7 research outputs found

    Communication of Simulation and Modelling Activities in Early Systems Engineering

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    In this paper we present a framework that aids and supports communication of modeling and simulation activities in early systems engineering. We do this by analyzing existing simulation and modelling frameworks, both in systems engineering as well as more generic frameworks. For each framework, we discuss its purpose, main outcomes and the tools and methods used in the framework. Using this overview, we argue that in order to apply simulation and modeling techniques fully in conceptual systems design, it is necessary to use a framework focused on communication and aimed at four key issues. We extract a generic process from the discussed frameworks and discuss for each step of this process how these issues should be addressed. We also explain how this framework should be supported with tooling. Finally we discuss a simulation study of a medical imaging system that gave us initial experiences on the approach presented here. We conclude that this framework shows promise in supporting the communication of a modeling and simulation study in a multidisciplinary settin

    Towards automating the sizing process in conceptual (airframe) systems architecting

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    Presented is a method for automated sizing of airframe systems, ultimately aiming to enable an efficient and interactive systems architecture evaluation process. The method takes as input the logical view of the system architecture. A source-sink approach combined with a Design Structure Matrix (DSM) sequencing algorithm is used to orchestrate the sequence of the sub-system sizing tasks. Bipartite graphs and a maximum matching algorithm are utilized to identify and construct the computational sizing workflows. A recursive algorithm, based on fundamental dimensions of additive physical quantities (e.g., weight, power, etc.) is employed to aggregate variables at the system level. The evaluation, based on representative test cases confirmed the correctness of the proposed method. The results also showed that the proposed approach overcomes certain limitations of existing methods and looks very promising as an initial systems architectural design enabler

    Executable Architectures Using Cuckoo Search Optimization Coupled with OPM and CPN-A Module: A New Meta-Architecture Model for FILA SoS

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    Understanding System of Systems (SoS) requires novel ways to apply systems engineering processes. Acknowledged SoS have recognized objectives, a designated manager and resources for the SoS. The goal of this research is to develop a proof of concept tool suite for Acknowledged SoS systems simulation. This suite is named flexible, intelligent and learning architectures for System of Systems (FILA-SoS). FILA-SoS assists the SoS manager in architecture generation, selection, and implementation working as an aid for decision making. Binary cuckoo search constrained optimization is used to generate meta-architectures which are evaluated by a fuzzy assessor for quality assurance. The architecture is then converted into an executable structure using Object Process Methodology (OPM) and Colored Petri Nets (CPN). A hybrid methodology comprising of OPM and CPN approach is implemented for simulating the acquisition environment. Initial application for a Search and Rescue (SAR) SoS, consisting of 25 individual systems with ten capabilities gave promising results

    Flexible and Intelligent Learning Architectures for SOS (FILA-SoS)

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    Multi-faceted systems of the future will entail complex logic and reasoning with many levels of reasoning in intricate arrangement. The organization of these systems involves a web of connections and demonstrates self-driven adaptability. They are designed for autonomy and may exhibit emergent behavior that can be visualized. Our quest continues to handle complexities, design and operate these systems. The challenge in Complex Adaptive Systems design is to design an organized complexity that will allow a system to achieve its goals. This report attempts to push the boundaries of research in complexity, by identifying challenges and opportunities. Complex adaptive system-of-systems (CASoS) approach is developed to handle this huge uncertainty in socio-technical systems

    Application of Executable Architecture in Early Concept Evaluation using the DoD Architecture Framework

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    The increasing complexity in the development of today\u27s modern warfighting systems demands a systematic evaluation approach in the assessment of the envisaged capability and estimating the cost effectiveness, especially in the early stages of Concept Development. This research focused on the development of early Concept evaluation methodology through the use of Executable Architecture (EA) through the System Architecting process. Particularly, the methodology was applied in the assessment of a proposed Multi-tiered Unmanned Aircraft System System-of-System that is designed provide target acquisition and conduct dynamic strike on Theater Ballistic Missile launchers. Through the implementation of the evaluation methodology using dynamic modeling of the system-under-design, the research was able to provide quantitative assessment of different design parameters on the overall system effectiveness, as measured using a set of pre-determined Measures-of-Effectiveness. Specifically, Innoslate was used to develop the EA model of a fictitious multi-tier Unmanned Aircraft System System-of-Systems, and provided quantitative assessment of the overall system performance due to changes in the design parameters. Specification, the research showed that the proposed evaluation methodology provides system architects with the tool to 1) evaluate different design parameters, 2) understand the overall system capability given sub-system capabilities, and 3) determine sub-system requirement given desired system performance

    Computational intelligence based complex adaptive system-of-systems architecture evolution strategy

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    The dynamic planning for a system-of-systems (SoS) is a challenging endeavor. Large scale organizations and operations constantly face challenges to incorporate new systems and upgrade existing systems over a period of time under threats, constrained budget and uncertainty. It is therefore necessary for the program managers to be able to look at the future scenarios and critically assess the impact of technology and stakeholder changes. Managers and engineers are always looking for options that signify affordable acquisition selections and lessen the cycle time for early acquisition and new technology addition. This research helps in analyzing sequential decisions in an evolving SoS architecture based on the wave model through three key features namely; meta-architecture generation, architecture assessment and architecture implementation. Meta-architectures are generated using evolutionary algorithms and assessed using type II fuzzy nets. The approach can accommodate diverse stakeholder views and convert them to key performance parameters (KPP) and use them for architecture assessment. On the other hand, it is not possible to implement such architecture without persuading the systems to participate into the meta-architecture. To address this issue a negotiation model is proposed which helps the SoS manger to adapt his strategy based on system owners behavior. This work helps in capturing the varied differences in the resources required by systems to prepare for participation. The viewpoints of multiple stakeholders are aggregated to assess the overall mission effectiveness of the overarching objective. An SAR SoS example problem illustrates application of the method. Also a dynamic programing approach can be used for generating meta-architectures based on the wave model. --Abstract, page iii

    Search-based system architecture development using a holistic modeling approach

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    This dissertation presents an innovative approach to system architecting where search algorithms are used to explore design trade space for good architecture alternatives. Such an approach is achieved by integrating certain model construction, alternative generation, simulation, and assessment processes into a coherent and automated framework. This framework is facilitated by a holistic modeling approach that combines the capabilities of Object Process Methodology (OPM), Colored Petri Net (CPN), and feature model. The resultant holistic model can not only capture the structural, behavioral, and dynamic aspects of a system, allowing simulation and strong analysis methods to be applied, it can also specify the architectural design space. Both object-oriented analysis and design (OOA/D) and domain engineering were exploited to capture design variables and their domains and define architecture generation operations. A fully realized framework (with genetic algorithms as the search algorithm) was developed. Both the proposed framework and its suggested implementation, including the proposed holistic modeling approach and architecture alternative generation operations, are generic. They are targeted at systems that can be specified using object-oriented or process-oriented paradigm. The broad applicability of the proposed approach is demonstrated on two examples. One is the configuration of reconfigurable manufacturing systems (RMSs) under multi-objective optimization and the other is the architecture design of a manned lunar landing system for the Apollo program. The test results show that the proposed approach can cover a huge number of architecture alternatives and support the assessment of several performance measures. A set of quality results was obtained after running the optimization algorithm following the proposed framework --Abstract, page iii
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