Davide Manca

BzzOde: a new C++ class for the solution of stiff and non-stiff ordinary differential equation systems

A new code for the solution of ordinary differential equation (ODE) systems was developed in C++ language. Three main aspects were studied: robustness, efficiency and ease of use. BzzOde is a new C++ class intended to solve both stiff and non-stiff ODE problems numerically. Neither FORTRAN 77 nor Fortran 90 was adopted as the reference language. C++ was chosen in order to increase the implementation efficiency and the ease of use and consistency features of the library. Although BzzOde is intended to solve both stiff and non-stiff problems, this paper will only deal with stiff problems since they are the most interesting and commonly occurring ones in everyday chemical problem solving. Several examples taken from both the literature and real life cases, such as chemical kinetics problems, were investigated by comparing the BzzOde performances with state of the art Fortran ODE solvers. The paper describes the robustness feature and performance of BzzOde applied not only to classical problems but also to specific tests that involve medium and large eigenvalue imaginary parts, discontinuous systems and problems with constrained integration variables. Medium-large ODE systems describing real life literature problems analyze and benchmark the efficiency of the ODE solvers tested. New algorithmic techniques for identifying the discontinuity points, for working with constrained variables and for increasing the Jacobian evaluation performance of a sparse ODE system are proposed and critically examined. A detailed description for the benchmark problems and corresponding results is reported in appendixes A and B.

Infrared Thermographic Image Processing for the Operation and Control of Heterogeneous Combustion Chambers

The measurement of temperature in a combustion chamber, using conventional devices such as thermocouples, can be misleading. An infrared thermographic camera can achieve a non-intrusive measure. Having acquired a still image of, for example, a klin, it can be used to produce a map of the effective temperature of the waste bed, walls, and combustion gases. This paper describes a technique for processing an infrared image to identify what really happens within such a combustion chamber. The use of a thermographic camera, to produce a temperature map of a combustion chamber, can be helpful, particularly for control purposes. This paper addresses the criteria adopted in the selection of the thermographic system, in terms of both wavelength sensitivity and geometric location within the chamber. Moreover, a detailed description of the zonal method is reported, together with the identification procedure adopted to infer the temperature map from an infrared image. As a matter of fact, the presence of soot and fly-ash within the combustion chamber does complicate the radiative model, because a gray gas analogy must be accounted for. Soot and fly-ash give rise to a foggy and diffusive effect on the image with a consequent apparent homogeneous temperature profile. To simulate the effective radiative energy flux entering the camera lens and impinging on the CCD photoelectric cell, a raytracing technique has been developed. Each discrete area and volume, within the combustion chamber, emits a pencil of radiation, which after passing through the hot gases, reaches the CCD device. Such a light pencil is generated by the energy emitted and reflected from the discrete surfaces, plus all the energies emitted by the volumes of gas distributed along the path, minus any attenuation. The total energy balance equations, coming from the zonal method, must be coupled with the temperature-energy maps acquired by the infrared camera to identify the unknown effective temperatures. Once the temperatures of the walls and bed are known, it is possible to use them to improve the control strategy by means of a set of new measures and combustion efficiency indexes, which are usually unavailable when conventional thermocouples are adopted. Finally, a validation of the proposed procedure is presented with an online application to an incinerator for industrial solid waste. The combustion dynamics within the primary kiln is analyzed and quantified, in terms of both absolute temperatures and characteristic times.

Modeling the controlled release of microencapsulated drugs: theory and experimental validation

Abstract The release of active principles from microencapsulated drugs has been studied and treated extensively in the literature. However, only empirical or semiempirical models have been proposed. Often, such models are not able to describe correctly the articulated behavior of the release phenomenon. This paper, based on a first principles approach, defines a fully theoretical model of the release process within the human body. The key point of this work is the penetration theory that describes the experimental evidence of release dependency from square root of time. In addition, the paper deals with the observed lead-lag time characterizing the release dynamics of active principle that diffuses towards the external solution. A detailed analysis of the transport phenomena involved, focuses the attention on the diffusive mechanism, which is strictly related to the existing affinity between active principle and polymer coating. Finally, the good agreement between experimental release data, for different active principles, and corresponding simulated curves allows the proposed model to be considered of real value for predictive design purposes.

