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Multi-objective optimization of a municipal solid waste gasifier

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Abstract

Municipal solid waste (MSW) is the largest waste stream around the world and has a great potential for syngas generation through gasification process. Many researchers have worked on biomass and coal gasification; however, a few of them have considered MSW as feedstock. The present study employs a combination of computational fluid dynamics (CFD) approach, response surface method (RSM), and genetic algorithm (GA) to optimize a MSW-driven gasifier with the simultaneous consideration of efficiency and environmental effects. This study is conducted for Rasht city which is located in the north of Iran and highly suffers from waste disposal problems. This work is to investigate the influence of major parameters on the performance of the gasifier and to find out the optimal set of design variables. The results illustrate that the efficiency of the gasifier is more influenced by the geometric parameters rather than equivalence ratio; however, the effects of equivalence ratio and geometrical parameters on total emission of pollutants are comparable. The efficiency and total emission of pollutants of the best trade-off design (or optimal design) are observed to be 32.2% and 4.8 ppm, respectively.

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Abbreviations

A :

Area (m2) or pre-exponential factor or Empirical constant for reaction rate

B :

Empirical constant for reaction rate

α :

Absorption factor

C :

Molecular Concentration (kg mol m−3) or linear-anisotropic phase function coefficient

C D :

Coefficient of drag

C l :

Modeling constant for particle-eddy interaction time

C s, C ∞ :

vapor concentration at particle surface and in the bulk gas (kmol m−3).

C 1ε :

Turbulent constant

C 2ε :

Turbulent constant

C μ :

Turbulent constant

c p :

Specific heat (J kg−1 K−1)

D :

Dual mass transfer coefficient (m2 s−1)

d :

Particle diameter (m)

E :

Activation energy (J kmol−1)

F :

Particle body force (N kg−1)

f v, 0, f w, 0 :

Initial volatile fraction and Initial moisture fraction of fuel

G :

Incident radiation

G k :

Generation of turbulent kinetic energy

g :

Gravitational acceleration (m s−2)

∆H ° , H :

Heat of reaction (at 298 K and 1 atm)

HHV :

High heating value (J kg−1)

h :

Specific enthalpy of gas phase (J kg−1) or convective heat transfer coefficient (W m−2 K−1)

h fg :

Latent heat of moisture/volatile matters (J kg−1)

I :

Radiation intensity

J :

Mass diffusion flux

k :

Reaction rate constant or Turbulent kinetic energy (m2 s−2)

k c :

thermal conductivity of bulk gas (W m−1 K−1)

L :

Height of gasifier (m)

l :

Height of entrance (m)

l e :

Eddy length scale (m)

M w :

Molecular weight (kg mol−1)

m :

Mass (kg)

m p, o :

Initial mass of particle (kg)

\( \dot{m} \) :

Mass flow rate (kg s−1)

n :

Temperature exponent

P :

Pressure (Pa)

Pr:

Prandtl number

q r :

Radiation heat flux

\( \hat{R} \) :

Rate of reaction (kg m−3 s−1)

R :

Universal gas constant (J kmol K−1)

r :

Rate of reaction (kg m−3 s−1)

Re:

Reynolds number

S :

Source term or Sobol (sensitivity) indices

S r :

Net production rate of species (kmol m−3 s−1)

t :

Time (s)

t e :

Eddy life time (s)

t cross :

Eddy crossing time (s)

T :

Temperature (K)

T′:

Fluctuating temperature (K)

\( \overline{T^{\prime }} \) :

Mean temperature component (K)

u :

Velocity (m s−1)

u′:

Fluctuating velocity component (m s−1)

\( \overline{u^{\prime }} \) :

Mean velocity component (m s−1)

V. R :

Total variance

V :

Variance

v :

Velocity (m s−1)

\( {v}_r^{\prime } \) :

Reactant stoichiometric coefficient of reaction r

\( {v}_r^{\prime \prime } \) :

Product stoichiometric coefficient of reaction r

X :

Symbol denoting species or Mass fraction of solid particle

x :

Coordinate (m)

Y :

Mass fraction or Initial solid mass fraction

y :

Symbol denoting a data

μ :

viscosity (kg m−1 s−1)

ρ :

Density (kg m−3)

τ :

Shear stress (N m−2) or Particle relaxation time (s)

σ:

Stephen-Boltzmann coefficient or Turbulent prandtl number

ε :

Scatter factor or Turbulent dissipation rate (m2 s−3)

ζ :

Normally distributed random number

θ R :

Radiation temperature

δ ij :

Kronecker delta

η :

effectiveness factor

η ′ :

Forward rate exponent

η ′′ :

Backward rate exponent

λ :

Thermal conductivity (W m−1 K−1)

atm :

Atmosphere

b :

Backward

c :

Conduction

D :

Drag

eq :

Equilibrium

f :

Forward

g :

Gas phase

h :

Heating

i :

Species i or Spatial coordinate or Initial

j :

Momentum or Spatial coordinate or Species j

k :

Turbulent kinetic energy

m :

Mass

p :

Particle phase or product

R :

Reactant

r :

Reaction

s :

Solid

t :

Turbulence

v :

Vapor

ε :

Turbulent dissipation rate

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Authors and Affiliations

  1. Department of Mechanical Engineering, University Campus 2, University of Guilan, Rasht, Iran

    Ali Bahari

  2. Faculty of Mechanical Engineering, University of Guilan, Rasht, Iran

    Kazem Atashkari & Javad Mahmoudimehr

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  1. Ali Bahari
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Bahari, A., Atashkari, K. & Mahmoudimehr, J. Multi-objective optimization of a municipal solid waste gasifier. Biomass Conv. Bioref. 11, 1703–1718 (2021). https://doi.org/10.1007/s13399-019-00592-1

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