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The upper limit of the thermal conductivity and the mechanical strength are predicted for the polyethylene chain, by performing the ab initio calculation and applying the quantum mechanical non-equilibrium Green’s function approach. Specially, there are two main findings from our calculation: (1) the thermal conductivity can reach a high value of 310 Wm−1 K−1 in a 100 nm polyethylene chain at room temperature and the thermal conductivity increases with the length of the chain; (2) the Young’s modulus in the polyethylene chain is as high as 374.5 GPa, and the polyethylene chain can sustain 32.85%±0.05% (ultimate) strain before undergoing structural phase transition into gaseous ethylene.
In this study, the behavior of a widely graded soil prone to suffusion and necessity of homogeneity quantifi cation for such a soil in internal stability considerations are discussed. With the help of suffusion tests, the dependency of the particle washout to homogeneity of sample is shown. The validity of the great infl uence of homogeneity on suffusion processes by the presentation of arguments and evidences are established. It is emphasized that the internal stability of a widely graded soil cannot be directly correlated to the common geotechnical parameters such as dry density or permeability. The initiation and propagation of the suffusion processes are clearly a particle scale phenomenon, so the homogeneity of particle assemblies (micro-scale) has a decisive effect on particle rearrangement and washout processes. It is addressed that the guidelines for assessing internal stability lack a fundamental, scientifi c basis for quantifi cation of homogeneity. The observation of the segregation processes within the sample in an ascending layered order (for downwards fl ow) inspired the author to propose a new packing model for granular materials which are prone to internally instability.
It is shown that the particle arrangement, especially the arrangement of soil skeleton particles or the so-called primary fabric has the main role in suffusiv processes. Therefore, an experimental approach for identifi cation of the skeleton in the soil matrix is proposed. 3D models of Sequential Fill Tests using Discrete Element Method (DEM) and 3D models of granular packings for relative, stochastically and ideal homogeneous particle assemblies were generated, and simulations have been carried out.
Based on the numerical investigations and in dependency on the soil skeleton behavior, an approach for measurement of relevant scale, the so-called Representative Elementary Volume (REV) for homogeneity investigation is proposed. The development of a new testing method for quantifi cation of homogeneity is introduced (in-situ). An approach for quantifi cation of homogeneity in numerically or experimentally generated packings (samples) based on image processing method of MATLAB has been introduced. A generalized experimental method for assessment of internal stability for widely graded soils with dominant coarse matrix is developed, and a new suffusion criterion based on ideal homogeneous internally stable granular packing is designed.
My research emphasizes that in a widely graded soils with dominant coarse matrix, the soil fractions with diameters bigger than D60 build essentially the soil skeleton. The mass and spatial distribution of these fractions governs the internal stability, and the mass and distribution of the fi ll fractions are a secondary matter. For such a soil, the homogeneity of the skeleton must be cautiously measured and verified.
Nanostructured materials are extensively applied in many fields of material science for new industrial applications, particularly in the automotive, aerospace industry due to their exceptional physical and mechanical properties. Experimental testing of nanomaterials is expensive, timeconsuming,challenging and sometimes unfeasible. Therefore,computational simulations have been employed as alternative method to predict macroscopic material properties. The behavior of polymeric nanocomposites (PNCs) are highly complex.
The origins of macroscopic material properties reside in the properties and interactions taking place on finer scales. It is therefore essential to use multiscale modeling strategy to properly account for all large length and time scales associated with these material systems, which across many orders of magnitude. Numerous multiscale models of PNCs have been established, however, most of them connect only two scales. There are a few multiscale models for PNCs bridging four length scales (nano-, micro-, meso- and macro-scales). In addition, nanomaterials are stochastic in nature and the prediction of macroscopic mechanical properties are influenced by many factors such as fine-scale features. The predicted mechanical properties obtained by traditional approaches significantly deviate from the measured values in experiments due to neglecting uncertainty of material features. This discrepancy is indicated that the effective macroscopic properties of materials are highly sensitive to various sources of uncertainty, such as loading and boundary conditions and material characteristics, etc., while very few stochastic multiscale models for PNCs have been developed. Therefore, it is essential to construct PNC models within the framework of stochastic modeling and quantify the stochastic effect of the input parameters on the macroscopic mechanical properties of those materials.
