L'épuisement annoncé dans les prochaines décennies des ressources fossiles qui fournissent actuellement plus de 70% du carburant consommé dans les transports terrestres, aériens et maritimes au niveau mondial, incite à l'identification et le développement de nouvelles sources d'énergies renouvelables. La production de biocarburants issue de l'exploitation de la biomasse représente une des voies de recherche les plus prometteuses. Si la première génération des biocarburants (production à partir de plantes sucrières, de céréales ou d'oléagineux) atteint ses limites (concurrence avec les usages alimentaires, en particulier), la deuxième génération, produite à partir de ressources carbonées non alimentaires (lignocellulosique, mélasse, vinasse...), pourrait prendre le relais, une fois que les procédés de conversion seront suffisamment maîtrisés. À plus long terme, une troisième génération pourrait voir le jour, qui reposerait sur l'exploitation de la biomasse marine (microalgues, en particulier) mais où de nombreux verrous restent toutefois à lever : optimisation des procédés de culture et de récolte, extraction à coût réduit, optimisation des voies métaboliques etc. Il est à retenir que la stratégie nationale de recherche et d'innovation (SNRI) a retenu quatre « domaines clés » pour l'énergie : le nucléaire, le solaire photovoltaïque, les biocarburants de deuxième génération et les énergies marines. Ceux-ci sont complétés, au nom de leur contribution potentielle à la lutte contre le changement climatique, par le stockage du CO2, la conversion de l'énergie (dont les piles à combustible) et l'hydrogène. Le présent projet de recherche s'intéresse à explorer des voies d'amélioration de l'efficacité de la biotransformation de matière organique non alimentaire de nature industrielle en biocarburants de deuxième génération. En particulier, on s'intéressera à deux aspects complémentaires : l'optimisation des organismes microbiens et des voies métaboliques pour l'amélioration du rendement biologique de fabrication de biocarburants ; l'optimisation des procédés de mise en culture des microorganismes et d'extraction des biocarburant. Le projet de thèse consiste à mettre en œuvre les biotechnologies blanches, la biologie de synthèse et le génie des procédés pour la caractérisation de souches bactériennes, de leurs voies métaboliques et de prototypes expérimentaux pour la fabrication de biocarburants, de méthane et d'hydrogène à partir de rejets provenant de l'industrie sucrière de La Réunion, à savoir la mélasse ou la vinasse. Ce projet permettrait d'envisager de nouvelles perspectives de valorisation pour ces déchets industriels et de participer à la construction, à terme, d'une industrie réunionnaise durable des biocarburants et de l'hydrogène. / Hydrogen is a candidate for the next generation fuel with a high energy density and an environment friendly behavior in the energy production phase. Micro-organism based biological production of hydrogen currently suffers low hydrogen production yields because the living cells must sustain different cellular activities other than the hydrogen production to survive. To circumvent this, a team have designed a synthetic cell-free system by combining 13 different enzymes to synthesize hydrogen from cellobiose. This assembly has better yield than microorganism-based systems. We used methods based on differential equations calculations to investigate how the initial conditions and the kinetic parameters of the enzymes influenced the productivity of a such system and, through simulations, to identify those conditions that would optimize hydrogen production starting with cellobiose as substrate. Further, if the kinetic parameters of the component enzymes of such a system are not known, we showed how, using artificial neural network, it is possible to identify alternative models that allow to have an idea of the kinetics of hydrogen production. During our study on the system using cellobiose, other cell-free assemblies were engineered to produce hydrogen from different raw materials. Interested in the reconstruction of synthetic systems, we decided to conceive various tools to help the automation of the assembly and the modelling of these new synthetic networks. This work demonstrates how modeling can help in designing and characterizing cell-free systems in synthetic biology.

