identifier: Turki, Assia  (2021). Un système de collecte télémétrique pour NFV sur une plateforme Kubernetes au niveau d’un mini-centre de données.  Mémoire de maîtrise électronique, Montréal, École de technologie supérieure.

subject:
NFV
Kubernetes
centre de données
télémétrie
métriques

abstract: La technologie NFV est la solution idéale pour que les fournisseurs de services puissent offrir des réseaux fiables et efficaces et répondre aux besoins urgents. Les déploiements NFV font face à des défis importants comme l’observabilité qui couvre la collecte d’informations liées a la plateforme est aux applications(métriques). Cette opération (télémétrie) se faisait par des sondes physiques et des séparateurs dans le réseau. Cependant, NFV sur une plateforme K8s a fait apparaitre de nouvelles métriques tel que la consommation de ressources des conteneurs. La télémétrie peut servir de source pour l’approvisionnement avancé et l’assurance de service, permettant non seulement des actions correctives, mais aussi préventives par rapport au fonctionnement des services réseaux. En plus, les centres de données exigent une détection d’anomalies et des réactions rapides afin de minimiser le risque de dysfonctionnement. Pour ce fait, il est important d’avoir de nouvelles approches de collecte. Cette recherche propose un système capable de collecter les nouvelles métriques qui adoptera le concept de la diffusion en temps réel et l’apprentissage automatique afin d’en déduire plus de données pour une meilleure visibilité sur les services réseaux. Notre système de collecte télémétrique s’appuie sur une comparaison entre les alternatives technologiques pour une collecte, une diffusion, un traitement et une visualisation de télémétrie bien réussis. Cette solution a pu être testée dans une entreprise ou les résultats ont été prometteurs et positifs.


identifier: Lazli, Lilia  (2021). Diagnostic de la maladie d’Alzheimer par fusion d’images IRM et TEP avec segmentation de tissus floue-génétique-possibiliste et classification par SVDD.  Thèse de doctorat électronique, Montréal, École de technologie supérieure.

type:
Mémoire ou thèse
Non évalué par les pairs

subject: maladie d'alzheimer

subject: système d’aide au diagnostic assisté par ordinateur

subject: fusion multimodale anatomo-fonctionnelle

subject: quantification de volumes des tissus cérébraux

subject: algorithmes génétiques

subject: modèles de description de données par vecteurs de support

subject: stratégie diviser-et-conquérir

abstract:
Les systèmes de diagnostic assisté par ordinateur (DAO) interviennent pour aider les neuroradiologues et d’autres professionnels de la santé à établir un diagnostic pertinent de l’état des patients, en offrant un effet synergique entre des méthodes d’apprentissage automatique par ordinateur et ces professionnels.

Dans ce cadre, cette thèse propose un système de DAO pour diagnostiquer la maladie d'Alzheimer (MA), selon deux modules principaux. Le premier module a pour tâche la segmentation des tissus cérébraux basée sur la fusion des images multimodales anatomique (IRM) et fonctionnelle (TEP), et prenant en compte les effets du bruit, de l'inhomogénéité d’intensité, de volume partiel dans les voxels, de variation anatomique au sein des compartiments de tissus purs et des modifications de volume tissulaire résultantes de la MA et du traitement. L’approche développée repose sur la logique floue, la théorie des possibilités et les algorithmes génétiques afin d’assurer un modèle adéquat pour chaque image traitée et dont les paramètres sont optimisés. Le processus suit les étapes suivantes : (1) modélisation du degré de relation entre les voxels et les tissus cérébraux correspondants ; (2) fusion à l'aide d'un opérateur conjonctif possibiliste afin de fusionner les cartes floues des images IRM et TEP ; (3) décision fournissant deux types d’images, des images étiquetées en tissus cérébraux et des images de synthèse anatomo-fonctionnelles qui identifient les zones cérébrales affectées par la MA. Le second module a pour tâche la classification des images fusionnées et segmentées afin de distinguer les patients atteints de la MA de sujets normaux. L’approche développée exploite le modèle de description de données par vecteurs de support (SVDD), une technique apparentée aux séparateurs à vastes marges, avec l’avantage additionnel d’un apprentissage non supervisé et un grand pouvoir de détection des données aberrantes. La stratégie « diviseret- conquérir » est appliquée pour réduire les coûts de calcul et surmonter le problème d'échelle du classifieur SVDD.

Les expériences de validation menées sur des images cérébrales réelles et synthétiques (tirées de bases de données standard ADNI et OASIS) de patients atteints de la MA montrent de bons résultats. Ainsi, la performance visuelle de l'approche de segmentation proposée montre une bonne concordance entre les images de référence et celles segmentées par l’approche proposée, comme l’attestent les coefficients de Tanimoto et la similarité de Jaccard. Quant à la classification par SVDD, les métriques de performance communes comme la précision de classification (AC), la sensibilité (SE), la spécificité (SP) et l’aire sous la courbe (AUC) montrent aussi de bons résultats. Plus précisément, la validation croisée à 10 tours montre clairement la supériorité du système de DAO proposé par rapport à des systèmes concurrents, avec un pourcentage (%) de classification en termes de AC, SE, SP et AUC de 93.65, 90.08, 92.75 et 97.3 pour l’ADNI ; 91.46, 92, 91.78 et 96.7 pour l’OASIS et 85.09, 86.41, 84.92 et 94.6 pour les images réelles.

Le travail est décrit dans trois articles. L’article 1 décrit un modèle hybride de segmentation basé sur les AG, l’algorithme des c-moyennes floues et l’algorithme des c-moyennes possibilistes (PCM). Dans l’article 2, afin d’augmenter la robustesse face aux bruit et artefacts, l’algorithme PCM est remplacé dans le modèle hybride par son analogue c-moyennes possibilistes floues. Finalement, l’article 3 décrit un système complet de DAO, dont la classification est basée sur le modèle SVDD et sur la stratégie « diviser-et-conquérir », alors que la segmentation est basée d’une part sur la fusion multimodale et d’autre part sur le modèle hybride à base des AG, l’algorithme des c-moyennes floues corrigées par biais et l’algorithme des c-moyennes floues possibilistes.


identifier: Alomari, Ahmad  (2021). Integrating new representation perspectives at the operational level of BPM+.  Thèse de doctorat électronique, Montréal, École de technologie supérieure.

subject: niveau d’abstraction opérationnel

subject: processus d’affaires

subject: gestion des processus d’affaires

subject: modélisation des processus d’affaires (BPM)

subject: notation de modélisation des processus d’affaires (BPMN)

subject: langages de modélisation

abstract:
Business process management has received lots of attention over the past few decades due to the significant benefits for organizations, and it became a primary discipline for operations management. An essential concept of business process management is representing organizational processes using business process models. The representation of organizational business processes in the form of business process models keeps growing in importance and appropriate modeling standards are a critical success element for successful business process modeling projects. One of the main challenges of representing business processes is that there is no definitive best way to represent them. Users prefer a common business process representation and established modeling standards. In the emerging market of business modeling standards, most users are still trying to identify which standards meet their needs.

BPM+ is a novel business process modeling approach that helps represent process models in a consistent and structured way to meet the process representation needs of different stakeholders. BPM+ is based on an abstraction hierarchy that includes three levels: strategic, tactical, and operational. This abstraction enables the business process modeling user to represent the business process at different levels of abstraction. The main goal of this thesis is to integrate new perspectives at the BPM+ operational level of abstraction and evaluate how a specialized/operational BPM-stakeholder perspective can be used to improve the existing organizational business process model repository.

In order to achieve this goal, this thesis proposes a method to define and validate the many graphical representations perspectives needed at the operational level. An a priori version of the representation perspective was designed based on the findings from the literature review. The a priori version was iteratively refined through a series of ontological analyses and a survey. As a result, an ontologically validated decision tree perspective was proposed to demonstrate the feasibility of the proposal.

The research results show that:
1. The operational BPM+ level allows for generating business process models that represent the needs of various stakeholders involved in operational business processes;
2. A new operational process perspective representation, in the shape of a decision tree and its modeling constructs, are ontologically validated then demonstrated to show an example of how an operational process can be represented; and
3. A BPMN extension is presented to show how this new perspective can be used in the modeling language most used by users with BPM experience.


identifier: Roy, Jonathan  (2021). Applicability of systems and software quality engineering methods and models to information security in cloud computing services.  Thèse de doctorat électronique, Montréal, École de technologie supérieure.

subject:
qualité des systèmes et des logiciels
ingénierie de la qualité
ingénierie des exigences de qualité
sécurité de l'information
informatique en nuage
services informatiques en nuage

abstract:
Industry continues to aggressively adopt cloud computing services, motivated by the potential benefits of their native characteristics. Additionally, information technology (IT) outsourcing experts consider security to be the most important non-functional requirement of cloud computing services. Consequently, a growing number of systems and software engineers must confront the quality engineering of cloud-based information systems (IS) to mitigate or avoid potential user or stakeholder risks. It has been well-established that the early application of quality engineering to IS development during requirement activities is a major milestone and contributor to building high quality IS. Furthermore, the application of quality engineering requires the use of a quality model with the capacity to support both the definition of quality requirements and their subsequent evaluation. However, the extent to which ISO/IEC 25000 quality models are applicable to information security in cloud computing services has not been identified.

Accordingly, this thesis proposes the use of the ISO/IEC 25030 quality requirements framework as a systematic approach to answer the research question “To what extent do ISO/IEC 25000 quality models support the definition of quality requirements related to information security in cloud computing services?” Here, we use IS research design science practices to evaluate and extend the applicability of the ISO/IEC 25030 quality requirements framework to information security in cloud computing services. We also use the extended framework to answer the research question while illustrating its applicability to the quality requirement definition of cloud-based IS.

