System Dynamics (SD) is an approach to modelling that has found wide application in systems modelling. Although originally rooted in the engineering discipline, SD models have been formulated for problems in diverse fields including management, health, education and the social sciences and has attracted interest from modellers with little mathematical or engineering training. Developing a valid model is of primary importance in the System Dynamics modelling process. To establish that a model produces the right behaviour for the right reasons, it is essential to ensure that the structure of the model represents the corresponding real world system. Amongst the verification procedures employed in the model building process, dimensional analysis is used to verify the syntactical correctness of the model’s equations. However, dimensional analysis is frequently not given the highest priority as a verification tool in the model building process especially among those less experienced in mathematical modelling or who lack confidence in the use of mathematics. Therefore, the potential lack of dimensional consistency within some Systems Dynamics model raises serious doubts about the validity of the model, the results generated and hence the policy decisions that follow. The aim of this research is to summarise the various problems related to validation and verification that can occur in the process of SD modelling and to suggest an alternative approach. Firstly, this research devises an algorithm, “TAID” (Tree Analysis of Influence Diagrams), which analyses influence diagrams and derives dimensionally correct equations. Secondly, a software tool “I, Model” is developed to demonstrate the utility of the algorithm. Finally the revised approach to SD modelling is evaluated to measure its impact on the learning and modelling experience of SD modellers. The outcomes of the small evaluation study indicate that the modellers preferred the TAID approach over the traditional SD modelling approach during the model implementation stage. The two principal benefits that this research can offer to the SD community are: firstly, a software tool based on this new approach that can ease the transition from a qualitative system model to a verified quantitative simulation model and thereby extend the benefits of quantitative SD modelling to a wider range of users; and, secondly, to improve the SD modelling experience of all users of SD methodology but especially for those modellers who have limited mathematical experience.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:606323 |
| Date | January 2012 |
| Creators | Komanapalli, Golda Word |
| Publisher | London South Bank University |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
Page generated in 0.0021 seconds