纵向通风公路隧道空气污染浓度适时预报算法

公路隧道空气污染模型的计算通常采用有限体积法,耗时费力,在通风系统的动态调控中不易使用.根据隧道内污染物浓度沿隧道长度近似线性分布的特点,从二阶偏微分方程表示的隧道通风污染模型中推导出了动态预测隧道出口空气污染物浓度的线性迭代方程,对方程中新出现的变量提出了可行的计算方法,同时对方程所描述的物理过程进行了解释．用西汉高速秦岭隧道内的CO浓度的实测数据对方程进行了验证,发现此方程能够在离线的情况下粗略预报隧道出口CO浓度值．为进一步改善预报精度,利用实测数据对上述方程进行修正,提出了一种带有观测误差修正的预报算法,并用现场数据对修正后的预报算法进行验证,结果表明修正后的预报算法能够更准确地在线预测隧道出口实际CO浓度值．

Short-period forecasting algorithm for air pollution concentration in road tunnel with longitudinal ventilation

The computation of road tunnel air pollution model often adopted finite volume method, and was time-consuming, strenuous, difficult to be used in dynamical ventilation control system of road tunnel. Pollution concentration distribution in road tunnels was near linear along tunnel length. According to this characteristic, a new linear iteration formula was deduced from tunnel ventilation pollution model described by partial differential equation of second order. The practical methods to compute new variables in the formula were proposed. And the physical process denoted by the formula was illustrated. Then the formula was validated with detected CO concentrations from Qingling tunnel of Xihan highway, and it is found that the formula can cursorily offline forecast CO concentration in road tunnel outlets. To improve forecast precision, the previous formula was amended using detected data. And another predictive method with observation error correction was put forward and validated with the detected data. The results show this method can more accurately online forecast CO concentration in the tunnel outlets.