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An Industrial Park Layout Design Method Considering Pipeline Length Based on FLUTE Algorithm
Mario R. Eden, Marianthi Ierapetritou and Gavin P. Towler (Editors) Proceedings of the 13th International Symposium on Process Systems Engineering – PSE 2018 July 1-5, 2018, San Diego, California, USA © 2018 Elsevier B.V. All rights reserved. https://doi.org/10.1016/B978-0-444-64241-7.50027-6
An Industrial Park Layout Design Method Considering Pipeline Length Based on FLUTE Algorithm Ruiqi Wanga, Yan Wub, Yufei Wanga*, Xiao Fengb, Mengxi Liua a
College of Chemical Engineering, China University of Petroleum - Beijing, No.18, Fuxue Road, Beijing, 102249, China b School of Chemical Engineering and Technology, Xi’an Jiaotong University, No.28, Xianning West Road, Xi’an, 710049, China [email protected]
Abstract The layout of an industrial park can significantly impact its economic benefit and safety. In terms of economy, a good layout means shorter pipeline length, leading to lower pipeline cost and material transport cost. In practice, the layout of an industrial park is manually determined based on experience according to the relationship of upstream and downstream. In academia, few systematic programming method has been proposed, and most of them only consider one-to-one connection pattern, pipeline networks with multi-branch are ignored. For systematic programming method, it has always been difficult to calculate the minimum length of pipeline network with multi-branch in an industrial park. FLUTE (Fast Lookup Table Based Wirelength Estimation Technique) algorithm is an accurate and fast method to solve rectilinear Steiner minimum tree problem based on a lookup table. In this paper, a novel method based on FLUTE algorithm is came up to calculate the minimum length of steam pipeline network in an industrial park and determine the layout. The total pipeline cost, which includes steam pipeline cost and material pipeline cost, is set as an objective function. Genetic algorithm is employed to optimize the layout of several plants in an industrial park. In the case study, it can be seen that, the calculation time is significantly reduced, and a better layout is obtained. Keywords: Industrial park layout; Pipeline network; Rectilinear Steiner minimum tree; FLUTE; Genetic algorithm
1. Introduction Layout design is a key step which must be passed in the process of chemical engineering design and construction. A good layout can reduce the capital cost for the pipeline and operation cost for material transportation, and enhance safety. Economy and safety are the main factors considered in the layout problem. Researches in chemical engineering layout can be divided into two aspects: one is to study the facility layout within a plant, and the other is to study the plant layout within an industrial park. Many researches about the facility layout within a plant are reported. Penteado and Ciric (1996) proposed a MINLP approach to determine the coordinates of facilities in a plant, considering land cost, piping cost, protection devices cost and risk cost. In their work, protection devices can prevent accidents or minimize the damage to the other nearby facilities, resulting in a protection devices cost at the same time. Patsiatzis et al. (2004)
194
R. Wang et al.
quantified the risk cost using FEI (Dow Fire & Explosion Index) system, while piping cost and protection cost were also involved to determine the layout of a plant. Latifi et al. (2017) worked out an optimal layout of a plant considering uncertainty and domino effects, and the allowance of multi-layer layout in this work makes this model more practical. Very few works have been done for designing the plant layout in an industrial park. A noteworthy difference between the facility layout and plant layout is pipeline network with branches. Pipeline networks, such as steam pipeline work, existed widely within an industrial park. Studies about facility layout mentioned above only calculated the lengths and costs of pipelines with point-to-point structure. It has always been difficult to calculate the minimum length of pipeline network with multi-branch in an industrial park. Wu and Wang (2017) firstly came up with an algorithm based on Kruskal algorithm to work out the minimum length and arrangement of pipeline network within an industrial park. Then Wu et al. (2016) combined this algorithm with risk evaluation to determine the layout of plants. But their algorithm is expensive in calculation time. A rectilinear Steiner minimal tree (RSMT) is a tree with minimum total edge length in Manhattan distance to connect a given set of nodes possibly through some extra nodes (Chu and Wong, 2008). Many algorithms have been come up to solve RSMT problem. GeoSteiner is an exact RSMT software developed by Warme et al. (2015) , but is relatively expensive in calculation time. Chen et al. (2002) proposed an algorithm called Refined Single Trunk Tree (RST-T), which is very effective for low-degree networks but not for high-degree networks. FLUTE (Fast Lookup Table Based Wirelength Estimation Technique) (Chu and Wong, 2005) is a fast and relatively accurate algorithm for RSMT. It achieves a good balance between calculation time and accuracy (Chu, 2004b). In this work, an industrial park layout design method is proposed, in which the problem of minimum length of pipeline network is converted to RSMT problem and calculated based on FLUTE algorithm. In the case study, the proposed method was compared with Wu and Wang’s work (2017). From the result, it can be seen that, when solving the same case, the calculation time of the proposed method is 38.9 s and Wu’s method is 69215.0 s. Calculation time is reduced sharply, and a better layout is obtained.
