Application of model-based systems engineering on a university satellite design team

Nottage, Dustin; Corns, Steven

doi:10.1016/j.procs.2012.01.044

Cited by 3 publications

(3 citation statements)

References 2 publications

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“…An overview of multiple MBSE methodologies is summarized in Estefan (). Several research efforts including Nottage and Corns [], Delp [2008], and Spangelo et al. [2010] have applied MBSE to space systems.…”

Section: Introductionmentioning

confidence: 99%

“…An overview of multiple MBSE methodologies is summarized in Estefan (2007). Several research efforts including Nottage and Corns [2012], Delp [2008], andSpangelo et al [2010] have applied MBSE to space systems. The work presented in this article extends this previous work by integrating these MBSE principles within a disaggregated space system concept optimization framework.…”

Section: Introductionmentioning

confidence: 99%

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Disaggregated Space System Concept Optimization: Model-Based Conceptual Design Methods

et al. 2015

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Optimal design techniques have proven to be an effective systems engineering tool. Using systems architecture as the foundation, this paper explores the use of mixed variable optimization models for synthesizing and evaluating disaggregated space system concepts. Model-based conceptual design (MBCD) techniques are used to identify and assess system architectures based upon estimated system cost and performance trades. The Disaggregated Integral System Concept Optimization (DISCO) methodology is introduced, and then applied to a space-based, fire detection mission. Several results are obtained that indicate potential cost effectiveness gains from the concept design optimization of a fire detection mission. The general methodology has broad applicability for MBCD of systems, but is particularly useful for dynamic, nonlinear disaggregated space systems. C⃝ 2016 Wiley Periodicals, Inc. Syst Engin 18: 549-567, 2015

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Disaggregated Space System Concept Optimization: Model-Based Conceptual Design Methods

et al. 2015

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“…The SeaLion mission architecture team seeks to take advantage of these efficiency gains that MBSE can achieve. Space projects have been taking advantage of MBSE such as the ExoMars mission, Euclid, Galileo, and nanosatellite programs [18][19][20]. CubeSat projects have also been using MBSE and have shown to "hold promise of reducing the burden of system engineering tasks" [21] and can "promote uniformity and consistency across future CubeSat models" [21].…”

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confidence: 99%

Model Based Systems Engineering with a Docs-as-Code Approach for the SeaLion CubeSat Project

Chiu

Marquez

Asundi

2023

Systems

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The SeaLion mission architecture team sought to create a model-based systems engineering approach to assist improving CubeSat success rates as well as for the SeaLion CubeSat project to guide an implementation for the flight software. This is important because university CubeSat teams are growing in number but often have untrained students as their core personnel. This was done using a document-as-code, or docs-as-code, approach. With this the team created tools for the systems architecture with the Mach 30 Modeling Language to create an architecture that is easy to learn and use even for newly admitted team members with little to no training. These tools generate documents via its own code for easy presentation on a local file system without any proprietary software while keeping the model content format-agnostic.

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Using model‐based systems engineering as a framework for improving test and evaluation activities

Bjorkman

Sarkani

Mazzuchi

2012

Systems Engineering

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Model‐based systems engineering (MBSE) approaches are based on a paradigm shift from document‐centric engineering to model‐based engineering. Although MBSE methods are intended to apply across the entire system life cycle, one area that has not received much attention to date is the role of test and evaluation. Test and evaluation activities provide information that reduces the uncertainty about system performance, effectiveness, and suitability. This uncertainty reduction becomes particularly important within the context of defense systems, which can cost billions of dollars. This paper describes a methodology that uses an MBSE framework and Monte Carlo simulation to define uncertainty reduction goals for test planners to use in developing test strategies and detailed test designs for evaluating technical performance parameters. As tests are completed, physical models can be updated with test data and additional analyses conducted with combat models to determine if the system meets user requirements. The methodology is demonstrated through a simple case study involving a series of tests to predict the landing performance of an aircraft. ©2012 Wiley Periodicals, Inc. Syst Eng 16:

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Application of model-based systems engineering on a university satellite design team

Cited by 3 publications

References 2 publications

Disaggregated Space System Concept Optimization: Model-Based Conceptual Design Methods

Disaggregated Space System Concept Optimization: Model-Based Conceptual Design Methods

Model Based Systems Engineering with a Docs-as-Code Approach for the SeaLion CubeSat Project

Using model‐based systems engineering as a framework for improving test and evaluation activities

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