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 Monte Carlo(MC)method offers significant advantages in handling complex geometries and physical processes in particle transport problems and has become a widely used approach in reactor physics analysis,radiation ...The Monte Carlo(MC)method offers significant advantages in handling complex geometries and physical processes in particle transport problems and has become a widely used approach in reactor physics analysis,radiation shielding design,and medical physics.However,with the rapid advancement of new nuclear energy systems,the Monte Carlo method faces challenges in efficiency,accuracy,and adaptability,limiting its effectiveness in meeting modern design requirements.Overcoming technical obstacles related to high-fidelity coupling,high-resolution computation,and intelligent design is essential for using the Monte Carlo method as a reliable tool in numerical analysis for these new nuclear energy systems.To address these challenges,the Nuclear Energy and Application Laboratory(NEAL)team at the University of South China developed a multifunctional and generalized intelligent code platform called MagicMC,based on the Monte Carlo particle transport method.MagicMC is a developing tool dedicated to nuclear applications,incorporating intelligent methodologies.It consists of two primary components:a basic unit and a functional unit.The basic unit,which functions similarly to a standard Monte Carlo particle transport code,includes seven modules:geometry,source,transport,database,tally,output,and auxiliary.The functional unit builds on the basic unit by adding functional modules to address complex and diverse applications in nuclear analysis.MagicMC introduces a dynamic Monte Carlo particle transport algorithm to address time-space particle transport problems within emerging nuclear energy systems and incorporates a CPU-GPU heterogeneous parallel framework to enable high-efficiency,high-resolution simulations for large-scale computational problems.Anticipating future trends in intelligent design,MagicMC integrates several advanced features,including CAD-based geometry modeling,global variance reduction methods,multi-objective shielding optimization,high-resolution activation analysis,multi-physics coupling,and radiation therapy.In this paper,various numerical benchmarks-spanning reactor transient simulations,material activation analysis,radiation shielding optimization,and medical dosimetry analysis-are presented to validate MagicMC.The numerical results demonstrate MagicMC's efficiency,accuracy,and reliability in these preliminary applications,underscoring its potential to support technological advancements in developing high-fidelity,high-resolution,and high-intelligence MC-based tools for advanced nuclear applications.展开更多
随着自动驾驶技术的快速发展,如何保证自动驾驶系统的安全性变得愈发重要,因此预期功能安全(Safety of The Intended Functionality, SOTIF)的概念应运而生,它主要是为了减少由于系统非预期的感知和决策错误而引起的危害。本文提出了一...随着自动驾驶技术的快速发展,如何保证自动驾驶系统的安全性变得愈发重要,因此预期功能安全(Safety of The Intended Functionality, SOTIF)的概念应运而生,它主要是为了减少由于系统非预期的感知和决策错误而引起的危害。本文提出了一种依托自然驾驶数据的SOTIF自动化生成测试用例的方法。通过采集360°IBEO与环视摄像头数据,分析了4000多个前车切入场景,对关键变量进行参数化建模。采用改进的Monte-Carlo抽样技术,处理独立与非独立随机变量的联合分布,生成覆盖广泛场景的测试用例。实验结果表明该方法显著提升了测试用例生成效率,全面覆盖边角、危险及极端场景,解决了SOTIF测试中自动化生成测试用例的难题,为自动驾驶系统的预期功能安全评估提供了有效支持。展开更多
Gassy soils are distributed in relatively shallow layers the Quaternary deposit in Hangzhou Bay area. The shallow gassy soils significantly affect the construction of underground projects. Proper characterization of s...Gassy soils are distributed in relatively shallow layers the Quaternary deposit in Hangzhou Bay area. The shallow gassy soils significantly affect the construction of underground projects. Proper characterization of spatial distribution of shallow gassy soils is indispensable prior to construction of underground projects in the area. Due to the costly conditions required in the site investigation for gassy soils, only a limited number of gas pressure data can be obtained in engineering practice, which leads to the uncertainty in characterizing spatial distribution of gassy soils. Determining the number of boreholes for investigating gassy soils and their corresponding locations is pivotal to reducing construction risk induced by gassy soils. However, this primarily relies on the engineering experience in the current site investigation practice. This study develops a probabilistic site investigation optimization method for planning investigation schemes (including the number and locations of boreholes) of gassy soils based on the conditional random field and Monte Carlo simulation. The proposed method aims to provide an optimal investigation scheme before the site investigation based on prior knowledge. Finally, the proposed approach is illustrated using a case study.展开更多
