Automated inter-model parameter connection synthesis for simulation model integration

Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 2007.Includes bibliographical references (p. 73-75).New simulation modeling environments have been developed such that multiple models can be integrated into a single model. This conglomeration of model data allows designers to better understand the physical phenomenon being modeled. Models are integrated together by creating connections between their interface parameters, referred to as parameter mapping, that are either shared by common models or flow from the output of one model to the input of a second model. However, the process of integrating simulation models together is time consuming, and this development time can outweigh the benefit of the increased understanding. This thesis presents two algorithms that are designed to automatically generate and suggest these parameter mappings. The first algorithm attempts to identify previously built integration model templates that have a similar function. Model interfaces and integration models are represented by attributed graphs. Interface graph nodes represent interface parameters and arcs relate the input and output parameters, and integration models graph nodes represent interface graphs and arc represent parametric connections between interface graph nodes.(cont.) A similarity based pattern matching algorithm initially compares interface graphs in two integration model graphs. If the interface graphs are found to match, the algorithm attempts to apply the template integration model's parameter mappings to the new integration model. The second algorithm compares model interface parameters directly. The algorithm uses similarity measures developed for the pattern matching algorithm to compare model parameters. Parameter pairs that are found to be very similar are processed using a set of model integration rules and logic and those pairs that fit these criteria are mapped together. These algorithms were both implemented in JAVA and integrated into the modeling environment DOME (Distributed Object-based Modeling Environment). A small set of simulation models were used to build both new and template integration models in DOME. Tests were conducted by recording the time required to build these integration models manually and using the two proposed algorithms. Integration times were generally ten times faster but some inconsistencies and mapping errors did occur. In general the results are very promising, but a wider variety of models should be used to test these two algorithms.by Thomas Ligon.S.M

Towards a search engine for functionally appropriate, Web-enabled models and simulations

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 2006.Includes bibliographical references (p. 100-104).New emerging modeling and simulation environments have the potential to provide easy access to design models and simulations on the Internet, much as the World Wide Web (WWW) has provided easy access to information. To support sharing, integration and reuse of web-enabled applications (design models and simulations), a search engine for functionally appropriate/similar models is needed. There are ongoing efforts to develop ontological descriptions for web content and simulation model functionality, where semantics of available services are explicitly represented using a shared knowledge representation of concepts and rules. Simulation publishers are responsible of semantically marking up the interfaces with such ontological annotations. In contrast to such an approach, this work proposes a flexible, implicit, pattern matching solution that does not require any extra annotations to accompany, the models, much as the way current web search engines operate. A learning-through-association, similarity-based approach was developed. It uses only pre-existing low-level information in web-enabled simulation interfaces-such as model and parameters names, parameter units, parameter scale, input/output structure, causality, and documentation - to synthesize templates that become archetypes for functional concepts.(cont.) Then, different interfaces are matched against templates and are classified based on how they are similar to a certain template. Newly found functionally similar interfaces can be merged into the original template, thereby both generalizing the pattern for a functional role and strengthening the most critical aspects of the pattern. This thesis also developed algorithms based on graph theory and pre-defined heuristic attributes similarity metrics. The information from model interfaces is represented using Attributed Relational Graphs (ARG), where nodes represent parameters and arcs represent causality relationships. Templates are represented as Fuzzy Attributed Relational Graphs, which are extended ARGs whose node attributes are fuzzy sets. Then, a bipartite graph-matching algorithm is used to compare graphs and the similarity between an interface and a template. Graph merging algorithm is also designed for template generalization. A prototype implementation of proposed algorithms is developed and applied to a suite of real-life engineering models. Results validate the hypothesis and demonstrated the plausibility of the approach.by Qing Cao.Ph.D

To appear in the journal of Artificial Intelligence for Engineering Design, Analysis and Manufacturing (AI EDAM) Knowledge Rich Catalog Services for Engineering Design

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