The effect of gradient exhaust strategy and blind plate installation on the inhibition of backflow and thermal stratification in data center cabinets is systematically investigated in this study through numericalmetho...The effect of gradient exhaust strategy and blind plate installation on the inhibition of backflow and thermal stratification in data center cabinets is systematically investigated in this study through numericalmethods.The validated Re-Normalization Group(RNG)k-ε turbulence model was used to analyze airflow patterns within cabinet structures equipped with backplane air conditioning.Key findings reveal that server-generated thermal plumes induce hot air accumulation at the cabinet apex,creating a 0.8℃ temperature elevation at the top server’s inlet compared to the ideal situation(23℃).Strategic increases in backplane fan exhaust airflow rates reduce server 1’s inlet temperature from 26.1℃(0%redundancy case)to 23.1℃(40%redundancy case).Gradient exhaust strategies achieve equivalent server temperature performance to uniform exhaust distributions while requiring 25%less redundant airflow.This approach decreases the recirculation ratio from1.52%(uniformexhaust at 15%redundancy)to 0.57%(gradient exhaust at equivalent redundancy).Comparative analyses demonstrate divergent thermal behaviors:in bottom-server-absent configurations,gradient exhaust reduces top server inlet temperatures by 1.6℃vs.uniformexhaust,whereas top-serverabsent configurations exhibit a 1.8℃ temperature increase under gradient conditions.The blind plate implementation achieves a 0.4℃ top server temperature reduction compared to 15%-redundancy uniform exhaust systems without requiring additional airflow redundancy.Partially installed server arrangements with blind plates maintain thermal characteristics comparable to fully populated cabinets.This study validates gradient exhaust and blind plate technologies as effective countermeasures against cabinet-scale thermal recirculation,providing actionable insights for optimizing backplane air conditioning systems in mission-critical data center environments.展开更多
开关柜温度异常是导致电力系统故障的重要因素,准确预测其温度变化对保障电网安全稳定运行具有重要意义。然而,开关柜温度受到负荷条件、环境因素、设备老化等多重因素的复杂非线性影响,传统预测方法难以有效捕捉其时序依赖特性和多因...开关柜温度异常是导致电力系统故障的重要因素,准确预测其温度变化对保障电网安全稳定运行具有重要意义。然而,开关柜温度受到负荷条件、环境因素、设备老化等多重因素的复杂非线性影响,传统预测方法难以有效捕捉其时序依赖特性和多因素耦合关系。为解决这一问题,提出了一种基于深度学习的PNNA(Pearson Neural Network with Attention)温度预测模型。该模型采用三路并行架构:首先通过混合特征选择策略,结合皮尔逊相关系数、互信息分析和递归特征消除技术,从多维影响因素中筛选出最优特征子集;然后利用双向LSTM、多头时间注意力机制和时间卷积网络三条并行路径分别捕获长期时序依赖、关键时间模式和局部时序特征;最后通过门控融合机制智能整合三路特征表示。实验结果表明该模型可以用于实时监控和预警开关柜的热状态,预防过热导致的设备故障和安全事故,为电力系统的安全稳定运行提供有力的支持。展开更多
Due to the practical problems of the high costs and the long development cycle of China’s cabinet production,a computer-aided design method of the cabinet based on style imagery is proposed.According to the principle...Due to the practical problems of the high costs and the long development cycle of China’s cabinet production,a computer-aided design method of the cabinet based on style imagery is proposed.According to the principle of the conjoint analysis method, the rough set theory and the weight coefficient of different components of the cabinet,a multi-dimensional model of style imagery to evaluate the cabinet is built. Then the related constants of style imagery are calculated and the cabinet components library is also built by the three-dimensional modeling.Finally,with recombinant technology and the mapping model between cabinet style and external characteristics,the prototype system based on Visual Studio is proposed.This system actualizes the bidirectional reasoning between product style imagery and the shape features,which can assist designers to produce more creative designs,greatly improve the efficiency of cabinet development and increase the profits of companies.展开更多
开关柜上的一些关键部位,比如断路器触头,不能直接安装温度传感器,为了获取合适的温度传感监测点,以实现对开关柜的监测和保护;文中以KYN28A-12型10 k V开关柜为研究对象,建立开关柜三维物理模型,通过Ansys仿真,得到开关柜在额定工况下...开关柜上的一些关键部位,比如断路器触头,不能直接安装温度传感器,为了获取合适的温度传感监测点,以实现对开关柜的监测和保护;文中以KYN28A-12型10 k V开关柜为研究对象,建立开关柜三维物理模型,通过Ansys仿真,得到开关柜在额定工况下的温度场分布规律,初步为后续的监测点选取提供仿真理论基础。为应对开关柜复杂的运行条件,笔者对开关柜在环境温度、载流量等不同工况下进行温度场仿真,基于仿真结果和理论分析,最终综合选取了一些温度变化差异较大的母排节点作为温度监测点,并具体分析了这些监测点在不同工况条件下的温升影响差异,验证了文中选取的温度监测点的合理性。展开更多
基金financially supported by the Basic Research Funds for the Central Government“Innovative Team of Zhejiang University”under contract number(2022FZZX01-09).