Results from this thesis show that on the one hand ISO/IEC 25000 quality models cannot adequately mitigate the top threats to cloud computing services. On the other hand, the application of the extended framework demonstrates that these quality models can be tailored to the quality requirements definition of cloud-based IS for the purposes of mitigating or avoiding potential user or stakeholder risks.


identifier: Abu Aisha, Tareq  (2021). Developing a sustainable intermodal transportation system to enhance the efficiency of port's activities.  Thèse de doctorat électronique, Montréal, École de technologie supérieure.

subject:
terminaux à conteneurs
transport maritime
transport intermodal
durabilité
plan d'aménagement

abstract:
Transporting millions of containers through the container terminal at the seaport per year while ensuring minimum handling operations cost and emission is challenging for the container terminals. Today, the intermodal container terminal is considered as a hearth for most intermodal transportation systems. The intermodal container terminal in the seaport is a complex system that requires careful planning in order to perform operations efficiently. Thus, inefficiently operating the terminal can slow down the flow of containers to their destination as well as increase the dwell time of the ship in the port, which leads to an increase in the total cost and affects sustainability. Consequently, there is a need for new methodologies and technologies that guarantee enhancements of terminal performance, increase capacity, and mitigate negative impacts on the environment. In a large number of cases, the seaports are usually surrounded by big cities. Hence, improving new layouts for the container terminal will lead to the faster, cheaper, and more efficient transfer of containers from their origin to the destination in a sustainable way. In this study, the Port of Montreal is used as a case study to validate the proposed layout and experiments.

In my first article, titled "Developing the Seaport Container Terminal Layout to Enhance Efficiency of the Intermodal Transportation System and Port Operations - Case of the Port of Montreal," we developed a new container terminal layout. An efficient layout of the container terminal can be achieved by reducing the distance and disposition between the quay and rail tracks. We propose a novel layout to reduce the cost and accelerate container flow, thus improving the handling system's effectiveness. We develop a MILP model to estimate and analyze the performance considering the arcs congestion for the current layouts and the new proposed layout. We present a study case on The Port of Montreal to validate the suggested solution. We found that the projected layout reduces the total cost and time for transporting containers from the port to their destination.

Despite the advantages of intermodal transportation, it still has undesirable effects connected with congestion and emission. In the second article, titled "Optimization of Container Terminal Layouts in the Seaport - Case of Port of Montreal," the intermodal transportation system and its effect on port efficiency were addressed. The article investigates the role of the proposed layout in minimizing the cost of transport containers from the ship to the final destination and emissions generated from these operations. The proposed layout can improve the sustainability of port activities by decreasing the distance between the berth and interface points as well as avoiding double handling. The model was formulated as multi-objective optimization, and we use the ε-constraint method to solve the problem. The results illustrate that the proposed layout resulted in a considerable reduction in both the total cost of transport containers to their final destination and emission associated with these operations.

Since different modes of transportation and resources interact and function together, the system is becoming quite complex to understand its behaviour and predict the effect of changing in some parameters. In this regard, we developed a simulation model in the third paper titled "A Simulation Approach to Compare Different Container Terminal Layouts." A discrete simulation model is developed using the SIMAN simulation language and then implemented through the Arena software application. This study aims to improve the performance and handling capacity of the terminal by recommending a new layout. Computational experiments were conducted to evaluate and compare both layouts' performance using data collected from the Port of Montreal. The results indicate that terminal layout design has a significant impact on terminal performance under the configuration of different transportation modes.


identifier: Delisle, Pierre-Luc  (2021). Normalisation réaliste d’images médicales pour de la segmentation multi-domaine.  Mémoire de maîtrise électronique, Montréal, École de technologie supérieure.

subject:
IRM 3D
segmentation du cerveau
réseau de neurones antagonistes
normalisation d’intensités

abstract:
Les réseaux de neurones profonds sont au cœur de l’actualité scientifique depuis maintenant plusieurs années. Les progrès accomplis dans le domaine de la recherche fondamentale se sont transposés dans des applications dans le domaine médical. La classification automatique des voxels dans une image médicale à l’aide d’un réseau de neurones convolutif permet entre autres de suivre le développement d’un organe ou l’évolution d’une maladie.

L’accessibilité des données d’imagerie médicale à des fins d’entraînement d’algorithmes d’apprentissage automatique est une principale limitation inhérente au domaine. En raison du coût et de l’expertise requis afin d’annoter des ensembles de données, ces derniers ne sont généralement composés que de quelques images. Cela a un impact direct sur la capacité de généralisation des algorithmes d’apprentissage. Un des moyens de remédier à cette disponibilité limitée se trouve dans la normalisation d’ensembles de données issus de plusieurs domaines d’imagerie. Un domaine d’imagerie peut être un site où l’image est acquise, un protocole d’imagerie ou encore le type d’équipement servant à l’acquisition de l’image médicale. Les approches conventionnelles de normalisation couramment utilisées sont basées sur la normalisation en fonction d’un seul ensemble de données. Toutefois, cette stratégie ne peut exploiter l’information structurelle et l’information intrinsèque des échelles d’intensités aux images issues de plusieurs ensembles de données. Par conséquent, ignorer ces informations entraine une performance suboptimale pour un algorithme de segmentation. La correction des intensités des images par un processus de normalisation intelligent qui aligne les distributions des tissus sur une échelle commune entre les ensembles de données permettrait l’apprentissage d’une tâche à partir de plusieurs ensembles de données différents. Cela aurait pour conséquences d’améliorer la disponibilité des données et la capacite de généralisation des algorithmes d’apprentissage.

Ce travail propose une nouvelle méthode de normalisation conjointe a la segmentation. Cette méthode est apprise à l’aide d’une architecture orientée à la fois par les données et par une tâche. Dans notre méthode, trois réseaux s’entraînent simultanément afin d’apprendre la relation entre une image d’entrée issue d’un domaine d’imagerie quelconque et une sortie normalisée. La fonction de transfert optimale liant les distributions d’intensités des images à travers les différents jeux de données est ainsi apprise. Elle a pour but de produire non seulement une carte de segmentation précise, mais également des images intermédiaires normalisées médicalement réalistes et interprétables. Les images sont dites réalistes puisque les changements apportés à l’image n’affectent ni les structures ni sa capacite à être interprétée par un clinicien. Ces caractéristiques importantes recherchées entre autres afin de rendre compréhensible l’image intermédiaire produite, sont rendues possibles par une architecture antagoniste pourvue d’un générateur d’images normalisées et un discriminateur de domaines. Il s’agit d’une architecture simple et évolutive en fonction du nombre de domaines d’imagerie.

La performance de notre méthode est évaluée à l’aide de trois ensembles de données composés de sujets enfants et adultes, soit iSEG, MRBrainS et ABIDE. Les résultats révèlent le potentiel de notre méthode de normalisation pour une tâche de segmentation avec une amélioration de l’indice Dice allant jusqu’à 57,5% par rapport à nos résultats de base consistant en l’apprentissage et le test d’un algorithme de segmentation sur des ensembles de données issus de domaines différents. Notre méthode permet de s’attaquer directement au problème de disponibilité des données en permettant l’apprentissage simultané sur plusieurs domaines d’imagerie différents.


identifier: Ghafourzadeh, Donya  (2021). Reconstructing, transferring and editing of 3D surfaces.  Thèse de doctorat électronique, Montréal, École de technologie supérieure.

subject:
infographie
animation
modélisation de formes
modèles de géométrie maillée

abstract:
The authoring of realistic 3D faces and making a 3D character ready for animation are timeconsuming and tedious tasks. This thesis first addresses the problem of transferring the animation setup between 3D characters. We transfer skeletons and skinning weights between characters with distinct mesh topologies. Our pipeline takes as inputs a source character rig (mesh, hierarchy of joints, and skinning weights) and a target character mesh. We compute joint locations and orientations that embed the source skeleton in the target mesh, as well as skinning weights to bind the target geometry to the new skeleton. We first compute the geometric correspondence between source and target meshes. The resulting geometric correspondence is then used to formulate attribute transfer as an energy minimization and filtering problem. We demonstrate our approach on a variety of source and target bipedal characters, varying in mesh topology and morphology.

Afundamental task of transferring animation is to establish an accurate geometric correspondence between the two characters. State-of-the-art mapping methods that exist today are globally good, but imperfections often exist and are often localized to a specific region. Consequently, we propose a novel approach to improve a given surface mapping through local refinement. The approach receives an established mapping between two surfaces and follows four phases: (i) creation of a sparse set of landmarks in mismatching regions; (ii) segmentation with a low-distortion region-growing process based on flattening the segmented parts; (iii) optimization of the deformation of segmented parts to align the landmarks in the planar parameterization domain; and (iv) aggregation of the mappings from segments to update the surface mapping. In addition, we propose a new approach to deform the mesh in order to meet constraints (in our case, the landmark alignment of phase (iii)). We incrementally adjust the cotangent weights for the constraints and apply the deformation in a fashion that guarantees that the deformed mesh will be free of flipped faces and will have low conformal distortion. Our new deformation approach, Iterative Least Squares Conformal Mapping (ILSCM), outperforms other low-distortion deformation methods.

