In the machining process of aircraft monolithic parts,the initial residual stress redistribution and structural stiffness evolution often lead to unexpected distortions.On the other hand,the stress redistribution and ...In the machining process of aircraft monolithic parts,the initial residual stress redistribution and structural stiffness evolution often lead to unexpected distortions.On the other hand,the stress redistribution and stiffness reduction during the machining process depend on the material removal sequence.The essence of the stress redistribution is releasing the initial elastic strain energy.In the present study,the influence of the material removal sequence on the energy release is studied.Moreover,a novel optimization method is proposed for the material removal sequence.In order to evaluate the performance of the proposed method,the mechanism of the machining distortion is firstly analyzed based on the energy principle.Then a calculative model for the machining distortion of long beam parts is established accordingly.Moreover,an energy parameter related to the bending distortion and the procedure of the material removal sequence optimization is defined.Finally,the bending distortion analysis and material removal sequence optimization are performed on a long beam with a Z-shaped cross-section.Furthermore,simulation and experiments are carried out.The obtained results indicate that the optimized sequence results in a low distortion fluctuation and decreases the bending distortion.展开更多
Deep sequencing of small RNAs（sR NA） is widely used in sR NAs studies in plants. In order to investigate the sequencing frequency variation of sR NAs, the same sR NA samples from rice grains were sequenced twice usi...Deep sequencing of small RNAs（sR NA） is widely used in sR NAs studies in plants. In order to investigate the sequencing frequency variation of sR NAs, the same sR NA samples from rice grains were sequenced twice using deep sequencing technique. The sR NAs were classified into three categories, high abundance（〉 100 RPM）, medium abundance（10–100 RPM） and low abundance（1–10 RPM）. According to the repeat sequencing data of the same sample, highly expressed sR NAs（〉 100 RPM） were less subject to random drift, and 95% of the sR NAs Log2 ratio between two samples fell between-0.649 and 0.558. The same trend was observed in mediumly expressed sR NAs（10–100 RPM）, and 95% of the Log2 ratio fell between-0.535 and 0.759. As to lowly expressed sR NAs（1–10 RPM）, 95% of the Log2 ratio varied between-1.009 and 1.011. These results can be used as a theoretical guide to find differentially expressed s RNAs in sR NA studies in plants.展开更多
基金the National Natural Science Foundation of China(No.51405226)。
文摘In the machining process of aircraft monolithic parts,the initial residual stress redistribution and structural stiffness evolution often lead to unexpected distortions.On the other hand,the stress redistribution and stiffness reduction during the machining process depend on the material removal sequence.The essence of the stress redistribution is releasing the initial elastic strain energy.In the present study,the influence of the material removal sequence on the energy release is studied.Moreover,a novel optimization method is proposed for the material removal sequence.In order to evaluate the performance of the proposed method,the mechanism of the machining distortion is firstly analyzed based on the energy principle.Then a calculative model for the machining distortion of long beam parts is established accordingly.Moreover,an energy parameter related to the bending distortion and the procedure of the material removal sequence optimization is defined.Finally,the bending distortion analysis and material removal sequence optimization are performed on a long beam with a Z-shaped cross-section.Furthermore,simulation and experiments are carried out.The obtained results indicate that the optimized sequence results in a low distortion fluctuation and decreases the bending distortion.
基金supported by the National Natural Science Foundation of China(Grant No.31200973)Key Scientific Research Program of Henan Province,China(Grant No.141100110600)
文摘Deep sequencing of small RNAs（sR NA） is widely used in sR NAs studies in plants. In order to investigate the sequencing frequency variation of sR NAs, the same sR NA samples from rice grains were sequenced twice using deep sequencing technique. The sR NAs were classified into three categories, high abundance（〉 100 RPM）, medium abundance（10–100 RPM） and low abundance（1–10 RPM）. According to the repeat sequencing data of the same sample, highly expressed sR NAs（〉 100 RPM） were less subject to random drift, and 95% of the sR NAs Log2 ratio between two samples fell between-0.649 and 0.558. The same trend was observed in mediumly expressed sR NAs（10–100 RPM）, and 95% of the Log2 ratio fell between-0.535 and 0.759. As to lowly expressed sR NAs（1–10 RPM）, 95% of the Log2 ratio varied between-1.009 and 1.011. These results can be used as a theoretical guide to find differentially expressed s RNAs in sR NA studies in plants.
