Dissertations / Theses on the topic 'Urban network modelling'

In this study a dynamic assignment model is developed which estimates travellers' route and departure time choices and the resulting time varying traffic patterns during the morning peak. The distinctive feature of the model is that it does not restrict the geometry of the network to specific forms. The proposed framework of analysis consists of a travel time model, a demand model and a demand adjustment mechanism. Two travel time models are proposed. The first is based on elementary relationships from traffic flow theory and provides the framework for a macroscopic simulation model which calculates the time varying flow patterns and link travel times given the time dependent departure rate distributions; the second is based on queueing theory and models roads as bottlenecks through which traffic flow is either uncongested or fixed at a capacity independent of traffic density. The demand model is based on the utility maximisation decision rule and defines the time dependent departure rates associated with each reasonable route connecting, the O-D pairs of the network, given the total utility associated with each combination of departure time and route. Travellers' choices are assumed to result from the trade-off between travel time and schedule delay and each individual is assumed to first choose a departure time t, and then select a reasonable route, conditional on the choice of t. The demand model has therefore the form of a nested logit. The demand adjustment mechanism is derived from a Markovian model, and describes the day-to-day evolution of the departure rate distributions. Travellers are assumed to modify their trip choice decisions based on the information they acquire from recent trips. The demand adjustment mechanism is used in order to find the equilibrium state of the system, defined as the state at which travellers believe that they cannot increase their utility of travel by unilaterally changing route or departure time. The model outputs exhibit the characteristics of real world traffic patterns observed during the peak, i. e., time varying flow patterns and travel times which result from time varying departure rates from the origins. It is shown that increasing the work start time flexibility results in a spread of the departure rate distributions over a longer period and therefore reduces the level of congestion in the network. Furthermore, it was shown that increasing the total demand using the road network results in higher levels of congestion and that travellers tend to depart earlier in an attempt to compensate for the increase in travel times. Moreover, experiments using the queueing theory based travel time model have shown that increasing the capacity of a bottleneck may cause congestion to develop downstream, which in turn may result in an increase of the average travel time for certain O-D pairs. The dynamic assignment model is also applied to estimate the effects that different road pricing policies may have on trip choices and the level of congestion; the model is used to demonstrate the development of the shifting peak phenomenon. Furthermore, the effect of information availability on the traffic patterns is investigated through a number of experiments using the developed dynamic assignment model and assuming that guided drivers form a class of users characterised by lower variability of preferences with respect to route choice.

The level of air pollution in urban areas, which is largely affected by road traffic, is an issue of high political relevance. Congestion is most prevalent in urban areas and a common and increasingly present phenomenon worldwide. The first four chapters of this study have investigated how and to what extent models, which are used to predict emissions on road links in urban road networks, include the effects of congestion on emissions. In order to make this assessment, traffic engineering literature and empirical studies have been examined and used as a basis to review (current) emission models that exist or have been used around the world. Congestion causes changes in driving patterns of individual vehicles in a traffic stream, and these changes are subsequently reflected in changes in congestion indicators and changes in emission levels. This consideration and a literature review has led to a proposed 'congestion typology' of emission models, which reflects the different ways in which and the extent to which congestion has been incorporated in these models. The typology clarifies that six of in total ten families of emission models that were investigated in this thesis explicitly consider congestion in the modelling process (i.e. model variables are related to congestion), although this is done in different ways. For the remaining four families of emission models it was not possible to determine the extent to which congestion has been incorporated on the basis of literature review alone. Two families fell beyond the scope of this work since they cannot be used to predict emission on road links. For the other two families it became clear in the course of the thesis that the extent can be determined through analysis of driving pattern data (and other information with respect to e.g. data collection) that were used in the model development. A new methodology is presented in this thesis to perform this analysis and to assess the mean level of congestion in driving patterns (driving cycles). The analysis has been carried out for one important family of emission models, the so-called travel speed models ('average speed models'), which are used extensively in urban network modelling. For four current models (COPERT III, MOBILE 6, QGEPA 2002, EMFAC 2000), it is concluded that these models implicitly (i.e. congestion is inherently considered) take varying levels of congestion into account, but that this conclusion is subject to a number of limitations. It became clear in the course of this study that prediction of (the effects of) congestion in both traffic models and emission models is generally restricted to certain modelling dimensions. As a consequence, the effects of congestion are only partially predicted in current air emission modelling. Chapter 5 has attempted to address the question whether congestion is actually an important issue in urban network emission modelling or not. It also addressed the question if different types of emission models actually predict different results. On the basis of a number of selection criteria, two types of models were compared, i.e. one explicit model (TEE-KCF 2002) and two implicit models (COPERT III, QGEPA 2002). The research objectives have been addressed by applying these emission models to a case-study urban network in Australia (Brisbane) for which various model input attributes were collected from different sources (both modelled and field data). The findings are limited by the fact that they follow from one urban network with particular characteristics (fleet composition, signal settings, speed limits) and application of only a few particular emission models. The results therefore indicate that: 1. Changes in traffic activity (i.e. distribution of vehicle kilometres travelled on network links) over the day appear to have the largest effect on predicted traffic emissions. 2. Congestion is an important issue in the modelling of CO and HC emissions. This appears not to be the case for NOx emissions, where basic traffic composition is generally a more important factor. For the most congested parts in the urban network that have been investigated, congestion can more than double predicted emissions of CO and HC. 3. Different types of emission models can produce substantially different results when absolute (arithmetic) differences are considered, but can produce similar results when relative differences (ratio or percent difference) are considered.

