With the deployment of modern infrastructure for public transportation, several studies have analyzed movement patterns of people using smart card data and have characterized different areas. In this paper, we propose...With the deployment of modern infrastructure for public transportation, several studies have analyzed movement patterns of people using smart card data and have characterized different areas. In this paper, we propose the “movement purpose hypothesis” that each movement occurs from two causes: where the person is and what the person wants to do at a given moment. We formulate this hypothesis to a synthesis model in which two network graphs generate a movement network graph. Then we develop two novel-embedding models to assess the hypothesis, and demonstrate that the models obtain a vector representation of a geospatial area using movement patterns of people from large-scale smart card data. We conducted an experiment using smart card data for a large network of railroads in the Kansai region of Japan. We obtained a vector representation of each railroad station and each purpose using the developed embedding models. Results show that network embedding methods are suitable for a large-scale movement of data, and the developed models perform better than existing embedding methods in the task of multi-label classification for train stations on the purpose of use data set. Our proposed models can contribute to the prediction of people flows by discovering underlying representations of geospatial areas from mobility data.展开更多
One of the crucial factors affecting the carrying capacity of the cryogenic liquid launch vehicle is the effective volume of the tank.Theoretical and experimental investigations on vortex breaker mechanisms have propo...One of the crucial factors affecting the carrying capacity of the cryogenic liquid launch vehicle is the effective volume of the tank.Theoretical and experimental investigations on vortex breaker mechanisms have proposed promising schemes applied in the oxygen tank of the liquid-propellant launch vehicle to ensure the normal operation of the engine.In this paper,the liquid surface profile functions of the laminar core when the vortex generates were derived based on the Rankine vortex model.The dimensionless residual volume V/d3 and the Froude number were applied to compare the theoretical prediction of critical height with the actual simulation data of liquid oxygen.This comparison method can improve the model’s accuracy.The efficiency of different basic shapes of vortex breakers was tested by conducting CFD modelling on a non-vertical outflow tank under a specific operating condition.Simulation results suggest negligible effects of heat transfer and surface tension.A circular plate is considered the optimal vortex breaker shape in traditional vertical outflow tanks,while a higher optimize efficiency was discovered in the half baffle basic shape in a non-vertical outflow tank by comparing the dimensionless residual volume and flow coefficient.A 34.26%reduction in flow resistance of half baffle breaker can be reached when applying a twenty-degree outlet pipe chamfering setting compared to a zero-degree chamfer.Considering practical operating limitations,it is concluded that a vortex breaker mechanism in a half baffle basic shape with a radius of 2.5d and a height of 4/d is the optimal scheme,which is suitable for all types of tanks.Its optimization efficiency of the residual volume reduction is about 56.68%compared to a nobreaker installation case.Lastly,a general equation based on CFD simulation for predicting the residual volume under a certain outflow velocity was proposed:V=d3yaFr0:3,which trend is consistent with that of mathematical prediction V=d3yaFr1=3.This consistency proves the accuracy and applicability of optimization strategy in this paper.展开更多
We present a benchmark test suite and an automated machine learning procedure for evaluating supervised machine learning(ML)models for predicting properties of inorganic bulk materials.The test suite,Matbench,is a set...We present a benchmark test suite and an automated machine learning procedure for evaluating supervised machine learning(ML)models for predicting properties of inorganic bulk materials.The test suite,Matbench,is a set of 13 ML tasks that range in size from 312 to 132k samples and contain data from 10 density functional theory-derived and experimental sources.展开更多
One of the most accurate approaches for calculating lattice thermal conductivity,κ_(l),is solving the Boltzmann transport equation starting from third-order anharmonic force constants.In addition to the underlying ap...One of the most accurate approaches for calculating lattice thermal conductivity,κ_(l),is solving the Boltzmann transport equation starting from third-order anharmonic force constants.In addition to the underlying approximations of ab-initio parameterization,two main challenges are associated with this path:high computational costs and lack of automation in the frameworks using this methodology,which affect the discovery rate of novel materials with ad-hoc properties.Here,the Automatic Anharmonic Phonon Library(AAPL)is presented.It efficiently computes interatomic force constants by making effective use of crystal symmetry analysis,it solves the Boltzmann transport equation to obtain κ_(l),and allows a fully integrated operation with minimum user intervention,a rational addition to the current high-throughput accelerated materials development framework AFLOW.An“experiment vs.theory”study of the approach is shown,comparing accuracy and speed with respect to other available packages,and for materials characterized by strong electron localization and correlation.Combining AAPL with the pseudo-hybrid functional ACBN0 is possible to improve accuracy without increasing computational requirements.展开更多
文摘With the deployment of modern infrastructure for public transportation, several studies have analyzed movement patterns of people using smart card data and have characterized different areas. In this paper, we propose the “movement purpose hypothesis” that each movement occurs from two causes: where the person is and what the person wants to do at a given moment. We formulate this hypothesis to a synthesis model in which two network graphs generate a movement network graph. Then we develop two novel-embedding models to assess the hypothesis, and demonstrate that the models obtain a vector representation of a geospatial area using movement patterns of people from large-scale smart card data. We conducted an experiment using smart card data for a large network of railroads in the Kansai region of Japan. We obtained a vector representation of each railroad station and each purpose using the developed embedding models. Results show that network embedding methods are suitable for a large-scale movement of data, and the developed models perform better than existing embedding methods in the task of multi-label classification for train stations on the purpose of use data set. Our proposed models can contribute to the prediction of people flows by discovering underlying representations of geospatial areas from mobility data.
