The thesis describes an investigation into Air Traffic Control (ATC) complexity as a contributory factor in changes of controllers' workload. It is considered that ATC complexity, together with equipment interface and procedural demands comprise the task demands imposed on the en-route controller to perform certain activities, which mediated by performance shaping factors create workload. The data used to study this relationship came from ATC real-time simulations completed at EUROCONTROL CRDS in Budapest: recorded flown trajectories, communication performed by the controller (whether with other controllers or with the pilots), data entries related to flight data management, and instantaneous self-assessment ratings of workload provided by the controllers were used. The ATC complexity factors that have been consistently found to be important in the previous studies (related to aircraft density, flight attributes of each individual aircraft, aircraft conflicts and traffic disorder) and for which detailed calculation formula have been reported were selected for further analysis. Since the established set of factors resulted from multiple researches conducted in this field, it was assumed that some of these factors are correlated with one another, overlapping and possibly measuring similar concepts. Therefore, a reduction of the initial set of factors was performed by combining information contained within these factors into a smaller number of new artificial variables and by deleting statistically redundant portions of these factors prior to conducting further analysis. The Principal Component Analysis (PCA), which is the statistical method applied to achieve required reduction, resulted in the overall set of 6 complexity components, whose interpretations are driven by the factors that showed the strongest correlation with that component. In order to establish a link between ATC complexity and a controller's subjective workload, multiple regression analysis was performed, using the complexity components identified in the PCA as predictors of the workload ratings. In addition, some measures of controller’s activity (data entries made by the controllers related to flight data management, cumulative duration of radio calls, i.e. frequency occupancy time, and average duration of single calls) were added to the analysis to test whether information about the controller’s activity could be also useful for predicting workload, once the effect of complexity had been considered, and to verify whether the effect of complexity on workload could be mediated by the effect of complexity on the controller’s activity. The analysis revealed that both ATC complexity and the activities that the controller performs to deal with a demand imposed on him/her give a unique contribution to the prediction of workload ratings and therefore the workload of the controller is determined by both ATC complexity and controller’s activities. In addition, it was assumed that the workload is differently impacted by individual components of complexity, and further statistical analyses were performed to test this assumption. Understanding these differences could in fact facilitate comparison of the complexity levels of a single sector under different conditions, but also comparison of complexity levels of different sectors under same conditions. Firstly the changes in the workload and activities of the controllers under different conditions were investigated using analysis of variance. Subsequently, in order to be able to map these changes on the complexity components, it was necessary also to investigate into the changes that the complexity components undergo when observed under different conditions. The results revealed different behaviour of single complexity components when mapped on the changes recorded in the activities of the controller and workload, demonstrating that changes in controller’s activities and perceived workload are driven by different complexity components in different sectors and under different operational conditions. Shedding light on these contributors to the workload experienced by a controller can greatly facilitate the introduction of any change envisaged for the airspace under consideration. Namely, in the current structure, whenever new procedures or new working methods are subject to possible deployment, the identified complexity components could support the estimation of the impact that those changes would impose on the workload of the controller and further on decision making processes. Additionally, the complexity components are also applicable in the validation of the new concepts and new technologies to be introduced in the system when designing simulation scenarios against which new concepts would be assessed. As also demonstrated by the analysis, the comparison of different sectors, or even different sector