This study aims to develop computational models at four length scales (nano-, micro-, meso- and macro-scales) and hierarchical upscaling approaches bridging length scales from nano- to macro-scales. A framework for uncertainty quantification (UQ) applied to predict the mechanical properties
of the PNCs in dependence of material features at different scales is studied. Sensitivity and uncertainty analysis are of great helps in quantifying the effect of input parameters, considering both main and interaction effects, on the mechanical properties of the PNCs. To achieve this major
goal, the following tasks are carried out:
At nano-scale, molecular dynamics (MD) were used to investigate deformation mechanism of glassy amorphous polyethylene (PE) in dependence of temperature and strain rate. Steered molecular dynamics (SMD)were also employed to investigate interfacial characteristic of the PNCs.
At mico-scale, we developed an atomistic-based continuum model represented by a representative volume element (RVE) in which the SWNT’s properties and the SWNT/polymer interphase are modeled at nano-scale, the surrounding polymer matrix is modeled by solid elements. Then, a two-parameter model was employed at meso-scale. A hierarchical multiscale approach has been developed to obtain the structure-property relations at one length scale and transfer the effect to the higher length
scales. In particular, we homogenized the RVE into an equivalent fiber.
The equivalent fiber was then employed in a micromechanical analysis (i.e. Mori-Tanaka model) to predict the effective macroscopic properties of the PNC. Furthermore, an averaging homogenization process was also used to obtain the effective stiffness of the PCN at meso-scale.
Stochastic modeling and uncertainty quantification consist of the following ingredients:
- Simple random sampling, Latin hypercube sampling, Sobol’ quasirandom sequences, Iman and Conover’s method (inducing correlation in Latin hypercube sampling) are employed to generate independent and dependent sample data, respectively.
- Surrogate models, such as polynomial regression, moving least squares (MLS), hybrid method combining polynomial regression and MLS, Kriging regression, and penalized spline regression, are employed as an approximation of a mechanical model. The advantage of the surrogate models is the high computational efficiency and robust as they can be constructed from a limited amount of available data.
- Global sensitivity analysis (SA) methods, such as variance-based methods for models with independent and dependent input parameters, Fourier-based techniques for performing variance-based methods and partial derivatives, elementary effects in the context of local SA, are used to quantify the effects of input parameters and their interactions on the mechanical properties of the PNCs. A bootstrap technique is used to assess the robustness of the global SA methods with respect to their performance.
In addition, the probability distribution of mechanical properties are determined by using the probability plot method. The upper and lower bounds of the predicted Young’s modulus according to 95 % prediction intervals were provided.
The above-mentioned methods study on the behaviour of intact materials. Novel numerical methods such as a node-based smoothed extended finite element method (NS-XFEM) and an edge-based smoothed phantom node method (ES-Phantom node) were developed for fracture problems. These methods can be used to account for crack at macro-scale for future works. The predicted mechanical properties were validated and verified. They show good agreement with previous experimental and simulations results.
The polymeric clay nanocomposites are a new class of materials of which recently have become the centre of attention due to their superior mechanical and physical properties. Several studies have been performed on the mechanical characterisation of these nanocomposites; however most of those studies have neglected the effect of the interfacial region between the clays and the matrix despite of its significant influence on the mechanical performance of the nanocomposites.
There are different analytical methods to calculate the overall elastic material properties of the composites. In this study we use the Mori-Tanaka method to determine the overall stiffness of the composites for simple inclusion geometries of cylinder and sphere. Furthermore, the effect of interphase layer on the overall properties of composites is calculated. Here, we intend to get ounds for the effective mechanical properties to compare with the analytical results. Hence, we use linear displacement boundary conditions (LD) and uniform traction boundary conditions (UT) accordingly. Finally, the analytical results are compared with numerical results and they are in a good agreement.
The next focus of this dissertation is a computational approach with a hierarchical multiscale method on the mesoscopic level. In other words, in this study we use the stochastic analysis and computational homogenization method to analyse the effect of thickness and stiffness of the interfacial region on the overall elastic properties of the clay/epoxy nanocomposites. The results show that the increase in interphase thickness, reduces the stiffness of the clay/epoxy naocomposites and this decrease becomes significant in higher clay contents. The results of the sensitivity analysis prove that the stiffness of the interphase layer has more significant effect on the final stiffness of nanocomposites. We also validate the results with the available experimental results from the literature which show good agreement.