2. Methodology 2.1 Problem statement The objective function and constraints in this work are based on Wu and Wang’s work (2017). The free space in the industrial park is divided into several grids with the same size. Plants are treated as points. Each plant can only occupy one grid, which is put in the center of the grid. The distance between two plants is the distance between centers of the two grids and the distance is absolutely safe for plants. The pipeline must be arranged horizontally or vertically. Moreover, some plants should be put in some specific locations, according to the geographical and meteorological condition of the area where the industrial park sits. For example, the railway transportation plant should be located as near as possible to the railway line, and the air separation plant should be located in the upwind direction. Based on the assumption mentioned above, the aim of this work is to determine the location of plants in an industrial park to minimize the capital cost of the pipeline, including material pipeline and steam pipeline.
Industrial Park Layout Design Method Considering Pipeline Length
195
2.2 Objective function The objective function is set as the sum of material pipeline cost and steam pipeline cost, as is shown in Eq. (1). n
min C
3
¦a K ¦b L i
i 1
i
j
(1)
j
j 1
Where C is the total pipeline cost, n is the quantity of material pipeline, i represent different kinds of material flow, ai is the unit prize of i-th material pipeline, Ki is the length of i-th pipeline; j represent 3 different kinds of steam, bj is the unit prize of j-th steam pipeline, Lj is the length of j-th steam pipeline network. aj and bj come from the market prize. As the pipeline must be arranged horizontally or vertically, the Ki can be calculated by Eq. (2)
Ki | xin xout | | yin yout |
(2)
Where (xin, yin) and (xout, yout) is the coordinates of input and output plants respectively. The calculation of Lj is very complex that will be expressed in the next section. 2.3 Minimum length of steam pipeline network As mentioned in Introduction, the calculation of the minimum length of pipeline network has always been a thorny problem. In this work, this problem has been converted into RSMT problem. RSMT problem is to find a way to connect several given points by only horizontal and vertical lines. As is shown in figure 1, figure 1 (a) is the RSMT of the 3 given points, and figure 1 (b) is not. The Pipeline network connecting the plants of the steam generator or steam user, is the RSMT of those plants. Length vector is used to represent a certain connection. Figure 2 (a) is a connection of 4 given plants. The pipeline length of this connection is L1=2*h1+2*h2+h3+v1+v2+v3, so the length vector of this connection is p1= (2,2,1,1,1,1); figure 3 (b) is the shortest connection for the 4 plants, and the length is L2=h1+2*h2+h3+v1+v2+v3. The relevant length vector is p2= (1,2,1,1,1,1), which is called the optimal length vector. We can know which connection is shorter by comparing the length vector directly, instead of calculating the total length. For instance, length vector of (1,2,1,1,1,1) is shorter than (1,2,2,1,1,1) certainly.
Length=3
Length=4
v1
v1
v2
v2
v3
v3
h1 h2 h3 h2 h3 (a) (b) (a) (b) Figure 1 Examples of RSMT and non- Figure 2 Two connection patterns of 4 given plants RSTM
h1
R. Wang et al.
196
(a)
(b) Figure 3 Different relative locations of 4 plants
(c)
If the relative location of several plants is given and the edge lengths of grids are not given, many connections may be the shortest connection. Figure 3 (a) shows a kind of relative location of 4 plants (assuming that the lengths of edges are not determined). Both p3= (1,1,1,1,2,1) and p4= (1,2,1,1,1,1) may be the optimal length vector. Which one is optimal depends on the lengths of grid edges. In figure 3 (b), p3 is shorter, and in figure 3 (c) p4 is shorter. So p3 and p4 are called potential optimal length vector. For a certain relative location of plants, only few length vectors are potentially optimal comparing with all feasible connections. The authors of FLUTE previously calculated all the potential optimal length vectors for each condition of the relative location of points and saved the results. When the coordinates of plants are given, the relevant potential optimal length vectors for the relative location of those plants can be found. Then we calculate the lengths of each potential optimal length vector, and choose the shortest one. The minimum length of steam pipeline network and the arrangement can be obtained. This algorithm is very fast.
