## 4 Results
Many of the identified principles are based on metamodeling [64; 65; 66; 67; 68; 69; 70; 71; 72; 73; 74; 75], which is an origin point that determines the essence and form of creating a suitable model and applying the MBSE approach. At the metamodeling stage, an MBSE implementation plan is drawn up, which describes the planned standards for use, the structure of the model and systems, the roles of the participants, their areas of responsibility, and the semantics of the main concepts as well. All general concepts used at all levels of decomposition must be defined semantically [66; 67; 68; 69; 70; 71; 72; 73; 74; 75] to ensure the stability and interoperability of the model. This means that all concepts and terms using during model development are compatible with each other and do not have direct contradictions. However, different systems, models, and systems of systems can use different semantic definitions specific to a particular industry. To resolve possible conflicts at the metamodel level, it is recommended to provide a semantic transformation mechanism for information exchange between components with different semantic characteristics and features. The research in [79] alludes to the principles of semantics and metamodeling. The first step of the study was to develop concepts and their relationships that were gathered in a metamodel. Basically, concepts represent the elements, allowing their description, and formalize a domain. The study details the development of concepts and their relationships, which are subsequently assembled into a metamodel. It portrays concepts as crucial elements that aid in the description and formalization of a domain. While the term \"semantics\" is not explicitly mentioned, its substance aligns with the description, leading us to infer that the principle is indeed applied in the context of the study. The **stability of a system**[80; 81; 82; 83] generally means that when making small changes to the model or system, the functioning of the system as a whole will not be disturbed. In other words, with small violations of the links between the components of the system the system as a whole, it does not fail. As an example of this in an article [84], it is said that the stability could be technical features that are expected from the system as a whole, such as resilience, flexibility, and interoperability. An analysis of the application of the approach shows that it is important to provide a **hierarchy**, which involves dividing a system of systems into different levels of decomposition and nesting components within each other [84; 85; 86; 87; 88]. Hierarchical modeling involves integrating validated subcomponent-level, component-level, or subsystem-level models into a large-scale system-level model [85]. To determine the boundary conditions of a complex technical system, it is necessary to rise to the level of a hierarchically higher complex technical system and identify the incoming and outgoing data in the complex technical system under consideration, and vice versa to the hierarchical level of the lower complex technical system, and repeat this process iteratively [84; 85; 86; 87; 88]. As the model and structure of the system are built, these operations must be repeated and, if necessary, move along the chain to even higher and lower levels of complex technical systems. Depending on the context in which the system is considered, the chain of nesting of systems should be analyzed. In most cases, it is advisable to define no more than two-three such \"systems within systems\". It is also assumed that, in the general case, any chosen SoS has an SoS of hierarchically higher and lower levels. The hierarchical chain described above also considers the principle of **independence**[89], which implies that a virtual (digital) and a real object can evolve as a system without directly influencing each other. Reference [89] describes this concept in the context of design and manufacturing using the example of a pipe object.