designs within the same airspace, could be compared and contribute to the improvement of airspace design. / Die vorliegende Arbeit untersucht die Komplexität der Flugverkehrskontrolle (Air Traffic Control, ATC) als einen wesentlichen Einflussfaktor auf die Arbeitsbelastung des Radarlotsen. Die zentrale Annahme ist dabei, dass die Komplexität der ATC zusammen mit den Anforderungen aus den betrieblichen Rahmenbedingungen (technische Systemschnittstellen und Prozeduren) den Lotsen zu bestimmten Abläufen zwingen, welche die Arbeitsbelastung signifikant beeinflussen. Für die durchgeführten Untersuchungen standen Daten von ATC-Echtzeitsimulationen von EUROCONTROL CRDS Budapest zur Verfügung, die folgende Informationen umfassen: abgeflogene Flugtrajektorien, Kommunikationsprotokolle der Lotsen (untereinander oder zwischen Lotse und Pilot), Daten aus dem flight-data Management und Daten aus der regelmäßigen Selbstbewertung der Lotsen bezüglich ihrer aktuell gefühlten Arbeitsbelastung. Die bereits in früheren Studien identifizierten Komplexitätsvariablen (insbesondere die lokale Flugzeugdichte, spezifische Flugzeugeigenschaften, Konfliktsituationen zwischen Flugzeugen und die Verkehrslage betreffend) sowie hierzu erarbeitete mathematische Vorschriften bilden die Grundlage für die weiterführenden, detaillierten Untersuchungen. Aufgrund der Vielzahl an Komplexitätsvariablen aus diversen wissenschaftlichen Quellen war davon auszugehen, dass Korrelationen unter den Variablen vorliegen. Aus diesem Grund wurden zunächst statistisch redundante Informationen der ursprünglich vorliegenden Variablen reduziert, sodass als Ergebnis neue voneinander unabhängige Faktoren klassifiziert werden konnten. Die hierfür verwendete Hauptkomponentenanalyse (Principal Component Analysis - PCA) führte zu sechs statistisch signifikanten Komplexitätsfaktoren, die anhand der höchsten Korrelation zur zugeordneten Komponente interpretiert wurden. Um die Verbindung zwischen der ATC Komplexität und der subjektiv empfundenen Arbeitsbelastung herzustellen, wurde eine multiple Regressionsanalyse zwischen den Komplexitätsfaktoren und den abgeleiteten Arbeitsbelastungszuständen durchgeführt. Zusätzlich lagen für die Analyse der Arbeitsbelastung auch Daten über die Arbeitsaufgaben des Lotsen vor (bspw. Dateneinträge des Lotsen, Gesamtlänge der Funkanweisungen, durchschnittliche Länge der Funkanweisungen), um zu untersuchen, inwieweit sich aus den aktuell durchgeführten Arbeitsaufgaben bei gegebener Verkehrsnachfrage eine verlässliche Vorhersage über die Arbeitsbelastung ableiten lässt. Die Analyse zur Vorhersage der Arbeitsbelastung konnte zeigen, dass sowohl die ATC Komplexität als auch die aktuellen Arbeitsaufgaben einen individuellen und signifikanten Einfluss haben. Weiterhin wurde unterstellt, dass die spezifischen Komplexitätsfaktoren einen unterschiedlichen Effekt auf die Arbeitsbelastung ausüben. Die Überprüfung dieser Annahme war ebenfalls Bestandteil der umfangreichen statistischen Untersuchungen. Tatsächlich könnte ein fundamentales Verständnis der Komplexitätsgrade den Vergleich einzelner Luftraumsektoren unter verschiedenen operativen Randbedingungen, als auch den Vergleich unterschiedlicher Luftraumsektoren mit vergleichbaren operativen Randbedingungen wesentlich erleichtern. Zuerst wurden die Veränderungen der Arbeitsbelastung und -die Tätigkeiten der Lotsen unter Verwendung einer Varianzanalyse untersucht. Um eine valide Zuordnung zu den Komplexitätsfaktoren sicherzustellen, war es ebenfalls notwendig, die Veränderungen dieser Faktoren und Tätigkeiten unter wechselnden Randbedingungen zu analysieren. Die Analysen zeigen hierbei unterschiedliche Resultate bezüglich der jeweiligen Komplexitätsfaktoren. So beeinflussen die verschiedenen Komplexitätsfaktoren die Handlungsabläufe der Lotsen und die wahrgenommene Arbeitsbelastung, jedoch in Abhängigkeit von den ausgewählten Sektoren und den betrieblichen Randbedingungen. Unter Berücksichtigung dieser erarbeiteten Abhängigkeiten der Arbeitsbelastung des Lotsen können nun die Auswirkungen von Veränderungen im Luftraum zuverlässig bestimmt werden. Gerade in Bezug auf Veränderungen der gegenwärtigen Luftraumstruktur oder die Einführung neuer Prozeduren oder Arbeitsabläufe können die entwickelten Komplexitätsfaktoren bereits frühzeitig Aufschluss darüber geben, welche Konsequenzen solche Veränderungen auf die Arbeitsbelastung der Lotsen nach sich ziehen können und Entscheidungsprozesse unterstützen. Weiterhin sind die entwickelten Komplexitätsfaktoren als Grundlage für die Validierung neuer Konzepte und Technologien, gegebenenfalls unter Verwendung von entwickelten Simulationsszenarien, nutzbar. Darüber hinaus können die Komplexitätsfaktoren für die Gegenüberstellung von verschiedenen Luftraumsektoren genutzt werden und zur Abwägung bzw. Optimierung von Entwürfen eines Luftraumdesigns dienen.

