A hybrid model for selecting location of mobile cranes in bridge construction projects/Hibridinis modelis parenkant savaeigiu kranu vieta tiltu statybos objektuose/Jauktais modelis mobila celtna novietosanai buvlaukuma tiltu buvprojektiem/Mobiilsete kraanade asukohavaliku hubriidmudel sillaehitusprojektides.
Marzouk, Mohamed ; Hisham, Mohamed
1. Introduction
Optimum locations of equipment and other facilities is a main
concern in bridges projects. This task is considered complex due to the
presence of many variables and constraints which lead to decisions that
are not guaranteed to be the best decisions regarding time, cost, and
safety. Using optimization techniques in construction helps in solving
many problems including the site layout problem, and equipment
locations. The optimization technique used in this paper is Genetic
Algorithms (GAs). GAs are search algorithms that are based on the
natural selection and genetics to search through decision space for
optimum solutions. They employ a random yet directed search for locating
the globally optimal solution (Sanad et al. 2008). GAs have many
advantages such as: optimization with continuous or discrete variables;
dealing with a large number of variables; providing a list of optimum
variables, not just a single solution; and working with numerically
generated data, experimental data, or analytical functions (Haupt, Haupt
2004).
GAs have been applied in several applications. Zouein et al. (2002)
used GAs for solving site layout problem with unequal size and
constrained facilities. Sanad et al. (2008) used GAs to obtain optimal
construction site layout considering safety and environmental aspects.
Elbeltagi et al. (2004) uses GAs in optimization of temporary facilities
locations in integration with a scheduling tool. Ning et al. (2010)
developed a method that uses continuous dynamic searching scheme to
guide the max-min ant colony optimization algorithm to solve the dynamic
site layout planning problem under the two congruent objective functions
of minimizing safety concerns and reducing construction cost. Gholizadeh
et al. (2010) used harmony search algorithm to solve the problem of
assigning a set of predetermined facilities to a set of pre-allocated
locations within a construction site.
Mobile cranes are considered main type of equipment that is used in
bridges construction sites. Choosing the suitable mobile cranes and
their positions in bridges construction sites is a very important task
that must be done accurately. Any failure in achieving this task in an
efficient manner leads to excessive losses related to safety and costs.
A lot of efforts have been made to generate 3D models in different
applications. Raynar (1990) used artificial intelligence techniques to
find the minimum number of crane positions necessary to erect structural
steel. Al-Hussein et al. (2005) developed optimization algorithm for
selection and on site location of mobile cranes. Tam and Leung (2002)
integrated GAs with 3D visualization for optimum positioning of tower
cranes. Tantisevi and Akinci (2009) presented an approach for
automatically generating motions of mobile cranes to support conflict
detection by extending existing approaches in product and process
modeling and visualization of construction operations. Behzadan and
Kamat (2010) presented augmented reality that employs graphical
visualization to plan and design construction operations. Realistic
visual outputs are created and translated into three-dimensional (3D)
virtual contents (CAD model engineering) of the animated scenes.
Tantisevi and Akinci (2007) presented an approach for generating
workspaces that encapsulate spaces occupied by mobile cranes moving
during an operation. Hasan et al. (2010) presented an automated system
which is designed to assist practitioners in calculating the mobile
crane's support reactions and in designing the supporting system.
Wu et al. (2011) presented an algorithm for selecting mobile cranes on
construction sites which takes into account the lifting capacity, the
geometrical characteristics of the crane, the dimensions of equipments
and riggings, and the ground bearing pressure. Tantisevi and Akinci
(2008) presented an approach that determines possible locations of
mobile cranes based on discrete-event simulation of crane operations
incorporating dynamic behaviors of cranes.
Bridge Information Modeling (BrIM) is considered a big innovation
in bridge engineering and construction industry. It is not just a
geometrical representation of bridges, but it is an intelligent
representation of bridges since it contains all information needed about
bridges through their whole lifecycle. Bridge information modeling goes
beyond traditional bridge design by fostering data reuse in different
processes. Thus, 3D model of the bridge serves as a window into the vast
information asset, and organizations begin to optimize business
processes that cross the bridge lifecycle by more flexible access to
information about the bridge (Peters 2009). BrIM has great effect on the
improvements of the three main concerns of bridges stakeholders which
are quality, schedule, and cost and it is needed for bridges since it
creates consistency in information in different phases from design to
maintenance (Marzouk et al. 2010). The paper presents a hybrid model
that integrates BrIM and GAs to select best mobile cranes positions in
bridge construction site to meet erection requirements and site
constraints in order to minimize the time of erection.
