Stand age plays a crucial role in forest biomass estimation and carbon cycle modeling.Assessing the uncertainty of stand age prediction models and identifying the key driving factors in the modeling process have becom...Stand age plays a crucial role in forest biomass estimation and carbon cycle modeling.Assessing the uncertainty of stand age prediction models and identifying the key driving factors in the modeling process have become major challenges in forestry research.In this study,we selected the Shaanxi-Gansu-Ningxia region of Northeast China as the research area and utilized multi-source datasets from the summer of 2019 to extract information on spectral,textural,climatic,water balance,and stand characteristics.By integrating the Random Forest(RF)model with Monte Carlo(MC)simulation,we constructed six regression models based on different combina-tions of features and evaluated the uncertainty of each model.Furthermore,we investigated the driving factors influencing stand age modeling by analyzing the effects of different types of features on age inversion.Model performance and accuracy were assessed using the root mean square error(RMSE),mean absolute error(MAE),and the coefficient of determination(R^(2)),while the relative root mean square error(rRMSE)was employed to quantify model uncertainty.The results indicate that the scenarios with more obvious improve-ment in accuracy and effective reduction in uncertainty were Scenario 3 with the inclusion of climate and water balance information(RMSE=25.54 yr,MAE=18.03 yr,R^(2)=0.51,rRMSE=19.17%)and Scenario 5 with the inclusion of stand characterization informa-tion(RMSE=18.47 yr,MAE=13.05 yr,R^(2)=0.74,rRMSE=16.99%).Scenario 6,incorporating all feature types,achieved the highest accuracy(RMSE=17.60 yr,MAE=12.06 yr,R^(2)=0.77,rRMSE=14.19%).In this study,elevation,minimum temperature,and diameter at breast height(DBH)emerged as the key drivers of stand-age modeling.The proposed method can be used to identify drivers and to quantify uncertainty in stand-age estimation,providing a useful reference for improving model accuracy and uncertainty assessment.展开更多
In loosely coupled or large-scale problems with high dominance ratios,slow fission source convergence can take extremely long time,reducing Monte Carlo(MC)criticality calculation efficiency.Although various accelerati...In loosely coupled or large-scale problems with high dominance ratios,slow fission source convergence can take extremely long time,reducing Monte Carlo(MC)criticality calculation efficiency.Although various acceleration methods have been developed,some methods cannot reduce convergence times,whereas others have been limited to specific problem geometries.In this study,a new fission source convergence acceleration(FSCA)method,the forced propagation(FP)method,has been proposed,which forces the fission source to propagate and accelerate fission source convergence.Additionally,some stabilization techniques have been designed to render the method more practical.The resulting stabilized method was then successfully implemented in the MC transport code,and its feasibility and effectiveness were tested using the modified OECD/NEA,one-dimensional slab benchmark,and the Hoogenboom full-core problem.The comparison results showed that the FP method was able to achieve efficient FSCA.展开更多
Scramjet is the most promising propulsion system for Air-breathing Hypersonic Vehicle(AHV),and the Infrared(IR)radiation it emits is critical for early warning,detection,and identification of such weapons.This work pr...Scramjet is the most promising propulsion system for Air-breathing Hypersonic Vehicle(AHV),and the Infrared(IR)radiation it emits is critical for early warning,detection,and identification of such weapons.This work proposes an Adaptive Reverse Monte Carlo(ARMC)method and develops an analytical model for the IR radiation of scramjet considering gaseous kerosene and hydrogen fueled conditions.The evaluation studies show that at a global equivalence ratio of 0.8,the IR radiation from hydrogen-fueled plume is predominantly from H_(2)O and spectral peak is 1.53 kW·Sr^(-1)·μm^(-1)at the 2.7μm band,while the kerosene-fueled plume exhibits a spectral intensity approaching 7.0 kW·Sr^(-1)·μm^(-1)at the 4.3μm band.At the backward detection angle,both types of scramjets exhibit spectral peaks within the 1.3-1.4μm band,with intensities around10 kW·Sr^(-1)·μm^(-1).The integral radiation intensity of hydrogen-fueled