1,721,413 research outputs found
Model-based optimization of the primary drying step during freeze-drying
Full text linkSince large molecules are considered the key driver for growth of the pharmaceutical industry, the focus of the pharmaceutical industry is shifting from small molecules to biopharmaceuticals: around 50% of the approved biopharmaceuticals are freeze-dried products. Therefore, freeze- drying is an important technology to stabilise biopharmaceutical drug products which are unstable in an aqueous solution. However, the freeze-drying process is an energy and time-consuming process. The use of mechanistic modelling to gather process knowledge can assist in optimisation of the process parameters during the operation of the freeze-drying process. By applying a dynamic shelf temperature and chamber pressure, which are the only controllable process variables, the processing time can be decreased by a factor 2 to 3
Model-based characterisation of twin-screw granulation system for continuous solid dosage manufacturing
No full textContinuous twin-screw granulation has received increased attention as it can be embedded in a continuous manufacturing line allowing 24/7 production capacity eliminating scale-up requirements and intermediate storage. The screws have a modular structure (interchangeable transport and kneading discs) allowing greater flexibility in equipment design. However, process knowledge should be further developed both under steady state and dynamic conditions. Mechanistic models incorporating the underlying mechanisms are therefore applied. In this study, the principle constitutive mechanisms such as aggregation and breakage are included in a population balance modelling framework. Based on an experimental inflow granule size distribution and mean residence time of the granulator, predictions of the outflow granule size distribution were made. Experimental data was used for calibrating the model for individual screw modules in the twin-screw granulator. The results showed that the successive kneading blocks lead to a granulation regime-separation inside the twin-screw granulator. The first kneading block after wetting caused an increase in the aggregation rate, which was reduced after the second kneading block. The breakage rate increased successively along the length of the granulator. Such a physical separation between the granulation regimes will be promising for future design and advanced control of the continuous granulation process
Extending the benchmark simulation model n<sup>o</sup>2 with processes for nitrous oxide production and side-stream nitrogen removal
No full textIn this work the Benchmark Simulation Model No.2 is extended with processes for nitrous oxide production and for side-stream partial nitritation/Anammox (PN/A) treatment. For these extensions the Activated Sludge Model for Greenhouse gases No.1 was used to describe the main waterline, whereas the Complete Autotrophic Nitrogen Removal (CANR) model was used to describe the side-stream (PN/A) treatment. Comprehensive simulations were performed to assess the extended model. Steady-state simulation results revealed the following: (i) the implementation of a continuous CANR side-stream reactor has increased the total nitrogen removal by 10%; (ii) reduced the aeration demand by 16% compared to the base case, and (iii) the activity of ammonia-oxidizing bacteria is most influencing nitrous oxide emissions. The extended model provides a simulation platform to generate, test and compare novel control strategies to improve operation performance and to meet the new plant performance criteria such as minimization of greenhouse gas (in particular of nitrous oxide) emissions
Optimal Design of Algae Biorefinery Processing Networks for the production of Protein, Ethanol and Biodiesel
Full text linkIn this study, optimal design of algal biorefinery using microalgae with respect to techno-economic criteria is studied. A systematic methodology using superstructure-based optimization is used to this end. A superstructure representing a wide range of technologies developed for processing microalgae to produce end products is formulated. The corresponding technical and economic data is collected and structured using a generic input-output mass balance models. An optimization problem is formulated and solved to identify the optimal designs. The effect of uncertainties inherent in economic analysis such as microalgae production cost, composition of microalgae (e.g. oil content) and biodiesel/bioethanol market prices is considered. New optimal processing paths are found with potential of producing higher amount of biodiesel. Last, the methodology is intended as decision support tool for early-stage concept screening to enhance the future development of algal biorefinery
A numerical procedure for model identifiability analysis applied to enzyme kinetics
No full textThe proper calibration of models describing enzyme kinetics can be quite challenging. In the literature, different procedures are available to calibrate these enzymatic models in an efficient way. However, in most cases the model structure is already decided on prior to the actual calibration exercise, thereby bypassing the challenging task of model structure determination and identification. Parameter identification problems can thus lead to ill-calibrated models with low predictive power and large model uncertainty. Every calibration exercise should therefore be preceded by a proper model structure evaluation by assessing the local identifiability characteristics of the parameters. Moreover, such a procedure should be generic to make sure it can be applied independent from the structure of the model.
We hereby apply a numerical identifiability approach which is based on the work of Walter and Pronzato (1997) and which can be easily set up for any type of model. In this paper the proposed approach is applied to the forward reaction rate of the enzyme kinetics proposed by Shin and Kim (1998). Structural identifiability analysis showed that no local structural model problems were occurring. In contrast, the practical identifiability analysis revealed that high values of the forward rate parameter V-f led to identifiability problems. These problems were even more pronounced at higher substrate concentrations, which illustrates the importance of a proper experimental design to avoid (practical) identifiability problems. By using the presented approach it is possible to detect potential identifiability problems and avoid pointless calibration (and experimental!) effort
Benchmarking of Control Strategies for Wastewater Treatment Plants
Full text linkWastewater treatment plants are large non-linear systems subject to large perturbations in wastewater flow rate, load and composition. Nevertheless these plants have to be operated continuously, meeting stricter and stricter regulations. Many control strategies have been proposed in the literature for improved and more efficient operation of wastewater treatment plants. Unfortunately, their evaluation and comparison – either practical or based on simulation – is difficult. This is partly due to the variability of the influent, to the complexity of the biological and biochemical phenomena and to the large range of time constants (from a few minutes to several days). The lack of standard evaluation criteria is also a tremendous disadvantage. To really enhance the acceptance of innovative control strategies, such an evaluation needs to be based on a rigorous methodology including a simulation model, plant layout, controllers, sensors, performance criteria and test procedures, i.e. a complete benchmarking protocol.
