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- All Subjects: Resilience
- Creators: Anderies, John M
Description
Quantum resilience is a pragmatic theory that allows systems engineers to formally characterize the resilience of systems. As a generalized theory, it not only clarifies resilience in the literature, but also can be applied to all disciplines and domains of discourse. Operationalizing resilience in this manner permits decision-makers to compare and contrast system deployment options for suitability in a variety of environments and allows for consistent treatment of resilience across domains. Systems engineers, whether planning future infrastructures or managing ecosystems, are increasingly asked to deliver resilient systems. Quantum resilience provides a way forward that allows specific resilience requirements to be specified, validated, and verified.
Quantum resilience makes two very important claims. First, resilience cannot be characterized without recognizing both the system and the valued function it provides. Second, resilience is not about disturbances, insults, threats, or perturbations. To avoid crippling infinities, characterization of resilience must be accomplishable without disturbances in mind. In light of this, quantum resilience defines resilience as the extent to which a system delivers its valued functions, and characterizes resilience as a function of system productivity and complexity. System productivity vis-à-vis specified “valued functions” involves (1) the quanta of the valued function delivered, and (2) the number of systems (within the greater system) which deliver it. System complexity is defined structurally and relationally and is a function of a variety of items including (1) system-of-systems hierarchical decomposition, (2) interfaces and connections between systems, and (3) inter-system dependencies.
Among the important features of quantum resilience is that it can be implemented in any system engineering tool that provides sufficient design and specification rigor (i.e., one that supports standards like the Lifecycle and Systems Modeling languages and frameworks like the DoD Architecture Framework). Further, this can be accomplished with minimal software development and has been demonstrated in three model-based system engineering tools, two of which are commercially available, well-respected, and widely used. This pragmatic approach assures transparency and consistency in characterization of resilience in any discipline.
Quantum resilience makes two very important claims. First, resilience cannot be characterized without recognizing both the system and the valued function it provides. Second, resilience is not about disturbances, insults, threats, or perturbations. To avoid crippling infinities, characterization of resilience must be accomplishable without disturbances in mind. In light of this, quantum resilience defines resilience as the extent to which a system delivers its valued functions, and characterizes resilience as a function of system productivity and complexity. System productivity vis-à-vis specified “valued functions” involves (1) the quanta of the valued function delivered, and (2) the number of systems (within the greater system) which deliver it. System complexity is defined structurally and relationally and is a function of a variety of items including (1) system-of-systems hierarchical decomposition, (2) interfaces and connections between systems, and (3) inter-system dependencies.
Among the important features of quantum resilience is that it can be implemented in any system engineering tool that provides sufficient design and specification rigor (i.e., one that supports standards like the Lifecycle and Systems Modeling languages and frameworks like the DoD Architecture Framework). Further, this can be accomplished with minimal software development and has been demonstrated in three model-based system engineering tools, two of which are commercially available, well-respected, and widely used. This pragmatic approach assures transparency and consistency in characterization of resilience in any discipline.
ContributorsRoberts, Thomas Wade (Author) / Allenby, Braden (Thesis advisor) / Chester, Mikhail (Committee member) / Anderies, John M (Committee member) / Arizona State University (Publisher)
Created2015
Description
Design is a fundamental human activity through which we attempt to navigate and manipulate the world around us for our survival, pleasure, and benefit. As human society has evolved, so too has the complexity and impact of our design activities on the environment. Now clearly intertwined as a complex social-ecological system at the global scale, we struggle in our ability to understand, design, implement, and manage solutions to complex global issues such as climate change, water scarcity, food security, and natural disasters. Some have asserted that this is because complex adaptive systems, like these, are moving targets that are only partially designed and partially emergent and self-organizing. Furthermore, these types of systems are difficult to understand and control due to the inherent dynamics of "wicked problems", such as: uncertainty, social dilemmas, inequities, and trade-offs involving multiple feedback loops that sometimes cause both the problems and their potential solutions to shift and evolve together. These problems do not, however, negate our collective need to effectively design, produce, and implement strategies that allow us to appropriate, distribute, manage and sustain the resources on which we depend. Design, however, is not well understood in the context of complex adaptive systems involving common-pool resources. In addition, the relationship between our attempts at control and performance at the system-level over time is not well understood either. This research contributes to our understanding of design in common-pool resource systems by using a multi-methods approach to investigate longitudinal data on an innovative participatory design intervention implemented in nineteen small-scale, farmer-managed irrigation systems in the Indrawati River Basin of Nepal over the last three decades. The intervention was intended as an experiment in using participatory planning, design and construction processes to increase food security and strengthen the self-sufficiency and self-governing capacity of resource user groups within the poorest district in Nepal. This work is the first time that theories of participatory design-processes have been empirically tested against longitudinal data on a number of small-scale, locally managed common-pool resource systems. It clarifies and helps to develop a theory of design in this setting for both scientific and practical purposes.
ContributorsRatajczyk, Elicia Beth (Author) / Anderies, John M (Thesis advisor) / York, Abigail (Committee member) / Shivakoti, Ganesh P (Committee member) / Arizona State University (Publisher)
Created2018