scramjet is generally higher than kerosene-fueled scramjet,particularly in 1-3μm band.Meanwhile,at wide detection angles,the solid walls become the predominant radiation source.The radiation intensity is highest in1-3μm and weakest in 8-14μm band,with values of 21.5 kW·Sr^(-1)and 0.57 kW·Sr^(-1)at the backward detection angles,respectively.Significant variations in the radiation contributions from gases and solids are observed across different bands under the two fuel conditions,especially within 3-5μm band.This research provides valuable insights into the IR radiation characteristics of scramjets,which can aid in the development of IR detection systems for AHV.展开更多
Volcanic terrains exhibit a complex structure of pyroclastic deposits interspersed with sedimentary processes,resulting in irregular lithological sequences that lack lateral continuity and distinct stratigraphic patte...Volcanic terrains exhibit a complex structure of pyroclastic deposits interspersed with sedimentary processes,resulting in irregular lithological sequences that lack lateral continuity and distinct stratigraphic patterns.This complexity poses significant challenges for slope stability analysis,requiring the development of specialized techniques to address these issues.This research presents a numerical methodology that incorporates spatial variability,nonlinear material characterization,and probabilistic analysis using a Monte Carlo framework to address this issue.The heterogeneous structure is represented by randomly assigning different lithotypes across the slope,while maintaining predefined global proportions.This contrasts with the more common approach of applying probabilistic variability to mechanical parameters within a homogeneous slope model.The material behavior is defined using complex nonlinear failure criteria,such as the Hoek-Brown model and a parabolic model with collapse,both implemented through linearization techniques.The Discontinuity Layout Optimization(DLO)method,a novel numerical approach based on limit analysis,is employed to efficiently incorporate these advances and compute the factor of safety of the slope.Within this framework,the Monte Carlo procedure is used to assess slope stability by conducting a large number of simulations,each with a different lithotype distribution.Based on the results,a hybrid method is proposed that combines probabilistic modeling with deterministic design principles for the slope stability assessment.As a case study,the methodology is applied to a 20-m-high vertical slope composed of three lithotypes(altered scoria,welded scoria,and basalt)randomly distributed in proportions of 15%,60%,and 25%,respectively.The results show convergence of mean values after approximately 400 simulations and highlight the significant influence of spatial heterogeneity,with variations of the factor of safety between 5 and 12 in 85%of cases.They also reveal non-circular and mid-slope failure wedges not captured by traditional stability methods.Finally,an equivalent normal probability distribution is proposed as a reliable approximation of the factor of safety for use in risk analysis and engineering decision-making.展开更多
本文提出了一种新的延时累加算法。基于底层的JCOGIN(J combinatorial geometry Monte Carlo transport infrastructure)框架和新的延时累加算法,通用型Monte Carlo中子-光子输运模拟软件JMCT的计数能力得到了较大提高。对所考察的非重...本文提出了一种新的延时累加算法。基于底层的JCOGIN(J combinatorial geometry Monte Carlo transport infrastructure)框架和新的延时累加算法,通用型Monte Carlo中子-光子输运模拟软件JMCT的计数能力得到了较大提高。对所考察的非重复结构的单层几何模型问题,JMCT的计数效率较MCNP 4C程序所采用的list scoring技巧高约28%;对于较复杂的重复结构几何模型问题,JMCT的大规模精细计数效率比MCNP 4C高约两个量级。JMCT目前的计数能力为反应堆物理分析及多燃耗步计算奠定了良好的基础。展开更多
An approach for generating test problems by a computer using the Monte Carlo method based upon user-given characterizations is described.A single point X~* is prespocified by the user to be a solution of the test prob...An approach for generating test problems by a computer using the Monte Carlo method based upon user-given characterizations is described.A single point X~* is prespocified by the user to be a solution of the test problems.The approach is flex- ible enough to specify function values,gradients,Hesse,degeneracy degree and ill- conditioned degree at the point X~*.Other numerical features such as indefiniteness, convexity are also under user's control.展开更多
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