The level of air pollution in urban areas, which is largely affected by road traffic, is an issue of high political relevance. Congestion is most prevalent in urban areas and a common and increasingly present phenomenon worldwide. The first four chapters of this study have investigated how and to what extent models, which are used to predict emissions on road links in urban road networks, include the effects of congestion on emissions. In order to make this assessment, traffic engineering literature and empirical studies have been examined and used as a basis to review (current) emission models that exist or have been used around the world. Congestion causes changes in driving patterns of individual vehicles in a traffic stream, and these changes are subsequently reflected in changes in congestion indicators and changes in emission levels. This consideration and a literature review has led to a proposed 'congestion typology' of emission models, which reflects the different ways in which and the extent to which congestion has been incorporated in these models. The typology clarifies that six of in total ten families of emission models that were investigated in this thesis explicitly consider congestion in the modelling process (i.e. model variables are related to congestion), although this is done in different ways. For the remaining four families of emission models it was not possible to determine the extent to which congestion has been incorporated on the basis of literature review alone. Two families fell beyond the scope of this work since they cannot be used to predict emission on road links. For the other two families it became clear in the course of the thesis that the extent can be determined through analysis of driving pattern data (and other information with respect to e.g. data collection) that were used in the model development. A new methodology is presented in this thesis to perform this analysis and to assess the mean level of congestion in driving patterns (driving cycles). The analysis has been carried out for one important family of emission models, the so-called travel speed models ('average speed models'), which are used extensively in urban network modelling. For four current models (COPERT III, MOBILE 6, QGEPA 2002, EMFAC 2000), it is concluded that these models implicitly (i.e. congestion is inherently considered) take varying levels of congestion into account, but that this conclusion is subject to a number of limitations. It became clear in the course of this study that prediction of (the effects of) congestion in both traffic models and emission models is generally restricted to certain modelling dimensions. As a consequence, the effects of congestion are only partially predicted in current air emission modelling. Chapter 5 has attempted to address the question whether congestion is actually an important issue in urban network emission modelling or not. It also addressed the question if different types of emission models actually predict different results. On the basis of a number of selection criteria, two types of models were compared, i.e. one explicit model (TEE-KCF 2002) and two implicit models (COPERT III, QGEPA 2002). The research objectives have been addressed by applying these emission models to a case-study urban network in Australia (Brisbane) for which various model input attributes were collected from different sources (both modelled and field data). The findings are limited by the fact that they follow from one urban network with particular characteristics (fleet composition, signal settings, speed limits) and application of only a few particular emission models. The results therefore indicate that: 1. Changes in traffic activity (i.e. distribution of vehicle kilometres travelled on network links) over the day appear to have the largest effect on predicted traffic emissions. 2. Congestion is an important issue in the modelling of CO and HC emissions. This appears not to be the case for NOx emissions, where basic traffic composition is generally a more important factor. For the most congested parts in the urban network that have been investigated, congestion can more than double predicted emissions of CO and HC. 3. Different types of emission models can produce substantially different results when absolute (arithmetic) differences are considered, but can produce similar results when relative differences (ratio or percent difference) are considered.
Thesis (PhD Doctorate)
Doctor of Philosophy (PhD)
School of Environmental Planning
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Traditional network design problems only consider the long-term stationary travel patterns (e.g., fixed OD demand) and short-term variations of human mobility are ignored. This study aims to integrate human mobility characteristics and travel patterns into network design problems using a space-time network structure. Emerging technologies such as location-based social network platforms provide a unique opportunity for understanding human mobility patterns that can lead to advanced modeling techniques. To reach our goal, at first multimodal network design problems are investigated by considering safety and flow interactions between different modes of transport. We develop a network reconstruction method to expand a single-modal transportation network to a multi-modal network where flow interactions between different modes can be quantified. Then, in our second task, we investigate the trajectory of moving objects to see how they can reveal detailed information about human travel characteristics and presence probability with high-resolution detail. A time geography-based methodology is proposed to not only estimate an individual’s space-time trajectory based on his/her limited space-time sample points but also to quantify the accuracy of this estimation in a robust manner. A series of measures including activity bandwidth and normalized activity bandwidth are proposed to quantify the accuracy of trajectory estimation, and cutoff points are suggested for screening data records for mobility analysis. Finally, a space-time network-based modeling framework is proposed to integrate human mobility into network design problems. We construct a probabilistic network structure to quantify human’s presence probability at different locations and time. Then, a Mixed Integer Nonlinear Programming (MINLP) model is proposed to maximize the spatial and temporal coverage of individual targets. To achieve near optimal solutions for large-scale problems, greedy heuristic, Lagrangian relaxation and simulated annealing algorithms are implemented to solve the problem. The proposed algorithms are implemented on hypothetical and real world numerical examples to demonstrate the performance and effectiveness of the methodology on different network sizes and promising results have been obtained.

Urbanisation often exerts large-scale adverse effects on coastal areas and estuaries, which are ecologically diverse and highly productive habitats. Understanding the ecological resilience of these habitats is a prerequisite for their management. Direct quantification of ecosystem functioning using conventional approaches, however, is difficult and time-consuming. This difficulty has greatly restricted ecosystem-level research and thus, the ability to predict an ecosystem’s responses to urbanisation. The main aim of this thesis was to assess the impact of urbanisation on estuarine sandflats. I developed a novel food web analytical approach, by combining stable isotope (13C) enrichment, compartmental modelling, and ecological network analysis techniques to quantify food web dynamics. This approach was tested with estuarine sandflats, which is one of the most important coastal habitats worldwide. The novel approach allows quantitative testing of specific hypotheses about food web dynamics through manipulative experiments, by comparing system indices that reflect ecosystem condition. Further, I conducted manipulative experiments using this approach to investigate the structural and functional response of a multi-level estuarine sandflat food web to two common anthropogenic stressors from urbanisation, namely, organic enrichment and physical disturbance.
Thesis (PhD Doctorate)
Doctor of Philosophy (PhD)
Giffith School of Environment
Science, Environment, Engineering and Technology
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In many parts of the world snow melt runoff influence discharge from combined sewer overflows (CSO) and flooding in urban drainage systems. Despite this, urban snow hydrology is a field that has received little attention from the urban drainage community. The objectives of this research were to better understand urban snow hydrology and through field work and hydrological modelling quantify effects of anthropogenic activities (AA) on snow distribution, and melt in an urban environment. This means in principle how the presence (design geometry) and operation of roads and buildings influence the snow distribution and melt in urban areas. The Risvollan urban catchment (20 ha) located in Trondheim, Norway, was used as a study area. A literature review of urban snow hydrology was also carried out.