Lastly, we propose an approach to construct realistic 3D facial morphable models (3DMM) that allows an intuitive facial attribute editing workflow. Current face modeling methods using 3DMM suffer from a lack of local control. We thus create a 3DMM by combining local part-based 3DMM for the eyes, nose, mouth, ears, and facial mask regions. Our local PCA-based approach uses a novel method to select the best eigenvectors from the local 3DMM to ensure that the combined 3DMM is expressive, while allowing accurate reconstruction. The editing controls we provide to the user are intuitive as they are extracted from anthropometric measurements found in the literature. Out of a large set of possible anthropometric measurements, we filter those that have meaningful generative power given the face data set. We bind the measurements to the part-based 3DMM through mapping matrices derived from our data set of facial scans.


identifier: Fallaha, Charles  (2021). Design of a sliding mode controller with model-based switching functions applied to robotic systems.  Thèse de doctorat électronique, Montréal, École de technologie supérieure.

subject: modes glissants

subject: exosquelette

subject: robot

subject: fonctions de glissement basées sur le modèle

subject: commutations haute-fréquence

subject: contrôle robuste

subject: quadri-rotor

abstract: This thesis presents an in-depth study sliding mode control applied on electromechanical systems which dynamic model can be formalized according to the standard mathematical structure of robotic manipulator arms. More specifically, this research work focuses on an innovative design of nonlinear sliding surfaces based on the dynamic model of robotic systems. The design of the nonlinear model-based surfaces consists in simplifying the nonlinear terms of the torque control input including the inertia, accelerations and gravity matrices by using them in the sliding surfaces themselves. Thus, compared to the typical design of linear sliding surfaces, the resulting torque control law is considerably simplified, and becomes linear as a function of the position and velocity error vectors. This simplification thus leads to a reduction in transient dynamic constraints and in digital and analog noise levels originating from the signals of the sensors that are part of the closed-loop control system. In addition, the compensation of the inertia matrix in the sliding surfaces ensures a total decoupling of the high-frequency chattering phenomenon originating from the discontinuous term of the torques control law. This decoupling in turn induces a general reduction in the chattering levels on all axes. In addition, the design of model-based sliding surfaces also generates a complementary study on the gravity matrix of the robotic system. Indeed, this complementary study makes it possible to characterize novel algebraic properties linked to the gravity matrix which serve to establish a compensation criterion for the latter in the very design of sliding surfaces. It is also possible to use the characteristics of the gravity matrix to mathematically validate the latter, thus providing a way to complement the traditional mathematical validation of the inertia and acceleration matrices of the robot model. In order to experimentally validate the model-based sliding surface design approach, a test bench including a prototype of an exoskeleton arm with 7 degrees of freedom is first used. Compared to the conventional approach, the proposed approach demonstrates a significant reduction in dynamic constraints as well as in the chattering levels on the torque inputs of the exoskeleton, while ensuring very good trajectory tracking performance. In order to subsequently demonstrate the generalization of the approach on other robotic systems, an experimental application has also been validated on a commercial quad copter drone. Lastly, the literature review positions our research work with relation to recent scientific publications, and proves the originality of the proposed approach, since to the best of our knowledge, no similar method using the design of model-based sliding surfaces on robotic systems has been developed to date.


identifier: Randriamasinoro, Njakarison Menja  (2021). Modélisation et optimisation de réseau infonuagique et de calcul périphérique.  Mémoire de maîtrise électronique, Montréal, École de technologie supérieure.

subject:
informatique en brouillard
équilibre de Nash
jeu de transport
jeu non coopératif
meilleure réponse

abstract:
Le calcul périphérique "edge computing" est récemment apparu pour fournir des services aux applications exigeants des contraintes strictes, en termes de qualité de service, telles que les applications 5G à faible latence. Cependant, en raison de leur capacité de calcul limitée, les centres de données "edge" ne sont pas en mesure de répondre à un grand nombre de requêtes des utilisateurs. Une combinaison du "edge" et de l’infonuagique est donc nécessaire pour livrer un service évolutif, à proximité des utilisateurs.

Le défis principal auquel est confronté un système aussi complexe, combinant le "edge", le centre de données "core" et le nuagepublique, est l’allocation optimale des ressources, assurant la qualité de service (QdS) des applications et satisfaisant les contraintes de capacité. Dans ce mémoire, nous présentons un modèle mathématique permettant d’optimiser l’allocation des ressources dans un environnement de "edge cloud", pouvant supporter plusieurs applications.

Les méthodes d’optimisation traditionnelles ne sont plus appropriées pour résoudre un tel problème. Nous modélisons le problème comme un jeu non coopératif et montrons qu’il est transformable à un jeu de transport classique. Nous proposons ensuite une solution pour le jeu basée sur l’élimination des stratégies strictement dominées et la méthode de meilleure réponse. Le but est d’identifier l’équilibre de Nash parmi l’ensemble des points d’équilibres générés dans le jeu. Les simulations expérimentales montrent que notre solution surpasse les travaux précédents.


identifier: Ben Cheikh Larbi, Aziz  (2021). Mise à l’échelle hybride des microservices conteneurisés.  Mémoire de maîtrise électronique, Montréal, École de technologie supérieure.

subject:
docker
conteneur
mise à l’échelle hybride
microservice

abstract:
La mise à l’échelle automatique est primordiale pour les fournisseurs de services infonuagiques. La précision et la réactivité sont des critères recherchés afin d’éviter des coûts financiers supplémentaires. D’une part, la sur-allocation de ressources engendre un coût d’achat et d’utilisation de plus de machines. D’autre part, la sous-allocation engendre une dégradation du QoS qui se traduit en violations des SLAs.

Dans le domaine des conteneurs, la solution la plus populaire est la mise à l’échelle horizontale de Kubernetes (HPA). Dans ce travail, nous proposant deux algorithmes de mise à l’échelle hybride bénéficiant des avantages du scaling horizontal et vertical à la fois. En outre, notre deuxième algorithme utilise un profileur, capable d’estimer le besoin en CPU pour répondre à un certain nombre de requêtes reçues. Nos algorithmes ont été testés dans différentes situations et leurs performances sont comparées à ceux de HPA de Kubernetes. Les résultats obtenus démontrent une amélioration importante de QoS, d’utilisation et d’allocation de ressources, ainsi que dans la consommation d’énergie.


identifier: Karimi, Sina  (2021). Robot navigation on construction sites using building information modeling and geographic information system.  Mémoire de maîtrise électronique, Montréal, École de technologie supérieure.

subject:
BIM
GIS
IFC
robot mobile
ontology
path planning
collecte de données
navigation

abstract:
Productivity is one of the issues that construction industry needs to address. The interest in gaining higher rate of efficiency in construction projects is growing especially with advancement in other technological disciplines such as robotics, sensors, etc. Among different propositions to cope with productivity issue, construction automation has shown great potential in this regard. Progress monitoring of construction projects is one of the challenges that requires some level of automation. Conventional methods of progress monitoring rely on textual data and subjective interpretation of the employees involved in this regard. With advancement in mobile robots’ capabilities in recent years, the interest in deploying robots on construction sites is increasing since they are able to navigate autonomously and acquire data. The robots can gather new kinds of on-site data that can be used for progress monitoring. One of the steps in mobile robot deployment on construction sites, is the autonomous navigation. Indoor and outdoor robot navigation can be improved with the building-related data namely Building Information Modeling (BIM) and Geographic Information System (GIS). The former can provide the building elements features and the latter would provide the surrounding site information of a construction project. BIM-GIS would provide semantic information that can be used for enhanced obstacle avoidance, improved path planning, and semantic navigation. The semantic navigation of mobile robots enables non-experts since they share their domain-specific knowledge. In this dissertation, we develop the following:
• A Systematic Literature Review (SLR) using novel methods of bibliometric analysis combined with qualitative analysis to identify the state-of-the-art and the gaps in using BIM and GIS for robot navigation.
• An Ontology-based approach to bridge the construction and robot navigation knowledge using established ontologies. The ontology is then used to retrieve the relevant information to be translated to the robotic system.
• A BIM-based path planner using IFC semantics integrated with robot navigation system using building elements geometries and semantics.

The building-related knowledge used in this research is gathered from different sources including detailed and thorough literature review, a case study and established standards of the robotic domain. We used experimental field test to validate our approach with an industrial partner. This research contributes to the field of robot deployment on construction sites to collect data that can be used for many applications such as progress monitoring, quality control and safety inspection. The developed solutions can be used for safer, easier and more intuitive mobile robot deployment on construction sites.


identifier: Rougeau-Moss, Vincent  (2021). Auto-filtrage des entrées par le complément spectral et des normalisations fréquentielles et l’utilisation de filtres en loi de puissance pour les réseaux de neurones convolutifs.  Mémoire de maîtrise électronique, Montréal, École de technologie supérieure.

subject:
CNN
apprentissage profond
Fourier
prétraitement des images
analyse fréquentielle
normalisation
classification d’images

abstract: Ce mémoire porte sur l’utilisation de procédés de prétraitement des images à l’aide du domaine de Fourier, afin d’améliorer les taux de précision des CNN (convolutional neural network) de classification d’images. Pour ce faire, trois nouvelles méthodes sont proposées. La première est la SFSC (Self-Filtering by the Spectral Complement) qui consiste à l’utilisation d’un auto-filtrage des entrées combiné à des combinaisons de normalisation et moyennage fréquentiels, afin de simplifier les images et les rendre plus simples à analyser par les CNN. La deuxième et troisième méthode portent sur un filtrage des images d’entrées ou de la sortie de la SFSC, à l’aide de filtres en loi de puissance qui évoluent au cours de l’apprentissage. L’efficacité de nos nouveaux procédés est vérifiée au travers d’expérimentations sur un total de 14 architectures uniques, ayant des poids aléatoires ou prédéfinis, pour trois types de tâche de classification d’images : la classification générale d’images naturelles (CIFAR), la classification de textures (DTD) et la classification fine des émotions du visage (KDEF). La forte polyvalence et l’adaptabilité de la SFSC lui ont permis d’améliorer tous les modèles utilisés, à l’exception du DenseNet et du Wide ResNet sur CIFAR, qui ont eu de légères pertes globales de moins de 1 % de précision. Quant aux filtres en loi de puissance, ceux-ci ne sont pas adaptés aux modèles pré-entraînés et fonctionnaient généralement moins bien que la SFSC, bien qu’ils l’aient dépassé dans certains cas. De futures recherches pourront utiliser nos méthodes et nos conclusions afin de les améliorer, les utiliser autrement avec les CNN ou développer de nouveaux procédés utilisant le domaine fréquentiel avec les CNN.


identifier: Gill, Marie-Philippe  (2021). Predicting the severity of Parkinson’s disease symptoms with smartwatches during daily living.  Mémoire de maîtrise électronique, Montréal, École de technologie supérieure.

