The method of mathematical model and further computer simulation is an effective way to the theoretical study of emulsion polymerization and the scale-up of the reactors. In this work, Monte Carlo method has been used...The method of mathematical model and further computer simulation is an effective way to the theoretical study of emulsion polymerization and the scale-up of the reactors. In this work, Monte Carlo method has been used to simulate the nucleation of emulsion polymerization. The effects of emulsifier concentration [S] and initiator concentration [I] on various parameters such as the number of the particles (N p), the average diameter of the latex particles (D p), monomer conversion (x) and average radical number per particle (n) have been studied. The quantitative equations between [S], [I] and N p are in accord absolutely with the classical theory of Smith-Ewart.展开更多
Scheduling is a major concern in construction planning and management, and current construction simulation research typically targets the shortest total duration. However, uncertainties are inevitable in actual constr...Scheduling is a major concern in construction planning and management, and current construction simulation research typically targets the shortest total duration. However, uncertainties are inevitable in actual construction, which may lead to discrepancies between the actual and planned schedules and increase the risk of total duration delay. Therefore, developing a robust construction scheduling technique is of vital importance for mitigating disturbance and improving completion probability. In the present study, the authors propose a robustness analysis method that involves underground powerhouse construction simulation based on the Markov Chain Monte Carlo(MCMC) method. Specifically, the MCMC method samples construction disturbances by considering the interrelationship between the states of parameters through a Markov state transition probability matrix, which is more robust and efficient than traditional sampling methods such as the Monte Carlo(MC) method. Additionally, a hierarchical simulation model coupling critical path method(CPM) and a cycle operation network(CYCLONE) is built, using which construction duration and robustness criteria can be calculated. Furthermore, a detailed measurement method is presented to quantize the robustness of underground powerhouse construction, and the setting model of the time buffer is proposed based on the MCMC method. The application of this methodology not only considers duration but also robustness, providing scientific guidance for engineering decision making. We analyzed a case study project to demonstrate the effectiveness and superiority of the proposed methodology.展开更多
Two methods currently available for evaluating the probability of Multiple Site Damage(MSD)occurrence were studied in this paper.One of the methods is a probabilistic analysis approach based on the statistical theory ...Two methods currently available for evaluating the probability of Multiple Site Damage(MSD)occurrence were studied in this paper.One of the methods is a probabilistic analysis approach based on the statistical theory and fatigue characteristics of each structural detail,and the other is an approach which defines the initial damage scenario by means of Monte-Carlo simulation,and multiple initial crack scenarios are randomly generated.A modified method based on the Monte-Carlo simulation was proposed in this paper,in which the random fluctuation of the stress was considered to give more accurate evaluation results.In the presented method,the probability of MSD occurrence in a structural element containing multiple details was calculated based on the Monte-Carlo simulation and the p-S-N curve of a single structural detail.Fatigue tests were accomplished using specimens containing 21-similar-details to obtain the fatigue life corresponding to MSD occurrence.Tests on single-detail specimens and static calibration tests were also conducted to get the basic fatigue properties of the material and the degree of stress fluctuation.The aforementioned three methods were compared and validated via the test results.The influence of the stress random fluctuation degree on the probability of MSD occurrence and influence of the distribution types on evaluating the MSD occurrence probability were discussed.展开更多
文摘The method of mathematical model and further computer simulation is an effective way to the theoretical study of emulsion polymerization and the scale-up of the reactors. In this work, Monte Carlo method has been used to simulate the nucleation of emulsion polymerization. The effects of emulsifier concentration [S] and initiator concentration [I] on various parameters such as the number of the particles (N p), the average diameter of the latex particles (D p), monomer conversion (x) and average radical number per particle (n) have been studied. The quantitative equations between [S], [I] and N p are in accord absolutely with the classical theory of Smith-Ewart.
基金supported by the Innovative Research Groups of the National Natural Science Foundation of China(Grant No.51321065)the National Natural Science Foundation of China(Grant Nos.9121530151439005)
文摘Scheduling is a major concern in construction planning and management, and current construction simulation research typically targets the shortest total duration. However, uncertainties are inevitable in actual construction, which may lead to discrepancies between the actual and planned schedules and increase the risk of total duration delay. Therefore, developing a robust construction scheduling technique is of vital importance for mitigating disturbance and improving completion probability. In the present study, the authors propose a robustness analysis method that involves underground powerhouse construction simulation based on the Markov Chain Monte Carlo(MCMC) method. Specifically, the MCMC method samples construction disturbances by considering the interrelationship between the states of parameters through a Markov state transition probability matrix, which is more robust and efficient than traditional sampling methods such as the Monte Carlo(MC) method. Additionally, a hierarchical simulation model coupling critical path method(CPM) and a cycle operation network(CYCLONE) is built, using which construction duration and robustness criteria can be calculated. Furthermore, a detailed measurement method is presented to quantize the robustness of underground powerhouse construction, and the setting model of the time buffer is proposed based on the MCMC method. The application of this methodology not only considers duration but also robustness, providing scientific guidance for engineering decision making. We analyzed a case study project to demonstrate the effectiveness and superiority of the proposed methodology.
文摘Two methods currently available for evaluating the probability of Multiple Site Damage(MSD)occurrence were studied in this paper.One of the methods is a probabilistic analysis approach based on the statistical theory and fatigue characteristics of each structural detail,and the other is an approach which defines the initial damage scenario by means of Monte-Carlo simulation,and multiple initial crack scenarios are randomly generated.A modified method based on the Monte-Carlo simulation was proposed in this paper,in which the random fluctuation of the stress was considered to give more accurate evaluation results.In the presented method,the probability of MSD occurrence in a structural element containing multiple details was calculated based on the Monte-Carlo simulation and the p-S-N curve of a single structural detail.Fatigue tests were accomplished using specimens containing 21-similar-details to obtain the fatigue life corresponding to MSD occurrence.Tests on single-detail specimens and static calibration tests were also conducted to get the basic fatigue properties of the material and the degree of stress fluctuation.The aforementioned three methods were compared and validated via the test results.The influence of the stress random fluctuation degree on the probability of MSD occurrence and influence of the distribution types on evaluating the MSD occurrence probability were discussed.
