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Proefschrift Universiteit van Amsterdam. / Auters namen op de omslag: Henk-Jan Ramaker en Eric van Sprang. Met bibliogr., lit. opg. - Met samenvatting in het Nederlands.

This thesis is concerned with sequence logic as found in industrial control systems, with the focus being on process and manufacturing control systems. At its core is the assertion that there is a need for a better approach to the development of industrial sequence logic to satisfy the life-cycle requirements, and that many of the ingredients required to deliver such an approach are now available. The needs are discussed by considering the business case for automation and deficiencies with traditional approaches. A set of requirements is then derived for an integrated development environment to address the business needs throughout the control system life-cycle. The strengths and weaknesses of relevant control system technology and standards are reviewed and their bias towards implementation described. Mathematical models, graphical methods and software tools are then assessed with respect to the requirements for an integrated development environment. A solution to the requirements, called Synect is then introduced. Synect combines a methodology using familiar graphical notations with Petri net modelling supported by a set of software tools. Its key features are justified with reference to the requirements. A set of case studies forms the basis of an evaluation against business needs by comparing the Synect methodology with current approaches. The industrial relevance and exploitation are then briefly described. The thesis ends with a review of the key conclusions along with contributions to knowledge and suggestions for further research.

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<p> A bench scale continuous settling unit was constructed and its operation compared to results of batch settling tests. The particulate solids used were polystyrene spheres with a mean diameter of 285 microns. The concentration profile within the slurry in both the batch and the continuous studies was observed using a light extinction technique.</p> <p> The results show that for the material used in this study, the solids flux limitation of the continuous settler could not be exceeded: the limiting condition in the operation was always the clarification capacity or upward velocity. The batch flux plot shows that this will be the case for any material which exhibits a flux plot that is essentially a single concave curve downwards.</p> / Thesis / Master of Engineering (MEngr)

The microbiome has become a focus of research, particularly in the field of human health and precision medicine, due to its role in human development, immunity, and nutrition. Microbiome profiling studies have become more tractable and advanced in large part thanks to advancements in metagenomics. One such study is the Black Women’s Health Study (BWHS), which aims to better understand health risks and disease development specific to Black women, who are more susceptible to certain health conditions. However, a major obstacle for reproducibility of microbiome research is the high sensitivity of microbial compositions to external factors and batch-to-batch technical variability, resulting in batch effects that often hinder analysis of factors of interest. While batch effect adjustment methods have been developed for other biomedical data, they do not appropriately account for two unique features of microbiome data: 1) its compositional nature, and 2) extreme overdispersion and zero-inflation. My dissertation addresses these challenges by evaluating and improving batch effect correction methods for microbiome data and then applies these approaches to data from BWHS. First, I evaluated ComBat-Seq, along with existing microbiome-specific tools, in removing batch effects from both simulated 16S rRNA and real-world shotgun metagenomic sequencing data while preserving effects belonging to biological factors of interest. Second, I applied ComBat-Seq in an epidemiological study in which I identified several oral health-related genera among adult Black women to be associated with the host’s geographic location in the US. Finally, I introduced an extension to ComBat-Seq that improves its performance in batch effect correction on rare taxa with outliers via imputation. I demonstrated that, by replacing zeroes with predicted non-zero read counts that follow the observed compositional structure of the data, imputation effectively reduced the number of problematic cases in which outliers were intensified after batch effect correction. Collectively, my thesis demonstrates that 1) when the specific features of microbiome data are accounted for, batch effect correction methods offer a promising solution to address batch effect in microbiome data and improve microbiome profiling studies and 2) it is important to consider social/environmental factors associated with the host’s physical location when studying the oral microbiome.

Yes / In this work, for the first time, the synthesis of benzyl acetate via the esterification of acetic acid and benzyl alcohol is investigated in the reactive distillation system using a middle vessel (MVD), inverted (IBD), and conventional batch reactive distillation columns. The measurement of the performance of these column schemes is determined in terms of profitability through minimization of the batch time for a defined separation task. The control variables (reboil ratio for MVD, IBD columns) and (reflux ratio in case of CBD column) are considered as piecewise constants over batch time. The optimization results obviously indicate that the CBD system is a more attractive process in terms of batch time reduction, and maximum achievable yearly profit as compared to the MVD, and IBD operations.

Yes / The synthesis of ethyl benzoate (EtBZ) via esterification of benzoic acid (BeZ) with ethanol in a reactive distillation is challenging due to complex thermodynamic behaviour of the chemical reaction and the difficulty of keeping the reactants together in the reaction zone (ethanol having the lowest boiling point can separate from the BeZ as the distillation proceeds) causing a significant decrease in the conversion of BeZ in a conventional reactive distillation column (batch or continuous). This might be the reason of not reporting the use of reactive distillation for EtBZ synthesis although the study of BeZ esterification reaction is available in the public literature. Our recently developed Integrated Conventional Batch Distillation (i-CBD) column offers the prospect of revisiting such reactions for the synthesis of EtBZ, which is the focus of this work. Clearly, i-CBD column outperforms the Conventional Batch Distillation (CBD) column in terms of product amount, purity and conversion of BeZ and eliminates the requirement of excess use of ethanol. For example, compared with CBD column, the i-CBD operation can yield EtBZ at a much higher purity (0.925 compared to 0.730) and can convert more benzoic acid (93.57% as opposed to only 74.38%).

