Flow Routing in Prismatic Symmetrical Compound Channels by Applications of the Apparent Shear Force (ASF)
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- Korean Journal of Hydrosciences
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- v.8
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- pp.41-56
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- 1997
A new routing computer model for the symmetric compound channel called the ASRMCS(Apparent Shear Force Muskingum-Cunge Method in Symmetry) has been developed. The Muskingum-Cunge routing method is adapted. The Apparent Shear Force (ASF) between the deep main channel and the shallow floodplan flow is introduced while the flow is routed. The nonlinear parameter method is applied. The temporal and spatial increments are varied according to the flow rate. The adaptation of above schemes is tested against the routed hydrographs using the DAMBRK model. The results of general routing practice of Muskingum-Cunge Method(GPMC) are also compared with those of above two models. The results of the new model match remarkably well with those of DAMBRK. The routed hydrographs show a smooth variation from the inflow boundary condition without any distortions caused by the difference of cross-section shape. However, the results of GPMC, showing early rise and fall of routed hydrograph, have considerable differences from those of the ASFMCS and DAMBRK.
This paper analyzes the fairness and efficiency of channel sharing when heterogeneous wireless networks that have different transmission power and/or coverage coexist with the contention-based channel access protocol. First, we show that the existing CSMA (carrier sensing multiple access) protocol, that is a prevailing contention-based mechanism, results in significant unfairness of channel access because of (1) the asymmetric capability of carrier sensing and (2) the blindness of binary exponential backoff and link adaptation mechanisms to the interference-driven transmission failures. Next, we derive the feasible region of carrier sensing thresholds that assures spatial reuse and fair channel sharing simultaneously. Moreover, we establish an analytical model for per-system throughput and investigate the effect of contention window size and transmission rate on the fairness and efficiency of channel sharing. Finally, we compare the performance of several approaches for fair channel sharing via simulations under various network configurations.
Introduction: Diffusion is process by which an innovation is communicated through certain channel overtime among the members of a social system(Rogers 1983). Bass(1969) suggested the Bass model describing diffusion process. The Bass model assumes potential adopters of innovation are influenced by mass-media and word-of-mouth from communication with previous adopters. Various expansions of the Bass model have been conducted. Some of them proposed a third factor affecting diffusion. Others proposed multinational diffusion model and it stressed interactive effect on diffusion among several countries. We add a spatial factor in the Bass model as a third communication factor. Because of situation where we can not control the interaction between markets, we need to consider that diffusion within certain market can be influenced by diffusion in contiguous market. The process that certain type of retail extends is a result that particular market can be described by the retail life cycle. Diffusion of retail has pattern following three phases of spatial diffusion: adoption of innovation happens in near the diffusion center first, spreads to the vicinity of the diffusing center and then adoption of innovation is completed in peripheral areas in saturation stage. So we expect spatial effect to be important to describe diffusion of domestic discount store. We define a spatial diffusion model using multinational diffusion model and apply it to the diffusion of discount store. Modeling: In this paper, we define a spatial diffusion model and apply it to the diffusion of discount store. To define a spatial diffusion model, we expand learning model(Kumar and Krishnan 2002) and separate diffusion process in diffusion center(market A) from diffusion process in the vicinity of the diffusing center(market B). The proposed spatial diffusion model is shown in equation (1a) and (1b). Equation (1a) is the diffusion process in diffusion center and equation (1b) is one in the vicinity of the diffusing center.