Optimization of the direct synthesis of dimethyl ether from CO₂ rich synthesis gas: closing the loop between experimental investigations and model-based reactor design

Abstract

Kinetic modeling, model-based optimization and experimental validation for the direct DME synthesis.

Modeling the Direct Synthesis of Dimethyl Ether using Artificial Neural Networks

“…Furthermore, the consistency of this effect throughout the entire investigated gas flow range can be attributed to a constant selectivity towards DME. A detailed description of the observed phenomena can be found elsewhere 28. Model predictions in this operational range demonstrate the high level of agreement between the simulated and measured values, also showing a smooth mapping and the ANN's ability to generalize and make predictions for unseen data within the model's validity range.…”

“…At low temperatures, the low reaction rates lead to overall low conversion and yield. Hence, resulting in small DME amounts in the product gas and thus in a reduced measuring accuracy 28. Therefore, the deviations of both models can be mainly attributed to experimental measurement uncertainties.…”

“…For this purpose, additional simulations were performed for unobserved data within and beyond the model's validity range. The lumped model published in our previous work 28 is employed for a comparative analysis of the ANN's predictions. Since both models were fitted to the same experimental data, these are valid in the same range of conditions, thus, providing a sufficient basis for comparison.…”

“…Shallow feedforward ANNs (ANNs with one hidden layer) were designed and implemented in Matlab® software R2018a v9.4.0. The experimental kinetic data used for training and testing were acquired and published in a previous work 28. The used data set consists of 180 experiments carried out in a fixed bed reactor at 50 bar using a 1:1 mechanical mixture of a commercial CZA catalysts and γ ‐Al 2 O 3 .…”

Kinetics of the direct DME synthesis from CO2 rich syngas under variation of the CZA-to-γ-Al2O3 ratio of a mixed catalyst bed

“…With regard to the composition of the catalyst bed, previous investigations 14, [20][21][22][23] have shown on the basis of simulated and experimental data that optimization can lead to signicant enhancement of the process performance. For instance, in the studies of Peláez et al 15 and Peinado et al 24 the authors showed that for CO 2 rich synthesis gas a signicant increase in the performance is achieved by increasing the CZA-to-g-Al 2 O 3 ratio.…”