The Common Land Model(CoLM) was coupled with the IAP Dynamic Global Vegetation Model(IAPDGVM), and the performance of this combined CoLMIAP model was evaluated. Offline simulations using both the original Common Land ...The Common Land Model(CoLM) was coupled with the IAP Dynamic Global Vegetation Model(IAPDGVM), and the performance of this combined CoLMIAP model was evaluated. Offline simulations using both the original Common Land Model(CoLM-LPJ) and CoLM-IAP were conducted. The CoLM-IAP coupled model showed a significant improvement over CoLMLPJ, as the deciduous tree distribution decreased over temperate and boreal regions, while the distribution of evergreen trees increased over the tropics. Some biases in CoLM-LPJ were preserved, including the overestimation of evergreen trees in tropical savanna, the underestimation of boreal evergreen trees, and the absence of boreal shrubs. However, most of these biases did not exist in a further coupled simulation of IAP-DGVM with the Community Land Model(CLM), for which the parameters of IAP-DGVM were optimized. This implies that further improvement is needed to deal with the differences between CoLM and CLM in parameterizations of landbased physical and biochemical processes.展开更多
In order to decisively determine the adsorption selectivity of zirconium MOF(UiO-66) towards anionic versus cationic species, the adsorptive removal of the anionic dyes(Alizarin Red S.(ARS), Eosin(E), Fuchsin Acid(FA)...In order to decisively determine the adsorption selectivity of zirconium MOF(UiO-66) towards anionic versus cationic species, the adsorptive removal of the anionic dyes(Alizarin Red S.(ARS), Eosin(E), Fuchsin Acid(FA)and Methyl Orange(MO)) and the cationic dyes(Neutral Red(NR), Fuchsin Basic(FB), Methylene Blue(MB),and Safranine T(ST)) has been evaluated. The results clearly reveal a significant selectivity towards anionic dyes. Such an observation agrees with a plethora of reports of UiO-66 superior affinity towards other anionic species(Floride, PO_4^(3-), Diclofenac sodium, Methylchlorophenoxy-propionic acid, Phenols, CrO_4^(2-), SeO_3^(2-), and AsO_4^-). The adsorption process of ARS as an example has been optimized using the central composite design(CCD). The resultant statistical model indicates a crucial effect of both pH and sorbent mass. The optimum conditions were determined to be initial dye concentration 11.82 mg.L^(-1), adsorbent amount 0.0248 g, shaking time of 36 min and pH 2. The adsorption process proceeds via pseudo-second order kinetics(R^2= 0.999). The equilibrium data were fit to Langmuir and Tempkin models(R^2= 0.999 and 0.997 respectively). The results reveal an exceptional removal for the anionic dye(Alizarin Red S.) with a record adsorption capacity of400 mg·g^(-1). The significantly high adsorption capacity of UiO-66 towards ARS adds further evidence to the recently reported exceptional performance of MOFs in pollutants removal from water.展开更多
In the enzymatic membrane reactor for separating casein hydrolysate, backflushing technology has been used to decrease the fouling of the membrane. Predication of the backflushing efficiency poses a complex non-linear...In the enzymatic membrane reactor for separating casein hydrolysate, backflushing technology has been used to decrease the fouling of the membrane. Predication of the backflushing efficiency poses a complex non-linear problem as the system integrates enzymatic hydrolysis, membrane separation and periodic backflushing together. In this paper an alternative artificial neural network approach is developed to predict the backflushing efficiency as a function of duration and interval. A contour plot of backflushing performance is presented to model these effects, and the backflushing conditions have been optimized as duration of 10 s and interval of 10 min using this neural network. Also, simple neural networks are established to predict the time evolution of flux before and after backflushing. The results predicted by the models are in good agreement with the experimental data, and the average deviations for all the cases are well within ±5%. The neural network approach is found to be capable of modeling the backflushing with confidence.展开更多
