Flyrock in bench blasting: a comprehensive review ;A Bull Eng Geol Envir

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Bulletin of Engineering Geology andthe EnvironmentThe official journal of the IAEG ISSN 1435-9529 Bull Eng Geol EnvironDOI 10.1007/s10064-014-0588-6

Flyrock in bench blasting: a comprehensivereview

A. K. Raina, V. M. S. R. Murthy &A. K. Soni

1 23

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ORIGINAL PAPER

Flyrock in bench blasting: a comprehensive review

A. K. Raina • V. M. S. R. Murthy • A. K. Soni

Received: 20 June 2013 / Accepted: 25 February 2014

� Springer-Verlag Berlin Heidelberg 2014

Abstract Flyrock is unwanted throw of rock fragments

during bench blasting in mines and civil constructions.

Perfunctory attempts by researchers to predict the flyrock

range using mathematical, empirical and ANN based

models do not address the issue in totality. Thus, flyrock

continues to haunt the blaster. The research on the subject

is, thus, still in its infancy. This paper identifies the lacu-

nae, through a comprehensive review of the existing

models, and suggests measures for better prediction and

understanding of the problem on a holistic plane. One of

the main reasons for improper predictions is the lack of

data on flyrock in comparison to blast vibrations owing to

statutory restrictions, avoidance of reporting and conse-

quent constraints on experimentation. While fragmentation

and throw of rock accompanied by subsequent vibration

and air overpressure are essential constituents of the

blasting, flyrock is not. This probably is one of the main

errors in predictive domains. In addition, rock mass prop-

erties play a major role in heaving of rock fragments during

blasting. Barring density of the rock, other rock mass

properties have practically been ignored in all the models.

At the end of this paper, for future investigations, a

methodology for prediction of flyrock is also given.

Keywords Surface bench blasting � Flyrock prediction �Safety � Danger zone � Literature review

Introduction

Blasting is a rock-explosive interaction system. The explo-

sive after detonation releases gases, which in turn produces

pressures to the order of a few GPa. The outcome of blasting

is primarily dependent upon the rock mass, explosive prop-

erties, blast design, and execution of blast according to the

standard design procedures. Fragmented rock, heap, ground

vibrations, air overpressure, noise, fumes, dust, and flyrock

(Fig. 1) are some of the outcomes of a blast, further classified

into favourable and unfavourable parameters.

The ground vibrations and air overpressure have

received significant attention from the researchers. Thus,

the regulations and guidelines for prediction and control of

vibrations and air overpressure are, more or less, defined.

There is, however, a degree of subjectivity in assessing the

absolute effects of ground vibrations and air overpressure

and the investigations are markedly different in terms of

response of the people living in nearby areas. One of the

major concerns—the flyrock, in contrast, cannot be sub-

jective as no one can be hit by an imaginary flyrock (Ro-

senthal and Morlock 1987). Flyrock is defined as the

excessive random throw of rock fragments from a blast that

can travel distances beyond desired values and present a

serious threat to people and property in and around the

mine. There can be small to fatal accidents (Verkis 2011;

Fig. 2) due to flyrock and is, thus, a subject of concern.

Flyrock is one of the contentious issues in surface blast-

ing. The phenomenon of flyrock is important since it

involves risk to people and structures (Objects of concern;

Fig. 3) within and outside the mining area. The vulnerability

of different objects of concern is explained in Table 1.

The accidents due to flyrock are rarely reported (Davies

1995) and is one of the major problems in prediction

regime. However, the flyrock that cause no damage are

A. K. Raina (&) � A. K. Soni

Regional Centre Unit-I, CSIR—Central Institute of Mining and

Fuel Research, 3rd Floor MECL Complex, Seminary Hills,

Nagpur 440 006, India

e-mail: [email protected]

V. M. S. R. Murthy � A. K. Soni

Department of Mining Engineering, Indian School of Mines,

Dhanbad 826 008, India

123

Bull Eng Geol Environ

DOI 10.1007/s10064-014-0588-6

Author's personal copy

frequent and could be documented for improving the

accuracy of existing prediction models. Jenkis and Floyd

(2000) concluded that flyrock is responsible for more

injuries and fatalities than any other blast related accidents.

