Coal and ore underground mining generates subsidence and deformation of the land surface. Those defor- mations may cause damage to buildings and infrastructures. The environmental impact of subsidence will not be acce...Coal and ore underground mining generates subsidence and deformation of the land surface. Those defor- mations may cause damage to buildings and infrastructures. The environmental impact of subsidence will not be accepted in the future by the society in many countries. Especially acceptance of the ground deformations decreases every year there, where the mining regions are densely urbanized, the The only solution is to limit the subsidence or its impact on the infrastructure. The first is not rentable for the mining industry, the second depends on the precise subsidence prediction and good preventing management involved in the mining areas. The precision of the subsidence prediction depends strictly on the mathematical model of the deformation phenomenon and on the uncertainty of the input data. The subsidence prediction in the geological conditions of the raw materials used to be made on the basis of numerical modeling or the stochastic models. A modified solution of the stochastic model by Knothe will be presented in the paper. The author focuses on the precise description of the deposit shape and on the time dependent displacements of the rock mass. A two parameters＇ time function has been introduced in the algorithm.展开更多
Plant capacity for water storage leads to time lags between basal stem sap flow and transpiration in various woody plants. Internal water storage depends on the sizes of woody plants. However, the changes and its infl...Plant capacity for water storage leads to time lags between basal stem sap flow and transpiration in various woody plants. Internal water storage depends on the sizes of woody plants. However, the changes and its influencing factors in time lags of basal stem flow during the development of herbaceous plants including crops remain unclear. A field experiment was conducted in an arid region of Northwest China to examine the time lag characteristics of sap flow in seed-maize and to calibrate the transpiration modeling. Cross-correlation analysis was used to estimate the time lags between stem sap flow and meteorological driving factors including solar radiation（R_s） and vapor pressure deficit of the air（VPD_（air））. Results indicate that the changes in seed-maize stem sap flow consistently lagged behind the changes in R_s and preceded the changes in VPD_（air） both on hourly and daily scales, suggesting that light-mediated stomatal closures drove sap flow responses. The time lag in the maize＇s sap flow differed significantly during different growth stages and the difference was potentially due to developmental changes in capacitance tissue and/or xylem during ontogenesis. The time lags between stem sap flow and R_s in both female plants and male plants corresponded to plant use of stored water and were independent of total plant water use. Time lags of sap flow were always longer in male plants than in female plants. Theoretically, dry soil may decrease the speed by which sap flow adjusts ahead of shifts in VPD_（air） in comparison with wet soil and also increase the speed by which sap flow adjusts to R_s. However, sap flow lags that were associated with R_s before irrigation and after irrigation in female plants did not shift. Time series analysis method provided better results for simulating seed-maize sap flow with advantages of allowing for fewer variables to be included. This approach would be helpful in improving the accuracy of estimation for canopy transpiration and conductance using meteorological measurements.展开更多
This paper presents experimental and theoretical methods to study the damage layer evolution of a breakwater made with concrete hollow squares in marine environment.Wetting time was directly related to the performance...This paper presents experimental and theoretical methods to study the damage layer evolution of a breakwater made with concrete hollow squares in marine environment.Wetting time was directly related to the performance degradation of the breakwater by observation.The thickness of damage layer was detected by means of ultrasonic testing.Meanwhile,some samples drilled from concrete hollow squares were analyzed by SEM and XRD in order to illustrate the damage mechanism.Subsequently,a theoretical model containing wetting time ratio was established to simulate the damage layer evolution based on Fick’s second law,which could be suggested to predict the service life of concrete structures in marine environment.展开更多
In response to the production capacity and functionality variations, a genetic algorithm （GA） embedded with deterministic timed Petri nets（DTPN） for reconfigurable production line（RPL） is proposed to solve its s...In response to the production capacity and functionality variations, a genetic algorithm （GA） embedded with deterministic timed Petri nets（DTPN） for reconfigurable production line（RPL） is proposed to solve its scheduling problem. The basic DTPN modules are presented to model the corresponding variable structures in RPL, and then the scheduling model of the whole RPL is constructed. And in the scheduling algorithm, firing sequences of the Petri nets model are used as chromosomes, thus the selection, crossover, and mutation operator do not deal with the elements in the problem space, but the elements of Petri nets model. Accordingly, all the algorithms for GA operations embedded with Petri nets model are proposed. Moreover, the new weighted single-objective optimization based on reconfiguration cost and E/T is used. The results of a DC motor RPL scheduling suggest that the presented DTPN-GA scheduling algorithm has a significant impact on RPL scheduling, and provide obvious improvements over the conventional scheduling method in practice that meets duedate, minimizes reconfiguration cost, and enhances cost effectivity.展开更多