A gridded urban hydrology model (GUHM) was developed as part of the study. The principal idea of the GUHM is to subdivide an urban catchment into orthogonal equal area grid cells. The snow routine in the GUHM is based on an energy balance approach, which together with a soil-runoff routine is used to calculate a time series of rain, snow water equivalent (SWE), snow melt, and runoff, for each grid cell. In GUHM, processes such as snow clearing of roads, locally low albedos, heat/shadowing from buildings, and effects of slope and aspect are included in the model structure.

A technique for observing time series of snow covered area (SCA) for an urban catchment is presented. The method is based on image processing and neural network technology to calculate SCA from a time series of images taken from a tall building in the Risvollan catchment. It was shown that SCA on roads and roofs in general becomes more rapidly snow free during melt periods compared to the park areas of the Risvollan catchment. This can be explained by snow clearing of roads, snowdrift from roofs and high snow melt rates on roofs and roads. The high melt rates was attributed to locally low albedos in vicinity to roads, rooftop snow packs exposure to wind and solar radiation, in addition to anthropogenic heat release from the roofs themselves.

Field observations of SWE were carried out in the Risvollan catchment and it was shown that areal mean SWE located on/or nearby roads and buildings were significantly lower during mid and end of the winter, than in park areas. This can be attributed to higher melt rates caused by AA. A time series of SCA and SWE was obtained through field work for the period from 2000 to 2003 in the Risvollan catchment.

The GUHM was applied and calibrated for the Risvollan catchment for a three year period. Two seasons were used as validation period. Comparison between the simulated and observed SWE, SCA and runoff data showed that the GUHM was able to simulate snow accumulation and melt for whole seasons with short time resolution (1 hour) satisfactory.

The GUHM was used to quantify effects of AA on snow distribution and melt for six different land use scenarios in the Risvollan catchment for the period June 1998 to June 2003. The modelling results showed that when the area coverage of buildings and roads increased, the SCA and SWE more rapidly decreased during melt periods. Because of this more runoff will be produced in the early winter season (Jan-March) compared to if the catchment had been covered with only sparsely vegetated areas.

The simulation results showed that when the impervious surface covers of a catchment increase, the peak and volume runoff will also increase, as expected.

Both the field observations and the hydrological model study carried out in this work showed that AA lowers SCA and SWE more rapidly in an urban environment compared to more untouched terrain. The reasons for this are redistribution of snow, and strong snow melt rates on roads, roofs, and in snow deposit areas. Low albedos and anthropogenic heat release are the main reasons for the enhanced snow melt rates.

The antecedents and consequences of social capital were investigated in this thesis, in the context of addressing the conceptual debate as to whether social capital is an individual or a group based phenomenon. The social status of individuals and the rurality of place of residence were both found to play a significant role in determining the social capital of an individual. Investigating the consequences of social capital on self-rated happiness and health status, it was found that both individual and context level social capital were important, particularly in determining an individual’s level of happiness. Findings showed that social capital comprised of both individual and group aspects. By investigating social capital in Bhutan, the thesis contributes to understanding the operation of social capital in a developing country context.

The renewal of derelict inner-city urban districts suffering from high levels of socio-economic deprivation and sustainability problems is one of the key research areas in urban planning and regeneration. Subject to a wide range of social, economical and environmental factors, decision support for an optimal allocation of residential and service lots within such districts is regarded as a complex task. Pre-assessment of various neighbourhood factors before the commencement of actual location allocation of various public services is considered paramount to the sutainable outcome of regeneration projects. Spatial assessment in such derelict built-up areas requires planning of lot assignment for residential buildings in a way to maximize accessibility to public services while minimizing the deprivation of built neighbourhood areas. However, the prediction of socio-economic deprivation impact on the regeneration districts in order to optimize the location-allocation of public service infrastructure is a complex task. This is generally due to the highly conflicting nature of various service structures with various socio-economic and environmental factors. In regards to the problem given above, this thesis presents the development of an evolutionary AI-based decision support systemto assist planners with the assessment and optimization of regeneration districts. The work develops an Adaptive Network Based Fuzzy Inference System (ANFIS) based module to assess neighbourhood districts for various deprivation factors. Additionally an evolutionary genetic algorithms based solution is implemented to optimize various urban regeneration layouts based upon the prior deprivation assessment model. The two-tiered framework initially assesses socio-cultural deprivation levels of employment, health, crime and transport accessibility in neighbourhood areas and produces a deprivation impact matrix overthe regeneration layout lots based upon a trained, network-based fuzzy inference system. Based upon this impact matrix a genetic algorithm is developed to optimize the placement of various public services (shopping malls, primary schools, GPs and post offices) in a way that maximize the accessibility of all services to regenerated residential units as well as contribute to minimize the measure of deprivation of surrounding neighbourhood areas. The outcome of this research is evaluated over two real-world case studies presenting highly coherent results. The work ultimately produces a smart urban regeneration toolkit which provides designer and planner decision support in the form of a simulation toolkit.

