17 decision support system for optimum soft clay improvement technique

Civil Engineering
Decision support system for optimum soft clay improvement technique
for highway construction projects
Ibrahim Mahmoud Mahdi, Ahmed M. Ebid ⇑
, Rana Khallaf
Structural Engineering and Construction Management Department, Faculty of Engineering, Future University in Egypt, New Cairo, Cairo, Egypt
a r t i c l e i n f o
Article history:
Received 30 March 2019
Revised 26 July 2019
Accepted 13 August 2019
Available online xxxx
Keywords:
DSS
VE
AHP
Soft clay improvement
Highway embankment
a b s t r a c t
Identifying a soft clay improvement strategy is a main challenging in highway construction projects due
to the various conditions involved. Hence, the objective of this paper is to present a Decision Support
System (DSS) to select the optimum soft clay improvement technique for this type of projects. Value
Engineering (VE) is integrated with Analytical Hierarchy Process (AHP) for the proposed (DSS). Using
the AHP provides a robust means of identifying the relative importance of any criteria or factors for soft
clay improvement alternatives. The scope of this study includes four of the most commonly used tech-
niques for soft clay improvement: soil replacement, pre-loading, vertical drains, and the construction
of embankments on piles. The proposed methodology was verified using four case studies of highways
under construction in northern Egypt. The results show that the proposed (DSS) successfully predicted
the optimum soft clay improvement technique in three out of the four cases.
Ó 2019 THE AUTHORS. Published by Elsevier BV on behalf of Faculty of Engineering, Ain Shams Uni-
versity. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
1. Introduction
Multiple challenges face construction projects in achieving the
project objectives while balancing all the constraints. Therefore,
it is crucial to explore all possible approaches that would help
reach the project objectives related to cost, time, performance,
and quality. For highway construction projects, soft clay improve-
ment is one of the main items that affect both the cost and time of
a project. This is particularly important when the highway is
founded on a surface layer of soft clay. The main target of soft clay
improvement in this case is to enhance the mechanical properties
of the existing soft soil. This enables it to support the weight of the
highway embankment and the traffic loads acting on it with
acceptable safety factors and embankment settlement as per the
project specifications. In this study, four soft clay improvement
alternative techniques are considered. One of these technique is
to replace the whole soft layer with compacted granular soil
(referred to as embankment on replacement), the second one is
to construct a granular filter on the soft soil, load it with embank-
ment load and wait until the soft layer consolidates then reshape
the distorted embankment and construct the road (referred to as
embankment with pre-loading). The third technique is similar to
the second one but adds the utilization of vertical drains (wick
drains) to speed up the consolidation process (referred to as
embankment with vertical drains). The fourth alternative, denoted
embankment on piles uses a recently developed system in which
the embankment is supported on a grid of piles connected by
two perpendicular layers of geo-grid at the ground surface. The
arching effect generated in the embankment soil and the tie action
provided by the geo-grid layers act together as virtual raft transfer-
ring the embankment loads to the grid of piles. A small cap on each
pile is used to prevent punching [31].
2. Objective
The aim of this research is to develop a decision support system
(DSS) for optimum soft clay improvement of highway sloped
embankments on soft clay during the early design phase. Value engi-
neering (VE) integrated with Analytical Hierarchy Process (AHP) and
Delphi are used to develop this assessment approach. The developed
(DSS) considered eight factors which are cost, construction duration,
constructability, sustainability, environmental impact, risk impact
and safety, technology impact, and infrastructure conflict to recom-
mend the optimum improvement technique considering all points
of view not just the cost reduction one. Also, using AHP provides a
robust tool for identifying the relative level of importance of the cri-
https://doi.org/10.1016/j.asej.2019.08.007
2090-4479/Ó 2019 THE AUTHORS. Published by Elsevier BV on behalf of Faculty of Engineering, Ain Shams University.
This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
⇑ Corresponding author.
E-mail addresses: ibrahim.mahdi@fue.edu.eg (I.M. Mahdi), ahmed.abdelkha-
leq@fue.edu.eg (A.M. Ebid), rana.khallaf@fue.edu.eg (R. Khallaf).
Peer review under responsibility of Ain Shams University.
Production and hosting by Elsevier
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Please cite this article as: I. M. Mahdi, A. M. Ebid and R. Khallaf, Decision support system for optimum soft clay improvement technique for highway con-
struction projects, Ain Shams Engineering Journal, https://doi.org/10.1016/j.asej.2019.08.007

teria used for the selection of the optimum soft clay improvement
alternative. The following sections describe the Value Engineering,
Delphi technique, and the AHP conducted in this study. The pro-
posed (DSS) is verified using highway under-construction projects
in the north of Egypt at current market conditions.
3. Background
3.1. Value engineering
The construction industry faces numerous challenges in its effort
to achieve project objectives while maintaining project constraints.
Therefore, the optimum strategy is to study all possible approaches
that increase the value with minimum effort, cost, and time while
achieving optimal performance and quality. Value Engineering
(VE) was introduced to the construction industry during the late
nineteen fifties and has been employed worldwide for over 60 years.
Since its early beginnings, this technique has been widely applied in
construction projects [22,7,16,4,10]. VE is a systematic approach,
which aims at achieving value for money by providing all necessary
functions at the lowest cost. Chen et al. [4] classified VE as an orga-
nized application that uses both technical knowledge and common
sense to identify and eliminate unnecessary project costs and
thereby achieve value-for-money. Chavan [3] categorized VE as
one of the most appropriate and systematic techniques to improve
value in construction projects. The VE process explores con-
structability, manufacturability, and maintainability of a project at
the early stages and thereby identifies potential conflicts as well as
savings [24,17,5]. The VE process, denoted as a VE job plan, is an
organized problem-solving technique which consists of several
phases, namely, information, creativity, evaluation, development,
and proposal. The creativity phase is the most crucial phase to pro-
duce innovative ideas. This phase requires existing information
and experiential knowledge from past projects [23]. Dell’lsolla [7]
utilized his wide practical experience in the construction manage-
ment and value engineering to declare that VE should be performed
as early as possible before securing of funds, approval of services,
systems, or design to maximize the value. Potential savings from
VE applications are much greater with its early application. When
VE is applied at a later stage, increased investment is required to
implement any changes as well as more effort to withstand potential
stronger resistance to change.
