IDEAS home Printed from https://ideas.repec.org/a/eee/reensy/v134y2015icp260-267.html
   My bibliography  Save this article

Sequential designs for sensitivity analysis of functional inputs in computer experiments

Author

Listed:
  • Fruth, J.
  • Roustant, O.
  • Kuhnt, S.

Abstract

Computer experiments are nowadays commonly used to analyze industrial processes aiming at achieving a wanted outcome. Sensitivity analysis plays an important role in exploring the actual impact of adjustable parameters on the response variable. In this work we focus on sensitivity analysis of a scalar-valued output of a time-consuming computer code depending on scalar and functional input parameters. We investigate a sequential methodology, based on piecewise constant functions and sequential bifurcation, which is both economical and fully interpretable. The new approach is applied to a sheet metal forming problem in three sequential steps, resulting in new insights into the behavior of the forming process over time.

Suggested Citation

  • Fruth, J. & Roustant, O. & Kuhnt, S., 2015. "Sequential designs for sensitivity analysis of functional inputs in computer experiments," Reliability Engineering and System Safety, Elsevier, vol. 134(C), pages 260-267.
    • Handle: RePEc:eee:reensy:v:134:y:2015:i:c:p:260-267
    DOI: 10.1016/j.ress.2014.07.018
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0951832014001732
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.ress.2014.07.018?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Confalonieri, R. & Bellocchi, G. & Bregaglio, S. & Donatelli, M. & Acutis, M., 2010. "Comparison of sensitivity analysis techniques: A case study with the rice model WARM," Ecological Modelling, Elsevier, vol. 221(16), pages 1897-1906.
    2. Iooss, Bertrand & Ribatet, Mathieu, 2009. "Global sensitivity analysis of computer models with functional inputs," Reliability Engineering and System Safety, Elsevier, vol. 94(7), pages 1194-1204.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Roux, Sébastien & Loisel, Patrice & Buis, Samuel, 2019. "A filter-based approach for global sensitivity analysis of models with functional inputs," Reliability Engineering and System Safety, Elsevier, vol. 187(C), pages 119-128.
    2. Neves Costa, João & Ambrósio, Jorge & Andrade, António R. & Frey, Daniel, 2023. "Safety assessment using computer experiments and surrogate modeling: Railway vehicle safety and track quality indices," Reliability Engineering and System Safety, Elsevier, vol. 229(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Drignei, Dorin, 2011. "A general statistical model for computer experiments with time series output," Reliability Engineering and System Safety, Elsevier, vol. 96(4), pages 460-467.
    2. López-Lopera, Andrés F. & Idier, Déborah & Rohmer, Jérémy & Bachoc, François, 2022. "Multioutput Gaussian processes with functional data: A study on coastal flood hazard assessment," Reliability Engineering and System Safety, Elsevier, vol. 218(PA).
    3. Paleari, Livia & Movedi, Ermes & Zoli, Michele & Burato, Andrea & Cecconi, Irene & Errahouly, Jabir & Pecollo, Eleonora & Sorvillo, Carla & Confalonieri, Roberto, 2021. "Sensitivity analysis using Morris: Just screening or an effective ranking method?," Ecological Modelling, Elsevier, vol. 455(C).
    4. Frédéric Branger & Louis-Gaëtan Giraudet & Céline Guivarch & Philippe Quirion, 2014. "Sensitivity analysis of an energy-economy model of the residential building sector," CIRED Working Papers hal-01016399, HAL.
    5. Gilardelli, Carlo & Confalonieri, Roberto & Cappelli, Giovanni Alessandro & Bellocchi, Gianni, 2018. "Sensitivity of WOFOST-based modelling solutions to crop parameters under climate change," Ecological Modelling, Elsevier, vol. 368(C), pages 1-14.
    6. Priyadarshi, Anupam & Chandra, Ram & Kishi, Michio J. & Smith, S.Lan & Yamazaki, Hidekatsu, 2022. "Understanding plankton ecosystem dynamics under realistic micro-scale variability requires modeling at least three trophic levels," Ecological Modelling, Elsevier, vol. 467(C).
