The lofty and extensive Tibetan Plateau has significant mass elevation effect(MEE). In recent years, a great effort has been made to quantify MEE, with the recognition of intra-mountain basal elevation(MBE) as the mai...The lofty and extensive Tibetan Plateau has significant mass elevation effect(MEE). In recent years, a great effort has been made to quantify MEE, with the recognition of intra-mountain basal elevation(MBE) as the main determinant of MEE. In this study, we improved the method of estimating MEE with MODIS and NECP data, by refining temperature laps rate, and dividing MBE plots, and then analyzed the spatio-temporal variation of MEE in the Plateau. The main conclusions include: 1) the highest average annual MEE of the plateau is as high as 11.5488°C in the southwest of the plateau, where exists a high-MEE core and MEE takes on a trend of decreasing from the core to the surrounding areas; 2) in the interior of the plateau, the maximum monthly MEE is 14.1108°C in the highest MBE plot(4934 m) in August; while the minimum monthly MEE appeared primarily in January and February; 3) in the peripheral areas of the plateau, annual mean MEE is relatively low, mostly between 3.0068°C–5.1972°C, where monthly MEE is high in January and December and low in June and July, completely different from the MEE time-series variation in the internal parts of the plateau.展开更多
For oil pipeline in mountain areas,high hydrostatic pressure in the pipeline may cause error-opening of pressure relief valves,and oil is discharged from the pipeline to the pressure relief tanks,bringing spilling-ove...For oil pipeline in mountain areas,high hydrostatic pressure in the pipeline may cause error-opening of pressure relief valves,and oil is discharged from the pipeline to the pressure relief tanks,bringing spilling-over risk of the pressure relief tanks.Therefore,simulating the error-opening situations of the pressure relief valves and investigating the oil discharge process are necessary for checking the possibility of the spilling-over accident and then proposing measures to improve the pressure relief system.This research focuses on a continuous undulating oil pipeline with large elevation difference and a station along this pipeline,which is named B station in this paper,is studied.By OLGA software,simulation model of the pressure relief system of B station is established,and the accuracy of the model is verified by reconstructing a real accident and making a comparison with the actual accident data.The maximum discharge rate reached 8284 m3/h when the pressure relief valve was opened by mistake in the inlet and outlet of the station.The accumulated filling time of the two pressure relief tanks is 200 s,which is in good agreement with the accident data.On this basis,for error-opening of the pressure relief valves at the inlet and outlet of B station,simulation is performed to investigate variations of the discharge velocity,discharge flow rate,accumulated discharge volume and ventilation volume of the vent valve.The discharge velocity is found to be over the maximum velocity allowed for safety consideration.According to the accumulated discharge volume,it is inferred that spilling over of the pressure relief tanks will be caused once error-opening of the pressure relief valve occurs.Also it is judged that the existing breathing valve can not satisfy the ventilation requirement in case of failure of the pressure relief valves.From these simulation results,it is proposed that increasing the number of vent valves,replacing the manual valves with electrically operated valves,and employing security control interlock protection program are improvement measures to guarantee safe,efficient and reliable operation of the pressure relief system at B station.展开更多
Climate change is one of the greatest threats facing the global community and has been mainly induced by increasing atmospheric concentrations of greenhouse gases resulting from fossil fuel energy use and change in ve...Climate change is one of the greatest threats facing the global community and has been mainly induced by increasing atmospheric concentrations of greenhouse gases resulting from fossil fuel energy use and change in vegetation cover. This study used modelling techniques to determine how changes in climate could affect vegetation productivity in the northern part of Nigeria. Climatic parameters (Rainfall, Minimum and Maximum Temperatures) as well as coarse Normalised Difference Vegetation Index (NDVI) data for the growing seasons of 1981-2009 were utilised. Because of the relationship between climatic parameters and vegetation, Spatial method of data interpolation was tested. Results from the prediction elevation values ranged from -3e-9 to 2e-9. It was observed from prediction variance map that the values were higher in the upper portion of the study area which comprised Gusau (GS), Jos (JS), Katsina (KT), Minna (MN) and Zaria (ZR) and lower in the middle and lower parts of the study area which comprised mainly Funtua, Kano, Maiduguri and Sokoto. Further studies are encouraged with high resolution imageries and more meteorological data to cover the montane and forest zone of the country to determine the level of climatic impacts particularly on vegetation productivity in general.展开更多
