NASA Integrated Model-Centric Architecture (NIMA) model use and re-use

Conroy, Mike; Mazzone, Rebecca; Wang, Lin

doi:10.1109/aero.2013.6497424

Cited by 4 publications

(4 citation statements)

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“…SE as a discipline is involved throughout the lifecycle of a project and thus should involve communicating with multiple subunits. A high level of communication is necessary within the SE group, and between related functions for a given project 21,22 . So in order to gain all the advantages MBSE has to offer, the organizational form has to be adjusted 23 .…”

Section: Discussionmentioning

confidence: 99%

“…A high level of communication is necessary within the SE group, and between related functions for a given project. 21,22 So in order to gain all the advantages MBSE has to offer, the organizational form has to be adjusted. 23 According to Kellner et al, 23 "walls and borders" between different subunits need to be broken up to create a cohesive team where all disciplines are involved from the start of a project.…”

Section: Integrationmentioning

confidence: 99%

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MBSE adoption experiences in organizations: Lessons learned

Henderson,

McDermott,

Salado

2023

Systems Engineering

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Lessons learned through MBSE adoption efforts is one of the key ways of communicating best practices and recommendations for MBSE. This study compiles lessons learned from published case studies and practitioner interviews. Lessons are summarized into categories such as adoption strategy, modeling practices, and communication. This paper provides a source for future adopters of MBSE to review best practices and recommendations from a multitude of different experiences. This should improve the adoption and implementation of MBSE.

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Section: Discussionmentioning

confidence: 99%

Section: Integrationmentioning

confidence: 99%

MBSE adoption experiences in organizations: Lessons learned

Henderson,

McDermott,

Salado

2023

Systems Engineering

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“…The Science Mission Directorate sponsored the first fault management (FM) workshop (Fesq, Fretz, and Newhouse, 2013) to identify and characterize the problems faced by recent missions; a follow-on FM workshop was held on April 9-12, 2012. Finally, NASA's Office of the Chief Engineer has convened the NASA Integrated Model-centric Architecture (Conroy, Mazzone, and Lin, 2013) activity to leverage the game-changing potential of model-based systems engineering as a means to conquer system complexity. Each of these efforts targets a different aspect of the broader resilience challenge.…”

Section: Technical Motivation and Opportunitiesmentioning

confidence: 99%

Engineering Resilient Space Systems

Day¹,

Ingham²,

Murray³

et al. 2015

INSIGHT

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Several distinct trends will influence space exploration missions in the next decade. Destinations are becoming more remote and mysterious, science questions more sophisticated, and, as mission experience accumulates, the most accessible targets are visited, advancing the knowledge frontier to more difficult, harsh, and inaccessible environments. This leads to new challenges including: hazardous conditions that limit mission lifetime, such as high radiation levels surrounding interesting destinations like Europa or toxic atmospheres of planetary bodies like Venus; unconstrained environments with navigation hazards, such as free-floating active small bodies; multielement missions required to answer more sophisticated questions, such as Mars Sample Return (MSR); and long-range missions, such as Kuiper belt exploration, that must survive equipment failures over the span of decades. These missions will need to be successful without a priori knowledge of the most efficient data collection techniques for optimum science return. Science objectives will have to be revised 'on the fly', with new data collection and navigation decisions on short timescales. Yet, even as science objectives are becoming more ambitious, several critical resources remain unchanged. Since physics imposes insurmountable light-time delays, anticipated improvements to the Deep Space Network (DSN) will only marginally improve the bandwidth and communications cadence to remote spacecraft. Fiscal resources are increasingly limited, resulting in fewer flagship missions, smaller spacecraft, and less subsystem redundancy. As missions visit more distant and formidable locations, the job of the operations team becomes more challenging, seemingly inconsistent with the trend of shrinking mission budgets for operations support. How can we continue to explore challenging new locations without increasing risk or system complexity? These challenges are present, to some degree, for the entire Decadal Survey mission portfolio, as documented in Vision and Voyages for Planetary Science in the

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“…In MBSE, quantitative evaluations are usually applied to help improve the design scheme of the spacecraft. One of the mature MBSE applications is conducted by NASA, who developed an MBSE infrastructure [4] and applied it to help design CubeSat [5], James Weber Space Telescope [6], and the MARS 2020 project [7].…”

Section: Introductionmentioning

confidence: 99%

Multi-Granularity Genetic Programming Optimization Method for Satellite System Topology and Parameter

Dong²

2021

IEEE Access

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Granular computing is usually considered as a representative method for solving complex problems, which can be solved quickly through freely switching among different granular models. In this paper, a genetic programming method based on the concept of granular computing is proposed to provide an efficient solution for optimizing the topology and parameters of a satellite system simultaneously. According to the coupling relationship of multiple physical fields, the multi-granularity description method of the satellite system scheme is defined and a multi-granularity digital satellite model is constructed. The genetic programming method is improved according to the principle of falsity preserving in granular computing. The concept and calculation method of granular risk factor are proposed to allow different individuals of the current population to switch among different granularities. The convergence difficulty caused by the complexity, hugeness and high integration of satellites is effectively alleviated. The application to design and optimize an earth observation satellite proves the effectiveness of the proposed method.

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NASA Integrated Model-Centric Architecture (NIMA) model use and re-use

Cited by 4 publications

References 0 publications

MBSE adoption experiences in organizations: Lessons learned

MBSE adoption experiences in organizations: Lessons learned

Engineering Resilient Space Systems

Multi-Granularity Genetic Programming Optimization Method for Satellite System Topology and Parameter

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