Large-scale separation of substances present at low concentrations is readily performed by adsorption in packed beds that requires recurring energy-intensive regeneration of the adsorbent. The present work uses numerical simulations previously developed for industrial-scale packed-bed benzene sorption on activated carbon with temperature-swing regeneration by steam to investigate the influence of steam properties and regeneration strategy on total energy performance and breakthrough behaviour.

It is shown that using saturated steam lowers both the steam mass and energy consumption during regeneration of a fixed amount of benzene, whereas using superheated steam returns the bed to a more fresh-like state after each regeneration stage. The most promising variation tried implies a 19% reduction in the energy consumption. Furthermore, the importance of accounting for the real industrial cycling conditions in the optimization of packed-bed adsorbers is highlighted. It is shown that the participation of different sections of the bed during adsorption varies with the regeneration strategy, but is never as localized as predicted from a model for a fresh bed without cycling. Finally, the present results also show that the effluent purity attained during regeneration increases when high-temperature saturated steam is used, e.g. a 60-degree increase in steam temperature raises the purity by 11%.

低浓度物质的大规模分离很容易通过填充床中的吸附进行，这需要吸附剂的重复能量密集型再生。目前的工作使用先前为工业规模填充床苯吸附在活性炭上通过蒸汽变温再生而开发的数值模拟，以研究蒸汽性质和再生策略对总能量性能和突破行为的影响。

结果表明，在固定数量的苯再生过程中，使用饱和蒸汽可以降低蒸汽质量和能耗，而使用过热蒸汽可以在每个再生阶段后使床层恢复到更新鲜的状态。尝试的最有希望的变体意味着能耗降低 19%。此外，强调了在填充床吸附器优化中考虑实际工业循环条件的重要性。结果表明，吸附过程中床的不同部分的参与随再生策略的不同而变化，但从未像没有循环的新鲜床模型预测的那样局部化。最后，目前的结果还表明，当使用高温饱和蒸汽时，再生过程中获得的出水纯度会增加，例如