2.2 Demarcation as a theoretical process The demarcation of a particular system is a theoretical process that takes as raw materials the components of the system with their respective attributes and function(s) to determine its complex articulation with the environment for a given context. Therefore, the demarcation is a purely symbolic operation with respect to such a particular system, which becomes the abstracted, purified object of a discourse that aims to be objective and true. The demarcation process thus produces objective (scientific) knowledge about the actually functioning system through (i) its purification followed by (ii) its articulation in the specific context in which it functions, or will function.
It is also important to remember that the object of knowledge (the particular system that is subjected to the demarcation) is not the same as the material object (the real existing system), and they exist in different domains. However, the demarcation, as a theoretical process performed in the object of knowledge, produces a knowledge effect on the material object in the specific environment in which it exists or will potentially exist.
2.4 Classification of Systems
There are many ways in which systems can be classified according to their own characteristics or the focus of analysis. A proper classification is very important as it indicates the correct theoretical and experimental tools that are needed to develop objective knowledge of a particular system. In the following subsections, we will address a few general classes of systems, namely [2]: (i) natural and human‐made, (ii) material and conceptual, (iii) static and dynamic, and (iv) closed and open. Other classes of systems will be defined in the upcoming chapters as we introduce new concepts.
2.4.1 Natural and Human‐Made Systems
Through this classification, natural systems are the ones that come into being by natural processes without human intervention. Natural systems thus exist. Human‐made systems are the ones that exist (or have potential to exist) by human intervention, i.e. humans are their agents of production. There is also a hybrid class, called human‐modified systems, where either human made and natural subsystems are part of the same system, or humans directly intervene in natural systems.
The correct classification is clearly related to the demarcation of the system. In some sense, all systems on the planet Earth are human modified; however, classifying it as human made or natural may indicate the most important determinations for the particular system that is analyzed in the specific context in which it exists (or may potentially exist).
Example 2.4 The car and the wind turbine presented in the previous sections can be classified as human‐made systems. The atmosphere of the planet Earth can be classified as a natural system as it has come into being without human intervention. However, in specific places where there are too many cars, or too many wind turbines, the atmosphere may change its internal dynamics because of different air composition that is due to chemical residues produced by cars or because of variations in air flows caused by turbines. In these cases, there is a human intervention and we could say that, in those specific regions, the atmosphere becomes a human‐modified system.
2.4.2 Material and Conceptual Systems
Systems that manifest themselves in a material form are classified as material systems. They are composed of concrete components. Conceptual systems exist in a symbolic domain as plans, drawings, schemes, equations, specifications, or computer simulations used to create, produce, or improve material systems. Conceptual systems can also be concrete in some cases when a given material system is emulated on smaller scales or with elements of similar properties; in this case, a conceptual system is also a material system. There is also a possibility of hybrid material‐conceptual systems as, for example, hardware‐in‐the‐loop simulation platforms [3]. Further, the idea of digital twins can be seen as a hybrid system where there is a one‐to‐one map between an operating material system and its symbolic counterpart [4]. These last two approaches indicate some features of cyber‐physical systems, but we are not yet ready to understand what cyber theoretically means.
Example 2.5 The wind turbine presented in Example 2.3 serves as an illustration of all cases. It is first a purely conceptual system where the components with their attributes are combined on paper based on dynamical equations, and it is then tested in a specialized computer simulator. The second phase is prototyping and a proof‐of‐concept phase on a small scale. This emulation of the material system to be produced is still conceptual as it is not implemented in its real conditions. The real wind turbine tested under controlled conditions, not yet connected to the real grid but to a virtual emulator building a hardware‐in‐the‐loop simulation, is a hybrid conceptual‐material system. The wind turbine in the field is a material system. If its operation is monitored and its operating behavior related to its digital twin, then we have another kind of hybrid system.
2.4.3 Static and Dynamic Systems
A static system is the one dominantly composed of structural components so that its state does not change, or changes in a negligible way, in time and space. A dynamic system is related to frequent changes in state; they are usually related to operating and flow components. Dynamic systems can have several subclasses, such as (i) linear or nonlinear, (ii) discrete time or continuous time, (iii) periodic or event‐driven, (iv) deterministic or stochastic (or adaptive), (v) single input or multiple input, (vi) single output or multiple output, or (vii) stable or unstable (or chaotic). These characterizations are very important for any engineering system, either conceptual or material. The theory of dynamical systems – which is strongly mathematical – is at the core of most scientific and technological developments in the contemporary age [5]. New computer‐based approaches are also becoming more and more prominent [6, 7], introducing new methods in different sciences and also in technical activities. Note that these methods refer to theoretical practices applied to conceptual systems, but that are used to implement and operate material systems. We will return to this in upcoming chapters where we will discuss artificial intelligence, self‐organization, and agent‐based models.
Example 2.6 The wind turbine of Example 2.3 once again provides us a good illustration. The tower of the wind turbine is a structural component (a subsystem) that is classified as static since it is not expected to change its state in time and space. The turbine itself (the rotating machine; an operating component) is a dynamical system whose changes are coupled with the wind movement (a flow component) that will determine the electric energy conversion, which can be measured by current and voltage as a function of time. It can be classified as a nonlinear continuous stochastic system.
2.4.4 Closed and Open Systems
Systems that have negligible interactions with their environments are called closed systems. In contrast, open systems are interwoven with their environment, exchanging data, matter, and energy. Despite all material systems being open, the concept of closed system is important to indicate the degree of interactions that are external to it. Moreover, such a concept has a great scientific value as it is used to define physical limits and laws of “purified” systems as an abstract object. Moving from a closed (abstracted) to a open (physical) system could be understood as a way to produce a material system from a conceptual one.
The demarcation of the system is key here as well. Once a particular system has its boundaries defined, it is possible to determine if it can be theoretically treated as a closed system. Usually, a closed system is associated with the analysis of the conditions of production, considering either the other two conditions of existence ideal for its functioning or completely neglecting them. The differentiation between closed and open systems is the basis for studying and quantifying their level of organization and uncertainty, as we will see in the next chapters.