SECURITY RISKS AND SAFETY HAZARDS FOR BUILDING FACADES

M.D. Netherton & M.G. Stewart, The University of Newcastle, NSW, Australia

ABSTRACT

Building facades in commercial and residential buildings in Australia, UK and elsewhere are highly

vulnerable to terrorist threats involving explosive blast loading. The modelling of consequences to built

infrastructure when subject to blast loading is well developed; however, considerable uncertainty remains

with respect to system response and explosive loading parameters. In this paper, structural facades are

assessed - with a focus on glazing - as this is a structural and load-capacity system that poses significant

safety hazards when effected by explosive blast loads. A new computational tool that undertakes a

probabilistic risk assessment procedure is developed to predict damage and safety hazard risks following

blast loading of glazing. The software tool is called "Blast-RF" (Blast Risks for Facades). The structural

reliability analysis uses stress limit states and the UK Glazing Hazard Guide's rating criteria to calculate

probabilities of glazing damage and safety hazards conditional on a given blast scenario. The reliability

analysis considers the variability of explosive material energetic output (pressure, impulse) glazing stress

limit, fragment drag coefficient, glazing dimensions, stand-off distance and explosive weight. This

allows the prediction of likelihood and extent of damage and/or casualties; information which will be

useful for risk mitigation considerations, emergency service's contingency and response planning,

collateral damage estimation, weaponeering and post-blast forensic analysis.

1. INTRODUCTION

Damage to infrastructure from explosive blast

loads is a threat that will remain as a potential

hazard into the future; particularly in terms of

terrorism, where a favoured method of attack is

via Vehicle Borne Improvised Explosive Devices

(VBIEDs) detonated within urban environments.

The use of terrorist-style explosive blast loads

within urban environments typically aims to

maximise disruption, damage or destruction to

infrastructure, public systems or people. Military

planners, on the other hand, try to minimise

collateral damage that may occur as a result of

ordnance delivered into areas where civilian

infrastructure and military targets are in close

proximity, which tends to also occur in complex

urban environs.

Nearly all current explosive blast modelling

techniques are deterministic and design tools and

specifications are likely to be conservative (i.e.,

provide an upper bound value of damage or safety

hazard). The ability to obtain a deterministic result

to a problem is naturally very attractive to decision

makers. However, such confidence is illusory, as

deterministic methods fail to consider degrees of

uncertainty associated with many aspects of

threats and vulnerabilities and the degree of

conservatism in predictions is not known. One

method for dealing with such uncertainties utilises

structural reliability theory, where quantitative

advice can be provided to decision makers in the

form of probabilities of damage or safety hazard.

Society readily accepts the use of probabilistic

techniques in risk-based decision-making and

applies them to a range of potentially hazardous

industries and situations [1].

The need for a decision-making framework that

enables security and blast risks to be quantified in

a rational and consistent manner has been widely

recognized and decision frameworks for security

risk management developed. Although a number

of decision frameworks exist, these are often

developed for initial risk screening or

ranking/prioritisation purposes, and so a key issue

which is largely unresolved is the quantification of

security risks and effectiveness and costs of

mitigating measures. However, the quantification

of security risks to assess existing risks and the

effectiveness of protective measures is recently

being addressed by some researchers (e.g., [2-9]).

When a structure is directly targeted by a VBIED

or military ordnance there is often widespread

damage to nearby structures; where significant

damage can occur to concrete, masonry or glass

facade elements; as per the 1995 bombing of the

Alfred P Murrah Federal Building, Okalahoma

City, USA, where facade damage was observed on

buildings up to 1.6 km away from the detonation

point. Further, a greater safety hazard may occur

to adjacent structures than to the target itself; as

evidenced by the VBIED attack on the Australian

Embassy in Jakarta, Indonesia in 2004 (see Figure

1).

Figure 1. Blast Damage to Glass Facades on Buildings

Adjacent to the Australian Embassy in Jakarta, Indonesia,

2004. (Image used with permission of the Australian Federal

Police).

Hence, with the exception of extraordinarily large

blasts, most damage occurs to a building's facade,

particularly glazed areas, causing high casualties

and significant damage to building interiors. It

follows that the effects of explosive blast loading

on building facades is worthy of detailed risk and

safety hazard analysis, and for glass facades in

particular.

