DFG Priority Program Research Articles

Mastering the rheology of fresh concrete: New knowledge from a DFG priority program SPP 2005

AbstractThe processing of cement‐based building materials represents the technological core in the construction and maintenance of structures. However, a scientific framework for mastering rheology‐based processes is still in an early stage of its development. The reason for this is the extremely high complexity of cementitious systems. This complexity includes the high chemical reactivity of mineral binders, the complex multi‐phase nature of fresh concrete or mortar, and a wide range of deformation rates during various technological processes, which result in extremely high demands for characterization and simulation methods. The goal of the DFG Priority Program SPP 2005 “Opus Fluidum Futurum – Rheology of reactive, multiscale, multiphase construction materials” is to ascertain and describe the scientific fundamentals for understanding and, subsequently, designing rheology‐based construction processes as well as for developing innovative, sustainable building materials and associated pioneering processing technologies. The article at hand presents the purpose and the structure of the collaborative research as well as the achievements of the priority program. Furthermore, it offers some insights into ongoing and planned research.

Experience with German Research Consortia in the Field of Chemical Biology of Native Nucleic Acid Modifications.

The chemical biology of native nucleic acid modifications has seen an intense upswing, first concerning DNA modifications in the field of epigenetics and then concerning RNA modifications in a field that was correspondingly rebaptized epitranscriptomics by analogy. The German Research Foundation (DFG) has funded several consortia with a scientific focus in these fields, strengthening the traditionally well-developed nucleic acid chemistry community and inciting it to team up with colleagues from the life sciences and data science to tackle interdisciplinary challenges. This Perspective focuses on the genesis, scientific outcome, and downstream impact of the DFG priority program SPP1784 and offers insight into how it fecundated further consortia in the field. Pertinent research was funded from mid-2015 to 2022, including an extension related to the coronavirus pandemic. Despite being a detriment to research activity in general, the pandemic has resulted in tremendously boosted interest in the field of RNA and RNA modifications as a consequence of their widespread and successful use in vaccination campaigns against SARS-CoV-2. Funded principal investigators published over 250 pertinent papers with a very substantial impact on the field. The program also helped to redirect numerous laboratories toward this dynamic field. Finally, SPP1784 spawned initiatives for several funded consortia that continue to drive the fields of nucleic acid modification.

Experiments on large-scale structures in fully developed turbulent pipe flow

The experimental results reported in present paper represent contributions from the Cottbus large pipe facility to DFG-priority program SPP 1881: Turbulent Superstructures. Fundamental questions regarding turbulence statistics and structures in fully developed turbulent pipe flow were addressed, utilizing thermal and optical measuring techniques integrated into the pipe facility. The facility enables unique in-situ calibration for the hot-wire probe and it has full optical access that allows performing Particle Image Velocimetry and 3D Lagrangian Particle Tracking measurements, resulting in consistent and accurate pipe flow data. A streamwise-spanwise field of view up to ≈20×2 pipe radii has been set for both optical techniques with 4–8 high resolution cameras for a friction Reynolds number range of 8⋅102≤R+≤18⋅103. The setup enabled field of measurements with an unprecedented dynamic range in turbulent pipe flow at high Reynolds numbers with spatial resolution better than 1 vector/mm. Proper Orthogonal Decomposition and Shake-The-Box algorithm were used, highlighting energy contents of the large-scale motions in fully developed turbulent pipe flow regime.