EM算法是近年来常用的求后验众数的估计的一种数据增广算法,但由于求出其E步中积分的显示表达式有时很困难,甚至不可能,限制了其应用的广泛性.而Monte Carlo EM算法很好地解决了这个问题,将EM算法中E步的积分用Monte Carlo模拟来有效实...EM算法是近年来常用的求后验众数的估计的一种数据增广算法,但由于求出其E步中积分的显示表达式有时很困难,甚至不可能,限制了其应用的广泛性.而Monte Carlo EM算法很好地解决了这个问题,将EM算法中E步的积分用Monte Carlo模拟来有效实现,使其适用性大大增强.但无论是EM算法,还是Monte Carlo EM算法,其收敛速度都是线性的,被缺损信息的倒数所控制,当缺损数据的比例很高时,收敛速度就非常缓慢.而Newton-Raphson算法在后验众数的附近具有二次收敛速率.本文提出Monte Carlo EM加速算法,将Monte Carlo EM算法与Newton-Raphson算法结合,既使得EM算法中的E步用Monte Carlo模拟得以实现,又证明了该算法在后验众数附近具有二次收敛速度.从而使其保留了Monte Carlo EM算法的优点,并改进了Monte Carlo EM算法的收敛速度.本文通过数值例子,将Monte Carlo EM加速算法的结果与EM算法、Monte Carlo EM算法的结果进行比较,进一步说明了Monte Carlo EM加速算法的优良性.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
A microscopic understanding of the complex solute-defect interaction is pivotal for optimizing the alloy’s macroscopic mechanical properties.Simulating solute segregation in a plastically deformed crystalline system ...A microscopic understanding of the complex solute-defect interaction is pivotal for optimizing the alloy’s macroscopic mechanical properties.Simulating solute segregation in a plastically deformed crystalline system at atomic resolution remains challenging.The objective is to efficiently model and predict a phys-ically informed segregated solute distribution rather than simulating a series of diffusion kinetics.To ad-dress this objective,we coupled molecular dynamics(MD)and Monte Carlo(MC)methods using a novel method based on virtual atoms technique.We applied our MD-MC coupling approach to model off-lattice carbon(C)solute segregation in nanoindented Fe-C samples containing complex dislocation networks.Our coupling framework yielded the final configuration through efficient parallelization and localized en-ergy computations,showing C Cottrell atmospheres near dislocations.Different initial C concentrations resulted in a consistent trend of C atoms migrating from less crystalline distortion to high crystalline distortion regions.Besides unraveling the strong spatial correlation between local C concentration and defect regions,our results revealed two crucial aspects of solute segregation preferences:(1)defect ener-getics hierarchy and(2)tensile strain fields near dislocations.The proposed approach is generic and can be applied to other material systems as well.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supported by the National Natural Science Foundation of China(Nos.12475174 and U2267207)YueLuShan Center Industrial Innovation(No.2024YCII0108)+2 种基金Natural Science Foundation of Hunan Province(No.2022JJ40345)Science and Technology Innovation Project of Hengyang(No.202250045336)the Project of State Key Laboratory of Radiation Medicine and Protection,Soochow University(No.GZK12023031)。
文摘The Monte Carlo(MC)method offers significant advantages in handling complex geometries and physical processes in particle transport problems and has become a widely used approach in reactor physics analysis,radiation shielding design,and medical physics.However,with the rapid advancement of new nuclear energy systems,the Monte Carlo method faces challenges in efficiency,accuracy,and adaptability,limiting its effectiveness in meeting modern design requirements.Overcoming technical obstacles related to high-fidelity coupling,high-resolution computation,and intelligent design is essential for using the Monte Carlo method as a reliable tool in numerical analysis for these new nuclear energy systems.To address these challenges,the Nuclear Energy and Application Laboratory(NEAL)team at the University of South China developed a multifunctional and generalized intelligent code platform called MagicMC,based on the Monte Carlo particle transport method.MagicMC is a developing tool dedicated to nuclear applications,incorporating intelligent methodologies.It consists of two primary components:a basic unit and a functional unit.The basic unit,which functions similarly to a standard Monte Carlo particle transport code,includes seven modules:geometry,source,transport,database,tally,output,and auxiliary.The functional unit builds on the basic unit by adding functional modules to address complex and diverse applications in nuclear analysis.MagicMC introduces a dynamic Monte Carlo particle transport algorithm to address time-space particle transport problems within emerging nuclear energy systems and incorporates a CPU-GPU heterogeneous parallel framework to enable high-efficiency,high-resolution simulations for large-scale computational problems.Anticipating future trends in intelligent design,MagicMC integrates several advanced features,including CAD-based geometry modeling,global variance reduction methods,multi-objective shielding optimization,high-resolution activation analysis,multi-physics coupling,and radiation therapy.In this paper,various numerical benchmarks-spanning reactor transient simulations,material activation analysis,radiation shielding optimization,and medical dosimetry analysis-are presented to validate MagicMC.The numerical results demonstrate MagicMC's efficiency,accuracy,and reliability in these preliminary applications,underscoring its potential to support technological advancements in developing high-fidelity,high-resolution,and high-intelligence MC-based tools for advanced nuclear applications.