The data presented by Bajpayee et al. (2002), Rehak et al.

(2001) and other workers concluded that flyrock is

responsible for 30 % of the blasting related accidents.

Fletcher and D’Andrea (1987) recorded in the years

1978–1985 that flyrock was responsible for 24 % of the

blasting accident injuries that occurred in surface mines.

The causes of flyrock are attributed among others to site

geology/rock conditions, bench face conditions, improper

blast design, improper explosive selection, explosive

loading, and distribution of explosive in the blast hole,

inappropriate delay allocation or carelessness.

Despite the existence of several state of the art techniques,

the flyrock phenomenon continues to happen though the

incidences have reduced over time (Verkis 2011; McKenzie

2009; Verkis and Lobb 2007; Amini et al. 2011; Stojadinovic

et al. 2011; Rezaei et al. 2011; Kricak et al. 2012 etc.). This is

the reason for the increased focus on the subject of flyrock

(Raina et al. 2013), to understand the problem in a holistic

plane and addressing the issue in a comprehensive manner. The

main concern in predictions is explained below and Fig. 4:

• The maximum distance (Rmax) a flyrock can travel in a

given mining/blasting condition.

• The distribution of flyrock about a face.

• The location of object of concern and its vulnerability

to damage.

• On the same horizontal plane as that of the blast.

• On a different plane than that of the blast—more

likely to represent a hilly mine condition.

• The probability of flyrock occurrence.

• The probability of flyrock hitting a particular object of

concern.

Fig. 1 Output parameters in blasting

Fig. 2 Safety pyramid (Verkis 2011)

Fig. 3 Objects of concern with

respect to flyrock

A. K. Raina et al.

123


Definition of flyrock security zone (danger zone)

Fletcher and D’Andrea (1987) while investigating major

causes of accidents due to blasting in surface mines viz.

inadequate blasting area security, excessive flyrock and

misfires proposed the relative ranges of different flyrock

zones (Fig. 5). However, their definition is suitable only for

throw, excessive throw, since several authors (e.g., Rich-

ards and Moore 2004) have shown that the flyrock danger

zone is not uniform about the blast but is skewed towards

the front of the blast face.

Reasons for flyrock occurrence

There can be several reasons for the occurrence of flyrock

ranging from abnormalities in blast pattern or their

implementation, explosive use, known or unknown rock

mass conditions and lack of security area (Kuberan and

Prasad 1992; Bhandari 1994; Kopp 1994; Mandal 1997;

Adhikari 1999; Kecojevic and Radomsky 2005). There are

ample numbers of references that have reported the effects

of above said factors on generation of flyrock. Fletcher and

D’Andrea (1987) explained that excessive flyrock gets

projected beyond the normal blast area and is generated

due to:

1. Too much explosive energy for the amount of burden,

2. Stemming is insufficient,

3. Venting of explosive energy through a weak plane.

The important reasons are the local anomalies in rock

mass, blast pattern and charging as shown in Fig. 6 (Raina

et al. 2006). This is probably one of the reasons that a

precise rock mass description does not find place in the

Fig. 4 The basic premise of

flyrock analysis

Table 1 Vulnerability of

objects of concern to flyrock

and danger zone demarcation

Working type Area/zone Vulnerability

Equipment Structures Personnel

Mining (primary blasting) Blasting H

Mining H H H

Outside Mining H H H

Mining (secondary blasting) (As above) H H H

Civil and construction (channels,

power houses, slopes, industrial

installations)

Blasting H H H

Demolition Blasting H H H

Fig. 5 Different zones of

flyrock (after Fletcher and

D’Andrea 1987)

Flyrock in bench blasting

123


predictive models. A further compilation of important

factors resulting in flyrock is summarized in Table 2 along

with relevant references.

