-
Journal ofTerramechanics, Vol. 24, No. 4, pp. 263-280, 1987.
Printed in Great Britain.
0022-4898/8753.00+0.00 Pergamon Journals Ltd.
1988 ISTVS
THE ROLE OF MEAN MAXIMUM PRESSURE IN SPECIFY ING CROSS-COUNTRY
MOBIL ITY FOR ARMOURED F IGHTING
VEHICLE DES IGN*
J . G. HETHERINGTON~" and I. LITTLETON~"
Summary--This paper examines the relationship between a military
vehicle's mobility and its survivability. The theoretical model
governing this relationship is based on a series of steps, each of
which is critically examined. The tactical role of the vehicle is
translated into a mobility requirement stated in terms of the
percentage of ground to be trafficable in specified areas. The
assessment of soil strength is achieved using the cone index, the
statistical handling of which is described. The link between
Vehicle Cone Index and Rowland's Mean Maximum Pressure (MMP) is
discussed, as is its role as an indicator of vehicle mobility.
Vehicle and armour weight follow directly from Rowland's MMP,
leading to an assessment of survivability. Examples are given of
the effects of varying the mobility requirement, the threat level
and the armour type on the ultimate survivability of the
vehicle.
INTRODUCTION
THE MILITARY vehicle designer often refers to the trade-off
between mobility and protection. The argument normally runs as
follows:
"A high level of protection leads to high vehicle weight which
results in poor cross-country performance."
The argument can be developed by examining the influence of
protection and mobility on survivability:
"At one extreme one can go for a very light vehicle, which will
have a high cross-country mobility, poor protection and therefore a
poor chance of surviving an attack. However due to its high
mobility, its exposure to attack will be greatly reduced. At the
other extreme one can go for a very heavy vehicle, which will have
a poor cross-country performance, but a good chance of surviving an
attack. However, due to its poor mobility, its exposure to attack
will be greatly increased."
It is not immediately clear which of these two options would
offer the better chance of survival; indeed for a particular
vehicle role there will exist an optimum in this spectrum of choice
somewhere between these two extremes. The aim of this paper is to
examine these assertions to see what part the effective
characterisation of cross-country vehicle mobility can play in
enhancing the conceptual design of Armoured Fighting Vehicles
(AFVs).
THE EFFECT OF VEHICLE WEIGHT ON CROSS-COUNTRY PERFORMANCE
When add i t iona l load is app l ied to a saturated, cohes ive
soil, the inc rement is t ransmi t ted direct ly to the pore water.
The soil part ic les exper ience no extra load and thus the shear
strength o f the soil is unaf fected by the addi t ional load.
Vehicle t ract ion depends on soil shear strength and so is unaf
fected by the load increment. The extra load will, however ,
cause
*Presented at the 4th Annual British Conference, ISTVS, Sutton
Bonington, 23-24 September 1986. tRoyal Military College of
Science, Shrivenham, Swindon, Wilts. SN6 8LA, U.K.
263
-
264 3. G. HETHERINGTON and 1. LITTLETON
extra sinkage and therefore extra rolling resistance. This
results in the relationship between drawbar pull and weight
depicted in Fig. 1.
300-
113 ~ 200-
100 -
0 50 ~5 ~0 6'5 70
I I -
VEHICLE MASS (T)
FIG. 1. Typical relationships for drawbar pull vs vehicle mass
on clay.
In a coarse-grained soil an increment of load enhances the
inter-particle friction, increasing the shear strength and
therefore the derivable traction. In this case, both the traction
and the rolling resistance increase, although the increase in
traction dominates. Results obtained at model scale for a tracked
vehicle on sand at The Royal Military College of Science (RMCS) [1]
are compared with the predictions of Turnage [2] in Fig. 2. The
contrast in behaviour suggests that whilst extra protection will
inevitably reduce cross-country performance on cohesive soils, it
is likely that it actually improves performance on purely
frictional soils. Of course, this extra potential performance for
the very heavily armoured vehicle on sandy soils would only be
available if extra power were supplied, and the vehicle would have
to be dedicated to operations in the desert. Few armies can afford
the luxury of vehicles dedicated to a desert role, and are obliged
to operate in regions with cohesive soils.
