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The Bundesanstalt für Materialforschung und -prüfung (BAM) collaborates with TNO to develop a software framework for automated calibration of structural models based on monitoring data. The ultimate goal is to include such models in the asset management process of engineering structures. As a basis for developing the framework, a multi-span road bridge consisting of ten simply supported steel box girders was selected as a test case. Our group measured output-only vibration data from one box girder under ambient conditions. From the data, we determined eigenfrequencies and mode shapes. In parallel, we developed a preliminary structural model of the box girder for the purpose of predicting its modal properties. In this contribution, we provide an overview of the measurement campaign, the operational modal analysis, the structural modeling and qualitatively compare the identified with the predicted modes. As an outlook, we discuss the further steps in the calibration process and future applications of the calibrated model.
Managing aging engineering structures requires damage identification, capacity reassessment, and prediction of remaining service life. Data from structural health monitoring (SHM) systems can be utilized to detect and characterize potential damage. However, environmental and operational variations impair the identification of damages from SHM data. Motivated by this, we introduce a Bayesian probabilistic framework for building models and identifying damage in monitored structures subject to environmental variability. The novelty of our work lies (a) in explicitly considering the effect of environmental influences and potential structural damages in the modeling to enable more accurate damage identification and (b) in proposing a methodological workflow for model‐based structural health monitoring that leverages model class selection for model building and damage identification. The framework is applied to a progressively damaged reinforced concrete beam subject to temperature variations in a climate chamber. Based on deflections and inclinations measured during diagnostic load tests of the undamaged structure, the most appropriate modeling approach for describing the temperature‐dependent behavior of the undamaged beam is identified. In the damaged state, damage is characterized based on the identified model parameters. The location and extent of the identified damage are consistent with the cracks observed in the laboratory. A numerical study with synthetic data is used to validate the parameter identification. The known true parameters lie within the 90% highest density intervals of the posterior distributions of the model parameters, suggesting that this approach is reliable for parameter identification. Our results indicate that the proposed framework can answer the question of damage identification under environmental variations. These findings show a way forward in integrating SHM data into the management of infrastructures.
This data article presents a set of primary, analyzed, and digitalized mechanical testing datasets for nine copper alloys. The mechanical testing methods including the Brinell and Vickers hardness, tensile, stress relaxation, and low-cycle fatigue (LCF) testing were performed according to the DIN/ISO standards. The obtained primary testing data (84 files) mainly contain the raw measured data along with the testing metadata of the processes, materials, and testing machines. Five secondary datasets were also provided for each testing method by collecting the main meta- and measurement data from the primary data and the outputs of data analyses. These datasets give materials scientists beneficial data for comparative material selection analyses by clarifying the wide range of mechanical properties of copper alloys, including Brinell and Vickers hardness, yield and tensile strengths, elongation, reduction of area, relaxed and residual stresses, and LCF fatigue life. Furthermore, both the primary and secondary datasets were digitalized by the approach introduced in the research article entitled “Toward a digital materials mechanical testing lab” [1]. The resulting open-linked data are the machine-processable semantic descriptions of data and their generation processes and can be easily queried by semantic searches to enable advanced data-driven materials research.
Nowadays geotechnical engineering firms have powerful software tools to extent their consult-ing business also into dynamic soil-structure interaction, which before has been restricted to a rather small community of specialized experts in this field, and they certainly do. This is par-ticularly true with respect to non-seismic sources, that is all kinds of human induced vibrations. Hence, there is a demand from clients as well as from contractors to have guidance on the re-quirements as well as the limits of numerical modelling of soil-structure interaction. From the literature as well as from relevant standards, recommendations for the numerical modelling of soil-structure interaction problems involving seismic actions are well known, e. g. ASCE/SEI 4-16. There are, however, some particularities when dealing with human-induced vibrations, which are absent in seismic analyses. For human-induced excitations very little specific guid-ance has been published in the past. A machine foundation on a homogeneous half space ex-cited by harmonic loads with excitation frequency between 4 Hz and 64 Hz has been ana-lysed by means of several commercially available software packages. Parametric studies have been performed to verify if recommendations for seismic soil-structure analyses are valid for non-seismic analyses as well. This paper provides details on the benchmark example and the most important conclusions from the undertaken parametric studies.
