SMC再生SBS沥青的流变性能和微观特性研究

【目的】探究新型温拌再生剂甲基苯乙烯共聚物(styreneic methyl copolymer,SMC)对老化苯乙烯系热塑性弹性体(styrene butadiene styrene,SBS)改性沥青的再生效果和再生机理。【方法】首先,在室内制备不同老化程度的沥青。然后,采用SMC再生剂对不同老化程度的SBS改性沥青进行再生。接着,对再生后的SBS改性沥青进行动态剪切流变和低温弯曲蠕变试验,以评价其流变性能。最后,开展红外光谱试验以揭示其作用机理,进行电镜扫描试验以验证SMC再生剂的再生效果。【结果】SMC再生剂会降低老化SBS改性沥青的车辙因子,降低老化SBS改性沥青的恢复率,同时会使老化SBS改性沥青的低温性能得到极大提升。SMC再生剂未与SBS改性沥青发生化学反应,两者仅为物理共混。同时,SMC再生剂能够弥补沥青因老化产生的裂缝。【结论】SMC再生剂对老化SBS改性沥青具有较好的修复效果,能够为沥青的再生提供一种新的途径。

真空羽流中相变过程DSMC仿真方法研究

真空燃气羽流快速膨胀过程中,其中的H_(2)O和CO_(2)等组元容易发生凝结相变现象.为了研究真空羽流中水蒸气的相变产物冰晶对羽流红外信号、侵蚀等污染效应的影响,开展羽流中相变过程的数值模拟方法研究.基于稀薄两相羽流双向耦合DSMC方法,采用经典成核理论和液滴生长理论,建立了真空羽流的相变过程的数值仿真方法.对水蒸气在拉法尔喷管中自凝结试验的仿真.通过与试验结果的对比,对经典成核理论进行了修正,对成核率给出了10^(3)的修正因子,可以得到与试验符合的仿真结果,表明对成核理论修正后,可以应用到稀薄流动的数值模拟中.对某发动机真空羽流相变流场的仿真,在核心区得到与CFD相近的结果.仿真结果表明,在羽流流场中,由于相变,存在较多的冰晶颗粒,在计算条件下,羽流核心区冰晶数密度最大达到10^(15) m^(-3)的量级,冰晶直径在约10^(-8) m的量级.在真空环境下,随着羽流向倒流区无限制膨胀,倒流区流场内也会出现一定数量的冰晶颗粒,数密度从10^(7)~10^(10)m^(-3)的量级,直径在5.0×10^(-10)m的量级.颗粒在空间的数密度、尺寸等分布与气相分布存在差异,需要开展相关污染效应的影响研究.

基于多策略改进的SMC-GTO电机速度跟踪控制

针对传统控制算法在农业机器人驱动电机速度控制方面存在的响应时间长、跟踪效果差以及参数整定难度大,导致驱动电机转速难以在短时间内收敛至预期值的问题,提出一种基于多策略改进的SMC-GTO电机速度跟踪控制算法。首先,为了缩短驱动电机速度响应时间,提高速度跟踪效果,设计了一种新型趋近率的改进滑模控制器(I-SMC);其次,为了快速整定滑模控制器参数,引入了多策略改进的大猩猩部队优化算法(MIGTO)。仿真结果表明:I-SMC能够将电机运行过程中的动态误差累计与过冲控制在0 rad/s内,并且可以在0.4 s内响应至预定速度。MIGTO算法在开发和探索阶段均展现出卓越的性能,尤其在整定基于新型趋近率的改进滑模控制器参数工作中表现突出。该研究通过引入I-SMC和MIGTO算法,成功改进了驱动电机速度控制方式,有效缩短了响应时间,提升了速度跟踪效果。

Monte Carlo方法在移动通信可靠性分析中的应用

文章主要探讨Monte Carlo方法在移动通信可靠性分析中的应用,并引入重要抽样技术对Monte Carlo方法进行优化。首先,文章介绍Monte Carlo方法的基本原理及其在移动通信可靠性分析中的应用。其次,引入重要抽样技术对该方法进行优化。最后,利用优化网络工程工具(Optimized Network Engineering Tools,OPNET)模拟平台构建相应的移动通信网络模型,并对比Monte Carlo方法和本文研究的优化方法在不同样本数量下的性能差异。结果表明,重要抽样技术的引入显著提高了Monte Carlo方法在移动通信可靠性分析中的准确性和效率,减少了方差,验证了该方法在移动通信可靠性分析中的有效性和实用性。