2. Proposed hybrid model
The proposed hybrid model integrates different commercial software
packages. First, 3D BrIM module is developed taking into consideration
site boundaries and conditions. The coordinates of erection locations
and site boundaries are then exported to the GAs module which determines
the mobile crane locations that satisfy the safety, clearance, and site
boundaries constraints. These locations are then exported to the BrIM
module. The mobile crane model and other site conditions are visualized
in the BrIM module while the locations that are selected by GAs module
and contradict with these conditions are excluded. The erection process
is simulated by using the animation feature of BrIM. This simulation is
done at the locations that previously selected by the GAs model and
don't contradict with site conditions. The best location for the
crane is then chosen based on simulation results, where the location
that provides minimum erection time is selected. Fig. 1 shows the
connectivity between different software packages and methods to achieve
the required integration. A detailed description of the methodology is
presented in the below sections.
[FIGURE 1 OMITTED]
[FIGURE 2 OMITTED]
3. Developing 3D BrIM module
The 3D bridge information module is developed using several
commercial software packages. In the proposed framework, Tekla
structures software is utilized. The developed module is an intelligent
module that has several attributes. Although this module is used in
several purposes such as cost estimation, 4D modeling, and drawings
creation; this module is needed to be integrated with the construction
site conditions in order to choose the suitable mobile crane equipment
positions and plan their movement in the construction site, therefore,
the construction site is needed to be represented accurately to achieve
the required task. Google Sketchup software is proposed to be used in
representing the construction site. This software is used to capture the
construction site location from Google Earth as shown in Fig. 2. The
site boundaries and surrounding conditions are then be drawn and
highlighted as shown in Fig. 3. The drawn site boundaries and
surrounding buildings are then exported from Google Sketchup to Tekla
Structures software as a reference model of extension DWG. This
reference model assists in modeling surrounding buildings and
conditions, and shows the site boundaries and the original 3D BrIM model
together. Fig. 4 depicts the 3D BrIM model, site boundaries, and
surrounding buildings models.
It should be noted that the surrounding buildings are modeled as
building blocks with low level of detail because the purpose of modeling
these buildings is to determine and visualize the surrounding
constraints that may affect choosing the cranes' positions. The
erection locations of bridge beams or segments, and the site boundaries
are essentially the main inputs in the GAs module. Tekla Structures
layout manager is used to extract these positions by choosing the
erection locations and the site boundaries. The extracted points are
opened in Microsoft Excel sheet; consequently, it is easy to link the
extracted coordinates with the GAs model which is developed in Microsoft
Excel sheet.
[FIGURE 3 OMITTED]
[FIGURE 4 OMITTED]
[FIGURE 5 OMITTED]
4. Genetic algorithm module
GA module is used to obtain the possible locations of a mobile
crane in a bridge construction site during erection of beams on the
bridge piers. The obtained positions are then inserted to Bridge
Information Modeling software to perform animation and simulation for
erection process, and then choose the position that minimize the
erection time. The utilized optimization technique takes into account
two erection locations (at both edges of bridge pier). This is done
while the effective pier widths related to the two erection locations
are calculated automatically by the module. In addition, site
boundaries, safety during lifting and erection, and clearance
constraints are considered in GA module. The safety is achieved by
choosing a crane that affords lifting the load, and not exceeding the
limited lifting radii and boom lengths. All constraints and equations
used in developing the GA module are listed below. Fig. 5 shows a mobile
crane model and the parameters used in deriving the equations that are
used in the optimization process.
[R.sub.L] = [square root of ([([X.sub.er] - [X.sub.cr]).sup.2] +
[([Y.sub.er] - [Y.sub.cr]).sup.2]]), (1)
where [R.sub.L]--the lifting radius, m; [X.sub.er] and
[Y.sub.er]--the plan coordinates of erection location, m, while
[X.sub.cr] and [Y.sub.cr]--the plan coordinates of the centre of the
crane, m.
L = [[R.sub.L] [+ or -] [AA.sub.R] - [C.sub.3] cos [alpha]]/cos
[alpha], (2)
where L--the main boom length, m; [C.sub.3]--sheave offset, m.
[C.sub.1] is the boom clearance, m, as reported by Al-Hussein et
al. (2005) in Eq (3):
[C.sub.1] = [L - [[[D.sub.1] - [C.sub.4] cos ([phi] -
[alpha])]/cos[alpha]] - [[H.sub.1]/sin[alpha]]]/ [tg[alpha] +
[1/tg[alpha]]], (3)
where [D.sub.1]--the effective width that affects the erection or
the load placing process, m. It is the distance between the edge of the
building (or bridge pier) and the point of the load placing or erection.
