David Kaslow

Applying Model Based Systems Engineering (MBSE) to a standard CubeSat

Model Based Systems Engineering (MBSE) is an emerging technology that is providing the next advance in modeling and systems engineering. MBSE uses Systems Modeling Language (SysML) as its modeling language. SysML is a domain-specific modeling language for systems engineering used to specify, analyze, design, optimize, and verify systems. An MBSE Challenge project was established to model a hypothetical FireSat satellite system to evaluate the suitability of SysML for describing space systems. Although much was learned regarding modeling of this system, the fictional nature of the FireSat system precluded anyone from actually building the satellite. Thus, the practical use of the model could not be demonstrated or verified. This paper reports on using MBSE and SysML to model a standard CubeSat and applying that model to an actual CubeSat mission, the Radio Aurora Explorer (RAX) mission, developed by the Michigan Exploration Lab (MXL) and SRI International.

Integrated model-based systems engineering (MBSE) applied to the Simulation of a CubeSat mission

Small satellite missions are becoming increasingly complex as scientists and engineers propose to utilize them to accomplish more ambitious science and technology goals. Small satellites such as CubeSats are challenging to design because they have limited resources, coupled subsystems, and must operate in dynamic environments. Model Based Systems Engineering (MBSE) is a key practice to advance systems engineering that can benefit CubeSat missions. MBSE creates a system model that helps integrate other discipline specific engineering models and simulations. The system level model is initiated at the start of a project and evolves throughout development. It provides a cohesive and consistent source of system requirements, design, analysis, and verification. This paper describes an integrated, executable MBSE representation of the Radio Aurora Explorer (RAX) CubeSat mission. The purpose of the RAX mission is to study the formation of magnetic field-aligned electron density irregularities in the Earths ionosphere, which are known to disrupt tracking and communication between Earth and orbiting spacecraft. The RAX CubeSat model describes the configuration and properties for various systems and subsystems, and is capable of executing behavior and parametric models for analyzing subsystem functions and states of the spacecraft. It is comprised of a SysML model created with MagicDraw®, a set of analytical models developed in MATLAB®, and a high fidelity space system simulation model created in STK®. ModelCenter was used to integrate the analytical and simulation models. The integrated analyses were linked to the SysML model using MBSE Analyzer, a bridge between SysML tools and ModelCenter. Behavioral models were executed for a representative RAX mission to study energy state and data collection capabilities. This work was undertaken to demonstrate the power, scalability, and utility of MBSE tools and methods that are available to help meet the challenge of designing spacecraft missions of ever-increasing complexity. The RAX CubeSat model will be made available to the academic community for further study and potential extension for more complex missions.

Model based systems engineering (MBSE) applied to Radio Aurora Explorer (RAX) CubeSat mission operational scenarios

Small satellites are more highly resource-constrained by mass, power, volume, delivery timelines, and financial cost relative to their larger counterparts. Small satellites are operationally challenging because subsystem functions are coupled and constrained by the limited available commodities (e.g. data, energy, and access times to ground resources). Furthermore, additional operational complexities arise because small satellite components are physically integrated, which may yield thermal or radio frequency interference. In this paper, we extend our initial Model Based Systems Engineering (MBSE) framework developed for a small satellite mission by demonstrating the ability to model different behaviors and scenarios. We integrate several simulation tools to execute SysML-based behavior models, including subsystem functions and internal states of the spacecraft. We demonstrate utility of this approach to drive the system analysis and design process. We demonstrate applicability of the simulation environment to capture realistic satellite operational scenarios, which include energy collection, the data acquisition, and downloading to ground stations. The integrated modeling environment enables users to extract feasibility, performance, and robustness metrics. This enables visualization of both the physical states (e.g. position, attitude) and functional states (e.g. operating points of various subsystems) of the satellite for representative mission scenarios. The modeling approach presented in this paper offers satellite designers and operators the opportunity to assess the feasibility of vehicle and network parameters, as well as the feasibility of operational schedules. This will enable future missions to benefit from using these models throughout the full design, test, and fly cycle. In particular, vehicle and network parameters and schedules can be verified prior to being implemented, during mission operations, and can also be updated in near real-time with operational performance feedback.

Developing a CubeSat Model-Based System Engineering (MBSE) reference model — Interim status #2

Model-Based Systems Engineering (MBSE) is a key practice to advance the systems engineering discipline. The International Council on Systems Engineering (INCOSE) established the MBSE Initiative to promote, advance, and institutionalize the practice of MBSE. As part of this effort, the INCOSE Space Systems Working Group (SSWG) Challenge Team has been investigating the applicability of MBSE for designing CubeSats since 2011. The goal of the team is to provide a sufficiently complete CubeSat Reference Model that can be adapted to any CubeSat project. The INCOSE Systems Engineering Vision 2020 defines MBSE as “the formalized application of modeling to support system requirements, design, analysis, verification and validation activities beginning in the conceptual design phase and continuing throughout development and later life cycle phases.” At the core of MBSE is the development of the system model that helps integrate other discipline-specific engineering models and simulations. The team has been creating this system model by capturing all aspects of a CubeSat project using the Systems Modeling Language (SysML), which is a graphical modeling language for systems engineering. SysML diagrams are used to describe requirements, structures, behaviors, and parametrics from the system level down to the component level. Requirements and design are contained in the model rather than in a series of independent engineering artifacts. In the past three phases of the project, the team has created the initial iteration of the reference model, applied it to the Radio Aurora Explorer (RAX) mission, executed simulations of system behaviors, interfaced with commercial simulation tools, and demonstrated how behaviors and constraint equations can be executed to perform operational trade studies. The modeling effort starts anew in this fourth phase. The CubeSat Reference Model starts with an identification of potential stakeholders. A stakeholder is any entity that has an interest in the system including sponsor, end user, procurer, supplier, and regulatory agencies. The each stakeholders needs, objectives, constraints, and measures of effectiveness are incorporated in the model. Constraints are those items fixed and not subject to trades such as mission budget and schedule. One of the stakeholders is the Cal Poly CubeSat project. The Cal Poly CubeSat Specification has been populated into its own SysML model to enable the content of the specification to be related to the CubeSat Reference Model. The CubeSat mission enterprise consists of the space system, ground system, launch services, launch vehicle interface system, and communication services. Since the reference model is being developed by a team effort, there is an obligation to protect the investment of time and knowledge of each team member. There also needs to be a licensing environment that is conducive to a user organization supporting the development of and use of the model. There will be a license that allows for non-commercial use and prohibits incorporating the model or model features into a commercial product.