A numerical simulation was performed to study the flow pattern,mixing time and open-eye slag produced by argon gas injection in an industrial scale steel ladle under non-isothermal conditions.The liquid steel remains ...A numerical simulation was performed to study the flow pattern,mixing time and open-eye slag produced by argon gas injection in an industrial scale steel ladle under non-isothermal conditions.The liquid steel remains 5min before the injection,and thermal stratification and convective flows were analyzed.Three different sequences in stages employing various argon-gas flow rates were simulated.In the first case,a sequence with the highest flow rates of argon was applied,while in the second and the third sequences,the intermediate and the lowest flow rates of argon gas were used,respectively.For determining the chemistry homogenization,the mixing time was computed and analyzed in all three cases.It was found that the cold steel is located near the walls while the steel with a high temperature is accumulated in the center of the ladle above the argon-gas tuyere.The higher and lower flows promote a faster chemistry homogenization owing to the secondary recirculations that are developed closer to the walls.The results from steel temperature drop show a good concordance with plant trial measurements.展开更多
A water model and a high-speed video camera were utilized in the 300-t RH equipment to study the effect of steel flow patterns in a vacuum chamber on fast decarburization and a superior flow-pattern map was obtained d...A water model and a high-speed video camera were utilized in the 300-t RH equipment to study the effect of steel flow patterns in a vacuum chamber on fast decarburization and a superior flow-pattern map was obtained during the practical RH process. There are three flow patterns with different bubbling characteristics and steel surface states in the vacuum chamber： boiling pattern（BP）, transition pattern（TP）, and wave pattern（WP）. The effect of the liquid-steel level and the residence time of the steel in the chamber on flow patterns and decarburization reaction were investigated, respectively. The liquid-steel level significantly affected the flow-pattern transition from BP to WP, and the residence time and reaction area were crucial to evaluate the whole decarburization process rather than the circulation flow rate and mixing time. A superior flow-pattern map during the practical RH process showed that the steel flow pattern changed from BP to TP quickly, and then remained as TP until the end of decarburization.展开更多
An identification-based approach for aircraft engine modeling using the nonlinear HammersteinWiener representation was proposed.Hammerstein-Wiener modeling for both limited flight envelope and extended flight envelope...An identification-based approach for aircraft engine modeling using the nonlinear HammersteinWiener representation was proposed.Hammerstein-Wiener modeling for both limited flight envelope and extended flight envelope was investigated.Simulation shows that the resulting model can be valid over 10%variation of rotational speed of the engine,compared with those linear models that are only valid over 3%—5%change of rotational speed.It is further demonstrated that the proposed method can be utilized over large envelope up to 20% variation of rotational speed of the engine.The fundamental idea is to use nonlinear models to extend the feasible/valid region rather than those linear models.This may consequently simplify the switching logic in the onboard digital control units.This is often overlooked in aircraft engine control community,but has been emphasized in the research.展开更多
In the context of the energy and climate crises,it is crucial for organizations to utilize advanced methods to reduce energy consumption and energy costs.This study explores the application of deep learning models for...In the context of the energy and climate crises,it is crucial for organizations to utilize advanced methods to reduce energy consumption and energy costs.This study explores the application of deep learning models for predicting energy demands in retail stores,which can enhance market efficiency and contribute to grid stability.We analyze a detailed electricity consumption dataset from a hypermarket in Hungary,focusing on 48-hour forecasts at 15-minute intervals.Our methodology includes the implementation of classical models such as ARIMA and linear regression,as well as state-of-the-art deep learning models like TiDE and foundational models such as Lag-Llama in a“zero shot prediction”as well as a“finetuning”scenario.展开更多
Modeling HIV/AIDS progression is critical for understanding disease dynamics and improving patient care. This study compares the Exponential and Weibull survival models, focusing on their ability to capture state-spec...Modeling HIV/AIDS progression is critical for understanding disease dynamics and improving patient care. This study compares the Exponential and Weibull survival models, focusing on their ability to capture state-specific failure rates in HIV/AIDS progression. While the Exponential model offers simplicity with a constant hazard rate, it often fails to accommodate the complexities of dynamic disease progression. In contrast, the Weibull model provides flexibility by allowing hazard rates to vary over time. Both models are evaluated within the frameworks of the Cox Proportional Hazards (Cox PH) and Accelerated Failure Time (AFT) models, incorporating critical covariates such as age, gender, CD4 count, and ART status. Statistical evaluation metrics, including Akaike Information Criterion (AIC), Bayesian Information Criterion (BIC), log-likelihood, and Pseudo-R2, were employed to assess model performance across diverse patient subgroups. Results indicate that the Weibull model consistently outperforms the Exponential model in dynamic scenarios, such as younger patients and those with co-infections, while maintaining robustness in stable contexts. This study highlights the trade-off between flexibility and simplicity in survival modeling, advocating for tailored model selection to balance interpretability and predictive accuracy. These findings provide valuable insights for optimizing HIV/AIDS management strategies and advancing survival analysis methodologies.展开更多