Glass is a material commonly found in facade

systems. Stewart, et al. [4] and Stewart and

Netherton [5] have described a risk-based

framework that also considered threat scenarios,

attack probabilities and relative threat likelihoods

to assess damage risks and life-cycle costs of

protective measures, for annealed and toughened

glazing. This work has evolved to now include

safety hazard risks, which is the main topic of the

present paper. As such, this paper describes a new

probabilistic computational model - called "Blast-

RF" (Blast Risks for Facades) - that incorporates

existing (deterministic) blast-response models

within an environment that considers threat and

vulnerability uncertainty and variability via

probability and structural reliability theory. The

structural reliability analysis uses stress limit

states and the rating criteria of the UK Glazing

Hazard Guide to calculate probabilities of glazing

damage and safety hazards conditional on a given

blast scenario. This allows the prediction of

likelihood and extent of damage and/or casualties

for a single window or for an entire building

facade. The reliability analysis considers the

variability of explosive material energetic output

(in terms of pressure and impulse), glazing stress

limit, fragment drag coefficient, glazing

dimensions, stand-off distance and explosive

weight. This means that glazing stress (used to

assess damage) and post-blast location of glass

fragments (used to assess safety hazard) are also

variable, which then leads to estimates of risk.

Blast-RF may then be used:

(i) as a decision support tool to mitigate

damage,

(ii) by emergency services to predict the extent

and likelihood of damage and hazard levels

in contingency planning and emergency

response simulations,

(iii) in collateral damage estimation and

weaponeering by military planners, or

(iv) in post-blast forensics.

The vulnerability of existing buildings to

explosive blast loading is dominated by the large

inventory of monolithic glazing in existing

buildings. Hence, the present paper describes the

risks of damage and safety hazards for annealed

and toughened glazing; although work is

continuing to consider laminated glazing. The

present paper considers the uncertainty and

variability associated with blast loads from the

high explosive Trinitrotoluene (TNT) for annealed

and fully tempered window glazing

configurations. The outcomes of the reliability

analysis are probabilities of glazing damage and

safety hazards; which are presented for all

windows in a typical 20 storey commercial

building. A Blast Reliability Curve (BRC) is

developed to show the probability of safety

hazards (for different ranges) for a single window.

The effect of explosive material and stand-off on

these security risks is also assessed. While the

current application is for structural glazing, in

principle, the structural reliability method can be

applied to other load-resistance systems such as

bridges, pipelines, communication towers,

hardened structures, etc. Note that the threat

scenarios for the present paper are intentionally

hypothetical and do not represent actual beliefs.

2. PROBABILISTIC ANALYSIS OF

GLAZING DAMAGE AND SAFETY

HAZARD RISKS

2.1 CALCULATION OF RISKS

A threat scenario may be characterised by

particular explosive charge weight, stand-off

distance, height of charge, charge shape, type of

explosive material, etc. The probability of failure

for a structure conditional on the occurrence of a

specific threat scenario is generalised as

Pr failure i( ) = Pr G(X) 0[ ] (1)

where i is the threat scenario (known explosive

weight, stand-off, etc.), G(X ) is the limit state

function and X is the vector of all relevant

variables. See Stewart et al. [4] and Stewart and

Netherton [5] for further information on reliability

theory and the probabilistic modelling of simple

facade systems subject to terrorist explosive

attack; within which, details are given on the

assessment of risks for new and existing glass

facades and cost-effective risk mitigation

solutions.

A reliability analysis using probabilistic models of

load and system response is complicated since

structural system failure modes are neither

statistically independent nor fully dependent,

material properties will be spatially variable and

time-dependent and random variables can be non-

normal. As such, a closed form solution is not

tractable. Hence, the probability of failure for this

paper's monolithic glazing will be obtained from a

stochastic Single Degree of Freedom (SDOF)

model which will utilise event-based Monte-Carlo

computer simulation analysis.

2.2 BLAST LOADING

Blast loading results in time-varying pressure

loads; where load intensity is influenced by the

magnitude, shape and location of the detonation

charge, explosive material, stand-off distance, and

geometry and orientation of the target. The values

of peak overpressure and impulse decrease with

distance, but the duration tends to increase. The

time-pressure history can be idealised, and usually

only the positive pulse is needed for surfaces

directly exposed to the blast; although negative

impulses may need to be considered when overall

motion of the structure is of interest or within

urban or confined areas. The following blast

loading assumptions are made in the derivation of

the structural response of glazing [10]:

(i) Pressure-time profile is idealised by a

triangular function.

