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HOW TO ASSESS EXTERNAL EXPLOSION PRESSURE WAVES
J. Hauschild •
TÜV NORD SysTec GmbH & Co.KG, Hamburg, Germany e-mail: ¡hauschild@tuev-nord.de
H.-P. Berg •
Bundesamt für Strahlenschutz, Salzgitter, Germany e-mail: hberg@bfs.de
ABSTRACT
External hazards can be safety significant contributors to the risk in case of operation of industrial plants. This has been strongly underlined by the nuclear accidents at Fukushima-Daiichi in March 2011.The paper concentrates on the procedure to assess external hazard explosion pressure waves within probabilistic safety assessment. This assessment starts with a screening procedure in order to determine scope and content of the analysis. The second step is to choose an appropriate approach in case that a full scope analysis has to be performed. Several methods can be applied to evaluate the probability of occurrence of an external explosion event at a plant. The presented results indicate that the probability of occurrence of external explosion pressure waves can be successfully assessed by means of the Monte Carlo simulation, in particular in difficult site-specific conditions.
1 INTRODUCTION
External hazards (e.g. earthquake, flooding including tsunamis, external explosion) can be safety significant contributors to the risk in case of nuclear power plant operation because such hazards have the potential to trigger initiating events simultaneously and reduce the level of redundancy by damaging redundant systems or their supporting systems. This has been strongly underlined by the nuclear accidents at the Fukushima-Daiichi nuclear power plants in March 2011.
Therefore, comprehensive safety assessments have to be performed in advance with most actual site-specific data und current knowledge of new research results. Potential methods to analyse existing plants, in particular those built to earlier standards, systematically regarding the adequacy of their existing protection against different types of hazards are deterministic as well as probabilistic.
For all external hazards the first step is a screening process in order to determine scope and content of the assessment to be performed. The approach for these screening processes is different for each type of external hazard.
This paper deals with the assessment of external explosion pressure waves, resulting from accidents of transport means on the road, railway or river, and the calculation of their probabilities at the plant under consideration.
Although some part of this paper is correlated to the application with respect to nuclear power plants, the presented approach is independent from the type of installation and can also be applied to other industrial plants.
In contrast with almost all internal hazards, external hazards can simultaneously affect the whole plant, including back up safety systems and non-safety systems alike.
The assessment of external hazards requires detailed knowledge of natural processes, along with the plant itself and the whole site layout. In addition, the potential for widespread failures and hindrances to human intervention can occur. For multi-plant sites this makes the situation even more complex and it requires appropriate interface arrangements to deal with the potential effects on several facilities.
An explosion is a rapid and abrupt energy release, which produces a pressure wave and/or shock wave. A pressure wave has a certain pressure rise time, whereas a shock wave has zero pressure rise time.
Explosion is used broadly to mean any chemical reaction between solids, liquids, vapours or gases which may cause a substantial rise in pressure, possibly to impulse loads, fire or heat. An explosion can take the form of a deflagration or a detonation.
In deflagrations, the reaction zone travels through the explosive mass at subsonic speed, while the propagation mechanism is heat transfer (by conduction, radiation and convection). Reaction zone propagation velocities (flame speeds) of deflagrations may vary over a wide range and so do the corresponding explosion pressures. One example of a deflagration experiment is shown in Figure 1; in this case the deflagration was very short and lasted less than one second.
Figure 1. Experiment of a deflagration (Shepherd 2007)
The major characteristic of a detonation is its extremely high speed: the explosion zone moves at a supersonic speed. While, for deflagrations the flame speeds are low (typically one to several hundreds of metres per second), detonation flame speeds in air can easily reach one to two kilometres per second.
The propagation mechanism of a detonation is an extremely rapid and sharp compression occurring in a shock wave as one can see from Figure 2. In contrast to a reversible adiabatic compression, shock compression occurs irreversibly (non-isotropic), due to the extreme rapidity with which it occurs.
Both types of explosion pressure waves (caused by detonation of liquids or solid explosives or air-gas mixtures and such pressure waves caused by deflagrations of only air-gas mixtures) have to be taken into account in the safety assessment of the plant under consideration.
In order to determine scope and content of the assessment to be performed the first step of the assessment is a screening procedure.
