基于NSGA-Ⅱ算法的木材干燥能耗多目标优化

Multi-Objective Optimization of Energy Consumption for Wood Drying Based on NSGA-II Algorithm

通过计算流体力学(CFD),研究了在常规蒸汽干燥中,空气温度、相对湿度、风速及其相互作用对桦木干燥时间和能耗的影响,以期得到干燥时间短、且能耗低的桦木干燥工艺参数。应用最优拉丁超立方(Opt LHD)采样确定了设计空间中的样本点,并进行CFD数值模拟;采用三阶响应面方法构建近似代理模型,分析了干燥条件对干燥时间和能耗的影响;基于快速非支配排序遗传算法(NSGA-II)多目标优化的Pareto解集,获得最佳木材干燥条件参数。结果表明:该方法可以有效缩短干燥时间,并降低能耗,可为木材干燥工艺的优化提供参考依据。

Computational fluid dynamics(CFD)was used to analyze the impact of air temperature,relative humidity,wind speed,and their interactions on drying time and energy consumption in conventional steam drying of birch wood.The aim was to obtain optimal drying parameters for birch wood with shorter drying time and lower energy consumption.Optimal Latin Hypercube Design(Opt LHD)sampling was applied to determine sample points in the design space and conduct CFD numerical simulation.The third-order response surface method was used to construct an approximate proxy model and analyze the effects of drying conditions on drying time and energy consumption.Based on the Pareto solution set of multi-objective optimization using the Fast Non-dominated Sorting Genetic Algorithm II(NSGA-II),the best wood drying parameters were obtained.The results showed that this experimental method can effectively reduce drying time and energy consumption and provide reference for wood drying process optimization.