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Wind turbines are exposed to a high number of load cycles during their service lifetime. Therefore, the fatigue strength verification plays an important role in their design. In general, the nominal stress method is used for the fatigue verification of the most common used butt-welded joints. The Eurocode 3 part 1–9 is the current design standard for this field of application. This paper presents recent results of fatigue tests on small-scaled specimens and large components with transverse butt welds to discuss the validity of the FAT-class. Furthermore, results from numerical simulations for the verification with the effective notch stress and the crack propagation approach are used for comparison. Based on the consistency between the numerical results and the fatigue tests, the influence of the seam geometry on the fatigue resistance was investigated. Finally, a prediction of the fatigue strength of butt-welded joints with plate thicknesses up to 80 mm was carried out.
AbstractThe sustainable and resource-efficient production of wind energy plants requires the use of modern high-strength fine-grain structural steels. This applies to both foundation and erection structures, like mobile or ship cranes. During the assembly of steel structures, unacceptable defects can occasionally be found in the weld area. In most cases, the economical solution would be local thermal gouging of the affected areas and re-welding. Due to the high shrinkage restraint of the joint groove in the overall structure, the superposition of global and local welding-induced stresses may lead to crack formation and component failure, particularly in interaction with the degradation of the microstructure and mechanical properties of high-strength steels during the repair process. However, manufacturers hardly have any information about these issues and there is a lack of recommendations and guidelines to take these safety-relevant aspects into account in adequate repair concepts. The aim of this research is to derive recommendations for repair concepts appropriate to the stresses and materials involved providing a basis for standards and guidelines to avoid cold cracking, damage and expensive reworking especially for high-strength steels. Part 1 of this study involves systematic investigations of influences of shrinkage restraint during repair welding of two high-strength steels S500MLO for offshore application and S960QL for mobile crane structures. The quantification of the shrinkage restraint of repair weld joints was achieved by means of experimental and numerical restraint intensity analysis. In welding experiments with self-restrained slot specimens, restraint intensity and introduction of hydrogen via the welding arc using anti spatter spray were varied systematically to analyse the effect on welding result, residual stresses and cold cracking. It could be shown that increasing restraint intensities result in significantly higher transverse residual stress levels. In the case of hydrogen introduction S500MLO showed no cold cracking independent of the restraint conditions. However, S960QL was found to be considerably cold cracking sensitive if hydrogen is introduced. With increasing restraint intensity length and number of cold cracks increases significantly. Part 2 [1] of this study is focussed on microstructure and residual stresses due to gouging and stress optimization via adequate heat control parameters in repair welding.
The high potential of hydrogen as a key factor on the pathway towards a climate neutral economy, leads to rising demand in technical applications, where gaseous hydrogen is used. For several metals, hydrogen-metal interactions could cause a degradation of the material properties. This is especially valid for low carbon and highstrength structural steels, as they are commonly used in natural gas pipelines and analyzed in this work.
This work provides an insight to the impact of hydrogen on the mechanical properties of an API 5L X65 pipeline steel tested in 60 bar gaseous hydrogen atmosphere. The analyses were performed using the hollow specimen technique with slow strain rate testing (SSRT). The nature of the crack was visualized thereafter utilizing μCT imaging of the sample pressurized with gaseous hydrogen in comparison to one tested in an inert atmosphere.
The combination of the results from non-conventional mechanical testing procedures and nondestructive imaging techniques has shown unambiguously how the exposure to hydrogen under realistic service pressure influences the mechanical properties of the material and the appearance of failure.
AbstractRed mud is the waste of bauxite refinement into alumina, the feedstock for aluminium production1. With about 180 million tonnes produced per year1, red mud has amassed to one of the largest environmentally hazardous waste products, with the staggering amount of 4 billion tonnes accumulated on a global scale1. Here we present how this red mud can be turned into valuable and sustainable feedstock for ironmaking using fossil-free hydrogen-plasma-based reduction, thus mitigating a part of the steel-related carbon dioxide emissions by making it available for the production of several hundred million tonnes of green steel. The process proceeds through rapid liquid-state reduction, chemical partitioning, as well as density-driven and viscosity-driven separation between metal and oxides. We show the underlying chemical reactions, pH-neutralization processes and phase transformations during this surprisingly simple and fast reduction method. The approach establishes a sustainable toxic-waste treatment from aluminium production through using red mud as feedstock to mitigate greenhouse gas emissions from steelmaking.
