Referate

Ohne Zusammenfassung     

Bonner J?gertag

Ohne Zusammenfassung     

Bonner J?gertage 1996

Ohne ZusammenfassungEingesetzt wurde ein Druckkostenzuschuß der LÖBF/LAfAO NRW, Dez. Forschungsstelle für Jagdkunde und Wildschadenverhütung, für dessen Gewährung verbindlich gedankt wird. — Die Schriftleitung     

Prediction of backside micromotion in total knee replacements by finite element simulation

The micromotion at the interface between the polyethylene tibial insert and metal tibial tray [corrected] in modular total knee replacements [corrected] has been shown to contribute to wear particle-induced osteolysis and may [corrected] cause implant failure. Therefore, studying the design parameters that are involved in the backside wear process is an important task that may lead to improvement in new total knee replacements. In the present study, a finite element model was developed to predict the backside micromotion along the entire modular interface. Both the linear elastic constitutive model and non-linear J2-plasticity constitutive model were considered in the finite element model for polyethylene and were corroborated against published results obtained from displacement controlled knee simulator wear tests. The finite element simulation with the non-linear J2-plasticity constitutive model was able to predict backside micromotion [corrected] more accurately than the simulation with the linear elastic constitutive model. [corrected] The developed finite element model (including the non-linear J2-plasticity constitutive model) was then applied to assess the effects of the tibial tray locking mechanism design (dovetails versus fullperipheral [corrected] design) and different levels of interference fit on insert micromotion. The developed finite element model, implementing the non-linear J2-plasticity constitutive model, was shown to successfully predict clinical amounts of backside micromotion and could be used for the design and development of total knee replacements for the reduction of backside micromotion and polyethylene [corrected] wear.     

[2.2]Paracyclophane as a Target of the Organic Solid State: Emergent Properties via Supramolecular Construction

In this account, we review the synthesis of [2.2]paracyclophanes in the organic solid state. Reactions in crystalline solids provide a means to obtain molecules with high degrees of stereocontrol that can also be unattainable in solution. We show that [2.2]paracyclophanes form in the solid state stereospecifically and in quantitative yield via intermolecular [2+2] double photodimerization reactions. The double cycloaddition that affords a paracyclophane in the solid state does not readily occur in solution. Small molecules in the form of hydrogen-bond-donor templates can provide access to [2.2]paracyclophanes in a solid by design. A [2.2]paracyclophane obtained using a hydrogen-bond template is shown to exhibit attractive optical properties and has been employed as a building block of a metal-organic framework (MOF).     

Visual Target Localization with the Spincopter

The goal of the Spincopter project was to design an energy efficient aircraft capable of autorotation glide that could be used for both indoor and outdoor surveillance. This paper demonstrates how to utilize the self-rotating capability of the Spincopter in order to acquire a 3D image of its environment and localize predefined object(s). The omnidirectional capabilities of such an UAV extends the otherwise very limited field of view of conventional cameras usually used for aerial photography and surveillance. The paper presents the theoretical background and the actual implementation of such a system. It presents the resulting images and offers a brief survey of the image quality.     

Prediction of diesel fuel cold properties using artificial neural networks

In this paper, two neural networks, multilayer perceptron and networks with radial-basis function, were used to predict important cold properties of commercial diesel fuels, namely cloud point and cold filter plugging point. The developed models predict the named properties using cetane number, density, viscosity, contents of total aromatics, and distillation temperatures at 10, 50, and 90 vol. % recovery as input data. The training algorithms, number of hidden layer neurons, and number of training data points were optimized in order to obtain a model with optimal predictive ability. The results indicated better prediction of cloud and cold filter plugging points in the case of multilayer perceptron networks. The obtained absolute error mean for the optimal neural network models (0.58°C for the cloud point and 1.46°C for the cold filter plugging point) are within the range of repeatability of standard cold properties determination methods.     

Relay-based critical point estimation of a process with the PID controller in the loop

The proposed procedure is implemented without breaking the loop with the controller in operation, by activating a cascade of band-pass filters in series with a relay in the inner loop and a notch filter in the outer loop. A highly accurate estimate of the critical point of a process G_p(s) is obtained in the presence of measurement noise and load disturbance. The effectiveness of the proposed procedure is illustrated using a test batch consisting of stable, integrating and unstable processes, including dead-time.