Active learning accelerated Monte-Carlo simulation based on the modified K-nearest neighbors algorithm and its application to reliability estimations

This paper proposes an active learning accelerated Monte-Carlo simulation method based on the modified K-nearest neighbors algorithm.The core idea of the proposed method is to judge whether or not the output of a random input point can be postulated through a classifier implemented through the modified K-nearest neighbors algorithm.Compared to other active learning methods resorting to experimental designs,the proposed method is characterized by employing Monte-Carlo simulation for sampling inputs and saving a large portion of the actual evaluations of outputs through an accurate classification,which is applicable for most structural reliability estimation problems.Moreover,the validity,efficiency,and accuracy of the proposed method are demonstrated numerically.In addition,the optimal value of K that maximizes the computational efficiency is studied.Finally,the proposed method is applied to the reliability estimation of the carbon fiber reinforced silicon carbide composite specimens subjected to random displacements,which further validates its practicability.

An enhanced image binarization method incorporating with Monte-Carlo simulation

We proposed an enhanced image binarization method.The proposed solution incorporates Monte-Carlo simulation into the local thresholding method to address the essential issues with respect to complex background,spatially-changed illumination,and uncertainties of block size in traditional method.The proposed method first partitions the image into square blocks that reflect local characteristics of the image.After image partitioning,each block is binarized using Otsu’s thresholding method.To minimize the influence of the block size and the boundary effect,we incorporate Monte-Carlo simulation into the binarization algorithm.Iterative calculation with varying block sizes during Monte-Carlo simulation generates a probability map,which illustrates the probability of each pixel classified as foreground.By setting a probability threshold,and separating foreground and background of the source image,the final binary image can be obtained.The described method has been tested by benchmark tests.Results demonstrate that the proposed method performs well in dealing with the complex background and illumination condition.

Principle of Line Configuration and Monte-Carlo Simulation for Shared Multi-Channel System

Based on the steady-state solution of finite-state birth and death process, the principle of line configuration for shared multi-channel system is analyzed. Call congestion ratio equation and channel utilization ratio equation are deduced, and visualized data analysis is presented. The analy-sis indicates that, calculated with the proposed equations, the overestimate for call congestion ratio and channel utilization ratio can be rectified, and thereby the cost of channels can be saved by 2000 in a small system.With MATLAB programming, line configuration methods are provided. In order to generally and intuitively show the dynamic running of the system, and to analyze,promote and improve it, the system is simulated using M/M/n/n/m queuing model and Monte-Carlo method. In addition, the simulation validates the correctness of the theoretical analysis and optimizing configuration method.

Study on the Relationship between Lamellar Spacing and Growth Rate inthe Regular Eutectic Growthby Monte-Carlo Simulation

A modified Monte-Carlo(MC) method to simulate the regular growth of binary eutectic alloys is presented. It is found that the growth rate has a linear dependence on the chemical potential difference between the solid and liquid; the relation between the lamellar spacing A and growth rate R accords well with the prediction of Jackson-Hunt(JH) theory unless the growth rate is very low.

Monte-Carlo Simulation of Response Functions for Natural Gamma-Rays in LaBr_3 Detector System with Complex Borehole Configurations

Usually, there are several methods, e.g. experiment, interpolation experiment-based, analytic function, and Monte-Carlo simulation, to calculate the response functions in LaBr3（Ce） detectors. In logging applications, the experiment-based methods cannot be adopted because of their limitations. Analytic function has the advantage of fast calculating speed, but it is very difficult to take into account many effects that occur in practical applications. On the contrary, Monte-Carlo simulation can deal with physical and geometric configurations very tactfully. It has a distinct advantage for calculating the functions with complex configurations in borehole. A new application of LaBr3（Ce） detector is in natural gamma-rays borehole spectrometer for uranium well logging. Calculation of response functions must consider a series of physical and geometric factors under complex logging conditions, including earth formations and its relevant parameters, different energies, material and thickness of the casings, the fluid between the two tubes, and relative position of the LaBr3（Ce） crystal to steel ingot at the front of logging tube. The present work establishes Monte-Carlo simulation models for the above-mentioned situations, and then performs calculations for main gamma-rays from natural radio-elements series. The response functions can offer experimental directions for the design of borehole detection system, and provide technique basis and basic data for spectral analysis of natural gamma-rays, and for sonrceless calibration in uranium quantitative interpretation.