Mean-field modeling and phase-field simulation of grain growth under directional driving forces
(2024)
Directional grain growth is a common phenomenon in the synthetic and natural evolution of various polycrystals. It occurs in the presence of an external driving force, such as a temperature gradient, along which grains show a preferred, yet competitive, growth. Novel additive manufacturing processes, with intense, localized energy deposition, are prominent examples of when directional grain growth can occur, beneath the melting pool. In this work, we derive a phenomenological mean-field model and perform 3D phase-field simulations to investigate the directional grain growth and its underlying physical mechanisms. The effect of the intensity of driving force is simulated and systematically analyzed at the evolving growth front as well as various cross-sections perpendicular to the direction of the driving force. We found that although the directional growth significantly deviates from normal grain growth, it is still governed by a power law relation <R> α tⁿ with an exponent n ~ 0.6–0.7. The exponent n exhibits a nontrivial dependence on the magnitude of the directional driving force, such that the lowest growth exponent is observed for intermediate driving forces. We elaborate that this can originate from the fact that the forces at grain boundary junctions evolve out of balance under the influence of the directional driving force. With increasing the driving forces, the growth exponent asymptotically approaches a value of n ≈ 0.63, imposed by the largest possible grain aspect ratio for given grain boundary energies. The current combined mean-field and phase-field framework pave the way for future exploration in broader contexts such as the evolution of complex additively manufactured microstructures.
A systematic study on a face‐centered cubic‐based compositionally complex alloy system Al–Co–Cr–Cu–Fe–Ni in its single‐phase state is carried out, where a mother senary compound Al₈Co₁₇Cr₁₇Cu₈Fe₁₇Ni₃₃ and five of its suballoys, obtained by removing one element at a time, are investigated and exhaustively analyzed determining the contribution of each alloying element in the solid solution. The senary and the quinaries are compared using experimental techniques including X‐ray absorption spectroscopy, X‐ray diffraction, transmission electron microscopy, and first principles hybrid Monte Carlo/molecular dynamics simulations. Chemical short‐range order and bond length distances have been determined both at the experimental and computational level. Electronic structure and local atomic distortions up to 5.2 Å have been correlated to the microhardness values. A linear regression model connecting hardness with local lattice distortions is presented.
Titanium and its alloys are known to allow the straightforward laser-based manufacturing of ordered surface nanostructures, so-called high spatial frequency laser-induced periodic surface structures (HSFL). These structures exhibit sub-100 nm spatial periods – far below the optical diffraction limit. The resulting surface functionalities are usually enabled by both, topographic and chemical alterations of the nanostructured surfaces. For exploring these effects, multi-method characterizations were performed here for HSFL processed on Ti–6Al–4V alloy upon irradiation with near-infrared ps-laser pulses (1030 nm, ≈1 ps pulse duration, 1–400 kHz) under different laser scan processing conditions, i.e., by systematically varying the pulse repetition frequency and the number of laser irradiation passes. The sample characterization involved morphological and topographical investigations by scanning electron microscopy (SEM), atomic force microscopy (AFM), tactile stylus profilometry, as well as near-surface chemical analyses hard X-ray photoelectron spectroscopy (HAXPES) and depth-profiling time-of-flight secondary ion mass spectrometry (ToF-SIMS). This provides a quantification of the laser ablation depth, the geometrical HSFL characteristics and enables new insights into the depth extent and the nature of the non-ablative laser-induced near-surface oxidation accompanying these nanostructures. This allows to answer the questions how the processing of HSFL can be industrially scaled up, and whether the latter is limited by heat-accumulation effects.
AbstractThis work addresses the critical need for multifunctional materials and substrate‐independent high‐precision surface modification techniques that are essential for advancing microdevices and sensing elements. To overcome existing limitations, the versatility of mussel‐inspired materials (MIMs) is combined with state‐of‐the‐art multiphoton direct laser writing (DLW) microfabrication. In this way, 2D and 3D MIM microstructures of complex designs are demonstrated with sub‐micron to micron resolution and extensive post‐functionalization capabilities. This study includes polydopamine (PDA), mussel‐inspired linear, and dendritic polyglycerols (MI‐lPG and MI‐dPG), allowing their direct microstructure on the substrate of choice with the option to tailor the patterned topography and morphology in a controllable manner. The functionality potential of MIMs is demonstrated by successfully immobilizing and detecting single‐stranded DNA on MIM micropattern and nanoarray surfaces. In addition, easy modification of MIM microstructure with silver nanoparticles without the need of any reducing agent is shown. The methodology developed here enables the integration of MIMs in advanced applications where precise surface functionalization is essential.
