多股进料搅拌釜停留时间分布的信息熵

Information entropy of residence time distribution in stirred tank with multiple inlets

以具有4股进料和单股出料的搅拌釜为例,将信息熵理论用于分析停留时间的分布,用信息熵混合度来表征整个装置内的混合情况.当4股同时进料却只在一股加入示踪剂时,方差分析结果表明:底部进料的示踪剂在整个装置内混合良好,这与示踪剂主要分布在装置下部,未能在整个装置内实现良好混合的现象不符.通过信息熵分析,发现搅拌雷诺数越大、示踪剂进料位置离装置出口越远,则示踪剂混合情况越好.此外,按叠加规则计算得到的总停留时间分布曲线与实际值吻合良好,两者信息熵混合度的相对偏差小于2%,验证了叠加规则的正确性.可见,在多股进料条件下,将信息熵理论应用于停留时间分布的分析,比方差分析更能准确地反映流体的流动与混合情况.

Information entropy theory was used to analyze residence time distribution（RTD）in a stirred tank with four inlets and one outlet.The information entropy mixing degree was applied to characterize the quality of mixing within the whole tested apparatus.When the tracer was injected in one of the four inlets,the variance analysis showed that the mixing of the tracer in the whole tank was perfect.The result was different from the experiment where the tracer mainly distributed at the bottom of the tank and didn＇t have the best mixing performance.The information entropy analysis indicated that the mixing degree of the tracer was enhanced with the increase of Reynolds number and the distance between tracer inlet and product outlet.Furthermore,the overall RTD cures based on the superposition rule showed an excellent agreement with the experimental results.The relative deviation（RD）of information entropy mixing degree was less than 2%,which validatesd the superposition rule.In conclusion,information entropy theory is more suitable for analyzing RTD than variance analysis,reflecting the flow and mixing characteristics for flow system with multiple inlets more accurately.