Prediction of flyrock travel distance and size

of the flyrock

Different approaches can be traced from the literature for

prediction of flyrock. These approaches can be classified in

Fig. 7.

Mathematical models

Lundborg et al. (1975) used a semi-empirical approach to

estimate flyrock range. Based on the conservation of

momentum and the scaling laws of spherical charge, a

relationship between charge diameter ‘d’ and rock velocity

‘V0’ was obtained. They proposed the following relation-

ship for initial velocity (V0) throw and size of flyrock in

crater blasting in granite blocks.

V0 ¼10d � 2600

Tb � qr

;

Lm ¼ 260d2=3;

Tb ¼ 0:1d2=3;

where, Lm = flyrock range in m, d = hole diameter in

inch, Tb = size of rock fragment (m), and qr = density of

rock in g/cm3.

Fig. 6 Conceptual diagram

showing modes of flyrock

occurrence with arrows

representing probable throw

(after Raina et al. 2006). a Less

burden near stemming zone.

b Fractured top with high

charge. c Excessive charge/less

stemming. d Face indentation.

e Presence of a cavity (thus,

building a bomb) over charging.

f Weak bed within competent

strata dipping out of face.

g Weak bed within competent

strata dipping into face.

h Excessive front row burden

resulting in the least free face

for next row holes

A. K. Raina et al.

123


Chiapetta et al. (1983) derived two expressions for the

distance travelled by the flyrock. Air resistance, wind-

direction and speed are neglected. This is a reasonable

assumption given that flyrock usually (but not always)

travels\300 feet distance and rises only a few hundred feet

at maximum. These relationships are:

R1 ¼ V0 �2 sin 2h

g;

R2 ¼ V0 � cos V0 sin hþ 2V0 sin hþ 2gHð Þg

;

where R1 = distance travelled (m) by the rock along a hori-

zontal line at the original elevation of the rock on the face,

R2 = total distance travelled (m) by a fragment ejected from

the blast accounting for its heights above the pit floor, V0 -

= initial velocity of the flyrock, h = the angle of departure

with the horizontal, and g = gravitational constant.

The resistive forces in air could be generally neglected,

taking account of the preceding remark on variability in the

work of Chiapetta (op. cit.) and, thus, arriving at an

expression for V0.

Roth (1979) established a relation for obtaining the

flyrock travel range. In his approach, the critical variable in

all the flyrock range calculations was the estimation of V0,

the initial flyrock velocity. He used Gurney’s equation to

calculate the initial velocity of the fragments propelled by

an explosive given by:

V0 ¼ 2E0:5f ql=ml

h i;

where (2E)0.5 is Gurney’s constant, a function of explosive,

ql = linear charge concentration and ml = total mass of

material per unit of length.

Empirical models

Gupta (1990) established an empirical relation amongst

stemming length, burden and flying distance of projectiles,

as given below:

Table 2 Dominant reasons for flyrock occurrence

Group Parameters Description References

Rock mass Inconsistent strata Presence of voids, incompetent

beds in competent strata, known

or unknown anomalies in the

strata

Heck (1992), Bajpayee et al. (2002), Raina et al.

(2006), Verkis and Lobb (2007), McKenzie (2009)

Blast design Burden Excessive confinement Fletcher and D’Andrea (1986, 1987), Bajpayee et al.

(2002), Richards and Moore (2004), Raina et al.

(2008, 2011)

Stemming Low stemming height, improper

stemming material

Chiapetta et al. (1983), Fletcher and D’Andrea (1986),

Gupta (1990), Kopp (1994), Bajpayee et al. (2002)

Delay Poor hole to hole and row to row

delay timings

Blaster’s Handbook (ISEE)

Execution Drilling and loading, Face

condition

Inaccurate drilling,

implementation of blast design,

irregular face

Heck (1992), Fletcher and D’Andrea (1986), Adhikari

(1999)

Fig. 7 Flyrock prediction

models and methods


123


L ¼ 155:2� D�1:37;

where L = ratio of length of stemming column to burden

(ls/B), D = distance travelled by the flying fragments in

meters.

