No / The reverse osmosis (RO) desalination process to make fresh water from seawater has been studied here. First, a model for the process is developed. Sensitivity of different operating parameters (feed flow rate, feed pressure) and design parameters (internal diameter, total number of tubes) on the recovery ratio are studied via repetitive simulation. Finally, an optimisation framework for the process is developed so as to maximize the recovery ratio or a profit function using different energy recovery devices, subjectto general constraints. The optimal operating parameters (feed flow rate, feed pressure) and design parameters (internal diameter, total number of tubes) are determined by solving the optimisation problem using an efficient successive quadratic programming (SQP) based method. The optimal values for the decision variables depend on the constraints introduced, and are also sensitive to variations in water and energy prices, as well as feed concentration. The use ofthe emerging energy recovery devices is widely justified, reporting much higher reductions in operating costs than the traditional technology used for this purpose. Using a pressure exchanger device, it is possible to reduce energy consumption by up to 50%.

During the takeoff for a trampoline skill the trampolinist should produce sufficient vertical velocity and angular momentum to permit the required skill to be completed in the aerial phase without excessive horizontal travel. The aim of this study was to investigate the optimum technique to produce forward somersault rotation. A seven-segment, subject-specific torque-driven computer simulation model of the takeoff in trampolining was developed in conjunction with a model of the reaction forces exerted on the trampolinist by the trampoline suspension system. The ankle, knee, hip, and shoulder joints were torque-driven, with the metatarsal-phalangeal and elbow joints angle-driven. Kinematic data of trampolining performances were obtained using a Vicon motion capture system. Segmental inertia parameters were calculated from anthropometric measurements. Viscoelastic parameters governing the trampoline were determined by matching an angle-driven model to the performance data. The torque-driven model was matched to the performance data by scaling joint torque parameters from the literature, and varying the activation parameters of the torque generators using a simulated annealing algorithm technique. The torque-driven model with the scaled isometric strength was evaluated by matching the performance data. The evaluation produced close agreement between the simulations and the performance, with an average difference of 4.4% across three forward rotating skills. The model was considered able to accurately represent the motion of a trampolinist in contact with a trampoline and was subsequently used to investigate optimal performance. Optimisations for maximum jump height for different somersaulting skills and maximum rotation potential produced increases in jump height of up to 14% and increases of rotation potential up to 15%. The optimised technique for rotation potential showed greater shoulder flexion during the recoil of the trampoline and for jump height showed greater plantar flexion and later and quicker knee extension before takeoff. Future applications of the model can include investigations into the sensitivity of the model to changes in initial conditions, and activation, strength, and trampoline parameters.

A computer simulation model of the table contact phase of gymnastics vaulting was developed to gain an understanding of the mechanics of this phase of the vault. The model incorporated a gymnast and a vaulting table, and used a novel two-state contact phase representation to simulate the interaction between these two bodies during the table contact phase. The gymnast was modelled in planar form using seven segments, with torque generators acting at the wrist, shoulder, hip and knee joints. The model also allowed for shoulder retraction and protraction, displacement of the glenohumeral joint centre and flexion/extension of the fingers. The table was modelled as a single rigid body that could rotate. The model was personalised to an elite gymnast so that simulation outputs could be compared with the gymnast's performance. Kinematic data of vaulting performances were obtained using a optoelectronic motion capture system. Maximal voluntary joint torques were also measured using an isovelocity dynamometer, and a torque - angle - angular velocity relationship was used to relate joint torques to joint angles and angular velocities. A set of model system parameters was determined using a gymnast-specific angle-driven model by matching four simulations to their respective performances concurrently. The resulting parameters were evaluated using two independent trials, and found to be applicable to handspring entry vaults. The torque-driven model was successfully evaluated, and shown to produce realistic movements, with mean overall differences between simulations and recorded performances of 2.5% and 8.6% for two different handspring entry vaults. The model was applied to further understanding of the mechanics of the table contact phase of gymnastics vaulting. Optimisation showed that there was limited potential (1.3%) for the gymnast to improve performance through technique changes during the table contact phase. However, with additional changes in configuration at table contact post-flight rotation could be increased by 9.8% and post-flight height could be increased by 0.14m. Angular momentum was found to always decrease during the table contact phase of the vault, although the reductions were less when maximising post-flight rotation.

