Search

The recuperation of otherwise lost waste heat provides a formidable way to decrease the primary energy consumption of many technical systems. A possible route to achieve that goal is through the use of Stirling engines, which have shown to be reliable and efficient devices. One can increase their performance by optimizing the piston motion. Here, it is investigated to which extent the cycle averaged power output can be increased by using a special class of adjustable sinusoidal motions (the AS class). In particular the influence of the regeneration effectiveness on the piston motion is examined. It turns out that with the optimized piston motion one can achieve performance gains for the power output of up to 50% depending on the loss mechanisms involved. A remarkable result is that the power output does not depend strongly on the limitations of the regenerator, in fact&mdash, depending on the loss terms&mdash, the influence of the regenerator practically vanishes.

The Stirling engine is one of the most promising devices for the recovery of waste heat. Its power output can be optimized by several means, in particular by an optimized piston motion. Here, we investigate its potential performance improvements in the presence of dissipative processes. In order to ensure the possibility of a technical implementation and the simplicity of the optimization, we restrict the possible piston movements to a parametrized class of smooth piston motions. In this theoretical study the engine model is based on endoreversible thermodynamics, which allows us to incorporate non-equilibrium heat and mass transfer as well as the friction of the piston motion. The regenerator of the Stirling engine is modeled as ideal. An investigation of the impact of the individual loss mechanisms on the resulting optimized motion is carried out for a wide range of parameter values. We find that an optimization within our restricted piston motion class leads to a power gain of about 50% on average.

In an effort to improve the accuracy of common 1-D analysis for frequency domain helicopter-borne electromagnetic data at reasonable computing costs, a 3-D inversion approach is developed. The strategy is based on the prior localization of an entire helicopter-borne electromagnetic survey to parts which are actually affected by expected local 3-D anomalies and a separate inversion of those sections of the surveys (cut-&-paste strategy). The discrete forward problem, adapted from the complete Helmholtz equation, is formulated in terms of the secondary electric field employing the finite difference method. The analytical primary field calculation incorporates an interpolation strategy that allows to effectively handle the enormous number of transmitters. For solving the inverse problem, a straightforward Gauss-Newton method and a Tikhonov-type regularization scheme are applied. In addition, different strategies for the restriction of the domain where the inverse problem is solved are used as an implicit regularization. The derived linear least squares problem is solved with Krylov-subspace methods, such as the LSQR algorithm, that are able to deal with the inherent ill-conditioning. As the helicopter-borne electromagnetic problem is characterized by a unique transmitter-receiver relation, an explicit representation of the Jacobian matrix is used. It is shown that this ansatz is the crucial component of the 3-D HEM inversion. Furthermore, a tensor-based formulation is introduced that provides a fast update of the linear system of the forward problem and an effective handling of the sensitivity related algebraic quantities. Based on a synthetic data set of a predefined model problem, different application examples are used to demonstrate the principal functionality of the presented algorithm. Finally, the algorithm is applied to a data set obtained from a real field survey in the Northern German Lowlands. Die vorliegende Arbeit beschäftigt sich mit der 3-D Inversion von Hubschrauberelektromagnetikdaten im Frequenzbereich. Das vorgestellte Verfahren basiert auf einer vorhergehenden Eingrenzung des Messgebiets auf diejenigen Bereiche, in denen tatsächliche 3-D Strukturen im Untergrund vermutet werden. Die Resultate der 3-D Inversion dieser Teilbereiche können im Anschluss wieder in die Ergebnisse der Auswertung des komplementären Gesamtdatensatzes integriert werden, welche auf herkömmlichen 1-D Verfahren beruht (sog. Cut-&-Paste-Strategie). Die Diskretisierung des Vorwärtsproblems, abgeleitet von einer Sekundärfeldformulierung der vollständigen Helmholtzgleichung, erfolgt mithilfe der Methode der Finiten Differenzen. Zur analytischen Berechnung der zugehörigen Primärfelder wird ein Interpolationsansatz verwendet, welcher den Umgang mit der enorm hohen Anzahl an Quellen ermöglicht. Die Lösung des inversen Problems basiert auf dem Gauß-Newton-Verfahren und dem Tichonow-Regularisierungsansatz. Als Mittel der zusätzlichen impliziten Regularisierung dient eine räumliche Eingrenzung des Gebiets, auf welchem das inverse Problem gelöst wird. Zur iterativen Lösung des zugrundeliegenden Kleinste-Quadrate-Problems werden Krylov-Unterraum-Verfahren, wie der LSQR Algorithmus, verwendet. Aufgrund der charakteristischen Sender-Empfänger-Beziehung wird eine explizit berechnete Jakobimatrix genutzt. Ferner wird eine tensorbasierte Problemformulierung vorgestellt, welche die schnelle Assemblierung leitfähigkeitsabhängiger Systemmatrizen und die effektive Handhabung der zur Berechnung der Jakobimatrix notwendigen algebraischen Größen ermöglicht. Die Funktionalität des beschriebenen Ansatzes wird anhand eines synthetischen Datensatzes zu einem definierten Testproblem überprüft. Abschließend werden Inversionsergebnisse zu Felddaten gezeigt, welche im Norddeutschen Tiefland erhoben worden.