智能汽车轨迹跟踪MPC-RBF-SMC协同控制策略研究

针对自动驾驶车辆行驶过程中模型失配以及外部环境干扰导致车辆轨迹跟踪环节精确性不高的问题,提出了一种结合车辆运动学模型预测控制(MPC)、径向基(RBF)神经网络和滑模控制(SMC)的轨迹跟踪控制策略。通过建立车辆运动学MPC模型计算当前状态车辆期望横摆角速度,并将其与实际横摆角速度的偏差输入RBF-SMC控制器,利用RBF快速逼近非线性模型的特点,结合滑模控制输出前轮转角,实现车辆的横向轨迹跟踪控制。仿真结果表明,与传统的控制器相比,该方法轨迹跟踪精度显著提高,并在不同行驶工况下表现出较好的鲁棒性。

基于Monte-Carlo仿真的恒应力加速试验方案模拟评价

为了保证可靠性加速试验方案的正确性和可行性,提出基于仿真的模拟评价方法。以最具代表性的Weibull寿命分布产品的恒应力加速寿命试验为例,以代表试验结果准确性和稳定性的指标——中位寿命估计值渐进方差的均值和标准差作为评价指标,通过Monte-Carlo仿真模拟生成失效数据,对不同试验方案的统计精度和稳定性进行评价,为加速寿命试验优化设计的工程实现提供了思路和实例验证。

基于SMCS模型的高强螺栓及节点火灾全过程断裂性能模拟

高强螺栓广泛应用于钢结构节点连接,火灾高温会影响其基本材性和断裂行为,从而影响螺栓节点抗火性能甚至整体结构抗倒塌性能。基于10.9级高强螺栓火灾全过程(升温段、降温段、火灾后)单轴拉伸试验结果,结合有限元模拟,对不同温度历程和应力三轴度对应的螺栓SMCS断裂模型进行校准,并与螺栓材性试验和T-stub节点试验结果对比验证;对T-stub节点火灾全过程断裂行为进行参数分析,研究损伤准则和温度历程对节点失效模式和变形特征的影响。结果表明:校准的SMCS模型能够有效、准确地预测螺栓和节点在火灾全过程和高应力三轴度(0.3~1.2)下的受拉断裂行为,适用预测误差在12%以内;拉伸温度和峰值温度是影响高强螺栓抗断能力的主要因素,螺栓抗断能力随温度升高而提高;不同温度历程下T-stub节点可能发生翼缘板屈服断裂、翼缘板和螺栓同时屈服断裂、螺栓屈服断裂三种失效模式,且节点的变形能力(延性系数)与失效模式有关,确定钢板母材和螺栓的断裂模型是准确预测节点失效模式的关键。

The DNA damage repair complex MoMMS21-MoSMC5 is required for infection-related development and pathogenicity of Magnaporthe oryzae

The conserved DNA damage repair complex,MMS21-SMC5/6(Methyl methane sulfonate 21-Structural maintenance of chromosomes 5/6),has been extensively studied in yeast,animals,and plants.However,its role in phytopathogenic fungi,particularly in the highly destructive rice blast fungus Magnaporthe oryzae,remains unknown.In this study,we functionally characterized the homologues of this complex,MoMMS21 and MoSMC5,in M.oryzae.We first demonstrated the importance of DNA damage repair in M.oryzae by showing that the DNA damage inducer phleomycin inhibited vegetative growth,infection-related development and pathogenicity in this fungus.Additionally,we discovered that MoMMS21 and MoSMC5 interacted in the nuclei,suggesting that they also function as a complex in M.oryzae.Gene deletion experiments revealed that both MoMMS21 and MoSMC5 are required for infection-related development and pathogenicity in M.oryzae,while only MoMMS21 deletion affected growth and sensitivity to phleomycin,indicating its specific involvement in DNA damage repair.Overall,our results provide insights into the roles of MoMMS21 and MoSMC5 in M.oryzae,highlighting their functions beyond DNA damage repair.