Value Engineering (VE) can be viewed as a rigorous, interdisci-
plinary problem solving technique, which focuses on improving
the value of the functions that are required to accomplish the
objective of any product, process, service, or organization. The
highest performance in VE is achieved when the focus is mainly
to increase the value rather than to reduce the costs. Gudem
et al. [8] stated that implementing VE in projects can bring about
numerous benefits, such as reducing costs by 20% to 30%, enhanc-
ing operational performance by 40% to 50%, and upgrading product
quality by 30% to 50%. The application of VE in this research is lim-
ited to the determination of the optimum technique to improve
soft clay layers underlying the highway sloped embankment of
highway projects during the conceptual design phase.
Value study generally involves three stages: (i) pre-workshop
(preparation); (ii) workshop (execution of the six-phase job Plan);
and (iii) post-workshop (documentation and implementation)
[28]. The most crucial phases in the VE methodology are the func-
tional analysis, the creativity in finding alternatives, and the eval-
uation process.
3.2. Decision support systems
Decision support systems such as multi-criteria decision-
making (MCDM) are created to channel expert judgment and form
educated opinions to make decisions. The objective of an MCDM is
to structure a problem and identify and evaluate the multiple cri-
teria available. These techniques have been used in construction
management research in areas such as highway management, pro-
ject delivery methods, and risk identification and ranking
[15,32,14,13]. However, no previous research has proposed a DSS
for soil improvement techniques. In this paper, the selected MCDM
technique is the Analytic Hierarchy Process (AHP).
3.3. Delphi technique
The Delphi technique is a tool used to collect data and achieve
consensus on an issue. An advantage of this methodology is that it
does not require all experts to be physically located in one place,
which makes it easier to identify experts without any geographic
constraints. It also eliminates biases since all experts provide input
individually and are not swayed by group dynamics. Multiple
rounds are conducted to achieve consensus between participants
to facilitate decision-making. Hallowell and Gambatese [9]
reported that usually 1 to 3 rounds are conducted in a study, which
mainly depends on the presence of consensus or dissent in the
results of each round. It has been widely used in construction man-
agement research for reporting and decision-making among other
uses [21,29,13].
3.4. Analytical hierarchy process (AHP)
It was developed by Saaty [26–27]. The AHP is used to calculate
the relative importance and weighting of multiple alternatives and
consists of the following steps: (i) creating a hierarchical arrange-
ment of criteria (goals); (ii) performing pair-wise comparison of
criteria and alternatives in the comparison matrix using a proper
scale; (iii) pair-wise evaluation of elements in the hierarchy (goals,
criteria (sub-criteria) and alternatives); and (iv) calculation of the
maximal eigenvectors (kmax) and the consistency index
CI ¼ kmaxÀn
nÀ1
Â Ã
. The consistency of the decision is obtained with con-
sistency ratio CR. If in the comparison matrix CR is less than 0.10,
then the estimated relative importance of the criteria (priority of
the alternative) is deemed acceptable.
3.5. Soft clay improvement techniques for highway projects
3.5.1. Embankments on soil replacement
This alternative is based on replacing the entire top soft layer
with well-compacted granular soil. The replacement layer should
be extended horizontally beyond the toe of the slope from both
sides at a distance equal to its thickness to ensure that the dissi-
pated embankment load will be contained within the replacement
layer, as shown in Fig. 1a. It is a simple technique to improve the
soil strength beneath the embankment utilizing the same kind of
labor and equipment used for the construction of the embankment.
This technique may be suitable for top soft layers up to 3.0 m thick,
but it is uneconomical for thicker layers.
3.5.2. Embankments with pre-loading
In this technique, the soil beneath the embankment is improved
by using the weight of the embankment itself as pre-loading on the
top soft layer. The soft soil tends to consolidate under loading and
the excess water dissipates into the adjacent permeable layers.
However, consolidation is a very slow process, which may need
weeks or even months to achieve the desired effect depending
on the properties and the thickness of the soft layer. Because of
that, it is a common practice to use a granular filter on the top of
the soft layer to speed up the consolidation process, as shown in
Fig. 1b. The thickness of this filter is designed to ensure that the
2 I.M. Mahdi et al. / Ain Shams Engineering Journal xxx (xxxx) xxx

volume of the voids between the particles is large enough to
absorb the excess water from the consolidating soft layer. It is a
common practice to use a geotextile layer below the embankment
to act as a filter that allows water to pass through and prevents soil
particles from moving. In addition, two perpendicular layers of
geo-grid are commonly used below the embankment to increase
the global stability and minimize the differential settlement
caused by consolidation (Sadok et al. [25]).
3.5.3. Embankments with vertical drains
This technique is commonly used for thicker soft-top layers
(>9.0 m). It uses the same concept of consolidation described pre-
viously with one additional enhancement. Instead of waiting for
the water to flow through the soft layer to the top or bottom sur-
face, which may take a considerable amount of time, a fast track
vertical path is provided by using vertical sand drains or vertical
wick drains to direct the water from the top filter layer down to
the permeable bottom layer (refer to Fig. 1c). This system consid-
erably speeds up the consolidation. The down side is that sand
drains cost almost as much as piles, while wick drains need special
equipment and highly skilled labor to install [19]. Like pre-loading
technique, two layers of geo-grid and one layer of geotextile are
used below the embankment.