Monte-Carlo simulation of a stochastic differential equation

For solving higher dimensional diffusion equations with an inhomogeneous diffusion coefficient,Monte Carlo（MC） techniques are considered to be more effective than other algorithms, such as finite element method or finite difference method. The inhomogeneity of diffusion coefficient strongly limits the use of different numerical techniques. For better convergence, methods with higher orders have been kept forward to allow MC codes with large step size. The main focus of this work is to look for operators that can produce converging results for large step sizes. As a first step, our comparative analysis has been applied to a general stochastic problem.Subsequently, our formulization is applied to the problem of pitch angle scattering resulting from Coulomb collisions of charge particles in the toroidal devices.

Analysis of typhoon wind hazard in Shenzhen City by Monte-Carlo Simulation

As one of the most serious natural disasters,many typhoons affect southeastern China every year.Taking Shenzhen,a coastal city in southeast China as an example,we employed a Monte-Carlo simulation to generate a large number of virtual typhoons for wind hazard analysis.By analyzing 67-year historical typhoons data from 1949 to 2015 using the Best Track Dataset for Tropical Cyclones over the Western North Pacific recorded by the Shanghai Typhoon Institute,China Meteorological Administration(CMASTI),typhoon characteristic parameters were extracted and optimal statistical distributions established for the parameters in relation to Shenzhen.We employed the Monte-Carlo method to sample each distribution to generate the characteristic parameters of virtual typhoons.In addition,the Yah Meng(YM)wind field model was introduced,and the sensitivity of the YM model to several parameters discussed.Using the YM wind field model,extreme wind speeds were extracted from the virtual typhoons.The extreme wind speeds for different return periods were predicted and compared with the current structural code to provide improved wind load information for wind-resistant structural design.

Monte-Carlo Simulation of Surface Crack Growth Rate for Offshore Structural Steel E36-Z35

The Monte- Carlo method is used to simulate the surface fatigue crack growth rate for offshore structural steel E36-Z35, and to determine the distributions and relevance of the parameters in the Paris equation. By this method, the time and cost of fatigue crack propagation testing can be reduced. The application of the method is demonstrated by use of four sets of fatigue crack propagation data for offshore structural steel E36-Z35. A comparison of the test data with the theoretical prediction for surface crack growth rate shows the application of the simulation method to the fatigue crack propagation tests is successful.

Monte-Carlo simulation for determining SNR and DQE of linear array plastic scintillating fiber

Fundamental characteristics of the plastic-scintillating fiber (PSF) for wide energy range of electromag- netic radiation (X & γ) have been studied to evaluate possibility of using the PSF as an imaging detector for industrial purposes. Monte-Carlo simulation program (GEANT4.5.1, 2003) was used to generate the data. In order to evaluate image quality of the detector, fiber array was irradiated under various energy and fluxes. Signal to noise ratio (SNR) as well as detector quantum efficiency (DQE) were obtained.

An analysis of the radar backscatter from oil-covered sea surfaces using moment method and Monte-Carlo simulation: preliminary results

An analysis of the radar backscattering from the ocean surface covered by oil spill is presented using a mi- crowave scattering model and Monte-Carlo simulation. In the analysis, a one-dimensional rough sea sur- face is numerically generated with an ocean waveheight spectrum for a given wind velocity. A two-layered medium is then generated by adding a thin oil layer on the simulated rough sea surface. The electric fields backscattered from the sea surface with two-layered medium are computed with the method of moments （MoM）, and the backscattering coefficients are statistically obtained with N independent samples for each oil-spilled surface using the Monte-Carlo technique for various conditions of surface roughness, oil-layer thickness, frequency, polarization and incidence angle. The numerical simulation results are compared with theoretical models for clean sea surfaces and SAR images of an off-spilled sea surface caused by the Hebei （Hebei province, China） Spirit oil tanker in 2007. Further, conditions for better oil spill extraction are sought by the numerical simulation on the effects of wind speed and oil-layer thickness at different inci- dence angles on the backscattering coefficients.

