The geospatial sciences face grand information technology(IT)challenges in the twenty-first century:data intensity,computing intensity,concurrent access intensity and spatiotemporal intensity.These challenges require ...The geospatial sciences face grand information technology(IT)challenges in the twenty-first century:data intensity,computing intensity,concurrent access intensity and spatiotemporal intensity.These challenges require the readiness of a computing infrastructure that can:(1)better support discovery,access and utilization of data and data processing so as to relieve scientists and engineers of IT tasks and focus on scientific discoveries;(2)provide real-time IT resources to enable real-time applications,such as emergency response;(3)deal with access spikes;and(4)provide more reliable and scalable service for massive numbers of concurrent users to advance public knowledge.The emergence of cloud computing provides a potential solution with an elastic,on-demand computing platform to integrateobservation systems,parameter extracting algorithms,phenomena simulations,analytical visualization and decision support,and to provide social impact and user feedbackthe essential elements of the geospatial sciences.We discuss the utilization of cloud computing to support the intensities of geospatial sciences by reporting from our investigations on how cloud computing could enable the geospatial sciences and how spatiotemporal principles,the kernel of the geospatial sciences,could be utilized to ensure the benefits of cloud computing.Four research examples are presented to analyze how to:(1)search,access and utilize geospatial data;(2)configure computing infrastructure to enable the computability of intensive simulation models;(3)disseminate and utilize research results for massive numbers of concurrent users;and(4)adopt spatiotemporal principles to support spatiotemporal intensive applications.The paper concludes with a discussion of opportunities and challenges for spatial cloud computing(SCC).展开更多
By using finite-time thermodynamics, the optimal performance of a Stirling heat engine with thermal resistance, heat leak and regenerative loss is studied. The fundamental optimal relation is derived and the bounds of...By using finite-time thermodynamics, the optimal performance of a Stirling heat engine with thermal resistance, heat leak and regenerative loss is studied. The fundamental optimal relation is derived and the bounds of power output and efficiency are deduced from it. Then the significance of the relation and bounds are revealed. The results obtained here may provide some new theoretical guides for the optimal design of Stirling heat engines.展开更多
The tropical Pacific is currently experiencing an El Nifio event. Various coupled models with different degrees of complexity have been used to make real-time E1 Nifio predictions, but large uncertainties exist in the...The tropical Pacific is currently experiencing an El Nifio event. Various coupled models with different degrees of complexity have been used to make real-time E1 Nifio predictions, but large uncertainties exist in the inten- sity forecast and are strongly model dependent. An intermediate coupled model （ICM） is used at the Institute of Oceanology, Chinese Academy of Sciences （IOCAS）, named the IOCAS ICM, to predict the sea surface temper- ature （SST） evolution in the tropical Pacific during the 2015-2016 E! Nifio event. One unique feature of the IOCAS ICM is the way in which the temperature of subsurface water entrained in the mixed layer （Te） is parameterized. Observed SST anomalies are only field that is utilized to initialize the coupled prediction using the IOCAS ICM. Examples are given of the model＇s ability to predict the SST conditions in a real-time manner. As is commonly evident in E1 Nifio- Southern Oscillation predictions using coupled models, large discrepancies occur between the observed and pre- dicted SST anomalies in spring 2015. Starting from early summer 2015, the model can realistically predict warming conditions. Thereafter, good predictions can be made through the summer and fall seasons of 2015. A transition to normal and cold conditions is predictecl to occur in rote spring 2016. Comparisons with other model predictions are made and factors influencing the prediction performance of the IOCAS ICM are also discussed.展开更多
A new cyclic model of a four-reservoir isothermal chemical potential transformer with irreversible mass transfer, mass leakage and internal dissipation is put forward in this paper. The optimal relation be-tween the c...A new cyclic model of a four-reservoir isothermal chemical potential transformer with irreversible mass transfer, mass leakage and internal dissipation is put forward in this paper. The optimal relation be-tween the coefficient of performance (COP) and the rate of energy pumping of the generalized irre-versible four-reservoir isothermal chemical potential transformer has been derived by using finite-time thermodynamics or thermodynamic optimization. The maximum COP and the corresponding rate of energy pumping, as well as the maximum rate of energy pumping and the corresponding COP, have been obtained. Moreover, the influences of the irreversibility on the optimal performance of the iso-thermal chemical potential transformer have been revealed. It was found that the mass leakage affects the optimal performance both qualitatively and quantitatively, while the internal dissipation affects the optimal performance quantitatively. The results obtained herein can provide some new theoretical guidelines for the optimal design and development of a class of isothermal chemical potential trans-formers, such as mass exchangers, electrochemical, photochemical and solid state devices, fuel pumps, etc.展开更多
基金We thank Drs.Huadong Guo and Changlin Wang for inviting us to write this definition and field review paper.Research reported is partially supported by NASA(NNX07AD99G and SMD-09-1448),FGDC(G09AC00103)Environmental Informatics Framework of the Earth,Energy,and Environment Program at Microsoft Research Connection.We thank insightful comments from reviewers including Dr.Aijun Chen(NASA/GMU),Dr.Thomas Huang(NASA JPL),Dr.Cao Kang(Clark Univ.),Krishna Kumar(Microsoft),Dr.Wenwen Li(UCSB),Dr.Michael Peterson(University of Nebraska-Omaha),Dr.Xuan Shi(Geogia Tech),Dr.Tong Zhang(Wuhan University),Jinesh Varia(Amazon)and an anonymous reviewer.This paper is a result from the collaborations/discussions with colleagues from NASA,FGDC,USGS,EPA,GSA,Microsoft,ESIP,AAG CISG,CPGIS,UCGIS,GEO,and ISDE.