3.5.4. Embankments on piles
This technique avoids loading the top soft layer altogether.
Instead, the loads from the embankment are transferred down to
the supporting strata using piles. To achieve this goal without
using a concrete raft, a combination of arching action in embank-
ment soil and tie action in geo-grid layers is utilized to form a
structural system that can transfer the embankment loads to the
piles, as shown in Fig. 1d. This mechanism is based on dividing
the embankment loads into three parts. The first part contains
the soil in and above the arching zone and is transferred directly
to the piles by arching action. The second and third parts consist
of the soil below the arching zone. The second part is transferred
to the piles through the geo-grid while the third part is supported
directly on the soft soil layer and causes it to settle [30]. In order to
minimize the third part, van Eekelen [30] recommends that the
spacing between piles be kept at less than 2.5 m and that the min-
imum embankment height to be equal to 0.66 times the spacing.
4. Methodology
4.1. Estimating cost and construction duration for each alternative
In order to estimate the cost and duration (for construction) of
each alternative, structural design must be carried out to deter-
mine the dimensions, specifications, and quantities of materials
used. The technical bases of this structural design are described
for each alternative in Appendix A.
4.2. Development of the decision support system (DSS) for optimum
soft clay improvement technique of sloped embankments
Selecting the optimum technique depends on many factors such
as the soft layer thickness, embankment height, existing highway
constraints, as well as the characteristics of soft clay improvement
technique. In this study, eight factors are considered to identify the
Fig. 1. Soft clay improvement techniques: (a) Replacement, (b) Pre-loading, (c) Vertical drains and (d) Embankment on piles.
I.M. Mahdi et al. / Ain Shams Engineering Journal xxx (xxxx) xxx 3

optimum soft clay improvement alternative. These factors are: (1)
cost; (2) construction duration; (3) constructability; (4) sustain-
ability; (5) environmental impact; (6) risk impact and safety; (7)
technology impact; and (8) infrastructure conflict. These eight fac-
tors are evaluated and ranked using the Delphi technique.
The DSS that combines AHP and Delphi for soft clay improve-
ment alternatives (SIA) with respect to all eight evaluation factors
were conducted in one excel sheet for ease of use. The output of
this (DSS) is relative weights (or scores) of each alternative for a
certain combination of embankment height and thickness of the
soft clay layer considering all eight evaluation factors. The alterna-
tive with the highest weight (score) is the optimum choice for that
combination.
5. Applying the developed (DDS) on case of Egypt at present
conditions
The proposed methodology was applied to highway construc-
tion projects in Egypt considering the present conditions such as
material prices, labor productivity and equipment availability.
The details of the calculations are presented in the following
sections.
5.1. Estimating cost and construction duration for each alternative
Quantities of each alternative were calculated using
Eqs. (1)–(17) (see appendix) for embankment heights from 1 m
to 12 m and using an embankment length equal to 100 m and
thicknesses of the soft clay layer ranging from 1 m to 9 m. Hence,
the cost and duration for each case were calculated using the aver-
age current prices and productivity in the Egyptian market, which
are illustrated in Table 1. Those prices were collected from BOQ &
Specifications department of (NECB) consultancy firm.
Based on the calculated values, the relative weights for both the
cost and the duration for each alternative were calculated for each
combination of embankment height and thickness of clay layer.
Tables 2 and 3 show the calculated weights for each alternative.
Sample of the calculations is presented in Appendix B.
5.2. Identifying the relative weights of the factors using the Delphi
technique
Eight Egyptian highway construction experts were involved in
this process with the following characteristics: two highway con-
sultant engineers with an experience of more than 20 years, two
heads of technical office of highway construction companies with
an experience of more than 15 years, two senior highway design
engineers with an experience of more than 10 years, and two fac-
ulty staff members at universities (one specialized in soil mechan-
ics and the other specialized in construction management) with an
experience of more than 20 years each. The experts were asked to
assess the four soft clay improvement techniques in terms of the
eight factors considered. These factors are: cost, construction dura-
tion, constructability, sustainability, environmental impact, risk
Table 1
Considered unit price, number of crew, and crew productivity.
Item Unit Cost (LE)/Unit Crew productivity (/month) No. of crew Total productivity (/month)
Pavement (m2
) 300 1200 2 2400
road base (m3
) 100 4500 2 9000
Pitching (m2
) 150 125 6 750
Embankment (m3
) 200 4000 6 24,000
Replace./Filter (m3
) 250 2000 6 12,000
Wick drain (m) 100 12,000 1 12,000
Geo-grid (m2
) 100 7500 1 7500
Pile (m3
) 8000 2500 1 2500
Indirect cost (/month) 200,000
Table 2
Samples of relative weights of soft clay improvement alternatives with respect to the cost factor.
Embankment height (m)
4 m 8 m 12 m
Alternative Soft clay thick.
3 m 6 m 9 m 3 m 6 m 9 m 3 m 6 m 9 m
Embankment on Replacement 87% 64% 48% 90% 71% 59% 91% 76% 64%
Embankment with Pre-Loading 99% 85% 65% 100% 93% 82% 100% 96% 88%
Embankment with VL. drains 100% 99% 93% 99% 100% 100% 99% 100% 100%
Embankment on piles 90% 100% 100% 57% 64% 62% 39% 43% 44%
Table 3
Samples of relative weights of soft clay improvement alternatives with respect to the time factor.
Embankment height (m)
4 m 8 m 12 m
Alternative Soft clay thick.
3 m 6 m 9 m 3 m 6 m 9 m 3 m 6 m 9 m
Embankment on Replacement 100% 85% 70% 100% 93% 79% 100% 100% 87%
Embankment with Pre-Loading 64% 35% 19% 73% 48% 29% 78% 60% 39%
Embankment with VL. drains 79% 70% 61% 83% 80% 73% 85% 89% 82%
Embankment on piles 95% 100% 100% 91% 100% 100% 86% 100% 100%

impact and safety, technology impact, and infrastructure conflict.
