Dry powder inhalers (DPIs) are a common therapeutic modality for lung diseases such as asthma, but they are also used to treat systemic diseases such as diabetes. Advantages of DPIs include their portable design and low manufacturing costs. Another advantage of DPIs is their breath activation, which makes them popular among patients. In a passive DPI drug is only released when the patient inhales. When the patient inhales, air flows through the device. The flow of air entrains a dry powder formulation inside the device and carries it to the lung. Currently, no DPI exists which can deliver drug independent of the patient to the desired target site in the lung. This is because drug release depends on the patient’s inhalation manoeuvre. To maximize the effect of the treatment it is necessary to optimize DPIs to achieve drug delivery that (A) is independent of the inhalation manoeuvre and (B) is targeted to the correct site in the lung. Therefore, this thesis aims to apply numerical and experimental methods to optimize DPIs systematically. First, two clinically justifiable cost functions have been developed corresponding to the DPI design objectives (A) and (B). An Eulerian-Eulerian (EE) computational fluid dynamics (CFD) approach has then been used to optimize a DPI entrainment geometry. Three different optimized entrainment geometries have been found corresponding to three different therapeutic applications. Second, the CFD approach has been validated experimentally. This is the first experimental study to validate an EE CFD approach for DPI modelling. Third, a personalized medicine approach to DPI design has been proposed. The development of this approach makes it possible to achieve the design objectives for patients with highly different lung functions. Finally, an adaptive DPI with a variable bypass element has been developed. This DPI achieves design objectives (A) and (B) for patients with highly different lung functions with a single device. In contrast to the personalized medicine approach, there is no need to select the optimal amount of bypass, since the device adapts automatically.

This thesis presents simulation method and simulation software Witness as a decision management instrument of a company, applied in STEKO spol. s r.o. The goal of this thesis is to create a model of real business process in the simulation program and following optimalization.

PhD thesis deals with application of simulation and optimization methods in the field of waste and biomass utilization for energy purposes. Current situation in this field is described in the introductory. Following chapters deal with approaches of creating mathematical models of apparatus and processes used in the field of interest for simulation and optimization purposes. Stochastic methods, which are widely applied for real problems solution, are mentioned as well. The core of the thesis consists in proposal of systematic approach and its application for simulation and optimization model building used in the field of interest. The application is demonstrated through two case studies. The first one deals with the building of simulation model of an existing waste-to-energy plant using its operation data. The second study deals with optimization model building and its application for a problem regarding utilization of biomass in an existing energy system.

An accurate model for RO process has significant importance in the simulation and optimization proposes. A steady state model of RO process is developed based on solution diffusion theory to describe the permeation through membrane and thin film approach is used to describe the concentration polarization. The model is validated against the operation data reported in the literature. For the sake of clear understanding of the interaction of feed temperature and salinity on the design and operation of RO based desalination systems, simultaneous optimization of design and operation of RO network is investigated based on two-stage RO superstructure via MINLP approach. Different cases with several feed concentrations and seasonal variation of seawater temperature are presented. Also, the possibility of flexible scheduling in terms of the number of membrane modules required in operation in high and low temperature seasons is investigated A simultaneous modelling and optimization method for RO system including boron removal is then presented. A superstructure of the RO network is developed based on double pass RO network (two-stage seawater pass and one-stage brackish water pass). The MINLP problem based on the superstructure is used to find out an optimal RO network which will minimize the total annualized cost while fulfilling a given boron content limit. The effect of pH on boron rejection is investigated at deferent seawater temperatures. The optimal operation policy of RO system is then studied in this work considering variations in freshwater demand and with changing seawater temperature throughout the day. A storage tank is added to the RO layout to provide additional operational flexibility and to ensure the availability of freshwater at all times. Two optimization problems are solved incorporating two seawater temperature profiles, representing summer and winter seasons. The possibility of flexible scheduling of cleaning and maintenance of membrane modules is investigated. Then, the optimal design and operation of RO process is studied in the presence of membrane fouling and including several operational variations such as variable seawater temperature. The cleaning schedule of single stage RO process is formulated as MINLP problem using spiral wound modules. NNs based correlation has been developed based on the actual fouling data which can be used for estimating the permeability decline factors. The correlation based on actual data to predict the annual seawater temperature profile is also incorporated in the model. The proposed optimization procedure identified simultaneously the optimal maintenance schedule of RO network including its design parameters and operating policy. The steady state model of RO process is used to study the sensitivity of different operating and design parameters on the plant performance. A non-linear optimization problem is formulated to minimize specific energy consumption at fixed product flow rate and quality while optimizing the design and operating parameters. Then the MINLP formulation is used to find the optimal designs of RO layout for brackish water desalination. A variable fouling profile along the membrane stages is introduced to see how the network design and operation of the RO system are to be adjusted Finally, a preliminary control strategy for RO process is developed based on PID control algorithm and a first order transfer function (presented in the Appendix).

