针对多部位损伤(Multiple Site Damage,MSD)结构安全性评估问题,通过Monte-Carlo方法对MSD结构的失效概率进行预测和分析。首先,基于多孔铝板的多裂纹萌生试验,得出裂纹萌生寿命服从对数正态分布,为多裂纹萌生分析提供支持;通过多孔铝...针对多部位损伤(Multiple Site Damage,MSD)结构安全性评估问题,通过Monte-Carlo方法对MSD结构的失效概率进行预测和分析。首先,基于多孔铝板的多裂纹萌生试验,得出裂纹萌生寿命服从对数正态分布,为多裂纹萌生分析提供支持;通过多孔铝板的剩余强度试验得到铆钉孔直径、铆钉孔间距和裂纹萌生位置对结构剩余强度均有一定影响。其次,通过对裂纹萌生寿命分布进行随机抽样生成初始裂纹并使用组合法结合Paris公式,实现多裂纹随机扩展的模拟;在试验数据基础上,对传统的Irwin塑性区连通准则进行改进,发现改进的Irwin塑性区连通准则在孔间距大于10mm时的误差大大降低,并结合净截面屈服准则以获得更好的剩余强度预测结果;将随机性的裂纹萌生和扩展过程与确定性的剩余强度预测方法相结合,建立基于Monte-Carlo方法的MSD结构的失效概率预测模型。最后,通过算例分析,该模型能够得到MSD结构的失效概率曲线,实现结构安全性评估。结果表明MSD结构的失效概率会在短时间内迅速增加,需要在裂纹萌生寿命附近进行限制。展开更多
The investigation was carried out on the technical problems of finishing the inner surface of elbow parts and the action mechanism of particles in elbow precision machining by abrasive flow.This work was analyzed and ...The investigation was carried out on the technical problems of finishing the inner surface of elbow parts and the action mechanism of particles in elbow precision machining by abrasive flow.This work was analyzed and researched by combining theory,numerical and experimental methods.The direct simulation Monte Carlo(DSMC)method and the finite element analysis method were combined to reveal the random collision of particles during the precision machining of abrasive flow.Under different inlet velocity,volume fraction and abrasive particle size,the dynamic pressure and turbulence flow energy of abrasive flow in elbow were analyzed,and the machining mechanism of particles on the wall and the influence of different machining parameters on the precision machining quality of abrasive flow were obtained.The test results show the order of the influence of different parameters on the quality of abrasive flow precision machining and establish the optimal process parameters.The results of the surface morphology before and after the precision machining of the inner surface of the elbow are discussed,and the surface roughness Ra value is reduced from 1.125μm to 0.295μm after the precision machining of the abrasive flow.The application of DSMC method provides special insights for the development of abrasive flow technology.展开更多
The modified sum-peak method estimates radioactivity by using only the peak and the sum-peak count rates.To verify the modified sum-peak method,the dependence of the full energy peak efficiency on the source-to-detect...The modified sum-peak method estimates radioactivity by using only the peak and the sum-peak count rates.To verify the modified sum-peak method,the dependence of the full energy peak efficiency on the source-to-detector distance in a high-purity germanium detector system was studied using a Geant4 Monte Carlo simulation.The effect of the deadlayer in the germanium crystal was estimated by reference to experiments on 241 Am and the relative efficiency of the detector.The peak efficiency dependence on the source-to-detector distance was compared between the simulation and measurements.The modified sum-peak method is discussed with respect to these peak efficiencies.展开更多
Measurement uncertainty plays an important role in laser tracking measurement analyses. In the present work, the guides to the expression of uncertainty in measurement(GUM) uncertainty framework(GUF) and its supplemen...Measurement uncertainty plays an important role in laser tracking measurement analyses. In the present work, the guides to the expression of uncertainty in measurement(GUM) uncertainty framework(GUF) and its supplement, the Monte Carlo method, were used to estimate the uncertainty of task-specific laser tracker measurements. First, the sources of error in laser tracker measurement were analyzed in detail, including instruments, measuring network fusion, measurement strategies, measurement process factors(such as the operator), measurement environment, and task-specific data processing. Second, the GUM and Monte Carlo methods and their application to laser tracker measurement were presented. Finally, a case study involving the uncertainty estimation of a cylindricity measurement process using the GUF and Monte Carlo methods was illustrated. The expanded uncertainty results(at 95% confidence levels) obtained with the Monte Carlo method are 0.069 mm(least-squares criterion) and 0.062 mm(minimum zone criterion), respectively, while with the GUM uncertainty framework, none but the result of least-squares criterion can be got, which is 0.071 mm. Thus, the GUM uncertainty framework slightly underestimates the overall uncertainty by 10%. The results demonstrate that the two methods have different characteristics in task-specific uncertainty evaluations of laser tracker measurements. The results indicate that the Monte Carlo method is a practical tool for applying the principle of propagation of distributions and does not depend on the assumptions and limitations required by the law of propagation of uncertainties(GUF). These features of the Monte Carlo method reduce the risk of an unreliable measurement of uncertainty estimation, particularly in cases of complicated measurement models, without the need to evaluate partial derivatives. In addition, the impact of sampling strategy and evaluation method on the uncertainty of the measurement results can also be taken into account with Monte Carlo method, which plays a guiding role in measurement planning.展开更多