(ii) Explosive detonates on or very near to the

ground (it is thus considered a

hemispherical charge), and

(iii) The blast wave loads an infinitely wide

surface (a building facade in a continuous

urban streetscape), so clearing effects are

negligible.

The peak reflected pressure and impulse are

obtained from the Conventional Weapons Effects

Program, CONWEP [10]. The energetic explosive

output from both TNT and ANFO is variable, even

when the explosive weight is precisely known.

The defined variability of energetic explosive

output for TNT is not readily available. However,

as it is a compound regularly manufactured in

controlled industrial processes, any material

variability - and thus energetic variability - will be

relatively low. As such, this paper assumes a

coefficient of variation (COV) of 0.05, which

demonstrates slight variability, yet reasonable

surety; however, the value will require future

confirmation. The variability of energetic

explosive output for ANFO is likely to be much

higher due to other factors such as moisture

contamination, altered mix ratios and different

fuels. Regardless of which explosive is used in the

analysis, this paper considers that the inherent

pressure/impulse variability within a blast-wave

that travels through air is described by a COV of

0.10.

The accuracy of the CONWEP model also needs

to be quantified. As CONWEP is used primarily as

a design tool, it is to be expected that peak

reflected pressure and impulse predictions will

over-estimate actual (or field test) results, as this

will lead to conservative design outcomes.

Huntington-Thresher and Cullis [11] estimate that

actual blast loads may be 75-80% of the

CONWEP predictions, see Figure 2. However, this

data is obtained from small charges, so the

CONWEP model error for larger charges is

unknown at this stage. For the time being the

CONWEP model error assumes a mean of 1.0

with no variability. Confirmation of inherent blast

wave variability and CONWEP model error for

different explosives and scenarios is an area for

further research.

Figure 2. Comparison of Explosive Test Impulse

Measurements and CONWEP Predictions [11].

2.3 GLAZING DAMAGE

Pritchard [12] states that the property of glass

most relevant to its susceptibility to explosion

damage is its extreme brittleness, that it breaks

suddenly and will exhibit no permanent yield or

deformation. He further states that under ordinary

circumstances glass breaks only in response to

tensile stress and that a window subject to

overpressure from explosions will fail in flexural

tension. In practice, the strength of glass is not that

associated with a perfectly smooth homogenous

material, as the presence of many surface flaws

and micro-cracks (from which failures originate)

dictate that the tensile strength of glass is lower

than that theoretically possible. In this paper, the

glass is assumed to fail if the predicted stresses

exceed the capacity of the glass; where the limit

state is

G(X) = fail ME pred (2)

where pred is the predicted peak tensile stress

obtained from the SDOF model, fail is the

capacity of the glass and ME is the model error.

Clearly, Eqn. (2) represents first-crack window

response [13].

The structural response of a monolithic glass

structural element is modelled using SDOF

equivalent systems. Where a dynamic load

(idealised as a triangular pulse) is applied to the

glazing and leads to the derivation of response

parameters such as windowpane deflection and

post-crack glass fragment velocity. A full

discussion on SDOF modelling of monolithic

glazing is described elsewhere [5]. Suffice to say,

the SDOF method used herein solves the equations

of motion by numerical integration, from which,

calculated deflections in the glass panel are used

to determine peak tensile stresses on the inner

surface of the window [14]. Elemental velocities

and accelerations are also calculated during each

step of the numerical solution.

2.4 GLASS SAFETY HAZARDS

Glazing safety hazards are focused on safety of

building occupants and not on humans exposed to

blast-pressure induced trauma (such as

pedestrians), as studies show that flying debris is

the cause of the greatest number of injuries, with

glass posing the greatest threat. The post-break

behaviour of glass and the consequential glass

hazard effects are widely reported and hazard

ratings such as the UK's Glazing Hazard Guide's

rating scheme [15] have been developed, see

Figure 3.

Figure 3. The UK Glazing Hazard Guide's Rating Scheme.

During modelling of the glazing's structural

response, it is presumed that first cracks appear

when the centre of the window pane has displaced

to such an extent that the peak tensile stress limit

state is exceeded. It is further presumed that the

entire pane fails within the next analytical time

step. Following which, a fragment of glass at the

centre of the window pane is released from the

monolithic mass and proceeds across the space

behind the window; where the fragment's mass is

taken to be that measured during tests [16]. The

elemental velocity recorded at the time of stress

exceedence is used as one of the initial parameters

in the calculation of any fragment's trajectory. It is

assumed that fragments travel through free air and

encounters drag forces from this medium. Flight-

path co-ordinates are derived from the solution of

coupled differential equations of the equations of

motion, whilst considering that air resistance

provides a fluid drag force quadratic to the

fragment speed [17].