Approach of technical decision-making by element flow analysis and Monte-Carlo simulation of municipal solid waste stream

This paper deals with the procedure and methodology which can be used to select the optimal treatment and disposal technology of municipal solid waste （MSW）, and to provide practical and effective technical support to policy-making, on the basis of study on solid waste management status and development trend in China and abroad. Focusing on various treatment and disposal technologies and processes of MSW, this study established a Monte-Carlo mathematical model of cost minimization for MSW handling subjected to environmental constraints. A new method of element stream （such as C, H, O, N, S） analysis in combination with economic stream analysis of MSW was developed. By following the streams of different treatment processes consisting of various techniques from generation, separation, transfer, transport, treatment, recycling and disposal of the wastes, the element constitution as well as its economic distribution in terms of possibility functions was identified. Every technique step was evaluated economically. The Mont-Carlo method was then conducted for model calibration. Sensitivity analysis was also carried out to identify the most sensitive factors. Model calibration indicated that landfill with power generation of landfill gas was economically the optimal technology at the present stage under the condition of more than 58% of C, H, O, N, S going to landfill. Whether or not to generate electricity was the most sensitive factor. If landfilling cost increases, MSW separation treatment was recommended by screening first followed with incinerating partially and composting partially with residue landfilling. The possibility of incineration model selection as the optimal technology was affected by the city scale. For big cities and metropolitans with large MSW generation, possibility for constructing large-scale incineration facilities increases, whereas, for middle and small cities, the effectiveness of incinerating waste decreases.

Monte-Carlo Simulation on the Failure of Fiber in a Single Filament Composite

A Monte-Carlo method is used to simulate gradual fracture of fiber in a single filament composite with the increase of virtual stress. A simple computational algorithm is developed to judge where breaking point will happen in the composite and a probability model based on Weibull- distribution is designed to calculate the average fragment length by producing stable and uniform random number in (0, 1). Compared to the published experiment results, the simulating average fragment length is quite perfect.

Electron beam irradiation on novel coronavirus(COVID-19):A Monte-Carlo simulation

The novel coronavirus pneumonia triggered by COVID-19 is now raging the whole world.As a rapid and reliable killing COVID-19 method in industry,electron beam irradiation can interact with virus molecules and destroy their activity.With the unexpected appearance and quickly spreading of the virus,it is urgently necessary to figure out the mechanism of electron beam irradiation on COVID-19.In this study,we establish a virus structure and molecule model based on the detected gene sequence of Wuhan patient,and calculate irradiated electron interaction with virus atoms via a Monte Carlo simulation that track each elastic and inelastic collision of all electrons.The characteristics of irradiation damage on COVID-19,atoms’ionizations and electron energy losses are calculated and analyzed with regions.We simulate the different situations of incident electron energy for evaluating the influence of incident energy on virus damage.It is found that under the major protecting of an envelope protein layer,the inner RNA suffers the minimal damage.The damage for a^100-nm-diameter virus molecule is not always enhanced by irradiation energy monotonicity,for COVID-19,the irradiation electron energy of the strongest energy loss damage is 2 keV.

MONTE-CARLO SIMULATION FOR ATOMIC DEPOSITION OF AMORPHOUS ELECTROLESS Ni_(80)P_(20) COATING

Atomic growth process and structure of Amorphous Electroless Coating have been studied, using Monte-Carlo simulation method. The simulation results of amorphous Ni80P20 coating show that PDFs are in accordance with practical values. The migrations of adatoms in coating's growth are different from that of solidification of amorphous materials. In some cases, the migrated adatoms in the process of growth of amorphous coating are not enough to occupy all vacancies and traps, so the amorphous coating is micro-porous. The immovable probability k and the largest migration distance of adatoms, which lie on the electroless bath components, affect the PDF, volume density and microporosity remarkably.

Monte-Carlo simulation of pinhole collimator of a small field of view gamma camera for small animal imaging

Needs in scintimammography applications,especially for small animal cardiac imaging,lead to develop a small field of view,high spatial resolution gamma camera with a pinhole collimator.However the ideal pinhole collimator must keep a compromise between spatial resolution and sensitivity.In order to design a pinhole collimator with an optimized sensitivity and spatial resolution,the spatial resolution and the geometric sensitivity response as a function of the source to collimator distance has been obtained by means of Monte-Carlo simulation for a small field of view gamma camera with a pinhole collimator of various-hole diameters.The results show that the camera with pinhole of 1 mm,1.5 mm and 2 mm diameter has respectively spatial resolution of 1.5 mm,2.25 mm and 3 mm and geometric sensitivity of 0.016%,0.022%and 0.036%,while the source to collimator distance is 3 cm.We chose the pinhole collimator with hole diameter size of 1.2 mm for our the gamma camera designed based on the trade-off between sensitivity and resolution.

