Applications of graph transformation in tools for domain-specific modeling languages

The use of domain-specific languages (DSLs) has been proposed as an approach to cost-e ectively develop families of software systems in a restricted application domain. Domain-specific languages in combination with the accumulated knowledge and experience of previous implementations, can in turn be used to generate new applications with unique sets of requirements. For this reason, DSLs are considered to be an important approach for software reuse. However, the toolset supporting a particular domain-specific language is also domain-specific and is per definition not reusable. Therefore, creating and maintaining a DSL requires additional resources that could be even larger than the savings associated with using them. As a solution, di erent tool frameworks have been proposed to simplify and reduce the cost of developments of DSLs. Developers of tool support for DSLs need to instantiate, customize or configure the framework for a particular DSL. There are di erent approaches for this. An approach is to use an application programming interface (API) and to extend the basic framework using an imperative programming language. An example of a tools which is based on this approach is Eclipse GEF. Another approach is to configure the framework using declarative languages that are independent of the underlying framework implementation. We believe this second approach can bring important benefits as this brings focus to specifying what should the tool be like instead of writing a program specifying how the tool achieves this functionality. In this thesis we explore this second approach. We use graph transformation as the basic approach to customize a domain-specific modeling (DSM) tool framework. The contributions of this thesis includes a comparison of di erent approaches for defining, representing and interchanging software modeling languages and models and a tool architecture for an open domain-specific modeling framework that e ciently integrates several model transformation components and visual editors. We also present several specific algorithms and tool components for DSM framework. These include an approach for graph query based on region operators and the star operator and an approach for reconciling models and diagrams after executing model transformation programs. We exemplify our approach with two case studies MICAS and EFCO. In these studies we show how our experimental modeling tool framework has been used to define tool environments for domain-specific languages.

Design Aspects of Megawatt-Range Direct-Driven Permanent MagnetWind Generators

Direct-driven permanent magnet synchronous generator is one of the most promising topologies for megawatt-range wind power applications. The rotational speed of the direct-driven generator is very low compared with the traditional electrical machines. The low rotational speed requires high torque to produce megawatt-range power. The special features of the direct-driven generators caused by the low speed and high torque are discussed in this doctoral thesis. Low speed and high torque set high demands on the torque quality. The cogging torque and the load torque ripple must be as low as possible to prevent mechanical failures. In this doctoral thesis, various methods to improve the torque quality are compared with each other. The rotor surface shaping, magnet skew, magnet shaping, and the asymmetrical placement of magnets and stator slots are studied not only by means of torque quality, but also the effects on the electromagnetic performance and manufacturability of the machine are discussed. The heat transfer of the direct-driven generator must be designed to handle the copper losses of the stator winding carrying high current density and to keep the temperature of the magnets low enough. The cooling system of the direct-driven generator applying the doubly radial air cooling with numerous radial cooling ducts was modeled with a lumped-parameter-based thermal network. The performance of the cooling system was discussed during the steady and transient states. The effect of the number and width of radial cooling ducts was explored. The large number of radial cooling ducts drastically increases the impact of the stack end area effects, because the stator stack consists of numerous substacks. The effects of the radial cooling ducts on the effective axial length of the machine were studied by analyzing the crosssection of the machine in the axial direction. The method to compensate the magnet end area leakage was considered. The effect of the cooling ducts and the stack end area effects on the no-load voltages and inductances of the machine were explored by using numerical analysis tools based on the three-dimensional finite element method. The electrical efficiency of the permanent magnet machine with different control methods was estimated analytically over the whole speed and torque range. The electrical efficiencies achieved with the most common control methods were compared with each other. The stator voltage increase caused by the armature reaction was analyzed. The effect of inductance saturation as a function of load current was implemented to the analytical efficiency calculation.

Identification of Some Additional Loss Components in High-Power Low-Voltage Permanent Magnet Generators

