TY - JOUR A1 - Zhao, Jun-Hua A1 - Lu, Lixin A1 - Zhang, Zhiliang A1 - Guo, Wanlin A1 - Rabczuk, Timon T1 - Continuum modeling of the cohesive energy for the interfaces between _lms, spheres, coats and substrates JF - Computational Materials Science N2 - Continuum modeling of the cohesive energy for the interfaces between _lms, spheres, coats and substrates KW - Angewandte Mathematik KW - Strukturmechanik Y1 - 2015 SP - 432 EP - 438 ER - TY - JOUR A1 - Zhao, Jun-Hua A1 - Jia, Yue A1 - Wei, Ning A1 - Rabczuk, Timon T1 - Binding energy and mechanical stability of two parallel and crossing carbon nanotubes JF - Journal of Applied Mechanics N2 - Binding energy and mechanical stability of two parallel and crossing carbon nanotubes KW - Angewandte Mathematik KW - Strukturmechanik Y1 - 2015 ER - TY - JOUR A1 - Zhao, Jiyun A1 - Lu, Lixin A1 - Rabczuk, Timon T1 - The tensile and shear failure behavior dependence on chain length and temperature in amorphous polymers JF - Computational Materials Science N2 - The tensile and shear failure behavior dependence on chain length and temperature in amorphous polymers KW - Angewandte Mathematik KW - Strukturmechanik Y1 - 2015 SP - 567 EP - 572 ER - TY - JOUR A1 - Yang, Shih-Wei A1 - Budarapu, Pattabhi Ramaiah A1 - Mahapatra, D.R. A1 - Bordas, Stéphane Pierre Alain A1 - Zi, Goangseup A1 - Rabczuk, Timon T1 - A Meshless Adaptive Multiscale Method for Fracture JF - Computational Materials Science N2 - A Meshless Adaptive Multiscale Method for Fracture KW - Angewandte Mathematik KW - Strukturmechanik Y1 - 2015 SP - 382 EP - 395 ER - TY - CHAP A1 - Wiggenbrock, Jens A1 - Smarsly, Kay ED - Gürlebeck, Klaus ED - Lahmer, Tom T1 - A GENERIC FRAMEWORK SUPPORTING DISTRIBUTED COMPUTING IN ENGINEERING APPLICATIONS T2 - Digital Proceedings, International Conference on the Applications of Computer Science and Mathematics in Architecture and Civil Engineering : July 20 - 22 2015, Bauhaus-University Weimar N2 - Modern distributed engineering applications are based on complex systems consisting of various subsystems that are connected through the Internet. Communication and collaboration within an entire system requires reliable and efficient data exchange between the subsystems. Middleware developed within the web evolution during the past years provides reliable and efficient data exchange for web applications, which can be adopted for solving the data exchange problems in distributed engineering applications. This paper presents a generic approach for reliable and efficient data exchange between engineering devices using existing middleware known from web applications. Different existing middleware is examined with respect to the suitability in engineering applications. In this paper, a suitable middleware is shown and a prototype implementation simulating distributed wind farm control is presented and validated using several performance measurements. KW - Angewandte Informatik KW - Angewandte Mathematik KW - Building Information Modeling KW - Computerunterstütztes Verfahren KW - Data, information and knowledge modeling in civil engineering; Function theoretic methods and PDE in engineering sciences; Mathematical methods for (robotics and) computer vision; Numerical modeling in engineering; Optimization in engineering applications Y1 - 2015 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:gbv:wim2-20170314-28260 SN - 1611-4086 ER - TY - JOUR A1 - Wang, Quan A1 - Arash, Behrouz T1 - Announcement of a virtual special issue on computational carbon nanoscience JF - Carbon N2 - The Carbon journal is pleased to introduce a themed collection of recent articles in the area of computational carbon nanoscience. This virtual special issue was assembled from previously published Carbon articles by Guest Editors Quan Wang and Behrouz Arash, and can be accessed as a set in the special issue section of the journal website homepage: www.journals.elsevier.com/carbon. The article below by our guest editors serves as an introduction to this virtual special issue, and also a commentary on the growing role of computation as a tool to understand the synthesis and properties of carbon nanoforms and their behavior in composite materials. KW - Kohlenstoff KW - Nanowissenschaften KW - Verbundwerkstoff Y1 - 2015 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:gbv:wim2-20170428-31695 SP - 370 EP - 372 ER - TY - JOUR A1 - Vu-Bac, N. A1 - Silani, Mohammad A1 - Lahmer, Tom A1 - Zhuang, Xiaoying A1 - Rabczuk, Timon T1 - A unified framework for stochastic predictions of Young's modulus of clay/epoxy nanocomposites (PCNs) JF - Computational Materials Science N2 - A unified framework for stochastic predictions of Young's modulus of clay/epoxy nanocomposites (PCNs) KW - Angewandte Mathematik KW - Stochastik KW - Strukturmechanik Y1 - 2015 SP - 520 EP - 535 ER - TY - JOUR A1 - Vu-Bac, N. A1 - Rafiee, Roham A1 - Zhuang, Xiaoying A1 - Lahmer, Tom A1 - Rabczuk, Timon T1 - Uncertainty quantification for multiscale modeling of polymer nanocomposites with correlated parameters JF - Composites Part B: Engineering N2 - Uncertainty quantification for multiscale modeling of polymer nanocomposites with correlated parameters KW - Angewandte Mathematik KW - Stochastik KW - Strukturmechanik Y1 - 2015 SP - 446 EP - 464 ER - TY - THES A1 - Vu, Bac Nam T1 - Stochastic uncertainty quantification for multiscale modeling of polymeric nanocomposites N2 - 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. KW - Polymere KW - nanocomposite KW - Nanoverbundstruktur KW - stochastic KW - multiscale Y1 - 2015 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:gbv:wim2-20160322-25551 ER - TY - CHAP A1 - Volkov, Andrey A1 - Kirschke, Heiko A1 - Chelyshkov, Pavel A1 - Sedov, Artem A1 - Lysenko, Denis ED - Gürlebeck, Klaus ED - Lahmer, Tom T1 - THE CRITERIA’S SET WITH INVARIANT DESIGN BUILDING ELEMENTS ON THE BASE OF THREE IMPUTATIONS: “CONVENIENCE”, “SAFETY” AND “ENERGY-EFFICIENCY” T2 - Digital Proceedings, International Conference on the Applications of Computer Science and Mathematics in Architecture and Civil Engineering : July 20 - 22 2015, Bauhaus-University Weimar N2 - The paper deals with the formalization of the criteria for constructing building management systems. We consider three criteria - “convenience”, “safety” and “energyefficiency”. For each objective proposed method of calculation. KW - Angewandte Informatik KW - Angewandte Mathematik KW - Building Information Modeling KW - Computerunterstütztes Verfahren KW - Data, information and knowledge modeling in civil engineering; Function theoretic methods and PDE in engineering sciences; Mathematical methods for (robotics and) computer vision; Numerical modeling in engineering; Optimization in engineering applications Y1 - 2015 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:gbv:wim2-20170314-27956 SN - 1611-4086 ER -