Data reconciliation for mineral and metallurgical processes : Contributions to uncertainty tuning and dynamic balancing : Application to control and optimization

Pour avoir un fonctionnement de l'usine sûr et bénéfique, des données précises et fiables sont nécessaires. D'une manière générale, une information précise mène à de meilleures décisions et, par conséquent, de meilleures actions pour aboutir aux objectifs visés. Dans un environnement industriel, les données souffrent de nombreux problèmes comme les erreurs de mesures (autant aléatoires que systématiques), l'absence de mesure de variables clés du procédé, ainsi que le manque de consistance entre les données et le modèle du procédé. Pour améliorer la performance de l'usine et maximiser les profits, des données et des informations de qualité doivent être appliquées à l'ensemble du contrôle de l'usine, ainsi qu'aux stratégies de gestion et d'affaires. Comme solution, la réconciliation de données est une technique de filtrage qui réduit l'impact des erreurs aléatoires, produit des estimations cohérentes avec un modèle de procédé, et donne également la possibilité d'estimer les variables non mesurées. Le but de ce projet de recherche est de traiter des questions liées au développement, la mise en œuvre et l'application des observateurs de réconciliation de données pour les industries minéralurgiques et métallurgiques. Cette thèse explique d’abord l'importance de régler correctement les propriétés statistiques des incertitudes de modélisation et de mesure pour la réconciliation en régime permanent des données d’usine. Ensuite, elle illustre la façon dont les logiciels commerciaux de réconciliation de données à l'état statique peuvent être adaptés pour faire face à la dynamique des procédés. La thèse propose aussi un nouvel observateur de réconciliation dynamique de données basé sur un sous-modèle de conservation de la masse impliquant la fonction d'autocovariance des défauts d’équilibrage aux nœuds du graphe de l’usine. Pour permettre la mise en œuvre d’un filtre de Kalman pour la réconciliation de données dynamiques, ce travail propose une procédure pour obtenir un modèle causal simple pour un circuit de flottation. Un simulateur dynamique basé sur le bilan de masse du circuit de flottation est développé pour tester des observateurs de réconciliation de données et des stratégies de contrôle automatique. La dernière partie de la thèse évalue la valeur économique des outils de réconciliation de données pour deux applications spécifiques: une d'optimisation en temps réel et l’autre de commande automatique, couplées avec la réconciliation de données. En résumé, cette recherche révèle que les observateurs de réconciliation de données, avec des modèles de procédé appropriés et des matrices d'incertitude correctement réglées, peuvent améliorer la performance de l'usine en boucle ouverte et en boucle fermée par l'estimation des variables mesurées et non mesurées, en atténuant les variations des variables de sortie et des variables manipulées, et par conséquent, en augmentant la rentabilité de l'usine.To have a beneficial and safe plant operation, accurate and reliable plant data is needed. In a general sense, accurate information leads to better decisions and consequently better actions to achieve the planned objectives. In an industrial environment, data suffers from numerous problems like measurement errors (either random or systematic), unmeasured key process variables, and inconsistency between data and process model. To improve the plant performance and maximize profits, high-quality data must be applied to the plant-wide control, management and business strategies. As a solution, data reconciliation is a filtering technique that reduces impacts of random errors, produces estimates coherent with a process model, and also gives the possibility to estimate unmeasured variables. The aim of this research project is to deal with issues related to development, implementation, and application of data reconciliation observers for the mineral and metallurgical industries. Therefore, the thesis first presents how much it is important to correctly tune the statistical properties of the model and measurement uncertainties for steady-state data reconciliation. Then, it illustrates how steady-state data reconciliation commercial software packages can be used to deal with process dynamics. Afterward, it proposes a new dynamic data reconciliation observer based on a mass conservation sub-model involving a node imbalance autocovariance function. To support the implementation of Kalman filter for dynamic data reconciliation, a procedure to obtain a simple causal model for a flotation circuit is also proposed. Then a mass balance based dynamic simulator of froth flotation circuit is presented for designing and testing data reconciliation observers and process control schemes. As the last part of the thesis, to show the economic value of data reconciliation, two advanced process control and real-time optimization schemes are developed and coupled with data reconciliation. In summary, the study reveals that data reconciliation observers with appropriate process models and correctly tuned uncertainty matrices can improve the open and closed loop performance of the plant by estimating the measured and unmeasured process variables, increasing data and model coherency, attenuating the variations in the output and manipulated variables, and consequently increasing the plant profitability

Comprehensive characterization of an aspen (<i>Populus tremuloides</i>) leaf litter sample that maintained ice nucleation activity for 48 years

Decaying vegetation was determined to be a potentially important source of atmospheric ice nucleation particles (INPs) in the early 1970s. The bacterium Pseudomonas syringae was the first microorganism with ice nucleation activity (INA) isolated from decaying leaf litter in 1974. However, the ice nucleation characteristics of P. syringae are not compatible with the characteristics of leaf litter-derived INPs since the latter were found to be sub-micron in size, while INA of P. syringae depends on much larger intact bacterial cells. Here we determined the cumulative ice nucleation spectrum and microbial community composition of the historic leaf litter sample 70-S-14 collected in 1970 that conserved INA for 48 years. The majority of the leaf litter-derived INPs were confirmed to be sub-micron in size and to be sensitive to boiling. Culture-independent microbial community analysis only identified Pseudomonas as potential INA. Culture-dependent analysis identified one P. syringae isolate, two isolates of the bacterial species Pantoea ananatis, and one fungal isolate of Mortierella alpina as having INA among 1170 bacterial colonies and 277 fungal isolates, respectively. Both Pa. ananatis and M. alpina are organisms that produce heat-sensitive sub-micron INPs. They are thus both likely sources of the INPs present in sample 70-S-14 and may represent important terrestrial sources of atmospheric INPs, a conclusion that is in line with other recent results obtained in regard to INPs from soil, precipitation, and the atmosphere.</p

