Sustainability Of Complex Systems Research Articles

Understanding complexity paradigm and sustainability of complex systems: The role of theoretical physics

This brief review discusses the complexity paradigm and the sustainability of complex biological, ecological, and socio-economic systems. This paradigm is considered to complement the reductionism paradigm in explaining the natural phenomena. We suggest that the concepts used in theoretical physics can be considered to describe the specific case of complex systems and to develop their dynamical models.

Industrial Big Data and Computational Sustainability: Multi-Method Comparison Driven by High-Dimensional Data for Improving Reliability and Sustainability of Complex Systems

Sustainable development is of great significance. The emerging research on data-driven computational sustainability has become an effective way to solve this problem. This paper presents a fault diagnosis and prediction framework for complex systems based on multi-dimensional data and multi-method comparison, aimed at improving the reliability and sustainability of the system by selecting methods with relatively superior performance. This study took the avionics system in the industrial field as an example. Based on the literature research on typical fault modes and fault diagnosis requirements of avionics systems, three popular high-dimensional data-driven fault diagnosis methods—support vector machine, convolutional neural network, and long- and short-term memory neural network—were comprehensively analyzed and compared. Finally, the actual bearing failure data were used for programming in order to verify and compare various methods and the process of selecting the superior method driven by high-dimensional data was fully demonstrated. We attempt to provide a sustainable development idea that continuously explores multi-method integration and comparison, aimed at improving the calculation efficiency and accuracy of reliability assessments, optimizing system performance, and ultimately achieving the goal of long-term improvement of system reliability and sustainability.

Evolution in Prebiotic Systems: Cooperation In Utility-Based Agents

Prebiotic evolution is one of the major challenges in complex systems theory. What differentiates the living from the nonliving is a perennial source of debate. It has been recently affirmed that discussions about if and how we can draw a line that separates life from non-life are useless. He motivates this using a "continuity thesis" (CT) argument i.e the existence of a continuum between inanimate and living state of matter. For other authors CT it is equivalent to say that there is no unbridgeable gap between inorganic matter and living systems, plus the corollary that the emergence of life is considered a highly probable event. This is related to the problem of how the minimal complexity required for a chemical system to start on the path of Darwinian evolution has been achieved. The CT from one side, and a trend towards an increasing complexity on the other, seems to require the existence of a constant driving force behind abiogenesis for two distinct reasons: a) to counterbalance destructive tendencies like hydrolysis in the evolving chemical structures and b) reduce the role played by chance to a minimum acceptable for a scientific discourse. In this work, I present a brief review of what has been considered the main driving forces behind prebiotic evolution i.e. self-organization of far-from-equilibrium open systems and (generalized) Darwinian evolutionary mechanism. I argue that, in order to explain the robustness and sustainability of complex systems not yet fully capable of Darwinian evolution a third element must be added: cooperation between molecular autonomous agents properly defined. In this work, I propose a general theoretical result to show how cooperation formation between a population molecular utility-based agents can give rise to self-sustaining networks.

ENGINEERING SUSTAINABLE COMPLEX SYSTEMS

Abstract Given the most competitive nature of global business environment, effective engineering innovation is a critical requirement for all levels of system lifecycle development. The society and community expectations have increased beyond environmental short term impacts to global long term sustainability approach. Sustainability and engineering competence skills are extremely important due to a general shortage of engineering talent and the need for mobility of highly trained professionals [1]. Engineering sustainable complex systems is extremely important in view of the general shortage of resources and talents. Engineers implement new technologies and processes to avoid the negative environmental, societal and economic impacts. Systems thinking help engineers and designers address sustainable development issues with a global focus using leadership and excellence. This paper introduces the Systems Engineering (SE) methodology for designing complex and more sustainable business and industrial solutions, with emphasis on engineering excellence and leadership as key drivers for business sustainability. The considerable advancements achieved in complex systems engineering indicate that the adaptation of sustainable SE to business needs can lead to highly sophisticated yet widely useable collaborative applications, which will ensure the sustainability of limited resources such as energy and clean water. The SE design approach proves critical in maintaining skills needed in future capable workforce. Two factors emerged to have the greatest impact on the competitiveness and sustainability of complex systems and these were: improving skills and performance in engineering and design, and adopting SE and human systems integration (HSI) methodology to support sustainability in systems development. Additionally, this paper provides a case study for the application of SE and HSI methodology for engineering sustainable and complex systems.

The development of an integrated model for assessing sustainability of complex systems

Currently, there are numerous indicators (single and composite) for measuring impacts in the three pillars, though current thinking emphasises the need for system thinking rather than the reductionist concept of pillars. Most existing indices/methods measure single aspects of sustainability and the more integrated indicators are aimed at national or global level assessments. A review of existing indicators, methods and models within the context of complex system sustainability showed that no single existing index, method or model was able to assess sustainability of complex systems. Most fail to account for complex system characteristics, such as system dynamics, interconnections and interdependencies of system components, a system’s ability to learn and remember, emergence of novel behaviours, co-evolution, etc. This paper presents the methodology used to develop a new model for assessing sustainability of complex systems based on risk.

A thermodynamic methodology to assess how different cultivation methods affect sustainability of agricultural systems

SUMMARY To evaluate environmental sustainability of complex systems, such as agricultural cultivation, it is necessary to adopt a systemic approach that considers all mass and energy flows that drive processes and that interlace, amplify, and influence each other. Emergy analysis, a thermodynamic-ecological methodology developed by Odum (1988), produces powerful indicators to evaluate process efficiency and to assess long-term sustainability. We performed a comparison among three cherry crops with different cultivation methods (traditional, biological and integrated) employing different inputs (natural and non-natural), in order to understand how agricultural systems should be developed in order to be economically successful with respect to the environment. Traditional methods using high quantities of non-natural inputs demonstrated unsustainability, while the integrated method of natural and purchased inputs turned out to be the best. The emergy approach demonstrated a powerful methodology to assess sustainability, and the indications obtained for cherry crops could be extrapolated to other types of cultivation.