TY - THES A1 - Bendalla, Abdulmagid Sedig Khalafallah T1 - Nonlinear Numerical Modelling of Cable Elements in Bridges for Dynamic Analysis N2 - Identifying cable force with vibration-based methods has become widely used in engineering practice due to simplicity of application. The string taut theory provides a simple definition of the relationship between natural frequencies and the tension force of a cable. However, this theory assumes a perfectly flexible non-sagging cable pinned at its ends. These assumptions do not reflect all cases, especially when the cable is short, under low tension forces or the supports are partially flexible. Extradosed bridges, which are distinguished from cable-stayed bridges by their low pylon height, have shorter cables. Therefore the application of the conventional string taut theory to identify cable forces on extradosed bridge cables might be inadequate to identify cable forces. In this work, numerical modelling of an extradosed bridge cable saddled on a circular deviator at pylon is conducted. The model is validated with the catenary analytical solution and its static and dynamic behaviours are studied. The effect of a saddle support is found to positively affect the cable stiffness by geometric means; longer saddle radius increases the cable stiffness by suppressing the deformations near the saddle. Further, accounting the effects of bending stiffness in the numerical model by using beam elements show considerable deviation from models with truss elements (i.e. zero bending stiffness). This deviation is manifested when comparing the static and dynamic properties. This motivates a more thorough study of bending stiffness effects on short cables. Bending stiffness effects are studied using two rods connected with several springs along their length. Under bending moments, the springs resist the rods' relative axial displacement by the springs' transverse component. This concept is used to identify bending stiffness values by utilizing the parallel axis theorem to quantify ratios of the second moment of area. These ratios are calculated based on the setup of the springs (e.g. number of springs per unit length, transverse stiffness, etc...). The numerical model based on this concept agrees well with the theoretical values computed using upper and lower bounds of the parallel axis theorem. The proposed concept of quantifying ratios of the second moment of area using springs as connection between cable rods is applied on an actual extradosed bridge geometry. The model is examined by comparison to the previously validated global numerical model. The two models showed good correlation under various changing parameters. This allowed further study of the effects of stick/slip behaviour between cable rods on an actual bridge geometry. KW - Kabel KW - Nonlinear Cable Analysis KW - Bending Stiffness of cable elements KW - Biegesteifigkeit Y1 - 2019 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:gbv:wim2-20191007-39940 ER - TY - THES A1 - Düring, Serjoscha T1 - Between plan and reality: tracing the development dynamics of the Lanzhou New Area - a computational approach N2 - Contemporary planning practice is often criticized as too design-driven with a lack of both quantitative evaluation criteria and employment of models that anticipate the self-organizational forces shaping cities, resulting in significant gaps between plan and reality. This study aims to introduce a modular toolbox prototype for spatial-analysis in data-poor environments. It is proposed to integrate designing, evaluation, and monitoring of urban development into one framework, thus supporting data-driven, on-demand urban design, and planning processes. The proposed framework’s value will exemplarily be tested, focussing on the analysis and simulation of spatiotemporal growth trajectories taking the Lanzhou New Area as a case-study - a large scale new town project that struggles to attract residents and businesses. Conducted analysis suggests that more attention should be given to spatiotemporal development paths to ensure that cities work more efficiently throughout any stage of development. Finally, early hints on general design strategies to achieve this goal are discussed with the assistance of the proposed toolbox. KW - Stadtplanung KW - Geoinformationssystem KW - evidence-based design KW - computational planning KW - network analysis KW - Grasshopper 3D KW - spatial analysis Y1 - 2019 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:gbv:wim2-20191108-40002 ER - TY - THES A1 - von Butler, Natalie T1 - Scalarization Methods for Multi-Objective Structural Optimization N2 - Scalarization methods are a category of multiobjective optimization (MOO) methods. These methods allow the usage of conventional single objective optimization algorithms, as scalarization methods reformulate the MOO problem into a single objective optimization problem. The scalarization methods analysed within this thesis are the Weighted Sum (WS), the Epsilon-Constraint (EC), and the MinMax (MM) method. After explaining the approach of each method, the WS, EC and MM are applied, a-posteriori, to three different examples: to the Kursawe function; to the ten bar truss, a common benchmark problem in structural optimization; and to the metamodel of an aero engine exit module. The aim is to evaluate and compare the performance of each scalarization method that is examined within this thesis. The evaluation is conducted using performance metrics, such as the hypervolume and the generational distance, as well as using visual comparison. The application to the three examples gives insight into the advantages and disadvantages of each method, and provides further understanding of an adequate application of the methods concerning high dimensional optimization problems. KW - Mehrkriterielle Optimierung KW - Gestaltoptimierung KW - Multiobjective Optimization KW - Structural Optimization KW - Scalarization Methods Y1 - 2019 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:gbv:wim2-20191030-40106 ER - TY - THES A1 - Zafar, Usman T1 - Probabilistic Reliability Analysis of Wind Turbines N2 - Renewable energy use is on the rise and these alternative resources of energy can help combat with the climate change. Around 80% of the world's electricity comes from coal and petroleum however, the renewables are the fastest growing source of energy in the world. Solar, wind, hydro, geothermal and biogas are the most common forms of renewable energy. Among them, wind energy is emerging as a reliable and large-scaled source of power production. The recent research and confidence in the performance has led to the construction of more and bigger wind turbines around the world. As wind turbines are getting bigger, a concern regarding their safety is also in discussion. Wind turbines are expensive machinery to construct and the enormous capital investment is one of the main reasons, why many countries are unable to adopt to the wind energy. Generally, a reliable wind turbine will result in better performance and assist in minimizing the cost of operation. If a wind turbine fails, it's a loss of investment and can be harmful for the surrounding habitat. This thesis aims towards estimating the reliability of an offshore wind turbine. A model of Jacket type offshore wind turbine is prepared by using finite element software package ABAQUS and is compared with the structural failure criteria of the wind turbine tower. UQLab, which is a general uncertainty quantification framework developed at ETH Zürich, is used for the reliability analysis. Several probabilistic methods are included in the framework of UQLab, which include Monte Carlo, First Order Reliability Analysis and Adaptive Kriging Monte Carlo simulation. This reliability study is performed only for the structural failure of the wind turbine but it can be extended to many other forms of failures e.g. reliability for power production, or reliability for different component failures etc. It's a useful tool that can be utilized to estimate the reliability of future wind turbines, that could result in more safer and better performance of wind turbines. KW - Windturbine KW - Windenergie KW - Wind Turbines KW - Wind Energy KW - Reliability Analysis KW - Zuverlässigkeitsanalyse Y1 - 2019 U6 - http://dx.doi.org/10.25643/bauhaus-universitaet.3977 ER -