After collecting and analyzing the results, they were sent to the
experts for a second round. The results received showed some dis-
sent so a third round was necessary. The results of applying the
Delphi method for the considered eight factors are illustrated in
Table 4. Sample of the calculations is presented in Appendix B.
5.3. Development of the analytical hierarchy process (AHP) model
The AHP process was used as described in the previous section to
estimate the relative weights of soft clay improvement alternatives
with respect to six of the eight evaluation factors: constructability,
sustainability, environmental impact, risk impact and safety, tech-
nology impact, and infrastructure conflict. The remaining factors
(cost and duration) were calculated depending on the respective
characteristics of each alternative since quantitative data could be
calculated for both factors. The results of the AHP are summarized
in Table 5. Sample of the calculations is presented in Appendix B.
5.4. Mapping the optimum improvement technique using the
developed (DSS)
Combining relative weights of each alternative with respect to
cost and duration with those of the remaining evaluating factors
and triangulating them using the results of the Delphi methodol-
ogy for each combination of embankment height and soft clay
layer thickness gives a clear map for the optimum choice of soft
clay improvement for any combination. This map is illustrated in
Table 6 and can be used by researchers or practitioners to deter-
mine the optimum method to choose in case of similar conditions
to those in Egypt.
5.5. Varifiing the optimum improvement technique map
The (DSS) optimum choices shown in Table 7 were selected
directly from Table 6 based on embankment height and thickness
of soft clay layer and verified using case studies of highway pro-
jects under-construction in Northern Egypt where soft clay layers
are commonly encountered. (NECB) was the contractor’s consul-
tant in the following four case studies:
(i) 30 June highway – Port Said; it is a new strategic highway
passes in the soft clay at Suez Canal zone. The embankment
at the considered section was 6.0 height (at crossing tunnel)
and was located on 32.0 to 35.0 m thick soft clay, the soil
Table 4
Relative weights of evaluation factors using Del-
phi method.
Evaluation factors Relative weight
Cost 41.5%
Construction duration 23.7%
Constructability 7.6%
sustainability 4.2%
Environmental impact 5.1%
Risk impact and safety 5.9%
Technology impact 4.2%
Infrastructure conflict 7.6%
Table 5
Relative weights of soft clay improvement alternatives with respect to evaluation factors.
Soft clay improvement alternative Constructability Sustainability Environmental Risk and Safety Technology Infrastructure
Alt.1 Embankment on Replacement 32% 32% 12% 32% 16% 30%
Alt.2 Embankment with Pre-Loading 38% 14% 34% 38% 14% 40%
Alt.3 Embankment with VL. drains 12% 16% 33% 12% 36% 12%
Alt.4 Embankment on piles 18% 38% 21% 18% 34% 18%
Table 6
Optimum soft clay improvement alternatives for different embankment heights and soft layer thickness.
REP: Embankment on replacement.
PRE: Embankment with pre-loading.
VL.: Embankment with vertical drains.
PILE: Embankment on piles.
Table 7
Case study results.
Project Embankment
height (m)
Soft clay
thickness (m)
Actual Soil
improvement technique used
(DSS) Soil
improvement technique
30 June highway – Port Said (14 + 400 to 21 + 450) 6.0 >30 VL. VL.
Port Said-Damietta highway At Ashtom El-Gamil City 4.0 >30 PILE PILE
Banha-El Mansoura highway At Kafr-Shokr (45 + 500) 5.5 9.0 REP. PILE
Zagazeg – Elsemballawen highway (19 + 800 to 21 + 400) 5.0–8.0 2.0–4.5 REP. REP.

report suggested both pre-loading and vertical drains tech-
niques to improve the soft layer and the contractors (DETAC
Co. & Misr Delta Co.) chose the vertical drains techniques.
(ii) Port Said-Damietta highway; the location was at the approach
of Ashtom-Elgamil bridge near Port-Said. Embankment
height was 4.0 m and rested on 26.0 m of soft clay. Both con-
sultant and contractor (EL-Safa Co.) agreed to use piles option.
(iii) Banha-El Mansoura highway; the considered zone was the
approach of new bridge at Kafr-Shokr village, approach
height was 5.5 m and rested on 9.0 m of soft clay. Both
replacement and piles techniques were suggested in the soil
report and the contractor (SAMCO) chose the replacement
alternative.
(iv) Zagazeg – Elsemballawen highway, this project aims to dou-
ble the width of the existing highway, the embankment
height was varied between 5.0 m in typical sections and
8.0 m at crossing tunnels, that soft clay layer thickness was
about 2.0 to 4.5 m and the contractor was El-Salam Interna-
tional Co. which carried out the recommended replacement
layer as per soil report.
Case studies locations are shown in Fig. 2. Real recommended
improvement techniques were collected by the authors from their
consulting work. Verification results shows good matching between
the actual chosen soft clay improvement technique and the pro-
posed optimum technique calculated by the (DSS). The improve-
ment technique recommended in real-life matched the technique
calculated using the (DSS) in three out of four of the projects.
6. Verification results and discussion
Table 6 summarized the results of applying the developed (DSS)
considering the present conditions in Egypt. It covers all combina-
tions of soft clay thickness between (1.0 to 9.0 m) and embank-
ment height between (3.0–12.0 m). This mapping leads to the
following findings:
For thin soft soil layers (3.0–4.0 m thick), replacement is the
optimum choice regardless of embankment height. This makes
sense because it eliminates any negative impact of soft soil lay-
ers at a reasonable cost and with little impact on time and
constructability.