National essential medicine policy （NEMP） is an important part of new health care reform and core content of national drug policy. We chose Hebei province as a case to study, utilized standard methods from WHO/HAl a...National essential medicine policy （NEMP） is an important part of new health care reform and core content of national drug policy. We chose Hebei province as a case to study, utilized standard methods from WHO/HAl and built interrupted time series （ITS） model to qualitatively and quantitatively evaluate the effects of NEMP in Hebei province from the utilization of essential medicines. Shortly after implementing EMP, the purchasing and utilization rate of essential medicines significantly increased, but no further continuous effects. In order to perfect the essential medicine policy, training of rational drug utilization should be strengthened, hierarchical essential medicine list and dynamic monitoring on the effect of NEMP are necessary.展开更多
In order to evaluate the efficiency of the automated storage/retrieval system(AS/RS)accurately,and compare different layouts of the AS/RS using mean travel time,under randomized storage conditions,an exact,geometry-ba...In order to evaluate the efficiency of the automated storage/retrieval system(AS/RS)accurately,and compare different layouts of the AS/RS using mean travel time,under randomized storage conditions,an exact,geometry-based analytical model is presented.The model can be used to compute the expected single-command and dual-command travel time for a storage/retrieval(S/R)machine which can travel simultaneously horizontally and vertically as it moves along a storage aisle.The rack may be either square in time or non square in time.Additionally,the alternative layouts of the AS/RS and travel-time models are examined.Comparing with setting the I/O point at the left-lower corner of the rack,setting the I/O point at any point at the vertical edge can help enhance the efficiency of the AS/RS.展开更多
目的基于药品零售价格大数据构建药品价格指数,描述其波动特征,发挥其药品价格宏观监管作用,促进药品价格保持合理水平。方法运用链式拉氏指数构建原理建立药品价格指数模型,运用时间序列模型描述指数波动特征,识别并分析药品价格波动...目的基于药品零售价格大数据构建药品价格指数,描述其波动特征,发挥其药品价格宏观监管作用,促进药品价格保持合理水平。方法运用链式拉氏指数构建原理建立药品价格指数模型,运用时间序列模型描述指数波动特征,识别并分析药品价格波动异常状况。结果2015年1月—2020年12月,药品价格总指数小幅上涨,累计涨幅为14.43%,年均涨幅约2.40%,市场化改革成效较为显著。通过基于局部加权回归的季节趋势分解(seasonal-trend decomposition using loess,STL)方法对获得的药品价格总指数时间序列进行分析,指数呈长期平缓上升趋势,不规则波动值为-1.41~2.03,说明药品价格受外因影响较小,周期性特征仍有待进一步研究。2015年1月—2020年12月,根据药品价格指数共监测到价格异常风险32次。结论药品价格指数较全面地反映药品价格走势,对于药品价格异常波动具有一定的预警作用,能够为我国药品价格监管提供有效工具。展开更多
China’s energy system requires a thorough transformation to achieve carbon neutrality.Here,leveraging the highly acclaimed the Integrated MARKAL-EFOM System model of China(China TIMES)that takes energy,the environmen...China’s energy system requires a thorough transformation to achieve carbon neutrality.Here,leveraging the highly acclaimed the Integrated MARKAL-EFOM System model of China(China TIMES)that takes energy,the environment,and the economy into consideration,four carbon-neutral scenarios are proposed and compared for different emission peak times and carbon emissions in 2050.The results show that China’s carbon emissions will peak at 10.3–10.4 Gt between 2025 and 2030.In 2050,renewables will account for 60%of total energy consumption(calorific value calculation)and 90%of total electricity generation,and the electrification rate will be close to 60%.The energy transition will bring sustained air quality improvement,with an 85%reduction in local air pollutants in 2050 compared with 2020 levels,and an early emission peak will yield more near-term benefits.Early peak attainment requires the extensive deployment of renewables over the next decade and an accelerated phasing out of coal after 2025.However,it will bring benefits such as obtaining better air quality sooner,reducing cumulative CO_(2) emissions,and buying more time for other sectors to transition.The pressure for more ambitious emission reductions in 2050 can be transmitted to the near future,affecting renewable energy development,energy service demand,and welfare losses.展开更多
This paper combines grey model with time series model and then dynamic model for rapid and in-depth fault prediction in chemical processes. Two combination methods are proposed. In one method, historical data is intro...This paper combines grey model with time series model and then dynamic model for rapid and in-depth fault prediction in chemical processes. Two combination methods are proposed. In one method, historical data is introduced into the grey time series model to predict future trend of measurement values in chemical process. These predicted measurements are then used in the dynamic model to retrieve the change of fault parameters by model based diagnosis algorithm. In another method, historical data is introduced directly into the dynamic model to retrieve historical fault parameters by model based diagnosis algorithm. These parameters are then predicted by the grey time series model. The two methods are applied to a gravity tank example. The case study demonstrates that the first method is more accurate for fault prediction.展开更多
The numerical simulation of modern aero-engine combustion chamber needs accurate description of the interaction between turbulence and chemical reaction mechanism. The Large Eddy Simulation(LES) method with the Transp...The numerical simulation of modern aero-engine combustion chamber needs accurate description of the interaction between turbulence and chemical reaction mechanism. The Large Eddy Simulation(LES) method with the Transported Probability Density Function(TPDF) turbulence combustion model is promising in engineering applications. In flame region, the impact of chemical reaction should be considered in TPDF molecular mixing model. Based on pioneer research, three new TPDF turbulence-chemistry dual time scale molecular mixing models were proposed tentatively by adding the chemistry time scale in molecular mixing model for nonpremixed flame. The Aero-Engine Combustor Simulation Code(AECSC) which is based on LES-TPDF method was combined with the three new models. Then the Sandia laboratory's methane-air jet flames: Flame D and Flame E were simulated. Transient simulation results show that all the three new models can predict the instantaneous combustion flow pattern of the jet flames. Furthermore,the average scalar statistical results were compared with the experimental data. The simulation result of the new TPDF arithmetic mean modification model is the closest to the experimental data:the average error in Flame D is 7.6% and 6.6% in Flame E. The extinction and re-ignition phenomena of the jet flames especially Flame E were captured. The turbulence time scale and the chemistry time scale are in different order in the whole flow field. The dual time scale TPDF combustion model has ability to deal with both the turbulence effect and the chemistry reaction effect, as well as their interaction more accurately for nonpremixed flames.展开更多
