Model Based Systems Engineering (MBSE) is now widely accepted throughout the industry, from commercial to aerospace and defense. However, while we understand and accept the principles of MBSE, successful adoption and implementation is still a challenge within the industry. The migration from document‐based systems engineering processes to MBSE requires more than purchasing tools and a one‐week course on Systems Modeling Language (SysML). MBSE does not change the practice of Systems Engineering as defined in the INCOSE SE Handbook or ISO/IEEE 15288, but it does affect the way in which systems engineering processes are implemented and supported within and across organizations. Organizations adopting MBSE must address issues such as new skill and competency requirements for systems engineers, model and data management over the lifecycle of the system, and integration with other engineering tools and processes, among others. It is not a tool problem or a modeler problem. It is an enterprise problem and requires an enterprise approach. The approach must be defined and guided by an enterprise architecture, which is broader than just the engineering tools and their interfaces. It includes the enterprise strategic vision, capabilities, operational concepts, organizations, and material solutions required to achieve MBSE adoption, how they relate to one another, and their evolution over time. This paper provides a broad overview of the fundamentals of MBSE adoption and the broader effort of digital engineering transformation, presenting the digital engineering environment as a system‐of‐systems. It presents the use of enterprise architecture as a roadmap for MBSE adoption within the industry.

Complex, cyber‐physical systems must be founded on a digital blueprint that provides the most accurate representation of the system by federating information from engineering models across multiple enterprise repositories. This blueprint would serve as the digital surrogate of the system and evolve as the actual system matures across its lifecycle, from conception and design to production and operations. This paper presents a graph‐based approach for realizing the digital blueprint, which we refer to as the Total System Model. The paper is divided into five parts. Part 1 provides an introduction to use cases for model‐based systems engineering. Part 2 introduces graph concepts for the Total System Model. Part 3 provides a demonstration of the graph‐based approach using Syndeia software as a representative application. Part 4 provides a summary of this paper, and Part 5 lays out potential directions for future work.

Sand tiger sharks are an iconic large shark species held in aquaria worldwide. They rarely reproduce under managed care, with only seven aquaria reporting limited and sporadic success. For the first time in the Americas, a full-term young was born in an aquarium. The young was the result of breeding among a group of sharks purposefully brought together in 2016 for reproduction. Sharks were maintained in natural seawater and exposed to natural light and seasonal temperature fluctuations similar to their in situ counterparts. Decreased food consumption associated with breeding season and gestation was observed. Gestation time estimated from breeding observations and parturition was 321 days. Although the neonate was stillborn, this was a significant achievement. The husbandry details described within will be useful for other aquaria striving to support the reproduction of sand tiger sharks.

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