This book is a Scientific and Technical Report produced by the IWA Task Group on Benchmarking of Control Strategies for Wastewater Treatment Plants. The goal of the Task Group includes developing models and simulation tools that encompass the most typical unit processes within a wastewater treatment system (primary treatment, activated sludge, sludge treatment, etc.), as well as tools that will enable the evaluation of long-term control strategies and monitoring tasks (i.e. automatic detection of sensor and process faults). Work on these extensions has been carried out by the Task Group during the past five years, and the main results are summarized in Benchmarking of Control Strategies for Wastewater Treatment Plants. Besides a description of the final version of the already well-known Benchmark Simulation Model no. 1 (BSM1), the book includes the Benchmark Simulation Model no. 1 Long-Term (BSM1_LT) – with focus on benchmarking of process monitoring tasks – and the plant-wide Benchmark Simulation Model no. 2 (BSM2).
Flux identification methods of sedimentation
No full textAny reasonable model of sedimentation contains the nonlinear hindered-settling flux function. If one assumes ideal conditions and no compression, then there exist several theoretically possible ways of identifying a large part of the flux function from only one experiment by means of formulas derived from the theory of partial differential equations. Such identification methods, including new results on centrifugal settling, are reviewed and compared with synthetic data (simulated experiments)
Benchmarking of Control Strategies for Wastewater Treatment Plants
No full textWastewater treatment plants are large non-linear systems subject to large perturbations in wastewater flow rate, load and composition. Nevertheless these plants have to be operated continuously, meeting stricter and stricter regulations. Many control strategies have been proposed in the literature for improved and more efficient operation of wastewater treatment plants. Unfortunately, their evaluation and comparison – either practical or based on simulation – is difficult. This is partly due to the variability of the influent, to the complexity of the biological and biochemical phenomena and to the large range of time constants (from a few minutes to several days). The lack of standard evaluation criteria is also a tremendous disadvantage. To really enhance the acceptance of innovative control strategies, such an evaluation needs to be based on a rigorous methodology including a simulation model, plant layout, controllers, sensors, performance criteria and test procedures, i.e. a complete benchmarking protocol.
This book is a Scientific and Technical Report produced by the IWA Task Group on Benchmarking of Control Strategies for Wastewater Treatment Plants. The goal of the Task Group includes developing models and simulation tools that encompass the most typical unit processes within a wastewater treatment system (primary treatment, activated sludge, sludge treatment, etc.), as well as tools that will enable the evaluation of long-term control strategies and monitoring tasks (i.e. automatic detection of sensor and process faults). Work on these extensions has been carried out by the Task Group during the past five years, and the main results are summarized in Benchmarking of Control Strategies for Wastewater Treatment Plants. Besides a description of the final version of the already well-known Benchmark Simulation Model no. 1 (BSM1), the book includes the Benchmark Simulation Model no. 1 Long-Term (BSM1_LT) – with focus on benchmarking of process monitoring tasks – and the plant-wide Benchmark Simulation Model no. 2 (BSM2).
Benchmarking of Control Strategies for Wastewater Treatment Plants
No full textWastewater treatment plants are large non-linear systems subject to large perturbations in wastewater flow rate, load and composition. Nevertheless these plants have to be operated continuously, meeting stricter and stricter regulations. Many control strategies have been proposed in the literature for improved and more efficient operation of wastewater treatment plants. Unfortunately, their evaluation and comparison – either practical or based on simulation – is difficult. This is partly due to the variability of the influent, to the complexity of the biological and biochemical phenomena and to the large range of time constants (from a few minutes to several days). The lack of standard evaluation criteria is also a tremendous disadvantage. To really enhance the acceptance of innovative control strategies, such an evaluation needs to be based on a rigorous methodology including a simulation model, plant layout, controllers, sensors, performance criteria and test procedures, i.e. a complete benchmarking protocol. This book is a Scientific and Technical Report produced by the IWA Task Group on Benchmarking of Control Strategies for Wastewater Treatment Plants. The goal of the Task Group includes developing models and simulation tools that encompass the most typical unit processes within a wastewater treatment system (primary treatment, activated sludge, sludge treatment, etc.), as well as tools that will enable the evaluation of long-term control strategies and monitoring tasks (i.e. automatic detection of sensor and process faults). Work on these extensions has been carried out by the Task Group during the past five years, and the main results are summarized in Benchmarking of Control Strategies for Wastewater Treatment Plants. Besides a description of the final version of the already well-known Benchmark Simulation Model no. 1 (BSM1), the book includes the Benchmark Simulation Model no. 1 Long-Term (BSM1_LT) – with focus on benchmarking of process monitoring tasks – and the plant-wide Benchmark Simulation Model no. 2 (BSM2)
- …