A computer simulation model of a springboard and a diver was developed to investigate diving takeoff techniques in the forward and the reverse groups. The springboard model incorporated vertical, horizontal and rotational movements based on experimental data. The diver was modelled as an eight-segment link system with torque generators acting at the metatarsal-phalangeal, ankle, knee, hip and shoulder joints. Wobbling masses were included within the trunk, thigh and shank segments to allow for soft tissue movement. The foot-springboard interface was represented by spring-dampers acting at the heel, ball and toes of the foot. The model was personalised to an elite diver so that simulation output could be compared with the diver's own performance. Kinematic data of diving performances from a one-metre springboard were obtained using high speed video and personalised inertia parameters were determined from anthropometric measurements. Joint torque was calculated using a torque / angle / angular velocity relationship based on the maximum voluntary torque measured using an isovelocity dynamometer. Visco-elastic parameters were determined using a subject-specific angledriven model which matched the simulation to the performance in an optimisation process. Four dives with minimum and maximum angular momentum in the two dive groups were chosen to obtain a common set of parameters for use in the torque-driven model. In the evaluation of the torque-driven model, there was good agreement between the simulation and performance for all four dives with a mean difference of 6.3%. The model was applied to optimise for maximum dive height for each of the four dives and to optimise for maximum rotational potential in each of the two dive groups. Optimisation results suggest that changing techniques can increase the dive height by up to 2.0 cm. It was also predicted that the diver could generate rotation almost sufficient to perform a forward three and one-half somersault tuck and a reverse two and one-half somersault tuck.

This thesis presents a novel evolutionary optimisation algorithm that can improve the quality of solutions in simulation-based optimisation. Simulation-based optimisation is the process of finding optimal parameter settings without explicitly examining each possible configuration of settings. An optimisation algorithm generates potential configurations and sends these to the simulation, which acts as an evaluation function. The evaluation results are used to refine the optimisation such that it eventually returns a high-quality solution. The algorithm described in this thesis integrates multi-objective optimisation, parallelism, surrogate usage, and noise handling in a unique way for dealing with simulation-based optimisation problems incurred by these characteristics. In order to handle multiple, conflicting optimisation objectives, the algorithm uses a Pareto approach in which the set of best trade-off solutions is searched for and presented to the user. The algorithm supports a high degree of parallelism by adopting an asynchronous master-slave parallelisation model in combination with an incremental population refinement strategy. A surrogate evaluation function is adopted in the algorithm to quickly identify promising candidate solutions and filter out poor ones. A novel technique based on inheritance is used to compensate for the uncertainties associated with the approximative surrogate evaluations. Furthermore, a novel technique for multi-objective problems that effectively reduces noise by adopting a dynamic procedure in resampling solutions is used to tackle the problem of real-world unpredictability (noise). The proposed algorithm is evaluated on benchmark problems and two complex real-world problems of manufacturing optimisation. The first real-world problem concerns the optimisation of a production cell at Volvo Aero, while the second one concerns the optimisation of a camshaft machining line at Volvo Cars Engine. The results from the optimisations show that the algorithm finds better solutions for all the problems considered than existing, similar algorithms. The new techniques for dealing with surrogate imprecision and noise used in the algorithm are identified as key reasons for the good performance.

