Abstract
Environmental risk management consists of making decisions on human activities or construction designs that are affected by the environment and/or have consequences or impacts on it. In these cases, decisions are made such that risk is minimized. In this regard, the forthcoming paper develops a close form that relates risk with cost, hazard, and vulnerability; and then focuses on vulnerability. The vulnerability of a system under an external action can be described by the conditional probability of the degrees of damage after an event. This vulnerability model can be obtained by a simplicial regression of those outputs, as a response variable, on explanatory variables. After a theoretical explanation, the authors present the case study of a nuclear power plant containment building. Once a given overpressure is registered inside the containment building, three possible outputs are to be considered: serviceability, breakdown, and collapse. The study consists of three steps: (a) modelling the containment building using the finite element method; (b) given an overpressure, simulating uncertain parameters related to material constitutive equations in order to obtain the corresponding proportions; (c) performing a simplicial regression to obtain a meaningful vulnerability model. The simulation provides normalized-to-unity outputs under the overpressure conditions. The obtained vulnerability model is in definite correspondence with previous results in nuclear power plant safety analysis reports.
Similar content being viewed by others
References
Aguado A, Vives A, Egozcue J, Mirambell E (1991) Consideraciones sobre las bandas de tolerancia de la fuerza de pretensado en edificios de contención de centrales nucleares. 2as Jornadas Ibero-Latinoamericanas del Hormigón Pretensado 481–508
Aitchison J (1986) The statistical analysis of compositional data. Monographs on statistics and applied probability. Chapman & Hall Ltd., London. (Reprinted in 2003 with additional material by The Blackburn Press)
Aitchison J, Shen SM (1980) Logistic-normal distributions: some properties and uses. Biometrika 67(2):261–272
Aitchison J, Barceló-Vidal C, Egozcue JJ, Pawlowsky-Glahn V (2002) A concise guide for the algebraic-geometric structure of the simplex, the sample space for compositional data analysis. In: Bayer U, Burger H, Skala W (eds), Proceedings of IAMG’2002—the annual conference of the International Association for Mathematical Geosciences, Vol I and II, pp 387–392. Selbstverlag der Alfred-Wegener-Stiftung, Berlin
Barbat AH, Cervera M, Cirauqui C, Hanganu A, Oñate E (1995) Evaluación de la presión de fallo del edificio de contención de una central nuclear tipo PWR-W. Parte 2: Simulación numérica. Revista Internacional de Métodos Numéricos para Cálculo y Diseño en Ingeniería 11:451–475
Benjamin JR, Cornell AC (1981) Probabilidad y Estadística en Ingeniería Civil. McGraw-Hill, Bogotá 685 p
Cervera M, Barbat AH, Hanganu A, Oñate E, Cirauqui C (1995) Evaluación de la presión de fallo del edificio de contención de una central nuclear tipo PWR-W. Parte 1: Metodología. Revista Internacional de Métodos Numéricos para Cálculo y Diseño en Ingeniería 11:271–294
Consejo de Seguridad Nuclear (2011) Pruebas de resistencia realizadas a las centrales nucleares españolas. Informe final tras el accidente de Fuckushima Daiichi
Crusells-Girona M (2011) Design criteria of containment buildings for nuclear power plants. Revista de Obras Públicas 158(3523):31–46
Egozcue JJ (2009) Reply to “On the Harker variation diagrams;..” by J. A. Cortés. Math Geosci 41(7):829–834
Egozcue JJ, Daunis-i-Estadella J, Pawlowsky-Glahn V, Hron K, Filzmoser P (2012) Simplicial regression. The normal model. J Appl Prob Stat (JAPS) 6(1—-2):87–108
Egozcue JJ, Pawlowsky-Glahn V (2005) Groups of parts and their balances in compositional data analysis. Math Geol 37(7):795–828
Egozcue JJ, Pawlowsky-Glahn V, Mateu-Figueras G, Barceló-Vidal C (2003) Isometric logratio transformations for compositional data analysis. Math Geol 35(3):279–300
Embrechts P, Klppelberg C, Mikosch T (1997) Modelling extremal values. Springer Verlag, Berlin
Hammersley JM, Handscom J (1964) Monte Carlo methods. Springer, New York
Hibbitt K, Sorensen (2002) ABAQUS/CAE user’s manual. Hibbitt, Karlsson & Sorensen, Incorporated, Pawtucke
International Atomic Energy Agency (2001) Risk management: a tool for improving nuclear power plant performance. IAEA-TECDOC-1209
Jankowiak T, Lodygowski T (2013) Identification of parameters of concrete damage plasticity constitutive model
Lubliner J, Oliver J, Oller S, Onate E (1989) A plastic-damage model for concrete. Int J Solids Struct 25(3):299–326
Pawlowsky-Glahn V, Egozcue JJ (2001) Geometric approach to statistical analysis on the simplex. Stoch Environ Res Risk Assess (SERRA) 15(5):384–398
Pawlowsky-Glahn V, Egozcue JJ, Tolosana-Delgado R (2015) Modeling and analysis of compositional data. Statistics in practice. Wiley, Chichester
Tolosana-Delgado R, van den Boogaart K (2011) Linear models with compositions in R, Ch 26. In: Pawlowsky-Glahn V, Buccianti A (eds) Compositional data analysis: theory and applications. Wiley, Chichester
Tolosana-Delgado R, von Eynatten H (2009) Grain-size control on petrographic composition of sediments: compositional regression and rounded zeroes. Math Geosci 41:869–886
U.S. Nuclear Regulatory Commission (1984) Probabilistic safety analysis procedures guide. NUREG/CR-2815
U.S. Nuclear Regulatory Commission (2006) Containment integrity research at sandia national laboratories. an overview. NUREG/CR-6906
U.S. Nuclear Regulatory Commission (2007) Design limits, loading combinations, materials, construction, and testing of concrete containments. Regulatory Guide 1.201. Revision 1
U.S. Nuclear Regulatory Commission (2010) Containment structural integrity evaluation for internal pressure loadings above design-basis pressure. Regulatory Guide 1:216
U.S. Nuclear Regulatory Commission (2015) Guidelines for categorizing structures, systems, and components in nuclear power plants according to their safety significance. Regulatory Guide 1.136. Revision 3
Acknowledgments
This research has been supported by the Spanish Ministry of Education, Culture, and Sports under a scholarship (BOE n. 190, August 9th, 2012) to collaborate with the Department of Applied Mathematics III at UPC-BarcelonaTech from September 2012 to June 2013. The research has also been supported by the Spanish Ministry of Science and Technology under projects ‘Ingenio Mathematica (i-MATH)’ (Ref. No. CSD2006-00032) and ‘CODA-RSS’ (Ref. MTM2009-13272); from the Spanish Ministry of Economy and Competitiveness under the project ‘METRICS’ (Ref. MTM2012-33236), and from the Agència de Gestió d’Ajuts Universitaris i de Recerca of the Generalitat de Catalunya under the project Ref. 2009SGR424.
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Musolas, A., Egozcue, J.J. & Crusells-Girona, M. Vulnerability models for environmental risk assessment. Application to a nuclear power plant containment building. Stoch Environ Res Risk Assess 30, 2287–2301 (2016). https://doi.org/10.1007/s00477-015-1179-1
Published:
Issue Date:
DOI: https://doi.org/10.1007/s00477-015-1179-1