200-
150-
100-
50-
0
FIG. 2.
El Measured
. . . . . Theory (Turnage, Reference 2)
T I I I I I I I 50 100 150 200 250 300 350 LOAD (N)
Drawbar pull vs load for model track in sand (from ref. 1).
VEHICLE WEIGHT AND PROTECTION
Although detailed designs will show some departure from any
generalised statement, it is possible to draw some broad
conclusions about the proportion of total vehicle weight which is
given over to armour. Analysis of post-war main battle tanks of
various nations shows that about 45% of the vehicle all up weight
is devoted to protection (Fig. 3). The figure for a
-
MEAN MAXIMUM PRESSURE IN CROSS-COUNTRY MOBILITY 265
----- PAY'LOA
FIG. 3. Approximate distribution of vehicle mass for main battle
tank.
MICV (Mechanised Infantry Combat Vehicle) is nearer 40% (Fig.
4). The assumption of a fixed proportion of vehicle weight being
available for armour provides the link between a specified level of
mobility and the achievable level of protection.
FIG. 4. Approximate distribution of vehicle mass for MICV.
ARMOUR AND SURVIVABILITY
The evaluation of the survivability of an armoured fighting
vehicle is very complex. The range of attacks to which the vehicle
may be subjected includes: direct fire [both kinetic energy (KE)
and chemical energy (CE)] which attacks the front, rear and sides
of the vehicle almost at horizontal; a variety of artillery
delivered top attack weapons designed to attack the more lightly
armoured areas of the vehicle; and attack to the underneath by
mines.
Threat analyses, both present and future, indicate that direct
fire KE and CE constitutes the majority threat. Thus, although top
attack weapons and mines pose a considerable problem to the
armourer, the majority of armour will continue to be provided as
protection to horizontal attack. Whittaker [3] analysed the
distribution of horizontal attacks on vehicles and developed
"Directional Probability Variations" which describe the probability
of an attack, sustained by a vehicle, coming from within a
specified frontal are + u (Fig. 5). A
-
266 J .G. HETHERINGTON and 1. LITTLETON
FIG 5. Frontal arc _+ u .
plot of his probability function is given in Fig. 6. Altough the
arrival on the scene of hand-held anti-tank guided weapons has
shifted some of the attacks from the front to the sides and rear,
it is argued that this effect has been neutralized by the further
concentration of attack on the front of a vehicle due to the
increased range achievable. Whittaker's directional probability
variations therefore still provide a realistic description of the
distribution of attacks on a vehicle, and show a concentration of
attacks to the front. It is unlikely that the weight quota afforded
to the armour will provide sufficient armour to make it totally
immune to all attacks. It is therefore necessary to provide
all-round protection against a lower level of threat whilst
providing immunity against the highest level of threat within as
big a frontal arc as possible. The aim, therefore, is to maximise
the size of the immune frontal arc, to provide the maximum
survivability. By evaluating the directional probability variation
within this immune frontal arc, a quantitative estimate of
survivability can be obtained.
o u_
1.0
~ o.8
.< ~ 06-
8~ o.4-
i 0.2"
i i 30 ~0 910 120 150 180 u
FIG. 6. Whittaker's directional probability variations.
THE CONCEPTUAL DESIGN ROUTE
In practice the design of an armoured fighting vehicle will be a
process of evolutionary engineering, with innovations providing
gradual improvements in performance. However, if one is seeking to
quantify the effect of cross-country performance on survivability,
it is instructive to follow a conceptual design route determined
principally by off-road performance. A proposed scheme is presented
in Fig. 7, in which the tactical decision of field of operation
provides the initial step. By specifying the areas of the earth's
surface on which the vehicle is required to operate, the number of
days of the year on which the vehicle must be
-
MEAN MAXIMUM PRESSURE IN CROSS-COUNTRY MOBILITY 267
I WHAT PERCENTAGE I OF GROUND I
, r
I RCI of weakest soil on which vehicle must operate
~r
ql-
' vehicle front I I I I
Remainder distributed optimally
I Immune frontal arc
Survivability
I f
Statement of required mobiliw
ln-situ soil strength survey
(vc[)
MMP = 10.4 VC[ 1
W = (MMP).mbV"~ 1.26
40-46% of vehicle mass available for armour
Optimal armour distribution leads to assessment of
survivability
FIG. 7.
able to traverse the ground and the percentage of that ground
which must be trafficable, a characteristic weakest soil across
which the vehicle must be able to travel is specified. The
foregoing is a theoretical and highly optimistic statement.