基于多元最小二乘-Monte Carlo模型在土石方测量中的应用研究

针对目前土方测量效率低,计算土方量精度差的现状,提出利用无人机进行土方测量,利用MATLAB软件进行编程,构建多元最小二乘-Monte Carlo模型对土方量进行计算,与传统的GNSS-RTK数据采集方法以及利用南方CASS软件计算结果对比,结果表明,利用无人机采集数据效率高,多元最小二乘-Monte Carlo模型取得结果精度更高。

Machine learning-enhanced Monte Carlo and subset simulations for advanced risk assessment in transportation infrastructure

The maintenance of safety and dependability in rail and road embankments is of utmost importance in order to facilitate the smooth operation of transportation networks.This study introduces a comprehensive methodology for soil slope stability evaluation,employing Monte Carlo Simulation(MCS)and Subset Simulation(SS)with the"UPSS 3.0 Add-in"in MS-Excel.Focused on an 11.693-meter embankment with a soil slope(inclination ratio of 2H:1V),the investigation considers earthquake coefficients(kh)and pore water pressure ratios(ru)following Indian zoning requirements.The chance of slope failure showed a considerable increase as the Coefficient of Variation(COV),seismic coefficients(kh),and pore water pressure ratios(ru)experienced an escalation.The SS approach showed exceptional efficacy in calculating odds of failure that are notably low.Within computational modeling,the study optimized the worst-case scenario using ANFIS-GA,ANFIS-GWO,ANFIS-PSO,and ANFIS-BBO models.The ANFIS-PSO model exhibits exceptional accuracy(training R2=0.9011,RMSE=0.0549;testing R2=0.8968,RMSE=0.0615),emerging as the most promising.This study highlights the significance of conducting thorough risk assessments and offers practical insights into evaluating and improving the stability of soil slopes in transportation infrastructure.These findings contribute to the enhancement of safety and reliability in real-world situations.

Emergent topological ordered phase for the Ising-XY model revealed by cluster-updating Monte Carlo method

The two-component cold atom systems with anisotropic hopping amplitudes can be phenomenologically described by a two-dimensional Ising-XY coupled model with spatial anisotropy.At low temperatures,theoretical predictions[Phys.Rev.A 72053604(2005)]and[arXiv:0706.1609]indicate the existence of a topological ordered phase characterized by Ising and XY disorder but with 2XY ordering.However,due to ergodic difficulties faced by Monte Carlo methods at low temperatures,this topological phase has not been numerically explored.We propose a linear cluster updating Monte Carlo method,which flips spins without rejection in the anisotropy limit but does not change the energy.Using this scheme and conventional Monte Carlo methods,we succeed in revealing the nature of topological phases with half-vortices and domain walls.In the constructed global phase diagram,Ising and XY-type transitions are very close to each other and differ significantly from the schematic phase diagram reported earlier.We also propose and explore a wide range of quantities,including magnetism,superfluidity,specific heat,susceptibility,and even percolation susceptibility,and obtain consistent and reliable results.Furthermore,we observed first-order transitions characterized by common intersection points in magnetizations for different system sizes,as opposed to the conventional phase transition where Binder cumulants of various sizes share common intersections.The critical exponents of different types of phase transitions are reasonably fitted.The results are useful to help cold atom experiments explore the half-vortex topological phase.

Monte Carlo Simulations of Doping Properties of a Spin-3/2 Ising Nanotube

The effect of spin-1 impurities doping on the magnetic properties of a spin-3/2 Ising nanotube is investigated using Monte Carlo simulations within the Blume-Emery-Griffiths model in the presence of an external magnetic field. The thermal behaviors of the order parameters and different macroscopic instabilities as well as the hysteretic behavior of the material are examined in great detail as a function of the dopant density. It is found that the impurities concentration affects all the system magnetic properties generating for some specific values, compensation points and multi-cycle hysteresis. Doping conditions where the saturation/remanent magnetization and coercive field of the investigated material can be modified for permanent or soft magnets synthesis purpose are discussed.

Research on a Monte Carlo global variance reduction method based on an automatic importance sampling method

Global variance reduction is a bottleneck in Monte Carlo shielding calculations.The global variance reduction problem requires that the statistical error of the entire space is uniform.This study proposed a grid-AIS method for the global variance reduction problem based on the AIS method,which was implemented in the Monte Carlo program MCShield.The proposed method was validated using the VENUS-Ⅲ international benchmark problem and a self-shielding calculation example.The results from the VENUS-Ⅲ benchmark problem showed that the grid-AIS method achieved a significant reduction in the variance of the statistical errors of the MESH grids,decreasing from 1.08×10^(-2) to 3.84×10^(-3),representing a 64.00% reduction.This demonstrates that the grid-AIS method is effective in addressing global issues.The results of the selfshielding calculation demonstrate that the grid-AIS method produced accurate computational results.Moreover,the grid-AIS method exhibited a computational efficiency approximately one order of magnitude higher than that of the AIS method and approximately two orders of magnitude higher than that of the conventional Monte Carlo method.