The transition of the North African electricity system towards renewable energy technologies is analyzed in this thesis. Large potentials of photovoltaics (PV), concentrating solar power (CSP) and onshore wind power provide the opportunity to achieve a long-term shift from conventional power sources to a highly interconnected and sustainable electricity system based on renewable energy sources (RES). A multi-dimensional analysis evaluates the economic and technical effects on the electricity market as well as the socio-economic impact on manufacturing and employment caused by the large deployment of renewable energy technologies. The integration of renewable energy (RE) into the electricity system is modeled in a linear optimization model RESlion which minimizes total system costs of the long-term expansion planning and the hourly generation dispatch problem. With this model, the long-term portfolio mix of technologies, their site selection, required transmission capacities and the hourly operation are analyzed. The focus is set on the integration of renewable energy in the electricity systems of Morocco, Algeria, Tunisia, Libya and Egypt with the option to export electricity to Southern European countries. The model results of RESlion show that a very equal portfolio mix consisting of PV, CSP and onshore wind power is optimal in long-term scenarios for the electricity system. Until the year 2050, renewable energy sources dominate with over 70% the electricity generation due to their cost competiveness to conventional power sources. In the case of flexible and dispatchable electricity exports to Europe, all three RE technologies are used by the model at a medium cost perspective. The socio-economic impact of the scenarios is evaluated by a decision model (RETMD) for local manufacturing and job creation in the renewable energy sector which is developed by incorporating findings from expert interviews in the RE industry sector. The electricity scenarios are assessed regarding their potential to create local economic impact and local jobs in manufacturing RE components and constructing RE power plants. With 40,000 to 100,000 new jobs in the RE sector of North African countries, scenarios with substantial RE deployment can provide enormous benefits to the labor market and lead to additional economic growth. The deployment of renewable energy sources in North Africa is consequently accelerated and facilitated by finding a trade-off between an optimal technology portfolio from an electricity system perspective and the opportunities through local manufacturing. By developing two model approaches for evaluating the effects of renewable energy technologies in the electricity system and in the industrial sector, this thesis contributes to the literature on energy economics and energy policy for the large-scale integration of renewable energy in North Africa.:Abstract iii Acknowledgement iv Table of contents v List of tables ix List of figures xii List of abbreviations xvi 1 Introduction 1 1.1 Renewable energy in North Africa 2 1.2 Research questions and aim of this thesis 3 1.2.1 Modeling of electricity systems 4 1.2.2 Modeling of manufacturing and employment impact 6 1.2.3 Optimal renewable energy scenarios 6 1.3 Related research 7 1.4 Structure of thesis 7 2 Modeling fundamentals for electricity systems with renewable energy sources 9 2.1 Energy system modeling 9 2.2 Electricity models 16 2.2.1 Classifications and taxonomy 17 2.2.2 Differences between operation models and planning models 20 2.2.3 Typical modeling approaches 21 2.3 Optimization models 23 2.3.1 Basic model structure 23 2.3.2 Objective functions of electricity models 24 2.3.3 Technical aspects of electricity systems as models constraints 26 2.3.4 Combining different objectives in energy scenarios 27 2.4 Models for high shares of renewable energy 28 2.5 Models for North African electricity systems 31 2.6 Conclusions for model development 34 3 Electricity system of North Africa 36 3.1 Market structure 36 3.2 National targets for renewable energy 40 3.2.1 Morocco 40 3.2.2 Algeria 41 3.2.3 Tunisia 42 3.2.4 Libya 42 3.2.5 Egypt 43 3.3 Long-term development of electricity demand 44 3.4 Electricity exports to Europe 47 3.5 Geopolitical risks for the electricity system 51 4 Development of the electricity market model RESlion 53 4.1 Model requirements and modeling goals 53 4.2 Modeling of renewable energy technologies 56 4.2.1 Onshore wind power plants and wind resources 59 4.2.2 PV power plants and solar resources 61 4.2.3 CSP plants and solar resources 63 4.2.4 Hydro power plants and energy storage systems 65 4.3 General model approach of RESlion 65 4.4 Model description