subject:
Parkinson
montres intelligentes
on/off
tremblement
dyskinésie

abstract: Parkinson’s Disease (PD) is a neurodegenerative disease that affects millions of people worldwide and can significantly affect the quality of life. Currently, the Movement Disorder Society Unified Parkinson’s Disease Rating Scale (MDS-UPDRS) test evaluates the disease’s progression and is considered the gold standard. However, the test is done on average once or twice a year to assess motor and non-motor symptoms related to PD. It only provides a snapshot of the symptoms on a given day which is a significant limitation of the test. There is a need for passive, longitudinal, and in-the-wild home monitoring of the disease as PD symptoms can fluctuate for various reasons, such as the quality of sleep, from one day to the next. Monitoring the symptoms during daily life can provide essential insights and lead to better health care decisions for patients by providing information about how severe the symptoms are on average throughout the whole year. As a result, clinicians could find the most optimal medication schedule and dosage for patients, which has the potential to reduce side-effects of the medication like dyskinesia. Most of the work has been done either in clinical environments or at home with scripted tasks that subjects need to complete at specific times, which can be an additional burden. This is why this work aims to quantify the medication status (on/off), the severity of tremor, and dyskinesia from a single wrist-worn smartwatch during passive monitoring. Using the accelerometer of the Apple Watch, we propose three approaches to solve this problem. The first one is based on time series features extraction with an Extreme Gradient Boosting (XGBoost), while the second uses embeddings with different classifiers like Probabilistic Linear Discriminant Analysis (PLDA), K-Nearest Neighbors (KNN), and Support Vector Regression (SVR). The third approach is a fusion of both approaches using a simple average. We experimented with different data pre-processing methods, such as using a High-Pass Filter (HPF) to remove the gravity component. We also detected and removed inactivity in the signals. Furthermore, we artificially generated new samples with various data augmentation techniques such as linear combination, Gaussian noise, resampling, and rotation. Finally, the third approach was the most successful and achieved a weighted Mean Square Error (MSE) of 1.129, 0.429, and 0.462 for on/off, tremor, and dyskinesia. Thus, for each symptom, a different combination of data pre-processing and augmentation successfully improved the overall MSE.


identifier: Zhuldybina, Mariia  (2021). Quality control of printed electronics using terahertz radiation.  Thèse de doctorat électronique, Montréal, École de technologie supérieure.

subject:
électronique imprimée
contrôle de qualité
spectroscopie térahertz
tests non destructifs

abstract:
Graphic printing and electronics production are two high volume manufacturing technologies. Their combination brings a new fabrication technique and unique form of electronic applications. Printable electronics (PE) is a new advanced manufacturing technology that enables lower-cost fabrication for large-volume production of electronic devices. PE is a promising, environmentally friendly alternative route to produce display or energy products at a low cost and with new possibilities like flexible devices. One of the main challenges of this new technology is to scale it up to the industrial level. For the successful industrialization of this technology, reliability, and repeatability in both equipment and processes should be provided using efficient quality control. Currently, quality control is assessed manually or using well-developed laboratory techniques, which could be destructive or more time-consuming. To apply these methods in a production line, the specific conditions such as an appropriate illumination, a particular direction, a specific speed production, or even a cleanroom environment must be considered. These severely restrict the value of PE as an industrial manufacturing technique and requires developing an efficient in-line characterization technique to control the quality of fabrication process.

This work focuses on studying and developing terahertz time-domain spectroscopy (THz-TDS) as a characterization tool for the quality control of printed process. During the last decade, THz-TDS has received a lot of attention due to its contactless, non-destructive, high-resolution, non-invasive abilities for quality control. In non-destructive testing of materials, quality control is often based on sampling the condition of a production line. To ensure THz light interacts with the printed conductive materials, we introduced a simple strategy using THz metamaterials as a printing quality control bar (QCB).

To prove our idea, we printed QCBs using two types of printing techniques, which demonstrates the potential of using continuous roll to roll printing to manufacture functional printed devices. Our work employs QCBs in the same way that a test pattern is indispensable for quality control using offset color printing. In offset printing, the printed area of the control structure is around a 1 cm2. Our concept is quite similar.

In the framework of this thesis, two types of metamaterials have been designed and studied for the tracking of printing quality : geometrical variation and conductivity.

Implementation of metamaterials as a quality control structure is one of the possible solutions for an in-line and in-situ process monitoring in industrial production environments and a route to closed-loop control the quality.


identifier: Pishvaeian, Seyedpedram  (2021). Production planning of perishable products in an unreliable manufacturing system.  Mémoire de maîtrise électronique, Montréal, École de technologie supérieure.

subject:
produits périssables
système de fabrication non fiable
simulation
plan expérimental
politique de contrôle stochastique

abstract:
The current study tries to provide an optimal solution to the problem of production planning of perishable products in a failure-prone manufacturing system. The system under study has consisted of a single manufacturing machine producing one type of product, in which the machine is subject to random failures and repairs and the products are perishable. Even though the customer demand must be satisfied, shortages are allowed. Products are no longer usable after a certain course of time and must be discarded from the inventories on hand after their expiration.

The objective of this study is to propose optimal control policies minimizing the total cost imposed on the system, including holding, shortage, and perishability costs. The decision and state variables for this model are the production rate and stock level of finished perishable products, respectively. A simulation-based approach in combination with the experimental design and the response surface methodology provides us with the opportunity to obtain the optimal values for the parameters under study.

Through these models, three major scenarios to study the behavior of the system will be scrutinized. First, the situation in which both customer demand rate, and products’ lifetime are constant and predetermined will be studied. For the second case, it is assumed that products may perish at different times; however, the demand rate follows an unvarying pattern. In the last case, the randomness will be added to customer demand rate, while the products’ shelf life remains unchanged and constant. It has been suggested that in all cases, the proposed policies are valid, verified by the extensive sensitivity analyses performed and work well.


identifier: Alzidani, Mahmoud  (2021). Optimization of the scheduling strategy using meta-heuristics approach in the context of cellular manufacturing with multiples products.  Thèse de doctorat électronique, Montréal, École de technologie supérieure.

subject:
fabrication cellulaire
algorithme de méta-heuristique
makespan
éléments exceptionnels.

abstract:
Production scheduling is at the heart of the plant's planning and control system. One of the attractive production planning systems is Cellular Manufacturing Systems (CMS). CMS is a structural system based on group theory. Several advantages of the SFC concept mainly include the reduction of makespan and flow time. CMS is an NP-hard optimization problem. Depending on the size of the problem, the number of machines, and the number of parts, the computing time required to obtain the optimal solution increases exponentially. To solve NPhard optimization problems, metaheuristic algorithms are the best solution to get good solutions in a reasonable time.

In this work, we propose a new methodology to optimize parts' sequence in each manufacturing cell, including exceptional items. This technique is based on the RC-Filter algorithm. The proposed methodology was used to optimize the sequence of parts, including exceptional items, to minimize the time required. The proposed approach has been validated using thirteen problems taken from the literature. The results were compared to those provided by the Extended Great Deluge.

A cellular manufacturing system is a structured system based on the concept of a group. One of the advantages of this concept is that it can reduce production time. Optimizing cell manufacturing systems are categorized as NP-Hard, where the computational time increases exponentially with the problem's size. Utilizing metaheuristic algorithms will be an excellent solution to solve the NP-Hard problem in a reasonable time. In this work, we proposed a new hybrid approach to optimize the sequence of parts in each cell and exceptional elements. The proposed hybrid methodology is based on the RC-Filter algorithm and the Extended Great Deluge algorithm. The proposed tool is used to optimize the sequence of parts, including exceptional items in each cell, in order to minimize makespan. The proposed approach was validated using 13 problems, and the results were compared with those provided by other algorithms. A cellular manufacturing environment is generally the most efficient environment for minimizing makespan, flow time, and handling.

On the other hand, in most cases, a cell production environment requires distinctive elements' performance. This task generates many delays and intercellular movements. This problem is seen as a fundamental challenge to be solved to achieve the minimum makespan with exceptional elements and the minimum intercellular movement. In this work, a methodology was proposed, called the simulated annealing meta-heuristic algorithm, to obtain the best sequence of parts, allowing the minimum makespan.

This work has been divided into two steps, and each step contains two parts; these steps are as follows:

In the first part of the first step, we used simulated annealing to find the best sequence of exceptional elements without changing the cell's architecture. This is an optimization step as a jobshop problem, as there was much intercellular movement. In the second part, we optimized the sequence in each cell. These two parts represent the first stage of this work. To reduce intercellular movements, we used a dynamic cellular environment. In the second step of this work, a dynamic manufacturing cell was used. This step has two parts. In the first part, new cells were designed using only exceptional elements. Likewise, the machines used to manufacture exceptional items have been transferred to other cells. During the first part, the exceptional elements were made from a specific cell architecture. The goal of this part was to give the minimum of inter-cellular movements and manipulations. The second part of this step was to save the original cells' configuration, and the part sequences were optimized in each of them. Part sequence optimization was performed using the simulated annealing algorithm.


identifier: Alosta, Mahmud  (2021). Investigating AI-based approaches for data processing on IOT edge devices.  Thèse de doctorat électronique, Montréal, École de technologie supérieure.

subject:
internet des objets (IdO)
informatique de périphérie
apprentissage automatique
web sémantique
logique floue
analyse de périphérie

abstract:
The unprecedented dissemination of sensor technologies and their applications in different aspects of contemporary life has significantly contributed to the emergence of the Internet of Things (IoT). IoT envisions seamless integration of digital and physical worlds fabricating the ever witnessed stupendous network of connected devices. These devices have been harnessed to serve a diversity of applications including smart buildings, transportation, health, and agriculture. Fundamentally, collecting data is the main objective of such deployed networks. These data are constantly being generated leading to enormous volumes of raw sensory data that require further manipulation to convert it to valuable insight.

