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Ein Riss im Rotor ruft eine lokale Steifigkeitsänderung hervor. Die vorliegende Arbeit ermittelt die Steifigkeitsänderung einer angerissenen Welle. Dazu wird ein Kohäsivzonenmodell eingesetzt. Das Modell wurde für die erste Rissöffnungsmode bei ebenem Verzerrungszustand in Abhängigkeit der Mehrachsigkeit des Spannungszustandes (Triaxialität) entwickelt. Außerdemwird das Kohäsivzonenmodell bei einem eindimensionalen Kontinuumsrotor als FE Modell ausgeführt.
The objective of this work is to develop a method which solves the nonlinear elastohydrodynamic contact problem in a fast and precise way using model order reduction techniques. The reduction procedure is based on a projection onto a low-dimensional subspace using different hyper-reduction procedures. The method provides fast and highly accurate reduced order models for stationary and transient, Newtonian and Non-Newtonian EHD line and point contact problems.
The gas foil bearing (GFB) technology is a key factor for the transition to oil-free rotating machinery. Among numerous advantages, GFBs offer the unique ability to be lubricated with working fluids such as refrigerants. However, the computational analysis of refrigerant-lubricated GFB–rotor systems represents an interdisciplinary problem of enormous complexity. This work pushes forward existing limits of feasibility and establishes a new strategy that enables stability and bifurcation analyses.
The impact of two non-uniform elastic rods is considered and a recursive method was developed that solves the inverse problem: Find the location-dependent impedance function of the impacting rod that generates a prescribed impact force. The developed method delivers exact solutions in closed-form. Moreover, a condition is derived which states if a physically meaningful solution exists. Finally, the underlying 1D model has been validated experimentally.
A specific cost-efficient type of plain journal bearing is the porous journal bearing, which possesses a pervious bush that serves as a lubricant reservoir. The current work is concerned with modeling porous journal bearings in multibody systems, for which dynamical models are needed to investigate the bearing's behavior. Such porous journal bearing models as well as models of elementary rotor-bearing systems including these, were developed and investigated during the course for this work.
To counter lubricant shortage at a frictional contact (starvation), lubrication liquids, e.g. oils, are actively transported from a distant location towards the undersupplied tribocontact. This is done via small channels or generally via structures cut into a flat surface. In this way one can use capillary force as a cheap and reliable driver of the lubricant flow. Numerical modeling and experiments show that this method can be considered a promising new option to enhance tribocontact operation.
This work considers dampers that do not solely focus on a single strategy but instead combine them. The capabilities of conventional dry friction dampers are expanded by taking into account piecewise defined contact geometries. This leads to friction dampers that change their behavior depending on the amplitude of the oscillations. The vibration damping device in this work, introduces damping at high oscillation amplitudes and takes advantage of absorption at low oscillation amplitudes.
This work presents an efficient solution procedure for the elastohydrodynamic (EHD) contact problem considering structural dynamics. The contact bodies are modeled using reduced finite element models. Singly diagonal implicit Runge-Kutta (SDIRK) methods are used for adaptive time integration. The structural model is coupled with the nonlinear Reynolds Equation using a monolithic coupling approach. Finally, a reduced order model of the complete nonlinear coupled problem is constructed.
A nonparametric identification method for highly nonlinear systems is presented that is able to reconstruct the underlying nonlinearities without a priori knowledge of the describing nonlinear functions. The approach is based on nonlinear Kalman Filter algorithms using the well-known state augmentation technique that turns the filter into a dual state and parameter estimator, of which an extension towards nonparametric identification is proposed in the present work.