3. Case study 3.1 Basic data The case from Wu and Wang’s work (2017) is used, so that the proposed method can be compared with theirs. The case comes from a real petrochemical industrial park, which contains 20 plants and they should be arranged as 4×5 form. The distance between adjacent plants is set as 400 m. The plants and steam requirement are shown in Table 1, in which 1 means the plant needs steam and 0 means the plant does not need steam. This case contains 76 material flows. The type and diameter of a pipeline can be determined according to the property, flow rate and flow velocity of the transported material. In this work, the steam pipeline for the same degree has the same diameter. According to the geographical and meteorological condition of the area where the industrial park sits, 5 plants should be placed in the specific locations. They are shown in Figure 4. Both Wu and Wang’s method and the proposed method are implemented respectively to determine the layout of this case. The program of Wu and Wang’s method is provided by them. MATLAB is used to run the two programs. Genetic algorithm, which is also adopted in Wu and Wang’s work, is employed to solve the model for a fair competition. Genetic algorithm is generally regarded as one of the most effective algorithms. The generation is set as 1000, and the individual is set as 50. FLUTE is supplied by the authors in their official website (Chu, 2004).
Industrial Park Layout Design Method Considering Pipeline Length
197
Table 1 The plants and steam requirement of industrial park Number
Name
1 2 3 4 5 6 7 8 9
Power station Crude oil fractionation plant Gas separation plant Hydrogenation plant Residue and wax hydrodesuifurization plant Air compression and separation plant Fluid catalytic cracking plant Light hydrocarbon recovery plant Liquefied petroleum gas desulfuration and demercaptan plant Sulfur recovery plant Aromatic combine plant Hydrogen production Continuous reforming plant Naphtha hydrotreating Polypropylene and polyester Delayed coking plant Sewage treatment area Tank farm Railway transport department Central control room
10 11 12 13 14 15 16 17 18 19 20 RTD
High pressure steam 1 0 1 0 1 0 1 1 1
Middle pressure steam 1 1 1 1 1 1 1 1 1
Low pressure steam 1 1 1 1 1 1 1 1 1
0 1 1 1 0 1 0 0 0 0 0
1 1 1 1 1 1 1 0 1 1 0
1 1 0 0 0 1 0 1 0 0 1
RTD
COF
PS
STA
RTD RTD
HP HP
DC DC
STA STA
TF
HU
PP
GS
TF TF
RWH RWH
NH NH
AC AC
LPG DD
SR
FCC
DC
HU HU
SR SR
COF COF
CR CR
CCR
LHR
RWH
HP
CCR
FCC FCC
LPG LPG DD DD
LHR LHR
CCR CCR
ACS
AC
CR
NH
ACS
PP PP
GS GS
PS PS
ACS ACS
STA
TF
High pressure steam pipeline
Middle pressure steam pipeline
Low pressure steam pipeline
Figure 4 The plants with fixed location
(a) The layout form Wu’s (b) The layout from the method proposed method Figure 5 The layouts from two methods
3.2 Results The numerical results are presented in Table 2. The final layouts from Wu and Wang’s method and the proposed method are shown in figure 5 (a) and figure 5 (b) respectively.
198 Table 2 Numerical results of the two methods Wu and Wang’s method Calculation time 69,215.0 s (19.2 h) Steam pipeline cost (103 ¥) 2,475 Material pipeline cost (103 ¥) 10,581 Total pipeline cost (103 ¥) 13,056
R. Wang et al.
The proposed method 38.9 s 2,660 9,818 12,478
From the result, we can see that the calculation time has been reduced sharply. The proposed method is 1779 times faster than Wu’s method. And a better layout with lower total pipeline cost is obtained.
