During the last century, the number of car users has increased as an effect of the increasing population growth. To manage the environmental and infrastructural challenges that comes with a more congested traffic network, traffic planning has become of higher importance to analyze the current traffic state and to predict future capacity challenges and effects of investments. These analysis and evaluations are commonly performed in different traffic analysis tools, where updated and realistic traffic demand needs to be provided to ensure reasonable results. In this thesis, a macroscopic model of Norrköping municipality constructed in the traffic demand modelling software Visum and a daily Origin-Destination(OD)-matrix is considered. The goal of this thesis is to produce a method that modify the current daily demand matrix into hourly demand matrices, called hourly target matrices, that represents a typical weekday. The goal is also to implement and evaluate the OD-estimation algorithm Simultaneous Perturbation Stochastic Approximation (SPSA) to obtain updated and valid demand matrices for the network model of Norrköping. The method of dividing the daily demand matrix into hourly target matrices is based on the paper by Spiess %26 Suter (1990). The method makes use of the available daily trip purpose matrices combined with hourly link flow observations from 96 links in a multiple linear regression model to obtain 24 hourly demand matrices. The resulting matrices are compared with the link flow observations and has different levels of R^2-fit, the maximum fit is 85.79 % and the minimum fit is 55.89 %. The average R^2-value is 72 %. The OD-estimation based on SPSA is performed on the AM and PM peak hours. The algorithm is implemented in Python scripts that are called from Visum where the traffic assignments is calculated. The result is an increase in R^2-value since the link flow difference between estimated and observed link flow is decreased. In total, the estimated link flows are improved by 7.4 % in the AM peak hour and 15.6 % in the PM peak hour. The total absolute change in OD-demand is 3 871 trips for AM peak hour and 6 452 trips for the PM peak hour. The estimated OD-matrices are evaluated by qualitatively visualizing the difference in heat maps and in the quantitative measure structural similarity index. The result is no major structural change from the hourly target matrices which verifies that the information used when the target matrices is produced still is considered. The total demand increased in both hours, with 505 respectively 2 431 trips and flows in some OD-pairs has a very high percental change. This was restricted by adding a penalty term to the SPSA-algorithm on the PM peak hour. The result of penalized SPSA is a much less increase of total demand as well as less percental change of the OD-flows. Though, this to a cost of not decreasing the link flow difference in the same magnitude.

Monoclonal antibodies (MAbs) have an expanding market for use in diagnostic and therapeutic applications. Industrial production of these biopharmaceuticals is usually achieved based on fed-batch cultures of mammalian cells in bioreactors (Chinese hamster ovary (CHO) and Hybridoma cells), which can express different kinds of recombinant proteins. In order to reach high cell densities in these bioreactors, it is necessary to carry out an optimization of their production processes. Hence, macroscopic model equations must be developed to describe cell growth, nutrient consumption and product generation. These models will be very useful for designing the bioprocess, for developing robust controllers and for optimizing its productivity.<p>This thesis presents a new kinetic model of hybridoma cell metabolism in fed batch culture and typical illustration of a systematic methodology for mathematical modelling, parameter estimation and model-based optimization and state estimation of bioprocesses. <p>In the first part, a macroscopic model that takes into account phenomena of overflow metabolism within glycolysis and glutaminolysis is proposed to simulate hybridoma HB-58 cell cultures. The model of central carbon metabolism is reduced to a set of macroscopic reactions. The macroscopic model describes three metabolism states: respiratory metabolism, overflow metabolism and critical metabolism. The model parameters and confidence intervals are obtained via a nonlinear least squares identification. It is validated with experimental data of fed-batch hybridoma cultures and successfully predicts the dynamics of cell growth and death, substrate consumption (glutamine and glucose) and metabolites production (lactate and ammonia). Based on a sensitivity analysis of the model outputs with respect to the parameters, a model reduction is proposed. <p>In the next step, the effort is directed to the maximization of biomass productivity in fed-batch cultures of hybridoma cells based on the overflow metabolism model. Optimal feeding rate, on the one hand, for a single feed stream containing both glucose and glutamine and, on the other hand, for two separate feed streams of glucose and glutamine are determined using a Nelder-Mead simplex optimization algorithm. Two different objective functions (performance criteria) are considered for optimization; the first criterion to be maximized is the biomass productivity obtained at the end of the fed-batch culture, the second criterion to be minimized is the difference between global substrate consumption and the maximum respiratory capacity.