No description available.

No description available.

No description available.

No description available.

No description available.

The chemical industry is an essential part of modern society and therefore has a responsibility to develop solutions for the problems facing it. A major problem is continuing to match the material demands of a growing global population whilst simultaneously decreasing the consumption of finite natural resources and limiting the emissions of greenhouse gasses. An optimised catalytic system that shortens, or intensifies, the process chain for the production of chemicals can be an effective solution to this challenge. Auto-tandem catalysis is where a single metal-ligand complex facilitates two or more sequential transformations. For example: alkenes are hydroformylated into aldehydes which are then hydrogenated into alcohols. The alcohols have use as plasticisers or surfactants for metal extraction. A previously reported auto-tandem catalysis system was shown to be capable of sequential hydroformylation-hydrogenation of 1-octene to nonanol. It consisted of the neutral rhodium precursor [Rh(acac)(CO)2] and the bidentate ligand xantphos in 10% iPrOH/H2O co-solvent at temperatures of 160°C. Investigations, reported in this thesis, revealed that xantphos type ligands, with their large bite-angle, and high temperatures are required to generate the hydrogenation activity. However, in contrast to the previous system, water is not necessary; with the same results produced in toluene:iPrOH solutions and water:iPrOH solutions. It is proposed that the iPrOH or H2O has a direct influence in the catalytic cycle, either as a hydrogen-shuttle or generates a cationic rhodium species, known to be active in hydrogenation. High temperature NMR studies show the standard resting state of the hydroformylation catalyst is still predominant at high temperatures therefore the proposed catalytic cycle starts from this step. A recurring problem in the industrial process chain is the separation of the catalyst from the final products. Combing a TiO2 ceramic membrane with a POSS (polyhedral oligomeric silsesquioxane) modified tin catalyst and phosphonium iodide co-catalyst, for the coupling of epoxides and CO2 to make cyclic carbonates, was investigated. The catalyst system showed good substrate compatibility for a range of epoxides. In a prototype membrane set-up the system demonstrated a long catalyst life time, however significant leaching was also observed.

The underlying opportunity for this study is that process materials may show considerable change in their electrical properties in response to an injected signal over a wide frequency range. The use of this concept to demonstrate the construction of tomographic images for a range of frequency bands is described. These can then provide a deeper understanding and interpretation of a process under investigation. The thesis presents an in-depth review of the characteristics of the various wideband signals that could be used for simultaneous spectral measurements. This includes an objective selection process that demonstrates that a Chirp signal form offers key advantages. It then addresses the details of the developed method and algorithms for WElT systems that deploy a Chirp wideband excitation signal and a further aspect of the method, based on the time-frequency analysis, particularly wavelet transform, which is used to reveal spectral data sets. The method has been verified by simulation studies which are described. To provide measurements over a required frequency range a linear chirp is deployed as the excitation signal and corresponding peripheral measurements are synthesised using a 2D model. The measurements are then analysed using a wavelet transform algorithm to reveal spectral datasets which are exemplified in the thesis. The thesis then examines the feasibility of the presented method through various experimental trials; an overview of the implementation of the electronic system is included. This provides a single-channel EIT chirp excitation implementation, in essence simulating a real-time parallel data collection system. through the use of pseudo-static tests on foodstuff materials. The experimental data were then analysed and tomographic images reconstructed using the frequency banded data. These included results illustrate the promise of this composite approach in exploiting sensitivity to variations over a wide frequency range. They indicate that the described method can augment an EIT sensing procedure to support spectroscopic analysis of the process materials.

Achieving optimal efficiency of production in the industrial sector is a process that is continuously under development. In several industrial installations separators, produced by Alfa Laval, may be found, and therefore it is of interest to make these separators operate more efficiently. The separator that is investigated separates impurities and water from crude oil. The separation performance is partially affected by the settings of process parameters. In this thesis it is investigated whether optimal or near optimal process parametersettings, which minimize the water content in the output, can be obtained.Furthermore, it is also investigated if these settings of a session can be testedto conclude about their suitability for the separator. The data that is usedin this investigation originates from sensors of a factory-installed separator.It consists of five variables which are related to the water content in theoutput. Two additional variables, related to time, are created to enforce thisrelationship. Using this data, optimal or near optimal process parameter settings may be found with an optimization technique. For this procedure, a Gaussian Process with the Deep Kernel Learning extension (GP-DKL) is used to model the relationship between the water content and the sensor data. Three models with different kernel functions are evaluated and the GP-DKL with a Spectral Mixture kernel is demonstrated to be the most suitable option. This combination is used as the objective function in a Basin-hopping optimizer, resulting in settings which correspond to a lower water content.Thus, it is concluded that optimal or near optimal settings can be obtained. Furthermore, the process parameter settings of a session can be tested by utilizing the Bayesian properties of the GP-DKL model. However, due to large posterior variance of the model, it can not be determined if the process parameter settings are suitable for the separator.

