To find out the reason of resulting in the crease recovery of a fabric and provide theoretical guidance for designing a new material with good creasing-recovery property,the relationship between the creasing-recovery ...To find out the reason of resulting in the crease recovery of a fabric and provide theoretical guidance for designing a new material with good creasing-recovery property,the relationship between the creasing-recovery force and the crease-recovery angle of a woven fabric was investigated by self-setup experimental device.The results show that the crease-recovery angle of a woven fabric is correlated with the creasing-recovery force of the fabric in a linear relation.Furthermore,it is found that the internal stress is the principal force of affecting the creasing-recovery property of a woven fabric.In addition,the relationship between the tensile property of a woven fabric and the creasing-recovery property of the fabric has also been investigated,showing that the lower relaxation velocity of tensile stress of a fabric is,the better creasing-recovery property of the fabric has.展开更多
The resistance loss of transportation was studied and the influences of buoyancy layout,mineral content and elastic modulus of flexible hose were investigated based on three-dimensional finite element model of fluid-s...The resistance loss of transportation was studied and the influences of buoyancy layout,mineral content and elastic modulus of flexible hose were investigated based on three-dimensional finite element model of fluid-solid interaction by MSC.MARC/MENTAT software.The numerical results show that the resistance losses increase with the increase of mineral content Cv and velocity of internal fluid v and decrease with the increase of elastic modulus E of flexible hose.The buoyancy layout and the velocity of internal fluid have greater impacts on the resistance losses than the elastic modulus of flexible hose.In order to reduce the resistance losses and improve the efficiency of the deep-ocean mining,Cv and v must be restricted in a suitable range (e.g.10%-25% and 2.5-4 m/s).Effective buoyancy layout (such as Scheme C and D) should be adopted and the suitable material of moderate E should be used for the flexible hose in deep-ocean mining.展开更多
The recently developed quasi-analytical algo-rithm (QAA) is a promising algorithm for deriving inherentoptical properties from ocean color. Unlike the conventionalsemi-analytical algorithm, QAA does not need a priorik...The recently developed quasi-analytical algo-rithm (QAA) is a promising algorithm for deriving inherentoptical properties from ocean color. Unlike the conventionalsemi-analytical algorithm, QAA does not need a prioriknowledge of the spectral shape of chlorophyll absorption.However, several empirical relations, which may not be uni-versally applicable and can result in low noise tolerance, areinvolved in QAA. In this study, the Bayesian inversion theoryis introduced to improve the performance of QAA. In theestimation of total absorption coefficient at the referencewavelength, instead of empirical algorithms used in the QAAthe Bayesian approach is employed in combination with anoptical model that uses separate parameters to account ex-plicitly for the contribution of molecular and particle scat-terings to remote sensing reflectance, a priori knowledgeproduced by the QAA, the Akaike’s Bayesian informationcriterion (ABIC) for choosing the optimal regularizationparameter, and genetic algorithms for global optimization.Coefficients at other wavelengths are then derived using anempirical estimate of particle backscattering spectral shape.When applied to a simulated dataset synthesized by IOCCG,the Bayesian algorithm outperforms QAA algorithm, espe-cially in higher chlorophyll concentration waters. The rootmean square errors (RMSEs) between the true and the de-rived a(440) and bb(440) are reduced from 0.918 and 0.039m–1 for QAA-555 to 0.367 and 0.023 m–1 for Bayes-555, 0.205and 0.007 m–1 for QAA-640 to 0.092 and 0.005 m–1 forBayes-640, and 0.207 and 0.007 m–1 for QAA-blending to0.096 and 0.005 m–1 for Bayes-blending. Results of noise sen-sitivity analysis show that the Bayesian algorithm is morerobust than QAA.展开更多
文摘To find out the reason of resulting in the crease recovery of a fabric and provide theoretical guidance for designing a new material with good creasing-recovery property,the relationship between the creasing-recovery force and the crease-recovery angle of a woven fabric was investigated by self-setup experimental device.The results show that the crease-recovery angle of a woven fabric is correlated with the creasing-recovery force of the fabric in a linear relation.Furthermore,it is found that the internal stress is the principal force of affecting the creasing-recovery property of a woven fabric.In addition,the relationship between the tensile property of a woven fabric and the creasing-recovery property of the fabric has also been investigated,showing that the lower relaxation velocity of tensile stress of a fabric is,the better creasing-recovery property of the fabric has.
基金Project(2006AA09Z240)supported by the National High Technology Research and Development Program of China
文摘The resistance loss of transportation was studied and the influences of buoyancy layout,mineral content and elastic modulus of flexible hose were investigated based on three-dimensional finite element model of fluid-solid interaction by MSC.MARC/MENTAT software.The numerical results show that the resistance losses increase with the increase of mineral content Cv and velocity of internal fluid v and decrease with the increase of elastic modulus E of flexible hose.The buoyancy layout and the velocity of internal fluid have greater impacts on the resistance losses than the elastic modulus of flexible hose.In order to reduce the resistance losses and improve the efficiency of the deep-ocean mining,Cv and v must be restricted in a suitable range (e.g.10%-25% and 2.5-4 m/s).Effective buoyancy layout (such as Scheme C and D) should be adopted and the suitable material of moderate E should be used for the flexible hose in deep-ocean mining.
基金This work was supported by the“863”Program of China(Grant No.2004AA639860)the National Natural Science Foundation of China(Grant No.40306028)the Guangdong Natural Science Foundation(Grant No.32616).
文摘The recently developed quasi-analytical algo-rithm (QAA) is a promising algorithm for deriving inherentoptical properties from ocean color. Unlike the conventionalsemi-analytical algorithm, QAA does not need a prioriknowledge of the spectral shape of chlorophyll absorption.However, several empirical relations, which may not be uni-versally applicable and can result in low noise tolerance, areinvolved in QAA. In this study, the Bayesian inversion theoryis introduced to improve the performance of QAA. In theestimation of total absorption coefficient at the referencewavelength, instead of empirical algorithms used in the QAAthe Bayesian approach is employed in combination with anoptical model that uses separate parameters to account ex-plicitly for the contribution of molecular and particle scat-terings to remote sensing reflectance, a priori knowledgeproduced by the QAA, the Akaike’s Bayesian informationcriterion (ABIC) for choosing the optimal regularizationparameter, and genetic algorithms for global optimization.Coefficients at other wavelengths are then derived using anempirical estimate of particle backscattering spectral shape.When applied to a simulated dataset synthesized by IOCCG,the Bayesian algorithm outperforms QAA algorithm, espe-cially in higher chlorophyll concentration waters. The rootmean square errors (RMSEs) between the true and the de-rived a(440) and bb(440) are reduced from 0.918 and 0.039m–1 for QAA-555 to 0.367 and 0.023 m–1 for Bayes-555, 0.205and 0.007 m–1 for QAA-640 to 0.092 and 0.005 m–1 forBayes-640, and 0.207 and 0.007 m–1 for QAA-blending to0.096 and 0.005 m–1 for Bayes-blending. Results of noise sen-sitivity analysis show that the Bayesian algorithm is morerobust than QAA.