Typically, IoT data are transmitted to the cloud for processing and to deduce a meaningful outcome. Additionally, several IoT use-cases require the cloud to send back some instruction to fulfill actuation purposes. Considering the ever-increasing number of IoT connected devices and the limited network capacity, several challenges have arisen. First, blindly transmitting data to the cloud has amplified the stress in the network, leading to network bottlenecks. In addition, the reliance on the central cloud topology has raised the cost of IoT data manipulation. This cost can be envisioned in the bandwidth cost, in addition to the cloud operational cost. Furthermore, several time-sensitive IoT applications might not tolerate the latency imposed by the round-trip from sensor nodes to the cloud. All aforementioned issues have stimulated investigating alternative solutions that push such computing capabilities to the network edge and close to data sources. Auspiciously, this has become feasible thanks to the recent diversity and advancement that has been seen in the IoT edge devices endowing them the capability to handle a variety of use-cases. This also has been simultaneously accompanied with a broad investigation of the applicability of several AI-based techniques to perform IoT data manipulation tasks. More specifically, several AI-based techniques including semantic web, machine learning, and fuzzy logic have been widely investigated and accepted as key enabler to reveal the ambiguity of raw sensor data and to support decision-making tasks. Although the advantages introduced by these techniques have been widely acknowledged in the IoT domain, the growing tendency to extend such intelligence to the network edge has revealed several challenges. This includes their applicability to perform under resource-restricted platforms, in addition to, their consistency in unstable environments that the IoT edge based solutions are highly exposed to.

The main objective of this dissertation is to examine through several case studies the applicability of AI-based techniques in maintaining balanced efficiency in data processing and analysis tasks. This efficiency is obtained taking into consideration the resource-constrained aspect that is featured in a considerable portion of IoT edge devices. In addition, each case study represents a research problem that has been addressed individually in this thesis. Thus, the contributions introduced by this work correspond to the presented case studies and are structured sequentially interrelated objectives. The first contribution is proposed to assess the feasibility of edge-based solutions in performing timely and efficient event detection tasks based on the semantic web and complex event processing techniques. The feasibility of the semantic annotation process in performing efficient event detection and modeling, in addition to data filtration tasks on IoT edge devices was examined. Second, in order to support IoT edge solutions to not only detect events on time but also to predict events and contemplate them in advance, we have examined the combination of Machine Learning and fuzzy logic techniques. More specifically, we have investigated and applied best practices for efficient ML and FL-based solution deployment in resource-limited environments. Third, in view of the challenges of using ML models in real-time, we have investigated a fuzzy logic based approach to keep track of model performance. The proposed mechanism is intended to maintain an acceptable real-time model performance in accordance with balanced resource utilization on IoT edge devices.

In all analyzed cases, we conducted a deep exploration of the related subjects of research and supported our assumptions by a thorough analysis of real-life use cases. In addition, we have validated our assumptions with several proof-of-concept implementations. Such methodology demonstrated progress in highlighting a variety of perspectives and recognizing open issues and potential research issues within the scope of the presented research.


identifier: Boussard, Vivien  (2021). CRC-based error correction methods and algorithms applied to video communications over vehicular and IoT wireless networks.  Thèse de doctorat électronique, Montréal, École de technologie supérieure.

subject:
transmission sans fil
Wi-Fi
802.11p
Bluetooth Low Energy
Cyclic Redundancy Check
correction d’erreurs

abstract:
Video content transmission constitute the main category of data transmitted in the world nowadays. The quality of the transmitted content is ever increasing, thanks to the deployment of networks able to support huge traffic loads at high speeds, along with strategies to reduce the amount of data necessary to carry video information, based on more efficient video encoders. However, the quality of the video stream perceived by the end user can be greatly degraded by transmission errors. In fact, a packet can either be corrupted or lost during the transmission due to channel impairments, which result in missing video information that must be recovered. Several strategies exist to recover such information. Retransmission of the damaged packet can be performed. However, this option is not always valid under real time constraints as in video streaming, or to avoid increasing the global network load. To recover missing information, error correction methods can be applied at the receiver’s side.

In this thesis, we propose error correction methods at the receiver’s side based on the properties of the widely used error detection code Cyclic Redundancy Check (CRC). These methods use the syndrome of a corrupted packet computed at the receiver to produce the exhaustive list of error patterns that could have resulted in such syndrome, containing up to a defined number of errors. We propose different approaches to achieve such error correction. First, we present an arithmetic-based approach which performs logical operations (XORs) on the fly and does not need memory storage to operate. The second approach we propose is an optimized table approach, in which the repetitive computations of the first method are precomputed prior to the communication and stored in efficiently constructed tables. It allows this method to be significantly faster at the cost of memory storage. The error correction validation is performed through a two-step process, which cross-checks the candidate list with another error detection code, the checksum, and then validates the syntax of the encoded packet to test its decodability. We test these new methods with wireless transmission simulations of H.264 and HEVC compressed video content over Wi-Fi 802.11p and Bluetooth Low energy channels. The latter allows the most significant error correction rates and the reconstruction of a near-optimal video even when the channel’s quality starts to decrease.


identifier: Enamundram, Muni Venkata Naga Karthik  (2021). Unsupervised three-dimensional segmentation of scoliotic spines from MR volumes with uncertainty estimation.  Mémoire de maîtrise électronique, Montréal, École de technologie supérieure.

subject:
segmentation des vertèbres
scoliose
synthèse multimodale
CycleGAN 3D
incertitude

abstract:
Vertebral bone segmentation from magnetic resonance (MR) images is a challenging task. Due to the inherent nature of the modality to emphasize soft tissues of the body, common thresholding algorithms are ineffective in detecting bones in MR images. On the other hand, it is relatively easier to segment bones from computed tomography (CT) images because of the high contrast between bones and the surrounding regions.

This thesis proposes a novel method for a simple thresholding-based segmentation of the scoliotic spine that generates its 3D model by performing a cross-modality synthesis between MR and CT domains. However, this implicitly assumes the availability of paired MR-CT data, which is rare, especially in the case of scoliotic patients. Therefore, the proposed method is completely unsupervised and fully three-dimensional (3D). A 3D CycleGAN model is trained for an unpaired volume-to-volume translation across MR and CT domains. Then, the Otsu thresholding algorithm is applied to the synthesized CT volumes for easy segmentation of the vertebral bones. The resulting segmentation is used to reconstruct a 3D model of the spine. The unsupervised nature of the problem along with the lack of ground truth CT data make it difficult to objectively analyze the performance of the 3D CycleGAN. Therefore, a Bayesian adaptation of CycleGAN is proposed for capturing the uncertainty information in the form of aleatoric and epistemic uncertainties during translation. This enhancement makes the model self-sufficient by providing a measure of the confidence in the model’s predictions while simultaneously making it more interpretable for the Otsu segmentation task.

Ablation-study type experiments were run to determine the importance of uncertainty estimation and the improvement in the quality of translated volumes is also shown. The proposed method is quantitatively validated on 46 scoliotic vertebrae in 5 patients with varying degrees of the spinal curvature by computing the point-to-surface mean distance between the landmark points for each vertebra obtained from pre-operative X-rays and the surface of the segmented vertebrae. The study results in a mean distance error of 3.17 ± 1.04 mm. Based on qualitative and quantitative results, it is concluded that the proposed framework is able to obtain good segmentations and 3D models of the scoliotic spines along with the crucial uncertainty information, all after training from unpaired data in an unsupervised manner.


identifier: Pepin, Étienne  (2020). Keypoint masking for analyzing segmented medical image data.  Mémoire de maîtrise électronique, Montréal, École de technologie supérieure.

subject:
skull-strip
extraction de cerveau
points-clés
neuro-image
filtre de Gauss

abstract: This thesis investigates different methods of using segmentation masks, in the context of keypoint analysis of medical images and specifically the human brain in magnetic resonance images (MRI). Recent studies have used keypoints extracted following skull-stripping, i.e. first removing all non-brain image content. However we hypothesized that skull-stripping prior to convolution filtering (e.g. Gaussian derivative filtering used in 3D SIFT-Rank keypoint extraction) will lead to random boundary effects that will hinder brain analysis. To test this hypothesis, we compare against keypoints extracted from natural images prior to skull-stripping. Our experiment replicates a recent large-scale neuroimage family indexing experiment on data from Human Connectome Project, where classification results improve on average 2% for keypoints extracted from natural data vs. skull-stripped data. We develop a theoretical model explaining and predicting experimental results based on the properties of a n-dimensional normal distribution. Our methodology is general, and we expect our results to generalize to other non-brain data, e.g. natural image regions and other classification systems based on linear convolution, e.g. convolutional neural networks.


identifier: Vedaei Sabegh, Ali  (2021). Investigating the thermally grown oxides and attributed effects of scales on heat transfer and interfacial friction between the ingot and die during the open-die forging process.  Thèse de doctorat électronique, Montréal, École de technologie supérieure.

subject: forgeage à matrice ouverte

subject: oxydation à haute température

subject: cinétique d'oxydation

subject: analyse XRD

subject: analyse EDS

subject: fractions d'épaisseur de couche d'oxyde

subject: transfert de chaleur

subject: indentation

subject: frottement

subject: essai d'anneau

abstract:
Bulk metal forming is indicated for the deformation techniques for materials with a high volume to surface ratio. The classic bulk metal deformation methods continue to survive despite the emergence of novel deformation techniques. As one of the oldest bulk metal forming methods, open-die forging is a classic method, commonly employed to deform largesize ingots. In this method, the ingot is plastically deformed between two flat platens, where a post-forging step like machining will be needed afterward. Open-die forging can be realized as cold, warm, and hot deformation. During the hot deformation of steels, it is inevitable to experience the forming of thermally grown oxides. The steel surface will react with the interactive gaseous environment to form different oxide layers. The formed oxide layers are a cause of material waste. The scale can detach and penetrate ingot by deformation loads causing cracks and failures. The formed oxide layers have very low conductivity, which makes them act as insulators. Thus, the heat transfer of ingot is remarkably affected by the presence of oxide layers. Oxide layers can affect the interfacial friction between anvils and ingot. The anvils are costly to repair or replace. Hence, the effect of oxide layers on interfacial friction is critical to be investigated.