<p>The optimal multi exponential feed rate trajectory improves the biomass productivity by 10% as compared to the optimal single exponential feed rate. Moreover, this result is validated by the one obtained with the analytical approach in which glucose and glutamine are fed to the culture so as to control the hybridoma cells at the critical metabolism state, which allows maximizing the biomass productivity. The robustness analysis of optimal feeding profiles obtained with different optimization strategies is considered, first, with respect to parameter uncertainties and, finally, with respect to model structure errors.<p>Finally, the overflow metabolism model is used to develop an extended Kalman filter for online estimation of glucose and glutamine in hybridoma cell fed-batch cultures based on the considered available measurements (biomasses (on-line), lactate and ammonia (on-line or off-line)). The observability conditions are examined, and the performances are analysed with simulations of hybridoma cell fed-batch cultures. Glutamine estimation sensitivity is enforced by minimizing a cost function combining a usual least-squares criterion with a state estimation sensitivity criterion. <p> / Doctorat en Sciences de l'ingénieur / info:eu-repo/semantics/nonPublished

La congestion des autoroutes est un problème qui apparait de façon récurrente et qui a un large impact économique, environnemental et social. Ce problème peut être résolu en augmentant la capacité des autoroutes ou en diminuant la demande de trafic. Ces solutions sont longues à mettre en oeuvre et sont très coûteuses. Une solution accessible à plus court terme consiste à mettre en oeuvre un système de gestion du trafic. Dans cette optique, plusieurs actions et mesures de contrôle ont été développées pour améliorer l’efficacité des autoroutes. Parmi ces actions, on peut citer le contrôle d’accès et la limitation dynamique de la vitesse. Le contrôle d’accès consiste en une régulation du flux de véhicules désirant entrer sur une autoroute à partir d’une rampe. Nous avons développé la stratégie DFC (Différence de Flux Caractérisée par une densité désirée). Elle vise à maintenir sur la chaussée principale, au niveau de la rampe d’entrée,une densité inférieure à une cible déterminée au préalable à l’aide de simulations. Cette nouvelle stratégie a été comparée aux stratégies existantes telles que ALINEA et PI-ALINEA. La stratégie DFC présente l’intérêt de ne pas générer de phénomènes oscillatoires dans les trajectoires du flux et de ne pas nécessiter de paramètres à régler. La limitation dynamique de la vitesse impose sur plusieurs tronçons de la chaussée principale une limitation de vitesse qui dépend des conditions de circulation. L’objectif est d’éviter la congestion au niveau d’un goulot d’étranglement qui se trouve en aval. Nous avons proposé plusieurs stratégies de limitation dynamique de la vitesse. Elles utilisent toutes le modèle de trafic METANET. Deux des méthodes proposées exploitent le terme d’anticipation du modèle METANET et la troisième est basée sur le flux. Enfin, les différentes stratégies de limitation dynamique de la vitesse ont été utilisées en coordinationavec le contrôle d’accès DFC. La coordination permet d’obtenir des résultats meilleurs qu’un contrôle d’accès utilisé seul ou une limitation dynamique de la vitesse utilisée seule. / The highways congestion is a problem which appears in a recurring way and which has a wide economic, environmental and social impact. This problem can be resolved by increasing the highways capacity or by decreasing the traffic demand. These solutions are long to operate and are very expensive. An accessible solution in the shorter run consists in implementing a traffic management system.In this optics, several actions and control measures were developed to improve the efficiency of highways. Among these actions, we can quote the ramp metering control and the dynamic speed limits.The ramp metering consists of a regulation of the vehicles flow wishing to enter on a highway from an on-ramp. We developed the DFC strategy (Différence de Flux Characterisée par une densité désirée). It aims at maintaining on the main road, at the vicinity of the on-ramp, a density lower than a target beforehand determined by means of simulations. This new strategy was compared with the existing strategies such as ALINEA and PI-ALINEA. The DFC strategy presents the interest not to generate oscillatory phenomena in the trajectories of flow and not to require parameters to be adjusted. The dynamic speed limits imposes on several sections of the main road a speed limit which depends on traffic conditions. The objective is to avoid the congestion at a downstream bottleneck. We proposed several strategies of dynamic speed limits. They use quite the METANET model of traffic. Two of the proposed methods exploit the model METANET anticipation term and the third is based on the flow. Finally, the various strategies of dynamic speed limits were used in coordination with the DFC ramp metering. The coordination allows to obtain the results better than ramp metering used only or dynamic speed limits used only.