Accurate knowledge of who knows whom in organizations have important benefits for individual work performance and managerial decision making,but people are not very accurate when recalling connections among others in ...Accurate knowledge of who knows whom in organizations have important benefits for individual work performance and managerial decision making,but people are not very accurate when recalling connections among others in their social networks.The present study investigates how holisticanalytic thinking styles influence the extent people can accurately perceive network relationships and choose the right persons to form a coalition in a fictious persuasive task We focused on two dimensions of holistic-analytic thinking style,namely attention to field(as opposed to parts)and interactionist(as opposed to dispositionist)causal theory Results from 281 participants reveals that while individuals with greater attention to field were more accurate in recalling relationships in asocial network those inclined toward interactionism in causal theory were less accurate Furthermore,greater attention to field enhanced the effectiveness of coalition member selection,in part through the mediationof accurate network perception;while interactionism,via the full mediation of network perception,indirectly led to less effective coalition choice.展开更多
The study of the spallation of thermal barrier coatings on turbine blades and its influence is of great significance for gas turbine safety operation.However,numerical simulation related to thermal barrier coatings is...The study of the spallation of thermal barrier coatings on turbine blades and its influence is of great significance for gas turbine safety operation.However,numerical simulation related to thermal barrier coatings is difficult and time-costly,which makes it hard to meet engineering demands.Therefore,this work establishes a rapid prediction model for the surface temperature and cooling efficiency of turbine blades with localized spallation of thermal barrier coatings based on a thin-wall thermal resistance model.Firstly,the influence of localized spallation of thermal barrier coatings on the cooling efficiency of typical turbine blades is numerically investigated.Then,based on the simulation data set and multi-layer perception(MLP)neural network,an intelligent prediction model for the temperature and cooling efficiency distribution of localized spallation of coatings is constructed,which can rapidly predict the surface temperature and cooling efficiency of the blade under the situation of spallation of coating at any position on the blade surface.The results show that,under a certain spallation area,the shape of localized coating spallation has little influence on the cooling efficiency,while the increase of spallation thickness will cause a linear increase in the average temperature of the blade surface.The prediction error of the proposed rapid prediction model for the average surface temperature and cooling efficiency of blades is within 2%,and the prediction error of the temperature and cooling efficiency at the spallation position is within 6%for 80%of the samples,with an overall average error within 10%.It is concluded from the rapid prediction model that when the depth of coating spallation increases,the closer the spallation position is to the leading edge of the blade,the greater the difference in cooling efficiency is,and the degree of influence of coating spallation on the cooling efficiency also increases.展开更多
基金Supported by National Natural Science Foundation of China(71872171)。
文摘Accurate knowledge of who knows whom in organizations have important benefits for individual work performance and managerial decision making,but people are not very accurate when recalling connections among others in their social networks.The present study investigates how holisticanalytic thinking styles influence the extent people can accurately perceive network relationships and choose the right persons to form a coalition in a fictious persuasive task We focused on two dimensions of holistic-analytic thinking style,namely attention to field(as opposed to parts)and interactionist(as opposed to dispositionist)causal theory Results from 281 participants reveals that while individuals with greater attention to field were more accurate in recalling relationships in asocial network those inclined toward interactionism in causal theory were less accurate Furthermore,greater attention to field enhanced the effectiveness of coalition member selection,in part through the mediationof accurate network perception;while interactionism,via the full mediation of network perception,indirectly led to less effective coalition choice.
基金supported by the National Natural Science Foundation of China(No.52206090)the Jiangsu Provincial Natural Science Foundation(No.BK20220901)+2 种基金the National Major Science and Technology Projects of China(No.Y2022-Ⅲ-0004-0013)Engineering Research Center of Low-Carbon Aerospace Power Ministry of Education(No.CEPE2024020)the China Postdoctoral Science Foundation(No.2022TQ0149).
文摘The study of the spallation of thermal barrier coatings on turbine blades and its influence is of great significance for gas turbine safety operation.However,numerical simulation related to thermal barrier coatings is difficult and time-costly,which makes it hard to meet engineering demands.Therefore,this work establishes a rapid prediction model for the surface temperature and cooling efficiency of turbine blades with localized spallation of thermal barrier coatings based on a thin-wall thermal resistance model.Firstly,the influence of localized spallation of thermal barrier coatings on the cooling efficiency of typical turbine blades is numerically investigated.Then,based on the simulation data set and multi-layer perception(MLP)neural network,an intelligent prediction model for the temperature and cooling efficiency distribution of localized spallation of coatings is constructed,which can rapidly predict the surface temperature and cooling efficiency of the blade under the situation of spallation of coating at any position on the blade surface.The results show that,under a certain spallation area,the shape of localized coating spallation has little influence on the cooling efficiency,while the increase of spallation thickness will cause a linear increase in the average temperature of the blade surface.The prediction error of the proposed rapid prediction model for the average surface temperature and cooling efficiency of blades is within 2%,and the prediction error of the temperature and cooling efficiency at the spallation position is within 6%for 80%of the samples,with an overall average error within 10%.It is concluded from the rapid prediction model that when the depth of coating spallation increases,the closer the spallation position is to the leading edge of the blade,the greater the difference in cooling efficiency is,and the degree of influence of coating spallation on the cooling efficiency also increases.