文摘The effect of gradient exhaust strategy and blind plate installation on the inhibition of backflow and thermal stratification in data center cabinets is systematically investigated in this study through numericalmethods.The validated Re-Normalization Group(RNG)k-ε turbulence model was used to analyze airflow patterns within cabinet structures equipped with backplane air conditioning.Key findings reveal that server-generated thermal plumes induce hot air accumulation at the cabinet apex,creating a 0.8℃ temperature elevation at the top server’s inlet compared to the ideal situation(23℃).Strategic increases in backplane fan exhaust airflow rates reduce server 1’s inlet temperature from 26.1℃(0%redundancy case)to 23.1℃(40%redundancy case).Gradient exhaust strategies achieve equivalent server temperature performance to uniform exhaust distributions while requiring 25%less redundant airflow.This approach decreases the recirculation ratio from1.52%(uniformexhaust at 15%redundancy)to 0.57%(gradient exhaust at equivalent redundancy).Comparative analyses demonstrate divergent thermal behaviors:in bottom-server-absent configurations,gradient exhaust reduces top server inlet temperatures by 1.6℃vs.uniformexhaust,whereas top-serverabsent configurations exhibit a 1.8℃ temperature increase under gradient conditions.The blind plate implementation achieves a 0.4℃ top server temperature reduction compared to 15%-redundancy uniform exhaust systems without requiring additional airflow redundancy.Partially installed server arrangements with blind plates maintain thermal characteristics comparable to fully populated cabinets.This study validates gradient exhaust and blind plate technologies as effective countermeasures against cabinet-scale thermal recirculation,providing actionable insights for optimizing backplane air conditioning systems in mission-critical data center environments.
文摘开关柜温度异常是导致电力系统故障的重要因素,准确预测其温度变化对保障电网安全稳定运行具有重要意义。然而,开关柜温度受到负荷条件、环境因素、设备老化等多重因素的复杂非线性影响,传统预测方法难以有效捕捉其时序依赖特性和多因素耦合关系。为解决这一问题,提出了一种基于深度学习的PNNA(Pearson Neural Network with Attention)温度预测模型。该模型采用三路并行架构:首先通过混合特征选择策略,结合皮尔逊相关系数、互信息分析和递归特征消除技术,从多维影响因素中筛选出最优特征子集;然后利用双向LSTM、多头时间注意力机制和时间卷积网络三条并行路径分别捕获长期时序依赖、关键时间模式和局部时序特征;最后通过门控融合机制智能整合三路特征表示。实验结果表明该模型可以用于实时监控和预警开关柜的热状态,预防过热导致的设备故障和安全事故,为电力系统的安全稳定运行提供有力的支持。
基金The National Natural Science Foundation of China(No.71271053)the Scientific Innovation Research of College Graduates in Jiangsu Province(No.CXLX13_082)
文摘Due to the practical problems of the high costs and the long development cycle of China’s cabinet production,a computer-aided design method of the cabinet based on style imagery is proposed.According to the principle of the conjoint analysis method, the rough set theory and the weight coefficient of different components of the cabinet,a multi-dimensional model of style imagery to evaluate the cabinet is built. Then the related constants of style imagery are calculated and the cabinet components library is also built by the three-dimensional modeling.Finally,with recombinant technology and the mapping model between cabinet style and external characteristics,the prototype system based on Visual Studio is proposed.This system actualizes the bidirectional reasoning between product style imagery and the shape features,which can assist designers to produce more creative designs,greatly improve the efficiency of cabinet development and increase the profits of companies.
文摘开关柜上的一些关键部位,比如断路器触头,不能直接安装温度传感器,为了获取合适的温度传感监测点,以实现对开关柜的监测和保护;文中以KYN28A-12型10 k V开关柜为研究对象,建立开关柜三维物理模型,通过Ansys仿真,得到开关柜在额定工况下的温度场分布规律,初步为后续的监测点选取提供仿真理论基础。为应对开关柜复杂的运行条件,笔者对开关柜在环境温度、载流量等不同工况下进行温度场仿真,基于仿真结果和理论分析,最终综合选取了一些温度变化差异较大的母排节点作为温度监测点,并具体分析了这些监测点在不同工况条件下的温升影响差异,验证了文中选取的温度监测点的合理性。
