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Global sensitivity analysis methods using response surface descriptions: applied to the COPERT III road traffic emission model
Linköping University, Department of Mathematics, Statistics. Linköping University, Faculty of Arts and Sciences.
(English)Manuscript (Other academic)
Abstract [en]

Sensitivity analyses may be local or global, one at a time or all at a time, or classified in other ways. This paper examines some response surface methods for instant calculations of many sensitivities at the same time. The appropriateness of replacing the original model with a simpler response surface is discussed.The methods are also compared with one at a time methods. Sensitivity results are calculated by applying the methods to the COPERT III model. The conclusion is that a simple response surface method should be preferred.

National Category
Natural Sciences
Identifiers
URN: urn:nbn:se:liu:diva-14297OAI: oai:DiVA.org:liu-14297DiVA, id: diva2:23142
Available from: 2007-02-13 Created: 2007-02-13 Last updated: 2012-12-17
In thesis
1. Sensitivity and Uncertainty Analysis Methods: with Applications to a Road Traffic Emission Model
Open this publication in new window or tab >>Sensitivity and Uncertainty Analysis Methods: with Applications to a Road Traffic Emission Model
2007 (English)Doctoral thesis, comprehensive summary (Other academic)
Alternative title[sv]
Känslighets- och osäkerhetsanalysmetoder : med tillämpningar på en emissionsmodell för vägtrafik
Abstract [en]

There is always a need to study the properties of complex input–output systems, properties that may be very difficult to determine. Two such properties are the output’s sensitivity to changes in the inputs and the output’s uncertainty if the inputs are uncertain.

A system can be formulated as a model—a set of functions, equations and conditions that describe the system. We ultimately want to study and learn about the real system, but with a model that approximates the system well, we can study the model instead, which is usually easier. It is often easier to build a model as a set of combined sub-models, but good knowledge of each sub-model does not immediately lead to good knowledge of the entire model. Often, the most attractive approach to model studies is to write the model as computer software and study datasets generated by that software.

Methods for sensitivity analysis (SA) and uncertainty analysis (UA) cannot be expected to be exactly the same for all models. In this thesis, we want to determine suitable SA and UA methods for a road traffic emission model, methods that can also be applied to any other model of similar structure. We examine parts of a well-known emission model and suggest a powerful data-generating tool. By studying generated datasets, we can examine properties in the model, suggest SA and UA methods and discuss the properties of these methods. We also present some of the results of applying the methods to the generated datasets.

Abstract [sv]

Det finns alltid behov av att studera egenskaper hos komplexa input-output-system, egenskaper som kan vara mycket svåra att få fram. Två sådana egenskaper är ut fallets känslighet mot förändringar i ingångsvärdena och utfallets osäkerhet om ingångsvärdena har osäkerhet.

Ett system kan formuleras som en modell-en mängd funktioner, ekvationer och betingelser som tillsammans liknar systemet. Vi vill egentligen studera och lära oss det verkliga systemet, men med en modell som approximerar det verkliga systemet bra kan man studera modellen istället, vilket i de flesta fall är enklare. Det är oftast enklare att bygga en modell som en mängd kombinerade delmodeller, men bra kunskap om varje delmodell leder inte omedelbart till bra kunskap om hela modellen. Det enklaste tillvägagångssättet för modellstudier är oftast att studera datamängder som genererats av modellen genom ett datorprogram.

Metoder för känslighetsanalys (SA) och osäkerhetsanalys (UA) kan inte förväntas vara likadana för varje modell. I den här avhandlingen ska vi studera SA- och UA-metoder och resultat för en emissionsmodell för vägtrafik, men metoderna kan även användas för andra modeller av liknande struktur. Vi undersöker en välkänd emissionsmodell och föreslår ett kraftfullt verktyg för att generera data. Genom att studera genererade datamängder kan vi undersöka egenskaper i modellen, föreslå SA- och VA-metoder och diskutera metodernas egenskaper. Vi visar också några resultat när man tillämpar metoderna på de genererade datamängderna.

Place, publisher, year, edition, pages
Matematiska institutionen, 2007. p. 24 + papers 1-5
Series
Linköping Studies in Arts and Sciences, ISSN 0282-9800 ; 383Linköping Studies in Statistics, ISSN 1651-1700 ; 8
Keywords
Emission, Grid, Model, Pollutant, Response surface, Road traffic, Sensitivity analysis, Simulation, Uncertainty analysis, Avgaser, Vägtrafik, Miljöaspekter
National Category
Probability Theory and Statistics
Identifiers
urn:nbn:se:liu:diva-8315 (URN)978-91-85715-72-5 (ISBN)
Public defence
2007-03-16, BL32, Hus B, Campus Valla, Linköpings universitet, Linköping, 10:15 (English)
Opponent
Supervisors
Available from: 2007-02-13 Created: 2007-02-13 Last updated: 2020-03-24Bibliographically approved

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Eriksson, Olle

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