Des catastrophes comme celles de Ghislenghien (Belgique), Ludwigshafen (Allemagne), ou Lyon (France), ont été attribuées à des travaux à proximité de réseaux de gaz. Bien que les canalisations soient une des méthodes les plus sures de transport pour les substances dangereuses, chaque année plusieurs cas d'accidents sont enregistrés en France. La plupart d'entre eux sont attribués à des travaux à proximité des réseaux et certains illustrent le manque de fiabilité des informations fournies. Pour prévenir de tels accidents qui impliquent les ouvriers et le public, les autorités françaises ont mis en place deux réglementations : DT-DICT : pour la sécurisation des réseaux à proximité d'excavation ; Multifluide : pour celle des réseaux dangereux lors d'événements aléatoires. Eviter de tels accidents nécessite d'acquérir et de contrôler des informations 3D concernant les différents réseaux urbains, et particulièrement ceux enterrés. Des stratégies de prévention doivent alors être adoptées. Voilà pourquoi travailler sur les réseaux et leur visualisation et la cartographie des risques, en prenant en compte le flou, est une recherche récente et importante. Les applications logicielles que je développe devraient aider les services publics et les entrepreneurs à se concentrer sur la prévention des événements dangereux grâce à des ensembles de données précises pour les utilisateurs, la définition d'un réseau de géomatique, mais aussi des méthodes telles que la triangulation, la modélisation par éléments, les calculs géométriques, l'intelligence artificielle, la réalité virtuelle
Disasters like the ones that happened in Ghislenghien (Belgium), Ludwigshafen (Germany), or Lyon (France), have been attributed to excavations in the vicinity of gas pipelines. Though pipes are one of the safest methods of transportation for conveying hazardous substances, each year many cases of damage to gas pipes are recorded in France. Most of them are due to works in the vicinity of the networks and some illustrate the lack of reliability of the provided information. Concessionaries have to take stock of the situation and to suggest areas of improvement, so that everyone could benefit from networks becoming safer.To prevent such accidents which involve workers and the public, French authorities enforce two regulations: DT / DICT: reform of the network no-damage by securing the excavations, Multifluide: reform which is interested in securing networks of hazardous events.So, to avoid such accidents or other problems, it is necessary to acquire and control the 3D information concerning the different city networks, especially buried ones.Preventive strategies have to be adopted. That’s why working on the networks and their visualization and risk cartography, taking the blur into account, is a recent and appropriate research. The software applications I develop should help the utility and construction contractors and focus on the prevention of hazardous events thanks to accurate data sets for users and consumers, the definition of a geomatics network but also some methods such as triangulation methods, element modeling, geometrical calculations, Artificial Intelligence, Virtual Reality

Ces travaux considèrent les Smart Grid électrique comme point de départ pour proposer un nouveau modèle de gestion des réseaux de chaleur, baptisé Optimisation Dynamique des réseaux de chaleur pour une transition vers les Réseaux Intelligents (acronyme DOTS en anglais). Le modèle DOTS est constitué de trois parties : la modélisation dynamique des réseaux de distribution, l'optimisation du réseau de chaleur dans son ensemble et une évaluation multicritère de sa performance. La modélisation physique des réseaux est associée à une représentation en graphes orientés et à une méthode modifiée des volumes finis. En complément, ce travail propose l'utilisation d'un nouvel indicateur de fonctionnement dynamique appelé Facteur de Charge des Conduites (PSF en anglais pour Pipe Supply Factor). Le PSF donne le rapport entre l'énergie entrant dans une conduite et l'énergie qui en ressort. L'optimisation est divisée en deux étapes : L'optimisation de l'ordre de mobilisation des différents systèmes de production (dispatch) et l'optimisation de la température de génération. Le dispatch correspond à un ordre de priorité basé sur le coût de production et l'optimisation des températures de production est optimisée grâce à la minimisation de la production totale, de la demande non satisfaite(déficit) et de l'excès de chaleur (surplus). L'évaluation globale du réseau de chaleur se fait au travers d’indicateurs énergétiques, économiques et de qualité de service. Les résultats indiquent la possibilité de la transition des réseaux de chaleur (existants ou nouveaux) vers les Smart Thermal Networks et leur capacité à devenir partie intégrante du modèle Smart City
Based on the relevance of Heat as one of the primary end-uses of energy in a city and the stillsmall amount of literature on the transition of District Heating (DH) into Smart Thermal Networks, themain objective of the present research is to propose a novel model for system management of DH bycombining Modeling, Simulation, and Optimization tools. This with the aim to be a proof of conceptthat demonstrates the possibility of DH systems to transition into Smart Thermal Networks and theircapabilities of integration into the Smart City model. The present research takes the electricity smart gridas the starting point to propose a new model of DH system management named Dynamic Optimizationof DH for its Transition to Smart Networks (DOTS). This model is constituted by three parts: themodeling of DH networks, the optimization of DH systems, and the evaluation of DH systems. Themodeling approach is based on the physical modeling of DH networks using Oriented Graphs and avariation of the Finite Volumes method. The optimization is divided into two steps: The Dispatchoptimization using linear programming formulation, and the Generation Temperature optimization usingnon-linear programming formulation. The evaluation of DH is done through energy, economic and, newto DH, Quality of Service (QoS) indicators. To account for the dynamics of heat distribution, the presentresearch proposes the use of a new operative indicator named the Pipe Supply Factor (PSF) to allow thenetwork to consider the delay times and the thermal inertia of the system