A pre-selection space time model was proposed to estimate the traffic condition at poor-data-detector,especially non-detector locations.The space time model is better to integrate the spatial and temporal information ...A pre-selection space time model was proposed to estimate the traffic condition at poor-data-detector,especially non-detector locations.The space time model is better to integrate the spatial and temporal information comprehensibly.Firstly,the influencing factors of the "cause nodes" were studied,and then the pre-selection "cause nodes" procedure which utilizes the Pearson correlation coefficient to evaluate the relevancy of the traffic data was introduced.Finally,only the most relevant data were collected to compose the space time model.The experimental results with the actual data demonstrate that the model performs better than other three models.展开更多
This paper presents the application of autoregressive integrated moving average （ARIMA）, seasonal ARIMA （SARIMA）, and Jordan-Elman artificial neural networks （ANN） models in forecasting the monthly streamflow of...This paper presents the application of autoregressive integrated moving average （ARIMA）, seasonal ARIMA （SARIMA）, and Jordan-Elman artificial neural networks （ANN） models in forecasting the monthly streamflow of the Kizil River in Xinjiang, China. Two different types of monthly streamflow data （original and deseasonalized data） were used to develop time series and Jordan-Elman ANN models using previous flow conditions as predictors. The one-month-ahead forecasting performances of all models for the testing period （1998-2005） were compared using the average monthly flow data from the Kalabeili gaging station on the Kizil River. The Jordan-Elman ANN models, using previous flow conditions as inputs, resulted in no significant improvement over time series models in one-month-ahead forecasting. The results suggest that the simple time series models （ARIMA and SARIMA） can be used in one-month-ahead streamflow forecasting at the study site with a simple and explicit model structure and a model performance similar to the Jordan-Elman ANN models.展开更多
A new higher-order continuum model is proposed by considering the coupling and lane changing effects of the vehicles on two adjacent lanes. A stability analysis of the proposed model provides the conditions that ensur...A new higher-order continuum model is proposed by considering the coupling and lane changing effects of the vehicles on two adjacent lanes. A stability analysis of the proposed model provides the conditions that ensure its linear stability. Issues related to lane changing, shock waves and rarefaction waves, local clustering and phase transition are also investigated with numerical experiments. The simulation results show that the proposed model is capable of providing explanations to some particular traffic phenomena commonly observable in real traffic flows.展开更多
Objective To construct a model of Seasonal Autoregressive Integrated Moving Average （SARIMA） for forecasting the epidemic of Japanese encephalitis （JE） in Xianyang, Shaanxi, China, and provide valuable reference ...Objective To construct a model of Seasonal Autoregressive Integrated Moving Average （SARIMA） for forecasting the epidemic of Japanese encephalitis （JE） in Xianyang, Shaanxi, China, and provide valuable reference information for JE control and prevention. Methods Theoretically epidemiologic study was employed in the research process. Monthly incidence data on JE for the period from Jan 2005 to Sep 2014 were obtained from a passive surveillance system at the Center for Diseases Prevention and Control in Xianyang, Shaanxi province. An optimal SARIMA model was developed for JE incidence from 2005 to 2013 with the Box and Jenkins approach. This SARIMA model could predict JE incidence for the year 2014 and 2015. Results SARIMA （1, 1, 1） （2, 1, 1）12 was considered to be the best model with the lowest Bayesian information criterion, Akaike information criterion, Mean Absolute Error values, the highest R2, and a lower Mean Absolute Percent Error. SARIMA （1, 1, 1） （2, 1, 1）12 was stationary and accurate for predicting JE incidence in Xianyang. The predicted incidence, around 0.3/100 000 from June to August in 2014 with low errors, was higher compared with the actual incidence. Therefore, SARIMA （1, 1, 1） （2, 1, 1）12 appeared to be reliable and accurate and could be applied to incidence prediction. Conclusions The proposed prediction model could provide clues to early identification of the JE incidence that is increased abnormally （≥0.4/100 000）. According to the predicted results in 2014, the JE incidence in Xianyang will decline slightly and reach its peak from June to August.The authors wish to thank the staff from the CDCs from 13 counties of Xianyang, Shaanxi province, China, for their contribution to Japanese encephalitis cases reporting.展开更多
In order to solve the problem of artificial generation and low efficiency of test sequences for zone controller (ZC), a model-based automatic generation method of test sequence is proposed. Firstly, the timed automata...In order to solve the problem of artificial generation and low efficiency of test sequences for zone controller (ZC), a model-based automatic generation method of test sequence is proposed. Firstly, the timed automata model is established based on function analysis of the zone controller, and the correctness of the model is verified by UPPAAL. Then by parsing the timed automata model files, state information and transition conditions can be extracted to generate test case sets. Finally, according to the serialization conditions of test cases, the test cases are serialized into test sequences by using the improved depth first search algorithm. A case, the ZC controls the train running within its jurisdiction, shows that the method is correct and can effectively improve the efficiency of test sequence generation.展开更多