The second step is to propose an appropriate approach for those cases where a full scope analysis has to be performed.
Figure 2. Detonation as the strongest type of explosion (Shepherd 2007)
In the latter case several methods can be applied to evaluate the probability of occurrence of an external explosion event, in particular fault tree analysis, event tree analysis and Monte Carlo simulation.
The results presented in the following illustrate that the probability of occurrence of external explosion pressure waves can be successfully assessed by means of the Monte Carlo simulation.
2 GUIDANCE ON ASSESSING EXTERNAL EVENTS
Since 2005, a revised guideline for a probabilistic safety assessment (BfS 2005) as well as revised and extended supporting technical documents (FAK PSA 2005a and 2005b) are issued in Germany which describe the methods and data to be used in performing probabilistic safety assessment in the frame of comprehensive safety reviews.
In these documents, probabilistic considerations of aircraft crash, external flooding, earthquake and explosion pressure waves are required. Also on international level, new recommendations regarding external hazards including explosions pressure waves are recently issued (see, e. g., IAEA 2003a, 2009, 2010).
For the site evaluation for nuclear installations which will be built in the future safety requirements have been developed (IAEA 2003b). In that context activities in the region that involve the handling, processing, transport and storage of chemicals having a potential for explosions or for the production of gas clouds capable of deflagration or detonation shall be identified.
Hazards associated with chemical explosions shall be expressed in terms of overpressure and toxicity (if applicable), with account taken of the effect of distance. A site shall be considered unsuitable if such activities take place in its vicinity and there are no practicable solutions available.
The safety assessment should demonstrate that threats from external hazards are either removed, minimised or tolerated. This may be done by showing that safety related plant buildings and equipment are designed to meet appropriate performance criteria against the postulated external hazard, and by the provision of safety systems which respond to mitigate the effects of fault sequences.
Explosion pressure waves with relevance to the site can be caused by shipping, fabrication, storage and reloading of explosive materials in closer distances to a nuclear power plant or any other industrial plant with a high hazard potential (e. g., process industry).
These different causes lead to two significant different types of risky situations for the site and the plant which have to be assessed within a probabilistic safety assessment:
1. The explosive material is available as a stationary source in the neighbourhood of the plant under consideration (e.g., a storage or a fabrication facility).
2. The explosive material is mobile, i.e. it is shipped in close distance to the plant on the road, by train or on ships along a river or the sea nearby.
In the latter case, the situation is not stable and changes with the varying distances. Moreover, the transport way could be a straight line or a bent which has to be addressed in the calculations -see (Hauschild & Andernacht 2010) for a straight road and (Berg & Hauschild 2010) for a bent river.
Usually, a uniformly distributed accident probability is assumed along the transport way. However, in reality the accident probability may increase in junctions or confluences and - in case of rivers and roads - in curves or strictures. Such on example is explained in section 5 in more detail.
Accidents with explosive material are not only theoretical considerations but happen in reality, sometimes with catastrophic consequences. One extremely severe transportation accident took place in June 2009 in Viareggio which resulted in comprehensive safety evaluations (Pontiggia et al. 2010). Although no industrial plant was damaged in this accident, the potential explosion severity is visible. The accident followed the derailment of a train carrying 14 tank cars of liquefied petroleum gas. The first tank car was punctured after the derailment releasing its entire content that ignited causing an extended and severe flash-fire that set on fire several houses and lead to 31 fatalities.
A more recent accident happened in January 2011 on the river Rhine in Germany, fortunately without any environmental consequences. However, a ship capsized and blocked for many weeks the river for other transportation but, in particular, had the potential to lead to an explosion because - in addition to 2400 tons mainly of sulphuric acid - one tank also contained water and hydrogen.
8 SCREENING PROCESS
In a first step, the important areas of the plant are divided into the three classes A, B and C for the analysis of explosion pressure waves to reflect the degree of protection against the impact by the explosion pressure waves. These classes are the same as for the consideration of aircraft crashes (Berg 2005).
Class A contains systems, where in case of their damages a hazard state directly arises or where an initiating event may occur which cannot be controlled by the emergency cooling system.
