Computers and Chemical Engineering 106 (2017) 23–39 Contents lists available at ScienceDirect Computers and Chemical Engineering journal homepage: www.elsevier.com/locate/compchemeng Sensitivity analysis and stochastic modelling of lignocellulosic feedstock pretreatment and hydrolysis Sumit Kumar Verma, F. Fenila, Yogendra Shastri * Department of Chemical Engineering, Indian Institute of Technology Bombay, Powai, Room 311, Mumbai, 400076, India a r t i c l e i n f o Article history: Received 8 December 2016 Received in revised form 16 May 2017 Accepted 17 May 2017 Available online 21 May 2017 Keywords: Lignocellulosic biomass acid pretreatment Enzymatic hydrolysis Global sensitivity analysis Ito process Mean reverting process a b s t r a c t Pretreatment and hydrolysis of lignocellulosic biomass are affected by several uncertainties, which must be systematically considered for a robust process design. In this work, stochastic simulations for expected uncertainties in feedstock composition, kinetic parameter values, and operational parameter values for these two steps were performed. The results indicated that these uncertainties significantly impacted the concentration profiles, which could also affect the optimal batch time. Global sensitivity analysis was then used to identify the critical uncertain parameters. In the feedstock components, cellulose and xylan fractions for acid pretreatment and cellulose fraction for enzymatic hydrolysis were important. Temperature was the most sensitive operating parameter for both acid pretreatment and hydrolysis. The activation energies for different reactions were ranked in terms of their impact on process output. The selected parameters were used to develop stochastic process models using Ito process and mean reverting process for feed composition and kinetic parameter uncertainty. © 2017 Elsevier Ltd. All rights reserved. 1. Introduction Production of biomass-based renewable fuels such as ethanol from lignocellulosic biomass like agricultural residue, forestry residue, and dedicated energy crops have generated substantial interest in recent times (Hahn-Hägerdal et al., 2006). However, conversion of lignocellulosic biomass to ethanol is currently economically not feasible. While process development research continues at the interface of science and engineering, process design improvement and optimization is a potential avenue to achieve techno-economic feasibility and enable scale-up from pilot to commercial scale. It will lead to better material and energy efficiencies, higher yields, lower waste generation, and improved cost-efficiency. However, the presence of various uncertainties cre- ates several challenges for process design and optimization. A number of uncertainties influence the overall process of ethanol production from lignocellulosic feedstock (Kenney et al., 2013). From the viewpoint of the process operation, the uncertain- ties can be categorized into two types, namely internal and external. Internal uncertainty refers to the lack of process knowledge such as reaction mechanism, model structure, and the kinetic param- eter values. On the other hand, external uncertainty captures the * Corresponding author. E-mail addresses: yshastri@iitb.ac.in, y.shastri@gmail.com (Y. Shastri). impact of market conditions that impact the process via flow rate, feedstock composition, product specification, prices, and supply of utilities. Following factors are of particular importance with respect to the biochemical processing of lignocellulosic biomass: • Variation in feedstock composition: Various potential lignocel- lulosic feedstock alternatives such as forest residues, agricultural residues (corn stover, bagasse, and rice husk), municipal solid wastes, as well as dedicated energy crops such as Jatropha curcas, switchgrass, sorghum, and Miscanthus, are being proposed and evaluated (Sukumaran et al., 2010). The composition of each of these feedstock will vary from each other. The composition even for the same feedstock can vary significantly due to the impact of short-term weather fluctuations and site-specific production techniques. Templeton et al. (2009) quantified the significant variability in corn stover composition collected from different locations in the Midwestern US Hu et al. (2010) found that the composition varied for leaves, internodes, and nodes of switchgrass. Moreover, the composition will also depend on the harvest date and cultivation treatment. Ash content can also vary significantly as a result of a change in intrinsic biomass properties, such as plant type, maturity, and anatomical fraction collected (Tao et al., 2012; Kenney et al., 2013). For instance, the range of ash varied from 0.1% in woody biomass (such as debarked pinewood) to as high as 25% in the herbaceous crop (such as rice straw) (Tao et al., 2012). http://dx.doi.org/10.1016/j.compchemeng.2017.05.015 0098-1354/© 2017 Elsevier Ltd. All rights reserved.