After the trajectory simulation model of rudder control rocket with six degrees of freedom is established by Matlab/ Simulink, the simulated targeting of rudder control rocket with rudder angle error and starting cont...After the trajectory simulation model of rudder control rocket with six degrees of freedom is established by Matlab/ Simulink, the simulated targeting of rudder control rocket with rudder angle error and starting control moment error is carried out respectively by means of Monte Carlo method and the distribution of impact points of rudder control rocket is counted from all the successful subsamples. In the case of adding interference errors associated with rudder angle error and starting time error, the simulation analysis of impact point dispersion is done and its lateral and longitudinal correction abilities at different targeting angles are simulated to identify the effects of these factors on characteristics and control precision of the rudder control rocket, which provides the relevant reference for high-precision design of rudder control system.展开更多
Tooth modification technique is widely used in gear industry to improve the meshing performance of gearings. However, few of the present studies on tooth modification considers the influence of inevitable random error...Tooth modification technique is widely used in gear industry to improve the meshing performance of gearings. However, few of the present studies on tooth modification considers the influence of inevitable random errors on gear modification effects. In order to investigate the uncertainties of tooth modification amount variations on system＇s dynamic behaviors of a helical planetary gears, an analytical dynamic model including tooth modification parameters is proposed to carry out a deterministic analysis on the dynamics of a helical planetary gear. The dynamic meshing forces as well as the dynamic transmission errors of the sun-planet 1 gear pair with and without tooth modifications are computed and compared to show the effectiveness of tooth modifications on gear dynamics enhancement. By using response surface method, a fitted regression model for the dynamic transmission error（DTE） fluctuations is established to quantify the relationship between modification amounts and DTE fluctuations. By shifting the inevitable random errors arousing from manufacturing and installing process to tooth modification amount variations, a statistical tooth modification model is developed and a methodology combining Monte Carlo simulation and response surface method is presented for uncertainty analysis of tooth modifications. The uncertainly analysis reveals that the system＇s dynamic behaviors do not obey the normal distribution rule even though the design variables are normally distributed. In addition, a deterministic modification amount will not definitely achieve an optimal result for both static and dynamic transmission error fluctuation reduction simultaneously.展开更多
The conduct mechanism of the doped polymer is considered. In an asymmetrysystem composed of high polymer and doping conductive matte, chain or congeries framework will beformed between the conductive particles to impr...The conduct mechanism of the doped polymer is considered. In an asymmetrysystem composed of high polymer and doping conductive matte, chain or congeries framework will beformed between the conductive particles to improve the conductance characteristic. In thisprocession, the conductive particles interact to each other. In this paper, we describe theconductance of the doped polymer by Monte Carlo method. The results accord with the experimentsquite well. It can be concluded that there is an evident change of doped polymer from nonconductorto metal.展开更多
Straightness error is an important parameter in measuring high-precision shafts. New generation geometrical product speeifieation（GPS） requires the measurement uncertainty characterizing the reliability of the resul...Straightness error is an important parameter in measuring high-precision shafts. New generation geometrical product speeifieation（GPS） requires the measurement uncertainty characterizing the reliability of the results should be given together when the measurement result is given. Nowadays most researches on straightness focus on error calculation and only several research projects evaluate the measurement uncertainty based on ＂The Guide to the Expression of Uncertainty in Measurement（GUM）＂. In order to compute spatial straightness error（SSE） accurately and rapidly and overcome the limitations of