Monte-Carlo simulation of cement neutron field distribution characteristics in PGNAA

The distribution characteristics of the neutron field in cement was simulated using the MCNP code to comply with the requirements of an online Prompt Gamma Neutron Activation Analysis system.Simulation results showed that the neutron relative flux proportion reduced with increasing cement thickness.When the cement thickness remains unchanged,the reduced proportion of thermal neutrons increases to a small extent,but the epithermal, intermediate,and fast neutrons will decrease according to the geometric progression.H element in the cement mainly affects the reduction of fast neutrons and other single-substance elements,e.g.,O,Ca,56Fe,Si,and Al.It also slows down the reduction of the fast neutrons via inelastic scattering.O contributes more than other elements in the reduction of fast neutrons.Changing the H content affects the thermal,epithermal,intermediate,and fast neutrons, while changing the Ca,Fe,and Si contents only influences the thermal,epithermal,and intermediate neutrons;hence, there is little effect on the reduction of fast neutrons.

基于Plant Simulation的化纤自动落丝系统仿真实验分析

基于Plant Simulation软件,构建一种化纤自动落丝系统的3D数字化模型,对系统效率关键输入因子进行参数化设置,将系统各工位三维数字模型导入软件中建立层次化运动机构图形结构,并运用Simltalk语言实现三维动作仿真,通过基础物理参数设置,保证了仿真数字化模型与现实系统更具一致性。通过多级实验设计分析了系统影响因子对于系统效率的影响特性曲线,并进一步通过动态参数化实验方法,计算出双输入因子对系统效能影响的敏感度。该实验结果可为化纤自动落丝系统的建设成本控制与可行性分析提供指导,具有较好的工程应用价值。

基于Simulation X的多轴转向系统功能安全仿真分析

基于ISO 26262《道路车辆功能安全》的标准要求,对特种车的多轴电液转向系统进行分析,以提高系统的安全性和可靠性。运用Simulation X软件建立详细的多轴特种车仿真模型,通过模拟故障模式注入进行仿真试验。对仿真结果和数据进行分析,评估得到故障的严重性、暴露度和可控性,从而确定相应的汽车安全完整性等级。基于故障注入仿真的汽车功能安全分析方法,在系统早期设计阶段可以作为评估架构安全性的重要手段。

基于Plant Simulation的压气机叶片型线加工产线分析与优化

运用专业仿真软件Plant Simulation,根据压气机叶片型线机械加工工艺特点和物料运行流程建立生产线仿真模型,从产能、设备利用率及产线瓶颈等多方面进行仿真分析与优化。结果表明:Plant Simulation仿真平台的仿真可以找出规划设计方案中存在的问题并验证方案的合理性。该仿真结果为型线机械加工产线的优化设计提供了可靠依据,达到了节约投资成本和缩短设计周期的目的。

Exhaustive review of acceleration strategies for Monte Carlo simulations in photon transit

Monte Carlo simulation techniques have become the quintessence and a pivotal nexus of inquiry in the realm of simulating photon movement within biological fabrics.Through the stochastic sampling of tissue archetypes delineated by explicit optical characteristics,Monte Carlo simulations possess the theoretical capacity to render unparalleled accuracy in the depiction of exceedingly intricate phenomena.Nonetheless,the quintessential challenge associated with Monte Carlo simulation methodologies resides in their extended computational duration,which significantly impedes the refinement of their precision.Consequently,this discourse is specifically dedicated to exploring innovations in strategies and technologies aimed at expediting Monte Carlo simulations.It delves into the foundational concepts of various acceleration tactics,evaluates these strategies concerning their speed,accuracy,and practicality,and amalgamates a comprehensive overview and critique of acceleration methodologies for Monte Carlo simulations.Ultimately,the discourse envisages prospective trajectories for the employment of Monte Carlo techniques within the domain of tissue optics.