This paper presents a novel numerical procedure based on the framework of isogeometric analysis for static, free vibration, and buckling analysis of laminated composite plates using the first-order shear deformation theory. The isogeometric approach utilizes non-uniform rational B-splines to implement for the quadratic, cubic, and quartic elements. Shear locking problem still exists in the stiffness formulation, and hence, it can be significantly alleviated by a stabilization technique. Several numerical examples are presented to show the performance of the method, and the results obtained are compared with other available ones.
Spatial time domain reflectometry (spatial TDR) is a new measurement method for determining water content profiles along elongated probes (transmission lines). The method is based on the inverse modeling of TDR reflectograms using an optimization algorithm. By means of using flat ribbon cables it is possible to take two independent TDRmeasurements from both ends of the probe, which are used to improve the spatial information content of the optimization results and to consider effects caused by electrical conductivity. The method has been used for monitoring water content distributions on a full-scale levee model made of well-graded clean sand. Flood simulation tests, irrigation tests, and long-term observations were carried out on the model. The results show that spatial TDR is able to determine water content distributions with an accuracy of the spatial resolution of about ±3 cm compared to pore pressure measurements and an average deviation of ±2 vol % compared to measurements made using another independent TDR measurement system.
The present article aims to provide an overview of the consequences of dynamic soil-structure interaction (SSI) on building structures and the available modelling techniques to resolve SSI problems. The role of SSI has been traditionally considered beneficial to the response of structures. However, contemporary studies and evidence from past earthquakes showed detrimental effects of SSI in certain conditions. An overview of the related investigations and findings is presented and discussed in this article. Additionally, the main approaches to evaluate seismic soil-structure interaction problems with the commonly used modelling techniques and computational methods are highlighted. The strength, limitations, and application cases of each model are also discussed and compared. Moreover, the role of SSI in various design codes and global guidelines is summarized. Finally, the advancements and recent findings on the SSI effects on the seismic response of buildings with different structural systems and foundation types are presented. In addition, with the aim of helping new researchers to improve previous findings, the research gaps and future research tendencies in the SSI field are pointed out.
We perform both classical molecular dynamics simulations and beam model calculations to investigate the Young's modulus of kinked silicon nanowires (KSiNWs). The Young's modulus is found to be highly sensitive to the arm length of the kink and is essentially inversely proportional to the arm length. The mechanism underlying the size dependence is found to be the interplay between the kink angle potential and the arm length potential, where we obtain an analytic relationship between the Young's modulus and the arm length of the KSiNW. Our results provide insight into the application of this novel building block in nanomechanical devices.
Der vorliegende Beitrag beschreibt die Problematik bei der Prognose verkehrsbedingter Schadstoff-Immissionen. Im Mittelpunkt steht die Entwicklung und der Aufbau einer Simulationsumgebung zur Evaluation von umweltorientierten Verkehrsmanagement-Strategien. Die Simulationsumgebung wird über die drei Felder Verkehr, Emission, Immission entwickelt und findet zunächst Anwendung in der Evaluation verkehrlicher Maßnahmen für die Friedberger Landstraße in Frankfurt am Main.
Scaling of concrete due to salt frost attack is an important durability issue in moderate and cold climates. The actual damage mechanism is still not completely understood. Two recent damage theories—the glue spall theory and the cryogenic suction theory—offer plausible, but conflicting explanations for the salt frost scaling mechanism. The present study deals with the cryogenic suction theory, which assumes that freezing concrete can take up unfrozen brine from a partly frozen deicing solution during salt frost attack. According to the model hypothesis, the resulting saturation of the concrete surface layer intensifies the ice formation in this layer and causes salt frost scaling. In this study an experimental technique was developed that makes it possible to quantify to which extent brine uptake can increase ice formation in hardened cement paste (used as a model material for concrete). The experiments were carried out with low temperature differential scanning calorimetry, where specimens were subjected to freeze–thaw cycles while being in contact with NaCl brine. Results showed that the ice content in the specimens increased with subsequent freeze–thaw cycles due to the brine uptake at temperatures below 0 °C. The ability of the hardened cement paste to bind chlorides from the absorbed brine at the same time affected the freezing/melting behavior of the pore solution and the magnitude of the ice content.