Large eddy simulation of iron(III) oxide nanoparticle synthesis in spray flames

The SpraySyn burner has been developed to investigate nanoparticle synthesis from spray flames by various diagnostic methods and simulations from research groups within the DFG (German Research Foundation) priority program SPP1980. We investigate the formation of iron oxide nanoparticles from iron nitrate dissolved in a mixture of ethanol and ethyl hexanoic acid. In the SpraySyn experiment, the nanoparticle precursor solution is injected and atomized via an air-blast nozzle, surrounded by a pilot flame. The solvent itself is combustible, such that the droplets evaporate at high heating rates in a highly reactive environment. We investigate the synthesis flame in large eddy simulations. The liquid droplets are described by Lagrangian particles, and gas-phase combustion is modeled by the flamelet-generated manifold approach with adaptations for particle inception. The nanoparticle dynamics are predicted by three models: a monodisperse model, a bimodal model, and a sectional model. The monodisperse and bimodal models account in terms of number-, surface-, and volume-concentration from inception, coagulation, and sintering processes, while the sectional model accounts for inception and coagulation and provides the particle size distribution. The comparison of nanoparticle sizes with the in-situ measurements shows that the bimodal model can be a suitable alternative approach to the computationally expensive sectional model.

Breathe and burn: Novel roles for myoglobin in thermogenesis

Breathe and burn: Novel roles for myoglobin in thermogenesis

Design of a 3D composite structure considering data uncertainties and various failure mechanisms

AbstractThis study has been performed within the research project MuScaBlaDes “Multi‐scale failure analysis with polymorphic uncertainties for optimal design of rotor blades” as part of the DFG Priority Programme (SPP 1886) “Polymorphic Uncertainty Modelling for the Numerical Design of Structures” started in 2016. A three‐dimensional structure consisting of glass fiber reinforced plastic (GFRP) components glued by epoxy resin (EP) is designed considering uncertainties in geometrical and material properties. Different stresses, the vertical deflection, the global stability and the fatigue behavior should fulfill the defined restrictions in the optimization process. A global optimum is searched for four different topologies by minimizing the elastic strain energy density as well as the overall manufacturing costs.

Method for Calculating Plastic Deformation of High Resolution and Large Contact Area

AbstractIn a rolling contact, the tribological properties in terms of friction, wear, and fatigue are significantly influenced by the surface roughness. Due to solid contact of the surfaces in the contact area, the roughness and thus also the tribological properties change during the service life of the contact. The initial load leads to major changes of the tribological properties figured out by Brecher et al. (2019, “Influence of the Metalworking Fluid on the Micropitting Wear of Gears,” Wear, 61(434–435), p. 202996). Prediction of the initial changes in topography in the contact area is necessary for specific optimization of rolling contacts. Especially for dry rolling–sliding contact, the roughness of the surfaces is crucial for the lifetime, which is part of the investigations within the DFG priority program 2074 (357505886). In this work, an elastic-plastic contact algorithm for calculating plastic deformation for dry contact of rough surfaces with large contact area and high resolution is presented. Due to the nonlinearity behavior associated with plastic deformation, the plastic contact algorithm is based on an iterative approach. An optimized meshing strategy is implemented to calculate the elastic pressure distribution on the surface. Corresponding to the two-dimensional pressure distribution, the three-dimensional stress distribution allows the consideration of residual stresses and interactions of the microscopic peaks of the rough surface. Furthermore, the three-dimensional plastic strain distribution allows the application of an analytical approach to represent the plastic deformation of the surface. Finally, the solution of a plastic contact calculation with an exemplary topography measured on a real rough surface is presented.

Analysis of model and data uncertainties for the failure of adhesive bonds in composite materials

AbstractThis study has been performed within the research project MuScaBlaDes “Multi‐scale failure analysis with polymorphic uncertainties for optimal design of rotor blades" as part of the DFG Priority Programme (SPP 1886) “Polymorphic Uncertainty Modelling for the Numerical Design of Structures" started in 2016. Stress concentrations in adhesive bonds of a composite structure influence the structural integrity and can initiate the overall failure. Their numerical prediction always depends on present model and data uncertainties. For that, the development of an efficient numerical model and the role of the quality of data is presented. The assessment of the numerical models is shown by comparing predicted strains to measured ones.