Grown over the past 70 years, Finkl Steel Co. is the largest producer of open-die forgings in Canada, with in-house melting, forging, heat treating, machining, testing, and inspection facilities. Finkl Steel Co. employs open-die forging to serve the industries of plastic injection molds, automotive, aerospace, oil and gas, construction, and mining. However, the company has experienced over hundred kilograms of material waste for each ingot due to thermal oxidation. The ingot temperature gradient, which is affected by scale layers, has caused undesired material characteristics. Furthermore, the interfacial friction between die and ingot is influenced by the presence of oxide. The deformation loads are significantly crucial for the company, and the anvils are costly to be repaired due to wear. This study was defined in this context and had aimed to experimentally and numerically assess the thermal oxidation and its effects on heat transfer and interfacial friction of large-size ingots. This study has resulted in three publications, which can be explained as follows:

In the first article, the thermal oxidation of two high-strength steels was investigated. The chemical composition of both steels was the same, except Ni's concentration, which was almost six times (2.92 wt%), to investigate Ni's effect on oxidation. Four oxidation temperatures of 1000, 1100, 1150, 1200 °C, and oxidation times of 3,10, 20, 30, and 60 min were allocated to evaluate the effect of oxidation time and temperature. Since the sample's weight increases during the formation of oxide layers, the weight variation can indicate the steel's oxidation rate. So, differential thermal analysis equipped with thermogravimetry (TG) was employed. The samples were heated to the desired oxidation temperature under argon flow, where a unit switches the argon to air at that temperature. The sample is exposed to air for desired oxidation time. The outcomes for both steels demonstrated that by increasing the oxidation temperature and oxidation time, the oxidation increased. However, two steels' weight changes showed that the steel with the higher amount of Ni had less thermal oxidation than steel with lower Ni. The obtained activation energy for steel with higher Ni was 275 KJ mol−1 compared to 238 KJ mol−1 for steel with lower Ni, which shows higher oxidation resistance by the addition of Ni. To investigate Ni's underlying mechanism for less oxidation, X‐ray diffraction (XRD) analyses were conducted to investigate the different layers. In addition to three general layers of wustite, magnetite, and hematite, two layers of spinel (FeOCr2O3) and chromite (Cr2O3) were present. Energy‐dispersive X‐ray spectroscopy (EDS) showed the concentration of Ni on the top side of oxide layers. Also, there was a Cr rich layer at the interface of oxide-metal. This Cr rich layer was thicker for steel with higher Ni. All these layers acted as obstacles against diffusion of oxygen and Fe, suppressing the accessibility of cations and anions to each other and consequently decreasing oxidation at high temperatures. So, the material waste was less by the addition of Ni.

In the second study, the study aimed to assess the effect of oxide growth on large-size ingots' cooling. The samples were heated to oxidation temperature under argon gas and then exposed to air for a determined time employing a radiative furnace. A confocal laser microscope measured the formed oxide thickness, where a parabolic behavior was seen for both steels. The formed oxide layers on high Ni steel was thinner compared to low Ni steel. It was found out that the thickness fraction of the wustite layer increased by increasing the oxidation temperature, and that of the hematite decreased. However, the thickness fraction of magnetite stayed the same for all testing conditions. Also, the relative thickness fraction of layers was the same for formed oxide layers on both steels. In other words, although the formed oxide layers were thinner for high Ni steel, they had the same fractions of low Ni steel. For the ingot’s cooling simulation, the steels' thermal properties were acquired by both the flash laser method and JMatPro software. The cooling rates, h-values, were obtained by Holman’s equations for finite element simulations. The finite element results demonstrated that the ingot with an oxide layer tends to cool faster from higher temperature than the ingot without an oxide layer, despite the oxide layers' insulation effect. The is due to the higher radiation coefficient of the oxide layer compared to the steel surface, which facilitates heat loss through vast ingot surfaces. However, sometimes the ingot stays more than hours in the furnace in an industrial situation, leading to thicker oxide layers. For an industrial case, a 7.8 mm oxide layer was observed. This oxide layer was employed in finite element simulation, and it was found that the ingot with this oxide layer has 200 K more temperature compared to the ingot without oxide. So, the oxide layer's insulation effect comes after a certain thickness is attained, where before that thickness, it causes higher heat loss. Also, in contact with the anvils, the thicker oxide layer prevented a temperature rise of 194 K on anvils. The developed finite element models were verified by experimental measurement of ingot surface temperature by a thermal camera.

In the final article, the effect of thermally grown oxides on the interfacial friction between the ingot and die are evaluated. The ring test is a commonly employed method for assessing interfacial friction. Prior to the ring test, indentation tests were conducted to investigate the mechanical properties of formed oxide layers on different steels and use them for the ring test's finite element simulation. An indentation tool is penetrated to the oxide surface up to a determined load and kept for a dwell time, and then unloaded. The indentation outcomes showed that the hardness and young modulus of formed oxide layers on steel with the higher concentration of Ni were lower than oxide formed on steel with lower Ni. Friction calibration curves were obtained by finite element simulations. The rings were deformed at high temperatures of 1273, 1373, 1423, and 1473 K between two flat platens. The variation of internal diameter was recorded concerning the variation of height for different friction coefficients. The developed simulations were verified by experimental ring tests. For ring tests, rings with geometrical dimensions of 18:9:6 mm were machined from blocks. These rings were oxidized in a radiative furnace for a determined time and then plastically deformed. The outcomes showed that the oxide layer can act as an additional lubricant at high temperatures.


identifier: Muñoz, Mario Felipe  (2021). Fully on-chain blockchain systems: a feasibility analysis based on LogLog and ZipZap.  Mémoire de maîtrise électronique, Montréal, École de technologie supérieure.

subject:
chaîne de blocs
normes de tokénisation
certification forestière
tokénisation de l’énergie

abstract:
This thesis compares two separate tokenization systems to ascertain the contexts where a fully on-chain approach is viable. Both systems were developed by the author, featuring somewhat homologous functionality in spite of great differences in industrial context and performance. Note that although the work on LogLog has been published already, work on ZipZap is still ongoing. Thus, descriptions of the latter will not be as rigorous as with the former.

LogLog

When it comes to sustainability, many certification systems live and die by their capacity to track a volume from source to destination. This is because customers (and consequently, auditors) are increasingly concerned with where products are sourced (“Are these local materials?”) and what is their environmental impact is (“How much CO2 did this generate? Was this made from recycled goods?”). The Forest Sustainability Council (FSC), one of the largest forestry authorities in North America, created many of its standards and frameworks to meet these market demands. The FSC is responsible for tracking the provenance of all wood volumes that its members use and labelling the volumes accordingly. Though widely respected, their certifications rely on trusted third parties and extensive record keeping, two characteristics that do not efficiently address problems like bribery and “creative” inventory practices. Blockchain technology is an attractive solution, since it offers many novel and valuable improvements to provenance-based certifications, such as increased traceability, auditability and access to information. However, distributed ledger systems are not without their limitations. Notably, they are often inefficient in their capacity to store large amounts of data and/or metadata, which is why many researches often suggest a multiple-database approach where large files are kept off-chain. That type of design entails significant trade-offs for the sake of lower transaction fees: imperfect traceability (changes to off-chain files are not necessarily tracked), lower availability (introducing more systems that all need to be up) and a diminished level of informational integrity (off-chain files are much more easily modified).

In contrast with these approaches, we propose LogLog: an entirely on-chain system for tracking wood volumes throughout a supply chain and enforcing FSC certification standards. LogLog is ERC-1155 compliant and meets the base requirements for a forestry supply chain. Our Proof-of- Concept demonstrates the power and flexibility of smart contracts when expressing complex domain-specific semantics related to supply chains in the forest industry (like determining the correct labelling for a volume using the FSC category matrix, or calculating the FSC percentage of a volume, for example).

We successfully implemented two reference implementations of our design using Solidity and deployed them over the Ethereum blockchain. Our evaluation uses realistic parameters and suggests our prototype is a viable alternative to current multiple-database systems in contexts where data integrity is a strict requirement.

ZipZap

In the last few years, the energy industry has increasingly invested into smart grid technologies. Smart grids are power grids with a high degree of automation and enhanced data collection capacities. However, another concurrent industry trend is the decentralization of the aforementioned power grids. More data means more risks and although a higher degree of decentralization means greater availability, it also results in a massive attack surface area increase. These facts have been some of the primary motivations driving industry specialists to consider blockchain systems to help automate operations (using smart contracts) and ensure data integrity (due to blockchains’ inherent cryptographic characteristics).

HydroQuebec is no exception to this trend. Having a vested interest in developing possible ways to integrate DLTs into smart grids, they sponsored our research into the topic. ZipZap is the first step towards a full-fledged blockchain-based smart grid system. At its current development stage, ZipZap is a blockchain solution for local energy tokenization, although its range of use cases will expand to include at least some form of price bidding and IoT integration. Also, just like LogLog, ZipZap is ERC-1155 compliant.

