Rates and activation energies of nitronium ion formation and reaction in the nitration of toluene in ∼78% sulphuric acid

Computers & Chemical Engineering

Vassiliadis

2018

Thermal runaways in exothermic batch reactions are a major economic, health and safety risk in industry. In literature most stability criteria for such behaviour are not reliable for nonlinear non-steady state systems. In this work, Lyapunov exponents are shown to predict the instability of highly nonlinear batch processes reliably and are hence incorporated in standard MPC schemes, leading to the intensication of such processes. The computational time is of major importance for systems controlled by MPC. The optimal tuning of the initial perturbation and the time frame reduces the computational time when embedded in MPC schemes for the control of complex batch reactions. The optimal tuning of the initial perturbation and time horizon, dening Lyapunov exponents, has not been carried out in literature so far and is here derived through sensitivity analyses. The computational time required for this control scheme is analysed for the intensication of complex reaction schemes.

Section: Industrial Case Study: Nitration Of Toluenementioning

confidence: 99%

Optimal Laypunov exponent parameters for stability analysis of batch reactors with Model Predictive Control

Computers & Chemical Engineering

Vassiliadis

2018

“…The reactor dimensions for this system are given in Table 1. (Chen et al, 2008;Luo and Chang, 1998;Mawardi, 1982;Sheats and Strachan, 1978).…”

Section: Industrial Case Study: Nitration Of Toluenementioning

confidence: 99%

Thermal stability criterion of complex reactions for batch processes

Chemical Engineering Research and Design

Vassiliadis

2019

Thermal stability of batch processes is a major factor for the safe and efficient production of polymers and pharmaceutical chemicals. The prediction of the thermal stability for such processes was shown in Kähm and Vassiliadis (2018d) to be unreliable with most stability criteria found in literature also presenting a novel criterion, K, which was shown to give reliable stability predictions for single reactions of higher order. This work provides a detailed derivation for the generalization of thermal stability criterion K applied to reaction networks of arbitrary complexity, consisting of parallel and competing reactions of both exothermic and endothermic nature. The generalized thermal stability criterion K is then applied to Model Predictive Control (MPC) frameworks to intensify batch processes in a safe manner, reducing the time required to reach the target conversion. Several illustrative computational case studies are presented, highlighting the proposed methodology and verifying its validity.

“…The nitration of toluene is a relevant process in industry, consisting of endothermic and exothermic reactions (Halder et al, 2008). Thermal runaways can occur still, (Chen et al, 2008;Luo and Chang, 1998;Mawardi, 1982;Sheats and Strachan, 1978).…”

Section: Industrial Case Study: Nitration Of Toluenementioning

confidence: 99%

Robust thermal stability for batch process intensification with model predictive control

Kanavalau

Masters

Computers & Chemical Engineering

et al. 2019

Thermal runaways in exothermic batch reactors present major safety and economic issues for industry.Control systems currently used are not capable of detecting thermal runaway behaviour and achieve nominally safe operation by carrying out the reaction at a low temperature. Recently, improvements in safety and process intensity have been achieved by using Model Predictive Control (MPC) with embedded stability criteria. The reliance of this approach on accurate model predictions makes plantmodel mismatch a crucial issue. The most common source of plant-model mismatch is uncertainty of model parameters. Scenario-based MPC and worst case MPC are used with stability criterion K and Lyapunov exponents in this work. The effect of all uncertain parameters on thermal runaway potential can be identified easily for simulations in this work. Hence, worst case MPC results in a computationally more efficient control scheme than scenario-based MPC, whilst ensuring the same extent of safety and process intensification.