Integral Layout Optimization of Subsea Production Control System Considering Three-Dimensional Space Constraint

The subsea production control system, characterized by a complex and diverse structure and high cost, is one of the essential parts of a subsea production system. The rational layout of the subsea production control system is essential to reduce development costs and ensure safe production in offshore fields. Most previous studies on layout design in offshore fields have focused on the oil- and gas-gathering system. However, the layout of the subsea production control system has not thoroughly been researched to date and the seabed terrain and integral optimization have rarely been discussed. This paper focuses on the multi-layer star structure and multi-layer star-tree structure, two common layout structures of subsea production control systems, and establishes the corresponding model with obstacle and seabed terrain conditions. Obtaining the lowest possible total cost was the aim of the model. A hybrid algorithm combining the adaptive mutation particle swarm algorithm and the A-star algorithm was applied to integrally optimize the subsea distribution unit and umbilical touch down point positions, the pipe connection topology and pipe routes. The practicality of this approach is demonstrated by designing a layout with one FPSO and 22 subsea control modules. The results indicate that the multi-layer star-tree layout structure has a lower total cost compared to that of the multi-layer star layout structure. In addition, the results were compared with a case that ignores the seabed terrain, indicating differences in the total construction cost. This method provides engineers with quantitative references and reliable cost estimates to make decisions regarding the layout of the subsea production control system.

General models for topology layout of oil and gas star-tree pipeline network

Oil&gas gathering pipeline network structure is a significant part of oil&gas field construction, and the rational construction of pipeline network is directly related to the efficiency and benefits of oil&gas field production. Therefore, optimizing the gathering and transportation system of oil and gas fields is the key to reducing development costs. The star-tree type pipe network is widely used in the gathering and transportation system. In order to optimize the star-tree pipe networks (STPNs) that has restrictions on the processing capacity and gathering radius of the station as a whole, this paper establishes four models of pipe network layout with specific constraints. They are Mixed-Integer Linear Programming Models with a large number of discrete variables. We take two virtual fields as examples, use CPLEX solver to solve the above four models as a whole, to obtain the optimal scheme, and also figure out the investment of the pipeline network. We further optimize the hierarchical optimization of the pipeline network with special constraints, then compare and analyze results obtained by the overall optimization. Finally, models are applied to an actual oil field and an actual gas field as examples to optimize the layout, which verifies the validity and feasibility of the models.

Evaluation of ZigBee Topology Effect on Throughput and End to End Delay Due to Different Transmission Bands for IoT Applications

ZigBee is widely used in wireless network in Internet of Things (IoT) applications to remotely sensing and automation due to its unique characteristics compared to other wireless networks. According to ZigBee classification of IEEE 802.15.4 standard, the network consists of four layers. The ZigBee topology is represented in second layer. Furthermore, the ZigBee topology consists of three topologies, star, tree and mesh. Also there are many transmission bands allowed in physical layer, such as 2.4 GHz, 915 MHz, 868 MHz. The aim of this paper is to evaluate the effect of ZigBee topologies on End to End delay and throughput for different transmission bands. Riverbed Modeler is used to simulate multiple ZigBee proposed scenarios and collect the results. The results of the study recommend which topology should be used at each transmission band to provide lowest End to End delay or obtain maximum throughput, which is case sensitive in some IoT applications that required for example minimum delay time or sending high amount of data.

Tight Bounds on 1-Harmonious Coloring of Certain Graphs

Graph coloring is one of the most studied problems in graph theory due to its important applications in task scheduling and pattern recognition. The main aim of the problem is to assign colors to the elements of a graph such as vertices and/or edges subject to certain constraints. The 1-harmonious coloring is a kind of vertex coloring such that the color pairs of end vertices of every edge are different only for adjacent edges and the optimal constraint that the least number of colors is to be used. In this paper, we investigate the graphs in which we attain the sharp bound on 1-harmonious coloring. Our investigation consists of a collection of basic graphs like a complete graph, wheel, star, tree, fan, and interconnection networks such as a mesh-derived network, generalized honeycomb network, complete multipartite graph, butterfly, and Benes networks. We also give a systematic and elegant way of coloring for these structures.

Starless bias and parameter-estimation bias in the likelihood-based phylogenetic method

ABSTRACTI analyzed various site pattern combinations in a 4-OTU case to identify sources of starless bias and parameter-estimation bias in likelihood-based phylogenetic methods, and reported three significant contributions. First, the likelihood method is odd in that it may not generate a star tree with sequences that are equidistant from each other. This behaviour, dubbed starless bias, happens in a 4-OTU tree when there is an excess (i.e., more than expected from a star tree and a substitution model) of conflicting phylogenetic signals supporting the three resolved topologies equally. Special site pattern combinations leading to rejection of a star tree, when sequences are equidistant from each other, were identified. Second, fitting gamma distribution to model rate heterogeneity over sites is strongly confounded with tree topology, especially in conjunction with the starless bias. I present examples to show dramatic differences in the estimated shape parameter α between a star tree and a resolved tree. There may be no rate heterogeneity over sites (with the estimated α > 10000) when a star tree is imposed, but α < 1 (suggesting strong rate heterogeneity over sites) when an (incorrect) resolved tree is imposed. Thus, the dependence of “rate heterogeneity” on tree topology implies that “rate heterogeneity” is not a sequence-specific feature, cautioning against interpreting a small α to mean that some sites are under strong purifying selection and others not. Thirdly, because there is no existing (and working) likelihood method for evaluating a star tree with continuous gamma-distributed rate, I have implemented the method for JC69 in a self-contained R script for a four-OTU tree (star or resolved), in addition to another R script assuming a constant rate over sites. These R scripts should be useful for teaching and exploring likelihood methods in phylogenetics.