Flinchum and Rapp (1993), explained the procedures for

measuring open face in bench blasting, by various sur-

veying methods and provided mathematical formula for

calculating and designing proper hole placement and

explosive load configuration. A concept called ‘‘Pattern

Footage’’ was developed in conjunction with a USBM

study to minimise air-blast and flyrock. The pattern footage

is determined by using the following equation:

Pf ¼d

12

� �2

�K;

where Pf = pattern footage, d = explosive diameter, and

K = empirical constant.

By utilising the pattern footage from the above formula,

burden was determined by the following equation:

ffiffiffiffiffiPf

p¼ Burden (Square pattern); ðorÞ

ffiffiffiffiffiPf

p¼ 0:85� Burden (Rectangular pattern):

Desired drill pattern spacing was then determined byPf

B= spacing (toe burden may be greater than the pattern

burden). The authors concluded that because of blasting

requirements, the information is not suitable under all

conditions. The authors advised the users to make their

own tests to determine the safety and suitability of this

information for their own purposes.

Richards and Moore (2004), while defining the three

modes of flyrock viz. rifling, face burst and cratering

developed, a scaled burden method for calculation of initial

velocity of such flyrock travel distance.

Face burst : Lmax ¼k2

g

pm

B

2:6

Cratering : Lmax ¼k2

g

pm

ls

2:6

Rifling : Lmax ¼k2

g

pm

ls

2:6

sin 2h0

where, h = drill hole angle, Lmax = maximum throw (m),

m = charge mass/m (kg/m); B = burden, ls = stemming

Height (m), and g = gravitational constant.

Raina et al. (2006) developed a model for determining

Factor of Safety for horizontal (FSH) and vertical (FSV)

flyrock/throw in opencast mines. The parameters needed

to work out the Factor of Safety were very simple, related

to the rock mass, and blast design parameters. The Factor

of Safety, a dimensionless quantity, was devised using

blast design parameters with correction factors for dif-

ferent field and explosive situations. This factor defines a

range of flyrock depending on the factor of safety, rather

than predicting a single value of range of flyrock. A

factor of safety of 1.5 was considered to be safe for

flyrock.

McKenzie (2009) developed equations to predict the

maximum flyrock travel range, and the particle size

(achieving the maximum range) for blasts of varying rock

density, hole diameter, explosive density, and state of

confinement. He based his findings on the previous studies

of Lundborg (1974) and Lundborg et al. (1975). He defined

the flyrock travel range in terms of hole diameter, shape

factor, and size of rock fragment that achieves maximum

projection distance in terms of rock density and shape

factor. The study was an important one in defining the

danger zone of blasting.

Stojadinovic et al. (2011) used approximate numerical

solutions and the Runge–Kutta algorithm of 4th order to

estimate the maximum travel distance of flyrock and the

safe distance. They used an approximate shape (sphere) for

predictions. They concluded that the maximum throw is

obtained at an angle of 45�, which is in contradiction of the

findings of McKenzie (2009). They also discussed that

launch velocities based on impulsive approach (Little

2007) that yielded improper results and that launch

velocities are case specific.

Fuzzy logic, artificial neural network based models

Amini et al. (2011) used a support vector machine to

predict flyrock in a copper mine in Iran and concluded that

SVM works better than ANN.

Rezaei et al. (2011) developed a fuzzy model for pre-

diction of flyrock in a mine in Iran considering the inac-

curacies in available prediction models. They concluded

that powder factor was the most contributing and density

the least contributing factor in flyrock prediction. This,

however, is in contrast with the classical study of Lundborg

(1974) and Lundborg et al. (1975) in which density of the

rock is considered to be one of the major factors in flyrock

travel distance prediction.

