The coupling model of major influence factors such state affecting the chloride diffusion process in concrete is as environmental relative humidity, load-induced crack and stress discussed. The probability distributio...The coupling model of major influence factors such state affecting the chloride diffusion process in concrete is as environmental relative humidity, load-induced crack and stress discussed. The probability distributions of the critical chloride concentration Cc, the chloride diffusion coefficient D, and the surface chloride concentration Cs were determined based on the collected natural exposure data. And the estimation of probability of corrosion initiation considering the coupling effects of influence factors is presented. It is found that the relative humidity and curing time are the most effective factors affecting the probability of corrosion initiation before and after 10 years of exposure time. At the same exposure time, the influence of load-induced crack and stress state on the probability of corrosion initiation is obvious, in which the effect of crack is the most one展开更多
集装箱码头系统是一个由多个子系统组成的复杂的生产系统,系统内资源的调度也是非线性的复杂问题,同时涉及多种多样的不确定性因素。从不确定性的角度出发,主要考虑码头装卸设备运行参数的概率分布,研究岸桥和集卡之间的协调调度问题。...集装箱码头系统是一个由多个子系统组成的复杂的生产系统,系统内资源的调度也是非线性的复杂问题,同时涉及多种多样的不确定性因素。从不确定性的角度出发,主要考虑码头装卸设备运行参数的概率分布,研究岸桥和集卡之间的协调调度问题。采用多学科变量耦合优化设计的方法,同时考虑了集装箱任务的时间窗约束,分别建立集卡分派子模型和集卡配置子模型。并将完工时刻和集卡数量作为公用设计变量连接两个子模型,建立了协调调度耦合模型。选取上海港某码头的数据编写算例,在Visual Studio 2012环境下调用Gurobi4.0求解该耦合模型,反复迭代计算后得出最优的集卡分派方案相对于最初的调度方案,总延误时间成本下降了90.69%,集卡数量下降了30.76%,验证了本模型的有效性和实用性。展开更多
Indoor air pollution resulting from volatile organic compounds(VOCs),especially formaldehyde,is a significant health concern needed to predict indoor formaldehyde concentration(Cf)in green intelligent building design....Indoor air pollution resulting from volatile organic compounds(VOCs),especially formaldehyde,is a significant health concern needed to predict indoor formaldehyde concentration(Cf)in green intelligent building design.This study develops a thermal and wet coupling calculation model of porous fabric to account for the migration of formaldehyde molecules in indoor air and cotton,silk,and polyester fabric with heat flux in Harbin,Beijing,Xi’an,Shanghai,Guangzhou,and Kunming,China.The time-by-time indoor dry-bulb temperature(T),relative humidity(RH),and Cf,obtained from verified simulations,were collated and used as input data for the long short-term memory(LSTM)of the deep learning model that predicts indoor multivariate time series Cf from the secondary source effects of indoor fabrics(adsorption and release of formaldehyde).The trained LSTM model can be used to predict multivariate time series Cf at other emission times and locations.The LSTM-based model also predicted Cf with mean absolute percentage error(MAPE),symmetric mean absolute percentage error(SMAPE),mean absolute error(MAE),mean square error(MSE),and root mean square error(RMSE)that fell within 10%,10%,0.5,0.5,and 0.8,respectively.In addition,the characteristics of the input dataset,model parameters,the prediction accuracy of different indoor fabrics,and the uncertainty of the data set are analyzed.The results show that the prediction accuracy of single data set input is higher than that of temperature and humidity input,and the prediction accuracy of LSTM is better than recurrent neural network(RNN).The method’s feasibility was established,and the study provides theoretical support for guiding indoor air pollution control measures and ensuring human health and safety.展开更多