We created three ZipZap prototypes: Heavyweight, Featherweight and Lightweight. The first one is fully on-chain, and the two latter are hybridized. All three were developed in Solidity and deployed using Ethereum. Our evaluation uses realistic parameters and suggests that although none of the current prototypes are economically viable, changes in scale and/or choice of blockchain system could easily result in a viable alternative with otherwise minimal data structure modifications.


identifier: Zinsalo, Joël Mètogbé  (2020). Conception, modélisation et analyse de la performance d’un système géothermique amélioré à fractures multiples pour la production d’électricité.  Thèse de doctorat électronique, Montréal, École de technologie supérieure.

subject:
système géothermique amélioré
fracture discrète
énergie renouvelable
production d’électricité
puits multiples
perméabilité anisotrope
hétérogénéité
pertes d’eau
efficacité énergétique
management de réservoir
centrale géothermique
sélection de fluide
Cycle Organique de Rankine

abstract:
La production d’électricité par le système géothermique amélioré attire de plus en plus l’attention des chercheurs depuis une cinquantaine d’années. Le système géothermique amélioré consiste à extraire l'énergie thermique des roches chaudes et sèches par injection d'eau sous forte pression dans un réservoir artificiellement créé pour la production d'électricité. La géothermie profonde est une énergie durable, propre, et renouvelable. L’énergie géothermique est aussi une alternative aux énergies fossiles. La modélisation des différents processus dans un système géothermique amélioré est très complexe et nécessite beaucoup de recherches, développements numériques et beaucoup de temps de calcul. Dans cette thèse, plusieurs modèles sont développés pour plus de réalisme. Le réservoir géothermique considéré est anisotrope en perméabilité, hétérogène et la perte d’eau est prise en compte. La rentabilité du système géothermique amélioré dépend de plusieurs facteurs dont l’analyse est très importante en vue d’améliorer la performance du système. Plusieurs facteurs abordés dans cette thèse influencent la performance et la rentabilité du système : l’hétérogénéité du réservoir d’un système géothermique amélioré, les pertes d’eau inévitables dans le réservoir vers la formation environnante, l’espacement entre les puits d’injection et de production, l’épaisseur de fracture, l’inclinaison des puits d’injection et de production, la direction de l’écoulement régional, la disposition des puits d’injection et de production lorsque plusieurs puits sont mis en oeuvre pour la production optimale d’électricité, la sélection du fluide secondaire dans un cycle Organique de Rankine (ORC) couplé au réservoir, les stratégies d’injection du fluide dans le réservoir et sa récupération qui nécessite une analyse approfondie.

Dans les études antérieures, l’injection du fluide dans le réservoir du système géothermique amélioré est basée sur les expériences issues de l’industrie pétrolière et gazière. La stratégie d’injection est un facteur clé de succès ou d’échec d’un système géothermique amélioré. Il importe d’explorer toutes les possibilités d’injection et de récupération du fluide. L’analyse des stratégies d’injection et de récupération permet d’éviter une rupture thermique prématurée qui peut écourter la durée de vie du réservoir. La durabilité et la rentabilité d’un système géothermique amélioré sont très préoccupantes pour intéresser les gouvernants et investisseurs. Il est donc important de fournir à l'industrie une gestion améliorée des stratégies d'injection de fluide dans le réservoir afin de maximiser l'extraction de chaleur. C’est pour cette raison que la première partie de cette thèse est axée sur six scénarios en vue d’étudier les stratégies d’injection et de récupération du fluide avec un modèle de fractures discrètes sur 40 ans de production d’électricité. En se basant sur les conditions aux limites et paramètres utilisés dans cette thèse, les résultats ont montré que le scénario 1 est le meilleur avec une puissance électrique effective de 9,65 MWe. Dans ce meilleur scénario, la température de production augmente de 167,9 °C à une valeur maximale de 170,4 °C, puis diminue au fur et à mesure que l'injection continue et elle atteint 166 °C à la fin de la production. L'impédance d'écoulement du réservoir est d'environ 0,22 MPa/(kg/s). Une analyse de sensibilité a été conduite en étudiant l’influence de l’ouverture de fracture, la conductivité thermique de fracture, la distance entre fractures sur la température de production et la puissance électrique effective. Lorsque les valeurs d'ouverture de fractures sont supérieures à 0.1 mm, on constate une diminution de la température de production, de la puissance électrique effective et du temps de rupture thermique. Une distance entre fractures hydrauliques de 25 m donne des résultats intéressants et cette valeur est fortement recommandée. Les résultats obtenus dépendent fortement des propriétés physiques de la formation géologique et des propriétés thermodynamiques du fluide géothermal. La méthodologie adoptée dans cette étude peut être mise en oeuvre pour tout réservoir d’un système géothermique amélioré.

Dans un réservoir de système géothermique amélioré, la pré-existence de fractures naturelles, de petites fissures, et la variabilité des propriétés pétrophysiques rendent le réservoir hétérogène. La pré-existence de petites fissures et l’injection de l’eau sous forte pression provoque des pertes d’eau inévitable vers la formation géologique environnante. Ces deux phénomènes (hétérogénéité et pertes d’eau) sont difficiles à quantifier et ils rendent la modélisation complexe. La variabilité de la perméabilité dans toutes les directions fait que le réservoir est anisotrope en perméabilité. Pour ainsi évaluer le potentiel de production d’électricité du système géothermique amélioré, la prise en compte de l’anisotropie en perméabilité, l’hétérogénéité du réservoir et les pertes d’eau est capitale pour une production durable réelle. Dans la deuxième partie de cette thèse, l’hétérogénéité du réservoir, les pertes d’eau inévitables et l’anisotropie en perméabilité sont prises en compte. Une analyse de sensibilité sur une période de 40 ans de production a été conduite afin d'évaluer l'influence des pertes d'eau et de l'hétérogénéité du réservoir pendant toute la production. L'impact de l'inclinaison du puits, de la distance entre les puits d'injection et de production sur la température de production, et sur la puissance électrique effective a également été étudié. En négligeant les pertes d’eau dans la modélisation, la performance du système est surestimée et la durée de vie du système peut arriver plutôt que prévue. En supposant que le réservoir est homogène alors qu’il est hétérogène en réalité, la performance du système est surestimée ce qui rend la prédiction douteuse. Dans le but de quantifier l’effet de l’hétérogénéité du réservoir sur la performance du système, trois cas hétérogènes (H1, H2, H3) et un cas homogène (H4) ont été adoptés. Une combinaison de couches a été proposée et les propriétés pétrophysiques sont calculées sur la base de moyenne pondérée. Sept (7) critères de comparaison ont été établis : la température de production (comparaison de sa variation durant tout le processus d’extraction), la baisse de la température de production au puits de production qui devrait être comprise entre 5% et 15%, l’écart relatif entre la puissance électrique effective moyenne dans le cas homogène et celle obtenue dans les trois différents cas hétérogènes étudiés, la pression de production, l’impédance du réservoir qui est la chute de pression requise pour circuler 1 kg d’eau du puits d’injection au puits de production, la puissance électrique effective moyenne et le taux d’extraction de chaleur. De tous les critères établis, seul le taux d’extraction de chaleur permet de déterminer le niveau d’hétérogénéité du réservoir. Le taux d'extraction de chaleur varie de 0 à 39,4%, de 0 à 41,1%, de 0 à 42,9% et de 0 à 45,3% pour les cas H1, H2, H3 et H4, respectivement. Il sort des résultats que le cas H1 est plus hétérogène. L'inclinaison du puits a une faible influence sur la température de production. La puissance électrique effective plus élevée est obtenue dans le cas des puits verticaux dans lesquels la puissance électrique effective augmente de 9,47 MWe à 9,83 MWe en 19,3 ans et diminue de 9,83 MWe à 9,20 MWe. Plus la distance entre les puits d'injection et de production est grande, plus le réservoir doit être grand et les pertes d'eau deviennent importantes. La puissance électrique efficace maximale est obtenue pour les puits verticaux avec un espacement de 540 m, la durée de rupture thermique est de 25,6 ans et la puissance électrique effective moyenne est de 9,7 MWe. Le temps de rupture thermique augmente avec l'augmentation de l'espacement des puits. L'augmentation de la perte d'eau de 0% à 10% pour un espacement de puits de 500 m se traduit par une diminution de l'efficacité énergétique du système géothermique amélioré de 2,4-2,2 à 2,3-2,1. La direction du flux régional du puits de production au puits d'injection améliore les performances du système.

La troisième partie de ce projet de thèse aborde la possibilité d’utiliser plusieurs puits d’injection et de production pour maximiser l’extraction de la chaleur du réservoir. La disposition des puits d’injection et de production joue un rôle capital dans l’évaluation du potentiel de production d’électricité en considérant la poroélasticité du réservoir. Dans la troisième partie de cette thèse, une conception et un choix optimal de plusieurs puits d’injection et de production ont été mis en oeuvre. Neuf (9) scénarios ont été envisagés en considérant pour référence le système conventionnel à un puits d’injection et un puits de production (cas 1), un puits d’injection et deux puits de production (cas 2), un puits d’injection et trois puits de production (cas 3), trois puits d’injection alignés et un puit de production (cas 4), trois puits d’injection alignés et deux puits de production alignés (cas 5), trois puits d’injection alignés et trois puits de production alignés (cas 6), deux puits d’injection alignés et un puit de production (cas 7), deux puits d’injection alignés et deux puits de production (cas 8), deux puits d’injection alignés et trois puits de production alignés (cas 9). Toutes ces configurations ont été étudiées afin d'extraire une quantité d'énergie suffisante et de permettre au fluide d'atteindre un plus grand volume dans le réservoir hétérogène. Des résultats de l’étude, il ressort que la configuration avec trois puits d'injection et deux puits de production alignés correspondant au cas 5 offre la meilleure performance du système géothermique. L'augmentation du débit de fluide d'injection de 75 l/s à 125 l/s avec une température d'injection de 60 °C conduit à une diminution de la puissance électrique de 10,40 - 9,40 MWe à 6,84 - 4,53 MWe car plus le débit volumique est élevé, plus les pertes en eau sont grandes. La température de production moyenne après une période de 40 ans est de 164,8 °C et réduite de 3,1%, ce qui est acceptable. La température du fluide injecté et le gradient hydraulique ont une faible influence sur la température de production et le taux d'extraction de chaleur. L'effet du gradient hydraulique sur la température du fluide produit est perceptible pour une valeur de gradient hydraulique supérieure à 10 mm/m.