Permanent magnet generators (PMG) represent the cutting edge technology in modern wind mills. The efficiency remains high (over 90%) at partial loads. To improve the machine efficiency even further, every aspect of machine losses has to be analyzed. Additional losses are often given as a certain percentage without providing any detailed information about the actual calculation process; meanwhile, there are many design-dependent losses that have an effect on the total amount of additional losses and that have to be taken into consideration. Additional losses are most often eddy current losses in different parts of the machine. These losses are usually difficult to calculate in the design process. In this doctoral thesis, some additional losses are identified and modeled. Further, suggestions on how to minimize the losses are given. Iron losses can differ significantly between the measured no-load values and the loss values under load. In addition, with embedded magnet rotors, the quadrature-axis armature reaction adds losses to the stator iron by manipulating the harmonic content of the flux. It was, therefore, re-evaluated that in salient pole machines, to minimize the losses and the loss difference between the no-load and load operation, the flux density has to be kept below 1.5 T in the stator yoke, which is the traditional guideline for machine designers. Eddy current losses may occur in the end-winding area and in the support structure of the machine, that is, in the finger plate and the clamping ring. With construction steel, these losses account for 0.08% of the input power of the machine. These losses can be reduced almost to zero by using nonmagnetic stainless steel. In addition, the machine housing may be subjected to eddy current losses if the flux density exceeds 1.5 T in the stator yoke. Winding losses can rise rapidly when high frequencies and 10–15 mm high conductors are used. In general, minimizing the winding losses is simple. For example, it can be done by dividing the conductor into transposed subconductors. However, this comes with the expense of an increase in the DC resistance. In the doctoral thesis, a new method is presented to minimize the winding losses by applying a litz wire with noninsulated strands. The construction is the same as in a normal litz wire but the insulation between the subconductors has been left out. The idea is that the connection is kept weak to prevent harmful eddy currents from flowing. Moreover, the analytical solution for calculating the AC resistance factor of the litz-wire is supplemented by including an end-winding resistance in the analytical solution. A simple measurement device is developed to measure the AC resistance in the windings. In the case of a litz-wire with originally noninsulated strands, vacuum pressure impregnation (VPI) is used to insulate the subconductors. In one of the two cases studied, the VPI affected the AC resistance factor, but in the other case, it did not have any effect. However, more research is needed to determine the effect of the VPI on litz-wire with noninsulated strands. An empirical model is developed to calculate the AC resistance factor of a single-layer formwound winding. The model includes the end-winding length and the number of strands and turns. The end winding includes the circulating current (eddy currents that are traveling through the whole winding between parallel strands) and the main current. The end-winding length also affects the total AC resistance factor.

Properties and algorithms of the hyper-star graph and its related graphs

The hyper-star interconnection network was proposed in 2002 to overcome the drawbacks of the hypercube and its variations concerning the network cost, which is defined by the product of the degree and the diameter. Some properties of the graph such as connectivity, symmetry properties, embedding properties have been studied by other researchers, routing and broadcasting algorithms have also been designed. This thesis studies the hyper-star graph from both the topological and algorithmic point of view. For the topological properties, we try to establish relationships between hyper-star graphs with other known graphs. We also give a formal equation for the surface area of the graph. Another topological property we are interested in is the Hamiltonicity problem of this graph. For the algorithms, we design an all-port broadcasting algorithm and a single-port neighbourhood broadcasting algorithm for the regular form of the hyper-star graphs. These algorithms are both optimal time-wise. Furthermore, we prove that the folded hyper-star, a variation of the hyper-star, to be maixmally fault-tolerant.

Automatic Inference of Graph Models for Complex Networks with Genetic Programming

Complex networks can arise naturally and spontaneously from all things that act as a part of a larger system. From the patterns of socialization between people to the way biological systems organize themselves, complex networks are ubiquitous, but are currently poorly understood. A number of algorithms, designed by humans, have been proposed to describe the organizational behaviour of real-world networks. Consequently, breakthroughs in genetics, medicine, epidemiology, neuroscience, telecommunications and the social sciences have recently resulted. The algorithms, called graph models, represent significant human effort. Deriving accurate graph models is non-trivial, time-intensive, challenging and may only yield useful results for very specific phenomena. An automated approach can greatly reduce the human effort required and if effective, provide a valuable tool for understanding the large decentralized systems of interrelated things around us. To the best of the author's knowledge this thesis proposes the first method for the automatic inference of graph models for complex networks with varied properties, with and without community structure. Furthermore, to the best of the author's knowledge it is the first application of genetic programming for the automatic inference of graph models. The system and methodology was tested against benchmark data, and was shown to be capable of reproducing close approximations to well-known algorithms designed by humans. Furthermore, when used to infer a model for real biological data the resulting model was more representative than models currently used in the literature.

