The time-driven activity-based costing has received extensive attention from scholars both at home and abroad in recent years,which has been applied to the calculation of manufacturing operations and the cost of produ...The time-driven activity-based costing has received extensive attention from scholars both at home and abroad in recent years,which has been applied to the calculation of manufacturing operations and the cost of products.However, this approach is rarely introduced into the service sector.As to the hospitality industry, the profitability of the customer usually plays a decisive role in the business process.Therefore, this article takes the hotel service industry as the research point and allocates the costs of resources of each departments to customers according to time drivers.The focus of this paper is to calculate the costs of customers ,and then analyze the profitability of customers in order to take the appropriate marketing strategies to improve the hotel service industry Drofitabilitv.展开更多
The classical discrete element approach(DEM)based on Newtonian dynamics can be divided into two major groups,event-driven methods(EDM)and timedriven methods(TDM).Generally speaking,TDM simulations are suited for cases...The classical discrete element approach(DEM)based on Newtonian dynamics can be divided into two major groups,event-driven methods(EDM)and timedriven methods(TDM).Generally speaking,TDM simulations are suited for cases with high volume fractions where there are collisions between multiple objects.EDM simulations are suited for cases with low volume fractions from the viewpoint of CPU time.A method combining EDM and TDM called Hybrid Algorithm of event-driven and time-driven methods(HAET)is presented in this paper.The HAET method employs TDM for the areas with high volume fractions and EDM for the remaining areas with low volume fractions.It can decrease the CPU time for simulating granular flows with strongly non-uniform volume fractions.In addition,a modified EDM algorithm using a constant time as the lower time step limit is presented.Finally,an example is presented to demonstrate the hybrid algorithm.展开更多
A coupled numerical method for the direct numerical simulation of particle-fluid systems is formulated and implemented, resolving an order of magnitude smaller than particle size. The particle motion is described by t...A coupled numerical method for the direct numerical simulation of particle-fluid systems is formulated and implemented, resolving an order of magnitude smaller than particle size. The particle motion is described by the time-driven hard-sphere model, while the hydrodynamic equations governing fluid flow are solved by the lattice Boltzmann method （LBM）, Particle-fluid coupling is realized by an immersed boundary method （IBM）, which considers the effect of boundary on surrounding fluid as a restoring force added to the governing equations of the fluid. The proposed scheme is validated in the classical flow-around-cylinder simulations, and preliminary application of this scheme to fluidization is reported, demonstrating it to be a promising computational strategy for better understanding complex behavior in particle-fluid systems.展开更多
文摘The time-driven activity-based costing has received extensive attention from scholars both at home and abroad in recent years,which has been applied to the calculation of manufacturing operations and the cost of products.However, this approach is rarely introduced into the service sector.As to the hospitality industry, the profitability of the customer usually plays a decisive role in the business process.Therefore, this article takes the hotel service industry as the research point and allocates the costs of resources of each departments to customers according to time drivers.The focus of this paper is to calculate the costs of customers ,and then analyze the profitability of customers in order to take the appropriate marketing strategies to improve the hotel service industry Drofitabilitv.
基金supported by a grant from Department of Energy and Process Engineering,Norwegian University of Science and Technology,Institute for Energy Technology(IFE)and SINTEF through the FACE(Multiphase Flow Assurance Innovation Center)project.
文摘The classical discrete element approach(DEM)based on Newtonian dynamics can be divided into two major groups,event-driven methods(EDM)and timedriven methods(TDM).Generally speaking,TDM simulations are suited for cases with high volume fractions where there are collisions between multiple objects.EDM simulations are suited for cases with low volume fractions from the viewpoint of CPU time.A method combining EDM and TDM called Hybrid Algorithm of event-driven and time-driven methods(HAET)is presented in this paper.The HAET method employs TDM for the areas with high volume fractions and EDM for the remaining areas with low volume fractions.It can decrease the CPU time for simulating granular flows with strongly non-uniform volume fractions.In addition,a modified EDM algorithm using a constant time as the lower time step limit is presented.Finally,an example is presented to demonstrate the hybrid algorithm.
基金sponsored by Ministry of Finance under the grant ZDYZ2008-2National Key Science and Technology Project under the grant 2008ZX05014-003-006HZthe Chinese Academy of Sciences under the grant KGCX2-YW-124
文摘A coupled numerical method for the direct numerical simulation of particle-fluid systems is formulated and implemented, resolving an order of magnitude smaller than particle size. The particle motion is described by the time-driven hard-sphere model, while the hydrodynamic equations governing fluid flow are solved by the lattice Boltzmann method （LBM）, Particle-fluid coupling is realized by an immersed boundary method （IBM）, which considers the effect of boundary on surrounding fluid as a restoring force added to the governing equations of the fluid. The proposed scheme is validated in the classical flow-around-cylinder simulations, and preliminary application of this scheme to fluidization is reported, demonstrating it to be a promising computational strategy for better understanding complex behavior in particle-fluid systems.