Class B contains systems where in case of their damages a hazard state not directly arises, but where an initiating event may occur which is controlled by the emergency cooling system. Class C contains these safety systems needed for core cooling. Typical examples of these different classes are (Berg 2010): A: e.g. primary circuit, B: e.g. turbine building, C: separated emergency building.
Basic idea in case of explosion pressure waves is a prescribed check if the frequency of core damage states is less than 1E-07 per year for the plant under consideration. This is the case when
■ the total occurrence frequency of the event "explosion pressure wave" (i.e. the sum of all contributions from detonation and deflagration) is determined to be less than 1E-05 per year,
■ the building of classes A and C are designed against the load assumptions shown in Figure 3,
the safety distances according to the BMI guideline (BMI 1976) are fulfilled, based on the formula (1):
R = 8 m ■ 3
L_ kg
(1)
with
R = safety distance (in m) of the place where the explosive gas is handled from to the
respective plant which should be larger than 100 m, and L = assumed mass of the explosive material (in kg).
It should be noticed that the total mass to be assumed depends on the type of explosive material.
For the case that the prerequisites of this prescribed check are met, no further probabilistic considerations are necessary.
Figure 3. Pressure behaviour at the building for a single pressure wave according to (BMI 1976).
Otherwise the procedure has to be in accordance with the graded process of evidence regarding explosion pressure waves as presented in Table 1 (Berg & Hauschild 2011).
Table 1. The graded process of analysing explosion pressure waves
Criteria Extent of analysis
Occurrence frequency <1E-05 per year Verification using the prescribed check
Classes A and C are designed according to load assumptions and safety distances determined in length lR according to (BMI 1976)
Not fulfilled Conservative estimation of occurrence
frequency
Fulfilled
Not fulfilled Detailed probabilistic safety analysis
Not fulfilled
4 METHODS AS RECOMMENDED IN THE GERMAN PSA DOCUMENT FOR NUCLEAR POWER PLANTS
4.1 Introduction
The German PSA document on methods (FAK PSA 2005a) describes the approaches to be used in the probabilistic safety assessment which have to be performed in the frame of comprehensive safety reviews of nuclear power plants.
One part of this approach is dedicated to the screening process already explained in section 2, the further parts of this document deal in more detail with the occurrence frequency of explosion pressure waves taking into account the site-specific situation, sources of possible explosion pressure waves in the surrounding of the plant, and the procedure for the calculation of occurrence frequencies of accidents during transportation of explosive material by ships, trains or trucks and of accidents of stationary plants near the plant under consideration.
4.2 Assessment
In case that the plant buildings classified as A and C are designed according to the BMI guideline (BMI 1976) and the safety margins regarding distance and mass of the explosive material are kept, it can be assumed that in the most unfavourable case of an explosion pressure wave event
■ no event is initiated which directly leads to a hazard state,
■ due to the event explosion pressure wave a system failure occurs in the class B and an initiating event is initiated which can be controlled by the emergency cooling system as designed,
■ the emergency cooling system is protected against the effects of the event explosion pressure wave.
In the most unfavourable case, a loss of offsite power with destruction of the secondary plant parts (main heat sink, feed water supply) can be assumed, which occurs with the total occurrence frequency of the event explosion pressure wave. It is assumed for simplifying the analysis that together with the occurrence of this event those systems which are outside of the classes A and C fail.
For the calculation of the frequency of the hazard state, resulting from explosion pressure waves, this initiating event and the incident-controlling functions of the emergency cooling system (stochastic non-availabilities) are to be modelled and quantified in an event tree (or using another appropriate method).
The frequency of the event explosion pressure wave to be chosen is the sum of all contributions of the events detonation and deflagration, as far as they can lead to an hazardous state of the plant, resulting from accidents during transportation procedures or the operation of stationary plants in the surrounding of the plant under consideration.
The occurrence frequency of a detonation is several orders of magnitude lower compared with a deflagration (Federal Minister for Research and Development 1990). As far as the distance of the area where the deflagration started has a distance larger than 100 m from the plant under consideration (see safety margins in accordance with (BMI 1976), no endangerment of the plant buildings has to be assumed.