Monjezi et al. (2010) used an artificial neural network to

predict fragmentation and flyrock in blasting operations in

an iron ore mine in Iran. In contrast, however, Rezaei et al.

A. K. Raina et al.

123


(2011) and Amini et al. (2011) showed that fuzzy and SVM

models work better than ANN models. Mohamad et al.

(2012) used ANN to predict the flyrock range due to

blasting of boulders.

The uncertainty with ANN predictions is that the

explicit model is not known and that variation in the

number of data sets defines the boundary conditions for the

models. It is not clear whether such models can be exten-

ded by extending the learning. Moreover, the validation of

the models in the same data set does not improve despite

significant learning cycles. However, such models are an

easy way to find the importance and sensitivity of the

contributing parameters.

Setting of danger zone

Consequence based method

In this method, danger zones have been solely set based on

consequence, i. e., the maximum distance of rock projection

or expected ground vibration plus a defined safety margin. A

flyrock zone (danger zone) is between two and eight times

the calculated rock throw distances. On the assumption that

any impact on the target by flyrock is unacceptable, the fly-

rock danger zone will be more than 300 m. In India, the

flyrock danger zone set by the DGMS is 500 m and based on

consequence. This approach is satisfactory where the

requirements for distance can easily be accommodated.

Increasingly, with the development of sites in ever-closer

locations to potentially sensitive areas (human settlements),

danger zone distances are imposing severe constraints on

blasting operations. This method is quite subjective and raw

in nature and needs a scientific basis.

Rosenthal and Morlock (1987; OSMRE regulations),

states that Flyrock travelling in the air or along the ground

shall not be cast from the blasting site:

1. More than one-half the distance to the nearest dwelling

or other occupied structure,

2. Beyond the area of access control of mine for the given

blast,

3. Beyond the permitted boundary of the mine.

Risk based method

Davies (1995) gave an approach to the setting of ‘‘Danger

zones’’ by considering the incidence of flyrock, which is

calculated from the available data, and the probability that

a predicted distance will be exceeded. The frequency of

impact by ‘‘wild flyrock’’, at a constant distance, for single

shot is given as follows:

I ¼ Nf pdpppe

� �;

where I = target impact frequency (impact/year);

N = total number of blasts per year, pd = probability of

wild flyrock travelling the target distance, pp = probability

of wild flyrock travelling on an impact trajectory, and

pe = probability of target exposure.

Assuming the targets are people, an impact frequency of

10-6 per year compares with the risk that is incurred by

population resident around a major industrial area (a

potential upper bound for tolerable societal risk from major

industrial hazards is between 10-3 and 10-5). For under

reporting of flyrock incidents, the risk figures calculated

above should be increased by a factor of 2–3. The setting of

danger zone on the basis of risk requires information on the

frequency of flyrock occurrence and realisation of hazards.

The risk analysis method given by Davis (1995) is a

comprehensive one but is very complicated in assessment.

Hence, it is difficult to adopt the same. The adoption of this

criterion can be cumbersome, as most of the time, the

incidence of flyrock is not reported or is unnoticed many

times (as mentioned by Davis also) and requires a huge

database to arrive at some conclusions.

St. George and Gibson (2001) developed a stochastic

model with a probabilistic approach to simulate the blasting

with respect to flyrock ejection from the face and collar. They

concluded that the boulder size and drag had a major effect

on the maximum travel distance of the flyrock.

Richards and Moore (2004), while defining the flyrock

range, showed that the flyrock danger zone should be based

on probability and should assume an ellipsoidal shape (see

Fig. 3) about the blast face. Raina et al. (2013) demon-

strated that the flyrock zone is not isotropic in nature, and

there are at least two green zones along the strike of the

blast bench where the probabilities of flyrock are minimal.