Enhancing Precision in Radiotherapy Delivery: Validating Monte Carlo Simulation Models for 6 MV Elekta Synergy Agility LINAC Photon Beam Using Two Models of the GAMOS Code

The most crucial requirement in radiation therapy treatment planning is a fast and accurate treatment planning system that minimizes damage to healthy tissues surrounding cancer cells. The use of Monte Carlo toolkits has become indispensable for research aimed at precisely determining the dose in radiotherapy. Among the numerous algorithms developed in recent years, the GAMOS code, which utilizes the Geant4 toolkit for Monte Carlo simula-tions, incorporates various electromagnetic physics models and multiple scattering models for simulating particle interactions with matter. This makes it a valuable tool for dose calculations in medical applications and throughout the patient’s volume. The aim of this present work aims to vali-date the GAMOS code for the simulation of a 6 MV photon-beam output from the Elekta Synergy Agility linear accelerator. The simulation involves mod-eling the major components of the accelerator head and the interactions of the radiation beam with a homogeneous water phantom and particle information was collected following the modeling of the phase space. This space was po-sitioned under the X and Y jaws, utilizing three electromagnetic physics mod-els of the GAMOS code: Standard, Penelope, and Low-Energy, along with three multiple scattering models: Goudsmit-Saunderson, Urban, and Wentzel-VI. The obtained phase space file was used as a particle source to simulate dose distributions (depth-dose and dose profile) for field sizes of 5 × 5 cm2 and 10 × 10 cm2 at depths of 10 cm and 20 cm in a water phantom, with a source-surface distance (SSD) of 90 cm from the target. We compared the three electromagnetic physics models and the three multiple scattering mod-els of the GAMOS code to experimental results. Validation of our results was performed using the gamma index, with an acceptability criterion of 3% for the dose difference (DD) and 3 mm for the distance-to-agreement (DTA). We achieved agreements of 94% and 96%, respectively, between simulation and experimentation for the three electromagnetic physics models and three mul-tiple scattering models, for field sizes of 5 × 5 cm2 and 10 × 10 cm2 for depth-dose curves. For dose profile curves, a good agreement of 100% was found between simulation and experimentation for the three electromagnetic physics models, as well as for the three multiple scattering models for a field size of 5 × 5 cm2 at 10 cm and 20 cm depths. For a field size of 10 × 10 cm2, the Penelope model dominated with 98% for 10 cm, along with the three multiple scattering models. The Penelope model and the Standard model, along with the three multiple scattering models, dominated with 100% for 20 cm. Our study, which compared these different GAMOS code models, can be crucial for enhancing the accuracy and quality of radiotherapy, contributing to more effective patient treatment. Our research compares various electro-magnetic physics models and multiple scattering models with experimental measurements, enabling us to choose the models that produce the most reli-able results, thereby directly impacting the quality of simulations. This en-hances confidence in using these models for treatment planning. Our re-search consistently contributes to the progress of Monte Carlo simulation techniques in radiation therapy, enriching the scientific literature.

Chord length sampling correction analysis for dispersion fuel in Monte Carlo simulation

Dispersion fuels,knowned for their excellent safety performance,are widely used in advanced reactors,such as hightemperature gas-cooled reactors.Compared with deterministic methods,the Monte Carlo method has more advantages in the geometric modeling of stochastic media.The explicit modeling method has high computational accuracy and high computational cost.The chord length sampling(CLS)method can improve computational efficiency by sampling the chord length during neutron transport using the matrix chord length?s probability density function.This study shows that the excluded-volume effect in realistic stochastic media can introduce certain deviations into the CLS.A chord length correction approach is proposed to obtain the chord length correction factor by developing the Particle code based on equivalent transmission probability.Through numerical analysis against reference solutions from explicit modeling in the RMC code,it was demonstrated that CLS with the proposed correction method provides good accuracy for addressing the excludedvolume effect in realistic infinite stochastic media.

