Mimicking nature for resilient resource and infrastructure network design

Chatterjee, Abheek; Layton, Astrid

doi:10.1016/j.ress.2020.107142

Cited by 45 publications

(15 citation statements)

References 83 publications

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“… Ahmadian et al (2020) have presented a model to test and improve the recovery capability during a disruptive event. Finally, a combined evaluation of resilience and sustainability has been proposed by Chatterjee & Layton (2020) ; these authors balanced redundancy and efficiency for optimizing the network configuration under normal conditions and unexpected events. Three quali-quantitative studies have evaluated resilience too, by presenting either general parameters to assess the level of readiness to disruptions ( Sureeyatanapas et al, 2020 ), or by evaluating the supply chain readiness with the aim of improving the preparation and reducing the decisional uncertainty in responding to the disruption ( Chowdhury & Quaddus, 2016 ), or by proposing a resilient supplier selection model in a disaster scenario to reduce the vulnerability of a supply chain system ( Haldar et al, 2014 ).…”

Section: Resultsmentioning

confidence: 99%

A literature review on quantitative models for supply chain risk management: Can they be applied to pandemic disruptions?

Rinaldi

Murino

Gebennini

et al. 2022

Computers & Industrial Engineering

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Section: Resultsmentioning

confidence: 99%

A literature review on quantitative models for supply chain risk management: Can they be applied to pandemic disruptions?

Rinaldi

Murino

Gebennini

et al. 2022

Computers & Industrial Engineering

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“…Interested readers may refer to previous work, which has adapted ENA for applications in industrial networks, [66][67][68][69][70][71] power grids, 72 water distribution networks, 73,74 and supply chains. 75 Consider the architecture presented in Figure 3(C). The goal is to represent the network architecture and its task-flows in an N X N flow matrix.…”

Section: Sos Architectures' Doso Evaluationmentioning

confidence: 99%

Ecology‐inspired resilient and affordable system of systems using degree of system order

Chatterjee

Malak

Layton

2021

Systems Engineering

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An optimal trade-off between resilience (the ability to survive and recover from disruptions) and affordability is highly desirable in System of Systems (SoS) architectures. However, it is difficult to design SoS architectures for these goals as existing resilience evaluation methods require detailed disruption models that are not readily available in the early stages of design. Biological ecosystems (nature's resilient SoS) achieve these goals through a unique balance of efficient and redundant interactions in their architectures-measured using the metric Degree of System Order (DoSO).This research tests if this ecological architecting principle and the DoSO metric are useful for designing resilient and affordable SoS. The resilience versus affordability tradespace of a large number of notional SoS architectures is investigated using the DoSO metric. Results indicate that the majority of Pareto optimal SoS architectures, under various disruptions, lie in the ecologically-identified favorable DoSO range. Further, SoS architectures within this DoSO range were found to have better resilience and affordability attributes, in general, than the architectures outside it. DoSO evaluation does not require knowledge of disruption scenarios and is the first network architecture metric to consider resilience versus affordability trade-offs, making it a valuable addition to the SoS engineering toolset.

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“…Ecologists have developed methodologies and metrics to capture the resilient traits, such as ecological robustness (R ECO ), cycling index, and degree of system order (DoSO) [7], [8]. To mimic the resilient nature from ecosystems, such metrics have been used to guide the resilient design for various human-made networks, including water distribution networks [9], supply chains [10], and industrial by-product networks [11].…”

Section: Introductionmentioning

confidence: 99%

An Extended Model for Ecological Robustness to Capture Power System Resilience

Hao¹,

Davis²,

Poor³

2023

Preprint

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The long-term resilient property of ecosystems has been quantified as ecological robustness (R ECO ) in terms of the energy transfer over food webs. The R ECO of resilient ecosystems favors a balance of food webs' network efficiency and redundancy. By integrating R ECO with power system constraints, the authors are able to optimize power systems' inherent resilience as ecosystems through network design and system operation. A previous model used on real power flows and aggregated redundant components for a rigorous mapping between ecosystems and power systems. However, the reactive power flows also determine power systems resilience; and the power components' redundancy is part of the global network redundancy. These characteristics should be considered for R ECO -oriented evaluation and optimization for power systems. Thus, this paper extends the model for quantifying R ECO in power systems using real, reactive, and apparent power flows with the consideration of redundant placement of generators. Recalling the performance of R ECO -oriented optimal power flows under N-x contingencies, the analyses suggest reactive power flows and redundant components should be included for R ECO to capture power systems' inherent resilience.

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Mimicking nature for resilient resource and infrastructure network design

Cited by 45 publications

References 83 publications

A literature review on quantitative models for supply chain risk management: Can they be applied to pandemic disruptions?

A literature review on quantitative models for supply chain risk management: Can they be applied to pandemic disruptions?

Ecology‐inspired resilient and affordable system of systems using degree of system order

An Extended Model for Ecological Robustness to Capture Power System Resilience

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