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Uncertainty-Aware Robustness Analysis of Blended-Wing-Body Cabin Evacuation Under the Faa 90-Second Requirement (14 CFR § 25.803) Cover

Uncertainty-Aware Robustness Analysis of Blended-Wing-Body Cabin Evacuation Under the Faa 90-Second Requirement (14 CFR § 25.803)

Open Access
|Mar 2026

References

  1. Scholz D. New blended wing body (BWB) aircraft – Is 50% fuel reduction a credible claim? Hamburg: Hamburg University of Applied Sciences (HAW Hamburg); 2026. https://doi.org/10.48441/4427.3163
  2. Lee DS, Fahey DW, Skowron A, Allen MR, Burkhardt U, Chen Q, Doherty SJ, Freeman S, Forster PM, Fuglestvedt JS, Gettelman A, De León RR, Lim LL, Lund MT, Millar RJ, Owen B, Penner JE, Pitari G, Prather MJ, et al. The contribution of global aviation to anthropogenic climate forcing for 2000 to 2018. Atmos Environ. 2020;244:117834. https://doi.org/10.1016/j.atmosenv.2020.117834
  3. Teoh R, Schumann U, Majumdar A, Stettler MEJ. Mitigating the climate forcing of aircraft contrails by small-scale diversions and technology adoption. Environ Sci Technol. 2020;54(5):2941–2950. https://doi.org/10.1021/acs.est.9b05608
  4. Brazzola G, Grimm V, Patt A. Definitions and implications of climate-neutral aviation. Nat Clim Change. 2022;12:115–121. https://doi.org/10.1038/s41558-022-01404-7
  5. Braun M, Grimme W, Oesingmann K. Pathway to net zero: Reviewing sustainable aviation fuels, environmental impacts and pricing. J Air Transp Manag. 2024;117:102580. https://doi.org/10.1016/j.jairtraman.2024.102580
  6. Jagtap SS, Childs PR, Stettler ME. Conceptual design-optimisation of a subsonic hydrogen-powered long-range blended-wing-body aircraft. Int J Hydrogen Energy. 2024;96:639–651. https://doi.org/10.1016/j.ijhydene.2024.11.331
  7. Adler EJ, Martins JR. Energy demand comparison for carbon-neutral flight. Prog Aerosp Sci. 2024;152:101051. https://doi.org/10.1016/j.paerosci.2024.101051
  8. Melis DJ, Silva JM, Yeun R, Wild G. The effect of airline passenger anthropometry on aircraft emergency evacuations. Saf Sci. 2020;128:104749. https://doi.org/10.1016/j.ssci.2020.104749
  9. Song C, Shao Q, Zhu P, Dong M, Yu W. An emergency aircraft evacuation simulation considering passenger overtaking and luggage retrieval. Reliab Eng Syst Saf.2022;229:108851. https://doi.org/10.1016/j.ress.2022.108851
  10. Xu C, Witlox F. Understanding total evacuation time perception in airplane emergency: a stated preference approach. Safety Science. 2022;146:105540. https://doi.org/10.1016/j.ssci.2021.105540
  11. Ronchi E. Developing and validating evacuation models for fire safety engineering. Fire SafJ. 2021;120:103020. https://doi.org/10.1016/j.firesaf.2020.103020
  12. Xie W, Lee EWM, Cheng Y, Shi M, Cao R, Zhang Y. Evacuation performance of individuals and social groups under different visibility conditions: Experiments and surveys. Int J Disaster Risk Reduct. 2020;47:101527. https://doi.org/10.1016/j.ijdrr.2020.101527
  13. Wang K, Yuan W, Liang W, Yao Y. An optimal guidance strategy for fire evacuations: A hybrid modeling approach. J Build Eng. 2023;73:106796. https://doi.org/10.1016/j.jobe.2023.106796
  14. Wang X, Xia G, Zhao J, Wang J, Yang Z, Loughney S, Fang S, Zhang S, Xing Y, Liu Z. A novel method for the risk assessment of human evacuation from cruise ships in maritime transportation. Reliab Eng Syst Saf. 2023;230:108887. https://doi.org/10.1016/j.ress.2022.108887
  15. Roosenbrand E, van Manen J, Gillingwater D. Operational contrail minimisation of transatlantic flights through altitude diversions. Transp Res Part D Transp Environ. 2023;122:103902. https://doi.org/10.1016/j.trd.2023.103902.
  16. Wang S, Wang J, Wang X. Risk analysis of human evacuation aboard passenger ships based on fuzzy DEMATEL-ISM-BN. Ocean Eng. 2024;313:119520. https://doi.org/10.1016/j.oceaneng.2024.119520
