1,721,022 research outputs found
Modellazione multiscala di celle a combustibile ad ossidi solidi: dalla microstruttura alle prestazioni
No full textIn questo studio si presenta un approccio modellistico integrato per la simulazione di celle a combustibile ad ossidi solidi (SOFC). La modellazione copre in primis gli aspetti microstrutturali degli elettrodi porosi compositi costituenti la cella, le cui proprietà effettive di trasporto e reazione sono predette con la teoria di percolazione e/o con la ricostruzione numerica della microstruttura in funzione di composizione, distribuzione granulometrica delle polveri e condizioni di sinterizzazione. Le proprietà effettive costituiscono i parametri dei modelli di trasporto e reazione all'interno della cella, basati su bilanci di massa e carica, che permettono di ottenere la distribuzione delle variabili di campo e l'efficienza energetica del sistema. L'accoppiamento della modellazione microstrutturale con quella di trasporto e reazione permette di correlare i due livelli di scala cosicché i modelli tra loro integrati sono utilizzati come strumento interpretativo dei dati sperimentali e come strumento per l'ottimizzazione di prestazione e design.In this study an integrated modelling framework for the simulation of solid oxide fuel cells (SOFC) is presented. The modelling firstly covers the microstructural aspects of porous composite electrodes which constitute the cell, whose effective transport and reaction properties are predicted by means of percolation theory and/or numerical reconstruction of the microstructure as a function of composition, particle size distribution and sintering conditions. The effective properties are parameters of the models of transport and reaction within the cell, based on mass and charge conservation balances, which allow to obtain the field variables distribution and the energetic efficiency of the system. Coupling the microstructural modelling with the transport and reaction modelling enables the correlation of the two different scale levels, so that the integrated models are used as interpretative tool of experimental data as well as design tool for optimize the performance
On the effectiveness of heat-exchanger bypass control
Full text linkIn heat exchangers with bypassing, a fraction of the flowrate of one fluid (typically the one whose temperature needs to be controlled tightly) bypasses the exchanger and mixes right after the exchanger outlet with the fraction flowing through the exchanger. The advantages of this configuration are long known. Among them, the most significant is that it can improve heat-transfer control because the temperature dynamics is significantly faster than in a standard heat-exchanger configuration. Additionally, it can increase the rangeability of the process wherein the heat exchanger operates. Existing rules of thumb do not provide univocal indications for assigning the design bypass flowrate. In this study, using a simple graphical representation of steady-state heat and mass balances originally proposed for conventional heat-exchanger design, we clarify why and under which design conditions bypass control can be effective. Increased rangeability results from the fact that the heat-exchanger steady-state gain can be assigned by design when a bypass configuration is used, whereas it typically cannot in a conventional heat exchanger. The design bypass flowrate should therefore be assigned so as to make the heat exchanger operate in a region where the steady-state gain is relatively high (and constant)
Model-based monitoring of an intensified unit for continuous pharmaceutical filtration-drying
No full textActive pharmaceutical ingredient (API) separation from synthesis and crystallization
mother liquors is typically carried out in pharmaceutical manufacturing through filtration
and drying. These steps are of utmost importance, as impurities herein retained will
inevitably end up in the drug product. Recently, a novel carousel has been developed for
carrying out filtration and drying in a continuous intensified fashion. The unit represents
a step forward with respect to traditional batch filtration and drying, as continuous
operation can reduce the variability of the product quality. However, the occurrence of
faults compromising product compliance can be assessed only upon discharge of the final
cake of API crystals, when its purity can be measured. In this work, we develop a modelbased
monitoring system for the unit, based on state and parameter estimation. The
implemented monitoring system succeeds in tracking the product critical quality
attributes (CQAs), and in detecting common faults for the carousel, such as sudden
variations of the feed attributes
Optimal Indicator-Variable Approach for Trajectory Synchronization in Uneven-Length Multiphase Batch Processes
Full text linkPartial least-squares regression models assessing the end-point product quality in batch processes require that all of the measured variable trajectories across the historical batches have the same length. Most of the conventional and advanced methodologies for batch synchronization need some prior knowledge about the process to carry out one or more of the following activities: partitioning of the batches into phases, selection of an appropriate indicator variable that is then used to synchronize the batches, or selection of a reference batch to which all other batches are matched. We present an optimal indicator-variable approach for phase partitioning and trajectory synchronization in uneven-length multiphase batch processes. The main advantages are that partitioning into phases and selection of the most appropriate indicator variable within each phase are performed automatically rather than manually and are carried out simultaneously rather than disjointly based on a surrogate optimization framework that maximizes the performance of the product quality assessment model under development. Therefore, differently from conventional and advanced synchronization methodologies currently available, the proposed method is completely process-agnostic, which enhances applicability to complex batch processes. Also, in terms of computational times, it scales favorably with the calibration data set size. An industrial fed-batch process for the manufacturing of a specialty chemical and a simulated fed-batch process for the manufacturing of penicillin are used as test beds and demonstrate that the new indicator-variable approach has a superior performance than models built using other synchronization strategies