La littérature récente montre qu'il existe un potentiel important de décarbonation et d'amélioration de l'efficacité des réseaux d’énergie, qui peut être exploité grâce à la synergie offerte par les systèmes multi-énergies (MES). Les technologies de couplages, telles que les centrales de cogénération, les pompes à chaleur et les stockages thermiques, sont largement recommandées pour une flexibilité accrue et un meilleur taux de pénétration des énergies renouvelables dans les secteurs du chauffage et de l'électricité. Sur la base de ce constat, la taille et le nombre de technologies de couplage dans les réseaux de distribution de chaleur, telles que les centrales de production combinée de chaleur et d'électricité (cogénération) et les pompes à chaleur (PAC), augmentent. Ces technologies étant exclusivement gérées par les gestionnaires de réseaux de chauffage urbain, leur fonctionnement devient parfois sous-optimal du point de vue du réseau électrique et elles peuvent entraîner une surcharge des réseaux de distribution d'électricité basse tension (en particulier pour les grandes puissances installées). Des modèles de simulation et d'optimisation intégrés sont nécessaires pour exploiter efficacement les synergies sans compromettre les réseaux de distribution composants les MES. Ces modèles ne sont pas encore développés. Les outils classiques de simulation mono-vecteur d’énergie ne sont pas capables d’intégrer les paramètres de fonctionnement couplé clés des réseaux de distribution multi vecteurs. Une nouvelle méthodologie de simulation et d'optimisation de MES est développée dans cette thèse, basée sur une approche d'Extended Energy Hub (EEH). Une structure générale de modélisation est d'abord proposée sous forme modulaire, afin de pouvoir être facilement adaptée à tout type de réseaux énergétiques multi vecteurs. Celle-ci est ensuite utilisée pour développer les détails d'un modèle intégré de flux de charges régissant les réseaux couplés de chauffage et de distribution d'électricité. Plusieurs études de cas, traitant de topologies de réseaux radiales et maillées, sont considérées pour la démonstration et la validation numérique du modèle proposé. Ce modèle de flux de charges est en outre combiné avec un algorithme d'optimisation (PSO) afin de mener des études de flux de puissances intégrées optimaux. Le potentiel offert par cette démarche est illustré par l'étude du placement optimal des technologies de couplage, comme les pompes à chaleur (PAC), dans les réseaux couplés de chauffage et de distribution d'électricité. La capacité de l'outil développé est de plus illustrée par l'exploitation des synergies des réseaux couplés en présence d'énergies renouvelables intermittentes et d'un signal de prix de l'électricité variable. Il est démontré que les méthodologies de simulation et d'optimisation basées sur l'EEH, proposées dans cette thèse sont très efficaces, flexibles et facilement évolutives pour intégrer les paramètres de fonctionnement clés des réseaux intégrés d'électricité et de chauffage urbain. Les modèles développés peuvent ainsi être utilisés comme plate-forme d’études de l'intégration des réseaux intelligents et des réseaux thermiques intelligents
Recent literature shows that there is a significant potential of decarbonisation and efficiency improvement that can be achieved through the synergy from multi-energy systems (MESs). Coupling technologies, such as co-generation plants, heat pumps and thermal storages are widely recommended as means of unlocking additional flexibility and increasing the penetration of renewables in the heating and electricity sectors. In view of that, the size and number of coupling technologies, such as combined heat and power plants and heat pumps (HPs), being installed in the heat distribution networks are increasing. As these technologies are exclusively managed by the district heating network operators, their operation sometimes becomes suboptimal from the electricity network point of view, and they (in particular large HPs) may cause overloading of the low voltage electricity distribution networks. Integrated simulation and optimisation models are required to exploit the synergies effectively without compromising the constituent distribution networks of MES. Such models are not yet well developed. The conventional single-energy-carrier simulation tools are not capable of capturing key operating parameters of the multi-carrier distribution networks either. A novel methodology for simulation and optimisation of MES is developed in this thesis based on an Extended Energy Hub (EEH) approach. The general framework is first developed in modular form so that it can be easily adapted for any type of multi-carrier energy networks. The framework is then used to develop the details of an integrated load flow model governing coupled heating and electricity distribution networks. Various load flow case studies with radial and meshed topologies are considered for demonstration and numerical validation of the proposed model. The load flow model is further combined with a particle swarm optimisation algorithm in order to conduct integrated optimal power flow studies. Its contribution to the state of art is demonstrated by studying the optimal placement of coupling technologies, such as HPs and boilers in coupled heating and electricity distribution networks. The capacity of the model is further illustrated by exploiting the synergies using HPs together with thermal storage in the presence of intermittent renewables and variable electricity price signal. It is shown that the EEH-based simulation and optimisation methodologies proposed in this thesis are very effective, flexible and easily scalable in capturing the key operating parameters of integrated electricity and district heating networks. The models can be used as a platform for further studies on integration of smart grids and smart thermal networks

Dans un contexte de dérèglement climatique, d’augmentation des inondations en milieu urbain,d’augmentation des incertitudes, les gestionnaires urbains sont obligés d’innover pour concevoir des stratégies de gestion des risques adéquates. Parmi ces stratégies, rendre les villes résilientes est devenu un impératif. Le concept de résilience est un concept pluridisciplinaire qui définit la capacité d’un système à absorber une perturbation et à récupérer ses fonctions par la suite. Cette notion renvoie à une innovation technique, urbaine, sociale, architecturale, économique et politique et enjoint à une remise en question des stratégies traditionnelles de gestion du risque. Cette injonction à l’innovation s’adapte parfaitement à la complexité urbaine, économique, politique, sociale, écologique du monde contemporain. De ce fait, le concept de résilience s’intègre aux enjeux d’étalement urbain et aux risques associés. Pourtant, malgré cette adéquation théorique et conceptuelle, la résilience demeure complexe à intégrer dans les pratiques des urbanistes et acteurs territoriaux. Sa multitude de définitions et d’approches a favorisé son abstraction et son manque d’opérationnalisation. Face à ce constat, cette recherche se propose de répondre à ces lacunes opérationnelles en construisant un système spatial d’aide à la décision afin de clarifier et favoriser l’intégration du concept dans les pratiques urbaines. L’idée défendue est que la résilience urbaine incarne les aptitudes et capacités d’une ville et de sa population à mettre en place avant, pendant et après un événement perturbateur de façon à en limiter les impacts négatifs. Ce positionnement scientifique permet donc d’analyser la résilience urbaine sur un long pas de temps, mettant en avant des capacités proactives que le système urbain doit développer de façon à (ré) agir face à l’inondation. Ce travail s’est appuyé sur un partenariat socio-économique avec la Ville d’Avignon et son Service SIG (Système d’Information Géographique). L’approche a permis de construire trois indicateurs de mesure afin d’aborder la résilience urbaine, technique et social. Ces indicateurs ont permis d’acquérir des informations sur les variables définissant des potentiels de résilience qui favoriseraient l’émergence d’une réponse adéquate face à une inondation urbaine. L’utilisation de techniques de géovisualisation a permis de favoriser la visualisation des traitements et des résultats afin d’expliciter la démarche auprès des gestionnaires urbains. Parallèlement, des ateliers de concertation ont été montés afin de présenter et discuter des résultats obtenus grâce aux indicateurs avec les responsables et gestionnaires des infrastructures critiques.La co-construction de ces indicateurs, afin de construire une analyse et une connaissance autour de la résilience urbaine, suivis de la mise en place d’ateliers avec les acteurs du territoire, afin de favoriser le processus décisionnel territorial, a permis de développer une culture de résilience. Ce système spatial d’aide à la décision a donc permis la mutualisation des connaissances théoriques et pratiques autour des questions de risques urbains et de résilience afin de parvenir à un consensus nécessaire pour la prise de décision et l’opérationnalisation de la résilience
In a context of climate change, increased urban flooding and increased uncertainty, urbanmanagers are forced to innovate to design appropriate risk management strategies. Among thesestrategies, making cities resilient has become an imperative. The concept of resilience is amultidisciplinary concept that defines the ability of a system to absorb a disturbance and then recoverits functions. This concept refers to technical, urban, social, architectural, architectural, economic andpolitical innovation and calls into question traditional risk management systems. This injunction toinnovation is perfectly adapted to the urban, economic, political, social and ecological complexity ofthe contemporary world. As a result, the concept of resilience is integrated with urban sprawl issues andassociated risks. However, despite this theoretical and conceptual adequacy, resilience remains complexto integrate into the practices of urban planners and territorial actors. Its multitude of definitions andapproaches have contributed to its abstraction and lack of operationalization.In response to this observation, this research aims to address these operational gaps by buildinga spatial decision support system to clarify and promote the integration of the concept into urbanpractices. The idea behind this approach is that urban resilience embodies the abilities and capacities ofa city and its population to develop before, during and after a disruptive event in order to limit itsnegative impacts. This scientific positioning therefore makes it possible to analyze urban resilience as acontinuum, highlighting proactive capacities that the urban system must develop in order to (re)act inthe face of flooding. This work was based on a socio-economic partnership with the City of Avignonand its GIS Service (Geographic Information System). The approach made it possible to build threemeasurement indicators to address the urban, technical and social resilience of the Avignon area. Theseindicators have made it possible to acquire information on the variables defining potential resilience thatwould foster the emergence of an adequate response to a natural disaster and more precisely to an urbanflood. The use of geovisualization techniques has made it possible to visualize treatments and results inorder to explain the approach to urban managers. At the same time, consultation workshops were heldto present and discuss the results obtained through the indicators with critical infrastructure managersand managers.The co-construction of these indicators, in order to build an analysis and knowledge aroundurban resilience, followed by the implementation of workshops with stakeholders in the territory, inorder to promote the territorial decision-making process, has made it possible to develop a culture ofresilience. This spatial decision support system has therefore made it possible to pool theoretical andpractical knowledge on urban risk and resilience issues in order to reach the consensus necessary fordecision-making and the operationalization of resilience

