This report deals with the transient behaviour of process systems such as those normally encountered by the chemical engineer. Two competing approaches for the numerical solution of this problem are described. The first is an "equation oriented" approach, and the second is an "equipment oriented11 or "modular" approach. The concept of modularity is discussed, and a brief presentation of its advantages is given. A program DYNSYS-B was written to apply the modular approach to transient studies. The program employs a predictor-corrector technique to solve the system's differential equations in a sequential fashion. The DYNSYS-8 program was applied to a multicomponent liquid-liquid extraction unit with heat effects and reflux, with the object of evaluating the program and gaining some experience with its use. Based on this study. we believe that the program is readily applied to the solutions of many problems. Some suggestions are made for improving the computation efficiency of the program. / Thesis / Master of Engineering (MEngr)

Consider two Markovian N-policy queueing models in discrete time, one with batch arrival, the other with batch service. In this paper the transient behaviour of both models is studied and the analogous continuous time results are achieved by a limiting process. The steady state solution for the model with batch arrival is derived. (author's abstract) / Series: Forschungsberichte / Institut für Statistik

The Internet has been more and more intensively used in recent years. Although network infrastructure has been regularly upgraded, and the ability to manage heavy traffic greatly increased, especially on the core networks, congestion never ceases to appear, as the amount of traffic that flow on the Internet seems to be increasing at an even faster rate. Thus, congestion control mechanisms play a vital role in the functioning of the Internet. Active Queue Management (AQM) is a popular type of congestion control mechanism that is implemented on gateways (most notably routers), which can predict and avoid the congestion before it happens. When properly configured, AQMs can effectively reduce the congestion, and alleviate some of the problems such as global synchronisation and unfairness to bursty traffic. However, there are still many problems regarding AQMs. Most of the AQM schemes are quite sensitive to their parameters setting, and these parameters may be heavily dependent on the network traffic profile, which the administrator may not have intensive knowledge of, and is likely to change over time. When poorly configured, many AQMs perform no better than the basic drop-tail queue. There is currently no effective method to compare the performance of these AQM algorithms, caused by the parameter configuration problem. In this research, the aim is to propose a new analytical model, which mainly uses discrete-time queueing theory. A novel transient modification to the conventional equilibrium-based method is proposed, and it is utilised to further develop a dynamic interactive model of responsive traffic and bottleneck queues. Using step-by-step analysis, it represents the bursty traffic and oscillating queue length behaviour in practical network more accurately. It also provides an effective way of predicting the behaviour of a TCP-AQM system, allowing easier parameter optimisation for AQM schemes. Numerical solution using MATLAB and software simulation using NS-2 are used to extensively validate the proposed models, theories and conclusions.

Les garnitures mécaniques sont utilisées dans de multiples applications pour réaliser l'étanchéité autour d'arbres en rotation. Ces composants peuvent fonctionner efficacement pendant plusieurs années en conditions stables, mais leur durée de vie est significativement réduite lorsque les conditions varient. L'objectif de ce travail de recherche est de développer et d’utiliser un banc d'essais et code de calcul pour étudier l'impact de pulsations de pression, d’inversions de pression et du chargement dynamique résultant sur les performances de garnitures mécaniques ayant des faces mésalignées et présentant des défauts de planéité.Le solveur fluide d'un modèle numérique de garnitures mécaniques a été étendu aux conditions transitoires. Un module résolvant la dynamique des forces et des moments a été ajouté afin de prédire le déplacement axial et les déplacements angulaires de la face montée de manière flexible. Afin de caractériser les performances de garnitures, un banc d'essais générant des pulses de pression a été instrumenté et des méthodes de mesure de perte de volume d'huile et d'entrée d'eau mises en place.Des garnitures mécaniques à faces parallèles puis mésalignées, fonctionnant sous pulsations et inversions de pression, ont été testées expérimentalement et simulées. Seules de très faibles augmentations d'eau dans l'huile ont été observées, sans augmentation au cours du temps, et sans fuite d'huile mesurable. Les faibles valeurs d'entrées d'eau sont dues à la faible épaisseur de film et à la courte durée des inversions de pression. Une garniture mécanique expérimentale à fort défaut de planéité a aussi été testée. Contrairement aux autres paramètres, le défaut de planéité semble augmenter significativement la fuite et promouvoir les entrées d'eau et pourrait ainsi être à l'origine de certaines défaillances. / Face seals are mechanical devices used to seal rotating shafts in numerous applications. While they can operate efficiently under steady conditions for years, they tend to fail prematurely when operating in severe, or rapidly varying conditions. The focus of this research work is the development and use of an experimental and a numerical method to investigate the impact of pressure pulses, pressure inversions and induced dynamic loading on the performance of mechanical face seals exhibiting face misalignment and waviness.The fluid solver of a state-of-the art face seal numerical model was extended to transient conditions and a module solving the dynamics for the axial and angular degrees of freedom of the flexibly-mounted stator added. A system-level experimental setup generating pressure pulses was instrumented and methods to characterise face seal performance in terms of oil volume loss and ingression of water outer-fluid selected and implemented.Face seals, with flat and misaligned faces, operating under pressure pulses and pressure inversions were experimentally tested and simulated. They show only slight increase of water in the oil, no increase over time, and no measurable oil leakage. The low water ingression is due to low film thickness combined with the short duration of pressure inversions. An exploratory face seal of high waviness was also experimentally tested. Contrary to the other parameters, the waviness appears to significantly increase the leakage and promote water ingression and could thus be at the origin of some seal failures.

Developing and improving upon a good empirical model for an engine can be time-consuming and costly. The goal of this thesis has been to evaluate data-driven modelling, specifically neural networks, to see how well it can handle training for some static models like the mass flow of air into the cylinder, mean effective pressure and pump mean effective pressure but also for transient modelling, specifically the exhaust gas temperature. These models are evaluated against the classical empirical models to see if neural networks are a viable modelling option. This is done with five different types of neural networks which are trained. These are the feed-forward neural network, Nonlinear autoregressive exogenous model network, layer recurrent network, long short term memory network and gated recurrent network.The inputs were determined by looking at more simple physical models but also looking at the covariance to determine the usefulness of the input. If the calculation time is small for the specific network, the neural network structure is tested and optimized by training many networks and finding the median/mean result for that specific test.The result has shown that the static models are handled very well by the most simple feed-forward network. For the exhaust temperature, both NARX and Layer recurrent network could predict and handle it well giving results very close to the empirical models and could be a viable option for transient modelling, on the other hand, Long short term memory, gated recurrent network and the feed-forward network had trouble predicting the exhaust gas temperature and returned bad results while training.