Identification of complex models of type 2 diabetes from IVGTT data by model-based design of experiments
No full textIntravenous glucose tolerance tests (IVGTTs) are typically used to assess insulin resistance and insulin secretion activities in subjects affected by type 2 diabetes by adopting minimal models. However, the amount of information that can be obtained from IVGTTs for the purpose of model identification is intrinsically related to the dynamics triggered by the intravenous glucose infusion and to the individual specificity. This paper shows how the information content of clinical data from conventional IVGTTs can be handled by model-based design of experiments (MBDoE) techniques when the goal is to estimate the set of parameters of a complex model of type 2 diabetes. MBDoE allows to analyse and improve the information content of IVGTTs by optimising the sample allocation in such a way as to decrease the degree of correlation between critical parameters. © 2013 Elsevier B.V
Data-driven tools for the optimization of a pharmaceutical process through its knowledge-driven model
No full textThe use of computationally demanding knowledge-driven models to optimize a process might encounter substantial numerical challenges. Because a model is an abstraction and approximation of the process, calculating the exact model optimum might not be necessary because its industrial implementation is bound to be an approximate one. Here we are exploring an alternative optimization route through a surrogate model. Because one of the decision variables affecting the optimization is time-varying, the Design of Dynamic Experiments is used to estimate the surrogate model. The process considered here is a freeze-drying process widely used in the pharmaceutical industry. The model used is a stochastic model describing the process in great detail. It is shown that the proposed data-driven route calculates the optimum in about 8 h, as opposed to 22 h for the knowledge-driven model, while sacrificing only < 15% in the computed value of the process performance
Backstepping methodology to troubleshoot plant-wide batch processes in data-rich industrial environments
Full text linkTroubleshooting batch processes at a plant-wide level requires first finding the unit causing the fault, and then understanding why the fault occurs in that unit. Whereas in the literature case studies discussing the latter issue abound, little attention has been given so far to the former, which is complex for several reasons: the processing units are often operated in a non-sequential way, with unusual series-parallel arrangements; holding vessels may be required to compensate for lack of production capacity, and reacting phenomena can occur in these vessels; and the evidence of batch abnormality may be available only from the end unit and at the end of the production cycle. We propose a structured methodology to assist the troubleshooting of plant-wide batch processes in data-rich environments where multivariate statistical techniques can be exploited. Namely, we first analyze the last unit wherein the fault manifests itself, and we then step back across the units through the process flow diagram (according to the manufacturing recipe) until the fault cannot be detected by the available field sensors any more. That enables us to isolate the unit wherefrom the fault originates. Interrogation of multivariate statistical models for that unit coupled to engineering judgement allow identifying the most likely root cause of the fault. We apply the proposed methodology to troubleshoot a complex industrial batch process that manufactures a specialty chemical, where productivity was originally limited by unexplained variability of the final product quality. Correction of the fault allowed for a significant increase in productivity
A Disturbance Estimation Approach for Online Model-based Redesign of Experiments in the Presence of Systematic Errors
No full textOnline Model-Based Redesign of Experiment (OMBRE) strategies represent a valuable support to the development of dynamic deterministic models, allowing for the dynamic update of the experimental conditions to yield the most informative data for the parameter identification task. However, the effectiveness of OMBRE strategies may be severely affected by the presence of systematic modelling errors. In this paper, a disturbance estimation approach is exploited within an OMBRE framework (DEOMBRE) in order to achieve a statistically satisfactory estimation of the model parameters, thus avoiding (or reducing) constraint violations even in the presence of systematic modelling errors. A case study illustrates the benefits of the new approach. © 2011 Elsevier B.V
Powder composition monitoring in continuous pharmaceutical solid-dosage form manufacturing using state estimation – Proof of concept
Full text linkIn continuous solid-dosage form manufacturing, the powder feeding system is responsible for supplying downstream the correct formulation of the drug product ingredients. The composition of the powder delivered by the feeding system is inferred from the measurements of powder mass flow from the system feeders. The mass flows are, in turn, inferred from the loss in weight measured in the feeder hoppers. Most loss-in-weight feeders post-process the mass flow signal to deliver a smoothed value to the user. However, such estimated mass flows can exhibit a low signal-to-noise ratio. As the feeders are critical elements of the control strategy of the manufacturing line, better instantaneous estimates of mass flow are desirable for improving the quality assurance. In this study, we propose a model-based approach for monitoring the composition of the powder fed to a continuous solid-dosage line. The monitoring system is based on a moving-horizon state estimator, which carries out model-based reconciliation of the feeder mass measurements, thus enabling accurate composition estimation of the powder mixture. Experimental datasets from a direct compression line are used to validate the methodology. Results demonstrate improvement with respect to current industrial solutions
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