MultiAspect Graphs: Algebraic representation and algorithms

We present the algebraic representation and basic algorithms for MultiAspect Graphs (MAGs). A MAG is a structure capable of representing multilayer and time-varying networks, as well as higher-order networks, while also having the property of being isomorphic to a directed graph. In particular, we show that, as a consequence of the properties associated with the MAG structure, a MAG can be represented in matrix form. Moreover, we also show that any possible MAG function (algorithm) can be obtained from this matrix-based representation. This is an important theoretical result since it paves the way for adapting well-known graph algorithms for application in MAGs. We present a set of basic MAG algorithms, constructed from well-known graph algorithms, such as degree computing, Breadth First Search (BFS), and Depth First Search (DFS). These algorithms adapted to the MAG context can be used as primitives for building other more sophisticated MAG algorithms. Therefore, such examples can be seen as guidelines on how to properly derive MAG algorithms from basic algorithms on directed graph. We also make available Python implementations of all the algorithms presented in this paper.Comment: 59 pages, 6 figure

A Unifying Model for Representing Time-Varying Graphs

Graph-based models form a fundamental aspect of data representation in Data Sciences and play a key role in modeling complex networked systems. In particular, recently there is an ever-increasing interest in modeling dynamic complex networks, i.e. networks in which the topological structure (nodes and edges) may vary over time. In this context, we propose a novel model for representing finite discrete Time-Varying Graphs (TVGs), which are typically used to model dynamic complex networked systems. We analyze the data structures built from our proposed model and demonstrate that, for most practical cases, the asymptotic memory complexity of our model is in the order of the cardinality of the set of edges. Further, we show that our proposal is an unifying model that can represent several previous (classes of) models for dynamic networks found in the recent literature, which in general are unable to represent each other. In contrast to previous models, our proposal is also able to intrinsically model cyclic (i.e. periodic) behavior in dynamic networks. These representation capabilities attest the expressive power of our proposed unifying model for TVGs. We thus believe our unifying model for TVGs is a step forward in the theoretical foundations for data analysis of complex networked systems.Comment: Also appears in the Proc. of the IEEE International Conference on Data Science and Advanced Analytics (IEEE DSAA'2015

Model predictive control of a free piston compressor/expander with an integrated linear motor/alternator

Linear positive displacement machines are becoming increasingly more attractive for applications that are normally known as unconquerable niches of rotary and scroll machines. Free-piston machines are characterized by the absence of a crank mechanism, since there is a direct transformation of electrical energy into the piston movement. From the point of view of manufacturing, these machines benefit from a higher robustness and reliability because of less mechanical components involved and reduced frictional losses associate with a conventional crank mechanism. However, the major challenge in replacing the rotary machines by linear ones is a lower efficiency at lower speeds which is unavoidable because of the nature of linear motion: continuous operation means a reciprocating movement within a stroke length with significantly long periods of acceleration and deceleration when the speed is far from its optimal value. However, the advantage of free-piston machines is the fact that the motion profile is freely configurable within physical constraints, which provides a possibility to optimize the speed given the efficiency map of particular linear motor. While the methods and results of the efficiency assessment for rotary machines are widely available, there is a lack of these analyses for linear machines. The current study provides in-depth analyses of a double-coil iron core linear motor also acting as a generator

Solar heat driven water circulation and aeration system for aquaculture

The proposed design concept of water aeration and updraft circulation in aquaculture is based on the Organic Rankine Cycle (ORC) technology and uses a solar energy absorbed by a floating collector. The pressure required for the aerator is created by evaporating a working fluid and optimized for an average depth of a pond. The working pressure is defined by the maximum achievable temperature of the working fluid. The condensing heat is rejected at a certain depth with the lowest temperature and drives the convective circulation. A prototype is designed by using common materials and off-the-shelf components to ensure maintenance-free and proper capacity to fulfil the needs of an average or a small aquaculture farm: the working fluid in the working chamber evaporates increasing in volume and pumping air out of the vessel as well as the expanded working fluid in the second working chamber. The working fluid is cooled down in the condenser which is submerged into the pond and it is condensed while decreasing in volume. The new design can perform multiple cycles per day increasing the volume of pumped air. In order to make the operation of this unit possible during the night, a heat buffer with a phase changing material (PCM) is used. A parametric study of suitable working fluids and PCMs has been performed in order to select the most appropriate combination for the target applications

Experimental characterization of single screw expander performance under different testing conditions and working fluids

During the last years, one of the most popular ways to recover low-grade waste heat is the organic Rankine cycle (ORC). This technology is widely studied and continuously optimized and, as a result, there are many efficient installations available on the market utilizing heat with stable parameters such as from geothermal sources or from the biomass combustion process. However, if a variable hot source in terms of either temperature or flow rate is introduced, the expansion devices have to work at non-optimal conditions, which decrease the global efficiency of ORC installations, e.g. in the case of waste heat recovery. In order to characterize the performance of a positive displacement expander close enough to the optimum, the influence of pressure ratios, filling factor, and working fluid properties on power output is studied. In this paper, experimental results obtained on a small-scale ORC test setup based on an 11 kWe single-screw expander are presented. Two working fluids are used during the tests, i.e. R245fa and SES36 (Solkatherm). These working fluids are common for ORC installations exploiting low-temperature waste heat. The waste heat source is simulated by an electrically heated thermal oil loop with adjustable temperature and flow rate. Various waste heat inlet flow rates are considered in order to find an optimal evaporation pressure and to maximize the power output with different heat source profiles. Based on the experimental data, the expander model is developed. For each working fluid, optimal working conditions are determined. In most cases, there is under-expansion due to a relatively small built-in volume ratio, causing certain losses. By means of the model, the ideal expansion process is simulated and compared with the real one obtained experimentally to quantify these losses and conclusions can be drawn whether significant benefits can be offered by using an optimized expander instead of an ”off-the-shelf” reversed compressor