We use conditional nonlinear optimal perturbation （CNOP） to investigate the optimal precursory disturbances in the Zebiak- Cane El Nino-Southern Oscillation （ENSO） model. The conditions of the CNOP-type precursors...We use conditional nonlinear optimal perturbation （CNOP） to investigate the optimal precursory disturbances in the Zebiak- Cane El Nino-Southern Oscillation （ENSO） model. The conditions of the CNOP-type precursors are highly likely to evolve into El Nino events in the Zebiak-Cane model. By exploring the dynamic behaviors of these nonlinear El Nino events caused by the CNOP-type precursors, we find that they, as expected, tend to phase-lock to the annual cycles in the Zebiak-Cane model with the SSTA peak at the end of a calendar year. However, E1 Nino events with CNOPs as initial anomalies in the linearized Zebiak-Cane model are inclined to phase-lock earlier than nonlinear E1 Nino events despite the existence of annual cycles in the model. It is clear that nonlinearities play an important role in El Nino＇s phase-locking. In particular, nonlinear temperature advection increases anomalous zonal SST differences and anomalous westerlies, which weakens anomalous upwelling and acts on the increasing anomalous vertical temperature difference and, as a result, enhances E1 Nino and then delays the peak SSTA. Finally, we demonstrate that nonlinear temperature advection, together with the effect of the annual cycle, causes El Nino events to peak at the end of the calendar year.展开更多
Pipes,especially buried pipes,in cold regions generally experience a rash of failures during cold weather snaps.However,the existing heuristic models are unable to explain the basic processes involving frost actions.T...Pipes,especially buried pipes,in cold regions generally experience a rash of failures during cold weather snaps.However,the existing heuristic models are unable to explain the basic processes involving frost actions.This is because the frost action is not a direct load but one that causes variations in pipe-soil interactions resulting from the coupled thermo-hydro-mechanical process in soils.This paper developed and implemented a holistic multiphysics simulation model for freezing soils and extended it to the analysis of pipe-soil systems.The theoretical framework was implemented to analyze both static and dynamic responses of buried pipes subjected to frost actions.The multiphysics simulations reproduced phenomena commonly observed during frost actions,e.g.,ice fringe advancement and an increase in the internal stress of pipes.The influences of important design factors,i.e.,buried depth and overburden pressure,on pipe responses were simulated.A fatigue cracking criterion was utilized to predict the crack initialization under the joint effects of frost and dynamic traffic loads.The frost effects were found to have detrimental effects for accelerating fatigue crack initialization in pipes.展开更多
基金supported by Strategic Priority Research Program of the Chinese Academy of Sciences (Grant No. XDA05110103)the National Basic Research Program of China (Grant No. 2010CB951801)
文摘The Common Land Model(CoLM) was coupled with the IAP Dynamic Global Vegetation Model(IAPDGVM), and the performance of this combined CoLMIAP model was evaluated. Offline simulations using both the original Common Land Model(CoLM-LPJ) and CoLM-IAP were conducted. The CoLM-IAP coupled model showed a significant improvement over CoLMLPJ, as the deciduous tree distribution decreased over temperate and boreal regions, while the distribution of evergreen trees increased over the tropics. Some biases in CoLM-LPJ were preserved, including the overestimation of evergreen trees in tropical savanna, the underestimation of boreal evergreen trees, and the absence of boreal shrubs. However, most of these biases did not exist in a further coupled simulation of IAP-DGVM with the Community Land Model(CLM), for which the parameters of IAP-DGVM were optimized. This implies that further improvement is needed to deal with the differences between CoLM and CLM in parameterizations of landbased physical and biochemical processes.