Bandopadhyay et al. (2003) discussed the potential

application of fuzzy set theory in evaluating risk using

linguistic variables/values. They used the Yager’s meth-

odology for ordinal multi-objective decision based on

fuzzy sets to evaluate risk due to environmental factors of

blasting in mines including flyrock.

Little (2007) and Little and Blair (2010) defined and pre-

sented the consequences and risk matrix based approaches for

flyrock risk assessment while simulating conditions as per the

criterion of Richards and Moore (2004) and Davies (1995).

They defined the qualitative and quantitative risk assessment

methods for flyrock. They concluded that the reasons for

flyrock in a blast are mainly because of the mismatch between

the energy available and the work to be done.

Raina et al. (2011) devised a risk based criterion using

the Factor of Safety concept and threat ratio (acceptable


123


distance of flyrock to the distance of object of concern) and

concluded that the risk criterion can be used to devise a

dynamic danger zone for blasting. The concept was ini-

tially validated with data of three mines (Raina et al. 2008).

The concept of the development is shown in Fig. 8.

Blanchier (2013) proposed a methodology, based on pyro-

technic risk studies, to estimate the range and risk due to fly-

rock while taking into account the rock mass and blast patterns.

Some intricacies in flyrock prediction

Air-drag prediction and its importance

All bodies moving in gaseous or fluid medium experience a

resistance to their movement. The resistive force depends

on the viscosity of the medium as well as the pressure,

which develops on the surface of the body due to the

deflection and retardation of the flow medium. Viscosity

resistance is called friction drag. The pressure developed

due to the retarded flow resistance is called pressure drag.

The effect of each of these components depends on the

correlation between velocity, linear dimensions of the

moving body and viscosity. The correlation is characterised

by the Reynolds criterion (Chernigovskii 1985).

The air drag jair can be given by following relationship.

jair ¼ bdv2;

where,

bd ¼cxqairsf

2m

Fig. 8 Risk based criterion for

flyrock (Raina et al. 2011)

Fig. 9 Flyrock—a holistic view

A. K. Raina et al.

123


cx = drag coefficient, and qair = density of air (g/cm3).

The drag factor bd depends on the shape and mass of

fragments. The drag coefficient for fragments of different

shapes varies between 1.2 and 1.8.

Actual initial velocity: calculation

To calculate the error in the calculated range of rock

movement due to inaccuracy in obtaining the initial

velocity of projection, considered for a particular

instance of projection of rock fragment with initial

velocity V0 and the launch angle h0 = 45� without

considering air-drag. Also, assume that the point at

which the rock fragment is blown away and that point at

which it falls on the free face are on the same horizontal

plane. The range of movement (D) in this case will be

given by: D ¼ V20

sin 2hg

; after differentiating, we get DDD¼

2 DVV0þ cot 2h0 � Dh0

� �: Hence, for h0 = 45� DD

D¼ 2 DV

V0:

In this manner, error in velocity of projection (DV/

V0) = ±0.1, leads to the error in the range of DD/

D = ±0.2. However, the movement of a rock fragment

in the air predetermines the possibility of wide errors in

the calculated range of rock displacement. The reason for

this can be found in the uncertain shape, mass of frag-

ment and translational movement.

Availability of data

One of the major issues is the data pertaining to the flyrock

that is quite negligible (Raina et al. 2013) or unreported

(Davies 1995). This poses a major constraint in the

Table 3 Comparative assessment of the popular predictive models of flyrock

Model References Major parameters Advantages Disadvantages Lacunae

identified

Mathematical Lundborg

(1974)

V0 = f(d, Tb, qr) Maximum throw, tacit air

drag

Field conditions not

discussed. The objective

was to assess maximum

throw

Aimed at

generating

maximum throw

of fragment

Chiapetta

et al.