Bacterial biofilms pose serious problems in medical and industrial settings. One of the major societal challenges lies in the increasing resistance of bacteria against biocides used in antimicrobial treatments, e.g., via overabundant use in medicine, industry, and agriculture or cleaning and disinfection in private households. Hence, new efficient bacteria-repellent strategies avoiding the use of biocides are strongly desired. One promising route to achieve bacteria-repellent surfaces lies in the contactless and aseptic large-area laser-processing of technical surfaces. Tailored surface textures, enabled by different laser-processing strategies that result in topographic scales ranging from nanometers to micrometers may provide a solution to this challenge. This article presents a current state-of-the-art review of laser-surface subtractive texturing approaches for controlling the biofilm formation for different bacterial strains and in different environments. Based on specific properties of bacteria and laser-processed surfaces, the challenges of anti-microbial surface designs are discussed, and future directions will be outlined.
Information on the condition and reliability of an offshore jacket structure provided by a vibration-based structural health monitoring system can guide decisions on inspection and maintenance. When selecting the sensor setup, the designer of the monitoring system must assess its overall benefit compared to its costs before installation. The potential benefit of continuously monitoring the dynamic response of a jacket structure can be formally quantified through a value of information analysis from Bayesian decision theory. In this contribution, we present a framework for optimizing the placement of vibration sensors on offshore jacket structures by maximizing the value of information of the monitoring system. To solve the resulting discrete optimization problem, we adapt a genetic algorithm. The framework is demonstrated in a numerical example considering a redundant jacket-type steel frame. The numerical study shows that monitoring the vibration response of the frame is beneficial. Good sensor setups consist of relatively few sensors located towards the upper part of the
frame. The adapted genetic algorithm performs similarly well as established sequential sensor placement algorithms and holds substantial promise for application to real jacket structures.
The effect of resting time on the rheological properties of cement suspensions is generally explained by early formed structure and overconsumption of polycarboxylate superplasticizers (PCEs). In this paper, we propose that the influence of resting time on the rheological properties is closely related to size variation of non-absorbed PCE. To identify this, glass bead suspensions were prepared with various amounts of PCE and ionic solution, and their rheological properties were evaluated at various times. We found that the yield stress increases with time at higher PCE concentrations and higher ionic strength solutions. Adsorbed PCE during resting tends to bridge the particles rather than disperse them. In addition, it was found that hydrodynamic radius of PCE increased with resting time, and depletion forces resulting from non-absorbed PCE size changes correlate well with the increased yield stress.
Effect of Tensile Loading and Temperature on the Hydrogen Solubility of Steels at High Gas Pressure
(2023)
The hydrogen solubility in ferritic and martensitic steels is affected by hydrostatic stress, pressure, and temperature. In general, compressive stresses decrease but tensile stresses increase the hydrogen solubility. This important aspect must be considered when qualifying materials for high‐pressure hydrogen applications (e.g., for pipelines or tanks) by using autoclave systems. In this work, a pressure equivalent for compensating the effect of compressive stresses on the hydrogen solubility inside of closed autoclaves is proposed to achieve solubilities that are equivalent to those in pipelines and tanks subjected to tensile stresses. Moreover, it is shown that the temperature effect becomes critical at low temperatures (e.g., under cryogenic conditions for storing liquid hydrogen). Trapping of hydrogen in the microstructure can increase the hydrogen solubility with decreasing temperature, having a solubility minimum at about room temperature. To demonstrate this effect, the generalized law of the hydrogen solubility is parameterized for different steels using measured contents of gaseous hydrogen. The constant parameter sets are verified and critically discussed with respect to the high‐pressure hydrogen experiments.
