Introduction to Sensitivity Analysis

Saltelli, Andrea; Ratto, Marco; Andres, Terry; Campolongo, Francesca; Cariboni, Jessica; Gatelli, Debora; Saisana, Michaela; Tarantola, Stefano

doi:10.1002/9780470725184.ch1

Cited by 40 publications

(8 citation statements)

References 35 publications

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“…A sensitivity analysis can be performed to determine the influence of uncertainties for different TP inputs on the quality of the trajectory prediction. In the field of sensitivity analysis, there is a distinction between sensitivity and uncertainty analysis [23]. A sensitivity analysis attributes uncertainty in the model output(s) to uncertainty in model inputs.…”

Section: Sensitivity Analysismentioning

confidence: 99%

Trajectory Prediction Sensitivity Analysis Using Monte Carlo Simulations Based on Inputs’ Distributions

Rudnyk

Ellerbroek

2019

Journal of Air Transportation

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To facilitate the increasing amount of air traffic, current and future decision support tools for air traffic management require an efficient and accurate trajectory prediction. With uncertainty inherent to almost all inputs of a trajectory predictor, the accurate prediction is not a simple task. In this study, Monte Carlo simulations of a ground-based trajectory predictor are performed to estimate the prediction uncertainty up to 20 minutes look-ahead time and to assess the correlation between inputs and prediction errors. Selected inputs are aircraft bank angle, constant calibrated airspeed and Mach number speed settings, vertical speed, temporary level-offs, air temperature, lapse rate, wind, and air traffic control intent. These inputs are provided in the form of their distribution functions obtained from observed data such as surveillance data, weather forecasts, and air traffic controllers' inputs. Simulations are performed for heavy and medium wake turbulence category aircraft. Results indicate that with a 20 minute look-ahead time, when outliers are not considered, along-track errors can reach up to 18 nautical miles, whereas altitude errors can reach up to around 13,000 feet. Cross-track errors in cruise highly depend on the lateral deviations due to ATC instructions, and, in this study, are within 10 nautical miles. Wind conditions, vertical speed, calibrated airspeed, Mach number speed setting, and temporary level-offs are determined to be the most influential inputs.

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Section: Sensitivity Analysismentioning

confidence: 99%

Trajectory Prediction Sensitivity Analysis Using Monte Carlo Simulations Based on Inputs’ Distributions

Rudnyk

Ellerbroek

2019

Journal of Air Transportation

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“…Experimental approach "Sensitivity analysis" has multiple definitions in the literature (Saltelli et al, 2008). We refer to sensitivity analysis as the evaluation of changes in the outputs of a model in response to incremental perturbations to the inputs to the model.…”

Section: Markal Modelmentioning

confidence: 99%

Analysis of alternative pathways for reducing nitrogen oxide emissions

Loughlin

Kaufman

Lenox

et al. 2015

Journal of the Air & Waste Management Association

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Strategies for reducing tropospheric ozone (O 3 ) typically include modifying combustion processes to reduce the formation of nitrogen oxides (NO x ) and applying control devices that remove NO x from the exhaust gases of power plants, industrial sources and vehicles. For portions of the U.S., these traditional controls may not be sufficient to achieve the National Ambient Air Quality Standard for ozone. We apply the MARKet ALlocation (MARKAL) energy system model in a sensitivity analysis to explore whether additional NO x reductions can be achieved through extensive electrification of passenger vehicles, adoption of energy efficiency and conservation measures within buildings, and deployment of wind and solar power in the electric sector. Nationally and for each region of the country, we estimate the NO x implications of these measures. Energy efficiency and renewable electricity are shown to reduce NO x beyond traditional controls. Wide-spread light duty vehicle electrification produces varied results, with NO x increasing in some regions and decreasing in others. However, combining vehicle electrification with renewable electricity reduces NO x in all regions.Implications: State governments are charged with developing plans that demonstrate how air quality standards will be met and maintained. The results presented here provide an indication of the national and regional NO x reductions available beyond traditional controls via extensive adoption of energy efficiency, renewable electricity, and vehicle electrification. IntroductionNational Ambient Air Quality Standards (NAAQS) specify maximum allowable air pollutant concentrations in the United States. The 8-hr NAAQS for tropospheric ozone (O 3 ), a principal component of photochemical smog, was set at 75 ppb in (Federal Register, 2008. State air quality agencies are charged with developing State Implementation Plans (SIPs) to bring nonattainment areas into attainment with the standard. Since O 3 is formed through a photochemical reaction involving nitrogen oxides (NO x ) and volatile organic compounds (VOCs), and since this reaction is limited by NO x in most parts of the country, O 3 SIPs typically focus on reducing NO x .State actions related to SIPs, combined with a range of federal regulations, have reduced U.S. NO x emissions by 51% from 1990 to 2014 (U.S. Environmental Protection Agency [EPA], 2015a). Over that period, electric sector NO x was reduced by 73% and onroad vehicle NO x by 53%. The majority of these reductions have been achieved by modifying combustion processes and placing control devices on the exhaust systems of stationary and mobile sources. For example, many coal-fired electric utilities reduce emissions via low-NO x burners (LNB) and selective catalytic reduction (SCR) systems, and modern passenger cars and trucks are fitted with catalytic converters.One approach for developing an O 3 SIP is to estimate the NO x reductions that could be achieved through greater application of traditional controls, such as LNB and SCR. The state's emis...

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“…Saltelli et al [16] characterize the question of composite indicators as follows: "Composite indicators tend to sit between advocacy (when they are used to draw attention to an issue) and analysis (when they are used to capture complex, multidimensional phenomena)." The topic of composite indicators has been described by the OECD [17], which defines, in six steps, why they should be created and what the goals that should thus be fulfilled are.…”

Section: Introductionmentioning

confidence: 99%

“…A related practice is an 'uncertainty analysis' that focuses more on quantifying uncertainty in a model output. Ideally, uncertainty and sensitivity analyses should run in tandem, with an uncertainty analysis proceeding in the current practice [16]. Sensitivity analysis can serve a number of useful purposes in the economy of modeling [16].…”

Section: Introductionmentioning

confidence: 99%

“…Ideally, uncertainty and sensitivity analyses should run in tandem, with an uncertainty analysis proceeding in the current practice [16]. Sensitivity analysis can serve a number of useful purposes in the economy of modeling [16]. Uncertainty quantification studies, which may include sensitivity analysis and uncertainty analysis, are essential in risk assessments.…”

Section: Introductionmentioning

confidence: 99%

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Uncertainty and Sensitivity Analyses of PISA Efficiency: Distance Based Analysis Approach

2015

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Introduction to Sensitivity Analysis

Cited by 40 publications

References 35 publications

Trajectory Prediction Sensitivity Analysis Using Monte Carlo Simulations Based on Inputs’ Distributions

Trajectory Prediction Sensitivity Analysis Using Monte Carlo Simulations Based on Inputs’ Distributions

Analysis of alternative pathways for reducing nitrogen oxide emissions

Uncertainty and Sensitivity Analyses of PISA Efficiency: Distance Based Analysis Approach

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