Development and Applications of Self-learning Simulation in Finite Element Analysis

Numerical analysis such as the finite element analysis (FEA) have been widely used to solve many engineering problems. Constitutive modelling is an important component of any numerical analysis and is used to describe the material behaviour. The accuracy and reliability of numerical analysis is greatly reliant on the constitutive model that is integrated in the finite element code. In recent years, data mining techniques such as artificial neural network (ANN), genetic programming (GP) and evolutionary polynomial regression (EPR) have been employed as alternative approach to the conventional constitutive modelling. In particular, EPR offers great advantages over other data mining techniques. However, these techniques require a large database to learn and extract the material behaviour. On the other hand, the link between laboratory or field tests and numerical analysis is still weak and more investigation is needed to improve the way that they matched each other. Training a data mining technique within the self-learning simulation framework is currently considered as one of the solutions that can be utilised to accurately represent the actual material behaviour. In this thesis an EPR based machine learning technique is utilised in the heart of the self-learning framework with an automation process which is coded in MATLAB environment. The methodology is applied to simulate different material behaviour in a number of structural and geotechnical applications. Two training strategies are used to train the EPR in the developed framework, total stress-strain and incremental stress-strain strategies. The results show that integrating EPR based models in the framework allows to learn the material response during the self-learning process and provide accurate predictions to the actual behaviour. Moreover, for the first time, the behaviour of a complex material, frozen soil, is modelled based on the EPR approach. The results of the EPR model predictions are compared with the actual data and it is shown that the proposed model can capture and reproduce the behaviour of the frozen soil with a very high accuracy. The developed EPR based self-learning methodology presents a unified approach to material modelling that can also help the user to gain a deeper insight into the behaviour of the materials. The methodology is generic and can be extended to modelling different engineering materials

VISUALIZATION OF GENETIC ALGORITHM BASED ON 2-D GRAPH TO ACCELERATE THE SEARCHING WITH HUMAN INTERVENTIONS.

The Genetic Algorithm is an area in the field of Artificial Intelligence that is founded on the principles of biological evolution. Visualization techniques help in understanding the searching behaviour of Genetic Algorithm. lt also makes possible the user interactions during the searching process. It is noted that active user intervention increases the acceleration of Genetic Algorithm towards an optimal solution. In proposed research work, the user is aided by a visualization based on the representation of multidimensional Genetic Algorithm data on 2-0 space. The aim of the proposed approach is to study the benefit of using visualization techniques to explorer Genetic Algorithm data based on gene values. The user participates in the search by proposing a new individual. This is difTerent from existing Interactive Genetic Algorithm in which selection and evaluation of solutions is done by the users. A tool termed as VIGA-20 (Visualization of Genetic Algorithm using 2-0 Graph) is implemented to accomplish this goal. This visual tool enables the display of the evolution of gene values from generation to generation to observing and analysing the behaviour of the search space with user interactions. Individuals for the next generation are selected by using the objective function. Hence, a novel humanmachine interaction is developed in the proposed approach. The efficiency of the proposed approach is evaluated by two benchmark functions. The analysis and comparison of VIGA-20 is based on convergence test against the results obtained from the Simple Genetic Algorithm. This comparison is based on the same parameters except for the interactions of the user. The application of proposed approach is the modelling the branching structures by deriving a rule from best solution of VIGA-20. The comparison of results is based on the different user's perceptions, their involvement in the VIGA-20 and the difference of the fitness convergence as compared to Simple Genetic Algorithm

Modelling and analysing user views of telecommunications services

User views of calls are modelled by behaviour trees, which are synchronised to form a network of users. High level presentations of the models are given using process algebra and an explicit theory of features, including precedences. These precedences abstractly encapsulate the possible state spaces which result from different combinations of features. The high level presentation supports incremental development of features and testing and experimentation through animation. Interactions which are not detected during the experimentation phase may be found through static analysis of the high level presentation, through dynamic analysis of the under-lying low level transition system, and through verification of temporal properties through model-checking. In each case, interactions are resolved through manipulation of the feature precedences

On interoperability and conformance assessment in service composition

The process of composing a service from other services typically involves multiple models. These models may represent the service from distinct perspectives, e.g., to model the different roles of systems involved in the service, and at distinct abstraction levels, e.g., to model the service’s capability, interface or the orchestration that implements the service. The consistency among these models needs to be maintained in order to guarantee the correctness of the composition process. Two types of consistency relations are distinguished: interoperability, which concerns the ability of different roles to interoperate, and conformance, which concerns the correct implementation of an abstract model by a more concrete model. This paper discusses the need for and use of techniques to assess interoperability and conformance in a service composition process. The paper shows how these consistency relations can be described and analysed using concepts from the COSMO framework. Examples are presented to illustrate how interoperability and conformance can be assessed