Actions project INFRASTAR (Innovation and Networking for Fatigue and Reliability Analysis of Structures - Training for Assessment of Risk) provides research training for 12 PhD students. The project aims to improve knowledge for optimizing the design of new structures as well as for more realistic verification of structural safety and more accurate prediction of the remaining fatigue lifetime of existing concrete structures.
First, the INFRASTAR research framework is detailed. Then it will be exemplified through the presentation of the major results of the four PhD students involved in the work package dealing with auscultation and monitoring. This includes the development and improvement of Fiber Optics (FO) and Coda Wave Interferometry (CWI) for crack sizing and imagery, new sensor technologies and integration, information management, monitoring strategy for fatigue damage investigation and lifetime prediction.
Damage detection of reinforced concrete (RC) structures is becoming a more attractive domain due to the safety issues arising in the last few decades. The damage in concrete can be caused by excessive exploitation of the structure or environmental effects. The cracks in concrete can be detected by different nondestructive testing methods. However, the available methods used for this purpose have numerous limitations. The technologies available in the market nowadays have difficulties detecting slowly progressive, locally limited damage. In addition, some of These methods cannot be applied, especially in hard-to-reach areas in the superstructures. In order to avoid these deficiencies, an embedded ultrasonic methodology can be used to detect cracks in RC structures. In this study, the methodology of crack detection supported with the advanced Signal processing algorithm was proposed and verified on RC structures of various types, and cracks occurring between embedded sensors can be detected. Moreover, different pairs of ultrasonic sensors located in the considered structures are used for the analysis of the sensitivity of distance between them. It is shown that the ultrasonic sensors placed in the range of 1.5–2 m can detect cracks, even when the other methods failed to detect changes in the structure. The obtained results confirmed that diffuse ultrasonic sensor methodology is able to monitor real structures more effectively than traditional techniques.
In additive manufacturing (AM) Laser Metal Deposition (LMD), parts are built by welding layers of powder feedstock onto a substrate. Applications for steel powders include forging tools and structural components for various industries. For large parts, the choice of tool-paths influences the build-rate, the part performance and the distortions in a highly geometry-dependent manner. With weld-path lengths in the range of hundreds of meters, a reliable, automated tool path generation is essential for the usability of LMD processes.
In this contribution, automated tool-path generation approaches are shown and their results are discussed for arbitrary geometries. The investigated path strategies are the classical approaches: “Zig-zag-” and “contour-parallel-strategies”. After generation, the tool-paths are automatically formatted into g-code for experimental build-up and ASCII for a numerical simulation model. Finally, the tool paths are discussed in regards to volume-fill, microstructure and porosity for the experimental samples.
This work presents a part of the IGF project 18737N “Welding distortion simulation” (FOSTA P1140)
In additive manufacturing (AM) directed energy deposition (DED), parts are built by welding layers of powder or wire feedstock onto a substrate with applications for steel powders in the fields of forging tools, spare parts, and structural components for various industries. For large and bulky parts, the choice of toolpaths influences the build rate, the mechanical performance, and the distortions in a highly geometry-dependent manner. With weld-path lengths in the range of hundreds of meters, a reliable, automated tool-path generation is essential for the usability of DED processes. This contribution presents automated tool-path generation approaches and discusses the results for arbitrary geometries. Socalled “zig-zag” and “contour-parallel” processing strategies are investigated and the tool-paths are automatically formatted into machine-readable g-code for experimental validation to build sample geometries. The results are discussed in regard to volume-fill, microstructure, and porosity in dependence of the path planning according to photographs and metallographic cross-sections.
This key comparison aims to assess the capabilities of the participants to determine the amount-of-substance fraction oxygen in nitrogen. The GAWG has classified this as a track B comparison, due to the unexpected 50 μmol/mol argon mole fraction content of the transfer standards, which effects the achievable performance of some measurement techniques such a GC-TCD. The separation of oxygen and argon is challenging, and not all systems in use are equally well designed for it. As this analytical challenge due to a substantial fraction of argon in the transfer standards became a reality, the Gas Analysis Working Group (GAWG) decided to qualify this key comparison as a regular key comparison and not as a core comparison, which may be used to support calibration and measurement capabilities (CMCs) for oxygen in nitrogen, or for oxygen in nitrogen mixtures containing argon only (see also the section on support to CMCs).
A pilot study for the quantitative surface analysis of multi-element alloy films has been performed by the Surface Analysis Working Group (SAWG) of the Consultative Committee for Amount of Substance (CCQM). The aim of this pilot study is to ensure the equivalency in the measurement capability of national metrology institutes for the quantification of multi-element alloy films. A Cu(In,Ga)Se2 (CIGS) film with non-uniform depth distribution was chosen as a representative multi-element alloy film. The atomic fractions of the reference and the test CIGS films were certified by isotope dilution - inductively coupled plasma/mass spectrometry. A total number counting (TNC) method was used as a method to determine the signal intensities of the constituent elements, which are compared with their certified atomic fractions. The atomic fractions of the CIGS films were measured by various methods, such as Secondary Ion Mass Spectrometry (SIMS), Auger Electron Spectroscopy (AES), X-ray Photoelectron Spectroscopy (XPS), X-Ray Fluorescence (XRF) analysis and Electron Probe Micro Analysis (EPMA) with Energy Dispersive X-ray Spectrometry (EDX). Fifteen laboratories from eight National Metrology Institutes (NMIs), one Designated Institute (DI) and six non-NMIs participated in this pilot study. Although the average atomic fractions of 18 data sets showed rather poor relative standard deviations of about 5.5 % to 6.8 %, they were greatly improved to about 1.5 % to 2.2 % by excluding 5 strongly deviating data sets from the average atomic fractions. In this pilot study, the average expanded uncertainties of SIMS, XPS, AES, XRF and EPMA were 3.84%, 3.68%, 3.81%, 2.88% and 2.90%, respectively. These values are much better than those in the key comparison K-67 for composition of a Fe-Ni alloy film. As a result, the quantification of CIGS films using the TNC method was found to be a good candidate as a subject for a CCQM key comparison.