GUM, a quasi particle swarm optimization（QPSO） is proposed to solve the minimum zone SSE and Monte Carlo Method（MCM） is developed to estimate the measurement uncertainty. The mathematical model of minimum zone SSE is formulated. In QPSO quasi-random sequences are applied to the generation of the initial position and velocity of particles and their velocities are modified by the constriction factor approach. The flow of measurement uncertainty evaluation based on MCM is proposed, where the heart is repeatedly sampling from the probability density function（PDF） for every input quantity and evaluating the model in each case. The minimum zone SSE of a shaft measured on a Coordinate Measuring Machine（CMM） is calculated by QPSO and the measurement uncertainty is evaluated by MCM on the basis of analyzing the uncertainty contributors. The results show that the uncertainty directly influences the product judgment result. Therefore it is scientific and reasonable to consider the influence of the uncertainty in judging whether the parts are accepted or rejected, especially for those located in the uncertainty zone. The proposed method is especially suitable when the PDF of the measurand cannot adequately be approximated by a Gaussian distribution or a scaled and shifted t-distribution and the measurement model is non-linear.展开更多
A two-dimensional （2D） full band self-consistent ensemble Monte Carlo （MC） method for solving the quantum Boltzmann equation, including collision broadening and quantum potential corrections, is developed to exten...A two-dimensional （2D） full band self-consistent ensemble Monte Carlo （MC） method for solving the quantum Boltzmann equation, including collision broadening and quantum potential corrections, is developed to extend the MC method to the study of nano-scale semiconductor devices with obvious quantum mechanical （QM） effects. The quantum effects both in real space and momentum space in nano-scale semiconductor devices can be simulated. The effective mobility in the inversion layer of n and p channel MOSFET is simulated and compared with experimental data to verify this method. With this method 50nm ultra thin body silicon on insulator MOSFET are simulated. Results indicate that this method can be used to simulate the 2D QM effects in semiconductor devices including tunnelling effect.展开更多
The influencing factors of the equipment support activity process have the characteristics of nonlinearity, high dimension, many constraints, random uncertainty and fuzzy uncertainty. Monte Carlo method can solve the ...The influencing factors of the equipment support activity process have the characteristics of nonlinearity, high dimension, many constraints, random uncertainty and fuzzy uncertainty. Monte Carlo method can solve the above problems commendably. This paper analyzes the main equipment support activity process and establishes the sampling plan and simulation model of the medium maintenance process based on Monte Carlo method, and the simulation result verifies a fact that the medium maintenance time can be effectively reduced when parallel operation on some procedures is used. It has a practical value and can give good advice to achieve the capability of equipment supportability.展开更多
One of the most critical and complicated steps in mine design is a selection of suitable mining method based upon geological,geotechnical,geographical,safety and economical parameters.The aim of this study is developi...One of the most critical and complicated steps in mine design is a selection of suitable mining method based upon geological,geotechnical,geographical,safety and economical parameters.The aim of this study is developing a Monte Carlo simulation to selection the optimum mining method by using effective and major criteria and at the same time,taking subjective judgments of decision makers into consideration.Proposed approach is based on the combination of Monte Carlo simulation with conventional Analytic Hierarchy Process(AHP).Monte Carlo simulation is used to determine the confdence level of each alternative’s score,is calculated by AHP,with the respect to the variance of decision makers’opinion.The proposed method is applied for Jajarm Bauxite Mine in Iran and eventually the most appropriate mining methods for this mine are ranked.展开更多