In order to obtain space-time coupling relationship of anchor-cable to improve supporting effect for deep coal mine rock roadway, FLAC3D was used to investigate into mechanical characteristics of the roadway whose cro...In order to obtain space-time coupling relationship of anchor-cable to improve supporting effect for deep coal mine rock roadway, FLAC3D was used to investigate into mechanical characteristics of the roadway whose crosssection shape was vertical wall and semi-circular arch when the roadway was supported by bolts and metal mesh. The results show that the extent of stress concentrations, the range failure zone, and the deformation at the roof center and two spandrels of roadway are greater than those at other positions, except at the floor. The reasonable positions of anchor-cable supporting are the roof center and two spandrels of roadway. The anchor-cable should be installed at good time with bolts supporting after roadway driving be- cause it can improve the stress states of deep surrounding rock around the roadway and control the roadway deformation effec- tively. The engineering practice has proven that the sustained deformation of deep surrounding rocks is effectively controlled when the anchor-cable supporting is adopted at reasonable positions of the roadway at good time.展开更多
Understanding the variations in microscopic pore-fracture structures(MPFS) during coal creep under pore pressure and stress coupling is crucial for coal mining and effective gas treatment. In this manuscript, a triaxi...Understanding the variations in microscopic pore-fracture structures(MPFS) during coal creep under pore pressure and stress coupling is crucial for coal mining and effective gas treatment. In this manuscript, a triaxial creep test on deep coal at various pore pressures using a test system that combines in-situ mechanical loading with real-time nuclear magnetic resonance(NMR) detection was conducted.Full-scale quantitative characterization, online real-time detection, and visualization of MPFS during coal creep influenced by pore pressure and stress coupling were performed using NMR and NMR imaging(NMRI) techniques. The results revealed that seepage pores and microfractures(SPM) undergo the most significant changes during coal creep, with creep failure gradually expanding from dense primary pore fractures. Pore pressure presence promotes MPFS development primarily by inhibiting SPM compression and encouraging adsorption pores(AP) to evolve into SPM. Coal enters the accelerated creep stage earlier at lower stress levels, resulting in more pronounced creep deformation. The connection between the micro and macro values was established, demonstrating that increased porosity at different pore pressures leads to a negative exponential decay of the viscosity coefficient. The Newton dashpot in the ideal viscoplastic body and the Burgers model was improved using NMR experimental results, and a creep model that considers pore pressure and stress coupling using variable-order fractional operators was developed. The model’s reasonableness was confirmed using creep experimental data. The damagestate adjustment factors ω and β were identified through a parameter sensitivity analysis to characterize the effect of pore pressure and stress coupling on the creep damage characteristics(size and degree of difficulty) of coal.展开更多
In clinical settings,different kinds of patient monitoring systems and depth of anesthesia monitoring(DoA)systems have been widely used to assess the depth of sedation and patient's state.However,all these monitor...In clinical settings,different kinds of patient monitoring systems and depth of anesthesia monitoring(DoA)systems have been widely used to assess the depth of sedation and patient's state.However,all these monitoring systems are independent of each other.To date,no monitoring system has focused on the synchronized neural activities,cerebral metabolism,autonomic nervous system,and drug effects on the brain,as well as their interactions between neural activities and cerebral metabolism(i.e.,neurovascular coupling),and between brain and heart(i.e.,brain-heart coupling).In this study,we developed a time-synchronized multimodal monitoring system(TSMMS)that integrates electroencephalogram(EEG),near-infrared spectroscopy(NIRS),and standard physiological monitors(electrocardiograph,blood pressure,oxygen saturation)to provide a comprehensive view of the patient's physiological state during surgery.The coherence and Granger causality(GC)methods were used to quantify the neurovascular coupling and brain-heart coupling.The response surface model was used to estimate the combined propofol-remifentanil drug effect on the brain.TSMMS integrates data from various devices for a comprehensive analysis of vital signs.It enhances anesthesia monitoring through detailed EEG features,neurovascular,and brain-heart coupling indicators.Additionally,a response surface model estimates the combined effects of propofol and remifentanil,aiding anesthesiologists in drug administration.In conclusion,TSMMS provides a new tool for studying the coupling mechanism among neural activities,cerebral metabolism,and autonomic nervous system during general anesthesia.展开更多
