To meet the requirements of specifications,intelligent optimization of steel bar blanking can improve resource utilization and promote the intelligent development of sustainable construction.As one of the most importa...To meet the requirements of specifications,intelligent optimization of steel bar blanking can improve resource utilization and promote the intelligent development of sustainable construction.As one of the most important building materials in construction engineering,reinforcing bars(rebar)account for more than 30%of the cost in civil engineering.A significant amount of cutting waste is generated during the construction phase.Excessive cutting waste increases construction costs and generates a considerable amount of CO_(2)emission.This study aimed to develop an optimization algorithm for steel bar blanking that can be used in the intelligent optimization of steel bar engineering to realize sustainable construction.In the proposed algorithm,the integer linear programming algorithm was applied to solve the problem.It was combined with the statistical method,a greedy strategy was introduced,and a method for determining the dynamic critical threshold was developed to ensure the accuracy of large-scale data calculation.The proposed algorithm was verified through a case study;the results confirmed that the rebar loss rate of the proposed method was reduced by 9.124%compared with that of traditional distributed processing of steel bars,reducing CO_(2)emissions and saving construction costs.As the scale of a project increases,the calculation quality of the optimization algorithmfor steel bar blanking proposed also increases,while maintaining high calculation efficiency.When the results of this study are applied in practice,they can be used as a sustainable foundation for building informatization and intelligent development.展开更多
Indoor thermal comfort and passive solar heating technologies have been extensively studied.However,few studies have explored the suitability of passive solar heating technologies based on differentiated thermal comfo...Indoor thermal comfort and passive solar heating technologies have been extensively studied.However,few studies have explored the suitability of passive solar heating technologies based on differentiated thermal comfort demands.This work took the rural dwellings in Northwest China as the research object.First,the current indoor and outdoor thermal environment in winter and the mechanism of residents’differentiated demand for indoor thermal comfort were obtained through tests,questionnaires,and statistical analysis.Second,a comprehensive passive optimized design of existing buildings was conducted,and the validity of the optimized combination scheme was explored using DesignBuilder software.Finally,the suitability of passive solar heating technology for each region in Northwest China was analyzed based on residents’differentiated demand for indoor thermal comfort.The regions were then classified according to the suitability of the technology for these.The results showed that the indoor heating energy consumption was high and the indoor thermal environment was not ideal,yet the solar energy resources were abundant.Indoor comfort temperature indexes that match the functional rooms and usage periods were proposed.For the buildings with the optimized combination scheme,the average indoor temperature was increased significantly and the temperature fluctuation was decreased dramatically.Most regions in Northwest China were suitable for the development of passive solar heating technology.Based on the obtained suitability of the technology for the regions of Northwest China,these were classified into most suitable,more suitable,less suitable,and unsuitable regions.展开更多
基金funded by Nature Science Foundation of China(51878556)the Key Scientific Research Projects of Shaanxi Provincial Department of Education(20JY049)+1 种基金Key Research and Development Program of Shaanxi Province(2019TD-014)State Key Laboratory of Rail Transit Engineering Informatization(FSDI)(SKLKZ21-03).
文摘To meet the requirements of specifications,intelligent optimization of steel bar blanking can improve resource utilization and promote the intelligent development of sustainable construction.As one of the most important building materials in construction engineering,reinforcing bars(rebar)account for more than 30%of the cost in civil engineering.A significant amount of cutting waste is generated during the construction phase.Excessive cutting waste increases construction costs and generates a considerable amount of CO_(2)emission.This study aimed to develop an optimization algorithm for steel bar blanking that can be used in the intelligent optimization of steel bar engineering to realize sustainable construction.In the proposed algorithm,the integer linear programming algorithm was applied to solve the problem.It was combined with the statistical method,a greedy strategy was introduced,and a method for determining the dynamic critical threshold was developed to ensure the accuracy of large-scale data calculation.The proposed algorithm was verified through a case study;the results confirmed that the rebar loss rate of the proposed method was reduced by 9.124%compared with that of traditional distributed processing of steel bars,reducing CO_(2)emissions and saving construction costs.As the scale of a project increases,the calculation quality of the optimization algorithmfor steel bar blanking proposed also increases,while maintaining high calculation efficiency.When the results of this study are applied in practice,they can be used as a sustainable foundation for building informatization and intelligent development.
基金supported by the National Natural Science Foundation of China(Grant Nos.52078419 and 51678483)supported by the Doctoral Dissertation Innovation Fund of Xi’an University of Technology(310–252072116).
文摘Indoor thermal comfort and passive solar heating technologies have been extensively studied.However,few studies have explored the suitability of passive solar heating technologies based on differentiated thermal comfort demands.This work took the rural dwellings in Northwest China as the research object.First,the current indoor and outdoor thermal environment in winter and the mechanism of residents’differentiated demand for indoor thermal comfort were obtained through tests,questionnaires,and statistical analysis.Second,a comprehensive passive optimized design of existing buildings was conducted,and the validity of the optimized combination scheme was explored using DesignBuilder software.Finally,the suitability of passive solar heating technology for each region in Northwest China was analyzed based on residents’differentiated demand for indoor thermal comfort.The regions were then classified according to the suitability of the technology for these.The results showed that the indoor heating energy consumption was high and the indoor thermal environment was not ideal,yet the solar energy resources were abundant.Indoor comfort temperature indexes that match the functional rooms and usage periods were proposed.For the buildings with the optimized combination scheme,the average indoor temperature was increased significantly and the temperature fluctuation was decreased dramatically.Most regions in Northwest China were suitable for the development of passive solar heating technology.Based on the obtained suitability of the technology for the regions of Northwest China,these were classified into most suitable,more suitable,less suitable,and unsuitable regions.