4. Conclusion The calculation of the minimum length of pipeline network has always been a thorny problem in the process of industrial park layout design. In this work, FLUTE algorithm is firstly applied in the calculation of the minimum length of a pipeline network. And a mathematical model is established to obtain the layout of an industrial park with the lowest pipeline cost. Both the previous method and the proposed method are used to solve the same case. The result illustrates that, with the proposed method, the calculation time is reduced sharply while a better layout is obtained.
References: H. Chen, C. Qiao, F. Zhou, C. Cheng, 2002. Refined Single Trunk Tree: A Rectilinear Steiner Tree Generator For Interconnect Prediction, In Proc. ACM Intl. Workshop on System Level Interconnect Prediction, pp. 85-89. C. Chu, 2004, FLUTE, http://home.eng.iastate.edu/~cnchu/flute.html, accessed 29 November 2017 C. Chu, 2004b. FLUTE: Fast Lookup Table Based Wirelength Estimation Technique, In Proc. International Conference on Computer Aided Design, pp. 696-701. C. Chu, Y. Wong, 2005. Fast and Accurate Rectilinear Steiner Minimal Tree Algorithm for VLSI Design., In Proc. International Symposium on Physical Design, pp. 28-35. C. Chu, Y. Wong, 2008, FLUTE: Fast Lookup Table Based Rectilinear Steiner Minimal Tree Algorithm for VLSI Design, IEEE Transactions on Computer-aided Design of Intergrated Circuits and Systems, 1, 27, 70-83. S.E. Latifi, E. Mohammadi, N. Khakzad, 2017, Process plant layout optimization with uncertainty and considering risk, Computers & Chemical Engineering, 106, 224-242. D.I. Patsiatzis, G. Knight, L.G. Papageorgiou, 2004, An MILP approach to safe process plant layout, Chemical Engineering Research and Design, 82, A5, 579-586. F.D. Penteado, A.R. Ciric, 1996, An MINLP Approach for Safe Process Plant Layout, Industrial & Engineering Chemistry Research, 4, 35, 1354-1361. D. Warme, P. Winter, M. Zachariasen, 2015, GeoSteiner, http://geosteiner.net/, accessed 29 November 2017. Y. Wu, Y. Wang, 2017, A Chemical Industry Area-wide Layout Design Methodology for Piping Implementation, Chemical Engineering Research & Design, 118, 81-93. Y. Wu, Y. Wang, X. Feng, S. Feng, 2016, A Genetic Algorithm Based Plant Layout Design Methodology Considering Piping and Safety, Chemical Engineering Transactions, 52, 25-30.
An Industrial Park Layout Design Method Considering Pipeline Length Based on FLUTE Algorithm Ruiqi Wanga, Yan Wub, Yufei Wanga*, Xiao Fengb, Mengxi Liua a
College of Chemical Engineering, China University of Petroleum - Beijing, No.18, Fuxue Road, Beijing, 102249, China b School of Chemical Engineering and Technology, Xi’an Jiaotong University, No.28, Xianning West Road, Xi’an, 710049, China [email protected]
Abstract The layout of an industrial park can significantly impact its economic benefit and safety. In terms of economy, a good layout means shorter pipeline length, leading to lower pipeline cost and material transport cost. In practice, the layout of an industrial park is manually determined based on experience according to the relationship of upstream and downstream. In academia, few systematic programming method has been proposed, and most of them only consider one-to-one connection pattern, pipeline networks with multi-branch are ignored. For systematic programming method, it has always been difficult to calculate the minimum length of pipeline network with multi-branch in an industrial park. FLUTE (Fast Lookup Table Based Wirelength Estimation Technique) algorithm is an accurate and fast method to solve rectilinear Steiner minimum tree problem based on a lookup table. In this paper, a novel method based on FLUTE algorithm is came up to calculate the minimum length of steam pipeline network in an industrial park and determine the layout. The total pipeline cost, which includes steam pipeline cost and material pipeline cost, is set as an objective function. Genetic algorithm is employed to optimize the layout of several plants in an industrial park. In the case study, it can be seen that, the calculation time is significantly reduced, and a better layout is obtained. Keywords: Industrial park layout; Pipeline network; Rectilinear Steiner minimum tree; FLUTE; Genetic algorithm
1. Introduction Layout design is a key step which must be passed in the process of chemical engineering design and construction. A good layout can reduce the capital cost for the pipeline and operation cost for material transportation, and enhance safety. Economy and safety are the main factors considered in the layout problem. Researches in chemical engineering layout can be divided into two aspects: one is to study the facility layout within a plant, and the other is to study the plant layout within an industrial park. Many researches about the facility layout within a plant are reported. Penteado and Ciric (1996) proposed a MINLP approach to determine the coordinates of facilities in a plant, considering land cost, piping cost, protection devices cost and risk cost. In their work, protection devices can prevent accidents or minimize the damage to the other nearby facilities, resulting in a protection devices cost at the same time. Patsiatzis et al. (2004)