For the work presented in this paper, [D.sub.1] is calculated for two
erection locations of beams which are at the edges of a bridge pier. The
work presented in this paper assumes that the beams erection is done by
two cranes, so, the point of carrying the load is near the beam edge.
The calculations are done for one crane and repeated for the other crane
by the same methodology. Calculation of [D.sub.1] is done based on the
orientation of the bridge pier. For example, for the case shown in Fig.
6, two effective widths are considered [D.sub.1(1)] and [D.sub.1(2)] as
per Equations.
[[theta].sub.1] = [tg.sup.-1] [[absolute value of ([Y.sub.er1] -
[Y.sub.cr])]/[absolute value of ([X.sub.er1] - [X.sub.cr])]], (4)
[[beta].sub.1] = [gamma] + [[theta].sub.1] - 90[degrees], (5)
[D.sub.1(1)] = [B/cos [[beta].sub.1]], (6)
[[theta].sub.2] = [tg.sup.-1] [[absolute value of ([Y.sub.er2] -
[Y.sub.cr])]/[absolute value of ([X.sub.er2] - [X.sub.cr])]], (7)
[[beta].sub.2] = 90[degrees] - [gamma], (8)
[D.sub.1(2)] = B/[cos([[beta].sub.2] + [[beta].sub.2])]. (9)
The GA module was developed using evolver software which is MS
Excel Add-In. All variables and equations are modeled in an excel sheet
where the optimization process is to be applied. The genes of the
developed GA module are: [X.sub.cr], [Y.sub.cr], [[alpha].sub.1] and
[[alpha].sub.2]. The first two genes represent the location of the
center of the crane, while the last two genes represent the inclination
angle between the boom and the ground for the two erection locations.
The objective function is maximization, and minimization of Eq (1) for
the two erection locations. This is achieved by maximizing and
minimizing the radius at the first erection location and then checking
that the resulted location of the crane satisfies safety and clearance
requirements for the second erection location, and then maximizing and
minimizing radius at second erection location and then checking that the
resulted location of the crane satisfies safety and clearance
requirements for the first erection location. Therefore, optimization
process will be performed for four cases.
Safety constraints are satisfied by keeping the lifting radius and
the boom length within their limits which are defined in mobile crane
charts. Representing safety constraints in the GA module is done by
inserting the lifting radii, and boom lengths ranges that achieve safety
for lifting a certain load. The limits for the first two genes
([X.sub.cr] and [Y.sub.cr]) are obtained from the values extracted by
the Tekla Layout manager software as discussed before. The GA module
calculates the lifting radii from Eq (1), and calculates the boom
lengths from Eq (2). The erection locations ([X.sub.er] and [Y.sub.er])
are also extracted by the Tekla Layout manager software. The module
calculates the effective widths for the two erection locations based on
the different cases of pier orientation by inserting the number of the
case, and the angle of rotation between the pier axis and X axis. The
model requires specific parameters related to each crane to be inserted
by the user based on mobile crane geometry such as sheave offsets
([C.sub.3], and [C.sub.4]), [Z.sub.cr] (height from ground to boom pin),
and AAR (distance between boom pin to rotation centre).
5. Choosing best cranes' locations
The GA module provides several feasible solutions. The GA module
doesn't take into consideration other site conditions such as the
presence of utilities (such as pipes) at shallow depths, and the
available spaces in site based on the schedule. This is attributed to
the fact that GA module is designated to consider final position at
placing the load without considering these site conditions, and without
considering erection time minimization. BrIM module is an effective tool
in choosing the best crane location based on the results retrieved from
the GA module. Representing resulted crane locations is be done using
Tekla Structures software by inserting the resulted locations as IFC
components as shown in Fig. 7. 4D modeling is an effective feature in
BrIM. It depends on linking a time schedule to the components of the
BrIM model, thus, the project team visualizes what is to be constructed
at a specific date, the achieved work at this date, and compare actual
work with planned work. This feature has an important role in choosing
crane location because it represents the available spaces and the
restricted spaces in the site at time of erection. Fig. 8 shows 4D
modeling in Tekla Structures software, while Fig. 9 shows the project
status at a specific erection date. The next step is exporting the 4D
model, generated by BrIM module, including site boundaries, surrounding
buildings, and represented crane locations from Tekla Structures
software to Navisworks Manage software. The extension of the exported
file is to be IFC. The model of the existing utilities such as cables,
water pipes, or sewer pipes are also be imported from other BIM software
packages to Navisworks manage software. The next step is to import the
3D mobile crane model and exclude the crane locations that contradict
with existing utilities or site conditions at the date of erection. Fig.