Production parallel systems are space-shared and employ batch queues in which the jobs submitted to the systems are made to wait before execution. Thus, jobs submitted to parallel batch systems incur queue waiting times in addition to the execution times. Prediction of these queue waiting times is important to provide overall estimates to the users and can also help meta-schedulers make scheduling decisions. In the first part of our research, we have developed an integrated framework PQStar for identification and prediction of jobs with short queue waiting times. Analyses of the job traces of supercomputers reveal that about 56 to 99% of the jobs incur queue waiting times of less than an hour. Hence, identifying these quick starters or jobs with short queue waiting times is Essential for overall improvement on queue waiting time predictions. An important aspect of our prediction strategy for quick starters is that it considers the processor occupancy state and the queue state at the time of the job submission in addition to the job characteristics including the requested number of processors and the estimated runtime. Our experiments with different Production supercomputer job traces show that our prediction strategies can lead to correct identification of about 20% more quick starters on an average and provide tighter bounds for these jobs, and result in about 24% higher overall prediction accuracy on an average than the next best existing method. We have also developed a framework for predicting ranges of queue waiting times for other classes of jobs by employing multi-class classification on similar jobs in history. Our hierarchical prediction strategy first predicts the point wait time of a job using dynamic k- Nearest Neighbor (kNN) method. It then performs a multi-class classification using Support Vector Machines (SVMs) among all the classes of the jobs. The probabilities given by the SVM for the predicted class (obtained from the kNN), along with its neighboring classes, are used to provide a set of ranges of wait times with probabilities. Our experiments with different production supercomputer job traces show that our prediction strategies can lead to about 8% improved accuracy on an average in prediction of the non-quick starters, compared to the next best existing method. Finally, we have used these predictions and probabilities in a meta-scheduling strategy that distributes jobs to different queues/sites in a multi-queue/grid environment for minimizing wait times of the jobs. For a given target job, we first identify the queues/sites where the job can be a quick starter to get a set of candidate queues/sites for the scheduling of the job. We then compute the expected value of the predicted wait time in each of the candidate queues/sites, and schedule the job to the one with minimum expected value, for the execution of the job. We have performed experiments with different production supercomputer job traces and synthetic traces for various system sizes, partitioning schemes and different workloads. These experiments have shown that our scheduling strategy gives much improved performance when compared to the existing scheduling policies by reducing the overall average queue waiting times of the jobs by about 47% on an average.

Batch distillation with chemical reaction when takes place in the same unit is referred to as batch reactive distillation process. The combination reduces the capital and operating costs considerably. Among many different types of batch reactive distillation column configurations, (a) conventional (b) inverted (c) semi-batch columns are considered here. Three reaction schemes such as (a) esterification of methanol (b) esterification of ethanol (c) hydrolysis of methyl lactate are studied here. Four different types of dynamic optimisation problems such as (a) maximum conversion (b) maximum productivity (c) maximum profit and (d) minimum time are formulated in this work. Optimal design and or operation policies are obtained for all the reaction schemes. A detailed rigorous dynamic model consisting of mass, energy balances, chemical reaction and thermodynamic properties is considered for the process. The model was incorporated within the dynamic optimisation problems. Control Vector Parameterisation (CVP) technique was used to convert the dynamic optimisation problem into a nonlinear programming problem which was solved using efficient SQP (Successive Quadratic Programming) method available within the gPROMS (general PROcess Modelling System) software. It is observed that multi-reflux ratio or linear reflux operation always led to better performance in terms of conversion, productivity for all reaction schemes compared to that obtained using single reflux operation. Feed dilution (in the case of ethanol esterification) led to more profit even though productivity was found to be lower. This was due to reduction in feed price because of feed dilution. Semi-batch reactive distillation opertation (for ethanol esterification) led to better conversion compared to conventional batch distillation, however, the total amount of acetic acid (reactant) was greater in semi-batch operation. Optimisation of design and operation (for ethanol esterification) clearly showed that a single cloumn will not lead to profitable operation for all possible product demand profile. Also change in feed and /or product price may lead to adjust the production target to maximise the profitability. In batch distillation, total reflux operation is recommended or observed at the begining of the operation (as is the case for methnaol or ethanol esterification). However, in the case of hydrolysis, total reflux operation was obseved at the end of the operation. This was due to lactic acid (being the heaviest) was withrawn as the final bottom product.