HPGe γ谱仪点源探测效率计算的蒙特卡罗方法研究

在CT 扫描精确获得HPGe探测器结构尺寸的基础上，用MCNP4C蒙特卡罗程序建立了HPGeγ谱仪计算点源的物理模型；通过对探测器死层尺寸的精确校正，确定了探测器死层厚度为0．38 cm；以点源物理模型和探测器死层校正尺寸为基础，分别计算了60 Co、133 Ba、137 Cs、241 Am和152 Eu标准点源各能量分支的探测效率，并与实验结果比较，计算在59．54～1408．01 keV能量范围内探测效率的最大相对偏差为2．39％，最小相对偏差为0．13％。

一种基于蒙卡解析耦合的无源效率刻度方法

目的将蒙卡模拟与解析计算相结合,建立一种无源效率刻度方法。方法通过蒙卡模拟对所需型号的探测器进行点对点探测效率计算,建立探测效率网格;从探测效率网格中插值,并使用数值积分方法对常用的点源、圆盘、圆柱、烧杯、球形、U型管、马林杯样品的探测效率进行解析。结果使用上述耦合方法进行无源效率刻度计算,结果表明:0.2~3 MeV能量范围内的刻度结果与使用蒙卡模拟的刻度结果相对偏差大部分在10%以内,最大相对偏差为18.06%,计算时间缩短了至少86%。应用上述耦合方法对ORTEC公司产的某型号HPGe探测器进行点源无源效率刻度,与实验刻度结果吻合很好,相对偏差均在10%以内。结论该方法可以推广到HPGe、LaBr^(3)、Na I等多种探测器的无源效率刻度实际应用中。

泡沫铝弹性接触静力学行为的多尺度模拟

对泡沫铝的宏、细观组织结构,基于MC方法建立与材料制备工艺相应的数值模型,作为多尺度模拟的前提。通过计算模拟和统计分析大量数值试样的力学性能,得到了不同制备工艺制得的泡沫铝的弹性模量的分散性特点。借鉴代表性体积单元方法(RVE)和完全多格方法(FMG)的思想,采用基于"巨原子"模型的多尺度关联方法,并以简化的物理势场描述巨原子间的关系,设计了原子—巨原子—有限元多尺度算法。通过算例探讨了与理想刚性平面接触时,泡沫铝接触表面的应力集中情况。

基于GEANT4探讨入射窗材料对HPGe探测器探测效率的影响

针对不同入射窗材料影响HPGe探测器探测效率的问题,首先用GEANT4模拟HPGeγ谱仪标准点源的探测效率并与实测效率进行对此,其相对偏差在4%以内,验证了GEANT4所建立的模型可用于HPGeγ谱仪点源探测效率的模拟。然后基于所建立的HPGe探测模型针对不同入射窗材料、不同入射窗厚度、不同点源发射立体角和不同能量射线对于高纯锗探测器探测效率的影响进行模拟。研究结果表明,在低能射线方面,铍窗的探测效率最高,碳窗与铍窗接近,铝窗的探测效率最低,但随着点源发射立体角的增大,碳窗、铝窗和铍窗的探测效率趋于接近;在中高能射线方面,碳窗、铝窗和铍窗的探测效率几乎相同。在入射窗厚度的选择方面,在入射窗很薄(0.5mm)时,铝窗和铍窗的探测效率相同,在入射窗厚度为1cm之内时,达到相同的探测效率,铝窗的厚度只需要碳窗和铍窗厚度的一半。这为高纯锗探测器在用于不同能量伽马射线的探测时入射窗的选择提供指导。

Monte Carlo Simulation of Impurity Scattering Effect in Resonant-Phonon-Assisted Terahertz Quantum-Cascade Lasers

We study the influence of ionized impurity scattering on the electron transport in resonant-phonon-assisted terahertz （THz） quantum-cascade lasers （QCLs）. We treat the ionized impurity scattering rates within the single subband static screening approximation. We find that the ionized impurity scattering supplies an additional current channel across the device,and affects the electrondistribution in different subbands. We conclude that the ionized impurity scattering should be taken into account in the study of the transport properties of resonant-phonon-assisted THz QCLs.

Growth Mechanism of Microcrystalline Silicon Films by Scaling Theory and Monte Carlo Simulation

Hydrogenated microcrystalline silicon （~c-Si：H） films with a high deposition rate of 1.2nm/s were prepared by hot-wire chemical vapor deposition （HWCVD）. The growth-front roughening processes of the μc-Si..H films were investi- gated by atomic force microscopy. According to the scaling theory, the growth exponent β≈0.67, the roughness exponent α≈0.80,and the dynamic exponent 1/z = 0.40 are obtained. These scaling exponents cannot be explained well by the known growth models. An attempt at Monte Carlo simulation has been made to describe the growth process of μc-Si： H film using a particle reemission model where the incident flux distribution,the type and concentration of growth radical, and sticking,reemission,shadowing mechanisms all contributed to the growing morphology.

