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ICSE 2015 The International Conference on Computing in Civil and Building Engineering Paris, France July 20 - 21, 2015 Biogeography Based CO2 and Cost.

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Presentation on theme: "ICSE 2015 The International Conference on Computing in Civil and Building Engineering Paris, France July 20 - 21, 2015 Biogeography Based CO2 and Cost."— Presentation transcript:

1 ICSE 2015 The International Conference on Computing in Civil and Building Engineering Paris, France July 20 - 21, 2015 Biogeography Based CO2 and Cost Optimization of RC Cantilever Retaining Walls DR. IBRAHIM AYDOGDU & DR.ALPER AKIN

2 Biogeography Based CO2 and Cost Optimization of RC Cantilever Retaining Walls, Aydogdu and AKIN 07.21.2015 In this study  The development of minimizing the cost and the CO2 emission of the RC retaining wall design has been performed by Biogeography Based Optimization (BBO) algorithm.  Computer programs are developed which minimizes the cost and the CO2 emission of the RC retaining walls.  Program Language: Fortran  Standards: ACI 318-14 ICSE 2015, PARIS, FRANCE2/16

3 Biogeography Based CO2 and Cost Optimization of RC Cantilever Retaining Walls, Aydogdu and AKIN Optimization Concept  Optimization is a mathematical process (method) used to find optimum value (design) of a problem defined in specific objective(s) and constraints.  Components of optimization problem  Objective function  Design or decision variables  Constraints 07.21.2015ICSE 2015, PARIS, FRANCE3/16

4 Biogeography Based CO2 and Cost Optimization of RC Cantilever Retaining Walls, Aydogdu and AKIN Optimization Problem Objective Functions: Minimize cost, CO 2 and weighted aggregate of the cost and the CO 2 of RW Design Constraints: American Concrete Institute (ACI 318-05)  stability constraints (overturning, sliding and bearing )  Moment and shear capacity constraints  Reinforcement arrangement constraints  Geometric constraints 07.21.2015ICSE 2015, PARIS, FRANCE4/16

5 Biogeography Based CO2 and Cost Optimization of RC Cantilever Retaining Walls, Aydogdu and AKIN Design Variables: total base width (X1) toe projection (X2) bottom and thickness of the stem (X3 and X4) thickness of the heel and the toe (X5) key distance from the toe (X6) thickness and the height of the key (X7 and X8) Optimization Problem first stem reinforcement together (R1), The second stem reinforcement together (R2) The toe reinforcement together (R3) The heel reinforcement together (R4) The key reinforcement together (R5) 07.21.2015ICSE 2015, PARIS, FRANCE5/16

6 Biogeography Based CO2 and Cost Optimization of RC Cantilever Retaining Walls, Aydogdu and AKIN 07.21.2015 OPTIMIZATION TECHNIQUES Deterministic Techniques (Mathematical Programming Techniques)  Integer Programming Technique  Branch and Bound Method Stochastic Techniques  Genetic Algorithm  Simulated Annealing  Artificial Immune System  Particle Swarm Optimization  Ant Colony Optimization  Harmony Search Method  Firefly Algorithm  Intelligent Water Drops Algorithm ICSE 2015, PARIS, FRANCE6/16

7 Biogeography Based CO2 and Cost Optimization of RC Cantilever Retaining Walls, Aydogdu and AKIN Biogeography-Based Optimization  The BBO algorithm was developed by simulating the theory of island biogeography which describes the extinction and migrations of species between islands. The method is considered in two complementary components:  Migration part : Solutions are modified based on the immigration rate  Mutation part: Solutions are renewed according to their mutation probability. 07.21.2015ICSE 2015, PARIS, FRANCE7/16

8 Biogeography Based CO2 and Cost Optimization of RC Cantilever Retaining Walls, Aydogdu and AKIN Biogeography-Based Optimization Steps of BBO algorithm: Step-1: Initialize the method parameters and define the optimization problem. Step-2: Initialize the population. initial RW designs of the population are generated randomly. The designs evaluated. Immigration and emigration rates of the designs are calculated Step-3: Migration: The designs in the populations are modified calculated according to their immigration and emigration rates Step-4: Mutation: If the design has high mutation probability the design is updated using random search. The procedure from step 2 to 4 is repeated until maximum iteration is reached. 07.21.2015ICSE 2015, PARIS, FRANCE8/16