文摘In order to decisively determine the adsorption selectivity of zirconium MOF(UiO-66) towards anionic versus cationic species, the adsorptive removal of the anionic dyes(Alizarin Red S.(ARS), Eosin(E), Fuchsin Acid(FA)and Methyl Orange(MO)) and the cationic dyes(Neutral Red(NR), Fuchsin Basic(FB), Methylene Blue(MB),and Safranine T(ST)) has been evaluated. The results clearly reveal a significant selectivity towards anionic dyes. Such an observation agrees with a plethora of reports of UiO-66 superior affinity towards other anionic species(Floride, PO_4^(3-), Diclofenac sodium, Methylchlorophenoxy-propionic acid, Phenols, CrO_4^(2-), SeO_3^(2-), and AsO_4^-). The adsorption process of ARS as an example has been optimized using the central composite design(CCD). The resultant statistical model indicates a crucial effect of both pH and sorbent mass. The optimum conditions were determined to be initial dye concentration 11.82 mg.L^(-1), adsorbent amount 0.0248 g, shaking time of 36 min and pH 2. The adsorption process proceeds via pseudo-second order kinetics(R^2= 0.999). The equilibrium data were fit to Langmuir and Tempkin models(R^2= 0.999 and 0.997 respectively). The results reveal an exceptional removal for the anionic dye(Alizarin Red S.) with a record adsorption capacity of400 mg·g^(-1). The significantly high adsorption capacity of UiO-66 towards ARS adds further evidence to the recently reported exceptional performance of MOFs in pollutants removal from water.
基金Supported by the National Natural Science Foundation of China (No. 20306023).
文摘In the enzymatic membrane reactor for separating casein hydrolysate, backflushing technology has been used to decrease the fouling of the membrane. Predication of the backflushing efficiency poses a complex non-linear problem as the system integrates enzymatic hydrolysis, membrane separation and periodic backflushing together. In this paper an alternative artificial neural network approach is developed to predict the backflushing efficiency as a function of duration and interval. A contour plot of backflushing performance is presented to model these effects, and the backflushing conditions have been optimized as duration of 10 s and interval of 10 min using this neural network. Also, simple neural networks are established to predict the time evolution of flux before and after backflushing. The results predicted by the models are in good agreement with the experimental data, and the average deviations for all the cases are well within ±5%. The neural network approach is found to be capable of modeling the backflushing with confidence.
基金sponsored by the Knowledge Innovation Program of the Chinese Academy of Sciences(Grant No.KZCX2-YW-QN203)the National Basic Research Program of China(Grant Nos.2010CB950400&2012CB955202)the National Natural Science Foundation of China(Grant No.41176013)
文摘We use conditional nonlinear optimal perturbation （CNOP） to investigate the optimal precursory disturbances in the Zebiak- Cane El Nino-Southern Oscillation （ENSO） model. The conditions of the CNOP-type precursors are highly likely to evolve into El Nino events in the Zebiak-Cane model. By exploring the dynamic behaviors of these nonlinear El Nino events caused by the CNOP-type precursors, we find that they, as expected, tend to phase-lock to the annual cycles in the Zebiak-Cane model with the SSTA peak at the end of a calendar year. However, E1 Nino events with CNOPs as initial anomalies in the linearized Zebiak-Cane model are inclined to phase-lock earlier than nonlinear E1 Nino events despite the existence of annual cycles in the model. It is clear that nonlinearities play an important role in El Nino＇s phase-locking. In particular, nonlinear temperature advection increases anomalous zonal SST differences and anomalous westerlies, which weakens anomalous upwelling and acts on the increasing anomalous vertical temperature difference and, as a result, enhances E1 Nino and then delays the peak SSTA. Finally, we demonstrate that nonlinear temperature advection, together with the effect of the annual cycle, causes El Nino events to peak at the end of the calendar year.
文摘Pipes,especially buried pipes,in cold regions generally experience a rash of failures during cold weather snaps.However,the existing heuristic models are unable to explain the basic processes involving frost actions.This is because the frost action is not a direct load but one that causes variations in pipe-soil interactions resulting from the coupled thermo-hydro-mechanical process in soils.This paper developed and implemented a holistic multiphysics simulation model for freezing soils and extended it to the analysis of pipe-soil systems.The theoretical framework was implemented to analyze both static and dynamic responses of buried pipes subjected to frost actions.The multiphysics simulations reproduced phenomena commonly observed during frost actions,e.g.,ice fringe advancement and an increase in the internal stress of pipes.The influences of important design factors,i.e.,buried depth and overburden pressure,on pipe responses were simulated.A fatigue cracking criterion was utilized to predict the crack initialization under the joint effects of frost and dynamic traffic loads.The frost effects were found to have detrimental effects for accelerating fatigue crack initialization in pipes.