Diffusion Monte Carlo Study of Bond Dissociation Energies for BH2, B（OH）2, BCl2, and BCI

On basis of bond dissociation energies （BDEs） for BH2, B（OH）2, BCl2, and BCl, the diffusion Monte Carlo （DMC） method is applied to explore the BDEs of HB-H, HOB-OH, ClB-Cl, and B-Cl. The effect of the choice of orbitals, as well as the backflow transformation, is studied. The Slater-Jastrow DMC algorithm gives BDEs of 359.1±0.12 kJ/mol for HB-H, 410.5±0.50 kJ/mol for HOB-OH, 357.8±1.46 kJ/mol for ClB-Cl, and 504.5±0.96 kJ/mol for B-Cl using B3PW91 orbitals and similar BDEs when B3LYP orbitals are used. DMC with backflow corrections （BF-DMC） gives a HB-H BDE of 369.9±0.12 kJ/mol which is close to one of the available experimental value （375.8 kJ/mol）. In the case of HOB-OH BDE, the BF-DMC calculation is 446.04-1.84 k J/mol that is closer to the experimental BDE. The BF-DMC BDE for ClB-Cl is 343.2±2.34 kJ/mol and the BF-DMC B-Cl BDE is 523.3±0.33 kJ/mol, which are close to the experimental BDEs, 341.9 and 530.0 kJ/mol, respectively.

Extremum response surface method of reliability analysis on two-link flexible robot manipulator

In order to present a new method for analyzing the reliability of a two-link flexible robot manipulator,Lagrange dynamics differential equations of the two-link flexible robot manipulator were established by using the integrated modal method and the multi-body system dynamics method.By using the Monte Carlo method,the random sample values of the dynamic parameters were obtained and Lagrange dynamics differential equations were solved for each random sample value which revealed their displacement,speed and acceleration.On this basis,dynamic stresses and deformations were obtained.By taking the maximum values of the stresses and the deformations as output responses and the random sample values of dynamic parameters as input quantities,extremum response surface functions were established.A number of random samples were then obtained by using the Monte Carlo method and then the reliability was analyzed by using the extremum response surface method.The results show that the extremum response surface method is an efficient and fast reliability analysis method with high-accuracy for the two-link flexible robot manipulator.

Time-variant reliability analysis of three-dimensional slopes based on Support Vector Machine method

In the reliability analysis of slope, the performance functions derived from the most available stability analysis procedures of slopes are usually implicit and cannot be solved by first-order second-moment approach. A new reliability analysis approach was presented based on three-dimensional Morgenstem-Price method to investigate three-dimensional effect of landslide in stability analyses. To obtain the reliability index, Support Vector Machine （SVM） was applied to approximate the performance function. The time-consuming of this approach is only 0.028% of that using Monte-Carlo method at the same computation accuracy. Also, the influence of time effect of shearing strength parameters of slope soils on the long-term reliability of three-dimensional slopes was investigated by this new approach. It is found that the reliability index of the slope would decrease by 52.54% and the failure probability would increase from 0.000 705% to 1.966%. In the end, the impact of variation coefficients of c andfon reliability index of slopes was taken into discussion and the changing trend was observed.

Ordered Toroid Structures of Nanoparticles in Self-attractive Semiflexible Polymer/Nanoparticle Composites

By employing dynamic Monte Carlo simulations, we investigate a coil-to-toroid transition of self-attractive semiflexible polymers and the spatial distributions of nanoparticles in self- attractive semiflexible polymer/nanoparticle composites. The conformation of self-attractive semiflexible polymers depends on bending energy and self-attractive interactions between monomers in polymer chains. A three-stage process of toroid formation for self-attractive semiflexible chains is shown： several isolated toroids, a loose toroid structure, and a compact toroid structure. Utilizing the compact toroid conformations of self-attractive semiflexible chains, we can control effectively the spatial distributions of nanoparticles in self-attractive semiflexible polymer nanocomposites, and an unconventional toroid structure of nanoparti- cles is observed.

Elbow precision machining technology by abrasive flow based on direct Monte Carlo method

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.

Nash Model Parameter Uncertainty Analysis by AM-MCMC Based on BFS and Probabilistic Flood Forecasting

A hydrologic model consists of several parameters which are usually calibrated based on observed hy-drologic processes. Due to the uncertainty of the hydrologic processes, model parameters are also uncertain, which further leads to the uncertainty of forecast results of a hydrologic model. Working with the Bayesian Forecasting System (BFS), Markov Chain Monte Carlo simulation based Adaptive Metropolis method (AM-MCMC) was used to study parameter uncertainty of Nash model, while the probabilistic flood forecasting was made with the simu-lated samples of parameters of Nash model. The results of a case study shows that the AM-MCMC based on BFS proposed in this paper is suitable to obtain the posterior distribution of the parameters of Nash model according to the known information of the parameters. The use of Nash model and AM-MCMC based on BFS was able to make the probabilistic flood forecast as well as to find the mean and variance of flood discharge, which may be useful to estimate the risk of flood control decision.