双馈风力发电机的无功功率SMC控制

为了在DFIG系统启动时获得更好的功率调节性能,在DFIG机侧引入滑模控制器(SMC)。在无功功率调节电压环节加入基于指数趋近律的动态滑模变结构控制器,仿真结果显示在加入SMC控制器后,有功功率及无功功率的启动调节时间约缩短了1 s,系统稳定性也有所提升,表明该方法有效、合理,适用于工程。

Optimization of the Use of Spherical Targets for Point Cloud Registration Using Monte Carlo Simulation

Registrations based on the manual placement of spherical targets are still being employed by many professionals in the industry.However,the placement of those targets usually relies solely on personal experience without scientific evidence supported by numerical analysis.This paper presents a comprehensive investigation,based on Monte Carlo simulation,into determining the optimal number and positions for efficient target placement in typical scenes consisting of a pair of facades.It demonstrates new check-up statistical rules and geometrical constraints that can effectively extract and analyze massive simulations of unregistered point clouds and their corresponding registrations.More than 6×10^(7)sets of the registrations were simulated,whereas more than 100 registrations with real data were used to verify the results of simulation.The results indicated that using five spherical targets is the best choice for the registration of a large typical registration site consisting of two vertical facades and a ground,when there is only a box set of spherical targets available.As a result,the users can avoid placing extra targets to achieve insignificant improvements in registration accuracy.The results also suggest that the higher registration accuracy can be obtained when the ratio between the facade-to-target distance and target-to-scanner distance is approximately 3:2.Therefore,the targets should be placed closer to the scanner rather than in the middle between the facades and the scanner,contradicting to the traditional thought.Besides,the results reveal that the accuracy can be increased by setting the largest projected triangular area of the targets to be large.

Monte Carlo method for evaluation of surface emission rate measurement uncertainty

The aim of this study is to evaluate the uncertainty of 2πα and 2πβ surface emission rates using the windowless multiwire proportional counter method.This study used the Monte Carlo method (MCM) to validate the conventional Guide to the Expression of Uncertainty in Measurement (GUM) method.A dead time measurement model for the two-source method was established based on the characteristics of a single-channel measurement system,and the voltage threshold correction factor measurement function was indirectly obtained by fitting the threshold correction curve.The uncertainty in the surface emission rate was calculated using the GUM method and the law of propagation of uncertainty.The MCM provided clear definitions for each input quantity and its uncertainty distribution,and the simulation training was realized with a complete and complex mathematical model.The results of the surface emission rate uncertainty evaluation for four radioactive plane sources using both methods showed the uncertainty’s consistency E_(n)<0.070 for the comparison of each source,and the uncertainty results of the GUM were all lower than those of the MCM.However,the MCM has a more objective evaluation process and can serve as a validation tool for GUM results.

Evaluation of the Reliability of a System: Approach by Monte Carlo Simulation and Application

The objective of this paper is to evaluate the reliability of a system in its different states (absence of failures, partial failure and total failure) and to propose actions to improve this reliability by an approach based on Monte Carlo simulation. It consists of a probabilistic evaluation based on Markov Chains. In order to achieve this goal, the functionalities of Markov Chains and Monte Carlo simulation steps are deployed. The application is made on a production system. .

Health risk assessment of trace metal(loid)s in agricultural soils based on Monte Carlo simulation coupled with positive matrix factorization model in Chongqing, southwest China

This study aimed to investigate the pollution characteristics, source apportionment, and health risks associated with trace metal(loid)s(TMs) in the major agricultural producing areas in Chongqing, China. We analyzed the source apportionment and assessed the health risk of TMs in agricultural soils by using positive matrix factorization(PMF) model and health risk assessment(HRA) model based on Monte Carlo simulation. Meanwhile, we combined PMF and HRA models to explore the health risks of TMs in agricultural soils by different pollution sources to determine the priority control factors. Results showed that the average contents of cadmium(Cd), arsenic (As), lead(Pb), chromium(Cr), copper(Cu), nickel(Ni), and zinc(Zn) in the soil were found to be 0.26, 5.93, 27.14, 61.32, 23.81, 32.45, and 78.65 mg/kg, respectively. Spatial analysis and source apportionment analysis revealed that urban and industrial sources, agricultural sources, and natural sources accounted for 33.0%, 27.7%, and 39.3% of TM accumulation in the soil, respectively. In the HRA model based on Monte Carlo simulation, noncarcinogenic risks were deemed negligible(hazard index <1), the carcinogenic risks were at acceptable level(10^(-6)<total carcinogenic risk ≤ 10^(-4)), with higher risks observed for children compared to adults. The relationship between TMs, their sources, and health risks indicated that urban and industrial sources were primarily associated with As, contributing to 75.1% of carcinogenic risks and 55.7% of non-carcinogenic risks, making them the primary control factors. Meanwhile, agricultural sources were primarily linked to Cd and Pb, contributing to 13.1% of carcinogenic risks and 21.8% of non-carcinogenic risks, designating them as secondary control factors.