2.5 BLAST-RF MODEL

The Blast-RF model has the following

capabilities:

• Glazing response solver:

o single degree of freedom (SDOF) model or

o LS-DYNA non-linear finite element model

• ANFO or TNT equivalent explosive weight,

• Variability of explosive weight,

• Detonation coordinates (x,y,z) from centre of

glazing,

• Monolithic or laminated glazing,

• Variability of glazing stress limit state,

• Variable window aspect ratios,

• Different glazing support conditions,

• Variability of material and dimensional

properties, and

• Variability of glass-fragment drag-coefficient.

Monte-Carlo simulation analysis is the

computational method used. The output is given in

terms of the probability of:

• damage (first cracking of glazing), and

• glazing safety hazard criteria based on glass

fragment trajectory.

3. ILLUSTRATIVE CAPABILITIES

As an illustrative example, a typical 20 storey

commercial building considered herein is assumed

76 m high and 35 m wide. The facade comprises

2 m 2 m windows (simply supported on all four

sides), 17 windows per floor, each window being

separated horizontally by 50 mm and vertically by

1800 mm; 340 windows in all. Young’s modulus

is E=69 GPa. According to the Australian glazing

design code AS 1288 [18], an acceptable design

solution for wind loading of these windows is

either 10 mm annealed glass or 8 mm fully

tempered (toughened) glass. The threat scenarios

considered involve a TNT explosive mass of

W=100 kg placed on the ground at a stand-off

distance of R=10 m from the front and centre of

the building. The statistical parameters input to the

Blast-RF model are shown in Table 1.

Table 1. Statistical Parameters

Parameter Mean COV Distribution

TNT energetic output (W) 100.0 kg 0.05 Normal

Explosive stand-off (R) 10.0 m 0.03 Normal

Glass height and width 2.0 m 0.01 Normal

Tensile stress limit - Annealed glass 84.8 MPa 0.28 Normal

- Fully tempered glass 159.6 MPa 0.10 Normal

Glass fragment mass 0.028 kg 0.00 Deterministic

Fragment drag coefficient - Annealed glass 1.72 0.137 Triangular

- Fully tempered glass 1.38 0.170 Triangular

Blast impulse variability 1.00 0.10 Normal

CONWEP Model error 1.00 0.00 Deterministic

SDOF Model error 1.00 0.00 Deterministic

One of the advantages of probabilistic risk

assessments is that all parameter distribution types

are readily assimilated. Whilst most parameters in

the present paper are normally distributed, one of

them, the drag coefficient (CD) of a glass

fragment, has a triangular distribution. This is to

account for the higher likelihood of a maximum

CD of 2.05 for annealed glazing (which usually has

fragments/shards with large aspect ratios) or the

higher likelihood of a minimum CD of 1.05

following the fracture of fully tempered glazing

(where square-like fragments are typically

observed). Given that these CD values are absolute

limits, any distribution with a long probability

"tail" is not appropriate.

Figures 4 to 7 provide typical output from the

Blast-RF model; the utility of which supports four

distinct capabilities, which are now described.

3.1 RISK MITIGATION ADVICE

The Blast-RF model can be used to plot and assess

the risks associated with an existing facade (for a

given threat scenario) and then compare them

against the risks associated with a proposed

mitigation solution; such as, what is the

quantifiable change in risk if a stronger glass pane

is fitted, or a greater standoff distance is enforced?

Figure 4 shows how the risk (or probability) of

window damage can be plotted across the face of a

20-storey building, for either 10 mm annealed or 8

mm fully tempered (toughened) glazing

configurations.

In both scenarios, all 340 windows were subject to

the same VBIED containing 100 kg of TNT

detonated on the ground 10 m in front of the

ground-floor's centre window. Similar plots can be

created for changes in any variables; i.e. what

would be the reduction in risk if vehicles were

held at 25 m away, as compared to the current 10

m? Alternatively, what if no vehicle of 1000 kg

tare could enter a given street or if pedestrian

traffic could only approach to within 25 m of an

entrance? All manner of variables can be entered

into the Blast-RF model and the associated

probability of damage contours subsequently

plotted. For the 100 kg VBIED described above,

Figure 4b shows that for the 16th floor and above,

the risks of window damage approach zero; even

though the risks for the lower eight floors are

similar for both glazings. Further, the average

damage risk (across the whole facade) for 8 mm

fully tempered glazing is 0.52, as compared to

0.77 for 10 mm annealed glazing; a 32% reduction

in the average risk of window damage.