Mass elevation effect(MEE) refers to the thermal effect of huge mountains or plateaus, which causes the tendency for temperature-related montane landscape limits to occur at higher elevations in the inner massifs than...Mass elevation effect(MEE) refers to the thermal effect of huge mountains or plateaus, which causes the tendency for temperature-related montane landscape limits to occur at higher elevations in the inner massifs than on their outer margins. MEE has been widely identified in all large mountains, but how it could be measured and what its main forming-factors are still remain open. This paper, supposing that the local mountain base elevation(MBE) is the main factor of MEE, takes the Qinghai-Tibet Plateau(QTP) as the study area, defines MEE as the temperature difference(ΔT) between the inner and outer parts of mountain massifs, identifies the main forming factors, and analyzes their contributions to MEE. A total of 73 mountain bases were identified, ranging from 708 m to 5081 m and increasing from the edges to the central parts of the plateau. Climate data(1981–2010) from 134 meteorological stations were used to acquire ΔT by comparing near-surface air temperature on the main plateau with the free-air temperature at the same altitude and similar latitude outside of the plateau. The ΔT for the warmest month is averagely 6.15℃, over 12℃ at Lhatse and Baxoi. A multivariate linear regression model was developed to simulate MEE based on three variables(latitude, annual mean precipitation and MBE), which are all significantly correlated to ΔT. The model could explain 67.3% of MEE variation, and the contribution rates of three independent variables to MEE are 35.29%, 22.69% and 42.02%, respectively. This confirms that MBE is the main factor of MEE. The intensive MEE of the QTP pushes the 10℃ isotherm of the warmest month mean temperature 1300–2000 m higher in the main plateau than in the outer regions, leading the occurrence of the highest timberline(4900 m) and the highest snowline(6200 m) of the Northern Hemisphere in the southeast and southwest of the plateau, respectively.展开更多
The extreme temperature differences in flat steel box girder of a cable-stayed bridge were studied.Firstly,by using the long-term measurement data collected by the structural health monitoring system installed on the ...The extreme temperature differences in flat steel box girder of a cable-stayed bridge were studied.Firstly,by using the long-term measurement data collected by the structural health monitoring system installed on the Runyang Cable-stayed Bridge,the daily variations as well as seasonal ones of measured temperature differences in the box girder cross-section area were summarized.The probability distribution models of temperature differences were further established and the extreme temperature differences were estimated with a return period of 100 years.Finally,the temperature difference models in cross-section area were proposed for bridge thermal design.The results show that horizontal temperature differences in top plate and vertical temperature differences between top plate and bottom plate are considerable.All the positive and negative temperature differences can be described by the weighted sum of two Weibull distributions.The maximum positive and negative horizontal temperature differences in top plate are 10.30°C and13.80°C,respectively.And the maximum positive and negative vertical temperature differences between top plate and bottom plate are 17.30°C and 3.70°C,respectively.For bridge thermal design,there are two vertical temperature difference models between top plate and bottom plate,and six horizontal temperature difference models in top plate.展开更多
基金supported by the Natural Science Foundation of China (Grant Nos.41401111 and 41601091)
文摘The lofty and extensive Tibetan Plateau has significant mass elevation effect(MEE). In recent years, a great effort has been made to quantify MEE, with the recognition of intra-mountain basal elevation(MBE) as the main determinant of MEE. In this study, we improved the method of estimating MEE with MODIS and NECP data, by refining temperature laps rate, and dividing MBE plots, and then analyzed the spatio-temporal variation of MEE in the Plateau. The main conclusions include: 1) the highest average annual MEE of the plateau is as high as 11.5488°C in the southwest of the plateau, where exists a high-MEE core and MEE takes on a trend of decreasing from the core to the surrounding areas; 2) in the interior of the plateau, the maximum monthly MEE is 14.1108°C in the highest MBE plot(4934 m) in August; while the minimum monthly MEE appeared primarily in January and February; 3) in the peripheral areas of the plateau, annual mean MEE is relatively low, mostly between 3.0068°C–5.1972°C, where monthly MEE is high in January and December and low in June and July, completely different from the MEE time-series variation in the internal parts of the plateau.
文摘For oil pipeline in mountain areas,high hydrostatic pressure in the pipeline may cause error-opening of pressure relief valves,and oil is discharged from the pipeline to the pressure relief tanks,bringing spilling-over risk of the pressure relief tanks.Therefore,simulating the error-opening situations of the pressure relief valves and investigating the oil discharge process are necessary for checking the possibility of the spilling-over accident and then proposing measures to improve the pressure relief system.This research focuses on a continuous undulating oil pipeline with large elevation difference and a station along this pipeline,which is named B station in this paper,is studied.By OLGA software,simulation model of the pressure relief system of B station is established,and the accuracy of the model is verified by reconstructing a real accident and making a comparison with the actual accident data.The maximum discharge rate reached 8284 m3/h when the pressure relief valve was opened by mistake in the inlet and outlet of the station.The accumulated filling time of the two pressure relief tanks is 200 s,which is in good agreement with the accident data.On this basis,for error-opening of the pressure relief valves at the inlet and outlet of B station,simulation is performed to investigate variations of the discharge velocity,discharge flow rate,accumulated discharge volume and ventilation volume of the vent valve.The discharge velocity is found to be over the maximum velocity allowed for safety consideration.According to the accumulated discharge volume,it is inferred that spilling over of the pressure relief tanks will be caused once error-opening of the pressure relief valve occurs.Also it is judged that the existing breathing valve can not satisfy the ventilation requirement in case of failure of the pressure relief valves.From these simulation results,it is proposed that increasing the number of vent valves,replacing the manual valves with electrically operated valves,and employing security control interlock protection program are improvement measures to guarantee safe,efficient and reliable operation of the pressure relief system at B station.