AbstractTwo‐photon polymerization (2PP) additive manufacturing (AM) utilizes feedstocks of ceramic nanoparticles of a few nanometers in diameter, enabling the fabrication of highly accurate technical ceramic design with structural details as small as 500 nm. The performance of these materials is expected to differ from conventional AM ceramics, as nanoparticles and three‐dimensional printing at high resolution introduce new microstructural aspects. This study applies 2PP‐AM of yttria‐stabilized zirconia to investigate the mechanical response behavior under compressive load, probing the influence of smallest structural units induced by the line packing during the printing process, design of sintered microblocks, and sintering temperature and thereby microstructure. We find a dissipative mechanical response enhanced by sintering at lower temperatures than conventional. The pursued 2PP‐AM approach yields a microstructured material with an increased number of grain boundaries that proposedly play a major role in facilitating energy dissipation within the here printed ceramic material. This microplastic response is further triggered by the filigree structures induced by hollow line packing at the order of the critical defect size of ceramics. Together, these unique aspects made accessible by the 2PP‐AM approach contribute to a heterogeneous nano‐ and microstructure, and hint toward opportunities for tailoring the mechanical response in future ceramic applications.
ISO 14837-32:2015 and DIN EN 1998-1/NA:2021 as well as prEN 1997-2:2022 allow for us-ing correlations between the results of in-situ soil penetration tests and shear wave velocity (or shear modulus) to determine soil properties to be used in dynamic analyses. While the ISO and prEN standards even provide some recommendations on specific correlations to be used, the DIN standard does not. Due to the statistical nature of such correlations their general applica-bility has to be verified. We collected data sets from test sites from Germany as well as New Zealand at which cone penetration tests (CPT) as well as seismic site investigation methods were conducted. These sites comprise sandy soils as well as clayey soils, mixed soils as well as glacial soils. We compare the results of several correlations between CPT results and shear wave velocity. The accuracy of such correlations is assessed with respect to the accuracy of seismic in-situ tests. It turns out that for clean sands such correlations between CPT and Vs have a similar order of variability as seismic in-situ tests conducted at the same site. The higher the fines portion of the soil, the higher the variability of the statistical correlations, and conse-quently the less the general applicability. For glacial soils and other special soil types usage of statistical correlations to determine dynamic soil properties is not recommended.
The design of bridges often overlooks the vertical component of earthquakes or considers it of secondary importance, despite compelling evidence indicating specific structural damage caused by primary earthquake waves. Conversely, during the operational phase, the combined influence of ground motion and moving loads from vehicles can significantly impact the structural health monitoring (SHM) of bridges. This study aims to evaluate the simultaneous effect of vertical earthquake vibrations and moving vehicle loads on simply supported bridges. The research employs a practical methodology based on the eigenfunction expansion method to analyze change of deflection due to the effect of these concurrent forces under seven different earthquake records. It is shown that within a realistic range of vehicle mass and velocity, the average of changing the maximum deflection at the mid-span of the main beam (denoted as M_n) reaches up to 163% under various scenarios. Subsequently, the seismic parameters influencing this phenomenon are identified through a statistical analysis of set of 100 different earthquake records with unique features. A linear regression equation is presented to predict the M_n based on the earthquake specific properties. Additionally, to control the vertical vibration of bridge systems, a novel vibration suppression system utilizing steel pipe dampers is introduced, and its reliability is examined across a broad spectrum of bridge flexural rigidity. The results indicate that the system's efficiency depends on M_n and the soil type of the bridge construction, enabling a reduction in structural sections (up to 27%) while achieving the same maximum target deflection in the initial state. This efficiency leads to a more economical design solution, emphasizing the potential benefits of the proposed system for practical application.
NDT Data-Supported Structural Reassessments based on Regression Relations in Measuring Data Analysis
(2024)
Non-destructive Testing (NDT) provides valuable data about structural elements, supporting the assessment of existing infrastructures without incurring additional structural damage from inspections. Simultaneously, the uncertainty in measurement, which quantifies the quality of measurement results, plays a crucial role in decisions aimed at, e.g., optimizing maintenance strategies, rehabilitation works and Structural Health Monitoring (SHM) implementations. The Guide to the Expression of Uncertainty in Measurement (GUM) framework has already been considered for non-destructive concrete testing. Regarding that, extensive measurements with sophisticated scopes need to be conducted by experts as an obligatory process.
This study illustrates how NDT results describing the inner structure of a concrete element can effectively support the reassessment of bridges in operation. To achieve this, the study considers the various measurable positions of the resisting longitudinal tendons of a bridge structure to investigate the displacement change under dynamic service loads.