Certainly one could specify the tactical requirement very
precisely. For example it is essential that a UK main battle tank
is
-
268 J.G. HETHERINGTON and I. LITTLETON
able to traverse river valleys in the Federal Republic of
Germany 365 days a year. One is bound to accept a small proportion
of the ground as non-trafficable, say 10%, giving a requirement for
90% terrain trafficability. The difficulty lies in translating this
precise mobility requirement into a characteristic weakest soil.
The dual requirement is for
(a) an efficient system of in situ, soil strength measurement
and (b) a comprehensive survey for the variation of this
measurement with area and season.
The Bevameter and cone penetrometer are two popular examples of
a wide range of devices which have been suggested for in situ soil
strength measurement. The cone penetrometer is adopted here and a
discussion of the validity of its use will follow later. It is
assumed, therefore, that it has been possible to convert the
precise tactical mobility requirement into a figure, the remoulded
cone index (RCI), which represents the weakest soil over which the
vehicle must be able to pass to conform with the tactical mobility
requirement [the vehicle cone index, (VCI)]. Rowland [4] developed
a conversion from VCI to Mean Maximum Pressure (MMP), and through
the Rowland expression
MMP - - -
where W is the weight of the vehicle m is the number of road
wheels b is the track breadth p is the track plate length
and d is the diameter of the road wheels,
1.26 W
mb,/
it is possible to relate the permissible weight of the vehicle
to the required value of MMP. The validity of Rowland's expression
for MMP has been the subject of recent criticism by Garber and Wong
[5] and the subject of research by Bowring [1] and Lord [6] and
will be discussed in a later section. The vehicle weight is thus
determined, provided the geometrical parameters of the track system
are fixed, and the armour will occupy a fixed proportion of the
vehicle weight. For a threat level specified in terms of the
thickness of rolled homogeneous steel armour (RHA) which can be
penetrated at normal, the thickness of other armours (e.g.
aluminium or complex) which will provide equivalent protection can
be found. The front of the vehicle is armoured to provide total
immunity to the perceived threat and the remainder of available
armour is distributed on the vehicle in such a way as to maximise
the directional probability variation within the arc of immunity,
and thus the vehicle's survivability. The chain is thus completed
and the relationship between mobility and survivability established
in quantifiable terms.
As has been indicated above, two links in the chain need more
careful examination, and this follows in the subsequent sections.
The chain also needs extending, for the term "survivability" used
above refers to the chance of a vehicle surviving a sustained hit.
As was discussed in the introduction, an important aspect of
survivability is cross-country speed and agility, so that exposure
to attack is minimised. This extension is the subject of continuing
study and will be published shortly by Wright and Rollo [7].
IN SITU SOIL-STRENGTH MEASUREMENT USING THE CONE PENETROMETER
The cone penetrometer provides an easy and convenient system for
measuring soil
strength in the field and has been used successfully by US Army
Waterways Experiment
-
MEAN MAXIMUM PRESSURE IN CROSS-COUNTRY MOBILITY 269
Station (WES) as a descriptor of soil strength in establishing
empirical soil-vehicle relationships [8]. Moreover, Rohani and
Baladi [9] have, through analysing the mechanism of penetration,
established a correlation between the cone penetrometer readings
obtained and the expected value, predicted in terms of conventional
soil strength parameters c and qb (see, for example, Fig. 8).
FIG. 8.
- 80-
a z
0 60- 0
8 S
40-
20-
1
/ 2'o 4'0 6'o 8'0
MEASURED CONE INDEX, PSI
Comparison of predicted and measure cone index for clay (tk = 0)
after Rohani and Baladi (ref. 9).
