Using domain specific languages to capture design knowledge for model-based systems engineering

Design synthesis is a fundamental engineering task that involves the creation of structure from a desired functional specification; it involves both creating a system topology as well as sizing the system's components. Although the use of computer tools is common throughout the design process, design synthesis is often a task left to the designer. At the synthesis stage of the design process, designers have an extensive choice of design alternatives that need to be considered and evaluated. Designers can benefit from computational synthesis methods in the creative phase of the design process. Recent increases in computational power allow automated synthesis methods for rapidly generating a large number of design solutions. Combining an automated synthesis method with an evaluation framework allows for a more thorough exploration of the design space as well as for a reduction of the time and cost needed to design a system. To facilitate computational synthesis, knowledge about feasible system configurations must be captured. Since it is difficult to capture such synthesis knowledge about any possible system, a design domain must be chosen. In this thesis, the design domain is hydraulic systems. In this thesis, Model-Driven Software Development concepts are leveraged to create a framework to automate the synthesis of hydraulic systems will be presented and demonstrated. This includes the presentation of a domain specific language to describe the function and structure of hydraulic systems as well as a framework for synthesizing hydraulic systems using graph grammars to generate system topologies. Also, a method using graph grammars for generating analysis models from the described structural system representations is presented. This approach fits in the context of Model-Based Systems Engineering where a variety of formal models are used to represent knowledge about a system. It uses the Systems Modeling Language developed by The Object Management Group (OMG SysML™) as a unifying language for model definition.M.S.Committee Chair: Paredis, Chris; Committee Member: McGinnis, Leon; Committee Member: Schaefer, Dir

Model Continuity in Discrete Event Simulation: A Framework for Model-Driven Development of Simulation Models.

Most of the well known modeling and simulation methodologies state the importance of conceptual modeling in simulation studies and they suggest the use of conceptual models during the simulation model development process. However, only a limited number of methodologies refers to howto move from a conceptual model to an executable simulation model. Besides, existing modeling and simulation methodologies do not typically provide a formal method for model transformations between the models in different stages of the development process. Hence, in the current M&S practice, model continuity is usually not fulfilled. In this article, a model driven development framework for modeling and simulation is in order to bridge the gap between different stages of a simulation study and to obtain model continuity. The applicability of the framework is illustrated with a prototype modeling environment and a case study in the discrete event simulation domain

A Metamodeling Approach to Teaching Conceptual Modeling at Large

In the authors\u27 university there is a challenge, with respect to Conceptual Modeling topics, of bridging the gap between bachelor-level studies and research work. At bachelor-level, Conceptual Modeling is subordinated to Software Engineering topics consequently making extensive use of software design standards. However, at doctoral level or in project-based work, modeling methods must be scientifically framed within wider-scoped paradigms - Design Science, Enterprise Modeling etc. In order to bridge this gap, we developed a teaching artifact to present Conceptual Modeling as a standalone discipline that can produce its own artifacts, driven by requirements in a variety of domains. The teaching artifact is an agile modeling method that is iteratively implemented by students. The key takeaway revelation for students is that a modeling language is a knowledge schema that can be tailored and migrated for specific purposes just like a database schema, to accommodate an application domain and its modeling requirements

Functional Ontologies and Their Application to Hydrologic Modeling: Development of an Integrated Semantic and Procedural Knowledge Model and Reasoning Engine

This dissertation represents the research and development of new concepts and techniques for modeling the knowledge about the many concepts we as hydrologists must understand such that we can execute models that operate in terms of conceptual abstractions and have those abstractions translate to the data, tools, and models we use every day. This hydrologic knowledge includes conceptual (i.e. semantic) knowledge, such as the hydrologic cycle concepts and relationships, as well as functional (i.e. procedural) knowledge, such as how to compute the area of a watershed polygon, average basin slope or topographic wetness index. This dissertation is presented as three papers and a reference manual for the software created. Because hydrologic knowledge includes both semantic aspects as well as procedural aspects, we have developed, in the first paper, a new form of reasoning engine and knowledge base that extends the general-purpose analysis and problem-solving capability of reasoning engines by incorporating procedural knowledge, represented as computer source code, into the knowledge base. The reasoning engine is able to compile the code and then, if need be, execute the procedural code as part of a query. The potential advantage to this approach is that it simplifies the description of procedural knowledge in a form that can be readily utilized by the reasoning engine to answer a query. Further, since the form of representation of the procedural knowledge is source code, the procedural knowledge has the full capabilities of the underlying language. We use the term functional ontology to refer to the new semantic and procedural knowledge models. The first paper applies the new knowledge model to describing and analyzing polygons. The second and third papers address the application of the new functional ontology reasoning engine and knowledge model to hydrologic applications. The second paper models concepts and procedures, including running external software, related to watershed delineation. The third paper models a project scenario that includes integrating several models. A key advance demonstrated in this paper is the use of functional ontologies to apply metamodeling concepts in a manner that both abstracts and fully utilizes computational models and data sets as part of the project modeling process

Generating collaborative systems for digital libraries: A model-driven approach

This is an open access article shared under a Creative Commons Attribution 3.0 Licence (http://creativecommons.org/licenses/by/3.0/). Copyright @ 2010 The Authors.The design and development of a digital library involves different stakeholders, such as: information architects, librarians, and domain experts, who need to agree on a common language to describe, discuss, and negotiate the services the library has to offer. To this end, high-level, language-neutral models have to be devised. Metamodeling techniques favor the definition of domainspecific visual languages through which stakeholders can share their views and directly manipulate representations of the domain entities. This paper describes CRADLE (Cooperative-Relational Approach to Digital Library Environments), a metamodel-based framework and visual language for the definition of notions and services related to the development of digital libraries. A collection of tools allows the automatic generation of several services, defined with the CRADLE visual language, and of the graphical user interfaces providing access to them for the final user. The effectiveness of the approach is illustrated by presenting digital libraries generated with CRADLE, while the CRADLE environment has been evaluated by using the cognitive dimensions framework

Business Process Simulation: Transformation of BPMN 2.0 to Discrete Event System Specification

Theoretical modeling is a complicated characteristic of a simulation study that straight affects the quality and effectiveness of simulation projects. This paper presents a model to model transformation from a conceptual modeling language to a simulation model specification. BPMN (Business Process Model and Notation) is worn for theoretical modeling and DEVS (Discrete Event System Specification) is elected for simulation model requirement. Simulation is a dynamic feature of MDSE and which explains the need of coherent M&S formalisms for simulation activities.Accordingly, this paper presents the simulation of service systems based on DEVS models. It defines a transformation approach of BPMN models into DEVS simulation models based on the metamodel approach, and describes the enrichment of obtained DEVS models through performance indicators (time and costs)