no / In this work, a model based MINLP (mixed integer nonlinear programming) optimisation framework is developed for evaluating boron rejection in a reverse osmosis (RO) desalination process. A mathematical model (for the RU process) based on solution diffusion model and thin film theory is incorporated in the optimisation framework. A superstructure of the RU network is developed which includes two passes: (a) seawater pass containing normal two-stage RU system housing seawater membrane modules and (b) the brackish water pass (BW) accommodating brackish water membrane modules. For fixed freshwater demand, the objective of this work is to demonstrate the effectiveness of the MINLP approach for analyzing and optimizing the design and operation of RU network while attaining desired limit on boron concentration in the freshwater produced. The effect of seasonal variation in seawater temperature and pH on boron removal efficiency is also discussed.

L'objectif principal de la thèse a été d'étudier le comportement triboélectrique des contacts glissants à sec entre matériaux polymères (ABS, PE, PP, PS et deux types de PVC), incluant la possibilité de contrôler et d'optimiser les résultats générés, en termes de charge électrique et d’usure. Un tribomètre linéaire a été conçu et construit, afin de permettre le réglage des principales variables de contrôle du processus de charge triboélectrique : force normale, vitesse de glissement, durée et course. Ce dispositif facilite la mesure de certaines grandeurs physiques caractérisant les conditions de frottement: les variations des forces normale et tangentielle, ainsi que le déplacement relatif entre les éprouvettes. De plus, la charge électrique générée et l’augmentation de la température à la surface du polymère ont été aussi été mesurées et mise en relation avec les propriétés tribologiques. Les expériences ont montré que le niveau et la distribution de la charge générée par le frottement sec dépendent de la force normale appliquée, du temps de frottement (le nombre de cycles), de la vitesse de glissement, des propriétés mécaniques des matériaux et de la rugosité ou de la texture des surfaces en contact. La décharge couronne peut être utilisée pour déposer une charge initiale sur les surfaces avant le glissement. La modélisation du processus de charge triboélectrique a été faite avec la méthodologie des plans d’expériences. Les résultats peuvent alors être utilisés pour prédire et optimiser la charge triboélectrique. Des cartes de contrôle peuvent assurer le monitoring du processus et la détection de variations non-maîtrisés de la charge générée par effet triboélectrique. / The main objective of the thesis was to study the triboelectric behavior of dry sliding contacts between polymeric materials (ABS, PE, PP, PS and two types of PVC), including the possibility to control and optimize the results in terms of either surface charge generated or wear. A linear tribometer with tribocharging capabilities was designed and built, to enable the study of the sliding contact between solids and to allow the adjustment of main tribocharging control variables: normal force, sliding speed, time and stroke. This device also provided measurement data to characterize the friction condition: the variations of the normal and tangential forces, as well as the relative displacement between the specimens. Furthermore, the electric charge generated and temperature raise due to rubbing on the surface of the polymer were measured, so that to investigate the relationship between the tribological properties. The experiments showed that the level and distribution of the charge generated by dry friction depends on the normal force applied, friction time (cycle), sliding speed, material mechanical properties and surface roughness or texture. Corona discharge may be used to provide initial charge on the surfaces before sliding. Modelling of tribocharging processes was done using the design of experiments methodology. The models can be used to predict and optimize the tribocharging. Control charts were used to monitor the process and detect the special causes of variation in the charge generated by triboelectric effect.