(1983)

Kinematic equations used,

elevation of origin and

place of fall of flyrock

defined. Assumes that 45�launch angle will result in

farthest flyrock throw

Origin and landing positions

taken into consideration

which are necessary for the

mines where objects of

concern are at different

levels

Kinematic equations may not

work owing to air drag

which are further dependent

on shape of the particle and

initial velocity of the

fragment

Blast design

parameters are

not part of the

equation

Roth

(1979)

Uses ballistic trajectories and

Gurney’s constant to predict

flyrock travel distance

Trajectory equations may be

of importance but less

relevant to blasting

Gurney’s constant is difficult

to evaluate. Ballistic

kinematics may not work

with particles ejected form

blasts

Blast design

parameters not

directly taken

into account,

major rock

properties

ignored

Empirical Gupta

(1990)

Uses burden and stemming in

prediction

Burden and Stemming are

two major and useful blast

design parameters

Other conditions not used Rock properties

not taken into

account

Richards

and

Moore

(2004)

Burden and stemming

considered separately in

three equations

Rock properties and other

blast conditions are taken

as a constant

h is considered only in one

equation

The size of shape

of particles not

considered

Raina

et al.

(2011)

Factor of Safety for blasting

worked out for the first time

as a function of blast design

parameters. Risk based on

Factor of Safety and Threat

Ratio defined

Blast design and rock

properties including

uncertainties associated

with blasting considered

The throw of fragments is

limited owing to difficult

mining conditions

The shape and

size of particles,

the relationship

of these to

throw are not

considered

Mckenzie

(2009)

Uses scaled depth of burial of

explosive charge which are

further dependent on

stemming etc.

Blast design parameters

based on actual data

considered for assessing

maximum possible throw

The relationship of Initial

velocity with other

parameters of blasting are

difficult to gauge

The relationship

of fragment size

and shape needs

to be considered


123


prediction of flyrock travel distance. The reason for non-

availability of data is non-reporting of the issue because of

underlying legalities. This is a lacuna in the prediction of

flyrock range and size and needs attention to achieve a

plausible solution.

Discussion

It is quite evident from the above that blast design

parameters play a significant role in the generation of the

flyrock. The placement of explosive charge in relation to

the borehole configuration plays a major role in conjunc-

tion with weak planes in the rock mass, and other face

conditions including damaged front or top of the blast face.

The paper is aimed at presenting a holistic view of the

flyrock phenomenon ranging from the source, factors

affecting the origin of flyrock, the predictive models,

probability, and risk associated with the most contentious

issue in blasting. A summary of the issues discussed in the

paper is shown in Fig. 9.

There have been significant developments in the pre-

diction of flyrock on different lines as discussed above.

However, the holistic solution to the problem is still

lacking. The prediction of flyrock range as explained in

Fig. 3 is dependent on the initial velocity of the flyrock and

its launch angle. However, the air drag comes into picture

owing to the shape and size of the flyrock. This compli-

cates the issue of prediction. In order to ascertain the

requirements for further developments, a relative assess-

ment of the most discussed predictive models has been

provided in Table 3.

As is evident from the above table and discussions, there

is a need to:

1. Generate significant data and log the same for predic-

tive purposes while monitoring maximum parameters

relating to rock mass and blast design.

2. Develop equations that precisely predict the initial

velocity of the flyrock fragments considering the

properties of rock mass (including the face indenta-

tions, presence of incompetent strata, etc.) and blast

design parameters.

3. Develop relationships, which address the relationship

of flyrock fragment shape to that of the in situ block

size.

4. Use the above data with the ANN or other advance

statistical methods to ascertain the importance and

sensitivity of rock mass and blast design parameters.

5. Develop a comprehensive model for flyrock fragment

throw or range using the above details.

With the above approach, it is expected that an acceptable

model of flyrock range prediction will be developed in the

future. The Danger Zone or Area Security Zone will then

be easy to demarcate.

Acknowledgments This paper forms part of the Ph.D. work of the

first Author. Authors are thankful to the Director CSIR-CIMFR for his

permission to publish the paper. The help rendered by colleagues and

other staff at CSIR-CIMFR is duly acknowledged.

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