For soft clay layers thicker than 4.0 m, the embankment height
has a greater significance on deciding the optimum soft clay
improvement technique. In case of lower embankment heights
(up to 5 m), embankment on piles technique is the most suit-
able choice. This result is reasonable because the relatively
lightweight embankment significantly reduces the cost of piles.
On the other hand, for thicker embankments (more than 5 m),
the best choice for soft clay improvement is the vertical drains
technique. This result is logical because this technique is much
cheaper than piles and a noticeable reduction in indirect cost is
also realized by avoiding the longer construction duration
required for a piled alternative.
Embankment with pre-loading is the optimum choice for a lim-
ited range of conditions. For thicknesses of the soft clay layer in
the 3.0–4.0 m range and embankment heights of more than
9.0 m, this technique is suitable. This is because the relatively
long time required to construct the high embankment is suffi-
cient to consolidate the relatively thin soft clay layer, which
minimizes the indirect cost of the project.
It should be noted that these findings are based on the relative
weights, prices, and rates of productivity that are used in the DSS.
This makes the findings valid for highway construction projects in
Egypt in the current (2018) market conditions and the boundaries
between alternatives will shift with changes in the weights and
market conditions.
Fig. 2. Locations of case studies in north of Egypt.

7. Conclusions
The conclusions of this research could be summarized as
follows:
Using the (AHP) along with the Delphi technique allowed cap-
turing tacit and implicit knowledge through the use of a combi-
nation of calculations and expert opinion.
The developed (DSS) needs surveying for market prices and
expert opinions to be tuned for certain country/region and cer-
tain market conditions
Applying the tuned (DSS) on a range of soft clay thicknesses in
combined with a range of embankment heights produces a map
for the optimum improving technique.
The generated map of optimum improving technique is accu-
rate only for the considered country/region and market
conditions
The optimum improving technique could be selected directly
from the generated map based on thickness of soft clay and
embankment height without any farther calculations of cost
and time because they are already estimated for each combina-
tion during generating the map.
The tuned (DSS) for Egypt in current market conditions was suc-
cessfully applied and verified using four highway construction
projects.
This research was concerned in sloped embankments only
where is no restriction on bottom embankment width. For farther
studies, the same (DSS) technique could be used select the opti-
mum retaining system for restricted sites highway projects.
Appendix A. (Technical bases for geotechnical design)
Generally, the design of the highway embankment itself does
not depend on the soft clay improvement technique as long as
the minimum embankment height required in the piled technique
is observed. Hence, this part of design is common for all alterna-
tives. The compacted soil of embankment is usually specified as
non-plastic granular soil (Class A-1 A-2) according to the
AASHTO classification [20]. The safe embankment side slope
depends on the unit weight of the soil and its shear strength
parameters. Generally for the previously mentioned AASHTO
classes, the unit weight ranges from 1.8 to 2.2 t/m3
, the angle of
internal friction ranges between 36° and 40°, and cohesion
strength ranges between 0.0 and 5.0 t/m2
, Bowles [1]. Accordingly,
the side slope ranges between 2V:3H and 1V:2H depending on soil
type and embankment height.
Side slopes must be protected against erosion; usually 40 cm
thick pitching or 15 to 20 cm lean concrete is used [2]. Road base
and pavement are constructed on the top surface of the embank-
ment. The base layer is usually built of crushed stone with depth
depending on the structural design of the roadway pavement. Traf-
fic load on the road are provided by applicable design code but may
be approximately taken as 2.0 t/m2
[12].
Common values of pavement layers and embankment soil
parameters were considered in this study. These parameters are
as follows: (i) thickness of base layer = 0.35 m; (ii) thickness of
asphalt pavement = 0.15 m; (iii) unit weight = 2.0 t/m3
; (iv) angle
of internal friction = 38°; and no cohesion (Yang 2004). Based on
the previous parameters, in order to achieve an acceptable safety
factor of 1.5 against slope failure, the side slope angle should not
exceed 27.5°, which is equivalent to a slope of (1V:2H) [6].
Considering a 1.0 m width sidewalk on each side of the roadway
and a side slope protected with 0.4 m thick pitching with 1.0 m
width flat toe at top and bottom of slope. Hence, for an embank-
ment with a top width (B top), length (L embankment), slope
height (H slope), and replacement thickness (H rep.), the following
quantities may be calculated as follows:
Pavement area ðm2
Þ
¼ ðBtop À 2:0ÞL embankment ð1Þ
Base layer volume ðm3
Þ
¼ 0:35 Â B top Â L embankment ð2Þ
Embankmentvolume ðm3
Þ
¼ L embankment Â H slope ðB top þ 2 H Þ ð3Þ
Slope pitching area ðm2
Þ
¼ ð4:5 H slope þ 4:0Þ:L embankment ð4Þ
Required land area ðm2
Þ
¼ ðB top þ 4 H slope þ 2 H repÞ:L embankment ð5Þ
In addition to these quantities that are common to all alterna-
tives, additional quantities should be calculated based on the
specific soft clay improvement technique as shown in the follow-
ing section.