Numerical analysis of plain and fiber reinforced concrete structures during cyclic loading: Influence of frictional sliding and crack roughness

AbstractConcrete is a quasi‐brittle material, characterized by a non‐negligible, finite‐sized fracture process zone (FPZ) in which various toughening mechanisms play a significant role on crack development and propagation. Concrete is often reinforced with fibers to improve the serviceability and longevity of concrete structures by controlling the maximal crack widths and providing residual carrying capacity to initiated cracks. In quasi‐brittle materials such as concrete, toughening mechanisms such as crack deflection due to the presence of large heterogeneities, contact shielding, i.e., wedging and crack closure induced by debris and rough crack faces, crack bridging by tough aggregates, unbroken ligaments and fibers (in fiber‐reinforced concretes), are mostly governing damage evolution under monotonic and especially under cyclic loadings [1]. All these items contribute to a complex non‐linear response in terms of load‐displacement curves observed in experimental investigations. Many investigations have been performed on plain concrete, but not so many for high‐performance fiber‐reinforced concrete [2] which is the main subject of investigation within the DFG Priority Program 2020. In order to better understand the influence of these toughening mechanisms on the formation of hysteresis during cyclic loading‐unloading of plain and steel fiber‐reinforced high‐performance concrete, we model these mechanisms and their evolving influence on damage development using a discrete crack approach, and take into account the imperfect closure of cracks and friction between crack faces that come in contact during loading/unloading of the specimen. Within the scope of this contribution, we present the formulation of the model and illustrate its performance through selected numerical experiments under monotonic and cyclic loading of plain and fiber‐reinforced high‐performance concrete specimens. Model predictions are compared with laboratory measurements.

Experimental platforms for the investigation of spatiotemporal patterns in the rhizosphere—Laboratory and field scale

AbstractThe numerous feedback loops between roots, microorganisms, soil chemical and physical properties, and environmental variables result in spatial parameter patterns which are highly dynamic in time. In order to improve our understanding of the related rhizosphere processes and their relevance at the soil–plant system scale, experimental platforms are required. Those platforms should enable (1) to relate small scale observations (nm to dm) to system behaviour, (2) the integration of physical, chemical and biological sampling approaches within the same experiment, and (3) sampling at different time points during the life cycle of the system in question. Here we describe what requirements have to be met and to what extent this has been achieved in practice by the experimental platforms which were set up within the framework of DFG priority programme 2089 “Rhizosphere Spatiotemporal Organisation—a key to rhizosphere functions”. It is discussed to what extent theoretical considerations could be accommodated, in particular for the comparison across scales, i.e., from laboratory to field scale. The latter scale is of utmost importance to overcome the trade‐off between fraction of life cycle covered and the avoidance of unrealistic root length densities.

Relational and Fine-Grained Argument Mining

In our project ReMLAV, funded within the DFG Priority Program RATIO (http://www.spp-ratio.de/), we focus on relational and fine-grained argument mining. In this article, we first introduce the problems we address and then summarize related work. The main part of the article describes our research on argument mining, both coarse-grained and fine-grained methods, and on same-side stance classification, a relational approach to the problem of stance classification. We conclude with an outlook.

DFG priority program SPP 1613 “Fuels Produced Regeneratively Through Light-Driven Water Splitting”

Article DFG priority program SPP 1613 “Fuels Produced Regeneratively Through Light-Driven Water Splitting” was published on June 1, 2020 in the journal Zeitschrift für Physikalische Chemie (volume 234, issue 6).

DFG priority program SPP 1613 “Fuels Produced Regeneratively Through Light-Driven Water Splitting”

Article DFG priority program SPP 1613 “Fuels Produced Regeneratively Through Light-Driven Water Splitting” was published on May 1, 2020 in the journal Zeitschrift für Physikalische Chemie (volume 234, issue 5).

PARTEC 2019 – Overcome the Challenges in Particle and Powder Technology

AbstractNo abstract.

DFG priority program SPP 1613 “Fuels Produced Regeneratively Through Light-Driven Water Splitting”

Article DFG priority program SPP 1613 “Fuels Produced Regeneratively Through Light-Driven Water Splitting” was published on April 1, 2020 in the journal Zeitschrift für Physikalische Chemie (volume 234, issue 4).