A stratified sampling Monte Carlo method to analyze the reliability of structural systems is presented. Introducing a small exploratory simulation, this method overcomes the difficulties for getting the systematic sam...A stratified sampling Monte Carlo method to analyze the reliability of structural systems is presented. Introducing a small exploratory simulation, this method overcomes the difficulties for getting the systematic sampling probability of all the strata. Several useful and efficient stratification methods are given and the strategies of stratification and simulation are studied. A general conclusion has been presented corresponding to actual engineering structures. The strict theoretical proof has been given,and it is especially effective to solve probabilistic integration. Statistic error of evaluating failure probability is reduced obviously. Especially in highly non-linear and nonreonvex problems, it is more accurate than other methods. Compared with other variance reduction techniques, this method can obtain a more obvious variance reduction and an increased sampling efficiency. Moreover, without strict limiting condition, it is convenient to use. This method is especially suitable to solve the reliability problem of structural systems with multiple failure modes and highly non-linear safety margin equations.展开更多
基金Under the auspices of the Natural Science Foundation of China(No.32371875,32001249)。
文摘Stand age plays a crucial role in forest biomass estimation and carbon cycle modeling.Assessing the uncertainty of stand age prediction models and identifying the key driving factors in the modeling process have become major challenges in forestry research.In this study,we selected the Shaanxi-Gansu-Ningxia region of Northeast China as the research area and utilized multi-source datasets from the summer of 2019 to extract information on spectral,textural,climatic,water balance,and stand characteristics.By integrating the Random Forest(RF)model with Monte Carlo(MC)simulation,we constructed six regression models based on different combina-tions of features and evaluated the uncertainty of each model.Furthermore,we investigated the driving factors influencing stand age modeling by analyzing the effects of different types of features on age inversion.Model performance and accuracy were assessed using the root mean square error(RMSE),mean absolute error(MAE),and the coefficient of determination(R^(2)),while the relative root mean square error(rRMSE)was employed to quantify model uncertainty.The results indicate that the scenarios with more obvious improve-ment in accuracy and effective reduction in uncertainty were Scenario 3 with the inclusion of climate and water balance information(RMSE=25.54 yr,MAE=18.03 yr,R^(2)=0.51,rRMSE=19.17%)and Scenario 5 with the inclusion of stand characterization informa-tion(RMSE=18.47 yr,MAE=13.05 yr,R^(2)=0.74,rRMSE=16.99%).Scenario 6,incorporating all feature types,achieved the highest accuracy(RMSE=17.60 yr,MAE=12.06 yr,R^(2)=0.77,rRMSE=14.19%).In this study,elevation,minimum temperature,and diameter at breast height(DBH)emerged as the key drivers of stand-age modeling.The proposed method can be used to identify drivers and to quantify uncertainty in stand-age estimation,providing a useful reference for improving model accuracy and uncertainty assessment.
基金supported by the National Natural Science Foundation of China(Nos.11775126,11545013,11605101)the Young Elite Scientists Sponsorship Program by CAST(No.2016QNRC001)+1 种基金Science Challenge Project by MIIT of China(No.TZ2018001)Tsinghua University,Initiative Scientific Research Program。
文摘In loosely coupled or large-scale problems with high dominance ratios,slow fission source convergence can take extremely long time,reducing Monte Carlo(MC)criticality calculation efficiency.Although various acceleration methods have been developed,some methods cannot reduce convergence times,whereas others have been limited to specific problem geometries.In this study,a new fission source convergence acceleration(FSCA)method,the forced propagation(FP)method,has been proposed,which forces the fission source to propagate and accelerate fission source convergence.Additionally,some stabilization techniques have been designed to render the method more practical.The resulting stabilized method was then successfully implemented in the MC transport code,and its feasibility and effectiveness were tested using the modified OECD/NEA,one-dimensional slab benchmark,and the Hoogenboom full-core problem.The comparison results showed that the FP method was able to achieve efficient FSCA.
