Spectrum of continuous two-contours system

A deterministic continuous dynamical system is considered. This system contains two contours. The length of theith contour equalsci,i= 1, 2. There is a moving segment (cluster) on each contour. The length of the cluster, located on theith contour, equalsli,i= 1, 2. If a cluster moves without delays, then the velocity of the cluster is equal to 1. There is a common point (node) of the contours. Clusters cannot cross the node simultaneously, and therefore delays of clusters occur. A set of repeating system states is called a spectral cycle. Spectral cycles and values of average velocities of clusters have been found. The system belongs to a class of contour systems. This class of dynamical systems has been introduced and studied by A.P. Buslaev.

An Adaptive Fish Swarm-Based Mobile Coverage in WSNs

Swarm intelligent algorithms are embedded into sensor networks to achieve perfect coverage with minimal cost. However, these methods are often highly complex and easily fall into the local optimum when balancing coverage and resource consumption. We introduce adaptive improved fish swarm optimization (AIFS) that extricates each node from the local optimum and reduces overlap and overflow coverage. Drawing on the habits of fish, AFIS ensures node mobility with respect to the food concentration at a certain point. Node dispersion shows good compromise under coordination by two presented parameters, namely, food concentration and crowd density. In addition to inheriting properties from traditional fish swarm, the initial random nodes become dispersed without overflow in assisting the proposed jumping and dodging behavior. The resulting network avoids potential local optima and improves the network boundary coverage efficiency. The convergence speed and efficiency of AIFS are verified. Extensive simulation experiments reveal that an improved coverage gain is obtained, and computation cost and overflow waste are reduced.

Application of Systems Analysis Techniques in Optimizing Gas Lift Installations

Systems analysis technqiues are applied to several well cases in order to optimize production rate and gas consumption of a continuous flow gas lift system. It is a procedure whereby various components, such as well capability, tubing size, flowline size, and separator pressure are analyzed in conjunction with the entire system in order to optimize the individual well or group of wells in a field. The solution point (node) can be taken anywhere in the system, but normally taken at the bottom or top of the well, and preferably both. Example problems will show the most logical manner to increase the flow rate, reduce the gas consumption, or both. A lowering of separator pressure to increase the flow rate may be a serious mistake. Examples will show that a more logical approach may be to increase the flowline size. In conclusion, all the individual components of a system must be analyzed in conjunction with the entire system for proper final analysis.