文摘针对多部位损伤(Multiple Site Damage,MSD)结构安全性评估问题,通过Monte-Carlo方法对MSD结构的失效概率进行预测和分析。首先,基于多孔铝板的多裂纹萌生试验,得出裂纹萌生寿命服从对数正态分布,为多裂纹萌生分析提供支持;通过多孔铝板的剩余强度试验得到铆钉孔直径、铆钉孔间距和裂纹萌生位置对结构剩余强度均有一定影响。其次,通过对裂纹萌生寿命分布进行随机抽样生成初始裂纹并使用组合法结合Paris公式,实现多裂纹随机扩展的模拟;在试验数据基础上,对传统的Irwin塑性区连通准则进行改进,发现改进的Irwin塑性区连通准则在孔间距大于10mm时的误差大大降低,并结合净截面屈服准则以获得更好的剩余强度预测结果;将随机性的裂纹萌生和扩展过程与确定性的剩余强度预测方法相结合,建立基于Monte-Carlo方法的MSD结构的失效概率预测模型。最后,通过算例分析,该模型能够得到MSD结构的失效概率曲线,实现结构安全性评估。结果表明MSD结构的失效概率会在短时间内迅速增加,需要在裂纹萌生寿命附近进行限制。
基金Projects(51206011,U1937201)supported by the National Natural Science Foundation of ChinaProject(20200301040RQ)supported by the Science and Technology Development Program of Jilin Province,China+1 种基金Project(JJKH20190541KJ)supported by the Education Department of Jilin Province,ChinaProject(18DY017)supported by Changchun Science and Technology Program of Changchun City,China。
文摘The investigation was carried out on the technical problems of finishing the inner surface of elbow parts and the action mechanism of particles in elbow precision machining by abrasive flow.This work was analyzed and researched by combining theory,numerical and experimental methods.The direct simulation Monte Carlo(DSMC)method and the finite element analysis method were combined to reveal the random collision of particles during the precision machining of abrasive flow.Under different inlet velocity,volume fraction and abrasive particle size,the dynamic pressure and turbulence flow energy of abrasive flow in elbow were analyzed,and the machining mechanism of particles on the wall and the influence of different machining parameters on the precision machining quality of abrasive flow were obtained.The test results show the order of the influence of different parameters on the quality of abrasive flow precision machining and establish the optimal process parameters.The results of the surface morphology before and after the precision machining of the inner surface of the elbow are discussed,and the surface roughness Ra value is reduced from 1.125μm to 0.295μm after the precision machining of the abrasive flow.The application of DSMC method provides special insights for the development of abrasive flow technology.
文摘The modified sum-peak method estimates radioactivity by using only the peak and the sum-peak count rates.To verify the modified sum-peak method,the dependence of the full energy peak efficiency on the source-to-detector distance in a high-purity germanium detector system was studied using a Geant4 Monte Carlo simulation.The effect of the deadlayer in the germanium crystal was estimated by reference to experiments on 241 Am and the relative efficiency of the detector.The peak efficiency dependence on the source-to-detector distance was compared between the simulation and measurements.The modified sum-peak method is discussed with respect to these peak efficiencies.
基金Project(51318010402)supported by General Armament Department Pre-Research Program of China
文摘Measurement uncertainty plays an important role in laser tracking measurement analyses. In the present work, the guides to the expression of uncertainty in measurement(GUM) uncertainty framework(GUF) and its supplement, the Monte Carlo method, were used to estimate the uncertainty of task-specific laser tracker measurements. First, the sources of error in laser tracker measurement were analyzed in detail, including instruments, measuring network fusion, measurement strategies, measurement process factors(such as the operator), measurement environment, and task-specific data processing. Second, the GUM and Monte Carlo methods and their application to laser tracker measurement were presented. Finally, a case study involving the uncertainty estimation of a cylindricity measurement process using the GUF and Monte Carlo methods was illustrated. The expanded uncertainty results(at 95% confidence levels) obtained with the Monte Carlo method are 0.069 mm(least-squares criterion) and 0.062 mm(minimum zone criterion), respectively, while with the GUM uncertainty framework, none but the result of least-squares criterion can be got, which is 0.071 mm. Thus, the GUM uncertainty framework slightly underestimates the overall uncertainty by 10%. The results demonstrate that the two methods have different characteristics in task-specific uncertainty evaluations of laser tracker measurements. The results indicate that the Monte Carlo method is a practical tool for applying the principle of propagation of distributions and does not depend on the assumptions and limitations required by the law of propagation of uncertainties(GUF). These features of the Monte Carlo method reduce the risk of an unreliable measurement of uncertainty estimation, particularly in cases of complicated measurement models, without the need to evaluate partial derivatives. In addition, the impact of sampling strategy and evaluation method on the uncertainty of the measurement results can also be taken into account with Monte Carlo method, which plays a guiding role in measurement planning.
