Paul Serban Agachi

Development, calibration and evaluation of two mathematical models for pollutant transport in a small river

The present research has two main objectives (1) to build two models for concentration prediction in a stream subject to a pollutant release and (2) to investigate options for estimating the parameters of the models. The models rely on the fundamental advection-dispersion equation and were developed, calibrated and evaluated using tracer data from experiments conducted in the Murray Burn in Edinburgh, UK. During the evaluation by comparison against field data both models were able to predict the main features of the observations at the first three monitoring sites, but results at the final site were less good. These types of models rely very much on the ability to make good estimates of velocity and dispersion coefficients along the stream. Although these parameters could be estimated using tracer experiments, it would be easier if they could be estimated from other hydraulic data such as the water flow rate and the channel characteristics. For the Murray Burn such models for parameter estimation were developed in the form of non-linear relationships with flow rate. This approach could be used to calculate the parameters for other similar streams, if the coefficients in the equations were similar. Alternatively, further work would be needed to explore how these coefficients vary between streams.

Model Predictive Control of the waste water treatment plant based on the Benchmark Simulation Model No.1-BSM1

Abstract Control of the WWTP is not a trivial task sinos the unit is nonlinear, features large time constants and delays, and interaction between variables is important. Model Predictive Control algorithm is a good candidate for such demanding task. The paper presents the results for controlling the WWTP using MPC. The Benchmark Simulation Model No. 1-BSM1 has been used as a standard for performance assessment and evaluation of the control strategy. Control of the Dissolved Oxygen in the aerated reactors and nitrate level in the anoxic compartments has been performed using the MPC control strategy. Air flow rate in the aerated reactors and internal recycle flow have been chosen as manipulated variables. The obtained results show the incentives of MPC over classical PI control with respect to overshoot and time response. A combined feedback-feedforward MPC scheme is also proposed for disturbance rejection and its incentives are shown.

Techno-economical and environmental evaluations of IGCC power generation process with carbon capture and storage (CCS)

Abstract Integrated Gasification Combined Cycle (IGCC) is a power generation technology in which the solid feedstock (coal, lignite, biomass etc.) is partially oxidized with oxygen and steam to produce syngas. In a conventional IGCC design for power generation without carbon capture, the syngas is purified for dust and hydrogen sulphide removal and then sent to a Combined Cycle Gas Turbine (CCGT) for power production. Carbon capture and storage (CCS) technologies are expected to play a significant role in the coming decades for reducing the greenhouse gas emissions. IGCC is one of the power generation technologies having the highest potential to capture carbon dioxide with low penalties in term of plant energy efficiency, capital and operational costs. This paper investigates the most important techno-economical and environmental indicators (e.g. net and gross power output, ancillary power consumption, plant efficiency, specific capital cost investment, operational costs, specific carbon dioxide emissions etc.) for power generation with CCS applied to an IGCC scheme. The coal-based IGCC case study investigated in the paper produces around 400 MW net electricity with 90 % carbon capture rate. Similar power plant schemes without carbon capture step were used as references for comparison.

Optimal Process Control and Operation of an Industrial Heat Integrated Fluid Catalytic Cracking Plant Using Model Predictive Control

Abstract Nowadays, the optimal control of a heat integrated industrial plant becomes one of the most important research areas in the chemical industry. There are at least two main reasons why this topic is interesting: first, the reduction of production costs applying the heat integration techniques and second, process optimization through advanced control alternatives, when taking into account the improvement of the plant safety in operation and the increasing of the products quality. It is known that the heat integration destabilizes the whole plant, advanced control being needed to make the plant operational. Due to its complexity, the fluid catalytic cracking (FCC) process is a good candidate to apply heat integration and advanced control techniques. It is well known that the investigation of an entire FCC plant taking into account the complex dynamic behavior in conditions of heat integration has not been studied yet. In this study a real FCC plant from a Romanian refinery was used for simulation and at the same time for the implementation of a model predictive control (MPC) strategy in conditions of a previous retrofitted heat integration plant configuration. The aim of this research is to study the complex dynamic behavior of the heat integrated plant under the effect of the main disturbances and to develop an optimal advanced control scheme for the same heat integrated FCC industrial plant. The implemented MPC strategy focused on the response of the heat integrated process in terms of operation, product quality and cost reduction of the heat integrated plant. To simulate the FCC heat integrated process Aspen HySys software was used. In the simulation, the reactor-regenerator section, the main fractionator and the retrofitted heat exchanger network (used for preheating the feedstock before entering the riser) are included.

Mining of graphics for information and knowledge retrieval

Abstract The oversupply of data, information and knowledge, even after preliminary keywords and topics search, is a well-known problem in R&D activities. One of the approaches aimed at limiting the negative impact of the surplus of information is its automated intelligent preprocessing and reuse. The paper describes a method for identification of the concepts which is based on combination of subject-driven document clustering, shape analysis, trends understanding and relevant context retrieval via semantic analysis. The goal is to extract potentially interesting knowledge from a set of documents based on analysis of graphical information and next to explain the mechanism of the studied process. The proposed method is implemented in the software suite which contains source searching tool, plot comparator and semantic analyzer. The method has been applied to identify the calculation process, using channel geometry characteristics, of the longitudinal dispersion coefficients for one branch of the Somes river in Romania.