Furthermore, this study aims to simplify and optimize existing NDT data analysis procedures by employing regression analysis, enabling the detection of structural features. This regression analysis yields a modifier for determining the correct depth of an object within the structural element. The method is validated through laboratory experiments, including the use of an ultrasonic measurement system. As a result, it provides unbiased and accurately measured results, while ensuring that the measurement data can remain uncorrelated. Major advantages include efficient computation, a wider scope, and avoiding redundant information about the measuring process.
The findings demonstrate that employing the proposed NDT analysis method, with its enhanced practicability, can significantly augment the efficiency of NDT data-supported structural reassessments across various scenarios.
Automated computational workflows are a powerful concept that can improve the usability and reproducibility of simulation and data processing approaches. Although used very successfully in bioinformatics, workflow environments in materials science are currently commonly applied in the field of atomistic simulations. This work showcases the integration of a discrete element method (DEM) simulation of powder pressing in the convenient SimStack workflow environment. For this purpose, a Workflow active Node (WaNo) was developed to generate input scripts for the DEM solver using LIGGGHTS Open Source Discrete Element Method Particle Simulation code. Combining different WaNos in the SimStack framework makes it possible to build workflows and loop over different simulation or evaluation conditions. The functionality of the workflows is explained, and the added user value is discussed. The procedure presented here is an example and template for many other simulation methods and issues in materials science and engineering.
The injection of hydrogen into the natural-gas grid is an alternative during the process of a gradual decarbonization of the heat and power supply. When dealing with hydrogen-enriched natural gas mixtures, the performance of the reference equations of state habitually used for natural gas should be validated by using high-precision experimental thermophysical data from multicomponent reference mixtures prepared with the lowest possible uncertainty in composition. In this work, we present experimental density data for an 11-compound high-calorific (hydrogen-free) natural gas mixture and for two derived hydrogen-enriched natural gas mixtures prepared by adding (10 and 20) mol-% of hydrogen to the original standard natural gas mixture. The three mixtures were prepared gravimetrically according to ISO 6142–1 for maximum precision in their composition and thus qualify for reference materials. A single-sinker densimeter was used to determine the density of the mixtures from (250–350) K and up to 20 MPa. The experimental density results of this work have been compared to the densities calculated by three different reference equations of state for natural gas related mixtures: the AGA8-DC92 EoS, the GERG-2008 EoS, and an improved version of the GERG-2008 EoS. While relative deviations of the experimental density data for the hydrogen-free natural gas mixture are always within the claimed uncertainty of the three considered equations of state, larger deviations can be observed for the hydrogen-enriched natural gas mixtures from any of the three equations of state, especially for the lowest temperature and the highest pressures.
The systematic transfer of solvent-free, additive flame retardant (FR) formulations from epoxy resins to glass fiber-reinforced epoxy composites (GFRECs) through prepregs is difficult. Additionally, obtaining data on their post-fire mechanics is often challenging. Utilizing melamine polyphosphate (MPP), ammonium polyphosphate (APP), and silane-coated ammonium polyphosphate (SiAPP) FRs with low-melting inorganic silicates (InSi) in an 8:2 proportion and 10% loading by weight in a diglycidyl ether of bisphenol A (DGEBA) resin, a systematic investigation of the processing properties, room-temperature mechanics, and temperature-based mechanics of the systems was performed. The resin was cured with a dicyandiamide hardener (DICY) and a urone accelerator. The results revealed no substantial impact of these FRs at the current loading on the resin's glass transition temperature or processability. However, the fire residues from cone calorimetry tests of the composites containing FRs were found to be only 15-20% of the thickness of the resins, implying a suppression of intumescence upon transfer. At room temperature, the decrease in the flexural modulus for the composites containing FRs was negligible. Exposure of the composites in a furnace at 400°C as a preliminary study before ignition tests was shown to cause significant flexural moduli reductions after 2.5 min of exposure and complete delamination after 3 min making further testing unviable. This study emphasizes the need for future research on recovering modes of action upon transfer of FR formulations from resins to composites. Based on the challenges outlined in this investigation, sample adaptation methods for post-fire analysis will be developed in a future study.
Addressing a strategy for publishing open and digital research data, this article presents the approach for streamlining and automating the process of storage and conversion of research data to those of semantically queryable data on the web. As the use case for demonstrating and evaluating the digitalization process, the primary datasets from low‐cycle‐fatigue testing of several copper alloys are prepared. The fatigue test ontology (FTO) and ckan.kupferdigital data management system are developed as two main prerequisites of the data digitalization process. FTO has been modeled according to the content of the fatigue testing standard and by reusing the basic formal ontology, industrial ontology foundry core ontology, and material science and engineering ontology. The ckan.kupferdigital data management system is also constructed in such a way that enables the users to prepare the protocols for mapping the datasets into the knowledge graph and automatically convert all the primary datasets to those machine‐readable data which are represented by the web ontology language. The retrievability of the converted digital data is also evaluated by querying the example competency questions, confirming that ckan.kupferdigital enables publishing open data that can be highly reused in the semantic web.