文摘Coal and ore underground mining generates subsidence and deformation of the land surface. Those defor- mations may cause damage to buildings and infrastructures. The environmental impact of subsidence will not be accepted in the future by the society in many countries. Especially acceptance of the ground deformations decreases every year there, where the mining regions are densely urbanized, the The only solution is to limit the subsidence or its impact on the infrastructure. The first is not rentable for the mining industry, the second depends on the precise subsidence prediction and good preventing management involved in the mining areas. The precision of the subsidence prediction depends strictly on the mathematical model of the deformation phenomenon and on the uncertainty of the input data. The subsidence prediction in the geological conditions of the raw materials used to be made on the basis of numerical modeling or the stochastic models. A modified solution of the stochastic model by Knothe will be presented in the paper. The author focuses on the precise description of the deposit shape and on the time dependent displacements of the rock mass. A two parameters＇ time function has been introduced in the algorithm.
基金support from the National Key Basic Research Program of China (2016YFC0400207)the National Natural Science Foundation of China (51439006, 91425302)the 111 Program of Introducing Talents of Discipline to Universities (B14002)
文摘Plant capacity for water storage leads to time lags between basal stem sap flow and transpiration in various woody plants. Internal water storage depends on the sizes of woody plants. However, the changes and its influencing factors in time lags of basal stem flow during the development of herbaceous plants including crops remain unclear. A field experiment was conducted in an arid region of Northwest China to examine the time lag characteristics of sap flow in seed-maize and to calibrate the transpiration modeling. Cross-correlation analysis was used to estimate the time lags between stem sap flow and meteorological driving factors including solar radiation（R_s） and vapor pressure deficit of the air（VPD_（air））. Results indicate that the changes in seed-maize stem sap flow consistently lagged behind the changes in R_s and preceded the changes in VPD_（air） both on hourly and daily scales, suggesting that light-mediated stomatal closures drove sap flow responses. The time lag in the maize＇s sap flow differed significantly during different growth stages and the difference was potentially due to developmental changes in capacitance tissue and/or xylem during ontogenesis. The time lags between stem sap flow and R_s in both female plants and male plants corresponded to plant use of stored water and were independent of total plant water use. Time lags of sap flow were always longer in male plants than in female plants. Theoretically, dry soil may decrease the speed by which sap flow adjusts ahead of shifts in VPD_（air） in comparison with wet soil and also increase the speed by which sap flow adjusts to R_s. However, sap flow lags that were associated with R_s before irrigation and after irrigation in female plants did not shift. Time series analysis method provided better results for simulating seed-maize sap flow with advantages of allowing for fewer variables to be included. This approach would be helpful in improving the accuracy of estimation for canopy transpiration and conductance using meteorological measurements.
基金The authors would like to acknowledge the financial support by the National Natural Science Foundation of China(11832013,11772164)the National Basic Research Program of China(973 Program,2009CB623203)+1 种基金the Key Research Program of Society Development of Ningbo(2013C51007)K.C.Wong Magna Fund in Ningbo University.
文摘This paper presents experimental and theoretical methods to study the damage layer evolution of a breakwater made with concrete hollow squares in marine environment.Wetting time was directly related to the performance degradation of the breakwater by observation.The thickness of damage layer was detected by means of ultrasonic testing.Meanwhile,some samples drilled from concrete hollow squares were analyzed by SEM and XRD in order to illustrate the damage mechanism.Subsequently,a theoretical model containing wetting time ratio was established to simulate the damage layer evolution based on Fick’s second law,which could be suggested to predict the service life of concrete structures in marine environment.
基金This project is supported by Key Science-Technology Project of Shanghai City Tenth Five-Year-Plan, China (No.031111002)Specialized Research Fund for the Doctoral Program of Higher Education, China (No.20040247033)Municipal Key Basic Research Program of Shanghai, China (No.05JC14060)
文摘In response to the production capacity and functionality variations, a genetic algorithm （GA） embedded with deterministic timed Petri nets（DTPN） for reconfigurable production line（RPL） is proposed to solve its scheduling problem. The basic DTPN modules are presented to model the corresponding variable structures in RPL, and then the scheduling model of the whole RPL is constructed. And in the scheduling algorithm, firing sequences of the Petri nets model are used as chromosomes, thus the selection, crossover, and mutation operator do not deal with the elements in the problem space, but the elements of Petri nets model. Accordingly, all the algorithms for GA operations embedded with Petri nets model are proposed. Moreover, the new weighted single-objective optimization based on reconfiguration cost and E/T is used. The results of a DC motor RPL scheduling suggest that the presented DTPN-GA scheduling algorithm has a significant impact on RPL scheduling, and provide obvious improvements over the conventional scheduling method in practice that meets duedate, minimizes reconfiguration cost, and enhances cost effectivity.
