Home Project-material MODELLING, SIMULATION AND SENSITIVITY ANALYSIS OF A FATTY ACID METHYL ESTER (FAME) REACTIVE DISTILLATION (RD) PROCESS USING ASPEN PLUS

MODELLING, SIMULATION AND SENSITIVITY ANALYSIS OF A FATTY ACID METHYL ESTER (FAME) REACTIVE DISTILLATION (RD) PROCESS USING ASPEN PLUS

Dept: CHEMICAL ENGINEERING File: Word(doc) Chapters: 1-5 Views: 3

Abstract

Reactive distillation, being an intensified process of combining reaction and distillation in a single vessel, is an ongoing research. This work considered the use of this novel process to investigate the esterification of a fatty acid methyl ester, an alternative fuel, biodiesel, which is a potential economic bedrock via modelling, simulation and sensitivity analysis in Aspen Plus. The selection of FAME was conducted based on the source of the oil for quality biodiesel and on its compatibility with the software; these led to the selection of oleic acid as the fatty acid of the process. A reactive distillation process for a reaction between oleic acid and methanol was then set up in the Aspen environment and tested for convergence, after a successful simulation, two operating parameters (reflux ratio and reboiler duty) were varied from 2.0-5.5 and 1350-1800 W, respectively. Afterwards, graphical representations of composition profiles, temperature profiles and sensitivities
1.0 INTRODUCTION

Modelling and simulation may enhance the insight, clarify dependencies, predict

behaviour, explore the system boundaries; however, they will not reveal knowledge that is

unknown. A model is a reflection of the experiments that have been performed and a good

trade-off between realism and simplicity (Diran, 1999)

Process engineering offers the knowledge about an application. Understanding a process is

always the basis of modelling and control. A rigorous dynamic process model should be

developed to increase the understanding about the operation fundamentals and to test the

control hypothesis. Experimental model verification is essential to be aware of all

uncertainties and peculiarities of the process (Luyben, 1996)

Generally, a model intended for a simulation study can be a type developed with the help

of simulation software. Mathematical model classifications include deterministic (input and

output variables are fixed values) or stochastic (at least one of the input or output variables

is probabilistic), static (time is not taken into account) or dynamic (time-varying

interactions among variables are taken into account). The solutions of modelling are often

referred to as simulations, that is, they simulate or reproduce the behaviour of physical

systems and processes. Typically, simulation models are stochastic and dynamic (Maria,

1997)

The art of foretelling and predicting the future with the use of computers has become

increasingly popular, as the speed and memory of the machines have increased. In addition,

the desire to understand what happens in systems in which measurements are impossible

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or impractical has brought about the development of many computational models.

Regardless of the aims of these computer models, they all suffer the same drawback:

uncertainty (Ekberg, 1999)

To further increase the thoroughness of the investigation, a computer-simulated model is

subjected to different conditions of process parameters. The response and reaction of the

model to these parameters reveal parameters upon/to which the model is independent,

unresponsive or insensitive, and those to which it is easily affected or reactive, that is,

sensitivity analysis. Attunement of the computer model to these parameters in itself is an

experiment, which helps to manifest the permissive of operating conditions applicable to

the real life version of the model

The recent shortcomings of conventional petroleum have increased the research for

alternative energy sources, which offer a lot of promise economically and otherwise.

Biodiesel is a prominent subject in this area of research, hence the reason this project

studies. Biodiesel is considered as a “direct-pour” alternative fuel to petroleum diesel, as it

requires almost no modification to most modern diesel engines. It can be produced locally

and, therefore, reduces foreign oil dependence. It has been reported that biodiesel

combustion can result in less air pollutant emissions, such as carbon monoxide, sulphur dioxide, particulate matter, hydrocarbons, but with slightly higher nitrogen oxides. Since the

feedstock of biodiesel is mostly renewable, it significantly reduces carbon dioxide emission

during its whole life cycle

Fatty acid methyl esters (FAME), valuable oleo-chemicals and main constituent of

biodiesel, can be manufactured in a continuous process using reactive distillation. (Dimian,

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2007)

Reactive distillation (RD) is the process in which chemical reaction and separation are

carried out simultaneously within a fractional distillation apparatus. It may be advantageous

for liquid-phase reaction systems when the reaction must be carried out with a large excess

of one or more of the reactants, when a reaction can be driven to completion by removal of

one or more of the products as they are formed, or when the product recovery or by-product

recycle scheme is complicated or made infeasible by azeotrope formation (Perry et al

1997).

With regards to fatty acid ester production and purification, and more specifically to largescale production of biodiesel, it would appear that reactive distillation could provide an

efficient and integrated approach to obtain the desired fatty acid esters. Biodiesel is a

renewable, clean-burning diesel replacement that is reducing U.S. dependence on foreign

petroleum, creating jobs and improving the environment. Technically, biodiesel is defined

as a fuel comprised of mono-alkyl esters of long chain fatty acids derived from vegetable

oils or animal fats, designated B100, and meeting the requirements of ASTM D 6751.

Computer simulations have become increasingly popular in many different areas over the

years, owing mainly to more effective and cheaper machines. In many cases, the trend

seems to be that computer simulations are replacing experiments, at least in areas in which

experiments are very difficult, expensive or impossible. One such area is that of attempting

to foresee what will happen in the future (Ekberg, 1999)

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1.1 Problem Statement

Industrially, some operators do not operate at optimal process conditions because they are

unaware of the dependency of the process outputs upon certain parameters. To gain insight

into the favourable conditions and to make performance predictions of industrial processes

of the subject matter to different operating conditions, the sensitivity of a simulated model

process needs to be analysed.

1.2 Aim

The aim of this research is to ascertain the behaviour of an ASPEN PLUS simulated model

of a fatty acid methyl ester reactive distillation process, when subjected to different

operating parameter conditions.

1.3 Objectives Of Study

The objectives intended to be achieved in this work include:

1. Developing the model of the process in Aspen PLUS environment,

2. Subjecting the model to different operating conditions of deciding variables, and

3. Examining, discovering and interpreting the functional response of a reactive

distillation process of a fatty acid methyl ester to these variables.

1.4 Significance of Study

The findings of this study will reveal the behaviour of the purity of a fatty acid methyl ester

towards variations in some certain operating parameters involved in reactive distillation

process. These findings will help in guiding the plant operators on how to choose the values

of the operating parameters for efficient production.

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1.6 Scope of Study

This work borders on the use of ASPEN PLUS to investigate the behaviour and

functionality of a fatty acid methyl ester reactive distillation process when product mole

fraction is the selected output variable.


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