Ultra-High-Performance Fiber-Reinforced Cementitious Composite (UHPFRC) offers several advantages compared to concrete, notably due to the strain hardening behavior under tensile actions. Structures made of this composite material are lightweight and highly durable, thanks to the UHPFRC waterproofing quality. Nonetheless, the tensile behavior leads to a different cracking pattern than conventional concrete and is not fully understood yet. This paper presents a combined approach using both passive ultrasonic (US) stress wave (or acoustic emission) and active US stress wave monitoring to localize and quantify damage progression in a full-scale UHPFRC beam during experimental load testing. The proposed monitoring approach involves 24 US transducers that are embedded randomly throughout a 4.2- meter-long laboratory UHPFRC T-beam. Continuous monitoring enabled accurate localization of US stress sources caused by loading-induced cracking as well as from pulses generated by the embedded US transducers. This study shows that it is possible to predict the location and shape of the macro-crack that is linked to structural failure early on, i.e., just after the end of the elastic domain. This combined approach opens new possibilities to monitor the structural behavior and detect damage on UHPFRC structures before they affect the structural behavior in terms of deflection and strain.
To safely dispose of nuclear waste in underground facilities, engineered barrier systems are needed to seal shafts and galleries. The material used in these barriers must be adapted to the host rock parameters. Shrinking and cracking must be avoided to provide a barrier with almost zero permeability. For repositories in salt rock environments, several types of salt concrete (SC) are possible construction materials. Within the project SealWasteSafe, we compared the behavior of an innovative alkali-activated material (AAM) with standard SC in their hydration and hardening phase. To monitor the microstructural changes within the two materials SC and AAM, acoustic emission (AE) signals have been recorded for up to ~250 days on 340-litercubic specimens. The phenomenon of AE is defined as the emission of elastic waves in materials due to the release of localized internal energy. Such energy release can be caused by the nucleation of micro-fracture, e.g., in concrete while curing or when exposed to load. The occurrence of AE events gives first rough indications of microstructural changes and potentially occurring cracking and thus, provides insights for structural health monitoring (SHM). The results show, that for the first 28 days after casting, less AE activity was detected in the AAM compared to SC. After 61 days, in the AAM material, the number of AE events exceeded those observed in the SC. However, the majority of the AE detected and located in AAM was related to surface effects, and not to microstructural changes or occurring cracks within the bulk volume. Additionally, the source location analysis indicated, that despite lower activity in SC, we observed some clustering of the events. In contrast, in AAM, the activity inside the specimen is randomly distributed over the whole volume. The monitoring results help to estimate the material’s sealing properties which are crucial to assess their applicability as sealing material for engineered barriers.
Combined passive ultrasonic (US) stress wave [better known as acoustic emission (AE)] and active US stress wave monitoring has been shown to provide a more holistic picture of ongoing fracture processes, damage progression, as well as slowly occurring aging and degradation mechanisms in concrete structures. Traditionally, different data analysis techniques have been used to analyze the data generated from these two monitoring techniques. For passive US stress wave monitoring, waveform amplitudes, hit rates, source localization, and b-value analysis, among others, have been used to detect and locate cracking. On the other hand, amplitude tracking, magnitude squared coherence (MSC), and coda wave interferometry (CWI) are examples of analyses that have been employed for active US stress wave monitoring. In this paper, we explore some of these data analysis techniques and show where their respective applications and limitations might be. After providing an overview of the monitoring approach and the different data analysis techniques, results and observations from selected laboratory experiments are discussed. Finally, suggestions for further work are proposed.
Manufacturing and Application of Lightweight Aggregates from Construction and Demolition Waste
(2024)
The objective of the REALight project is the development of a thermal process to produce lightweight aggregates in pilot scale and the implantation of a method to recover gypsum. Beside construction and demolition waste, various industrial by‐products are studied as raw materials. The raw materials have so far been unused or used in applications with lower quality requirements. To prove the performance of the lightweight aggregates, their technical properties are tested and their use in different applications is studied, e.g., for lightweight mortars as well as lightweight concretes.