Large-scale graph generation: Recent results of the SPP 1736 – Part II

Abstract The selection of input data is a crucial step in virtually every empirical study. Experimental campaigns in algorithm engineering, experimental algorithmics, network analysis, and many other fields often require suited network data. In this context, synthetic graphs play an important role, as data sets of observed networks are typically scarce, biased, not sufficiently understood, and may pose logistic and legal challenges. Just like processing huge graphs becomes challenging in the big data setting, new algorithmic approaches are necessary to generate such massive instances efficiently. Here, we update our previous survey [35] on results for large-scale graph generation obtained within the DFG priority programme SPP 1736 (Algorithms for Big Data); to this end, we broaden the scope and include recently published results.

Design Considerations of Efficient Photo-Electrosynthetic Cells and its Realization Using Buried Junction Si Thin Film Multi Absorber Cells

AbstractAs is obvious from previous work on semiconductor photoelectrochemistry, single junction semiconductors do not provide either the required maximum photovoltage or a high photocurrent for solar water splitting, which is required for efficient stand-alone devices. From these experiences we conclude, that multi-junction devices must be developed for bias-free water splitting. In this article we present our design considerations needed for the development of efficient photo-electro-synthetic cells, which have guided us during the DFG priority program 1613. At first, we discuss the fundamental requirements, which must be fulfilled to lead to effective solar water splitting devices. Buried junction and photoelectrochemical arrangements are compared. It will become clear, that the photovoltaic (PV) and electrochemical (EC) components can be optimized separately, but that maximized conversion efficiencies need photovoltages produced in the photovoltaic part of the device, which are adapted to the electrochemical performance of the electrolyzer components without energetic losses in their coupling across the involved interfaces. Therefore, in part 2 we will present the needs to develop appropriate interface engineering layers for proper chemical and electronic surface passivation. In addition, highly efficient electrocatalysts, either for the hydrogen or oxygen evolution reaction (HER, OER), must be adjusted in their energetic coupling to the semiconductor band edges and to the redox potentials in the electrolyte with minimized losses in the chemical potentials. The third part of our paper describes at first the demands and achievements on developing multijunction thin-film silicon solar cells. With different arrangements of silicon stacks a wide range of photovoltages and photocurrents can be provided. These solar cells are applied as photocathodes in integrated directly coupled PV-EC devices. For this purpose thin Pt and Ni catalyst layers are used on top of the solar cells for the HER and a wire connected RuO2counter electrode is used for the OER. Electrochemical stability has been successfully tested for up to 10,000 s in 0.1 M KOH. Furthermore, we will illustrate our experimental results on interface engineering strategies using TiO2as buffer layer and Pt nanostructures as HER catalyst. Based on the obtained results the observed improvements, but also the still given limitations, can be related to clearly identified non-idealities in surface engineering either related to recombination losses at the semiconductor surface reducing photocurrents or due to not properly-aligned energy states leading to potential losses across the interfaces.

Water‐induced failure mechanics for concrete

AbstractThis work outlines a micro‐mechanical framework for modeling water‐induced damage mechanism of concrete. Concrete has a highly heterogeneous micro‐structure and its composite behavior is very complex. Due to that various effects must be considered for analyzing failure response at micro scale, e.g. modeling the solid skeleton, fluid bulk phases and their interaction. For obtaining a deeper understanding of the influence of water on the concrete at the micro‐level, a micro‐computed‐tomography (micro‐CT) scan has been conducted at IfB to illustrate the micro‐structure geometry and concrete content. These data are required to build the constitutive model and the design of the numerical simulations, in line with [1]. Then a micro‐mechanical model is developed for the coupled problem of fluid‐saturated heterogeneous porous media at fracture. The modeling of microscopic cracks in porous heterogeneous media can be achieved in a convenient way by a continuum phase‐field approach, which is based on the regularization of sharp crack discontinuities [2,3]. This avoids the use of complex discretization methods for crack discontinuities, and can account for complex crack patterns. The numerical examples proposed in this contribution stem out from the DFG Priority Program SPP 2020 “Cyclic Damage Processes in High‐Performance Concretes in the Experimental Virtual Lab”.