  17. Liu Y, Zhang Z, Mao Z. Analysis of influencing factors in pre-evacuation time using interpretive structural modeling. Saf Sci. 2020;128:104785. https://doi.org/10.1016/j.ssci.2020.104785
  18. Akbar AE, Hassanain MA. BIM-based simulation tools for occupant evacuation: A scoping review. Facilities. 2023;41(9–10):623–645. https://doi.org/10.1108/F-01-2023-0006
  19. Fu M, Liu R, Ragan E. An immersive virtual reality experimental study of occupants’ behavioral compliance during indoor evacuations. Int J Disaster Risk Reduct. 2024;107:104420. https://doi.org/10.1016/j.ijdrr.2024.104420
  20. Martínez-Val R, Hedo J, Pérez E. Uncommon exit arrangement effects in airplane emergency evacuation. Proc Inst Mech Eng Part G J Aerosp Eng. 2018. https://doi.org/10.1177/0954410017714007
  21. Senanayake GP, Kieu M, Zou Y, Dirks K. Agent-based simulation for pedestrian evacuation: A systematic literature review. Int J Disaster Risk Reduct. 2024;111:104705. https://doi.org/10.1016/j.ijdrr.2024.104705
  22. Sun H, Han G, Zhang X, Ruan X. Grasping emergency dynamics: A review of group evacuation techniques and strategies in major emergencies. J Saf Sci Resil. 2025;6(1):1–20. https://doi.org/10.1016/j.jnlssr.2024.05.006
  23. Turgut Y, Bozdag CE. Modeling pedestrian group behavior in crowd evacuations. Fire Mater. 2022;46(2):420–442. https://doi.org/10.1002/fam.2978
  24. Xie W, Lee EWM, Lee YY. Simulation of spontaneous leader–follower behaviour in crowd evacuation. Automation in Construction. 2022;134:104100. https://doi.org/10.1016/j.autcon.2021.104100.
  25. Haghani M. Optimising crowd evacuations: Mathematical, architectural and behavioural approaches. Saf Sci. 2020;128:104745. https://doi.org/10.1016/j.ssci.2020.104745
  26. Aldahlawi RY, Akbari V, Lawson G. A systematic review of methodologies for human behavior modelling and routing optimization in large-scale evacuation planning. Int J Disaster Risk Reduct. 2024;110:104638. https://doi.org/10.1016/j.ijdrr.2024.104638
  27. Ronchi E, Reneke PA, Peacock RD. A method for the analysis of behavioural uncertainty in evacuation modelling. Fire Technology. 2014;50(6):1545–1571. https://doi.org/10.1007/s10694-013-0352-7
  28. MacGillivray BH. Handling uncertainty in models of seismic and postseismic hazards: Toward robust methods and resilient societies. Risk Anal. 2021;41(9):1499–1512. https://doi.org/10.1111/risa.13663
  29. Auza A, Asadi E, Chenari B. A systematic review of uncertainty handling approaches for electric grids considering electrical vehicles. Energies. 2023;16(13). https://doi.org/10.3390/en16134983
  30. Campolongo F, Saltelli A, Cariboni J. From screening to quantitative sensitivity analysis. A unified approach. Comput Phys Commun. 2011;182(4):978-988. https://doi.org/10.1016/j.cpc.2010.12.039
  31. Khalili SM, Mojtahedi M, Steinmetz-Weiss C, Sanderson D. A systematic literature review on transit-based evacuation planning in emergency logistics management: Optimisation and modelling approaches. Buildings. 2024;14(1). https://doi.org/10.3390/buildings14010176
  32. Andreadakis A, Dalaklis D. Systematic review of the problematic factors in the evacuation of cruise/large passenger vessels and existing solutions. Appl Sci. 2024;14(24). https://doi.org/10.3390/app142411723
  33. Zhang X, Zhang H, Wang S, Xiao Z, Zhang W. Analysis of the impact of small group behavior on cruise ship emergency evacuation. Appl Sci. 2023;13(17). https://doi.org/10.3390/app13179976
  34. Fu L, Cao S, Song W, Fang J. The influence of emergency signage on building evacuation behavior: An experimental study. Fire Mater. 2018;43(1):22–33. https://doi.org/10.1002/fam.2665
  35. Giannoulaki M, Christoforou Z. Pedestrian walking speed analysis: A systematic review. Sustainability. 2024;16(11). https://doi.org/10.3390/su16114813
  36. Santiago A, Butakoff C, Eguzkitza B, Gray RA, May-Newman K, Pathmanathan P, et al. Design and execution of a verification, validation, and uncertainty quantification plan for a numerical model of left ventricular flow after LVAD implantation. PLoS Comput Biol. 2022;18(6):e1010141. https://doi.org/10.1371/journal.pcbi.1010141