A. Embankment on soil replacement
Volume of replacement ðm3
Þ
¼ ðRequired land areaÞ Â ðH repÞ ð6Þ
B. Embankment with pre-loading
Filter thickness ðmÞ ¼ H clay=6 ð7Þ
Consolidation time ðmonthÞ ¼ H clay
2
=3 ð8Þ
Geotextile area ðm2
Þ ¼ Required land area ð9Þ
Geo À grid area ðm2
Þ ¼ 2 Â Required land area ð10Þ
C. Embankment with vertical drains
Total wick drain length mð Þ
¼ 0:25 Required land areað Þ Á H clay þ Hrep:ð Þ ð11Þ
Consolidation time ðmonthÞ ¼ H clay=3 ð12Þ
D. Embankment on piles
In order to estimate the quantities parametrically, the ultimate
pile capacity was estimated based on standard penetration test
values (N30),[18]. Considering (N30) for the dense granular soil
equals to 50, bearing strength reduction factor for board piles
equals to 7, and safety factor equals 2.0, the allowable working
load of pile with diameter (D) and stock length (L stock) could be
calculated as follows:
PilecapacityðtonÞ ¼ 133D2
þ 15:7D Â Lstock ð13Þ
Maximum pile load could be calculated as follows considering
spacing of 2.5 Â 2.5 m:
Pile Load ðtonÞ
¼ 2:5 Â 2:5 Â 2:0 Â H slope ¼ 13:5 H slope ð14Þ
From Eqs. (13) and (14), and assuming that (D ¼ Hslope=18),
then stock length (L stock) equals (0.4 H slope) and total pile length
equals to (L stock + H clay):

Pile volume ðm3
Þ ¼ H slope
2
Á ðL stock þ H clayÞ=400 ð15Þ
Total volume of piles ðm3
Þ
¼ Pile volume Á Required land area=6:25 ð16Þ
Regarding the two layers of geo-grid, they area could be calcu-
lated considering 50% lap as follows:
Geo À grid Area ðm2
Þ ¼ 1:5 Â 2 Â Required land area ð17Þ
Eqs. (1)–(17) were used to calculate the quantities and duration
needed for each alternative. The Application section provides the
steps taken and a discussion of the steps for the proposed DSS.
Appendix B. (Sample of DSS Calculations)
A. Sample of BOQ Calculations:
The BOQ of different alternatives for embankment length,
height and top width of 100.0 m, 4.0 m and 20.0 m respectively
with side slopes of 1V:2H rested on 3.0 m thick soft clay layer
could be calculated as follows:
Pavement area (m2
)
= ð20:0 À 2:0Þ Â 100:0 = 1800
Base layer volume (m3
)
= 0:35 Â 20:0 Â 100:0 = 700
Embankment volume (m3
)
= 100:0 Â 4:0 Â ð20 þ 2 Â 4:0Þ = 11200
Slope pitching area (m2
)
= ð4:5 Â 4:0 þ 4:0Þ Â 100:0 = 2200
For embankment on soil replaceement (H rep = 3.0 m)
Required land area (m2
)
= ð20:0 þ 4 Â 4:0 þ 2 Â 3:0Þ Â 100 = 4200
Volume of replacement (m3
)
= 4200 Â 3:0 = 12600
For embankment with pre-loading (H rep = 0.5 m)
Filter thickness (m) = 3:0=6 = 0.5
)
= ð20:0 þ 4 Â 4:0 þ 2 Â 0:5Þ Â 100 = 3700
Filter volume (m3
) = 3700 Â 0:5 = 1850
Consolidation time (month) = 3:02
=3 = 3.0
Geotextile area (m2
) = 3700 = 3700
Geo-grid area (m2
) = 2 Â 3700 = 7400
For embankment with vertical drains (H rep = 0.5 m)
Filter thickness (m) = 3:0=6 = 0.5
)
= ð20:0 þ 4 Â 4:0 þ 2 Â 0:5Þ Â 100 = 3700
Filter volume (m3
) = 3700 Â 0:5 = 1850
Geotextile area (m2
) = 3700 = 3700
Geo-grid area (m2
) = 2 Â 3700 = 7400
Consolidation time (month) = 3:0=3 = 1.0
Total wick drain length (m)
= 0:25 Â 3700 Â ð3:0 þ 0:5Þ = 3238
For embankment on piles (H rep = 0.0 m)
)
= ð20:0 þ 4 Â 4:0 þ 2 Â 0:0Þ Â 100 = 3600
Pile Diameter (D) (m) = 4:0=18 = 0.22
Stock length (L stock) (m) = 0:4 Â 4:0 = 1.60
Pile length (m) =Max½10mOrð1:6 þ 3:0ÞŠ = 10.0
Pile volume (m3
) = 0:785 Â 0:222
Â 10:0 = 0.38
Total volume of piles (m3
) = 0:38 Â 3600=6:25 = 219
Geo-grid Area (m2
) = 1:5 Â 2 Â 3600 = 10800
B. Sample of Cost and Time Calculations:
Time and cost for the previously calculated BOQ could be calcu-
lated using the unit prices and productivity rates listed in Table 1
as follows:
For embankment on soil replacement
Item Cost (LE) Time (month)
Pavement 1800 Â 300
= 540 000
1800/2400
= 0.75
Base layer 700 Â 100
= 70 000
700/9000
= 0.08
Embankment 11200 Â 200
= 2 240 000
11 200/24 000
= 0.47
Slope pitching 2200 Â 150
= 330 000
2200/750
= 2.93
Replacement 12600 Â 250
= 3 150 000
12 600/12 000
= 1.05
Site preparation – 4200/4200
= 1.0
Indirect cost 6.3 Â 200 000
= 1 260 000
–
Total 7 590 000 6.30
For embankment with pre-loading
= 540 000
1800/2400
= 0.75
= 70 000
700/9000
= 0.08
Embankment 11 200 Â 200
= 2 240 000
11 200/24 000
= 0.47
= 330 000
2200/750
= 2.93
Filter 1850 Â 250
= 462 500
1850/12 000
= 0.15
= 0.88
Geotextile 3700 Â 100
= 370 000
3700/7500
= 0.50
Geo-grid 7400 Â 100
= 740 000
7400/7500
= 1.00
Consolidation time – 3.0
= 1 952 000
–
Total 6 704 500 9.76
For embankment with vertical drains
= 540 000
1800/2400
= 0.75
= 70 000
700/9000
= 0.08
Embankment 11 200 Â 200
= 2 240 000
11 200/24 000
= 0.47
= 330 000
2200/750
= 2.93
Filter 1850 Â 250
= 462 500
1850/12 000
= 0.15

(Sample of DSS Calculations) (continued)
= 0.88
Geotextile 3700 Â 100
= 370 000
3700/7500
= 0.50
= 740 000
7400/7500
= 1.00
Consolidation time – 1.0
wick drain 3238 Â 100
= 323 800
3238/12 000
= 0.27
= 1 600 000
–
Total 6 676 300 8.0
For embankment on piles
= 540 000
1800/2400
= 0.75
= 70 000
700/9000
= 0.08
Embankment 11200 Â 200
