(209d) Process Engineering Inspired Comparison of Sustainability and Resilience Specific Features of Natural and Human-Built Process Systems

From chemical and biological engineering points of views, sustainability and resilience means long term planning, design and control of robust large scale processes. In the past decades mankind built "artificial" processes against the principles of the natural (e.g. biological) processes, to achieve more profit in a short time horizon. In order to keep balance in the space of finite resources and reservoirs, we have to pay more attention to the computer assisted engineering of large water-food-energy- ecosystem related process networks.

The structure and functionalities of the complex natural and human-built processes are more sophisticated, than the networks in sense of network science, on the one hand. However, the case-specific local functionalities of the individual building blocks in these structures are less complex, than the various specific mathematical methods, on the other. As an intermediate solution, we have developed Programmable Structures that can be generated from two functional meta-prototypes and from the declaration of the process network. The meta-prototypes and the generated process structures are prepared for the semantically distinguished, but syntactically uniform representation of the "model specific conservation law based, additive" measures, and of the "over-writable" signals.

Applying this methodology, we studied many different process systems from cellular signaling, through technological systems to the ecosystem involved agricultural process networks. The results from the analysis of these quite different processes, studied by a unified approach, oriented our theoretical interest toward model based comparison of sustainability- and resilience-specific features of natural and human-built processes.

According to the preliminary investigations on this comparison, it became obvious that we can learn useful (chemical and biological engineering based) sustainability related design and control principles. The most important lessons can be summarized as follows:

1. Both natural and human-built processes are determined by "model specific conservation law based" stoichiometric balance processes, but the natural processes are inherently self-determined, while human-built ones are determined by short term decisions. As a consequence of the self-determinedness, natural processes prefer local solutions, in contrary to the more and more global character of human-built processes.
2. Another common feature is that the primary (controlling) information is carried by conservation law based vehicle processes in both natural and artificial processes. However, in natural processes a direct feedback exists between the signal and the vehicle process. In the lack of this feedback, human generated information processes are often characterized by the (sometimes useful, sometimes harmful) far reaching effects. The basic architecture of natural processes is characterized by the mutual cooperative control feedback between the functionally connected neighbors. However, the artificial processes are controlled by the hierarchically organized human decisions.
3. The secondary (evaluating) information appears only in the human-built processes, in form of objectives (i.e. interests). Accordingly, the evaluation feedback in the artificial processes are manifested in the various forms of usually hierarchical optimization. Nevertheless, consciously designed cooperative evaluation feedback amongst the functionally connected neighbors could also be applied in the human-built process architectures. Engineering designed and controlled cooperation means that the functionally connected neighbors must tend to evolve mutually suboptimal, compromise functioning.

Programmable Structure of process models helped to learn the clear separation of the chemistry invented "model specific conservation laws based" additive measures from the over-writable signs. This, combined with biology invented cooperative feedback, suggested design and operation principles for sustainable complex process systems, as follows:

- to consider long term balances of the model specific conservation laws based measures;

- to understand "information process" as a sub-process of "conservation process" that consumes less measures, but effects more on the functioning of the complementing sub-processes and the environment, than 'vice versa'; and

- to understand cooperative process as a mutual (control or evaluation) feedback between the functionally connected neighbors.

The existence and utilization of these principles will be illustrated by some recently studied examples for biosystem, ecosystem, (bio)technological and agro-environmental process networks.