文摘A numerical simulation was performed to study the flow pattern,mixing time and open-eye slag produced by argon gas injection in an industrial scale steel ladle under non-isothermal conditions.The liquid steel remains 5min before the injection,and thermal stratification and convective flows were analyzed.Three different sequences in stages employing various argon-gas flow rates were simulated.In the first case,a sequence with the highest flow rates of argon was applied,while in the second and the third sequences,the intermediate and the lowest flow rates of argon gas were used,respectively.For determining the chemistry homogenization,the mixing time was computed and analyzed in all three cases.It was found that the cold steel is located near the walls while the steel with a high temperature is accumulated in the center of the ladle above the argon-gas tuyere.The higher and lower flows promote a faster chemistry homogenization owing to the secondary recirculations that are developed closer to the walls.The results from steel temperature drop show a good concordance with plant trial measurements.
基金financially supported by the National Natural Science Foundation of China (No.51704203)the PhD Early Development Program of Taiyuan University of Science and Technology (Nos. 20152008, 20152013, and 20152018)+2 种基金Shanxi Province Science Foundation for Youths (No. 201601D202027)Key Project of Research and Development Plan of Shanxi Province (Nos. 201603D111004 and 201603D121010)NSFC-Shanxi Coal Based Low Carbon Joint Fund (No. U1510131)
文摘A water model and a high-speed video camera were utilized in the 300-t RH equipment to study the effect of steel flow patterns in a vacuum chamber on fast decarburization and a superior flow-pattern map was obtained during the practical RH process. There are three flow patterns with different bubbling characteristics and steel surface states in the vacuum chamber： boiling pattern（BP）, transition pattern（TP）, and wave pattern（WP）. The effect of the liquid-steel level and the residence time of the steel in the chamber on flow patterns and decarburization reaction were investigated, respectively. The liquid-steel level significantly affected the flow-pattern transition from BP to WP, and the residence time and reaction area were crucial to evaluate the whole decarburization process rather than the circulation flow rate and mixing time. A superior flow-pattern map during the practical RH process showed that the steel flow pattern changed from BP to TP quickly, and then remained as TP until the end of decarburization.
文摘An identification-based approach for aircraft engine modeling using the nonlinear HammersteinWiener representation was proposed.Hammerstein-Wiener modeling for both limited flight envelope and extended flight envelope was investigated.Simulation shows that the resulting model can be valid over 10%variation of rotational speed of the engine,compared with those linear models that are only valid over 3%—5%change of rotational speed.It is further demonstrated that the proposed method can be utilized over large envelope up to 20% variation of rotational speed of the engine.The fundamental idea is to use nonlinear models to extend the feasible/valid region rather than those linear models.This may consequently simplify the switching logic in the onboard digital control units.This is often overlooked in aircraft engine control community,but has been emphasized in the research.
文摘In the context of the energy and climate crises,it is crucial for organizations to utilize advanced methods to reduce energy consumption and energy costs.This study explores the application of deep learning models for predicting energy demands in retail stores,which can enhance market efficiency and contribute to grid stability.We analyze a detailed electricity consumption dataset from a hypermarket in Hungary,focusing on 48-hour forecasts at 15-minute intervals.Our methodology includes the implementation of classical models such as ARIMA and linear regression,as well as state-of-the-art deep learning models like TiDE and foundational models such as Lag-Llama in a“zero shot prediction”as well as a“finetuning”scenario.
文摘Modeling HIV/AIDS progression is critical for understanding disease dynamics and improving patient care. This study compares the Exponential and Weibull survival models, focusing on their ability to capture state-specific failure rates in HIV/AIDS progression. While the Exponential model offers simplicity with a constant hazard rate, it often fails to accommodate the complexities of dynamic disease progression. In contrast, the Weibull model provides flexibility by allowing hazard rates to vary over time. Both models are evaluated within the frameworks of the Cox Proportional Hazards (Cox PH) and Accelerated Failure Time (AFT) models, incorporating critical covariates such as age, gender, CD4 count, and ART status. Statistical evaluation metrics, including Akaike Information Criterion (AIC), Bayesian Information Criterion (BIC), log-likelihood, and Pseudo-R2, were employed to assess model performance across diverse patient subgroups. Results indicate that the Weibull model consistently outperforms the Exponential model in dynamic scenarios, such as younger patients and those with co-infections, while maintaining robustness in stable contexts. This study highlights the trade-off between flexibility and simplicity in survival modeling, advocating for tailored model selection to balance interpretability and predictive accuracy. These findings provide valuable insights for optimizing HIV/AIDS management strategies and advancing survival analysis methodologies.
