Nor Alafiza Yunus, Zainuddin Abd. Manan, Haslenda Hashim and Rafiqul Gani. BY: NOR ALAFIZA YUNUS 5th PSE ASIA, July 25-28, 2010 Singapore

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1 Nor Alafiza Yunus, Zainuddin Abd. Manan, Haslenda Hashim and Rafiqul Gani BY: NOR ALAFIZA YUNUS 1

2 Outline Introduction Motivation Objective Methodology Results Future work 2/21

3 Introduction Chemical Product Design Structure of molecules / process flow sheets Specify the structures FA: Forward approach Determine the structures that match the target Use property or behavior models RA: Reverse approach Specify the properties Set of target (desired) properties 3/21

4 Introduction Layer 1 Layer 2 Layer 3 Target Layer 1: Start searching at bigger space Layer 2: Reduce searching space when a constraint was introduce eliminate unwanted candidates Layer 3: Further reduce searching space when more constraints were introduce Target area: Finally, the right candidate was able to find at a small target area 4/21

5 Motivation i Gasoline Shortage of fossil supply Emit large amount of CO2 Gasoline Bio- fuel Prolong the gasoline supply & Reduce CO2 emission i Method of blending Computer aided method GAMS & ICAS software 5/21

6 Objective To find a set of feasible blend of gasoline and bio-fuel which are could reduce fossil fuel consumption using a systematic computer aided approach 6/21

7 Methodology Step 1 Step 2 Identify target properties and target values Identify properties model Step 3 Step 4 Step 5 Identify the possible blend mixture Generate the possible blend candidates Validate the model 7/21

8 Methodology step Task Method & tools Output 1 Identify the important target Literature (journals) property p Blending gguideline Set the target value for each target property Literature (journals), Blending regulation Existing gproduct List of target properties List of constraints 2 Identify pure and mixture property model Literature, calculated directly from chemical structure Pure property models Mixture property models 3 Identify the feasible mixture ICAS List of feasible blend compositions 4 Generate the possible mixture candidates GAMS List of several possible mixture candidates 5 Model validation Experiment Experimental data ICAS: Integrated Computer Aided System 8/21

9 Methodology Step 1 Identify target properties and target values Step 2 Identify properties model Target Property value Step 3 Identify the possible blend mixture Heating Value > 35 MJ/kg Step 4 Generate the possible blend candidates Step 5 Validate the model Octane number Density > kg/m 3 Kinematic viscosity < 2.41 mm 2 /s 9/21

10 Methodology Step 1 Identify target properties and target values Step 2 Identify properties model Property Model Step 3 Identify the possible blend mixture Step 4 Generate the possible blend candidates Heating Value Octane number HV mix = x i HV i ON = x i ON i Step 5 Validate the model Density mix xi i 1 Kinematic viscosity mix exp i ln i mix 10/21

11 Methodology Step 1 Identify target properties and target values Step 2 Identify properties model Step 3 Identify the possible blend mixture Step 4 Generate the possible blend candidates PT-flash (multiphase) calculation Thermodynamic model Soave-Redlich-Kwong Step 5 Validate the model 11/21

12 Methodology Step 1 Identify target properties and target values Step 2 Identify properties model Step 3 Identify the possible blend mixture Step 4 Generate the possible blend candidates Step 5 Validate the model 12/21

13 Methodology Step 1 Identify target properties and target values Step 2 Identify properties model Step 3 Identify the possible blend mixture Step 4 Generate the possible blend candidates Step 5 Validate the model 13/21

14 Methodology Step 1 Identify target properties and target values Using GAMS (General Step 2 Algebraic Modeling System) Identify properties model Property constraint: Step 3 Identify the possible HV = x i HV i blend mixture ON = x i ON i Step 4 Generate the possible mix xi i blend candidates 1 mix exp i ln i mix Step 5 Validate the model Volume constraint V gasoline V ethanol 0.o5 14/21

15 Methodology Step 1 Identify target properties and target values Step 2 Target ρ ν HHV Wt % Identify properties model ON Properties (kg/m 3 ) (mm 2 /s) (KJ/kg) O 2 Step 3 Identify the possible blend mixture Step 4 Generate the possible blend candidates Gasoline Ethanol Step 5 Validate the model Butanol MTHF /21

16 Methodology Step 1 Identify target properties and target values Step 2 Identify properties model Step 3 Identify the possible blend mixture Step 4 Generate the possible blend candidates Future work Step 5 Validate the model 16/21

17 Results Composition Mix 1 Mix2 Mix3 Mix4 Mix5 Mix6 Gasoline Ethanol Butanol MTHF Property HV Density Viscosity ON /21

18 Results 100 vo olume perce ent (%) gasoline ethanol butanol MTHF All candidates consist of butanol Butanol is most favorable component due to attractive characteristics It has higher energy content which is close to gasoline energy content, less prone to water contamination and less corrosive 0 mix1 mix2 mix3 mix4 mix5 mix6 18/21

19 Conclusion A systematic computer aided technique is a resources efficient technique which is suitable to find a set of target candidates Property model availability is one of the challenges in chemical product design 19/21

20 Future work Including emission factor to produce a green fuel Model validation through h a series of experimental work 20/21

21 Ak Acknowledgment ld CAPEC, Technical University of Denmark, Denmark Universiti iti Teknologi Malaysia, Malaysia. 21/21

22 THANK YOU Q&A session 5th PSE ASIA, July 25 28, 2010 Singapore 22