of RESlion 69 4.4.1 Introduction to the model structure 69 4.4.2 Temporal coverage 70 4.4.3 Objective function 72 4.4.4 Technology independent model constraints 74 4.4.5 Regional electricity exchange: Transmission lines 76 4.4.6 Renewable energy technologies 78 4.4.7 Hydro and storage power plants 80 4.4.8 Uncertainty of input parameters and assumptions 81 4.5 Modeling of expansion planning 83 4.6 Modeling of detailed hourly generation dispatch 83 4.7 Extension options to a Mixed Integer Linear Programming model 84 4.8 Solver selection and implementation environment 85 5 Model-based analysis of future electricity scenarios for North Africa 86 5.1 Scenario assumptions 86 5.2 Scenario definition 89 5.3 Technical and economic input data 94 5.4 Model adjustment 99 5.4.1 Electricity generation in reference year 2010 99 5.4.2 Testing of results with detailed hourly generation dispatch 100 5.5 Electricity scenarios for North Africa by 2050 102 5.5.1 Development of the generation system 102 5.5.2 System and generation costs 106 5.5.3 Site selection of RES generation capacities 108 5.5.4 Regional transmission lines 114 5.5.5 Energy storage systems 118 5.5.6 Technology specific generation 119 5.5.7 CO2 emissions 126 5.6 Sensitivity analyses 126 5.6.1 Adaption of market conditions: Split of electricity markets 127 5.6.2 Technology focus 127 5.6.3 Adaption of cost trends for fossil fuels, transmission lines and storage systems 129 5.7 Technology specific findings for CSP, PV and wind power 131 5.7.1 Typical sites and locations for electricity generation from RES 131 5.7.2 Influence of wind speeds and solar irradiation 131 5.7.3 Interactions with conventional power plants 132 5.8 Electricity scenarios with export to Europe 133 5.9 Discussion of RESlion model and its results 139 6 Model development for socio-economic impact analysis 142 6.1 The idea of combining a cost-optimized electricity system with a socio-economic analysis 142 6.2 Literature review and terminology 145 6.3 Data acquisition and further studies 148 6.4 Model description of RETMD 151 6.4.1 Model objectives 151 6.4.2 Model structure and decision modeling 152 6.4.3 Model limitations and uncertainties 156 6.5 Data input of RETMD 157 6.5.1 Construction of reference power plants 157 6.5.2 Operation of reference power plants 159 6.5.3 Status quo of local manufacturing in recent RE projects 160 6.6 Sensitivity of RETMD on market size and know-how 161 6.7 Discussion of model achievements 163 7 Manufacturing and employment impact of optimized electricity scenarios 165 7.1 Demand scenarios for the RE markets from 2012 to 2030 165 7.2 Economic impact and employment creation 166 7.3 Technology specific development of local manufacturing 168 7.4 Country specific development of local manufacturing 172 7.5 Potentials of local manufacturing in each scenarios 174 7.6 Local economic impact 176 7.7 Local employment impact 177 7.8 Evaluation of scenario results 181 7.9 Electricity system analysis and RE manufacturing: Results and discussion of the combined analysis 183 8 Conclusions and outlook 186 8.1 Conclusion on model developments 186 8.2 Conclusion on renewable energy in North Africa 187 8.3 Outlook and further research 189 9 Bibliography 191 10 Appendix 210

Rund 70 % der Energieaufnahme von elektrischen Antriebssystemen wird von quasistationären Antrieben in Transportanlagen hervorgerufen. Eine gesteigerte Energieeffizienz führt neben reduzierten Energiekosten zu weiteren Nutzeffekten, wie z.B. einem verringerten Kühlaufwand, einem kleinerem Bauraum und einer höheren Lebensdauer der Komponenten. Zur Steigerung der Energieeffizienz dieser Transportanlagen werden in dieser Arbeit Methoden zur Auslegung der zugehörigen Antriebssysteme unter besonderer Berücksichtigung des Förderprozesses erarbeitet. Als repräsentative Transportanwendungen werden Pumpen- und Förderbandanlagen untersucht. Dabei wird das gesamte elektromechanische System analysiert, um das volle Energiesparpotenzial zu erfassen – beginnend mit dem Lastprofil des transportierten Förderguts bis hin zur elektrischen Energieversorgung. Hierzu werden alle Systemkomponenten modelliert, um die Verluste in verschiedenen Betriebspunkten im Volllast- und Teillastbereich abzuschätzen. Darauf aufbauend erfolgt die Erarbeitung praktikabler Projektierungshinweise und prozessspezifischer Auswahldiagramme, welche eine schnelle Vorauswahl der energieeffizientesten Antriebstopologie ermöglichen. Da die Verlustmodelle auf frei zugänglichen Datenblattangaben basieren, können die vorgestellten Methoden und Auswahlkriterien bereits in einem frühen Projektierungsstadium zur Auslegung einer energieeffizienten Transportanlage angewandt werden.