10 shows a location which is excluded due to the presence of casted slab
and beams above this location which prevents the crane from lifting and
placing the load in its erection location.
[FIGURE 6 OMITTED]
[FIGURE 7 OMITTED]
[FIGURE 8 OMITTED]
[FIGURE 9 OMITTED]
[FIGURE 10 OMITTED]
[FIGURE 11 OMITTED]
[FIGURE 12 OMITTED]
6. Simulation and animation
After the exclusion of contradicting positions, different trials
are executed to choose the best crane location. In each trial, a
simulation of the erection process is done by inserting the mobile crane
to capture the selected location and perform boom movement animation.
The animation starts by lifting the beam from the truck (or stored
position) and ends with placing the beam in its final position. The
position of the truck or the stored position is determined based on site
conditions, and safety requirements. The purpose of simulation and
animation is to determine the crane locations that have the least number
of boom maneuvers from lifting to placing the load. As the number of
boom maneuvers decreases, the erection time decreases, and that achieves
the goal of using BrIM with GAs which is to minimize time of erection.
Fig. 11 shows a snapshot of animation done by Navisworks software to
simulate the erection process. The time used in the animation is
obtained from the distances moved by the boom during erection, and the
velocity of the boom movement while carrying the load obtained from the
crane specifications.
7. Checking safety requirements
BrIM is used to check the safety requirements with respect to
carrying loads in the bridge construction site by a specific crane. This
is done in three-steps procedure: 1) a hyperlink is created to activate
specified crane charts by just clicking on the crane model; 2)
visualizing the weight of any beam or structure member which is an
attribute of the intelligent components of the BrIM module. This step is
achieved in Navisworks Manage software by setting Quick properties to be
visualized as IFC for the category, and weight for the attribute, thus,
the weight value is visualized by just pointing the component; 3)
performing necessary measurements for the boom angle and the lifting
radius. Fig. 12 depicts this procedure illustrating; the crane charts,
weight of component, and boom angle and lifting radius are all
visualized together. As such, the user decides whether the crane is
capable to lift the required weight based on its current location or
not.
8. Conclusions
The paper presented a hybrid model that integrates GAs and BrIM for
choosing the best locations for mobile cranes in bridges'
construction sites. The paper illustrated how to represent bridge
construction site and surrounding obstacles in BrIM module by
integrating different software packages such as Google Sketchup and
Tekla Structures. The site boundaries and the coordinates of erection
locations are exported from the BrIM module using Tekla Structures
layout manager. The paper presented the development made in GA module
for optimizing the location of mobile cranes. The GA module was
developed using Evolver software (MS Excel Add-In). The developed module
takes into consideration two erection locations (at edges of a bridge
pier). It also takes into account the change in the effective widths
which depends on the orientation of the bridge pier with respect to the
site coordinates. Safety and clearance constraints are taken into
account in the developed model. The resulted crane locations are
exported to BrIM module. By integrating the resulted crane locations, 4D
model, site boundaries, mobile crane 3D model, and surrounding buildings
in Navisworks Manage software; the infeasible locations are excluded.
The best position is chosen from the remaining locations by importing
the crane model in these locations and simulating erection process. The
chosen location is the one that has minimum boom maneuvering and time of
erection. The paper also presented the procedure for checking safety
requirements with respect to carrying loads in the bridge construction
site by a specific crane.
Caption: Fig. 1. Connectivity between different components
Caption: Fig. 2. Capturing construction site by Google Sketchup
Caption: Fig. 3. Highlighting site boundaries and surrounding
buildings
Caption: Fig. 4. Site boundaries representation in Tekla structures
Caption: Fig. 5. Parameters of GA module
Caption: Fig. 6. Estimation of effective widths
Caption: Fig. 7. Exporting GA feasible solutions to Tekla
structures
Caption: Fig. 8. Generating 4D modeling
Caption: Fig. 9. Demonstrating project status at a specific date
Caption: Fig. 10. Excluded location due to clashes
Caption: Fig. 11. Simulation and animation of beam erection in BrIM
Caption: Fig. 12. Checking safety requirement procedure
doi: 10.3846/bjrbe.2013.23
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Received 9 May 2011; accepted 6 June 2011
Mohamed Marzouk (1) ([mail]), Mohamed Hisham (2)
Dept of Structural Engineering, Cairo University, 12613 Giza, Egypt
E-mails: (1) mmarzouk@staff.cu.edu.eg; (2) mhanafy@saudioger.com