New findings in the research of concrete fatigue

An increasing use of high-performance concretes—accompanied by an increasing slenderness of structures—will require a specific fatigue design more often. This holds true especially for structures having to resist very high numbers of load cycles throughout their operating service life. Generally, these are long spanning, slender bridge structures, structures for wind energy turbines or machine foundations. For standard structures—and most common bridges—the fatigue resistance of concrete does not become decisive in design. Before the introduction of Eurocode 2 and CEB/FIP Model Code 1990—with design concepts based on Wöhler-curves—research regarding concrete fatigue was rare and often focused on counting the bearable number of cycles until failure. However, knowledge at time on the gradual deterioration phenomena, which finally results in a fatigue failure, was hardly available. In the time since, design rules were cautiously corrected, for example, in fib Model Code 2010, but, knowledge on the mechanisms of fatigue deterioration is still very limited. With the development of concretes with higher compressive strengths, more slender structures have become possible, in which the ratio of the dead load to the variable loads, relevant for fatigue, has substantially decreased. These concretes often show compressive strengths exceeding 100 MPa, outstanding workability, small maximum grain sizes and additionally contain fiber reinforcement. These concretes are hardly comparable to conventional concrete mixtures. For this reason, research about the phenomena of deterioration of high-performance concrete was intensified over the last decade. Currently, a large joint research project is the Priority Programme 2020 “Cyclic Deterioration of High-Performance Concrete in an Experimental-Virtual Lab” which is funded by the German Research Foundation (DFG). Within various tandem-projects experts in material science, building materials technology and numerical modeling are working together to identify and characterize the damage mechanisms under fatigue loading and to develop quantitative prediction models. On the occasion of the 65th birthday of Professor Ludger Lohaus, Institute of Building Materials Science at Leibniz University of Hannover, Germany, who is the initiator and coordinator of the aforementioned DFG Priority Programme 2020, this issue of “Structural Concrete” is partly dedicated to fatigue and cyclic behavior of concrete and concrete structures. Professor Lohaus has been very active in the research on concrete fatigue and has driven it forward in many regards. It has been his continuing effort to transfer fundamental research results into practice (especially in structures for offshore wind-energy) and standardization, whether for Eurocode 2, fib Model Code 2010 or for the current preparations for fib Model Code 2020. The undersigned congratulate him very warmly on his birthday—also on behalf of the involved researchers of the DFG Priority Programme 2020—and we wish him all the best for the future, especially good health. We hope you enjoy reading this issue and wish you new insights and inspirations. The authors are members of the Programme Committee of the DFG Priority Programme 2020 “Cyclic Deterioration of High-Performance Concrete in an Experimental-Virtual Lab,” funded by the German Research Foundation (DFG).

Analysis of polymorphic data uncertainties in engineering applications

In this contribution, several case studies with data uncertainties are presented which have been performed in individual projects as part of the DFG (German Research Foundation) Priority Programme SPP 1886 “Polymorphic uncertainty modelling for the numerical design of structures.” In all case studies numerical models with uncertainties are derived from engineering problems describing concepts for handling and incorporating measurement data, either of model input parameters or of the system response. The first case study deals with polymorphic uncertain data based on computer tomographic scans with respect to air voids which are acquired, simplified and integrated in numerical models of adhesive bonds. In the second case study, the variation sensitivity analysis is presented to provide suitable prior knowledge for numerical soil analyses, for example, in order to reduce required input data. The uncertainty in friction processes is treated in case study 3 whereby measurement data are used in data driven methods to improve the numerical predictions. In case study 4, the failure behavior of die‐cast window hinges, which is affected by an uncertain initial pore distribution, is investigated by means of a Markov chain approach. In the last two case studies, mathematical methods of statistical inference and updating algorithms for uncertainty models are shown. Due to the heterogeneous spectrum of problems, a generalized strategy for data modeling, acquisition, and assimilation is developed and applied on each case study.