Journal
SUSTAINABILITY
Volume 14, Issue 1, Pages -Publisher
MDPI
DOI: 10.3390/su14010414
Keywords
business aviation; turboprop; electric motor; specific power; Monte Carlo simulation
Funding
- Natural Sciences and Engineering Research Council [OGP0155871]
- Finnish Foundation for Economic Foundation [200153]
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Computational decision-making in real world environmental and sustainability contexts often involves comparing uncertain factors and difficult dimensions. Monte Carlo simulation modeling has been commonly used to integrate uncertain inputs and construct probability distributions of outputs. Visual analytics and data visualization can support processing, analyzing, and communicating the influence of multi-variable uncertainties on decision-making. This paper introduces the Simulation Decomposition (SimDec) technique to quantitatively examine carbon emissions resulting from greater airline electrification in the aviation industry. SimDec decomposes a Monte Carlo model of the flying range of all-electric aircraft based on improvements to batteries and motor efficiencies. SimDec's generalizability and simple visualization of complex uncertainties make it a powerful tool in environmental decision-making.
Computational decision-making in real world environmental and sustainability contexts frequently requires the need to contrast numerous uncertain factors and difficult-to-capture dimensions. Monte Carlo simulation modelling has frequently been employed to integrate the uncertain inputs and to construct probability distributions of the resulting outputs. Visual analytics and data visualization can be used to support the processing, analyzing, and communicating of the influence of multi-variable uncertainties on the decision-making process. In this paper, the novel Simulation Decomposition (SimDec) analytical technique is used to quantitatively examine carbon emission impacts resulting from a transformation of the aviation industry toward a state of greater airline electrification. SimDec is used to decompose a Monte Carlo model of the flying range of all-electric aircraft based upon improvements to batteries and motor efficiencies. Since SimDec can be run concurrently with any Monte Carlo model with only negligible additional overhead, it can easily be extended into the analysis of any environmental application that employs simulation. This generalizability in conjunction with its straightforward visualizations of complex stochastic uncertainties makes the practical contributions of SimDec very powerful in environmental decision-making.
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