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Leading edge serrations are well-known for their aeroacoustic potential in reducing aerofoil-turbulence interaction noise and are also associated with certain aerodynamic advantages. To prepare leading edge serrations for industrial application, two obstacles remain to be addressed. First is a combined analysis of the aeroacoustic and the aerodynamic performance of leading edge serrations to develop optimum designs. Second is the need to examine the transferability of the known effects of leading edge serrations from a single aerofoil to full rotors, which are considered to be the final area of application.
This thesis aims to assist in the transfer of a well-investigated aerofoil with serrated leading edges from the rigid to the rotating domain. With this purpose, a single aerofoil type is selected and thoroughly analysed, experimentally and numerically, to generate a reliable data basis for aerodynamic performance and noise reduction capability. Aside from gathering information on the overall performance, the spatial distribution of the noise sources is localised, and the spectral composition of the noise reduction is found to follow a clearly defined scaling law. Aerodynamically, generated vortices are found to be responsible for a complex three-dimensional separation mechanism of the leading edge serrations, causing a delay of stall.
The generated data basis is then used to design low-pressure axial fans of minimum complexity by keeping the initially chosen aerofoil type. The experimentally identified noise reduction mechanisms for the serrated axial fans are found to be more diverse than the single aerofoil and highly dependent on the inflow conditions and the operation point of the fan. A highly similar pattern for the spectral scaling of the noise reduction supports the finding that at optimum operation conditions, the previously identified noise reduction mechanisms for the single aerofoils are transferable to the rotating domain. On the other hand, additional aerodynamic mechanisms are found to dominate the noise reduction for the instability region of the fan, also contributing to reduced blade-to-blade interaction effects. Moreover, the blade-tip leakage flow is altered by delaying the development of coherent structures.
The next step towards a more general description of the aeroacoustic and aerodynamic dependencies is developing a comprehensive model based on artificial neural networks. This model allows a combined analysis of the aerodynamic and acoustic performance of rotors with serrated leading edges and shows an accurate prediction of the overall performance and the spectral composition of the radiated noise. It also enables the development of multi-objective optima for serration designs and motivates further studies into the generalisability of the observed trends. Furthermore, the developed model represents a feasible tool to create tailored serration designs for maximum efficiency in both aeroacoustics and aerodynamics, contributing to the development of future low-noise fans and rotating machinery.
The Chylla–Haase polymerization reactor is widely accepted as a benchmark process for the evaluation of control strategies for batch reactors. In this contribution a control concept based on Exact I/O-Linearization is proposed and compared to a conventional cascade control structure. In order to adapt the exact linearization control strategy to various polymerization products and batch conditions, an advanced probabilistic inference algorithm (Sigma-Point Kalman Filter) is applied and investigated. Sigma-Point Kalman Filters have the major improvement of simplified implementation compared to local linearization methods (i.e. Extended Kalman Filter) because no analytical Jacobians are required. Stochastic simulation studies are introduced and show the effectiveness, accuracy and benefit of the control concept. Within several scenarios a satisfying robustness against structural errors in the underlying model equations for the nonlinear control law and the inference algorithm is demonstrated. Furthermore it is pointed out, that with little effort in reassembling the plant design, control performance can be improved significantly.
To power dynamic processes in cells, the actin and microtubule cytoskeletons organize into complex structures. Although it is known that cytoskeletal coordination is vital for cell function, the mechanisms by which cross-linking proteins coordinate actin and microtubule activities remain poorly understood. In particular, it is unknown how the distinct mechanical properties of different actin architectures modulate the outcome of actin-microtubule interactions. To address this question, we engineered the protein TipAct, which links growing microtubule ends via end-binding proteins to actin filaments. We show that growing microtubules can be captured and guided by stiff actin bundles, leading to global actin-microtubule alignment. Conversely, growing microtubule ends can transport, stretch and bundle individual actin filaments, thereby globally defining actin filament organization. Our results provide a physical basis to understand actin-microtubule cross-talk, and reveal that a simple cross-linker can enable a mechanical feedback between actin and microtubule organization that is relevant to diverse biological contexts.
Actin droplet machine
(2019)
The actin droplet machine is a computer model of a three-dimensional network of actin bundles developed in a droplet of a physiological solution, which implements mappings of sets of binary strings. The actin bundle network is conductive to travelling excitations, i.e. impulses. The machine is interfaced with an arbitrary selected set of k electrodes through which stimuli, binary strings of length k represented by impulses generated on the electrodes, are applied and responses are recorded. The responses are recorded in a form of impulses and then converted to binary strings. The machine's state is a binary string of length k: if there is an impulse recorded on the ith electrode, there is a '1' in the ith position of the string, and '0' otherwise. We present a design of the machine and analyse its state transition graphs. We envisage that actin droplet machines could form an elementary processor of future massive parallel computers made from biopolymers.