Unfortunately, homogeneous soils rarely present themselves in
practice, where the natural process of deposition and man's
intervention in tillage, result in both lateral and vertical
variations in soil gradations, void ratio and moisture content. The
lateral variations are described, for strategically important
areas, in the NATO Cross Country Mobility (CMM) maps. Rowland et aL
[10] have investigated the variation of cone index in the critical
layer with area and season within this zone, producing detailed and
valuable estimates of the proportion of land surface having a
particular strength. By selecting a "critical layer", some of the
more intractable problems of handling cone index data are avoided.
Figure 9 shows the variation of cone index with moisture content
and depth for a well controlled test site. Although at any
particular depth there is a discernible relationship between cone
index and moisture content, the variation with depth is simply a
function of the stratified nature of the soil. Equally
problematical are the data of Fig. 10 which shows the variation of
cone index and moisture content on a particular day within a small
area of a typical North German layered soil.
Soil strength information is fundamental to predicting cross
country mobility, however wise selection and handling of the data
is vital if meaningful predictions are to result.
STATISTICAL TREATMENT OF CONE INDEX VALUES The inherent
variability of cone index readings demands a statistical treatment
of field
data. Kogure et al. [11] described the essential statistical
techniques which have been
-
270 J.G. HETHERINGTON and 1. LITTLETON
O O 200
180-
160-
140 -
120-
1OO -
80-
60-
404
20-
FIG. 9.
~ 0 0 SOIL : F INE GRAINED S ILTY SAND
mm
0--100 mrn
MOISTURE CONTENT % i I ~ - - i
10 2i0 3TO 40 510 6'0 70
Values of cone index against moisture content (controlled site,
RMCS).
E E
100-
200
300
400-
5CO-
CONE INDEX
10 20 30 40 50 60 70 80 90 1OO 110 120 130 140 I I r ? I L I I I
I L i I I
o
O
1CJ 2~0 3'0 MOISTURE CONTENT %
CONE INDEX MOISTURE CONTENT
FIG. 10. Variation of C1 and moisture content with depth --
North German layered soil.
developed below. The techniques will be described in the context
of 60 cone index readings taken on a single day within an
apparently homogeneous, fiat, silty clay field. Testing was
conducted in four batches of fifteen readings, each of which can be
treated as a separate sample of size 15 (Table 1).
Each sample consists of 15 independent observations of the
variable cone index from the (infinitely large) number of readings
which could have been taken from the chosen area. By simply
combining the batches in various ways, sample sizes of 15, 30, 45
and 60 data can be
-
MEAN MAXIMUM PRESSURE IN CROSS-COUNTRY MOBILITY
TABLE 1.
271
Sample 1 Sample 2 Sample 3 Sample 4
120 175 190 142 170 130 180 175 190 180 175 157 125 172 135 180
130 172 190 165 Values shown 145 167 130 175 are average of 172 160
135 165 readings taken 145 157 145 120 at 150mmand 185 145 180 150
300mmdepth. 200 140 185 125 160 145 120 147 202 180 150 175 145 160
180 155 160 150 152 127 190 145 170 142
Sample mean 163 Standard deviation 26
159 161 153
13 23 Mean of all sixty data = 158.9
Standard deviation = 21.5
19
obtained, and this fact will be used to demonstrate the benefits
which accrue from large samples. For each sample, the mean and
standard deviation have been tabulated in Table 1.
Drawing inferences from the data is greatly facilitated if it
can be shown that they follow the normal distribution. The goodness
of fit can be investigated using the Chi-squared distribution as
follows. The range within which the sixty data of Table 1 fall is
divided into a number of cells. Using the mean and standard
deviation of the sixty data, the number of data which would be
expected to occur in each cell, assuming the data are normally
distributed, (E) is calculated and compared with the number which
is observed to occur in each cell (O).
A value of X2m is evaluated for all as follows:
(O - E ) 2 X2m - - -
E
and then summed over all the cells to give a value of X2m for
the whole sample. In this case the value of X2m is 6.549. Although
there were eight cells, the size of the sample, n, the mean, x and
the sample standard deviation, S, were used in establishing the
expected value in each class, and so there are only 5 degrees of
freedom. From the X 2 distribution,
X~5%) (5) = 11.07.
Since the value of the X 2 statistic obtained from the goodness
of fit test is less than the value from the X~5~) distribution, it
is not possible, at this level of confidence, to reject the
hypothesis that the sample comes from a normally distributed
population.
