Wind barriers have attracted significant attention as an effective measure to ensure train safety under crosswinds.However,in past decades,the influence of structural parameters such as the height and ventilation rati...Wind barriers have attracted significant attention as an effective measure to ensure train safety under crosswinds.However,in past decades,the influence of structural parameters such as the height and ventilation ratio of wind barriers on the difference of the average pressure coefficient between the train windward and leeward surface(ΔCp)has not been fully investigated.To determine the influence of the interaction among the three factors,namely the wind barrier height(H),ventilation ratio(R),and distance to the train(D),twenty five numerical simulation cases with different structural parameters were considered based on an orthogonal design.The shear stress transfer(SST)k-ωturbulent model was employed to calculate the wind pressure coefficients,and the calculation accuracy was validated by using wind tunnel experiments.The results indicated that with an increase in R,ΔCp first decreased and then increased,andΔCp decreased while D increased.Moreover,with the increase in H,ΔCp first increased and then decreased.Therefore,these three factors must be considered during the installation of wind barriers.Furthermore,according to a range analysis(judging the relative importance of the three factors intuitively),the three factors were ranked in the following order:R>H>D.Based on a variance analysis,R was found to be of high significance toΔCp,followed by H,which was significant,whereas D had relatively insignificant influence.Finally,the optimal values of R and H were determined to be 20%and 110 mm,respectively.And when R=40%,H=85 mm,the train was relatively unsafe under these such conditions.The findings of this study provide significant guidance for the structural design of wind barriers.展开更多
传统的暖通空调(heating, ventilation and air conditioning, HVAC)系统声学设计多依赖于设计人员的经验,重复性工作多,自动化水平低。为实现智能化设计,应用有向无环图、带权有向邻接矩阵、科学计算可视化等方法将通风管道消声系统的...传统的暖通空调(heating, ventilation and air conditioning, HVAC)系统声学设计多依赖于设计人员的经验,重复性工作多,自动化水平低。为实现智能化设计,应用有向无环图、带权有向邻接矩阵、科学计算可视化等方法将通风管道消声系统的声学设计过程系统化。提出一种能够自动计算管道内任意处噪音及特定的房间内噪声值的算法,包括三维模型构建,噪声衰减图生成,声学路径确定,声学单元解算,声学结果可视化等关键环节。实验结果表明:该系统鲁棒性强,计算结果准确,响应快速。所提算法结果与设计人员利用传统方法计算出的结果误差不超过±2%,计算时长均小于0.2 s,常见的中小规模的通风系统计算时间则在0.1 s以内。基于此算法计算得出的噪声值结果能够与三维模型结合,直观展示噪声分布情况,在通风空调系统设计过程中提供参考依据。展开更多
基金Project(51822803)supported by the National Natural Science Foundation of ChinaProject(2019JJ50688)supported by Hunan Provincial Natural Science Foundation,China+1 种基金Project(kq1905005)supported by Training Program for Excellent Young Innovators of Changsha,ChinaProject(CX20210775)supported by Hunan Provincial Innovative Foundation for Postgraduates,China。
文摘Wind barriers have attracted significant attention as an effective measure to ensure train safety under crosswinds.However,in past decades,the influence of structural parameters such as the height and ventilation ratio of wind barriers on the difference of the average pressure coefficient between the train windward and leeward surface(ΔCp)has not been fully investigated.To determine the influence of the interaction among the three factors,namely the wind barrier height(H),ventilation ratio(R),and distance to the train(D),twenty five numerical simulation cases with different structural parameters were considered based on an orthogonal design.The shear stress transfer(SST)k-ωturbulent model was employed to calculate the wind pressure coefficients,and the calculation accuracy was validated by using wind tunnel experiments.The results indicated that with an increase in R,ΔCp first decreased and then increased,andΔCp decreased while D increased.Moreover,with the increase in H,ΔCp first increased and then decreased.Therefore,these three factors must be considered during the installation of wind barriers.Furthermore,according to a range analysis(judging the relative importance of the three factors intuitively),the three factors were ranked in the following order:R>H>D.Based on a variance analysis,R was found to be of high significance toΔCp,followed by H,which was significant,whereas D had relatively insignificant influence.Finally,the optimal values of R and H were determined to be 20%and 110 mm,respectively.And when R=40%,H=85 mm,the train was relatively unsafe under these such conditions.The findings of this study provide significant guidance for the structural design of wind barriers.
文摘传统的暖通空调(heating, ventilation and air conditioning, HVAC)系统声学设计多依赖于设计人员的经验,重复性工作多,自动化水平低。为实现智能化设计,应用有向无环图、带权有向邻接矩阵、科学计算可视化等方法将通风管道消声系统的声学设计过程系统化。提出一种能够自动计算管道内任意处噪音及特定的房间内噪声值的算法,包括三维模型构建,噪声衰减图生成,声学路径确定,声学单元解算,声学结果可视化等关键环节。实验结果表明:该系统鲁棒性强,计算结果准确,响应快速。所提算法结果与设计人员利用传统方法计算出的结果误差不超过±2%,计算时长均小于0.2 s,常见的中小规模的通风系统计算时间则在0.1 s以内。基于此算法计算得出的噪声值结果能够与三维模型结合,直观展示噪声分布情况,在通风空调系统设计过程中提供参考依据。