Realistic and real-time computational simulation of biological organs (e.g., human kidneys, human liver) is a necessity when one tries to build a quality surgical simulator that can simulate surgical procedures involving these organs. Currently deformable models, spring-mass models, or finite element models are widely used to achieve the realistic simulations and/or the real-time performance. It is widely agreed that continuum mechanics based numerical techniques are preferred over deformable models or spring-mass models, but those techniques are computationally expensive and hence the higher accuracy offered by those numerical techniques come at the expense of speed. Hence there is a need to study the speed of different numerical techniques, while keeping an eye on the accuracy offered by those numerical techniques. Such studies are available for the Finite Element Method (FEM) but rarely available for the Boundary Element Method (BEM). Hence the present work aims to conduct a study on the viability of BEM for the real-time simulation of biological organs, and the present study is justified by the fact that BEM is considered to be inherently efficient when compared to mesh based techniques like FEM. A significant portion of literature on the real-time simulation of biological organs suggests the use of BEM to achieve better simulations. When one talks about the simulation of biological organs, one needs to have the geometry of a biological organ in hand. Geometry of biological organs of interest is not readily available many a times, and hence there is a need to extract the three dimensional (3D) geometry of biological organs from a stack of two dimensional (2D) scanned images. Software packages that can readily reconstruct 3D geometry of biological organs from 2D images are expensive. Hence, a novel procedure that requires only a few free software packages to obtain the geometry of biological organs from 2D image sequences is presented. The geometry of a pig liver is extracted from CT scan images for illustration purpose. Next, the three dimensional geometry of human kidney (left and right kidneys of male, and left and right kidneys of female) is obtained from the Visible Human Dataset (VHD). The novel procedure presented in this work can be used to obtain patient specific organ geometry from patient specific images, without requiring any of the many commercial software packages that can readily do the job. To carry out studies on the speed and accuracy of BEM, a source code for BEM is needed. Since the BEM code for 3D elasticity is not readily available, a BEM code that can solve 3D linear elastostatic problems without accounting for body forces is developed from scratch. The code comes in three varieties: a MATLAB version, a Fortran version (sequential version), and a Fortran version (parallelized version). This is the first free and open source BEM code for 3D elasticity. The developed code is used to carry out studies on the viability of BEM for the real-time simulation of biological organs, and a few representative problems involving kidneys and liver are found to give accurate solutions. The present work demonstrates that it is possible to simulate linear elastostatic behaviour in real-time using BEM without resorting to any type of precomputations, on a computer cluster by fully parallelizing the simulations and by performing simulations on different number of processors and for different block sizes. Since it is possible to get a complete solution in real-time, there is no need to separately prove that every type of cutting, suturing etc. can be simulated in real-time. Future work could involve incorporating nonlinearities into the simulations. Finally, a BEM based simulator may be built, after taking into account details like rendering.