Biased Decision-Making in Realistic Extra-Procedural Nuclear Control Room Scenarios

  • Emil AndersenEmail author
  • Igor Kozine
  • Anja Maier
Conference paper


In normal operations and emergency situations, operators of nuclear control rooms rely on procedures to guide their decision-making. However, in emergency situations, these procedures may be insufficient in guiding operators.



We thank our research partners from the Halden HAMMLAB at the Institute for Energy Technology (IFE) in Norway for their continued support, in particular, Andreas Bye, Lars Holmgren, Salvatore Massaiu, Espen Nystad and Stine Strand. The work reported in this paper is part-funded by the OECD Halden Reactor Project.


  1. 1.
    Burian BK (2006) Design guidance for emergency and abnormal checklists in aviation. In: Proceedings of the Human Factors and Ergonomics Society 50th Annual Meeting, vol 50, pp 1–6CrossRefGoogle Scholar
  2. 2.
    Burian BK (2005) Do you smell smoke? Issues in the design and content of checklists for smoke, fire, and fumes. In: Emergency and abnormal situations symposiumGoogle Scholar
  3. 3.
    Lau N et al (2008) Ecological interface design in the nuclear domain: an application to the secondary subsystems of a boiling water reactor plant simulator. IEEE Trans Nucl Sci 55(6):3579–3596CrossRefGoogle Scholar
  4. 4.
    Weyer U, Braseth AO, Eikås M, Hurlen L, Kristiansen P, Kvalem J (2010) Safety presentation in large screen displays - a new approach. In: SPE intelligent energy conference and exhibitionGoogle Scholar
  5. 5.
    Braseth AO, Øritsland TA (2013) Visualizing complex processes on large screen displays: design principles based on the information rich design concept. Displays 34(3):215–222CrossRefGoogle Scholar
  6. 6.
    Wreathall J, Reason J (1993) Latent failures and human performance in significant operating events. JWCo. IncGoogle Scholar
  7. 7.
    U.S. Nuclear Regulatory Commission (2002) Review of findings for human performance contribution to risk in operating events (NUREG/CR-6753, INEEL/EXT-01-01166)Google Scholar
  8. 8.
    Massaiu S (2010) Critical features of emergency procedures: empirical insights form simulations of nuclear power plant operation. Training, pp 277–284Google Scholar
  9. 9.
    Du P, MacDonald EF (2015) Products’ shared visual features do not cancel in consumer decisions. J Mech Des 137(7):71409CrossRefGoogle Scholar
  10. 10.
    Du P, MacDonald EF (2013) Eye-tracking data predicts importance of product features and saliency of size change, vol 5. In: 25th Int Conf Des Theory Methodol ASME 2013 Power Transm Gearing Conf, vol 136, no 8, p V005T06A024Google Scholar
  11. 11.
    Goucher-Lambert K, Cagan J (2014) The impact of sustainability on consumer preference judgments (DETC2014-34739). In: ASME 2014 Int Des Eng Tech Conf Comput Inf Eng Conf, vol 137, no c, pp 1–11, Aug 2014Google Scholar
  12. 12.
    Goucher-Lambert K, Moss J, Cagan J (2017) Inside the mind: using neuroimaging to understand moral product preference judgments involving sustainability. J Mech Des 139(4):41103CrossRefGoogle Scholar
  13. 13.
    Faerber SJ, Carbon CC (2013) Jump on the innovator’s train: cognitive principles for creating appreciation in innovative product designs. Res Eng Des 24(3):313–319CrossRefGoogle Scholar
  14. 14.
    Reid TN, MacDonald EF, Du P (2013) Impact of product design representation on customer judgment. J Mech Des 135(9):91008CrossRefGoogle Scholar
  15. 15.
    Wei ST, Ou LC, Luo MR, Hutchings JB (2014) Package design: colour harmony and consumer expectations. Int J Des 8(1):109–126Google Scholar
  16. 16.
    Perez Mata M, Ahmed-Kristensen S, Brockhoff PB, Yanagisawa H (2017) Investigating the influence of product perception and geometric features. Res Eng Des 28(3):357–379CrossRefGoogle Scholar
  17. 17.
    Andersen E, Maier A (2017) The attentional capture of colour in visual interface design: a controlled-environment study. In: Proceedings of the international conference on engineering design, ICED, vol 8, no DS87-8Google Scholar
  18. 18.
