在数学规划的领域里定义了互逆规划--各自目标函数与约束条件位置相互交换的一对规划.接着指出,尽管互逆规划与对偶规划在表面上似乎类似,但是二者存在5点不同:(1)是否为同一个问题的不同;(2)存在"对偶间隙"与否的不同;(3)设...在数学规划的领域里定义了互逆规划--各自目标函数与约束条件位置相互交换的一对规划.接着指出,尽管互逆规划与对偶规划在表面上似乎类似,但是二者存在5点不同:(1)是否为同一个问题的不同;(2)存在"对偶间隙"与否的不同;(3)设计变量数目的不同;(4)是否单目标与多目标问题的不同;(5)问题合理与否的不同.然后,基于互逆规划的定义,用以审视结构拓扑优化模型,给出如下结果:(1)从这个角度洞悉,在结构优化中,确实有不合理的模型一直被沿用着;(2)找到了修正不合理模型使之合理化的方法;(3)对于给定体积下的柔顺度最小化(MCVC)模型,指出了其不合理的原因;(4)MCVC模型实际是互逆规划的m方,由此建立起其对应的s方,即给出了多个柔顺度约束的体积最小化(MVCC)模型;(5)给出了MVCC模型中的结构柔顺度约束的物理解释和算法,论证了ICM(independent continuous and mapping)方法以往关于全局化应力约束的概念和方法;(6)数值算例表明了MCVC与MVCC模型作为互逆规划的差异,且印证了MVCC模型的合理性.MCVC模型在不同体积约束及多工况下不同的权系数时,得到最优拓扑不同;但MVCC模型在多工况柔顺度约束下可得到唯一的最优拓扑.展开更多
Accurate predictions of sea surface temperature(SST)are crucial due to the significant impact of SST on the global ocean-atmospheric system and its potential to trigger extreme weather events.Many existing machine-lea...Accurate predictions of sea surface temperature(SST)are crucial due to the significant impact of SST on the global ocean-atmospheric system and its potential to trigger extreme weather events.Many existing machine-learning-based ssT predictions adapt the traditional iterative point-wise prediction mechanism,whose predicting horizons and accuracy are limited owing to the high sensitivity to cumulative errors during iterative predictions.Therefore,this paper proposes a novel granulation-based long short-term memory(LsTM)-random forest(RF)combination model that can fully capture the feature dependencies involved in the fluctuation of SsT sequences,reduce the cumulative error in the iteration process,and extend the prediction horizons,which includes two sub-models(adaptive granulation model and hybrid prediction model).They can restack the one-dimensional ssT time-series into multidimensional feature variables,and achieve a strong forecasting ability.The analysis shows that the proposed model can achieve more accurate prediction-hours in nearly all prediction ranges from 1 to 125 h.The average prediction error of the proposed model in 25-125 h is 0.07 K,similar to that(0.067 K)in the first 24 h,which exhibits a high generalization performance and robustness and isthus a promising platform for the medium-and long-term forecasting of hourly SSTs.展开更多
This study addresses the pressing need to assess foundation bearing capacity in Opolo,Yenagoa,Bayelsa State,Nigeria.The significance lies in the dearth of comprehensive geotechnical data for construction planning in t...This study addresses the pressing need to assess foundation bearing capacity in Opolo,Yenagoa,Bayelsa State,Nigeria.The significance lies in the dearth of comprehensive geotechnical data for construction planning in the region.Past research is limited and this study contributes valuable insights by integrating Geographic Information System(GIS)with the Generalized Reciprocal Method(GRM).To collect data,near-surface seismic refraction surveys were conducted along three designated lines,utilizing ABEM Terraloc Mark 6 equipment,Easy Refract,and ArcGIS 10.4.1 software.This methodology allowed for the determination of key geotechnical parameters essential for soil characterization at potential foundation sites.The results revealed three distinct geoseismic layers.The uppermost layer,within a depth of 0.89 to 1.50 meters,exhibited inadequate compressional and shear wave velocities and low values for oedometric modulus,shear modulus,N-value,ultimate bearing capacity,and allowable bearing capacity.This indicates the presence of unsuitable,soft,and weak alluvial deposits for substantial structural loads.In contrast,the second layer(1.52 to 3.84 m depth)displayed favorable geotechnical parameters,making it suitable for various construction loads.The third layer(15.00 to 26.05 m depth)exhibited varying characteristics.The GIS analysis highlighted the unsuitability of the uppermost layer for construction,while the second and third layers were found to be fairly competent and suitable for shallow footing and foundation design.In summary,this study highlights the importance of geotechnical surveys in Opolo’s construction planning.It offers vital information for informed choices,addresses issues in the initial layer,and suggests secure,sustainable construction options.展开更多
The present paper gives the design of a new HGMS for magnetic separation of sulphides.The main characteristics of this HGMS are using iron-cladding saddle shaped magnetic coil for instead of the ordinary magnet,and co...The present paper gives the design of a new HGMS for magnetic separation of sulphides.The main characteristics of this HGMS are using iron-cladding saddle shaped magnetic coil for instead of the ordinary magnet,and combining reciprocal-linear motion with vibration to actuate the separation box,and the magnetic field intensity is high up to 2T as well.For improving the magnet system design,a modified finite element method is used to calculate the distribution of magnetic field intensity of separation space of the magnetic coil,and according to the calculation results the magnetic leakage coefficient can be determined easily,thus making designers apart from the empirical way.展开更多
文摘在数学规划的领域里定义了互逆规划--各自目标函数与约束条件位置相互交换的一对规划.接着指出,尽管互逆规划与对偶规划在表面上似乎类似,但是二者存在5点不同:(1)是否为同一个问题的不同;(2)存在"对偶间隙"与否的不同;(3)设计变量数目的不同;(4)是否单目标与多目标问题的不同;(5)问题合理与否的不同.然后,基于互逆规划的定义,用以审视结构拓扑优化模型,给出如下结果:(1)从这个角度洞悉,在结构优化中,确实有不合理的模型一直被沿用着;(2)找到了修正不合理模型使之合理化的方法;(3)对于给定体积下的柔顺度最小化(MCVC)模型,指出了其不合理的原因;(4)MCVC模型实际是互逆规划的m方,由此建立起其对应的s方,即给出了多个柔顺度约束的体积最小化(MVCC)模型;(5)给出了MVCC模型中的结构柔顺度约束的物理解释和算法,论证了ICM(independent continuous and mapping)方法以往关于全局化应力约束的概念和方法;(6)数值算例表明了MCVC与MVCC模型作为互逆规划的差异,且印证了MVCC模型的合理性.MCVC模型在不同体积约束及多工况下不同的权系数时,得到最优拓扑不同;但MVCC模型在多工况柔顺度约束下可得到唯一的最优拓扑.