Accidents involving liquids : A step ahead in modeling pool spreading, evaporation and burning

The manuscript focuses on the modeling of industrial accidents involving liquid substances, i.e. liquid pools. The paper discusses how to improve Webbers model (1990) for evaluating the liquid pool dynamics in terms of spreading (onto land and water) and evaporation rates. In particular, our attention was devoted to the following points: friction term in presence of film boiling; evaluation of the friction velocity; determination of the wind profile index; evaluation of the conductive heat flux; the pool radius dynamics; turbulent mixing onto water; dispersion model input data. The paper presents, also, how to couple the proposed model to the pool burning dynamics. This allows simulating the burning of a spreading pool. Thanks to its prompt response in terms of CPU time, the proposed model is helpful not only under risk assessment or under emergency preparedness, but also during accident response. A comparison between experimental data and the model predictions validates the model effectiveness in simulating real accidental events.

Improved ODE integrator and mass transfer approach for simulating a cyclic adsorption process

Abstract This paper introduces two methods specifically tailored to minimise the CPU time required to simulate a Rapid Pressure Swing Adsorption (RPSA) process to Cyclic Steady State (CSS) using a Full Pellet Model (FPM) approach to mass transfer. The first technique introduces the ODE integrator BzzOde (developed in c++ ) to an existing fortran90 source code (presently using the integrator VODE) for the simulation of an adsorption process. CPU comparisons using two analytical solutions and a four-step RPSA cycle show BzzOde provides significant computational improvements over VODE. Coupled with the introduction of BzzOde is the Mass-transfer Model Switch (MMS), which automatically activates the computationally demanding FPM only after the simpler Linear Driving Force (LDF) model has established CSS. This concept provides a better estimate of the initial conditions passed to the FPM by extrapolating CSS profiles obtained with the LDF model. While significant reductions in CPU time were observed for a non-isothermal RPSA simulation employing the MMS, the initial mole fraction for the bed had a major impact on the improvements afforded with the MMS for the equivalent isothermal simulation. All numerical simulations were performed using a successive substitution approach to CSS convergence.

The Viareggio LPG railway accident: Event reconstruction and modeling

This manuscript describes in detail the LPG accident occurred in Viareggio on June 2009 and its modeling. The accident investigation highlighted the uncertainty and complexity of assessing and modeling what happened in the congested environment close to the Viareggio railway station. Nonetheless, the analysis allowed comprehending the sequence of events, the way they influenced each other, and the different possible paths/evolutions. The paper describes suitable models for the quantitative assessment of the consequences of the most probable accidental dynamics and its outcomes. The main finding is that after about 80 s from the beginning of the release the dense-gas cloud reached the surrounding houses that were destroyed successively by internal explosions. This fact has two main implications. First, it shows that the adopted modeling framework can give a correct picture of what happened in Viareggio. Second, it confirms the need to develop effective mitigation measures because, in case of this kind of accidents, there is no time to apply any protective emergency plans/actions.

Dynamic conceptual design of industrial processes

This paper focuses on chemical process design and layout optimization based on a theoretical approach that takes into account the dynamic feature of price/cost fluctuations. As originally supposed, conceptual and systematic process design consider fixed prices and costs as input data in their models. These models do not account for well-known price and cost fluctuations such as electric energy and crude oil prices. The conventional modeling approach to conceptual design can find a sub-optimal solution because of neglecting the dynamic changes of economic terms within a given time horizon. This manuscript modifies the perspective, and considers the fluctuations of prices and costs within the conceptual design activity, in order to maximize a so-called economic potential. The term fluctuation refers to the deterministic variations of prices and costs while it does not quantify the stochastic oscillations of the market. These oscillations are bound to the mood of investors and require a forecasting approach, which is typical of forms of investment such as the exchange-traded derivatives. A straightforward case study, based on an energy intensive chemical process, shows the benefits and the opportunities of this approach. The mathematical model is based on the implementation of dynamic superstructures, which call for a MINLP formulation. Finally, the manuscript presents and discusses some numerical results and the economic benefits coming from the dynamic approach to conceptual design.