    Jansson DG, Smith SM (1991) Design fixation. Des Stud 12(1):3–11CrossRefGoogle Scholar
  19. 19.
    Vasconcelos LA, Crilly N (2016) Inspiration and fixation: questions, methods, findings, and challenges. Des Stud 42:1–32CrossRefGoogle Scholar
  20. 20.
    Nikander JB, Liikkanen LA, Laakso M (2014) The preference effect in design concept evaluation. Des Stud 35(5):473–499CrossRefGoogle Scholar
  21. 21.
    Viswanathan VK, Linsey JS (2013) Design fixation and its mitigation: a study on the role of expertise. J Mech Des 135(5):51008CrossRefGoogle Scholar
  22. 22.
    Kahneman D, Klein G (2009) Conditions for intuitive expertise: a failure to disagree. Am Psychol 64(6):515–526CrossRefGoogle Scholar
  23. 23.
    Gigerenzer G, Gaissmaier W (2011) Heuristic decision making. Annu Rev Psychol 62(1):451–482CrossRefGoogle Scholar
  24. 24.
    Massaiu S, Holmgren L (2014) Diagnosis and decision-making with emergency operating procedures in non-typical conditions: a HAMMLAB study with U.S. Operators. In: HWR-1121. Halden, Norw. OECD Halden React. Proj.Google Scholar
  25. 25.
    Massaiu S, Holmgren L (2016) A HAMMLAB HRA data collection with U.S. operators. HWR-1123. In: HWR-1123. Halden, Norw. OECD Halden React. Proj. OECD Halden Reactor Project, Halden, NorwayGoogle Scholar
  26. 26.
    Nickerson RS (1998) Confirmation bias: a ubiquitous phenomenon in many guises. Rev Gen Psychol 2(2):175–220CrossRefGoogle Scholar
  27. 27.
    Simon HA (1992) What is an explanation of behavior? Psychol Sci 3(3):150–161CrossRefGoogle Scholar
  28. 28.
    Shanteau J (1992) Competence in experts: the role of task characteristics. Organ Behav Hum Decis Process 53(2):252–266CrossRefGoogle Scholar
  29. 29.
    Shanteau J (1992) How much information does an expert use? is it relevant? Acta Psychol (Amst) 81(1):75–86CrossRefGoogle Scholar
  30. 30.
    Dreyfus SE (2004) The five-stage model of adult skill acquisition. Bull Sci Technol Soc 24(3):177–181CrossRefGoogle Scholar
  31. 31.
    Bruner JS, Potter MC (1964) Interference in visual recognition. Science 144(3617):424–425CrossRefGoogle Scholar
  32. 32.
    Ross L, Anderson CA (1982) Shortcomings in the attribution process: on the origins and maintenance of erroneous social assessments. Judgm Under Uncertain Heuristics Biases 1977:129–153CrossRefGoogle Scholar
  33. 33.
    Anderson CA, Lepper MR, Ross L (1980) Perseverance of social theories: the role of explanation in the persistence of discredited information. J Pers Soc Psychol 39(6):1037–1049CrossRefGoogle Scholar
  34. 34.
    Baron J (1995) Myside bias in thinking about abortion. Think Reason 1(3):221–235CrossRefGoogle Scholar
  35. 35.
    Wason PC (1960) On the failure to eliminate hypotheses in a conceptual task. Q J Exp Psychol 12(3):129–140CrossRefGoogle Scholar
  36. 36.
    Griffin D, Tversky A (1992) The weighing of evidence and the determinants of confidence. Cogn Psychol 24(3):411–435CrossRefGoogle Scholar
  37. 37.
    Vasconcelos LA, Cardoso CC, Sääksjärvi M, Chen C-C, Crilly N (2017) Inspiration and fixation: the influences of example designs and system properties in idea generation. J Mech Des 139(3):31101CrossRefGoogle Scholar
  38. 38.
    Hallihan GM, Cheong H, Shu LH (2012) Confirmation and cognitive bias in design cognition, In: Volume 7: 9th international conference on design education; 24th international conference on design theory and methodology, p 913Google Scholar
  39. 39.
    Walmsley S, Gilbey A (2017) Debiasing visual pilots’ weather-related decision making. Appl Ergon 65:200–208CrossRefGoogle Scholar
  40. 40.
    Cook MB, Smallman HS (2008) Human factors of the confirmation bias in intelligence analysis: decision support from graphical evidence landscapes. Hum Factors J Hum Factors Ergon Soc 50(5):745–754CrossRefGoogle Scholar
  41. 41.
    Galinsky AD, Moskowitz GB (2000) Counterfactuals as behavioral primes: priming the simulation heuristic and consideration of alternatives. J Exp Soc Psychol 36(4):384–409CrossRefGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Technical University of DenmarkKongens LyngbyDenmark

Personalised recommendations