Simulation of anaerobic digestion processes using stochastic algorithm

Background: the anaerobic digestion (ad) processes involve numerous complex biological and chemical reactionsoccurring simultaneously. appropriate and efficient models are to be developed for simulation of anaerobic digestionsystems. although several models have been developed, mostly they suffer from lack of knowledge on constants,complexity and weak generalization. the basis of the deterministic approach for modelling the physico and bio-chemicalreactions occurring in the ad system is the law of mass action, which gives the simple relationship between the reactionrates and the species concentrations. the assumptions made in the deterministic models are not hold true forthe reactions involving chemical species of low concentration. the stochastic behaviour of the physicochemicalprocesses can be modeled at mesoscopic level by application of the stochastic algorithms.method: in this paper a stochastic algorithm (gillespie tau leap method) developed in matlab was applied topredict the concentration of glucose, acids and methane formation at different time intervals. by this the performanceof the digester system can be controlled. the processes given by adm1 (anaerobic digestion model 1) were taken forverification of the model.results: the proposed model was verified by comparing the results of gillespie’s algorithms with the deterministicsolution for conversion of glucose into methane through degraders. at higher value of ‘?‘ (timestep), thecomputational time required for reaching the steady state is more since the number of chosen reactions is less. whenthe simulation time step is reduced, the results are similar to ode solver.conclusion: it was concluded that the stochastic algorithm is a suitable approach for the simulation of complexanaerobic digestion processes. the accuracy of the results depends on the optimum selection of tau value.