The in-depth integration of healthy China with national fitness and the hope to achieve the long-term goal of “leading Sports Nation” by 2035, can’t be realized without gyms where people do physical exercise. The i...The in-depth integration of healthy China with national fitness and the hope to achieve the long-term goal of “leading Sports Nation” by 2035, can’t be realized without gyms where people do physical exercise. The international academic community recognizes that the 21<sup>st</sup> century is the golden time for sustainable and quality development. Taking a national perspective, authors of this paper studied the feasibility of building underground gyms in China through the approach of interdisciplinary research, as well as its dilemmas and pathways, and found out that quality development of underground space can effectively address challenges for large cities in China by increasing the resilience of urban area, and give full engage to underground capacity in striving for the goal of carbon peak and carbon neutrality. Underground gyms can also be incorporated into resident’s 15-min fitness circle, satisfying people’s needs of doing exercise at any time and in an easily-accessible place. However, China’s underground area development has been hindered by unclear property rights, chaotic action and utilization, and relatively backward laws and regulations. Moreover, building underground gyms still has to solve many problems such as poor air quality, severe sweat smell, and excessive bacteria and viruses. It is suggested that the capable authorities shall first clarify laws and regulations over place compound utilization, property rights and fire protection to facilitate the process of building underground gyms;encourage fitness practitioners to explore underground areas as gyms, and transfer their ground business to underground;then produce an intelligent and systematic solution of air quality improvement featuring oxygen-enrichment and “sterilization” with integration, a variety of instruments to monitor air quality of indoor gyms in real-time, to realize automatic control and management, and truly create worry-free and oxygen-enriched underground gyms with no sweat smell and no fear of bacteria and viruses.展开更多
大跨空间结构风荷载的取值是该类结构抗风设计关注重点,通常借助风洞试验或数值风洞确定,但其费用高周期长等特点限制其广泛应用.机器学习方法近年受到关注,逐渐应用于结构的风荷载预测并取得了不错的效果.利用核主成分分析(Kernel Prin...大跨空间结构风荷载的取值是该类结构抗风设计关注重点,通常借助风洞试验或数值风洞确定,但其费用高周期长等特点限制其广泛应用.机器学习方法近年受到关注,逐渐应用于结构的风荷载预测并取得了不错的效果.利用核主成分分析(Kernel Principal Component Analysis,KPCA)对数据进行降维处理,借助可以集成学习的XGBoost机器学习模型,采用十折交叉验证对超参数进行选择,编写了基于机器学习的大跨空间结构风荷载预测程序.通过对多个已有工程项目风洞试验结果的学习训练和预测结果比对,证明该方法具有处理数据能力较强、预测效率较高及泛化能力较强等特点.随机选取未参与模型训练的风向角下数据进行模型准确性验证,结果表明模型的R2值均达到0.9左右,预测值与试验值较为接近,体型系数在迎风区的预测精度略低于背风区,而极值风压则在背风区的预测精度好于迎风区.展开更多
文摘The in-depth integration of healthy China with national fitness and the hope to achieve the long-term goal of “leading Sports Nation” by 2035, can’t be realized without gyms where people do physical exercise. The international academic community recognizes that the 21<sup>st</sup> century is the golden time for sustainable and quality development. Taking a national perspective, authors of this paper studied the feasibility of building underground gyms in China through the approach of interdisciplinary research, as well as its dilemmas and pathways, and found out that quality development of underground space can effectively address challenges for large cities in China by increasing the resilience of urban area, and give full engage to underground capacity in striving for the goal of carbon peak and carbon neutrality. Underground gyms can also be incorporated into resident’s 15-min fitness circle, satisfying people’s needs of doing exercise at any time and in an easily-accessible place. However, China’s underground area development has been hindered by unclear property rights, chaotic action and utilization, and relatively backward laws and regulations. Moreover, building underground gyms still has to solve many problems such as poor air quality, severe sweat smell, and excessive bacteria and viruses. It is suggested that the capable authorities shall first clarify laws and regulations over place compound utilization, property rights and fire protection to facilitate the process of building underground gyms;encourage fitness practitioners to explore underground areas as gyms, and transfer their ground business to underground;then produce an intelligent and systematic solution of air quality improvement featuring oxygen-enrichment and “sterilization” with integration, a variety of instruments to monitor air quality of indoor gyms in real-time, to realize automatic control and management, and truly create worry-free and oxygen-enriched underground gyms with no sweat smell and no fear of bacteria and viruses.
文摘大跨空间结构风荷载的取值是该类结构抗风设计关注重点,通常借助风洞试验或数值风洞确定,但其费用高周期长等特点限制其广泛应用.机器学习方法近年受到关注,逐渐应用于结构的风荷载预测并取得了不错的效果.利用核主成分分析(Kernel Principal Component Analysis,KPCA)对数据进行降维处理,借助可以集成学习的XGBoost机器学习模型,采用十折交叉验证对超参数进行选择,编写了基于机器学习的大跨空间结构风荷载预测程序.通过对多个已有工程项目风洞试验结果的学习训练和预测结果比对,证明该方法具有处理数据能力较强、预测效率较高及泛化能力较强等特点.随机选取未参与模型训练的风向角下数据进行模型准确性验证,结果表明模型的R2值均达到0.9左右,预测值与试验值较为接近,体型系数在迎风区的预测精度略低于背风区,而极值风压则在背风区的预测精度好于迎风区.