Inputs of plastic impurities into the environment via the application of fertilizers are regulated in Germany and the EU by means of ordinances. Robust and fast analytical methods are the basis of legal regulations. Currently, only macro- and large microplastic contents (>1 mm) are measured. Microplastics (1–1,000 µm), are not yet monitored. Thermal analytical methods are suitable for this purpose, which can determine the mass content and can also be operated fully automatically in routine mode. Thermal extraction desorption-gas chromatography/mass spectrometry (TED-GC/MS) allows the identification of polymers and the determination of mass contents in solid samples from natural environments. In accordance with the German or European Commission (EC) Fertiliser Ordinance, composting plants should be monitored for microplastic particles with this method in the future. In this context a compost plant was sampled. At the end of the rotting process, the compost was sieved and separated in a coarse (>1 mm) and a fine fraction (<1 mm). The fine fraction was processed using density separation comparing NaCl and NaI as possible salt alternative and screened for microplastic masses by TED-GC/MS with additional validation and quality assurance experiments. With TED-GC/MS total microplastics mass contents of 1.1–3.0 μg/mg in finished compost could be detected with polyethylene mainly. What differs much to the total mass of plastics in the coarse fraction with up to 60 μg/mg, which were visually searched, identified via ATR-FTIR and gravimetrically weighted.
Laser melting manufacturing of large elements of lunar regolith simulant for paving on the Moon
(2023)
The next steps for the expansion of the human presence in the solar system will be taken on the Moon. However, due to the low lunar gravity, the suspended dust generated when lunar rovers move across the lunar soil is a significant risk for lunar missions as it can affect the systems of the exploration vehicles. One solution to mitigate this problem is the construction of roads and landing pads on the Moon. In addition, to increase the sustainability of future lunar missions, in-situ resource utilization (ISRU) techniques must be developed. In this paper, the use of concentrated light for paving on the Moon by melting the lunar regolith is investigated. As a substitute of the concentrated sunlight, a high-power CO2 laser is used in the experiments. With this set-up, a maximum laser spot diameter of 100 mm can be achieved, which translates in high thicknesses of the consolidated layers. Furthermore, the lunar regolith simulant EAC-1A is used as a substitute of the actual lunar soil. At the end of the study, large samples (approximately 250 × 250 mm) with interlocking capabilities were fabricated by melting the lunar simulant with the laser directly on the powder bed. Large areas of lunar soil can be covered with these samples and serve as roads and landing pads, decreasing the propagation of lunar dust. These manufactured samples were analysed regarding their ineralogical composition, internal structure and mechanical properties.
Laser powder bed fusion is one of the most promising additive manufacturing techniques for printing complex-shaped metal components. However, the formation of subsurface porosity poses a significant risk to the service lifetime of the printed parts. In-situ monitoring offers the possibility to detect porosity already during manufacturing. Thereby, process feedback control or a manual process interruption to cut financial losses is enabled.
Short-wave infrared thermography can monitor the thermal history of manufactured parts which is closely connected to the probability of porosity formation. Artificial intelligence methods are increasingly used for porosity prediction from the obtained large amounts of complex monitoring data. In this study, we aim to identify the potential and the challenges of deep-learning-assisted porosity prediction based on thermographic in-situ monitoring.
Therefore, the porosity prediction task is studied in detail using an exemplary dataset from the manufacturing of two Haynes282 cuboid components. Our trained 1D convolutional neural network model shows high performance (R² score of 0.90) for the prediction of local porosity in discrete sub-volumes with dimensions of (700 x 700 x 40) μm³.
It could be demonstrated that the regressor correctly predicts layer-wise porosity changes but presumably has limited capability to predict differences in local porosity. Furthermore, there is a need to study the significance of the used thermogram feature inputs to streamline the model and to adjust the monitoring hardware. Moreover, we identified multiple sources of data uncertainty resulting from the in-situ monitoring setup, the registration with the ground truth X-ray-computed tomography data and the used pre-processing workflow that might influence the model’s performance detrimentally.
This paper presents a novel approach for developing sustainable building materials through Sequential Learning. Data sets with a total of 1367 formulations of different types of alkali-activated building materials, including fly ash and blast furnace slag-based concrete and their respective compressive strength and CO2-footprint, were compiled from the literature to develop and evaluate this approach. Utilizing this data, a comprehensive computational study was undertaken to evaluate the efficacy of the proposed material design methodologies, simulating laboratory conditions reflective of real-world scenarios. The results indicate a significant reduction in development time and lower research costs enabled through predictions with machine learning. This work challenges common practices in data-driven materials development for building materials. Our results show, training data required for data-driven design may be much less than commonly suggested. Further, it is more important to establish a practical design framework than to choose more accurate models. This approach can be immediately implemented into practical applications and can be translated into significant advances in sustainable building materials development.