Public transport network design deals with finding the most efficient network solution among a set of alternatives, that best satisfies the often-conflicting objectives of different network stakeholders like passengers and operators. Simulation-based Optimisation (SBO) is a discipline that solves optimisation problems by combining simulation and optimisation models. The former is used to evaluate the alternative solutions, while the latter searches for the optimal solution among them. A SBO model for designing public transport networks is developed in this dissertation. The context of the research is the MyCiTi Bus Rapid Transit (BRT) network in the City of Cape Town, South Africa. A multi-objective optimisation algorithm known as the Non-dominated Sorting Genetic Algorithm (NSGA-II) is integrated with Activity-based Travel Demand Model (ABTDM) known as the Multi-Agent Transport Simulation (MATSim). The steps taken to achieve the research objectives are first to generate a set of feasible network alternatives. This is achieved by manipulating the existing routes of the MyCiTi BRT with a computer based heuristic algorithm. The process is guided by feasibility conditions which guarantee that each network has routes that are acceptable for public transport operations. MATSim is then used to evaluate the generated alternatives, by simulating the daily plans of travellers on each network. A typical daily plan is a sequential ordering of all the trips made by a commuter within a day. Automated Fare Collection (AFC) data from the MyCiTi BRT was used to create this plan. Lastly, the NSGA-II is used to search for an efficient set of network solutions, also known as a Pareto set or a non-dominated set in the context of Multi-objective Optimisation (MOO). In each generation of the optimisation process, MATSim is used to evaluate the current solution. Hence a suitable encoding scheme is defined to enable a smooth iv translation of the solution between the NSGA-II and MATSim. Since the solution of multi-objective optimisation problems is a set of network solutions, further analysis is done to identify the best compromise solution in the Pareto set. Extensive computational testing of the SBO model has been carried out. The tests involve evaluating the computational performance of the model. The first test measures the repeatability of the model's result. The second computational test considers its performance relative to indicators like the hypervolume and spacing indicators as well as an analysis of the model's Pareto front. Lastly, a benchmarking of the model's performance when compared with other optimisation algorithms is carried out. After testing the so-called Simulation-based Transit Network Design Model (SBTNDM), it is then used to design pubic transport networks for the MyCiTi BRT. Two applications are considered for the model. The first application deals with the public transport performance of the network solutions in the Pareto front obtained from the SBTNDM. In this case study, different transport network indicators are used to measure how each solution performs. In the second scenario, network design is done for the 85th percentile of travel demand on the MyCiTi network over 12 months. The results show that the model can design robust transit networks. The use of simulation as the agency of optimisation of public transport networks represents the main innovation of the work. The approach has not been used for public transport network design to date. The specific contribution of this work is in the improved modelling of public transport user behaviour with Agent-based Simulation (ABS) within a Transit Network Design (TND) framework. This is different from the conventional approaches used in the literature, where static trip-based travel demand models like the four-step model have mostly been used. Another contribution of the work is the development of a robust technique that facilitates the simultaneous optimisation of network routes and their operational frequencies. Future endeavours will focus on extending the network design model to a multi-modal context.

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L'optimisation de l'association " antenne - système" est une préoccupation majeure des concepteurs de tags RFID UHF et micro-ondes. L'évaluation conjointe de l'énergie reçue par ces antennes et de l'énergie re-rayonnée permettrait aux concepteurs d'évaluer directement les potentialités de télé-alimentation de leurs tags ainsi que la qualité de la communication. Pour répondre à cette problématique, nous avons développé une stratégie originale de modélisation et de simulation de systèmes RFID intégrés reposant sur l'utilisation du langage VHDL-AMS; langage compatible avec la majorité des outils de Conception Assistée par Ordinateur utilisés en microélectronique. La solution que nous proposons consiste en une modélisation à différents niveaux d'abstraction du système RFID que nous souhaitons optimiser, y compris le lien RF et les antennes. Nous adaptons ainsi le flot de conception classique largement utilisé en électronique numérique à un problème de conception mixte et RF.

Das Thermomanagement in Brennstoffzellenfahrzeugen (FCEV) stellt eine komplexe Herausforderung dar. Insbesondere, wenn im Zuge thermischer Optimierungen, wie sie bereits im Bereich batterieelektrischer Fahrzeuge etabliert sind, komplexe Verschaltungen der beteiligten Fahrzeugsysteme vorgenommen werden. Im Rahmen des Forschungsprojektes HZwo:InTherm wurden an der TU Chemnitz verschiedene Ansätze zur Simulation von Thermomanagementstrukturen in Brennstoffzellenfahrzeugen (FCEV) sowohl in Matlab/Simulink als auch in KULI untersucht. Augenmerk lag hierbei auf einem stabilen Zusammenspiel der Teilsysteme Brennstoffzelle, Hybridbatterie, Tanksystem, Wärmepumpe, Fahrgastzelle sowie Traktionsmaschine und Leistungselektronik. Als besondere Herausforderung zeigte sich hierbei die Simulation geschlossener Kühlkreisläufe mit inkompressiblem Kühlmedium sowie die Umsetzung eines möglichst generalisierten Modellaufbaus für die implementierten Teilmodelle. Im Rahmen dieses Beitrags sollen sowohl die Modellierungsansätze als auch die erzielten Ergebnisse vorgestellt und diskutiert werden. / Thermal management in fuel cell electric vehicles (FCEV) poses a complex challenge. Especially for thermal optimisations with complex interconnections, as it is already state of the art in battery electric vehicles. Within the research project HZwo:InTherm different approaches for the simulation of thermal management systems of FCEV have been under investigation, in both Matlab/Simulink as well as in KULI. Focus was the stable interaction of the subsystems fuel cell, hybrid battery, tank system, heat pump, passenger cabin as well as traction motors and inverters. A particular challenge is the simulation of a closed coolant loop with incompressible coolant liquid and its model realization with generalized model structures for the different parts of the model. This article presents both the modelling approach as well as the simulation results.