文摘The geospatial sciences face grand information technology(IT)challenges in the twenty-first century:data intensity,computing intensity,concurrent access intensity and spatiotemporal intensity.These challenges require the readiness of a computing infrastructure that can:(1)better support discovery,access and utilization of data and data processing so as to relieve scientists and engineers of IT tasks and focus on scientific discoveries;(2)provide real-time IT resources to enable real-time applications,such as emergency response;(3)deal with access spikes;and(4)provide more reliable and scalable service for massive numbers of concurrent users to advance public knowledge.The emergence of cloud computing provides a potential solution with an elastic,on-demand computing platform to integrateobservation systems,parameter extracting algorithms,phenomena simulations,analytical visualization and decision support,and to provide social impact and user feedbackthe essential elements of the geospatial sciences.We discuss the utilization of cloud computing to support the intensities of geospatial sciences by reporting from our investigations on how cloud computing could enable the geospatial sciences and how spatiotemporal principles,the kernel of the geospatial sciences,could be utilized to ensure the benefits of cloud computing.Four research examples are presented to analyze how to:(1)search,access and utilize geospatial data;(2)configure computing infrastructure to enable the computability of intensive simulation models;(3)disseminate and utilize research results for massive numbers of concurrent users;and(4)adopt spatiotemporal principles to support spatiotemporal intensive applications.The paper concludes with a discussion of opportunities and challenges for spatial cloud computing(SCC).
文摘By using finite-time thermodynamics, the optimal performance of a Stirling heat engine with thermal resistance, heat leak and regenerative loss is studied. The fundamental optimal relation is derived and the bounds of power output and efficiency are deduced from it. Then the significance of the relation and bounds are revealed. The results obtained here may provide some new theoretical guides for the optimal design of Stirling heat engines.
基金the National Natural Science Foundation of China(41490644,41475101 and41421005)the CAS Strategic Priority Project+1 种基金the Western Pacific Ocean System(XDA11010105,XDA11020306 and XDA11010301)the NSFC-Shandong Joint Fund for Marine Science Research Centers(U1406401)
文摘The tropical Pacific is currently experiencing an El Nifio event. Various coupled models with different degrees of complexity have been used to make real-time E1 Nifio predictions, but large uncertainties exist in the inten- sity forecast and are strongly model dependent. An intermediate coupled model （ICM） is used at the Institute of Oceanology, Chinese Academy of Sciences （IOCAS）, named the IOCAS ICM, to predict the sea surface temper- ature （SST） evolution in the tropical Pacific during the 2015-2016 E! Nifio event. One unique feature of the IOCAS ICM is the way in which the temperature of subsurface water entrained in the mixed layer （Te） is parameterized. Observed SST anomalies are only field that is utilized to initialize the coupled prediction using the IOCAS ICM. Examples are given of the model＇s ability to predict the SST conditions in a real-time manner. As is commonly evident in E1 Nifio- Southern Oscillation predictions using coupled models, large discrepancies occur between the observed and pre- dicted SST anomalies in spring 2015. Starting from early summer 2015, the model can realistically predict warming conditions. Thereafter, good predictions can be made through the summer and fall seasons of 2015. A transition to normal and cold conditions is predictecl to occur in rote spring 2016. Comparisons with other model predictions are made and factors influencing the prediction performance of the IOCAS ICM are also discussed.
基金the Program for New Century Excellent Talents of China (Grant No. NCET-04-1006)the Foundation for the Author of National Excellent Doctoral Dissertation of China (Grant No. 200136)
文摘A new cyclic model of a four-reservoir isothermal chemical potential transformer with irreversible mass transfer, mass leakage and internal dissipation is put forward in this paper. The optimal relation be-tween the coefficient of performance (COP) and the rate of energy pumping of the generalized irre-versible four-reservoir isothermal chemical potential transformer has been derived by using finite-time thermodynamics or thermodynamic optimization. The maximum COP and the corresponding rate of energy pumping, as well as the maximum rate of energy pumping and the corresponding COP, have been obtained. Moreover, the influences of the irreversibility on the optimal performance of the iso-thermal chemical potential transformer have been revealed. It was found that the mass leakage affects the optimal performance both qualitatively and quantitatively, while the internal dissipation affects the optimal performance quantitatively. The results obtained herein can provide some new theoretical guidelines for the optimal design and development of a class of isothermal chemical potential trans-formers, such as mass exchangers, electrochemical, photochemical and solid state devices, fuel pumps, etc.
