has been relegated to only special applications due to high‐equipment capital cost required. Besides that, conceptual development of extraction processes for natural oils, fats, cosmetic, and pharmaceuticals based on supercritical fluid technology is hindered by the lack of suitable design tools and reliable thermodynamic data and models at high pressure. Optimization of SFE processes involves a search for the optimum conditions above the critical point that is in a narrow limit and needs special care. Process simulation is used for the design, development, analysis, and optimization of technical processes and is mainly applied to chemical plants and chemical processes. Integration of optimization techniques into simulation practice, specifically into commercial software, has become nearly ubiquitous, as most discrete‐event simulation packages now include some form of optimization routines. Even though modeling, simulation, and optimization tools have been widely used for design of chemical processes, their application has been very limited in vegetable oil processing particularly at supercritical conditions. In line with this limitation, there is a dearth need for literature on this topic. So far there has been no book written on modeling, simulation optimization of SFE processes in the market.
This book provides a complete guideline on tools and techniques for modeling of SFE as well as SCFE processes and phenomena and provides details for both SFE and SCFE from managing the experiments to modeling and simulation optimization. The book also includes the fundamentals of SFE as well as the necessary experimental techniques to validate the models.
The simulation optimization section includes the use of process simulators, conventional optimization techniques, and state‐of‐the‐art genetic algorithm methods. Numerous practical examples and case studies on the application of the modeling and optimization techniques on the SFE processes are also provided. Detailed thermodynamic modeling with and without cosolvent and nonequilibrium system modeling is another feature of the book.
The book consists of seven chapters. Chapter 1 presents an overview of the field of supercritical and subcritical fluid extraction (SSFE) and their importance to food, cosmetic and pharmaceutical industries. Chapter 2 describes the concepts and methodologies for modeling, simulation, and optimization. It presents conservation laws related to SFE traditional first principle modeling and optimization techniques, as well as advanced artificial intelligence (AI) techniques such as genetic algorithm, fuzzy logic, and artificial neural network. The characteristics and physical properties of palm oil as the most referred solute in the book, and descriptions of some existing palm oil industrial processes are presented in Chapter 3. In Chapter 4, the first principle methodology is applied for modeling of properties of palm oil components, mixtures, and for the SFE of palm oil components. Modeling applications involving advanced techniques such as AI, ANN, and fuzzy logics and ANFIS are discussed in Chapter 5. Next, Chapter 6 describes experimental design concepts and procedures as well as statistical optimization techniques involving SSFE processes. Finally, optimization of SSFE using first principle modeling and other advanced techniques are presented in Chapter 7. The colored version of few figures from this chapter can be viewed on the product's page of the following website, https://www.wiley.com
Zainuddin Abdul Manan, Gholamreza Zahedi,
School of Chemical and Energy Engineering,
Faculty of Engineering, Universiti Teknologi Malaysia,
UTM Johor Bahru 81310
Johor Malaysia
Ana Najwa Mustapa
Universiti Teknologi MARA
Nomenclature
SymbolDefinitionAAD:Average Absolute DeviationANFIS:Adaptive Neuro Fuzzy Inference SystemANN:Artificial Neural NetworkBi:Biot number, (kf Rp)/DsC (kg/m3):Oil concentration in the supercritical fluid phase
:Oil concentration in the supercritical phaseCOG:Centre of Gravity:Oil concentration at the surface of the vetiver particleDext (m):Diameter of extraction column, , :Axial dispersion coefficient, Molecular diffusion coefficient, Diffusivity of oil in the vetiver particleF:Percent of extractFIS:Fuzzy Inference SystemFPM:First Principle ModelGA:Genetic AlgorithmGB:Gray BoxK:Extract equilibrium constant between solid and fluid phase (‐)k:Equilibrium constant:Mass transfer coefficientL(m):Length of extractorMLP:Multilayer Perceptronn0 (kmol):Initial mole of solute in the bedNF:Neuro‐FuzzyOECs:Overall Extraction CurvesP (MPa):PressurePDE:Partial differential equationPeb, Pep:Peclet number for the bed, (L ν)/Dl, Peclet number for the vetiver particle, (Rp ν)/DsQ:Degree of MembershipQ :Flow rate of supercritical fluid, (νAερf)q (kg/m3):Oil concentration in the solid phaseRe:Reynolds numberRMSE:Root Mean Square ErrorRp(m):Vetiver particle radiusr (m):Axial coordinate in the vetiver particleSFE:Supercritical Fluid ExtractionSc:Schmidt number, μf/(ρf Dm)Sh:Sherwood number, (2Rp kf)/DmT:Temperature (K)t:Time (s)V (m/s):Velocity of the fluidWB:White Boxx(m):Distance of a point in bed from place of input fluidxo:Initial mass fraction of extractable oil in solid phasez:Dimensionless axial coordinate along the bed, x/LSubscripta:Apparentb:Bedc:Criticalext:Fluidi:Inter phasep:Particles:Surface of particle0:At time zeroGreek Letter:Supercritical fluid viscosityμ:Membership functionρ:Dimensionless radial coordinate in the vetiver particle, r/Rpρ (kg/m3):Density:Supercritical fluid densityε:Void fraction of packed bed:Interstitial fluid velocityτ:Dimensionless time, (t ν)/L:Rate of increase of mass per unit volume−(∇. ρv):Net rate of mass addition per unit volume by convectionρv:Mass flux(∇. ρv):Net rate of mass efflux per unit volume:Mass per unit volume times acceleration− ∇ ρ:Pressure force on element per unit volume−[∇. τ]:Viscous force on element per unit volume+ρg:Gravitational force on element per unit volume−(∇. q):Rate of internal energy addition by heat conduction per unit volume−(τ : ∇ v):Irreversible rate of internal energy increase per unit volume by viscous dissipation