Virtual Reality and Augmented-Virtual Reality as Tools to Train Industrial Operators

Abstract The need for developing an improved methodology to better train operators is crucial since their performance directly influences the process in terms of productivity, quality, profitability, stability, and controllability. Meanwhile, human machine interfaces have intensified the complexity faced by operators in modern plants, where a human error may result in significant financial and resource losses. This paper proposes the implementation and adoption of Virtual Reality (VR) and Augmented-Virtual Realty (AVR) to train operators in industrial plants. A detailed and immersive 3D model of the plant allows the operators understanding the details of both equipment and operating conditions. The complex dynamic behavior and control strategies of the process can be reproduced with a highly detailed 3D virtual environment by employing and coupling a dynamic process simulator and a dynamic real-time accident simulator. The AVR feature allows enhancing and improving the understanding and skill of field operators by letting them know the process operating conditions that dynamically change within the plant section where they work. The same can be said of process dynamics in case of abnormal and accident conditions. The positive outcome of this operator-training tool consists in increasing the reliability, cost effectiveness, environmental friendliness, and safety of the process.

Advanced Applications in Process Control and Training Needs of Field and Control Room Operators

OCCUPATIONAL APPLICATIONS Operators play a vital role in production and safety in industrial processes. Since the introduction of advanced control techniques, such as model predictive control and real-time optimization, operators’ acquisition of adequate mental models to develop complex cause-and-effect relationship explaining plant behavior has been increasingly challenged. Additionally, distinct challenges have arisen with respect to crew coordination between control room and field operators to orchestrate a coordinated flow of actions to assess situations or choose a course of action. Based on an analysis of training needs, it is argued that traditional training practice, such as the use of operator training simulators, could be advanced by using current training environments, such as virtual reality training simulators. This would allow using modern training technology and its advancements in parallel to the advancements of control techniques to support production and safety at its best. TECHNICAL ABSTRACT Background: Extensive integration of various modern methods in the process industry has changed the tasks of industrial operators. The integration of advanced technology and control algorithms lead to new challenges faced by control room and field operators, from both technical and crew-coordination complexity perspectives. From a technical perspective, couplings, dynamic effects, non-transparency, conflicting goals, comprehension of model predictive control, and real-time optimization challenge the development of an accurate mental model. From a crew-coordination complexity perspective, control room operators and field operators face the challenge to orchestrate their individual actions into a coordination flow of actions to assess a situation and solve problems. Purpose: The purpose of this article is to highlight the cognitive and teamwork requirements of operators and to note the limitations of current training practices compared to the training objectives that need to be achieved individually and as a team. Methods: Evidence is presented from instance-based learning theory and theories addressing the acquisition of mental models, instances, and skills for crew-coordination complexity; this is used to suggest that current training practices match only a subset of the challenging training objectives that are essential to use technology efficiently and safely. Results: Findings from the cognitive training need analysis are linked to training objectives and training methods based on the learning theories presented. Additionally, arguments for using different training environments (operator training simulators, virtual reality training simulators) to achieve the training objectives in an optimal way are presented. Conclusions: It is concluded that advancements in the applications of process control techniques call for a new mindset in the training of operators. Advanced training methods and environments can be one way of helping the operator to improve performance reduce errors and enhance safety.

Testing and analyzing different training methods for industrial operators: an experimental approach

1. Abstract Process industry is known for its complexity and sensitivity with critical procedures saturated with demanding human-machine interfaces that may induce human errors thus resulting in abnormal situations. Abnormal situations may lead to near misses and even to severe accidents, which can result in loss of production and even in casualties and fatalities. This paper aims at abridging the gap between the highly demanding human machine interfaces and the training methods employed in the process industry by experimentally analyzing the effectiveness of distinct training methods in a virtually simulated abnormal situation. The performance of operators is measured by means of suitable Key Performance Indicators (KPIs) applied to the specific case study. In particular, we analyze experimentally two distinct training methods based respectively on a Power Point presentation and a 3D virtual environment. The positive outcomes of this approach consist in increasing the reliability, cost effectiveness, environmental friendliness, and safety of the process. This work is the result of the interaction between chemical engineers and experimental psychologists, which may open new horizons to scientific research.