L’accélération du processus d’urbanisation, constatée à l’échelle mondiale depuis les dernières décennies, conduit à une artificialisation progressive des milieux naturels. La construction d’infrastructures de transport ou de nouveaux bâtiments fragmente les paysages de manière irréversible et cause une réduction des habitats écologiques et de leur connectivité. Le maintien de la fonctionnalité des réseaux écologiques, s’intègre désormais dans les politiques d’aménagement du territoire ou d’urbanisme soucieuses de la préservation de la biodiversité.En se focalisant plus particulièrement sur les évolutions urbaines à l’horizon 2030 dans l’Aire Urbaine de Besançon (développement résidentiel et variations de trafic routier), cette thèse cherche à évaluer l’impact potentiel des formes d’urbanisation sur la connectivité des réseaux écologiques des espèces animales. Ce travail de recherche privilégie l’approche par la modélisation en s’inscrivant à la fois dans le champ de la géographie théorique et quantitative et de l’écologie du paysage.L’application de cette démarche se fait en trois étapes : (1) simuler le développement résidentiel et ses évolutions de trafic associées à l’horizon 2030, à l’aide de cinq scénarios prospectifs présentant des formes urbaines différenciées ; (2) modéliser les réseaux écologiques de plusieurs espèces animales avec des graphes paysagers construits à partir de cartes d’occupation du sol et de données écologiques ; et (3) évaluer les impacts potentiels de chaque scénario sur les réseaux écologiques à partir de ces graphes à l’aide de métriques de connectivité, par mesure de la perte de connectivité imputable à chaque scénario de développement résidentiel.Les résultats obtenus montrent que les formes de villes denses et compactes, contrairement aux villes étalées, sont celles qui favorisent le mieux le maintien des connectivités écologiques pour la plupart des groupes d’espèces analysés. Des analyses plus approfondies mettent en avant la contribution importante des variations de trafic aux impacts écologiques de chaque scénario.D’après les analyses de sensibilité effectuées, le modèle utilisé est robuste, ce qui montre l’intérêt de la modélisation dans le processus d’aide à la décision pour la protection environnementale et la planification urbaine afin de penser la ville de demain de manière durable
The global increase of urbanization during the past decades have induced a progressive artificialization of natural environments. The building of transport infrastructures and new housings causes a landscape fragmentation in an irreversible way and a strong decrease of the connectivity of ecological habitats. Maintaining the functionality of ecological networks is becoming a major goal of sustainable urban planning policies. With a special focus on urban evolutions in the horizon 2030 in the urban area of Besançon in eastern France (residential development and road traffic evolutions), this thesis aims to assess the potential impact of urban forms on landscape connectivity of animal species’ ecological networks. This research work promotes a modelling approach both on the field of theoretical and quantitative geography and landscape ecology.This approach follows three main steps: (1) simulating residential development and its associated road traffic changes using five prospective scenarios of differentiated urban forms; (2) modelling landscape graphs of various animal species using land-cover maps and ecological data; (3) assessing the potential impacts of each scenario on ecological networks from these graphs using connectivity metrics, with measures of the connectivity decrease attributable to each residential development scenario. Contrary to sprawled cities, the results show that compact and dense urban forms best promote the maintenance of ecological connectivity for the majority of species groups. Further analysis highlights the great contribution of road traffic evolutions regarding the ecological impacts of each scenario.According to some sensitivity analysis, the model used is quite robust. It demonstrates the interest of modelling in the decision-making process for environmental conservation and urban planning to think out the city of tomorrow in a sustainable way

