Jan Schöneberger

Optimum experimental design for key performance indicators

Abstract In this paper the methods of experimental design are used to minimize the uncertainty of the prediction of specific process output quantities, the so called key performance indicators. This is achieved by experimental design for constrained parameter estimation problems. We formulate these problems and apply our methods to an example from chemical reaction kinetics.

Improving the efficiency of membrane bioreactors by a novel model-based control of membrane filtration

Abstract In this work, a new model-based control strategy for membrane separation is presented which is based on an automated recognition of current dominant filtration mechanisms during the operation. For this purpose, a model-based optimization framework is proposed which includes parameter identifiability and estimation, as well as an enhanced model discrimination step. Based on the developed approach, it is now possible to identify time points, i.e., time intervals where a certain model is valid or more appropriate. Thus, suitable control actions can be carried out in order to increase the permeability respective to each mechanism improving the filtration performance in membrane bioreactors (MBR). The validation of the novel approach is demonstrated using experimental data from a test cell as well as from an MBR pilot plant.

An efficient approach to robust simulation of claus processes in coking plants

Abstract Claus Combustion is a significant process unit in coking plants. Its main purpose is the destruction of gaseous contaminants such as H 2 S combined with the recovery of sulphur. However, since the feed flow contains much more components, it implies a complex gas reaction process, which can be divided into two parts, the furnace and the waste heat boiler, where additionally the condensation of sulphur takes place. All partial reactions occur with very different velocities and thus a complex kinetic model, involving all reactions is required. This leads to a stiff system for simulation tasks, which causes lacks of robustness concerning convergence properties. On the other hand, simulation robustness is absolutely necessary, since this process is linked to other process units in the entire coking plant. In this work, novel numerical approaches are proposed in order to assure convergence and robustness allowing flexibility for any changes of boundary conditions. For the furnace, modelled as CSTR, mainly the self-generation of initial values and the prevention of singularities in the jacobian matrices leads to robustness concerning convergence. For the waste heat reboiler, modelled as a PFR, discretisation by orthogonal collocation along the tubes including a step size control guarantees convergence. Since condensation of certain components may occur, flexibility for model switching is integrated in the step size control algorithm.

Process development and catalyst testing under industrial conditions

The development of new processes or modifications of existing industrial processes often leads to acceptance issues, because not all real conditions can be reproduced in non industrial facilities. The investigations under ideal conditions are mostly indispensable for scientific tasks but lead to risks resulting from transferring university results to industry. In this article, a solution to this problem is presented combining the experimental work in university facilities with the needs of industrial plant employers. A tiered approach using preliminary scientific experiments without impurities from lab to miniplant scale followed by a bypass operation with the real industrial plant combines the advantages of the both sides. In line with this approach, intensive theoretical and experimental studies were carried out in the lab of the chair “Process Dynamics and Operation” of the “Technische Universtität Berlin” for the development of a new emission-free sulfuric acid process. In a further step, a mobile, modular, and fully automated experimental set-up is built and shipped to the industrial partner, where it is operated in bypass to the industrial sulfuric acid plant. Main objectives are to obtain important insights regarding long-term stability and interaction of secondary components. The application of this approach in a real case study shows that a very fast and cost effective process development can be realized with the minimum on risk. In this work, the very successful development of the emission-free sulfuric acid process is presented. Deep information of the reaction mechanism of the sulfur dioxide hydrogenation and side reactions was determined. The results presented in this article allow the development of optimal operational strategies for the whole sulfuric acid plant, which give a completely new perspective to the established process.

Design and modeling of a new periodical-steady state process for the oxidation of sulfur dioxide in the context of an emission free sulfuric acid plant

The oxidation of sulfur dioxide over vanadium pentoxide catalysts represents a basic step in the sulfuric acid production process. In conventional sulfuric acid plants the SO2 oxidation represents the limiting step with respect to the SO2 emissions. Due to the fact that the SO2 oxidation is an equilibrium reaction, sulfuric acid plants always have SO2 emissions. In this work, a new process concept is presented, which uses the transient behaviour of the reaction in two reactors operating under unsteady conditions (Saturated Metal Phase reactor). Besides several advantages, which can increase the efficiency of the whole sulfuric acid process drastically, the SMP Reactor is a key component for an efficient operation of a sulfuric acid plant which reduces the emissions down to zero while keeping the necessary conditions for the hydrogenation unit installed downstream. For this purpose, a mathematical model is used, which describes the dynamic effects of the SO2 oxidation. The model has been experimentally verified in a Miniplant, which works with commercial catalyst pellets.