基金supported by Second Tibetan Plateau Scientific Expedition and Research Program(STEP)-‘Dynamic monitoring and simulation of water cycle in Asian water tower area’[grant number 2019QZKK0206]Open Fund of the State Key Laboratory of Remote Sensing Science[grant number OFSLRSS202201]+1 种基金Ningxia Science and Technology Department Flexible Introduction talent project[grant number 2021RXTDLX14]Fengyun Application Pioneering Project[grant number FY-APP-2022.0205].
文摘Accurate predictions of sea surface temperature(SST)are crucial due to the significant impact of SST on the global ocean-atmospheric system and its potential to trigger extreme weather events.Many existing machine-learning-based ssT predictions adapt the traditional iterative point-wise prediction mechanism,whose predicting horizons and accuracy are limited owing to the high sensitivity to cumulative errors during iterative predictions.Therefore,this paper proposes a novel granulation-based long short-term memory(LsTM)-random forest(RF)combination model that can fully capture the feature dependencies involved in the fluctuation of SsT sequences,reduce the cumulative error in the iteration process,and extend the prediction horizons,which includes two sub-models(adaptive granulation model and hybrid prediction model).They can restack the one-dimensional ssT time-series into multidimensional feature variables,and achieve a strong forecasting ability.The analysis shows that the proposed model can achieve more accurate prediction-hours in nearly all prediction ranges from 1 to 125 h.The average prediction error of the proposed model in 25-125 h is 0.07 K,similar to that(0.067 K)in the first 24 h,which exhibits a high generalization performance and robustness and isthus a promising platform for the medium-and long-term forecasting of hourly SSTs.
文摘This study addresses the pressing need to assess foundation bearing capacity in Opolo,Yenagoa,Bayelsa State,Nigeria.The significance lies in the dearth of comprehensive geotechnical data for construction planning in the region.Past research is limited and this study contributes valuable insights by integrating Geographic Information System(GIS)with the Generalized Reciprocal Method(GRM).To collect data,near-surface seismic refraction surveys were conducted along three designated lines,utilizing ABEM Terraloc Mark 6 equipment,Easy Refract,and ArcGIS 10.4.1 software.This methodology allowed for the determination of key geotechnical parameters essential for soil characterization at potential foundation sites.The results revealed three distinct geoseismic layers.The uppermost layer,within a depth of 0.89 to 1.50 meters,exhibited inadequate compressional and shear wave velocities and low values for oedometric modulus,shear modulus,N-value,ultimate bearing capacity,and allowable bearing capacity.This indicates the presence of unsuitable,soft,and weak alluvial deposits for substantial structural loads.In contrast,the second layer(1.52 to 3.84 m depth)displayed favorable geotechnical parameters,making it suitable for various construction loads.The third layer(15.00 to 26.05 m depth)exhibited varying characteristics.The GIS analysis highlighted the unsuitability of the uppermost layer for construction,while the second and third layers were found to be fairly competent and suitable for shallow footing and foundation design.In summary,this study highlights the importance of geotechnical surveys in Opolo’s construction planning.It offers vital information for informed choices,addresses issues in the initial layer,and suggests secure,sustainable construction options.
文摘The present paper gives the design of a new HGMS for magnetic separation of sulphides.The main characteristics of this HGMS are using iron-cladding saddle shaped magnetic coil for instead of the ordinary magnet,and combining reciprocal-linear motion with vibration to actuate the separation box,and the magnetic field intensity is high up to 2T as well.For improving the magnet system design,a modified finite element method is used to calculate the distribution of magnetic field intensity of separation space of the magnetic coil,and according to the calculation results the magnetic leakage coefficient can be determined easily,thus making designers apart from the empirical way.
