【摘要】 基团贡献（GC）法一般用于预测有机物的热力学属性参数,但对过程指标的预测能力有限,如热力循环过程的效率。本文发展了一种结合GC法和有机朗肯循环（ORC）热效率解析模型的方法,可以高效快速地估算有机朗肯循环的热效率,从而在某种程度上克服GC方法的局限性。利用GC法与ORC热效率解析模型,筛选了60多种用于中低温有机朗肯循环的有机工质。首先,运用GC方法预测了60多种有机工质的临界温度Tc,临界压力Pc,潜热r,液体的定压比热容c等热力学属性。其次,基于由热力学第二定律推得的ORC解析模型,可直接由GC法预测的热力学参数直接确定ORC的输出功wout和热效率η等性能指标。计算结果表明,与NIST数据相比,本文采用的GC模型具有足够的精度来估算热力学参数(T_c,P_c,r,c,w_out,η的平均相对误差分别为4.45%,9.29%,5.85%,11.5%,10.8%,2.9%)。其中热效率的平均相对误差最小（约为2.9%）,且所有预测值的误差在0～24%的范围内。本研究表明GC方法与ORC解析模型结合,不仅提供了一种估算热效率的直接方法（无需状态方程）,并且提供了一种快速准确的方法来评估有机工质的热力学性能。本文研究成果也为指导基于GC法的ORC有机工质计算机辅助设计提供借鉴。更多还原

【Abstract】 The group-contribution(GC)methods suffer from a limitation concerning to the prediction of process-related indexes,e.g.,thermal efficiency.Recently developed analytical models for thermal efficiency of organic Rankine cycles(ORCs)provide a possibility of overcoming the limitation of the GC methods because these models formulate thermal efficiency as functions of key thermal properties.Using these analytical relations together with GC methods,more than60 organic fluids are screened for medium-low temperature ORCs.The results indicate that the GC methods can estimate thermal properties with acceptable accuracy(mean relative errors are 4.45%-11.50%);the precision,however,is low because the relative errors can vary from less than 0.1% to 45.0%.By contrast,the GC-based estimation of thermal efficiency has better accuracy and precision.The relative errors in thermal efficiency have an arithmetic mean of about 2.9% and fall within the range of 0-24.0%.These findings suggest that the analytical equations provide not only a direct way of estimating thermal efficiency but an accurate and precise approach to evaluating working fluids and guiding computer-aided molecular design of new fluids for ORCs using GC methods.更多还原