In case of accidents with materials with the potential of a detonation (in particular explosives, ammunition, gases exothermically disintegrating) the detonation is expected to occur at the accident location, i.e. at a transport route or a fixed industrial installation. Here the approach as provided in formula (2) is applied:
H = H ■ W (2)
11 E,SMZ 11 U,SMZ ''Z V*)
with
HE,SMZ Annual frequency of a explosion pressure wave by explosives, ammunition or gases exothermically disintegrating in the surroundings of the nuclear power plant,
HU,SMZ Annual frequency of accidents with explosives, ammunition or gases exothermically disintegrating in the surroundings of the nuclear power plant,
WZ Conditional probability of the ignition in an accident.
The deflagration pressure of max. 10 bar drops over 100 m around a factor 1E04, so that within the power station pressure values within the range of the wind pressures are reached.
In case of explosive gas air mixtures (combustible gases with air; inflammable steams, e.g. also of liquid gas, with air) clouds can be appear and a drifting of these clouds from the place where the accident happened into the direction of the plant is possible.
In this situation the deflagration can take place in the area of the plant buildings. The approach applied for this case is described in the following equation (Federal Minister for Research and Development 1990):
H E,GLG ~ HU,GLG ' WM ■ WD ■ WZ (3)
with
HE,GLG Annual frequency of an explosion pressure wave by gas air mixtures in the surroundings of the nuclear power plant,
HU,GLG Annual frequency of accidents with combustible gas in the surroundings of the nuclear power plant,
WM Conditional probability for the development of an explosive gas air mixture in case of an accident with combustible gas,
WD Conditional probability for drifting the gas air mixture to the nuclear power plant (as a result of temporal averaging of the arising wind directions),
WZ Conditional probability of the ignition at the area of the plant.
In a more detailed verification the assumptions introduced can be replaced by plant-specific proofs, considering the different effects of the determined explosion pressure waves.
In the case of a deviation from the BMI guideline (BMI 1976) partial results of the total occurrence frequency of the event arise which contribute directly to the frequency of the hazard states. These contributions are to be determined by a differentiated view of the assigned explosion pressure waves and their effects.
5 MONTE CARLO SIMULATION
5.1 Application
The following application is a case study that represents the evaluation of the probability of
occurrence of an external explosion pressure wave that takes place near a plant. The probability of
occurrence is assessed on the condition that an accident with combustible gas already occurred.
The application is not restricted to a special field of industry; plants of process industry might be in the focus as well as nuclear power plants. It is assumed that the external explosion pressure wave is initiated by an accident of a gas-tanker that carries explosive liquids on a river.
Although the application is described in a generalized way, it incorporates several elements that are typical in order to assess the impact of explosion pressure waves: accident, wind direction, wind speed and ignition.
It should be noticed that the events, boundary conditions and parameters given in Figure 4 to 7 and Tables 2 and 3 are only example values and do not represent conditions of any specific application.
5.1.1 Plant environment
The plant and its environment are depicted in Figure 4. The length lS of the section of interest is 4800m and the width wS is 1800m. The river is subdivided into 7 subsections; each subsection is characterised by an individual length, width and gas-tanker accident frequency.
Figure 4. Plant environment and hazardous scenario. The vertical distance between the plant and the river is between 440m (dR-1) and 780m (dR-
2).
In the given application ships can reach every location at the river. An accident at the river-coordinate (xi, yi) may cause the development of explosive gas mixture.
Depending on the wind direction ^ the cloud of gas mixture can drift to the plant. An ignition of the gas mixture close to the plant (within the radius rP) is in the focus of this study. All relevant application parameters of Figure 4 are given in Table 2.
Table 2. Relevant application parameters
Description
Parameters
length ls 4800m
width ws 1800m distance [dR-1, dR-2] [440m, 780m]
radius rP 150m
plant 100m x 100m
5.1.2 Assumptions
The case study depends on the following assumptions:
Empirical-distributed accident probability depending on the subsection of the river on condition that the accident already occurred. It is assumed, that the accident frequency is higher in sections with confluences or curves than in straight river-sections. Uniformly-distributed accident-coordinate (xi, yi) on condition that the accident occurred in the river-section i.
The development of explosive gas mixture occurs with fixed probability wG. Empirical-distributed wind direction. Empirical-distributed wind speed.
Exponentially-distributed ignition probability depending on the time. An explosion within the radius rP around the plant is in the focus of this study. The parameters and distribution models are given in Figures 5 to 7 and Table 3.
