Model-based estimation and control methods for batch cooling crystallizers

This thesis addresses the problem of online multi-resource management in embedded real-time systems. It focuses on three research questions. The first question concentrates on how to design an efficient hierarchical scheduling framework for supporting independent development and analysis of component based systems, to provide temporal isolation between components. The second question investigates how to change the mapping of resources to tasks and components during run-time efficiently and predictably, and how to analyze the latency of such a system mode change in systems comprised of several scalable components. The third question deals with the scheduling and analysis of a set of parallel-tasks with real-time constraints which require simultaneous access to several different resources. For providing temporal isolation we chose a reservation-based approach. We first focused on processor reservations, where timed events play an important role. Common examples are task deadlines, periodic release of tasks, budget replenishment and budget depletion. Efficient timer management is therefore essential. We investigated the overheads in traditional timer management techniques and presented a mechanism called Relative Timed Event Queues (RELTEQ), which provides an expressive set of primitives at a low processor and memory overhead. We then leveraged RELTEQ to create an efficient, modular and extensible design for enhancing a real-time operating system with periodic tasks, polling, idling periodic and deferrable servers, and a two-level fixed priority Hierarchical Scheduling Framework (HSF). The HSF design provides temporal isolation and supports independent development of components by separating the global and local scheduling, and allowing each server to define a dedicated scheduler. Furthermore, the design addresses the system overheads inherent to an HSF and prevents undesirable interference between components. It limits the interference of inactive servers on the system level by means of wakeup events and a combination of inactive server queues with a stopwatch queue. Our implementation is modular and requires only a few modifications of the underlying operating system. We then investigated scalable components operating in a memory-constrained system. We first showed how to reduce the memory requirements in a streaming multimedia application, based on a particular priority assignment of the different components along the processing chain. Then we investigated adapting the resource provisions to tasks during runtime, referred to as mode changes. We presented a novel mode change protocol called Swift Mode Changes, which relies on Fixed Priority with Deferred preemption Scheduling to reduce the mode change latency bound compared to existing protocols based on Fixed Priority Preemptive Scheduling. We then presented a new partitioned parallel-task scheduling algorithm called Parallel-SRP (PSRP), which generalizes MSRP for multiprocessors, and the corresponding schedulability analysis for the problem of multi-resource scheduling of parallel tasks with real-time constraints. We showed that the algorithm is deadlock-free, derived a maximum bound on blocking, and used this bound as a basis for a schedulability test. We then demonstrated how PSRP can exploit the inherent parallelism of a platform comprised of multiple heterogeneous resources. Finally, we presented Grasp, which is a visualization toolset aiming to provide insight into the behavior of complex real-time systems. Its flexible plugin infrastructure allows for easy extension with custom visualization and analysis techniques for automatic trace verification. Its capabilities include the visualization of hierarchical multiprocessor systems, including partitioned and global multiprocessor scheduling with migrating tasks and jobs, communication between jobs via shared memory and message passing, and hierarchical scheduling in combination with multiprocessor scheduling. For tracing distributed systems with asynchronous local clocks Grasp also supports the synchronization of traces from different processors during the visualization and analysis

Model based kinetics estimation for crystallization processes

Abstact onl

Model based kinetics estimation for crystallization processes

Abstact onl

Modeling local/periodic temperature variation in catalytic reactions

This paper introduces a dynamic simulation model for investigation of local and transient effects in catalytic reaction systems. More specifically, the model allows inspection of the effects of supplying thermal energy directly to the catalytic particles in stead of applying energy to the whole reactor volume. With simulation results it is shown that for a certain type of catalytic reaction system the obtainable yield of product and the selectivity of the reaction toward that product can be significantly increased when thermal energy is supplied directly to the catalyst. It is also shown that the results can be improved even further by supplying thermal energy periodically in stead of continuously

Rapid crystallization process development strategy from lab to industrial scale with PAT tools in skid configuration

Batch cooling crystallization is a commonly used separation and purification step in the pharmaceutical industry. Various properties of the crystalline product from a batch crystallizer can have a strong impact on the efficiency of downstream processes such as filtration and drying, on the formulation process and on the dissolution behaviour of the drug. Development of the crystallization processes presents a major challenge in the process development of an active pharmaceutical ingredient (API). Therefore, it is beneficial to develop a rapid crystallization process development strategy to industrial scale. In this paper we present a strategy for rapid process development and apply this strategy for androsta-1,4-diene-3,17-dione, cyclic 1742,2-dimethyltrimethylene acetal), a pharmaceutical intermediate produced by Merck Sharp and Dohme. The major advantages of the strategy are that there is no requirement of the crystallizer design modification, the calibration of the process analytical technology (PAT) tools can be performed at industrial scale, and the determination of the operating window can be done directly at the industrial scale. This strategy allows for process optimization directly at the industrial scale, thus eliminating the need for time-intensive scale-dependent study. The implementation of this strategy at industrial scale was performed with the help of PAT tools arranged in a unique skid-based configuration. The skid which contains both the concentration sensors and the crystal size distribution (CSD) sensors can be connected to the existing crystallizers, thereby avoiding the time and cost-intensive modifications in the crystallizer design. The modular nature of the skid offers opportunities to choose the PAT tools which complement the solute-solvent model system. The skid makes it possible to gather the relevant information concerning the thermodynamics and kinetics of the model system in situ during the crystallization runs at the industrial scale. A strategy for process development based on a sensor skid is beneficial for the industry as it is intrinsically rapid and can be combined with the development of control strategies which lead to consistent product qualit