文摘One of the crucial factors affecting the carrying capacity of the cryogenic liquid launch vehicle is the effective volume of the tank.Theoretical and experimental investigations on vortex breaker mechanisms have proposed promising schemes applied in the oxygen tank of the liquid-propellant launch vehicle to ensure the normal operation of the engine.In this paper,the liquid surface profile functions of the laminar core when the vortex generates were derived based on the Rankine vortex model.The dimensionless residual volume V/d3 and the Froude number were applied to compare the theoretical prediction of critical height with the actual simulation data of liquid oxygen.This comparison method can improve the model’s accuracy.The efficiency of different basic shapes of vortex breakers was tested by conducting CFD modelling on a non-vertical outflow tank under a specific operating condition.Simulation results suggest negligible effects of heat transfer and surface tension.A circular plate is considered the optimal vortex breaker shape in traditional vertical outflow tanks,while a higher optimize efficiency was discovered in the half baffle basic shape in a non-vertical outflow tank by comparing the dimensionless residual volume and flow coefficient.A 34.26%reduction in flow resistance of half baffle breaker can be reached when applying a twenty-degree outlet pipe chamfering setting compared to a zero-degree chamfer.Considering practical operating limitations,it is concluded that a vortex breaker mechanism in a half baffle basic shape with a radius of 2.5d and a height of 4/d is the optimal scheme,which is suitable for all types of tanks.Its optimization efficiency of the residual volume reduction is about 56.68%compared to a nobreaker installation case.Lastly,a general equation based on CFD simulation for predicting the residual volume under a certain outflow velocity was proposed:V=d3yaFr0:3,which trend is consistent with that of mathematical prediction V=d3yaFr1=3.This consistency proves the accuracy and applicability of optimization strategy in this paper.
基金This work was intellectually led and funded by the United States Department of Energy,Office of Basic Energy Sciences,Early Career Research Program,which provided funding for A.D.,Q.W.,A.G.,D.D.,and A.J.Lawrence Berkeley National Laboratory is funded by the DOE under award DE-AC02-05CH11231This research used the Lawrencium computational cluster resource provided by the IT Division at the Lawrence Berkeley National Laboratory(Supported by the Director,Office of Science,Office of Basic Energy Sciences,of the U.S.Department of Energy under Contract No.DE-AC02-05CH11231)This research used resources of the National Energy Research Scientific Computing Center(NERSC),a U.S.Department of Energy Office of Science User Facility operated under Contract No.DE-AC02-05CH11231.
文摘We present a benchmark test suite and an automated machine learning procedure for evaluating supervised machine learning(ML)models for predicting properties of inorganic bulk materials.The test suite,Matbench,is a set of 13 ML tasks that range in size from 312 to 132k samples and contain data from 10 density functional theory-derived and experimental sources.
基金support by the DOE(DE-AC02-05CH11231),specifically the Basic Energy Sciences program under Grant#EDCBEEpartial support by DOD-ONR(N00014-13-1-0635,N00014-11-1-0136,and N00014-15-1-2863)the Alexander von Humboldt Foundation for financial support(Fritz-Haber-Institut der Max-Planck-Gesellschaft,14195 Berlin-Dahlem,Germany).
文摘One of the most accurate approaches for calculating lattice thermal conductivity,κ_(l),is solving the Boltzmann transport equation starting from third-order anharmonic force constants.In addition to the underlying approximations of ab-initio parameterization,two main challenges are associated with this path:high computational costs and lack of automation in the frameworks using this methodology,which affect the discovery rate of novel materials with ad-hoc properties.Here,the Automatic Anharmonic Phonon Library(AAPL)is presented.It efficiently computes interatomic force constants by making effective use of crystal symmetry analysis,it solves the Boltzmann transport equation to obtain κ_(l),and allows a fully integrated operation with minimum user intervention,a rational addition to the current high-throughput accelerated materials development framework AFLOW.An“experiment vs.theory”study of the approach is shown,comparing accuracy and speed with respect to other available packages,and for materials characterized by strong electron localization and correlation.Combining AAPL with the pseudo-hybrid functional ACBN0 is possible to improve accuracy without increasing computational requirements.
