Three-dimensional ocean subsurface temperature and salinity structures(OST/OSS)in the South China Sea(SCS)play crucial roles in oceanic climate research and disaster mitigation.Traditionally,real-time OST and OSS are ...Three-dimensional ocean subsurface temperature and salinity structures(OST/OSS)in the South China Sea(SCS)play crucial roles in oceanic climate research and disaster mitigation.Traditionally,real-time OST and OSS are mainly obtained through in-situ ocean observations and simulation by ocean circulation models,which are usually challenging and costly.Recently,dynamical,statistical,or machine learning models have been proposed to invert the OST/OSS from sea surface information;however,these models mainly focused on the inversion of monthly OST and OSS.To address this issue,we apply clustering algorithms and employ a stacking strategy to ensemble three models(XGBoost,Random Forest,and LightGBM)to invert the real-time OST/OSS based on satellite-derived data and the Argo dataset.Subsequently,a fusion of temperature and salinity is employed to reconstruct OST and OSS.In the validation dataset,the depth-averaged Correlation(Corr)of the estimated OST(OSS)is 0.919(0.83),and the average Root-Mean-Square Error(RMSE)is0.639°C(0.087 psu),with a depth-averaged coefficient of determination(R~2)of 0.84(0.68).Notably,at the thermocline where the base models exhibit their maximum error,the stacking-based fusion model exhibited significant performance enhancement,with a maximum enhancement in OST and OSS inversion exceeding 10%.We further found that the estimated OST and OSS exhibit good agreement with the HYbrid Coordinate Ocean Model(HYCOM)data and BOA_Argo dataset during the passage of a mesoscale eddy.This study shows that the proposed model can effectively invert the real-time OST and OSS,potentially enhancing the understanding of multi-scale oceanic processes in the SCS.展开更多
Spacecraft in the aerospace field and military equipment in the military field are at risk of being impacted by external objects,which can cause local damage to the structure.The randomness of local damage is a newcha...Spacecraft in the aerospace field and military equipment in the military field are at risk of being impacted by external objects,which can cause local damage to the structure.The randomness of local damage is a newchallenge for structural design,and it is essential to take random damage into account in the conceptual design phase for the purpose of improving structure’s resistance to external shocks.In this article,a random damaged structure is assumed to have damages of the same size and shape at random locations,and the random damage is considered as multiple damage conditions of the structure.In order to improve the randomness and comprehensiveness of the multiple damage conditions,the stacking strategy is used to generate the distribution of the damage area.Following this strategy,the topology optimization design of the random damaged structure,which is to minimize the weight of the structure with a constraint on the stress of the structure under multiple damage conditions,is formulated based on the independent continuousmapping(ICM)method.The dual sequence quadratic programming(DSQP)algorithm combined with the stress globalization method is adopted to solve the optimization problem.The numerical examples demonstrate the effectiveness and applicability of the proposed method in the topology optimization of strength-safe continuum structures.展开更多
基金jointly supported by the National Key Research and Development Program of China(2022YFC3104304)the National Natural Science Foundation of China(Grant No.41876011)+1 种基金the 2022 Research Program of Sanya Yazhou Bay Science and Technology City(SKJC-2022-01-001)the Hainan Province Science and Technology Special Fund(ZDYF2021SHFZ265)。
文摘Three-dimensional ocean subsurface temperature and salinity structures(OST/OSS)in the South China Sea(SCS)play crucial roles in oceanic climate research and disaster mitigation.Traditionally,real-time OST and OSS are mainly obtained through in-situ ocean observations and simulation by ocean circulation models,which are usually challenging and costly.Recently,dynamical,statistical,or machine learning models have been proposed to invert the OST/OSS from sea surface information;however,these models mainly focused on the inversion of monthly OST and OSS.To address this issue,we apply clustering algorithms and employ a stacking strategy to ensemble three models(XGBoost,Random Forest,and LightGBM)to invert the real-time OST/OSS based on satellite-derived data and the Argo dataset.Subsequently,a fusion of temperature and salinity is employed to reconstruct OST and OSS.In the validation dataset,the depth-averaged Correlation(Corr)of the estimated OST(OSS)is 0.919(0.83),and the average Root-Mean-Square Error(RMSE)is0.639°C(0.087 psu),with a depth-averaged coefficient of determination(R~2)of 0.84(0.68).Notably,at the thermocline where the base models exhibit their maximum error,the stacking-based fusion model exhibited significant performance enhancement,with a maximum enhancement in OST and OSS inversion exceeding 10%.We further found that the estimated OST and OSS exhibit good agreement with the HYbrid Coordinate Ocean Model(HYCOM)data and BOA_Argo dataset during the passage of a mesoscale eddy.This study shows that the proposed model can effectively invert the real-time OST and OSS,potentially enhancing the understanding of multi-scale oceanic processes in the SCS.
基金supported by the National Natural Science Foundation of China (Grant 11872080).
文摘Spacecraft in the aerospace field and military equipment in the military field are at risk of being impacted by external objects,which can cause local damage to the structure.The randomness of local damage is a newchallenge for structural design,and it is essential to take random damage into account in the conceptual design phase for the purpose of improving structure’s resistance to external shocks.In this article,a random damaged structure is assumed to have damages of the same size and shape at random locations,and the random damage is considered as multiple damage conditions of the structure.In order to improve the randomness and comprehensiveness of the multiple damage conditions,the stacking strategy is used to generate the distribution of the damage area.Following this strategy,the topology optimization design of the random damaged structure,which is to minimize the weight of the structure with a constraint on the stress of the structure under multiple damage conditions,is formulated based on the independent continuousmapping(ICM)method.The dual sequence quadratic programming(DSQP)algorithm combined with the stress globalization method is adopted to solve the optimization problem.The numerical examples demonstrate the effectiveness and applicability of the proposed method in the topology optimization of strength-safe continuum structures.