Im Rahmen der vorliegenden Arbeit wird gezeigt, wie ein Gebäude- und Anlagensimulationsprogramm mit bekannten Optimierungsalgorithmen gekoppelt und zur theoretischen Lösung optimaler Steuer- und Regelprobleme in der Gebäudetechnik eingesetzt werden kann. Theoretische Optimallösungen erlauben im Sinne eines optimalen Vergleichsprozesses die Bewertung praktisch anderweitig umsetzbarer Steuerungs- und Regelungsmechanismen. Die im Hinblick auf ein gewähltes Gütekriterium erforderliche Notwendigkeit zur Verbesserung von vorhandenen Steuerungs- und Regelungsszenarien sowie die theoretisch maximal erreichbaren Extremwerte lassen sich leicht abschätzen.

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Tracked vehicles are designed to operate in various terrains, ranging from soft mud to hard tarmac. This wide range of terrains presents significant challenges for the suspension system, as its components must be suitable for all types of terrain. The selection of these components is crucial for minimizing acceleration levels within the vehicle, ensuring that personnel can comfortably endure extended durations inside. BAE Systems Hägglunds AB develops and produces an armored tracked vehicle called the CV90. Within the CV90’s suspension system, a key component known as the torsion bar, a rotational spring, plays a primary role in reducing the vehicle’s motion. The CV90 vehicle has seven wheels on each side, with each wheel having its dedicated torsion bar. To measure the whole-body vibration experienced within the vehicle, a measurement called the Vibrational Dose Value (VDV) is utilized. The main objective of this thesis is to develop a data-driven model to optimize the suspension system by identifying the combination of torsion bars that generates the smallest VDV. The data used for optimization is based on simulations of the CV90 vehicle in a virtual environment. In the simulation, the CV90 vehicle, with its full dynamics, is driven over a specific virtual road at a particular velocity. The simulation itself cannot be manipulated; only the input values can be adjusted. Thus, we consider the simulation as a black box, which led us to implement the black-box optimization algorithm known as Particle-Swarm. In this thesis, four different roads, each with velocities ranging from four to seven different levels, were provided to the optimization model. The results show that the model identifies a combination of torsion bars that generates a small VDV for all combinations of velocities and roads, with an average VDV improvement of around 20% - 60% compared to a reference case. Since this thesis serves as a proof of concept, the conclusion is that the devised method is effective and suitable for addressing the problem at hand. Nonetheless, for seamless integration of this method into the tracked vehicle development process, further research is necessary.

The diploma thesis deals with the use of a simulation model for the development of an automatic algorithm for the creation of a routing table and route evaluation in a transport system. It includes a search of modeling and simulation issues and state-space search issues with an analysis of available search methods. The simulation model of the transport system is created in the software Tecnomatix Plant Simulation, where an algorithm for automatic creation of routing tables for routing and evaluation of routes according to static criteria is subsequently developed and tested. The work presents a proposal for the principle of the algorithm for evaluating the routes of the transport system, including dynamic criteria and their optimization.

