Stochastic perturbations and periodic excitations are generally regarded as sources to induce critical transitions in complex systems. However, we find that they are also able to slow down an imminent critical transit...Stochastic perturbations and periodic excitations are generally regarded as sources to induce critical transitions in complex systems. However, we find that they are also able to slow down an imminent critical transition. To illustrate this phenomenon, a periodically driven bistable eutrophication model with Gaussian white noise is introduced as a prototype class of real systems.The residence probability(RP) is presented to measure the possibility that the given system stays in the oligotrophic state versus Gaussian white noise and periodic force. Variations in the mean first passage time(MFPT) and the mean velocity(MV) of the first right-crossing process are also calculated respectively. We show that the frequency of the periodic force can increase the MFPT while reduce the MV under different control parameters. Nevertheless, the noise intensity or the amplitude may result in an increase of the RP only in the case of control parameters approaching the critical values. Furthermore, for an impending critical transition, an increase of the RP appears with the interaction between the amplitude and noise intensity or the combination of the noise intensity and frequency, while the interaction of the frequency and amplitude leads to an extension of the MFPT or a decrease of the MV. As a result, an increase of the RP and MFPT, and a decrease of the MVobtained from our results claim that it is possible to slow down an imminent critical transition via Gaussian white noise and periodic force.展开更多
Based upon the micro-stochastic failure mechanisms of composites,a new micromechanical statistical model,i.e.randomly enlarging critical core theory,for the tensile failure of unidirectional composites is proposed,wit...Based upon the micro-stochastic failure mechanisms of composites,a new micromechanical statistical model,i.e.randomly enlarging critical core theory,for the tensile failure of unidirectional composites is proposed,with which we can overcome the primary imperfections of the existing chain-of-bundles probability model.On the basis of the established statistical model,the strength distribution and the failure criterion of composites are derived.The predictions of strength for T300/5208 and glass/epoxy show very good agreement with the existing experimental results,thus verifying the reasonableness and correctness of the present theory.展开更多
Using sudden cardiac deaths as an example and maximizing survival rate as the goal, this paper studies the influence of multi-stage medical logistics system optimization on the survival rate of sudden illness. A distr...Using sudden cardiac deaths as an example and maximizing survival rate as the goal, this paper studies the influence of multi-stage medical logistics system optimization on the survival rate of sudden illness. A distribution model of survival is built, drone and ambulance arrival probability over time are discussed, a formula is proposed for maximum possible survival rate based on the probability of emergency medical logistics reaching the patient, and the results are analyzed using empirical data fitting distribution and numerical experiments performed with the model. The model is discussed as a reference point for management decision making by changing model parameters. Results show that compared to using current ambulance vehicles, ambulance drones delivering medical equipment for first aid on-site in emergencies can significantly increase survival rate, and the effect of collaborative multi-stage logistics optimization is better than that of any single stage logistics response optimization. Simulation results show that the medical rescue logistics service radius, speed, loading capacity and performance of ambulance drones impact the probability of survival, and there is an optimal service radius depending on the shape of probability distribution, which provides new information for management decisions.展开更多
基金supported by the National Natural Science Foundation of China(Grant Nos.11772255&11872305)the Fundamental Research Funds for the Central Universities+2 种基金Shaanxi Province Project for Distinguished Young ScholarsInnovation Foundation for Doctor Dissertation of Northwestern Polytechnical Universitythe China Postdoctoral Science Foundation
文摘Stochastic perturbations and periodic excitations are generally regarded as sources to induce critical transitions in complex systems. However, we find that they are also able to slow down an imminent critical transition. To illustrate this phenomenon, a periodically driven bistable eutrophication model with Gaussian white noise is introduced as a prototype class of real systems.The residence probability(RP) is presented to measure the possibility that the given system stays in the oligotrophic state versus Gaussian white noise and periodic force. Variations in the mean first passage time(MFPT) and the mean velocity(MV) of the first right-crossing process are also calculated respectively. We show that the frequency of the periodic force can increase the MFPT while reduce the MV under different control parameters. Nevertheless, the noise intensity or the amplitude may result in an increase of the RP only in the case of control parameters approaching the critical values. Furthermore, for an impending critical transition, an increase of the RP appears with the interaction between the amplitude and noise intensity or the combination of the noise intensity and frequency, while the interaction of the frequency and amplitude leads to an extension of the MFPT or a decrease of the MV. As a result, an increase of the RP and MFPT, and a decrease of the MVobtained from our results claim that it is possible to slow down an imminent critical transition via Gaussian white noise and periodic force.
基金Project supported by the National Natural Science Foundation of China
文摘Based upon the micro-stochastic failure mechanisms of composites,a new micromechanical statistical model,i.e.randomly enlarging critical core theory,for the tensile failure of unidirectional composites is proposed,with which we can overcome the primary imperfections of the existing chain-of-bundles probability model.On the basis of the established statistical model,the strength distribution and the failure criterion of composites are derived.The predictions of strength for T300/5208 and glass/epoxy show very good agreement with the existing experimental results,thus verifying the reasonableness and correctness of the present theory.
基金supported by the National Natural Science Foundation of China (Grant No. 71390333)the National Key Technology R&D Program of China during the 12th Five-Year Plan Period (Grant No. 2013BAD19B05)
文摘Using sudden cardiac deaths as an example and maximizing survival rate as the goal, this paper studies the influence of multi-stage medical logistics system optimization on the survival rate of sudden illness. A distribution model of survival is built, drone and ambulance arrival probability over time are discussed, a formula is proposed for maximum possible survival rate based on the probability of emergency medical logistics reaching the patient, and the results are analyzed using empirical data fitting distribution and numerical experiments performed with the model. The model is discussed as a reference point for management decision making by changing model parameters. Results show that compared to using current ambulance vehicles, ambulance drones delivering medical equipment for first aid on-site in emergencies can significantly increase survival rate, and the effect of collaborative multi-stage logistics optimization is better than that of any single stage logistics response optimization. Simulation results show that the medical rescue logistics service radius, speed, loading capacity and performance of ambulance drones impact the probability of survival, and there is an optimal service radius depending on the shape of probability distribution, which provides new information for management decisions.