Le paysage constitue à la fois un cadre de vie pour les populations humaines et un support du cycle de vie des espèces animales. Les modifications du paysage induites par les dynamiques d’occupation du sol se répercutent sur ces deux dimensions, l’une esthétique et l’autre écologique. Ces logiques étant généralement étudiées dans des champs disciplinaires différents, peu de recherches ont porté sur la manière dont elles s’articulent selon les modifications des structures paysagères.Ce travail cherche donc à modéliser de manière rétrospective la coévolution spatiale des fonctions esthétique et écologique du paysage à partir de métriques spatiales basées sur des données d’occupation du sol. Il se focalise sur les changements intervenus dans les franges urbaines de deux agglomérations françaises (Besançon et Paris) durant les 30 dernières années.La démarche adoptée a d’abord visé à modéliser, à partir des données d’occupation du sol, (1)les préférences paysagères d’un ensemble d’individus et (2) la connectivité écologique pour un ensemble d’espèces animales. En mobilisant de manière complémentaire des analyses statistiques multivariées et des analyses spatiales, le cœur du travail a ensuite consisté à étudier comment ces deux fonctions ont évolué de manière convergente ou divergente au cours du temps. Les résultats donnent de nouveaux éléments de compréhension des relations entre esthétique et écologie du paysage et amènent à s’interroger sur l’intérêt de la modélisation spatiale pour une gestion du paysage conciliant la préservation du cadre de vie des habitants et la conservation de la biodiversité
Landscape is both a backdrop to the lives of human populations and a medium for the life cycle of animal species. Landscape changes induced by land-use and land-cover dynamics affect both these dimensions, the one aesthetic, and the other ecological. Because these rationales areusually studied within different disciplines, little research has been done into how the two clashor combine as and when landscape structures change. This work seeks therefore to model the spatial co-evolution of the aesthetic and ecological functions of landscape retrospectively usingspatial metrics based on land-cover data. It focuses on changes in the urban fringes of two French cities (Paris and Besançon) over the last 30 years. The approach attempts first to use land-cover data to model (1) the landscape preferences of a set of individuals and (2) the ecological connectivity of a set of animal species. Drawing on both multivariate statistical analysis and spatial analysis, the core of this work consists in investigating how the two functions have evolved in convergent or divergent ways over time. The results provide fresh insight into the relationship between landscape aesthetics and landscape ecology and raise questions about the value of spatial modelling for a landscape management approach that endeavours to reconcile the preservation of residents’ living environments and the conservationof biodiversity

Water distribution systems convey drinking water from treatment plant and make available to consumers’ taps. It consists of essential components like pipes, valves, pumps, tanks and reservoirs etc. The main concern in the working of a water distribution system is to assure customer demands under a choice of quantity and quality throughout the complete life span for the probable loading situations. However, in some cases, the existing infrastructure may not be adequate to meet the customer’s requirements. In such cases, system modeling plays an important role in proper management of water supply systems. In present scenario, modeling plays a significant task in appropriate execution of water distribution system. From the angle of taking management decisions valve throttling control and pumps speed control are very important. These operational problems can be addressed by manual control or by automatic control. The problem is the use of manual controls that slow down the effectiveness of the system. It reduces the efficiency of operation of valve or pump. To improve the efficiency of such water distribution systems, an automatic control based technology has been developed that links the operation of the variable speed pump control or valve throttling control. By employing an automatic control, the pump can adjust its speed at all times to meet the actual flow requirements of each load served. In case of real system design Simulink is the most widely used tool. Commercial software package Matlab/Simulink used for creation of WDS model. The goal was to produce a model that could numerically analyze the dynamic performance of a water distribution system. A Comparison of single platform methodology (Simulink based control) and double platform methodology (Matlab and EPANET based control) has been done. Nonlinear Dynamic Inversion (DI) Control system model is developed for WDS model in Matlab/Simulink environment. Controller gain parameters are the very important value in control prospective. If the controller gain parameters are chosen incorrectly, the controlled process input can be unstable, i.e. its output diverges, with or without oscillation Tuning is the adjustment of control parameters (gains) to the optimum values for the desired control response. There are several methods for tuning controller like manual tuning (Trial and error procedure), Ziegler-Nichols method, Output Constraint Tuning (OCT) etc. Establishment of a pump operational policy by which all the reservoirs can be fed simultaneously to meet their requirements without creating undue transients. Tune the gain of DI controllers by different tuning methods and evaluate the best tuning method on the basis of controller performance. Development of meaningful additional objective is search of lower bound pump speed on the basis of control time or settling time. To bring the pump speeds in feasible range, application of constraint in pumps speed is introduced. The magnitude of constraints can be found using Monte Carlo methods. Monte Carlo methods are frequently used in simulating physical and mathematical systems. This method may be the most commonly applied statistical method in engineering and science disciplines. Another benefit is providing increased confidence that a model is robust using Monte Carlo testing. Model development for generalized control system for water distribution network provides the simplification needed for the simulation of large systems. Model development is based on the study of symmetric and non symmetric small, irregular networks, as well as large, regular and open bifurcating water distribution system. The problem considered in this section is that of flow dynamics in simple to complex, regular network which bifurcates in the form of a branching tree. In addition the control application of the flow network is investigated using valves as the manipulated variables to control branch flow rates. Communication between the network hydraulics coming from EPANET and control algorithm develop on Matlab (Programming Language) can be generalized with the help of development of general purpose control algorithm model.

Short duration intense rainfall causes an increase in rainfall derived infiltration and inflow (RDII) in aging sewer networks, which leads to Sanitary Sewer Overflows (SSOs). This, in turn, causes various detrimental impacts, both on human health and the environment. This research aims to quantify the benefits of Water Sensitive Urban Design (WSUD) approaches to mitigate the negative impacts of rainfall induced SSOs. In this context, this research develops a generalised framework for assessing and mitigating the impacts of intense rainfall on the performance of the sanitary sewer network. The first part of the developed framework involves detailed hydraulic modelling to evaluate the performance of the sewer network. The second part deals with the development of SSO mitigation strategies based on popular WSUD approaches. This study also demonstrates the application of the developed framework for a case study catchment in Melbourne, Australia. A detailed hydraulic modelling to analyse the performance of the case study sewer network during a wet (2010) and a dry year (2008) has been presented. The hydraulic performance analysis found that the system experienced 23 ML of sewer overflow volume in 2010 as compared to 3.42 ML in 2008. Towards mitigating the negative impacts of SSOs, this study has implemented two commonly used WSUD approaches, namely rainwater tanks and rain gardens for the case study sewer network. A detailed hydraulic modelling has been undertaken with rainwater tanks and rain gardens (individually and in combination) for the wet year 2010. It was observed that rainwater tanks (individually) could lead to a maximum reduction in SSO volume by 33% when compared to the base case overflow volume of 23 ML. A higher reduction in SSO volume up to a maximum of 45% was observed when rain gardens were implemented in conjunction with rainwater tanks. Such an analysis will benefit the urban water authorities to develop sustainable WSUD based mitigation strategies for controlling SSOs in their sewer system. Thus, the study will be beneficial for the community and the environment.