Comparison of reverse flow and counter-current reactors in the case of selective catalytic reduction of NOx

Abstract The paper is focused on the comparison between a reverse flow reactor (RFR) and a counter-current reactor (CCR) in terms of the performances that may be achieved in these kinds of reactors when selective catalytic reduction (SCR) of NO x with ammonia is carried out. In order to investigate the performances of both reactor configurations, a mathematical model based on heat and mass balances for gas and solid phase was used. The possibility of achieving auto-thermal operation, even when a gas with a low temperature is going to be fed to the reactor was investigated. The temperature profiles, the reactants conversion, as well as the response to disturbances in the feeding flow have been used as criteria for comparison. Numerical simulations have shown that the CCR model is able to provide the same results as the RFR model in terms of temperature profiles when certain values of heat transfer coefficient, switching time, flow conditions and reactor geometry are taken into consideration. As a consequence of such similar thermal behaviour, the CCR model could be applied as a limiting case of RFR operation when the fast switching of the flow direction conditions is taken into account. Nevertheless, this analogy provides a simple basis for short-cut calculations since the steady-state profile of a CCR can be computed much easier than the periodic steady-state of a RFR.

Artificial Neural Networks Modelling of PID and Model Predictive Controlled Waste Water Treatment Plant Based on the Benchmark Simulation Model No.1

Abstract The paper presents techniques for the design and training of Artificial Neural Networks (ANN) models for the dynamic simulation of the controlled Benchmark Simulation Model no. 1 (BSM1) Waste Water Treatment Plant (WWTP). The developed ANN model of the WWTP and its associated control system is used for the assessment of the plant behaviour in integrated urban waste water system simulations. Both embedded PID (Proportional-Integral-Derivative) control and Model Predictive Control (MPC) structures for the WWTP are investigated. The control of the Dissolved Oxygen (DO) mass concentration in the aerated reactors and nitrate (NO) mass concentration in the anoxic compartments are presented. The ANN based simulators reveal good accuracy for predicting important process variables and an important reduction of the simulation time, compared to the first principle WWTP simulator.

Selection of Models for Pollutant Transport in River Reaches Using Case Based Reasoning

Abstract The paper presents a case based reasoning (CBR) tool designed for the identification of crucial information for the modelling of pollutant transport in rivers. The developed CBR tool is using a case base comprising published information. This information regards pollutant transport modelling work carried out for different rivers. The models from the case base are designed for a specific river reach. For an unstudied reach it is possible to find a model for pollutant transport based on the comparison between the characteristics of that river reach with the characteristics of the already studied reaches, stored in the case base. The reaches of Somes River were compared against the reaches in the case base, and information for pollutant transport modelling was identified. The developed tool is also applicable in the case of other rivers were no detailed concentration measurements are available and the mathematical models for pollutant transport are needed.

Sensitivity study of a heat integrated FCC plant

Abstract The fluid catalytic cracking (FCC) process continues to play a key role in a refinery [1]. The FCC is one of the most energy consuming processes from the refinery, especially because of the fractionator. Therefore, the goal of increasing the efficiency and the economical benefits may be achieved through continuously improving of the energy consumption and FCC operation. The results of a previous work [2] - a case study using real data from a FCC plant presently exploited in a Romanian refinery - confirmed that it is possible to save energy from the FCC plant by adding new heat exchangers, re-piping, and improving the performance of the existing heat exchangers. The investigation of the entire heat integrated FCC plant behavior has not been studied yet. Nevertheless, this kind of studies is subjected to the high complexity of a FCC process. Moreover, the thermal integration of a process may induce more instability in its operation [1]; consequently a parametric sensitivity analysis was necessary to be used in this work in order to study the influence of different operating parameters values on the behavior of the retrofitted heat integrated design of the FCC plant. The Aspen Plus has been used to create the model of the integrated FCC plant. The simulations revealed a strong nonlinearity of the FCC process [3], affecting the products separation efficiency, and identifying the behavior of the integrated plant under the presence of different kind of disturbances.

Computational fluid dynamics applied to study the hemodynamics in sangvin vessels. Case study - the portal system.

Abstract The blood flow under physiologic conditions is an important field of study. Detection and quantification of the normal and abnormal blood flow in vessels serve as basis for diagnosis and/or surgical planning. The blood flow complex characteristics have been investigated through simulations based on mathematical models that include constitutive equations describing the hemodymanics and its relations with the deformable vessels wall. The computational techniques applied to model the blood flow in the circulatory system investigated either the velocity field or the pressure field, but not both of them in the same time, treating the vessel walls as rigid ones or considering significantly simplified or reduced geometries for the deformable wall models. The approximation of rigid-walls was made mostly due to the difficulty of solving the coupled blood flow/vessel deformation problem and was justified by the observation that, under normal conditions, wall deformability does not significantly alter the velocity field. Modeling of the three-dimensional blood flow in compliant vessels is extremely challenging for a number of additional reasons such as: geometry acquisition, accurate constitutive description of the behavior and induced movement of the tissue, inflow and outflow boundary conditions, etc. The computational fluid dynamics (CFD) technique is applyed to describe the blood flow in a segment of portal vein system. The reconstructed model of the vessels provides geometric boundaries for the CFD blood flow model. In this respect a finite difference grid is going to be generated over the finite element model geometry. Hemodymanics parameters such as velocity magnitude, pressure and wall shear stress are going to be computed.