基金supported by the National Natural Science Foundation of China(No.12102356)。
文摘Scramjet is the most promising propulsion system for Air-breathing Hypersonic Vehicle(AHV),and the Infrared(IR)radiation it emits is critical for early warning,detection,and identification of such weapons.This work proposes an Adaptive Reverse Monte Carlo(ARMC)method and develops an analytical model for the IR radiation of scramjet considering gaseous kerosene and hydrogen fueled conditions.The evaluation studies show that at a global equivalence ratio of 0.8,the IR radiation from hydrogen-fueled plume is predominantly from H_(2)O and spectral peak is 1.53 kW·Sr^(-1)·μm^(-1)at the 2.7μm band,while the kerosene-fueled plume exhibits a spectral intensity approaching 7.0 kW·Sr^(-1)·μm^(-1)at the 4.3μm band.At the backward detection angle,both types of scramjets exhibit spectral peaks within the 1.3-1.4μm band,with intensities around10 kW·Sr^(-1)·μm^(-1).The integral radiation intensity of hydrogen-fueled scramjet is generally higher than kerosene-fueled scramjet,particularly in 1-3μm band.Meanwhile,at wide detection angles,the solid walls become the predominant radiation source.The radiation intensity is highest in1-3μm and weakest in 8-14μm band,with values of 21.5 kW·Sr^(-1)and 0.57 kW·Sr^(-1)at the backward detection angles,respectively.Significant variations in the radiation contributions from gases and solids are observed across different bands under the two fuel conditions,especially within 3-5μm band.This research provides valuable insights into the IR radiation characteristics of scramjets,which can aid in the development of IR detection systems for AHV.
基金the project PID2022-139202OB-I00Neural Networks and Optimization Techniques for the Design and Safe Maintenance of Transportation Infrastructures:Volcanic Rock Geotechnics and Slope Stability(IA-Pyroslope),funded by the Spanish State Research Agency of the Ministry of Science,Innovation and Universities of Spain and the European Regional Development Fund,MCIN/AEI/10.13039/501100011033/FEDER,EU。
文摘Volcanic terrains exhibit a complex structure of pyroclastic deposits interspersed with sedimentary processes,resulting in irregular lithological sequences that lack lateral continuity and distinct stratigraphic patterns.This complexity poses significant challenges for slope stability analysis,requiring the development of specialized techniques to address these issues.This research presents a numerical methodology that incorporates spatial variability,nonlinear material characterization,and probabilistic analysis using a Monte Carlo framework to address this issue.The heterogeneous structure is represented by randomly assigning different lithotypes across the slope,while maintaining predefined global proportions.This contrasts with the more common approach of applying probabilistic variability to mechanical parameters within a homogeneous slope model.The material behavior is defined using complex nonlinear failure criteria,such as the Hoek-Brown model and a parabolic model with collapse,both implemented through linearization techniques.The Discontinuity Layout Optimization(DLO)method,a novel numerical approach based on limit analysis,is employed to efficiently incorporate these advances and compute the factor of safety of the slope.Within this framework,the Monte Carlo procedure is used to assess slope stability by conducting a large number of simulations,each with a different lithotype distribution.Based on the results,a hybrid method is proposed that combines probabilistic modeling with deterministic design principles for the slope stability assessment.As a case study,the methodology is applied to a 20-m-high vertical slope composed of three lithotypes(altered scoria,welded scoria,and basalt)randomly distributed in proportions of 15%,60%,and 25%,respectively.The results show convergence of mean values after approximately 400 simulations and highlight the significant influence of spatial heterogeneity,with variations of the factor of safety between 5 and 12 in 85%of cases.They also reveal non-circular and mid-slope failure wedges not captured by traditional stability methods.Finally,an equivalent normal probability distribution is proposed as a reliable approximation of the factor of safety for use in risk analysis and engineering decision-making.
文摘本文提出了一种新的延时累加算法。基于底层的JCOGIN(J combinatorial geometry Monte Carlo transport infrastructure)框架和新的延时累加算法,通用型Monte Carlo中子-光子输运模拟软件JMCT的计数能力得到了较大提高。对所考察的非重复结构的单层几何模型问题,JMCT的计数效率较MCNP 4C程序所采用的list scoring技巧高约28%;对于较复杂的重复结构几何模型问题,JMCT的大规模精细计数效率比MCNP 4C高约两个量级。JMCT目前的计数能力为反应堆物理分析及多燃耗步计算奠定了良好的基础。
文摘An approach for generating test problems by a computer using the Monte Carlo method based upon user-given characterizations is described.A single point X~* is prespocified by the user to be a solution of the test problems.The approach is flex- ible enough to specify function values,gradients,Hesse,degeneracy degree and ill- conditioned degree at the point X~*.Other numerical features such as indefiniteness, convexity are also under user's control.