This research addresses real-time task scheduling in industrial process control. It includes a constraint-based scheduler which is based on MSP.RTL, a tool for real-time multiprocessor scheduling problems with a wide variety of timing constraints. This dissertation extends previous work in two broad directions: improving the tool itself and broadening the application domain of the tool to include wired and wireless industrial process control. For the tool itself, we propose enhancements to MSP.RTL in three steps. In the first step, we modify the data structure for representing the temporal constraint graph and cutting the memory usage in half. In the second step, we model the search problem as a constraint satisfaction problem (CSP) and utilize backmarking and conflict-directed backjumping to speed up the search process. In the third step, we perform the search from the perspective of constraint satisfaction programming. As a result, we are able to use existing CSP techniques efficiently, such as look ahead, backjumping and consistency checking. Compared to the various ad hoc heuristics used in the original version, the new approach is more systematic and powerful. To exercise the new MSP.RTL tool, we acquired an updated version of the Boeing 777 Integrated Airplane Information Management System(AIMS). This new benchmark problem is more complicated than the old one used in the original tool in that data communications are described in messages and a message can have multiple senders and receivers. The new MSP.RTL tool successfully solved the new benchmark problem, whereas the old tool would not be able to do so. In order to apply real-time scheduling in industrial process control, we carry out our research in two directions. First, we apply the improved tool to traditional wired process control. The tool has been successfully applied to solve the block assignment problem in Fieldbus networks, where each block comprising the control system is assigned to a specific device such that certain metrics of the system can be optimized. Wireless industrial control has received a lot of attention recently. We experimented with the tool to schedule communications on a simulated wireless industrial network. In order to integrate the scheduler in real wireless process control systems, we are building an experimental platform based on the WirelessHART standard. WirelessHART, as the first open wireless standard for process control, defines a time synchronized MAC layer, which is ideal for real time process control. We have successfully implemented a prototype WirelessHART stack on Freescale JM128 toolkits and built some demo applications on top of it. Even with the scheduler tool to regulate communications in a wireless process control, it may still be possible that communications cannot be established on an inferior wireless link within an expected period. In order to handle this type of failures, we propose to make the control modules aware of the unreliability of wireless links, that is, to make the control modules adapt to the varying link qualities. PID(Proportional, Integral, Derivative) modules are the most used control modules. We developed PIDPlus, an enhanced PID algorithm to cope with possible lost inputs and outputs. It has been shown that PIDPlus can drastically improve the stability of the control loop in cases of unreliable wireless communications. / text