Collective Driving to Mitigate Climate Change: Collective-Adaptive Cruise Control

The transportation sector is the largest producer of greenhouse gas (GHG) emissions in the United States. Energy-optimal algorithms are proposed to reduce the transportation sector’s fuel consumption and emissions. These algorithms optimize vehicles’ speed to lower energy consumption and emissions. However, recent studies argued that these algorithms could negatively impact traffic flow, create traffic congestions, and increase fuel consumption on the network-level. To overcome this problem, we propose a collective-energy-optimal adaptive cruise control (collective-ACC). Collective-ACC reduces fuel consumption and emissions by directly optimizing vehicles’ trajectories and indirectly by improving traffic flow. Collective-ACC is a bi-objective non-linear integer optimization. This optimization was solved by the Non-dominated Sorting Genetic Algorithm (NSGA-II). Collective-ACC was compared with manual driving and self-centered adaptive cruise control (i.e., conventional energy-optimal adaptive cruise controls (self-centered-ACC)) in a traffic simulation. We found that collective-ACC reduced fuel consumption by up to 49% and 42% compared with manual driving and self-centered-ACC, respectively. Collective-ACC also lowered CO2, CO, NOX, and PMX by up to 54%, 70%, 58%, and 64% from manual driving, respectively. Game theory analyses were conducted to investigate how adopting collective-ACC could impact automakers, consumers, and government agencies. We propose policy and business recommendations to accelerate adopting collective-ACC and maximize its environmental benefits

Biological Control of Soybean Charcoal Rot Caused by Macrophomina Phaseolina Using Trichoderma harzianum

In this study, the antagonistic effect of Trichoderma harzianum T100 as a potential biocontrol agent against soybean charcoal rot caused by Macrophomina phaseolina were evaluated in in vitro and in vivo conditions. In dual culture tests, isolate T100 inhibited the mycelial growth of pathogen (55.3 %), then over ran and sporulated on the mycelia of M. phaseolina. Microscopic examination of mycelial interaction sites of T. harzianum and M. phaseolina showed that T100 penetrated mycelial cells of pathogen, moved inside and lysed them. Volatile test results indicated that the antagonist inhibited the mycelial growth of pathogen (12.2 %) and decreased the production of microsclerotia in culture media. Data from greenhouse experiments showed that, treatment of soil with T. harzianum T100 resulted in a high percentage of fresh and dry weights of root (57.5 % and 53.6 %) and aerial parts (22.9 % and 11.8 %) of soybean in sterile soil in compared with control. Additionally, reduction of microsclerotial formation on soybean root and steam, microsclerotial coverage, (62.5 %) showed the antagonist ability for initial inoculums reduction in later season

Air Emission Impact of Low-Level Automated Vehicle Technologies in the U.S. Metropolitan Areas

Environmental savings of low-level automated vehicles in US metropolitan area

Microbial antagonists against plant pathogens in Iran: A review

The purpose of this article was to give a comprehensive review of the published research works on biological control of different fungal, bacterial, and nematode plant diseases in Iran from 1992 to 2018. Plant pathogens cause economical loss in many agricultural products in Iran. In an attempt to prevent these serious losses, chemical control measures have usually been applied to reduce diseases in farms, gardens, and greenhouses. In recent decades, using the biological control against plant diseases has been considered as a beneficial and alternative method to chemical control due to its potential in integrated plant disease management as well as the increasing yield in an eco-friendly manner. Based on the reported studies, various species of Trichoderma, Pseudomonas, and Bacillus were the most common biocontrol agents with the ability to control the wide range of plant pathogens in Iran from lab to the greenhouse and field conditions

Hemodynamic Stability during Induction of Anesthesia in Elderly Patients: Propofol + Ketamine versus Propofol + Etomidate

Introduction: Various methods have been recommended to prevent hemodynamic instability caused by propofol induction. Current study evaluates hemodynamic effects of ketamine and propofol in comparison to etomidate and propofol during anesthesia induction. Methods: Sixty-two patients over 50 years old undergoing elective surgeries were randomly assigned to ketamine + propofol (ketofol) (n=30) and etomidate + propofol (etofol) (n=32) groups. Patients in ketofol group were induced with ketamine 0.75 mg/kg and propofol 1 mg/kg. In etofol group, induction was performed with etomidate 0.2 mg/kg and propofol 1 mg/kg. Hemodynamic states before and after induction, first, third and sixth minutes after intubation were measured and compared between groups. Results: There was no difference between groups in systolic (SAP), diastolic (DAP) and mean arterial pressure (MAP), heart rate (HR) and blood oxygen saturation (SaO2). There was significant decrease in SAP, DAP and MAP after induction and 6 minutes after intubation and in HR after induction than values before induction. There was significant increase in SaO2 in all evaluated periods than before induction in etofol group; however, the difference in ketofol group was not significant. Conclusion: Both methods of induction -ketamine + propofol and etomidate + propofol- are effective in maintaining hemodynamic stability and preventing hemodynamic changes due to propofol administration