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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