文摘National essential medicine policy （NEMP） is an important part of new health care reform and core content of national drug policy. We chose Hebei province as a case to study, utilized standard methods from WHO/HAl and built interrupted time series （ITS） model to qualitatively and quantitatively evaluate the effects of NEMP in Hebei province from the utilization of essential medicines. Shortly after implementing EMP, the purchasing and utilization rate of essential medicines significantly increased, but no further continuous effects. In order to perfect the essential medicine policy, training of rational drug utilization should be strengthened, hierarchical essential medicine list and dynamic monitoring on the effect of NEMP are necessary.
基金The National Key Technology R&D Program of China during the 11th Five-Year Plan Period(No.2006BAH02A06)
文摘In order to evaluate the efficiency of the automated storage/retrieval system(AS/RS)accurately,and compare different layouts of the AS/RS using mean travel time,under randomized storage conditions,an exact,geometry-based analytical model is presented.The model can be used to compute the expected single-command and dual-command travel time for a storage/retrieval(S/R)machine which can travel simultaneously horizontally and vertically as it moves along a storage aisle.The rack may be either square in time or non square in time.Additionally,the alternative layouts of the AS/RS and travel-time models are examined.Comparing with setting the I/O point at the left-lower corner of the rack,setting the I/O point at any point at the vertical edge can help enhance the efficiency of the AS/RS.
文摘目的基于药品零售价格大数据构建药品价格指数,描述其波动特征,发挥其药品价格宏观监管作用,促进药品价格保持合理水平。方法运用链式拉氏指数构建原理建立药品价格指数模型,运用时间序列模型描述指数波动特征,识别并分析药品价格波动异常状况。结果2015年1月—2020年12月,药品价格总指数小幅上涨,累计涨幅为14.43%,年均涨幅约2.40%,市场化改革成效较为显著。通过基于局部加权回归的季节趋势分解(seasonal-trend decomposition using loess,STL)方法对获得的药品价格总指数时间序列进行分析,指数呈长期平缓上升趋势,不规则波动值为-1.41~2.03,说明药品价格受外因影响较小,周期性特征仍有待进一步研究。2015年1月—2020年12月,根据药品价格指数共监测到价格异常风险32次。结论药品价格指数较全面地反映药品价格走势,对于药品价格异常波动具有一定的预警作用,能够为我国药品价格监管提供有效工具。
基金supported by the National Natural Science Foundation of China (71690243 and 51861135102)the Ministry of Science and Technology of the People’s Republic of China (2018YFC1509006)the World Bank Group (7202065)
文摘China’s energy system requires a thorough transformation to achieve carbon neutrality.Here,leveraging the highly acclaimed the Integrated MARKAL-EFOM System model of China(China TIMES)that takes energy,the environment,and the economy into consideration,four carbon-neutral scenarios are proposed and compared for different emission peak times and carbon emissions in 2050.The results show that China’s carbon emissions will peak at 10.3–10.4 Gt between 2025 and 2030.In 2050,renewables will account for 60%of total energy consumption(calorific value calculation)and 90%of total electricity generation,and the electrification rate will be close to 60%.The energy transition will bring sustained air quality improvement,with an 85%reduction in local air pollutants in 2050 compared with 2020 levels,and an early emission peak will yield more near-term benefits.Early peak attainment requires the extensive deployment of renewables over the next decade and an accelerated phasing out of coal after 2025.However,it will bring benefits such as obtaining better air quality sooner,reducing cumulative CO_(2) emissions,and buying more time for other sectors to transition.The pressure for more ambitious emission reductions in 2050 can be transmitted to the near future,affecting renewable energy development,energy service demand,and welfare losses.
基金Supported by the Shandong Natural Science Foundation(ZR2013BL008)
文摘This paper combines grey model with time series model and then dynamic model for rapid and in-depth fault prediction in chemical processes. Two combination methods are proposed. In one method, historical data is introduced into the grey time series model to predict future trend of measurement values in chemical process. These predicted measurements are then used in the dynamic model to retrieve the change of fault parameters by model based diagnosis algorithm. In another method, historical data is introduced directly into the dynamic model to retrieve historical fault parameters by model based diagnosis algorithm. These parameters are then predicted by the grey time series model. The two methods are applied to a gravity tank example. The case study demonstrates that the first method is more accurate for fault prediction.
基金co-supported by the National Key R&D Program of China(Nos.2017YFB0202400 and 2017YFB0202402)the National Natural Science Foundation of China(No.91741125)the Project of Newton International Fellowship Alumnus from Royal Society(No.AL120003)
文摘The numerical simulation of modern aero-engine combustion chamber needs accurate description of the interaction between turbulence and chemical reaction mechanism. The Large Eddy Simulation(LES) method with the Transported Probability Density Function(TPDF) turbulence combustion model is promising in engineering applications. In flame region, the impact of chemical reaction should be considered in TPDF molecular mixing model. Based on pioneer research, three new TPDF turbulence-chemistry dual time scale molecular mixing models were proposed tentatively by adding the chemistry time scale in molecular mixing model for nonpremixed flame. The Aero-Engine Combustor Simulation Code(AECSC) which is based on LES-TPDF method was combined with the three new models. Then the Sandia laboratory's methane-air jet flames: Flame D and Flame E were simulated. Transient simulation results show that all the three new models can predict the instantaneous combustion flow pattern of the jet flames. Furthermore,the average scalar statistical results were compared with the experimental data. The simulation result of the new TPDF arithmetic mean modification model is the closest to the experimental data:the average error in Flame D is 7.6% and 6.6% in Flame E. The extinction and re-ignition phenomena of the jet flames especially Flame E were captured. The turbulence time scale and the chemistry time scale are in different order in the whole flow field. The dual time scale TPDF combustion model has ability to deal with both the turbulence effect and the chemistry reaction effect, as well as their interaction more accurately for nonpremixed flames.