<div><p><br></p></div><p>This study makes use of a Time-Resolved Raman Spectroscopy (TRRS) system developed in the Purdue Civil Engineering spectroscopy laboratory to advance technology critical to enable field deployment of Raman spectroscopic systems, with a primary focus on developing solutions to overcome two specific barriers to Raman analysis in the natural environment: (1) obtaining Raman spectra of chemical compounds at field-relevant concentrations, and (2) realizing economical spatial monitoring. To inform both streams of activity, this work first explores the role of component choice and apparatus design on Raman system output. A component-level Raman system transfer function is developed in terms of intensity, wavelength, and time which yields detailed insight into system performance that greatly exceeds traditional single “system factor” treatments of apparatus effects. The modelling frame provided by the transfer function is universally applicable in that it is inclusive of the majority of component choices that may be encountered in any open-path or closed-path Raman system, and is likely to be valuable in efforts to assess the performance benefits and limitations of system designs, modify or tailor apparatus layouts, facilitate experiment design, and compare results obtained on different systems. </p><p><br></p><p>The system characterization offered by the transfer function is then employed to develop a multi-photon counting algorithm realized through digital signal processing (DSP) which captures photon arrivals traditionally ignored in conventional counting methods. This approach increases acquired Raman intensity for any given analyte by using detector output voltage or a voltage-time product as an energy proxy – an approach that is likey broadly applicable to any spectroscopic techniques employing detectors that make use of the photoelectric effect. In experiments carried out on analytes (nitrate, isopropanol, and rhodamine 6G) in aqueous solutions, enhanced observations enabled by the multi-photon counting algorithm are shown to increase observed Raman intensities of low Raman-yield solutions 2.0-3.1-fold compared to single-threshold analysis, and also extend the upper observation limit of strong Raman-yield solutions that would traditionally saturate detectors using a binary photon counting scheme. Notably, the improved performance offered by the multi-photon counting algorithm is realized through comparison of multi-photon and conventional counting algorithms applied to the same data in a post-processing exercise, thus eliminating any effects of test-to-test variation on results, and highlighting the ability to employ the developed counting approach without modification of traditional systems.</p><p><br></p><p>Additional insights from the system transfer function are also used to inform exploration of a novel approach to enable spatial environmental monitoring via Raman spectroscopy by combining fiber optics, optical switch technology, and the Raman system prototype. Tests designed to evaluate the system configured as a multiplexed optically switched fiber optic network demonstrate the potential to deliver excitation and collect Raman scattering from different desired monitoring locations with a sole excitation source and a single detector over substantial distances. Using nitrate as an example compound of interest, it is demonstrated that the system has a detection limit of 5 ppm within approximately 1.5 meters, which increases to 15 ppm at 100 m, and 38 ppm at 200 m. Modelling informed using the developed system transfer function highlights that improving the prototype by eliminating fiber connectors and making use of commercially available visible-light optimized fiber can substantially extend the range of the system, offering a 15-ppm nitrate detection limit at 2100 m. As increases in laser power, testing time, and collection optic efficiency are all also straightforward and viable, the prototype demonstrates realistic potential to achieve field relevant detection sensitivity over great distance.</p><p><br></p><p>As a final demonstration of system potential, a set of experiments on aqueous nitrate solutions is performed to understand the influence of turbidity, fluorescence, optics size, and varied raw data integration lengths on Raman observations. Results demonstrate that cumulative advances in the TRRS system establish a new generation of Raman spectroscopic sensing amenable to long-term environmental monitoring over significant spatial extent in complex in-situ conditions. Specific advances made herein include enhanced power delivery and scattered light collection informed by the system transfer function, increases in sensitivity from multi-photon counting, and incorporation of optical multiplexing. Overall, the Time-Resolved Raman Spectroscopic System (TRRS) now offers a set of capabilities that bring in-field deployment within practical reach.</p>