基金Project(50925829) supported by the National Science Fund for Distinguished Young Scholars of ChinaProject(50908148) supported by the National Natural Science Foundation of ChinaProjects(2009-K4-23,2010-11-33) supported by the Research of Ministry of Housing and Urban Rural Development of China
文摘The coupling model of major influence factors such state affecting the chloride diffusion process in concrete is as environmental relative humidity, load-induced crack and stress discussed. The probability distributions of the critical chloride concentration Cc, the chloride diffusion coefficient D, and the surface chloride concentration Cs were determined based on the collected natural exposure data. And the estimation of probability of corrosion initiation considering the coupling effects of influence factors is presented. It is found that the relative humidity and curing time are the most effective factors affecting the probability of corrosion initiation before and after 10 years of exposure time. At the same exposure time, the influence of load-induced crack and stress state on the probability of corrosion initiation is obvious, in which the effect of crack is the most one
文摘集装箱码头系统是一个由多个子系统组成的复杂的生产系统,系统内资源的调度也是非线性的复杂问题,同时涉及多种多样的不确定性因素。从不确定性的角度出发,主要考虑码头装卸设备运行参数的概率分布,研究岸桥和集卡之间的协调调度问题。采用多学科变量耦合优化设计的方法,同时考虑了集装箱任务的时间窗约束,分别建立集卡分派子模型和集卡配置子模型。并将完工时刻和集卡数量作为公用设计变量连接两个子模型,建立了协调调度耦合模型。选取上海港某码头的数据编写算例,在Visual Studio 2012环境下调用Gurobi4.0求解该耦合模型,反复迭代计算后得出最优的集卡分派方案相对于最初的调度方案,总延误时间成本下降了90.69%,集卡数量下降了30.76%,验证了本模型的有效性和实用性。
基金This work was supported by the National Natural Science Foundation of China(52278129)the Key Scientific and Technological Innovation Team of Shaanxi Province(2023-CX-TD-29)Xiaohu Yang greatly acknowledged the support by the K.C.Wong Education Foundation.
文摘Indoor air pollution resulting from volatile organic compounds(VOCs),especially formaldehyde,is a significant health concern needed to predict indoor formaldehyde concentration(Cf)in green intelligent building design.This study develops a thermal and wet coupling calculation model of porous fabric to account for the migration of formaldehyde molecules in indoor air and cotton,silk,and polyester fabric with heat flux in Harbin,Beijing,Xi’an,Shanghai,Guangzhou,and Kunming,China.The time-by-time indoor dry-bulb temperature(T),relative humidity(RH),and Cf,obtained from verified simulations,were collated and used as input data for the long short-term memory(LSTM)of the deep learning model that predicts indoor multivariate time series Cf from the secondary source effects of indoor fabrics(adsorption and release of formaldehyde).The trained LSTM model can be used to predict multivariate time series Cf at other emission times and locations.The LSTM-based model also predicted Cf with mean absolute percentage error(MAPE),symmetric mean absolute percentage error(SMAPE),mean absolute error(MAE),mean square error(MSE),and root mean square error(RMSE)that fell within 10%,10%,0.5,0.5,and 0.8,respectively.In addition,the characteristics of the input dataset,model parameters,the prediction accuracy of different indoor fabrics,and the uncertainty of the data set are analyzed.The results show that the prediction accuracy of single data set input is higher than that of temperature and humidity input,and the prediction accuracy of LSTM is better than recurrent neural network(RNN).The method’s feasibility was established,and the study provides theoretical support for guiding indoor air pollution control measures and ensuring human health and safety.