Comparison of GUF and Monte Carlo methods to evaluate task-specific uncertainty in laser tracker measurement

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.

Regional Clustering and Synchronization of Provincial Business Fluctuations in China

In this article, we propose a novel, multilevel, dynamic factor model, to determine endogenously clustered regions for the investigation of regional clustering and synchronization of provincial business fluctuations in China. The parameter identification and model estimation was conducted using the Markov Chain Monte Carlo method. We then conducted an empirical study of the provincial business fluctuations in China(31 Chinese provinces are considered except Hong Kong, Macao, and Taiwan due to the data unavailability), which were sampled from January 2000 to December 2015. Our results indicated that these provinces could be clustered into four regions: leading, coincident, lagging, and overshooting. In comparison with traditional geographical divisions, this novel clustering into four regions enabled the regional business cycle synchronization to be more accurately captured. Within the four regional clusters it was possible to identify substantial heterogeneities among regional business cycle fluctuations, especially during the periods of the 2008 financial crisis and the ‘four-trillion economic stimulus plan'.

Study on slope reliability method Response Surface Method based on Morgenstern-Price Method

The combination of Morgenstern-Price Method （MPM） with Response Surface Method （RSM） improves the eonventional RSM by replacing Finite-Element Method （FEM） with MPM, which is a type of reliability analysis method-RSM based on MPM, and makes the computing process simpler. The stability of the slope was re-evaluated by use of Monte Carlo method （MCM） and the result contrasted with the fore is the conclusion. The reliability analysis of the artificial slope in Donggang Power Station was carried on, and obtained the reliable charaeteristics, which provided basis for the project.

Accuracy Analysis of Assembly Success Rate with Monte Carlo Simulations

Monte Carlo simulation was applied to Assembly Success Bate (ASK) analyses. ASR of two peg-in-hole robot assemblies was used as an example by taking component parts' sizes, manufacturing tolerances and robot repeatability into account. A statistic arithmetic expression was proposed and deduced in this paper, which offers an alternative method of estimating the accuracy of ASR, without having to repeat the simulations. This statistic method also helps to choose a suitable sample size, if error reduction is desired. Monte Carlo simulation results demonstrated the feasibility of the method.

Safety Assessment for Autonomous Aerial Refueling Based on Reachability Analysis

Autonomous aerial refueling(AAR)has demonstrated significant benefits to aviation by extending the aircraft range and endurance.It is of significance to assess system safety for autonomous aerial refueling.In this paper,the reachability analysis method is adopted to assess system safety.Due to system uncertainties,the aerial refueling system can be considered as a stochastic system.Thus,probabilistic reachability is considered.Since there is a close relationship between reachability probability and collision probability,the collision probability of the AAR system is analyzed by using reachability analysis techniques.Then,the collision probability is accessed by using the Monte-Carlo experiment method.Finally,simulations demonstrate the effectiveness of the proposed safety assessment method.

Algorithm for solving the bi-level decision making problem with continuous variables in the upper level based on genetic algorithm

Based on genetic algorithms, a solution algorithm is presented for the bi-level decision making problem with continuous variables in the upper level in accordance with the bi-level decision making principle. The algorithm is compared with Monte Carlo simulated annealing algorithm, and its feasibility and effectiveness are verified with two calculating examples.

SEMI-BLIND CHANNEL ESTIMATION OF MULTIPLE-INPUT/MULTIPLE-OUTPUT SYSTEMS BASED ON MARKOV CHAIN MONTE CARLO METHODS

This paper addresses the issues of channel estimation in a Multiple-Input/Multiple-Output (MIMO) system. Markov Chain Monte Carlo (MCMC) method is employed to jointly estimate the Channel State Information (CSI) and the transmitted signals. The deduced algorithms can work well under circumstances of low Signal-to-Noise Ratio (SNR). Simulation results are presented to demonstrate their effectiveness.

Application of response surface method for contact fatigue reliability analysis of spur gear with consideration of EHL

In order to consider the effects of elastohydrodynamic lubrication(EHL) on contact fatigue reliability of spur gear, an accurate and efficient method that combines with response surface method(RSM) and first order second moment method(FOSM) was developed for estimating the contact fatigue reliability of spur gear under EHL. The mechanical model of contact stress analysis of spur gear under EHL was established, in which the oil film pressure was mapped into hertz contact zone. Considering the randomness of EHL, material properties and fatigue strength correction factors, the proposed method was used to analyze the contact fatigue reliability of spur gear under EHL. Compared with the results of 1.5×105 by traditional Monte-Carlo, the difference between the two failure probability results calculated by the above mentioned methods is 2.2×10-4, the relative error of the failure probability results is 26.8%, and time-consuming only accounts for 0.14% of the traditional Monte-Carlo method(MCM). Sensitivity analysis results are in very good agreement with practical cognition. Analysis results show that the proposed method is precise and efficient, and could correctly reflect the influence of EHL on contact fatigue reliability of spur gear.