论文部分内容阅读
针对有机工质高温高压下密度的测量较为困难的问题,特别是超临界状态下,设计出高温高压下密度的测量方法,并提出了基于最小二乘支持向量机(LSSVM)的密度预测方法.该方法首先利用实验手段对有机工质在不同温度、压力点下的密度进行测量,并通过对该离散的实验段数据的学习,利用最小二乘支持向量机方法预测得到T-p面上密度的连续值,尤其是实验手段难以测量的超临界下的密度.基于该方法,以有机工质六甲基二硅氧烷为例,得到了其在T(600~850K)与p(1.3~2.25MPa)范围内的密度值及密度关于温度压力的函数公式,并将其结果与公布的密度数据对比,结果表明:两者的相对误差仅为2.4%,证明了方法的有效性.
In order to solve the problem of density measurement under high temperature and high pressure of organic working medium, especially in the supercritical state, the method of density measurement under high temperature and high pressure is designed and the density prediction method based on least squares support vector machine (LSSVM) is proposed. In this method, the density of organic working fluid under different temperature and pressure is first measured by means of experiment. By using the data from the discrete experimental section, the density of Tp surface is predicted by the method of least square support vector machine Value, especially the supercritical density which is difficult to measure by experimental method.Based on the method, taking the working medium hexamethyldisiloxane as an example, the density at T (600 ~ 850K) and p (1.3 ~ 2.25MPa ) Within the range of density and density as a function of temperature and pressure, and the result is compared with the published density data. The results show that the relative error between the two is only 2.4%, which proves the effectiveness of the method.