9 Biogeography Based CO2 and Cost Optimization of RC Cantilever Retaining Walls, Aydogdu and AKIN 07.21.2015 Design Example 3.5 m height retaining wall ICSE 2015, PARIS, FRANCE MaterialS TRENGTH Unit Price CO 2 emission Concrete24 MPa59.76 $/m 3 304.75 CO 2 /m 3 27 MPa62.50 $/m 3 324.76 CO 2 /m 3 30 MPa65.65 $/m 3 344.54 CO 2 /m 3 Steel400 MPa0.742 $/kg0.3857 CO 2 /kg 500 MPa0.770 $/kg0.3962 CO 2 /kg Unit CO 2 emissions and Unit Price of the Structural Materials DVL.B OUND U. B OUND X10.4H0.8H X20.1H0.6H X30.20 m0.50 m X40.20 m0.40 m X50.20 m0.3H X60.5H0.8H X70.20 m0.40 m X80.20 m0.90 m Lower and Upper Bounds of Cross Sectional Design Variables 9/16

10 Biogeography Based CO2 and Cost Optimization of RC Cantilever Retaining Walls, Aydogdu and AKIN 07.21.2015  population size=50  mutation probability=2  elitism parameter=2  maximum iteration=100,000. 3.5 m height retaining wall ICSE 2015, PARIS, FRANCE Input ParameterUnit Value Height of stemmH3.50 Concrete covermmcc50 Shrinkage and temporary reinforcement percent -  st 0.002 Surcharge loadkPaq10 Backfill slopedegreeβ30 Internal friction angle of retained soildegree  36 Internal friction angle of base soildegree ’’ 0.01 Unit weight of retained soilkN/m 3 γsγs 17.50 Unit weight of base soilkN/m 3 γ bs 18.50 Unit weight of concretekN/m 3 γcγc 23.50 Cohesion of base soilkPac65 Design load factor-LF1.7 Depth of soil in front of wallmD0.50 Factor of safety for overturning stability-FS o 1.5 Factor of safety for against sliding-FS s 1.5 Factor of safety for bearing capacity-FS b 3.0 Input Parameters 10/16

11 Biogeography Based CO2 and Cost Optimization of RC Cantilever Retaining Walls, Aydogdu and AKIN 07.21.2015 3.5 m height retaining wall ICSE 2015, PARIS, FRANCE Optimum Values Des. Var. HSBioGCFFAAFFADes. Var.HSBioGCFFAAFFA X1X1 2.72.6543.2582.906R1R1 10  102  222  265  16 X2X2 1.61.5691.4731.461R2R2 7  109  128  16 X3X3 0.350.3150.4620.463R3R3 1  10 --- X4X4 0.2 R4R4 10  129  129  149  12 X5X5 0.350.3130.3480.342R5R5 7  10 X6X6 1.92.452.882.607 X7X7 0.2 0.2010.2 X8X8 0.60.70.2040.644 Cost DetailsHSBioGCFFAAFFA Vol. Conc. (m 3 )2.031.871 2.171.93 Weight st. (kg)92.2097.78 110.0593.24 Cost Conc. ($)81.1074.82 86.7877.17 Cost st. ($)36.8839.11 44.0237.29 Cost Total ($)117.98113.93 130.8114.46 Optimum Values of Design Variables and Cost Details 11/16

12 Biogeography Based CO2 and Cost Optimization of RC Cantilever Retaining Walls, Aydogdu and AKIN 07.21.2015 Variations of optimum values with respect to different materials ICSE 2015, PARIS, FRANCE (Objective function: Minimize the CO 2 emission) (Objective function: Minimize the cost) 12/16

13 Biogeography Based CO2 and Cost Optimization of RC Cantilever Retaining Walls, Aydogdu and AKIN 07.21.2015 Variations of concrete and steel amounts of optimum designs with respect to different materials ICSE 2015, PARIS, FRANCE (Concrete amount of optimum designs) (Steel amount of optimum designs) 13/16

14 Biogeography Based CO2 and Cost Optimization of RC Cantilever Retaining Walls, Aydogdu and AKIN 07.21.2015 Conclusions 1.BBO resulted in better performance than those obtained in all previous research studies. The presented algorithm is powerful and efficient in finding the optimum solution for optimum cost design of RW problems. 2.The minimizing CO2 emission objective function does not have a material influence on the optimum cost of the retaining wall. Therefore, the minimizing CO2 emission objective function can be used in the cost optimization problem. ICSE 2015, PARIS, FRANCE14/16

15 Biogeography Based CO2 and Cost Optimization of RC Cantilever Retaining Walls, Aydogdu and AKIN 07.21.2015 Conclusions 3.if lower class materials are used, lower cost and CO2 emissions are obtained 4.Higher steel amount is obtained in the minimization of CO2 emission problem 5.Higher steel class reduces the steel amount and steel cost percentage ICSE 2015, PARIS, FRANCE15/16

16 07.21.2015

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