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。
文摘After the trajectory simulation model of rudder control rocket with six degrees of freedom is established by Matlab/ Simulink, the simulated targeting of rudder control rocket with rudder angle error and starting control moment error is carried out respectively by means of Monte Carlo method and the distribution of impact points of rudder control rocket is counted from all the successful subsamples. In the case of adding interference errors associated with rudder angle error and starting time error, the simulation analysis of impact point dispersion is done and its lateral and longitudinal correction abilities at different targeting angles are simulated to identify the effects of these factors on characteristics and control precision of the rudder control rocket, which provides the relevant reference for high-precision design of rudder control system.
基金Supported by National Natural Science Foundation of China(Grant No.51375013)Anhui Provincial Natural Science Foundation of China(Grant No.1208085ME64)
文摘Tooth modification technique is widely used in gear industry to improve the meshing performance of gearings. However, few of the present studies on tooth modification considers the influence of inevitable random errors on gear modification effects. In order to investigate the uncertainties of tooth modification amount variations on system＇s dynamic behaviors of a helical planetary gears, an analytical dynamic model including tooth modification parameters is proposed to carry out a deterministic analysis on the dynamics of a helical planetary gear. The dynamic meshing forces as well as the dynamic transmission errors of the sun-planet 1 gear pair with and without tooth modifications are computed and compared to show the effectiveness of tooth modifications on gear dynamics enhancement. By using response surface method, a fitted regression model for the dynamic transmission error（DTE） fluctuations is established to quantify the relationship between modification amounts and DTE fluctuations. By shifting the inevitable random errors arousing from manufacturing and installing process to tooth modification amount variations, a statistical tooth modification model is developed and a methodology combining Monte Carlo simulation and response surface method is presented for uncertainty analysis of tooth modifications. The uncertainly analysis reveals that the system＇s dynamic behaviors do not obey the normal distribution rule even though the design variables are normally distributed. In addition, a deterministic modification amount will not definitely achieve an optimal result for both static and dynamic transmission error fluctuation reduction simultaneously.
文摘The conduct mechanism of the doped polymer is considered. In an asymmetrysystem composed of high polymer and doping conductive matte, chain or congeries framework will beformed between the conductive particles to improve the conductance characteristic. In thisprocession, the conductive particles interact to each other. In this paper, we describe theconductance of the doped polymer by Monte Carlo method. The results accord with the experimentsquite well. It can be concluded that there is an evident change of doped polymer from nonconductorto metal.
基金supported by National Natural Science Foundation of China (Grant No. 51075198)Jiangsu Provincial Natural Science Foundation of China (Grant No. BK2010479)+2 种基金Innovation Research of Nanjing Institute of Technology, China (Grant No. CKJ20100008)Jiangsu Provincial Foundation of 333 Talents Engineering of ChinaJiangsu Provincial Foundation of Six Talented Peak of China
文摘Straightness error is an important parameter in measuring high-precision shafts. New generation geometrical product speeifieation（GPS） requires the measurement uncertainty characterizing the reliability of the results should be given together when the measurement result is given. Nowadays most researches on straightness focus on error calculation and only several research projects evaluate the measurement uncertainty based on ＂The Guide to the Expression of Uncertainty in Measurement（GUM）＂. In order to compute spatial straightness error（SSE） accurately and rapidly and overcome the limitations of GUM, a quasi particle swarm optimization（QPSO） is proposed to solve the minimum zone SSE and Monte Carlo Method（MCM） is developed to estimate the measurement uncertainty. The mathematical model of minimum zone SSE is formulated. In QPSO quasi-random sequences are applied to the generation of the initial position and velocity of particles and their velocities are modified by the constriction factor approach. The flow of measurement uncertainty evaluation based on MCM is proposed, where the heart is repeatedly sampling from the probability density function（PDF） for every input quantity and evaluating the model in each case. The minimum zone SSE of a shaft measured on a Coordinate Measuring Machine（CMM） is calculated by QPSO and the measurement uncertainty is evaluated by MCM on the basis of analyzing the uncertainty contributors. The results show that the uncertainty directly influences the product judgment result. Therefore it is scientific and reasonable to consider the influence of the uncertainty in judging whether the parts are accepted or rejected, especially for those located in the uncertainty zone. The proposed method is especially suitable when the PDF of the measurand cannot adequately be approximated by a Gaussian distribution or a scaled and shifted t-distribution and the measurement model is non-linear.
