基于CFD模拟的甲烷裂解太阳能管式反应器结构优化

太阳能裂解甲烷具有产物纯度高且环保的优点。对湍流条件下的甲烷高温裂解太阳能管式反应器进行计算流体力学（CFD）模拟，为提高太阳能甲烷裂解反应器的转化率，通过调节反应器结构对流场进行优化。为了更加准确计算太阳能辐射的加热效应，在湍流反应扩散模型中引入碳颗粒的生成和聚集模型，并采用离散坐标（DO）模型进行辐射模型求解。然后，在太阳能管式反应器中引入射流及挡板进行流场调节，并对挡板高度、射流流速及角度进行优化，达到强化反应过程的目的。优化后的反应器中，甲烷转化率可以提高约8%。以反应转化率和代表强化成本的黏性耗散为指标，筛选出不同离散条件下的Pareto最优解，并用支持向量机回归（SVR）算法对离散的Pareto最优解进行插值，得到操作曲线和与之相对应的最优射流角度及流速。

Structural optimization of methane cracking solar tube reactor based on CFD simulation

Solar cracking of methane has the advantages of high product purity and environmental protection. In this paper, flow field in a solar tube reactor for high-temperature cracking of methane is optimized through computational fluid dynamics (CFD) simulation by adjusting structure of the tube reactor under turbulent conditions. The carbon particle generation and aggregation model were introduced to calculate the heating effect of solar radiation more accurately. And the discrete-ordinates method (DO) model was used to solve radiation model. A jet flow and baffles were introduced to adjust and optimize the flow field. The baffle height, jet velocity and angle were optimized to enhance the reaction process. The Pareto optimal solution is screened through the definition method, and the Pareto optimal solution is encrypted with the machine learning prediction algorithm to obtain the actual operation encryption curve and corresponding operation parameters. As a result of the optimization, the conversion rate of methane is increased by about 8%. On the basis of the conversion rate, the viscosity dissipation, which represents the increase in strengthening costs, is used as an indicator to filter out the discrete Pareto optimal solution. The support vector regression (SVR) algorithm is used to interpolate the discrete Pareto optimal solution to obtain the operating curve, the corresponding jet angle and jet velocity.