(a) 10mm annealed glazing. (b) 8mm fully tempered glazing.

Figure 4. Damage Risk Contours (Probability of Window Damage) for Different Window Glass in a 20-storey Structure

Subject to 100 kg TNT Detonated 10 m in Front of Building.

The Blast-RF model can produce unique Blast

Reliability Curves (BRCs) for specific

threat/vulnerability scenarios. Again, details of

risk in terms of probability of failure can be shown

for the existing situation and readily compared

against mitigation options. In the BRCs shown at

Figure 5, the damage risks associated with a single

2 m 2 m, 10 mm annealed glass pane are

compared against the damage risks associated with

an 8 mm toughened glass replacement; for a range

of explosive threats located directly in front of the

single window (i.e. angle of incidence (AOI) = 0).

0

0.2

0.4

0.6

0.8

1

0 50 100 150 200 250 300 350

8 mm Fully Tempered Glazing10 mm Annealed GlazingPr

obab

ility

of

Gla

zing

Dam

age

Pr(f

ailu

re|

i)

Stand-off Distance (m)

100 kg

1000 kg500 kg

50 kg

250 kg

10 kg

Figure 5. Example BRC: 2 m 2 m Glass Windows with

Two Glazing Configurations (for AOI = 0).

Figure 5 shows for example, that for a stand-off of

20 m, the risk of the 10 mm annealed glass pane

failing (when subject to a relatively small 10 kg

TNT charge) is 0.74 as compared to only 0.23 for

the thinner yet stronger 8 mm toughened glass

pane. The question for decision makers can then

become - is the cost of the mitigation solution

acceptable for the quantitatively demonstrated risk

reduction? Stewart [7,9] and Stewart and

Netherton [5] illustrate how quantitative risk

information similar to that described herein can be

used to provide such decision support, such as

guidance on how life-cycle cost and cost-benefit

analyses can be used to optimise expenditure on

risk mitigation measures.

3.2 CONTINGENCY PLANNING AND

EMERGENCY RESPONSE

SIMULATIONS

If a facade window's tensile stress limit is

exceeded during blast-induced out-of-plane

deflections, then that glass pane will fail. The

Blast-RF model can be used to determine glazing

safety-hazards for personnel within buildings

effected by broken glass. Using post-break glass-

element nodal velocities and the UK Glazing

Hazard Guide's safety criteria [15] (see Figure 3),

contour plots can be produced which show the

probability of achieving either a Minimal, Low or

High safety-hazard.

Using the same 20-storey scenario as described

previously with 100 kg TNT detonated at 10 m, it

is possible to produce safety-hazard risk contour

plots, see Figures 6 and 7. In these figures the

probability of Minimal-Hazard is less than 0.001

and so contour plots are omitted for this hazard

level. Figures 6c and 7c show that whilst the High-

Hazard risks are similar for the lower six floors

regardless of glazing choice, Figure 7c shows a

significant reduction in safety risk for the windows

above the sixth floor when the stronger yet thinner

glazing is specified. For example, at the eleventh

floor the High-Hazard risk for 10 mm annealed

glazing is 0.6, but this reduces to only 0.1 when 8

mm fully tempered glazing is used. Across the

whole facade, the average High-Hazard safety risk

is 0.59 for the 10 mm annealed glazing, as

compared to 0.47 for the 8 mm fully tempered

glazing; a 20% reduction in risk of a High-Hazard.

This new type of advice will be of significant

benefit to emergency services personnel involved

in contingency planning for expected safety

hazards or the scale of casualties due to various

threat scenarios.

(a) No Break (b) Low Hazard (c) High Hazard

Figure 6. Risk Contours for Safety Hazards to Building Facade, for W=100 kg TNT, R= 10 m and 10 mm Annealed Glazing.

(a) No Break (b) Low Hazard (c) High Hazard

Figure 7. Risk Contours for Safety Hazards to Building Facade, for W=100 kg TNT, R= 10 m and 8 mm Fully Tempered

Glazing.

3.3 COLLATERAL DAMAGE ESTIMATION

FOR MILITARY PLANNERS

The ability to plot probability of damage/safety-

hazard contours in 3-dimensional space will

provide significant utility to the military targeting

process. Military planning staff continually seek

better methods for understanding what the most

likely collateral-damage will be for a given use of

a particular weapon.