La quatrième partie de ce projet de thèse est réservée à l’analyse de performance et à la sélection du fluide secondaire adéquat pour la production d’électricité en couplant la centrale géothermique et le réservoir pour une utilisation durable et efficace du système géothermique amélioré à fractures multiples sur 40 ans de fonctionnement. Vingt fluides de travail ont été choisis afin de sélectionner le meilleur en fonction du rendement énergétique et du rendement exergétique. Les résultats montrent que les fluides de travail ont un effet significatif sur la température de réinjection du géofluide et un léger effet sur la température de production. La température de réinjection varie de 56,5 °C à 108,4 °C selon le fluide de travail utilisé. Le fluide de travail le plus performant était le R1233zd(E), un réfrigérant hydrofluorooléfine, ininflammable avec un impact nul sur l'appauvrissement de la couche d'ozone et un très faible potentiel de réchauffement climatique. Dans les conditions de fonctionnement du réservoir EGS, une combinaison d'une pression d'entrée maximale de la turbine de 1,6 MPa, d'un débit massique maximal de réfrigérant de 50 kg/s et d'une température de condensation de 25 °C évite une formation de gouttelettes dans la turbine. Cette combinaison donne de meilleures performances avec un rendement énergétique de 15,8 – 16,0%, un rendement exergétique de 43,5 - 44,6%, une température d'entrée de la turbine de 121,3 - 156,3 ° C, une puissance électrique nette de 1,97 - 2,32 MW sur les 40 ans de production. Le rendement énergétique et le rendement exergétique diminuent avec l’augmentation de la température du condenseur.


identifier: Foroozmehr, Fayaz  (2021). Microstructure and fracture mechanics properties of 13% Cr-4% Ni martensitic stainless steels.  Thèse de doctorat électronique, Montréal, École de technologie supérieure.

subject:
ténacité JIc
propagation stable de la fissure
propagation instable
inclusion

abstract:
13% Cr-4% Ni martensitic stainless steels are used to manufacture the hydroelectric runners due to their high strength and toughness, as well as their good resistance against corrosion and cavitation erosion. As hydraulic turbine runners are subjected to cyclic loadings, fatigue cracking is the main source of damage during their useful lifetime, and regular inspections are performed to verify the severity of the damage, and carrying out the required reparations.

The main purpose of this study is characterizing the fracture behaviors of the hydroelectric runner component materials i.e. the cast (CA6NM), the wrought (415), the matching weld metals (410NiMo). The possibility of establishing relationships among fracture behavior, inclusion characteristics and austenite contents has motivated the study. The stress triaxiality ST ratios were measured on the necked region from the tension broken samples, and fracture micromechanics were characterized using the modified Rice and Tracey model describing ductile rupture in terms of void growth-ST ratio relationship. Linear-Elastic Fracture Mechanics (LEFM) is not applicable for small laboratory specimens of ductile materials, such as 13% Cr-4% Ni martensitic stainless steels, as large-scale yielding occurs during KIc testing. Elastic-Plastic Fracture Mechanics (EPFM) approach is therefore necessary to measure the strain energy release rate (J) for this category of stainless steels. The stable crack growth behavior of the substrate steel (CA6NM), the weld metals, and the Heat-Affected Zone (HAZ) was characterized during JIc-testing. The substrate steel was tested in heat-treated condition, whereas the weld metal and the HAZ were examined in both as-welded and heat-treated conditions. Fracture surfaces were examined using a Scanning Electron Microscope (SEM) coupled with an Energy Dispersive X-ray (EDX) spectrometer to reveal the nature of the second phase particles.

It was shown that fracture strain after necking can be estimated using size and spacing of inclusions when considerable void growth occurs before final rupture; however, in the cases in which negligible void growth occurs due to a very small inclusion spacing, the proposed model is not appropriate. The austenite content and the mechanical properties of the matrix should also be considered. The heat-treatment significantly improved the fracture toughness JIc of the weld metal and the HAZ by factors of 2 and 2.7, respectively. However, unstable propagations were occurred into the weld metal in the case of all the JIc tests performed on the HAZ. This is due to the detrimental effect of the very small inclusion spacing in the microstructure of the weld metal, resulting in an immediate coalescence of the nucleated micro-voids.


identifier: Loiselle, Guillaume  (2021). Développement d’un modèle semi-empirique de prévision de la surcote due au vent sur le lac Champlain.  Mémoire de maîtrise électronique, Montréal, École de technologie supérieure.

subject:
surcote
prévisions
prévision numérique du temps
lac Champlain
rivière Richelieu

abstract: La prévision des niveaux d’eau du lac Champlain est une composante clef du processus de prévision des inondations dans la région de la rivière Richelieu. Ces prévisions sont normalement réalisées avec des modèles hydrologiques qui prennent en considération uniquement les paramètres hydriques (précipitation, fonte, évapotranspiration, etc.), mais qui ne considèrent pas l’impact du vent sur les niveaux du lac. En effet, lorsque le vent souffle avec intensité sur un grand réservoir pendant une longue période de temps, un phénomène appelé « surcote » peut se produire. Cette surcote est le résultat du frottement entre le vent et la surface de l’eau et se traduit par une différence entre le niveau moyen et le niveau à l’exutoire du lac. L’objectif de cette étude est de créer un modèle semi-empirique de prévision de la surcote sur le lac Champlain dans le but d’améliorer la prévision des débits, et donc des inondations, dans la rivière Richelieu. Le modèle proposé utilise les prévisions de la vitesse et de la direction du vent à plusieurs endroits sur le lac, ainsi que la vitesse des rafales en plus d’être calibré sur plusieurs paliers de vitesses différents. Le modèle est calibré sur des observations provenant de stations météorologiques et hydrométriques et est validé sur un échantillon indépendant d’observations. L’étude présente aussi une comparaison entre le modèle proposé et un modèle développé par le USACE, inspiré de la formulation de Zuider Zee, réalisée sur vingt évènements de surcote survenus entre 2017-2019 en utilisant les données de prévisions de cinq systèmes numériques de prévision météorologiques (GDPS, RDPS, HRDPS, NOAA et ECMWF). Les données de prévision des cinq systèmes ont fait l’objet d’une correction de biais par quantiles. Les résultats montrent que le modèle proposé arrive à correctement prédire les évènements de surcote au moins 72 heures d’avance, une performance supérieure à celle du modèle du USACE. Ultimement, l’inclusion de la vitesse du vent et de la force des rafales à plusieurs endroits sur le lac améliore significativement la performance du modèle.


identifier: Sorto-Ventura, Kevin-Rafael  (2021). Study, modelling and control of bidirectional battery chargers for real-time simulation applications.  Mémoire de maîtrise électronique, Montréal, École de technologie supérieure.

subject:
chargeur de batterie
véhicule électrique
convertisseur multiniveaux
qualité de l’énergie
simulation en temps-réel

abstract: The work done in this project aims to propose a suitable AC-DC converter topology and control method for high power, bidirectional battery chargers. Moreover, another objective is to design equivalent converter models suitable for real-time simulation applications. This research is motivated by the growing presence of electric vehicles and the increasing demand for faster and bidirectional battery chargers. In addition to high power density and bidirectional power flow capability, the converter used in the battery charger should offer good power quality. Therefore, this thesis studies two multilevel converter topologies, which are able to minimize harmonic distortion on the grid due to their high number of output voltage levels. Thus, the single-phase 23-level H-PUC is proposed with a model predictive controller. By implementing this converter in real-time simulation using the RT-LAB software and OP4510 simulator, it is shown that the topology greatly reduces the AC current filtering requirements when compared to conventional converter topologies. Then, a deadbeat predictive controller for bidirectional power flow is developed for the three-phase PM-ANPC 13-level converter. Simulation results obtained in Simulink demonstrate that the proposed controller can effectively regulate the AC current and DC link voltage during both charging and discharging modes of operation. Finally, an equivalent model of the PM-ANPC converter is presented and validated against a reference model that uses blocks from the SimPowerSystems library in Simulink. Then, an OP4510 real-time simulator is used to illustrate the improved simulation performance of the equivalent model with respect to the reference model.


identifier: Arab, Naima  (2021). Study of the Impact of Power Converters Equipped with LC-LCL filters interfacing renewable energy sources to the grid.  Thèse de doctorat électronique, Montréal, École de technologie supérieure.

subject:
amortissement actif
convertisseurs multiniveaux PUC5
contrôle optimal
filtre LCL
Micro-réseau
partage de puissance
stabilité
stabiliser

abstract:
The demand and variety of power converters interfacing with renewable energy sources have been increasing steadily in recent years, presenting new challenges for the current centralized power grid. The microgrid is a new alternative that increases the penetration rate of the renewable energies (wind and photovoltaic energy, etc.) while the electrical power quality is improved. However, the increased penetration rate of the distributed generators DGs systems can pose problems with reverse power flow, voltage fluctuations and other issues to distribution networks. Beside this, the loads variations, the power generated by the renewable energy sources, and also the transition between grid-connected and the islanded modes impact the microgrid stability. The instabilities are linked to the fact that the power flow in this type of network is bidirectional. In addition, the power fluctuations generated by the renewable energy sources in MGs require the coordinated control of DGs, which allows further stable MG operation. Therefore, the reliability and stability are the major concerns in a microgrid system. On the other hand, distributed generators are equipped with an LC-LCL filter to produce higher power quality while relieving it for reactive power compensation and harmonic elimination.

As part of this doctoral thesis, the local control of a distributed generator which is connected to the loads and to the grid via an LCL filter has been optimally designed as to have the active damping based on LQR control. In addition, this proposed control takes into consideration the perturbation and the tracking of a desired reference model in order to guarantee the stability and robustness of the distributed generator. The controllers have been experimentally implemented using real time with dSPACE. Two applications have been successfully completed; first application is a distributed generator connected to the grid via an LCL filter (PUC5-LCL) and the second one is a single stage multifunctional SPV-APF-LCL which was designed to achieve optimal multifunctional operation for residential power supply.

In order to improve the power sharing between the distributed generators in a microgrid, a new droop control in the primary control has been proposed to keep the voltage and frequency of the microgrid constant. This droop control is based on supplementary control loop (stabilizer) added in the conventional droop control and is applied to several converters interfacing with renewable energy sources connected in parallel on the AC bus. The microgrid application with the proposed droop control has been verified in the real time environment using dSPACE and RT-LAB.

The application of its commands involves the modeling of these complete systems as well as the design of the appropriate regulators to deal with the resonances problems, instabilities and the high quality of energy transfer as well as the suitable power sharing performance.

All the theoretical studies are completely validated by simulation and experimentation analyses and discussions.