基金Project(D101106049710005) supported by the Beijing Science Foundation Program,ChinaProject(61104164) supported by the National Natural Science Foundation,China
文摘A pre-selection space time model was proposed to estimate the traffic condition at poor-data-detector,especially non-detector locations.The space time model is better to integrate the spatial and temporal information comprehensibly.Firstly,the influencing factors of the "cause nodes" were studied,and then the pre-selection "cause nodes" procedure which utilizes the Pearson correlation coefficient to evaluate the relevancy of the traffic data was introduced.Finally,only the most relevant data were collected to compose the space time model.The experimental results with the actual data demonstrate that the model performs better than other three models.
文摘This paper presents the application of autoregressive integrated moving average （ARIMA）, seasonal ARIMA （SARIMA）, and Jordan-Elman artificial neural networks （ANN） models in forecasting the monthly streamflow of the Kizil River in Xinjiang, China. Two different types of monthly streamflow data （original and deseasonalized data） were used to develop time series and Jordan-Elman ANN models using previous flow conditions as predictors. The one-month-ahead forecasting performances of all models for the testing period （1998-2005） were compared using the average monthly flow data from the Kalabeili gaging station on the Kizil River. The Jordan-Elman ANN models, using previous flow conditions as inputs, resulted in no significant improvement over time series models in one-month-ahead forecasting. The results suggest that the simple time series models （ARIMA and SARIMA） can be used in one-month-ahead streamflow forecasting at the study site with a simple and explicit model structure and a model performance similar to the Jordan-Elman ANN models.
基金supported by the National High Technology Research and Development Program of China(863)(511-0910-1031)the National"10th Five-Year"Science and Technique Important Program of China(2002BA404A07)
文摘A new higher-order continuum model is proposed by considering the coupling and lane changing effects of the vehicles on two adjacent lanes. A stability analysis of the proposed model provides the conditions that ensure its linear stability. Issues related to lane changing, shock waves and rarefaction waves, local clustering and phase transition are also investigated with numerical experiments. The simulation results show that the proposed model is capable of providing explanations to some particular traffic phenomena commonly observable in real traffic flows.
基金Supported by the Youth Project of Shaanxi University of Chinese Medicine(2015QN05)
文摘Objective To construct a model of Seasonal Autoregressive Integrated Moving Average （SARIMA） for forecasting the epidemic of Japanese encephalitis （JE） in Xianyang, Shaanxi, China, and provide valuable reference information for JE control and prevention. Methods Theoretically epidemiologic study was employed in the research process. Monthly incidence data on JE for the period from Jan 2005 to Sep 2014 were obtained from a passive surveillance system at the Center for Diseases Prevention and Control in Xianyang, Shaanxi province. An optimal SARIMA model was developed for JE incidence from 2005 to 2013 with the Box and Jenkins approach. This SARIMA model could predict JE incidence for the year 2014 and 2015. Results SARIMA （1, 1, 1） （2, 1, 1）12 was considered to be the best model with the lowest Bayesian information criterion, Akaike information criterion, Mean Absolute Error values, the highest R2, and a lower Mean Absolute Percent Error. SARIMA （1, 1, 1） （2, 1, 1）12 was stationary and accurate for predicting JE incidence in Xianyang. The predicted incidence, around 0.3/100 000 from June to August in 2014 with low errors, was higher compared with the actual incidence. Therefore, SARIMA （1, 1, 1） （2, 1, 1）12 appeared to be reliable and accurate and could be applied to incidence prediction. Conclusions The proposed prediction model could provide clues to early identification of the JE incidence that is increased abnormally （≥0.4/100 000）. According to the predicted results in 2014, the JE incidence in Xianyang will decline slightly and reach its peak from June to August.The authors wish to thank the staff from the CDCs from 13 counties of Xianyang, Shaanxi province, China, for their contribution to Japanese encephalitis cases reporting.
文摘In order to solve the problem of artificial generation and low efficiency of test sequences for zone controller (ZC), a model-based automatic generation method of test sequence is proposed. Firstly, the timed automata model is established based on function analysis of the zone controller, and the correctness of the model is verified by UPPAAL. Then by parsing the timed automata model files, state information and transition conditions can be extracted to generate test case sets. Finally, according to the serialization conditions of test cases, the test cases are serialized into test sequences by using the improved depth first search algorithm. A case, the ZC controls the train running within its jurisdiction, shows that the method is correct and can effectively improve the efficiency of test sequence generation.
