Database-driven hydraulic simulation of canal irrigation networks using object-oriented high-resolution methods

Canal hydraulic models can be used to understand the hydraulic behaviour of large and complex irrigation networks at low cost. A number of computational hydraulic models were developed and tested in the early 1970s and late 80s. Most were developed using finite difference schemes and procedural programming languages. In spite of the importance of these models, little progress was made on improving the numerical algorithms behind them. Software development efforts were focused more on developing the user interface rather than the core algorithm. This research develops a database-driven, object-oriented hydraulic simulation model for canal irrigation networks using modern high-resolution shock capturing techniques that are capable of handling variety of flow situations which includes trans-critical flow, shock propagation, flows through gated structures and channel networks. The technology platforms were carefully selected by taking into account a multi-user support and possible migration of the new software to a web-based one which integrates a Java-based object-oriented model with a relational database management system that is used to store network configuration and simulation parameters. The developed software is tested using a benchmark test suite formulated jointly by the Department for Environment, Food and Rural Affairs (DEFRA) and the Environment Agency (EA). A total of eight tests (seven of them adapted from the DEFRAjEA benchmark suite) were run and results compiled. The developed software has outperformed ISIS, REC-RAS and MIKE 11 in three of the benchmark tests and equally well for the other four. The outcome of this research is therefore a new category in hydraulic simulation software that uses modern shock-capturing methods fully integrated with a configurational relational database that has been fully evaluated and tested.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

A Framework for Evaluating Model-Driven Self-adaptive Software Systems

In the last few years, Model Driven Development (MDD), Component-based Software Development (CBSD), and context-oriented software have become interesting alternatives for the design and construction of self-adaptive software systems. In general, the ultimate goal of these technologies is to be able to reduce development costs and effort, while improving the modularity, flexibility, adaptability, and reliability of software systems. An analysis of these technologies shows them all to include the principle of the separation of concerns, and their further integration is a key factor to obtaining high-quality and self-adaptable software systems. Each technology identifies different concerns and deals with them separately in order to specify the design of the self-adaptive applications, and, at the same time, support software with adaptability and context-awareness. This research studies the development methodologies that employ the principles of model-driven development in building self-adaptive software systems. To this aim, this article proposes an evaluation framework for analysing and evaluating the features of model-driven approaches and their ability to support software with self-adaptability and dependability in highly dynamic contextual environment. Such evaluation framework can facilitate the software developers on selecting a development methodology that suits their software requirements and reduces the development effort of building self-adaptive software systems. This study highlights the major drawbacks of the propped model-driven approaches in the related works, and emphasise on considering the volatile aspects of self-adaptive software in the analysis, design and implementation phases of the development methodologies. In addition, we argue that the development methodologies should leave the selection of modelling languages and modelling tools to the software developers.Comment: model-driven architecture, COP, AOP, component composition, self-adaptive application, context oriented software developmen

Simulation of complex environments:the Fuzzy Cognitive Agent

The world is becoming increasingly competitive by the action of liberalised national and global markets. In parallel these markets have become increasingly complex making it difficult for participants to optimise their trading actions. In response, many differing computer simulation techniques have been investigated to develop either a deeper understanding of these evolving markets or to create effective system support tools. In this paper we report our efforts to develop a novel simulation platform using fuzzy cognitive agents (FCA). Our approach encapsulates fuzzy cognitive maps (FCM) generated on the Matlab Simulink platform within commercially available agent software. We firstly present our implementation of Matlab Simulink FCMs and then show how such FCMs can be integrated within a conceptual FCA architecture. Finally we report on our efforts to realise an FCA by the integration of a Matlab Simulink based FCM with the Jack Intelligent Agent Toolkit

A survey of agent-oriented methodologies

This article introduces the current agent-oriented methodologies. It discusses what approaches have been followed (mainly extending existing object oriented and knowledge engineering methodologies), the suitability of these approaches for agent modelling, and some conclusions drawn from the survey

Annotated bibliography of software engineering laboratory literature

An annotated bibliography of technical papers, documents, and memorandums produced by or related to the Software Engineering Laboratory is given. More than 100 publications are summarized. These publications cover many areas of software engineering and range from research reports to software documentation. This document has been updated and reorganized substantially since the original version (SEL-82-006, November 1982). All materials have been grouped into eight general subject areas for easy reference: the Software Engineering Laboratory; the Software Engineering Laboratory-software development documents; software tools; software models; software measurement; technology evaluations; Ada technology; and data collection. Subject and author indexes further classify these documents by specific topic and individual author