194
R. Wang et al.
quantified the risk cost using FEI (Dow Fire & Explosion Index) system, while piping cost and protection cost were also involved to determine the layout of a plant. Latifi et al. (2017) worked out an optimal layout of a plant considering uncertainty and domino effects, and the allowance of multi-layer layout in this work makes this model more practical. Very few works have been done for designing the plant layout in an industrial park. A noteworthy difference between the facility layout and plant layout is pipeline network with branches. Pipeline networks, such as steam pipeline work, existed widely within an industrial park. Studies about facility layout mentioned above only calculated the lengths and costs of pipelines with point-to-point structure. It has always been difficult to calculate the minimum length of pipeline network with multi-branch in an industrial park. Wu and Wang (2017) firstly came up with an algorithm based on Kruskal algorithm to work out the minimum length and arrangement of pipeline network within an industrial park. Then Wu et al. (2016) combined this algorithm with risk evaluation to determine the layout of plants. But their algorithm is expensive in calculation time. A rectilinear Steiner minimal tree (RSMT) is a tree with minimum total edge length in Manhattan distance to connect a given set of nodes possibly through some extra nodes (Chu and Wong, 2008). Many algorithms have been come up to solve RSMT problem. GeoSteiner is an exact RSMT software developed by Warme et al. (2015) , but is relatively expensive in calculation time. Chen et al. (2002) proposed an algorithm called Refined Single Trunk Tree (RST-T), which is very effective for low-degree networks but not for high-degree networks. FLUTE (Fast Lookup Table Based Wirelength Estimation Technique) (Chu and Wong, 2005) is a fast and relatively accurate algorithm for RSMT. It achieves a good balance between calculation time and accuracy (Chu, 2004b). In this work, an industrial park layout design method is proposed, in which the problem of minimum length of pipeline network is converted to RSMT problem and calculated based on FLUTE algorithm. In the case study, the proposed method was compared with Wu and Wang’s work (2017). From the result, it can be seen that, when solving the same case, the calculation time of the proposed method is 38.9 s and Wu’s method is 69215.0 s. Calculation time is reduced sharply, and a better layout is obtained.
2. Methodology 2.1 Problem statement The objective function and constraints in this work are based on Wu and Wang’s work (2017). The free space in the industrial park is divided into several grids with the same size. Plants are treated as points. Each plant can only occupy one grid, which is put in the center of the grid. The distance between two plants is the distance between centers of the two grids and the distance is absolutely safe for plants. The pipeline must be arranged horizontally or vertically. Moreover, some plants should be put in some specific locations, according to the geographical and meteorological condition of the area where the industrial park sits. For example, the railway transportation plant should be located as near as possible to the railway line, and the air separation plant should be located in the upwind direction. Based on the assumption mentioned above, the aim of this work is to determine the location of plants in an industrial park to minimize the capital cost of the pipeline, including material pipeline and steam pipeline.