基金Project supported by the Special Foundation for State Major Basic Research Program of China （Grant No G2000035602） and the National Natural Science Foundation of China （Grant No 90307006）.
文摘A two-dimensional （2D） full band self-consistent ensemble Monte Carlo （MC） method for solving the quantum Boltzmann equation, including collision broadening and quantum potential corrections, is developed to extend the MC method to the study of nano-scale semiconductor devices with obvious quantum mechanical （QM） effects. The quantum effects both in real space and momentum space in nano-scale semiconductor devices can be simulated. The effective mobility in the inversion layer of n and p channel MOSFET is simulated and compared with experimental data to verify this method. With this method 50nm ultra thin body silicon on insulator MOSFET are simulated. Results indicate that this method can be used to simulate the 2D QM effects in semiconductor devices including tunnelling effect.
基金the Special Research Fund for the Research on Armored Vehicle Supportability Requirement Analysis(No.51319050302)
文摘The influencing factors of the equipment support activity process have the characteristics of nonlinearity, high dimension, many constraints, random uncertainty and fuzzy uncertainty. Monte Carlo method can solve the above problems commendably. This paper analyzes the main equipment support activity process and establishes the sampling plan and simulation model of the medium maintenance process based on Monte Carlo method, and the simulation result verifies a fact that the medium maintenance time can be effectively reduced when parallel operation on some procedures is used. It has a practical value and can give good advice to achieve the capability of equipment supportability.
文摘One of the most critical and complicated steps in mine design is a selection of suitable mining method based upon geological,geotechnical,geographical,safety and economical parameters.The aim of this study is developing a Monte Carlo simulation to selection the optimum mining method by using effective and major criteria and at the same time,taking subjective judgments of decision makers into consideration.Proposed approach is based on the combination of Monte Carlo simulation with conventional Analytic Hierarchy Process(AHP).Monte Carlo simulation is used to determine the confdence level of each alternative’s score,is calculated by AHP,with the respect to the variance of decision makers’opinion.The proposed method is applied for Jajarm Bauxite Mine in Iran and eventually the most appropriate mining methods for this mine are ranked.
文摘A stratified sampling Monte Carlo method to analyze the reliability of structural systems is presented. Introducing a small exploratory simulation, this method overcomes the difficulties for getting the systematic sampling probability of all the strata. Several useful and efficient stratification methods are given and the strategies of stratification and simulation are studied. A general conclusion has been presented corresponding to actual engineering structures. The strict theoretical proof has been given,and it is especially effective to solve probabilistic integration. Statistic error of evaluating failure probability is reduced obviously. Especially in highly non-linear and nonreonvex problems, it is more accurate than other methods. Compared with other variance reduction techniques, this method can obtain a more obvious variance reduction and an increased sampling efficiency. Moreover, without strict limiting condition, it is convenient to use. This method is especially suitable to solve the reliability problem of structural systems with multiple failure modes and highly non-linear safety margin equations.
