During the anaerobic digestion (AD) of fruit and vegetable waste (FVW), excessive particle size reduction can lead to the overproduction and inhibition of methanogenic microorganisms. This paper presents an in-depth analysis through experimental assays, modeling, and response surface analysis of the effect of particle size on methane production. A simple model was proposed considering the inhibition of the growth of methanogenic microorganisms and surface-based hydrolysis kinetics. The model parameters were estimated using experimental data from batch systems fed with FVW of varying particle sizes (ranging from 1.8 to 1000 μm). Response surface methodology establishes a statistical model for estimating methane production based on particle size and concentration. Numerical and statistical analyses were conducted using Matlab R2024a and Minitab 24 software. A model with an R² of 0.89 was obtained, which determined an optimal concentration of 8.2 $\mathrm{k}\mathrm{g}·{\mathrm{m}}^{-3}$ and a particle size of 742.3 $\mathsf{\mu }\mathrm{m}$, yielding a methane production of 303.3 ${\mathrm{m}}^3·\mathrm{k}{\mathrm{g}}^{-1} \mathrm{V}\mathrm{S}$, similar to the experimentally obtained range of 300.95 to 316.7 ${\mathrm{m}}^3·\mathrm{k}{\mathrm{g}}^{-1} \mathrm{V}\mathrm{S}$.

This paper explores a parallel control structure for improving the behaviour of a chemical plant having recycling and multiple feed streams; a ternary system is taken as an example, having an A+B→C second-order irreversible reaction. Material recycling dynamics can induce the so-called snowball effect in the presence of disturbance in the feed stream. The snowball effect can be prevented by distributing load through the parallel control scheme. A control structure was thus proposed where product composition was regulated by means of simultaneous feedback manipulation of final column vapour boilup rate and reactor temperature. An extension was made for one reactor, one distillation column and recycle stream configuration. Nonlinear simulations showed that effective composition control could be obtained with moderate vapour boilup control efforts.

Anaerobic digestion (AD) of food waste is strongly influenced by substrate characteristics and operating conditions, particularly substrate composition, particle size, and substrate-to-inoculum (S/I) ratio. In this study, a modified ADM1-R3 model, incorporating a surface-based disintegration kinetics approach, was developed to evaluate the simultaneous influence of these factors on methane production. Sensitivity analysis identified the disintegration and hydrolysis constants as the most influential parameters, while principal component analysis supported a sequential calibration strategy. The model was calibrated using literature data and verified against independent datasets, achieving $R^2$ values of 0.9967 (calibration) and 0.9745–0.9880 (verification). Simulation results showed that optimal performance was observed at low S/I ratios (0.5–1) and intermediate particle sizes (1.4–4 mm), with maximum yields of 419, 744, and 581 $\mathrm{m}\mathrm{L}·{\mathrm{g}}^{-1} \mathrm{V}\mathrm{S}$ for carbohydrate-rich, protein- and lipid-rich, and mixed substrates, respectively. Overall, the model provides a consistent framework for analyzing AD behavior and identifying favorable operational conditions, although further validation under unstable operating conditions is required to fully assess its predictive capability.