Currently, air pollution represents one of the main environmental causes of mortality. It is also responsible by cutting lives short, reducing productivity through working days lost across the economy, increasing medical costs, and by considerable economic impacts. Europe's most serious air pollutants in terms of harm to human health are particulate matter, nitrogen dioxide and ground-level ozone. The principal objective of this thesis is to explore the capabilities of Integrated Assessment Modelling tools to cost-efficiently evaluate measures to improve the air quality, and furthermore to develop an urban Integrated Assessment Model (IAM). For this purpose a review of current integrated assessment methodologies to improve air quality, from simple (e.g. scenario approach) to more comprehensive ones (e.g. optimization approach) was done and some application tests were performed. Based on identified advantages of the revised approaches the Integrated Urban Air Pollution Assessment Model (IUAPAM) was designed and evaluated through its application to a selected urban case study (Porto Urban Area) considering different emission scenarios. The developed model is able to reproduce rapidly emission reduction scenarios and to estimate health impacts, making use of Artificial Neural Networks. Moreover, the use of Multi-Criteria Decision Analysis (MCDA) allows including social aspects and ranking air quality measures/scenarios. This research work contributes to a better understanding of the utility of IAM tools that are available to support the air quality decision-making process. IUPAM revealed to be useful to quickly evaluate the effect of local and regional policies focused on air pollution improvement
Atualmente a poluição atmosférica representa uma das principais causas ambientais de mortalidade. Ela é ainda responsável pela redução da esperança média de vida, redução da produtividade devido à redução de dias de trabalho, aumento de custos hospitalares, e por impactos económicos consideráveis. Os poluentes mais relevantes em termos de efeitos na saúde humana são o material particulado, o dióxido de azoto e o ozono troposférico. O objetivo principal da presente tese é o desenvolvimento e teste de um Modelo de Avaliação Integrada (MAI) que permita apoiar a seleção custo-eficiente de medidas de melhoria de qualidade do ar em cidades. Com essa finalidade foi efetuada uma revisão das atuais metodologias de avaliação integrada da qualidade do ar, das mais simples (análise de cenário) às mais complexas (abordagem de otimização), e foram efetuados alguns testes de aplicação que permitiram identificar as principais vantagens e limitações de cada abordagem. Foi desenvolvido um Modelo de Avaliação Integrada à Escala Urbana (MAIEU) que ultrapassa algumas das dificuldades das ferramentas existentes e aproveita as suas vantagens. O modelo foi avaliado através da sua aplicação a um caso de estudo urbano (Grande Porto) e a diferentes cenários de emissões. É capaz de reproduzir rapidamente cenários de redução de emissões, e de estimar os seus impactes na saúde, recorrendo a Redes Neuronais Artificiais. Para além disso, o uso de Análise Multicritério permitiu incluir aspetos sociais e criar uma classificação de medidas/cenários de qualidade do ar. Este trabalho contribui para uma melhor compreensão da utilidade dos MAI, disponíveis para apoiar o processo de tomada de decisão. O MAIEU, revelou ser útil para avaliar rapidamente o efeito de políticas regionais e locais focadas na melhoria da poluição atmosférica à escala urbana
Programa Doutoral em Ciências e Engenharia do Ambiente

Provision of water services is a critical strategy for addressing worldwide poverty, and this is one of the most pressing challenges of current times and is linked to population growth and climate change. Progress has been slow in achieving even the Millennium Development Goals aimed at improving coverage of adequate water services and professionals are struggling to cope with the diversity and scale of situations. Water services provision is a context-dependent process and many types of situations are very challenging, such as that of small developing towns. This thesis addresses the problems of urban centres in Pacific Island Countries and the aim is to provide formal explanations of difficulties in these locations to support recommendations that recognize local constraints and opportunities to best practice management. This is achieved largely by employing a perspective based on the science of Complex Adaptive Systems. This perspective has been chosen in recognition that water management incorporates complex interactions between social, technical and natural systems. The research is case study based, focusing primarily on Tarawa in the Pacific Island nation of Kiribati. The methodology includes historical review of the case study, and the use of historical review, as well as interviews and observation in the field as well as a cross-cutting email-based Delphi survey. This has generated qualitative and quantitative data to allow for the formulation of scientific models, an Agent Based Model describing the complex interactions involved in water service delivery; and Bayesian Network models describing the factors impacting on the chances of successful management interventions. With improved explanation of the complex situation, this has been used to support the formulation of a strategic and adaptive governance framework; aiming to introduce much needed organisational memory, and a consistent strategic direction set on the basis of the effective stakeholder interaction. By recognising weakness in capacity, it is possible to turn these into strengths by building and utilising local knowledge and commitment.
Pascal Perez

Water grids are a diverse and interconnected water supply systems that are emerging in response to the pressures of climate variability, climate change, and population growth. Water grid operation is guided by operating rules, which aim to manage supply and demand to meet multiple management criteria such as maximising water security, minimising operational cost, and minimising energy use. However, the diversity and interconnectedness of these water grids increases the number of possible configurations of the operating rules, and combined with uncertainty in forecast conditions, makes find optimal operating rules more challenging. Further, trade-offs between the criteria mean that multiple sets of operating rules can be considered optimal. Thus, this thesis proposes and demonstrates a framework of methods to meet these challenges and identify a set of optimal operating rules to support short-term – 1 to 5 year – operational planning of water grids.