Industrial Park Layout Design Method Considering Pipeline Length
195
2.2 Objective function The objective function is set as the sum of material pipeline cost and steam pipeline cost, as is shown in Eq. (1). n
min C
3
¦a K ¦b L i
i 1
i
j
(1)
j
j 1
Where C is the total pipeline cost, n is the quantity of material pipeline, i represent different kinds of material flow, ai is the unit prize of i-th material pipeline, Ki is the length of i-th pipeline; j represent 3 different kinds of steam, bj is the unit prize of j-th steam pipeline, Lj is the length of j-th steam pipeline network. aj and bj come from the market prize. As the pipeline must be arranged horizontally or vertically, the Ki can be calculated by Eq. (2)
Ki | xin xout | | yin yout |
(2)
Where (xin, yin) and (xout, yout) is the coordinates of input and output plants respectively. The calculation of Lj is very complex that will be expressed in the next section. 2.3 Minimum length of steam pipeline network As mentioned in Introduction, the calculation of the minimum length of pipeline network has always been a thorny problem. In this work, this problem has been converted into RSMT problem. RSMT problem is to find a way to connect several given points by only horizontal and vertical lines. As is shown in figure 1, figure 1 (a) is the RSMT of the 3 given points, and figure 1 (b) is not. The Pipeline network connecting the plants of the steam generator or steam user, is the RSMT of those plants. Length vector is used to represent a certain connection. Figure 2 (a) is a connection of 4 given plants. The pipeline length of this connection is L1=2*h1+2*h2+h3+v1+v2+v3, so the length vector of this connection is p1= (2,2,1,1,1,1); figure 3 (b) is the shortest connection for the 4 plants, and the length is L2=h1+2*h2+h3+v1+v2+v3. The relevant length vector is p2= (1,2,1,1,1,1), which is called the optimal length vector. We can know which connection is shorter by comparing the length vector directly, instead of calculating the total length. For instance, length vector of (1,2,1,1,1,1) is shorter than (1,2,2,1,1,1) certainly.
Length=3
Length=4
v1
v1
v2
v2
v3
v3
h1 h2 h3 h2 h3 (a) (b) (a) (b) Figure 1 Examples of RSMT and non- Figure 2 Two connection patterns of 4 given plants RSTM
h1
R. Wang et al.
196
(a)
(b) Figure 3 Different relative locations of 4 plants
(c)
If the relative location of several plants is given and the edge lengths of grids are not given, many connections may be the shortest connection. Figure 3 (a) shows a kind of relative location of 4 plants (assuming that the lengths of edges are not determined). Both p3= (1,1,1,1,2,1) and p4= (1,2,1,1,1,1) may be the optimal length vector. Which one is optimal depends on the lengths of grid edges. In figure 3 (b), p3 is shorter, and in figure 3 (c) p4 is shorter. So p3 and p4 are called potential optimal length vector. For a certain relative location of plants, only few length vectors are potentially optimal comparing with all feasible connections. The authors of FLUTE previously calculated all the potential optimal length vectors for each condition of the relative location of points and saved the results. When the coordinates of plants are given, the relevant potential optimal length vectors for the relative location of those plants can be found. Then we calculate the lengths of each potential optimal length vector, and choose the shortest one. The minimum length of steam pipeline network and the arrangement can be obtained. This algorithm is very fast.
3. Case study 3.1 Basic data The case from Wu and Wang’s work (2017) is used, so that the proposed method can be compared with theirs. The case comes from a real petrochemical industrial park, which contains 20 plants and they should be arranged as 4×5 form. The distance between adjacent plants is set as 400 m. The plants and steam requirement are shown in Table 1, in which 1 means the plant needs steam and 0 means the plant does not need steam. This case contains 76 material flows. The type and diameter of a pipeline can be determined according to the property, flow rate and flow velocity of the transported material. In this work, the steam pipeline for the same degree has the same diameter. According to the geographical and meteorological condition of the area where the industrial park sits, 5 plants should be placed in the specific locations. They are shown in Figure 4. Both Wu and Wang’s method and the proposed method are implemented respectively to determine the layout of this case. The program of Wu and Wang’s method is provided by them. MATLAB is used to run the two programs. Genetic algorithm, which is also adopted in Wu and Wang’s work, is employed to solve the model for a fair competition. Genetic algorithm is generally regarded as one of the most effective algorithms. The generation is set as 1000, and the individual is set as 50. FLUTE is supplied by the authors in their official website (Chu, 2004).
