Academic literature on the topic 'Analysis of directionality'

Production plants used in modern process industry must produce products that meet stringent environmental, quality and profitability constraints. In such integrated plants, non-linearity and strong process dynamic interactions among process units complicate root-cause diagnosis of plant-wide disturbances because disturbances may propagate to units at some distance away from the primary source of the upset. Similarly, implemented advanced process control strategies, backup and recovery systems, use of recycle streams and heat integration may hamper detection and diagnostic efforts. It is important to track down the root-cause of a plant-wide disturbance because once corrective action is taken at the source, secondary propagated effects can be quickly eliminated with minimum effort and reduced down time with the resultant positive impact on process efficiency, productivity and profitability. In order to diagnose the root-cause of disturbances that manifest plant-wide, it is crucial to incorporate and utilize knowledge about the overall process topology or interrelated physical structure of the plant, such as is contained in Piping and Instrumentation Diagrams (P&IDs). Traditionally, process control engineers have intuitively referred to the physical structure of the plant by visual inspection and manual tracing of fault propagation paths within the process structures, such as the process drawings on printed P&IDs, in order to make logical conclusions based on the results from data-driven analysis. This manual approach, however, is prone to various sources of errors and can quickly become complicated in real processes. The aim of this thesis, therefore, is to establish innovative techniques for the electronic capture and manipulation of process schematic information from large plants such as refineries in order to provide an automated means of diagnosing plant-wide performance problems. This report also describes the design and implementation of a computer application program that integrates: (i) process connectivity and directionality information from intelligent P&IDs (ii) results from data-driven cause-and-effect analysis of process measurements and (iii) process know-how to aid process control engineers and plant operators gain process insight. This work explored process intelligent P&IDs, created with AVEVA® P&ID, a Computer Aided Design (CAD) tool, and exported as an ISO 15926 compliant platform and vendor independent text-based XML description of the plant. The XML output was processed by a software tool developed in Microsoft® .NET environment in this research project to computationally generate connectivity matrix that shows plant items and their connections. The connectivity matrix produced can be exported to Excel® spreadsheet application as a basis for other application and has served as precursor to other research work. The final version of the developed software tool links statistical results of cause-and-effect analysis of process data with the connectivity matrix to simplify and gain insights into the cause and effect analysis using the connectivity information. Process knowhow and understanding is incorporated to generate logical conclusions. The thesis presents a case study in an atmospheric crude heating unit as an illustrative example to drive home key concepts and also describes an industrial case study involving refinery operations. In the industrial case study, in addition to confirming the root-cause candidate, the developed software tool was set the task to determine the physical sequence of fault propagation path within the plant. This was then compared with the hypothesis about disturbance propagation sequence generated by pure data-driven method. The results show a high degree of overlap which helps to validate statistical data-driven technique and easily identify any spurious results from the data-driven multivariable analysis. This significantly increase control engineers confidence in data-driven method being used for root-cause diagnosis. The thesis concludes with a discussion of the approach and presents ideas for further development of the methods.

La δ-proteobactérie Myxococcus xanthus est étudiée depuis des décennies pour sa capacité à s’auto-organiser en réponse à des stimuli environnementaux. Cette bactérie colonise des niches écologiques favorables grâce à sa capacité à se mouvoir sur des surfaces. Cette motilité lui permet d’avoir un comportement prédateur envers des organismes proies, alors qu’en absence de nutriments, elle met en place un processus développemental permettant la formation de corps fructifères contenant des myxospores résistant aux stress environnementaux. Tous ces comportements multicellulaires requièrent un contrôle dynamique de la polarité de la cellule, établi par trois protéines polaires : MglA, MglB et RomR. Ensemble, elles définissent la direction de la cellule, qui peut être rapidement inversée sous l’action du système chimiotactique Frz (réversion). Dans ce travail de thèse, à travers une approche expérimentale et computationnelle, nous avons mis en évidence que le système de régulation forme un nouveau type d’oscillateur protéique, contrôlé par deux protéines RomR et FrzX, qui agissent ensemble et de manière complémentaire pour déclencher la réversion à l’arrière des cellules. L’architecture unique de ce système permet une réponse très large à différents stimuli, essentielle pour de nombreux comportements multicellulaires. Afin de comprendre l’importance de ces transitions, nous avons mis au point un outil à haute résolution spatiale et temporelle afin de connecter les cellules individuelles aux comportements multicellulaires, et ainsi comprendre le rôle du système Frz dans un modèle multicellulaire de prédation<br>The δ-proteobacteria Myxococcus xanthus has been a model of study for decades for its self-organized behavior as a response of environmental stimuli. It colonizes favorable ecological niches by using surface motility. In particular, this motility allows M.xanthus to predate collectively over prey microorganisms, while under starvation they start a developmental process to form macroscopic fruiting bodies, filled with environmental resistant myxospores. All these multicellular behaviors require a dynamic control of the cell polarity established by the polarity proteins MglA, MglB and RomR. Together, they define the direction of movement of the cell, which can be rapidly inverted by the Frz chemosensory system (reversion). In this thesis work, through combined computational/experimental approaches, we highlight that the regulation system forms a new type of biochemical oscillator, controlled by two proteins RomR and FrzX, which act together through complementary action to trigger the reversion at the lagging pole. The unique architecture of this system allows a wide response to various stimuli, which could be very beneficial for collective cell behaviors. To understand the importance of these transitions, we have developed a new high-resolution single cell assay linking single cMARTINEAU EUGENIE 2018AIXM0089/016ED62 2018/03/21 62 SCES SCHell behaviors to multicellular structures at unprecedented spatial and temporal resolutions. This way, we have investigated the role of the newly identified biochemical oscillator in the multicellular model of predation