Being only in possession of the information afforded by the
fifteen readings of sample 1, and wishing to make an estimate of
the true mean value of the whole of the chosen area, one would only
be able to state, with a specified level of confidence, that the
mean lies within certain limits. The larger the sample and the
smaller the standard deviation, the smaller will
-
272 J .G. HETHERINGTON and I. LITTLETON
be the range within which the mean of the population can be said
to be, at a specified level of confidence. In fact one can state,
with a 100 ( l -a)% level of confidence that the following range
includes the population mean (#):
S 2 S 2 x - t~/2 x / - - < # < x + t~,2xf--
n n
where ~ is the mean of the sample, S 2 is the variance of the
sample, n is the sample size and t~/2 is obtained from t
distribution tables. For example, using the fifteen data available
from sample 1 alone, it can be stated with 95% confidence that the
range 148-178 includes the population mean whereas including the
sixty data available from all four samples, the range within which
the population mean can be expected to lie at the same level of
confidence is narrowed to between 153 and 164. Thus collecting more
data can either enhance the level of confidence one has that the
mean lies within a specified range, or reduce the range within
which the mean can be expected to lie at a specified level of
confidence.
Assuming the data to be normally distributed, the trafficability
assessment is simply made by entering the normal distribution with
the appropriate value of cone index. The data of Table 1 are for a
good, uniform site and therefore provide a somewhat unrealistic
example, However, for a low mobility vehicle with a VCIs0 of 140,
the probability (p) of encountering soil with strength greater than
this (i.e. the percentage of the ground trafficable) is found from
the normal distribution tables to be 81%. This statement is itself
the subject of uncertainty, due to the variation in the data. At
the 95% confidence level, it can be stated that p lies within the
range:
p - 1.96 x/p(1 -P )
-
MEAN MAXIMUM PRESSURE IN CROSS-COUNTRY MOBILITY 273
,,x, z
8
130'
120
110"
100
f X - - /I
~ ~b A 6~ SAMPLE S=E
FIG. 1 l. Effect of sample size on VCI assessment.
the relationship shown in Fig. 12. In the sequence of analysis
presented here, this relationship provides the link between
Rowland's MMP and the vehicle's ability to traverse ground with a
particular value of strength as determined by the RCI. It is
acknowledged that the use of Rowland's MMP and the relationship of
Fig. 12 may introduce errors, and it may be desirable to introduce
a more sophisticated model of soil/vehicle interaction at a later
stage.
FIG. 12.
i (VCi)~
300.
200
IO0
0 [ o 2'o ,,'o 6o 8'0 ,;o "-
VCI (psO
Relationship between MMP and (VCI)j or (VCI)50 (adapted from
ref. 4).
-
274 J.G. HETHERINGTON and I. LITTLETON
The Wong model examines the mechanics of the interaction between
a tensioned track supported on a system of suspended road wheels
and a deforming terrain. The pressure- sinkage response of the soil
is characterized by the equation p = kz" for steadily increasing
sinkage, with refinements to cope with the cyclic loading which
results from a sequence of road wheels. The model is able to
accommodate other forms of pressure sinkage relationship. In the
formulation, an array of simultaneous equations is developed which
are essentially statements of equilibrium and compatibility for the
soil-track interface.
The shear stress distribution beneath the track is deduced from
the characterisation of the shear stress vs shear strain
relationship for the soil, the degree of slip and the normal
pressure distribution beneath the track. The solution of the
assembled equations by computer yields comprehensive information
concerning a specific vehicle's performance over selected terrain.
Reference [ 13] presents convincing supportive evidence from
instrumented trials for track pressure distributions, drawbar pull
and sinkage of a tracked test vehicle on sand, snow and muskeg. The
model indicates the importance of both terrain stiffness (Fig. 13)
and initial track tension on the pressure distribution: stiffer
terrain and lower track tension both result in more pronounced
peaks of pressure beneath the wheel stations and therefore higher
MMP values. These and numerous other vehicle parameters, omitted by
Rowland, are shown to have an effect on the true surface ground
pressure distribution.