    7. Ciric, C. & Ciffroy, P. & Charles, S., 2012. "Use of sensitivity analysis to identify influential and non-influential parameters within an aquatic ecosystem model," Ecological Modelling, Elsevier, vol. 246(C), pages 119-130.
    8. Dzotsi, K.A. & Basso, B. & Jones, J.W., 2013. "Development, uncertainty and sensitivity analysis of the simple SALUS crop model in DSSAT," Ecological Modelling, Elsevier, vol. 260(C), pages 62-76.
    9. F. Grelot & J. Arnal & Pauline Bremond & Katrin Erdlenbruch & C. Durand & S. Durand & G. Gleyses & P. Jarnet & M. Liberti & S. Martini & A. Richard-Ferroudji & L. Albrecht & Jean-Stéphane Bailly & N. , 2009. "Risk perception and economic valuation of flood exposure. Study of two hydrologically contrasted territories [Perception du risque et évaluation économique de l'exposition aux inondations. Étude de," Working Papers hal-02593242, HAL.
    10. Ben Touhami, Haythem & Lardy, Romain & Barra, Vincent & Bellocchi, Gianni, 2013. "Screening parameters in the Pasture Simulation model using the Morris method," Ecological Modelling, Elsevier, vol. 266(C), pages 42-57.
    11. Confalonieri, R. & Bregaglio, S. & Acutis, M., 2012. "Quantifying plasticity in simulation models," Ecological Modelling, Elsevier, vol. 225(C), pages 159-166.
    12. Myrgiotis, Vasileios & Rees, Robert M. & Topp, Cairistiona F.E. & Williams, Mathew, 2018. "A systematic approach to identifying key parameters and processes in agroecosystem models," Ecological Modelling, Elsevier, vol. 368(C), pages 344-356.
    13. Maiorano, Andrea & Bregaglio, Simone & Donatelli, Marcello & Fumagalli, Davide & Zucchini, Antonio, 2012. "Comparison of modelling approaches to simulate the phenology of the European corn borer under future climate scenarios," Ecological Modelling, Elsevier, vol. 245(C), pages 65-74.
    14. Ye, Dongwei & Nikishova, Anna & Veen, Lourens & Zun, Pavel & Hoekstra, Alfons G., 2021. "Non-intrusive and semi-intrusive uncertainty quantification of a multiscale in-stent restenosis model," Reliability Engineering and System Safety, Elsevier, vol. 214(C).
    15. Confalonieri, Roberto & Bregaglio, Simone & Acutis, Marco, 2016. "Quantifying uncertainty in crop model predictions due to the uncertainty in the observations used for calibration," Ecological Modelling, Elsevier, vol. 328(C), pages 72-77.
    16. Wang, Zhaoyang & Shi, Yinfang & Hou, Cheng & Zhang, Puhan, 2024. "Sensitivity analysis of simulated Lycium barbarum L. yield in the WOFOST model under different climate conditions," Ecological Modelling, Elsevier, vol. 488(C).
    17. Olaru, Doina & Purchase, Sharon, 2014. "Rethinking validation: Efficient search of the space of parameters for an agent-based model," Australasian marketing journal, Elsevier, vol. 22(1), pages 60-68.
    18. Senga Kiessé, Tristan & Corson, Michael S. & Eugène, Maguy & Aubin, Joël & Wilfart, Aurélie, 2019. "Analysis of enteric methane emissions due to extreme variations in management practices of dairy-production systems," Agricultural Systems, Elsevier, vol. 173(C), pages 449-457.
    19. Pierre Étoré & Clémentine Prieur & Dang Khoi Pham & Long Li, 2020. "Global Sensitivity Analysis for Models Described by Stochastic Differential Equations," Methodology and Computing in Applied Probability, Springer, vol. 22(2), pages 803-831, June.
    20. Francisco A. Buendia-Hernandez & Maria J. Ortiz Bevia & Francisco J. Alvarez-Garcia & Antonio Ruizde Elvira, 2022. "Sensitivity of a Dynamic Model of Air Traffic Emissions to Technological and Environmental Factors," IJERPH, MDPI, vol. 19(22), pages 1-17, November.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:reensy:v:134:y:2015:i:c:p:260-267. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: https://www.journals.elsevier.com/reliability-engineering-and-system-safety .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.