An Efficient Discretization Approach for Partial Differential Equations describing Chemical Reaction Systems

In this work, an efficient solution approach based on the orthogonal collocation on finite elements is proposed for PDE-Systems describing chemical reaction systems. For this purpose, three discretization methods are compared to each other in terms of convergence, accuracy, and computation time. First, the simplest and most applied discretization method is the method of lines (ML). Here, the differential terms in the equation system are replaced by linear difference approximations. The second one is the multiple shooting (MS), which makes use of the boundary conditions, and thus, the PDE is reformulated to a root finding problem on ODE. Finally, the orthogonal collocation (OC) is a Runge-Kutta type discretization method that leads to the highest possible error order by collocating the discrete points at their optimal positions. These three approaches are tested for different numbers of discrete points on a PDE of the type which results from modelling fixed bed reactors (FBR). A test system with an existing analytical solution was chosen for an impartial comparison. In addition, two further case studies are considered to point out the advantages of the proposed discretization approach.

Sequential Flowsheet Optimization: Maximizing the Exergy Efficiency of a High-Pressure Water Scrubbing Process for Biogas Upgrade

Abstract Biogas is an important renewable energy source and potential raw material for the chemical industry. Its utilization frequently requires a treatment and/or upgrade step. The aim here is to maximize the exergy efficiency of a high-pressure water scrubbing process for upgrading biogas into biomethane by coupling a sequential modular simulation flowsheet with different optimization algorithms. By setting adequate operating pressures, and reducing cycle water and stripping air flowrates, an exergy efficiency of 92.4% is reached.

Know-how Protection and Software Architectures in Industry 4.0

Abstract In process design and development, engineers use MS-Excel and process simulators to create the engineering documents like heat and mass balances, process flow diagrams, equipment specifications, and data sheets. Manufacturers typically use their own programs for the design of the equipment. Starting with the basic design, asset management systems network and coordinate all the crafts involved in the planning and operation of a plant across sites and across the entire life cycle of the plant. In process control, real-time optimization (RTO) can be employed to determine the optimum control set points for current operating conditions and constraints. Especially for complex processes, a dynamic model of the process should be developed so that the control system can be properly designed. This paper takes the process simulator’s perspective. It builds on previous work by (Fricke and Schoneberger, 2015) about interfaces in Industry 4.0 (technical aspects) and enhances it by an analysis of the business value that players in process engineering add through their activities and shows how to protect know-how in process engineering (commercial aspects). The Process Simulation Cup example (Chemstations, 2016a) shows how software architecture aligns the technical and the commercial aspects.

Solving Dynamic Constraint Trajectory Optimization Problems by Applying the Concept of Pareto Frontiers

Abstract Dynamic constraint trajectory optimization problems (DCTOP) from process industry are hard to define from the practitioner’s view point and hard to solve from an algorithmic view point. Furthermore, when a solution is found it is not easy to understand it and thus it’s acceptance in praxis is suffering. In this paper an approach is presented to overcome these difficulties by transferring the single objective DCTOP into a multi objective problem. The approach is presented using the example of a typical DCTOP, the minimization of changeover times in a multipurpose plant with limited cooling capacities in the condensers of the distillation columns.

A Novel Approach to Mechanism Recognition in Escherichia Coli Fed-Batch Fermentations

Abstract In this work, a novel systematic approach to achieve an efficient mechanistic modeling and simulation of fed-batch fermentations is presented. In order to show the efficiency of the developed simulation framework, data of Escherichia coli fed-batch fermentations are used. Fermentation processes are characterized by its dynamic behavior described by parameters such as growth rate, substrate concentration and cellular metabolic activity. Although there are models able to describe individual fed-batch fermentations, they become unreliable when fitted to new fermentations. To overcome this drawback, in this work different models are used at different optimal time points enabling not only a better description of the process, but also a better understanding of non measurable characteristics. By these means, three models compete in different intervals of the process. The candidate models are: an Overflow metabolism model (OF), a Citric Acid Cycle model (CAC) and a Survival or Maintenance model (M). Using an adequate model sequence, acetate formation, substrate consumption and cell growth are predicted with high accuracy. Moreover, the data needed to fit the models are reduced and a standardization of the model to be applied in different process states is enabled. Besides, with the development of a robust and effective model, the possibility of an online implementation for monitoring and control of the fermentation is exhibited. The results show that an efficient process monitoring based on the Dissolved Oxygen Tension and the Mechanistic Recognition is only limited by the convergence velocity of the algorithm.