Vulnerability, Uncertainty, and Risk ©ASCE 2014
Tools for an Extended Risk Assessment for Ropax Ship-Ship Collision 1 1 1 Floris Goerlandt , Jakub Montewka and Pentti Kujala 1
Aalto University, Department of Applied Mechanics, Marine Technology, Research Group on Maritime Risk and Safety, P.O. Box 15300, FI-00076 AALTO, Finland. email:
[email protected] ABSTRACT This paper presents an extended risk assessment for a ship-ship collision where the struck ship is a RoPax vessel in an open sea area. The assessment combines state-of-the-art engineering models for assessing probabilities of events and their consequences in a Bayesian Belief Network (BBN). The overall model rationale is briefly outlined and abridged results are shown. The main focus of the paper however is the application of a relatively recently proposed uncertainty/bias-based risk perspective. In particular, special attention is given to the inadequacy of the BBN to express all decision-relevant uncertainty. The applied risk perspective highlights that probabilities do not fully account for uncertainty in terms of the strength of the knowledge base for making these probability statements, i.e. for evidential uncertainty. Furthermore, probabilities stemming from calculations using results of engineering models are conditional to the underlying assumptions and simplifications in these engineering models, which may be value-laden. This is reflected through a qualitative assessment of evidential biases. As a novelty, a qualitative analysis of evidential uncertainty and bias is proposed using a sensitivity-uncertainty-bias matrix triplet and an uncertainty-bias justification table, supplementing the BBN-based quantification of uncertainty. 1. INTRODUCTION Maritime transportation poses various risks in terms of loss of lives, environmental pollution and loss of property (Klanac et al., 2010). Particularly accidents involving RoPax vessels, carrying a large number of passengers, entail a potential of significant loss of life. This paper describes a model for assessing the risk of RoPax ship-ship collisions in an open sea area. The assessment focuses on the number of lives lost in such an accident. Two main accident scenarios are considered: i) the collision can result in a breach of the inner hull, leading to subsequent flooding, which may in turn result in ship loss, and ii) the collision does not result in extensive hull damage but the RoPax is disabled and drifts, which can lead to significant rolling due to wave and wind action, and potentially to ship capsizing. The loss of the RoPax vessel and subsequent loss of life is modeled in terms of exceedance of suitable limit states, respectively related to crashworthiness and stability. The exceedance of these limits is conditional to a multitude of situational
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factors. These relate to i) the impact scenario by which the striking vessel hits the RoPax (i.e. vessel mass ratio, impact speeds, angle and location), affecting the hull rupture, ii) the damage extent and hull breach size leading to a significant water ingress, conditional to the rupture of the inner hull, iii) the hydro-meteorological conditions which contribute to the probability of capsizing given a significant water ingress and iv) the maximum roll angle under which an intact, disables RoPax vessel capsizes. 2. MODEL LAYOUT AND RESULTS 2.1. Qualitative model layout The qualitative part of the model, i.e. the model structure constituting the chain of events from collision to the occurrence of a number of fatalities and the factors to which this event chain is conditional, is based on expert judgment and results and work concerning holistic accidental risk assessment presented in the literature (Konovessis and Vassalos, 2008; Vanem et al., 2007). It is shown in Figure 1. The white nodes are used to calculate the F-N curves and are present for mathematical reasons. The content of the light grey nodes is based on results of engineering models or is taken from the literature. Dark grey nodes are based on author’s subjective probability assessment.
Figure 1. Qualitative layout of the BBN for RoPax collision risk assessment 2.2. Quantitative model content The node content in BBNs is typically elicited from experts, the number of required probabilities depending on the number of variables and their states. As the network is relatively complex and a large number of probabilities would have to be elicited, preference is given to model node probabilities using parametric probability distributions (PPDs). These can be seen as representing aleatory uncertainty in the case of possibly repeating system states (e.g. mass ratio and speed of encountering ships in an area) and in case engineering models are applied to derive distributions of probability of limit exceedance (e.g. hull rupture). Otherwise, these PPDs can be
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considered (approximate) representations of epistemic uncertainty, indicating a range of values which an assessor believes to reasonably reflect the probability of the various states occurring. The overall BBN thus applies a mixed frequentist and subjectivist probability interpretation as considered appropriate for the nature of the respective variable, which seems plausible given common interpretations of probabilities in quantitative risk analysis (QRA), see (Aven and Reniers, 2013; Watson, 1994). Table 1 presents an overview of the PPDs applied for the various nodes in the BBN. The content of many nodes is derived from a range of engineering models. Table 1. An overview of all variables in the BBN model for RoPax ship collision Factor Variable name group Collision The probability of collision - per year parameters Collision speed Collision angle Striking location Relative striking location Collision mass ration Limiting speed Inner hull rupture Machinery damaged Collision angle significant Damage extent significant Ships stay separated after collision Ship Weather capsizing DSC conditions Capsizing in DSC Capsizing as a result of flooding Time taken to capsize in DSC Time taken to capsize flooding Probability of loss of life - flooding Probability of loss of life - DSC Probability of loss of life given Probability of loss of life given collision and DSC Accident Time of day response Evacuation time
Results
Variable symbol Pcoll V(A,B) α m r cmr Vru pture ihr md α sign des sss W DS C C DS C C f looding T T C DS C T T C f lood PLL| f lood PLL|DS C PLL|coll| f lood
PLL|coll|DS
Expression governing variable Unif(0.07, 0.007) If(α 135, N(14.2, 5.53), N(10.86,8.26))) Unif(10, 170) If(Unif(0,10)>8,1,0) Unif(-0.5,0.5) Logn(0.2548,0.7014) f(r,cmr,α) If(VA,B > Vru pture , 1, 0) If(And(ihr=1,m=1),1,If(And(ihr=0,m=1),0.5,0)) If(And(α45),1,0) If(And(ihr=1,cmr7,α s =1),1,0) If(And(V(A,B) >10,cmr