FIG. 13.
kN/m 2
300-
250 -
200
150-
100
50
0 i 2 3 4 5 5 7 8 cJ x103kNlm 3 TERRAIN STIFFNESS k
Variation of the computed value of mean maximum pressure with
terrain stiffness after Wong (ref. 5).
A programme of work at RMCS is seeking to examine the influence
of many of these parameters on MMP. A one tenth scale model of the
Challenger main battle tank track and suspension system (Fig. 14)
has been constructed for testing in the mobility bins. The model
offers the opportunity of varying the number of road wheels, road
wheel diameter, suspension stiffness, track tension, track plate
profile, and track pitch. As part of his study Bowring [1] examined
the dependence of MMP on the number of road wheels and road
-
MEAN MAXIMUM PRESSURE IN CROSS-COUNTRY MOBILITY 275
FIG. 14. One tenth scale model of challenger MBT.
wheel diameter for the model on a uniformly graded sand. Figure
15 demonstrates that the number of wheels significantly affects
MMP, whereas wheel diameter is relatively unimportant. An attempt
to correlate measured pressure with prediction of the Wong model is
in hand.
40.
35-
30-
25-
2o"
15
FIG, 15. Measured values of MMP from one tenth scale model
tests, compared with Rowland predictions (at depth of 23 ram)
(increase by factor of 1.75 to obtain values at surface).
-
276 ]. G. HETHERINGTON and I. LITTLETON
SURVIVABILITY ASSESSMENT
The procedure outlined in Fig. 7 has been carried out for (a) a
main battle tank (MBT) and (b) a mechanised infantry combat vehicle
(MICV), the results being presented in Figs 16-18
100
m < > 80
60-
40-
20-
M.B.T. THREAT : 500mmRHA ARMOUR:SPEC~L
TERRA~ :FRG RNER VALLEYS
P A S S
~ PASS
0 50 ~o ~% ~o do ~oo
TRAFFICABIL~Y (%)
FIG. 16.
t 10 50
VEHICLE : MBT
TERRAIN : FRG RIVER VALLEYS
CURRENT RANGE OF MBT MASS
i I 6O 710
!
FIG. 17.
go ' ~'o TRA FFICABILITY (%)
-
MEAN MAXIMUM PRESSURE IN CROSS-COUNTRY MOBILITY 277
lOO-
m < 90- _> >
~ co-
70-
VEHICLE : MBT
TERRAIN : FRG RIVER VALLEYS
No. OF PASSES : 50
6'0 ~o
FIG. 18.
s'o 9'0 TRAFFICABILITY (%)
m
>
D ~9
1OO
80-
60,
,4,0-
20-
MICV
THREAT =75ram RHA
ARMOUR : ALUMINUM
TB:~RAIN: FRG RIVER VALLEYS
\ LE PASS
50 PASS
50 ~o do ~o lOO
FIG. 19.
"mAFF~A~U'rY (%)
-
278 J .G . HETHERINGTON and I. L ITTLETON
VEHICLE : M ICV
TERRAIN : FRG RIVER VALLEYS
No. OF PAS,SES : SINGLE
100 HREAT
75mm
HA
60 "'>
40
20
50 ' 6'0 ~ 7~3 ~ 8~0 ~ 9~0 i
TRAFF ICABIL ITY (%)
FIG. 20.
for MBT and Figs 19-21 for MICV. The demands of mobility are
characterised in Fig. 16 and 19 where the requirement for fifty
pass trafficability has such a significant protection penalty that
survivability is greatly reduced. Figures 17 and 20 explore the
single pass case in greater detail by showing the effect of (a)
increased threat level and (b) armour type on surviability. The
current range of MBT masses will give 60 to 75% trafficability over
FRG river valleys and could offer protection to threats in the
range of 400-600 mm of RHA, if exclusively special armour were
used. The current MICV, however, will offer 75 to 95% single pass
trafficability and up to total immunity against threats in the
range 75-100 mm RHA. It becomes apparent from Fig. 18 that the
combination of multi-pass and high percentage trafficability proves
too demanding a requirement for MBTs, leaving the current
configuration of tank with insufficient protection to be viable. A
similar, though less severe, effect is apparent for MICVs in Fig.
21.