  37. Razavi S, Jakeman A, Saltelli A, Prieur C, Iooss B, Borgonovo E, et al. The future of sensitivity analysis: An essential discipline for systems modeling and policy support. Environ Model Softw. 2021;137:104954. https://doi.org/10.1016/j.envsoft.2020.104954
  38. Shao G, Hightower J, Schindel W. Credibility consideration for digital twins in manufacturing. Manuf Lett. 2022;35:24–28. https://doi.org/10.1016/j.mfglet.2022.11.009
  39. Gwynne MV, Kuligowski ED, Boyce KE, Nilsson D, Robbins AP, Lovreglio R, et al. Enhancing egress drills: Preparation and assessment of evacuee performance. Fire Mater. 2019;43(6):613–631. https://doi.org/10.1002/fam.2448
  40. Okonkwo P, Smith H. Review of evolving trends in blended wing body aircraft design. Prog Aerosp Sci. 2016;82:1–23. https://doi.org/10.1016/j.paerosci.2015.12.002
  41. Ma Y, Yuan J, Tan L, Liu Q, Li M. A model for aircraft cabin evacuation considering passenger type. J Saf Sci Resil. 2024;5(1):83–90. https://doi.org/10.1016/j.jnlssr.2023.12.002
  42. Xu C, Luo Y, Fuellhart K, Shao Q, Witlox F. Modeling exit choice behavior in airplane emergency evacuations. J Air Transp Manag. 2023;112:102450. https://doi.org/10.1016/j.jairtraman.2023.102450
  43. Lovreglio R, Kuligowski E, Gwynne S, Boyce KE. A pre-evacuation database for use in egress simulations. Fire Saf J. 2019;105:107–128. https://doi.org/10.1016/j.firesaf.2018.12.009
  44. Seike M, Kawabata N, Hasegawa M. Walking speed under emergency situation in smoke-filled tunnel with obstacles. Tunn Undergr Space Technol. 2023;133:104939. https://doi.org/10.1016/j.tust.2022.104939
  45. Chen K, Wang X, Li P, et al. Modeling and evaluating passenger evacuation and risk in blended wing body aircraft using continuous displacement agents. Discov Appl Sci. 2025;7:48. https://doi.org/10.1007/s42452-024-06325-y
  46. Sun X, Croke B, Roberts S, Jakeman A. Comparing methods of randomizing Sobol’ sequences for improving uncertainty of metrics in variance-based global sensitivity estimation. Reliab Eng Syst Saf. 2021;210:107499. https://doi.org/10.1016/j.ress. 2021.107499
  47. Nakayama MK, Tuffin B. Sufficient conditions for central limit theorems and confidence intervals for randomized quasi-Monte Carlo methods. ACM Trans Model Comput Simul. 2024;34(3):13. https://doi.org/10.1145/3643847
  48. Renardy M, Joslyn LR, Millar JA, Kirschner DE. To Sobol or not to Sobol? The effects of sampling schemes in systems biology applications. Math Biosci. 2021;337:108593. https://doi.org/10.1016/j.mbs.2021.108593
  49. Gobbin A, Khosravi R, Bardenhagen A. Emergency evacuation simulation of commercial aircraft: Influence of body- and behaviour parameters. SN Appl Sci. 2021;3:446. https://doi.org/10.1007/s42452-021-04295-z
  50. Galea ER. Investigating the expanded use of modelling and simulation for evacuation certifications using the airEXODUS Aircraft Evacuation Simulation Software. Washington (DC): Federal Aviation Administration; 2025. Available from: https://rosap.ntl.bts.gov/view/dot/82737
  51. Moustapha M, Sudret B. Surrogate-assisted reliability-based design optimization: A survey and a unified modular framework. Struct Multidiscip Optim. 2019;60:2157–2176. https://doi.org/10.1007/s00158-019-02290-y
  52. Li X, Yang Q, Wang Y, Han X, Cao Y, Fan L, Ma J. Development of surrogate models in reliability-based design optimization: A review. Math Biosci Eng. 2021;18(5):6386–6409. https://doi.org/10.3934/mbe.2021317
Language: English
Page range: 121 - 157
Submitted on: Feb 4, 2025
Accepted on: Mar 5, 2026
Published on: Mar 18, 2026
In partnership with: Paradigm Publishing Services
Publication frequency: 4 issues per year

© 2026 Arthur Conlas Dela Peña, published by ŁUKASIEWICZ RESEARCH NETWORK – INSTITUTE OF AVIATION
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.