基金Supported by the Science and Technological Fund of Anhui Province for Outstanding Youth （1108085J02）, the National Natural Science Foundation of Anhui Province （K J2010A090）
文摘In order to obtain space-time coupling relationship of anchor-cable to improve supporting effect for deep coal mine rock roadway, FLAC3D was used to investigate into mechanical characteristics of the roadway whose crosssection shape was vertical wall and semi-circular arch when the roadway was supported by bolts and metal mesh. The results show that the extent of stress concentrations, the range failure zone, and the deformation at the roof center and two spandrels of roadway are greater than those at other positions, except at the floor. The reasonable positions of anchor-cable supporting are the roof center and two spandrels of roadway. The anchor-cable should be installed at good time with bolts supporting after roadway driving be- cause it can improve the stress states of deep surrounding rock around the roadway and control the roadway deformation effec- tively. The engineering practice has proven that the sustained deformation of deep surrounding rocks is effectively controlled when the anchor-cable supporting is adopted at reasonable positions of the roadway at good time.
基金supported by the National Natural Science Foundation of China(Nos.52121003,51827901 and 52204110)China Postdoctoral Science Foundation(No.2022M722346)+1 种基金the 111 Project(No.B14006)the Yueqi Outstanding Scholar Program of CUMTB(No.2017A03).
文摘Understanding the variations in microscopic pore-fracture structures(MPFS) during coal creep under pore pressure and stress coupling is crucial for coal mining and effective gas treatment. In this manuscript, a triaxial creep test on deep coal at various pore pressures using a test system that combines in-situ mechanical loading with real-time nuclear magnetic resonance(NMR) detection was conducted.Full-scale quantitative characterization, online real-time detection, and visualization of MPFS during coal creep influenced by pore pressure and stress coupling were performed using NMR and NMR imaging(NMRI) techniques. The results revealed that seepage pores and microfractures(SPM) undergo the most significant changes during coal creep, with creep failure gradually expanding from dense primary pore fractures. Pore pressure presence promotes MPFS development primarily by inhibiting SPM compression and encouraging adsorption pores(AP) to evolve into SPM. Coal enters the accelerated creep stage earlier at lower stress levels, resulting in more pronounced creep deformation. The connection between the micro and macro values was established, demonstrating that increased porosity at different pore pressures leads to a negative exponential decay of the viscosity coefficient. The Newton dashpot in the ideal viscoplastic body and the Burgers model was improved using NMR experimental results, and a creep model that considers pore pressure and stress coupling using variable-order fractional operators was developed. The model’s reasonableness was confirmed using creep experimental data. The damagestate adjustment factors ω and β were identified through a parameter sensitivity analysis to characterize the effect of pore pressure and stress coupling on the creep damage characteristics(size and degree of difficulty) of coal.
基金supported by the National Natural Science Foundation of China(grant number 62073280)the Natural Science Fund for Distinguished Young Scholars,Hebei Province,China(F2021203033).
文摘In clinical settings,different kinds of patient monitoring systems and depth of anesthesia monitoring(DoA)systems have been widely used to assess the depth of sedation and patient's state.However,all these monitoring systems are independent of each other.To date,no monitoring system has focused on the synchronized neural activities,cerebral metabolism,autonomic nervous system,and drug effects on the brain,as well as their interactions between neural activities and cerebral metabolism(i.e.,neurovascular coupling),and between brain and heart(i.e.,brain-heart coupling).In this study,we developed a time-synchronized multimodal monitoring system(TSMMS)that integrates electroencephalogram(EEG),near-infrared spectroscopy(NIRS),and standard physiological monitors(electrocardiograph,blood pressure,oxygen saturation)to provide a comprehensive view of the patient's physiological state during surgery.The coherence and Granger causality(GC)methods were used to quantify the neurovascular coupling and brain-heart coupling.The response surface model was used to estimate the combined propofol-remifentanil drug effect on the brain.TSMMS integrates data from various devices for a comprehensive analysis of vital signs.It enhances anesthesia monitoring through detailed EEG features,neurovascular,and brain-heart coupling indicators.Additionally,a response surface model estimates the combined effects of propofol and remifentanil,aiding anesthesiologists in drug administration.In conclusion,TSMMS provides a new tool for studying the coupling mechanism among neural activities,cerebral metabolism,and autonomic nervous system during general anesthesia.