Η παρούσα διατριβή πραγματεύεται την ανάπτυξη μιας καινοτόμου μεθοδολογίας για την βελτιστοποίηση τόσο του σχεδιασμού όσο και της λειτουργίας βιομηχανικών εγκαταστάσεων. Η μεθοδολογία αυτή βασίζεται στη χρήση δυο μεθόδων Τεχνητής Νοημοσύνης (Έμπειρων Συστημάτων και Γενετικών Αλγόριθμων) για τη δημιουργία ενός λογισμικού το οποίο λαμβάνοντας από το χρήστη στοιχεία σχετικά με τα κριτήρια σχεδιασμού (ή ανασχεδιασμού) μιας διεργασίας καθώς και για τις συνθήκες λειτουργίας της θα εξαγάγει τόσο τις βέλτιστες διαθέσιμες τεχνολογίες για τη διεργασία αυτή όσο και τις βέλτιστες συνθήκες λειτουργίες των επιλεχθεισών τεχνολογιών. Προκειμένου να λειτουργήσει η αναπτυχθείσα μεθοδολογία πέρα από τα στοιχεία τα οποία παρέχει ο χρήστης είναι απαραίτητη η ύπαρξη μιας βάσης δεδομένων η οποία θα περιέχει τις διαθέσιμες τεχνολογίες οι οποίες είναι δυνατόν να χρησιμοποιηθούν για τη συγκεκριμένη διεργασία, δηλαδή όλα τα τμήματα εξοπλισμού που μπορούν να χρησιμοποιηθούν για τη διεργασία αυτή. Οι βέλτιστες διαθέσιμες τεχνολογίες, τις οποίες η μεθοδολογία επιλέγει από αυτή τη βάση δεδομένων, είναι τα τμήματα του εξοπλισμού εκείνα τα οποία πληρούν με τον καλύτερο δυνατό τρόπο τα κριτήρια σχεδιασμού της διεργασίας. Για την εύρεση των βέλτιστων τεχνολογιών για μια διεργασία για κάθε διαθέσιμη τεχνολογία πρέπει να λαμβάνονται υπόψη και τα εκτιμώνται: τεχνικά κριτήρια όπως τα όρια λειτουργίας της, η ολοκλήρωσή της στη διεργασίας (δηλαδή η διασύνδεσή της με άλλες τεχνολογίες που χρησιμοποιούνται στην ίδια διεργασία), οικονομικά κριτήρια όπως το κόστος εγκατάστασης, το κόστος λειτουργίας, ή / και το κόστος συντήρησης, περιβαλλοντικά στοιχεία όπως οι εκπομπές ρύπων, παραπροϊόντα. Η απαίτηση για ταυτόχρονη ικανοποίηση όλων αυτών των κριτηρίων καθιστά την εύρεση των βέλτιστων διαθέσιμων τεχνολογιών ένα περίπλοκο πρόβλημα για την επίλυση του οποίου απαιτείται εξειδικευμένη γνώση. Στην αναπτυχθείσα μεθοδολογία η γνώση αυτή καταχωρείται με κατάλληλο τρόπο στο σύστημα και κατά συνέπεια με τη χρήση του είναι δυνατόν ακόμη μη εξειδικευμένα άτομα να βρουν τις βέλτιστες διαθέσιμες τεχνολογίες (και τις βέλτιστες παραμέτρους λειτουργίας του). Η αναπτυχθείσα μεθοδολογία εφαρμόστηκε σε τρία προβλήματα ανασχεδιασμού του συστήματος συμπαραγωγής ενέργειας ενός διυλιστηρίου. Από τα αποτελέσματα που προέκυψαν από τις εφαρμογές αυτές γίνεται φανερό ότι η μεθοδολογία καταλήγει σε βέλτιστες λύσεις του προβλήματος για τις εκάστοτε συνθήκες και ότι ο αλγόριθμος της μεθοδολογίας είναι ιδιαίτερα εύρωστος υπό την έννοια ότι η σύγκλισή του δεν επηρεάζεται από τις τιμές των παραμέτρων που χρησιμοποιούνται για την εκτέλεσή του. / The thesis at hand deals with the development of a novel methodology for the optimisation of both the design and the operation of industrial plants. The methodology is based on two Artificial Intelligence techniques (Expert Systems and Genetic Algorithms) for the development of a software which, given from the user data related to the design criteria of the process, as well as the conditions of operation of the process, it will output both the best available technologies for that process as well as the optimal working conditions of the selected technologies. Apart from the data provided from the user, the methodology requires also a database which should contain the available technologies which can be used for the process at hand. These technologies are the various components of the equipment which can be used for the process. The best available technologies which are selected by the methodology from the database are those components which satisfy in the best possible way the design criteria. For the identification of the best technologies for a process the methodology assess (for each of the available techonologies): technical criteria such range of operation, its integration to the whole process (i.e. its connectivity with other technologies used in the process), financial criteria such as the cost of installation, the cost of operation and or the cost of maintenance, environmental criteria such as emissions of various pollutants, side products etc. The requirement of the simultaneous satisfaction of these criteria makes the identification of the best available technologies a complex problem which requires specific knowledge (expertise) in order to be solved. In the developed methodology this specific knowledge (expertise) is stored in a proper way in the system and therefore it is possible that even not-expert users of the system to identify the best available technnologies (and the best working conditions of the selected technologies). The developed methodology was applied to three problems of re-design of the cogeneration plant of a refinery. From the results obtain from these applications it is evident that the methodology converges to near optimal solutions for the criteria set each time and that the algorithm of the methodology is robust since its convergence is not affected by the value set for the algorithm's parameters during each of the runs.