Industrial Park Layout Design Method Considering Pipeline Length
197
Table 1 The plants and steam requirement of industrial park Number
Name
1 2 3 4 5 6 7 8 9
Power station Crude oil fractionation plant Gas separation plant Hydrogenation plant Residue and wax hydrodesuifurization plant Air compression and separation plant Fluid catalytic cracking plant Light hydrocarbon recovery plant Liquefied petroleum gas desulfuration and demercaptan plant Sulfur recovery plant Aromatic combine plant Hydrogen production Continuous reforming plant Naphtha hydrotreating Polypropylene and polyester Delayed coking plant Sewage treatment area Tank farm Railway transport department Central control room
10 11 12 13 14 15 16 17 18 19 20 RTD
High pressure steam 1 0 1 0 1 0 1 1 1
Middle pressure steam 1 1 1 1 1 1 1 1 1
Low pressure steam 1 1 1 1 1 1 1 1 1
0 1 1 1 0 1 0 0 0 0 0
1 1 1 1 1 1 1 0 1 1 0
1 1 0 0 0 1 0 1 0 0 1
RTD
COF
PS
STA
RTD RTD
HP HP
DC DC
STA STA
TF
HU
PP
GS
TF TF
RWH RWH
NH NH
AC AC
LPG DD
SR
FCC
DC
HU HU
SR SR
COF COF
CR CR
CCR
LHR
RWH
HP
CCR
FCC FCC
LPG LPG DD DD
LHR LHR
CCR CCR
ACS
AC
CR
NH
ACS
PP PP
GS GS
PS PS
ACS ACS
STA
TF
High pressure steam pipeline
Middle pressure steam pipeline
Low pressure steam pipeline
Figure 4 The plants with fixed location
(a) The layout form Wu’s (b) The layout from the method proposed method Figure 5 The layouts from two methods
3.2 Results The numerical results are presented in Table 2. The final layouts from Wu and Wang’s method and the proposed method are shown in figure 5 (a) and figure 5 (b) respectively.
198 Table 2 Numerical results of the two methods Wu and Wang’s method Calculation time 69,215.0 s (19.2 h) Steam pipeline cost (103 ¥) 2,475 Material pipeline cost (103 ¥) 10,581 Total pipeline cost (103 ¥) 13,056
R. Wang et al.
The proposed method 38.9 s 2,660 9,818 12,478
From the result, we can see that the calculation time has been reduced sharply. The proposed method is 1779 times faster than Wu’s method. And a better layout with lower total pipeline cost is obtained.
4. Conclusion The calculation of the minimum length of pipeline network has always been a thorny problem in the process of industrial park layout design. In this work, FLUTE algorithm is firstly applied in the calculation of the minimum length of a pipeline network. And a mathematical model is established to obtain the layout of an industrial park with the lowest pipeline cost. Both the previous method and the proposed method are used to solve the same case. The result illustrates that, with the proposed method, the calculation time is reduced sharply while a better layout is obtained.
References: H. Chen, C. Qiao, F. Zhou, C. Cheng, 2002. Refined Single Trunk Tree: A Rectilinear Steiner Tree Generator For Interconnect Prediction, In Proc. ACM Intl. Workshop on System Level Interconnect Prediction, pp. 85-89. C. Chu, 2004, FLUTE, http://home.eng.iastate.edu/~cnchu/flute.html, accessed 29 November 2017 C. Chu, 2004b. FLUTE: Fast Lookup Table Based Wirelength Estimation Technique, In Proc. International Conference on Computer Aided Design, pp. 696-701. C. Chu, Y. Wong, 2005. Fast and Accurate Rectilinear Steiner Minimal Tree Algorithm for VLSI Design., In Proc. International Symposium on Physical Design, pp. 28-35. C. Chu, Y. Wong, 2008, FLUTE: Fast Lookup Table Based Rectilinear Steiner Minimal Tree Algorithm for VLSI Design, IEEE Transactions on Computer-aided Design of Intergrated Circuits and Systems, 1, 27, 70-83. S.E. Latifi, E. Mohammadi, N. Khakzad, 2017, Process plant layout optimization with uncertainty and considering risk, Computers & Chemical Engineering, 106, 224-242. D.I. Patsiatzis, G. Knight, L.G. Papageorgiou, 2004, An MILP approach to safe process plant layout, Chemical Engineering Research and Design, 82, A5, 579-586. F.D. Penteado, A.R. Ciric, 1996, An MINLP Approach for Safe Process Plant Layout, Industrial & Engineering Chemistry Research, 4, 35, 1354-1361. D. Warme, P. Winter, M. Zachariasen, 2015, GeoSteiner, http://geosteiner.net/, accessed 29 November 2017. Y. Wu, Y. Wang, 2017, A Chemical Industry Area-wide Layout Design Methodology for Piping Implementation, Chemical Engineering Research & Design, 118, 81-93. Y. Wu, Y. Wang, X. Feng, S. Feng, 2016, A Genetic Algorithm Based Plant Layout Design Methodology Considering Piping and Safety, Chemical Engineering Transactions, 52, 25-30.