= 2 240 000
11 200/24000
= 0.47
= 330 000
2200/750 = 2.93
= 0.86
= 1 080 000
10 800/7500
= 1.44
Piles 219 Â 8000
= 1 752 000
219/2500
= 0.09
= 1 320 000
–
Total 7 332 000 6.6
C. Sample of Calculations for Alternatives Relative Weights
with Respect to Cost Time (Tables 2 and 3):
Relative weights of alternatives shown in the 1st column of
Table 2 could be calculated as the ratio between minimum cost
to alternative cost as follows:
Relative weight of Replacement alternative
= 6 676 300/7 590 000 = 0.87
Relative weight of Pre-loading alternative
= 6 676 300/6 704 500 = 0.99
Relative weight of VL. drains alternative
= 6 676 300/6 676 300 = 1.00
Relative weight of Emb. on piles alternative
= 6 676 300/7 332 000 = 0.90
Similarly, the relative weights of alternatives shown in the 1st
column of Table 3 could be calculated as the ratio between mini-
mum duration to alternative duration as follows:
Relative weight of Replacement alternative
= 6.3/6.3 = 1.00
Relative weight of Pre-loading alternative
= 6.3/9.76 = 0.64
Relative weight of VL. drains alternative
= 6.3/8.0 = 0.79
Relative weight of Emb. on piles alternative
= 6.3/6.6 = 0.95
D. Sample of Calculations for Alternatives Relative Weights
with Respect to rest of considered factors (Tables 4 and 5):
Relative weights of considered factors shown in Table 4 were
calculated by applying (AHP) on the questioner results. The 1st
request in the questioner is to evaluate the importance of consider
factor from 1 for less important to 10 for most important. In the
3rd round, the evaluations were settled and the average evaluation
for the considered factors were 9.80, 5.60, 1.80, 1.00, 1.20, 1.40,
1.00 and 1.80 for cost, construction duration, constructability,
sustainability, environmental impact, risk impact and safety,
technology impact, and infrastructure conﬂict respectively.
Accordingly, the relative weight of certain factor is the ratio
between its evaluations to the sum of the evaluations. For example,
the relative weight of cost is 9:8=ð9:80 þ 5:60 þ 1:80 þ 1:00þ
1:20 þ 1:40 þ 1:00 þ 1:80Þ ¼ 0:463
Similar approach was used to estimate the relative weights of
each improvement technique with respect to considered factors.
The 2nd request in the questioner is to arrange the four alterna-
tives from 1 for less favorable to 4 for most favorable alternative
with respect to each considered factor regardless cost and duration
which relative weights could be calculated from BOQ. For example,
the average evaluations of alternatives with respect to con-
structability were 3.2, 3.8, 1.2 and 1.8 for Replacement, Pre-
loading, Vertical drains and embankment on piles respectively,
hence, the relative weight of replacement alternative with respect
to constructability is 3:2=ð3:2 þ 3:8 þ 1:2 þ 1:8Þ ¼ 0:32
E. Sample of Alternative Score Calculations (Table 6):
The optimum soft clay improvement technique for certain
embankment height on a certain soft clay thickness is the alternative
with highest score. Those optimum alternatives were mapped in
Table 6 for embankment height ranged between 3.0 and 12.0 m
and soft clay thickness ranged between 1.0 and 9.0 m. The score of
each alternative is the sum of multiplied factor relative weight from
Table 4 by corresponding alternative relative weight from Tables 2, 3
and 5. For example, the scores of the four alternatives in case of 4.0 m
embankment height on 3.0 m soft clay thickness are:
Total
Similarly, the score of Pre-loading, VL. Drains and Embankment
on piles are 0.674, 0.666 and 0.678 respectively. Accordingly,
Replacement is the optimum alternative for this case.
F. Results of case study (Table 7):
The optimum improvement techniques for each of four cases in
Table 7 were selected directly from Table 6 based on the embank-
ment height and soft clay thickness.
Appendix C. (Samples for the expertise questioners)
See Fig. 3.

References
[1] Bowles J. Foundation analysis and design. 5th ed. New York, NY, USA: McGraw-
Hill; 1997.
[2] Brockenbrough R. Highway engineering handbook: building and rehabilitating
the infrastructure. 3rd ed. The McGraw-Hill Companies; 2009.
[3] Chavan AJ. Value engineering in construction industry. Int J Appl Innov Eng
Manage 2013;2(12):18–26.
[4] Chen WT, Chang PY, Huang YH. Assessing the overall performance of value
engineering workshops for construction projects. Int J Project Manage 2010;28
(5):514–27.
[5] Cooke J. Improving the value of products and processes by combining value
analysis techniques and lean methods with TRIZ. In: TRIZ FUTURE
CONFERENCE – Global Innovation Convention. p. 2.
[6] Das B. Advanced soil mechanics. New York, NY, USA: Taylor Francis; 2008.
[7] Dell’lsolla AJ. Value engineering: Practical Applicationsfor Design,
Construction, Maintenance and Operation, 1997. Kingston, USA: R.S.Means;
1998.
[8] Gudem M, Steinert M, Welo T, Leifer L. Redeﬁning customer value in lean
product development design projects. J Eng, Des Technol 2013;11(1):71–89.
