Comparison of conventional and spherical reactor for the industrial auto-thermal reforming of methane to maximize synthesis gas and minimize CO2

Auto-thermal reforming (ATR), a combination of exothermic partial oxidation and endothermic steam reforming of methane, is an important process to produce syngas for petrochemical industries. In a commercial ATR unit, tubular fixed bed reactors are typically used. Pressure drop across the tube, high manufacturing costs, and low production capacity are some disadvantages of these reactors. The main propose of this study is to offer an optimized radial flow, spherical packed bed reactor as a promising alternative for overcoming the drawbacks of conventional tubular reactors. In the current research, a one dimensional pseudo-homogeneous model based on mass, energy, and momentum balances is applied to simulate the performance of packed-bed reactors for the production of syngas in both tubular and spherical reactors. In the optimization section, the proposed work explores optimal values of various decision variables that simultaneously maximize outlet molar flow rate of H2, CO and minimize molar flow rate of CO2 from novel spherical reactor. The multi-objective model is transformed to a single objective optimization problem by weighted sum method and the single optimum point is found by using genetic algorithm. The optimization results show that the pressure drop in the spherical reactor is negligible in comparison to that of the conventional tubular reactor. Therefore, it is inferred that the spherical reactor can operate with much higher feed flow rate, more catalyst loading, and smaller catalyst particles

Inherently safe and economically optimal design using multi-objective optimization: the case of a refrigeration cycle

The economic viability of industrial processes strongly depends on their safe and reliable operation. The method of inherent safe process design enables systematic consideration of safety measures in order to ensure process safe operation at the early stages of process design. The challenge is that the economic measures that are often considered for the design of industrial processes are often incommensurable with the safety measures. In the present research, a novel framework is proposed in which the safety criteria are quantified based on consequence modeling and aggregated with the economic performance using multi-objective optimization programming. The developed methodology was applied to the design of a simple refrigeration cycle. The optimization algorithm was NSGA-II. The results suggested a strong trade-off between the competing economic and safety objectives in terms of Pareto frontiers that clearly quantified the required compromise. It was observed that only with a minor increase in the capital investment, it is possible to significantly improve the safety. While the case of the refrigeration cycle was selected as a demonstrating case, the research methodology is to large extend general and deemed to be acceptable to design and operation of other industrial processes