文摘Climate change is one of the greatest threats facing the global community and has been mainly induced by increasing atmospheric concentrations of greenhouse gases resulting from fossil fuel energy use and change in vegetation cover. This study used modelling techniques to determine how changes in climate could affect vegetation productivity in the northern part of Nigeria. Climatic parameters (Rainfall, Minimum and Maximum Temperatures) as well as coarse Normalised Difference Vegetation Index (NDVI) data for the growing seasons of 1981-2009 were utilised. Because of the relationship between climatic parameters and vegetation, Spatial method of data interpolation was tested. Results from the prediction elevation values ranged from -3e-9 to 2e-9. It was observed from prediction variance map that the values were higher in the upper portion of the study area which comprised Gusau (GS), Jos (JS), Katsina (KT), Minna (MN) and Zaria (ZR) and lower in the middle and lower parts of the study area which comprised mainly Funtua, Kano, Maiduguri and Sokoto. Further studies are encouraged with high resolution imageries and more meteorological data to cover the montane and forest zone of the country to determine the level of climatic impacts particularly on vegetation productivity in general.
基金National Natural Science Foundation of China(No.41571099,41030528)
文摘Mass elevation effect(MEE) refers to the thermal effect of huge mountains or plateaus, which causes the tendency for temperature-related montane landscape limits to occur at higher elevations in the inner massifs than on their outer margins. MEE has been widely identified in all large mountains, but how it could be measured and what its main forming-factors are still remain open. This paper, supposing that the local mountain base elevation(MBE) is the main factor of MEE, takes the Qinghai-Tibet Plateau(QTP) as the study area, defines MEE as the temperature difference(ΔT) between the inner and outer parts of mountain massifs, identifies the main forming factors, and analyzes their contributions to MEE. A total of 73 mountain bases were identified, ranging from 708 m to 5081 m and increasing from the edges to the central parts of the plateau. Climate data(1981–2010) from 134 meteorological stations were used to acquire ΔT by comparing near-surface air temperature on the main plateau with the free-air temperature at the same altitude and similar latitude outside of the plateau. The ΔT for the warmest month is averagely 6.15℃, over 12℃ at Lhatse and Baxoi. A multivariate linear regression model was developed to simulate MEE based on three variables(latitude, annual mean precipitation and MBE), which are all significantly correlated to ΔT. The model could explain 67.3% of MEE variation, and the contribution rates of three independent variables to MEE are 35.29%, 22.69% and 42.02%, respectively. This confirms that MBE is the main factor of MEE. The intensive MEE of the QTP pushes the 10℃ isotherm of the warmest month mean temperature 1300–2000 m higher in the main plateau than in the outer regions, leading the occurrence of the highest timberline(4900 m) and the highest snowline(6200 m) of the Northern Hemisphere in the southeast and southwest of the plateau, respectively.
基金Project(51178100)supported by the National Natural Science Foundation of ChinaProject(1105007001)supported by the Foundation of the Priority Academic Development Program of Higher Education Institute of Jiangsu Province,ChinaProject(3205001205)supported by the Teaching and Research Foundation for Excellent Young Teachers of Southeast University,China
文摘The extreme temperature differences in flat steel box girder of a cable-stayed bridge were studied.Firstly,by using the long-term measurement data collected by the structural health monitoring system installed on the Runyang Cable-stayed Bridge,the daily variations as well as seasonal ones of measured temperature differences in the box girder cross-section area were summarized.The probability distribution models of temperature differences were further established and the extreme temperature differences were estimated with a return period of 100 years.Finally,the temperature difference models in cross-section area were proposed for bridge thermal design.The results show that horizontal temperature differences in top plate and vertical temperature differences between top plate and bottom plate are considerable.All the positive and negative temperature differences can be described by the weighted sum of two Weibull distributions.The maximum positive and negative horizontal temperature differences in top plate are 10.30°C and13.80°C,respectively.And the maximum positive and negative vertical temperature differences between top plate and bottom plate are 17.30°C and 3.70°C,respectively.For bridge thermal design,there are two vertical temperature difference models between top plate and bottom plate,and six horizontal temperature difference models in top plate.