[9] Hallowell MR, Gambatese JA. Qualitative research: Application of the Delphi
method to CEM research. J Constr Eng Manage 2010:99–107. doi: https://doi.
org/10.1061/(ASCE)CO.1943-7862.0000137.
Fig. 3. Samples for the expertise questioners.

[10] Ismail A, Aminzadeh R, Aram A, Arshad I. Science publications value
engineering application in highway projects applying lean thinking in
construction and performance improvement. Am J Eng Appl Sci 2010;3
(4):699–703.
[12] Kezdi, A. Stabilized earth roads. Copyright (r) by Akademiai Kiado, Budapest,
Hungary; 1979.
[13] Khallaf R, Naderpajouh N, Hastak M. A systematic approach to develop risk
registry frameworks for complex projects. Built Environ Project Asset Manage
2018. doi: https://doi.org/10.1108/BEPAM-08-2017-0051.
[14] Li F, Phoon KK, Du X, Zhang M. Improved AHP method and its application in
risk identification. J Constr Eng Manage ASCE 2013;139:312–20.
[15] Liang R, Pensomboon G. Multicriteria decision-making approach for highway
slope hazard management. J Infrastruct Syst 2010;16:50–7.
[16] Male S, Kelly J, Gronqvist M, Graham D. Managing value as a management
style for projects. Int J Project Manage 2007;25(2):107–14.
[17] Nawi MM, Jalaluddin SMFWS, Zulhumadi F, Ibrahim JA, Baharum F. A strategy
for improving construction projects sustainability through value management
approach. Int J Appl Eng Res 2014;9(24):28377–85.
[18] NAVFAC DM-7.02 (Naval Facilities Engineering Command) (1986). Found
Earth Struct.; 1986.
[19] Nicholson P. Soil improvement and ground modification methods. Elsevier Inc;
2015.
[20] Nikolaides A. Highway engineering pavements, materials and control of
quality. Ó 2015 by Taylor Francis Group, LLC; 2015.
[21] Okoli C, Pawlowski SD. The Delphi method as a research tool: an example,
design considerations and applications. Inform Manage 2004;42:15–29.
[22] Palmer A, Kelly J, Male S. Holistic appraisal of value engineering in
construction in United States. J Constr Eng Manage 1996;122(4):324–8.
[23] Parker DE. Value engineering theory. Washington, D.C: Lawrence D. Miles
Value Foundation; 1985. p. 62–4.
[24] Perera S, Hayles CS, Kerlin S. An analysis of value management in practice: the
case of Northern Ireland’s construction industry. J Finan Manage Property
Constr 2011;16(2):94–110.
[25] Benmebarek Sadok, Berrabah Fouad, Benmebarek Naïma. Effect of
geosynthetic reinforced embankment on locally weak zones by numerical
approach. Comput Geotech 2015;65:115–25.
[26] Saaty TL. The analytic hierarchy process and the analytical network process:
planning, priority setting, resource allocation. New York, USA: McGraw-Hill;
2003.
[27] Saaty TL. Decision making with the analytic hierarchy process. Int J Serv Sci
2008;1(1).
[28] SAVE International. Value methodology standard and body of knowledge
Retrieved 2012, January 10 from http://www.value-eng.org, ; 2007.
[29] Sourani A, Sohail M. The Delphi method: review and use in construction
management research. Int J Constr Edu Res 2015;11(1):54–76. doi: https://doi.
org/10.1080/15578771.2014.917132.
[30] van Eekelen S. Basal Reinforced Piled Embankments Experiments, field studies
and the development and validation of a new analytical design model Ph.D
thesis. Technische Universiteit Delft; 2015.
[31] Wahls H. Design and construction of bridge approaches. Transport Res Board
Natl Res Council 1990.
[32] Xia B, Chan APC, Yeung JFY. Developing a fuzzy multicriteria decision-making
model for selecting Design-Build operational variations. J Constr Eng Manage
2011;137(12):1176–84.
Ibrahim Mahmoud Mahdi is a Professor of Project
Management at the Future University in Egypt. He
received his Ph.D. from University of Southampton,
England UK. Dr. Mahdi has over 30 years of professional
experience in all project management aspects including
Planning; Cost a, Risk management and Project Control.
He has been responsible for many assignments of highly
technical projects in Egypt, Kuwait and Gulf area espe-
cially KSA and UAE. His experience includes Preparing
tender’s packages; receiving and analyzing tenders,
making consultant and contractor recommendations,
issuing, executing and administering contracts; and
finally, supervising the construction to insure quality and schedule requirements
are met Dr. Mahdi has wide work experience in education and practicing project
management.
Ahmed M. Ebid is an Assistant Professor at the Future
University in Egypt. He received his Ph.D. in soil
mechanics from Ain-Shams Uni.-Egypt 2004. He is a
consultant in both geotechnical engineering and
designing concrete structures since 2012, He published
14 researches in geotechnical engineering, soil
mechanics, repairing using FRP and optimizing the
design of concrete elements.
Rana Khallaf is an Assistant Professor at the Structural
and Construction Management Department, Faculty of
Engineering and Technology, Future University in Egypt
(FUE). Dr. Rana has over 7 years of experience working
in Egyptian and American companies in the field of
construction project management consulting. She has
also previously cofounded a Project Management Con-
sultancy, which served US-based projects. She received
her PhD in Civil Engineering (Specialization: Construc-
tion Engineering and Management) from Purdue
University in the United States. She then worked as a
Lecturer at Purdue University before joining the Future
University in Egypt. Prior to that, she received her Bachelors and Masters degrees
from Ain shams University. She is active in research and her current interests
include: Public-private partnerships, Integrated project delivery, Game theory, Risk
analysis, Disaster risk reduction, as well as other contemporary topics.

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