文摘随着自动驾驶技术的快速发展,如何保证自动驾驶系统的安全性变得愈发重要,因此预期功能安全(Safety of The Intended Functionality, SOTIF)的概念应运而生,它主要是为了减少由于系统非预期的感知和决策错误而引起的危害。本文提出了一种依托自然驾驶数据的SOTIF自动化生成测试用例的方法。通过采集360°IBEO与环视摄像头数据,分析了4000多个前车切入场景,对关键变量进行参数化建模。采用改进的Monte-Carlo抽样技术,处理独立与非独立随机变量的联合分布,生成覆盖广泛场景的测试用例。实验结果表明该方法显著提升了测试用例生成效率,全面覆盖边角、危险及极端场景,解决了SOTIF测试中自动化生成测试用例的难题,为自动驾驶系统的预期功能安全评估提供了有效支持。
文摘Gassy soils are distributed in relatively shallow layers the Quaternary deposit in Hangzhou Bay area. The shallow gassy soils significantly affect the construction of underground projects. Proper characterization of spatial distribution of shallow gassy soils is indispensable prior to construction of underground projects in the area. Due to the costly conditions required in the site investigation for gassy soils, only a limited number of gas pressure data can be obtained in engineering practice, which leads to the uncertainty in characterizing spatial distribution of gassy soils. Determining the number of boreholes for investigating gassy soils and their corresponding locations is pivotal to reducing construction risk induced by gassy soils. However, this primarily relies on the engineering experience in the current site investigation practice. This study develops a probabilistic site investigation optimization method for planning investigation schemes (including the number and locations of boreholes) of gassy soils based on the conditional random field and Monte Carlo simulation. The proposed method aims to provide an optimal investigation scheme before the site investigation based on prior knowledge. Finally, the proposed approach is illustrated using a case study.
文摘EM算法是近年来常用的求后验众数的估计的一种数据增广算法,但由于求出其E步中积分的显示表达式有时很困难,甚至不可能,限制了其应用的广泛性.而Monte Carlo EM算法很好地解决了这个问题,将EM算法中E步的积分用Monte Carlo模拟来有效实现,使其适用性大大增强.但无论是EM算法,还是Monte Carlo EM算法,其收敛速度都是线性的,被缺损信息的倒数所控制,当缺损数据的比例很高时,收敛速度就非常缓慢.而Newton-Raphson算法在后验众数的附近具有二次收敛速率.本文提出Monte Carlo EM加速算法,将Monte Carlo EM算法与Newton-Raphson算法结合,既使得EM算法中的E步用Monte Carlo模拟得以实现,又证明了该算法在后验众数附近具有二次收敛速度.从而使其保留了Monte Carlo EM算法的优点,并改进了Monte Carlo EM算法的收敛速度.本文通过数值例子,将Monte Carlo EM加速算法的结果与EM算法、Monte Carlo EM算法的结果进行比较,进一步说明了Monte Carlo EM加速算法的优良性.
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 funding from the Ger-man Research Foundation(DFG)-BE 5360/1-1 and ThyssenKrupp Europe.
文摘A microscopic understanding of the complex solute-defect interaction is pivotal for optimizing the alloy’s macroscopic mechanical properties.Simulating solute segregation in a plastically deformed crystalline system at atomic resolution remains challenging.The objective is to efficiently model and predict a phys-ically informed segregated solute distribution rather than simulating a series of diffusion kinetics.To ad-dress this objective,we coupled molecular dynamics(MD)and Monte Carlo(MC)methods using a novel method based on virtual atoms technique.We applied our MD-MC coupling approach to model off-lattice carbon(C)solute segregation in nanoindented Fe-C samples containing complex dislocation networks.Our coupling framework yielded the final configuration through efficient parallelization and localized en-ergy computations,showing C Cottrell atmospheres near dislocations.Different initial C concentrations resulted in a consistent trend of C atoms migrating from less crystalline distortion to high crystalline distortion regions.Besides unraveling the strong spatial correlation between local C concentration and defect regions,our results revealed two crucial aspects of solute segregation preferences:(1)defect ener-getics hierarchy and(2)tensile strain fields near dislocations.The proposed approach is generic and can be applied to other material systems as well.