12 3 4 5 6 7 Figure 5. Empirical accident river-section frequencies.
■
Table 3. Parameters and distribution models
Description
Distribution
Parameters
accident river-section accident (x, y)-coordinate development of explosive gas mixture
wind direction 9 wind speed vW time t to ignition
empirical U(a, b) fixed probability empirical empirical Exp(X)
depending on river-section 0,3
Exp(0,01 s-1)
5.2 Basics
5.2.1 Monte Carlo Simulation
Detailed basics of the Monte Carlo simulation like random sampling, estimators and biasing techniques are specified for example in (Dubi 2000) and (Marseguerra & Zio 2002). In (Berg & Hauschild 2010), (Hauschild & Andernacht 2009) and (Hauschild & Andernacht 2010) the Monte Carlo simulation has been applied and verified successfully in order to estimate the probability of external explosion pressure waves.
Figure 6. Empirical wind-direction frequencies. 5.2.2 Distribution Models in use
The pdf of the uniform distribution U(a, b) with the parameters a < b is given by
1
f ( x) =
b - a
for a < x < b.
(4)
The pdf of the exponential distribution exp(X) with the parameter X > 0 is given by
f (x) = X • exp(-X • x) for x > 0.
(5)
Figure 7. Empirical wind-speed frequencies.
5.2.3 Estimators in use
As the last event estimator (lee) (Marseguerra et al. 1998) is used to predict the probability of an event (e.g. an explosion event), the observed frequency of explosions within the radius rP is determined. The sample mean probability is
1 N
pE = - PE (0
N ^ (6)
where PE(i) e {0, 1} and N = number of trials.
An alternative method is to compute the theoretical probability of an explosion event within the radius rP in each scenario the wind direction will move the explosive gas mixture to the plant. The advantage over the lee is that each scenario gives a contribution to the probability of occurrence. By analogy with transport theory, this procedure is called free flight estimator (ffe) (Marseguerra et al. 1998). Depending on the accident coordinate (xi, yi), the wind direction 9i and the wind speed vWi in trial i, the probability of an explosion event within the radius rP is given by
Pe (X V, ) = exp(-A •1 / vWl • di (xt, v, ))
- exp(-A • 1/ VWi • d2 (xi , V )) (7)
where di(x, 9) and d2(x, 9) are the distances between the accident coordinate and the intersection of the wind direction and the plant area with radius rP.
The intersection coordinates (xI, yI) of the wind direction 9 and the plant area with radius rP are determined by means of
X1 + (yt + tan(V, ) • (X - X ))2 = rp (8)
and
y I = ( yt + tan( V ) • ( XI - X ))2. (9)
The sample mean probability is
1N
PE PE ( X, , V, )
N i=i (10)
where N = number of trials. 5.3 Analysis
The Monte Carlo simulation is performed by means of the last event estimator and the free flight estimator.
The algorithm to model and solve the problem is based on the German PSA guideline (BfS 2005) and the supporting technical document on PSA methods (FAK PSA 2005a). The Monte Carlo simulation depends on a sequence of single events:
■ accident river-section: empirical-distributed (Figure 5),
■ accident (x, y)-coordinate: uniformly-distributed on condition that the accident occurred in the river-section i,
■ development of explosive gas mixture: fixed probability (0,3),
■ wind-direction 9: empirical-distributed (see Figure 6),
■ wind-speed vW: empirical-distributed (see Figure 7),
■ time t to ignition: Exp(0,01 s-1)-distributed.
5.4 Results
The results of the Monte Carlo simulation are evaluated on the condition that the accident already occurred.
In order to assess the frequency of occurrence of an external explosion event the frequency of accidents with combustible gas has to be considered. It should be noticed, that the results for the frequency of occurrence of an external explosion event will be several magnitudes lower than the results for the conditional explosion event probability given in this paper.
Different ranges of conditional explosion-probability PE are depicted in Figure 8 and 9.
Areas with higher gray-level intensity represent higher conditional explosion-probability. In order to compare the results to the conditional explosion event probability PE close to the plant (within the radius rP) the results in Figure 8 are normalised on the plant area rc-rP2.