Buzwagi Gold Mine (BGM) is operated by Acacia Mining and located in the Lake Victoria Goldfields of central Tanzania. The mine commenced its operation since April 2009 and treats a sulphide copper-gold ore to produce gold in form of doré bars and a concentrate containing gold, copper and silver. The BGM comminution circuit includes a primary crushing stage with a gyratory crusher and a two grinding circuits using a Semi-Autogenous Grinding (SAG) mill and a ball mill. The SAG mill circuit also includes a single-deck screen and a cone crusher while the ball mill circuit utilizes hydrocyclones. Currently, the grinding circuits are inefficient in achieving the aspired product fineness of xP,80 = 125 μm even at low to normal throughputs (450-600 t/h). An evaluation and optimization study of the circuit performance was conducted to improve the product fineness through circuit surveys, experimental lab work and simulations. In three full scale sampling campaigns, size distributions and solids contents of the samples were determined at selected points in the circuit. Further, several types of breakage tests were conducted; standard Bond tests to determine ore grindability and work indices, batch grinding tests to determine parameters for breakage and selection functions , and standard ball mill tests for mineral liberation characterization by an automated mineral liberation analyzer (MLA).The tests were conducted in a size range from 0.063 to 2 mm. Then, mass balance of the circuit was calculated and the models for mills, screens and hydrocyclones were employed in MODSIM (version 3.6.24). Firstly, simulations were conducted to optimize the existing plant. Several options were evaluated such as reduction of SAG screen aperture, adjustment of cyclone feed solids content and reduction of vortex finder and apex diameters. Moreover, simulations were also evaluated for a possible modification of the existing circuit and include; partial splitting of the cyclone underflow back to SAG mill, introduction of a second classification stage as well as introduction of a second ball mill. The evaluation of breakage tests and survey data revealed the following; the Bond work index obtained for the current ore ranges between 17.20 - 18.70 kWh/t compared to 14.50 - 16.50 kWh/t which was estimated during plant design.This indicates a change in hardness of the ore during the last 7 years. Harder ore means more energy requirement for an efficient operation, the consequence of which is increased costs. Thus, a periodic review of the ore hardness for ongoing mining operation is recommended. This will help in establishing better blends as well as prediction of appropriate tonnages for the existing ore types, so as to be efficiently treated by the available plant design. The work indices of the ore blends treated during survey were correlated with their quartz content and showed a strong linear relationship (R2= 0.95). Therefore, the work index for the BGM ore could be predicted based on known quartz content of the material. Further, the model could be used as a control tool for monitoring hardness variation of the SAG mill feed. The mineral liberation studies indicated that the valuable phase (pyrite-pyrrhotite) could be liberated at relatively coarser particle sizes (200-400 µm). This implies that, there could be no problem with the efficiency of the gravity circuit for the BGM operation, where the gold contained in pyrite-pyrrhotite could be easily concentrated. However, the efficiency of flotation and cyanidation processes will still require finer feed. In overall, the liberation characteristics of the ore blends treated during survey showed minor differences. The Bond efficiency factors of 48-61 % were obtained for the BGM grinding circuit, indicating an inefficient operation. This suggests that the operation could achieve targets by lowering the throughput. Further, the SAG mill circuit was characterized by fluctuating feed size of between xF,80 =102 to 185 mm. A need for control of the feed size as well as blending ratios was recommended for an efficient operation in terms of throughput and final product size. This could be achieved through closer monitoring of the primary crusher performance and proper control of the ratios for the SAG mill feeders drawing the ore from the stockpile. The ball mill grinding efficiency was poor and could be indicated by the fraction < 125 µm of only 5-9 % or xP, 80 : >400 µm in the mill discharge. This was deemed due to poor hydrocyclone performance which was characterized by higher feed solids content, coarser overflow xP,80: >200 µm as well as cut sizes, xT : > 200 µm. An improvement of product fineness up to 327 µm could be achieved during the simulation and optimization of the existing design. This could be achieved by modification of the operating conditions such as reduction of SAG screen aperture from 12 mm to 10 mm, reduction of vortex finder from 280 mm to 270.3 mm, reduction of apex diameter from 150 mm to 145.6 mm as well as adjustment of the cyclone feed solids content from 66.7 to 67.1 %. Based on this result, it was concluded that the current equipment could not achieve the target product quality (i.e. xP,80 = 125 µm ). Further simulations based on flowsheet modification options showed that a second ball mill (series configuration) can help to achieve the desired product fineness as well as an increase of throughput from 618 t/h to 780 t/h. Although the circulating load increases to approximately 500 % in this configuration, it is outweighed by the benefits. Importantly, this option is cost intensive and hence may be considered as a long term solution and especially after cost-benefit analysis. Finally, the results based on optimization of the existing design is recommended as short term solution for improvement of the BGM operation. Although the fineness achieved is still low (i.e. xP,80 = 327 µm) compared to the target (i.e. xP,80 = 125 µm), this gives additional advantage in the sense that, also better hydrocyclone performance is achieved in terms of overflow product (xP,80 = 105 µm vs. > 240 µm) , cut size (xT =133.1 µm vs. > 220 µm) and circulating load (CL =350 %). The improved overflow fineness will contribute to improved efficiency for the downstream processes.

