Based on the stochastic uncertainty of the system’s operating environment,this research presents statistical inferences on the mean time to failure(MTTF)of a K-out-of-N:G nonrepairable system model with switching fai...Based on the stochastic uncertainty of the system’s operating environment,this research presents statistical inferences on the mean time to failure(MTTF)of a K-out-of-N:G nonrepairable system model with switching failure under Poisson shocks.The standby component is switched to the operating component when an operating component fails,with a switching failure probability of p.The MTTF of the system is derived by using the Markov process theory and the Laplace transform for two cases where the shock threshold is a constant value or a random variable.The maximum likelihood estimator(MLE)of the MTTF is obtained,and based on this estimator,asymptotic confidence interval estimation and hypothesis testing are performed.Based on the setting of the basic parameter values,the MTTF under two different cases of the shock threshold is compared.The effect of each parameter on the MTTF is analyzed in numerical simulation.The effectiveness of the above statistical inference methods is also verified by numerical simulation.展开更多
The dynamic characteristics of cooking-related particle size distributions in real-world settings are not fully understood.Through a real-world campaign in a naturally-ventilated apartment in the northwest US,this stu...The dynamic characteristics of cooking-related particle size distributions in real-world settings are not fully understood.Through a real-world campaign in a naturally-ventilated apartment in the northwest US,this study investigates the temporal profiles of size-resolved particle number concentrations(PNCs)ranging from 0.3 to 10µm from frying cooking activities.The cooking scenarios included various combinations of window ventilation,venting range hood(VRH)use,and portable air cleaner(PAC)utilization.Following a standardized pan-frying protocol throughout seven scenarios,real-time PNCs of 16-size bins were measured in the kitchen.The PNCs were empirically compared among size bins,periods,and scenarios.The most abundant size ranges of cooking-related particles were 0.3–0.579µm in number(45%–71%of the total)and 2.685–5.182µm in mass(48%–57%of the total).Compared with the scenario without any cooking-fume mitigating measures,keeping the kitchen windows open reduced the mean PNCs during and within 1-h after cooking for PM_(0.3-2.5),PM_(2.5-10),and PM_(0.3-10)by 78%,92%,and 79%,respectively.By contrast,utilizing a VRH during cooking reduced the corresponding levels by 21%,69%,and 25%,respectively.Combined with running the VRH,using a PAC in the kitchen led to additional reductions of 84%,88%,and 84%,respectively.Additionally,the removal efficiencies of the three strategies generally increased with particle sizes.展开更多
This paper investigates a warm standby repairable retrial system with two types of components and a single reparman,where type 1 components have priority over type 2 in use.Failure and repair times for each type of co...This paper investigates a warm standby repairable retrial system with two types of components and a single reparman,where type 1 components have priority over type 2 in use.Failure and repair times for each type of component are assumed to be exponential distributions.The retrial feature is considered and the retrial time of each failed component is exponentially distributed.By using Markov process theory and matrix analytic method,the system steady-state probabil-ities are derived,and the system steady-state availability and some steady-state performance indices are obtained.Using the Bayesian approach,the system parameters can be estimated.The cost-benefit ratio function of the system is constructed based on the failed components and repairman's states.Numerical experiments are given to evaluate the effect of each parameter on the system steady-state availability and optimize the system cost-benefit ratio with repair rate as a decision variable.展开更多
基金supported by the National Natural Science Foundation of China[grant number 72071175]the Project of Hebei Key Laboratory of Software Engineering[grant number 22567637H]the Basic Innovative Research and Cultivation Project of Yanshan University[grant number 2023LGZD003].
文摘Based on the stochastic uncertainty of the system’s operating environment,this research presents statistical inferences on the mean time to failure(MTTF)of a K-out-of-N:G nonrepairable system model with switching failure under Poisson shocks.The standby component is switched to the operating component when an operating component fails,with a switching failure probability of p.The MTTF of the system is derived by using the Markov process theory and the Laplace transform for two cases where the shock threshold is a constant value or a random variable.The maximum likelihood estimator(MLE)of the MTTF is obtained,and based on this estimator,asymptotic confidence interval estimation and hypothesis testing are performed.Based on the setting of the basic parameter values,the MTTF under two different cases of the shock threshold is compared.The effect of each parameter on the MTTF is analyzed in numerical simulation.The effectiveness of the above statistical inference methods is also verified by numerical simulation.
基金the Fundamental Research Funds for the Central Universities,Sun Yat-sen University(22qntd4308)a special fund of Beijing Key Laboratory of Indoor Air Quality Evaluation and Control(No.BZ0344KF21-05)State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex(No.SCAPC202106).
文摘The dynamic characteristics of cooking-related particle size distributions in real-world settings are not fully understood.Through a real-world campaign in a naturally-ventilated apartment in the northwest US,this study investigates the temporal profiles of size-resolved particle number concentrations(PNCs)ranging from 0.3 to 10µm from frying cooking activities.The cooking scenarios included various combinations of window ventilation,venting range hood(VRH)use,and portable air cleaner(PAC)utilization.Following a standardized pan-frying protocol throughout seven scenarios,real-time PNCs of 16-size bins were measured in the kitchen.The PNCs were empirically compared among size bins,periods,and scenarios.The most abundant size ranges of cooking-related particles were 0.3–0.579µm in number(45%–71%of the total)and 2.685–5.182µm in mass(48%–57%of the total).Compared with the scenario without any cooking-fume mitigating measures,keeping the kitchen windows open reduced the mean PNCs during and within 1-h after cooking for PM_(0.3-2.5),PM_(2.5-10),and PM_(0.3-10)by 78%,92%,and 79%,respectively.By contrast,utilizing a VRH during cooking reduced the corresponding levels by 21%,69%,and 25%,respectively.Combined with running the VRH,using a PAC in the kitchen led to additional reductions of 84%,88%,and 84%,respectively.Additionally,the removal efficiencies of the three strategies generally increased with particle sizes.
基金This work was supported by the National Natural Science Foundation of China[Grant Number 72071175,72001070].
文摘This paper investigates a warm standby repairable retrial system with two types of components and a single reparman,where type 1 components have priority over type 2 in use.Failure and repair times for each type of component are assumed to be exponential distributions.The retrial feature is considered and the retrial time of each failed component is exponentially distributed.By using Markov process theory and matrix analytic method,the system steady-state probabil-ities are derived,and the system steady-state availability and some steady-state performance indices are obtained.Using the Bayesian approach,the system parameters can be estimated.The cost-benefit ratio function of the system is constructed based on the failed components and repairman's states.Numerical experiments are given to evaluate the effect of each parameter on the system steady-state availability and optimize the system cost-benefit ratio with repair rate as a decision variable.
