A Tabu search-based algorithm for mixed-integer nonlinear problems and its application to integrated process and control system design

The current model of the full-scale wastewater treatment plant (WWTP) model in Eindhoven uses a state-of-the-art model for the biological processes (ASM2d) and is calibrated for C- and N- removal in dry weather. However, for the ‘Kallisto’ project, which is an innovation programme aiming at a smart improvement of the surface water quality of the river Dommel by applying cost effective integrated system measures, the WWTP model needs to be improved to predict the WWTP performance under all conditions foreseen in the scenarios (e.g. storm events). A project approach was developed with parallel improvements in the different submodels, based on the interaction between submodels and the availability of several on-line sensors in influent, in-process and effluent. This is in contrast to most WWTP modelling studies, where focus is only on one submodel. It should lead to a well-balanced dynamic model that is able to predict WWTP behaviour under various conditions and that will be included in the integrated model, which will serve as an important decision support tool.

Engineering activities have in some sense reached a mature level. It is, however, well recognized that the results have not satisfied the corporate strategy that was determined in advance. This is probably due to the lack of another context for reflecting on the corporate strategy in engineering activities, and this may lead to failure in the competitive global market. The present work intends to develop a conceptual framework for engineering activities, in particular, focusing on the process system synthesis and design that are most influential to the other activities and congruent with a corporate strategy. The new context for the process system synthesis and design emphasizes on value-added activities. The discussions are based on the well-known concept of Michael Porter's value chain and on the extensive application of Bellman's “the principle of optimality” in a modified form. Despite the need for ongoing strategic corporative operations to be successful, these two concepts are not combined in an explicit way. The author proposes a conceptual framework for process system synthesis and design by combining the value chain concept with the modified form of “the principle of optimality” to satisfy multiple objectives. There are two sequential problems: the first is to maximize the monetary value added, and the second is to have the Pareto optimum or compromised solutions. Both are discussed, and an illustrative application is described.

Versal matrix families, normal forms and higher order bifurcations in dynamic chemical systems

The problem of integrated design and control optimization of process plants is discussed in this paper. We consider it as a nonlinear programming problem subject to differential-algebraic constraints. This class of problems is frequently multimodal and “costly” (i.e., computationally expensive to evaluate). Thus, on the one hand, local optimization techniques usually fail to locate the global solution, and, on the second hand, most global optimization methods require many simulations of the model, resulting in unaffordable computation times. As an alternative, one may consider global optimization methods which employ surrogate-based approaches to reduce computation times and which require no knowledge of the underlying problem structure. A challenging wastewater treatment plant (WWTP) benchmark model1 is used here to evaluate the performance of these techniques. Numerical experiments with different optimization solvers indicate that the proposed benchmark optimization problem is indeed multimodal, and that via global optimization we can achieve an improvement of the controllers' performance compared to the best tuned controllers' settings available in the literature. Moreover, these results show that surrogate-based methods may reduce computation times while ensuring convergence to the best known solutions.

Integrated Process and Controller Design Software Tool – ProCACD

System or process identification is a mathematical modeling of systems (processes) from test or experimental data. Process models obtained from identification process can be used for operator training simulator, analysis and design of safety systems, and design of process and control systems. This paper presents the Linear Parameter Varying (LPV) model identification for Industrial boiler furnace. LPV model is the development of linear time invariant models of different operating conditions along the overall operating trajectory and interpolation of linear models. The LPV model is adopted by considering the fact that boiler furnace in the thermal power plant has several operating conditions. By assuming that on every operating condition there are parameters changes, the LPV model is suitable for covering all operating conditions. The boiler furnace is modeled as LPV systems with Linear transfer function model structure. Identification algorithm used in the identification process is Prediction error method. Data needed for identification is taken from first principle model of the process with sampling time of 1 second. The identification result is simulated and validated with the measured data. The simulation result shows better accuracy for Linear Parameter Varying model.

A computer aided engineering system for development of catalytic processes

Developing an evolving multi-layer perceptron network by genetic algorithm to predict full-scale ‎municipal ‎wastewater treatment plant effluent

Challenges in the design of formulated products: multiscale process and product design