The number of trials, the simulation time and the results like mean value and variance are listed in Table 4.
Figures 8 and 9 indicate that the conditional explosion event probability decreases as the distance to the river (place of the assumed accident) increases. This is due to the exponentially distributed ignition probability which depends on the time or the distance to the accident.
Close to the river-sections 2 and 3 the conditional explosion event probability increases, this is due to the higher accident frequency in these sections combined with the specific wind-direction frequencies.
As the different Monte Carlo methods given in Table 4 are compared it can be found out, that both solutions fit a mean about 1,2E-03 which verifies the results as well as the adopted different Monte Carlo algorithms.
If the variance is regarded, the Monte Carlo simulation in combination with the free flight estimator is the most efficient approach.
Figure 8. Ranges of conditional explosion event probability PE - normalised on 1m2.
(x
-1000 v -500 ""^.000 -1500 1 1000 2000
Figure 9. Ranges of conditional explosion event probability PE - normalised on the plant area rc-rP2. Table 4. Conditional probability of an explosion event within the plant area with radius rP
Method Trials Time Mean Variance
analog MCS - lee 1E06 60.7s 1.21E-03 1.20E-03
analog MCS - ffe 1E06 65.1s 1.23E-03 1.13E-04
6 CONCLUDING REMARKS
6.1 Countermeasures to avoid or mitigate the adverse effects of external explosions
Knowledge of the explosion characteristics and the structural impact on buildings of the respective plant is necessary to determine the appropriate countermeasures in order to ensure a safe operation of the plant. However, fundamental changes of the plant under consideration are mainly possible only during the design and construction phase. In case of a plant already operating since several years, the implementation of effective countermeasures is much more difficult or even not possible.
On the one hand, comprehensive calculations can be performed to show that existing assumptions in the calculation provided for the licensing of the plant have been very conservative.
On the other hand, organizational and technical provisions can be taken to reduce the occurrence of an external explosion pressure wave at the plant.
One organizational possibility is to interdict the transport of explosive material, e.g. on a road, in the neighbourhood of the plant. Another solution is to close the road for transit traffic such that the road is only leading to the plant.
One technical countermeasure to reduce the explosion frequency on site is the installation of an automatic ignition system placed at a save distance from the site. An assessment has been performed for such an installation which showed that - if the igniters are correctly designed and installed - the shock wave impact after an ignition on the buildings will be limited and will not cause any structural damage.
6.2 Modelling of external explosions and potential for improvements of the methods
The evaluation of external hazards in relation to nuclear power plant design is traditionally considered as a two-step process. The detailed evaluation is preceded by a screening phase where potential scenarios are identified. Many scenarios are screened out on the basis of different criteria, such as distance from the site, probability of occurrence, expected consequence on the plant, or because their effects on the plant are expected to be enveloped by some others. Typically, explosion pressure waves are part of the probabilistic safety assessment as in case of comprehensive periodic safety reviews.
In the German safety guidance document on methods (FAK PSA 2005a) the screening process for the explosion events is explicitly described. The classes of buildings with respect to their protection are the same as for the aircraft crash assessments. Since the updated PSA guideline has been issued in 2005 also requiring the assessment of external events, first practical experience in performing and reviewing the external probabilistic safety assessments are available. One topic is the assessment of the conditional probability of the occurrence of external explosion pressure wave and the discussion of appropriate methods according to the state of art.
The procedure and methods applied are used for the evaluation of external explosion pressure waves with respect to nuclear power plants. However, they can also be applied to other types of industrial plants.
The presented case study and its results (Figures 7 to 8 and Table 4) in the second part of this paper indicate that the conditional probability of occurrence of external explosion pressure waves in consideration of realistic conditions (accident frequency depending on environmental conditions, wind direction and wind speed) can be successfully assessed by means of the Monte Carlo simulation.
As a next step the assessment of explosion events should be extended to include much more realistic boundary conditions:
■ the extent of the hazard and the explosive gas mixture,
■ ignition probability that depends on environmental conditions (Hauschild & Schalau 2011). Different ignition models are discussed in (Drewitz et al. 2009). The applied model should be
more realistic like the applied exponentially-distributed ignition model; moreover the applicability to integrate the new ignition model into Monte Carlo algorithm should be given.
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