Exergy analysis of industrial processes using AI techniques

A systematic approach: combining process optimisation exergy analysis and energy recovery for a better efficiency of industrial processes

“…To help the user in handling exergy data, some heuristics and general rules have been established (Feng and Zhu, 1997) without specific alternatives. To overcome this problem, De Jong et al (1996) proposed combining AI techniques, and more precisely CBR systems, and exergy analysis to improve industrial processes. In the chemical engineering field, CBR systems have already been adopted for process designing (Ataei, 2011;Ataei and Yoo, 2010), separation process design (Ghorbani et al, 2012;Staine and Favrat, 1996), reactive distillation (Homsak and Glavic, 1996), mixing equipment selection (Anantharaman, 2011), process alternatives generation (Anantharaman et al, 2006) and more recently for cogeneration plant design (Aspelund et al, 2007;Gundersen et al, 2009).…”

Process Optimization of Coke Oven Gas to Methanol Based on the Downgrade of By-Product Steam

“…(14), where 2 denotes exergy efficiency and EX o and EX in are the total exergy output and input, respectively. In the exergy efficiency calculation, the reference conditions, T 0 = 298.13 K and P 0 = 1 bar, are assumed [41].…”

A systematic approach: combining process optimisation exergy analysis and energy recovery for a better efficiency of industrial processes

“…This solution has been adapted for the production of ammonia. Note that this method of improvement was also developed elsewhere (De Jong et al, 1996). While the second suggested solution is already implemented in the nominal processes, the emphasis will be only placed on the first one, consisting of integrating a gas turbine downstream of the reactor.…”