Giacomo Filippo Porzio

Process Analysis and Modelling for 2nd Generation Lignocellulosic Bioethanol Production

In the present work, the most promising processing technologies for next generation ethanol production are assessed. A literature-based comparative analysis of the technologies in terms of yield, efficiency, feedstock and level of process integration is carried out in order to identify the most interesting ones. The aim of this paper is the analysis and validation based on literature data of a process simulation performed using the software Aspen Plus. The model is intended to understand the major process steps and focuses on the main aspects from an energy engineering point of view. Moreover it provides an useful tool for preliminary analysis of different configurations. Crucial aspects include high pretreatment yield, efficient hexose and pentose fermentation, enzyme strain development and solid residue valorization for process heat and power generation. Energy and mass balances are modeled, so to allow a comparison among different technological solutions. A plant able to process 240,000 kt/y of biomass is modeled, showing a production capacity of about 40,000 kt/y of ethanol. Ethanol productivity is over 300 L/t of dry biomass, and net process energy efficiency is calculated over 35%. The model developed focuses on the main steps of the production process allowing for further development or process optimization.

Process Integration in Energy and Carbon Intensive Industries Through Exploitation of Optimization Techniques and Decision Support

Process industries show an ever-increasing interest in reducing their environmental impact and energy consumption as well as maintaining an acceptable profit. This is particularly true for industries such as the steel one, which is among the highest energy consumers worldwide. Process modelling and optimization are techniques by which this problem can be effectively addressed, particularly if the overall system is optimised as a whole. In this article we describe a model for a discrete dynamic optimization of the process gas network in an integrated steel plant. The main sub-plants are modelled in order to calculate mass and energy balances in different scenarios of operation. The scenarios are then exploited within a multi-objective optimization problem, where cost and CO2 emissions are simultaneously minimised. The optimization is carried out by exploitation of evolutionary algorithms that enable a flexible problem formulation and to effectively generate a set of different trade-off solutions. Application of the model to an industrial case study results in an interesting potential for reduction of CO2 emissions and costs. The described optimisation model is embedded in a more general software tool to help the plant managers in their daily decision-making process.

Use of Clustering and Interpolation Techniques for the Time-Efficient Simulation of Complex Models within Optimization Tasks

Several widely used model optimization techniques such as, for instance, genetic algorithms, exploit on intelligent test of different input variables configurations. Such variables are fed to an arbitrary model and their effect is evaluated in terms of the output variables, in order to identify their optimal values according to some predetermined criteria. Unfortunately some models concern real world phenomena which involve a high number of input and output variables, whose interactions are complex. Consequently the simulations can be so time consuming that their use within an optimization procedure is unaffordable. In order to overcome this criticality, reducing the simulation time required for running the model within the optimization task, a novel method based on the combination of clustering and interpolation techniques is proposed. This technique is based on the use of a set of pre-run simulations of the original model, which are firstly used to cluster the input space and to assign to each cluster a suitable output value within the output space. Subsequently, in the simulation phase, an ad-hoc interpolation is performed in order to provide the final simulation results. The proposed method has been tested on a complex model of a blast furnace within an optimization problem and has obtained good results in terms of accuracy and time-efficiency of the simulation.

Steam Gasification Process of Chlorine-rich Shredder Granules: Experiments and Flow-sheeting Modelling for Process Evaluation and Scale-up

Gasification technology is gaining more and more importance, due to its engineering property of energy conversion of feedstock material into valuable gaseous process fuel. Using waste material the gasification process appears even more interesting, mostly when an ecological drawback like the production of low-pH and chlorine-rich syngas is turned into a substantial advantage. This is given when the acid gas is used for particular applications such as steel scrap preheating and simultaneous surface cleaning before its utilisation in steel plants. In this paper a lab-scale steam gasification process for the production of a chlorine-rich gas is presented. The produced syngas shows an interesting heating value as well as adequate chlorine content for its utilisation in the mentioned application. The overall process has been evaluated by means of flow-sheeting models to assess its performances in comparison with alternative solutions. Models are intended to calculate mass and energy balances as well as to evaluate the optimum process operating conditions considering the downstream utilisation of the syngas. Results of the models are presented in comparison with experimental data. Finally an outlook is given with regard to possible model applications as guidelines for process scale-up and optimisation.

Evaluation and Monitoring of Physico-Chemical Properties of Water Streams through Unconventional Techniques

Evaluation and monitoring of physical and chemical water properties such as electrical conductivity (EC) and Langelier Saturation Index (LSI) are important in all industrial processes. Analytical representation of these water properties is useful since process modeling and simulation are exploited to investigate industrial system behavior under conditions that cannot be easily or safely tested. Common simulation softwares usually do not estimate the mentioned water properties but using literature information an estimation is possible through unconventional techniques. In particular Aspen Plus software has available calculator blocks to customize in order to represent specific features. In the paper modelling of FORTRAN based calculator blocks are described, which have been developed using literature information to calculate electrical conductivity and Langelier Saturation Index in Aspen Plus software.

A Software Tool for Comparing the Economic Value of Different Scrap Mixes in Steel Production

The electric steel making cycle exploits steel scrap as primary raw material. Many different types of steel scrap are used, which differ in their contents of iron and other components (e.g. Zn coating, plastics, etc.). Depending on the kind of scrap, some pretreatment steps are required, which increase the actual costs of this material, but some valuable by products could also be extracted through this pre-treatment. Moreover, depending on the steel grade to be produced, some kinds of steel scraps can be more suitable as they convey also very costly micro-alloying elements which must be added in order to provide the steel with suitable properties. Therefore the real economic value of each kind of scrap is not always correctly estimated, as it depends on the steel to produce. In the paper a tool is presented, which supports an improved exploitation of the different kinds of steel scrap, in order to find the optimal scrap mix for each steel grade. This tool estimates and compares the steel total cost achieved by mixing different types of steel scrap and considering also the cost of energy and other raw materials.

A CO2-Management Tool for Integrated Steelworks

The present paper describes an holistic CO2-monitoring system for an integrated steel-making plant. Firstly, the implementation of a centralised Database in the steelwork, supported by a dedicated server, was required as a preparatory step to collect data with regard to the main energy and Carbon containing flows. The implementation of a CO2-monitoring system was necessary in order to measure and account the emissions. The holistic model, validated with real operating data, should be able to monitor and to control the CO2 outlet and is a valid tool to reduce such emissions through the management and optimization of the relevant flows.

Process Integration Analysis for Innovative Environmentally Friendly Recovery and Pre-Treatment of Steel Scrap

The use of zinc-coated steel (e.g. galvanized steel) in melting cycles based on Electric Arc Furnaces can increase the production of harmful dust and hazardous air emissions. A process to simultane ...