Despite the physiological and pathophysiological significance of microenvironmental gradients, e.g., for diseases such as cancer, tools for generating such gradients and analyzing their impact are lacking. Here, we present an integrated microfluidic-based workflow that mimics extracellular pH gradients characteristic of solid tumors while enabling high-resolution live imaging of, e.g., cell motility and chemotaxis, and preserving the capacity to capture the spatial transcriptome. Our microfluidic device generates a pH gradient that can be rapidly controlled to mimic spatiotemporal microenvironmental changes over cancer cells embedded in a 3D matrix. The device can be reopened allowing immunofluorescence analysis of selected phenotypes, as well as the transfer of cells and matrix to a Visium slide for spatially resolved analysis of transcriptional changes across the pH gradient. This workflow is easily adaptable to other gradients and multiple cell types and can therefore prove invaluable for integrated analysis of roles of microenvironmental gradients in biology.
AbstractThe correlation between altered extracellular pH and various pathological conditions, including cancer, inflammation and metabolic disorders, is well known. Bulk pH measurements cannot report the extracellular pH value at the cell surface. However, there is a limited number of suitable tools for measuring the extracellular pH of cells with high spatial resolution, and none of them are commonly used in laboratories around the world. In this study, a versatile ratiometric nanosensor for the measurement of extracellular pH was developed. The nanosensor consists of biocompatible polystyrene nanoparticles loaded with the pH-inert reference dye Nile red and is surface functionalized with a pH-responsive fluorescein dye. Equipped with a targeting moiety, the nanosensor can adhere to cell membranes, allowing direct measurement of extracellular pH at the cell surface. The nanosensor exhibits a sensitive ratiometric pH response within the range of 5.5–9.0, with a calculated pKa of 7.47. This range optimally covers the extracellular pH (pHe) of most healthy cells and cells in which the pHe is abnormal, such as cancer cells. In combination with the nanosensors ability to target cell membranes, its high robustness, reversibility and its biocompatibility, the pHe nanosensor proves to be well suited for in-situ measurement of extracellular pH, even over extended time periods. This pH nanosensor has the potential to advance biomedical research by improving our understanding of cellular microenvironments, where extracellular pH plays an important role.
AbstractLithium‐ion batteries, essential for electronics and electric vehicles, predominantly use cathodes made from critical materials like cobalt. Sulfur‐based cathodes, offering a high theoretical capacity of 1675 mAh g−1 and environmental advantages due to sulfur's abundance and lower toxicity, present a more sustainable alternative. However, state‐of‐the‐art sulfur‐based electrodes do not reach the theoretical capacities, mainly because conventional electrode production relies on mixing of components into weakly coordinated slurries. Consequently, sulfur‘s mobility leads to battery degradation—an effect known as the “sulfur‐shuttle”. This study introduces a solution by developing a microporous, covalently‐bonded, imine‐based polymer network grown in situ around sulfur particles on the current collector. The polymer network (i) enables selective transport of electrolyte and Li‐ions through pores of defined size, and (ii) acts as a robust host to retain the active component of the electrode (sulfur species). The resulting cathode has superior rate performance from 0.1 C (1360 mAh g−1) to 3 C (807 mAh g−1). Demonstrating a high‐performance, sustainable sulfur cathode produced via a simple one‐pot process, our research underlines the potential of microporous polymers in addressing sulfur diffusion issues, paving the way for sulfur electrodes as viable alternatives to traditional metal‐based cathodes.
High‐Entropy Alloys and Their Affinity with Hydrogen: From Cantor to Platinum Group Elements Alloys
(2024)
AbstractProperties of high‐entropy alloys are currently in the spotlight due to their promising applications. One of the least investigated aspects is the affinity of these alloys to hydrogen, its diffusion, and reactions. In this study, high pressure is applied at ambient temperature and stress‐induced diffusion of hydrogen is investigated into the structure of high‐entropy alloys (HEA) including the famous Cantor alloy as well as less known, but nevertheless important platinum group (PGM) alloys. By applying X‐ray diffraction to samples loaded into diamond anvil cells, a comparative investigation of transition element incorporating HEA alloys in Ne and H2 pressure‐transmitting media is performed at ambient temperature. Even under stresses far exceeding conventional industrial processes, both Cantor and PGM alloys show exceptional resistance to hydride formation, on par with widely used industrial grade Cu–Be alloys. The observations inspire optimism for practical HEA applications in hydrogen‐relevant industry and technology (e.g., coatings, etc), particularly those related to transport and storage.