Carbon fiber composites,characterized by their high specific strength and low weight,are becoming increasingly crucial in automotive lightweighting.However,current research primarily emphasizes layer count and orienta...Carbon fiber composites,characterized by their high specific strength and low weight,are becoming increasingly crucial in automotive lightweighting.However,current research primarily emphasizes layer count and orientation,often neglecting the potential of microstructural design,constraints in the layup process,and performance reliability.This study,therefore,introduces a multiscale reliability-based design optimization method for carbon fiber-reinforced plastic(CFRP)drive shafts.Initially,parametric modeling of the microscale cell was performed,and its elastic performance parameters were predicted using two homogenization methods,examining the impact of fluctuations in microscale cell parameters on composite material performance.A finite element model of the CFRP drive shaft was then constructed,achieving parameter transfer between microscale and macroscale through Python programming.This enabled an investigation into the influence of both micro and macro design parameters on the CFRP drive shaft’s performance.The Multi-Objective Particle Swarm Optimization(MOPSO)algorithm was enhanced for particle generation and updating strategies,facilitating the resolution of multi-objective reliability optimization problems,including composite material layup process constraints.Case studies demonstrated that this approach leads to over 30%weight reduction in CFRP drive shafts compared to metallic counterparts while satisfying reliability requirements and offering insights for the lightweight design of other vehicle components.展开更多
Objective:To analyze the application of deep inspiration breath hold technique in radiotherapy after breast-conserving surgery for left breast cancer and the improvement of cardiac dose.Methods:A total of 45 patients ...Objective:To analyze the application of deep inspiration breath hold technique in radiotherapy after breast-conserving surgery for left breast cancer and the improvement of cardiac dose.Methods:A total of 45 patients with left breast cancer treated in our hospital after breast-conserving surgery were selected,and the selection time was set from January 2020 to August 2022.All patients received radiotherapy.The right breast,heart,and lung volumes,and dose parameters of the heart,lungs,right breast,and left anterior descending coronary artery were compared under free breathing(FB)and deep inspiration breath hold(DIBH)technical modes.Results:The heart volume of the DIBH group was smaller than that of the FB group,and the left and right lung volumes were significantly larger than those of the FB group.In the DIBH group,the heart dose parameters V5,proper lung dose parameters,and left anterior descending coronary artery dose parameters were found lower than that of the FB group,and the differences were statistically significant(P<0.05).Conclusion:Compared with FB,the DIBH technique can reduce the heart’s size and increase the lung volume when used for radiotherapy after breast-conserving surgery for left breast cancer.It also reduces the dose to the heart,right lung,and left anterior descending coronary artery,thus protecting the heart and lungs.展开更多
The MGM(1,m,N)model is an effective grey multi-variate forecasting model that considers multiple system characteristic sequences affected by multiplefactors.Nevertheless,it isregularly inaccurate in the application Th...The MGM(1,m,N)model is an effective grey multi-variate forecasting model that considers multiple system characteristic sequences affected by multiplefactors.Nevertheless,it isregularly inaccurate in the application This is because the model requires a strong correlation between the system characteristic sequences That reduces the applicability of the model.To solve this problem,this paper proposes a novel multi-variate grey model.This model does not require a certain correlation between system characteristic sequences and has higher applicability Through numerical integration,a two-point trapezoidal formula,and a recursive method,thetime-response expressions ofthetwo model forms are obtained Some properties of the proposed model are further discussed Finally,the validity of the proposed model is evaluated by using two real cases related to China's invention patent development.Theresultsshow that the novel models outperformother models inbothsimulation and prediction applications.展开更多
基金supported by the S&T Special Program of Huzhou(Grant No.2023GZ09)the Open Fund Project of the ShanghaiKey Laboratory of Lightweight Structural Composites(Grant No.2232021A4-06).
文摘Carbon fiber composites,characterized by their high specific strength and low weight,are becoming increasingly crucial in automotive lightweighting.However,current research primarily emphasizes layer count and orientation,often neglecting the potential of microstructural design,constraints in the layup process,and performance reliability.This study,therefore,introduces a multiscale reliability-based design optimization method for carbon fiber-reinforced plastic(CFRP)drive shafts.Initially,parametric modeling of the microscale cell was performed,and its elastic performance parameters were predicted using two homogenization methods,examining the impact of fluctuations in microscale cell parameters on composite material performance.A finite element model of the CFRP drive shaft was then constructed,achieving parameter transfer between microscale and macroscale through Python programming.This enabled an investigation into the influence of both micro and macro design parameters on the CFRP drive shaft’s performance.The Multi-Objective Particle Swarm Optimization(MOPSO)algorithm was enhanced for particle generation and updating strategies,facilitating the resolution of multi-objective reliability optimization problems,including composite material layup process constraints.Case studies demonstrated that this approach leads to over 30%weight reduction in CFRP drive shafts compared to metallic counterparts while satisfying reliability requirements and offering insights for the lightweight design of other vehicle components.
文摘Objective:To analyze the application of deep inspiration breath hold technique in radiotherapy after breast-conserving surgery for left breast cancer and the improvement of cardiac dose.Methods:A total of 45 patients with left breast cancer treated in our hospital after breast-conserving surgery were selected,and the selection time was set from January 2020 to August 2022.All patients received radiotherapy.The right breast,heart,and lung volumes,and dose parameters of the heart,lungs,right breast,and left anterior descending coronary artery were compared under free breathing(FB)and deep inspiration breath hold(DIBH)technical modes.Results:The heart volume of the DIBH group was smaller than that of the FB group,and the left and right lung volumes were significantly larger than those of the FB group.In the DIBH group,the heart dose parameters V5,proper lung dose parameters,and left anterior descending coronary artery dose parameters were found lower than that of the FB group,and the differences were statistically significant(P<0.05).Conclusion:Compared with FB,the DIBH technique can reduce the heart’s size and increase the lung volume when used for radiotherapy after breast-conserving surgery for left breast cancer.It also reduces the dose to the heart,right lung,and left anterior descending coronary artery,thus protecting the heart and lungs.
基金Supported bythe National Natural Science Foundation of China(71701105)the Major Program of the National Social Science Fund of China(17ZDA092)+1 种基金the Key Research Project of Philosophy and Social Sciences in Universities of Jiangsu Province(2018SJZDI111)Key Projects of Open Topics of Jiangsu Productivity Society in2020(JSSCL2020A004)。
文摘The MGM(1,m,N)model is an effective grey multi-variate forecasting model that considers multiple system characteristic sequences affected by multiplefactors.Nevertheless,it isregularly inaccurate in the application This is because the model requires a strong correlation between the system characteristic sequences That reduces the applicability of the model.To solve this problem,this paper proposes a novel multi-variate grey model.This model does not require a certain correlation between system characteristic sequences and has higher applicability Through numerical integration,a two-point trapezoidal formula,and a recursive method,thetime-response expressions ofthetwo model forms are obtained Some properties of the proposed model are further discussed Finally,the validity of the proposed model is evaluated by using two real cases related to China's invention patent development.Theresultsshow that the novel models outperformother models inbothsimulation and prediction applications.