This dissertation deals with quantitative perfusion analysis of MRI contrast-enhanced image time sequences. It focuses on two so far separately used methods -- Dynamic contrast-enhanced MRI (DCE-MRI) and Dynamic susceptibility contrast MRI (DSC-MRI). The common problem of such perfusion analyses is the unreliability of perfusion parameters estimation. This penalizes usage of these unique techniques on a regular basis. The presented methods are intended to improve these drawbacks, especially the problems with quantification in DSC in case of contrast agent extravasation and instability of the deconvolution process in DCE using advanced pharmacokinetic models. There are a few approaches in literature combining DCE and DSC to estimate new parameters of the examined tissue, namely the relaxivity of the vascular and of the interstitial space. Originally, in this scheme, the 2CXM DCE model was used. Here various models for DCE analysis are tested keeping in mind the DCE-DSC combination. The ATH model was found to perform better in this setting compared to 2CXM. Finally, the ATH model was used in alternating DCE-DSC optimization algorithm and then in a truly fully simultaneous DCE-DSC. The processing was tested using simulated and in-vivo data. According to the results, the proposed simultaneous algorithm performs better in comparison with sequential DCE-DSC, unleashing full potential of perfusion analysis using MRI.

S tím, jak se neustále vyvíjejí nové technologie pro energeticky náročná průmyslová odvětví, stávající zařízení postupně zaostávají v efektivitě a produktivitě. Tvrdá konkurence na trhu a legislativa v oblasti životního prostředí nutí tato tradiční zařízení k ukončení provozu a k odstavení. Zlepšování procesu a projekty modernizace jsou zásadní v udržování provozních výkonů těchto zařízení. Současné přístupy pro zlepšování procesů jsou hlavně: integrace procesů, optimalizace procesů a intenzifikace procesů. Obecně se v těchto oblastech využívá matematické optimalizace, zkušeností řešitele a provozní heuristiky. Tyto přístupy slouží jako základ pro zlepšování procesů. Avšak, jejich výkon lze dále zlepšit pomocí moderní výpočtové inteligence. Účelem této práce je tudíž aplikace pokročilých technik umělé inteligence a strojového učení za účelem zlepšování procesů v energeticky náročných průmyslových procesech. V této práci je využit přístup, který řeší tento problém simulací průmyslových systémů a přispívá následujícím: (i)Aplikace techniky strojového učení, která zahrnuje jednorázové učení a neuro-evoluci pro modelování a optimalizaci jednotlivých jednotek na základě dat. (ii) Aplikace redukce dimenze (např. Analýza hlavních komponent, autoendkodér) pro vícekriteriální optimalizaci procesu s více jednotkami. (iii) Návrh nového nástroje pro analýzu problematických částí systému za účelem jejich odstranění (bottleneck tree analysis – BOTA). Bylo také navrženo rozšíření nástroje, které umožňuje řešit vícerozměrné problémy pomocí přístupu založeného na datech. (iv) Prokázání účinnosti simulací Monte-Carlo, neuronové sítě a rozhodovacích stromů pro rozhodování při integraci nové technologie procesu do stávajících procesů. (v) Porovnání techniky HTM (Hierarchical Temporal Memory) a duální optimalizace s několika prediktivními nástroji pro podporu managementu provozu v reálném čase. (vi) Implementace umělé neuronové sítě v rámci rozhraní pro konvenční procesní graf (P-graf). (vii) Zdůraznění budoucnosti umělé inteligence a procesního inženýrství v biosystémech prostřednictvím komerčně založeného paradigmatu multi-omics.