The bond between polymer fibers and the surrounding cementitious matrix is essential for the development of concrete reinforcement. The single fiber pull-out test (SFPT) is the standard characterization technique for testing the bond strength. However, the different phases of debonding cannot be distinguished by the SFPT. This study investigates the debonding of different polymer fibers from the surrounding cementitious matrix with a modified SFPT and proposes methods to change the SFPT setup to generate more valuable information on the debonding mechanism. The SFPT was equipped with linear variable differential transformers (LVDT), digital image correlation (DIC) and acoustic emission (AE) analysis. The results demonstrate that the modified SFPT allows a better understanding of the different phases of debonding during fiber pull-out. Furthermore, bond strength values calculated by different methods reveal that the chemical bond of the investigated polymers is not different as reported by previous studies. Deformation measurements performed using LVDTs and DIC are suitable measuring techniques to characterize the debonding mechanism in SFPT. A correlation between recorded AE and debonding phases was not found.
Iron Oxide Nanocubes as a New Certified Reference Material for Nanoparticle Size Measurements
(2023)
The rational design and increasing industrial use of nanomaterials require a reliable characterization of their physicochemical key properties like size, size distribution, shape, and surface chemistry. This calls for nanoscale reference materials (nanoRMs) for the validation and standardization of commonly used characterization methods closely matching real-world nonspherical nano-objects. This encouraged us to develop a nonspherical nanoRM of very small size consisting of 8 nm iron oxide nanocubes (BAM-N012) to complement spherical gold, silica, and polymer nanoRMs. In the following, the development and production of this nanoRM are highlighted including the characterization by transmission electron microscopy (TEM) and small-angle X-ray scattering (SAXS) as complementary methods for size and shape parameters, homogeneity and stability studies, and calculation of a complete uncertainty budget of the size features. The determination of the nanocubes’ edge length by TEM and SAXS allows a method comparison. In addition, SAXS measurements can also provide the mean particle number density and the mass concentration. The certified size parameters, area equivalent circular diameter and square edge length, determined by TEM with a relative expanded uncertainty below 9%, are metrologically traceable to a natural constant for length, the very precisely known (111) lattice spacing of silicon. Cubic BAM-N012 qualifies as a certified nanoRM for estimating the precision and trueness, validation, and quality assurance of particle size and shape measurements with electron microscopy and SAXS as well as other sizing methods suitable for nanomaterials. The production of this new iron oxide nanocube RM presents an important achievement for the nanomaterial community, nanomaterial manufacturers, and regulators.
Materials that support natural biodiversity on their surfaces can compensate for human activities that have a negative impact on nature and thus contribute to a carbon-neutral and nature-positive world. Specifically designing bioreceptive materials which favor the growth of biofilms on their surface is an approach complementing conventional, macroscopic green façades. But what exactly characterizes a bioreceptive substrate and how do biofilm and substrate interact? How and why does a spontaneous colonization and the formation of biofilms take place? What are biofilms and how can they be established in a laboratory setting? How can this existing knowledge be transferred to the artificial stone concrete so that this material can be tuned to increase (or decrease) its bioreceptivity?
This review paper aims at summarizing the existing state of knowledge on bioreceptive concrete and pointing out inconsistencies and contradictions which can only be removed by more interdisciplinary research in the field.
An automated and straightforward detection and data treatment strategy for the determination of the protein relative concentration in individual human cells by single cell–inductively coupled plasma–time-of-flight mass spectrometry (sc-ICP-ToF-MS) is proposed. Metal nanocluster (NC)-labeled specific antibodies for the target proteins were employed, and ruthenium red (RR) staining, which binds to the cells surface, was used to determine the number of cell events as well as to evaluate the relative volume of the cells. As a proof of concept, the expression of hepcidin, metallothionein-2, and ferroportin employing specific antibodies labeled with IrNCs, PtNCs, and AuNCs, respectively, was investigated by sc-ICP-ToF-MS in human ARPE-19 cells. Taking into account that ARPE-19 cells are spherical in suspension and RR binds to the surface of the cells, the Ru intensity was related to the cell volume (i.e., the cell volume is directly proportional to (Ru intensity)3/2), making it possible to determine not only the mass of the target proteins in each individual cell but also the relative concentration. The proposed approach is of particular interest in comparing cell cultures subjected to different supplementations. ARPE-19 cell cultures under two stress conditions were compared: a hyperglycemic model and an oxidative stress model. The comparison of the control with treated cells shows not only the mass of analyzed species but also the relative changes in the cell volume and concentration of target proteins, clearly allowing the identification of subpopulations under the respective treatment.