Network Similarity Measures and Automatic Construction of Graph Models using Genetic Programming

A complex network is an abstract representation of an intricate system of interrelated elements where the patterns of connection hold significant meaning. One particular complex network is a social network whereby the vertices represent people and edges denote their daily interactions. Understanding social network dynamics can be vital to the mitigation of disease spread as these networks model the interactions, and thus avenues of spread, between individuals. To better understand complex networks, algorithms which generate graphs exhibiting observed properties of real-world networks, known as graph models, are often constructed. While various efforts to aid with the construction of graph models have been proposed using statistical and probabilistic methods, genetic programming (GP) has only recently been considered. However, determining that a graph model of a complex network accurately describes the target network(s) is not a trivial task as the graph models are often stochastic in nature and the notion of similarity is dependent upon the expected behavior of the network. This thesis examines a number of well-known network properties to determine which measures best allowed networks generated by different graph models, and thus the models themselves, to be distinguished. A proposed meta-analysis procedure was used to demonstrate how these network measures interact when used together as classifiers to determine network, and thus model, (dis)similarity. The analytical results form the basis of the fitness evaluation for a GP system used to automatically construct graph models for complex networks. The GP-based automatic inference system was used to reproduce existing, well-known graph models as well as a real-world network. Results indicated that the automatically inferred models exemplified functional similarity when compared to their respective target networks. This approach also showed promise when used to infer a model for a mammalian brain network.

Object-Oriented Genetic Programming for the Automatic Inference of Graph Models for Complex Networks

Complex networks are systems of entities that are interconnected through meaningful relationships. The result of the relations between entities forms a structure that has a statistical complexity that is not formed by random chance. In the study of complex networks, many graph models have been proposed to model the behaviours observed. However, constructing graph models manually is tedious and problematic. Many of the models proposed in the literature have been cited as having inaccuracies with respect to the complex networks they represent. However, recently, an approach that automates the inference of graph models was proposed by Bailey [10] The proposed methodology employs genetic programming (GP) to produce graph models that approximate various properties of an exemplary graph of a targeted complex network. However, there is a great deal already known about complex networks, in general, and often specific knowledge is held about the network being modelled. The knowledge, albeit incomplete, is important in constructing a graph model. However it is difficult to incorporate such knowledge using existing GP techniques. Thus, this thesis proposes a novel GP system which can incorporate incomplete expert knowledge that assists in the evolution of a graph model. Inspired by existing graph models, an abstract graph model was developed to serve as an embryo for inferring graph models of some complex networks. The GP system and abstract model were used to reproduce well-known graph models. The results indicated that the system was able to evolve models that produced networks that had structural similarities to the networks generated by the respective target models.

A Note On Some Domination Parameters in Graph Products

In this paper, we study the domination number, the global dom ination number, the cographic domination number, the global co graphic domination number and the independent domination number of all the graph products which are non-complete extended p-sums (NEPS) of two graphs.

The P3 Intersection Graph

We define a new graph operator called the P3 intersection graph, P3(G)- the intersection graph of all induced 3-paths in G. A characterization of graphs G for which P-3 (G) is bipartite is given . Forbidden subgraph characterization for P3 (G) having properties of being chordal , H-free, complete are also obtained . For integers a and b with a > 1 and b > a - 1, it is shown that there exists a graph G such that X(G) = a, X(P3( G)) = b, where X is the chromatic number of G. For the domination number -y(G), we construct graphs G such that -y(G) = a and -y (P3(G)) = b for any two positive numbers a > 1 and b. Similar construction for the independence number and radius, diameter relations are also discussed.

The Edge C4 Graph of a Graph

Abstract. The edge C4 graph E4(G) of a graph G has all the edges of Gas its vertices, two vertices in E4(G) are adjacent if their corresponding edges in G are either incident or are opposite edges of some C4. In this paper, characterizations for E4(G) being connected, complete, bipartite, tree etc are given. We have also proved that E4(G) has no forbidden subgraph characterization. Some dynamical behaviour such as convergence, mortality and touching number are also studied

GALLAI AND ANTI-GALLAI GRAPHS OF A GRAPH

Abstract. The paper deals with graph operators-the Gallai graphs and the anti-Gallai graphs. We prove the existence of a finite family of forbidden subgraphs for the Gallai graphs and the anti-Gallai graphs to be H-free for any finite graph H. The case of complement reducible graphs-cographs is discussed in detail. Some relations between the chromatic number, the radius and the diameter of a graph and its Gallai and anti-Gallai graphs are also obtained.

Studies on some graph operators and related topics

Department of Mathematics, Cochin University of Science and Technology

Studies on Some Graph Classes

Department of Mathematics, Cochin University of Science and Technology

Studies on some generalizations of line graph and the power domination problem in graphs

Department of Mathematics, Cochin University of Science and Technology