Performances and efficiencies of displacement ventilation(DV) and partial ventilation(PV) for industrial halls of different configurations as well as the heat and mass transports within the industrial halls were numer...Performances and efficiencies of displacement ventilation(DV) and partial ventilation(PV) for industrial halls of different configurations as well as the heat and mass transports within the industrial halls were numerically investigated. Three levels of Rayleigh number(5.8×1010, 1.0×1012 and 2.1×1012) and two values of source contaminant flux(5 mg/s and 50 mg/s) were considered. The inlet Reynolds numbers were 2×104, 5×104, 1.5×105 and 4.5×105 for DV and 5×105, 1×106, 2×106 and 4×106 for PV, respectively. From the results, it is concluded that the above parameters have very complex impacts on the conjugated heat and mass transports. From points of view of acceptable indoor air quality and ventilation efficiency, PV at Re=1×106 with side-located sources and 65% of the supply air extracted through floor level outlets is the best choice when Ra=5.8×1010. However, DVs at Re=5×104 and Re=1.5×105with center-located sources and floor-mounted air suppliers are the best choices for Ra=1.0×1012 and Ra=2.1×1012, respectively. When source contaminant flux reaches 50 mg/s, local extraction as a supplement of general ventilation is recommended. The results can be a first approximation to 3D numerical investigation and preliminary ventilation system design guidelines for high-rise industrial halls.展开更多
以无人驾驶小巴为代表的客运自动驾驶工具在公交微循环中发挥着重要作用,为实现无人驾驶技术的商业化规模运用,除了传统的车辆性能测试外,还需评估其在复杂场景下的表现。由于测试数据缺乏,评价模型适用场景单一和评价方法主观等问题,...以无人驾驶小巴为代表的客运自动驾驶工具在公交微循环中发挥着重要作用,为实现无人驾驶技术的商业化规模运用,除了传统的车辆性能测试外,还需评估其在复杂场景下的表现。由于测试数据缺乏,评价模型适用场景单一和评价方法主观等问题,导致以往评价偏差较大。本文针对无人驾驶小巴的表现构建综合评价体系,并在实测数据的基础上,采用博弈论组合赋权的优劣解距离法(Technique for Order Preference by Similarity to Ideal Solution,TOPSIS)模型,对车辆在复杂场景下的表现进行综合评价。选取驾驶安全性、乘坐舒适性、车辆智能性及车辆高效性这4个评价维度,并细分为12个客观评价指标。首先,通过实地测试采集无人驾驶小巴在运行场景中的数据;其次,利用基于博弈论的组合赋权法,对层次分析法和熵权法获得的权重进行组合;最后,为验证模型的有效性,运用TOPSIS模型对3条具有不同复杂度的测试路线进行综合评价值的计算。结果显示,无人驾驶小巴表现评价中,准则层的重要程度排序为车辆智能性、驾驶安全性、乘坐舒适性、车辆高效性,指标层敏感指标则为自动驾驶状态、平均角速度。基于博弈论组合赋权的TOPSIS模型对不同场景复杂度路线进行的无人驾驶小巴表现评价结果与实际运行情况一致,展示了方法的有效性。展开更多
基金Project(2011BAJ03B07)supported by National Twelve Five-year Science and Technology Support Program of ChinaProject supported by the China Scholarship Council+1 种基金Project(51276057,51376198)supported by the National Natural Science Foundation of ChinaProject(CX2014B064)supported by Hunan Provincial Innovation Foundation for Postgraduate,China
文摘Performances and efficiencies of displacement ventilation(DV) and partial ventilation(PV) for industrial halls of different configurations as well as the heat and mass transports within the industrial halls were numerically investigated. Three levels of Rayleigh number(5.8×1010, 1.0×1012 and 2.1×1012) and two values of source contaminant flux(5 mg/s and 50 mg/s) were considered. The inlet Reynolds numbers were 2×104, 5×104, 1.5×105 and 4.5×105 for DV and 5×105, 1×106, 2×106 and 4×106 for PV, respectively. From the results, it is concluded that the above parameters have very complex impacts on the conjugated heat and mass transports. From points of view of acceptable indoor air quality and ventilation efficiency, PV at Re=1×106 with side-located sources and 65% of the supply air extracted through floor level outlets is the best choice when Ra=5.8×1010. However, DVs at Re=5×104 and Re=1.5×105with center-located sources and floor-mounted air suppliers are the best choices for Ra=1.0×1012 and Ra=2.1×1012, respectively. When source contaminant flux reaches 50 mg/s, local extraction as a supplement of general ventilation is recommended. The results can be a first approximation to 3D numerical investigation and preliminary ventilation system design guidelines for high-rise industrial halls.
文摘以无人驾驶小巴为代表的客运自动驾驶工具在公交微循环中发挥着重要作用,为实现无人驾驶技术的商业化规模运用,除了传统的车辆性能测试外,还需评估其在复杂场景下的表现。由于测试数据缺乏,评价模型适用场景单一和评价方法主观等问题,导致以往评价偏差较大。本文针对无人驾驶小巴的表现构建综合评价体系,并在实测数据的基础上,采用博弈论组合赋权的优劣解距离法(Technique for Order Preference by Similarity to Ideal Solution,TOPSIS)模型,对车辆在复杂场景下的表现进行综合评价。选取驾驶安全性、乘坐舒适性、车辆智能性及车辆高效性这4个评价维度,并细分为12个客观评价指标。首先,通过实地测试采集无人驾驶小巴在运行场景中的数据;其次,利用基于博弈论的组合赋权法,对层次分析法和熵权法获得的权重进行组合;最后,为验证模型的有效性,运用TOPSIS模型对3条具有不同复杂度的测试路线进行综合评价值的计算。结果显示,无人驾驶小巴表现评价中,准则层的重要程度排序为车辆智能性、驾驶安全性、乘坐舒适性、车辆高效性,指标层敏感指标则为自动驾驶状态、平均角速度。基于博弈论组合赋权的TOPSIS模型对不同场景复杂度路线进行的无人驾驶小巴表现评价结果与实际运行情况一致,展示了方法的有效性。