Enterprise modeling for CubeSats

Understanding the business aspect of a project or mission is of key importance in spacecraft systems engineering, including the mission cost, high level functions and objectives, workforce, hardware, and production of spacecraft. This is especially true for CubeSat missions, which typically deal with low costs, limited resources, low mass, low volume, and low power. Introducing enterprise modeling concepts to CubeSat missions allows for incorporation of analysis of cost, business processes, and requirements for the missions spacecraft and problem domain. The following describes an application of enterprise modeling to CubeSats.

Planning and Scheduling of Earth Observing Satellites

The roles and interactions of activity planning and scheduling for Earth Observing Satellites are based on factors such as mission objective, system assets and resources, system and spacecraft constraints, planning criteria, scheduling strategies, timelines, and desired level of automation and operator interaction. Activities are generalized into four categories: accomplish the mission objective, support the mission objective, manage the system resources, and maintain the system assets. This paper discusses factors that influence the planning and scheduling design and design complexities. Included is how the design addresses modeling of the spacecraft subsystems and states when incorporating spacecraft capabilities, constraints and operating guidelines.

A Model-Based Systems Engineering (MBSE) approach for defining the behaviors of CubeSats

This paper describes an eight-step approach for defining the behaviors of CubeSats that begins with mission requirements and ends with a functional architecture modeled as an activity hierarchy using the Object Management Groups (OMG) Systems Modeling Language (SysML). This approach could be applied to other satellite development efforts but the emphasis here is on CubeSats because of their historically high mission failure rate and the rapid growth in the number of these missions over the last few years. In addition, this approach complements the International Council on Systems Engineerings (INCOSE) Space Systems Working Groups (SSWG) efforts to develop a CubeSat Reference Model. This approach provides a repeatable, generalized method for CubeSat development teams to follow that incorporates standard systems engineering practices such as: a top-down approach, requirements analysis, use case development, and functional analysis. This effort uses a Model-Based Systems Engineering (MBSE) approach. Some of the benefits of using an MBSE approach over a traditional document-based approach are: enhanced communications, reduced development risk, improved quality, and enhanced knowledge transfer [1]. Systems engineering artifacts produced using this approach, such as definitions of the mission domain elements, requirements, use cases, and activities, are captured in a system model which serves as a single-source-of-truth for members of the CubeSat development team. Examples are provided throughout the paper which illustrates the application of this approach to a CubeSat development effort. Since most space missions are concerned with the generation or flow of information, the examples focus on requirements to collect and distribute mission data ending with a definition of the required system functionality to satisfy those requirements.

CubeSat Model Based System Engineering (MBSE) Reference Model - Development and Distribution - Interim Status #3

Model-Based Systems Engineering (MBSE) is a key practice to advance systems engineering that can benefit CubeSat missions. MBSE involves creating a system model that is a single source for systems engineering such as architecture development and interface management. The system model can also integrate other discipline specific engineering models and simulations. Our application of MBSE uses Systems Modeling Language (SysML), which is a graphical modeling language, to model all aspects of a system either directly or through an interface with another model. SysML diagrams are used to describe requirements, structures, behaviors, and parametrics from the system down to the component level. The model is intended for use by aerospace students in their classroom or by a team building a mission-specific CubeSat. The model is being developed by the Space Systems Working Group (SSWG) of the International Council on Systems Engineering (INCOSE). This paper provides an overview of the model development, architecture, and application; and it outlines the current direction of the SSWG.

COTS Implementation of a Sensor Planning Service GetFeasibility operation - Interim status #2

This paper reports on the progress of the design and implementation of a Web-based Sensor Planning Service (SPS) that provides GetCapabilities, DescribeTasking and GetFeasibility operations for optical and radar Earth imaging spacecraft. The design is founded on Analytical Graphics COTS Components capabilities and Standard Object Catalog (SOC).

COTS implementation of a Sensor Planning Service GetFeasibility operation

This paper reports on the status of a design of a Web-based service that determines the feasibility of a sensor tasking request. The design is based on Commercial Off The Shelf (COTS) capabilities from Analytical Graphics, Inc. (AGI). It is intended for application within a Sensor Planning Service. This Web-based service utilizes the open source parameters employed by the operations, as delineated in the OpenGIS® Sensor Planning Service Implementation Specification. A by-product of the design of this service is a recommendation of additional open-source sensor and tasking parameters.