Firstly, it is important to define what we mean by

the term collateral-damage, as distinct from the

related yet slightly different term of unintended-

damage. When military planners call for a

particular weapon to cause a desired effect against

a target, there is a clear expectation of some level

of military damage and casualties. Collateral-

damage on the other hand, is additional damage

that does not have a military implication or effect:

such as civilian casualties, civilian injuries, or loss

of some civilian functionality. Whilst unintended-

damage is desired by military planners, collateral-

damage is not. Indeed, many international laws,

treaties and conventions discuss the obligation of

Nation States to "Take all feasible precautions in

the choice of means and methods of attack with a

view to avoiding, and in any event to minimising,

incidental loss of civilian life, injury to civilians

and damage to civilian objects." [19]. Hence,

accurate CDE becomes even more critical in the

legal appreciation of plans to strike targets where

collateral-damage is expected. By using

probabilistic methods, military planners can

simulate variations in weapon selection and

desired placement(s) with a view to assessing

which courses of action reduce the risk of

collateral-damage to agreed and acceptable levels.

The use of probabilistic methods within the

broader military targeting community is well

accepted in terms of "weaponeering" (e.g. [20]);

however, the use of probabilistic methods in

support of CDE are not readily described in the

open literature, if anywhere at all. Thus, the

probabilistic approach developed herein would

appear to be a new capability.

3.4 POST-BLAST FORENSICS

It is often a challenging task for security agencies

to forensically determine, with confidence, the

weight and type of an explosive as used in a

VBIED attack. The Blast-RF model can be used as

a complementary source of information to the

forensic analyst. For example, in Figure 1,

assuming the facade of the building located to the

right of the Embassy has all of the same type and

size of glass, then is it possible to approximate the

whereabouts of a point where half the windows

are damaged (i.e., Pr(failure| i)=0.5). In this

scenario, this point is determined to be 60% of the

way (moving from front to back) along the side of

the building facing the Embassy. Using this

information, it is possible to reverse-engineer a

range of scenarios within Blast-RF and produce

damage contour plots with a view to emulating

observed damage patterns. For example, assume

that the glazing on the damaged building is 2 m

2 m 10 mm annealed glass panes. If the location of

Pr(failure| i)=0.5 is estimated to be 185 m from

the source of the VBIED with AOI=0 degrees,

then a BRC as shown in Figure 4 shows that the

explosive weight W is approximately 250 kg. This

inference is by no means exact; however, when

coupled with other non-exact and subjective data

such as crater shape and depth (assuming such

data can be actually gathered), it can provide the

analyst with more relevant information and thus

help determine, with perhaps more confidence, an

estimate of the charge weight and/or type of

explosive used.

4. DISCUSSION AND FUTURE WORK

The accuracy and credibility of probabilistic

modelling of safety hazard and damage risks is

dependent on accurate deterministic models of

blast loading and system response. Hence, there is

much need for the continued development and

refinement of deterministic blast loading and

system response models. The probabilistic

approaches described herein thus complement

deterministic modelling. There is also a need for

the variability and uncertainty of key model

parameters and phenomena to be quantified. This

could include the collection and statistical analysis

of field and experimental data, as well as the use

of engineering judgement and expert opinion if

such data is unavailable.

Work is progressing on the probabilistic modelling

of glass laminates in the prediction of likelihood

and extent of building occupant safety hazards and

casualties. Further, studies on the reliability of

masonry facades subject to similar blast loads

have commenced; with a view that the Blast-RF

model and associated probabilistic framework will

be a useful research tool in assessing the structural

reliability of any facade subject to explosive blast

loading.

5. CONCLUSIONS

The probabilistic methods described in this paper

can be used to complement - and improve - current

deterministic modelling of explosive blast loads

on infrastructure and monolithic glass facades in

particular. For a given explosive blast load

scenario, a new probabilistic tool - Blast-RF -

(which uses structural reliability theory, stress

limit states and the UK Glazing Hazard Guide's

rating criteria) can calculate probabilities of

glazing damage and/or broken-glass safety

hazards. The ability to probabilistically quantify

these probabilities is a new capability that

significantly enhances the information available to

decision makers involved in choices regarding

blast mitigation options, emergency planning,

collateral damage estimation and post-blast

forensics.

ACKNOWLEDGEMENTS

The support of the Australian Research Council is

gratefully acknowledged.

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