The stark reality of the protection/mobility trade-off as
displayed in Figures 16-21 emphasises the importance of careful
specification of the mobility requirement. A request for multi-pass
capability over a high proportion of the terrain will result in
poor protection. The corollary is, of course, that a demand for
total immunity will result in a correspondingly poor mobility.
Moreover a scarcity of terrain data, when statistically analysed,
would lead to an overpessimistic view of potential mobility and
again would result in reduced survivability. There are, of course,
two ways to break the two handed stranglehold on the AFV designer
described above. One is to develop more effective armour materials,
which provide better protection for a given weight w the other to
develop more efficient track/wheel and suspension systems to
provide lower ground pressures for a given vehicle mass.
-
MEAN MAXIMUM PRESSURE IN CROSS-COUNTRY MOBILITY 279
100
60
VEHICLE : MICV
TERRAIN : FRG RIVER VALLEYS
No. OF PASSES : FIFTY
40'
20
:5O 60 70 80 gO
TRAFFICABILiTY (%)
FIG. 21.
CONCLUSIONS
(i) A quantitat ive relat ionship has been established between
the mobi l i ty requirement and the resultant survivabil ity of
AFVs.
(ii) Excessive demands for mobi l i ty will result in poor
protect ion and vice versa. (iii) Only better a rmour materials or
better t rack/wheel and suspension systems can
simultaneously improve protect ion and mobil ity. (iv) Soil
strength data obtained with the cone penetrometer are subject to
large inherent
variat ions due to inconsistencies in terrain. (v) Statist ical
analysis of cone index data enables confidence levels to be placed
on terrain
assessment - - larger samples providing better predictions.
REFERENCES
[1] R. A. W. BOWRING, The Construction and Testing of a Model
for a Study of the Parameters which Affect Tracked Vehicle Ground
Pressure. MSc Thesis, RMCS, Shrivenham, UK (1985).
[2] G. W. TURNAGE, Performance of Soils under Track Loads.
Technical Report No M-71-5, US Army Waterways Experimental Station,
Vicksburg, MS, USA (1971).
[3] Whittaker's DPV for Tank Hulls. OA Group Note 544, RMCS,
Shrivenham, UK (1978). [4] D. ROWLAND, Tracked Vehicle Ground
Pressure. MVEE Report No 72031, MVEE, Chertsey, UK (1972). [5] i .
GARBER and J. Y. WONG, Prediction of ground pressure distribution
under tracked vehicles - - I. An
analytical method for predicting ground pressure distribution,
d. Terraraechanics 18 (1) (1981). [6] E.A. LORD, Investigation of
Track Vehicle MMP. MSc Thesis, RMCS, Shrivenham, UK (1986). [7]
R.A. WRIGHT and N. H. ROLLO, Survivor; a computer-aided analysis of
AFV mobility and survivability. ASC
Div I Advanced Study Report, RMCS, Shrivenham, UK (1986). [81 A.
A. RULA and C. J. NLrrTALL, JR, An Analysis of Ground Mobility
Models. Tech Report M-71-4, WES,
Vicksburg, MS, USA (1971).
-
280 J .G. HETHERINGTON and I. LITTLETON
[9] B. ROHAN~ and G. Y. BALADI, Correlation of mobility cone
index with fundamental engineering properties of soil. Proc. 7th
Int. Conf. Int. Soc. for Terrain-Vehicle Systems, Calgary, Canada
(1981).
[ 10] D. ROWLAND, H. J. DOVE and G. TORNTON," Terrain
Limitations to the Use of Agility. Memo 7525 Defence Operational
Analysis Establishment (1976).
[11] K. KOGURE, Y. OHIRA and H. YAMAGUCHI, Basic study of
probabilistic approach to prediction of soil trafficability - -
statistical characteristics of cone index. J. Terramechanics 22 (3)
(1985).
[12] J.Y. WONG, M. GARBER and J. PRESTON-THOMAS, Theoretical
prediction and experimental substantiation of the ground pressure
distribution and tractive performance of tracked vehicles. Proc.
Inst. Mech. Engrs. 19811 (15)(1984).
[ 13] J.Y. WONG and J. PRESTON-THOMAS, Parametric analysis of
tracked vehicle performance using an advanced computer simulation
model. Proc. Inst. Mech. Engrs 200 (D2) (1986).