Although induced gas flotation is routinely practiced on fixed platforms, there are special challenges for practicing this technology on deep water platforms. This paper presents an overview of the physical and chemical principals of how induced gas flotation actually works, reviews the special challenges involved in applying induced gas flotation technology on a floating platform, and outlines the process and vessel design requirements for the effective use of compact induced gas flotation on a deep water platform. The challenges for induced gas flotation on a floating platform include designing compact systems that minimize space and weight requirements, dealing with water that may contain hydrate inhibitors such as methanol, cleaning water with very small (and relatively stable) oil droplet size distributions, cleaning water below the Wax Appearance Temperature, and designing compact flotation cells that are tolerant of slosh-motion. The negative impact of process recycle streams on flotation will be illustrated. The successful practice of compact induced gas flotation on a deep water platform requires a combination of good overall process design, an understanding of the water chemistry involved, and well designed equipment. An example is given to illustrate how process design considerations can affect the performance of flotation as a water cleaning technology. Flotation Mechanisms There are three mechanisms by which oily contaminants are removed by induced gas flotation. These mechanisms operate singly or in combination depending upon the specific characteristics of the produced water and the level of attraction and wetting between the gas bubbles and the oily contaminants. The mechanisms are as follows:Oil coats the rising gas bubbles. This mechanism is operable when the contact angle between the oil and the gas bubble is low (wetting is high).Oil droplets and oily contaminants stick to a gas bubble and rise with it to the surface. This mechanism is operable at moderately low contact angles (modest attraction of oil to gas bubble) and is most efficient when contaminants and gas bubbles are of similar size.Oil droplets and oily contaminants are dragged behind in the wake of a rising gas bubble to the water's surface. This is the weakest interactive mechanism and does not require a low contact angle. Some authors believe that the third mechanism, although being the weakest, is dominant in most oilfield flotation systems.1,2 Mechanical Requirements for Efficient Flotation For all of the listed flotation mechanisms, efficiency is enhanced by maximizing the number of interactions between the contaminants and the gas bubbles. Interactions are maximized by the following:Uniform distribution of oily water throughout the flotation cellUniform distribution of gas bubbles throughout the flotation cellMinimizing the size of the gas bubblesMaximizing the size of the contaminants to be removedMaximizing the tendency of the contaminants to remain in contact with rising gas bubbles Vessel Hydraulics. The first points are related to flotation cell hydraulics.

The process design confronts chemical engineers with many challenges. These days they are predominantly related to customer requirements regarding project delivery time and cost. It forces us to apply the appropriate design philosophy. Currently, many countries are implementing a design process system called Building Information Modeling (BIM). According to the BIM methodology, object design should take into account 2D documentation, 3D models and the appropriate way to manage and share the design data. The BIM methodology also constitutes a challenge for high education universities that educate process and chemical engineers, since equipment or process design has so far been limited to creating 2D documentation without being able to manage and share it with other branches. Taking BIM into account, it is therefore advisable to introduce the ability to create 3D models for the equipment and the entire installations as well as to emphasize the management of design data. The chapter presents the management of design data introduced at the Faculty of Chemical Technology of the Poznan University of Technology as part of the student design classes in chemical and process engineering. Within this framework, the current design method was complemented by the creation of intelligent P&ID (2D) schematics, 3D models and process data management (1D). Data management is connected with the proper configuration of process data, the introduction of design progress control (statuses), and the creation of data sheets for each designed equipment. The chapter also presents the basis for the design as well as information about BIM and its current implementation in Poland.

Control System Design in Distillation Processes and its Dependence of the Original Process Design

A reliable model for wastewater treatment plant is essential in providing a tool for predicting its performance and to form a basis for controlling the operation of the process. This would minimize the operation costs and assess the stability of environmental balance. For the multi-variable, uncertainty, non-linear characteristics of the wastewater treatment system, an artificial fish school neural network prediction model is established standing on actual operation data in the wastewater treatment system. The model overcomes several disadvantages of the conventional BP neural network. The results of model calculation show that the predicted value can better match measured value, played an effect on simulating and predicting and be able to optimize the operation status. The establishment of the predicting model provides a simple and practical way for the operation and management in wastewater treatment plant, and has good research and engineering practical value.

Business process design is an integral part of e-business engineering. Given that e-business models usually involve a wide range of business processes across different business functions with complex activities, events, and documents, process design for e-business is a very challenging task. Although various process reference models (PRMs) have been developed to provide guidelines for process design, research on leveraging multiple PRMs to support process design for e-business has been scant. In this paper, we demonstrate that the diverse process design requirements in e-business are best satisfied by utilizing multiple PRMs via a case study. Then, we propose a collaborative approach grounded in knowledge management theory to integrating multiple process reference models to better support process design in e-business. We equip the integrated process repository with a set of novel features based on Web 2.0 technologies to enhance its utility, efficiency, and quality for process design support. A prototype system is developed and user experiments are conducted to evaluate the system.

Successful modeling of wastewater treatment plant (WWTP) processes requires an accurate description of the plant hydraulics. Common methods such as tracer experiments are difficult and costly and thus have limited applicability in practice; engineers are often forced to rely on their experience only. An implementation of grammar-based genetic programming with an encoding to represent hydraulic reactor models as program trees should fill this gap: The encoding enables the algorithm to construct arbitrary reactor models compatible with common software used for WWTP modeling by linking building blocks, such as continuous stirred-tank reactors. Discharge measurements and influent and effluent concentrations are the only required inputs. As shown in a synthetic example, the technique can be used to identify a set of reactor models that perform equally well. Instead of being guided by experience, the most suitable model can now be chosen by the engineer from the set. In a second example, temperature measurements at the influent and effluent of a primary clarifier are used to generate a reactor model. A virtual tracer experiment performed on the reactor model has good agreement with a tracer experiment performed on-site.